A TECHNIQUE FOR ASSIMILATING SSM I OBSERVATIONS OF MARINE ATMOSPHERICSTORMS - TESTS WITH ECMWF ANALYSES/

A variational analysis method to detect and correct displacement and a mplification errors in short-range forecasts of a data assimilation sy stem is developed and tested. Collectively these errors are termed dis tortion errors. The method uses a variational approach to solve a nonl inear least squares estimation problem with side constraints to determ ine the distortion that alters an a priori background field to best fi t the available observations. In this study, the data are Special Sens ing Microwave/Imager (SSM/I) retrievals of integrated water vapor and the a priori background fields are analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF). In practice the background fi elds would be operational 6-h forecasts. The necessary algorithms and methodologies were developed, implemented, and tested on a sufficient number of cases to demonstrate the utility of the method. Cases were s elected that have noticeable features in the SSM/I vertically integrat ed water vapor fields. In all cases studied, the SSM/I data, together with the distortion representation of error, produces significant chan ges to the ECMWF analyses, reducing the variance of the difference bet ween the analysis and SSM/I data by 45%-86%. Further work is suggested to examine impacts on objective analyses and subsequent numerical for ecasts.