arXiv Machine Learning

MAGPIE-Net: Predicting short-duration heavy-rainfall events in station neighborhoods from multitemporal FY-4A AGRI observations

arXiv:2608. 17753v1 Announce Type: new Abstract: Short-duration heavy-rainfall warning determines whether 1 h rainfall will exceed a threshold within a target-station neighborhood over the next few hours.

arXiv Machine Learning

Jul 7

Enhancing the Forecasting Capability of Multi-Model Blending Algorithms for Extreme Precipitation via Joint Use of Station and Gridded Observations

arXiv:2607. 04862v1 Announce Type: new Abstract: Accurate extreme precipitation forecasting is critical for disaster mitigation but remains challenging for numerical weather prediction (NWP) models due to systemic intensity underestimation and spatial displacement.

By Yu Wang, Yong Cao, Kan Dai, Yue Shen, Xiaoqing Zeng, Ruixia Zhao

safety

arXiv Machine Learning

Jun 26

CSU-PCAST: A Dual-Branch Transformer Framework for medium-range ensemble Precipitation Forecasting

arXiv:2510. 20769v2 Announce Type: replace-cross Abstract: Accurate medium-range precipitation forecasting is essential for hydrometeorological risk management but remains challenging for both numerical weather prediction (NWP) systems and data-driven models.

By Tianyi Xiong, Haonan Chen, Kelly Mahoney, Jingyin Tang, Tim Smith, Janice Bytheway

llms rag safety

arXiv Machine Learning

Jul 20

Physics-Based Deep Spatiotemporal Hyperlocal Radar Nowcasting with a Multi-Variable U-Net for High-Resolution Precipitation Forecasting

arXiv:2607. 16080v1 Announce Type: new Abstract: Precipitation nowcasting over the immediate 10-90 min period is important for flood management and real-time decision-making in urban regions.

By Akshay Sunil, Muhammed Rashid, Raja Sekhar Sivaraju, Sushma Nair, Subimal Ghosh

arXiv AI

Jul 15

OmniPMNet: Bridging discrete and gridded PM10 forecasts via omni-query neural processes

arXiv:2607. 11896v1 Announce Type: cross Abstract: Forecasting particulate matter (PM10) requires both station-scale accuracy and continuous spatial fields, especially during severe dust storms.

By Shuangshuang He, Shuo Wang

arXiv Machine Learning

Jun 18

Pointwise is Pointless? A Multimodal Ablation Study for Precipitation Nowcasting with Graph Neural Networks

arXiv:2606. 18436v1 Announce Type: cross Abstract: Sparse point observations are increasingly available for precipitation nowcasting, but it is unclear how much they improve dense radar-field forecasts.

By Oph\'elia Miralles, M\'at\'e Mile, Christoffer Artturi, Thomas Nipen, Ivar Seierstad

multimodal benchmarks

arXiv Machine Learning

6d ago

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling

arXiv:2608. 12271v1 Announce Type: new Abstract: Global weather reanalyses and forecasts resolve the evolving atmospheric state on coarse grids, but site-specific applications require predictions at arbitrary locations where near-surface conditions also depend on unresolved terrain and land-surface properties.

By Pedro Sousa (Department of Computer Science, University of Cambridge), Will Tebbutt (Department of Engineering, University of Cambridge), Sadiq Jaffer (Department of Computer Science, University of Cambridge), Robin Young (Department of Computer Science, University of Cambridge), Anil Madhavapeddy (Department of Computer Science, University of Cambridge), Richard E. Turner (Department of Engineering, University of Cambridge)

rag

arXiv Machine Learning

Jul 8

Integrating GNSS-Derived Zenith Wet Delay into a Weather Foundation Model Improves Precipitation Forecasting

arXiv:2607. 05658v1 Announce Type: cross Abstract: Global Navigation Satellite Systems (GNSS), best known for positioning, also serve weather science, as atmospheric water vapour delays their signals.

By Leonardo Trentini, Fanny Lehmann, Laura Crocetti, Benedikt Soja

fine-tuning benchmarks

arXiv Machine Learning

Jun 9

SwAIther-Precip: Lead-Time-Aware Bias Correction Enables Kilometer-Scale Downscaling of Global AI Precipitation Forecasts over Switzerland

arXiv:2605. 16163v2 Announce Type: replace-cross Abstract: Skillful medium-range precipitation forecasting at kilometer scale remains challenging over complex terrain because precipitation arises from multiscale nonlinear processes that global models cannot explicitly resolve at affordable cost.

By Dan Assouline, Erwan Koch, Federico Amato, Filippo Quarenghi, Daniele Nerini, Thibaut Loiseau, Kyle van de Langemheen, Tom Beucler

diffusion safety

arXiv Machine Learning

Jun 18

Spatiotemporal downscaling and nowcasting of urban land surface temperatures with deep neural networks

arXiv:2605. 13566v2 Announce Type: replace Abstract: Land Surface Temperature (LST) is a key variable for various applications, such as urban climate and ecology studies.

By Solomiia Kurchaba, Angela Meyer

benchmarks safety

arXiv Machine Learning

Jun 5

Performance Evaluation of GraphCast for Medium-Range Weather Forecasting over Brazil

arXiv:2606. 06348v1 Announce Type: new Abstract: The paradigm of global weather forecasting is rapidly shifting with the emergence of Machine Learning Weather Prediction models (MLWP).

By Wolfgang R. Rowell Jr., Lucas S. Kupssinsk\"u

benchmarks

arXiv Machine Learning

Jul 7

GlacierCastAI: Predicting Glacier Retreat from Multi-Modal Satellite Imagery and Climate Signals

arXiv:2607. 04117v1 Announce Type: new Abstract: ERA5 seasonal climate variables contain predictive information about future glacier retreat beyond what satellite imagery alone provides, yet existing deep learning methods focus on mapping current boundaries rather than forecasting future ones.

By Arunkumar Ramachandran

multimodal benchmarks

arXiv Machine Learning

Aug 4

Breaking the Statistical Similarity Trap in Extreme Convection Detection

arXiv:2509. 09195v2 Announce Type: replace Abstract: Current evaluation metrics for deep learning weather models create a "Statistical Similarity Trap", rewarding blurry predictions while missing rare, high-impact events.

By Md Tanveer Hossain Munim

computer-vision benchmarks safety

Related stories