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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

周志敏 胡扬 康兆萍

周志敏, 胡扬, 康兆萍. 2021. 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[J]. 大气科学, 45(6): 1−21 doi: 10.3878/j.issn.1006-9895.2105.21025
引用本文: 周志敏, 胡扬, 康兆萍. 2021. 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[J]. 大气科学, 45(6): 1−21 doi: 10.3878/j.issn.1006-9895.2105.21025
ZHOU Zhimin, HU Yang, KANG Zhaoping. 2021. Sensitivity of Microphysical Parameterization on the Numerical Simulation of a Meiyu Front Heavy Rainfall Process [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(6): 1−21 doi: 10.3878/j.issn.1006-9895.2105.21025
Citation: ZHOU Zhimin, HU Yang, KANG Zhaoping. 2021. Sensitivity of Microphysical Parameterization on the Numerical Simulation of a Meiyu Front Heavy Rainfall Process [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(6): 1−21 doi: 10.3878/j.issn.1006-9895.2105.21025

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

doi: 10.3878/j.issn.1006-9895.2105.21025
基金项目: 国家自然科学基金项目41620104009、41905071,国家重点研发计划项目2018YFC1507200,湖北省科技发展基金 2018Z05
详细信息
    作者简介:

    周志敏,男,1979年出生,副研究员,主要从事云降水物理和数值模拟研究。E-mail: zhouzm@whihr.com.cn

  • 中图分类号: P458

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

Funds: National Natural Science Foundation of China (Grants 41620104009, 41905071),National Key Research and Development Program of China (Grant 2018YFC1507200), Key Scientific and Technological Development Projects in Hubei Province in China (Grant 2018Z05)
  • 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。
  • 图  1  模式模拟区域,红色实心圆表示模式外层区域中心点

    Figure  1.  Geographical domain used in WRF model runs. The red solid circle indicates the central point of the outer domain

    图  2  2018年6月29日22:00至30日11:00(协调世界时,下同)基于ERA5再分析场的相关物理量时间平均分布:(a)200 hPa风矢量(单位:m s−1)和纬向风速(填色,单位:m s−1);(b)700 hPa风矢量(单位:m s−1)和温度(填色,单位:°C);(c)850 hPa水汽通量(单位:g s−1 hPa−1 cm−1)和水汽通量散度(填色,单位:10−7 g s−1 hPa−1 cm−2

    Figure  2.  The time means (2200 UTC 29 June to 1100 UTC 30 June 2018) of (a) wind vectors (units: m s−1) and zonal wind velocity (shaded; units: m s−1) at 200 hPa, (b) wind vectors (units: m s−1) and air temperature (units: °C) at 700 hPa, and (c) moisture flux (units: g s−1 hPa−1 cm−1) and moisture flux divergence (shaded; units: 10−7 g s−1 hPa−1 cm−2) at 850 hPa based on the ERA5 reanalysis

    图  3  图2,但为不同方案的模拟结果:(a1–a3)Morrison方案;(b1–b3)Thompson方案;(c1–c3)MY方案

    Figure  3.  Same as Fig. 2 but for the model output based on the (a1–a3) Morrison, (b1–b3) Thompson, and (c1–c3) MY microphysical schemes

    图  4  2018年6月29日22:00至30日11:00(a1、a2)Morrison方案、(b1、b2)Thompson方案、(c1、c2)MY方案模拟700 hPa位势高度场的标准差(第一行,单位:gpm)及垂直气流(第二行,单位:m s−1)空间分布

    Figure  4.  Spatial distribution of the standard deviation of the geopotential height (top line, units: gpm) and vertical airflow (bottom line, units: m s−1) at 700 hPa during 2200 UTC 29 June to 1100 UTC 30 June 2018 based on the model output of (a1, a2) Morrison, (b1, b2) Thompson, and (c1, c2) MY microphysical schemes

    图  5  2018年6月29日22:00至30日11:00(a)Morrison方案、(b)Thompson方案、(c)MY方案模拟湖北地区(108.35°E~116.25°E)的时间平均经向环流(风矢图,单位:m s−1)及西风(填色,单位:m s−1)的垂直剖面

    Figure  5.  Vertical section of the time-averaged meridional circulation (vectors, units: m s−1) and zonal wind (shaded, units: m s−1) based on the model output of (a) Morrison, (b) Thompson, and (c) MY microphysical schemes during 2200 UTC 29 June to 1100 UTC 30 June 2018

