Impact of Doppler Radar Data Assimilation on the Simulation of a Heavy Winter Rainfall

Using the POD-4DEnVar (Proper Orthogonal Decomposition-based four-dimensional ensemble variational assimilation) method, the impact of assimilation of different radar data on the simulation of a heavy rainfall is discussed. A suite of experiments to simulate a heavy rainfall process that occurred in Guangdong Province on 9 December 2015 have been conducted using NCEP reanalysis data and next-generation weather radar data collected at Meizhou. The results show that assimilation of the Doppler radar data is helpful to reduce the overestimation of precipitation simulated by the control experiment and improve the simulation of the precipitation structure. The simulation results obtained by assimilating different types of radar data are different, and the assimilation of both radial velocity and reflectivity yields the best result for precipitation simulation. The improvement in the simulation by the assimilation experiment is mainly achieved by adjusting winds and water vapor condition at the initial time. On the one hand, radar data assimilation weakens the convergence of the southerly and easterly flow in the heavy rain zone, which indirectly hinders water vapor transport associated with the warm moist flow to the storm area; on the other hand, radar data assimilation directly affects the water vapor condition related to the heavy rainfall by reducing the water vapor mixing ratio. The assimilation increments are much larger than the differences between data used in different assimilation experiments, which shows that assimilating different types of radar data has similar adjustment of the initial wind field and water vapor condition. Although there exist slight differences in the initial fields among the assimilation experiments, significant differences in precipitation simulation appear after about 16 hours of integration. The evolution of the initial deviations in different assimilation experiments is analyzed. It is found that average deviations of the 850-700 hPa vertical velocity and rainwater mixing ratio begin to increase rapidly when the model integration time reaches the 16th hour, and the rapid increases in these deviations are consistent with the rapid increase of precipitation deviation, indicating they are directly responsible for the increase in precipitation deviation. At the same time, with the increase in the deviations of the two variables, the difference total energy also develops. The deviations of the two variables grow the fastest when the difference total energy develops most rapidly, and the rapid growth of the difference total energy is preceded by that of the deviations of the variables and precipitation. Also, the region where the two variable deviations grow the most evidently is the area where the gradient of difference total energy is large.