Parcels v2.2.0: a Lagrangian Ocean Analysis tool for the petascale age

Parcels v2.2.0 builds upon previous versions of Parcels and adds a number of new features. most importantly

1. Improved advection-diffusion kernels, as detailed in this tutorial by @daanreijnders (#823)
2. Support for time-evolving sigma-grids (#660)
3. New interpolation scheme for tracers near coastlines, as detailed in this tutorial, thanks to @pierrick-giffard. (#815)
4. Addition of Kernels to calculate the TEOS-10 equation of state, thanks to @pdnooteboom (#816)
5. Partial implementation of AnalyticalAdvection Kernel following Döös et al 2017, see also this tutorial
6. Support for dimensions of length-1. This greatly simplifies creating FieldSets that are constant in longitude and/or latitude (#817)

Plus a large number of minor bug fixes

Parcels v2.1.5: a Lagrangian Ocean Analysis tool for the petascale age

Parcels v2.1.5 builds upon previous versions of Parcels and both improved the reliability as well as the efficiency and versatility of Parcels. In particular

1. Speed up by perhaps a factor 10(!) in some use-cases by switching data structure of ParticleSet from Array-of-Structures to Structure-of-Arrays (#678, thanks @angus-g!)
2. Support for sigma-grids with time-varying depth dimensions (#660, see also this tutorial)
3. Further fixes some issues with dask chunking (# 764, #774, #776)
4. Improves reliability when dt is very small (< 0.001 s) (#762)
5. Support for a new ErrorCode StopExecution (#780)
6. Support for python3.8 (#753)

And various other minor bug fixes

Parcels v2.1.4: a Lagrangian Ocean Analysis tool for the petascale age

Parcels v2.1.4 is a quick update on v2.1.3 that mostly improves the implementation of field-chunking using dask.

1. It fixes some Issues with dask chunking, particularly in 3D simulations (#738, #740 and #731)
2. It adds a von Mises distribution to parcels.random (#725)

And numerous smaller bugfixes.

Parcels v2.1.3: a Lagrangian Ocean Analysis tool for the petascale age

Parcels v2.1.3 is an update mostly focussing on improved memory behaviour when doing large simulations. In particular

1. It fixes some serious issues with memory usage for field chunking (see #668, #703 and #711), which have now been addressed in #719
2. Fixing xarray compatibility (#716)
3. Fixing a bug in cartopy.quiver (#714)
4. New kernels to compute density (#688)

And various other minor bug fixes

Parcels v2.1.2: a Lagrangian Ocean Analysis tool for the petascale age

Parcels v2.1.2 is a quick release build on previous versions v2.1.1. In particular:

1. It fixes a serious bug on some systems with floating point accuracy, that could lead to incorrect output files (see #670 and solution at #672). For this reason, all users are encouraged to use this new version v2.1.2 instead of v2.1.1.
2. It also fixes a smaller bug (#676) with the timestamps argument in Field.from_netcdf()

Parcels v2.1.1: a Lagrangian Ocean Analysis tool for the petascale age

Parcels v2.1.1 builds on previous versions v2.0.0. The major changes of v2.1.1 are:

[Note that v2.1.1 comes after a botched release of v2.1.0]

1. Parcels has a parallel MPI version! While working on multiple processors, the particles are spread over the processors for an efficient integration. (#625). See https://oceanparcels.org#parallel_install for instructions on how to install.
2. For an efficient loading of the Fieldset, the Field objects are now loaded by chunks, controlled by the parameter field_chunksize (#632). This results in lower memory usage and faster simulation. It is also a fundamental part of the parallel implementation, since for low number of particles per processor, the computation time is dominated by the loading of the data. A more efficient parallel version will be dynamically balancing the particles between the processors such to minimise the number of chunks loaded per processor. See this document for further background on the implementation.
3. An efficient writing of the particleset. For a quicker export of the data, particles are now dumped into npy files during simulation. The pickles are gathered into one single file at the end of the simulation. (#614)
4. A proper management of particle.dt modified by the kernel. If the kernel modifies particle.dt, the kernel will automatically be restarted with the updated dt. If you want to simply updates the dt for next kernel call, use particle.update_next_dt(new_dt). (#657)
5. New particles can now be added to the ParticleSet only via a temporary ParticleSet object. This enables a proper control of the particle.id in parallel (#629)
6. Field.gradient() function is not available anymore. This functionality was providing spurious results on curvilinear grids and was conflicting with the use of chunked fields. Users can still obtain easily an accurate field gradient (see example proposed in #633)
7. Using the time_periodic flag in FieldSet creation now requires the length of the period (#659)
8. Numerous bug fixes

Note that Parcels v2.1.1 is the last version to officially support Python 2.7. While all functionalities currently work with both Python 2 and 3, new development and code dependencies will progressively lead to incompatibility with Python 2. We strongly advice the users to switch to Python 3.

