Difference between global and regional aerosol model classifications and associated implications for spaceborne aerosol optical depth retrieval

作者：Pei Zhou, Yang Wang, Jane Liu, Linglin Xu, Xiang Chen, Likun Zhang · 发表于：Atmospheric Environment · 年份：2023 · DOI：10.1016/j.atmosenv.2023.119674 · 被引用次数：14 · 研究领域：Atmospheric aerosols and clouds、Atmospheric chemistry and aerosols、Atmospheric Ozone and Climate

Aerosol model are generally adopted to describe the physical and optical characteristics of aerosols in different regions, and this is important for climate and environmental studies as well as satellite aerosol retrieval. However, current mainstream aerosol retrieval algorithms still lack differentiated and dynamic descriptions of aerosol models, and the aerosol optical depth (AOD) retrieval accuracy is hence largely compromised. Therefore, in this study, we aimed to investigate the difference between global and regional aerosol model classifications and the impact of these differences on satellite AOD retrieval. We developed global and regional (for China) aerosol models through the K-means cluster analysis method, and used the 6SV radiative transfer model based on these global and regional aerosol models to simulate air pollution events. The cluster analysis revealed that both global and regional aerosols can be clustered into five main aerosol types with different optical and physical parameters. The aerosol types include strongly absorbing, moderately absorbing, weakly absorbing, dust and coarse-fine mixed aerosols. These two aerosol models exhibited distinct seasonal variations. Comparing the clustering results obtained with the two models at five Aerosol Robotic Network (AERONET) sites, we found that the proportion of strongly absorbing aerosols in the global results is low. According to the China clustering results, a higher proportion of strongly absorbing aerosols o...