The GSI capability to assimilate TRMM and GPM hydrometeor retrievals in HWRF

Abstract

Hurricane forecasting skills may be improved by utilizing increased precipitation observations available from the Global Precipitation Measurement mission (GPM). This study adds to the Gridpoint Statistical Interpolation (GSI) capability to assimilate satellite-retrieved hydrometeor profile data in the operational Hurricane Weather Research and Forecasting (HWRF) system. The newly developed Hurricane Goddard Profiling (GPROF) algorithm produces Tropical Rainfall Measuring Mission (TRMM)/GPM hydrometeor retrievals specifically for hurricanes. Two new observation operators are developed and implemented in GSI to assimilate Hurricane GPROF retrieved hydrometeors in HWRF. They are based on the assumption that all water vapour in excess of saturation with respect to ice or liquid is immediately condensed out. Two sets of single observation experiments that include assimilation of solid or liquid hydrometeor from Hurricane GPROF are performed. Results suggest that assimilating single retrieved solid or liquid hydrometeor information impacts the current set of control variables of GSI by adjusting the environment that includes temperature, pressure and moisture fields toward saturation with respect to ice or liquid. These results are explained in a physically consistent manner, implying satisfactory observation operators and meaningful structure of background error covariance employed by GSI. Applied to two real hurricane cases, Leslie (2012) and Gonzalo (2014), the assimilation of the Hurricane GPROF data in the innermost domain of HWRF shows a physically reasonable adjustment and an improvement of the analysis compared to observations. However, the impact of assimilating the Hurricane GPROF retrieved hydrometeors on the subsequent HWRF forecasts, measured by hurricane tracks, intensities, sizes, satellite-retrieved rain rates, and corresponding infrared images, is inconclusive. Possible causes are discussed.