1 Introduction Tropical cyclone(TC)intensity prediction is crucial for disaster preparedness and mitigation,as it directly affects millions of lives and causes billions in economic losses annually.A particularly chall...1 Introduction Tropical cyclone(TC)intensity prediction is crucial for disaster preparedness and mitigation,as it directly affects millions of lives and causes billions in economic losses annually.A particularly challenging aspect is the prediction of rapid intensification(RI)events,where TC wind speed increases by at least 30 knots within 24 hours.Current dynamical forecasting models struggle with RI prediction,with forecast errors for RI events being 2–3 times larger than non-RI events[1],as demonstrated by recent cases like Hurricane Bebinca in September 2024.展开更多
基金supported by the National Key Research and Development Program of China(No.2020YFA0608000)the Natural Science Foundation of Jiangsu Province(No.BK20240700).
文摘1 Introduction Tropical cyclone(TC)intensity prediction is crucial for disaster preparedness and mitigation,as it directly affects millions of lives and causes billions in economic losses annually.A particularly challenging aspect is the prediction of rapid intensification(RI)events,where TC wind speed increases by at least 30 knots within 24 hours.Current dynamical forecasting models struggle with RI prediction,with forecast errors for RI events being 2–3 times larger than non-RI events[1],as demonstrated by recent cases like Hurricane Bebinca in September 2024.
