Metadata-Version: 2.1
Name: diffusion-weather
Version: 0.0.1
Summary: Weather Forecasting with Diffusion
Home-page: https://github.com/openclimatefix/diffusion_weather
Author: Jacob Bieker
Author-email: jacob@openclimatefix.org
License: MIT License
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
License-File: LICENSE

# Diffusion Weather



## Installation

This library can be installed through

```bash
pip install diffusion-weather
```

## Example Usage


## Pretrained Weights
Coming soon! We plan to train a model on GFS 0.25 degree operational forecasts, as well as MetOffice NWP forecasts.
We also plan trying out adaptive meshes, and predicting future satellite imagery as well.

## Training Data
Training data will be available through HuggingFace Datasets for the GFS forecasts. The initial set of data is available for [GFSv16 forecasts, raw observations, and FNL Analysis files from 2016 to 2022](https://huggingface.co/datasets/openclimatefix/gfs-reforecast), and for [ERA5 Reanlaysis](https://huggingface.co/datasets/openclimatefix/era5). MetOffice NWP forecasts we cannot
redistribute, but can be accessed through [CEDA](https://data.ceda.ac.uk/).


