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precipitation-nowcasting-sevir
huilinsigehigh/precipitation-nowcasting-sevir
precipitation-nowcasting-sevir is a machine learning model from huilinsigehigh. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
A collection of deep learning models for radar precipitation nowcasting evaluated on the SEVIR VIL dataset.
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Updated Apr 26, 2026
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At a glance
- License
- mit
- Access
- Public
- Created
- Apr 22, 2026
- Updated
- Apr 26, 2026
- SHA
- 1834ecd8
Datasets
Model card
From the Hugging Face model README
Precipitation Nowcasting — SEVIR Benchmark Collection
A collection of deep learning models for radar precipitation nowcasting evaluated on the SEVIR VIL dataset.
🗂️ Models
| Model | Venue | Type | Input → Output | Resolution | Weights |
|---|---|---|---|---|---|
| DiffCast | CVPR 2024 | Residual Diffusion + PhyDNet | 5 → 20 frames | 128×128 | Official |
| PreDiff | NeurIPS 2023 | VAE + CuboidTransformer DDPM | 7 → 6 frames | 128×128 | Official |
| FlowCast | ICLR 2026 | Conditional Flow Matching | 13 → 12 frames | 384×384 | Official |
| NowcastNet-12in12out | Fine-tuned | GAN + optical flow | 12 → 12 frames | 384×384 | Self-trained |
| NowcastNet-13in36out | Fine-tuned | GAN + optical flow | 13 → 36 frames | 384×384 | Self-trained |
📁 Directory Structure
├── diffcast/
│ ├── weights/diffcast_phydnet_sevir128.pt # 754 MB
│ ├── run.py
│ └── diffcast.py
├── prediff/
│ ├── weights/
│ │ ├── vae/pretrained_sevirlr_vae_8x8x64_v1.pt # 322 MB
│ │ ├── earthformerunet/pretrained_sevirlr_earthformerunet_v1.pt # 522 MB
│ │ └── alignment/pretrained_sevirlr_alignment_avg_x_cuboid_v1.pt # 34 MB
│ └── test_prediff_sevir.py
├── flowcast/
│ ├── weights/
│ │ ├── autoencoder/early_stopping_model.pt # 979 MB
│ │ └── flowcast/early_stopping_model.pt # 880 MB
│ └── test_flowcast_sevir.py
└── nowcastnet/
├── weights/
│ ├── nowcastnet_12in12out_sevir_best_mse0.00653.ckpt # 231 MB
│ └── nowcastnet_13in36out_sevir_best_mse0.02209.ckpt # 232 MB
├── nowcastnet_model.py
└── train_nowcastnet_sevir.py
📊 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 | — | — | — | — | — | — |
NowcastNet and FlowCast CSI results to be added.
🚀 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
📖 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.
- License
- mit
- Languages
- en
- Created
- Apr 22, 2026
- Updated
- Apr 26, 2026