高级检索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

云微物理对一次吉林暖区降水过程的影响

祁璇 平凡 沈新勇

祁璇, 平凡, 沈新勇. 2021. 云微物理对一次吉林暖区降水过程的影响[J]. 大气科学, 45(5): 1−22 doi: 10.3878/j.issn.1006-9895.2007.20128
引用本文: 祁璇, 平凡, 沈新勇. 2021. 云微物理对一次吉林暖区降水过程的影响[J]. 大气科学, 45(5): 1−22 doi: 10.3878/j.issn.1006-9895.2007.20128
QI Xuan, PING Fan, SHEN Xinyong. 2021. Impact of Cloud Miscrophisics on a Process of Warm-Sector Precipitation over Jilin, Northeast China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(5): 1−22 doi: 10.3878/j.issn.1006-9895.2007.20128
Citation: QI Xuan, PING Fan, SHEN Xinyong. 2021. Impact of Cloud Miscrophisics on a Process of Warm-Sector Precipitation over Jilin, Northeast China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(5): 1−22 doi: 10.3878/j.issn.1006-9895.2007.20128

云微物理对一次吉林暖区降水过程的影响

doi: 10.3878/j.issn.1006-9895.2007.20128
基金项目: 国家重点研发计划项目2018YFC1506801,国家自然科学基金项目41790471、41975054,中国科学院战略性先导科技专项XDA20100304
详细信息
    作者简介:

    祁璇,女,1993年出生,硕士,主要从事暴雨、台风等高影响短时天气模拟的研究。E-mail: qixuan63@163.com

    通讯作者:

    沈新勇,E-mail: shenxy@nuist.edu.cn

  • 中图分类号: P426

Impact of Cloud Miscrophisics on a Process of Warm-Sector Precipitation over Jilin, Northeast China

Funds: National Key Research and Development Program of China (Grant 2018YFC1506801), National Natural Science Foundation of China (Grants 41790471, 41975054), Strategic Priority Research Program of Chinese Academy of Sciences (Grant XDA20100304)
  • 摘要: 本文运用WRF3.9区域数值模式模拟了2017年7月13日吉林省永吉县暖区暴雨,较好地再现了此次暴雨过程的中尺度对流系统的单体触发、线状对流群触发、组织化发展以及弓状回波等典型阶段的细致过程;在此基础上,分析了造成暖区降水的中尺度对流系统的云微物理特征,探讨了其影响暖区降水的可能机制。结果表明:吉林永吉暖区降水发生在东北冷涡主导的有利的多尺度环境配置下,引发暖区降水的中尺度系统主要是冷云系统,暖区范围大,过冷水分布位置高,冰晶粒子与过冷水并存,并存区的“播种”效应使得其下方生成大量霰。雨水质量收支及热量收支分析表明:暖区降水系统的触发及组织化阶段,雨水的主要来源是云滴碰并增长,主要汇项是冰晶对雨水的收集;而弓状回波阶段,降水的主要源项除了云滴碰并增长之外,霰融化作用也起到关键的作用,降水主要汇项在低层为雨水蒸发,高层为霰对雨滴的收集;暖区降水的主要热源是水汽凝结潜热释放,主要冷却项是雨水和云水的蒸发。弓状回波阶段,其前部的入流与地面冷垫上方的后向入流汇合后将水汽带入高层;“播种”效应使距地面8 km高度附近的霰粒子含量显著增多,该高度与水汽凝结释放大量潜热形成的高温区重合,故霰粒子大量融化为雨水,产生强降水过程。
  • 图  1  2017年7月13日00:00(左列;协调世界时,下同)和12:00(右列)天气尺度背景场分布:(a,e)200 hPa高空急流(填色阴影区域,单位:m s−1),500 hPa位势高度(蓝色实线,单位:dagpm)、温度(红色实线,单位:K)、槽线(红色粗实线)和西太平洋副热带高压(588黑色实线,单位:10 gpm);(b,f)700 hPa位势高度(蓝色实线,单位:10 gpm),广义位温(红色虚线,单位:K)、底层切变线(红色实线)和风场(矢量箭头,单位:m s−1);(c,g)850 hPa水汽通量(绿色阴影区,单位:g s−1 hPa−1 cm−1)、位势高度(蓝色实线,单位:10 gpm)、广义位温(GPT,红色虚线,单位:K)、风场(矢量箭头,单位:m s−1;打点区为低空急流区)和底层切变线(红色实线);(d,h)地面气压场(蓝色细实线,单位:hPa)、风场(矢量箭头,单位m s−1)和地面冷锋(蓝色粗实线)。图中五角星代表永吉,下同;字母“H”、“L”分别代表高压中心和低压中心位置

