{"id":13569787,"url":"https://github.com/CliMT/climt","last_synced_at":"2025-04-04T06:31:13.702Z","repository":{"id":45178092,"uuid":"74854230","full_name":"CliMT/climt","owner":"CliMT","description":"The official home of climt, a Python based climate modelling toolkit.","archived":false,"fork":false,"pushed_at":"2024-03-09T16:28:08.000Z","size":69656,"stargazers_count":164,"open_issues_count":38,"forks_count":45,"subscribers_count":14,"default_branch":"develop","last_synced_at":"2024-10-29T22:32:18.471Z","etag":null,"topics":["atmospheric-modelling","climate-model","python"],"latest_commit_sha":null,"homepage":"https://climt.readthedocs.io","language":"Fortran","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/CliMT.png","metadata":{"files":{"readme":"README.rst","changelog":"HISTORY.rst","contributing":"CONTRIBUTING.rst","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":"AUTHORS.rst","dei":null}},"created_at":"2016-11-26T22:32:37.000Z","updated_at":"2024-10-28T09:01:31.000Z","dependencies_parsed_at":"2023-09-21T19:32:30.445Z","dependency_job_id":"cda96f99-5584-4dc3-a404-fe5ec0a02f63","html_url":"https://github.com/CliMT/climt","commit_stats":{"total_commits":1305,"total_committers":11,"mean_commits":"118.63636363636364","dds":0.2628352490421456,"last_synced_commit":"c3bdf053b61001b787bf9c258bebf66ce5d654cd"},"previous_names":[],"tags_count":59,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CliMT%2Fclimt","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CliMT%2Fclimt/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CliMT%2Fclimt/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CliMT%2Fclimt/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CliMT","download_url":"https://codeload.github.com/CliMT/climt/tar.gz/refs/heads/develop","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":234205252,"owners_count":18796080,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["atmospheric-modelling","climate-model","python"],"created_at":"2024-08-01T14:00:44.276Z","updated_at":"2025-04-04T06:31:13.669Z","avatar_url":"https://github.com/CliMT.png","language":"Fortran","funding_links":[],"categories":["Climate computing and modeling","Observation and Conservation of Ecosystems","Climate Change","Uncategorized"],"sub_categories":["Ocean and Climate","Earth and Climate Modeling","Uncategorized"],"readme":"=====\nclimt\n=====\n\n\n.. image:: https://img.shields.io/pypi/v/climt.svg\n    :target: https://pypi.python.org/pypi/climt\n    :alt: PyPI\n\n.. image:: https://img.shields.io/travis/climt/climt.svg\n    :target: https://travis-ci.org/climt/climt\n    :alt: Continuous Integration\n\n.. image:: https://ci.appveyor.com/api/projects/status/h9ayx22cxyfwh5rh?svg=true\n    :target: https://ci.appveyor.com/project/JoyMonteiro/climt\n    :alt: Continuous Integration\n\n.. image:: https://img.shields.io/codecov/c/github/climt/climt.svg\n    :target: https://travis-ci.org/climt/climt\n    :alt: Coverage\n\n.. image:: https://readthedocs.org/projects/climt/badge/\n    :target: https://climt.readthedocs.io/en/latest/?badge=latest\n    :alt: Documentation Status\n\n.. image:: https://zenodo.org/badge/74854230.svg\n    :target: https://zenodo.org/badge/latestdoi/74854230\n    :alt: Zenodo DOI\n\n\n.. image:: ./docs/climt_logo.jpg\n    :height: 512px\n    :width: 512px\n    :align: center\n\n**climt** is a Toolkit for building Earth system models in Python. climt stands for *Climate Modelling\nand Diagnostics Toolkit* -- it is meant both for creating models and for generating diagnostics\n(radiative fluxes for an atmospheric column, for example). However, since it might eventually\ninclude model components for purposes other than climate modelling (local area models, large-eddy\nsimulation), we prefer to keep the abbreviation un-expanded!\n\nclimt hopes to enable researchers to easily perform online analysis and make\nmodifications to existing models by increasing the ease with which models\ncan be understood and modified. It also enables educators to write\naccessible models that serve as an entry point for students into Earth\nsystem modeling, while also containing state-of-the-art components.\n\nInitially climt contains only components for the atmosphere, and does not yet\ninclude a coupler. But there are plans to extend climt to a fully coupled Earth\nsystem model in the future. The toolkit is also written in such a way that it\ncould enable the development of non-climate models (e.g. weather prediction,\nlarge-eddy simulation). To do so requires only that the prognostic and\ndiagnostic schemes are wrapped into the correct Python-accessible interface.\n\nclimt builds on sympl_, which provides the base classes and  array and constants handling\nfunctionality. Thanks to sympl_ and Pint_, climt is also a fully units aware model. It is\nuseful to know how sympl_ works to use climt better. Read more about sympl_ at\nhttps://sympl.readthedocs.io.\n\n* Free software: BSD license\n* Documentation: https://climt.readthedocs.io.\n\nInstallation\n-------------\n\nNote - The GFS dynamical core has been made into a seperate package called \ngfs_dynamical_core_ for ease of maintenance. If you need the dynamical core, \nplease install this package from source or directly using pip. Doing this will\nautomatically install climt as well.\n\n    pip install gfs_dynamical_core\n\nclimt can be installed directly from the python package index using pip.\n\n    pip install climt\n\nshould work on most systems. From version 0.9.2 onwards, this command will\ninstall binary wheels, eliminating the requirement of a compiler on your\nsystem.\n\nDetailed instructions for Mac and Linux systems are available in the `documentation`_.\n\nFeatures\n--------\n\n* climt is fully units-aware!\n* Uses the xarray_ `DataArray` abstraction to build self describing model arrays. \n* Provides different levels of abstraction towards building a climate model.\n* Like sympl_, climt consciously uses descriptive names in the user API to ensure\n  model scripts are self-documenting.\n* Allows for quick prototyping of earth system model components.\n* Provides a clean and convenient interface to add new components.\n\nCiting climt\n------------\n\nIf you use climt in your research, please cite the following paper documenting sympl_ and climt\n\n    https://www.geosci-model-dev.net/11/3781/2018/\n\nCredits\n-------\n\nThis package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.\n\n.. _Cookiecutter: https://github.com/audreyr/cookiecutter\n.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage\n.. _sympl: https://github.com/mcgibbon/sympl\n.. _Pint: https://pint.readthedocs.io\n.. _xarray: http://xarray.pydata.org\n.. _documentation: http://climt.readthedocs.io/en/latest/installation.html\n.. _gfs_dynamical_core: https://github.com/Ai33L/gfs_dynamical_core\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FCliMT%2Fclimt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FCliMT%2Fclimt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FCliMT%2Fclimt/lists"}