5 papers · 1 filter
Phys-Diff: A Physics-Inspired Latent Diffusion Model for Tropical Cyclone Forecasting
Lei Liu, Xiaoning Yu, Kang Chen +4
Tropical cyclone (TC) forecasting is critical for disaster warning and emergency response. Deep learning methods address computational challenges but often neglect physical relatio…
FengWu-W2S: A deep learning model for seamless weather-to-subseasonal forecast of global atmosphere
Fenghua Ling, Kang Chen, Jiye Wu +4
Seamless forecasting that produces warning information at continuum timescales based on only one system is a long-standing pursuit for weather-climate service. While the rapid adva…
ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast
Wanghan Xu, Kang Chen, Tao Han +3
Data-driven weather forecast based on machine learning (ML) has experienced rapid development and demonstrated superior performance in the global medium-range forecast compared to…
FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation
Kun Chen, Tao Chen, Peng Ye +5
Data assimilation is a vital component in modern global medium-range weather forecasting systems to obtain the best estimation of the atmospheric state by combining the short-term…
FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting
Tao Han, Song Guo, Fenghua Ling +7
Kilometer-scale modeling of global atmosphere dynamics enables fine-grained weather forecasting and decreases the risk of disastrous weather and climate activity. Therefore, buildi…