diff --git a/.binder/environment.yml b/.binder/environment.yml
new file mode 100644
index 0000000..9da86f4
--- /dev/null
+++ b/.binder/environment.yml
@@ -0,0 +1,35 @@
+name: gfts
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python=3.11
+  - jupyter-book
+  - matplotlib
+  - numpy
+  - ghp-import
+  - xarray
+  - cftime
+  - netcdf4
+  - h5netcdf
+  - cartopy
+  - holoviews
+  - hvplot
+  - geoviews
+  - cartopy
+  - geopandas
+  - movingpandas
+  - pooch
+  - fsspec
+  - s3fs
+  - git
+  - jupyterlab-git
+  - "nodejs>=16,<17"
+  - jupyterlab-myst>=2.0.0
+  - pip:
+      - wget
+      - sphinx-exercise
+      - jupytext
+      - nbgitpuller
+      - mystmd
+      - xdggs
diff --git a/.github/workflows/deploy.yml b/.github/workflows/deploy.yml
new file mode 100644
index 0000000..f3c0d79
--- /dev/null
+++ b/.github/workflows/deploy.yml
@@ -0,0 +1,40 @@
+name: deploy
+
+on:
+  # Trigger the workflow on push to main branch and tutorial path
+  push:
+    branches:
+      - main
+    paths:
+      - visualisation/**
+
+# This job installs dependencies, build the jupyter notebook, and pushes it to `render`, a new `branch`
+jobs:
+  build:
+    name: Setup
+    runs-on: "ubuntu-latest"
+    defaults:
+      run:
+        shell: bash -l {0}
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up conda and dependencies
+        uses: mamba-org/setup-micromamba@v1
+        with:
+          environment-file: .binder/environment.yml
+          environment-name: xdggs
+          condarc: |
+            channels:
+              - conda-forge
+      # Build the book
+      - name: Build the jupyter book
+        run: |
+          jupyter-book build visualisation
+      # Deploy the book's HTML to gh-pages branch
+      - name: Deploy to GitHub Pages
+        uses: peaceiris/actions-gh-pages@v3
+        with:
+          publish_branch: gh-pages
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+          publish_dir: visualisation/_build/html
+          force_orphan: true
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..77defd5
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,40 @@
+# pre-commit is a tool to perform a predefined set of tasks manually and/or
+# automatically before git commits are made.
+#
+# Config reference: https://pre-commit.com/#pre-commit-configyaml---top-level
+#
+# Common tasks
+#
+# - Run on all files:   pre-commit run --all-files
+# - Register git hooks: pre-commit install --install-hooks
+#
+
+ci:
+  # pre-commit.ci will open PRs updating our hooks once a month
+  autoupdate_schedule: monthly
+
+exclude: "(.*/)?secrets/.*|code_of_conduct.md|rule_of_participation.md"
+
+repos:
+  # autoformat and lint Python code
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.8.0
+    hooks:
+      - id: ruff
+        args: ["--fix", "--show-fixes"]
+      - id: ruff-format
+
+  # Autoformat: markdown, yaml, javascript (see the file .prettierignore)
+  - repo: https://github.com/rbubley/mirrors-prettier
+    rev: v3.3.3
+    hooks:
+      - id: prettier
+
+  # Autoformat and linting, misc. details
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.5.0
+    hooks:
+      - id: end-of-file-fixer
+      - id: requirements-txt-fixer
+      - id: check-case-conflict
+      - id: check-executables-have-shebangs
diff --git a/visualisation/_config.yml b/visualisation/_config.yml
new file mode 100644
index 0000000..9d5fdba
--- /dev/null
+++ b/visualisation/_config.yml
@@ -0,0 +1,52 @@
+#######################################################################################
+# A default configuration that will be loaded for all jupyter books
+# See the documentation for help and more options:
+# https://jupyterbook.org/customize/config.html
+
+#######################################################################################
+# Book settings
+title: xdggs examples
+author: Pangeo # The author of the book
+copyright: "2024" # Copyright year to be placed in the footer
+logo: "./images/xdggs.png" # A path to the book logo
+only_build_toc_files: true
+
+# Force re-execution of notebooks on each build.
+# See https://jupyterbook.org/content/execute.html
+execute:
+  execute_notebooks: false
+  timeout: 1000
+
+# Add a launch button on a specific binder instance
+launch_buttons:
+  notebook_interface: "jupyterlab"
+  binderhub_url: "https://notebooks.gesis.org/binder/" # The URL for your BinderHub (e.g., https://mybinder.org)
+  jupyterhub_url: "http://pangeo-eosc.vm.fedcloud.eu/jupyterhub/" # The URL for your JupyterHub. (e.g., https://datahub.berkeley.edu)
+
+# Define the name of the latex output file for PDF builds
+latex:
+  latex_documents:
+    targetname: xdggs.tex
+
+# Add a bibtex file so that we can create citations
+bibtex_bibfiles:
+  - references.bib
+
+# Information about where the book exists on the web
+repository:
+  url: https://github.com/tinaok/xdggs_examples # Online location of your book
+  path_to_book: docs # Optional path to your book, relative to the repository root
+  branch: main # Which branch of the repository should be used when creating links (optional)
+
+# Add GitHub buttons to your book
+# See https://jupyterbook.org/customize/config.html#add-a-link-to-your-repository
+html:
+  use_issues_button: true
+  use_repository_button: true
+
+sphinx:
+  config:
+    html_js_files:
+      - https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js
+  extra_extensions:
+    - sphinx_exercise
diff --git a/visualisation/_toc.yml b/visualisation/_toc.yml
new file mode 100644
index 0000000..93ce78a
--- /dev/null
+++ b/visualisation/_toc.yml
@@ -0,0 +1,2 @@
+format: jb-book
+root: xdggs-explore-demo
diff --git a/visualisation/images/xdggs.png b/visualisation/images/xdggs.png
new file mode 100644
index 0000000..098f425
Binary files /dev/null and b/visualisation/images/xdggs.png differ
diff --git a/visualisation/readme.md b/visualisation/readme.md
new file mode 100644
index 0000000..e69de29
diff --git a/visualisation/xdggs-demo_icechunk_multilevel.ipynb b/visualisation/xdggs-demo_icechunk_multilevel.ipynb
new file mode 100644
index 0000000..9b1a718
--- /dev/null
+++ b/visualisation/xdggs-demo_icechunk_multilevel.ipynb
@@ -0,0 +1,6850 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d340a5ff-db29-4c13-8d7f-f02870e6ad17",
+   "metadata": {},
+   "source": [
+    "# Saving multilevel HEALPix Data in zarr and datatree \n",
+    "\n",
+    "In this notebook, we will demonstrate  examples of saving multilevel HEALPix data.  \n",
+    "\n",
+    "## Setup\n",
+    "\n",
+    "To run this notebook, you need to install XDGGS. You can find the xdggs repository here: [XDGGS GitHub Repository](https://github.com/xarray-contrib/xdggs.git).\n",
+    "\n",
+    "\n",
+    "1. You can either install `xdggs` with the necessary dependencies, use the following command:\n",
+    "\n",
+    "```bash\n",
+    "pip install xdggs\n",
+    "```\n",
+    "\n",
+    "2. You will need up to date xarray package :\n",
+    "\n",
+    "```bash\n",
+    "pip install -U xarray\n",
+    "```\n",
+    "\n",
+    "3. You can use zarr version zarr==2.18.4.  In a few weeks, it would work with icechunk as well. :\n",
+    "\n",
+    "```bash\n",
+    "#pip install icechunk\n",
+    "pip install -U zarr==2.18.4\n",
+    "```\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "52acd195-dfe4-41c2-add0-dc13fb879dde",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "#!pip install xdggs pint_xarray icechunk\n",
+    "!pip install xdggs\n",
+    "#!pip install icechunk\n",
+    "!pip install -U zarr==2.18.4"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "576f6d95-d774-49a8-9656-fe187cd5674b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install -U xarray"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "36cf9310-b950-4ff2-96ac-8b654b411947",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import warnings\n",
+    "\n",
+    "import healpy as hp\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "import xdggs\n",
+    "\n",
+    "warnings.filterwarnings(\"ignore\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e3963d96-2a87-466e-b235-702efa7bc87c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2024.11.0'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xr.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "076aefd9-7ad9-48a6-941c-2c019dd07d46",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2.18.4'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import zarr\n",
+    "\n",
+    "zarr.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "68c364ab-3db3-42c9-9872-83b83b599ae5",
+   "metadata": {},
+   "source": [
+    "##  Creating level8 Healpix dataset \n",
+    "HEALPix is designed to represent the sphere using spherical harmonics functions.\n",
+    "Following code with generate a test dateset. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "ee5acea7-f765-459e-9c72-565b434a3ef3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "chunk_size_8 4096\n"
+     ]
+    },
+    {
+     "data": {
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+       "\n",
+       ".xr-wrap {\n",
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+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
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+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 25MB\n",
+       "Dimensions:    (cells: 786432)\n",
+       "Coordinates:\n",
+       "  * cell_ids   (cells) int64 6MB dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;\n",
+       "    latitude   (cells) float64 6MB dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;\n",
+       "    longitude  (cells) float64 6MB dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 6MB dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=8, indexing_scheme=nested)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-71c07a42-9eb4-4d46-ba33-4cefec18af3e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-71c07a42-9eb4-4d46-ba33-4cefec18af3e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>cells</span>: 786432</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4013147c-473d-4969-b74e-56b036219641' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4013147c-473d-4969-b74e-56b036219641' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;</div><input id='attrs-900bc8ea-ffd0-47a9-a971-6f6a71445375' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-900bc8ea-ffd0-47a9-a971-6f6a71445375' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-113d8b5f-302a-40c0-b0b1-e02828faf4fa' class='xr-var-data-in' type='checkbox'><label for='data-113d8b5f-302a-40c0-b0b1-e02828faf4fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>8</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.00 MiB </td>\n",
+       "                        <td> 32.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (786432,) </td>\n",
+       "                        <td> (4096,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >786432</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;</div><input id='attrs-6ea6ca32-6127-4469-b8d4-0c3c4c99e2ee' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ea6ca32-6127-4469-b8d4-0c3c4c99e2ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d97ff083-57a7-45ff-9632-d2343ea0572a' class='xr-var-data-in' type='checkbox'><label for='data-d97ff083-57a7-45ff-9632-d2343ea0572a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.00 MiB </td>\n",
+       "                        <td> 32.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (786432,) </td>\n",
+       "                        <td> (4096,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >786432</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;</div><input id='attrs-94dfb12d-f6ee-4885-8df3-8a2d7cf5e8d7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-94dfb12d-f6ee-4885-8df3-8a2d7cf5e8d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18a71edb-ef93-42d6-856f-7ec951830070' class='xr-var-data-in' type='checkbox'><label for='data-18a71edb-ef93-42d6-856f-7ec951830070' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.00 MiB </td>\n",
+       "                        <td> 32.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (786432,) </td>\n",
+       "                        <td> (4096,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >786432</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-281fe74f-6e4b-4186-8591-b99c05ec5288' class='xr-section-summary-in' type='checkbox'  checked><label for='section-281fe74f-6e4b-4186-8591-b99c05ec5288' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;</div><input id='attrs-9af3f8c1-7774-43b2-8e66-411dfd4cb7ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9af3f8c1-7774-43b2-8e66-411dfd4cb7ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9861fea5-875c-498b-bea3-3b0a73abdfbf' class='xr-var-data-in' type='checkbox'><label for='data-9861fea5-875c-498b-bea3-3b0a73abdfbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.00 MiB </td>\n",
+       "                        <td> 32.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (786432,) </td>\n",
+       "                        <td> (4096,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >786432</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-1c050769-21dd-4983-ac2e-21c194423ed2' class='xr-section-summary-in' type='checkbox'  ><label for='section-1c050769-21dd-4983-ac2e-21c194423ed2' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>cell_ids</div></div><div class='xr-index-preview'>HealpixIndex(nside=8, indexing_scheme=nested)</div><input type='checkbox' disabled/><label></label><input id='index-476a101a-5015-4172-9f10-32a8970214ad' class='xr-index-data-in' type='checkbox'/><label for='index-476a101a-5015-4172-9f10-32a8970214ad' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>&lt;xdggs.healpix.HealpixIndex object at 0x7f6e6e8bf3e0&gt;</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a43fbfe5-a734-49d8-899b-f5b0d0b4d2e0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a43fbfe5-a734-49d8-899b-f5b0d0b4d2e0' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 25MB\n",
+       "Dimensions:    (cells: 786432)\n",
+       "Coordinates:\n",
+       "  * cell_ids   (cells) int64 6MB dask.array<chunksize=(4096,), meta=np.ndarray>\n",
+       "    latitude   (cells) float64 6MB dask.array<chunksize=(4096,), meta=np.ndarray>\n",
+       "    longitude  (cells) float64 6MB dask.array<chunksize=(4096,), meta=np.ndarray>\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 6MB dask.array<chunksize=(4096,), meta=np.ndarray>\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=8, indexing_scheme=nested)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 16 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "lmax = 3\n",
+    "level = 8\n",
+    "nside = 2**level\n",
+    "# compute Alm\n",
+    "# get the l and m availble for l<=lmax\n",
+    "l, m = hp.Alm.getlm(lmax=lmax)  # noqa: E741\n",
+    "\n",
+    "# count the number of alm map (1 for m=0 and 2 for m>0)\n",
+    "n_alm = (m == 0).sum() + 2 * (m > 0).sum()\n",
+    "function = np.zeros([n_alm, 12 * nside**2])\n",
+    "\n",
+    "alm = np.zeros([l.shape[0]], dtype=\"complex\")\n",
+    "\n",
+    "i = 0\n",
+    "\n",
+    "# array to store the l and m values of the A_lm\n",
+    "l_func = np.zeros(n_alm, dtype=\"int\")\n",
+    "m_func = np.zeros(n_alm, dtype=\"int\")\n",
+    "is_real_func = np.zeros(n_alm, dtype=\"int\")\n",
+    "\n",
+    "for k in range(l.shape[0]):\n",
+    "    alm[k] = 1.0\n",
+    "    function[i] = hp.reorder(hp.alm2map(alm, nside), r2n=True)\n",
+    "    l_func[i] = l[k]\n",
+    "    m_func[i] = m[k]\n",
+    "    is_real_func[i] = 1\n",
+    "    i += 1\n",
+    "    if m[k] > 0:\n",
+    "        alm[k] = complex(0, 1)\n",
+    "        function[i] = hp.reorder(hp.alm2map(alm, nside), r2n=True)\n",
+    "        l_func[i] = l[k]\n",
+    "        m_func[i] = m[k]\n",
+    "        is_real_func[i] = 0\n",
+    "        i += 1\n",
+    "    alm[k] = 0.0\n",
+    "lm = 3\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "\n",
+    "\n",
+    "for k in range(l_func.shape[0]):\n",
+    "    pos = (\n",
+    "        1\n",
+    "        + l_func[k] * (2 * lm + 1)\n",
+    "        + 2 * (is_real_func[k] - 0.5) * m_func[k]\n",
+    "        - 1\n",
+    "        + (lm + 1)\n",
+    "    )\n",
+    "    if is_real_func[k] == 1:\n",
+    "        title = \"$\\mathbb{R}(A_{\\ell=%d,m=%d})$\" % (l_func[k], m_func[k])\n",
+    "    else:\n",
+    "        title = \"$\\mathbb{I}(A_{\\ell=%d,m=%d})$\" % (l_func[k], m_func[k])\n",
+    "    if l_func[k] <= lm:\n",
+    "        hp.mollview(\n",
+    "            function[k],\n",
+    "            nest=True,\n",
+    "            hold=False,\n",
+    "            sub=(lm + 1, 2 * lm + 1, pos),\n",
+    "            title=title,\n",
+    "            cbar=False,\n",
+    "            cmap=\"coolwarm\",\n",
+    "        )\n",
+    "\n",
+    "\n",
+    "level = 8\n",
+    "cell_ids = np.arange(12 * 4**level)\n",
+    "grid_info = {\"grid_name\": \"healpix\", \"level\": level, \"indexing_scheme\": \"nested\"}\n",
+    "\n",
+    "ds_8 = (\n",
+    "    xr.Dataset(coords={\"cell_ids\": (\"cells\", cell_ids, grid_info)})\n",
+    "    .pipe(xdggs.decode)\n",
+    "    .pipe(lambda ds: ds.merge(ds.dggs.cell_centers()))\n",
+    "    .assign(\n",
+    "        data=lambda ds: np.cos(6 * np.radians(ds[\"latitude\"]))\n",
+    "        * np.sin(6 * np.radians(ds[\"longitude\"]))\n",
+    "    )\n",
+    ")\n",
+    "SH_L3_M2 = xr.DataArray(\n",
+    "    function[13, :], dims=(\"cells\"), coords={\"cell_ids\": (\"cells\", cell_ids, grid_info)}\n",
+    ")\n",
+    "ds_8[\"data\"] = SH_L3_M2\n",
+    "chunk_late = 12 * (4**2)\n",
+    "chunk_size_8 = int((ds_8.cells.size) / chunk_late)\n",
+    "print(\"chunk_size_8\", chunk_size_8)\n",
+    "ds_8 = ds_8.chunk(chunks={\"cells\": chunk_size_8})\n",
+    "ds_8"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b5c133e9-d79a-4119-9a1e-ad736a1509fd",
+   "metadata": {},
+   "source": [
+    "##  Creating level7 Healpix dataset \n",
+    "HEALPix is designed to represent the sphere using spherical harmonics functions.\n",
+    "Following code with generate a test dateset. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "aaaade42-e109-4ccf-be0d-11cf039c76cc",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "chunk_size_7 1024\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 6MB\n",
+       "Dimensions:    (cells: 196608)\n",
+       "Coordinates:\n",
+       "  * cell_ids   (cells) int64 2MB dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;\n",
+       "    latitude   (cells) float64 2MB dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;\n",
+       "    longitude  (cells) float64 2MB dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 2MB dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=7, indexing_scheme=nested)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e3cea2fa-1b95-41dd-a9b8-d2af69fcbf43' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e3cea2fa-1b95-41dd-a9b8-d2af69fcbf43' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>cells</span>: 196608</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-078101f0-951e-4e30-87da-250c670b5b41' class='xr-section-summary-in' type='checkbox'  checked><label for='section-078101f0-951e-4e30-87da-250c670b5b41' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;</div><input id='attrs-46e551ae-51c5-4307-b601-1648ed497485' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46e551ae-51c5-4307-b601-1648ed497485' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e39b80f-ff0f-4d52-9c68-c07894a13c97' class='xr-var-data-in' type='checkbox'><label for='data-2e39b80f-ff0f-4d52-9c68-c07894a13c97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>7</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 MiB </td>\n",
+       "                        <td> 8.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (196608,) </td>\n",
+       "                        <td> (1024,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >196608</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;</div><input id='attrs-ad9b9d03-19b4-4630-bd51-b017c7cae8bc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ad9b9d03-19b4-4630-bd51-b017c7cae8bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cf878ae-5c41-47bc-a789-0c567a9927c7' class='xr-var-data-in' type='checkbox'><label for='data-5cf878ae-5c41-47bc-a789-0c567a9927c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 MiB </td>\n",
+       "                        <td> 8.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (196608,) </td>\n",
+       "                        <td> (1024,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >196608</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;</div><input id='attrs-c7cf039b-a5e1-46c2-849f-87b9e2c47536' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c7cf039b-a5e1-46c2-849f-87b9e2c47536' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ab11d59-12a6-4f9e-827d-ac941f58e56d' class='xr-var-data-in' type='checkbox'><label for='data-3ab11d59-12a6-4f9e-827d-ac941f58e56d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 MiB </td>\n",
+       "                        <td> 8.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (196608,) </td>\n",
+       "                        <td> (1024,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >196608</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-76ae70cc-7390-4d99-b484-1bf3c4fe375d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-76ae70cc-7390-4d99-b484-1bf3c4fe375d' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;</div><input id='attrs-84cbe113-a4a3-4190-a290-aff0e8178e88' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-84cbe113-a4a3-4190-a290-aff0e8178e88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31eee069-4c51-443f-9855-b91c359dff0f' class='xr-var-data-in' type='checkbox'><label for='data-31eee069-4c51-443f-9855-b91c359dff0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 MiB </td>\n",
+       "                        <td> 8.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (196608,) </td>\n",
+       "                        <td> (1024,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >196608</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-a8c5c653-b316-460f-a844-51b1c3e64aa0' class='xr-section-summary-in' type='checkbox'  ><label for='section-a8c5c653-b316-460f-a844-51b1c3e64aa0' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>cell_ids</div></div><div class='xr-index-preview'>HealpixIndex(nside=7, indexing_scheme=nested)</div><input type='checkbox' disabled/><label></label><input id='index-9098e232-3df7-4997-879a-30a6a3bd8a58' class='xr-index-data-in' type='checkbox'/><label for='index-9098e232-3df7-4997-879a-30a6a3bd8a58' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>&lt;xdggs.healpix.HealpixIndex object at 0x7f6e6998c2c0&gt;</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-13994ca1-4ccf-45f3-9968-d3b533c6905d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-13994ca1-4ccf-45f3-9968-d3b533c6905d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 6MB\n",
+       "Dimensions:    (cells: 196608)\n",
+       "Coordinates:\n",
+       "  * cell_ids   (cells) int64 2MB dask.array<chunksize=(1024,), meta=np.ndarray>\n",
+       "    latitude   (cells) float64 2MB dask.array<chunksize=(1024,), meta=np.ndarray>\n",
+       "    longitude  (cells) float64 2MB dask.array<chunksize=(1024,), meta=np.ndarray>\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 2MB dask.array<chunksize=(1024,), meta=np.ndarray>\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=7, indexing_scheme=nested)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 16 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "lmax = 3\n",
+    "level = 7\n",
+    "nside = 2**level\n",
+    "# compute Alm\n",
+    "# get the l and m availble for l<=lmax\n",
+    "l, m = hp.Alm.getlm(lmax=lmax)  # noqa: E741\n",
+    "\n",
+    "# count the number of alm map (1 for m=0 and 2 for m>0)\n",
+    "n_alm = (m == 0).sum() + 2 * (m > 0).sum()\n",
+    "function = np.zeros([n_alm, 12 * nside**2])\n",
+    "\n",
+    "alm = np.zeros([l.shape[0]], dtype=\"complex\")\n",
+    "\n",
+    "i = 0\n",
+    "\n",
+    "# array to store the l and m values of the A_lm\n",
+    "l_func = np.zeros(n_alm, dtype=\"int\")\n",
+    "m_func = np.zeros(n_alm, dtype=\"int\")\n",
+    "is_real_func = np.zeros(n_alm, dtype=\"int\")\n",
+    "\n",
+    "for k in range(l.shape[0]):\n",
+    "    alm[k] = 1.0\n",
+    "    function[i] = hp.reorder(hp.alm2map(alm, nside), r2n=True)\n",
+    "    l_func[i] = l[k]\n",
+    "    m_func[i] = m[k]\n",
+    "    is_real_func[i] = 1\n",
+    "    i += 1\n",
+    "    if m[k] > 0:\n",
+    "        alm[k] = complex(0, 1)\n",
+    "        function[i] = hp.reorder(hp.alm2map(alm, nside), r2n=True)\n",
+    "        l_func[i] = l[k]\n",
+    "        m_func[i] = m[k]\n",
+    "        is_real_func[i] = 0\n",
+    "        i += 1\n",
+    "    alm[k] = 0.0\n",
+    "lm = 3\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "for k in range(l_func.shape[0]):\n",
+    "    pos = (\n",
+    "        1\n",
+    "        + l_func[k] * (2 * lm + 1)\n",
+    "        + 2 * (is_real_func[k] - 0.5) * m_func[k]\n",
+    "        - 1\n",
+    "        + (lm + 1)\n",
+    "    )\n",
+    "    if is_real_func[k] == 1:\n",
+    "        title = \"$\\mathbb{R}(A_{\\ell=%d,m=%d})$\" % (l_func[k], m_func[k])\n",
+    "    else:\n",
+    "        title = \"$\\mathbb{I}(A_{\\ell=%d,m=%d})$\" % (l_func[k], m_func[k])\n",
+    "    if l_func[k] <= lm:\n",
+    "        hp.mollview(\n",
+    "            function[k],\n",
+    "            nest=True,\n",
+    "            hold=False,\n",
+    "            sub=(lm + 1, 2 * lm + 1, pos),\n",
+    "            title=title,\n",
+    "            cbar=False,\n",
+    "            cmap=\"coolwarm\",\n",
+    "        )\n",
+    "\n",
+    "\n",
+    "cell_ids = np.arange(12 * 4**level)\n",
+    "grid_info = {\"grid_name\": \"healpix\", \"level\": level, \"indexing_scheme\": \"nested\"}\n",
+    "\n",
+    "ds_7 = (\n",
+    "    xr.Dataset(coords={\"cell_ids\": (\"cells\", cell_ids, grid_info)})\n",
+    "    .pipe(xdggs.decode)\n",
+    "    .pipe(lambda ds: ds.merge(ds.dggs.cell_centers()))\n",
+    "    .assign(\n",
+    "        data=lambda ds: np.cos(6 * np.radians(ds[\"latitude\"]))\n",
+    "        * np.sin(6 * np.radians(ds[\"longitude\"]))\n",
+    "    )\n",
+    ")\n",
+    "SH_L3_M2 = xr.DataArray(\n",
+    "    function[13, :], dims=(\"cells\"), coords={\"cell_ids\": (\"cells\", cell_ids, grid_info)}\n",
+    ")\n",
+    "ds_7[\"data\"] = SH_L3_M2\n",
+    "chunk_late = 12 * (4**2)\n",
+    "chunk_size_7 = int((ds_7.cells.size) / chunk_late)\n",
+    "print(\"chunk_size_7\", chunk_size_7)\n",
+    "ds_7 = ds_7.chunk(chunks={\"cells\": chunk_size_7})\n",
+    "ds_7"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "270999dc-b4a4-492e-a0e4-87e5eb08b55d",
+   "metadata": {},
+   "source": [
+    "## Open a EERIE Cloud  data in hearlpix, saved in zarr format from DKRZ, and importing the level9 dataset\n",
+    "\n",
+    "NextGems project provide their data set in healpix in zarr format. \n",
+    "Deatiled description of EERIE Cloud can be found here\n",
+    "https://easy.gems.dkrz.de/simulations/EERIE/eerie_data-access_online.html\n",
+    "\n",
+    "\n",
+    "I just want to show how to save sahred dimention or coordinate system between different levels here,\n",
+    "\n",
+    "I get time coordinate from this dataset as a test, saved it as 'root' "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "8f6b7df4-c438-4606-8abb-c27f1e7fa843",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
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+       ".xr-wrap {\n",
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+       "\n",
+       ".xr-text-repr-fallback {\n",
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+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
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+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
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+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
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+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
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+       "\n",
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+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
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+       "\n",
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+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
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+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
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+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
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+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
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+       "  overflow: hidden;\n",
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+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
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+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 3MB\n",
+       "Dimensions:   (time: 2, cells: 65536)\n",
+       "Coordinates:\n",
+       "    lat       (cells) float64 524kB dask.array&lt;chunksize=(65536,), meta=np.ndarray&gt;\n",
