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

摘要

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.