8 papers
Global kilometre-scale tropical cyclone inner-core vector winds from sparse scalar CYGNSS observations
Xinhai Han, Xiaohui Li, Jingsong Yang +11
Tropical cyclone (TC) inner-core surface wind vectors underpin intensity forecasting and storm-surge prediction, yet direct observations remain scarce: routine aircraft reconnaissa…
A Data-Driven Regional Model for Skillful Medium-Range Typhoon Prediction
Zeyi Niu, Wei Huang, Sirong Huang +7
Accurate prediction of tropical cyclones remains a major challenge for both numerical weather prediction and emerging artificial intelligence weather prediction systems. While rece…
StormDiT: A generative AI model bridges the 2-6 hour 'gray zone' in precipitation nowcasting
Haofei Sun, Yunfan Yang, Wei Han +6
Accurate short-term warnings for extreme precipitation are critical for global disaster mitigation but are hindered by a persistent predictability barrier at the 2-6 hour horizon -…
Data-driven solar forecasting enables near-optimal economic decisions
Zhixiang Dai, Minghao Yin, Xuanhong Chen +27
Solar energy adoption is critical to achieving net-zero emissions. However, it remains difficult for many industrial and commercial actors to decide on whether they should adopt di…
Intelligent Shanghai Typhoon Model (ISTM): A generative probabilistic emulator for typhoon hybrid modeling
Zeyi Niu, Wei Huang, Sirong Huang +5
To address the systematic underestimation of typhoon intensity in artificial intelligence weather prediction (AIWP) models, we propose the Intelligent Shanghai Typhoon Model (ISTM)…
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…
Machine Learning (ML)-Physics Fusion Model Outperforms Both Physics-Only and ML-Only Models in Typhoon Predictions
Zeyi Niu, Wei Huang, Hao Li +4
Data-driven machine learning (ML) models, such as FuXi, exhibit notable limitations in forecasting typhoon intensity and structure. This study presents a comprehensive evaluation o…
ML-Physical Fusion Models Are Accelerating the Paradigm Shift in Operational Typhoon Forecasting
Zeyi Niu
In this study, we develop a hybrid operational typhoon forecasting model that integrates the FuXi machine-learning (ML) model with the physics-based Shanghai Typhoon Model (SHTM) i…