大气科学学报2025，Vol.48Issue(3)：353-365,13.DOI:10.13878/j.cnki.dqkxxb.20250117001
中央气象台人工智能气象应用发展及思考
Advancing AI-based meteorological applications at the National Meteoro-logical Center
摘要
Abstract
Using the operational practices of the National Meteorological Center as a case study,this paper criti-cally examines the technical limitations currently faced in short-term and medium-to long-term weather forecas-ting as efforts progress seamless forecasting capabilities.Key challenges include improving the accuracy of fore-casts for extreme hazardous weather events and transitioning toward intelligent forecasting systems that effectively integrate both subjective and objective methods.Building on the historical trajectory of meteorological forecas-ting-particularly the advancement of numerical weather prediction through the integration of atmospheric,com-putational,and information sciences-this study highlights the growing importance of artificial intelligence(AI)as a critical enabler of forecasting capability.The article provides a comprehensive review of AI applications in meteorology over the past decade,including its use in monitoring and forecasting severe convective weather,ty-phoons,quantitative precipitation,secondary disasters such as mountain floods,intelligent grid-based forecasting of meteorological variables,risk assessments of meteorological disasters,and the automated generation of text and graphic forecast products.Particular attention is given to two AI-based models released in 2024:Fenglei,a nowcasting system for high-impact weather,and Fengqing,a global short-and medium-term forecasting model.The integration of AI with traditional meteorological techniques has significantly improved the accuracy of fore-casts for typhoons,heavy rainfall,and severe convection.The deployment of AI across operational systems at the National Meteorological Center has accelerated the digital and intelligent transformation of weather forecasting.The release and application of the Fenglei and Fengqing models represent a substantial step forward,positioning the center at the forefront of meteorological forecasting innovation.Nonetheless,several urgent issues remain from an operational perspective.There is a crucial need to reduce dependency on high-quality foreign datasets by leveraging the China Meteorological Administration's observational capabilities to build long-term,high-quality meteorological datasets.To address the inherent"black box"nature of AI models,effective statistical tools must be developed for interpreting their predictions.Moreover,integrating forecasters' intuitive knowledge into AI sys-tems may enhance model performance in forecasting rare extreme weather events,for which training samples are limited.Finally,advancing intelligent forecasting operations requires the development of integrated AI systems capable of supporting meteorologists across all phases of forecasting.This includes the construction of digital AI forecasting assistants that combine various algorithms-such as numerical models,intelligent grid forecasts,and large language models-into a unified operational framework.关键词
气象预报/业务/挑战/人工智能/大模型Key words
meteorological forecasting/operations/challenges/artificial intelligence/large model引用本文复制引用
张小玲,金荣花,代刊,于超,杨波,曹勇,赵伟,张小雯..中央气象台人工智能气象应用发展及思考[J].大气科学学报,2025,48(3):353-365,13.基金项目
国家自然科学基金联合基金项目(U2142202) （U2142202）
