NowcastDiT: Diffusion Transformers are Effective Precipitation Nowcasters

arXiv:2609.37038 · cs.LG, cs.AI, cs.CV · Submitted 2026-09-29 · Read on arXiv

cs.LG, cs.AI, cs.CV

Submitted: 2026-09-29

Updated: 2026-09-29

Comments: 28 pages, 11 figures

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Diffusion Model — 28× in this paper · explained in 8 episodes
• Transformer — 26× in this paper · explained in 2 episodes
• Diffusion Models — 24× in this paper · explained in 6 episodes
• GRPO — 9× in this paper · explained in 6 episodes
• Generative Modeling — 9× in this paper · explained in 3 episodes
• Reinforcement Learning — 8× in this paper · explained in 4 episodes
• Adaptation — 7× in this paper · explained in 1 episode
• Alignment — 7× in this paper · explained in 1 episode
• Ablation — 6× in this paper · explained in 1 episode
• Flow Matching — 5× in this paper · explained in 8 episodes
• Core — 4× in this paper · explained in 2 episodes
• Critical Success Index — 4× in this paper
• Benchmark — 3× in this paper · explained in 2 episodes
• Decode — 3× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Latent Diffusion Model — 3× in this paper · explained in 2 episodes
• Latent Diffusion Models — 3× in this paper · explained in 2 episodes
• alpha — 3× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Heidke Skill Score — 2× in this paper
• Physical Constraints — 2× in this paper · explained in 7 episodes
• Transformer Architecture — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Credit assignment — 1× in this paper · explained in 3 episodes
• Flow Matching Model — 1× in this paper · explained in 2 episodes
• GRPO Objective — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Learned Perceptual Image Patch Similarity — 1× in this paper
• Ornstein–Uhlenbeck Process — 1× in this paper · explained in 3 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Temporal Correlations — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Two-Stage Training Strategy — 1× in this paper · explained in 3 episodes
• Two-stage training — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Verifiable Rewards — 1× in this paper · explained in 2 episodes
• Vertically Integrated Liquid — 1× in this paper
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Wan: Open and Advanced Large-Scale Video Generative Models

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