Precipitation Nowcasting

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5 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Jul 13Week of Sep 28

Latest papers 27

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PrecipJEPA: JEPA-Regularized Future-State Prediction with Motion-Source Rendering for Precipitation Nowcasting
Sep 30, 2026Yufeng Zhu, Dan Niu, Qiliang Wu +4Precipitation Forecasting Joint-Embedding Predictive Architecture
Department of Automation, Southeast University, Nanjing 210096, China
NowcastDiT: Diffusion Transformers are Effective Precipitation Nowcasters
Sep 29, 2026Haoran Xu, Xingzhuo Guo, Yuchen Zhang +3Precipitation Forecasting Diffusion Transformer
School of Software, BNRist, Tsinghua University, China
MW-Nowcast: Six-hour ensemble nowcasting of extreme precipitation
Sep 28, 2026Ning Wang, Zuliang Fang, Weixin Jin +19Precipitation Forecasting Probabilistic Forecasting
Microsoft Corporation. · City University of Hong Kong. · University of Cambridge.
WeatherDiagFlow: Evidence-Grounded Radar Nowcasting with Diagnostic Flow Refinement
Sep 24, 2026Chunlei Shi, Yufeng Zhu, Yixiao Liang +4Precipitation Nowcasting Weather Forecasting
Department of Automation, Southeast University, Nanjing, China · Beijing Fengyun Meteorological Science and Technology Development Co., Ltd., Beijing, China · State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China +1
IRENE: A Convolutional GRU Ensemble Model for Radar Precipitation Nowcasting over Italy
Sep 15, 2026Alessandro Camilletti, Gabriele Franch, Elena Tomasi +1Convolutional RNNs Precipitation Forecasting
Fondazione Bruno Kessler
GenONet: A Generative operator Network for High-Resolution Precipitation Nowcasting
Sep 1, 2026Mohammad Kian Golkar, Luciano Alves de Oliveira, Mohammad KhanjaniPrecipitation Forecasting Spatiotemporal Forecasting
University of Illinois Urbana-Champaign · Sharif University of Technology
Diffusion-Based Refinement for Kilometer-Scale Probabilistic Precipitation Nowcasting
Aug 31, 2026Dohyun Park, Changhoon Song, Tengyuan Chang +2Precipitation Forecasting Probabilistic Forecasting
Department of Mathematical Sciences, Seoul National University, Seoul, Republic of Korea. · Research Institute of Mathematics, Seoul National University, Seoul,2026 Republic of Korea. · Department of Environmental Management, Seoul National University, Seoul, Republic of Korea.
FreCast: Refining Radar Echo Intensity via Phase-Preserving Amplitude Residual Diffusion for Precipitation Nowcasting
Aug 9, 2026Heping Fang, Zihuai Yin, Kaicheng Mao +2Precipitation Forecasting Spatiotemporal Forecasting
Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen 518055, China · Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China · Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering and the Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen 518055, China
Dense-Cast: A lightweight ensemble of deep learning architectures for precipitation nowcasting
Aug 6, 2026Gourav Jyoti Kalita, Hidam Kumarjit SinghPrecipitation Forecasting Deep Ensembles
Department of Electronics and Communication Technology, Gauhati University, Guwahati-781014, Assam, India
QWRF-Net: A Quantum-Wavelet Framework with Rectified Flow for Short-Term Precipitation Nowcasting
Aug 3, 2026Zhuo Wang, Chaorong Li, Wenjie Luo +1Precipitation Forecasting Spatiotemporal Forecasting
School of Computer Science and Technology (School of Artificial Intelligence), Yibin University, Yibin, 644000, Sichuan, China · College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, 400054, China
Physics-Based Deep Spatiotemporal Hyperlocal Radar Nowcasting with a Multi-Variable U-Net for High-Resolution Precipitation Forecasting
Jul 17, 2026Akshay Sunil, Muhammed Rashid, Raja Sekhar Sivaraju +2Precipitation Forecasting U-Net
Centre for Climate Studies, Indian Institute of Technology Bombay, Mumbai, India · Regional Meteorological Centre (RMC) in Colaba, Mumbai, India
RainODE: Continuous-Time Precipitation Forecasting with Latent Neural ODEs
Jun 29, 2026Yeeun Seong, Doyi Kim, Minseok Seo +1Precipitation Forecasting Time Series Forecasting
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
Pointwise is Pointless? A Multimodal Ablation Study for Precipitation Nowcasting with Graph Neural Networks
Jun 16, 2026Ophélia Miralles, Máté Mile, Christoffer Artturi +2Precipitation Forecasting Probabilistic Forecasting
Norwegian Meteorological Institute, Oslo, Norway
When the Past Matters: FlashBack Memory for Precipitation Nowcasting
Jun 15, 2026Yuhao Du, Boxiao Huang, Chengrong Wu +1Memory-Augmented Neural Networks Precipitation Forecasting
College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China · Fuqua School of Business, Duke University, North Carolina 27705, USA · Department of Computer Science, University of Manchester, Manchester M139PL, UK
Temporal Context Conditioning for Seasonality-Aware Precipitation Nowcasting of High-Intensity Rainfall
Jun 8, 2026Gijs van Nieuwkoop, Siamak MehrkanoonPrecipitation Forecasting U-Net
Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands
Learning to Refine: Spectral-Decoupled Iterative Refinement Framework for Precipitation Nowcasting
Jun 1, 2026Yunlong Zhou, Chen Zhao, Danyang Peng +2Precipitation Forecasting Spatiotemporal Forecasting
School of Intelligence Science and Technology, Nanjing University, Suzhou, 215163, China. · State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210023, China.
Probabilistic Precipitation Nowcasting with Rectified Flow Transformers
May 29, 2026Johannes Schusterbauer, Jannik Wiese, Nick Stracke +2Precipitation Forecasting Rectified Flow
Beyond MSE: Improving Precipitation Nowcasting with Multi-Quantile Regression
May 28, 2026Gijs van Nieuwkoop, Siamak MehrkanoonPrecipitation Forecasting Quantile Regression
Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands
Seeing Inside the Storm: Improving Nowcasting by Integrating Meteorological Drivers
May 22, 2026Minghui Qiu, Jun Chen, Lin Chen +5Precipitation Forecasting Remote Sensing
HKUST(GZ) · Guangzhou Meteorological Observatory
MambaRain: Multi-Scale Mamba-Attention Framework for 0-3 Hour Precipitation Nowcasting
May 14, 2026Chunlei Shi, Cui Wu, Xiang Xu +10Mamba Precipitation Forecasting
School of Automation, Southeast University · Nanjing XinDa Institute of Meteorological Science and Technology · Beijing Leninainfo Technology Co., Ltd. +5
VMU-Diff: A Coarse-to-fine Multi-source Data Fusion Framework for Precipitation Nowcasting
May 14, 2026Chunlei Shi, Hao Li, Yufeng Zhu +6Precipitation Forecasting Probabilistic Forecasting
Department of Automation, Southeast University, Nanjing 210096, China
McCast: Memory-Guided Latent Drift Correction for Long-Horizon Precipitation Nowcasting
May 13, 2026Penghui Wen, Yu Luo, Lintao Wang +4Memory-Augmented Neural Networks Precipitation Forecasting
School of Computer Science, The University of Sydney, Australia · School of Life and Environmental Science, The University of Sydney, Australia
Stable Attention Response for Reliable Precipitation Nowcasting
May 13, 2026Penghui Wen, Zexin Hu, Sen Zhang +6Precipitation Forecasting Attention Head Analysis
School of Computer Science, The University of Sydney Australia · Independent Researcher Australia · School of Life and Environmental Science, The University of Sydney Australia +3
PixelFlowCast: Latent-Free Precipitation Nowcasting via Pixel Mean Flows
May 11, 2026Yufeng Zhu, Chunlei Shi, Yongchao Feng +1Precipitation Forecasting Efficient Inference
IMPA-Net: Meteorology-Aware Multi-Scale Attention and Dynamic Loss for Extreme Convective Radar Nowcasting
Apr 27, 2026Haofei Cui, Guangxin He, Juanzhen Sun +5Precipitation Forecasting Multi-Scale Feature Fusion
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME) / International Joint Research Laboratory on Climate and Environment Change (ILCEC) / Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China. · Nanchang Meteorological Bureau, Nanchang 330000, China. · National Center for Atmospheric Research, Boulder, CO 80301, USA. +3
A Space-Time Transformer for Precipitation Nowcasting
Nov 14, 2025Levi Harris, Tianlong ChenPrecipitation Forecasting Transformer
UNC Chapel Hill
A Storm-Centric 250 m NEXRAD Level-II Dataset for High-Resolution ML Nowcasting
Oct 15, 2025Andy ShiPrecipitation Forecasting Precipitation Nowcasting