+       "    lon       (cells) float64 524kB dask.array&lt;chunksize=(65536,), meta=np.ndarray&gt;\n",
+       "  * time      (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "  * cell_ids  (cells) int64 524kB 0 1 2 3 4 5 ... 65531 65532 65533 65534 65535\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    msl       (time, cells) float64 1MB dask.array&lt;chunksize=(2, 65536), meta=np.ndarray&gt;\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=9, indexing_scheme=nested)\n",
+       "Attributes: (12/14)\n",
+       "    edition:            2\n",
+       "    centre:             ecmf\n",
+       "    centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    subCentre:          1003\n",
+       "    history:            🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IF...\n",
+       "    title:              nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512\n",
+       "    ...                 ...\n",
+       "    time_max:           2050-01-01T00:00:00.000000000\n",
+       "    frequency:          unknown\n",
+       "    creation_date:      2024-12-14T00:01:16Z\n",
+       "    authors:            Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECM...\n",
+       "    contact:            Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)\n",
+       "    license:            Creative Commons Attribution 4.0 International (CC BY...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-22ae3dad-6f20-411d-9aaf-1ba8effd46b8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-22ae3dad-6f20-411d-9aaf-1ba8effd46b8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li><li><span class='xr-has-index'>cells</span>: 65536</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-312dfbc9-505d-434e-b416-2ccdc3a34ceb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-312dfbc9-505d-434e-b416-2ccdc3a34ceb' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(65536,), meta=np.ndarray&gt;</div><input id='attrs-9d627da3-0087-408a-bc55-91b810fd7849' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d627da3-0087-408a-bc55-91b810fd7849' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14570b21-247f-48e7-ac35-28eca6253dd7' class='xr-var-data-in' type='checkbox'><label for='data-14570b21-247f-48e7-ac35-28eca6253dd7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512.00 kiB </td>\n",
+       "                        <td> 512.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (65536,) </td>\n",
+       "                        <td> (65536,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >65536</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(65536,), meta=np.ndarray&gt;</div><input id='attrs-fa11af02-a517-48c8-83e0-7acb89d06622' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa11af02-a517-48c8-83e0-7acb89d06622' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18f6731e-175b-44b0-be30-89067e350e5d' class='xr-var-data-in' type='checkbox'><label for='data-18f6731e-175b-44b0-be30-89067e350e5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512.00 kiB </td>\n",
+       "                        <td> 512.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (65536,) </td>\n",
+       "                        <td> (65536,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >65536</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-01-20 2020-01-20T01:00:00</div><input id='attrs-f3904f28-9f7b-48c8-aaec-7ec1cb0efdc9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f3904f28-9f7b-48c8-aaec-7ec1cb0efdc9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-062400de-e378-4b07-9379-b1dfd0102794' class='xr-var-data-in' type='checkbox'><label for='data-062400de-e378-4b07-9379-b1dfd0102794' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-01-20T00:00:00.000000000&#x27;, &#x27;2020-01-20T01:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 65532 65533 65534 65535</div><input id='attrs-fd26f739-3b68-4b43-8a81-5851b59f2615' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd26f739-3b68-4b43-8a81-5851b59f2615' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6792023b-b41e-45e3-97f2-bbd23fe474af' class='xr-var-data-in' type='checkbox'><label for='data-6792023b-b41e-45e3-97f2-bbd23fe474af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>9</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><pre>array([    0,     1,     2, ..., 65533, 65534, 65535])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6e5a4939-8abd-4168-b54b-b5cc4b60d6d4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6e5a4939-8abd-4168-b54b-b5cc4b60d6d4' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>msl</span></div><div class='xr-var-dims'>(time, cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2, 65536), meta=np.ndarray&gt;</div><input id='attrs-eb64e201-36a6-4723-87f9-40d872244731' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb64e201-36a6-4723-87f9-40d872244731' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1ae4327-958b-49f1-8be3-c5aec2540e6d' class='xr-var-data-in' type='checkbox'><label for='data-d1ae4327-958b-49f1-8be3-c5aec2540e6d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>151</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>msl</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>name :</span></dt><dd>Mean sea level pressure</dd><dt><span>cfName :</span></dt><dd>air_pressure_at_mean_sea_level</dd><dt><span>cfVarName :</span></dt><dd>msl</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2, 65536) </td>\n",
+       "                        <td> (2, 65536) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >65536</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">2</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-a34d5e78-5317-413f-8f85-df56142fb44c' class='xr-section-summary-in' type='checkbox'  ><label for='section-a34d5e78-5317-413f-8f85-df56142fb44c' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-578c7f20-fe28-4b60-9d6f-9cf0f1b60796' class='xr-index-data-in' type='checkbox'/><label for='index-578c7f20-fe28-4b60-9d6f-9cf0f1b60796' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-01-20 00:00:00&#x27;, &#x27;2020-01-20 01:00:00&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>cell_ids</div></div><div class='xr-index-preview'>HealpixIndex(nside=9, indexing_scheme=nested)</div><input type='checkbox' disabled/><label></label><input id='index-2345b3d0-74ca-4e34-9526-bdb957be0505' class='xr-index-data-in' type='checkbox'/><label for='index-2345b3d0-74ca-4e34-9526-bdb957be0505' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>&lt;xdggs.healpix.HealpixIndex object at 0x7f6e40ac6090&gt;</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ab989da9-6631-4cc4-ac75-aacd4974040a' class='xr-section-summary-in' type='checkbox'  ><label for='section-ab989da9-6631-4cc4-ac75-aacd4974040a' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>edition :</span></dt><dd>2</dd><dt><span>centre :</span></dt><dd>ecmf</dd><dt><span>centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>subCentre :</span></dt><dd>1003</dd><dt><span>history :</span></dt><dd>🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IFSMagician\r\n",
+       "</dd><dt><span>title :</span></dt><dd>nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512</dd><dt><span>description :</span></dt><dd>Simulation data from project &#x27;not Set&#x27; produced by Earth System Model &#x27;not Set&#x27; and run by institution &#x27;ecmf&#x27; for the experiment &#x27;not Set&#x27;</dd><dt><span>time_min :</span></dt><dd>2020-01-20T00:00:00.000000000</dd><dt><span>time_max :</span></dt><dd>2050-01-01T00:00:00.000000000</dd><dt><span>frequency :</span></dt><dd>unknown</dd><dt><span>creation_date :</span></dt><dd>2024-12-14T00:01:16Z</dd><dt><span>authors :</span></dt><dd>Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECMWF), Becker, Tobias (ECMWF), Beyer, Sebastian (AWI), Cheedela, Suvarchal Kumar (AWI), Dreier, Nils-Arne (DKRZ), Engels, Jan Frederik (DKRZ), Esch, Monika (MPIMet), Frauen, Claudia (DKRZ), Klocke, Daniel (MPIMet), Kölling, Tobias (MPIMet), Pedruzo-Bagazgoitia, Xabier (ECMWF), Putrasahan, Dian (MPIMet), Rackow, Thomas (ECMWF), Sidorenko, Dmitry (AWI), Schnur, Reiner (MPIMet), Stevens, Bjorn (MPIMet), Zimmermann, Janos (DKRZ)</dd><dt><span>contact :</span></dt><dd>Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)</dd><dt><span>license :</span></dt><dd>Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 3MB\n",
+       "Dimensions:   (time: 2, cells: 65536)\n",
+       "Coordinates:\n",
+       "    lat       (cells) float64 524kB dask.array<chunksize=(65536,), meta=np.ndarray>\n",
+       "    lon       (cells) float64 524kB dask.array<chunksize=(65536,), meta=np.ndarray>\n",
+       "  * time      (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "  * cell_ids  (cells) int64 524kB 0 1 2 3 4 5 ... 65531 65532 65533 65534 65535\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    msl       (time, cells) float64 1MB dask.array<chunksize=(2, 65536), meta=np.ndarray>\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=9, indexing_scheme=nested)\n",
+       "Attributes: (12/14)\n",
+       "    edition:            2\n",
+       "    centre:             ecmf\n",
+       "    centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    subCentre:          1003\n",
+       "    history:            🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IF...\n",
+       "    title:              nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512\n",
+       "    ...                 ...\n",
+       "    time_max:           2050-01-01T00:00:00.000000000\n",
+       "    frequency:          unknown\n",
+       "    creation_date:      2024-12-14T00:01:16Z\n",
+       "    authors:            Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECM...\n",
+       "    contact:            Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)\n",
+       "    license:            Creative Commons Attribution 4.0 International (CC BY..."
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds = xr.open_dataset(\n",
+    "    \"https://eerie.cloud.dkrz.de/datasets/nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512/zarr\",\n",
+    "    engine=\"zarr\",\n",
+    "    chunks={},\n",
+    "    consolidated=True,\n",
+    ")\n",
+    "ds = (\n",
+    "    ds[[\"msl\"]]\n",
+    "    .rename_dims({\"value\": \"cells\"})\n",
+    "    .assign_coords(\n",
+    "        cell_ids=(\n",
+    "            \"cells\",\n",
+    "            np.arange(12 * 4**9),\n",
+    "            {\"grid_name\": \"healpix\", \"level\": 9, \"indexing_scheme\": \"nested\"},\n",
+    "        )\n",
+    "    )\n",
+    "    .pipe(xdggs.decode)\n",
+    ")\n",
+    "\n",
+    "chunk_late = 12 * (4**2)\n",
+    "chunk_size_9 = int((ds.cells.size) / chunk_late)\n",
+    "# print(\"chunk_size_9\", chunk_size_9)\n",
+    "ds = ds.isel(cells=slice(0, 4 * chunk_size_9), time=slice(0, 2))\n",
+    "# ds = ds.chunk(chunks={\"cells\": chunk_size_9})\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "63c7cf6a-076d-4efb-a259-08b5ac78dfda",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d3ce20ca-d096-4c2a-b195-b9ab87d6d6db",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6638df95-d692-44d8-b118-ba6cffb51a7a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = ds.sel(cell_ids=slice(0, chunk_size_9 * 4)).isel(\n",
+    "    time=slice(0, 2)\n",
+    ")  # .dggs.explore(cmap=\"viridis\", alpha=0.8)  # center=0,"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "68ba89f8-f04c-4b4b-b5ea-72d2bad9cd93",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "root = xr.Dataset(coords={\"time\": ds.coords[\"time\"]})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "810843fa-3d9f-4390-8df3-1a3d4ab195cb",
+   "metadata": {},
+   "source": [
+    "## Create a datatree including different levels of HEALPix data\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "7095715e-d9ff-4370-b999-5f3f62103d48",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plevels = {\"/\": root, \"9\": ds, \"8\": ds_8, \"7\": ds_7}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "afdc0fbf-1960-41c9-8f64-23924b5d1d7c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 16B\n",
+       "Dimensions:  (time: 2)\n",
+       "Coordinates:\n",
+       "  * time     (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "Data variables:\n",
+       "    *empty*</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataTree</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4beab98f-c6bb-4f25-a378-0b12ac4292c8' class='xr-section-summary-in' type='checkbox'  ><label for='section-4beab98f-c6bb-4f25-a378-0b12ac4292c8' class='xr-section-summary' >Groups: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'><div style='display: inline-grid; grid-template-columns: 0px 20px auto; width: 100%;'><div style='grid-column-start: 1;border-right: 0.2em solid;border-color: var(--xr-border-color);height: 100%;width: 0px;'></div><div style='grid-column-start: 2;grid-row-start: 1;height: 1em;width: 20px;border-bottom: 0.2em solid;border-color: var(--xr-border-color);'></div><div style='grid-column-start: 3;'><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 3MB\n",
+       "Dimensions:   (time: 2, cells: 65536)\n",
+       "Coordinates:\n",
+       "  * time      (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "    lat       (cells) float64 524kB dask.array&lt;chunksize=(65536,), meta=np.ndarray&gt;\n",
+       "    lon       (cells) float64 524kB dask.array&lt;chunksize=(65536,), meta=np.ndarray&gt;\n",
+       "  * cell_ids  (cells) int64 524kB 0 1 2 3 4 5 ... 65531 65532 65533 65534 65535\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    msl       (time, cells) float64 1MB dask.array&lt;chunksize=(2, 65536), meta=np.ndarray&gt;\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=9, indexing_scheme=nested)\n",
+       "Attributes: (12/14)\n",
+       "    edition:            2\n",
+       "    centre:             ecmf\n",
+       "    centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    subCentre:          1003\n",
+       "    history:            🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IF...\n",
+       "    title:              nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512\n",
+       "    ...                 ...\n",
+       "    time_max:           2050-01-01T00:00:00.000000000\n",
+       "    frequency:          unknown\n",
+       "    creation_date:      2024-12-14T00:01:16Z\n",
+       "    authors:            Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECM...\n",
+       "    contact:            Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)\n",
+       "    license:            Creative Commons Attribution 4.0 International (CC BY...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>9</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-fa286503-4fe2-4526-affb-effda8212a4d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fa286503-4fe2-4526-affb-effda8212a4d' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'></div></div></li><li class='xr-section-item'><input id='section-35c80501-9922-4dff-94a0-abe595468805' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-35c80501-9922-4dff-94a0-abe595468805' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li><li><span class='xr-has-index'>cells</span>: 65536</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-238d8923-4f00-4672-8b85-0ef4b9cd5a30' class='xr-section-summary-in' type='checkbox'  checked><label for='section-238d8923-4f00-4672-8b85-0ef4b9cd5a30' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(65536,), meta=np.ndarray&gt;</div><input id='attrs-954e4c08-d8a8-45f3-a04d-ef17c39e44d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-954e4c08-d8a8-45f3-a04d-ef17c39e44d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8aced948-61be-4da2-a742-37937b3c5063' class='xr-var-data-in' type='checkbox'><label for='data-8aced948-61be-4da2-a742-37937b3c5063' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512.00 kiB </td>\n",
+       "                        <td> 512.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (65536,) </td>\n",
+       "                        <td> (65536,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >65536</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(65536,), meta=np.ndarray&gt;</div><input id='attrs-12fdb481-501f-4785-a363-420c10489607' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12fdb481-501f-4785-a363-420c10489607' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec884d5d-89d8-4666-81f6-cf6c909f440a' class='xr-var-data-in' type='checkbox'><label for='data-ec884d5d-89d8-4666-81f6-cf6c909f440a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 512.00 kiB </td>\n",
+       "                        <td> 512.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (65536,) </td>\n",
+       "                        <td> (65536,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >65536</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 65532 65533 65534 65535</div><input id='attrs-9c91a671-caf8-470b-bcc8-c55d59eaac42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c91a671-caf8-470b-bcc8-c55d59eaac42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d470f2f1-a0bf-4692-b48b-6d206c3e9fed' class='xr-var-data-in' type='checkbox'><label for='data-d470f2f1-a0bf-4692-b48b-6d206c3e9fed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>9</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><pre>array([    0,     1,     2, ..., 65533, 65534, 65535])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1037fc95-808c-4fa3-af8e-463cd2242d41' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1037fc95-808c-4fa3-af8e-463cd2242d41' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>msl</span></div><div class='xr-var-dims'>(time, cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(2, 65536), meta=np.ndarray&gt;</div><input id='attrs-5ad04156-7a2e-4eb4-aecc-a1872f089844' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ad04156-7a2e-4eb4-aecc-a1872f089844' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1150f7e-c83e-4587-ad18-391b6c548463' class='xr-var-data-in' type='checkbox'><label for='data-b1150f7e-c83e-4587-ad18-391b6c548463' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>151</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>msl</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>name :</span></dt><dd>Mean sea level pressure</dd><dt><span>cfName :</span></dt><dd>air_pressure_at_mean_sea_level</dd><dt><span>cfVarName :</span></dt><dd>msl</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                        <td> 1.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (2, 65536) </td>\n",
+       "                        <td> (2, 65536) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 3 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
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+       "</dd><dt><span>title :</span></dt><dd>nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512</dd><dt><span>description :</span></dt><dd>Simulation data from project &#x27;not Set&#x27; produced by Earth System Model &#x27;not Set&#x27; and run by institution &#x27;ecmf&#x27; for the experiment &#x27;not Set&#x27;</dd><dt><span>time_min :</span></dt><dd>2020-01-20T00:00:00.000000000</dd><dt><span>time_max :</span></dt><dd>2050-01-01T00:00:00.000000000</dd><dt><span>frequency :</span></dt><dd>unknown</dd><dt><span>creation_date :</span></dt><dd>2024-12-14T00:01:16Z</dd><dt><span>authors :</span></dt><dd>Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECMWF), Becker, Tobias (ECMWF), Beyer, Sebastian (AWI), Cheedela, Suvarchal Kumar (AWI), Dreier, Nils-Arne (DKRZ), Engels, Jan Frederik (DKRZ), Esch, Monika (MPIMet), Frauen, Claudia (DKRZ), Klocke, Daniel (MPIMet), Kölling, Tobias (MPIMet), Pedruzo-Bagazgoitia, Xabier (ECMWF), Putrasahan, Dian (MPIMet), Rackow, Thomas (ECMWF), Sidorenko, Dmitry (AWI), Schnur, Reiner (MPIMet), Stevens, Bjorn (MPIMet), Zimmermann, Janos (DKRZ)</dd><dt><span>contact :</span></dt><dd>Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)</dd><dt><span>license :</span></dt><dd>Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)</dd></dl></div></li></ul></div></div></div></div><div style='display: inline-grid; grid-template-columns: 0px 20px auto; width: 100%;'><div style='grid-column-start: 1;border-right: 0.2em solid;border-color: var(--xr-border-color);height: 100%;width: 0px;'></div><div style='grid-column-start: 2;grid-row-start: 1;height: 1em;width: 20px;border-bottom: 0.2em solid;border-color: var(--xr-border-color);'></div><div style='grid-column-start: 3;'><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
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+       "\n",
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+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 25MB\n",
+       "Dimensions:    (time: 2, cells: 786432)\n",
+       "Coordinates:\n",
+       "  * time       (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "  * cell_ids   (cells) int64 6MB dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;\n",
+       "    latitude   (cells) float64 6MB dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;\n",
+       "    longitude  (cells) float64 6MB dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 6MB dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=8, indexing_scheme=nested)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>8</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-45c89d9b-408f-4e70-b430-c3f18b2061c1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-45c89d9b-408f-4e70-b430-c3f18b2061c1' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'></div></div></li><li class='xr-section-item'><input id='section-31b4fefe-364d-40ac-9500-8226005c1139' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-31b4fefe-364d-40ac-9500-8226005c1139' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li><li><span class='xr-has-index'>cells</span>: 786432</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-28242c9d-5fb0-4a11-bde1-df08005e7933' class='xr-section-summary-in' type='checkbox'  checked><label for='section-28242c9d-5fb0-4a11-bde1-df08005e7933' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;</div><input id='attrs-02dc183b-de60-42d0-a43b-415936a3df6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02dc183b-de60-42d0-a43b-415936a3df6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f18ec0a3-6744-4eea-bd94-57e007f92588' class='xr-var-data-in' type='checkbox'><label for='data-f18ec0a3-6744-4eea-bd94-57e007f92588' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>8</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.00 MiB </td>\n",
+       "                        <td> 32.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (786432,) </td>\n",
+       "                        <td> (4096,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >786432</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;</div><input id='attrs-7fc943ba-929a-4440-b4d4-6a2725ce8db1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7fc943ba-929a-4440-b4d4-6a2725ce8db1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9c00577-a1b6-4150-b533-d7ed6d6a17a2' class='xr-var-data-in' type='checkbox'><label for='data-c9c00577-a1b6-4150-b533-d7ed6d6a17a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.00 MiB </td>\n",
+       "                        <td> 32.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (786432,) </td>\n",
+       "                        <td> (4096,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >786432</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4096,), meta=np.ndarray&gt;</div><input id='attrs-40a9d710-6007-4b6c-866d-e9ffd27ef1bc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-40a9d710-6007-4b6c-866d-e9ffd27ef1bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3769e2f-cca3-443c-92c7-0d689a295e01' class='xr-var-data-in' type='checkbox'><label for='data-a3769e2f-cca3-443c-92c7-0d689a295e01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.00 MiB </td>\n",
+       "                        <td> 32.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (786432,) </td>\n",
+       "                        <td> (4096,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >786432</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
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+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.00 MiB </td>\n",
+       "                        <td> 32.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (786432,) </td>\n",
+       "                        <td> (4096,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
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+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
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+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
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+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
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+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
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+       "  margin-top: 0;\n",
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+       "\n",
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+       ".xr-array-name {\n",
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+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
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+       ".xr-section-item input + label {\n",
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+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
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+       "  color: var(--xr-font-color2);\n",
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+       "\n",
+       ".xr-section-item input:focus + label {\n",
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+       "  color: var(--xr-disabled-color);\n",
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+       "\n",
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+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
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+       "\n",
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+       ".xr-dim-list li {\n",
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+       ".xr-dim-list:after {\n",
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+       ".xr-dim-list li:not(:last-child):after {\n",
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+       "\n",
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+       ".xr-var-item label,\n",
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+       "\n",
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+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 6MB\n",
+       "Dimensions:    (time: 2, cells: 196608)\n",
+       "Coordinates:\n",
+       "  * time       (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "  * cell_ids   (cells) int64 2MB dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;\n",
+       "    latitude   (cells) float64 2MB dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;\n",
+       "    longitude  (cells) float64 2MB dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 2MB dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=7, indexing_scheme=nested)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>7</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-07b008bd-dde6-4ff1-9658-817143f77d3c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-07b008bd-dde6-4ff1-9658-817143f77d3c' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'></div></div></li><li class='xr-section-item'><input id='section-8b02c460-c1a5-47e6-a207-55c1a0c566ec' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8b02c460-c1a5-47e6-a207-55c1a0c566ec' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li><li><span class='xr-has-index'>cells</span>: 196608</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-829ad08e-8bb5-4766-a00b-1b0e18e0ee96' class='xr-section-summary-in' type='checkbox'  checked><label for='section-829ad08e-8bb5-4766-a00b-1b0e18e0ee96' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;</div><input id='attrs-e6d471e3-9ef9-4274-a7a9-87af36392c3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6d471e3-9ef9-4274-a7a9-87af36392c3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-828bc9f5-2d2f-41b4-92e4-773491035b1a' class='xr-var-data-in' type='checkbox'><label for='data-828bc9f5-2d2f-41b4-92e4-773491035b1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>7</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 MiB </td>\n",
+       "                        <td> 8.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (196608,) </td>\n",
+       "                        <td> (1024,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >196608</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;</div><input id='attrs-8c199ce9-9285-4d85-9ab3-81a2a69fb5b6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c199ce9-9285-4d85-9ab3-81a2a69fb5b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58c78c14-cd71-4a8b-b70f-ec74381474dd' class='xr-var-data-in' type='checkbox'><label for='data-58c78c14-cd71-4a8b-b70f-ec74381474dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 MiB </td>\n",
+       "                        <td> 8.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (196608,) </td>\n",
