ai-models-graphcast-gfs 0.0.4

Run graphcast ai weather models with capabilities for GFS and GDAS initial conditions and NetCDF output

ai-models-graphcast-gfs

ai-models-graphcast-gfs is an extension of the ai-models-graphcast package, which itself is a plugin to run Google Deepmind's GraphCast with ai-models.

GraphCast: Learning skillful medium-range global weather forecasting, arXiv preprint: 2212.12794, 2022. https://arxiv.org/abs/2212.12794

GraphCast was created by Remi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Ferran Alet, Suman Ravuri, Timo Ewalds, Zach Eaton-Rosen, Weihua Hu, Alexander Merose, Stephan Hoyer, George Holland, Oriol Vinyals, Jacklynn Stott, Alexander Pritzel, Shakir Mohamed and Peter Battaglia.

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/.

Installation

To install the package, run:

pip install ai-models-graphcast-gfs

This will install the package and most of its dependencies.

Then to install graphcast dependencies (and Jax on GPU):

Graphcast and Jax

Graphcast depends on Jax, which needs special installation instructions for your specific hardware.

Please see the installation guide to follow the correct instructions.

We have prepared two requirements.txt you can use. A CPU and a GPU version:

For the preferred GPU usage:

pip install -r requirements-gpu.txt -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

For the slower CPU usage:

pip install -r requirements.txt