26 citations · 84 across the 28 of their papers we have counts for
11 papers · 1 filter
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…
Revealing the Potential of Learnable Perturbation Ensemble Forecast Model for Tropical Cyclone Prediction
Jun Liu, Tao Zhou, Jiarui Li +5
Tropical cyclones (TCs) are highly destructive and inherently uncertain weather systems. Ensemble forecasting helps quantify these uncertainties, yet traditional systems are constr…
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,…
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…
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…
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…
FuXi-Ocean: A Global Ocean Forecasting System with Sub-Daily Resolution
Qiusheng Huang, Yuan Niu, Xiaohui Zhong +5
Accurate, high-resolution ocean forecasting is crucial for maritime operations and environmental monitoring. While traditional numerical models are capable of producing sub-daily,…
Terrain-aware Deep Learning for Wind Energy Applications: From Kilometer-scale Forecasts to Fine Wind Fields
Chensen Lin, Ruian Tie, Shihong Yi +2
High-resolution wind information is essential for wind energy planning and power forecasting, particularly in regions with complex terrain. However, most AI-based weather forecasti…
A machine learning model for skillful climate system prediction
Chenguang Zhou, Lei Chen, Xiaohui Zhong +8
Climate system models (CSMs), through integrating cross-sphere interactions among the atmosphere, ocean, land, and cryosphere, have emerged as pivotal tools for deciphering climate…
FuXi-RTM: A Physics-Guided Prediction Framework with Radiative Transfer Modeling
Qiusheng Huang, Xiaohui Zhong, Xu Fan +2
Similar to conventional video generation, current deep learning-based weather prediction frameworks often lack explicit physical constraints, leading to unphysical outputs that lim…
Skillful Nowcasting of Convective Clouds With a Cascade Diffusion Model
Haoming Chen, Xiaohui Zhong, Qiang Zhai +6
Accurate nowcasting of convective clouds from satellite imagery is essential for mitigating the impacts of meteorological disasters, especially in developing countries and remote r…