The impact of Reconnaissance Data on Hurricane Intensity Forecasts with a Cycling WRF-EnKF system
To establish a baseline level of hurricane intensity prediction accuracy, a control run without any Reconnaissance data assimilation by the cycling WRF-EnKF system is designed (named as APCT). Also two other experiments are designed to exam the impacts on hurricane intensity prediction by assimilating: 1) flight-level and dropsonde observations (APRC), flight-level, dropsonde and TDR observations (APAR). The preliminary result shows, 1)The APRC has smaller position and intensity errors than the APCT, impressive improvement is on the minimal sea level pressure forecast; 2)Reducing the sample size to the storms only with TDR missions (which means only important storms are considered), the intensity errors of APCT, APRC and APAR are smaller than OFCL. APRC has smaller track and intensity forecast errors than APCT, which means the assimilation of flight-level and dropsonde observations has impact on hurricane track and intensity forecasts. But the assimilation of TDR observation doesn't show any improvement by comparing the forecast of APRC and APAR.
References F. Zhang, Y. Weng, J. A. Sippel, Z. Meng & C. H. Bishop, Cloud-resolving Hurricane Initialization and Prediction through Assimilation of Doppler Radar Observations with an Ensemble Kalman Filter: Humberto (2007). Mon. Wea. Rev., 137, 2105-2125 (2009). doi: 10.1175/2009MWR2645.1. F. Zhang, Y. Weng, J. F. Gamache & F. D. Marks, Performance of Convection-permitting Hurricane Initialization and Prediction during 2008-2010 with Ensemble Data Assimilation of Inner-core Airborne Doppler Radar Observations. Geophysical Research Letters, 38, L15810 (2011). doi:10.1029/2011GL048469. Y. Weng & F. Zhang, Assimilating Airborne Doppler Radar Observations with an Ensemble Kalman Filter for Convection-permitting Hurricane Initialization and Prediction: Katrina (2005). Monthly Weather Review, 140, 841-859 (2012). doi: http://dx.doi.org/10.1175/2011MWR3602.1.