Application Of Hybrid Variational-ensemble Assimilation Method In FY-3A Satellite Microwave Data

Based on the WRF model and the global clustering forecasting product issued by the European Center for Medium Range Weather Forecasting,the assimilation of FY-3A satellite microwave data was realized based on the Hybrid variational-ensemble data assimilation method in the case of the Beijing “7.21” extreme precipitation event in the 2012.Using Hybrid variational-ensemble data assimilation method directly assimilating FY-3A satellite microwave data,and compared to the three-dimensional variational assimilation method,the differences in assimilation incremental distribution were analyzed.Through a series of sensitivity tests,the effects of different mixed coefficients,different microwave data,different satellite sparse scale of Hybrid assimilation scheme were studied.The effects of microwave data of NOAA-16 satellites and of FY-3A satellites were compared based on Hybrid assimilation method.Results show that both assimilation methods can improve the simulated precipitation results,but the Hybrid assimilation method is better than the three-dimensional variational assimilation method,which can effectively reduce the false heavy rainfall,and improve the simulation of the location of heavy rainfall center.Both assimilation methods can change the physical information in the initial field,but the increments produced by those two methods are different in both magnitude and distribution.Three-dimensional variational assimilation method affects larger region in the simulation area for wind field,temperature field and relative humidity field than that of the Hybrid assimilation method.Increments obtained by the three-dimensional variational assimilation method are nearly homogeneous and isotropic,while the increments obtained by the Hybrid assimilation method are inhomogeneous,anisotropic and “flow-dependent”.Hybrid assimilation method makes the distribution of the initial field more reasonable,and it can improve the simulation of precipitation.Using the hybrid method,whether assimilating FY-3A Microwave Temperature Sounder data alone,the FY-3A Microwave Humidity Sounder data alone,or assimalating both microwave data can improve the simulation results of the improvement of precipitation,but the degree of improvement was different.The results of assimilating both microwave data is better than the othe two tests.In terms of assimilation increment,the Microwave Temperature Sounder data mainly affects the distribution of the assimilation increment.The addition of the Microwave Humidity Sounder data mainly affects the size of the assimilation increment.The incremental size is mainly dependent on the increase of the two kinds of data linear superposition.For this dissertation,the best choice of mixed coefficients was 0.5 and the satellite sparse scale was 120 km for Hybrid assimilation method.The results of the assimilation of two different type of satellites data were analyzed in the case of the historical Beijing “7.21” extreme precipitation event in 2012.After the quality control,the number of channels for AMSU-A data was more than that for Microwave Temperature Sounder data,the number of channels for the AMSU-B data is the same as for the Microwave Humidity Sounder data.After Bias Correction,the systematic errors of the NOAA satellite microwave data and the FY-3A microwave data into the assimilation model are effectively reduced,and the distribution tends to be reasonable,and the deviation of the two satellite data is equivalent.Compared to simultaneous assimilation of NOAA satellites AMSU-A and AMSU-B data,simultaneous assimilation of FY-3A satellite Microwave Temperature Sounder data and Microwave Humidity Sounder data is better for heavy rain and extremely heavy rain.For the adjustment of the initial field,the performance of the microwave thermometer data is greater,the wind field,the temperature field and the humidity field assimilation increment distribution are similar to those of the individual assimilating thermometer data.