Spring is a season of beauty and renewal in many parts of the world, but for certain Asian countries, it also marks the beginning of dust storm season. In March of this year, residents of Inner Mongolia in China were advised to stay indoors due to fast-moving winds reaching up to 100 kilometers per hour. The dust storm originated in Inner Mongolia and eventually reached Beijing, prompting officials to warn citizens to close their windows and remain inside. The storm reduced visibility to less than 90 meters, casting a yellow hue over the city.

Chinese meteorologists and scientists have been working to improve their forecasting systems for dust storms since the 1990s. However, they continue to strive for more accurate information on where and when these storms originate, as well as how they evolve as they move from one region to another. While these forecasting systems have been helpful, they are not without their limitations and errors.

Asian researchers and scientists are utilizing climate modeling and artificial intelligence to better predict the occurrence of dust storms. Improved predictions could save millions of dollars in damages to infrastructure, farms, and housing units, as losses in just one quarter can reach up to 4 million dollars.

The Sahara Desert in Africa is the world's largest source of sand for these storms, while the Gobi Desert in Asia is another significant contributor, located partly in Mongolia and partly in China. Scientists are working on AI-based solutions to predict sand storms, utilizing data from satellites, ground observation centers, and simulation models.

When fast winds blow over dry areas, they lift dust particles into the air, sometimes as high as 1500 meters, and transport them long distances. These dust storms can carry toxic bacteria and metal particles, posing a threat to both human health and the environment. During these storms, mortality rates increase due to both wind-related accidents and cardiovascular and respiratory diseases.

In addition to the health risks, dust storms also have a significant impact on the climate, reducing water and soil nutrition and potentially lowering crop yields. Mongolia estimates a 24% reduction in crop yields due to these storms, and globally, 334 million people are affected by sand storms each year.

Chinese AI systems have shown promising results in predicting dust storms, with a 13% reduction in errors compared to non-AI systems. These systems can forecast dust storms in 13 Asian countries, including China, Tajikistan, and Pakistan, 12 hours in advance on an hourly basis. Researchers are also working on developing mobile apps to provide the public with timely dust storm forecasts and alerts.

Chinese scientists have developed the DAPS (Dust Assimilation and Prediction System), which can provide 48-hour forecasts. This system utilizes data assimilation, combining observational data with AI model calculations for improved accuracy. Deep learning algorithms are used to remove bias in observational data, providing detailed forecasts on the density and spread of dust storms in China, Mongolia, Japan, South Korea, and North Korea.

Climate change also plays a role in exacerbating weather conditions, including dust storms. Arctic amplification, which changes wind circulation patterns, is one such factor. However, AI-based forecasting systems offer hope for improved predictions and early warnings, helping to mitigate the impact of these storms on human health and the environment.