双月刊

ISSN 1006-9895

CN 11-1768/O4

一次梅雨锋暴雨过程数值模拟的云微物理参数化敏感性研究
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中国气象局武汉暴雨研究所

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国家自然基金项目4162010400,国家重点研发计划项目 2018YFC1507200,湖北省科技发展基金项目2018Z05,国家自然基金项目41905071;


Research on Sensitivity of Microphysical Parameterization on Numerical Simulation on a Meiyu Front Heavy Rainfall Process
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Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research,Institute of Heavy Rain,China Meteorological Administration

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    摘要:

    梅雨锋暴雨中的云微物理过程对降水的演变有着重要影响。本文通过WRF(3.4.1)模式,针对2018年6月29日至30日一次梅雨锋背景下的暴雨过程进行数值模拟,分别采用了Morrison、Thompson和MY方案进行对比分析,结果发现:(1)三个方案模拟的背景场在天气尺度上,都与ERA5再分析资料一致,能够模拟出有利于强降水发生的环流场。云微物理过程对梅雨期暴雨的局地环流有着显著影响,不同方案存在明显差异,本次过程中,Thompson方案模拟出更强的局地环流系统变率和上升气流。三个方案的模拟降水均有所夸大,小时降水率始终大于观测值。冰相粒子融化或雨滴搜集云滴的高估可能是造成降水模拟值偏强的重要原因之一,总体来看,Morrison方案的模拟效果相对最优。(2)冰相粒子融化、雨滴收集云滴是雨滴增长的关键源项,蒸发则是其最重要的汇项。总的来说,雨滴对云滴的收集量大于冰相粒子融化。但上述过程在不同方案中存在空间上的差异,从而使得模拟降水的空间分布存在差异。(3)Thompson方案中,冰相粒子融化量最大,雨滴蒸发项显著大于其它两个方案,在底层表现得最为明显。同时,该方案水汽凝结效应最强,使得雨滴收集更多云滴。该方案模拟的雨滴最多,降水最强。该方案中凝华的主要产物为雪,且其在与过冷水碰并增长过程中占主导地位,故模拟的雪最多。4)Morrison方案中,水汽主要凝华为雪和少量霰(冰晶忽略不计);Thompson方案中水汽基本凝华为雪,其它冰相粒子极少;MY方案中,水汽主要凝华为雪和冰晶,冰晶总量略少于雪,但显著大于其它方案。5)云滴在凇附过程中的总体贡献大于雨滴。Morrison和 MY方案中,霰粒子收集云滴增长的量均最大。Morrison方案中,其它凇附过程不同程度发挥作用,而MY方案中,其它凇附过程几乎可忽略不计。并且,霰粒子收集云滴的增长量大于凝华过程产生的雪粒子总量。贝吉龙及凇附效应的差异,是不同方案中冰相粒子分布差异的关键原因之一。

    Abstract:

    Microphysical processes in Meiyu front rainfall have an important effect on evolution of precipitation. Based on WRF (version 3.4.1) model, one Meiyu front heavy rainfall case from 29 to 30 June is analyzed with 3 different microphysics schemes (Morrison, Thompson and MY). The main findings are as follows. (1) The general large-scale circulation of the Meiyu rainfall case could be reasonably reproduced by all the three experiments with different microphysics schemes, which was consistent with ERA5 reanalysis data. The local circulation during Meiyu front heavy rainfall was significantly influenced by microphysical processes and the differences in the local features between different experiments were evident. The local circulation and updraft in the Thompson experiment were stronger than those in the other two schemes. Precipitation in all the model output was overestimated and the hourly rain rate was always greater. The overestimation of melting of ice phase hydrometeors or accretion of cloud droplet by raindrop was one of the most important causes to the overestimation of modeled precipitation. On the whole, Morrison run performed relatively better. (2)Melting of ice phase hydrometeors and accretion of cloud droplet by rain drop were the key source terms to the growth of rain drop. And evaporation process was the most important sink term. On the whole, raindrop collecting cloud droplet contributed more than melting of ice phase hydrometeors to the growth of raindrop. However, for each scheme, differences of these microphysical process terms leaded to the difference of modeled precipitation in distribution. (3) Thompson run produced the largest amount of melting of ice phase hydrometeors and evaporation (especially in low level). At the same time, it produced the largest amount of condensation which leaded to more collection of cloud droplet by raindrop. Therefore, Thompson run produced most raindrop and rainfall. The predominant product through deposition and riming process was snow and the largest amount of snow was produced. (4) Through Bergeron process, Morrison run produced more snow than graupel (ice particles nearly could be neglected), Thompson run produced predominant snow and MY run produced more snow than ice particles (graupel nearly could be neglected). The largest amount of produced ice particles in MY run through the process leaded to more ice particles than that in other schemes. (5) Cloud droplet contributed more than raindrop in riming process. In Morrison and Thompson schemes, the amount of graupel collecting cloud droplet was larger than that through other riming processes. Other riming processes contributed the growth of graupel in different degrees in Morrison run, while other riming processes nearly could be neglected compared to graupel collecting cloud droplet. And MY run produced larger amount of snow growth by deposition. Therefore, differences of Bergeron and riming processes in all three schemes lead to the differences in ice phase hydrometeors distribution.

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  • 收稿日期:2021-02-03
  • 最后修改日期:2021-05-06
  • 录用日期:2021-05-07
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