Impact of Atmospheric Retrievals on Hurricane Florence/Michael Forecasts in a Regional NWP Model

Atmospheric temperature and water vapor profiles from the Infrared Atmospheric Sounding Interferometer and the Cross-track Infrared Sounder with acceptable qualities under clear condition and above clouds are derived using the Dual-Regression algorithm based on the Principle Component-based Radiative Transfer Model. The application of the derived atmospheric retrievals with high temporal and spatial resolutions in a regional weather model is studied for two hurricane cases by assimilating the retrievals in an hourly update cycle. Improvements on hurricane forecast are obtained by assimilating satellite retrievals as compared to both conventional operational data and radiance assimilation. Position of the predicted hurricane center, which is especially critical for landfall position, is corrected with a maximum improvement of 45 km compared to conventional assimilation. Predictions of heavy precipitation produced by hurricanes are improved with smaller bias and standard deviation. Precipitation scores used for the validation of predictions also show great improvements in heavy precipitation forecast against conventional data and radiance assimilation. Hurricane structure representation is substantially improved. Specifically, more symmetric structures, stronger warm cores, deeper convections, and more accurate winds lead to the improvements in precipitation forecasts. Potential applications of such approaches can be applied to assimilating the retrieved information from the geostationary satellite instruments by adding higher temporal and horizontal resolutions to the polar satellite hyperspectral sounding data.