AI-driven Global Aerosol-Meteorology Forecasting System has been avaliable on the Early Warning Platform of WMC-BJ
Recently, the world's first Artificial intelligence-driven Global Aerosol-Meteorology Forecasting System (AI-GAMFS), developed by a team led by CHE Huizheng, researcher from the Chinese Academy of Meteorological Sciences (CAMS), has been available on the International Meteorological Early Warning Operational Support Platform (hereinafter referred to as “the Early Warning Platform”) at the World Meteorological Centre Beijing (WMC-BJ).
As human activities and the impacts of climate change intensify, issues such as dust storms and wildfires—which contribute to atmospheric aerosol pollution, have become increasingly severe, heightening the urgent need for precise forecasts. The research team overcame key technical challenges in aerosol-meteorological spatiotemporal coupling intelligent forecasting, developed an AI large-scale model encompassing 54 forecast variables based on a 42-year global advanced aerosol reanalysis dataset, enabling more precise characterization of the complex interactions between aerosols and meteorological phenomena. Previously, AI-GAMFS has been implemented for operational work of National Meteorological Centre (NMC) of China Meteorological Administration (CMA) and meteorological services in 12 provinces (autonomous regions) across China, including Xinjiang, Ningxia, Inner Mongolia, Gansu, and Shaanxi.