https://en.people.cn/n3/2026/0605/c90000-20464294.html

An AI-driven Global Aerosol-Meteorology Forecasting System (AI-GAMFS) developed by the Chinese Academy of Meteorological Sciences (CAMS) improves the accuracy and speed of dust and air pollution forecasting.

Traditional forecasting models often calculate meteorological elements separately from aerosols such as dust, PM2.5, and smoke.

Through the application of AI, suspended aerosol particles can be linked with meteorological factors — such as temperature, wind speed, and pressure. This holistic approach allows the system to simulate the evolution of the atmosphere with much greater precision, dramatically enhancing forecast accuracy. In addition to precision, the AI model also delivers unparalleled speed. Traditional numerical forecasting relies on massive supercomputer clusters to solve complex physical equations, often taking hours to run a global forecast just a few times a day.

The technology is already moving from the lab to real-world application. The Lanzhou Institute of Arid Meteorology of the China Meteorological Administration (CMA) has accurately predicted over 10 major dust events across northern China since late last year, leveraging the model’s ability to deliver high-precision environmental weather forecasts for the next three to five days.

In addition to tracking storms, the system powers personalized public health alerts, such as warning allergy sufferers to wear N95 masks or helping hospitals prepare for spikes in respiratory illnesses.

Currently, AI-GAMFS has been deployed at the National Meteorological Center and over 10 provincial meteorological departments, including those in Gansu and Shaanxi. It has also been integrated into the CMA’s “MAZU” public early warning cloud platform, a system designed to deliver disaster alerts to the public. Fully open-sourced in line with international standards, the model provides developing countries with a low-cost, high-precision aerosol forecasting solution on a global scale.