| 红外高光谱观测值反演云参数 |
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| 引用本文： | 官莉,肖稳安,HUANG Hung-Lung.红外高光谱观测值反演云参数[J].大气科学,2007,31(6):1123-1128. |
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| 作者姓名： | 官莉 肖稳安 HUANG Hung-Lung |
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| 作者单位： | 1.南京信息工程大学遥感学院, 南京,210044 |
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| 基金项目： | 国家自然科学基金资助项目40605009，江苏省自然科学基金项目BK2006575 |
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| 摘 要： | 最小局部比辐射率变化MLEV算法根据在红外长波10～15 μm 区, 云的吸收、发射和散射具有相对有限的局部谱变化的特征, 利用对云敏感的长波红外辐射观测值来同时反演单层云的云顶高度和有效云比辐射率谱。先给定一些假想的云高初始猜测, 最佳的云高和比辐射率谱解使得用这些不同云高计算得到的比辐射率谱的局部变化最小, 该算法适用于高光谱(光谱分辨率从0.25～1 cm-1) 的大气红外探测器。通过用两种不同方案的内部比较及与激光雷达观测和MODIS业务云高产品的对比验证, 说明对卫星红外高光谱观测资料采用MLEV算法同时反演单层云的云顶高度和云有效比辐射率谱是非常有效的, 尤其是对中高云。
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| 关 键 词： | 高光谱 云参数 云顶高度 反演 MLEV算法 |
| 文章编号： | 1006-9895（2007）06-1123-06 |
| 修稿时间： | 2007-05-30 |
Retrieval of Cloud Parameters Using Infrared Hyperspectral Observations |
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| GUAN Li,XIAO Wen-An and HUANG Hung-Lung.Retrieval of Cloud Parameters Using Infrared Hyperspectral Observations[J].Chinese Journal of Atmospheric Sciences,2007,31(6):1123-1128. |
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| Authors: | GUAN Li XIAO Wen-An and HUANG Hung-Lung |
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| Institution: | 1 School of Remote Sensing, Nanjing University of Information Science ~ Technology, Nanjing 210044 2 University of Wisconsin, Madison WI 53705, USA |
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| Abstract: | This paper describes the theory and application of Minimum Local Emissivity Variance(MLEV) technique for simultaneous retrieval of cloud pressure level and effective spectral emissivity from high-spectral resolution radiances,for the case of single-layer clouds.The MLEV algorithm uses a physical approach,in which the local spectral variances of cloud emissivity are calculated for a number of cloud pressure levels.The optimal solution for the single-layer cloud emissivity spectrum is that having the "minimum local emissivity variance" among the retrieved emissivity spectra associated with different first-guess cloud pressure levels.This is due to the fact that the absorption,reflection,and scattering processes of clouds exhibit relatively limited localized spectral emissivity structure in the infrared long wave region.Validation with cloud lidar observations and MODIS cloud products indicates the MLEV algorithm is very effective,especially to mid-high clouds. |
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| Keywords: | hyperspectral cloud property cloud top height retrieval MLEV algorithm |
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