Comparisons of aerosol types and optical characters over Shouxian Area China observed from ground- and space-based systems

Abstract

This study evaluates the performance of moderate-resolution Imaging spectroradiometer (MODIS) in aerosol optical depth(AOD) and Ångström exponent(AE) retrievals under high aerosol loading conditions across various aerosol types, utilizing ground-based and space-borne aerosol measurements in Shouxian, China. The intercomparison reveals cloud-aerosol LiDAR with orthogonal polarization's (CALIOP) efficacy in detecting significant aerosol layers and the refinement of sunphotometer-based aerosol type classification through CALIPSO, achieving approximately 80% accuracy. Analysis of 2016-2017 data indicates substantial aerosol presence in Shouxian, with monthly mean AODs ranging from 0.35 to 0.72 at 550 nm, significantly above the global average. The predominant aerosol types were mixed-type (54.8%), desert dust (21.2%), urban/industrial(15.5%), biomass-burning aerosol (6.4%), and continental aerosol (12.1%), with frequent observations of elevated long-range transported aerosol layers. MODIS AOD retrievals generally align with sunphotometer measurements but exhibit higher biases, especially with increasing AOD magnitudes. However, there is a notable difference between MODIS and sunphotometer aerosol AE measurements, with MODIS accurately assessing BBA but showing varied performance across other aerosol types. The combination of AOD and AE of the DD aerosol type is the most accurate. Further analysis showed that MODIS AOD biases and AE biases are negatively correlated, these negative bias correlations show strong aerosol type sensitivities. Monthly analysis of MODIS and sunphotometer comparisons highlights varying performance, particularly during normalized difference vegetation index (NDVI) transitions, suggesting that local vegetation cycles and associated surface spectral reflectance changes significantly impact MODIS aerosol retrieval accuracy under high aerosol loading conditions.