A Preliminary Analysis of the Characteristics of Drylines and Its Triggering Convections in the Hetao and Surrounding Regions

  • Yiping ZHANG ,
  • Xiaoding YU ,
  • Di WANG ,
  • Yakai GUO ,
  • Wenbo WU ,
  • Xiaozhen HAO
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  • <sup>1.</sup>Henan Key Laboratory of Agrometeorological Ensuring and Applied Technique,Zhengzhou 450003,Henan,China;<sup>2.</sup>Henan Meteorological Observatory,Zhengzhou 450003,Henan,China;<sup>3.</sup>China Meteorological Administration Training Center,Beijing 100081,China

Received date: 2020-02-19

  Online published: 2021-10-28

Abstract

Based on the conventional aerological sounding and surface data and the satellite images, the paper preliminary discussed 52 convective weather processes triggered by drylines in Hetao and its surrounding regions during May to September from 2013 to 2017, and statistically analyzed the temporal and spatial distribution, the influence systems and the characteristics of surface meteorological elements and sounding environmental parameters around the drylines.The result shows that, (1) the drylines in the Hetao and its vicinity areas mainly appears on the north of Hetao, including its northwest and northeast, and the inner region, with the main orientations from east-northeast to south-southwest and northeast to southwest, the width of 80~100 km, and the length of about 300~800 km.The occurrence frequency of drylines has obvious annual change with the annual average of 10.4 times, that always appearing during June to August and at 11:00(Beijing time, the same as after) -17:00, especially at 14:00.(2) The convective weather processes triggered by drylines mostly occur in the situation of high-altitude northwest flow and Mongolia vortex with the influence of low trough south of the vortex, associated with convergence lines or shear lines in the atmospheric boundary layer.The drylines is mostly located at the intersection of the westerly flow in the south and southeast of the continental low and Mongolia low (or cyclone) and the southerly flow behind the coastal high in the surface weather chart.(3)The statistical characteristics of ground factors are as follows: the temperature on the dry side of the drylines is higher than on the wet side with the difference of 1~2 ℃.The sea level pressure on the wet side is slightly higher than that on the dry side and the pressure difference between the two sides generally ranges from 1.5~2 hPa.In addition, one of the most important features is the large dew point difference on both sides, with the average of 11 ℃, primarily between 10 and 16 ℃.The dew point gradient is generally above 10 ℃·(100 km)-1, with the maximum of 20 ℃·(100 km)-1 or above.The westerly wind is prevalent on the dry side while the southly wind on the wet side, producing the convergence flow field, which is another important feature.(4) According to the statistical results of sounding environmental parameters, the atmospheric precipitable water and the specific humidity of 700 and 850 hPa on the wet side are significantly larger than those on the dry side.The average atmospheric precipitable water on the wet and dry side are 2.5 cm and 1.5 cm separately.The average convective available potential energy on the wet side reaches the moderate intensity of 1440 J·kg-1.while on the dry side less than 10 J·kg-1, and the thermal instability on the wet side is more abundent.The deep vertical wind shear of 0~6 km on both sides is mostly moderate or above and slightly larger on the dry side, with the average of 12.2 m·s-1 and 13.1 m·s-1 on the wet and dry side respectively.

Cite this article

Yiping ZHANG , Xiaoding YU , Di WANG , Yakai GUO , Wenbo WU , Xiaozhen HAO . A Preliminary Analysis of the Characteristics of Drylines and Its Triggering Convections in the Hetao and Surrounding Regions[J]. Plateau Meteorology, 2021 , 40(5) : 1024 -1037 . DOI: 10.7522/j.issn.1000-0534.2020.00068

