Paper
15 August 2011 Assessment on aerosol direct radiative forcing over China land areas based on satellite data
Lin Chen, Guangyu Shi, Biao Wang, Peng Zhang
Author Affiliations +
Proceedings Volume 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing; 82031A (2011) https://doi.org/10.1117/12.910427
Event: Seventeenth China Symposium on Remote Sensing, 2010, Hangzhou, China
Abstract
Detailed data of spatial and temporal distribution and radiative properties of aerosols are required for assessment on aerosol direct radiative forcing. In recent years, with the development of remote sensing instruments as well as corresponding sophisticated inversion algorithms, the global aerosol distribution can be acquired by satellite remote sensing. The aerosol optical depth in the areas with high surface albedo can be inversed by the latest MODIS deep blue algorithm with good complementarity to the applicable areas with traditional dark target inversion scheme. Based on both algorithms, the distribution of aerosol optical depth over land areas of China in 2005 was provided, with an averaged value 0.31. Moreover, the aerosol optical depths are high in spring and summer while low value in autumn and winter, and greatly different in different areas. In addition, the surface albedo data inversed by MODIS and MISR were coupled into the self-developed radiative model,called RAD01. The aerosol direct radiative forcing at the top of atmosphere (TOA), on the surface and in the atmosphere over land areas of China were calculated as -7±2Wm-2, -21.9 ±6.4Wm-2 and 4.9±4.3Wm-2 respectively. Due to the strong absorptivity of aerosols over land areas of China, the aerosol radiative forcing on the surface was three times larger than that at TOA, with a strong heating effect on the atmosphere.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lin Chen, Guangyu Shi, Biao Wang, and Peng Zhang "Assessment on aerosol direct radiative forcing over China land areas based on satellite data", Proc. SPIE 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing, 82031A (15 August 2011); https://doi.org/10.1117/12.910427
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KEYWORDS
Aerosols

Satellites

Data modeling

Atmospheric particles

Remote sensing

Atmospheric modeling

Detection and tracking algorithms

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