Macro and Micro Characteristics of Extreme Heavy Rainfall Process in Jincheng of Shanxi Province on 11 July 2021

  • Hongxia WANG ,
  • Aimei MIAO ,
  • Guiqiang QIU ,
  • Zhiyong QU ,
  • Junmei YANG ,
  • Linyi Lü
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  • 1. Shanxi Meteorological Observatory,Taiyuan 030006,Shanxi,China
    2. Shani Meteorological Information Center,Taiyuan 030006,Shanxi,China
    3. Shanxi Artificial Precipitation Enhancement and Lightning Protection Technical Center,Taiyuan 030032,Shanxi,China
    4. Henan Meteorological Observatory,Zhengzhou 450003,Henan,China

Received date: 2022-08-04

  Revised date: 2022-12-01

  Online published: 2023-09-26

Abstract

Using ERA5 reanalysis data, automatic weather station data, FY4A satellite data, Doppler radar and Laser raindrop spectrometer data, the macro and micro characteristics of the extreme rainfall process in Jincheng, Shanxi Province on July 11, 2021 are analyzed. The results show that: (1) This extreme rainfall in Jincheng is the second highest rainfall in July since 1961. The strong divergence on the right of the upper jet entrance, the convergence of wind speed at the exit of lower jet, and the strong convergence near the warm shear line of the low vortex are the macro dynamic conditions of the extreme rainfall. The water vapor transfer by the low-level jet and the whole layer precipitable water above 65 mm, are the macro water vapor conditions, while 500 hPa trough is ahead of the cold shear lines on 700 hPa and 850 hPa is the macro dynamic unstable condition for this extreme heavy rainfall. (2) The extreme heavy rainfall is located in an irregular quadrilateral area surrounded by 500 hPa trough, 850 hPa and 700 hPa warm shear lines and ground dry line, which overlaps with the areas controlled by 500 hPa T-Td≤4 ℃, 700 hPa T-Td≤3 ℃, 850 hPa T-Td≤2 ℃, K index≥38 ℃ and Si index≤-1 ℃. The maximum extreme precipitation occurs in the large value area of the brightness temperature gradient on the southwest side of the convective cloud cluster and the low brightness temperature area in the southwest of the cloud cluster, which is within 0~30 km of the surface dry line and surface mesoscale shear lines. (3) The meso-α-scale warm shear line on 850 hPa, ground dry line and meso-β-scale surface shear lines and convergence lines triggered this extreme heavy rainfall in Jincheng. The strengthened easterly air flow on the surface layer is forced to converge and lift when it meets the trumpet shaped terrain opening eastward formed by Zhongtiao Mountain, Wangwu Mountain, Xionger Mountain and Song Mountain, promoting the convergence and rising movement in extreme precipitation areas and increasing the precipitation. (4) The lightning is located in the area where the cloud top brightness temperature is ≤220 K and the large value area of cloud top brightness temperature gradient. The peak value of lightning frequency is 10~35 minutes ahead of the peak value of precipitation, which is very significant for early warning of precipitation peak value. (5) The meso-α-scale low vortex warm shear system stimulates the development of the meso-α-scale vortex cloud system. The development and evolution of convective cloud clusters are backward development type. In the meso-α-scale vortex warm shear line cloud system, there are several organized meso-γ-scale convective cells with independent echo, which are guided by the southwest air flow moving to the northeast and form a train effect in the extreme precipitation area. The convective cell that leads to the largest rain peak in Manghe scenic area has the typical supercell storm structural characteristics. (6) The significant increase of cloud water content promotes the enhancement of precipitation intensity, and the high area of supercooled water content in -20~0 ℃ layer corresponds to the extremely heavy precipitation area on the ground. The extreme precipitation in Jincheng is stratiform and cumulus mixed cloud precipitation, and the particle size distribution of raindrops is wide. Small and medium raindrops with high concentration are the main contributors of extreme heavy precipitation. Compared with the typical continental convective precipitation process, the average range of the average generalized intercept common logarithm (lg(NW )) of raindrops in this extreme heavy precipitation process is large, but the mass weighted average diameter (DM ) is slightly smaller than the average range.

