Cloud-Resolving Hurricane Initialization and Prediction through Assimilation of Doppler Radar Observations with an Ensemble Kalman Filter

• Published in: Monthly weather review 2009-07, Vol.137 (7), p.2105-2125
• Main Authors: FUQING ZHANG, YONGHUI WENG, SIPPEL, Jason A, ZHIYONG MENG, BISHOP, Craig H
• Format: Article
• Language: English
• Subjects: Airborne radar; Amplification; Analysis; Cyclones; Data assimilation; Data collection; Doppler radar; Doppler radar observation; Doppler sonar; Earth, ocean, space; Echoes; Ensemble forecasting; Exact sciences and technology; External geophysics; Hurricanes; Kalman filters; Meteorology; Perturbation; Radar; Radar data; Radial velocity; Rain; Research methodology; Storm forecasting; Storms; Tropical depressions; Tropical storms; Velocity; Vortices; Weather forecasting
• ISSN: 0027-0644; 1520-0493
• DOI: 10.1175/2009MWR2645.1

This study explores the assimilation of Doppler radar radial velocity observations for cloud-resolving hurricane analysis, initialization, and prediction with an ensemble Kalman filter (EnKF). The case studied is Hurricane Humberto (2007), the first landfalling hurricane in the United States since the end of the 2005 hurricane season and the most rapidly intensifying near-landfall storm in U.S. history. The storm caused extensive damage along the southeast Texas coast but was poorly predicted by operational models and forecasters. It is found that the EnKF analysis, after assimilating radial velocity observations from three Weather Surveillance Radars-1988 Doppler (WSR-88Ds) along the Gulf coast, closely represents the best-track position and intensity of Humberto. Deterministic forecasts initialized from the EnKF analysis, despite displaying considerable variability with different lead times, are also capable of predicting the rapid formation and intensification of the hurricane. These forecasts are also superior to simulations without radar data assimilation or with a three-dimensional variational scheme assimilating the same radar observations. Moreover, nearly all members from the ensemble forecasts initialized with EnKF analysis perturbations predict rapid formation and intensification of the storm. However, the large ensemble spread of peak intensity, which ranges from a tropical storm to a category 2 hurricane, echoes limited predictability in deterministic forecasts of the storm and the potential of using ensembles for probabilistic forecasts of hurricanes.