    Figure  1.  Background circulation fields at 0000 UTC (left column) and 1200 UTC (right column) on July 13, 2017 : (a, e) High-level jet (shaded, units: m s−1) at 200 hPa; geopotential height (blue solid contours, units: 10 gpm), temperature (red solid contours, units: K), trough line (red bold line), the western Pacific subtropical high (black contours; units: 10 gpm) at 500 hPa. (b, f) Geopotential height (blue solid contours, units: dagpm), generalized potential temperature (red dash contours, units: K), trough-line (thick red solid line), and winds (vectors; units: m s−1; dotted areas denote lower-level jet) at 700 hPa. (c, g) Water vapor flux (shaded; units: g s−1 hPa−1 cm−1), geopotential height (blue solid contours; units: dagpm), generalized potential temperature (red dashed contours; unis: K), wind field (vectors; units: m s−1) and trough-line(red solid line) at 850 hPa. (d, h) Sea level pressure (blue thin solid contours, units: hPa), 10-m winds (vectors; units: m s−1), and cold front (blue bold solid line). Position of Yongji is marked by the star, the same below. Letters “H” and “L” denote high-pressure and low-pressure centers, respectively

    图  2  2017年7月13日(a)00:00、(b)06:00、(c)12:00长春站(54161)的探空观测以及(d)模式模拟区域。层结曲线(蓝色粗实线),状态曲线(黑色粗实线)。

    Figure  2.  Atmospheric sounding data as observed at Changchun station (54161) at (a) 0000 UTC, (b) 0600 UTC, and (c) 1200 UTC on July13, 2017, The location of the model domain is shown in (d). stratification curve (thick blue solid line), state curve (thick black solid line).

    图  3  2017年7月13日中尺度对流系统演变过程中观测(左列,obs)和模拟(右列,wrf)的累计降水分布(填色,单位:mm)对比:(a、b)07:00~13:00 6小时累计;(c、d)13:00~19:00的6小时累计;(e、f)07:00~19:00的12小时累计

    Figure  3.  Comparison of the observed (left column; obs) and simulated (right column; wrf) accumulative precipitation distributions (shaded, units: mm) during the evolution of the mesoscale convective systems: (a, b) 6-h period from 0700 UTC to 1300 UTC; (c, d) 6-h period from 1300 UTC to 1900 UTC; (e, f) 12-h period from 0700 UTC to 1900 UTC on July 13, 2017

    图  4  2017年7月13日中尺度对流系统演变过程中的(a–f)实况雷达拼图和(g–m)模拟综合雷达反射率(填色,单位:dBZ):(a,g)07:30;(b,h)09:30;(c,i)11:30;(d,k)13:30;(e,l)15:30;(f,m)17:30。黑色五角形代表永吉所在位置

    Figure  4.  The (a–f) observed and (g–l)simulated composite radar reflectivity (shaded; units: dBZ) during the evolution of the mesoscale convective system, at (a, g) 0730 UTC, (b, h) 0930 UTC, (c, i) 1130 UTC, (d, k) 1330 UTC, (e, l) 1530 UTC, and (f, m) 1730 UTC on July 13, 2017, respectively. Yongji’s location is indicated by the star

    图  5  2017年7月13日实际观测(a)07:00、(b)07:18、(c)08:42和(d)13:54雷达回波拼图(填色,单位:dBZ)以及模拟的(e)07:05、(f)07:15、(g)08:00和(h)14:00雷达综合雷达回波(填色,单位:dBZ)分布。黑色箭头代表选取的剖面位置,黑色方框代表选取的典型区域

