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CliMT is a Toolkit for building Earth system models in Python.

Project description

=====
CliMT
=====


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CliMT is a Toolkit for building Earth system models in Python. CliMT stands for *Climate Modelling
and diagnostics Toolkit* -- it is meant both for creating models and for generating diagnostics
(radiative fluxes for an atmospheric column, for example). However, since it might eventually
include model components for purposes other than climate modelling (local area models, large-eddy
simulation), we prefer to keep the abbreviation un-expanded!

CliMT hopes to enable researchers to easily perform online analysis and make
modifications to existing models by increasing the ease with which models
can be understood and modified. It also enables educators to write
accessible models that serve as an entry point for students into Earth
system modeling, while also containing state-of-the-art components.

Initially CliMT contains only components for the atmosphere, and does not yet
include a coupler. But there are plans to extend CliMT to a fully coupled Earth
system model in the future. The toolkit is also written in such a way that it
could enable the development of non-climate models (e.g. weather prediction,
large-eddy simulation). To do so requires only that the prognostic and
diagnostic schemes are wrapped into the correct Python-accessible interface.

CliMT builds on Sympl_, which provides the base classes and array and constants handling
functionality. Thanks to Sympl_ and Pint_, CliMT is also a fully units aware model. It is
useful to know how Sympl_ works to use CliMT better. Read more about Sympl_ at
https://sympl.readthedocs.io.

* Free software: BSD license
* Documentation: https://climt.readthedocs.io.

Installation
-------------

CliMT can be installed directly from the python package index using pip.

pip install climt

should work on most systems. From version 0.9.2 onwards, this command will
install binary wheels, eliminating the requirement of a compiler on your
system.

Detailed instructions for Mac and Linux systems are available in the `documentation`_.

Features
--------

* CliMT is fully units-aware!
* Uses the xarray_ `DataArray` abstraction to build self describing model arrays.
* Provides different levels of abstraction towards building a climate model.
* Like Sympl_, CliMT consciously uses descriptive names in the user API to ensure
model scripts are self-documenting.
* Allows for quick prototyping of earth system model components.
* Provides a clean and convenient interface to add new components.

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
.. _Sympl: https://github.com/mcgibbon/sympl
.. _Pint: https://pint.readthedocs.io
.. _xarray: http://xarray.pydata.org
.. _documentation: http://climt.readthedocs.io/en/latest/installation.html


=======
History
=======

v.0.14.3
-------

* Fix release issue because of pip API change

v.0.14.1
--------
* Fix appveyor fail due to pip changes

v.0.14.0
--------

* Fixed broken version numbers

v.0.12.0
--------

* new release to fix version numbers and create zenodo ID

v.0.9.4
-------

* Added attributes to inputs/outputs/ etc., to work with ScalingWrapper
Added tests as well.
* Added tests for constants functions
* Fixed requirements to ensure this version of climt installs
the correct versions of sympl and numpy.

v.0.9.3
-------

* Released because of a labelling issue. See 0.9.2 for details.

v.0.9.2
--------
* Updated documentation
* Cleaned up examples
* Added (*)_properties as a property to all components
* The gas constant for dry air in the Emanuel scheme is now renamed _Rdair
* RRTMG LW and SW are now OpenMP parallel
* Added Instellation component to calculate zenith angle
* Added tests to increase coverage
* New constants handling functionality added
* Travis builds now use stages
* Appveyor CI up and running
* Pre-installation of cython and numpy no longer necessary for source builds
* Added snow-ice component
* Ozone profiles do not need to be specified externally
* Now also tested on Python 3.6

Breaking Changes
----------------

* API for constants setting changed to `set_constant_from_dict` and `add_constants_from_dict`
* `GfsDynamicalCore` renamed to `GFSDynamicalCore` for consistency
* `get_prognostic_version` method of `ClimtImplicit` renamed to `prognostic_version`, and
no longer accepts timestep as an argument. The current timestep should be set in
`ClimtImplicit.current_time_step` during each iteration.
* `RRTMGShortwave` now uses sympl's solar constant by default instead of from fortran.

v.0.9.1
-------
* Held-Suarez and moist GCM with grey radiation work!
* Added DCMIP initial conditions, test 4 tried out.
* Dynamical core integrated now.
* BIG change in the build system. Tests pass on Mac as well
* Arrays can now have arbitrary dtype (to use qualitative, string, quantities)
* Added Emanuel Convection, surface energy balance model and ice sheet energy balance
* 2D coordinates are now supported for horizontal coordinates
* Replaced create_output_arrays() with a more general
get_state_dict_for() and get_numpy_arrays_from_state()
combination.
* State arrays now have coordinates
* Updated documentation
* RTD finally working, phew!
* Added RRTMG Longwave, Simple Physics
* Added helper functions to reduce boilerplate code in components

Breaking Changes
----------------

Latest
-------

* method to obtain piecewise constant prognostic has been renamed to
:code:`piecewise_constant_version`
* Ozone profile has been modified
* Heating rate for RRTMG top-of-atmosphere is no longer manually set to zero
* Components no longer accept constants during initialisation. All constant handling
is done internally.

v.0.9
------
* SlabSurface no longer uses depth_slab_surface as input
* changed order of outputs of GfsDynamicalCore and SimplePhysics to conform
to TimeStepper order of diagnostics, new_state
* get_default_state now accepts mid_levels and interface_levels instead of z
to specify vertical coordinates.
* mass_to_volume_mixing_ratio now uses numpy arrays instead of DataArrays.


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