Abstract

This study evaluates the long-term accuracy of six daily aerosol optical depth (AOD) datasets derived from the Moderate Resolution Imaging Spectroradiometers (MODIS) Dark Target (DT) at 3 and 10 km resolution, Deep Blue (DB), combined DT and DB datasets (DTB) and MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms and the Multi-angle Imaging SpectroRadiometer (MISR) Version 23, by comparing them with ground-based AOD observations in 18 Aerosol Robotic Network (AERONET) sites over the Amazon basin between 2000 and 2022. The AOD retrieval accuracy was also assessed under varying seasons, aerosol loading, particle size, elevation and land cover type. Overall results showed that Terra and Aqua-MODIS DB and MISR algorithms perform better, with about 88% of AOD retrievals within the expected error range. However, MISR presented a systematic high negative bias. MODIS DT 3 km overestimated AOD values and indicated unsatisfactory retrieval accuracy in almost all scenarios. MODIS and MISR retrievals showed improved performance under low aerosol loading, whereas Aqua-MODIS MAIAC under intermediate conditions (AOD>0.2). MISR indicated a large dependence on a coarse mode-dominated environment with considerable negative bias. Terra-MODIS MAIAC retrievals exhibited a smaller dependence for aerosol particle size distribution, while Terra-MODIS DB performed better for fine mode and Aqua-MODIS DB for coarse dominance. MAIAC also performed well under polluted scenarios in the dry season in contrast to the majority of satellite-based AOD retrievals, which showed good agreement under clean background conditions in the wet season. Almost all satellite-based retrievals showed higher uncertainty under extremely high altitudes (>3000 m) followed by non-satisfactory correlation and significant biases. Additionally, almost all satellite-based AOD retrievals indicated poor performance as vegetation coverage increases. On the contrary, MISR showed higher accuracy under forest type. In general, MODIS and MISR retrieval accuracy demonstrated distinct levels of dependencies that require further improvement in the Amazon Basin.

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