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利用美国俄克拉何马大学风暴分析和预测中心开发的中尺度ARPS模式及其资料分析和同化系统ADAS,将山东省济南齐河、临沂和连云港3部多普勒雷达基数据资料同化进ARPS模式中,对山东“4.28”飑线过程进行了数值对比试验。结果发现,模式采用热启动的方式可以模拟出此次飑线过程,对飑线造成的降水的强度和落区预报也较好。雷达资料同化对飑线地面中尺度系统的模拟有明显的改进作用,尤其是在前2~3 h效果非常明显,使模拟的地面雷暴高压和风场更接近实况。使用雷达资料进行同化循环,连续地将多部多普勒雷达资料同化到数值模式中,可以明显改进对飑线系统结构的模拟,较初始时刻同化雷达资料对飑线的模拟效果更好。因此,使用雷达资料进行快速分析和同化进行强对流天气预报是可行的,但模拟的降水偏强,这与雷达资料同化对于大范围暴雨预报的改进作用是不同的。
Based on the mesoscale ARPS model developed by the Storm Analysis and Prediction Center of the University of Oklahoma and its data analysis and assimilation system ADAS, three Doppler radar-based data from Qihe, Linyi and Lianyungang in Shandong Province were assimilated into the ARPS model In the Shandong “4.28 ” 飑 line process numerical comparison test. The results show that the model using hot start mode can simulate the process of the 飑 line, the precipitation caused by the 飑 line intensity and falling area prediction is also better. Radar data assimilation has a significant improvement on the simulation of meso-scale ground mesoscale system, especially in the first 2 ~ 3 h, which makes the simulated surface thunderstorm high pressure and wind field more realistic. The use of radar data for assimilation cycle and the continuous assimilation of multi-Doppler radar data to numerical model can significantly improve the simulation of the system of 飑-line system, which is better than the simulation of 飑 line by assimilating radar data at the initial time. Therefore, it is feasible to use radar data for rapid analysis and assimilation to forecast heavy convective weather, but the simulated precipitation is stronger, which is different from the radar data assimilation for the improvement of heavy rainstorm forecast.