NOTE

This code works with a version of MONC that puts the profiles of reference variables in the model dumps

LICENSE

These programs/scripts are free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with this program. If not, see http://www.gnu.org/licenses/.

Copyright (C) 2013-2014 Steven Boeing, ETHZ

Copyright (C) 2015 Steven Boeing, University of Leeds

CONTACT

S."lastname with oe" (at) leeds.ac.uk OR sjboing (at) "the usual g-mail suffix"

DESCRIPTION

This is a collection of scripts for post-processing (after-burning) MONC output

This directory includes the following scripts

• pp_MONC.py: Generic postprocessing routine for a single case. This is the code that users can modify easily
• pp_MONC_infrastucture.py: Classes and functions used in pp_MONC.py
• pp_MONC_constants.py: Physical constants from MONC, for calculation of derived variables
• pp_MONC_settings.py: Set what type of output to generate, and at which locations. Also sets part of the file path on different machines Uses .cfg configuration files
• fieldslist.py: Lists of variables to analyze
• areaspectra.py: code for calculating spectra (thanks Juerg Schmidli, ETHZ)
• .syscfg files: the settings on different systems (e.g. paths)
• .cfg files: the settings for different cases (e.g. bubbles on different domains)

REQUIREMENTS

Python with netcdf4python, numpy and scipy (for embedding C-code with weave)

OUTPUT FILES

• clouds.*.tar: tar file with 3d cloud fields (no gz, as cloud fields themselves are already compressed)
• cross_xy.*.nc: cross-sections in the x,y plane
• cross_xz.*.nc: cross-sections in the x,z plane
• cross_yz.*.nc: cross-sections in the y,z plane
• samp_1d.*.nc: sampled profile diagnostics
• spec_x.*.nc: spectra along the x-direction
• spec_y.*.nc: spectra along the y-direction
• stat_1d.*.nc: mean profile diagnostics
• stat_dom.*.nc: domain integrated diagnostics
• stat_int.*.nc: column integrated diagnostics
• stat_xz.*.nc: mean diagnostics in the x,z plane
• stat_yz.*.nc: mean diagnostics in the y,z plane

ADVANTAGES

• Easy to add a variable, and obtain a range of outputs on it.
• Correction for staggered grids already implemented.
• Easy to add e.g. vector operations exploiting standard python (see pp_MONC_infrastucture.py for examples, such as the calculation of vortivity in the hvort and vvort routines).
• Optional use of netcdf compression

KNOWN ISSUES/FEATURES

• The code works on 3D NetCDF files that include reference profiles for pressure and density, as well as the default checkpoint outputs. The reference checkpoint files are not included in checkpoints on the trunk, though a ticket has been raised to address the issue. SB has a version of the code that does output checkpoitn profiles.
• For very large cases, one could also run out of memory. Suggestions:
  • use node with more memory
  • delete temporary variables using "del", or restructure script
• The code works in serial. In theory, it would be easy to have different nodes/ cores could work on different parts of the data (memory permitting). It would be possible to restructure the code to use e.g. numba as well, but so far there has been no need to.

EXAMPLE USAGE

python pp_MONC.py bomex small_100 "bomex" is the case directory name "small_100" is the experiment name

python pp_MONC.py bomex small_100 -c default.cfg -s xcm.syscdf "bomex" is the case directory name "small_100" is the experiment name "default.cfg" is the configuration "xcm.syscfg" sets the paths on the xcm

The input files are located at e.g. /nfs/see-fs-01_users/"yourname"/MONCin/bomex/small_100/ (on the SEE systems in Leeds)

AVAILABLE VARIABLES

• See fieldslist.py for a list of fields and their description.

ADDING A VARIABLE

• Append the variable to the corresponding list in fieldslist.py (see the top of this file for more details)

• Add the output function and the calculation of the variable to pp_MONC.py. Output functions are

  process_var: process statistics and make cross sections

  stat_var: process only the statistics of the variable

  int_var: this is a height integrated variable

  ref_var: this is a reference variable profile

RETRIEVING VARIABLES FROM INPUT NETCDF

• The following functions are used:

  self.gv: get a variable

  self.gq: get a scalar

  self.gref: get a reference profile

CHANGING THE PATH OF INPUT/OUTPUT

• See pp_MONC_settings.py for default paths on a number of platforms