    图  6  2018年6月29日22:00至30日11:00(a)观测与(b)Morrison方案、(c)Thompson方案、(d)MY方案模拟的13 h累计降水量(填色,单位:mm)比较,红色矩形表示湖北省覆盖区

    Figure  6.  Spatial distribution of the cumulative rainfall in 13 h by (a) observations and base on (b) Morrison scheme, (c) Thompson scheme, and (d) MY scheme during 2200 UTC 29 June to 1100 UTC 30 June 2018. The area covered by the red rectangle indicates the domain of the Hubei Province

    图  7  2018年6月29日22:00至30日11:00观测(OBS)与Morrison方案、Thompson方案、MY方案模拟降水的小时降水率(简称RR,单位:mm h−1)的概率密度(PDF)比较

    Figure  7.  PDFs (probability density functions) comparison of the rain rate (RR) between the observations and WRF simulations using the three microphysical schemes (Morrison, Thompson, and MY) during 2200 UTC 29 June to 1100 UTC 30 June 2018

    图  8  2018年6月29日22:00至30日11:00降水的(a)小时区域(图6红色方框所示区域)平均(单位:mm)及(b)雨滴含量(单位:g m−3)平均值的时间变化曲线

    Figure  8.  Time series of the (a) area-averaged (area indicated by red rectangle in Fig.6) hourly rainfall intensity (units: mm) and (b) rainwater content (units: g m−3) during 2200 UTC 29 June to 1100 UTC 30 June 2018

    图  9  2018年6月29日22:00至30日11:00 Morrison方案(左列)、Thompson方案(中间列)以及MY方案(右列)中水成物的区域平均值随时间演变:冰晶(第一行);雪粒子(第二行);霰粒子(第三行)。填色表示冰相粒子含量(单位:g m−3);黑色实线为平均温度,等值线从0°C~−40°C,间隔10°C;红色实线表示云滴含量,等值线从5~35 g m−3,间隔5 g m−3;蓝色实线表示雨滴含量,等值线从5~55 g m−3,间隔5 g m−3

    Figure  9.  Time evolution (during 2200 UTC 29 June to 1100 UTC 30 June 2018) of area-averaged vertical profiles of ice (top line), snow (second line), and graupel (bottom line) hydrometeors by Morrison (left column), Thompson (middle column), and MY (right column) scheme, respectively. The shaded area indicates the distribution of ice phase hydrometeors (units: g m−3). The black solid lines indicates the average temperature, and the contours are from 0°C to −40°C with 10°C of intervals. The red dashed lines indicate the cloud droplet content (units: g m−3), and the contours are from 5 g m−3 to 35 g m−3 with 5 g m−3 of intervals. The blue dashed lines indicate the raindrop content (units: g m−3), and the contours are from 5 g m−3 to 55 g m−3 with 5 g m−3 of intervals

    图  10  2018年6月29日22:00至30日11:00的主要雨滴源汇项空间平均值(单位:g m−3)的时间变化:(a)Morrison方案;(b)Thompson方案;(c)MY方案

    Figure  10.  Time series of the volumetrically averaged content (units: g m−3) of the main source and sink terms of rain during 2200 UTC 29 June to 1100 UTC 30 June 2018 by (a) Morrison, (b) Thompson, and (c) MY schemes

    图  11  不同方案的雨滴主要源汇项总量(单位:g m−3)区域平均值的的垂直分布:(a)Morrison方案;(b)Thompson方案;(c)MY方案

    Figure  11.  Vertical profiles of area-averaged content (unit: g m−3) of the key sink and source termsof raindrop by (a) Morrison, (b) Thompson, and (c) MY schemes

    图  12  2018年6月29日22:00至30日11:00 Morrison方案(第一行)、Thompson方案(第二行)以及MY方案(第三行)中源项Mlt(左列)、CLcr(中间列)及汇项Evap(右列)的高度平均分布,单位:g m−3

    Figure  12.  Distribution of the height-averaged total amount of Mlt (left column), CLcr (middle column) source terms, and (c) Evap sink term (right column) of rain during 2200 UTC 29 June to 1100 UTC 30 June 2018 by Morrison (top line), (b) Thompson (second line), and MY (bottom line) schemes, units: g m−3

    图  13  不同方案的云滴主要源汇项总量(单位:g m−3))区域平均值的的垂直分布:(a)Morrison方案;(b)Thompson方案;(c)MY方案

    Figure  13.  Vertical profiles of area-averaged content (unit: g m−3) of the key sink and source termsof cloud droplet by (a) Morrison, (b) Thompson, and (c) MY schemes

