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The simultaneous retrieval of hyperspectral IR emissivity spectrum along with temperature and moisture profiles from AIRS

机译:同时检索高光谱IR发射率光谱以及空气中的温度和水分型材

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Surface emissivity plays an important role in the retrievals of surface and atmospheric parameters from satellite IR measurements. In this research, a physical algorithm has been developed to retrieve hyperspectral IR emissivity spectrum simultaneously with temperature and moisture profiles as well as surface skin temperature To retrieve the hyperspectral IR emissivity, the emissivity spectrum is represented by the eigenvectors, derived from the laboratory measured hyperspectral emissivity database, in the retrieval process Simulations are carried out with profiles over different land surface properties and results show that simultaneous retrieval of emissivity spectrum can improve the surface skin temperature as well as temperature and moisture profiles retrievals, particularly for the boundary layer moisture. The algorithm has further been applied to the Atmospheric Infrared Sounder (AIRS) radiance measurements, which covers a diversity of land surface types. The retrievals have then been compared with the ECMWF analyses and radiosonde observations, and shown a very good agreement.
机译:表面发射率在来自卫星IR测量的表面和大气参数的检索中起着重要作用。在该研究中,已经开发了一种物理算法,用于将高光谱IR发射率光谱同时检索温度和水分型材以及表面皮肤温度,以检索高光谱IR发射率,发射率光谱由实验室测量的高光谱衍生的特征向量表示发射率数据库,在检索过程模拟中,在不同的土地表面性质上进行型材,结果表明,同时检索发射率光谱可以改善表面皮肤温度以及温度和水分谱检测,特别是对于边界层水分。该算法进一步应用于大气红外发声器(空气)光线测量,涵盖了陆地表面类型的多样性。然后将检索与ECMWF分析和无线电探测器观察结果进行比较,并显示了非常良好的一致性。

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