    Figure  5.  The observed composite radar reflectivity (shaded; units: dBZ) at (a) 0700 UTC, (b) 0718 UTC, (c) 0842 UTC, and (d)1354 UTC on July 13, 2017, and the simulated composite radar reflectivity (shaded; units: dBZ) at (e) 0705 UTC, (f) 0715 UTC, (g) 0800 UTC, and (h) 1400 UTC on July 13, 2017, respectively. The black arrows indicate the positions of selected cross sections, and the black boxes indicate the typical areas

    图  6  2017年7月13日(a)14:00模拟的雷达反射率(填色,单位:dBZ,黑色方框区域为选取的典型区域),(b)模拟的云滴混合比在(a)方框内的区域均值(填色,单位:10−3 kg kg−1)随时间—气压的变化,(c)模拟的雨滴混合比区域均值(填色,单位:10−3 kg kg−1)和雨滴数浓度区均值(黑色实线,单位:m−3)随时间—气压的变化;(d)同(c),但为雪;(e)同(c),但为冰晶;(f)同(c),但为霰;虚线用来分割不同阶段

    Figure  6.  (a) The simulated composite radar reflectivity at 1400 UTC on July 13, 2017 (shaded; units: dBZ), the black box represent the selected typical area; (b) the change of simulated cloud regional average mixing ratios (shaded; units: 10−6 kg kg−1 s−1) with time and pressure over the box on (a); (c) the change of simulated rain regional average mixing ratios(shaded; units: 10−6 kg kg−1 s−1) and number concentration (black solid line; units: m−3) with time and pressure over the box in (a). (d) As in (c), but for snow. (e) As in (c), but for ice. (f) As in (c), but for graupel. Dotted lines are used to divide the different stages

    图  7  2017年7月13日模拟的(a)07:05、(b)07:15、(c)08:00和(d)14:00沿图5eh箭头位置的雷达反射率(填色,单位:dBZ)和风场(矢量箭头,水平分量单位:m s−1;垂直分量单位:0.2 m s−1)的剖面

    Figure  7.  The simulated vertical cross sections of radar reflectivity (shaded; units: dBZ) and flow vectors (vector arrow, horizontal component unit: m s−1; vertical component unit: 0.2 m s−1) following the black arrows at the corresponding times given in Fig. 5eh at (a) 0705 UTC, (b) 0715 UTC, (c) 0800 UTC and (d) 1400 UTC on July 13, 2017

    图  8  图7,但为垂直速度(填色,单位:m s-1)、水成物总量混合比(黑色等值线,单位:g kg-1)剖面。细实线代表0℃等温线,细虚线代表−20℃。

    Figure  8.  Same as Fig. 7, but for vertical velocity (shaded; units: m s−1) and total amount of hydrometeors (bold black contours; units: g kg−1). The thin black lines denote the 0℃ (solid) and −20℃ (dashed) isotherms

    图  9  图7,但为液态水成物总量(填色,单位:g kg−1)和冰相粒子总量(黑色等值线,单位:g kg-1)混合比的剖面

    Figure  9.  Same as Fig. 7, but for the total amount of liquid hydrometeors (shaded; units: g kg−1) and total amount of ice particles (bold solid contours; units: g kg−1)

    图  10  2017年7月13日模拟的(a)07:05、(b)07:15、(c)08:00和(d)14:00对应的图5eh典型区域内各水物质混合比区域平均值(单位:g kg−1)的垂直廓线。符号说明见附录,下同

    Figure  10.  Vertical profiles of the simulated mixing ratio of hydrometeors (units: g kg−1) averaged over the boxes at the corresponding times given in Fig. 5eh at (a) 0705 UTC, (b) 0715 UTC, (c) 0800 UTC and (d) 1400 UTC on July 13, 2017. See the appendix for the symbols in the chart, the same below

    图  11  图10,但为雨水质量收支的垂直廓线(单位:10−6 kg kg−1 s−1

    Figure  11.  As in Fig. 10, but for the mean conversion rate (units: 10−6 kg kg−1 s−1) related to rain

    图  12  图10,但为热量收支的垂直廓线(单位:10−3 K s−1

    Figure  12.  As in Fig. 10, but for the latent heating rate (units: 10−3 K s−1)

