Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

You can contribute in many ways:

Types of Contributions

Usage in Publications

If you use CliMT to perform research, your publication is a valuable resource for others looking to learn the ways they can leverage CliMT’s capabilities. If you have used CliMT in a publication, please let us know so we can add it to the list.

Presenting CliMT to Others

CliMT is meant to be an accessible, community-driven model. You can help the community of users grow and be more effective in many ways, such as:

  • Running a workshop
  • Offering to be a resource for others to ask questions
  • Presenting research that uses CliMT

If you or someone you know is contributing to the CliMT community by presenting it or assisting others with the model, please let us know so we can add that person to the contributors list.

Report Bugs

Report bugs at

If you are reporting a bug, please include:

  • Your operating system name and version.
  • Any details about your local setup that might be helpful in troubleshooting.
  • Detailed steps to reproduce the bug.

Fix Bugs

Look through the GitHub issues for bugs. Anything tagged with “bug” and “help wanted” is open to whoever wants to implement it.

Implement Features

Look through the GitHub issues for features. Anything tagged with “enhancement” and “help wanted” is open to whoever wants to implement it.

Write Documentation

CliMT could always use more documentation. You could:

  • Clean up or add to the official CliMT docs and docstrings.
  • Write useful and clear examples that are missing from the examples folder.
  • Create a Jupyter notebook that uses CliMT and share it with others.
  • Prepare reproducible model scripts to distribute with a paper using CliMT.
  • Anything else that communicates useful information about CliMT.

Submit Feedback

The best way to send feedback is to file an issue at

If you are proposing a feature:

  • Explain in detail how it would work.
  • Keep the scope as narrow as possible, to make it easier to implement.
  • Remember that this is a volunteer-driven project, and that contributions are welcome :)

Get Started!

Ready to contribute? Here’s how to set up climt for local development.

  1. Fork the climt repo on GitHub.

  2. Clone your fork locally:

    $ git clone
  3. Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:

    $ mkvirtualenv climt
    $ cd climt/
    $ python develop
  4. Create a branch for local development:

    $ git checkout -b name-of-your-bugfix-or-feature

    Now you can make your changes locally.

  5. When you’re done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:

    $ flake8 climt tests
    $ python test or py.test
    $ tox

    To get flake8 and tox, just pip install them into your virtualenv.

  6. Commit your changes and push your branch to GitHub:

    $ git add .
    $ git commit -m "Your detailed description of your changes."
    $ git push origin name-of-your-bugfix-or-feature
  7. Submit a pull request through the GitHub website.

Pull Request Guidelines

Before you submit a pull request, check that it meets these guidelines:

  1. The pull request should include tests.
  2. If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.rst.
  3. The pull request should work for Python 2.7, 3.4 and 3.5. Check and make sure that the tests pass for all supported Python versions.


In the CliMT code, we follow PEP 8 style guidelines (tested by flake8). You can test style by running “tox -e flake8” from the root directory of the repository. There are some exceptions to PEP 8:

  • All lines should be shorter than 80 characters. However, lines longer than this are permissible if this increases readability (particularly for lines representing complicated equations).
  • Space should be assigned around arithmetic operators in a way that maximizes readability. For some cases, this may mean not including whitespace around certain operations to make the separation of terms clearer, e.g. “Cp*T + g*z + Lv*q”.
  • While state dictionary keys are full and verbose, within components they may be assigned to shorter names if it makes the code clearer.
  • We can take advantage of known scientific abbreviations for quantities within components (e.g. “T” for “air_temperature”) even thought they do not follow pothole_case.


To run a subset of tests:

$ py.test tests.test_timestepping