The Application Of Doppler Radar Data Assimilation In The Squall Line Simulation

Using Mesoscale ARPS model and its data assimilation system ADAS and CCA which were developed at the Center for Analysis and Prediction of Storms, the Univer-sity of Oklahoma, six Doppler radars cardinal data were assimilated and comparative experiments were conducted for the squall line process which occurred in Central and southern Fujian Province on 22 March 2005, tested the effect of Doppler radar data on the forecast of squall line. with 1 hour assimilation window, designed a six rapid cycling assimilation of radar data experiments,to study the effect of Doppler radar data reflectivity and radial velocity and Assimilation of different cyclic frequency on the initial field and on the forecast of squall line The main results are as follows:1. Using Cyclic radar data assimilation techniques, Radar data assimilation could improve the initial field in the model.It was found that wind field, vertical velocity and cloud water, and other water substance field adjustment were more obvious on the initial field. Radar data assimilation could Improve the structure of the squall line simulation.2. Assimilating both radial wind and reflectivity data adjusted more significant of the initial field than single radial wind or reflectivity data. Simulated Composite reflectivity were more close to actual radar reflectivity. By comparing the experiment ,It found that Radial wind assimilation mainly improve initial wind field and increase the small-scale information. But the equivalent temperature and water vapor field were no significant change. Assimilating reflectivity data adjusted more significant of cloud water and rain water. But on the wind field adjustment is not obvious.Radar reflectiv-ity play more important on the initial enhancement of the vertical velocity than radial velocity3. ARPS model have a stronger ability to simulate squall line process, Radar data assimilation can Reduce the strong squall line simulation in time and space er-rors, ARPS model can improve numerical prediction; Using Cyclic multiple radar data assimilation techniques, the model is able to improve short-term forecasting of severe convective weather. in real-time applications.4. Assimilation of different frequencies had a positive effect on the assimilation results. In 1 hour assimilation cycle window, every 15 minutes interval radar data as- similation better than every 30 minutes, every 60 minutes. This suggested that radar data assimilation into the model the higher the frequency, better information to improve model initial fields, the more it can improve the forecasting ability of the squall line. No radar data assimilation experiment was the worst. on the initial field and on the forecast of squall line Simulated by ARPS model.