Evaluation of MODIS aerosol retrieval algorithms over the Beijing-Tianjin-Hebei region during low to very high pollution events

This study evaluates the performance of differentMODerate resolution Imaging Spectroradiometer (MODIS) aerosol algorithms during fine particle pollution events over the Beijing-Tianjin-Hebei region using Aerosol Robotic Network aerosol optical depth (AOD). These algorithms include the Deep Blue (DB) Collection 5.1 (C5) and Collection 6 (C6) algorithms at 10 km resolution, the Dark Target (DT) C5 and C6 algorithms at 10km, the DT C6 algorithm at 3km, and the Simplified Aerosol Retrieval Algorithm (SARA) at 500m, 3 km, and 10km resolutions. The DB C6 retrievals have 34-39% less uncertainties, 2-3 times smaller root-mean-square error (RMSE), and 3-4 times smallermean absolute error (MAE) than DB C5 retrievals. The DT C6 has 4-8%lower bias, 4-12% less overestimation, and smaller RMSE and MAE errors than DT C5. Due to underestimation of surface reflectance and the use of inappropriate aerosol schemes, 87-89% of the collocations of the DT C6 at 3 kmfall above the expected error (EE),with overestimation of 64-79% which is 15-27%higher than that for the DT C6 at 10km. The results suggest that the DT C6 at 3 kmresolution is less reliable than that at 10km. The SARA AOD has small RMSE and MAE errors with 90-96% of the collocations falling within the EE. Overall, the SARA showed 15-16% less uncertainty than the DB C6 (10 km), 69-72% less than the DT C6 (10 km), and 79-83% less than the DT C6 (3 km) retrievals.