Storm EVent ImagRy
SEVIR is an annotated, curated and spatio-temporally aligned dataset containing over 10,000 weather events that each consist of 384 km x 384 km image sequences spanning 4 hours of time. Images in SEVIR were sampled and aligned across five different data types: three channels (C02, C09, C13) from the GOES-16 advanced baseline imager, NEXRAD vertically integrated liquid mosaics, and GOES-16 Geostationary Lightning Mapper (GLM) flashes. Many events in SEVIR were selected and matched to the NOAA Storm Events database so that additional descriptive information such as storm impacts and storm descriptions can be linked to the rich imagery provided by the sensors.
Source: https://proceedings.neurips.cc//paper/2020/file/fa78a16157fed00d7a80515818432169-Paper.pdf
Variants: SEVIR
This dataset is used in 2 benchmarks:
| Task | Model | Paper | Date |
|---|---|---|---|
| Precipitation Forecasting | PreDiff | PreDiff: Precipitation Nowcasting with Latent … | 2023-07-19 |
| Weather Forecasting | IAM4VP | Implicit Stacked Autoregressive Model for … | 2023-03-14 |
| Weather Forecasting | Earthformer | Earthformer: Exploring Space-Time Transformers for … | 2022-07-12 |
| Weather Forecasting | ConvLSTM | Earthformer: Exploring Space-Time Transformers for … | 2022-07-12 |
| Weather Forecasting | PredRNN | PredRNN: A Recurrent Neural Network … | 2021-03-17 |
| Weather Forecasting | PhyDNet | Disentangling Physical Dynamics from Unknown … | 2020-03-03 |
Recent papers with results on this dataset: