Improved Tropical Storm Forecasts with GOES-13/15 Imager Radiance Assimilation and Asymmetric Vortex Initialization in HWRF

Abstract

he Geostationary Operational Environmental Satellite (GOES) imagers provide high temporal- and spatial-resolution data for many applications, such as monitoring severe weather events. In this study, radiance observations of four infrared channels from GOES-13 and GOES-15 imagers are directly assimilated using the National Centers for Environmental Prediction (NCEP) gridpoint statistical interpolation (GSI) analysis system to produce the initial conditions for the Hurricane Weather Research and Forecasting Model (HWRF). Impacts of GOES imager data assimilation on track and intensity forecasts are demonstrated for a landfalling tropical storm that moved across the Gulf of Mexico?Debby (2012). With a higher model top and a warm start, an asymmetric component is also added to the original HWRF symmetric vortex initialization. Two pairs of data assimilation and forecasting experiments are carried out for assessing the impacts of the GOES imager data assimilation on tropical storm forecasts. The first pair employs a symmetric vortex initialization and the second pair includes an asymmetric vortex initialization. Numerical forecast results from these experiments are compared against each other. It is shown that a direct assimilation of GOES-13 and GOES-15 imager radiance observations, which are available at all analysis times, in HWRF results in a consistently positive impact on the track and intensity forecasts of Tropical Storm Debby in the Gulf of Mexico. The largest positive impact on the track and intensity forecasts comes from a combined effect of GOES imager radiance assimilation and an asymmetric vortex initialization.