Numerical experiments demonstrate that WRF 3D-Var can successfully assimilate Doppler radial velocity and reflectivity from multiple radar sites, and extract useful information from the radar data to initiate the squall line convective system. Assimilation of both radial velocity and reflectivity results in sound analyses that show adjustments in both dynamical and thermo-dynamical fields consistent with the WRF 3D-Var balance constraint and background error correlation. The cycling of the Doppler radar data from the 12 radar sites at 2100 UTC 12 and 0000 UTC 13 June produces a more detailed mesoscale structure of the squall line convection in the model initial conditions at 0000 UTC 13 June. Evaluations of the ARW QPF skills with initialization via Doppler radar data assimilation demonstrate that the more radar data in temporal and spatial dimensions are assimilated, the more positive impact on the QPF skill is. Assimilation of both radial velocity and reflectivity has more positive impact on the QPF skill than assimilation of either radial velocity or reflectivity only. The improvement of the QPF skill with multiple radar data assimilation is more clearly observed in heavy rainfall than in light rainfall.
In addition to the improvement of the QPF skill, the simulated structure of the squall line is also enhanced by the multiple Doppler radar data assimilation in the WRF 3D-Var cycling experiment. The vertical airflow pattern shows typical characteristics of squall line convection. The cold pool and its related squall line convection triggering process are better initiated in the WRF 3D-Var analysis and simulated in the ARW forecast when multiple Doppler radar data are assimilated.