Assimilation of SSMIS Imager Channels Data in HWRF Using GSI

The imaging channels of the Special Sensor Microwave Imager/Sounder (SSMIS) on board the Defense Meteorological Satellite Program (DMSP) F-16, F-17 and F-18 satellites provides much needed information on sea surface wind and boundary layer water vapor for improving hurricane forecasts through data assimilation. In this study, the quality control and bias correction for SSMIS imager channels 12-16 employed in the operational Hurricane Weather Research and Forecasting (HWRF) system are carefully examined. It is found that the SSMIS cloud detection algorithm is not activated due to a major bug. Once this bug is fixed, it is further found that the quality control algorithm fails to identify some SSMIS cloudy radiances within and around hurricane rainfall bands. It is also found that the liquid water path (LWP) calculated at 85 GHz with horizontal polarization is more effective for cloud detection than the LWP calculated at 37 GHz with vertical-polarization. The threshold of liquid water path used in the cloud check is modified as well. Two modifications are made to the HWRF model from 2012 NCEP-Trunk: (i) The model top is raised to about 0.5 hPa; and (ii) the cycling of data assimilation employs a warm start. Three sets of numerical experiments are carried out to show the positive impacts of SSMIS imager channel radiance data assimilation on hurricane track and intensity forecasts. In the first set of experiments, only conventional data are assimilated. The second set of experiments is the same as the first set except for adding SSMIS data. The third set of experiments is the same as the second set except for using the modified quality control and bias correction algorithms. Results will be presented at the conference.