光谱学与光谱分析, 2016, 36 (12): 3895, 网络出版: 2016-12-30  

利用地基红外高光谱发射率数据进行云参数反演(2): 云滴有效半径和云水路径反演

Research on Cloud Phase Detemination Using Infrared Emissivity Spectrum Data (2): Retrieval of Cloud Effective Radius and Water Path
作者单位
解放军理工大学气象海洋学院, 江苏 南京 211101
摘要
云滴有效半径和云水路径等微物理参数是了解云的形成过程、 辐射效应以及云、 气溶胶和降水相互作用等问题的重要数据。 利用地基红外高光谱辐射数据开展了云微物理参数反演方法研究。 针对光谱数据的特点, 进行了基于云层发射率光谱和辐射光谱的敏感性分析, 在此基础上建立了云微物理参数与云发射率光谱差值和斜率等特征参数有关的查找表关系。 具体特征参数包括: 热红外波段862.1和934.9 cm-1的云层发射率之差、 中红外波段1 900.1和2 170.1 cm-1的云层发射率之差、 热红外波段900~1 000 cm-1区间的发射率光谱斜率和辐射值光谱斜率、 1 100~1 200 cm-1区间的发射率光谱斜率和辐射值光谱斜率等。 研究了臭氧波段云层透过率的计算方法及对查找关系的约束性, 选择了1 050~1 060 cm-1区间的云层透过率平均值作为约束特征参数。 实现了基于逐步搜索法的多重查找反演云滴有效半径和光学厚度, 并可通过经验关系计算云水路径。 研究表明, 该算法得到的水云的云滴有效半径与ARM计划中的MICROBASE产品基本相当, 冰云的云滴有效半径相对偏小, 两者的云水路径反演结果差异较大。 该反演算法较适合于光学厚度小于6的薄云。
Abstract
The cloud microphysical properties such as cloud effective radius and cloud water path are fundamental properties for understanding the cloud formation, radiative impacts and interactions with aerosol and precipitation. The downwelling infrared radiance spectra is studied here to retrieve microphysical properties of clouds. The sensitivity of the downwelling radiance spectra and cloud emissivity spectra to the liquid cloud and ice cloud effective radius and optical depth is analyzed. The look-up-tables are established for optically thin clouds (cloud optical depth less than 6) that rely on parameters of the slopes and differences of the emissivity spectra. These parameters include the difference in the emissivity between 862.1 and 934.9 cm-1, the difference in the emissivity between 1 900.1 and 2 170.1 cm-1, the slope of the cloud emissivity and the radiation between 900 and 1 000 cm-1, the slope of the cloud emissivity and the radiation between 1 100 and 1 200 cm-1. The look-up-tables are constrained by the incorporation of mean ozone band transmissivity between 1 050 and 1 060 cm-1. Cloud effective radius and optical depth can be obtained with by least squares fitting between observed and modeled above-mentioned multiple spectral parameters. The cloud water path can then be derived from the experiential relationship. The inversion results are compared with the ARM baseline cloud microphysics product (MICROBASE). It is shown that, the cloud effective radius is roughly in the same order of magnitude while the water paths derived from both method are of large differences especially for the liquid cloud path. The algorithm proposed in this paper is efficient for retrieving microphysical properties of thin clouds with cloud optical depth less than 6.

刘磊, 孙学金, 高太长. 利用地基红外高光谱发射率数据进行云参数反演(2): 云滴有效半径和云水路径反演[J]. 光谱学与光谱分析, 2016, 36(12): 3895. LIU Lei, SUN Xue-jin, GAO Tai-chang. Research on Cloud Phase Detemination Using Infrared Emissivity Spectrum Data (2): Retrieval of Cloud Effective Radius and Water Path[J]. Spectroscopy and Spectral Analysis, 2016, 36(12): 3895.

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