Analysis and Validation of the Aerosol Optical Depth of MODIS Products in Gansu Province, Northwest China

Abstract

The accurate determination of aerosol optical depth (AOD) is of great importance for climate change research and environmental monitoring. To understand the applicability of the MODIS aerosol product inversion algorithm in Gansu Province, this work uses ground-based solar photometer AOD observation data to validate the MODIS C6 version of the AOD product. Additionally, the retrieval accuracy of MODIS C6 Deep Blue (DB) algorithm AOD products and Deep Blue and Dark Target Fusion (DB–DT combined) algorithm AOD products for Gansu Province when setting different spatial sampling windows is compared and analyzed. Meanwhile, the monitoring effects of these two AOD algorithms in typical polluted atmospheric conditions in Gansu Province are compared. The results show that (1) the correlation between the MODIS AOD products of the two algorithms and the ground-based observation data decreases with an increasing spatial sampling window size. When the spatial sampling window of the two algorithms is set at 30 km × 30 km, it is more representative of the AOD value in Gansu Province, thus reflecting local characteristics. (2) When the spatial sampling window is set at 30 km × 30 km, the inversion effect of the DB algorithm AOD is better than that of the DB–DT combined algorithm AOD on different underlying surfaces. (3) The seasonal variability in the inversion accuracy of the DB algorithm AOD is less than that of the DB–DT combined algorithm, and it has inversion advantages in spring, autumn and winter, while the DB–DT combined algorithm outperforms the DB algorithm only in winter. The inversion effect of the two algorithms on AOD is influenced by the spatial sampling window setting. (4) Both the DB algorithm AOD and the DB–DT combined algorithm AOD can monitor the distribution of AOD in the central and western regions of Gansu, especially for high values of AOD under polluted atmospheric conditions, which represents a good monitoring effect. However, the two algorithms perform poorly in monitoring the southeast region of Gansu, while there is a discontinuous AOD distribution in the northwest region of Gansu. Overall, the MODIS DB algorithm AOD product has higher applicability in Gansu Province. This work provides a good reference for local air pollution and climate prediction.

Keywords

• MODIS
• aerosol optical depth (AOD)
• inversion algorithm
• Gansu Province
• Northwest China