GeoDES (Geospatial Diffusion-Based Evolution Synthesis)

Generating high-fidelity, physically consistent synthetic weather events for research.

GeoDES is a diffusion model for synoptic storm synthesis, based on the Denoising Diffusion Probabilistic Model (DDPM).

Installation

conda create --name geodes python==3.11.11

pip install numpy torch==2.6.0 torchvision torchaudio xarray diffusers==0.32.2 tqdm transformers==4.50.0 pandas matplotlib notebook accelerate==1.5.2 opencv-python==4.11.0.86 einops==0.8.1 wandb scipy scikit-learn

Training code

Spatial pretraining phase:

python train_2d.py --train --epochs 1 --lr 1e-9 --dataset <dataset> --name debug2d

Spatiotemporal training phase:

python train_3d.py --train --epochs 1 --lr 1e-9 --dataset <dataset> --img_model debug2d

Attributions

• SVD code is from https://github.com/wangqiang9/SVD_Xtend/

Contact

Please reach out to Sonia Cromp (cromp@wisc.edu, socromp.github.io) with any questions or comments (or postdoc opportunities :))!