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Proceedings Paper

GOES-R/ABI legacy profile algorithm evaluation using MSG/SEVIRI and AMSR-E
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Paper Abstract

The algorithm for the current Geostationary Operational Environmental Satellite (GOES) Sounders has been adapted to produce atmospheric temperature and moisture legacy profiles from simulated infrared radiances of the Advanced Baseline Imager (ABI) onboard the next generation GOES-R. The Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) Meteosat-8/9 is used as proxy to test the algorithm because it has many of the same spectral and spatial features as ABI. The impact of radiative transfer model on the algorithm is evaluated by comparing two models: the PFAAST and the RTTOV9.1. It is found that RTTOV9.1 is better than PFAAST. The selection of numerical forecast profiles as first guess in the retrieval is another key factor. We compared the retrievals by using a global model (ECMWF 12H forecast) and a regional (RAM-3H forecast) as first guess, respectively. It is found that the retrieval of low-level water vapor by regional model is better than global model because of the higher spatial/temporal resolution of regional model.

Paper Details

Date Published: 10 September 2008
PDF: 6 pages
Proc. SPIE 7085, Atmospheric and Environmental Remote Sensing Data Processing and Utilization IV: Readiness for GEOSS II, 70850F (10 September 2008); doi: 10.1117/12.791886
Show Author Affiliations
Xin Jin, Univ. of Wisconsin, Madison (United States)
Jun Li, Univ. of Wisconsin, Madison (United States)
Timothy J. Schmit, NOAA/NESDIS (United States)
Jinlong Li, Univ. of Wisconsin, Madison (United States)
Allen Huang, Univ. of Wisconsin, Madison (United States)
Mitchell D. Goldberg, NOAA/NESDIS (United States)


Published in SPIE Proceedings Vol. 7085:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization IV: Readiness for GEOSS II
Mitchell D. Goldberg; Hal J. Bloom; Philip E. Ardanuy; Allen H.-L. Huang, Editor(s)

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