Distinct spatiotemporal patterns and meteorological impacts of Gobi Desert and Taklimakan Desert dust storms over China

Abstract

Dust storms frequently impact China, driven largely by dust emissions from the Gobi and Taklimakan Deserts-two of East Asia's most significant dust sources. However, fundamental differences in their patterns and associated feedback mechanisms-particularly involving thermal and atmospheric processes-remain to be quantified. Here, we propose a novel framework integrating a rigorous hierarchical analysis with dynamic thresholding to enhance the precision and robustness of the dust storm-associated coarse-mode aerosol optical depth (DUST-cAOD) retrievals. By improving the Brightness Temperature Difference (BTD) algorithm, our method achieves 10-minute-resolution DUST-cAOD observations from 2016 to 2023. We build 32,767 hierarchical regression models to isolate and compare meteorological impacts of dust storms originating from the two Deserts. Our analysis reveals an intensification in frequency and impact of Gobi Desert-sourced dust storms. Annual occurrences increased from 6.25 events (2016–2019) to 14 events (2020–2023). Spatially, these storms affect 28.35 % of China’s land area-exceeding Taklimakan-sourced Desert storms by 37 %-and impact threefold more people. Mechanistically, Gobi Desert dust storms amplify through a positive feedback loop: thermal forcing strengthens the subtropical ridge (STR), reduces dewpoint temperatures, and elevates cloud liquid water content. In contrast, Taklimakan Desert dust storms intensify primarily through coupled precipitation-evaporation feedbacks. This study establishes the first systematic comparison of distinct mechanisms governing dust storms originating from the Gobi and Taklimakan Deserts. Our findings provide critical scientific support for improved early warning systems, region-specific mitigation strategies, and comprehensive assessments of dust-climate interactions across East Asia.