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Proceedings Paper

Assimilation of AIRS data using a mesoscale model
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Paper Abstract

The preliminary steps of assimilating AIRS radiance data into a mesoscale model are presented. First, a stand-alone 1D-Var driver is developed in order to retrieve temperature and specific humidity profiles from AIRS data using background profiles obtained from a mesoscale model. Vertical background error covariance matrices are calculated for both temperature and specific humidity. The inverses of the background error covariance matrices are estimated using a singular value decomposition procedure, in which the small singular values and associated small-scale structures in the background error covariances are removed. By comparing with two available collocated radiosonde data, it is then shown that AIRS radiance-derived vertical profiles of temperature and specific humidity are more consistent to radiosonde observations than the background profiles. Finally, a multi-profile retrieval is performed which produced largest analysis increments of temperature and moisture in the region of a mid- and upper-level moisture gradient associated with a cold front.

Paper Details

Date Published: 13 September 2007
PDF: 13 pages
Proc. SPIE 6685, Assimilation of Remote Sensing and In Situ Data in Modern Numerical Weather and Environmental Prediction Models, 668508 (13 September 2007); doi: 10.1117/12.740455
Show Author Affiliations
Matthew Carrier, The Florida State Univ. (United States)
Xiaolei Zou, The Florida State Univ. (United States)


Published in SPIE Proceedings Vol. 6685:
Assimilation of Remote Sensing and In Situ Data in Modern Numerical Weather and Environmental Prediction Models
Xiaolei Zou; Dale Barker; Francois-Xavier Le Dimet, Editor(s)

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