mlsanityData to 14 Oct 2026

NowcastDiT: Diffusion Transformers are Effective Precipitation Nowcasters

arXiv 2609.37038 ↗First posted 29 Sep 2026cs.LG cs.AI cs.CVcited by 0

On the map: Diffusion models → Flow matching, time series and science also fits: Diffusion foundations and sampling

Abstract (arXiv)

Precipitation nowcasting demands accurate short-term forecasts under strong spatiotemporal variability. Diffusion models are well suited to modeling complex precipitation distributions, yet existing approaches often introduce increasingly specialized designs, leaving the capability of a standard diffusion architecture underexplored. We show that a standard Diffusion Transformer already provides a simple and scalable foundation for precipitation nowcasting, with domain-specific requirements accommodated naturally within its design space. Based on this principle, we develop NowcastDiT and instantiate this flexibility through two complementary adaptations: a dynamics-aware noise prior for temporally coherent forecasts, and end-to-end reinforcement learning with timestep-aware rewards for meteorological skill. Experiments on SEVIR and MRMS benchmarks show that NowcastDiT achieves state-of-the-art performance in both perceptual quality and meteorological skill. These results suggest that standard DiT can serve as an effective foundation for precipitation nowcasting.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 40 of its 48 references that are in the map. First posted on arXiv 29 Sep 2026.

Builds on

40 of 48 references.

Closest ancestors · 2

Same direction, newest first

  1. 2023PreDiff: Precipitation Nowcasting with Latent Diffusion Models19 Jul
  2. 2022Flow Matching for Generative Modeling6 Oct

Other references · 38

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  4. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
  5. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  6. 2022Scalable Diffusion Models with Transformerscited by 6,054
  7. 2022Classifier-Free Diffusion Guidancecited by 5,847
  8. 2021RoFormer: Enhanced Transformer with Rotary Position Embeddingcited by 4,703
  9. 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesiscited by 4,181
  10. 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,708
  11. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,581
  12. 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,261
26 more
  1. 2023Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Modelscited by 1,476
  2. 2015Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcastingcited by 1,436
  3. 2023Training Diffusion Models with Reinforcement Learningcited by 982
  4. 2024WorldSimBench: Towards Video Generation Models as World Simulatorscited by 881
  5. 2025Flow-GRPO: Training Flow Matching Models via Online RLcited by 661
  6. 2024Latte: Latent Diffusion Transformer for Video Generationcited by 546
  7. 2026World Action Models are Zero-shot Policiescited by 465
  8. 2025DanceGRPO: Unleashing GRPO on Visual Generationcited by 413
  9. 2022MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolationcited by 309
  10. 2023Photorealistic Video Generation with Diffusion Modelscited by 306
  11. 2023Preserve Your Own Correlation: A Noise Prior for Video Diffusion Modelscited by 285
  12. 2020Query-Key Normalization for Transformerscited by 280
  13. 2025DiffusionNFT: Online Diffusion Reinforcement with Forward Processcited by 230
  14. 2025World Simulation with Video Foundation Models for Physical AIcited by 200
  15. 2020Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Predictioncited by 195
  16. 2022SimVP: Simpler yet Better Video Predictioncited by 184
  17. 2025MixGRPO: Unlocking Flow-based GRPO Efficiency with Mixed ODE-SDEcited by 178
  18. 2026Seedance 2.0: Advancing Video Generation for World Complexitycited by 160
  19. 2022Earthformer: Exploring Space-Time Transformers for Earth System Forecastingcited by 152
  20. 2023DiffCast: A Unified Framework via Residual Diffusion for Precipitation Nowcastingcited by 61
  21. 2024CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modellingcited by 56
  22. 2025RLVR-World: Training World Models with Reinforcement Learningcited by 40
  23. 2025How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Modelscited by 32
  24. 2025Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Modelscited by 9
  25. 2025Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Modelcited by 8
  26. 2024DuoCast: Duo-Probabilistic Diffusion for Precipitation Nowcastingcited by 4

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  2. 2026Just Weather Scoring: Efficient End-to-end Nowcasting with Distributional Diffusion
  3. 2025SimCast: Enhancing Precipitation Nowcasting with Short-to-Long Term Knowledge Distillation
  4. 2025Nowcast3D: Reliable precipitation nowcasting via gray-box learning
  5. 2025FlowCast: Advancing Precipitation Nowcasting with Conditional Flow Matching
  6. 2024Precipitation Nowcasting Using Diffusion Transformer with Causal Attention
  7. 2025RainDiff: End-to-end Precipitation Nowcasting Via Token-wise Attention Diffusion
  8. 2025STLDM: Spatio-Temporal Latent Diffusion Model for Precipitation Nowcasting