    图  13  2017年7月13日模拟的(a)07:05、(b)07:15、(c)08:00和(d)14:00沿对应的图5eh箭头方向剖面上的总绝热加热率(阴影;单位:K s−1)、水汽凝结为云滴pcc_pos(黑色等值线;0.01~0.1,间隔为0.02 K s−1)、水汽凝华为霰粒子prdg(紫色等值线;0.0005~0.0065,间隔为0.002 K s−1)以及雨水蒸发pre(蓝色等值线;−0.002~−0.008,间隔为−0.002 K s−1)加热率的垂直剖面

    Figure  13.  Vertical cross sections along the black arrows at the corresponding times given in Fig. 5eh at (a) 0705 UTC, (b) 0715 UTC, (c) 0800 UTC and (d) 1400 UTC on July 13, 2017: the total diabatic heating rate (shaded; units: K s−1), heating rate via condensation of cloud droplet (pcc_pos) (black solid contours; 0.01 to 0.1, at intervals of 0.02; units: K s−1), deposition of graupel (prdg) (purple contours; 0.0005 to 0.05, at intervals of 0.002; units: K s−1), and evaporation of rain (pre) (blue contours; −0.002 to −0.008, at intervals of −0.002; units: K s−1)

    图  14  图10a,但为雨水质量收支的垂直廓线(pgmlt数值扩大两倍,单位:10−6 kg kg−1 s−1

    Figure  14.  Sane as Fig. 10a, but for the mean conversion rate (the pgmlt value is doubled, units: 10−6 kg kg−1 s−1) related to the rain

    图  15  2017年7月13日永吉暖区降的云微物理机制概念模型

    Figure  15.  Conceptual model of cloud microphysics mechanisms related to the warm sector precipitation over Yongji

    表  1  WRFV3.9模式物理参数化方案配置

    Table  1.   Physical parameterization scheme configurations of WRFV3.9 mode

    类别选项
    水平分辨率9 km/3 km/1 km
    网格数421×331/505×481/793×682
    中心点(43.42°N,126.31°E)
    模式顶高50 hPa
    垂直层数37层
    积云参数化方案Kain-Fritsch (Kain and Pinto, 1989)
    微物理参数化方案Morrison (Morrison and Pinto, 2005)
    辐射方案CAM (Collins et al., 2006)
    陆面过程Noah (Chen and Dudhia. 2001)
    边界层方案YSU (Hong et al., 2006)
    近地面层方案Monin-Obukhov (Byun, 1990)
    下载: 导出CSV

    表  2  中尺度系统不同发展阶段,雨水的主要质量收支项区域平均值的垂直积分总量(单位:10−6 kg kg−1 s−1

    Table  2.   Total vertically integrated regional average values of the main mass sources and sinks (units: 10−6 kg kg−1 s−1) related to rain during different stages of the mesoscale system development

    不同阶段
    主要质量收支项(垂直积分总量/10−6 kg kg−1 s−1
    源项汇项
    单体触发阶段pra(3.44)无汇项
    线状群体触发阶段pra(4.12)piacr(0.48)pracg_r2g(0.21)pracs_r2s(0.16)
    组织化发展阶段pra(7.31)pgmlt(1.01)pre(1.58)piacr(1.50)pracg_r2g(1.38)pracs_r2s(0.50)
    弓状回波阶段pra(4.25)pgmlt(3.38)psmlt(0.71)pre(2.90)pracg_r2g(0.83)
    注:符号说明见附录,下同
    下载: 导出CSV

    表  3  中尺度系统不同发展阶段主要热量收支项区域平均值的整层积分总量(单位:10−3 K s−1)

    Table  3.   The total integrated regional average values of primary sources and sinks of latent heat (units: 10−3 K s−1) during different stages of the mesoscale system development

    不同阶段
    主要热量收支项(整层积分总量/10−3 K−1 s−1
    热量源项热量汇项
    对流单体触发阶段pcc_pos(23.75)pcc_neg(8.30)
    线状群体触发阶段pcc_pos(19.58)pcc_neg(7.84)
    组织化发展阶段pcc_pos(46.24)prd(2.57)prdg(3.74)psacwg(2.08)pre(3.96)pcc_neg(7.10)eprdg
    (2.57)
    弓状回波阶段pcc_pos(25.30)prd(2.40)prdg(4.67)psacwg(1.20)pre(7.19)pgmlt(1.12)evpmg(0.56)pcc_neg(3.90)eprdg(2.49)
    下载: 导出CSV

