This study examines a hurricane prediction system that uses an ensemble Kalman filter (EnKF) to assimilate high-resolution airborne radar observations for convection-permitting hurricane initialization and forecasting. This system demonstrated very promising performance, especially on hurricane intensity forecasts, through experiments over all 61 applicable NOAA P-3 airborne Doppler missions during the 2008-2010 Atlantic hurricane seasons. The mean absolute intensity forecast errors initialized with the EnKF-analysis of the airborne Doppler observations at the 24-to 120-h lead forecast times were 20-40% lower than the National Hurricane Center's official forecasts issued at similar times. This prototype system was first implemented in real-time for Hurricane Ike (2008). It represents the first time that airborne Doppler radar observations were successfully assimilated in real-time into a hurricane prediction model. It also represents the first time that the convection-permitting ensemble analyses and forecasts for hurricanes were performed in real-time. Also unprecedented was the on-demand usage of more than 23,000 computer cluster processors simultaneously in real-time.
All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)