Precipitation Nowcasting β€” SEVIR Benchmark Collection

A collection of deep learning models for radar precipitation nowcasting evaluated on the SEVIR VIL dataset.

πŸ—‚οΈ Models

Model Venue Type Input β†’ Output Resolution Weights
DiffCast CVPR 2024 Residual Diffusion + PhyDNet 5 β†’ 20 frames 128Γ—128 Official
PreDiff NeurIPS 2023 VAE + CuboidTransformer DDPM 7 β†’ 6 frames 128Γ—128 Official
FlowCast ICLR 2026 Conditional Flow Matching 13 β†’ 12 frames 384Γ—384 Official
NowcastNet-12in12out Fine-tuned GAN + optical flow 12 β†’ 12 frames 384Γ—384 Self-trained
NowcastNet-13in36out Fine-tuned GAN + optical flow 13 β†’ 36 frames 384Γ—384 Self-trained

πŸ“ Directory Structure

β”œβ”€β”€ diffcast/
β”‚   β”œβ”€β”€ weights/diffcast_phydnet_sevir128.pt   # 754 MB
β”‚   β”œβ”€β”€ run.py
β”‚   └── diffcast.py
β”œβ”€β”€ prediff/
β”‚   β”œβ”€β”€ weights/
β”‚   β”‚   β”œβ”€β”€ vae/pretrained_sevirlr_vae_8x8x64_v1.pt          # 322 MB
β”‚   β”‚   β”œβ”€β”€ earthformerunet/pretrained_sevirlr_earthformerunet_v1.pt  # 522 MB
β”‚   β”‚   └── alignment/pretrained_sevirlr_alignment_avg_x_cuboid_v1.pt # 34 MB
β”‚   └── test_prediff_sevir.py
β”œβ”€β”€ flowcast/
β”‚   β”œβ”€β”€ weights/
β”‚   β”‚   β”œβ”€β”€ autoencoder/early_stopping_model.pt   # 979 MB
β”‚   β”‚   └── flowcast/early_stopping_model.pt      # 880 MB
β”‚   └── test_flowcast_sevir.py
└── nowcastnet/
    β”œβ”€β”€ weights/
    β”‚   β”œβ”€β”€ nowcastnet_12in12out_sevir_best_mse0.00653.ckpt   # 231 MB
    β”‚   └── nowcastnet_13in36out_sevir_best_mse0.02209.ckpt   # 232 MB
    β”œβ”€β”€ nowcastnet_model.py
    └── train_nowcastnet_sevir.py

πŸ“Š Results on SEVIR VIL Test Set

Model Avg CSI↑ CSI@16 CSI@74 CSI@133 CSI@160 CSI@181 CSI@219
DiffCast 0.1657 0.3506 0.2694 0.1550 0.1158 0.0825 0.0209
PreDiff (Unaligned) 0.3655 0.7193 0.6118 0.3244 0.2474 0.2018 0.0884
PreDiff (Aligned) 0.3050 β€” β€” β€” β€” β€” β€”

NowcastNet and FlowCast CSI results to be added.

πŸš€ Quick Start

DiffCast

cd diffcast
pip install -r requirements.txt  # see DiffCast repo
python run.py --backbone phydnet --use_diff --eval \
  --ckpt_milestone weights/diffcast_phydnet_sevir128.pt

PreDiff

cd prediff
python test_prediff_sevir.py
# Requires: SEVIR dataset at C:/Users/.../datasets/sevir

FlowCast

cd flowcast
python test_flowcast_sevir.py
# Requires: preprocessed SEVIR H5 (see preprocess_sevir_test.py)

NowcastNet

cd nowcastnet
python train_nowcastnet_sevir.py --eval \
  --ckpt weights/nowcastnet_12in12out_sevir_best_mse0.00653.ckpt

πŸ“– References

  • DiffCast: Yu et al., "DiffCast: A Unified Framework via Residual Diffusion for Precipitation Nowcasting", CVPR 2024
  • PreDiff: Gao et al., "PreDiff: Precipitation Nowcasting with Latent Diffusion Models", NeurIPS 2023
  • FlowCast: Bhattacharya et al., "FlowCast: Scaling Precipitation Nowcasting with Conditional Flow Matching", ICLR 2026
  • NowcastNet: Zhang et al., "Skilful nowcasting of extreme precipitation with NowcastNet", Nature 2023

License

Model weights follow their original licenses. Code in this repository is MIT licensed.

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