细粒子气溶胶光学厚度和谱分布偏振的反演
收稿日期: 2011-12-31
修回日期: 2012-07-27
网络出版日期: 2012-08-22
基金资助
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Study on the Retrieval of Fine Mode Aerosol Optical Depth and Size Distribution Using Polarized Signal
Received date: 2011-12-31
Revised date: 2012-07-27
Online published: 2012-08-22
Supported by
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细粒子气溶胶物理和光学参数定量卫星遥感反演一直是环境和气候领域研究人员关注的重要课题。气溶胶参数卫星业务遥感产品主要是反演气溶胶光学厚度,它体现大气中气溶胶总含量的信息,而获取气溶胶谱分布函数有助于进一步了解气溶胶物理特性,并提高气溶胶其他参数的遥感探测精度。目前,陆地气溶胶卫星反演面临两个关键问题:一是气溶胶模式;二是地表反射贡献的去除,偏振遥感在这两方面有其独有的优势。本文以多角度偏振方法,采用RT3辐射传输模型建立矢量查找表,利用法国PARASOL探测器一级数据反演了京津唐地区的细粒子气溶胶光学厚度和谱分布参数,并使用AERONET地基观测数据对反演结果进行验证,结果表明:偏振方法能较高精度地实现细粒子气溶胶光学厚度反演,而谱分布的反演还需进一步改进。
蒋哲, 陈良富, 王中挺 . 细粒子气溶胶光学厚度和谱分布偏振的反演[J]. 地球信息科学学报, 2012 , 14(4) : 460 -464 . DOI: 10.3724/SP.J.1047.2012.00460
The remote sensing of microphysical and optical properties of fine mode aerosol has gain most attention in both environmental and climatological fields. Aerosol retrieval over land is confronted with two difficulties: selecting the aerosol type and taking out of the surface contribute. As the polarized light reflected by ground targets is small and stable enough to allow for correction in TOA measurements, polarization remote sensing has unique predominance and potential. Based on the directional polarization method, the fine mode aerosol optical depths and size distributions are retrieved using PARASOL Level 1B data through vector radiative transfer model and semi empirical surface polarized reflectance model. Aerosol model selecting is a key factor in the work of aerosol retrieval, so importing local aerosol model is essential in our work. Compared with the products of the ground-based AERONET, the precision of fine mode aerosol optical depth retrieving is bigger than 81% and size distribution retrieving needs to be improved. The results show that the directional polarization method is more accurate for the retrieval of fine mode aerosol and more stable in different seasons and different types of land surfaces. As aerosols over land are mostly composed of fine modes and coarse modes, we need farther study on the aerosol retrieval, such as importing scalar signal to vector method considering the different instrument characteristics and retrieval strategies of scalar and vector methods.
Key words： remote sensing; polarization; fine mode aerosol; size distribution
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