1 citations · 1 across the 12 of their papers we have counts for
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FuXi-Nowcast: Environment-conditioned deep learning for severe convection nowcasting
Lei Chen, Zijian Zhu, Xiaoran Zhuang +4
Severe convection produces localized hazards that often require warnings before radar echoes fully reveal storm development. Convective initiation and the maintenance of intense co…
A plug-and-play generative framework for multi-satellite precipitation estimation
Yunfan Yang, Haofei Sun, Xiuyu Sun +7
Reliable precipitation monitoring is essential for disaster risk reduction, water resources management, and agricultural decision-making. Multi-source satellite observations, parti…
FuXi-TC: A generative framework integrating deep learning and physics-based models for improved tropical cyclone forecasts
Shan Guo, Lei Chen, Yangyang Zhao +6
Tropical cyclones (TCs) are among the most devastating natural hazards, yet their intensity remains notoriously difficult to predict. NWP models are constrained by both computation…
Data-driven ensemble prediction of the global ocean
Qiusheng Huang, Xiaohui Zhong, Anboyu Guo +3
Data-driven models have advanced deterministic ocean forecasting, but extending machine learning to probabilistic global ocean prediction remains an open challenge. Here we introdu…
A Synergistic Approach: Dynamics-AI Ensemble in Tropical Cyclone Forecasting
Yonghui Li, Wansuo Duan, Hao Li +3
This study addresses a critical challenge in AI-based weather forecasting by developing an AI-driven optimized ensemble forecast system using Orthogonal Conditional Nonlinear Optim…
Generative artificial intelligence improves projections of climate extremes
Ruian Tie, Xiaohui Zhong, Zhengyu Shi +4
Climate change is amplifying extreme events, posing escalating risks to biodiversity, human health, and food security. GCMs are essential for projecting future climate, yet their c…