Background error in WRF model

Abstract

WRF model have been tuned and tested over Georgia’s territory for years. First time in Georgia the process of data assimilation in Numerical weather prediction is developing. This work presents how forecast error statistics appear in the data assimilation problem through the background error covariance matrix – B, where the variances and correlations associated with model forecasts are estimated. Results of modeling of background error covariance matrix for control variables using WRF model over Georgia with desired domain configuration are discussed and presented. The modeling was implemented in two different 3DVAR systems (WRFDA and GSI) and results were checked by pseudo observation benchmark cases using also default global and regional BE matrixes. The mathematical and physical properties of the covariances are also reviewed.