    表  4  霰粒子融化项扩大两倍后,弓状回波阶段雨水的主要质量收支项区域平均值的垂直积分总量(单位:10−6 kg kg−1 s−1

    Table  4.   Total vertically integrated regional average values of the main mass sources and sinks (units: 10−6kg kg−1 s−1) related to rain during the bow-shaped echo stage after the hail is doubled

    主要质量收支项(垂直积分总量/10−6 kg kg−1 s−1
    质量源项质量汇项
    弓状回波阶段pra(4.75)pgmlt(4.13)psmlt(0.87)pre(3.55)pracg_r2g(0.90)
    下载: 导出CSV

    A1  本文中符号说明

    A1.   Description of symbols in the paper

    符号说明符号说明
    qc云滴pra云滴碰并增长为雨滴
    qr雨滴pracg_g2r霰被雨滴收集
    qspracg_r2g雨滴被霰收集
    qi冰晶praci雨滴收集冰晶增加至霰
    qgpracis雨滴收集冰晶增加至雪
    eprd冰晶升华为水汽pracs_s2r雪被雨滴收集
    eprdg霰升华为水汽pracs_r2s雨滴被雪收集
    eprds雪升华为水汽prai冰晶自动转化为雪
    evpmg霰融化蒸发为水汽prc云滴自动转化为雨滴
    evpms雪融化蒸发为水汽prci冰晶碰并增长为雪
    mnuccc云滴接触冻结为冰晶prd水汽凝华为冰晶
    mnuccd水汽冻结为冰晶prds水汽凝华为雪
    mnuccr雨滴冻结为霰prdg水汽凝华为霰
    pcc_pos水汽凝结为云滴pre雨水蒸发为水汽
    pcc_neg云滴蒸发为水汽psacr雨滴收集雪增加至霰
    pgmlt霰融化为雨滴psacwg云滴撞冻为霰
    pgracs雪收集雨滴增加至霰psacws云滴撞冻增长为雪
    pgsacw雪收集云滴增加至霰psacwi云滴撞冻增长为冰晶
    piacr冰晶收集雨滴增加至霰pgsacw雪收集云滴增加至霰
    piacrs冰晶碰撞雨滴增加至雪psmlt雪融化为雨滴
    下载: 导出CSV
  • [1] Byun D W. 1990. On the analytical solutions of flux-profile relationships for the atmospheric surface layer [J]. J. Appl. Meteor., 29: 652−657. doi:10.1175/1520-0450(1990)029<0652:OTASOF>2.0.CO;2
    [2] 谌芸, 吕伟绮, 于超, 等. 2018. 北方一次暖区大暴雨降水预报失败案例剖析 [J]. 气象, 44(1): 15−25. doi: 10.7519/j.issn.1000-0526.2018.01.002

    Chen Yun, Lü Weiqi, Yu Chao, et al. 2018. Analysis of a forecast failure case of warm sector torrential rainfall in North China [J]. Meteorological Monthly (in Chinese), 44(1): 15−25. doi: 10.7519/j.issn.1000-0526.2018.01.002
    [3] Chen F, Dudhia J. 2001. Coupling an advanced land-surface/ hydrology model with the Penn State/ NCAR MM5 modeling system. Part I: Model description and implementation [J]. Mon. Wea. Rev., 129: 569−585. doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2
    [4] Collins W D, Rasch P J, Boville B A, et al. 2006. The formulation and atmospheric simulation of the community Atmosphere Model Version 3(CAM3) [J]. J. Climate., 19: 2144−2161. doi: 10.1175/JCLI3760.1
    [5] Fan J W, Zhang R Y, Li G H, et al. 2007. Effects of aerosols and relative humidity on cumulus clouds [J]. J. Geophys. Res.: Atmos., 112(D14): D14204. doi: 10.1029/2006JD008136
    [6] 傅佩玲, 胡东明, 张羽, 等. 2018. 2017年5月7日广州特大暴雨微物理特征及其触发维持机制分析 [J]. 气象, 44(4): 500−510. doi: 10.7519/j.issn.1000-0526.2018.04.003