+       "                        <td> (1024,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >196608</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;</div><input id='attrs-e0e47e2b-971c-4cd5-a83c-055b41f8198b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e0e47e2b-971c-4cd5-a83c-055b41f8198b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e5d64af-890c-4f24-961a-e6da47e455bf' class='xr-var-data-in' type='checkbox'><label for='data-8e5d64af-890c-4f24-961a-e6da47e455bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 MiB </td>\n",
+       "                        <td> 8.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (196608,) </td>\n",
+       "                        <td> (1024,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"63\" y1=\"0\" x2=\"63\" y2=\"25\" />\n",
+       "  <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"81\" y1=\"0\" x2=\"81\" y2=\"25\" />\n",
+       "  <line x1=\"88\" y1=\"0\" x2=\"88\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >196608</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a59ce6a-5d2a-4670-a71f-a724ba92c8c0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6a59ce6a-5d2a-4670-a71f-a724ba92c8c0' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1024,), meta=np.ndarray&gt;</div><input id='attrs-83fbeb23-d84d-4fc3-b149-c949278121ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-83fbeb23-d84d-4fc3-b149-c949278121ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37dac9fc-a942-4048-a115-6352d75ec551' class='xr-var-data-in' type='checkbox'><label for='data-37dac9fc-a942-4048-a115-6352d75ec551' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 1.50 MiB </td>\n",
+       "                        <td> 8.00 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (196608,) </td>\n",
+       "                        <td> (1024,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 192 chunks in 1 graph layer </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"6\" y1=\"0\" x2=\"6\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
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+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-f2892d3f-5fee-480b-a0d6-8ee2f0fc73c5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f2892d3f-5fee-480b-a0d6-8ee2f0fc73c5' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div></div></div></li><li class='xr-section-item'><input id='section-61628a4e-c060-4ada-8db7-72ead06cbcc5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-61628a4e-c060-4ada-8db7-72ead06cbcc5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-da5b1f02-7d49-475c-b334-113c04daf3c1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-da5b1f02-7d49-475c-b334-113c04daf3c1' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-01-20 2020-01-20T01:00:00</div><input id='attrs-52457daa-c0fe-4598-82ad-27eab863d60d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52457daa-c0fe-4598-82ad-27eab863d60d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51de88fb-eda8-4057-a09b-51a2c62ef0f6' class='xr-var-data-in' type='checkbox'><label for='data-51de88fb-eda8-4057-a09b-51a2c62ef0f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-01-20T00:00:00.000000000&#x27;, &#x27;2020-01-20T01:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0eb04c70-4abb-4dec-ae3d-d225da18d7e2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0eb04c70-4abb-4dec-ae3d-d225da18d7e2' class='xr-section-summary'  title='Expand/collapse section'>Inherited coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-88f15ded-694f-4ffb-ba98-ab2239840e0b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-88f15ded-694f-4ffb-ba98-ab2239840e0b' class='xr-section-summary'  title='Expand/collapse section'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-c0d3d9b7-1ca7-48c3-9ca6-98734f0e946c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c0d3d9b7-1ca7-48c3-9ca6-98734f0e946c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataTree>\n",
+       "Group: /\n",
+       "│   Dimensions:  (time: 2)\n",
+       "│   Coordinates:\n",
+       "│     * time     (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "├── Group: /9\n",
+       "│       Dimensions:   (time: 2, cells: 65536)\n",
+       "│       Coordinates:\n",
+       "│           lat       (cells) float64 524kB dask.array<chunksize=(65536,), meta=np.ndarray>\n",
+       "│           lon       (cells) float64 524kB dask.array<chunksize=(65536,), meta=np.ndarray>\n",
+       "│         * cell_ids  (cells) int64 524kB 0 1 2 3 4 5 ... 65531 65532 65533 65534 65535\n",
+       "│       Dimensions without coordinates: cells\n",
+       "│       Data variables:\n",
+       "│           msl       (time, cells) float64 1MB dask.array<chunksize=(2, 65536), meta=np.ndarray>\n",
+       "│       Indexes:\n",
+       "│           cell_ids  HealpixIndex(nside=9, indexing_scheme=nested)\n",
+       "│       Attributes: (12/14)\n",
+       "│           edition:            2\n",
+       "│           centre:             ecmf\n",
+       "│           centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "│           subCentre:          1003\n",
+       "│           history:            🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IF...\n",
+       "│           title:              nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512\n",
+       "│           ...                 ...\n",
+       "│           time_max:           2050-01-01T00:00:00.000000000\n",
+       "│           frequency:          unknown\n",
+       "│           creation_date:      2024-12-14T00:01:16Z\n",
+       "│           authors:            Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECM...\n",
+       "│           contact:            Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)\n",
+       "│           license:            Creative Commons Attribution 4.0 International (CC BY...\n",
+       "├── Group: /8\n",
+       "│       Dimensions:    (cells: 786432)\n",
+       "│       Coordinates:\n",
+       "│         * cell_ids   (cells) int64 6MB dask.array<chunksize=(4096,), meta=np.ndarray>\n",
+       "│           latitude   (cells) float64 6MB dask.array<chunksize=(4096,), meta=np.ndarray>\n",
+       "│           longitude  (cells) float64 6MB dask.array<chunksize=(4096,), meta=np.ndarray>\n",
+       "│       Dimensions without coordinates: cells\n",
+       "│       Data variables:\n",
+       "│           data       (cells) float64 6MB dask.array<chunksize=(4096,), meta=np.ndarray>\n",
+       "│       Indexes:\n",
+       "│           cell_ids  HealpixIndex(nside=8, indexing_scheme=nested)\n",
+       "└── Group: /7\n",
+       "        Dimensions:    (cells: 196608)\n",
+       "        Coordinates:\n",
+       "          * cell_ids   (cells) int64 2MB dask.array<chunksize=(1024,), meta=np.ndarray>\n",
+       "            latitude   (cells) float64 2MB dask.array<chunksize=(1024,), meta=np.ndarray>\n",
+       "            longitude  (cells) float64 2MB dask.array<chunksize=(1024,), meta=np.ndarray>\n",
+       "        Dimensions without coordinates: cells\n",
+       "        Data variables:\n",
+       "            data       (cells) float64 2MB dask.array<chunksize=(1024,), meta=np.ndarray>\n",
+       "        Indexes:\n",
+       "            cell_ids  HealpixIndex(nside=7, indexing_scheme=nested)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_all = xr.DataTree.from_dict(plevels)\n",
+    "ds_all"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c269f923-1bc1-4865-b3ac-997c799e2727",
+   "metadata": {},
+   "source": [
+    "## Save it to zarr\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3d0b2165-bef3-457d-b80c-1b6789a947e2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "ec498f96-8087-4282-a088-28b73e26e319",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_all.to_zarr(\"tree.zarr\", mode=\"w\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ecd4aff4-3373-4aca-8eaf-d641c38aa942",
+   "metadata": {},
+   "source": [
+    "### Plotting with xdggs is very simple, just use 'explore' function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "76fad969-05e9-42dd-98a7-26ce5b2a88d0",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "data = xr.open_datatree(\"tree.zarr\")\n",
+    "data\n",
+    "test = data[\"9\"][\"msl\"].isel(time=0).compute()\n",
+    "# test = data[\"7\"][\"data\"].compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "373b7b1f-fff6-4b26-aa3c-80651199129d",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "map2 = test.pipe(xdggs.decode).dggs.explore(center=0, cmap=\"coolwarm\", alpha=0.8)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b4762c84-9d04-49bc-a383-d754f360fd35",
+   "metadata": {},
+   "source": [
+    "### Selecting region to plot\n",
+    "#### Selection using healpix cell_ids"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "6ddad55a-cf8d-4446-907d-48c0d31045cd",
+   "metadata": {},
+   "outputs": [
+    {
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+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 16B\n",
+       "Dimensions:  (time: 2)\n",
+       "Coordinates:\n",
+       "  * time     (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "Data variables:\n",
+       "    *empty*</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataTree</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0bb686f9-d7a6-4e3d-91f3-3bd4e4ef7597' class='xr-section-summary-in' type='checkbox'  ><label for='section-0bb686f9-d7a6-4e3d-91f3-3bd4e4ef7597' class='xr-section-summary' >Groups: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'><div style='display: inline-grid; grid-template-columns: 0px 20px auto; width: 100%;'><div style='grid-column-start: 1;border-right: 0.2em solid;border-color: var(--xr-border-color);height: 100%;width: 0px;'></div><div style='grid-column-start: 2;grid-row-start: 1;height: 1em;width: 20px;border-bottom: 0.2em solid;border-color: var(--xr-border-color);'></div><div style='grid-column-start: 3;'><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 6MB\n",
+       "Dimensions:    (time: 2, cells: 196608)\n",
+       "Coordinates:\n",
+       "  * time       (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "    cell_ids   (cells) int64 2MB ...\n",
+       "    latitude   (cells) float64 2MB ...\n",
+       "    longitude  (cells) float64 2MB ...\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 2MB ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>7</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9da6a89a-1b15-445f-9937-9a4e2d907b1b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9da6a89a-1b15-445f-9937-9a4e2d907b1b' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'></div></div></li><li class='xr-section-item'><input id='section-0402bd8c-b4ae-4662-841b-58850ee89fc0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0402bd8c-b4ae-4662-841b-58850ee89fc0' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li><li><span>cells</span>: 196608</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0f0d27d9-ed6c-408f-ae41-9e60fd330792' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0f0d27d9-ed6c-408f-ae41-9e60fd330792' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2bd5f52f-9639-4beb-b61f-4aece599c5fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bd5f52f-9639-4beb-b61f-4aece599c5fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa520aa0-fce1-4e64-9ca8-002ac7361836' class='xr-var-data-in' type='checkbox'><label for='data-fa520aa0-fce1-4e64-9ca8-002ac7361836' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd><dt><span>level :</span></dt><dd>7</dd></dl></div><div class='xr-var-data'><pre>[196608 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-53991d7e-624c-42ee-8b50-b2708cf01ca3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53991d7e-624c-42ee-8b50-b2708cf01ca3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0fbf99c-eade-4db2-ae5e-1b1be127eecc' class='xr-var-data-in' type='checkbox'><label for='data-c0fbf99c-eade-4db2-ae5e-1b1be127eecc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[196608 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1067445d-1fb9-457b-8f4f-5ac352f226a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1067445d-1fb9-457b-8f4f-5ac352f226a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb397c8b-5575-4698-aff7-e2b080dcd7c5' class='xr-var-data-in' type='checkbox'><label for='data-eb397c8b-5575-4698-aff7-e2b080dcd7c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[196608 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-18dd6b0e-8199-4a6e-98b2-4f17f48bcbc5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-18dd6b0e-8199-4a6e-98b2-4f17f48bcbc5' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bea6f6bf-bf3a-4c3b-9f51-cbb640c785a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bea6f6bf-bf3a-4c3b-9f51-cbb640c785a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f00a96f-988e-41ac-ab8a-919e5ada77db' class='xr-var-data-in' type='checkbox'><label for='data-5f00a96f-988e-41ac-ab8a-919e5ada77db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[196608 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e72e2398-bee8-49ba-a94d-bf478e66c9ba' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e72e2398-bee8-49ba-a94d-bf478e66c9ba' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div><div style='display: inline-grid; grid-template-columns: 0px 20px auto; width: 100%;'><div style='grid-column-start: 1;border-right: 0.2em solid;border-color: var(--xr-border-color);height: 100%;width: 0px;'></div><div style='grid-column-start: 2;grid-row-start: 1;height: 1em;width: 20px;border-bottom: 0.2em solid;border-color: var(--xr-border-color);'></div><div style='grid-column-start: 3;'><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 25MB\n",
+       "Dimensions:    (time: 2, cells: 786432)\n",
+       "Coordinates:\n",
+       "  * time       (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "    cell_ids   (cells) int64 6MB 0 1 2 3 4 ... 786428 786429 786430 786431\n",
+       "    latitude   (cells) float64 6MB ...\n",
+       "    longitude  (cells) float64 6MB ...\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 6MB ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>8</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f55ae0fa-3e99-4ce5-af89-45d6b036fcaf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f55ae0fa-3e99-4ce5-af89-45d6b036fcaf' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'></div></div></li><li class='xr-section-item'><input id='section-19a19bb9-a087-4e06-b950-c1b67f425451' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-19a19bb9-a087-4e06-b950-c1b67f425451' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li><li><span>cells</span>: 786432</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6393833c-12d6-42a5-9b9e-8b2bf93d3f5f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6393833c-12d6-42a5-9b9e-8b2bf93d3f5f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 786429 786430 786431</div><input id='attrs-dac24105-33ab-4c91-8028-06b409396db8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dac24105-33ab-4c91-8028-06b409396db8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-837e39ad-8dfb-4fe5-94ff-e1ccc0407d87' class='xr-var-data-in' type='checkbox'><label for='data-837e39ad-8dfb-4fe5-94ff-e1ccc0407d87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd><dt><span>level :</span></dt><dd>8</dd></dl></div><div class='xr-var-data'><pre>array([     0,      1,      2, ..., 786429, 786430, 786431])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dc3cb51b-49d0-44c6-b04f-06aa6f05d5fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dc3cb51b-49d0-44c6-b04f-06aa6f05d5fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e3494e1-d47f-4267-9fab-c733087130f4' class='xr-var-data-in' type='checkbox'><label for='data-3e3494e1-d47f-4267-9fab-c733087130f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[786432 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-918b9f08-8c60-4cdf-92a0-ad7f65cac1e4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-918b9f08-8c60-4cdf-92a0-ad7f65cac1e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9e08937-cda5-476e-8a00-210945299e20' class='xr-var-data-in' type='checkbox'><label for='data-d9e08937-cda5-476e-8a00-210945299e20' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[786432 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e6d27ccd-a297-47a4-a08f-87d78e85e419' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e6d27ccd-a297-47a4-a08f-87d78e85e419' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-27fbd70e-1d71-442f-98ae-a9f78856bd23' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-27fbd70e-1d71-442f-98ae-a9f78856bd23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e95e8c1-986d-4cbb-bca3-6f981aab07d7' class='xr-var-data-in' type='checkbox'><label for='data-7e95e8c1-986d-4cbb-bca3-6f981aab07d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[786432 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-97d01999-f02f-48ca-9302-f443bdb01930' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-97d01999-f02f-48ca-9302-f443bdb01930' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div><div style='display: inline-grid; grid-template-columns: 0px 20px auto; width: 100%;'><div style='grid-column-start: 1;border-right: 0.2em solid;border-color: var(--xr-border-color);height: 1.2em;width: 0px;'></div><div style='grid-column-start: 2;grid-row-start: 1;height: 1em;width: 20px;border-bottom: 0.2em solid;border-color: var(--xr-border-color);'></div><div style='grid-column-start: 3;'><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 3MB\n",
+       "Dimensions:   (time: 2, cells: 65536)\n",
+       "Coordinates:\n",
+       "  * time      (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "    cell_ids  (cells) int64 524kB ...\n",
+       "    lat       (cells) float64 524kB ...\n",
+       "    lon       (cells) float64 524kB ...\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    msl       (time, cells) float64 1MB ...\n",
+       "Attributes: (12/14)\n",
+       "    authors:            Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECM...\n",
+       "    centre:             ecmf\n",
+       "    centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    contact:            Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)\n",
+       "    creation_date:      2024-12-14T00:01:16Z\n",
+       "    description:        Simulation data from project &#x27;not Set&#x27; produced by Ea...\n",
+       "    ...                 ...\n",
+       "    history:            🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IF...\n",
+       "    license:            Creative Commons Attribution 4.0 International (CC BY...\n",
+       "    subCentre:          1003\n",
+       "    time_max:           2050-01-01T00:00:00.000000000\n",
+       "    time_min:           2020-01-20T00:00:00.000000000\n",
+       "    title:              nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>9</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b1974ce1-859e-49ea-bfa0-b67145efebdb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b1974ce1-859e-49ea-bfa0-b67145efebdb' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'></div></div></li><li class='xr-section-item'><input id='section-f656e596-02ea-4195-a22b-ec0662758d31' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f656e596-02ea-4195-a22b-ec0662758d31' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li><li><span>cells</span>: 65536</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-84a9aebd-c58b-4c51-af97-e3c479fdf2db' class='xr-section-summary-in' type='checkbox'  checked><label for='section-84a9aebd-c58b-4c51-af97-e3c479fdf2db' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-77d8459c-d6e2-4f3e-9d34-0eca5745dcdc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77d8459c-d6e2-4f3e-9d34-0eca5745dcdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f91e5c19-7747-4b90-86a3-af52c5a4abb2' class='xr-var-data-in' type='checkbox'><label for='data-f91e5c19-7747-4b90-86a3-af52c5a4abb2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd><dt><span>level :</span></dt><dd>9</dd></dl></div><div class='xr-var-data'><pre>[65536 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-87240f67-103d-49eb-aac9-b7a9ad383800' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87240f67-103d-49eb-aac9-b7a9ad383800' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-101885aa-3f67-42f5-905c-f9deb707314a' class='xr-var-data-in' type='checkbox'><label for='data-101885aa-3f67-42f5-905c-f9deb707314a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>[65536 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f4d278b9-4c38-44d4-97af-00a29822aa98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4d278b9-4c38-44d4-97af-00a29822aa98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a88f0ca-ae14-423c-b18f-0c144fa8f65d' class='xr-var-data-in' type='checkbox'><label for='data-4a88f0ca-ae14-423c-b18f-0c144fa8f65d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>[65536 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c80a72e3-b26e-424e-8f55-0f091554eed1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c80a72e3-b26e-424e-8f55-0f091554eed1' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>msl</span></div><div class='xr-var-dims'>(time, cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6f0baead-f352-4ce7-a0f3-44aba7112aea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f0baead-f352-4ce7-a0f3-44aba7112aea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4146e952-2f82-4504-9162-017fb6fc25a2' class='xr-var-data-in' type='checkbox'><label for='data-4146e952-2f82-4504-9162-017fb6fc25a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>NV :</span></dt><dd>0</dd><dt><span>cfName :</span></dt><dd>air_pressure_at_mean_sea_level</dd><dt><span>cfVarName :</span></dt><dd>msl</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>name :</span></dt><dd>Mean sea level pressure</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>paramId :</span></dt><dd>151</dd><dt><span>shortName :</span></dt><dd>msl</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>[131072 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a5247680-b79e-47bf-a553-d1e04e89e6b4' class='xr-section-summary-in' type='checkbox'  ><label for='section-a5247680-b79e-47bf-a553-d1e04e89e6b4' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>authors :</span></dt><dd>Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECMWF), Becker, Tobias (ECMWF), Beyer, Sebastian (AWI), Cheedela, Suvarchal Kumar (AWI), Dreier, Nils-Arne (DKRZ), Engels, Jan Frederik (DKRZ), Esch, Monika (MPIMet), Frauen, Claudia (DKRZ), Klocke, Daniel (MPIMet), Kölling, Tobias (MPIMet), Pedruzo-Bagazgoitia, Xabier (ECMWF), Putrasahan, Dian (MPIMet), Rackow, Thomas (ECMWF), Sidorenko, Dmitry (AWI), Schnur, Reiner (MPIMet), Stevens, Bjorn (MPIMet), Zimmermann, Janos (DKRZ)</dd><dt><span>centre :</span></dt><dd>ecmf</dd><dt><span>centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>contact :</span></dt><dd>Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)</dd><dt><span>creation_date :</span></dt><dd>2024-12-14T00:01:16Z</dd><dt><span>description :</span></dt><dd>Simulation data from project &#x27;not Set&#x27; produced by Earth System Model &#x27;not Set&#x27; and run by institution &#x27;ecmf&#x27; for the experiment &#x27;not Set&#x27;</dd><dt><span>edition :</span></dt><dd>2</dd><dt><span>frequency :</span></dt><dd>unknown</dd><dt><span>history :</span></dt><dd>🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IFSMagician\r\n",
+       "</dd><dt><span>license :</span></dt><dd>Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)</dd><dt><span>subCentre :</span></dt><dd>1003</dd><dt><span>time_max :</span></dt><dd>2050-01-01T00:00:00.000000000</dd><dt><span>time_min :</span></dt><dd>2020-01-20T00:00:00.000000000</dd><dt><span>title :</span></dt><dd>nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512</dd></dl></div></li></ul></div></div></div></div></div></div></li><li class='xr-section-item'><input id='section-992c2c56-a57e-42e6-9177-6767a3b23085' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-992c2c56-a57e-42e6-9177-6767a3b23085' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-356267b6-3353-4ecb-b60e-2210b839e1aa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-356267b6-3353-4ecb-b60e-2210b839e1aa' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-01-20 2020-01-20T01:00:00</div><input id='attrs-491aa627-46aa-4cdd-b01c-35c3d28a492a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-491aa627-46aa-4cdd-b01c-35c3d28a492a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11126cc8-0120-4875-8ea2-8adc9778b3d2' class='xr-var-data-in' type='checkbox'><label for='data-11126cc8-0120-4875-8ea2-8adc9778b3d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-01-20T00:00:00.000000000&#x27;, &#x27;2020-01-20T01:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-87b1357f-91f8-4eef-9d12-0dccd0c73845' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-87b1357f-91f8-4eef-9d12-0dccd0c73845' class='xr-section-summary'  title='Expand/collapse section'>Inherited coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-ddec3413-397b-4d61-832b-e9f16ba9eacd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ddec3413-397b-4d61-832b-e9f16ba9eacd' class='xr-section-summary'  title='Expand/collapse section'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-087d6b34-5d69-4ca7-a016-8a772ce27ec1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-087d6b34-5d69-4ca7-a016-8a772ce27ec1' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataTree>\n",
+       "Group: /\n",
+       "│   Dimensions:  (time: 2)\n",
+       "│   Coordinates:\n",
+       "│     * time     (time) datetime64[ns] 16B 2020-01-20 2020-01-20T01:00:00\n",
+       "├── Group: /7\n",
+       "│       Dimensions:    (cells: 196608)\n",
+       "│       Coordinates:\n",
+       "│           cell_ids   (cells) int64 2MB ...\n",
+       "│           latitude   (cells) float64 2MB ...\n",
+       "│           longitude  (cells) float64 2MB ...\n",
+       "│       Dimensions without coordinates: cells\n",
+       "│       Data variables:\n",
+       "│           data       (cells) float64 2MB ...\n",
+       "├── Group: /8\n",
+       "│       Dimensions:    (cells: 786432)\n",
+       "│       Coordinates:\n",
+       "│           cell_ids   (cells) int64 6MB 0 1 2 3 4 ... 786428 786429 786430 786431\n",
+       "│           latitude   (cells) float64 6MB ...\n",
+       "│           longitude  (cells) float64 6MB ...\n",
+       "│       Dimensions without coordinates: cells\n",
+       "│       Data variables:\n",
+       "│           data       (cells) float64 6MB ...\n",
+       "└── Group: /9\n",
+       "        Dimensions:   (cells: 65536, time: 2)\n",
+       "        Coordinates:\n",
+       "            cell_ids  (cells) int64 524kB ...\n",
+       "            lat       (cells) float64 524kB ...\n",
+       "            lon       (cells) float64 524kB ...\n",
+       "        Dimensions without coordinates: cells\n",
+       "        Data variables:\n",
+       "            msl       (time, cells) float64 1MB ...\n",
+       "        Attributes: (12/14)\n",
+       "            authors:            Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECM...\n",
+       "            centre:             ecmf\n",
+       "            centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "            contact:            Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)\n",
+       "            creation_date:      2024-12-14T00:01:16Z\n",
+       "            description:        Simulation data from project 'not Set' produced by Ea...\n",
+       "            ...                 ...\n",
+       "            history:            🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IF...\n",
+       "            license:            Creative Commons Attribution 4.0 International (CC BY...\n",
+       "            subCentre:          1003\n",
+       "            time_max:           2050-01-01T00:00:00.000000000\n",
+       "            time_min:           2020-01-20T00:00:00.000000000\n",
+       "            title:              nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "e6678ba9-a8f4-47a6-a349-eebcc15a8a84",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6fa41089817045859d7122abeca04b9e",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f6e3b24…"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(\n",
+    "    data[\"7\"]\n",
+    "    .ds.pipe(xdggs.decode)\n",
+    "    .sel(cell_ids=slice(11000, 11100))[\"data\"]\n",
+    "    .dggs.explore(cmap=\"viridis\", alpha=0.8)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "2b2f3975-df36-4835-9bf2-dd2fd8b24cef",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0db4a87dec4842beb60018aefe806f58",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f6e287d…"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(\n",
+    "    data[\"8\"]\n",
+    "    .ds.pipe(xdggs.decode)\n",
+    "    .sel(cell_ids=slice(0, 1000))[\"data\"]\n",
+    "    .dggs.explore(cmap=\"viridis\", alpha=0.8)\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "26d27b4a-2423-4758-9139-aee69f3decc9",
+   "metadata": {},
+   "source": [
