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Workshop on AI Applications in Tropical Cyclone Analysis and Prediction Held in Shanghai, China




Workshop on AI Applications in Tropical Cyclone Analysis and Prediction Held in Shanghai, China

2026-04-29




From April 21 to 23, 2026, the ESCAP/WMO Typhoon Committee convened the “Workshop on AI Applications in Tropical Cyclone Analysis and Prediction cum Meeting of Expert Team on AI Applications in Tropical Cyclone Analysis and Forecasting” in Lingang, Shanghai, focusing on the application of artificial intelligence in typhoon analysis and forecasting. Hosted by the Asia-Pacific Typhoon Collaborative Research Center (AP-TCRC), the event gathered over 70 participants, including experts from WMO, Cambodia; China; Hong Kong, China; Japan; Lao PDR; Macao, China; Malaysia, Philippines; Republic of Korea; Thailand and Viet Nam, as well as leading AI research teams in the world and top universities in China.

The workshop highlighted the transformative potential of AI in meteorology, showcasing cutting-edge AI weather models such as DeepMind, AIFS, and several prominent Chinese models like Fengwu and Fuxi. Participants emphasized that amid global warming and the increasing frequency of extreme weather events, traditional forecasting methods are facing significant bottlenecks. Consequently, the deep integration of AI is viewed as a historic opportunity to achieve a leap forward in precision forecasting and early warning capabilities.

Throughout the workshop, experts engaged in thematic discussions covering a wide array of advanced applications, including AI-driven typhoon track and intensity prediction, satellite remote sensing, wind and precipitation analysis, and storm surge forecasting. The agenda also included strategic planning for 2026 and beyond, focusing on crucial collaborative topics like joint model evaluations, data exchange policies, and research on tropical disturbances.



Ultimately, the workshop reinforced a strong regional consensus to transition AI technologies from laboratories to frontline disaster prevention operations. The collaborative effort aims to support the United Nations' "Early Warnings for All" initiative, establishing a new paradigm for global disaster risk reduction and advancing international meteorological governance.













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