Performance and evaluation of remote sensing satellites for monitoring dust weather in East Asia

Abstract

Satellite remote sensing provides a rich data source for the real-Time and accurate acquisition of dust weather information in East Asia. However, there are few studies to evaluate whether these data can effectively and accurately reflect the dynamic process of dust weather. This study evaluates and compares the continuity, accuracy, and stability of five commonly used remote sensing products for monitoring dust weather in East Asia, based on recorded dust events (DEs) from 2019 to April 2025. The products evaluated are the Fengyun-4A/B (FY-4A/B) dust score (DST), infrared difference dust index (IDDI), Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD), Sentinel-5P absorbing aerosol index (AAI), and Himawari-8/9 AOD, using ground station PM10 concentration data. The results show that the daily spatial distribution of atmospheric dust presented by the five remote sensing products has good consistency. Notably, the AAI not only offers better continuity in depicting the spatial distribution of atmospheric dust compared to other aerosol products but also compensates for the shortcomings of other products that cannot detect UV-Absorbing aerosols mixed with clouds. Based on the evaluation using ground station PM10 data, the mean probability of correct detection (POCD) for atmospheric dust during multiple DEs for Sentinel-5P AAI, MODIS AOD, Himawari-8/9 AOD, FY-4A/B DST, and IDDI products were 57.16 %, 45.18 %, 31.25 %, 22.78 %, and 12.41 %, respectively. The mean probability of false detection (POFD) values were 88.66 %, 88.61 %, 92.04 %, 69.9 %, and 67.69 %, respectively. Overall, the Sentinel-5P AAI has the highest POCD in DEs but is unstable. At the same time, it also has a high POFD. The FY-4A/B IDDI has the lowest POCD, but it is relatively stable, and its POFD is low.