Google DeepMind GraphCast and GenCast

WARNING: For backwards compatibility, we have also left GraphCast data in the top level of the bucket. These will eventually be deleted in favour of the graphcast/ subdir.

Brief description of relevant library files:

• casting.py: Wrapper used around GraphCast to make it work using

• graphcast.py: The main GraphCast model architecture for one-step of

• solar_radiation.py: Computes Top-Of-the-Atmosphere (TOA) incident solar

Dependencies.

Chex, Dask, Dinosaur, Haiku, JAX, JAXline, Jraph, Numpy, Pandas, Python, SciPy, Tree, Trimesh, XArray and XArray-TensorStore.

License and Disclaimers

The Colab notebooks and the associated code are licensed under the Apache License, Version 2.0. You may obtain a copy of the License at: https://www.apache.org/licenses/LICENSE-2.0.

The model weights are made available for use under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). You may obtain a copy of the License at: https://creativecommons.org/licenses/by-nc-sa/4.0/.

This is not an officially supported Google product.

Unless required by applicable law or agreed to in writing, all software and materials distributed here under the Apache 2.0 or CC-BY-NC-SA 4.0 licenses are distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the licenses for the specific language governing permissions and limitations under those licenses.

GenCast and GraphCast are part of an experimental research project. You are solely responsible for determining the appropriateness of using or distributing GenCast, GraphCast or any outputs generated and assume all risks associated with your use or distribution of GenCast, GraphCast and outputs and your exercise of rights and permissions granted by Google to you under the relevant License. Use discretion before relying on, publishing, downloading or otherwise using GenCast, GraphCast or any outputs generated. GenCast, GraphCast or any outputs generated (i) are not based on data published by; (ii) have not been produced in collaboration with; and (iii) have not been endorsed by any government meteorological agency or department and in no way replaces official alerts, warnings or notices published by such agencies.

Copyright 2024 DeepMind Technologies Limited.

Citations

If you use this work, consider citing our papers (blog post, Science, arXiv, arxiv GenCast):

@article{lam2023learning,
  title={Learning skillful medium-range global weather forecasting},
  author={Lam, Remi and Sanchez-Gonzalez, Alvaro and Willson, Matthew and Wirnsberger, Peter and Fortunato, Meire and Alet, Ferran and Ravuri, Suman and Ewalds, Timo and Eaton-Rosen, Zach and Hu, Weihua and others},
  journal={Science},
  volume={382},
  number={6677},
  pages={1416--1421},
  year={2023},
  publisher={American Association for the Advancement of Science}
}

@article{price2023gencast,
  title={GenCast: Diffusion-based ensemble forecasting for medium-range weather},
  author={Price, Ilan and Sanchez-Gonzalez, Alvaro and Alet, Ferran and Andersson, Tom R and El-Kadi, Andrew and Masters, Dominic and Ewalds, Timo and Stott, Jacklynn and Mohamed, Shakir and Battaglia, Peter and Lam, Remi and Willson, Matthew},
  journal={arXiv preprint arXiv:2312.15796},
  year={2023}
}

Acknowledgements

The (i) GenCast and GraphCast communicate with and/or reference with the following separate libraries and packages and the colab notebooks include a few examples of ECMWF’s ERA5 and HRES data that can be used as input to the models. Data and products of the European Centre for Medium-range Weather Forecasts (ECMWF), as modified by Google. Modified Copernicus Climate Change Service information 2023. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains. ECMWF HRES datasets Copyright statement: Copyright "© 2023 European Centre for Medium-Range Weather Forecasts (ECMWF)". Source: www.ecmwf.int License Statement: ECMWF open data is published under a Creative Commons Attribution 4.0 International (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/ Disclaimer: ECMWF does not accept any liability whatsoever for any error or omission in the data, their availability, or for any loss or damage arising from their use.

Use of the third-party materials referred to above may be governed by separate terms and conditions or license provisions. Your use of the third-party materials is subject to any such terms and you should check that you can comply with any applicable restrictions or terms and conditions before use.

Contact

For feedback and questions, contact us at gencast@google.com. Any information collected via email will be used in accordance with Google's privacy policy.