activity
20232026
most citedFuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model

10 citations · 23 across the 24 of their papers we have counts for

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Showing physics.ao-phShow all

13 papers · 1 filter

physics.ao-ph2026

Composable multi-satellite precipitation estimation for evolving observing systems

Yunfan Yang, Haofei Sun, Xiuyu Sun +7

Rapid and spatially continuous precipitation monitoring is critical for flood, landslide, and other hydrometeorological hazard warnings, particularly in regions where rain-gauge an…

physics.ao-ph2026

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…

physics.ao-ph2026

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…

physics.ao-ph20251 cited

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…

physics.ao-ph2025

A data-driven global ocean forecasting model with sub-daily and eddy-resolving resolution

Yuan Niu, Qiusheng Huang, Xiaohui Zhong +7

High-fidelity ocean forecasting at high spatial and temporal resolution is essential for capturing fine-scale dynamical features, with profound implications for hazard prediction,…

physics.ao-ph2025

Enhanced predictions of the Madden-Julian oscillation using the FuXi-S2S machine learning model: Insights into physical mechanisms

Can Cao, Xiaohui Zhong, Lei Chen +2

The Madden-Julian Oscillation (MJO) is the dominant mode of tropical atmospheric variability on intraseasonal timescales, and reliable MJO predictions are essential for protecting…