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<p>This study analyzes ground-based observations and multi-source remote sensing data from eight dust storm events in 2024 at two sites: the Tazhong (TZ) station in the Taklamakan Desert interior and the Xiaotang (XT) station on its northern margin, systematically investigates the interrelationships among dust particle size, friction velocity (U*), and dust flux, and evaluates the applicability of remote sensing data in dust monitoring. The results indicate that particle size significantly influences both horizontal fluxes (Q) and vertical dust fluxes (F). Fine particles (d[0.5]) enhance surface dust flux, while coarse particles (D[4,3]—due to their greater gravitational settling—are less capable of sustained suspension, limiting their long-distance transport. A positive correlation exists between friction velocity (U*) and Q, whereas its impact on F is weaker, suggesting that vertical transport is regulated primarily by particle size, gravitational settling, and turbulent structures. Regarding remote sensing data, MODIS Aerosol Optical Depth (AOD) shows strong consistency with ground-based dust flux measurements, especially at the Xiaotang (XT) station, where AOD closely follows the variation trends of both Q and F. This reflects the effectiveness of remote sensing data in capturing changes in dust activity. Additionally, the Aerosol Absorbing Index (AAI) from Sentinel-5P exhibits a highly significant positive correlation with ground-level dust concentrations, effectively reflecting the vertical structure of dust events. This research provides valuable data support and theoretical foundation for dust warning systems and desertification control projects.</p>

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Study on the influence of key parameters of sand emission on dust flux based on multi-source data

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月26日

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  • Mayibaier Maihamuti,
  • Wen Huo,
  • Yongqiang Liu,
  • Yifei Wang,
  • Fan Yang,
  • Chenglong Zhou,
  • Xinghua Yang,
  • Ali Mamtimin,
  • Mierxiatijiang Maihemuti

摘要

This study analyzes ground-based observations and multi-source remote sensing data from eight dust storm events in 2024 at two sites: the Tazhong (TZ) station in the Taklamakan Desert interior and the Xiaotang (XT) station on its northern margin, systematically investigates the interrelationships among dust particle size, friction velocity (U*), and dust flux, and evaluates the applicability of remote sensing data in dust monitoring. The results indicate that particle size significantly influences both horizontal fluxes (Q) and vertical dust fluxes (F). Fine particles (d[0.5]) enhance surface dust flux, while coarse particles (D[4,3]—due to their greater gravitational settling—are less capable of sustained suspension, limiting their long-distance transport. A positive correlation exists between friction velocity (U*) and Q, whereas its impact on F is weaker, suggesting that vertical transport is regulated primarily by particle size, gravitational settling, and turbulent structures. Regarding remote sensing data, MODIS Aerosol Optical Depth (AOD) shows strong consistency with ground-based dust flux measurements, especially at the Xiaotang (XT) station, where AOD closely follows the variation trends of both Q and F. This reflects the effectiveness of remote sensing data in capturing changes in dust activity. Additionally, the Aerosol Absorbing Index (AAI) from Sentinel-5P exhibits a highly significant positive correlation with ground-level dust concentrations, effectively reflecting the vertical structure of dust events. This research provides valuable data support and theoretical foundation for dust warning systems and desertification control projects.