+    "#### Selection using latitude and longitude"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6274e5ce-7532-42f3-ae2f-c01ed73bee8e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "77961e92-ab5e-4eeb-876e-1ce577d2efac",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "f5aff0ac-c8b5-4fc1-a766-e460a51624f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b4c2c8aefe5a48659417a0594a00feea",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f6e3b6b…"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(\n",
+    "    data[\"7\"].ds.pipe(xdggs.decode).dggs.sel_latlon(latitude=48, longitude=0)[\"data\"]\n",
+    ").dggs.explore(center=0, cmap=\"viridis\", alpha=0.8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "a7b59a52-2de1-4116-8ab2-c93f9028cc61",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "61fef5f95e7f47eba09ca8ff2aab353d",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f6dfe74…"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(\n",
+    "    data[\"8\"]\n",
+    "    .ds[\"data\"]\n",
+    "    .pipe(xdggs.decode)\n",
+    "    .dggs.sel_latlon(longitude=[48, 47, 46], latitude=[-5, -5.3, -5.5])\n",
+    ").dggs.explore(center=0, cmap=\"viridis\", alpha=0.8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "37811f0c-bc79-4d5f-b71f-a465fccd2c1d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lat = np.arange(48.5, 49, 0.01)\n",
+    "lon = np.arange(0, 1, 0.01)\n",
+    "full_lat = np.repeat(lat, len(lon))\n",
+    "full_lon = np.tile(lon, len(lat))\n",
+    "\n",
+    "map1 = (\n",
+    "    data[\"8\"]\n",
+    "    .ds[\"data\"]\n",
+    "    .pipe(xdggs.decode)\n",
+    "    .dggs.sel_latlon(longitude=full_lon, latitude=full_lat)\n",
+    ").dggs.explore(center=0, cmap=\"viridis\", alpha=0.8)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9517d1eb-565d-4ebc-9be0-d73488e34757",
+   "metadata": {},
+   "source": [
+    "## Current Issue with Testing Different Datatree\n",
+    "\n",
+    "The levels exist “outside” the dataset, rather than being part of each coordinate, dimension, or data array. For me, this feels strange, as I believe levels should be integrated into each coordinate, dimension, or data array.\n",
+    "This is because we are re-using the Datatree concept, which may need improvement in future.  \n",
+    "\n",
+    "\n",
+    "## Whats next\n",
+    "\n",
+    "Plot different levels in a same figure using lonboard.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "a0beb228-43e0-4c8d-9111-da23ddbdfaa2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "\n",
+    "def create_arrow_table(polygons, arr, coords=None):\n",
+    "    from arro3.core import Array, ChunkedArray, Schema, Table\n",
+    "\n",
+    "    if coords is None:\n",
+    "        coords = [\"latitude\", \"longitude\"]\n",
+    "\n",
+    "    array = Array.from_arrow(polygons)\n",
+    "    name = arr.name or \"data\"\n",
+    "    arrow_arrays = {\n",
+    "        \"geometry\": array,\n",
+    "        \"cell_ids\": ChunkedArray([Array.from_numpy(arr.coords[\"cell_ids\"])]),\n",
+    "        name: ChunkedArray([Array.from_numpy(arr.data)]),\n",
+    "    } | {\n",
+    "        coord: ChunkedArray([Array.from_numpy(arr.coords[coord].data)])\n",
+    "        for coord in coords\n",
+    "        if coord in arr.coords\n",
+    "    }\n",
+    "\n",
+    "    fields = [array.field.with_name(name) for name, array in arrow_arrays.items()]\n",
+    "    schema = Schema(fields)\n",
+    "\n",
+    "    return Table.from_arrays(list(arrow_arrays.values()), schema=schema)\n",
+    "\n",
+    "\n",
+    "def normalize(var, center=None):\n",
+    "    from matplotlib.colors import CenteredNorm, Normalize\n",
+    "\n",
+    "    if center is None:\n",
+    "        vmin = var.min(skipna=True)\n",
+    "        vmax = var.max(skipna=True)\n",
+    "        normalizer = Normalize(vmin=vmin, vmax=vmax)\n",
+    "    else:\n",
+    "        halfrange = np.abs(var - center).max(skipna=True)\n",
+    "        normalizer = CenteredNorm(vcenter=center, halfrange=halfrange)\n",
+    "\n",
+    "    return normalizer(var.data)\n",
+    "\n",
+    "\n",
+    "def exploire_layer(\n",
+    "    arr,\n",
+    "    cell_dim=\"cells\",\n",
+    "    cmap=\"viridis\",\n",
+    "    center=None,\n",
+    "    alpha=None,\n",
+    "):\n",
+    "    from lonboard import SolidPolygonLayer\n",
+    "    from lonboard.colormap import apply_continuous_cmap\n",
+    "    from matplotlib import colormaps\n",
+    "\n",
+    "    if len(arr.dims) != 1 or cell_dim not in arr.dims:\n",
+    "        raise ValueError(\n",
+    "            f\"exploration only works with a single dimension ('{cell_dim}')\"\n",
+    "        )\n",
+    "\n",
+    "    cell_ids = arr.dggs.coord.data\n",
+    "    grid_info = arr.dggs.grid_info\n",
+    "\n",
+    "    polygons = grid_info.cell_boundaries(cell_ids, backend=\"geoarrow\")\n",
+    "\n",
+    "    normalized_data = normalize(arr.variable, center=center)\n",
+    "\n",
+    "    colormap = colormaps[cmap]\n",
+    "    colors = apply_continuous_cmap(normalized_data, colormap, alpha=alpha)\n",
+    "\n",
+    "    table = create_arrow_table(polygons, arr)\n",
+    "    layer = SolidPolygonLayer(table=table, filled=True, get_fill_color=colors)\n",
+    "\n",
+    "    return layer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5699b8d2-af07-45ef-9393-26bc8bc962a9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1b69d393-3d18-468e-916e-20b2d596990a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "eb7b0881-13a8-473c-b442-66ffdd0d9f6e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1d7260054fc74b70bbf001bf4108893c",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f6dfd19…"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import lonboard\n",
+    "\n",
+    "arr = data[\"7\"].ds.pipe(xdggs.decode).dggs.sel_latlon(latitude=48, longitude=0)[\"data\"]\n",
+    "arr2 = data[\"8\"].ds.pipe(xdggs.decode).dggs.sel_latlon(latitude=49, longitude=0)[\"data\"]\n",
+    "arr3 = data[\"9\"].isel(time=0).ds.pipe(xdggs.decode)[\"msl\"]\n",
+    "lonboard.Map(\n",
+    "    [\n",
+    "        exploire_layer(arr2, alpha=0.8),\n",
+    "        exploire_layer(arr, alpha=0.5),\n",
+    "        exploire_layer(arr3, alpha=0.1),\n",
+    "    ]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ddf9987a-f7c6-4874-9c4c-a81fd6d6ab45",
+   "metadata": {},
+   "source": [
+    "## Whats next\n",
+    "\n",
+    "Use WW3 unstructured grid originated data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "58f197a9-8ffd-4e17-8afe-59e2e41c6d44",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/visualisation/xdggs-explore-demo.ipynb b/visualisation/xdggs-explore-demo.ipynb
new file mode 100644
index 0000000..8312dc7
--- /dev/null
+++ b/visualisation/xdggs-explore-demo.ipynb
@@ -0,0 +1,7444 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d340a5ff-db29-4c13-8d7f-f02870e6ad17",
+   "metadata": {},
+   "source": [
+    "# Plotting HEALPix Data with XDGGS and Lonboard\n",
+    "\n",
+    "In this notebook, we will demonstrate several examples of plotting HEALPix data.  \n",
+    "This notebook is prepared for a poster presentation at the 3rd Destination Earth User eXchange, held from October 15 - October 16, 2024, in Darmstadt. You can find more information about the event here: [3rd Destination Earth User eXchange](https://destination-earth.eu/event/3rd-destination-earth-user-exchange/).\n",
+    "\n",
+    "Link to the poster on Zenodo: *[Insert link]*.\n",
+    "\n",
+    "## Setup\n",
+    "\n",
+    "To run this notebook, you need to install XDGGS along with Lonboard. You can find the xdggs repository here: [XDGGS GitHub Repository](https://github.com/xarray-contrib/xdggs.git).\n",
+    "\n",
+    "\n",
+    "1. You can either install `xdggs` with the necessary dependencies, use the following command:\n",
+    "\n",
+    "```bash\n",
+    "pip install xdggs\n",
+    "```\n",
+    "\n",
+    "This command installs the XDGGS package and it will also install all the required libraries, such as:\n",
+    "\n",
+    "- `xarray`\n",
+    "- `numpy`\n",
+    "- `xdggs`\n",
+    "- `lonboard`\n",
+    "- `arro3-core`\n",
+    "- `matplotlib`\n",
+    "\n",
+    "2. or use the `environment.yml` file that is made available in the `xdggs` examples github repository: [https://github.com/xdggs/examples/blob/main/.binder/environment.yml](https://github.com/xdggs/examples/blob/main/.binder/environment.yml)\n",
+    "\n",
+    "## Why Use Lonboard for Plotting in XDGGS?\n",
+    "\n",
+    "Lonboard uses GPU-based rendering, specifically leveraging WebGL through deck.gl. This enables efficient handling of large datasets, allowing for fast, interactive visualization of geospatial data directly in a browser. GPU-based rendering is essential when working with large-scale datasets that could slow down or crash traditional plotting libraries.\n",
+    "\n",
+    "Lonboard's high performance stems from its use of binary data formats such as GeoArrow and GeoParquet, which minimize data transfer and processing overhead. Unlike traditional libraries that rely on text formats like GeoJSON, Lonboard maintains a binary format throughout the entire pipeline. This approach reduces the number of data copies and avoids costly format conversions, leading to faster data transfers and more efficient rendering."
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "5be1eb97-2069-42c5-b23f-db5c7dc18a41",
+   "metadata": {
+    "collapsed": true,
+    "jupyter": {
+     "outputs_hidden": true
+    }
+   },
+   "source": [
+    "#Lets install our latest xdggs package with plotting functionality\n",
+    "\n",
+    "!pip install xdggs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "36cf9310-b950-4ff2-96ac-8b654b411947",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "import xdggs\n",
+    "\n",
+    "import warnings\n",
+    "\n",
+    "warnings.filterwarnings(\"ignore\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "68c364ab-3db3-42c9-9872-83b83b599ae5",
+   "metadata": {},
+   "source": [
+    "##  Plotting generated test dataset\n",
+    "HEALPix is designed to represent the sphere using spherical harmonics functions.\n",
+    "Following code with generate a test dateset. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "63afde4d-e99b-4f8c-9047-6ac44f5a2dc6",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x500 with 16 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import healpy as hp\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "lmax = 3\n",
+    "level = 8\n",
+    "nside = 2**level\n",
+    "# compute Alm\n",
+    "# get the l and m availble for l<=lmax\n",
+    "l, m = hp.Alm.getlm(lmax=lmax)  # noqa: E741\n",
+    "\n",
+    "# count the number of alm map (1 for m=0 and 2 for m>0)\n",
+    "n_alm = (m == 0).sum() + 2 * (m > 0).sum()\n",
+    "function = np.zeros([n_alm, 12 * nside**2])\n",
+    "\n",
+    "alm = np.zeros([l.shape[0]], dtype=\"complex\")\n",
+    "\n",
+    "i = 0\n",
+    "\n",
+    "# array to store the l and m values of the A_lm\n",
+    "l_func = np.zeros(n_alm, dtype=\"int\")\n",
+    "m_func = np.zeros(n_alm, dtype=\"int\")\n",
+    "is_real_func = np.zeros(n_alm, dtype=\"int\")\n",
+    "\n",
+    "for k in range(l.shape[0]):\n",
+    "    alm[k] = 1.0\n",
+    "    function[i] = hp.reorder(hp.alm2map(alm, nside), r2n=True)\n",
+    "    l_func[i] = l[k]\n",
+    "    m_func[i] = m[k]\n",
+    "    is_real_func[i] = 1\n",
+    "    i += 1\n",
+    "    if m[k] > 0:\n",
+    "        alm[k] = complex(0, 1)\n",
+    "        function[i] = hp.reorder(hp.alm2map(alm, nside), r2n=True)\n",
+    "        l_func[i] = l[k]\n",
+    "        m_func[i] = m[k]\n",
+    "        is_real_func[i] = 0\n",
+    "        i += 1\n",
+    "    alm[k] = 0.0\n",
+    "lm = 3\n",
+    "plt.figure(figsize=(12, 5))\n",
+    "for k in range(l_func.shape[0]):\n",
+    "    pos = (\n",
+    "        1\n",
+    "        + l_func[k] * (2 * lm + 1)\n",
+    "        + 2 * (is_real_func[k] - 0.5) * m_func[k]\n",
+    "        - 1\n",
+    "        + (lm + 1)\n",
+    "    )\n",
+    "    if is_real_func[k] == 1:\n",
+    "        title = \"$\\mathbb{R}(A_{\\ell=%d,m=%d})$\" % (l_func[k], m_func[k])\n",
+    "    else:\n",
+    "        title = \"$\\mathbb{I}(A_{\\ell=%d,m=%d})$\" % (l_func[k], m_func[k])\n",
+    "    if l_func[k] <= lm:\n",
+    "        hp.mollview(\n",
+    "            function[k],\n",
+    "            nest=True,\n",
+    "            hold=False,\n",
+    "            sub=(lm + 1, 2 * lm + 1, pos),\n",
+    "            title=title,\n",
+    "            cbar=False,\n",
+    "            cmap=\"coolwarm\",\n",
+    "        )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "e9066875-192b-4993-90eb-b309a7512d37",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
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+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
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+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
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+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 31MB\n",
+       "Dimensions:    (cells: 786432)\n",
+       "Coordinates:\n",
+       "  * cell_ids   (cells) int64 6MB 0 1 2 3 4 ... 786428 786429 786430 786431\n",
+       "    latitude   (cells) float64 6MB 0.1492 0.2984 0.2984 ... -0.2984 -0.1492\n",
+       "    longitude  (cells) float64 6MB 45.0 45.18 44.82 45.0 ... 315.2 314.8 315.0\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 6MB -0.9999 -0.9993 -0.9993 ... 0.9993 0.9999\n",
+       "    SH_L3_M2   (cells) float64 6MB -0.005323 -0.01065 ... -0.01065 -0.005323\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=8, indexing_scheme=nested, rotation=[0.0, 0.0])</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f73dd7e6-d254-4b20-9043-8ba39a397647' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f73dd7e6-d254-4b20-9043-8ba39a397647' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>cells</span>: 786432</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-05b8de7b-a315-4a1c-baca-4ba04ef1aa5e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-05b8de7b-a315-4a1c-baca-4ba04ef1aa5e' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 786429 786430 786431</div><input id='attrs-345e1a10-cf7c-4ddf-8f5d-f02b9cf61be2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-345e1a10-cf7c-4ddf-8f5d-f02b9cf61be2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db92c05d-3c78-4bf3-89b0-48adf9bff3ae' class='xr-var-data-in' type='checkbox'><label for='data-db92c05d-3c78-4bf3-89b0-48adf9bff3ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>8</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><pre>array([     0,      1,      2, ..., 786429, 786430, 786431])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1492 0.2984 ... -0.2984 -0.1492</div><input id='attrs-b63e0125-b40c-4d3c-9bce-a07ec261dfa6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b63e0125-b40c-4d3c-9bce-a07ec261dfa6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4feb661-5281-41e4-91db-e593c071c5f8' class='xr-var-data-in' type='checkbox'><label for='data-f4feb661-5281-41e4-91db-e593c071c5f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0.14920793,  0.29841687,  0.29841687, ..., -0.29841687,\n",
+       "       -0.29841687, -0.14920793])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.0 45.18 44.82 ... 314.8 315.0</div><input id='attrs-60abc674-5988-43f3-b47d-5161793be368' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60abc674-5988-43f3-b47d-5161793be368' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96a98067-6ebe-4adb-b742-bbc3f6f326e4' class='xr-var-data-in' type='checkbox'><label for='data-96a98067-6ebe-4adb-b742-bbc3f6f326e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 45.        ,  45.17578125,  44.82421875, ..., 315.17578125,\n",
+       "       314.82421875, 315.        ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1b07fd80-e830-4f2c-9588-16b88961ddda' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b07fd80-e830-4f2c-9588-16b88961ddda' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.9999 -0.9993 ... 0.9993 0.9999</div><input id='attrs-01079cf2-6932-4237-a617-96bbb2c22486' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01079cf2-6932-4237-a617-96bbb2c22486' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b505ac72-e5e9-47e0-8589-51b7ef284fdc' class='xr-var-data-in' type='checkbox'><label for='data-b505ac72-e5e9-47e0-8589-51b7ef284fdc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-0.99987793, -0.99934242, -0.99934242, ...,  0.99934242,\n",
+       "        0.99934242,  0.99987793])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SH_L3_M2</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.005323 -0.01065 ... -0.005323</div><input id='attrs-5bae0df4-216c-485f-86c7-fd4abb6da913' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5bae0df4-216c-485f-86c7-fd4abb6da913' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-538541de-94dd-46d6-acc4-7e50ec78a2da' class='xr-var-data-in' type='checkbox'><label for='data-538541de-94dd-46d6-acc4-7e50ec78a2da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-0.0053228 , -0.01064519, -0.01064519, ..., -0.01064519,\n",
+       "       -0.01064519, -0.0053228 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1a684466-2731-40f3-bca1-07c3b7483cd0' class='xr-section-summary-in' type='checkbox'  ><label for='section-1a684466-2731-40f3-bca1-07c3b7483cd0' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>cell_ids</div></div><div class='xr-index-preview'>HealpixIndex(nside=8, indexing_scheme=nested, rotation=[0.0, 0.0])</div><div></div><input id='index-4a58f7c4-819c-449e-8fb9-3c939ec066d1' class='xr-index-data-in' type='checkbox'/><label for='index-4a58f7c4-819c-449e-8fb9-3c939ec066d1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>&lt;xdggs.healpix.HealpixIndex object at 0x7f5f67fc8110&gt;</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3289a6f5-f625-4243-9267-1c4de303574d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3289a6f5-f625-4243-9267-1c4de303574d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 31MB\n",
+       "Dimensions:    (cells: 786432)\n",
+       "Coordinates:\n",
+       "  * cell_ids   (cells) int64 6MB 0 1 2 3 4 ... 786428 786429 786430 786431\n",
+       "    latitude   (cells) float64 6MB 0.1492 0.2984 0.2984 ... -0.2984 -0.1492\n",
+       "    longitude  (cells) float64 6MB 45.0 45.18 44.82 45.0 ... 315.2 314.8 315.0\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data       (cells) float64 6MB -0.9999 -0.9993 -0.9993 ... 0.9993 0.9999\n",
+       "    SH_L3_M2   (cells) float64 6MB -0.005323 -0.01065 ... -0.01065 -0.005323\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=8, indexing_scheme=nested, rotation=[0.0, 0.0])"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "level = 8\n",
+    "cell_ids = np.arange(12 * 4**level)\n",
+    "grid_info = {\"grid_name\": \"healpix\", \"level\": level, \"indexing_scheme\": \"nested\"}\n",
+    "\n",
+    "ds = (\n",
+    "    xr.Dataset(coords={\"cell_ids\": (\"cells\", cell_ids, grid_info)})\n",
+    "    .pipe(xdggs.decode)\n",
+    "    .pipe(lambda ds: ds.merge(ds.dggs.cell_centers()))\n",
+    "    .assign(\n",
+    "        data=lambda ds: np.cos(6 * np.radians(ds[\"latitude\"]))\n",
+    "        * np.sin(6 * np.radians(ds[\"longitude\"]))\n",
+    "        # data=function[k,:]\n",
+    "    )\n",
+    ")\n",
+    "SH_L3_M2 = xr.DataArray(\n",
+    "    function[13, :], dims=(\"cells\"), coords={\"cell_ids\": (\"cells\", cell_ids, grid_info)}\n",
+    ")\n",
+    "ds[\"SH_L3_M2\"] = SH_L3_M2\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ecd4aff4-3373-4aca-8eaf-d641c38aa942",
+   "metadata": {},
+   "source": [
+    "### Plotting with xdggs is very simple, just use 'explore' function"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "373b7b1f-fff6-4b26-aa3c-80651199129d",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1583f70a96604d4a8d09199d705c4eb4",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f5f5658…"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds[\"SH_L3_M2\"].dggs.explore(center=0, cmap=\"coolwarm\", alpha=0.8)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "023b7ad2-72d4-4cbf-928a-a23c5abd4050",
+   "metadata": {},
+   "source": [
+    "## Open a sample DestinE data in hearlpix (saved in zarr format with attributes)\n",
+    "\n",
+    "It is straigh forward to open dataset in xarray to use an annotated zarr file.  \n",
+    "\n",
+    "Here we have loaded grib file then transformed it to zarr file with following metadata, and assigned coordinate.  \n",
+    "\n",
+    "```.assign_coords(\n",
+    "    cell_ids=('value', np.arange(12*4**10 ), \n",
+    "              {\"grid_name\":\"healpix\",\"level\": 10, \"indexing_scheme\": \"nested\"}))\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "1082a625-32d9-4274-ab60-629ebfa91479",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 4GB\n",
+       "Dimensions:          (oceanModelLayer: 75, cells: 12582912)\n",
+       "Coordinates:\n",
+       "    cell_ids         (cells) int64 101MB dask.array&lt;chunksize=(100000,), meta=np.ndarray&gt;\n",
+       "    latitude         (cells) float64 101MB dask.array&lt;chunksize=(100000,), meta=np.ndarray&gt;\n",
+       "    longitude        (cells) float64 101MB dask.array&lt;chunksize=(100000,), meta=np.ndarray&gt;\n",
+       "  * oceanModelLayer  (oceanModelLayer) float64 600B 1.0 2.0 3.0 ... 74.0 75.0\n",
+       "    step             timedelta64[ns] 8B ...\n",
+       "    time             datetime64[ns] 8B ...\n",
+       "    valid_time       datetime64[ns] 8B ...\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    avg_thetao       (oceanModelLayer, cells) float32 4GB dask.array&lt;chunksize=(10, 100000), meta=np.ndarray&gt;\n",
+       "Attributes:\n",
+       "    Conventions:             CF-1.7\n",
+       "    GRIB_centre:             ecmf\n",
+       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    GRIB_edition:            2\n",
+       "    GRIB_subCentre:          1003\n",
+       "    history:                 2024-06-03T13:52 GRIB to CDM+CF via cfgrib-0.9.1...\n",
+       "    institution:             European Centre for Medium-Range Weather Forecasts</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-68308c49-7c56-41ba-8774-bfe05c3063fd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-68308c49-7c56-41ba-8774-bfe05c3063fd' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>oceanModelLayer</span>: 75</li><li><span>cells</span>: 12582912</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d1deed09-1feb-4559-8664-e7e586f7d475' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d1deed09-1feb-4559-8664-e7e586f7d475' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100000,), meta=np.ndarray&gt;</div><input id='attrs-72e68f88-22df-4b5a-9a4f-1b0680ae203d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72e68f88-22df-4b5a-9a4f-1b0680ae203d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-571f4c88-82fd-499c-a919-90ef9898f78b' class='xr-var-data-in' type='checkbox'><label for='data-571f4c88-82fd-499c-a919-90ef9898f78b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd><dt><span>resolution :</span></dt><dd>10</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 96.00 MiB </td>\n",
+       "                        <td> 781.25 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (12582912,) </td>\n",
+       "                        <td> (100000,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 126 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> int64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"5\" y1=\"0\" x2=\"5\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"24\" y1=\"0\" x2=\"24\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"25\" />\n",
+       "  <line x1=\"68\" y1=\"0\" x2=\"68\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n",
+       "  <line x1=\"87\" y1=\"0\" x2=\"87\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >12582912</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100000,), meta=np.ndarray&gt;</div><input id='attrs-24391f8a-f0d2-4346-9fb6-a1351730367c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24391f8a-f0d2-4346-9fb6-a1351730367c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e244c34-4e6e-45f8-801c-e750cc0c2b72' class='xr-var-data-in' type='checkbox'><label for='data-5e244c34-4e6e-45f8-801c-e750cc0c2b72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 96.00 MiB </td>\n",
+       "                        <td> 781.25 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (12582912,) </td>\n",
+       "                        <td> (100000,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 126 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"5\" y1=\"0\" x2=\"5\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"24\" y1=\"0\" x2=\"24\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"25\" />\n",
+       "  <line x1=\"68\" y1=\"0\" x2=\"68\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n",
+       "  <line x1=\"87\" y1=\"0\" x2=\"87\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >12582912</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(100000,), meta=np.ndarray&gt;</div><input id='attrs-ee781f7d-9403-474c-a070-ee6085120fa9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee781f7d-9403-474c-a070-ee6085120fa9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c90ace1-6c60-419e-a58d-9e3febf74d08' class='xr-var-data-in' type='checkbox'><label for='data-9c90ace1-6c60-419e-a58d-9e3febf74d08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 96.00 MiB </td>\n",
+       "                        <td> 781.25 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (12582912,) </td>\n",
+       "                        <td> (100000,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 126 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"5\" y1=\"0\" x2=\"5\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"24\" y1=\"0\" x2=\"24\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"25\" />\n",
+       "  <line x1=\"68\" y1=\"0\" x2=\"68\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n",
+       "  <line x1=\"87\" y1=\"0\" x2=\"87\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >12582912</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>oceanModelLayer</span></div><div class='xr-var-dims'>(oceanModelLayer)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... 73.0 74.0 75.0</div><input id='attrs-af1cd5c4-239c-43a0-8414-4cf983a0b697' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af1cd5c4-239c-43a0-8414-4cf983a0b697' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88e572b1-32c0-4adb-99d4-3910328627ea' class='xr-var-data-in' type='checkbox'><label for='data-88e572b1-32c0-4adb-99d4-3910328627ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(oceanModelLayer)</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14.,\n",
+       "       15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,\n",
+       "       29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,\n",
+       "       43., 44., 45., 46., 47., 48., 49., 50., 51., 52., 53., 54., 55., 56.,\n",
+       "       57., 58., 59., 60., 61., 62., 63., 64., 65., 66., 67., 68., 69., 70.,\n",
+       "       71., 72., 73., 74., 75.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-00320b5b-6119-4af9-aa34-9e466941d3e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00320b5b-6119-4af9-aa34-9e466941d3e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0fe01c9-c2dd-4b62-91bb-7250788e983e' class='xr-var-data-in' type='checkbox'><label for='data-b0fe01c9-c2dd-4b62-91bb-7250788e983e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=timedelta64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-637981f4-3d05-46b5-a1f2-6b4599c88e02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-637981f4-3d05-46b5-a1f2-6b4599c88e02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb81b108-a173-4e0f-8d4d-07c6e5acded9' class='xr-var-data-in' type='checkbox'><label for='data-cb81b108-a173-4e0f-8d4d-07c6e5acded9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-314bc960-7f3a-46ab-969d-7d723b2762b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-314bc960-7f3a-46ab-969d-7d723b2762b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd224c0c-2f50-4f38-8ff3-9d69bf2847c3' class='xr-var-data-in' type='checkbox'><label for='data-bd224c0c-2f50-4f38-8ff3-9d69bf2847c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=datetime64[ns]]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-24172536-6276-4006-a21d-f359d15bc734' class='xr-section-summary-in' type='checkbox'  checked><label for='section-24172536-6276-4006-a21d-f359d15bc734' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>avg_thetao</span></div><div class='xr-var-dims'>(oceanModelLayer, cells)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(10, 100000), meta=np.ndarray&gt;</div><input id='attrs-f25d7798-ac60-4c2a-8b21-5ed6f62dba24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f25d7798-ac60-4c2a-8b21-5ed6f62dba24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b35ee089-f82b-497b-aeaa-33eff890b455' class='xr-var-data-in' type='checkbox'><label for='data-b35ee089-f82b-497b-aeaa-33eff890b455' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>avg_thetao</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>150</dd><dt><span>GRIB_gridType :</span></dt><dd>healpix</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Time-mean sea water potential temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>12582912</dd><dt><span>GRIB_paramId :</span></dt><dd>263501</dd><dt><span>GRIB_shortName :</span></dt><dd>avg_thetao</dd><dt><span>GRIB_stepType :</span></dt><dd>avg</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>oceanModelLayer</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Time-mean sea water potential temperature</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 3.52 GiB </td>\n",
