Numerical Experiment of Assimilation of Doppler Radar Data with an Ensemble Kalman Filter
集合卡尔曼滤波同化多普勒雷达资料的数值试验

The ensemble Kalman filter (EnKF) is applied to assimilation of simulated Doppler radar data in a cloud model and its performances under different conditions are investigated.The results demonstrate that the EnKF assimilation method is able to produce analyses that accurately approximate the true state after several assimilation cycles.The EnKF assimilation of single radar data is slightly influenced by the radar location.More accurate analyses are obtained during the earlier period when dual-Doppler data are assimilated.It is also found that assimilating the rainwater mixing ratio obtained from the reflectivity results in a better performance of EnKF than directly assimilating the reflectivity.When both radial velocity and rainwater mixing ratio are assimilated,the quality of the EnKF analyses is improved.The covariances between the observed variables and the state variables are important to the quality of the analyses.The analysis error increases when only the covariances of radial velocity with velocities are estimated.As the amount of the observations decreases,the performance of the EnKF analyses is degraded.However,the EnKF can again provide accurate estimates by adding assimilation of the hypothetical surface wind and temperature observations.The EnKF technique is not especially sensitive to the radar observation errors.The initialization of the ensemble has an effect on the quality of the analyses,as do the ensemble size and the radius of influence for the observations.The assimilation is sensitive to the model errors.The EnKF is applied to dual-Doppler radar data of a Meiyu rainstorm.Results demonstrate that the EnKF assimilation method is able to retrieve the detailed structure of wind,thermodynamics and microphysics from dual-Doppler radar observations.The retrieved wind fields agree with the dual-Doppler synthesized winds and are accurate.The distributions of the retrieved perturbation pressures,perturbation temperature and microphysics are also reasonable through the examination of their physical consistency.The wind shear at middle and lower levels is the primary dynamical characteristics of the Meiyu heavy precipitation.The convective rainfall is often related to lower level convergence and upper level divergence coupled with the updraft.The convective system is characterized by high pressure at lower level and low pressure at upper level,associated with warmer at middle level and colder at lower and upper levels than the environment.The water vapor,cloud water and rainwater are associated with the convective cloud,the updraft and the reflectivity,respectively.