Direct Assimilation of Radar Reflectivity Data using a Convective-scale EnKF System
In this study, Doppler radar data are assimilated with a convective-scale ensemble Kalman Filter (EnKF) in combination with a double-moment (DM) microphysics scheme in order to improve the analysis and forecast of microphysical parameters and precipitation structure in hurricane simulations. We directly assimilate both radar reflectivity and radial velocity, evaluate the impact of Single- and Double-moment microphysical schemes on radar data assimilation, deal with the model error caused by microphysical parameterization schemes within data assimilation process, and seek the optimal efficient strategy for radar data assimilation. Our study shows that forecast initialized from EnKF radar data assimilation is able to maintain the hurricane structure throughout the first few forecast hours, suggesting that the EnKF analysis is well balanced. This system is able to develop reliable multivariate covariance among dynamic, thermodynamic, and microphysical variables and the prior estimates of radar observations. The precipitation forecasts show large sensitivity to the choice of microphysics schemes.
Ms. Jingyao Luo Shanghai Typhoon Institute