中文摘要：

利用自主构建的针对风暴尺度资料同化的WRF-EnSRF同化系统同化多普勒天气雷达资料,检验其在2003年一次梅雨锋暴雨以及2009年一次强对流天气过程的同化性能。结果显示,在两个例中该同化系统均表现出有效的同化能力,经过60 min同化的分析场和以该分析场集合做初值的30 min的集合预报结果都比较接近实际观测。在同化过程中,径向速度和反射率因子的观测增量均方差分别达到3～4 m/s和9～11 dBz。本文考察了初始扰动时全场扰动与对流区域局部扰动,以及扰动环境风场与否对同化效果的影响。试验结果表明,对流区局部扰动相对于全场扰动并没有提高同化效果;对于尺度较大的梅雨锋暴雨来说,扰动环境风场时同化效果较好。为了考察分析场在降水预报中的表现,在暴雨个例中,以分析场为初值做6 h降水预报,经过同化的集合预报和确定性预报结果都比没有经过同化的控制试验预报结果准确。

英文摘要：

An Ensemble Square Root Filter（EnSRF） data assimilation system concerning storm scale issues is built under the Weather Research Forecast（WRF） model framework and is tested with different types of severe weather events to examine the performance of this data assimilation system in convective scale application.One heavy rainfall event（5 July 2003） and one strong convective event（5 June 2009） are selected for conducting the tests.Results show that the analysis ensemble means at 60 min in both cases and the 30 min forecasts from these analyses are close to the observations.The standard deviations of increment in observation space reach 3 m/s to 4 m/s and 9 dBz to 11 dBz for radial velocity and reflectivity respectively.The impacts of different initial perturbation strategies are investigated in this paper,namely,adding initial perturbations to the entire computational domain and to the limited region around the observed storm area,perturbations to the environmental wind field or not.Results show that perturbing the limited region does not improve the analysis results compared to perturbing the entire forecast domain,while perturbing the environment wind field produces better results in the Meiyu heavy rain case,indicating the more significant impacts of environment uncertainty on relatively larger scale weather events.The impacts of data assimilation on precipitation forecast are also examined.In the heavy rain case,the forecast results show that within 6 h,both the single forecast and the ensemble forecast initialized from analysis obtained through the assimilation of radar observations are better than the corresponding result in the experiment without data assimilation.The above-mentioned experiment results indicate that this data assimilation system has the ability to be applied in storm scale issues.