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Validation of the community radiative transfer model
Authors:Shouguo Ding  Fuzhong Weng  Yong Han  Jun Li
Institution:a Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA
b Satellite Meteorology and Climatology Division, Center for Satellite Applications and Research, NOAA/NESDIS, Camp Springs, MD 20746, USA
c QSS Group, Incorporated, Camp Springs, MD 20746, USA
d Joint Center for Satellite Data Assimilation, NOAA/NESDIS, Camp Springs, MD 20746, USA
e Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, Madison, WI 53706, USA
f Space Science and Engineering Center, University of Wisconsin Madison, Madison, WI 53706, USA
Abstract:To validate the Community Radiative Transfer Model (CRTM) developed by the U.S. Joint Center for Satellite Data Assimilation (JCSDA), the discrete ordinate radiative transfer (DISORT) model and the line-by-line radiative transfer model (LBLRTM) are combined in order to provide a reference benchmark. Compared with the benchmark, the CRTM appears quite accurate for both clear sky and ice cloud radiance simulations with RMS errors below 0.2 K, except for clouds with small ice particles. In a computer CPU run time comparison, the CRTM is faster than DISORT by approximately two orders of magnitude. Using the operational MODIS cloud products and the European Center for Medium-range Weather Forecasting (ECMWF) atmospheric profiles as an input, the CRTM is employed to simulate the Atmospheric Infrared Sounder (AIRS) radiances. The CRTM simulations are shown to be in reasonably close agreement with the AIRS measurements (the discrepancies are within 2 K in terms of brightness temperature difference). Furthermore, the impact of uncertainties in the input cloud properties and atmospheric profiles on the CRTM simulations has been assessed. The CRTM-based brightness temperatures (BTs) at the top of the atmosphere (TOA), for both thin (τ<5) and thick (τ>30) clouds, are highly sensitive to uncertainties in atmospheric temperature and cloud top pressure. However, for an optically thick cloud, the CRTM-based BTs are not sensitive to the uncertainties of cloud optical thickness, effective particle size, and atmospheric humidity profiles. On the contrary, the uncertainties of the CRTM-based TOA BTs resulting from effective particle size and optical thickness are not negligible in an optically thin cloud.
Keywords:Validation  CRTM  DISORT  LBLRTM  AIRS  IASI  ECMWF
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