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2014年南京青奥会开幕式日降水过程数值模拟研究

查思佳 张慧娇 李逍潇 花少烽 陈宝君

查思佳, 张慧娇, 李逍潇, 等. 2020. 2014年南京青奥会开幕式日降水过程数值模拟研究[J]. 大气科学, 44(6): 1258−1274 doi: 10.3878/j.issn.1006-9895.2002.19200
引用本文: 查思佳, 张慧娇, 李逍潇, 等. 2020. 2014年南京青奥会开幕式日降水过程数值模拟研究[J]. 大气科学, 44(6): 1258−1274 doi: 10.3878/j.issn.1006-9895.2002.19200
ZHA Sijia, ZHANG Huijiao, LI Xiaoxiao, et al. 2020. Numerical Simulation of Precipitation Processes during the Opening Ceremony of the Nanjing 2014 Youth Olympic Games [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(6): 1258−1274 doi: 10.3878/j.issn.1006-9895.2002.19200
Citation: ZHA Sijia, ZHANG Huijiao, LI Xiaoxiao, et al. 2020. Numerical Simulation of Precipitation Processes during the Opening Ceremony of the Nanjing 2014 Youth Olympic Games [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(6): 1258−1274 doi: 10.3878/j.issn.1006-9895.2002.19200

2014年南京青奥会开幕式日降水过程数值模拟研究

doi: 10.3878/j.issn.1006-9895.2002.19200
基金项目: 国家自然科学基金项目41775132,西北区域人工影响天气能力建设项目ZQC-R18210
详细信息
    作者简介:

    查思佳,女,1995年出生,硕士研究生,从事云降水物理与人工影响天气研究。E-mail: mg1728003@smail.nju.edu.cn

    通讯作者:

    陈宝君,E-mail: chenbj@cma.gov.cn

  • 中图分类号: P426

Numerical Simulation of Precipitation Processes during the Opening Ceremony of the Nanjing 2014 Youth Olympic Games

Funds: National Natural Science Foundation of China (Grant 41775132), Weather Modification Capacity Construction Program of Northwest China (Grant ZQC-R18210)
  • 摘要: 为评估2014年南京青奥会开幕式日的人工催化消减雨作业效果,利用中尺度数值模式WRF对当日的云降水过程和催化作业开展数值模拟。本文系第一部分工作。首先对常用的八种云微物理方案的降水模拟效果进行评估,进一步选取Thompson和Milbrandt-Yau两个微物理方案对此次降水过程的云系结构和降水形成机制进行对比分析。模拟结果表明,采用Thompson和Milbrandt-Yau两个方案模拟的云系结构和降水形成的微物理机制是一致的。开幕式当天影响奥体场馆的降水由弱的积层混合云系产生,降水过程以冰相微物理过程为主。雪的融化是雨水的主要源项,Thompson方案中雪的融化对雨水的贡献率为72%,Milbrandt-Yau方案为60%,蒸发则是雨水的主要汇项,Thompson方案中蒸发对雨水的消耗率达94%,Milbrandt-Yau方案为95.6%。
  • 图  1  2014年8月16日00:00(a)500 hPa和(b)700 hPa天气形势图,黑色等值线表示位势高度,单位:gpm

    Figure  1.  Synoptic weather patterns at 0000 UTC August 16, 2014: (a) 500 hPa; (b) 700 hPa. Black contours denote the geopotential height, units: gpm

    图  2  2014年8月16日南京奥体中心测站实测的地面10 min降水量随时间变化

    Figure  2.  10-min precipitation as a function of time measured at the Nanjing Olympic Sports Center station on August 16, 2014

    图  3  南京站2014年8月16日00:00(第一行)和12:00(第二行)探空曲线:(a, c)层结曲线(实线为温度,虚线为露点,灰色粗实线为相对湿度);(b, d)环境风廓线(实线为u分量,正值代表西风;虚线为v分量,正值代表南风)

    Figure  3.  Sounding curves at 0000 UTC (first line) and 1200 UTC (second line) on August 16, 2014, at Nanjing station: (a, c) Stratification curve (temperature: solid line; dew point: dashed line; and relative humidity: gray thick solid line); (b, d) corresponding u (west wind, solid line) and v (south wind, dashed line) components of the horizontal wind

    图  4  模拟区域。黑点表示南京奥林匹克体育中心场馆位置

    Figure  4.  Model domain. The black dot denotes the Nanjing Olympic Sports Center (NOC) location

    图  5  南京站2014年8月16日12:00(a)温度和(b)露点温度垂直廓线的观测与不同微物理方案的模拟结果

    Figure  5.  Simulated profiles with different cloud microphysics schemes and observed profiles of (a) temperature and (b) dew point temperature at the Nanjing station at 1200 UTC on August 16, 2014

    图  6  2014年8月16日05:00(e)卫星观测云场(填色表示云量,单位:%)与(a–d, f–i)不同微物理方案模拟云场(填色表示云量,单位:kg m−2)对比:(a)Eta;(b)Lin;(c)WSM6;(d)Goddard;(f)Thompson;(g)WDM6;(h)Milbrandt-Yau;(i)NSSL

