# A Space-Time Transformer for Precipitation Nowcasting

arXiv: https://arxiv.org/abs/2511.11090 · HTML: https://mlsanity.com/paper/2511.11090/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 23 of its 34 references that are in the map.
- First posted on arXiv 14 Nov 2025.

## Builds on (most cited first, 23 of 23)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Layer Normalization](https://mlsanity.com/paper/1607.06450/) (2016)
- [Is Space-Time Attention All You Need for Video Understanding?](https://mlsanity.com/paper/2102.05095/) (2021)
- [ViViT: A Video Vision Transformer](https://mlsanity.com/paper/2103.15691/) (2021)
- [3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation](https://mlsanity.com/paper/1606.06650/) (2016)
- [Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images](https://mlsanity.com/paper/2201.01266/) (2022)
- [FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators](https://mlsanity.com/paper/2202.11214/) (2022)
- [Why do tree-based models still outperform deep learning on tabular data?](https://mlsanity.com/paper/2207.08815/) (2022)
- [Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction](https://mlsanity.com/paper/2003.01460/) (2020)
- [Delving into Deep Imbalanced Regression](https://mlsanity.com/paper/2102.09554/) (2021)
- [Earthformer: Exploring Space-Time Transformers for Earth System Forecasting](https://mlsanity.com/paper/2207.05833/) (2022)
- [Precipitation nowcasting with generative diffusion models](https://mlsanity.com/paper/2308.06733/) (2023)
- [GA-SmaAt-GNet: Generative Adversarial Small Attention GNet for Extreme Precipitation Nowcasting](https://mlsanity.com/paper/2401.09881/) (2024)
- [HRRRCast: a data-driven emulator for regional weather forecasting at convection allowing scales](https://mlsanity.com/paper/2507.05658/) (2025)
- [WeatherFusionNet: Predicting Precipitation from Satellite Data](https://mlsanity.com/paper/2211.16824/) (2022)
- [Super-resolution Probabilistic Rain Prediction from Satellite Data Using 3D U-Nets and EarthFormers](https://mlsanity.com/paper/2212.02998/) (2022)
- [A Variational U-Net for Weather Forecasting](https://mlsanity.com/paper/2111.03476/) (2021)
- [RainUNet for Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts](https://mlsanity.com/paper/2212.04005/) (2022)
- [Precipitation Prediction Using an Ensemble of Lightweight Learners](https://mlsanity.com/paper/2401.09424/) (2023)
- [Solving the Weather4cast Challenge via Visual Transformers for 3D Images](https://mlsanity.com/paper/2212.02456/) (2022)
- [A conditional Generative Adversarial network model for the Weather4Cast 2024 Challenge](https://mlsanity.com/paper/2412.00451/) (2024)
- [Skilful Precipitation Nowcasting Using NowcastNet](https://mlsanity.com/paper/2311.17961/) (2023)
- [Learning Robust Precipitation Forecaster by Temporal Frame Interpolation](https://mlsanity.com/paper/2311.18341/) (2023)

## Abstract (arXiv)

Until recently, numerical weather prediction (NWP) models have stood rivalless in operational forecasting despite a few limitations. Namely, physically-based models are computationally demanding and struggle at short lead times, reducing their utility for nowcasting. Motivated by these shortcomings, recent work proposes AI-weather prediction (AI-WP) alternatives that emulate analysis data with neural networks. While these data-driven approaches have achieved high skill for medium-range forecasting-applications of AI-WP to precipitation and to nowcasting are less explored. To these ends, this paper discusses textitSaTformer: a video transformer adapted for precipitation nowcasting. To ameliorate some problems related to what is essentially a fat-tailed regression task, we find it prudent to formulate nowcasting as a classification problem and employ a frequency-weighted loss. This straightforward approach scored first on the NeurIPS Weather4Cast 2025 ``Cumulative Rainfall'' challenge. Code and model weights are available: texttthrefgithub.com/leharris3/w4c-25github.com/leharris3/satformer.