Initializing a Hurricane Vortex with an Ensemble Kalman Filter
Yongsheng Chen, NCAR, Boulder, CO; and C. Snyder
Short-term hurricane track and intensity forecast can be largely affected by the errors in the initial vortex. Initializing a realistic hurricane vortex in a mesoscale forecast model still remains a challenge. A new ensemble Kalman filter (EnKF) vortex initialization scheme is proposed.
With this new scheme, hurricane positions and other characteristics which are continuously provided by the satellite and radar imagery can be easily assimilated in the ensemble forecast system. Numerical experiments using a simple 2D model and the Weather and Research Forecast (WRF) model demonstrate that assimilating hurricane position observations can prevent the ensemble track divergence. The subsequent ensemble or deterministic forecasts initialized from the EnKF analysis are improved..
Session 8A, Tropical Cyclone Prediction II - Initialisation
Wednesday, 26 April 2006, 10:30 AM-11:45 AM, Regency Grand BR 4-6
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