    Fu Peiling, Hu Dongming, Zhang Yu, et al. 2018. Microphysical characteristics, initiation and maintenance of record heavy rainfall over Guangzhou region on 7 May 2017 [J]. Meteorological Monthly (in Chinese), 44(4): 500−510. doi: 10.7519/j.issn.1000-0526.2018.04.003
    [7] Gao S T, Wang X R, Zhou Y S. 2004. Generation of generalized moist potential vorticity in a frictionless and moist adiabatic flow [J]. Geophys. Res. Lett., 31(12): L12113. doi: 10.1029/2003GL019152
    [8] Gao S T, Cui X P, Zhou Y S, et al. 2005. Surface rainfall processes as simulated in a cloud-resolving model [J]. J. Geophys. Res.: Atmos., 110(D10): D10202. doi: 10.1029/2004JD005467
    [9] 郭学良, 黄美元, 徐华英, 等. 1999. 层状云降水微物理过程的雨滴分档数值模拟 [J]. 大气科学, 23(6): 745−752. doi: 10.3878/j.issn.1006-9895.1999.06.11

    Guo Xueliang, Huang Meiyuan, Xu Huaying, et al. 1999. Rain category numerical simulations of microphysical processes of precipitation formation in stratiform clouds [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 23(6): 745−752. doi: 10.3878/j.issn.1006-9895.1999.06.11
    [10] 何立富, 陈涛, 孔期. 2016. 华南暖区暴雨研究进展 [J]. 应用气象学报, 27(5): 559−569. doi: 10.11898/1001-7313.20160505

    He Lifu, Chen Tao, Kong Qi. 2016. A review of studies on prefrontal torrential rain in South China [J]. Journal of Applied Meteorological Science (in Chinese), 27(5): 559−569. doi: 10.11898/1001-7313.20160505
    [11] Hobbs P V. 1980. The mesostructure and microstructure of extratropical cyclones [C]//Ⅷ International Conference of Cloud Physics. Clermont-Ferrand France, 2: 615-618.
    [12] 洪延超. 2012. 层状云结构和降水机制研究及人工增雨问题讨论 [J]. 气候与环境研究, 17(6): 937−950. doi: 10.3878/j.issn.1006-9585.2012.06.31

    Hong Yanchao. 2012. Research progress of stratiform cloud structure and precipitation mechanism and discussion on artificial precipitation problems [J]. Climatic and Environmental Research (in Chinese), 17(6): 937−950. doi: 10.3878/j.issn.1006-9585.2012.06.31
    [13] 黄士松. 1986. 华南前汛期暴雨 [M]. 广州: 广东科技出版社, 1-7.

    Huang Shisong. 1986. Rainstorms of the First Rainy Season in South China (in Chinese) [M]. Guangzhou: Guangdong Science & Technology Press, 1-7.
    [14] Huang Y J, Liu Y B, Xu M, et al. 2018. Forecasting severe convective storms with WRF-based RTFDDA radar data assimilation in Guangdong, China [J]. Atmospheric Research, 209: 131−143. doi: 10.1016/j.atmosres.2018.03.010
    [15] Hong Songyou, Noh Y, Dudhia J. 2006. A new vertical diffusion package with an explicit treatment of entrainment processes [J]. Mon. Wea. Rev., 134(9): 2318−2341. doi: 10.1175/MWR3199.1
    [16] 孔凡铀, 黄美元, 徐华英. 1991. 冰相过程在积云发展中的作用的三维数值模拟研究 [J]. 中国科学(B辑)(9): 1000−1008.

    Kong Fanyou, Huang Meiyuan, Xu Huaying. 1991. The 3D numerical simulation study on effect of ice phase processes in convective cloud in cumulus developing [J]. Science China (Part B) (in Chinese)(9): 1000−1008.
    [17] Kain J S., Fritsch J M 1989. A One-Dimensional Entraining/Detraining Plume Model and Its Application in Convective Parameterization [J]. Journal of the Atmospheric Science, 47(23): 2784−2802. doi:10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2
    [18] 茅家华, 平凡. 2015. 北京“721”特大暴雨云微物理特征分析 [J]. 科学技术与工程, 15(16): 121−127, 133. doi: 10.3969/j.issn.1671-1815.2015.16.021