    图  14  2018年6月29日22:00至30日11:00不同方案冰相粒子主要(a)汇项Mlt及源项(b)VD、(c)Col1、(d)Col2空间平均值(单位:g m−3)的时间变化

    Figure  14.  Time series of the volumetrically averaged content (units: g m−3) of the distribution of the height-averaged total amount of the (a) sink term Mlt and source term (b) VD, (c) Col1, (d) Col2 of rain during 2200 UTC 29 June to 1100 UTC 30 June 2018 by different schemes

    图  15  图11相似,但为云滴主要源汇项(CLcr, Col2, Cond)

    Figure  15.  Same as Fig.11 but for key sink and source of the cloud droplet (CLcr, Col2, and Cond)

    图  16  不同方案的冰晶、雪和霰粒子的凝华/升华项总量(单位:g m−3))区域平均值的的垂直分布:(a)Morrison方案;(b)Thompson方案;(c)MY方案

    Figure  16.  Vertical profiles of area-averaged content (unit: g m−3) of the the deposition/sublimation of ice, snow, and graupel by (a) Morrison, (b) Thompson, and (c) MY schemes

    图  17  2018年6月29日22:00至30日11:00(a)Morrison、(b)Thompson、(c)MY方案主要凇附项空间平均值(单位:g m−3)的时间变化

    Figure  17.  Time series of the volumetrically averaged content (units: g m−3) of riming terms during 2200 UTC 29 June to 1100 UTC 30 June 2018 by (a) Morrison, (b) Thompson, (c) MY schemes

    图  18  图11,但为雪粒子(霰粒子)搜集雨滴(云滴)的增长(CLcs、CLrs、CLcg和CLrg)

    Figure  18.  Same as Fig.11, but for the accretion (CLcs, CLrs, CLcg, and CLrg) of raindrops (cloud droplets) by the snow (graupel)

    表  1  模式参数设置

    Table  1.   The settings of model parameters

    模式选项参数设置
    嵌套双重嵌套
    网格精度外层9 km,内层3 km
    时间分辨率30 s,10 s
    网格设置601×481,526×391
    投影Mercator
    背景场ERA5
    短波辐射方案Dudhia (Dudhia, 1989)
    长波辐射方案rrtm (Mlawer et al., 1997)
    边界层参数化方案ACM2 (Pleim and Jonathan, 2007)
    积云对流参数化方案
    (外层网格)
    Kain-Fritsch (Kain and John, 2004)
    微物理参数化方案(1)Morrison (Morrison et al., 2009)
    (2)Thompson (Thompson et al., 2008)
    (3)Milbrant-Yao (MY, Milbrandt and Yao, 2005a, 2005b)
    地表方案Monin-Obukhov (Monin and Obukhov, 1954)
    陆面参数化方案Noah (Niu et al., 2011)
    下载: 导出CSV

    表  2  本文所用的微物理过程

    Table  2.   The microphysical source/sink terms

    简称含义
    CLcr雨滴对云滴的搜集碰并作用(acrretion of cloud droplet by raindrop)
    Mlt冰相粒子融化(包括所有类别冰相粒子)(melting of ice phase hydrometeors)
    Evap雨滴蒸发 (evaporation of raindrop)
    Col1冰相粒子与雨滴之间碰并 (accretion of raindrop by ice phase hydrometeors)
    Col2冰相粒子与云滴碰并 (accretion of cloud droplet by ice phase hydrometeors)
    Auto云滴向雨滴的自动转换 (auto conversion from cloud droplet to raindrop)
    VD冰相粒子凝华/生化(贝吉龙过程)(deposition/sublimation of ice phase hydrometeors)
    CLcs雪粒子搜集云滴增长(accretion of cloud droplet by snow)
    CLcg霰粒子搜集云滴增长 (accretion of cloud droplet by graupel)
    CLrs雪粒子搜集雨滴增长 (accretion of raindrop by snow)
    CLrg霰粒子搜集雨滴增长 (accretion of raindrop by graupel)
    ZVI冰晶凝华/升华 (deposition / sublimation of ice)
    ZVS水汽凝华成雪粒子 (deposition / sublimation of snow)
    ZVG水汽凝华成霰粒子 (deposition / sublimation of graupel)
    Cond水汽凝结成云滴 (condensation of vapor)
    下载: 导出CSV
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  • 收稿日期:  2021-02-03
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