A woman wearing a face mask walks on an overhead bridge in the central business district as dust and sand storm sweeps through Beijing, on April 13, 2023. Photo: VCG

Using advanced air pollution modeling (APM) and remote sensing satellite technology, a Chinese research team has found that among the frequent sand and dust weather events in China this spring, Mongolia's average contribution to the dust weather was 42 percent, and the contribution of Taklimakan Desert in Northwest China's Xinjiang Uygur Autonomous Region was 26 percent.

Led by Huang Jianping, an academician of the Chinese Academy of Sciences and professor of Lanzhou University, the team integrated ground-based observation and satellite remote sensing observation data, and used machine learning to effectively improve the dust prediction effect.

Researchers also used the improved numerical model, combined with the diffusion trajectory model, multi-source ground observation and satellite remote sensing data to determine the sources and transport paths of dust in northern China. The concentration weight trajectory analysis method is also being used to calculate the contribution of different sand sources to the sand and dust weather.

Chen Siyu, lead author of the paper and professor at Lanzhou University, pointed out that there have been 12 dust events in northern China since January, and the number of dust processes since 2023 is the most in the same period in nearly a decade. Among them, dust events from March 19 to 24 and April 9 to 11 have reached sandstorm level.

These events were dominated by two weather systems, the cold front and the Mongolian cyclone, which caused a large area of sand in Mongolia and promoted the transport of sand and dust across the border, resulting in short-time strong sandstorms in northern China. As the cold front pushed southward, sand and dust also spread southward, resulting in severe pollution in the Yangtze River Basin, Chen noted.

The result, an important achievement in the study of the causes and propagation mechanism of dust weather, was published in the latest issue of Advances in Atmospheric Sciences, a professional academic journal of the Institute of Atmospheric Physics under the Chinese Academy of Sciences.

This study provides an important scientific basis for China to predict and cope with sandstorm disasters, and the results indicate that it is imperative to speed up the China-Mongolian joint desertification control and promote intergovernmental international cooperation on climate change.

Huang said that the research team is currently carrying out large-scale field comprehensive observation experiments to develop parameterization schemes for wind erosion sand formation on different underlying surfaces, so as to improve the simulation accuracy of sand dust. Based on machine learning and multi-source data, a fine dust weather prediction system with high spatial and temporal resolution has been developed.

The implementation of this research will enhance the early identification of dust weather, improve the fine dust disaster warning and forecast system, effectively improve China's joint prevention and control of dust weather and its secondary disasters, and contribute to the cause of disaster weather forecast in China.

Global Times