Cite this article

Hongxia WANG , Aimei MIAO , Guiqiang QIU , Zhiyong QU , Junmei YANG , Linyi Lü . Macro and Micro Characteristics of Extreme Heavy Rainfall Process in Jincheng of Shanxi Province on 11 July 2021[J]. Plateau Meteorology, 2023 , 42(5) : 1232 -1246 . DOI: 10.7522/j.issn.1000-0534.2022.00103

References

null
Bringi V N Chandrasekar V Hubbert J, et al, 2003.Raindrop size distribution in different climatic regimes from Disdrometer and Dual-Polarized Radar analysis[J]. Journal of Atmospheric Sciences, 60: 354-365.
null
Doswell C A Brooks H E Maddox R A1996. Flash?ood forecasting: an ingredients-based methodology[J]. Weather and Forecasting11(4): 560–581.
null
Guhathakurta P Sreejith O P Menon P A2011. Impact of climate change on extreme rainfall events and flood risk in India[J]. Journal of Earth System Science120(3): 359-373.
null
Lehmann J Coumou D Frieler K2015. Increased record-breakingprecipitation events under global warming [J]. Climatic Change132(4): 501-515.
null
Orlanski L A1975. A rational subdivision of scales for atmospheric processes[J]. Bulletin of the American Meteorological Society, 56: 527-530.
null
Wang G L Zhang D L Sun J S2021. A multiscale analysis of a nocturnal extreme rainfall event of 14 July 2017 in Northeast China[J]. Monthly Weather Review149(1): 173-186.
null
Wu Y H Liu L P2017. Statistical characteristics of raindrop size distribution in the Tibetan Plateau and Southern China [J]. Advances in Atmospheric Sciences34(6): 727-736.
null
Xia R D Zhang D L2019. An observational analysis of three extreme rainfall episodes of 19-20 July 2016 along the Taihang Mountains in North China[J]. Monthly Weather Review, 147: 4199-4220.
null
丛芳, 刘黎平, 2011.新一代天气雷达与地面雨量资料的综合分析[J].气象37(5): 532-539.
null
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.
null
李哲, 高艳红, 蒋盈沙, 等, 2022. 城市与湖泊对华东地区一次切变线暴雨过程的影响[J]. 高原气象41(3): 655-670. DOI: 10. 7522/j. issn. 1000-0534. 2021. 00067 .
null
刘红武, 胡燕, 苏涛, 等, 2021. 2019年主汛期湖南两次致灾暴雨过程对比分析[J]. 高原气象40(5): 1101-1114. DOI: 10. 7522/j. issn. 1000-0534. 2020. 00087 .
null
刘红燕, 雷恒池, 2006.基于地面雨滴谱资料分析层状云和对流云降水的特征[J].大气科学30(4): 693-702.
null
刘西川, 高太长, 刘磊, 等, 2014.基于粒子成像测速技术的雨滴微物理特性研究[J].物理学报63(2): 292-303.
null
刘晓阳, 杨洪平, 李建通, 等, 2010.新一代天气雷达定量降水估测集成系统[J].气象36(4): 90-95.
null
柳臣中, 周筠臖, 谷娟, 等, 2015.成都地区雨滴谱特征[J].应用气象学报26(1): 112-121.
null
卢珊, 胡泽勇, 付春伟, 等, 2022. 黄土高原夏季极端降水及其成因分析[J]. 高原气象41(1): 241-254. DOI: 10. 7522/j. issn. 1000-0534. 2021. 00027 .
null
罗俊颉, 贺文彬, 李金辉, 等, 2012.2003年春季陕西省层状云降水的雨滴谱特征[J].气象38(9): 1129-1134.
null
明虎, 王敏仲, 阮征, 等, 2014.风廓线雷达对天山中部一次层状云降水过程的探测分析[J].气象40(12): 1513-1521.
null
牛若芸, 刘凑华, 刘为一, 等, 2018. 1981-2015年中国95°E以东区域性暴雨过程时、 空分布特征[J]. 气象学报76(2): 182-195.
null
史月琴, 高松影, 孙晶, 等, 2022. 辽宁一次区域性暴雨的特征条件与成因分析[J]. 高原气象41(3): 630-645. DOI: 10. 7522/j. issn. 1000-0534. 2021. 00094 .
null
王可法, 张卉慧, 张伟, 等, 2011.Parsivel激光雨滴谱仪观测降水中异常数据的判别及处理[J].气象科学31(6): 732-736.
null
徐珺, 毕宝贵, 谌芸, 等, 2018. “5·7”广州局地突发特大暴雨中尺度特征及成因分[J].气象学报76(4): 511-524.
null
杨晓军, 叶培龙, 徐丽丽, 等, 2022. 一次青藏高原东北侧边坡强对流暴雨的中尺度对流系统演变特征[J]. 高原气象41(4): 839-849. DOI: 10. 7522/j. issn. 1000-0534. 2021. 00023 .
null
杨晓亮, 王秀明, 杨敏, 等, 2022. 副热带高压控制下河北局地强降水触发与维持机制分析[J].气象48(6): 677-690.
null
钟敏, 车钦, 张蒙蒙, 等, 2020. 华中区域极端降水天气形势及物理量异常度特征[J].气象46(4): 503-516.
null
周旋, 孙继松, 张琳娜, 等, 2022. 华北地区持续性极端暴雨过程的分类特征[J].气象学报78(5): 761-777.
null
朱亚乔, 刘元波, 2013.地面雨滴谱观测技术及特征研究进展[J].地球科学进展28(6): 685-694.
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