Sep 30, 2026, cs.MMJ/K move · Enter open · S save

PrecipJEPA: JEPA-Regularized Future-State Prediction with Motion-Source Rendering for Precipitation Nowcasting

Yufeng Zhu, Dan Niu, Qiliang Wu, Weiwei Huang+3

Department of Automation, Southeast University, Nanjing 210096, China

Precipitation Forecasting Joint-Embedding Predictive Architecture Predictive Representation Learning Spatiotemporal Forecasting Precipitation Nowcasting

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Long-term precipitation nowcasting requires modeling radar-echo evolution while preserving localized high-intensity structures. Recent radar-specific studies motivate location-aware prediction and separating echo displacement from intensity change. However existing encoders learn historical representations mainly from final forecast errors. We propose PrecipJEPA, which couples a structured forecasting path with an auxiliary path that enriches its encoder from observed radar history. In the forecasting path, an online encoder first converts the observations into spatiotemporal tokens. The Task-Driven Future-State Predictor (TFP) combines these tokens with a recent-dynamics summary and spatiotemporal queries to construct future radar states. The Parallel Motion-Source Renderer (PMSR) decodes these states into motion and source-sink fields that transform the latest observation into future frames. During joint training, the History-Masked JEPA (H-JEPA) operates on the auxiliary path to predict masked historical features from visible context, directly supervising the same online encoder from the observed sequence. Experiments on SEVIR and MeteoNet show that PrecipJEPA improves highest-threshold CSI by 118.6% and 35.1%, respectively, over the strongest baselines, while maintaining the highest mean CSI throughout the 3-hour forecast.

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Latest papers 27