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: Our latest state-of-the-art ensemble forecasting model based on the Functional Generative Network (FGN) architecture. Includes operational (0.25°) and mini (1°) variants, as well as specialized cyclone models.
• WeatherNext Gen: Probabilistic ensemble forecasting model based on conditional diffusion.
• WeatherNext Graph: Deterministic forecasting model based on Graph Neural Networks.

We recommend starting with WeatherNext 2 for all new projects. WeatherNext Graph and Gen remain available for research and benchmarking against our original published papers.

Getting started with WeatherNext 2

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

Pre-trained weights and sample data are available on our 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 in your work, cite:

@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 [e-mail].