Parcels v2.1.0: a Lagrangian Ocean Analysis tool for the petascale age

Parcels v2.1.0 builds on previous versions v2.0.0. The major changes of v2.1.0 are:

1. Parcels has a parallel MPI version! While working on multiple processors, the particles are spread over the processors for an efficient integration. (#625). See https://oceanparcels.org#parallel_install for instructions on how to install.
2. For an efficient loading of the Fieldset, the Field objects are now loaded by chunks, controlled by the parameter field_chunksize (#632). This results in lower memory usage and faster simulation. It is also a fundamental part of the parallel implementation, since for low number of particles per processor, the computation time is dominated by the loading of the data. A more efficient parallel version will be dynamically balancing the particles between the processors such to minimise the number of chunks loaded per processor. See this document for further background on the implementation.
3. An efficient writing of the particleset. For a quicker export of the data, particles are now dumped into npy files during simulation. The pickles are gathered into one single file at the end of the simulation. (#614)
4. A proper management of particle.dt modified by the kernel. If the kernel modifies particle.dt, the kernel will automatically be restarted with the updated dt. If you want to simply updates the dt for next kernel call, use particle.update_next_dt(new_dt). (#657)
5. New particles can now be added to the ParticleSet only via a temporary ParticleSet object. This enables a proper control of the particle.id in parallel (#629)
6. Field.gradient() function is not available anymore. This functionality was providing spurious results on curvilinear grids and was conflicting with the use of chunked fields. Users can still obtain easily an accurate field gradient (see example proposed in #633)
7. Using the time_periodic flag in FieldSet creation now requires the length of the period (#659)
8. Numerous bug fixes

Note that Parcels v2.1.0 is the last version to officially support Python 2.7. While all functionalities currently work with both Python 2 and 3, new development and code dependencies will progressively lead to incompatibility with Python 2. We strongly advice the users to switch to Python 3.

Parcels v2.0.0: a Lagrangian Ocean Analysis tool for the petascale age

Parcels v2.0.0 builds on previous versions v2.0.0.beta and v2.0.0.beta2. It's the release which is fully described in the paper The Parcels v2.0 Lagrangian framework: new field interpolation schemes, by Delandmeter and van Sebille, 2019, GMD.

The major changes of v2.0.0 compared to v1.1.1 are

1. The order of arguments for Field interpolation has changed. This is now field[time, depth, lat, lon], which is consistent with the dimension order in which data is stored in the field.data numpy array (#503 and #276).

2. The dt argument has been dropped from Kernel definitions, so that the only arguments allowed in a Kernel are def kernelfunc(fieldset, particle, time) (#503)

3. Interpolation for C-grids is now done in a fluxes framework, instead of a velocity framework (#499 and #494).

4. Interpolation for B-grids (#573)

5. Support for np.float64 accuracy of particle locations. This can be set using the lonlatdepth_dtype argument in ParticleSet construction. Default is np.float64 for C-grids, and np.float32 for all other grids (#552 and #557)

Note also a number of other minor development:

• See v2.0.0.beta
• See v2.0.0.beta2
• Unpinning netcdf4 1.4.1 (#597)
• Numerous bug fixes

Parcels v2.0.0-beta2: a Lagrangian Ocean Analysis tool for the petascale age

This is the second beta version of Parcels v2.0.0. It builds upon v2.0.0beta, and compared to that version has a few important fixes and improvements:

• Support for np.float64 accuracy of particle locations. This can be set using the lonlatdepth_dtype argument in ParticleSet construction. Default is np.float64 for C-grids, and np.float32 for all other grids (#552 and #557)
• Renaming of the full_load argument in FieldSet.from_netcdf() construction to deferred_load, where deferred_load = not full_load, for consistency with how we normally call this mode. Default for netcdf files with more than three snapshots is deferred_load=True (#550)
• Support for Netcdf files without a time dimension, by using the timestamps argument in FieldSet construction (#540)
• New tutorials on how to work with 3-dimensional C-grid data such as NEMO (#531) and the UnitConverter classes (#516)
• Check if the keys in the dimensions dictionary are only lon, lat, depth and time (#545)
• Change in how variable name should be set in Field.from_netcdf(). Now use tuple variable=(Field_name, variable_name_in_NetCDF_file) (#545)
• Numerous bugfixes

Note also that there is a problem with the latest release of the netCDF4 library, v1.4.2 (Issue #513). For the time being, we recommend downgrading to v1.4.1, using conda install netcdf4=1.4.1

Parcels v2.0.0-beta: a Lagrangian Ocean Analysis tool for the petascale age

This is the beta-release of Parcels v2. Compared to the last v1.1.1 release, there are three important changes

1. The order of arguments for Field interpolation has changed. This is now field[time, depth, lat, lon], which is consistent with the dimension order in which data is stored in the field.data numpy array (#503 and #276).

2. The dt argument has been dropped from Kernel definitions, so that the only arguments allowed in a Kernel are def kernelfunc(fieldset, particle, time) (#503)

3. Interpolation for C-grids is now done in a fluxes framework, instead of a velocity framework. The details of this will be presented in a manuscript, to be submitted soon (#499 and #494)

Note that 1) and 2) above mean that Kernels written for Parcels v1 will break in this Parcels v2. If you're updating to this v2.0.0beta, therefore please update your custom Kernels.

Other updates since v1.1.1 are:

• New FieldSet.from_xarray_dataset() method to directly read xarray.DataSet objects (#476)
• An optional argument in Field.show() to control which depth level to plot (#478)
• ParticleSet.from_field() now also implemented for Curvilinear Fields (#496)
• And numerous small bug fixes