Comparative analysis of physical quantity characteristic of three extreme short-term heavy rainfalls with different intensities under cold vortex background during summer in Tianjin

doi:10.11755/j.issn.1006-7639-2025-03-0424

Abstract

Abstract:

The comparative analysis of local physical processes of rainfall with different intensities under similar circulation background is an effective way to improve the accurate forecasting ability of heavy precipitation events in the region. Based on multi-source data, this paper analyzed the thresholds of physical quantities of sudden increase of rainfall intensity during three heavy rainfall processes under the background of cold vortex in Tianjin on June 28 (hereinafter abbreviated as the “6·28” process), July 1 (hereinafter abbreviated as the “7·1” process) and July 26 (hereinafter abbreviated as the “7·26” process) in 2022. The results show that during the "6·28" process, the synergistic effects of extremely strong water vapor convergence (-8.0×10^-7 g·hPa^-1·cm^-2·s^-1), low lifting condensation level (962 hPa), and deep warm cloud layer (4.0 km), combined with the mesoscale vortices triggered by cold pool outflow and low-level convergence, as well as low-quality storms and the training effects, collectively resulted in a maximum rainfall intensity increase of 96.6 mm·h^-1.During the “7·26” process, the higher ambient temperatures (32.1 ℃) and convective effective potential energy (CAPE) (2 464 J·kg^-1) promoted the vertical development of high quality storms. However, the increasing proportion of ice phase particles limited the increase in rainfall intensity (88.8 mm·h^-1). During the “7·1” process, the weak vertical wind shear (1.3 m·s^-1) and insufficient cold pool strength (21.9 ℃) were impossible to trigger new convection, with the lowest increase in rainfall intensity (55.3 mm·h^-1). There are common thresholds of physical quantities before the sudden increase in rainfall intensity in the three processes: the CAPE greater than 1 200 J·kg^-1, the warm cloud layer thickness greater than 3.1 km, total atmospheric precipitable water greater than 47.5 mm, and the occurrence time of the surface convergence line being 1.5-2.0 h ahead of the occurrence time of heavy precipitation. The correlation coefficient between ET, CR, VIL and rainfall intensity increment exceeded 0.90, while the correlation coefficient between dew point change in the first hour and rainfall intensity increment was -0.90 during the extreme heavy rainfalls.

Key words: extreme short-term heavy rainfall, cold vortex, sudden increase in rainfall intensity, mesoscale vortex

摘要： 在相似环流背景下开展不同降雨强度降水过程的局地关键物理量对比分析，是提升该地区强降水事件精细化预报能力的有效路径。本文基于多源观测数据，对2022年6月28日（简称“6·28”过程）、7月1日（简称“7·1”过程）和7月26日（简称“7·26”过程）天津3次冷涡背景下的雨强突增过程开展物理量阈值分析。结果表明：“6·28”过程中，极强水汽辐合（-8.0×10?? g·hPa?1·cm?2·s?1）、低抬升凝结高度（962 hPa）与深厚暖云层（4.0 km）形成协同效应，叠加冷池出流与低空辐合触发的中尺度涡旋，以及低质心风暴和列车效应，共同导致本次过程雨强最大增幅达96.6 mm·h^-1；“7·26”过程以较高的环境温度（32.1 ℃）和对流有效位能（2 464 J·kg?1）促使高质心风暴垂直发展，但冰相粒子占比增加使得雨强增幅（88.8 mm·h^-1）受限；“7·1”过程受弱垂直风切变（1.3 m·s?1）与冷池强度（21.9 ℃）不足影响，冷池出流无法与低层辐合协同触发新对流，导致雨强增幅最低（55.3 mm·h^-1）。3次过程雨强跃增前均存在共性物理量阈值：对流有效位能大于1 200 J·kg?1、暖云层厚度大于3.1 km、整层大气可降水量大于47.5 mm，且地面辐合线出现时间超前强降水发生时间1.5~2.0 h。此外，回波顶高、组合反射率、垂直累积液态水含量与雨强增量的相关系数均超过0.90，前1 h露点温度变化与雨强增量的相关系数为-0.90。

关键词: 极端短时强降水, 冷涡, 雨强突增, 中尺度涡旋

CLC Number:

P445

JIN Zhenhua, BU Qingjun, HUANG Anning. Comparative analysis of physical quantity characteristic of three extreme short-term heavy rainfalls with different intensities under cold vortex background during summer in Tianjin[J]. Journal of Arid Meteorology, 2025, 43(3): 424-434.