    Figure  6.  Cloud fields simulated (shaded, units: kg m−2) with (a–d, f–i) different cloud microphysics schemes compared with (e) observations (shaded, units: %) at 0500 UTC on August 16, 2014: (a) Eta; (b) Lin; (c) WSM6; (d) Goddard; (f) Thompson; (g) WDM6; (h) Milbrandt–Yau; (i) NSSL

    图  7  2014年8月16日05:00不同微物理方案模拟的组合雷达反射率与(e)观测雷达组合反射率(单位:dBZ)对比:(a)Eta;(b)Lin;(c)WSM6;(d)Goddard;(f)Thompson;(g)WDM6;(h)Milbrandt-Yau;(i)NSSL

    Figure  7.  Composite radar reflectivity factor (units: dBZ) simulated with different cloud microphysics schemes compared with (e) observations at 0500 UTC on August 16, 2014: (a) Eta; (b) Lin; (c) WSM6; (d) Goddard; (f) Thompson; (g) WDM6; (h) Milbrandt–Yau; (i) NSSL

    图  8  2014年8月16日11:00(b–f)不同微物理方案模拟的组合雷达反射率与(a)观测组合雷达反射率(单位:dBZ)对比:(b)WSM6;(c)Thompson;(d)WDM6;(e)Milbrandt-Yau;(f)NSSL

    Figure  8.  Composite radar reflectivity factor (units: dBZ) simulated with different cloud microphysics schemes compared to (a) observations at 1100 UTC on August 16, 2014: (a) Observations; (b) WSM6; (c) Thompson; (d) WDM6; (e) Milbrandt-Yau; (f) NSSL

    图  9  图7,但为00:00~10:00累积降水量(单位:mm)空间分布对比

    Figure  9.  Same as Fig. 7, but for the fields of accumulation precipitation (units: mm) from 0000 UTC to 1000 UTC

    图  10  2014年8月16日08:00~18:00图9中红色矩形区域内Thompson方案(实线)和Milbrandt-Yau方案(虚线)模拟的不同水成物的空间积分总质量和区域平均降水率随时间变化:(a)云水;(b)雨水;(c)冰晶;(d)雪;(e)霰;(f)降水率

    Figure  10.  Time-dependence of domain-integrated total mass of different hydrometeor, and regionally averaged precipitation rate: (a) Cloud water; (b) rain water; (c) ice; (d) snow; (e) graupel; (f) precipitation rate in red rectangle region in Fig. 9 from 0800 UTC to 1800 UTC on August 16, 2014. The solid and dashed lines represent the simulations with the Thompson scheme and the Milbrandt–Yau scheme, respectively

    图  12  2014年8月16日09:00~12:00 Thompson方案(左列)和Milbrandt-Yau方案(右列)区域(图9红色矩形区域)平均的水成物质量混合比高度—时间分布: (a, b)云水;(c, d)冰晶;(e, f)雪;(g, h)霰;(i, j)雨水。黑色虚线为等温线,单位: °C,除(c)和(d)的水成物含量单位是mg kg−1外,其余均为g kg−1

    Figure  12.  Time–height distributions of regionally averaged (red rectangular region in Fig. 9) hydrometeor mixing ratio simulated with the Thompson scheme (left column) and the Milbrandt–Yau scheme (right column): (a, b) Cloud water; (c, d) ice; (e, f) snow; (g, h) graupel; (i, j) rain water from 0900 UTC to 1200 UTC, on August 16, 2014. The black dashed lines are isotherms, units: °C

    图  11  2014年8月16日(a、b)09:00、(c、d)10:00、(e、f)11:00和(g、h)12:00 Thompson方案(左列)和Milbrandt-Yau方案(右列)模拟的不同时刻云水(黑色)、雨水(绿色)、冰晶(橙色)、雪(蓝色)、霰(红色)和雹(紫色)混合比(单位:g kg−1)纬向垂直分布,箭头表示(u, w)风场。云水混合比等值线范围为0~2 g kg−1,间隔为0.1 g kg−1;雨水混合比等值线范围为0~0.3 g kg−1,间隔为0.02 g kg−1,冰晶混合比等值线范围为0~0.2 g kg−1,间隔为0.04 g kg−1;雪混合比等值线范围为0~3.2 g kg−1,间隔为0.4 g kg−1;霰混合比等值线范围为0~0.7 g kg−1,间隔为0.1 g kg−1;雹混合比等值线范围为0~0.3 g kg−1,间隔为0.03 g kg−1;黑色粗等值线为零度等温线;黑色三角表示南京奥林匹克体育中心场馆位置

