Assimilation experiments of the Rapid Refresh Hybrid scheme with wind,temperature and humidity data in the vertical observation network
In this study,a Rapid Refresh Hybrid system was constructed based on the Weather Research and Forecasting(WRF)model,WRF Hybrid Data Assimilation system,and Ensemble Transform Kalman Filter(ET-KF),while assimilating both Wind Profile Radar Detection(WPRD)and Microwave Radiometer(MWR)data.Experiments were performed on the impact of four important parameters on the system(that is,two tuning factors of static background error,localization scale and ensemble weighting factor),and contrast research was carried on to the results of the hybrid and 3DVAR schemes.Some encouraging conclusions were reached:Tuning these four parameters could improve performance of the Rapid Refresh Hybrid system,the analysis and forecast of the hybrid scheme with parameters not tuned were superior to those of 3DVAR,and the best results were those of the hybrid schemed with parameters tuned.