ADVANCES OF CRTM LAND-SURFACE MICROWAVE EMISSIVITY MODELING

Surface emissivity has direct impact on the radiance simulation of window channels and surface-sensible sounding and water vapor channels in data assimilation system. Accurate surface emissivity modeling can significantly increase the number and the quality of assimilated observations, which is controlled by the difference between the observation value and the model simulated values. Land surface emissivity is characterized by a variety of surface parameters that may have quite different tempo-spatial scales, e.g., seasonal vegetation cover and turbulent-scale surface soil moisture, etc. Surface emissivity models provide “real-time” or dynamic relationship with these parameters, which has apparent advantage over static emissivity database. Surface emissivity models may be also used to physically retrieve quality land surface variables, e.g., soil moisture, precipitation, which may be assimilated into the forecasting system as higher-level satellite data products. Many efforts have been made to improve CRTM surface emissivity models (CSEM). The physical MW emissivity model (CSEM-MW) developed by Weng et al [Weng et al., 2001; Weng et al., 2011; Chen et al., 2013] was refined to take into account the temperature difference between canopy and the underlying soil. A more general leaf inclination distribution model was introduced to improve the canopy volume scattering process. In particular, soil is treated as multi-layered media with vertically variable temperature, water content, and soil texture compositions. The soil model consists of two optional multi-layer soil RT schemes [Burke et al, 1979; Wilheit, 1978] and a core profiling model which implemented 120 discrete vertical layers. Soil profiles were constructed from the 4-layer soil outputs of GFS. The latest CSEM advances will be presented in this symposium. Analysis results based on forward CRTM simulation and GSI testing will be introduced.

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