    Figure  11.  The vertical cross sections of hydrometeor mixing ratio of cloud water (black contours), rain water (green contours), ice (orange contours), snow (blue contours), graupel (red contours), hail (purple contours), and winds (arrows) simulated with the Thompson scheme (left column) and the Milbrandt–Yau scheme (right column): (a, b) 0900 UTC, (c, d) 1000 UTC, (e, f) 1100 UTC, (g, h) 1200 UTC, on August 16, 2014. Cloud water mixing ratio contours range from 0 to 2 g kg−1, with an interval of 0.1 g kg−1; rain water mixing ratio contours range from 0 to 0.3 g kg−1, with an interval of 0.02 g kg−1; ice mixing ratio contours range from 0 to 0.2 g kg−1, with an interval of 0.04 g kg−1; snow mixing ratio contours range from 0 to 3.2 g kg−1, with an interval of 0.4 g kg−1; graupel mixing ratio contours range from 0 to 0.7 g kg−1, with an interval of 0.1 g kg−1; hail mixing ratio contours range from 0 to 0.3 g kg−1, with an interval of 0.03 g kg−1; the black thick contour line is the zero isotherm; the black triangle represents the NOC location

    12  (续)

    12.  (Continued)

    图  13  2014年8月16日09:00~12:00 Thompson方案(左列)和Milbrandt-Yau方案(右列)模拟的(a, b)雨水和(c, d)雪的源汇项微物理过程转化率随时间的变化(源项用正值表示,汇项用负值表示)。所有量均为图9红色矩形区域的平均值,图中没有给出那些相对贡献很小的过程

    Figure  13.  Microphysical conversion rates over time of source terms and sink terms of (a, b) rain water and (c, d) snow simulated with the Thompson scheme (left column) and the Milbrandt–Yau scheme (right column) from 0900 UTC to 1200 UTC, August 16, 2014 (the source term is represented by the positive value, and the sink term by the negative value). All the quantities are averages in red rectangular region in Fig. 9; the processes with relatively small contributions are not shown in the figures

    图  14  Thompson方案(左列)和Milbrandt-Yau方案(右列)模拟的区域(图9红色矩形区域)平均的(a, b)雨水和(c, d)雪的源汇项微物理过程转化率的垂直分布(2014年8月16日09:00~12:00的平均值)

    Figure  14.  Vertical distributions of regionally averaged (red rectangular region in Fig. 9) microphysical conversion rates of source terms and sink terms of (a, b) rain water and (c, d) snow simulated with the Thompson scheme (left column) and the Milbrandt–Yau scheme (right column) (averaged from 0900 UTC to 1200 UTC, August 16, 2014

    表  1  各微物理方案中的水成物预报量

    Table  1.   Predictors of hydrometeors in different microphysical schemes

    云微物理方案混合比预报量数浓度预报量
    Eta${Q}_{\mathrm{c} }\;{Q}_{\mathrm{r} }\;{Q}_{\mathrm{s} }$
    Lin${Q}_{\mathrm{c} } \;{Q}_{\mathrm{r} } \;{Q}_{\mathrm{i} } \;{Q}_{\mathrm{s} } \;{Q}_{\mathrm{g} }$
    WSM6${Q}_{\mathrm{c} }\;{Q}_{\mathrm{r} }\;{Q}_{\mathrm{i} }\;{Q}_{\mathrm{s} }\;{Q}_{\mathrm{g} }$
    Goddard${Q}_{\mathrm{c} }\;{Q}_{\mathrm{r} }\;{Q}_{\mathrm{i} }\;{Q}_{\mathrm{s} }\;{Q}_{\mathrm{g} }$
    Thompson${Q}_{\mathrm{c} }\;{Q}_{\mathrm{r} }\;{Q}_{\mathrm{i} }\;{Q}_{\mathrm{s} }\;{Q}_{\mathrm{g} }$${N}_{\mathrm{r} }\;{N}_{\mathrm{i} }$
    WDM6${Q}_{\mathrm{c} }\;{Q}_{\mathrm{r} }\;{Q}_{\mathrm{i} }\;{Q}_{\mathrm{s} }\;{Q}_{\mathrm{g} }$${N}_{\mathrm{c} }\;{N}_{\mathrm{r} }$
    Milbrandt-Yau${Q}_{\mathrm{c} }\;{Q}_{\mathrm{r} }\;{Q}_{\mathrm{i} }\;{Q}_{\mathrm{s} }\;{Q}_{\mathrm{g} }\;{Q}_{\mathrm{h} }$${N}_{\mathrm{c} }\;{N}_{\mathrm{r} }\;{N}_{\mathrm{i} }\;{N}_{\mathrm{s} }\;{N}_{\mathrm{g} }\;{N}_{\mathrm{h} }$
    NSSL${Q}_{\mathrm{c} }\;{Q}_{\mathrm{r} }\;{Q}_{\mathrm{i} }\;{Q}_{\mathrm{s} }\;{Q}_{\mathrm{g} }\;{Q}_{\mathrm{h} }$${N}_{\mathrm{c} }\;{N}_{\mathrm{r} }\;{N}_{\mathrm{i} }\;{N}_{\mathrm{s} }\;{N}_{\mathrm{g} }\;{N}_{\mathrm{h} }$
    注:下标c表示云水,下标r表示雨水,下标i表示冰晶,下标s表示雪,下标g表示霰,下标h表示雹。
    下载: 导出CSV
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  • 收稿日期:  2020-02-20
  • 网络出版日期:  2020-07-28
  • 刊出日期:  2020-11-20

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