doi:  10.3878/j.issn.1006-9895.1708.17187
多普勒天气雷达资料同化对冬季暴雨模拟的影响研究

The Impact of Doppler Radar Data Assimilation on the Simulation of a Winter Heavy Rainfall
摘要点击 853  全文点击 78  投稿时间:2017-07-04  修订日期:2017-08-26
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基金:  国家自然科学基金
中文关键词:  四维集合变分同化  雷达资料  冬季暴雨  初始偏差演变
英文关键词:  four-dimensional ensemble variational assimilation  radar data  winter heavy rainfall  initial deviation growth evolution
           
作者中文名作者英文名单位
杨雨轩yangyuxuan国防科技大学气象海洋学院
张立凤zhanglifeng国防科技大学气象海洋学院
张斌解放军61741部队
李逍解放军78127部队
引用:杨雨轩,张立凤,张斌,李逍.2018.多普勒天气雷达资料同化对冬季暴雨模拟的影响研究[J].大气科学
Citation:yangyuxuan,zhanglifeng.2018.The Impact of Doppler Radar Data Assimilation on the Simulation of a Winter Heavy Rainfall[J].Chinese Journal of Atmospheric Sciences (in Chinese)
中文摘要:
      采用基于本征正交分解的四维集合变分同化(POD-4DEnVar)方法,利用梅州站的多普勒天气雷达资料和NCEP资料,对2015年12月9日一次华南冬季暴雨过程进行同化试验,探讨了同化不同的雷达观测要素对暴雨模拟的影响。结果表明:同化多普勒天气雷达资料有利于削弱控制试验偏强降水的模拟结果,改善降水分布结构;同化不同的雷达观测要素得到的模拟结果不同,同时同化径向风和反射率的降水模拟结果最好。同化试验对降水模拟结果的改善主要通过调整初始时刻的风场和水汽条件来实现,一方面减弱偏南风和偏东风在暴雨区的辐合,阻碍海上暖湿气流对暴雨区的水汽输送,另一方面直接削弱暴雨区的水汽条件,大幅降低水汽混合比。同化试验相对于控制试验的同化增量远大于不同雷达观测要素的同化试验之间的分析场差异,这表明同化不同的雷达观测要素对初始风场和水汽条件的调整呈现类似的特征。虽然同化试验的初始场存在较小的差异,但随着模式积分,16h后模拟降水出现了明显差异。分析同化试验之间的初始偏差演变发现,850-700hPa的平均垂直速度偏差和雨水混合比偏差在模式积分至16h开始急剧增长,这种变量偏差的急剧增长与逐时降水偏差的迅速增加一致,是降水偏差增长的直接原因。另外,这两个变量偏差的增大,也伴随着偏差能量的增大,变量偏差增长最明显的时段为偏差能量增幅最大的时段,且偏差能量迅速增长早于变量偏差和降水偏差的迅速增长,变量偏差增长最明显的区域为偏差能量梯度较大的区域。
Abstract:
      Based on the Proper Orthogonal Decomposition-based four-dimensional ensemble variational assimilation (POD-4DEnVar) method, the impact of the assimilation of different radar data on the simulation of a heavy rainfall is discussed. They are tested with a heavy rainfall process that occurred in Guangdong Province on 9 December 2015 with NCEP reanalysis data and Next-Generation Weather Radar data of Meizhou. The results show that assimilation of the Doppler radar data are beneficial to weaken the superficial precipitation simulated by the control experiment and improve 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 will obtain the best results of the precipitation simulation. The improvement of the simulation results of the assimilation experiment is mainly achieved by adjusting the wind field and the water vapor condition at the initial time. The radar data assimilation on the one hand weakens the convergence of the southerly flow and the easterly flow in the heavy rain zone, indirectly hindering the water vapor transport of the warm humid air to the storm area, and on the other hand directly weakens the water vapor conditions of the heavy rainfall by reducing the water vapor mixing ratio. The assimilation increments are much larger than the differences among the 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 slight differences of the initial fields among the assimilation experiments exist, there is significant difference in precipitation simulation when the model integration time reaches 16th hour. The evolution of the initial deviations in different assimilation experiments is analyzed and it is found that the average deviations of the 850-700hPa vertical velocity and rainwater mixing ratio begin to increase rapidly when the model integration time reaches 16th hour, and the rapid increase of the variable deviation is consistent with the rapid increase of the precipitation deviation, which is the direct cause of the increase of the precipitation deviation. At the same time, with the increase of the deviations of the two variables, the difference total energy also develops. The deviations of the two variables have the fastest growth when the difference total energy develops the 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.
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