+       "                        <td> 3.81 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (75, 12582912) </td>\n",
+       "                        <td> (10, 100000) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1008 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"6\" x2=\"120\" y2=\"6\" />\n",
+       "  <line x1=\"0\" y1=\"10\" x2=\"120\" y2=\"10\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"16\" x2=\"120\" y2=\"16\" />\n",
+       "  <line x1=\"0\" y1=\"20\" x2=\"120\" y2=\"20\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"5\" y1=\"0\" x2=\"5\" y2=\"25\" />\n",
+       "  <line x1=\"12\" y1=\"0\" x2=\"12\" y2=\"25\" />\n",
+       "  <line x1=\"18\" y1=\"0\" x2=\"18\" y2=\"25\" />\n",
+       "  <line x1=\"24\" y1=\"0\" x2=\"24\" y2=\"25\" />\n",
+       "  <line x1=\"31\" y1=\"0\" x2=\"31\" y2=\"25\" />\n",
+       "  <line x1=\"37\" y1=\"0\" x2=\"37\" y2=\"25\" />\n",
+       "  <line x1=\"43\" y1=\"0\" x2=\"43\" y2=\"25\" />\n",
+       "  <line x1=\"50\" y1=\"0\" x2=\"50\" y2=\"25\" />\n",
+       "  <line x1=\"56\" y1=\"0\" x2=\"56\" y2=\"25\" />\n",
+       "  <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"25\" />\n",
+       "  <line x1=\"68\" y1=\"0\" x2=\"68\" y2=\"25\" />\n",
+       "  <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"25\" />\n",
+       "  <line x1=\"82\" y1=\"0\" x2=\"82\" y2=\"25\" />\n",
+       "  <line x1=\"87\" y1=\"0\" x2=\"87\" y2=\"25\" />\n",
+       "  <line x1=\"94\" y1=\"0\" x2=\"94\" y2=\"25\" />\n",
+       "  <line x1=\"101\" y1=\"0\" x2=\"101\" y2=\"25\" />\n",
+       "  <line x1=\"106\" y1=\"0\" x2=\"106\" y2=\"25\" />\n",
+       "  <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"25\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >12582912</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">75</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-9465060a-a41b-4d98-8677-cdba276f31fc' class='xr-section-summary-in' type='checkbox'  ><label for='section-9465060a-a41b-4d98-8677-cdba276f31fc' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>oceanModelLayer</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-23b6939d-3b83-4d79-97cd-20bcc8d1b21c' class='xr-index-data-in' type='checkbox'/><label for='index-23b6939d-3b83-4d79-97cd-20bcc8d1b21c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0, 10.0, 11.0, 12.0,\n",
+       "       13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0,\n",
+       "       25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 36.0,\n",
+       "       37.0, 38.0, 39.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0,\n",
+       "       49.0, 50.0, 51.0, 52.0, 53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0,\n",
+       "       61.0, 62.0, 63.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0,\n",
+       "       73.0, 74.0, 75.0],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;oceanModelLayer&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-33ec4f0c-1518-4224-9382-2013971b9383' class='xr-section-summary-in' type='checkbox'  checked><label for='section-33ec4f0c-1518-4224-9382-2013971b9383' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>GRIB_centre :</span></dt><dd>ecmf</dd><dt><span>GRIB_centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>GRIB_edition :</span></dt><dd>2</dd><dt><span>GRIB_subCentre :</span></dt><dd>1003</dd><dt><span>history :</span></dt><dd>2024-06-03T13:52 GRIB to CDM+CF via cfgrib-0.9.12.0/ecCodes-2.35.0 with {&quot;source&quot;: &quot;ec705b6c-3165-4a63-ac49-0a2e55d7e70c.grib&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd><dt><span>institution :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 4GB\n",
+       "Dimensions:          (oceanModelLayer: 75, cells: 12582912)\n",
+       "Coordinates:\n",
+       "    cell_ids         (cells) int64 101MB dask.array<chunksize=(100000,), meta=np.ndarray>\n",
+       "    latitude         (cells) float64 101MB dask.array<chunksize=(100000,), meta=np.ndarray>\n",
+       "    longitude        (cells) float64 101MB dask.array<chunksize=(100000,), meta=np.ndarray>\n",
+       "  * oceanModelLayer  (oceanModelLayer) float64 600B 1.0 2.0 3.0 ... 74.0 75.0\n",
+       "    step             timedelta64[ns] 8B ...\n",
+       "    time             datetime64[ns] 8B ...\n",
+       "    valid_time       datetime64[ns] 8B ...\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    avg_thetao       (oceanModelLayer, cells) float32 4GB dask.array<chunksize=(10, 100000), meta=np.ndarray>\n",
+       "Attributes:\n",
+       "    Conventions:             CF-1.7\n",
+       "    GRIB_centre:             ecmf\n",
+       "    GRIB_centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    GRIB_edition:            2\n",
+       "    GRIB_subCentre:          1003\n",
+       "    history:                 2024-06-03T13:52 GRIB to CDM+CF via cfgrib-0.9.1...\n",
+       "    institution:             European Centre for Medium-Range Weather Forecasts"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds = xr.open_dataset(\n",
+    "    # \"https://data-taos.ifremer.fr/DestinE/average_surface_temperature.zarr\",\n",
+    "    \"DestinE/average_surface_temperature.zarr\",\n",
+    "    engine=\"zarr\",\n",
+    "    chunks={},\n",
+    "    consolidated=True,\n",
+    ")\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bc508802-44c1-4678-aeba-50f1be890609",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       ".xr-index-data {\n",
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+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
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+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
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+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
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+       "\n",
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+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
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+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;avg_thetao&#x27; (cells: 12582912)&gt; Size: 50MB\n",
+       "array([27.385376, 27.390259, 27.359985, ..., 28.333618, 28.351196,\n",
+       "       28.343384], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * cell_ids         (cells) int64 101MB 0 1 2 3 ... 12582909 12582910 12582911\n",
+       "    latitude         (cells) float64 101MB 0.0373 0.0746 ... -0.0746 -0.0373\n",
+       "    longitude        (cells) float64 101MB 45.0 45.04 44.96 ... 315.0 315.0\n",
+       "    oceanModelLayer  float64 8B 2.0\n",
+       "    step             timedelta64[ns] 8B 1 days\n",
+       "    time             datetime64[ns] 8B 2023-01-01\n",
+       "    valid_time       datetime64[ns] 8B 2023-01-02\n",
+       "Dimensions without coordinates: cells\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=10, indexing_scheme=nested, rotation=[0.0, 0.0])\n",
+       "Attributes: (12/18)\n",
+       "    GRIB_NV:                         0\n",
+       "    GRIB_cfName:                     unknown\n",
+       "    GRIB_cfVarName:                  avg_thetao\n",
+       "    GRIB_dataType:                   fc\n",
+       "    GRIB_gridDefinitionDescription:  150\n",
+       "    GRIB_gridType:                   healpix\n",
+       "    ...                              ...\n",
+       "    GRIB_stepUnits:                  1\n",
+       "    GRIB_typeOfLevel:                oceanModelLayer\n",
+       "    GRIB_units:                      K\n",
+       "    long_name:                       Time-mean sea water potential temperature\n",
+       "    standard_name:                   unknown\n",
+       "    units:                           degree_Celsius</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'avg_thetao'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>cells</span>: 12582912</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e18958a8-79b0-41ba-a513-29aa3d48fe3b' class='xr-array-in' type='checkbox' checked><label for='section-e18958a8-79b0-41ba-a513-29aa3d48fe3b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>27.39 27.39 27.36 27.37 27.39 27.4 ... 28.37 28.35 28.33 28.35 28.34</span></div><div class='xr-array-data'><pre>array([27.385376, 27.390259, 27.359985, ..., 28.333618, 28.351196,\n",
+       "       28.343384], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-1dab4d42-4732-45c0-9a91-7bccb38bf677' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1dab4d42-4732-45c0-9a91-7bccb38bf677' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 ... 12582910 12582911</div><input id='attrs-98147ff0-9778-41a2-a280-6933d7684cd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98147ff0-9778-41a2-a280-6933d7684cd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bd9dc3e-9eeb-41bb-bec4-4c6f048dba96' class='xr-var-data-in' type='checkbox'><label for='data-8bd9dc3e-9eeb-41bb-bec4-4c6f048dba96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd><dt><span>resolution :</span></dt><dd>10</dd></dl></div><div class='xr-var-data'><pre>array([       0,        1,        2, ..., 12582909, 12582910, 12582911])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0373 0.0746 ... -0.0746 -0.0373</div><input id='attrs-0c8d69ba-a7b1-4ddb-b352-eadcb4e49ea7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c8d69ba-a7b1-4ddb-b352-eadcb4e49ea7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbbb1735-3089-4fec-8a86-406854acc9ac' class='xr-var-data-in' type='checkbox'><label for='data-fbbb1735-3089-4fec-8a86-406854acc9ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([ 0.03730194,  0.0746039 ,  0.0746039 , ..., -0.0746039 ,\n",
+       "       -0.0746039 , -0.03730194])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.0 45.04 44.96 ... 315.0 315.0</div><input id='attrs-cfa6d54f-eb26-4b6e-8b3d-678e0b8c3703' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfa6d54f-eb26-4b6e-8b3d-678e0b8c3703' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65d69939-37cc-4ffb-a597-b21d00f94e0d' class='xr-var-data-in' type='checkbox'><label for='data-65d69939-37cc-4ffb-a597-b21d00f94e0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([ 45.        ,  45.04394531,  44.95605469, ..., 315.04394531,\n",
+       "       314.95605469, 315.        ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oceanModelLayer</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-98e7526b-c51a-49b7-a6c5-a73c417161da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98e7526b-c51a-49b7-a6c5-a73c417161da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1f46c0a-e852-489c-b7c4-7a2f595d6e89' class='xr-var-data-in' type='checkbox'><label for='data-d1f46c0a-e852-489c-b7c4-7a2f595d6e89' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>original GRIB coordinate for key: level(oceanModelLayer)</dd><dt><span>units :</span></dt><dd>dimensionless</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>1 days</div><input id='attrs-4be52993-c055-4beb-8bc8-4ae469a840be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4be52993-c055-4beb-8bc8-4ae469a840be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9aba6a9d-89b5-46ef-b7ab-d99fc6f36971' class='xr-var-data-in' type='checkbox'><label for='data-9aba6a9d-89b5-46ef-b7ab-d99fc6f36971' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array(86400000000000, dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-01-01</div><input id='attrs-6d13f277-9a5c-461f-9a3a-d149c57e2711' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d13f277-9a5c-461f-9a3a-d149c57e2711' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a04a753-462f-4944-a1ab-119d185475ab' class='xr-var-data-in' type='checkbox'><label for='data-1a04a753-462f-4944-a1ab-119d185475ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2023-01-01T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>valid_time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2023-01-02</div><input id='attrs-7b2e679f-80a1-4965-8895-4ad5e75d4032' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b2e679f-80a1-4965-8895-4ad5e75d4032' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39820f9a-14ff-4b6a-9eac-9bbd4b49c681' class='xr-var-data-in' type='checkbox'><label for='data-39820f9a-14ff-4b6a-9eac-9bbd4b49c681' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(&#x27;2023-01-02T00:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d25b10d5-3190-4770-8ddb-dd6bc8472652' class='xr-section-summary-in' type='checkbox'  ><label for='section-d25b10d5-3190-4770-8ddb-dd6bc8472652' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>cell_ids</div></div><div class='xr-index-preview'>HealpixIndex(nside=10, indexing_scheme=nested, rotation=[0.0, 0.0])</div><div></div><input id='index-c4974212-4892-418b-81c7-93cacff4d82c' class='xr-index-data-in' type='checkbox'/><label for='index-c4974212-4892-418b-81c7-93cacff4d82c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>&lt;xdggs.healpix.HealpixIndex object at 0x7f5f3daa93a0&gt;</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9bc4e435-facb-4316-ac45-222497ce667a' class='xr-section-summary-in' type='checkbox'  ><label for='section-9bc4e435-facb-4316-ac45-222497ce667a' class='xr-section-summary' >Attributes: <span>(18)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>avg_thetao</dd><dt><span>GRIB_dataType :</span></dt><dd>fc</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>150</dd><dt><span>GRIB_gridType :</span></dt><dd>healpix</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Time-mean sea water potential temperature</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>12582912</dd><dt><span>GRIB_paramId :</span></dt><dd>263501</dd><dt><span>GRIB_shortName :</span></dt><dd>avg_thetao</dd><dt><span>GRIB_stepType :</span></dt><dd>avg</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>oceanModelLayer</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Time-mean sea water potential temperature</dd><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'avg_thetao' (cells: 12582912)> Size: 50MB\n",
+       "array([27.385376, 27.390259, 27.359985, ..., 28.333618, 28.351196,\n",
+       "       28.343384], dtype=float32)\n",
+       "Coordinates:\n",
+       "  * cell_ids         (cells) int64 101MB 0 1 2 3 ... 12582909 12582910 12582911\n",
+       "    latitude         (cells) float64 101MB 0.0373 0.0746 ... -0.0746 -0.0373\n",
+       "    longitude        (cells) float64 101MB 45.0 45.04 44.96 ... 315.0 315.0\n",
+       "    oceanModelLayer  float64 8B 2.0\n",
+       "    step             timedelta64[ns] 8B 1 days\n",
+       "    time             datetime64[ns] 8B 2023-01-01\n",
+       "    valid_time       datetime64[ns] 8B 2023-01-02\n",
+       "Dimensions without coordinates: cells\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=10, indexing_scheme=nested, rotation=[0.0, 0.0])\n",
+       "Attributes: (12/18)\n",
+       "    GRIB_NV:                         0\n",
+       "    GRIB_cfName:                     unknown\n",
+       "    GRIB_cfVarName:                  avg_thetao\n",
+       "    GRIB_dataType:                   fc\n",
+       "    GRIB_gridDefinitionDescription:  150\n",
+       "    GRIB_gridType:                   healpix\n",
+       "    ...                              ...\n",
+       "    GRIB_stepUnits:                  1\n",
+       "    GRIB_typeOfLevel:                oceanModelLayer\n",
+       "    GRIB_units:                      K\n",
+       "    long_name:                       Time-mean sea water potential temperature\n",
+       "    standard_name:                   unknown\n",
+       "    units:                           degree_Celsius"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = (\n",
+    "    ds[\"avg_thetao\"]\n",
+    "    .isel(oceanModelLayer=1)\n",
+    "    .pint.quantify()\n",
+    "    .pint.to({\"avg_thetao\": \"degC\"})\n",
+    "    .pint.dequantify()\n",
+    "    .pipe(xdggs.decode)\n",
+    "    .compute()\n",
+    ")\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "8b656e85-5a22-4c37-aaf5-84c7d611802f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 850x540 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "hp.cartview(data.data, nest=True, cmap=\"viridis\", flip=\"geo\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "c288d98b-b276-4355-aeec-90d13abc1c24",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8c95efda755a4e25ac270ff4c59955de",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f5f3d9e…"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.dggs.explore(center=0, cmap=\"viridis\", alpha=0.5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f763f849-be6a-4a1d-96e9-41c90f3d9676",
+   "metadata": {},
+   "source": [
+    "### With XDGGS, one can select points of data not only from cell_ids from DGGS, but also from latitude and longitude."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "a67b7fae-f300-4d46-a8cf-1db177ede0e3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5fe52104fd784f5bab974e469cbcd941",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f5f3c05…"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lon = np.arange(48, 49.5, 0.01)\n",
+    "lat = np.arange(354, 355, 0.01)\n",
+    "full_lat = np.repeat(lat, len(lon))\n",
+    "full_lon = np.tile(lon, len(lat))\n",
+    "\n",
+    "(data.dggs.sel_latlon(longitude=full_lon, latitude=full_lat)).dggs.explore(\n",
+    "    center=0, cmap=\"viridis\", alpha=0.8\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "270999dc-b4a4-492e-a0e4-87e5eb08b55d",
+   "metadata": {},
+   "source": [
+    "## Open a EERIE Cloud  data in hearlpix, saved in zarr format from DKRZ.\n",
+    "\n",
+    "NextGems project provide their data set in healpix in zarr format. \n",
+    "Deatiled description of EERIE Cloud can be found here\n",
+    "https://easy.gems.dkrz.de/simulations/EERIE/eerie_data-access_online.html\n",
+    "\n",
+    "After opening we need to assigne coordinate and meta data defining the grid system.    \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "8f6b7df4-c438-4606-8abb-c27f1e7fa843",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
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+       "</defs>\n",
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+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
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+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
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+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
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+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
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+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
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+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
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+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
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+       "\n",
+       ".xr-section-summary {\n",
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+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
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+       "\n",
+       ".xr-section-summary-in + label:before {\n",
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+       "  content: '►';\n",
+       "  font-size: 11px;\n",
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+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 383TB\n",
+       "Dimensions:  (time: 262537, value: 3145728)\n",
+       "Coordinates:\n",
+       "    lat      (value) float64 25MB dask.array&lt;chunksize=(3145728,), meta=np.ndarray&gt;\n",
+       "    lon      (value) float64 25MB dask.array&lt;chunksize=(3145728,), meta=np.ndarray&gt;\n",
+       "  * time     (time) datetime64[ns] 2MB 2020-01-20 ... 2050-01-01\n",
+       "Dimensions without coordinates: value\n",
+       "Data variables: (12/58)\n",
+       "    10si     (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    10u      (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    10v      (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    2d       (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    2t       (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    blh      (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    ...       ...\n",
+       "    tp       (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    tprate   (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    tsr      (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    tsrc     (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    ttr      (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "    ttrc     (time, value) float64 7TB dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;\n",
+       "Attributes: (12/13)\n",
+       "    edition:            2\n",
+       "    centre:             ecmf\n",
+       "    centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    subCentre:          1003\n",
+       "    history:            🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IF...\n",
+       "    title:              nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512\n",
+       "    ...                 ...\n",
+       "    time_min:           2020-01-20T00:00:00.000000000\n",
+       "    time_max:           2050-01-01T00:00:00.000000000\n",
+       "    creation_date:      2024-10-15T00:01:47Z\n",
+       "    authors:            Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECM...\n",
+       "    contact:            Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)\n",
+       "    license:            Creative Commons Attribution 4.0 International (CC BY...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-43cc3df9-50a4-4fd3-84fd-a6cecdeeff40' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-43cc3df9-50a4-4fd3-84fd-a6cecdeeff40' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 262537</li><li><span>value</span>: 3145728</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d3d33e63-9a00-4b95-838f-ccee4b65fea0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d3d33e63-9a00-4b95-838f-ccee4b65fea0' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3145728,), meta=np.ndarray&gt;</div><input id='attrs-571f95ce-26e8-4973-956f-b5617851a163' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-571f95ce-26e8-4973-956f-b5617851a163' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9fc8e59-46ee-4911-aafd-48d01efd8fb9' class='xr-var-data-in' type='checkbox'><label for='data-d9fc8e59-46ee-4911-aafd-48d01efd8fb9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.00 MiB </td>\n",
+       "                        <td> 24.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3145728,) </td>\n",
+       "                        <td> (3145728,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3145728,), meta=np.ndarray&gt;</div><input id='attrs-7eb7215f-b320-448f-b275-77d45d61bf04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7eb7215f-b320-448f-b275-77d45d61bf04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e24e42f-c32e-4ecd-b079-996c14a293b3' class='xr-var-data-in' type='checkbox'><label for='data-6e24e42f-c32e-4ecd-b079-996c14a293b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 24.00 MiB </td>\n",
+       "                        <td> 24.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (3145728,) </td>\n",
+       "                        <td> (3145728,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-01-20 ... 2050-01-01</div><input id='attrs-d98c6a20-5d99-4078-9ad6-34ac96eba3d3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d98c6a20-5d99-4078-9ad6-34ac96eba3d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee7f8adb-592d-4fcc-ae0e-64177fa5f8d7' class='xr-var-data-in' type='checkbox'><label for='data-ee7f8adb-592d-4fcc-ae0e-64177fa5f8d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-01-20T00:00:00.000000000&#x27;, &#x27;2020-01-20T01:00:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-20T02:00:00.000000000&#x27;, ..., &#x27;2049-12-31T22:00:00.000000000&#x27;,\n",
+       "       &#x27;2049-12-31T23:00:00.000000000&#x27;, &#x27;2050-01-01T00:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1bd9f8e4-258d-4d9e-80e2-935f5e4ac1fa' class='xr-section-summary-in' type='checkbox'  ><label for='section-1bd9f8e4-258d-4d9e-80e2-935f5e4ac1fa' class='xr-section-summary' >Data variables: <span>(58)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>10si</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-79b2b966-e319-4809-9208-53532bbca45f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79b2b966-e319-4809-9208-53532bbca45f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2de64781-46b6-4c8d-8948-b0645d92e2a0' class='xr-var-data-in' type='checkbox'><label for='data-2de64781-46b6-4c8d-8948-b0645d92e2a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>207</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>10si</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>10 metre wind speed</dd><dt><span>cfVarName :</span></dt><dd>si10</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
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+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>10u</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-0df925fe-721f-4a20-9fb8-1594e94a6de7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0df925fe-721f-4a20-9fb8-1594e94a6de7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60a7815a-75b1-47d9-a2b4-75f82b4c2b1b' class='xr-var-data-in' type='checkbox'><label for='data-60a7815a-75b1-47d9-a2b4-75f82b4c2b1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>165</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>10u</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>10 metre U wind component</dd><dt><span>cfName :</span></dt><dd>eastward_wind</dd><dt><span>cfVarName :</span></dt><dd>u10</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>10v</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-eed464a2-7263-459b-913d-278185369e5f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eed464a2-7263-459b-913d-278185369e5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20fbcc2f-f7d2-463f-9d56-880a389979a7' class='xr-var-data-in' type='checkbox'><label for='data-20fbcc2f-f7d2-463f-9d56-880a389979a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>166</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>10v</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>10 metre V wind component</dd><dt><span>cfName :</span></dt><dd>northward_wind</dd><dt><span>cfVarName :</span></dt><dd>v10</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
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+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>2d</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-e93a6de6-6068-4239-bf7e-e51af9915df7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e93a6de6-6068-4239-bf7e-e51af9915df7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18aedb99-bb55-4d74-a606-2aafd671b875' class='xr-var-data-in' type='checkbox'><label for='data-18aedb99-bb55-4d74-a606-2aafd671b875' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>168</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>2d</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>2 metre dewpoint temperature</dd><dt><span>cfVarName :</span></dt><dd>d2m</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>2t</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-21a552c8-faa2-42f3-87c0-d891b458213a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21a552c8-faa2-42f3-87c0-d891b458213a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a0a25f4-f213-47bf-b17e-52c69202810c' class='xr-var-data-in' type='checkbox'><label for='data-3a0a25f4-f213-47bf-b17e-52c69202810c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>167</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>2t</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>2 metre temperature</dd><dt><span>cfName :</span></dt><dd>air_temperature</dd><dt><span>cfVarName :</span></dt><dd>t2m</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>blh</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-289867a9-75f7-4e4b-921c-548e2fae4747' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-289867a9-75f7-4e4b-921c-548e2fae4747' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da35405b-8c81-46f5-875a-11ef7581f5cd' class='xr-var-data-in' type='checkbox'><label for='data-da35405b-8c81-46f5-875a-11ef7581f5cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>159</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>blh</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>name :</span></dt><dd>Boundary layer height</dd><dt><span>cfVarName :</span></dt><dd>blh</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>chnk</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-14aa324b-57ab-4125-a82c-a6d9bea9130c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14aa324b-57ab-4125-a82c-a6d9bea9130c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe0e418b-e0ba-4ee2-b1b9-04df56c0bdd9' class='xr-var-data-in' type='checkbox'><label for='data-fe0e418b-e0ba-4ee2-b1b9-04df56c0bdd9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>148</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>chnk</dd><dt><span>units :</span></dt><dd>Numeric</dd><dt><span>name :</span></dt><dd>Charnock</dd><dt><span>cfVarName :</span></dt><dd>chnk</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