    Mao Jiahua, Ping Fan. 2015. Analysis of cloud microphysical characteristics on Beijing “7.21” extreme rainfall [J]. Science Technology and Engineering (in Chinese), 15(16): 121−127, 133. doi: 10.3969/j.issn.1671-1815.2015.16.021
    [19] Mao J H, Ping F, Yin L, et al. 2018. A study of cloud microphysical processes associated with torrential rainfall event over Beijing [J]. J. Geophys. Res.: Atmos., 123(16): 8768−8791. doi: 10.1029/2018JD028490
    [20] Matejka T J, Houze Jr R A, Hobbs P V, et al. 1980. Microphysics and dynamics of clouds associated with mesoscale rainbands in extratropical cyclones [J]. Quart. J. Roy. Meteor. Soc., 106(447): 29−56. doi: 10.1002/qj.49710644704
    [21] Morrison H, Pinto J O. 2005. Mesoscale Modeling of Springtime Arctic Mixed-Phase Stratiform Clouds Using a New Two-Moment Bulk Microphysics Scheme [J]. Journal of the Atmospheric Sciences, 62(10): 3683−3704. doi: 10.1175/JAS3564.1
    [22] Nozumi Y, Arakawa T. 1968. Prefrontal rain bands located in the warm sector of subtropical cyclones over the ocean [J]. J. Geophy. Res., 73(2): 487−492. doi: 10.1029/JB073i002p00487
    [23] Schlamp R J, Pruppacher H R, Hamielec A E. 1975. A numerical investigation of the efficiency with which simple columnar ice crystals collide with supercooled water drops [J]. J. Atmos. Sci., 32(12): 2330−2337. doi:10.1175/1520-0469(1975)032<2330:ANIOTE>2.0.CO;2
    [24] Su T, Zhai G Q. 2017. The role of convectively generated gravity waves on convective initiation: A case study [J]. Mon. Wea. Rev., 145(1): 335−359. doi: 10.1175/MWR-D-16-0196.1
    [25] 陶诗言. 1980. 中国之暴雨 [M]. 北京: 科学出版社, 45-46.

    Tao Shiyan. 1980. Rainstorm in China (in Chinese) [M]. Beijing: Science Press, 45-46.
    [26] Van Weverberg K, van Lipzig N P M, Delobbe L. 2011. The impact of size distribution assumptions in a bulk one-moment microphysics scheme on simulated surface precipitation and storm dynamics during a low-topped supercell case in Belgium [J]. Mon. Weather. Rev., 139(4): 1131−1147. doi: 10.1175/2010MWR3481.1
    [27] 王宁, 云天, 姚帅, 等. 2018. 2017年吉林省两次极端降水成因的综合对比分析 [C]//第35届中国气象学会年会S1灾害天气监测、分析与预报. 合肥: 中国气象学会.

    Wang Ning, Yun Tian, Yao Shuai, et al. 2018. Comprehensive comparative analysis on the causes of two extreme precipitation events in Jinlin province in 2017 [C]//Proceedings of the 35th Annual Meeting of the Chinese Meteorological Society S1 Severe Weather Monitoring, Analysis and Forecast (in Chinese). Hefei: China Meteorological Society.
    [28] Wilson J W, Roberts R D. 2006. Summary of convective storm initiation and evolution during IHOP: Observational and modeling perspective [J]. Mon. Wea. Rev., 134(1): 23−47. doi: 10.1175/MWR3069.1
    [29] Weiss C C, and Bluestein H B. 2002. Airborne pseudo-dual Doppler analysis of a dryline-outflow boundary intersection [J]. Mon. Wea. Rev., 130: 1207−1226. doi:10.1175/1520-0493(2002)130<1207:APDDAO>2.0.CO;2
    [30] 吴亚丽, 蒙伟光, 陈德辉, 等. 2018. 一次华南暖区暴雨过程可预报性的初值影响研究 [J]. 气象学报, 76(3): 323−342. doi: 10.11676/qxxb2018.001

    Wu Yali, Meng Weiguang, Chen Dehui, et al. 2018. A study of the impact of initial conditions on the predict-ability of awarm-sector torrential rain over South China [J]. Acta Meteorologica Sinica (in Chinese), 76(3): 323−342. doi: 10.11676/qxxb2018.001
    [31] 伍志方, 蔡景就, 林良勋, 等. 2018. 2017年广州“5·7”暖区特大暴雨的中尺度系统和可预报性 [J]. 气象, 44(4): 485−499. doi: 10.7519/j.issn.1000-0526.2018.04.002

