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基于多角度偏振特性的云相态识别及验证
引用本文:程天海,陈良富,顾行发,余涛,田国良. 基于多角度偏振特性的云相态识别及验证[J]. 光学学报, 2008, 28(10): 1849-1855
作者姓名:程天海  陈良富  顾行发  余涛  田国良
作者单位:中国科学院遥感应用研究所遥感科学国家重点实验室,北京,100101;中国科学院研究生院,北京,100039;国家航大局航天遥感论证中心,北京,100101;中国科学院遥感应用研究所遥感科学国家重点实验室,北京,100101;国家航大局航天遥感论证中心,北京,100101
基金项目:国防科技工业民用专项科研技术研究项目,国家高技术研究发展计划(863计划)
摘    要:云相态识别是云参数研究的重要组成部分,为了有效识别水云和冰云,根据水云和冰云微物理性质的差别,研究了水云和冰云的单次散射特性,采用基丁倍加累加法的,人量辐射传输方程模拟了水云和冰云的多角度偏振特件.模拟结果表明,光谱的多角度偏振特件能够体现山水云粒子和冰云粒子微物理性质的差异,云在特定方向反射的偏振辐射强度对云相态非常敏感,可以用米进行云相念的识别,在模拟的基础上进行了云相态识别算法的研究,并利用多角度偏振卫星数据--POLDER 0.865μm通道数据进行了实例分析.识别结果与MODIS云相态产品及其1.38μm卷云榆测结果进行了比较.分析结果表明,基于多角度偏振特性云相态识别算法可以有效地进行云相态识别.

关 键 词:矢量辐射传输方程  云相态识别  偏振辐射强度  水云模型  冰云模型
收稿时间:2007-12-24

Cloud Phase Classification and Validation Based on Multi-Angular Polarized Characteristics of Cloud
Cheng Tianhai,Chen Liangfu,Gu Xingfa,Yu Tao,Tian Guoliang. Cloud Phase Classification and Validation Based on Multi-Angular Polarized Characteristics of Cloud[J]. Acta Optica Sinica, 2008, 28(10): 1849-1855
Authors:Cheng Tianhai  Chen Liangfu  Gu Xingfa  Yu Tao  Tian Guoliang
Affiliation:Cheng Tianhai1,2,3 Chen Liangfu1,3 Gu Xingfa1,3 Yu Tao1,3 Tian Guoliang1,31State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing Application,Chinese Academy of Sciences,Beijing 100101,China2Graduate University of Chinese Academy of Sciences,Beijing 100039,China3Center for National Spaceborne Demonstration,China
Abstract:Cloud phase recognition is important for cloud studies.The single-scattering properties of water cloud and ice cloud were studied to effectively identify them,in the light of the difference of microphysical characteristics between the two kinds of clouds,their polarized radiance was simulated by utilizing the vector radiative transfer equation based on adding-doubling method.The results indicate that the polarized radiance over a large range of scattering angles can show the distinction between water cloud ...
Keywords:vector radiative transfer equation  cloud phase classification  polarized radiance  water cloud model  ice cloud model  
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