靳振华, 卜清军, 黄安宁. 冷涡背景下天津夏季三次不同强度极端短时强降水物理量特征对比分析[J]. 干旱气象, 2025, 43(3): 424-434.

Figures/Tables 11

Tab.1 Main physical quantity list

因子分类	物理量	单位
对流潜势因子	对流有效位能（Convective Available Potential Energy，CAPE）	J·kg^-1
	抬升凝结高度（Lifted Condensation Level，LCL）	km
	湿层厚度（Humidity Layer Thickness，H_wet）	km
	暖云层厚度（Warm Cloud Layer Thickness，H_warm）	km
	0~6 km垂直风切变（0~6 km Vertical Wind Shear，SHR₆）	m·s^-1
	K指数	℃
	强天气威胁指数（Severe Weather Threat Index，SWEAT）
动力因子	垂直速度（Vertical Velocity，w）	Pa·s^-1
水汽因子	整层大气可降水量（Precipitable Water Vapor，P_WV）	mm
热力因子	假相当位温（Pseudo Equivalent Potential Temperature，θ_se）	K
回波参数	组合反射率（Composite Reflectivity，CR）	dBZ
	回波顶高（Echo Top，ET）	km
	垂直累积液态水含量（Vertical Integrated Liquid Water Content，VIL）	kg·m^-2

Fig.1 The extreme rainfall intensity areas of three short-term heavy rainfall processes in Tianjin in 2022（The circle digital indicates the sequence of occurrence of the extreme short-term heavy rainfalls at each station）

Fig.2 The increment of rainfall intensity compared to the previous hour at different stations and times during three short-term heavy rainfall processes in Tianjin in 2022

Fig.3 The circulation situation at 200 hPa, 500 hPa, 700 hPa, and 850 hPa before the occurrence of three extreme short-term heavy rainfall processes in Tianjin in 2022 (The black circle represents the cold vortex circulation, the letters A, B, C and D represent the centers of the cold vortex; wind vectors, Unit: m·s-1; the purple solid line represents trough lines, the area surrounded by the red line indicates the Tianjin area)

Fig.4 T-ln P diagram at Beijing station before three extreme short-term heavy rainfall processes in Tianjin in 2022

Fig.5 The increment rainfall intensity compared to the previous hour at different stations and times, as well as the maximum values of vertical velocity (w) and the specific humidity difference between 1 000 hPa and 850 hPa （?q1000-850） in the first 4 hours during three extreme short-term heavy rainfall processes in Tianjin in 2022

Fig.6 The time-height sections of water vapor flux divergence （the color shaded， Unit： 10-7 g·hPa-1·cm-2·s-1） and pseudo equivalent potential temperature θse （isolines， Unit： K） at different stations during three extreme short-term heavy rainfall processes in Tianjin in 2022

Fig.7 The increment of rainfall intensity compared to the previous hour, dew-point temperature and temperature in the previous hour of the ground at different stations and times during the three extreme short-term heavy rainfall processes in Tianjin in 2022

Fig.8 The vertical profile of the combinations reflectivity factor along the straight line of the strongest area of convective storm echo at Tanggu Station during three extreme short-term heavy rainfall processes in Tianjin in 2022 （Unit： dBZ）

Fig.9 The increment of rainfall intensity compared to the previous hour at different stations and times, as well as the maximum values of CR, ET and VIL in the previous hour during three extreme short-term heavy rainfall processes in Tianjin in 2022

Fig.10 The ground wind fields (wind vectors, Unit: m·s?1) and basic reflectivity at 1.5° elevation angle (the color shaded, Unit: dBZ) at different times during three extreme short-term heavy rainfall processes in Tianjin in 2022 (The red dotted line represents the ground convergence line, the letter D represents the center of the vortex)

