Core Insights - Alibaba's Damo Academy showcased advanced AI technologies and practices for addressing climate challenges at COP30, highlighting the "Baguang" meteorological model which has reduced typhoon intensity prediction errors by over 50% [1][3] - The upgraded Baguang model can predict significant global weather events, such as El Niño and cold waves, up to 12 months in advance, aiding in disaster prevention and socio-economic planning [1][7] Group 1: AI Technology and Applications - The Baguang meteorological model has been applied in regions like Zhejiang, Shandong, and Beijing, demonstrating its effectiveness in typhoon intensity forecasting [1][5] - Damo Academy's collaboration with Zhejiang Meteorological Bureau led to the development of the "Zhejiang Baguang" typhoon prediction model, which ranks first in path and intensity prediction capabilities among meteorological models [5][7] - The Baguang model's intensity forecast error for the super typhoon "Hagupit" was maintained at 5 m/s, significantly better than the 20 m/s error of other models [5] Group 2: Long-term Climate Forecasting - Damo Academy introduced the Baguang subseasonal and seasonal prediction models, extending the forecasting horizon to 12 months, which can identify long-term weather signals and provide early warnings for natural disasters [7] - Research collaboration with the Chinese Academy of Sciences demonstrated that the Baguang subseasonal model could capture extreme negative NAO signals four weeks in advance, predicting significant cold anomalies in Europe [7] - The Baguang seasonal model, based on probabilistic predictions, can forecast El Niño events 12 months ahead, outperforming other mainstream AI meteorological models [7][8]