    Wu Zhifang, Cai Jingjiu, Lin Liangxun, et al. 2018. Analysis of mesoscale systems and predictability of the torrential rain process in Guangzhou on 7 May 2017 [J]. Meteorological Monthly (in Chinese), 44(4): 485−499. doi: 10.7519/j.issn.1000-0526.2018.04.002
    [32] X ue, M., and W. J. Martin 2006. A high-resolution modeling study of the 24 May 2002 dryline case during IHOP. Part II: Horizontal convective rolls and convective initiation [J]. Mon. Wea. Rev., 134: 172−191. doi: 10.1175/MWR3072.1
    [33] 许焕斌, 段英. 1999. 云粒子谱演化研究中的一些问题 [J]. 气象学报, 57(4): 450−460. doi: 10.11676/qxxb1999.042

    Xu Huanbin, Duan Ying. 1999. Some questions in studying the evolution of size-distribution spectaum of hydrometeor particles [J]. Acta Meteorologica Sinica (in Chinese), 57(4): 450−460. doi: 10.11676/qxxb1999.042
    [34] 杨洁帆, 雷恒池, 胡朝霞. 2010. 一次层状云降水过程微物理机制的数值模拟研究 [J]. 大气科学, 34(2): 275−289. doi: 10.3878/j.issn.1006-9895.2010.02.04

    Yang Jiefan, Lei Hengchi, Hu Zhaoxia. 2010. Simulation of the stratiform cloud precipitation microphysical mechanism with the numerical model [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 34(2): 275−289. doi: 10.3878/j.issn.1006-9895.2010.02.04
    [35] YinL, Ping F, Mao J H. 2018. Cloud-resolving simulation and mechanistic analysis of a squall line in East China [J]. Atmospheric Research, 206: 13−29. doi: 10.1016/j.atmosres.2018.01.019
    [36] 于佳含, 巩远发, 毛文书. 2019. 2017年7月吉林永吉两次极端强降水过程的对比分析 [J]. 成都信息工程大学学报, 34(3): 287−296. doi: 10.16836/j.cnki.jcuit.2019.03.014

    Yu Jiahan, Gong Yuanfa, Mao Wenshu. 2019. Comparative analysis on two extreme severe precipitation events in Yongji county, Jilin province in July 2017 [J]. Journal of Chengdu University of Information Technology (in Chinese), 34(3): 287−296. doi: 10.16836/j.cnki.jcuit.2019.03.014
    [37] 袁敏, 平凡, 李国平. 2018. 台风“梅花”路径转折期间的结构特征分析与模拟 [J]. 大气科学, 42(5): 1000−1012. doi: 10.3878/j.issn.1006-9895.1707.17145

    Yuan Min, Ping Fan, Li Guoping. 2018. Diagnostic study and numerical simulation on the structure of typhoon “Muifa” during its two recurving processes [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 42(5): 1000−1012. doi: 10.3878/j.issn.1006-9895.1707.17145
    [38] Zhong L Z, Mu R, Zhang D L, et al. 2015. An observational analysis of warm-sector rainfall characteristics associated with the 21 July 2012 Beijing extreme rainfall event [J]. J. Geophys. Res.: Atmos., 120(8): 3274−3291. doi: 10.1002/2014JD022686
    [39] 周玉淑, 刘璐, 朱科锋, 等. 2014. 北京“7.21”特大暴雨过程中尺度系统的模拟及演变特征分析 [J]. 大气科学, 38(5): 885−896. doi: 10.3878/j.issn.1006-9895.2013.13185

    Zhou Yushu, Liu Lu, Zhu Kefeng, et al. 2014. Simulation and evolution characteristics of mesoscale systems occurring in Beijing on 21 July 2012 [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 38(5): 885−896. doi: 10.3878/j.issn.1006-9895.2013.13185
  • 加载中
图(15) / 表(5)
计量
  • 文章访问数:  128
  • HTML全文浏览量:  37
  • PDF下载量:  46
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-07-28
  • 录用日期:  2020-07-28
  • 网络出版日期:  2020-12-13

目录

    /

    返回文章
    返回