Experiments of Hurricane Initialization with Airborne Doppler Radar Data for the Advanced Research Hurricane WRF (AHW) Model

Initialization of the hurricane vortex in weather prediction models is vital to intensity forecasts out to at least 48 h. Airborne Doppler radar (ADR) data have sufficiently high horizontal and vertical resolution to resolve the hurricane vortex and its imbedded structures but have not been extensively used in hurricane initialization. Using the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation (3DVAR) system, the ADR data are assimilated to recover the hurricane vortex dynamic and thermodynamic structures at the WRF model initial time. The impact of the ADR data on three hurricanes, Jeanne (2004), Katrina (2005) and Rita (2005), are examined during their rapid intensification and subsequent weakening periods before landfall. With the ADR wind data assimilated, the three-dimensional winds in the hurricane vortex become stronger and the maximum 10-m winds agree better with independent estimates from best-track data than without ADR data assimilation. Through the multivariate incremental structure in WRF3DVAR analysis, the central sea level pressures (CSLPs) for the three hurricanes are lower in response to the stronger vortex at initialization. The size and inner-core structure of each vortex are adjusted closer to observations of these attributes. Addition of reflectivity data in assimilation produces cloud water and rainwater analyses in the initial vortex. The temperature and moisture are also better represented in the hurricane initialization. Forty-eight-hour forecasts are conducted to evaluate the impact of ADR data using the Advanced Research Hurricane WRF (AHW), a derivative of the Advanced Research WRF (ARW) model. Assimilation of ADR data improves the hurricane-intensity forecasts. Vortex asymmetries, size, and rainbands are also simulated better. Hurricane initialization with ADR data is quite promising toward reducing intensity forecast errors at modest computational expense.