LANZHOU, June 5 (Xinhua) -- As spring rolls around, people in Gansu Province, northwest China, must brace for sudden dust storms that cover cities in a yellow haze, make travel miserable, and pose health risks.

However, the people of Gansu are now better prepared than ever to face these challenges. Days before a storm is expected to hit, residents receive precise, real-time warnings rather than being caught off guard. Simple precautions such as wearing face masks and rescheduling travel plans can greatly mitigate the impact on public health and daily life.

This shift is driven by a technological breakthrough: the AI-driven Global Aerosol-Meteorology Forecasting System (AI-GAMFS). Developed by Chinese scientists, this artificial intelligence model is dramatically improving the accuracy and speed of dust and air pollution forecasting.

According to Gui Ke, an associate researcher at the Chinese Academy of Meteorological Sciences (CAMS), traditional forecasting models often calculate meteorological elements separately from aerosols -- microscopic solid particles or liquid droplets suspended in the atmosphere, such as dust, PM2.5, and smoke.

"Forecasting aerosols is far more complex and computationally expensive than traditional weather forecasting," Gui said. "It requires the system to simultaneously parse multiple aerosol sources, complex chemical transformations, and their multi-scale interactions with weather systems."

He explained that the application of AI, however, dynamically links suspended aerosol particles with meteorological factors -- such as temperature, wind speed, and pressure -- as a unified whole. 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 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.

In contrast, the AI-driven system runs on graphics processing units and can generate a global forecast in just 36 seconds -- over 100 times faster than traditional methods.

The technology is already moving from the lab to real-world application. According to Duan Haixia, a chief expert at the Lanzhou institute of arid meteorology of the China Meteorological Administration (CMA), the institute 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.

The system does more than track storms; it 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.