References

[1]Fritsch J M, Carbone R E, 2004.Improving quantitative precipitation forecasts in warm season: an USWRP research and development strategy [J].Bulletin of the American Meteorological Society, 85(7): 955-965.DOI: 10.1175/BAMS-85-7-955.
[2]Fujita T T, 1958.Structure and movement of a dry front[J].Bulletin of the American Meteorological Society, 39, 574-582.
[3]Hoch J, Markowski P, 2005.A climatology of springtime dryline position in the US Great Plains region[J].Journal of Climate, 18(12): 2132-2137.DOI: 10.1175/JCLI3392.1.
[4]Johns R H, Hirt W D, 1987.Derechos: widespread convectively induced windstorms[J].Weather and Forecasting.2(1): 32-49.DOI: 10.1175/1520-0434(1987)002<0032: DWCIW>2.0.CO; 2.
[5]Meng Z Y, Yan D C, Zhang Y J, 2013.General Features of squall lines in East China[J].Monthly Weather Review, 141(5): 1629-1647.DOI: 10.1175/MWR-D-12-00208.1.
[6]Olsen D A, Junker N W, Korty B, 1995.Evaluation of 33 years of quantitative precipitation forecasting at the NMC[J].Weather and Forecasting, 10(3): 498-511.DOI: 10.1175/1520-0434(1995)0102.0.CO; 2.
[7]Parsons D B, Shapiro M A, Miller E, 2000.The mesoscale structure of a nocturnal dryline and of a frontal-dryline merger[J].Monthly Weather Review, 128(11): 3824-3838.
[8]Peterson R E, 1983.The west Texas dryline: occurrence and behavior[J].Preprints 13th Conf On Severe Local Storms Tulsa OK.Australian Meteorological Magazine, J9-J11.
[9]Rhea J O, 1966.A study of thunderstorm formation along drylines[J].Journal of Applied Meteorology, 5, 58-63.DOI: 10.1175/1520-0450(1966)0052.0.CO; 2.
[10]Schaefer J T, 1974a.The life cycle of the dryline[J].Journal of Applied Meteorology, 13(4): 444-449.DOI: 10.1175/1520-0450(1974)013<0444: TLCOTD>2.0.CO; 2.
[11]Schaefer J T, 1974b.A simulative model of dryline motion[J].Journal of Applied Meteorology, 31(4): 956-964.DOI: 10.1175/1520-0469(1974)0312.0.CO; 2.
[12]Schaefer J T, 1973.The motion and morphology of the dryline.NOAA Tech.Memo.ERL NSSL-66, 81.PP.
[13]Schaefer J T, 1986.The dryline Mesoscale Meteorology and Forecasting[J].Bulletin of the American Meteorological Society, 549-572.
[14]Schultz D M, Weiss C C, Hoffman P M, 2007.The Synoptic Regulation of Dryline Intensity.Monthly Weather Review, 135(5): 1699-1709.DOI: 10.1175/MWR3376.1.
[15]Thompson R L, Edwards R, 1999.An overview of environmental conditions and forecast implications of the 3 May 1999 tornado outbreak[J].Weather and Forecasting, 15(6): 682-699.DOI: 10. 1175/1520- 0434(2000)0152.0.CO; 2.
