Impact Of Assimilating Surface And Radar Observations On Forcasting Of Squall Lines With A Hybrid Data Assimilation Method

The Weather Research and Forecasting(WRF)model with the hybrid ETKF-3DVAR(ensemble transform Kalman filter-three-dimensional variational data assimilation)data assimilation(DA)system is used to investigate the impact of assimilating the surface observations and radar data on a squall line forecast.We studied that the hybrid method of assimilating surface and radar observations has the potential of improving the prediction of squall line through observation system simulation experiments and real experiments and investigated the impact of different ensemble generation schemes on a squall line forecast by assimilating the surface observations.For the squall line in the Yangtze river basin on 22 July 2014,results of the observation system simulation experiments and real experiments show that assimilating only surface observations less improves the analysis and forecasts of the squall line than from assimilating both the surface and radar observations,with either the 3DVAR or hybrid method.The lower atmospheric environments,precipitation and reflectivity forecasts in the hybrid experiments have larger improvements than those in the 3DVAR.The assimilating effect has a better persistence in the temperature than in winds.In addition,the assimilating effect for the surface variables has a better persistence in the hybrid method than in the 3DVAR in the observation system simulation experiments.For the squall line in the Huang-Huai region in June 2009,a comparative experiment using three ensembles(created by using the different initial ensemble samples-RCV,by using different model physical process schemes-PPMP,and by combining the first two ensembles-BLE)assimilating the real surface observation once is conducted,results show that: assimilating the surface observations mainly adjusts the spatial structures of wind and water vapor mixing ratio below the level of 850 hPa;the RCV scheme mainly updates the wind distribution,the PPMP scheme updates the water vapor mixing ratio,and the BLE scheme has the characteristics of both RCV and PPMP.Assimilating surface observations can also improve 6-h precipitation forecasts,and the PPMP scheme can give a relatively better performance compared to PPMP and BLE,especially for the prediction of rainfall location and intensity.RCV and BLE schemes present a better simulation for the bow echo,and the performance with BLE is similar to that with RCV.PPMP and RCV schemes can adjust the position and intensity of the cold pool,and also influence the times of appearance and disappearance of the squall line.Generally,PPMP scheme has a more prominent impact on the squall line than RCV and BLE.In order to absorb surface observation information more effectively,the new SOIL ensemble is generated by adding perturbations of soil moisture and temperature in each of the PPMP ensemble members.A severe squall line occurred on 12 July 2014 in east China is examined.The SOIL can increase the spread of near ground moisture field,but has little influence on wind field;expected analysis increments produced in the low levels are mainly near the squall line,the SOIL hybrid experiment produces large analysis increments of water vapor mixing ratio whereas the RCV hybrid experiment generates very large wind increments.In addition,the assimilation of surface observations also improves the short-range forecasts of surface variables,precipitation,cold pool and the position of the gust front.Further investigations into dynamic and thermodynamic field show that the improvements are related to the increase of the convective instability and modifications of the updraft,the hydrometeor mixing ratio and the 0-6 km wind shear,which benefits from the lasting impact of assimilation of surface observations.But the degrees of modifications are not completely the same,which results in different forecasts in term of convection initiation time,gust front,hourly accumulated precipitation,cold pool and so on.