Abstract
A Doppler radar data assimilation system based on an ensemble Kalman filter (EnKF) method is developed. The system employs a meso-scale hydrostatic model, which includes the conceptual model of the efficiency of the water vapor conversion. A case of the rainfall occurred in Kinki region in 2003 is chosen as an application. Radial velocity and reflectivity observed by Miyama Doppler radar and Jogamori conventional radar are assimilated. The rainfall predicted by our developed system is compared with the prediction results of the four dimensional variational method (4D-VAR) and those of the conditional Kalman filter method. It is demonstrated that our system has equal accuracy to the 4D-VAR method. Also by the comparison of the EnKF method and the conditional Kalman filter method, it is made clear that the spatial correlation in error cannot be ignored.
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