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

Abstract

AbstractThis study evaluates the performance of different MODerate 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 10 km, the DT C6 algorithm at 3 km, and the Simplified Aerosol Retrieval Algorithm (SARA) at 500 m, 3 km, and 10 km resolutions. The DB C6 retrievals have 34–39% less uncertainties, 2–3 times smaller root‐mean‐square error (RMSE), and 3–4 times smaller mean 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 km fall above the expected error (EE), with overestimation of 64–79% which is 15–27% higher than that for the DT C6 at 10 km. The results suggest that the DT C6 at 3 km resolution is less reliable than that at 10 km. 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.