Evaluation of MODIS DT, DB, and MAIAC Aerosol Products over Different Land Cover Types in the Yangtze River Delta of China

Abstract

The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) has been widely used in atmospheric environment and climate change research. Based on data of the Aerosol Robotic Network and Sun–Sky Radiometer Observation Network in the Yangtze River Delta, the retrieval accuracies of MODIS C6.1 Dark Target (DT), Deep Blue (DB), and C6.0 Multi-angle Implementation of Atmospheric Correction (MAIAC) products under different land cover types, aerosol types, and observation geometries were analyzed. About 65.64% of MAIAC AOD is within the expected error (Within EE), which is significantly higher than 41.43% for DT and 56.98% for DB. The DT product accuracy varies most obviously with the seasons, and the Within EE in winter is more than three times that in spring. The DB and MAIAC products have low accuracy in summer but high in other seasons. The accuracy of the DT product gradually decreases with the increase in urban and water land-cover proportion. After being corrected by bias and mean relative error, the DT accuracy is significantly improved, and the Within EE increases by 24.12% and 32.33%, respectively. The observation geometries and aerosol types were also examined to investigate their effects on AOD retrieval.

Keywords

• Yangtze River Delta
• aerosol optical depth
• AERONET
• SONET
• MODIS
• aerosol type