Extended Abstract (1.4M)JP1J.7
Progress in Doppler radar data assimilation
Qin Xu, NOAA/NSSL, Norman, OK; and K. Nai, L. Wei, P. Zhang, L. Wang, H. Lu, and Q. Zhao
To optimally assimilate Doppler radar wind observations in combination with the background wind fields provided by model predictions, it is necessary to estimate and represent their error statistics as accurately as possible. Based on the non-isotropic form of error correlation function derived for background radial winds, an efficient statistic method is developed to estimate radar wind observation error and background wind error covariances from Doppler wind innovation (observation minus background) data. The estimated error statistics are used to improve the radar wind data assimilation with the 3.5-dimensional variational (3.5dVar) package developed for the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS). The 3.5dVar is updated by improved representations of the observation and background error covariances and their inverses. The upgraded 3.5dVar is tested with COAMPS and radar wind data collected by the KTLX radar and NSSL phased array radar for a number of severe storms that occurred in Oklahoma during May 2003 and June 2004. The progress will be reported at the conference along with a brief discussion of the challenges ahead.
Joint Poster Session 1J, Assimilation of Radar Data in NWP Models (Joint with 32Radar and 11Mesoscale)
Monday, 24 October 2005, 1:15 PM-3:00 PM, Alvarado F and Atria
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