[16]Ziegler C L, Rasmussen E N, 1998.The initiation of moist convection at the dryline: forecasting issues from a case study perspective[J].Weather and Forecasting, 13, 1106-1131.
[17]曾明剑, 王桂臣, 吴海英, 等, 2015.基于中尺度数值模式的分类强对流天气预报方法研究[J].气象学报, 73(5): 868-882.
[18]方祖亮, 俞小鼎, 王秀明, 2020.东北暖季干线统计分析[J].气象学报, 78(2): 260-276.
[19]费海燕, 王秀明, 周小刚, 等, 2016.中国强雷暴大风的气候特征和环境参数分析[J].气象, 42(12): 1513-1521.DOI: 10.7519/j.issn.1000-0526.2016.12.009.
[20]胡启元, 王楠, 李萍云, 等, 2020.陕西后向传播雷暴统计特征与机理初步研究[J].高原气象, 39(5): 973-985.DOI: 10.7522/j.issn.1000-0534.2019.00099.
[21]雷蕾, 孙继松, 王国荣, 等, 2012.基于中尺度数值模式快速循环系统的强对流天气分类概率预报试验[J].气象学报, 70(4): 752-765.
[22]雷雨顺, 吴宝俊, 吴正华, 1978.用不稳定能量理论分析和预报夏季强风暴的一种方法[J].大气科学, 2(4): 297-306.DOI: 10. 3878/j.issn.1006-9895.1978.04.04,
[23]孙继松, 戴建华, 何立富, 等, 2014.强对流天气预报的基本原理与技术方法[M].北京: 气象出版社, 282.
[24]孙淑清, 孟婵, 1992.中-<i>β</i>尺度干线的形成与局地强对流暴雨[J].气象学报, 50(2): 180-189.DOI: 10.11676/qxxb1992.020.
[25]陶祖钰, 范俊红, 李开元, 等, 2016.谈谈气象要素(压、 温、 湿、 风)的物理意义和预报应用价值[J].气象科技进展, 6(5): 59-64.
[26]王晓玲, 王海燕, 王珊珊, 等, 2015.边界层准静止干线触发的中尺度暴雨机理分析[J].高原气象, 34(5): 1310-1322.DOI: 10. 7522/j.issn.1000-0534.2014.00056.
[27]王秀明, 俞小鼎, 周小刚, 2015.中国东北龙卷研究: 环境特征分析[J].气象学报, 73(3): 425-441.DOI: 10.11676/qxxb2015.031.
[28]王秀明, 俞小鼎, 周小刚, 等, 2012."6.3"区域致灾雷暴大风形成及维持原因分析[J].高原气象, 31 (2): 504-514.
[29]王研峰, 黄武斌, 王聚杰, 等, 2019.一次甘肃天水强冰雹的雷达回波特征及成因分析[J].高原气象, 38(2): 368-376.DOI: 10. 7522/j.issn.1000-0534.2018.00077.
[30]许爱华, 孙继松, 许东蓓, 等, 2014.中国中东部强对流天气的天气形势分类和基本要素配置特征[J].气象, 40(4): 400-411.DOI: 10.7519/j.issn.1000-0526.2014.04.002.
[31]许东蓓, 苟尚, 肖玮, 等, 2018.两种类型短时强降水形成机理对比分析-以甘肃两次短时强降水过程为例[J].高原气象, 37(2): 524-534.DOI: 10.7522/j.issn.1000-0534.2017.00056.
[32]许东蓓, 许爱华, 肖玮, 等, 2015.中国西北四省区强对流天气形势配置及特殊性综合分析[J].高原气象, 34(4): 973-981.DOI: 10.7522/j.issn.1000-0534.2014.00102.
[33]俞小鼎, 王秀明, 李万莉, 等, 2020.雷暴与强对流临近预报[M].北京: 气象出版社, 416.
[34]俞小鼎, 姚秀萍, 熊廷南, 等, 2006.多普勒天气雷达原理与业务应用[M].北京: 气象出版社, 314.
[35]俞小鼎, 周小刚, 王秀明, 2012.雷暴与强对流临近天气预报技术进展[J].气象学报, 70(3): 311-337.DOI: 10.11676/qxxb2012.030.
[36]张桂莲, 杭月荷, 付丽娟, 等, 2020.“列车效应”诱发的一次河套地区致灾暴雨成因[J].高原气象, 39(4): 788-795.DOI: 10. 7522/j.issn.1000-0534.2019.00122.
[37]张小玲, 张涛, 刘鑫华, 等, 2010.中尺度天气的高空地面综合图分析[J].气象, 36(7): 143-150.
[38]张一平, 吴蓁, 苏爱芳, 等, 2013.基于流型识别和物理量要素分析河南强对流天气特征[J].高原气象, 32(5): 1492-1502.DOI: 10.7522/j.issn.1000-0534.2012.00139.
[39]郑媛媛, 姚晨, 郝莹, 等, 2011.不同类型大尺度环流背景下强对流天气的短时临近预报预警研究[J].气象, 37(7): 795-801.DOI: 10.7519/j.issn.1000-0526.2011.7.003.
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