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+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>e</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-4efffd8f-83b3-4bad-b123-902e48e177d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4efffd8f-83b3-4bad-b123-902e48e177d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d058e855-a793-48b1-9516-fad8cf4e870b' class='xr-var-data-in' type='checkbox'><label for='data-d058e855-a793-48b1-9516-fad8cf4e870b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>182</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>e</dd><dt><span>units :</span></dt><dd>m of water equivalent</dd><dt><span>name :</span></dt><dd>Evaporation</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_water_evaporation_amount</dd><dt><span>cfVarName :</span></dt><dd>e</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ewss</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-399ee3a1-d8c2-41a3-b96f-43eb32b90457' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-399ee3a1-d8c2-41a3-b96f-43eb32b90457' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa70d8e4-e28b-47cc-8ed3-67d3f56d767d' class='xr-var-data-in' type='checkbox'><label for='data-aa70d8e4-e28b-47cc-8ed3-67d3f56d767d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>180</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>ewss</dd><dt><span>units :</span></dt><dd>N m**-2 s</dd><dt><span>name :</span></dt><dd>Time-integrated eastward turbulent surface stress</dd><dt><span>cfName :</span></dt><dd>surface_downward_eastward_stress</dd><dt><span>cfVarName :</span></dt><dd>ewss</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
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+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fdir</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-9932d654-ec68-4b86-9829-162c2efc7085' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9932d654-ec68-4b86-9829-162c2efc7085' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44fc7bd7-0f9d-4136-b29f-c12daa55f6db' class='xr-var-data-in' type='checkbox'><label for='data-44fc7bd7-0f9d-4136-b29f-c12daa55f6db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>228021</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>fdir</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Total sky direct short-wave (solar) radiation at surface</dd><dt><span>cfVarName :</span></dt><dd>fdir</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
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+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
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+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
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+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hcc</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-d99e7a8e-8ce9-468b-b968-3346dee1f689' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d99e7a8e-8ce9-468b-b968-3346dee1f689' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75e89c4a-032c-488f-b735-eaf8f266fbbf' class='xr-var-data-in' type='checkbox'><label for='data-75e89c4a-032c-488f-b735-eaf8f266fbbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>188</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>highCloudLayer</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>hcc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>High cloud cover</dd><dt><span>cfVarName :</span></dt><dd>hcc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
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+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
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+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>i10fg</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-ef5981ec-570f-4807-9878-59cab717a1ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef5981ec-570f-4807-9878-59cab717a1ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e7c1b38-de5a-4d25-a03b-14a610433afa' class='xr-var-data-in' type='checkbox'><label for='data-4e7c1b38-de5a-4d25-a03b-14a610433afa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>228029</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>i10fg</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>Instantaneous 10 metre wind gust</dd><dt><span>cfVarName :</span></dt><dd>i10fg</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
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+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lcc</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-8e739836-b782-46b2-ba57-37f6aeb6b7e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e739836-b782-46b2-ba57-37f6aeb6b7e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a202676-ed39-4040-9fac-13776db50b20' class='xr-var-data-in' type='checkbox'><label for='data-5a202676-ed39-4040-9fac-13776db50b20' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>186</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>lowCloudLayer</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>lcc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Low cloud cover</dd><dt><span>cfVarName :</span></dt><dd>lcc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
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+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
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+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
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+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
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+       "\n",
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+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
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+       "\n",
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+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lgws</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-4fb49415-76c9-49cf-9efe-69629ce9ee0c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fb49415-76c9-49cf-9efe-69629ce9ee0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5aa98c2-f0f5-4d76-8a97-57ce0f171a95' class='xr-var-data-in' type='checkbox'><label for='data-d5aa98c2-f0f5-4d76-8a97-57ce0f171a95' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>195</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>lgws</dd><dt><span>units :</span></dt><dd>N m**-2 s</dd><dt><span>name :</span></dt><dd>Eastward gravity wave surface stress</dd><dt><span>cfVarName :</span></dt><dd>lgws</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
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+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>litota1</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-ede8cd1d-ff5f-410f-8086-7b9d854010db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ede8cd1d-ff5f-410f-8086-7b9d854010db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4411b4b-5b7c-4c31-8d3d-21033e956de2' class='xr-var-data-in' type='checkbox'><label for='data-a4411b4b-5b7c-4c31-8d3d-21033e956de2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>228051</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>entireAtmosphere</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>litota1</dd><dt><span>units :</span></dt><dd>km**-2 day**-1</dd><dt><span>name :</span></dt><dd>Averaged total lightning flash density in the last hour</dd><dt><span>cfVarName :</span></dt><dd>litota1</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
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+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lsp</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-dd3dd9a0-840d-46b2-826a-22e2f0ae61b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd3dd9a0-840d-46b2-826a-22e2f0ae61b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-354b0b91-e1f0-4553-92aa-7fa9883cefbf' class='xr-var-data-in' type='checkbox'><label for='data-354b0b91-e1f0-4553-92aa-7fa9883cefbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>142</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>lsp</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>name :</span></dt><dd>Large-scale precipitation</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_stratiform_precipitation_amount</dd><dt><span>cfVarName :</span></dt><dd>lsp</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mcc</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-30718f58-46eb-4846-8836-c1614c36d71c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30718f58-46eb-4846-8836-c1614c36d71c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fee447c-6254-48dc-97bf-c526b7f69f86' class='xr-var-data-in' type='checkbox'><label for='data-6fee447c-6254-48dc-97bf-c526b7f69f86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>187</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>mediumCloudLayer</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>mcc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Medium cloud cover</dd><dt><span>cfVarName :</span></dt><dd>mcc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
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+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
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+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mgws</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-f8ab2795-46c9-4f66-a6ea-ad9abcd47d29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8ab2795-46c9-4f66-a6ea-ad9abcd47d29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f469ee5-b968-48c5-922d-dada4579db62' class='xr-var-data-in' type='checkbox'><label for='data-3f469ee5-b968-48c5-922d-dada4579db62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>196</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>mgws</dd><dt><span>units :</span></dt><dd>N m**-2 s</dd><dt><span>name :</span></dt><dd>Northward gravity wave surface stress</dd><dt><span>cfVarName :</span></dt><dd>mgws</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>msl</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-726a33f1-e0a6-4cef-b17a-b2c7152a5ffb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-726a33f1-e0a6-4cef-b17a-b2c7152a5ffb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ffa4d7c-ed00-4a49-afa4-d547a59db763' class='xr-var-data-in' type='checkbox'><label for='data-2ffa4d7c-ed00-4a49-afa4-d547a59db763' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>151</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>msl</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>name :</span></dt><dd>Mean sea level pressure</dd><dt><span>cfName :</span></dt><dd>air_pressure_at_mean_sea_level</dd><dt><span>cfVarName :</span></dt><dd>msl</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
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+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mucape</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-e780d088-a04f-403c-af0a-ce5dc40ea0c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e780d088-a04f-403c-af0a-ce5dc40ea0c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8596c75-4e6e-4a22-9d86-90dacbf68011' class='xr-var-data-in' type='checkbox'><label for='data-e8596c75-4e6e-4a22-9d86-90dacbf68011' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>228235</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>mostUnstableParcel</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>mucape</dd><dt><span>units :</span></dt><dd>J kg**-1</dd><dt><span>name :</span></dt><dd>Most-unstable CAPE</dd><dt><span>cfVarName :</span></dt><dd>mucape</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
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+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nsss</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-2a111d10-dab1-4584-b4dc-a6e13db24eb3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a111d10-dab1-4584-b4dc-a6e13db24eb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df82772c-9c85-482d-aecc-1fc0d1e8fc6e' class='xr-var-data-in' type='checkbox'><label for='data-df82772c-9c85-482d-aecc-1fc0d1e8fc6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>181</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>nsss</dd><dt><span>units :</span></dt><dd>N m**-2 s</dd><dt><span>name :</span></dt><dd>Time-integrated northward turbulent surface stress</dd><dt><span>cfName :</span></dt><dd>surface_downward_northward_stress</dd><dt><span>cfVarName :</span></dt><dd>nsss</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rsn</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-34425052-f3c3-4ffa-85d9-9b58e2f28f7f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34425052-f3c3-4ffa-85d9-9b58e2f28f7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e45f043f-f1a8-4829-a70a-8858f171d594' class='xr-var-data-in' type='checkbox'><label for='data-e45f043f-f1a8-4829-a70a-8858f171d594' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>33</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>rsn</dd><dt><span>units :</span></dt><dd>kg m**-3</dd><dt><span>name :</span></dt><dd>Snow density</dd><dt><span>cfVarName :</span></dt><dd>rsn</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sd</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-88ecb039-6268-4d48-b198-4477901431a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88ecb039-6268-4d48-b198-4477901431a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2a7807f-7086-406d-873b-bba376843f80' class='xr-var-data-in' type='checkbox'><label for='data-b2a7807f-7086-406d-873b-bba376843f80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>141</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>sd</dd><dt><span>units :</span></dt><dd>m of water equivalent</dd><dt><span>name :</span></dt><dd>Snow depth</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_surface_snow_amount</dd><dt><span>cfVarName :</span></dt><dd>sd</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sf</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-ac4cdba7-6b88-4392-acf6-437245d64914' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac4cdba7-6b88-4392-acf6-437245d64914' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e95cdfba-cfa6-48c1-a458-9d5726206b9a' class='xr-var-data-in' type='checkbox'><label for='data-e95cdfba-cfa6-48c1-a458-9d5726206b9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>144</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>sf</dd><dt><span>units :</span></dt><dd>m of water equivalent</dd><dt><span>name :</span></dt><dd>Snowfall</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_snowfall_amount</dd><dt><span>cfVarName :</span></dt><dd>sf</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
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+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
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+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>skt</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-3c0bc4dc-930a-4f0c-9d0b-6077c3695802' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c0bc4dc-930a-4f0c-9d0b-6077c3695802' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-738eea09-84b4-485c-9f18-546ce4965bd7' class='xr-var-data-in' type='checkbox'><label for='data-738eea09-84b4-485c-9f18-546ce4965bd7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>235</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>skt</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Skin temperature</dd><dt><span>cfVarName :</span></dt><dd>skt</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slhf</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-506235da-2181-4bba-846d-3ab30b000906' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-506235da-2181-4bba-846d-3ab30b000906' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdf6d244-240a-4409-97a6-a307aa91c3ec' class='xr-var-data-in' type='checkbox'><label for='data-fdf6d244-240a-4409-97a6-a307aa91c3ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>147</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>slhf</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Surface latent heat flux</dd><dt><span>cfName :</span></dt><dd>surface_upward_latent_heat_flux</dd><dt><span>cfVarName :</span></dt><dd>slhf</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
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+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
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+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sp</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-10855e26-815b-4544-8c0b-bda20f4c7d1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10855e26-815b-4544-8c0b-bda20f4c7d1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae1b3b13-742a-4ba1-ba73-1dea6bc2cf71' class='xr-var-data-in' type='checkbox'><label for='data-ae1b3b13-742a-4ba1-ba73-1dea6bc2cf71' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>134</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>sp</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>name :</span></dt><dd>Surface pressure</dd><dt><span>cfName :</span></dt><dd>surface_air_pressure</dd><dt><span>cfVarName :</span></dt><dd>sp</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sro</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-0c577680-3913-4776-96c1-01a909712b34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c577680-3913-4776-96c1-01a909712b34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be4b5d6d-5706-4644-aaf6-74775996625c' class='xr-var-data-in' type='checkbox'><label for='data-be4b5d6d-5706-4644-aaf6-74775996625c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>8</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>sro</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>name :</span></dt><dd>Surface runoff</dd><dt><span>cfVarName :</span></dt><dd>sro</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
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+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sshf</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-cb2bc2cd-12c9-4092-9a9c-a3961920d81f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb2bc2cd-12c9-4092-9a9c-a3961920d81f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c5fa236-e719-4acb-be78-c29cc98182e8' class='xr-var-data-in' type='checkbox'><label for='data-9c5fa236-e719-4acb-be78-c29cc98182e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>146</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>sshf</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Surface sensible heat flux</dd><dt><span>cfName :</span></dt><dd>surface_upward_sensible_heat_flux</dd><dt><span>cfVarName :</span></dt><dd>sshf</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
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+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ssr</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-04d0a8e8-d947-4371-bebf-e1f2e0941e7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04d0a8e8-d947-4371-bebf-e1f2e0941e7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0167561b-5c80-4bce-9ace-b0a27383dbc0' class='xr-var-data-in' type='checkbox'><label for='data-0167561b-5c80-4bce-9ace-b0a27383dbc0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>176</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>ssr</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Surface net short-wave (solar) radiation</dd><dt><span>cfName :</span></dt><dd>surface_net_downward_shortwave_flux</dd><dt><span>cfVarName :</span></dt><dd>ssr</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
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+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ssrc</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-5fa9c0f0-482b-4707-9516-767f8632c891' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fa9c0f0-482b-4707-9516-767f8632c891' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72a39359-f3fe-410b-84f2-537d599b249f' class='xr-var-data-in' type='checkbox'><label for='data-72a39359-f3fe-410b-84f2-537d599b249f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>210</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>ssrc</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Surface net short-wave (solar) radiation, clear sky</dd><dt><span>cfName :</span></dt><dd>surface_net_downward_shortwave_flux_assuming_clear_sky</dd><dt><span>cfVarName :</span></dt><dd>ssrc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ssrd</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-02efac0b-9440-4ea9-a788-bfa3c166e99c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02efac0b-9440-4ea9-a788-bfa3c166e99c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29f931d2-0445-4184-afca-e565e4f8d647' class='xr-var-data-in' type='checkbox'><label for='data-29f931d2-0445-4184-afca-e565e4f8d647' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>169</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>ssrd</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Surface short-wave (solar) radiation downwards</dd><dt><span>cfName :</span></dt><dd>surface_downwelling_shortwave_flux_in_air</dd><dt><span>cfVarName :</span></dt><dd>ssrd</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ssrdc</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-a5afb936-0c31-49b4-aac0-618818402f2c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5afb936-0c31-49b4-aac0-618818402f2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b624321e-5ae4-4ce2-abe9-c519cb6c12d7' class='xr-var-data-in' type='checkbox'><label for='data-b624321e-5ae4-4ce2-abe9-c519cb6c12d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>228129</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>ssrdc</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Surface short-wave (solar) radiation downward clear-sky</dd><dt><span>cfVarName :</span></dt><dd>ssrdc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
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+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ssro</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-5544546c-b3f2-40e1-ab5b-df7e6faeb419' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5544546c-b3f2-40e1-ab5b-df7e6faeb419' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd818c23-442f-4922-896c-d79a3d696b4b' class='xr-var-data-in' type='checkbox'><label for='data-bd818c23-442f-4922-896c-d79a3d696b4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>9</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>ssro</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>name :</span></dt><dd>Sub-surface runoff</dd><dt><span>cfVarName :</span></dt><dd>ssro</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stl1</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-78d8f018-6045-4b8b-b12c-3674d478a243' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78d8f018-6045-4b8b-b12c-3674d478a243' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb94408e-55eb-406c-9070-dc31020218f6' class='xr-var-data-in' type='checkbox'><label for='data-bb94408e-55eb-406c-9070-dc31020218f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>139</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>stl1</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Soil temperature level 1</dd><dt><span>cfName :</span></dt><dd>surface_temperature</dd><dt><span>cfVarName :</span></dt><dd>stl1</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stl2</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-e2499d24-0734-4af4-bb2a-2ef00dad472d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2499d24-0734-4af4-bb2a-2ef00dad472d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47730e1f-80ef-453c-8822-7bf97f5e9d25' class='xr-var-data-in' type='checkbox'><label for='data-47730e1f-80ef-453c-8822-7bf97f5e9d25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>170</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>stl2</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Soil temperature level 2</dd><dt><span>cfVarName :</span></dt><dd>stl2</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stl3</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-39517996-e21a-40ae-b7bc-273eebd24b87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39517996-e21a-40ae-b7bc-273eebd24b87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cdfffb9-d8c0-42e8-951e-98f29cea8b40' class='xr-var-data-in' type='checkbox'><label for='data-7cdfffb9-d8c0-42e8-951e-98f29cea8b40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>183</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>stl3</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Soil temperature level 3</dd><dt><span>cfVarName :</span></dt><dd>stl3</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stl4</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-e1f61439-7eb8-4f50-817a-d7deef3c018c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1f61439-7eb8-4f50-817a-d7deef3c018c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e89780b8-ab65-4262-b0c7-a1ad386223a2' class='xr-var-data-in' type='checkbox'><label for='data-e89780b8-ab65-4262-b0c7-a1ad386223a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>236</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>stl4</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Soil temperature level 4</dd><dt><span>cfVarName :</span></dt><dd>stl4</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
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+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>str</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-0a4c529d-fc18-4729-be96-717e68283e64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a4c529d-fc18-4729-be96-717e68283e64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a834595-f4c6-4ca6-a47e-1dfbc00330ac' class='xr-var-data-in' type='checkbox'><label for='data-7a834595-f4c6-4ca6-a47e-1dfbc00330ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>177</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>str</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Surface net long-wave (thermal) radiation</dd><dt><span>cfName :</span></dt><dd>surface_net_upward_longwave_flux</dd><dt><span>cfVarName :</span></dt><dd>str</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>strc</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-c26b8d00-b925-43ef-9869-5338e704e31f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c26b8d00-b925-43ef-9869-5338e704e31f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d4a5059-9186-4776-a657-38876b89ff5f' class='xr-var-data-in' type='checkbox'><label for='data-5d4a5059-9186-4776-a657-38876b89ff5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>211</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>strc</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Surface net long-wave (thermal) radiation, clear sky</dd><dt><span>cfName :</span></dt><dd>surface_net_downward_longwave_flux_assuming_clear_sky</dd><dt><span>cfVarName :</span></dt><dd>strc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>strd</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-ca384a44-26f0-48cb-8ec9-a45059e5bd63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca384a44-26f0-48cb-8ec9-a45059e5bd63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-589b7157-51db-49b8-9be1-0e1156a578fe' class='xr-var-data-in' type='checkbox'><label for='data-589b7157-51db-49b8-9be1-0e1156a578fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>175</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>strd</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Surface long-wave (thermal) radiation downwards</dd><dt><span>cfVarName :</span></dt><dd>strd</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
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+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