References 24

[1]	曹艳察, 郑永光, 孙继松, 等, 2024. 东北冷涡背景下三类区域性强对流天气过程时空分布和环境特征对比分析[J]. 气象学报, 82(1): 22-36.
[2]	陈涛, 孙军, 谌芸, 等, 2019. 广州“5·7”局地突发特大暴雨过程的数值可预报性分析[J]. 气象, 45(9):1199-1 212.
[3]	褚颖佳, 郭飞燕, 高帆, 等, 2023. 冷涡影响下两次不同类型强对流过程对比分析[J]. 干旱气象, 41(2):279-289. DOI
[4]	段云霞, 崔锦, 李得勤, 等, 2024. 东北冷涡背景下两次强降水干侵入特征对比分析[J]. 干旱气象, 42(3): 357-366. DOI
[5]	刘胜男, 屈丽玮, 张蔚然, 等, 2024. 陕北两次不同强度的区域性暴雨过程特征对比[J]. 高原山地气象研究, 44(3): 48-57.
[6]	罗金芳, 吴君涛, 姜敏, 等, 2024. 鄂东北春季三类典型极端强降水特征分析[J]. 沙漠与绿洲气象, 18(2): 44-51.
[7]	齐铎, 袁美英, 周奕含, 等, 2020. 一次东北冷涡过程的结构特征与降水关系分析[J]. 高原气象, 39(4): 808-818. DOI
[8]	孙虎林, 黄焕卿, 于庆龙, 等, 2019. 2012—2017年珠江口海区短时强对流天气灾害的统计分析[J]. 海洋预报, 36(4): 35-43.
[9]	孙建华, 周玉淑, 傅慎明, 等, 2024. 近十年我国涡旋系统的研究进展[J]. 大气科学, 48(1): 228-260.
[10]	唐鹏, 张丽, 陈天宇, 等, 2024. 2019年6月下旬中昆仑山北坡两场强降水对比分析[J]. 沙漠与绿洲气象, 18(2): 27-34.
[11]	王万筠, 殷海涛, 窦策伟, 等, 2019. 天津地区三次低涡暴雨过程的诊断分析[J]. 气象与环境科学, 42(3): 42-50.
[12]	王莹, 王艳春, 易笑园, 等, 2024. 天津一次夜间极端短时强降水的中尺度特征及成因探究[J]. 气象, 50(12): 1 451-1 466.
[13]	王宗敏, 李江波, 王福侠, 等, 2015. 东北冷涡暴雨的特点及其非对称结构特征[J]. 高原气象, 34(6): 1 721-1 731.
[14]	魏庆, 周威, 吴容, 等, 2023. 盆地西部一次极端短时强降水过程的多源资料分析[J]. 高原山地气象研究, 43(2): 19-27.
[15]	徐灵芝, 许长义, 卜清军, 等, 2019. 非常规资料在天津沿海一次灾害暴雨过程中的应用[J]. 气象与环境科学, 42(3): 68-77.
[16]	杨吉, 郑媛媛, 夏文梅, 等, 2020. 东北冷涡影响下江淮地区一次飑线过程的模拟分析[J]. 气象, 46(3): 357-366.
[17]	易笑园, 陈宏, 张庆, 等, 2024. 渤海湾西岸一次局地极端短时强降水事件的成因分析[J]. 海洋气象学报, 44(3): 1-13.
[18]	俞小鼎, 2013. 短时强降水临近预报的思路与方法[J]. 暴雨灾害, 32(3): 202-209.
[19]	郁珍艳, 何立富, 范广洲, 等, 2011. 华北冷涡背景下强对流天气的基本特征分析[J]. 热带气象学报, 27(1): 89-94.
[20]	张楠, 杨晓君, $\boxed{\hbox{何群英}}$, 等, 2020. 一次台风残涡引发的天津局地暴雨中尺度对流过程分析[J]. 气象与环境学报, 36(4): 1-10.
[21]	张文龙, 崔晓鹏, 黄荣, 等, 2019. 北京“623”大暴雨的强降水超级单体特征和成因研究[J]. 大气科学, 43(5): 1 171-1 190.
[22]	张武龙, 杨康权, 康岚, 等, 2024. 川西高原和攀西地区不同级别短时强降水环境参量特征对比分析[J]. 高原山地气象研究, 44(2): 75-82.
[23]	郑永光, 宋敏敏, 2021. 冷涡影响中国对流性大风与冰雹的分布特征[J]. 热带气象学报, 37(5/6): 710-720.
[24]	ZHANG C, ZHANG Q, WANG Y, et al, 2008. Climatology of warm season cold vortices in East Asia:1979-2005[J]. Meteorology and Atmospheric Physics, 100(1): 291-301.