Open source models

WeatherNext models are available open source on GitHub, including model code, pretrained weights, and interactive demo notebooks.

Available models

The repository contains the following models:

WeatherNext 2 is recommended for research and self-hosted inference. WeatherNext Graph and Gen remain available for benchmarking against the original published papers.

Getting started

The easiest way to get started with WeatherNext 2 is by running the interactive Colab Notebook.

Pre-trained weights and sample data are available on the Google Cloud Bucket.

For installation instructions, model details, and training data, see the WeatherNext 2 README on GitHub.

License

The Colab notebooks and the associated code are licensed under the Apache License, Version 2.0 (Apache 2.0); you may not use these materials except in compliance with the Apache 2.0 license. You may obtain a copy of the License at: https://www.apache.org/licenses/LICENSE-2.0.

All other materials are licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0). You may obtain a copy of the License at: https://creativecommons.org/licenses/by/4.0/.

Unless required by applicable law or agreed to in writing, all software and materials distributed here under the Apache 2.0 or CC-BY 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.

Citation

If you use WeatherNext 2 or WeatherNext Cyclones in your work, cite the following publications:

General Weather Forecasting (WeatherNext 2 / FGN):

@article{alet2025skillful,
  title={Skillful joint probabilistic weather forecasting from marginals},
  author={Alet, Ferran and Price, Ilan and El-Kadi, Andrew and Masters, Dominic and Markou, Stratis and Andersson, Tom R and Stott, Jacklynn and Lam, Remi and Willson, Matthew and Sanchez-Gonzalez, Alvaro and Battaglia, Peter},
  journal={arXiv preprint arXiv:2506.10772},
  year={2025}
}

Tropical Cyclones (WeatherNext Cyclones):

@article{Alet2026,
  title={Operational Tropical Cyclone Forecasting with AI},
  author={Alet, Ferran and Andersson, Tom R. and Price, Ilan and Markou, Stratis and El-Kadi, Andrew and Masters, Dominic and Li, Amy and Merchant, Samier and Williams, Natalie and Thornton, Gregory and MacKay, Ken and Graham, Olivia and Uddin, Akib and Gaiarin, Ben and Shah, Devaja and Kruse, Elinor and Hogsett, Wallace and Zelinsky, David and Cangialosi, John and Martinez, Jonathan and Franklin, James and DeMaria, Mark and Musgrave, Kate and Bain, Caroline L. and Titley, Helen and Stott, Jacklynn and Lam, Remi and Bell, Aaron and Komarek, Paul and Willson, Matthew and Sanchez-Gonzalez, Alvaro and Battaglia, Peter},
  journal={Nature},
  year={2026},
  issn={1476-4687},
  doi={10.1038/s41586-026-10953-2},
  url={https://doi.org/10.1038/s41586-026-10953-2}
}

Contact

For questions about the codebase or models, contact weathernext@google.com.