FuXi
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Related Articles from SNS
Machine Learning (ML)-Physics Fusion Model Outperforms Both Physics-Only and ML-Only Models in Typhoon Predictions
Announce Type: replace Abstract: Data-driven machine learning (ML) models, such as FuXi, exhibit notable limitations in forecasting typhoon intensity and structure. This study presents a comprehensive evaluation of FuXi-SHTM, a hybrid ML-physics model, using all 2024 western North Pacific typhoon cases. The FuXi-SHTM hybrid demonstrates clear improvements in both track and intensity forecasts compared to the standalone SHTM, FuXi, and ECMWF HRES models.
ML-Physical Fusion Models Are Accelerating the Paradigm Shift in Operational Typhoon Forecasting
arXiv:2503.00424v2 Announce Type: replace Abstract: 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) into a dual physics-data-driven framework. By employing spectral nudging, the hybrid model named FuXi-SHTM leverages FuXi's robust large-scale forecasting capabilities alongside SHTM's mesoscale strengths, significantly enhancing track, intensity, and precipitation...