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Open AccessArticle

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

1
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
2
Department of Chemical and Biochemical Engineering, Center of Global and Regional Environmental Research, University of Iowa, Iowa City, IA 52242, USA
3
Laboratory of Critical Zone Evolution, School of Earth Sciences, China University of Geosciences, Wuhan 430074, China
*
Authors to whom correspondence should be addressed.
Academic Editors: Yang Liu and Omar Torres
Remote Sens. 2017, 9(8), 800; https://doi.org/10.3390/rs9080800
Received: 21 June 2017 / Revised: 27 July 2017 / Accepted: 1 August 2017 / Published: 3 August 2017
(This article belongs to the Special Issue Remote Sensing of Atmospheric Pollution)
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. View Full-Text
Keywords: aerosol; MODIS; retrieval bias; eastern China; AERONET aerosol; MODIS; retrieval bias; eastern China; AERONET
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MDPI and ACS Style

Tao, M.; Wang, Z.; Tao, J.; Chen, L.; Wang, J.; Hou, C.; Wang, L.; Xu, X.; Zhu, H. How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China? Remote Sens. 2017, 9, 800. https://doi.org/10.3390/rs9080800

AMA Style

Tao M, Wang Z, Tao J, Chen L, Wang J, Hou C, Wang L, Xu X, Zhu H. How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China? Remote Sensing. 2017; 9(8):800. https://doi.org/10.3390/rs9080800

Chicago/Turabian Style

Tao, Minghui; Wang, Zifeng; Tao, Jinhua; Chen, Liangfu; Wang, Jun; Hou, Can; Wang, Lunche; Xu, Xiaoguang; Zhu, Hao. 2017. "How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?" Remote Sens. 9, no. 8: 800. https://doi.org/10.3390/rs9080800

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