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华南暴雨模拟中物理过程参数化不确定性的量化分析

Quantitative Analysis of Parameterized Uncertainty of Physical Processes in Rainstorm Simulation over South China

  • 摘要: 模式中物理过程的不确定性对预报准确率的影响受到越来越多的关注。本文使用多因素方差分析以及Tukey’s检验来量化与物理过程参数化相关的模式不确定性并挑选出最优参数化方案组合。以2020年5月21-22日一次华南暴雨为例,选择与降水密切相关的云微物理方案、边界层方案以及积云对流方案共进行了80组试验。方差分析结果显示云微物理方案对于降水模拟结果以及模式预报效果最为重要,且不同物理过程之间的相互作用对模拟结果的影响不可被忽略。利用Tukey’s检验对比同一物理过程中不同参数化方案的差异,并基于泰勒评分挑选出最优参数化方案组合,为WSM7云微物理方案+YSU边界层方案+GF积云对流方案。除此之外,本文对比了不同云微物理方案的差异,从水成物以及微物理转换过程出发,分析了云微物理方案差异对降水模拟误差的影响。发现雹在此次极端降水的模拟中扮演重要角色;雨滴比含水量的变化主要源自冰相粒子的融化项;而雨滴蒸发量通过潜热吸收的方式影响冷池强度,进而影响后续的降水传播,并最终作用于强降水落区的分布。

     

    Abstract: More and more attention has been paid to the influence of the uncertainty of the physical processes on the prediction accuracy. In this paper, multivariate analysis of variance and Tukey"s test are used to quantify the model uncertainty related to the parameterization of physical processes and to select the optimal parameterization scheme combination. Taking a rainstorm in South China from May 21 to 22, 2020 as an example, the microphysics scheme, boundary layer scheme and cumulus convective scheme, which are closely related to precipitation, are selected to carry out 80 sets of experiments. The results of multivariate analysis of variance show that the microphysics scheme is the most important for precipitation simulation results and model prediction results, and the interactions between different physical processes cannot be ignored. Tukey"s test is used to compare the discrepancy among different parameterization schemes, and the optimal parameterization scheme combination is selected, which is WSM7 scheme + YSU scheme + GF scheme. In addition, this paper compares the differences of different microphysics schemes, and analyse the influence of the differences of microphysics schemes on the precipitation simulation error from the perspective of hydrometeors and microphysics conversion processes. The results show that hail plays an important role in the simulation of the extreme precipitation. The change of rainwater mixing ratio is mainly due to the melting term of ice particles. The evaporation of rain affects the intensity of cold pool through latent heat absorption, and then affects the subsequent precipitation propagation, finally affects the distribution of heavy precipitation.

     

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