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+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl1</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-4fc6f94d-314e-47c5-b5d4-be9a7f8f967f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fc6f94d-314e-47c5-b5d4-be9a7f8f967f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-528b3d79-4ca2-4410-a34a-1b246fbafbc6' class='xr-var-data-in' type='checkbox'><label for='data-528b3d79-4ca2-4410-a34a-1b246fbafbc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>39</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>swvl1</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 1</dd><dt><span>cfVarName :</span></dt><dd>swvl1</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl2</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-59cfcd62-9d7b-44f0-9bb3-fd97047044ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59cfcd62-9d7b-44f0-9bb3-fd97047044ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e1b3dc8-ac89-4e66-ac9c-4f08a8ec5a7c' class='xr-var-data-in' type='checkbox'><label for='data-2e1b3dc8-ac89-4e66-ac9c-4f08a8ec5a7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>40</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>swvl2</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 2</dd><dt><span>cfVarName :</span></dt><dd>swvl2</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl3</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-e78c89df-e5d1-474b-9458-651c0349749f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e78c89df-e5d1-474b-9458-651c0349749f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc37bc26-6d3d-4c48-b38f-430ee80d8bbe' class='xr-var-data-in' type='checkbox'><label for='data-cc37bc26-6d3d-4c48-b38f-430ee80d8bbe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>41</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>swvl3</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 3</dd><dt><span>cfVarName :</span></dt><dd>swvl3</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl4</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-04b4cb83-9da7-4c3b-bd48-b4cbac829913' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04b4cb83-9da7-4c3b-bd48-b4cbac829913' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e705952-599d-4649-b521-3d78cfe10a86' class='xr-var-data-in' type='checkbox'><label for='data-8e705952-599d-4649-b521-3d78cfe10a86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>42</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>swvl4</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 4</dd><dt><span>cfVarName :</span></dt><dd>swvl4</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcc</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-dc21e774-10e9-4b42-9ec0-bcccb17fca0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc21e774-10e9-4b42-9ec0-bcccb17fca0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54b58f28-0a64-4305-812e-3e2ecc5a0f31' class='xr-var-data-in' type='checkbox'><label for='data-54b58f28-0a64-4305-812e-3e2ecc5a0f31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>164</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>entireAtmosphere</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tcc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Total cloud cover</dd><dt><span>cfName :</span></dt><dd>cloud_area_fraction</dd><dt><span>cfVarName :</span></dt><dd>tcc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
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+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
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+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
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+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tciw</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-3e5b9adf-37e1-42e7-b7a4-66f679d698b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e5b9adf-37e1-42e7-b7a4-66f679d698b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40e090ae-99d2-4c5e-93f1-e6dd9731b61e' class='xr-var-data-in' type='checkbox'><label for='data-40e090ae-99d2-4c5e-93f1-e6dd9731b61e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>79</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>entireAtmosphere</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tciw</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column cloud ice water</dd><dt><span>cfVarName :</span></dt><dd>tciw</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
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+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
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+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
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+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tclw</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-74cc58f8-5226-4117-a157-f66bff67b326' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74cc58f8-5226-4117-a157-f66bff67b326' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07d3e799-1fb0-4475-8329-855e56b88b57' class='xr-var-data-in' type='checkbox'><label for='data-07d3e799-1fb0-4475-8329-855e56b88b57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>78</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>entireAtmosphere</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tclw</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column cloud liquid water</dd><dt><span>cfVarName :</span></dt><dd>tclw</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
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+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
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+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcrw</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-30d0bc2d-3697-4128-85bd-cd0a4c849a4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30d0bc2d-3697-4128-85bd-cd0a4c849a4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e54bebc6-3921-495a-a69c-3068aaaebc10' class='xr-var-data-in' type='checkbox'><label for='data-e54bebc6-3921-495a-a69c-3068aaaebc10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>228089</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>entireAtmosphere</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tcrw</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column rain water</dd><dt><span>cfVarName :</span></dt><dd>tcrw</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcsw</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-43654f99-ea19-438d-8c6c-8aef95631604' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43654f99-ea19-438d-8c6c-8aef95631604' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc8497a4-c84d-425f-b528-c74f2c9c505b' class='xr-var-data-in' type='checkbox'><label for='data-fc8497a4-c84d-425f-b528-c74f2c9c505b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>228090</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>entireAtmosphere</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tcsw</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column snow water</dd><dt><span>cfVarName :</span></dt><dd>tcsw</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcwv</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-fbaa943e-e446-4ac3-a2e8-a71b67694537' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fbaa943e-e446-4ac3-a2e8-a71b67694537' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b46d658-8229-4568-99da-181d3795a709' class='xr-var-data-in' type='checkbox'><label for='data-3b46d658-8229-4568-99da-181d3795a709' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>137</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>entireAtmosphere</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tcwv</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column vertically-integrated water vapour</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_atmosphere_mass_content_of_water_vapor</dd><dt><span>cfVarName :</span></dt><dd>tcwv</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"33\" x2=\"120\" y2=\"33\" />\n",
+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tisr</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-23a91980-7640-44e9-aca6-a481f48c960d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23a91980-7640-44e9-aca6-a481f48c960d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53859917-2c14-416c-b0c8-0a5e5f3509dc' class='xr-var-data-in' type='checkbox'><label for='data-53859917-2c14-416c-b0c8-0a5e5f3509dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>212</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>nominalTop</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tisr</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>TOA incident short-wave (solar) radiation</dd><dt><span>cfVarName :</span></dt><dd>tisr</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
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+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tp</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-41db1b44-166a-43b3-b10d-bc5fd37d18d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41db1b44-166a-43b3-b10d-bc5fd37d18d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71c519f8-3b1f-45b4-9e90-7ff9aa0ed207' class='xr-var-data-in' type='checkbox'><label for='data-71c519f8-3b1f-45b4-9e90-7ff9aa0ed207' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>228</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tp</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>name :</span></dt><dd>Total precipitation</dd><dt><span>cfVarName :</span></dt><dd>tp</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tprate</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-d50b6545-a5aa-44d7-96b0-b223f71b13dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d50b6545-a5aa-44d7-96b0-b223f71b13dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec168673-b7c5-459b-a01b-a09c3e8357b9' class='xr-var-data-in' type='checkbox'><label for='data-ec168673-b7c5-459b-a01b-a09c3e8357b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>260048</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tprate</dd><dt><span>units :</span></dt><dd>kg m**-2 s**-1</dd><dt><span>name :</span></dt><dd>Total precipitation rate</dd><dt><span>cfVarName :</span></dt><dd>tprate</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
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+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
+       "  <text x=\"140.000000\" y=\"18.786124\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,18.786124)\">262537</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tsr</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-8f93de7d-e7d3-483b-8ae9-ef66cf37feea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f93de7d-e7d3-483b-8ae9-ef66cf37feea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7be68867-663a-4866-afc0-be8e527e05fe' class='xr-var-data-in' type='checkbox'><label for='data-7be68867-663a-4866-afc0-be8e527e05fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>178</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>nominalTop</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tsr</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Top net short-wave (solar) radiation</dd><dt><span>cfName :</span></dt><dd>toa_net_upward_shortwave_flux</dd><dt><span>cfVarName :</span></dt><dd>tsr</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
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+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
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+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tsrc</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-3c372e75-4740-4082-8370-ab283e70dc4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c372e75-4740-4082-8370-ab283e70dc4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1573557b-38e7-41da-9e6e-433bb974e7ea' class='xr-var-data-in' type='checkbox'><label for='data-1573557b-38e7-41da-9e6e-433bb974e7ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>208</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>nominalTop</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>tsrc</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Top net short-wave (solar) radiation, clear sky</dd><dt><span>cfVarName :</span></dt><dd>tsrc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
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+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
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+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
+       "  <line x1=\"0\" y1=\"23\" x2=\"120\" y2=\"23\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"27\" x2=\"120\" y2=\"27\" />\n",
+       "  <line x1=\"0\" y1=\"29\" x2=\"120\" y2=\"29\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"120\" y2=\"31\" />\n",
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+       "  <line x1=\"0\" y1=\"35\" x2=\"120\" y2=\"35\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
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+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ttr</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-19dbdc0b-50da-44b9-8869-50ddceb0c7d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19dbdc0b-50da-44b9-8869-50ddceb0c7d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a670f2ca-d506-44a0-bd92-830fa084872b' class='xr-var-data-in' type='checkbox'><label for='data-a670f2ca-d506-44a0-bd92-830fa084872b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>179</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>nominalTop</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>ttr</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Top net long-wave (thermal) radiation</dd><dt><span>cfName :</span></dt><dd>toa_outgoing_longwave_flux</dd><dt><span>cfVarName :</span></dt><dd>ttr</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
+       "  <line x1=\"0\" y1=\"21\" x2=\"120\" y2=\"21\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ttrc</span></div><div class='xr-var-dims'>(time, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(3, 3145728), meta=np.ndarray&gt;</div><input id='attrs-dc6880e7-00d0-4675-b48c-6c60ac25605b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc6880e7-00d0-4675-b48c-6c60ac25605b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6b5a698-7093-4a0a-a3ff-e812f90ba950' class='xr-var-data-in' type='checkbox'><label for='data-d6b5a698-7093-4a0a-a3ff-e812f90ba950' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>209</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>nominalTop</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>accum</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>ttrc</dd><dt><span>units :</span></dt><dd>J m**-2</dd><dt><span>name :</span></dt><dd>Top net long-wave (thermal) radiation, clear sky</dd><dt><span>cfVarName :</span></dt><dd>ttrc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 6.01 TiB </td>\n",
+       "                        <td> 72.00 MiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (262537, 3145728) </td>\n",
+       "                        <td> (3, 3145728) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 87513 chunks in 2 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"87\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"1\" x2=\"120\" y2=\"1\" />\n",
+       "  <line x1=\"0\" y1=\"3\" x2=\"120\" y2=\"3\" />\n",
+       "  <line x1=\"0\" y1=\"5\" x2=\"120\" y2=\"5\" />\n",
+       "  <line x1=\"0\" y1=\"7\" x2=\"120\" y2=\"7\" />\n",
+       "  <line x1=\"0\" y1=\"9\" x2=\"120\" y2=\"9\" />\n",
+       "  <line x1=\"0\" y1=\"11\" x2=\"120\" y2=\"11\" />\n",
+       "  <line x1=\"0\" y1=\"13\" x2=\"120\" y2=\"13\" />\n",
+       "  <line x1=\"0\" y1=\"15\" x2=\"120\" y2=\"15\" />\n",
+       "  <line x1=\"0\" y1=\"17\" x2=\"120\" y2=\"17\" />\n",
+       "  <line x1=\"0\" y1=\"19\" x2=\"120\" y2=\"19\" />\n",
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+       "  <line x1=\"0\" y1=\"37\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"37\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,37.57224831999427 0.0,37.57224831999427\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"57.572248\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >3145728</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d5315d0-3fb9-444f-be58-46160e47293c' class='xr-section-summary-in' type='checkbox'  ><label for='section-7d5315d0-3fb9-444f-be58-46160e47293c' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5758267d-41f7-4fec-b73f-c5ddea9307f3' class='xr-index-data-in' type='checkbox'/><label for='index-5758267d-41f7-4fec-b73f-c5ddea9307f3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-01-20 00:00:00&#x27;, &#x27;2020-01-20 01:00:00&#x27;,\n",
+       "               &#x27;2020-01-20 02:00:00&#x27;, &#x27;2020-01-20 03:00:00&#x27;,\n",
+       "               &#x27;2020-01-20 04:00:00&#x27;, &#x27;2020-01-20 05:00:00&#x27;,\n",
+       "               &#x27;2020-01-20 06:00:00&#x27;, &#x27;2020-01-20 07:00:00&#x27;,\n",
+       "               &#x27;2020-01-20 08:00:00&#x27;, &#x27;2020-01-20 09:00:00&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2049-12-31 15:00:00&#x27;, &#x27;2049-12-31 16:00:00&#x27;,\n",
+       "               &#x27;2049-12-31 17:00:00&#x27;, &#x27;2049-12-31 18:00:00&#x27;,\n",
+       "               &#x27;2049-12-31 19:00:00&#x27;, &#x27;2049-12-31 20:00:00&#x27;,\n",
+       "               &#x27;2049-12-31 21:00:00&#x27;, &#x27;2049-12-31 22:00:00&#x27;,\n",
+       "               &#x27;2049-12-31 23:00:00&#x27;, &#x27;2050-01-01 00:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=262537, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f8173614-6f2b-4d55-8470-d70d7b3402e7' class='xr-section-summary-in' type='checkbox'  ><label for='section-f8173614-6f2b-4d55-8470-d70d7b3402e7' class='xr-section-summary' >Attributes: <span>(13)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>edition :</span></dt><dd>2</dd><dt><span>centre :</span></dt><dd>ecmf</dd><dt><span>centreDescription :</span></dt><dd>European Centre for Medium-Range Weather Forecasts</dd><dt><span>subCentre :</span></dt><dd>1003</dd><dt><span>history :</span></dt><dd>🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IFSMagician\r\n",
+       "</dd><dt><span>title :</span></dt><dd>nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512</dd><dt><span>description :</span></dt><dd>Simulation data from project &#x27;not Set&#x27; produced by Earth System Model &#x27;not Set&#x27; and run by institution &#x27;ecmf&#x27; for the experiment &#x27;not Set&#x27;</dd><dt><span>time_min :</span></dt><dd>2020-01-20T00:00:00.000000000</dd><dt><span>time_max :</span></dt><dd>2050-01-01T00:00:00.000000000</dd><dt><span>creation_date :</span></dt><dd>2024-10-15T00:01:47Z</dd><dt><span>authors :</span></dt><dd>Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECMWF), Becker, Tobias (ECMWF), Beyer, Sebastian (AWI), Cheedela, Suvarchal Kumar (AWI), Dreier, Nils-Arne (DKRZ), Engels, Jan Frederik (DKRZ), Esch, Monika (MPIMet), Frauen, Claudia (DKRZ), Klocke, Daniel (MPIMet), Kölling, Tobias (MPIMet), Pedruzo-Bagazgoitia, Xabier (ECMWF), Putrasahan, Dian (MPIMet), Rackow, Thomas (ECMWF), Sidorenko, Dmitry (AWI), Schnur, Reiner (MPIMet), Stevens, Bjorn (MPIMet), Zimmermann, Janos (DKRZ)</dd><dt><span>contact :</span></dt><dd>Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)</dd><dt><span>license :</span></dt><dd>Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 383TB\n",
+       "Dimensions:  (time: 262537, value: 3145728)\n",
+       "Coordinates:\n",
+       "    lat      (value) float64 25MB dask.array<chunksize=(3145728,), meta=np.ndarray>\n",
+       "    lon      (value) float64 25MB dask.array<chunksize=(3145728,), meta=np.ndarray>\n",
+       "  * time     (time) datetime64[ns] 2MB 2020-01-20 ... 2050-01-01\n",
+       "Dimensions without coordinates: value\n",
+       "Data variables: (12/58)\n",
+       "    10si     (time, value) float64 7TB dask.array<chunksize=(3, 3145728), meta=np.ndarray>\n",
+       "    10u      (time, value) float64 7TB dask.array<chunksize=(3, 3145728), meta=np.ndarray>\n",
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+       "    blh      (time, value) float64 7TB dask.array<chunksize=(3, 3145728), meta=np.ndarray>\n",
+       "    ...       ...\n",
+       "    tp       (time, value) float64 7TB dask.array<chunksize=(3, 3145728), meta=np.ndarray>\n",
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+       "Attributes: (12/13)\n",
+       "    edition:            2\n",
+       "    centre:             ecmf\n",
+       "    centreDescription:  European Centre for Medium-Range Weather Forecasts\n",
+       "    subCentre:          1003\n",
+       "    history:            🪄🧙‍♂️🔮 magic dataset assembly provided by gribscan.IF...\n",
+       "    title:              nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512\n",
+       "    ...                 ...\n",
+       "    time_min:           2020-01-20T00:00:00.000000000\n",
+       "    time_max:           2050-01-01T00:00:00.000000000\n",
+       "    creation_date:      2024-10-15T00:01:47Z\n",
+       "    authors:            Wieners, Karl-Hermann (MPIMet), Aguridan, Razvan (ECM...\n",
+       "    contact:            Wieners, Karl-Hermann (MPIMet), Rackow, Thomas (ECMWF)\n",
+       "    license:            Creative Commons Attribution 4.0 International (CC BY..."
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds = xr.open_dataset(\n",
+    "    \"https://eerie.cloud.dkrz.de/datasets/nextgems.IFS_9-FESOM_5-production.2D_hourly_healpix512/zarr\",\n",
+    "    engine=\"zarr\",\n",
+    "    chunks={},\n",
+    "    consolidated=True,\n",
+    ")\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "98110ef3-84e5-4b03-b496-12bfba14baf9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds = ds.assign_coords(\n",
+    "    cell_ids=(\n",
+    "        \"value\",\n",
+    "        np.arange(12 * 4**9),\n",
+    "        {\"grid_name\": \"healpix\", \"level\": 9, \"indexing_scheme\": \"nested\"},\n",
+    "    )\n",
+    ")"
+   ]
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+   "id": "27e4ebce-6612-42d9-902b-079d2c69d291",
+   "metadata": {
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+   },
+   "outputs": [
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+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;msl&#x27; (value: 3145728)&gt; Size: 25MB\n",
+       "array([100984.51660156, 100988.79394531, 100979.44824219, ...,\n",
+       "       101204.87207031, 101202.56152344, 101200.22753906])\n",
+       "Coordinates:\n",
+       "    lat       (value) float64 25MB 0.0746 0.1492 0.1492 ... -0.1492 -0.0746\n",
+       "    lon       (value) float64 25MB 45.0 45.09 44.91 45.0 ... 315.1 314.9 315.0\n",
+       "    time      datetime64[ns] 8B 2020-03-01T16:00:00\n",
+       "  * cell_ids  (value) int64 25MB 0 1 2 3 4 ... 3145724 3145725 3145726 3145727\n",
+       "Dimensions without coordinates: value\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=9, indexing_scheme=nested, rotation=[0.0, 0.0])\n",
+       "Attributes: (12/15)\n",
+       "    paramId:                    151\n",
+       "    dataType:                   fc\n",
+       "    numberOfPoints:             3145728\n",
+       "    typeOfLevel:                meanSea\n",
+       "    stepUnits:                  1\n",
+       "    stepType:                   instant\n",
+       "    ...                         ...\n",
+       "    name:                       Mean sea level pressure\n",
+       "    cfName:                     air_pressure_at_mean_sea_level\n",
+       "    cfVarName:                  msl\n",
+       "    missingValue:               9999\n",
+       "    NV:                         0\n",
+       "    gridDefinitionDescription:  150</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'msl'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>value</span>: 3145728</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d298a1d8-3b90-49ab-a359-a9a49bd43415' class='xr-array-in' type='checkbox' checked><label for='section-d298a1d8-3b90-49ab-a359-a9a49bd43415' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.01e+05 1.01e+05 1.01e+05 1.01e+05 ... 1.012e+05 1.012e+05 1.012e+05</span></div><div class='xr-array-data'><pre>array([100984.51660156, 100988.79394531, 100979.44824219, ...,\n",
+       "       101204.87207031, 101202.56152344, 101200.22753906])</pre></div></div></li><li class='xr-section-item'><input id='section-09f051b4-7a62-4df6-be1c-c361bdcf2bf5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-09f051b4-7a62-4df6-be1c-c361bdcf2bf5' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0746 0.1492 ... -0.1492 -0.0746</div><input id='attrs-669c9229-22fe-4a76-8d72-8188e37476ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-669c9229-22fe-4a76-8d72-8188e37476ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a689d96b-72a6-460f-8644-d6b94c47d797' class='xr-var-data-in' type='checkbox'><label for='data-a689d96b-72a6-460f-8644-d6b94c47d797' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0.0746039 ,  0.14920793,  0.14920793, ..., -0.14920793,\n",
+       "       -0.14920793, -0.0746039 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.0 45.09 44.91 ... 314.9 315.0</div><input id='attrs-5c56f283-914b-461e-8033-3a7448bfc145' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c56f283-914b-461e-8033-3a7448bfc145' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44474d29-3605-45ed-a28a-fbc43e0d269c' class='xr-var-data-in' type='checkbox'><label for='data-44474d29-3605-45ed-a28a-fbc43e0d269c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([ 45.        ,  45.08789062,  44.91210938, ..., 315.08789062,\n",
+       "       314.91210938, 315.        ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-03-01T16:00:00</div><input id='attrs-1b523914-1dca-4fff-8070-c42e05d4974e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b523914-1dca-4fff-8070-c42e05d4974e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12894873-e5b2-49c3-8d26-29cbdf9ed1b9' class='xr-var-data-in' type='checkbox'><label for='data-12894873-e5b2-49c3-8d26-29cbdf9ed1b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;2020-03-01T16:00:00.000000000&#x27;, dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(value)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 3145725 3145726 3145727</div><input id='attrs-0c908846-fe44-4115-ac4b-f4474238e3a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c908846-fe44-4115-ac4b-f4474238e3a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb953595-1d93-4c10-a9bd-89be21ec1ba0' class='xr-var-data-in' type='checkbox'><label for='data-fb953595-1d93-4c10-a9bd-89be21ec1ba0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>9</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><pre>array([      0,       1,       2, ..., 3145725, 3145726, 3145727])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-16117540-ac5a-40d0-bc3a-ac6272dd4ef4' class='xr-section-summary-in' type='checkbox'  ><label for='section-16117540-ac5a-40d0-bc3a-ac6272dd4ef4' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>cell_ids</div></div><div class='xr-index-preview'>HealpixIndex(nside=9, indexing_scheme=nested, rotation=[0.0, 0.0])</div><div></div><input id='index-5ae7ba50-f8b0-42c1-b7dd-40862b44f90d' class='xr-index-data-in' type='checkbox'/><label for='index-5ae7ba50-f8b0-42c1-b7dd-40862b44f90d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>&lt;xdggs.healpix.HealpixIndex object at 0x7f5f3daf8a40&gt;</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f1e6e9db-c258-4e22-b1cc-9b78d81f6afe' class='xr-section-summary-in' type='checkbox'  ><label for='section-f1e6e9db-c258-4e22-b1cc-9b78d81f6afe' class='xr-section-summary' >Attributes: <span>(15)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>151</dd><dt><span>dataType :</span></dt><dd>fc</dd><dt><span>numberOfPoints :</span></dt><dd>3145728</dd><dt><span>typeOfLevel :</span></dt><dd>meanSea</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>instant</dd><dt><span>gridType :</span></dt><dd>healpix</dd><dt><span>shortName :</span></dt><dd>msl</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>name :</span></dt><dd>Mean sea level pressure</dd><dt><span>cfName :</span></dt><dd>air_pressure_at_mean_sea_level</dd><dt><span>cfVarName :</span></dt><dd>msl</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>150</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'msl' (value: 3145728)> Size: 25MB\n",
+       "array([100984.51660156, 100988.79394531, 100979.44824219, ...,\n",
+       "       101204.87207031, 101202.56152344, 101200.22753906])\n",
+       "Coordinates:\n",
+       "    lat       (value) float64 25MB 0.0746 0.1492 0.1492 ... -0.1492 -0.0746\n",
+       "    lon       (value) float64 25MB 45.0 45.09 44.91 45.0 ... 315.1 314.9 315.0\n",
+       "    time      datetime64[ns] 8B 2020-03-01T16:00:00\n",
+       "  * cell_ids  (value) int64 25MB 0 1 2 3 4 ... 3145724 3145725 3145726 3145727\n",
+       "Dimensions without coordinates: value\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=9, indexing_scheme=nested, rotation=[0.0, 0.0])\n",
+       "Attributes: (12/15)\n",
+       "    paramId:                    151\n",
+       "    dataType:                   fc\n",
+       "    numberOfPoints:             3145728\n",
+       "    typeOfLevel:                meanSea\n",
+       "    stepUnits:                  1\n",
+       "    stepType:                   instant\n",
+       "    ...                         ...\n",
+       "    name:                       Mean sea level pressure\n",
+       "    cfName:                     air_pressure_at_mean_sea_level\n",
+       "    cfVarName:                  msl\n",
+       "    missingValue:               9999\n",
+       "    NV:                         0\n",
+       "    gridDefinitionDescription:  150"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = ds[\"msl\"].isel(time=1000).compute().pipe(xdggs.decode)\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "9b244f12-0600-48f2-890e-948df076353d",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f063922684b44f12a40b78bd146282bc",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f5ec807…"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.dggs.explore(center=0, cmap=\"viridis\", alpha=0.8)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b4762c84-9d04-49bc-a383-d754f360fd35",
+   "metadata": {},
