Assimilation of SSM/I and GOES Humidity Retrievals with a One-Dimensional Variational Analysis Scheme

Abstract

Abstract Total precipitable water (TPW) retrieved from Special Sensor Microwave/lmager (SSM/I) brightness temperatures and specific humidity retrieved from Geostationary Operational Environmental Satellite (GOES) radiances are assimilated using a one-dimensional (ID) variational analysis technique. The study is divided into two parts. First, collocations with radiosondes are performed to arm the quality of the satellite water vapor retrievals. Collocations are also performed with 6-h forecast Acids. Second, SSM/I TPW and GOES specific humidity are assimilated using a ID variational analysis technique that minimizes the error variance of the analyzed field. A global collocation study over the oceans for SSM/I TPW retrievals and 6-h forecasts of TPW shows that the rmse (with respect to radiosondes) are, respectively, 4.7 and 5.0 kg m−2. A separate collocation study over both the oceans and land for GOES retrieved TPW and 6-h forecasts of TPW yields rmse of 4.6 and 4.4 kg m−2, respectively, in the midlatitudes and 6.8 and 5.9 kg m−2 in the Tropics. The reduction of the 6-h forecast rmse when assimilating SSM/I TPW is 1 kg m−2, which is a reduction of 20% in the rmse. When GOES retrievals of specific humidity are assimilated, the elective reduction is 0.6 kg m−2. It is shown that in the upper levels of the troposphere (above 600 mb), the error reduction of specific humidity is largely due to the GOES retrievals, whereas in the lower troposphere (850 and 700 mb), the reduction is mostly due to the SSM/I TPW. This emphasizes the complementarity of the information contained at different wavelengths and the advantage of using multisensor retrievals in data analysis.