How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?

Abstract

Abstract:The rapid changes of aerosol sources in eastern China during recent decades could bring considerable uncertainties for satellite retrieval algorithms that assume little spatiotemporal variation in aerosol single scattering properties (such as single scattering albedo (SSA) and the size distribution for fine-mode and coarse mode aerosols) in East Asia. Here, using ground-based observations in six AERONET sites, we characterize typical aerosol optical properties (including their spatiotemporal variation) in eastern China, and evaluate their impacts on Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol retrieval bias. Both the SSA and fine-mode particle sizes increase from northern to southern China in winter, reflecting the effect of relative humidity on particle size. The SSA is~0.95 in summer regardless of the AEROENT stations in eastern China, but decreases to 0.85 in polluted winter in northern China. The dominance of larger and highly scattering fine-mode particles in summer also leads to the weakest phase function in the backscattering direction. By focusing on the analysis of high aerosol optical depth (AOD) (>0.4) conditions, we find that the overestimation of the AOD in Dark Target (DT) retrieval is prevalent throughout the whole year, with the bias decreasing from northern China, characterized by a mixture of fine and coarse (dust) particles, to southern China, which is dominated by fine particles. In contrast, Deep Blue (DB) retrieval tends to overestimate the AOD only in fall and winter, and underestimates it in spring and summer. While the retrievals from both the DT and DB algorithms show a reasonable estimation of the fine-mode fraction of AOD, the retrieval bias cannot be attributed to the bias in the prescribed SSA alone, and is more due to the bias in the prescribed scattering phase function (or aerosol size distribution) in both algorithms. In addition, a large yearly change in aerosol single scattering properties leads to correspondingly obvious variations in the time series of MODIS AOD bias. Our results reveal that the aerosol single scattering properties in the MODIS algorithm are insufficient to describe a large variation of aerosol properties in eastern China (especially change of particle size), and can be further improved by using newer AERONET data.

Performance of the NPP-VIIRS and aqua-MODIS Aerosol Optical Depth Products over the Yangtze River Basin

“…By contrast, the DB10K retrievals are easily underestimated in spring and summer, and overestimated in autumn and winter. Similar seasonal variations of the Aqua-MODIS C6 DT and DB AOD retrievals were analyzed in Eastern China by [32]. Besides, as for the DTB10K retrievals, the positive biases do not exhibit obvious seasonal variations, and are smaller than the other MODIS C6 products.…”

“…Both algorithms are unsuitable for snow-covered surfaces. The details about the two retrieval algorithms were already reported in previous researches [29][30][31][32]. The MODIS C6 10 km aerosol product also provides a set of DT and DB combined database (DTB).…”

“…However, it doesn't appear at KM. The reason may be the differences of aerosol type and surface reflectance between KM and the other sites [32]. Figure 8 illustrates the AOD seasonal variation of the high-quality satellite retrievals and CE318 observations, respectively at TH, HF, WH and KM from 2 May 2012 to 31 December 2016.…”

“…Meanwhile, the DTB10K AOD bias switches from positive at TH and HF to slightly negative at KM for the whole year. In order to have a good knowledge of the influence of the seasons on the satellite retrievals, according to [32], the daily mean Aqua-MODIS C6 (DT, DB and DTB) and VIIRS_EDR retrieval biases (AOD satellite -AOD CE318 ) have been performed over TH (Figure 9), HF ( Figure 10), WH ( Figure 11) and KM ( Figure 12) for the period of 2 May 2012-31 December 2016. Notice that in order to decrease the interference of the surface reflectance, the satellite-CE318 retrieval biases are selected only during AOD CE318 > 0.4.…”

Validation and Accuracy Analysis of the Collection 6.1 MODIS Aerosol Optical Depth Over the Westernmost City in China Based on the Sun‐Sky Radiometer Observations From SONET

“…There are many studies conducting to evaluate the accuracies of MODIS AOD, and some researches demonstrated that the aerosol retrieval from satellites has large improvements and with high effectiveness (Li et al, ; Zhang et al, ). Meanwhile, other scholars think that there still are many uncertainties in satellite aerosol data sets (Li et al, ; Tao et al, ; Tao et al, ). However, numerous scholars have compared the MODIS AOD products to the observations from Aerosol Robotic NETwork (AERONET) or China Aerosol Robot Sunphotometer Network (Fan et al, ; Hsu et al, ; Sayer et al, ; Sayer et al, ; Tao et al, ; Wang et al, ; Wei et al, ; Xie et al, ; Yan et al, ), and most of their MODIS aerosol retrievals are from DT algorithm or DB algorithm of C5.1 and C6.…”