+   "source": [
+    "### Selecting region to plot\n",
+    "#### Selection using healpix cell_ids"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "e6678ba9-a8f4-47a6-a349-eebcc15a8a84",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f066d21b17944a0b9fc592c9865c9717",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f5ec324…"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.sel(cell_ids=slice(0, 1000)).dggs.explore(cmap=\"viridis\", alpha=0.8)  # center=0,"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "26d27b4a-2423-4758-9139-aee69f3decc9",
+   "metadata": {},
+   "source": [
+    "#### Selection using latitude and longitude"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "f5aff0ac-c8b5-4fc1-a766-e460a51624f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ee05bf0181944556b033404c3950edf1",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f5f3da5…"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(\n",
+    "    data.dggs.sel_latlon(latitude=0, longitude=48)\n",
+    "    .expand_dims(\"cell_ids\")\n",
+    "    .pipe(xdggs.decode)\n",
+    ").dggs.explore(center=0, cmap=\"viridis\", alpha=0.8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "a7b59a52-2de1-4116-8ab2-c93f9028cc61",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0837e5da176b4b62b60dd0acc3a32c45",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f5ec3c5…"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(data.dggs.sel_latlon(longitude=[48, 47, 46], latitude=[-5, -5.3, -5.5])).dggs.explore(\n",
+    "    center=0, cmap=\"viridis\", alpha=0.8\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "37811f0c-bc79-4d5f-b71f-a465fccd2c1d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "24c419fc615547ffaded34ca24fda061",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f5ec324…"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lon = np.arange(48.5, 49, 0.01)\n",
+    "lat = np.arange(355, 355.5, 0.01)\n",
+    "full_lat = np.repeat(lat, len(lon))\n",
+    "full_lon = np.tile(lon, len(lat))\n",
+    "\n",
+    "(data.dggs.sel_latlon(longitude=full_lon, latitude=full_lat)).dggs.explore(\n",
+    "    center=0, cmap=\"viridis\", alpha=0.8\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9517d1eb-565d-4ebc-9be0-d73488e34757",
+   "metadata": {},
+   "source": [
+    "## Current Issue with Testing Different Datasets\n",
+    "\n",
+    "It is crucial to define a consistent coordinate 'name' and establish how attributes should be specified in order to test different data sources without having to re-define the coordinate name for each dataset. In **XDGGS**, we follow the convention below:\n",
+    "\n",
+    "```python\n",
+    ".assign_coords(\n",
+    "    cell_ids=('value', np.arange(12*4**10), \n",
+    "              {\"grid_name\": \"healpix\", \"level\": 10, \"indexing_scheme\": \"nested\"}))\n",
+    "```\n",
+    "\n",
+    "## Whats next\n",
+    "\n",
+    "Currently, selecting data by latitude and longitude must be done on a point-by-point basis. However, the conventional approach for users to select a region of interest is still a bounding box (bbox) using latitude and longitude. Therefore, enabling this functionality is a priority to streamline data selection."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/visualisation/xdggs_ww3_dataset.ipynb b/visualisation/xdggs_ww3_dataset.ipynb
new file mode 100644
index 0000000..c645046
--- /dev/null
+++ b/visualisation/xdggs_ww3_dataset.ipynb
@@ -0,0 +1,1673 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d340a5ff-db29-4c13-8d7f-f02870e6ad17",
+   "metadata": {},
+   "source": [
+    "# Creating multilevel HEALPix Data in zarr and datatree for WW3 model \n",
+    "\n",
+    "In this notebook, we will demonstrate examples of saving multilevel HEALPix data from WW3 model output.  \n",
+    "\n",
+    "## Setup\n",
+    "\n",
+    "To run this notebook, you need to install XDGGS. You can find the xdggs repository here: [XDGGS GitHub Repository](https://github.com/xarray-contrib/xdggs.git).\n",
+    "\n",
+    "\n",
+    "1. You can either install `xdggs` with the necessary dependencies, use the following command:\n",
+    "\n",
+    "```bash\n",
+    "pip install xdggs\n",
+    "```\n",
+    "\n",
+    "2. You will need up to date xarray package :\n",
+    "\n",
+    "```bash\n",
+    "pip install -U xarray\n",
+    "```\n",
+    "\n",
+    "3. You can use zarr version zarr==2.18.4.  In a few weeks, it would work with icechunk as well. :\n",
+    "\n",
+    "```bash\n",
+    "#pip install icechunk\n",
+    "pip install -U zarr==2.18.4\n",
+    "```\n"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "a9cdd9e3-dcbd-430e-8cf4-ae7ed5b8503e",
+   "metadata": {
+    "scrolled": true
+   },
+   "source": [
+    "#!pip install xdggs pint_xarray icechunk\n",
+    "!pip install xdggs\n",
+    "#!pip install icechunk\n",
+    "!pip install -U zarr==2.18.4"
+   ]
+  },
+  {
+   "cell_type": "raw",
+   "id": "51ecf055-d61b-480d-b433-137d701718cb",
+   "metadata": {},
+   "source": [
+    "!pip install -U xarray"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "36cf9310-b950-4ff2-96ac-8b654b411947",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import warnings\n",
+    "\n",
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "import xdggs\n",
+    "\n",
+    "warnings.filterwarnings(\"ignore\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e3963d96-2a87-466e-b235-702efa7bc87c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2024.11.0'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xr.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "076aefd9-7ad9-48a6-941c-2c019dd07d46",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2.18.4'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import zarr\n",
+    "\n",
+    "zarr.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "68c364ab-3db3-42c9-9872-83b83b599ae5",
+   "metadata": {},
+   "source": [
+    "##  Load npy data in  Healpix coordinate \n",
+    "2048 does not work"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "fa1d1c97-6b4e-4ebf-8291-6d00b3baf137",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "cannot reshape array of size 42336240 into shape (50331648,)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[6], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m file_path \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfile_2048.npy\u001b[39m\u001b[38;5;124m'\u001b[39m  \n\u001b[0;32m----> 2\u001b[0m data \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfile_path\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      3\u001b[0m total_cells \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlen\u001b[39m(data)\n\u001b[1;32m      4\u001b[0m level \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mround\u001b[39m(np\u001b[38;5;241m.\u001b[39mlog(total_cells \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m12\u001b[39m) \u001b[38;5;241m/\u001b[39m np\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;241m4\u001b[39m))\n",
+      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.12/site-packages/numpy/lib/npyio.py:456\u001b[0m, in \u001b[0;36mload\u001b[0;34m(file, mmap_mode, allow_pickle, fix_imports, encoding, max_header_size)\u001b[0m\n\u001b[1;32m    453\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mformat\u001b[39m\u001b[38;5;241m.\u001b[39mopen_memmap(file, mode\u001b[38;5;241m=\u001b[39mmmap_mode,\n\u001b[1;32m    454\u001b[0m                                   max_header_size\u001b[38;5;241m=\u001b[39mmax_header_size)\n\u001b[1;32m    455\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 456\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mformat\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_array\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mallow_pickle\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallow_pickle\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    457\u001b[0m \u001b[43m                                 \u001b[49m\u001b[43mpickle_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpickle_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    458\u001b[0m \u001b[43m                                 \u001b[49m\u001b[43mmax_header_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_header_size\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    459\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    460\u001b[0m     \u001b[38;5;66;03m# Try a pickle\u001b[39;00m\n\u001b[1;32m    461\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m allow_pickle:\n",
+      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.12/site-packages/numpy/lib/format.py:839\u001b[0m, in \u001b[0;36mread_array\u001b[0;34m(fp, allow_pickle, pickle_kwargs, max_header_size)\u001b[0m\n\u001b[1;32m    837\u001b[0m         array \u001b[38;5;241m=\u001b[39m array\u001b[38;5;241m.\u001b[39mtranspose()\n\u001b[1;32m    838\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 839\u001b[0m         \u001b[43marray\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshape\u001b[49m \u001b[38;5;241m=\u001b[39m shape\n\u001b[1;32m    841\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m array\n",
+      "\u001b[0;31mValueError\u001b[0m: cannot reshape array of size 42336240 into shape (50331648,)"
+     ]
+    }
+   ],
+   "source": [
+    "file_path = \"file_2048.npy\"\n",
+    "data = np.load(file_path)\n",
+    "total_cells = len(data)\n",
+    "level = round(np.log(total_cells / 12) / np.log(4))\n",
+    "\n",
+    "# Create cell_ids\n",
+    "cell_ids = np.arange(12 * 4**level)\n",
+    "# Define grid_info\n",
+    "grid_info = {\"grid_name\": \"healpix\", \"level\": level, \"indexing_scheme\": \"nested\"}\n",
+    "# Create xarray.Dataset\n",
+    "ds = xr.Dataset(\n",
+    "    {\"data\": ((\"cells\",), data)}, coords={\"cell_ids\": (\"cells\", cell_ids, grid_info)}\n",
+    ").pipe(xdggs.decode)\n",
+    "ds = ds.where(ds > 0, drop=True)\n",
+    "ds[\"data\"].dggs.explore(cmap=\"viridis\", alpha=0.8)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "64292206-39fe-43c7-9ca6-d17d7f6e80e7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "512\n",
+      "1024\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'9': <xarray.Dataset> Size: 41kB\n",
+       " Dimensions:   (cells: 2561)\n",
+       " Coordinates:\n",
+       "   * cell_ids  (cells) int64 20kB 174927 174931 174933 ... 906354 906496 906498\n",
+       " Dimensions without coordinates: cells\n",
+       " Data variables:\n",
+       "     data      (cells) float64 20kB 0.4569 0.3647 0.4264 ... 0.546 0.8065 0.8\n",
+       " Indexes:\n",
+       "     cell_ids  HealpixIndex(nside=9, indexing_scheme=nested),\n",
+       " '10': <xarray.Dataset> Size: 142kB\n",
+       " Dimensions:   (cells: 8901)\n",
+       " Coordinates:\n",
+       "   * cell_ids  (cells) int64 71kB 699708 699709 699710 ... 3625986 3625992\n",
+       " Dimensions without coordinates: cells\n",
+       " Data variables:\n",
+       "     data      (cells) float64 71kB 0.326 0.421 0.414 0.5363 ... 0.838 0.82 0.8\n",
+       " Indexes:\n",
+       "     cell_ids  HealpixIndex(nside=10, indexing_scheme=nested)}"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import xarray as xr\n",
+    "import xdggs  # Assuming xdggs is available\n",
+    "\n",
+    "# Define file sizes and initialize the dictionary\n",
+    "file_sizes = [512, 1024]  # , 2048]\n",
+    "plevels = {}\n",
+    "\n",
+    "# Process each file size\n",
+    "for file_size in file_sizes:\n",
+    "    print(file_size)\n",
+    "    # Construct the file name dynamically\n",
+    "    file_path = f\"file_{file_size}.npy\"\n",
+    "\n",
+    "    # Load the .npy file\n",
+    "    data = np.load(file_path)\n",
+    "\n",
+    "    # Calculate the level\n",
+    "    total_cells = len(data)\n",
+    "    level = round(np.log(total_cells / 12) / np.log(4))\n",
+    "\n",
+    "    # Create cell_ids\n",
+    "    cell_ids = np.arange(12 * 4**level)\n",
+    "\n",
+    "    # Define grid_info\n",
+    "    grid_info = {\"grid_name\": \"healpix\", \"level\": level, \"indexing_scheme\": \"nested\"}\n",
+    "\n",
+    "    # Create xarray.Dataset and apply filters\n",
+    "    ds = (\n",
+    "        xr.Dataset(\n",
+    "            {\"data\": ((\"cells\",), data)},\n",
+    "            coords={\"cell_ids\": (\"cells\", cell_ids, grid_info)},\n",
+    "        )\n",
+    "        .pipe(xdggs.decode)\n",
+    "        .where(lambda d: d > 0, drop=True)\n",
+    "    )\n",
+    "\n",
+    "    # Store in dictionary with level as key\n",
+    "    plevels[str(level)] = ds\n",
+    "\n",
+    "# Print the dictionary keys to confirm\n",
+    "plevels"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "810843fa-3d9f-4390-8df3-1a3d4ab195cb",
+   "metadata": {},
+   "source": [
+    "## Create a datatree including different levels of HEALPix data\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "7095715e-d9ff-4370-b999-5f3f62103d48",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# plevels = {\"/\": root, \"9\": ds, \"8\": ds_8, \"7\": ds_7}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "afdc0fbf-1960-41c9-8f64-23924b5d1d7c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
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+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
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+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
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+       "}\n",
+       "\n",
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+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
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+       "}\n",
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+       "  font-weight: 500;\n",
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+       "\n",
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+       "\n",
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+       "  grid-column: 1;\n",
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+       "}\n",
+       "\n",
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+       "}\n",
+       "\n",
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+       "\n",
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+       "}\n",
+       "\n",
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+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 0B\n",
+       "Dimensions:  ()\n",
+       "Data variables:\n",
+       "    *empty*</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataTree</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9b718ed7-0c52-43be-b1df-77485c24dffa' class='xr-section-summary-in' type='checkbox'  ><label for='section-9b718ed7-0c52-43be-b1df-77485c24dffa' class='xr-section-summary' >Groups: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'><div style='display: inline-grid; grid-template-columns: 0px 20px auto; width: 100%;'><div style='grid-column-start: 1;border-right: 0.2em solid;border-color: var(--xr-border-color);height: 100%;width: 0px;'></div><div style='grid-column-start: 2;grid-row-start: 1;height: 1em;width: 20px;border-bottom: 0.2em solid;border-color: var(--xr-border-color);'></div><div style='grid-column-start: 3;'><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 41kB\n",
+       "Dimensions:   (cells: 2561)\n",
+       "Coordinates:\n",
+       "  * cell_ids  (cells) int64 20kB 174927 174931 174933 ... 906354 906496 906498\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data      (cells) float64 20kB 0.4569 0.3647 0.4264 ... 0.546 0.8065 0.8\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=9, indexing_scheme=nested)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>9</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d3751e80-951c-4a15-ab20-1f4c04ddd405' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d3751e80-951c-4a15-ab20-1f4c04ddd405' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'></div></div></li><li class='xr-section-item'><input id='section-2b5d4608-2941-4478-8fb4-8d7557aee1b2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2b5d4608-2941-4478-8fb4-8d7557aee1b2' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>cells</span>: 2561</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5b08bb3e-09bf-427a-9b4b-6805b580c6b6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5b08bb3e-09bf-427a-9b4b-6805b580c6b6' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>174927 174931 ... 906496 906498</div><input id='attrs-9fd77c51-9d75-42cb-8c1d-57462041f9af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fd77c51-9d75-42cb-8c1d-57462041f9af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1315e3c-35c5-4a49-ab57-d025fabd22b5' class='xr-var-data-in' type='checkbox'><label for='data-f1315e3c-35c5-4a49-ab57-d025fabd22b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>9</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><pre>array([174927, 174931, 174933, ..., 906354, 906496, 906498])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1d78e1d9-e038-4690-b37f-36fa1eed1d6e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1d78e1d9-e038-4690-b37f-36fa1eed1d6e' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4569 0.3647 0.4264 ... 0.8065 0.8</div><input id='attrs-0e912a6e-fb76-4102-9583-04e3dff3bb23' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0e912a6e-fb76-4102-9583-04e3dff3bb23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4abab60-766a-4cfa-90c2-c894aafa29d8' class='xr-var-data-in' type='checkbox'><label for='data-d4abab60-766a-4cfa-90c2-c894aafa29d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.45686489, 0.36466668, 0.42636366, ..., 0.546     , 0.80650005,\n",
+       "       0.80000001])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cea34c78-0610-4709-8bed-75914c5b04ef' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cea34c78-0610-4709-8bed-75914c5b04ef' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div><div style='display: inline-grid; grid-template-columns: 0px 20px auto; width: 100%;'><div style='grid-column-start: 1;border-right: 0.2em solid;border-color: var(--xr-border-color);height: 1.2em;width: 0px;'></div><div style='grid-column-start: 2;grid-row-start: 1;height: 1em;width: 20px;border-bottom: 0.2em solid;border-color: var(--xr-border-color);'></div><div style='grid-column-start: 3;'><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+       "  --xr-background-color: var(--jp-layout-color0, white);\n",
+       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1f1f1f;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: inline-block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:focus + label {\n",
+       "  border: 2px solid var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 142kB\n",
+       "Dimensions:   (cells: 8901)\n",
+       "Coordinates:\n",
+       "  * cell_ids  (cells) int64 71kB 699708 699709 699710 ... 3625986 3625992\n",
+       "Dimensions without coordinates: cells\n",
+       "Data variables:\n",
+       "    data      (cells) float64 71kB 0.326 0.421 0.414 0.5363 ... 0.838 0.82 0.8\n",
+       "Indexes:\n",
+       "    cell_ids  HealpixIndex(nside=10, indexing_scheme=nested)</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>10</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-27da4514-fefa-4f1f-8d97-1cae4d59369f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-27da4514-fefa-4f1f-8d97-1cae4d59369f' class='xr-section-summary'  title='Expand/collapse section'>Groups: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><div style='display: inline-grid; grid-template-columns: 100%; grid-column: 1 / -1'></div></div></li><li class='xr-section-item'><input id='section-24dd5f30-99e5-4dd9-ab4a-dd63b07f7c8a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-24dd5f30-99e5-4dd9-ab4a-dd63b07f7c8a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>cells</span>: 8901</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-125b1bcd-9916-499f-bc16-b10218a97403' class='xr-section-summary-in' type='checkbox'  checked><label for='section-125b1bcd-9916-499f-bc16-b10218a97403' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cell_ids</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>699708 699709 ... 3625986 3625992</div><input id='attrs-58195394-d91a-4460-b3db-a4c286b42576' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58195394-d91a-4460-b3db-a4c286b42576' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ac813f3-e245-454b-95dc-997b7d0a88fd' class='xr-var-data-in' type='checkbox'><label for='data-5ac813f3-e245-454b-95dc-997b7d0a88fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_name :</span></dt><dd>healpix</dd><dt><span>level :</span></dt><dd>10</dd><dt><span>indexing_scheme :</span></dt><dd>nested</dd></dl></div><div class='xr-var-data'><pre>array([ 699708,  699709,  699710, ..., 3625985, 3625986, 3625992])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-629a195c-602c-45c7-b989-7f4a9c7349a0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-629a195c-602c-45c7-b989-7f4a9c7349a0' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(cells)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.326 0.421 0.414 ... 0.82 0.8</div><input id='attrs-3578d792-8267-4434-bd39-b21fb643d236' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3578d792-8267-4434-bd39-b21fb643d236' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b47c34d3-063e-4f76-b151-f06da89e22c2' class='xr-var-data-in' type='checkbox'><label for='data-b47c34d3-063e-4f76-b151-f06da89e22c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.32600001, 0.42100002, 0.41400002, ..., 0.83800006, 0.82000005,\n",
+       "       0.80000001])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-801ecd5c-4276-472a-8f09-eaec3006b4a3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-801ecd5c-4276-472a-8f09-eaec3006b4a3' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div></div></div></div></div></li><li class='xr-section-item'><input id='section-1bc72d13-d576-4119-b5e9-1588bb88a7cf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1bc72d13-d576-4119-b5e9-1588bb88a7cf' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0874c543-0873-430a-8e0f-66cc2fd3c8a8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0874c543-0873-430a-8e0f-66cc2fd3c8a8' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-667e5ad0-da66-451d-814c-97653471b183' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-667e5ad0-da66-451d-814c-97653471b183' class='xr-section-summary'  title='Expand/collapse section'>Inherited coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-0a684158-7e4e-42bb-acdc-189e0335770c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0a684158-7e4e-42bb-acdc-189e0335770c' class='xr-section-summary'  title='Expand/collapse section'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-03b2491c-51d6-4f7c-a9df-585099804207' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-03b2491c-51d6-4f7c-a9df-585099804207' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataTree>\n",
+       "Group: /\n",
+       "├── Group: /9\n",
+       "│       Dimensions:   (cells: 2561)\n",
+       "│       Coordinates:\n",
+       "│         * cell_ids  (cells) int64 20kB 174927 174931 174933 ... 906354 906496 906498\n",
+       "│       Dimensions without coordinates: cells\n",
+       "│       Data variables:\n",
+       "│           data      (cells) float64 20kB 0.4569 0.3647 0.4264 ... 0.546 0.8065 0.8\n",
+       "│       Indexes:\n",
+       "│           cell_ids  HealpixIndex(nside=9, indexing_scheme=nested)\n",
+       "└── Group: /10\n",
+       "        Dimensions:   (cells: 8901)\n",
+       "        Coordinates:\n",
+       "          * cell_ids  (cells) int64 71kB 699708 699709 699710 ... 3625986 3625992\n",
+       "        Dimensions without coordinates: cells\n",
+       "        Data variables:\n",
+       "            data      (cells) float64 71kB 0.326 0.421 0.414 0.5363 ... 0.838 0.82 0.8\n",
+       "        Indexes:\n",
+       "            cell_ids  HealpixIndex(nside=10, indexing_scheme=nested)"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_all = xr.DataTree.from_dict(plevels)\n",
+    "ds_all"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c269f923-1bc1-4865-b3ac-997c799e2727",
+   "metadata": {},
+   "source": [
+    "## Save it to zarr\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "ec498f96-8087-4282-a088-28b73e26e319",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_all.to_zarr(\"ww3.zarr\", mode=\"w\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ecd4aff4-3373-4aca-8eaf-d641c38aa942",
+   "metadata": {},
+   "source": [
+    "### Load multigrid data from zarr and plot them together"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "76fad969-05e9-42dd-98a7-26ce5b2a88d0",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d96170905294404d89f186f0fa44f954",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f1eec80…"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = xr.open_datatree(\"ww3.zarr\")\n",
+    "data\n",
+    "data[\"9\"][\"data\"].compute().pipe(xdggs.decode).dggs.explore(\n",
+    "    center=0, cmap=\"coolwarm\", alpha=0.8\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "a0beb228-43e0-4c8d-9111-da23ddbdfaa2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "\n",
+    "def create_arrow_table(polygons, arr, coords=None):\n",
+    "    from arro3.core import Array, ChunkedArray, Schema, Table\n",
+    "\n",
+    "    if coords is None:\n",
+    "        coords = [\"latitude\", \"longitude\"]\n",
+    "\n",
+    "    array = Array.from_arrow(polygons)\n",
+    "    name = arr.name or \"data\"\n",
+    "    arrow_arrays = {\n",
+    "        \"geometry\": array,\n",
+    "        \"cell_ids\": ChunkedArray([Array.from_numpy(arr.coords[\"cell_ids\"])]),\n",
+    "        name: ChunkedArray([Array.from_numpy(arr.data)]),\n",
+    "    } | {\n",
+    "        coord: ChunkedArray([Array.from_numpy(arr.coords[coord].data)])\n",
+    "        for coord in coords\n",
+    "        if coord in arr.coords\n",
+    "    }\n",
+    "\n",
+    "    fields = [array.field.with_name(name) for name, array in arrow_arrays.items()]\n",
+    "    schema = Schema(fields)\n",
+    "\n",
+    "    return Table.from_arrays(list(arrow_arrays.values()), schema=schema)\n",
+    "\n",
+    "\n",
+    "def normalize(var, center=None):\n",
+    "    from matplotlib.colors import CenteredNorm, Normalize\n",
+    "\n",
+    "    if center is None:\n",
+    "        vmin = var.min(skipna=True)\n",
+    "        vmax = var.max(skipna=True)\n",
+    "        normalizer = Normalize(vmin=vmin, vmax=vmax)\n",
+    "    else:\n",
+    "        halfrange = np.abs(var - center).max(skipna=True)\n",
+    "        normalizer = CenteredNorm(vcenter=center, halfrange=halfrange)\n",
+    "\n",
+    "    return normalizer(var.data)\n",
+    "\n",
+    "\n",
+    "def exploire_layer(\n",
+    "    arr,\n",
+    "    cell_dim=\"cells\",\n",
+    "    cmap=\"viridis\",\n",
+    "    center=None,\n",
+    "    alpha=None,\n",
+    "):\n",
+    "    from lonboard import SolidPolygonLayer\n",
+    "    from lonboard.colormap import apply_continuous_cmap\n",
+    "    from matplotlib import colormaps\n",
+    "\n",
+    "    if len(arr.dims) != 1 or cell_dim not in arr.dims:\n",
+    "        raise ValueError(\n",
+    "            f\"exploration only works with a single dimension ('{cell_dim}')\"\n",
+    "        )\n",
+    "\n",
+    "    cell_ids = arr.dggs.coord.data\n",
+    "    grid_info = arr.dggs.grid_info\n",
+    "\n",
+    "    polygons = grid_info.cell_boundaries(cell_ids, backend=\"geoarrow\")\n",
+    "\n",
+    "    normalized_data = normalize(arr.variable, center=center)\n",
+    "\n",
+    "    colormap = colormaps[cmap]\n",
+    "    colors = apply_continuous_cmap(normalized_data, colormap, alpha=alpha)\n",
+    "\n",
+    "    table = create_arrow_table(polygons, arr)\n",
+    "    layer = SolidPolygonLayer(table=table, filled=True, get_fill_color=colors)\n",
+    "\n",
+    "    return layer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "eb7b0881-13a8-473c-b442-66ffdd0d9f6e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4b291ed4ffe64734a5985dfee00e1a90",
+       "version_major": 2,
+       "version_minor": 1
+      },
+      "text/plain": [
+       "Map(layers=[SolidPolygonLayer(filled=True, get_fill_color=<pyarrow.lib.FixedSizeListArray object at 0x7f1eec80…"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import lonboard\n",
+    "\n",
+    "arr9 = (\n",
+    "    data[\"9\"]\n",
+    "    .ds[\"data\"]\n",
+    "    .pipe(xdggs.decode)  # .dggs.sel_latlon(latitude=48, longitude=0)[\"data\"]\n",
+    ")\n",
+    "arr10 = (\n",
+    "    data[\"10\"]\n",
+    "    .ds[\"data\"]\n",
+    "    .pipe(xdggs.decode)  # .dggs.sel_latlon(latitude=49, longitude=0)[\"data\"]\n",
+    ")\n",
+    "# cmap=\"Reds\"\n",
+    "lonboard.Map(\n",
+    "    [\n",
+    "        exploire_layer(\n",
+    "            arr9,\n",
+    "            alpha=1,\n",
+    "        ),\n",
+    "        exploire_layer(arr10, alpha=1),\n",
+    "    ]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ddf9987a-f7c6-4874-9c4c-a81fd6d6ab45",
+   "metadata": {},
+   "source": [
+    "## Whats next\n",
+    "\n",
+    "Use WW3 unstructured grid originated data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "58f197a9-8ffd-4e17-8afe-59e2e41c6d44",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}