Paper
13 September 2007 Assimilation of AIRS data using a mesoscale model
Author Affiliations +
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Matthew Carrier and Xiaolei Zou "Assimilation of AIRS data using a mesoscale model", Proc. SPIE 6685, Assimilation of Remote Sensing and In Situ Data in Modern Numerical Weather and Environmental Prediction Models, 668508 (13 September 2007); https://doi.org/10.1117/12.740455
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data modeling

Humidity

Atmospheric modeling

Error analysis

Matrices

Satellites

Infrared radiation

Back to Top