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  被引量:7

Sensitivity of Microphysical Parameterization on the Numerical Simulation of a Meiyu Front Heavy Rainfall Process

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作  者:周志敏[1,2] 崔春光 胡扬[1] 康兆萍 ZHOU Zhimin;CUI Chunguang;HU Yang;KANG Zhaoping(Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research,Institute of Heavy Rain,China Meteorological Administration,Wuhan 430205;State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,Beijing 100081)

机构地区:[1]中国气象局武汉暴雨研究所暴雨监测预警湖北省重点实验室,武汉430205 [2]中国气象科学研究院灾害天气国家重点实验室,北京100081

出  处:《大气科学》2021年第6期1292-1312,共21页Chinese Journal of Atmospheric Sciences

基  金:国家自然科学基金项目41620104009;国家重点研发计划项目2018YFC1507200;湖北省科技发展基金2018Z05;灾害天气国家重点实验室开放课题2021LASW-A03。

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模式(3.4.1版本),针对2018年6月29~30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云微物理参数化方案进行对比分析,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、雨滴搜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,雨滴对云滴的搜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,使得雨滴搜集更多云滴。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,霰粒子搜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,霰粒子搜集云滴的�Microphysical processes in the Meiyu front rainfall have an important effect on the evolution of precipitation.Based on the WRF(version 3.4.1)model,one Meiyu front heavy rainfall case from 29 to 30 June is analyzed with three different microphysics schemes(Morrison,Thompson,and MY).The main findings are as follows.(1)The general largescale circulation of the Meiyu rainfall case could be reasonably reproduced by all three experiments with different microphysics schemes,which was consistent with the ERA5 reanalysis data.The local circulation during the 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 the melting of ice phase hydrometeors or the accretion of cloud droplets by raindrops was one of the most important causes of the overestimation of the modelled precipitation.On the whole,the Morrison run performed relatively better.(2)The melting of ice phase hydrometeors and the accretion of cloud droplets by the raindrop were the key source terms to the growth of the raindrop.Moreover,the evaporation process was the most important sink term.On the whole,the raindrop collecting cloud droplet contributed more than the melting of ice phase hydrometeors to the growth of the raindrop.However,for each scheme,the differences of these microphysical process terms led to the difference of the modelled precipitation in distribution.(3)The Thompson run produced the largest amount of melting of ice phase hydrometeors and evaporation(especially in the low level).At the same time,it produced the largest amount of condensation that led to more collection of cloud droplets by raindrops.Therefore,the Thompson run produced the most raindrop and rainfall.The predominant product through the

关 键 词:梅雨锋暴雨 数值模拟 云微物理参数化 源汇项 

分 类 号:P458[天文地球—大气科学及气象学]

 

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