Evaluation of the MODIS C6 Aerosol Optical Depth Products over Chongqing, China

Abstract

Abstract:The Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (C6) aerosol optical depth (AOD) products from the 10/3 km Dark Target (DT) and Deep Blue (DB) algorithms are firstly evaluated using ground observed AODs by the sun photometer in Chongqing, a mountainous mega-city in southwest China. The validation results show that MODIS AODs from 10/3 km DT algorithm are comparable with those of the sun photometer, although there are slight overestimations. However, the DB algorithm substantially underestimates MODIS AODs when comparing with those of the sun photometer. Error analyses imply that the bias of surface reflectance estimation is the main error source for both algorithms. The cloud screening scheme of the DT algorithm is more effective than the DB algorithm. The cloud vicinity effect should be considered in the quality control processes for both of the algorithms. A sensitivity test suggests that in complex terrain area, like Chongqing, the collocation method in the validation of satellite products should be carefully selected according to local circumstances. When comparing the monthly mean AODs of MODIS products with sun photometer observations, it shows that the Terra MODIS AOD products are valid to represent the mean statuses in summer and autumn, but the monthly mean of Aqua MODIS AODs are limited in Chongqing.

Multi-dimensional satellite observations of aerosol properties and aerosol types over three major urban clusters in eastern China

“…Aerosol particles are characterized by their diameter, chemical composition and shape (both are size-dependent), and the number of aerosol particles of each size is described by the particle size distribution. Each of these aerosol properties varies with time and space (Unger et al, 2008;Shindell et al, 2009). The chemical composition of an aerosol particle determines its hygroscopicity and thus the ability to take up or release water vapor in response to changes in relative humidity (RH).…”

A Critical Evaluation of Deep Blue Algorithm Derived AVHRR Aerosol Product Over China

“…Over the Sichuan basin, the AVHRR‐DB AOT is also consistently lower than the MODIS C6.1 AOT (Dark‐Target retrieval as indicated by the algorithm flag in the MODIS product). The evaluation from Shi et al () shows that over the Sichuan Basin the MODIS‐Dark‐Target AOT (C6) slight overestimates the AOT with respect to Sun photometer derived values in Chongqing. However, the DB algorithm substantially underestimates the AOT and this is mainly due to the bias in the surface parameterization.…”

Sub-Mode Aerosol Volume Size Distribution and Complex Refractive Index from the Three-Year Ground-Based Measurements in Chengdu China

“…The spatial characteristics of aerosols can be obtained by remote sensing, one kind of non-contact method [13][14][15]. For instance, some studies analyzed the spatial-temporal distribution of aerosol optical depth (AOD) in Sichuan basin using satellite remote sensing [16,17]. Besides, aerosol optical parameters obtained by the ground-based remote sensing observation were statistically analyzed in this area [18][19][20][21].Although the above-mentioned research studies focus on the total-column aerosol properties by remote sensing methods, it still remains a big challenge to obtain the characteristics of sub-mode aerosol (fine-and coarse-mode) in Chengdu.…”