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Radar Characteristics of Straight-line Damaging Wind Producing Supercell Storms
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摘要: 基于中国东部平原地区31部S波段多普勒天气雷达数据和实况记录, 筛选出2002—2020年56次由超级单体风暴导致的25 m·s-1以上的直线型大风事件, 分析超级单体风暴多普勒天气雷达回波特征与其导致的直线型大风间关系, 获得产生直线型致灾大风的超级单体的量化结构特征, 为超级单体产生的大风的主客观监测预警提供参考。统计结果表明:产生致灾大风的超级单体60 dBZ以上强回波深厚, 平均厚度为5.5 km, 中层径向辐合特征显著, 最大中层径向辐合超过29 m·s-1;中气旋强度中等, 平均旋转速度为18.4 m·s-1, 可向上伸展至对流层中上层(7 km高度);超级单体反射率因子核下降、中气旋核下降、29 m·s-1以上中层径向辐合以及垂直积分液态水含量减小是预警直线型大风的重要指标;下击暴流导致的明显且对称的低仰角辐散速度对仅在4次事件中出现, 超级单体风暴由于其移动性, 不易出现对称的下击暴流。Abstract: Based on S-band Doppler weather radar data and damaging wind gust records, 56 damaging straight-line winds events from 2002 to 2020 above 25 m·s-1 caused by supercell storms are investigated. The relationship between Doppler weather radar echo characteristics and damaging straight-line winds caused by supercell storm is analyzed to obtain quantitative description of the structural characteristics. The results will be benefit for subjective and objective monitoring and warning of damaging straight-line winds produced by supercell storms. Superstorm is a highly organized strong convective storm with a long-life history, according to the statistical results, and it is possible to judge the potential of supercell storms that produce damaging gale by the Doppler weather radar echo structures. It shows that, in the supercell storm that produces damaging straight-line winds, the strong reflectivity echo above 60 dBZ is deep, and the average echo thickness of strong reflectivity is 5.5 km. The core height of the strong reflectivity of most supercell storms are above 6 km which indicate that the updraft in this kind of supercell storms can be very strong. The mid altitude radial convergence (MARC), the reflectivity core decline and rear inflow jet (RIJ) are important for warning of damaging straight-line winds features. The MARC is significant, the largest speed difference of the MARC is above 29 m·s-1 in most cases. The mesocyclone is mainly of medium intensity, the rotating speed of mesocyclone is 18.4 m·s-1 on average, which can extend up to the upper troposphere (7 km). The descending of supercell storm reflectivity core, the descending of mesocyclone core, the MARC which can exist for a long time with 29 m·s-1 largest radar radial speed difference and the decrease of vertically integrated liquid water content (VIL) value can be used as the warning indices of the damaging straight-line winds. Among them, the descending of supercell storm reflectivity core can give 15-minute precursor signal, the descending of mesocyclone core can give 8-minute precursor signal, the significant MARC can give 30-minute precursor signal, and the descending of VIL value can give 17-minute early warning signal of damaging winds. Based on narrow-band echo, the proportion that can be recognized as gust front of the supercell storm is low, and only a few damaging straight-line winds can be identified from the moving speed of storm or gust front characteristics. There are only 4 obvious low-level divergence velocity pairs identified in 56 cases, which indicate that most supercell storms produce asymmetric downburst because of horizontal movements.
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图 2 产生致灾大风的超级单体风暴718个样本的强回波(不低于60 dBZ反射率因子) 厚度(a)、45个样本的反射率因子核每个体扫下降幅度(b)以及下降提前时间(c)、56个样本的大风发生前反射率因子核最大扩展高度(d)箱线图
(线段最高点为统计最大值, 最低点为统计最小值, 箱线上部框线为第75百分位值, 箱线下部框线为第25百分位值, 箱内线为中位数, ·为平均值，下同)
Fig. 2 Boxplot of thickness of 718 samples (with reflectivity fator above 60 dBZ) (a), reflectivity core decline(b) and lead time of reflectivity core decline(c) of 45 samples, maximum extension height before strong wind in 56 samples(d) in straight-line damaging wind producing supercell storms
(the highest point is the statistical maximum, the lowest point is the statistical minimum, the box upper frame line is the 75th percentile threshold value, the lower frame line is the 25th percentile threshold value, line inside box is the median, · is the average, the same hereinafter)
图 3 致灾大风事件对应的461个样本的超级单体风暴垂直积分液态水含量(a)、18个样本的垂直积分液态水含量下降幅度(b)与垂直积分液态水含量每个体扫减小量(c)以及垂直积分液态水含量下降提前大风出现时间(d)箱线图
Fig. 3 Boxplot of vertical integrated liquid water content(VIL)of 461 samples(a), reduction of VIL(b), VIL descending per volume scanning(c) and lead time of VIL decline before strong wind(d) of 18 samples in straight-line damaging wind producing supercell storms
图 4 产生致灾大风的超级单体风暴内577个样本的中气旋最大旋转速度(a)、32个样本的核心下降幅度(b)及下降提前时间(c)、577个样本的中气旋最大切变高度(d)箱线图
Fig. 4 Boxplot of maximum rotation speed of 577 samples(a), core decline(b) and lead time of core decline(c) of 32 samples,height of maximum rotation speed of 577 samples(d) in straight-line damaging wind producing supercell storms
图 5 产生致灾大风的超级单体401个样本的风暴中层径向辐合最强辐合值(a)、47个样本的提前时间(b)、401个样本的底高(c)和顶高(b)箱线图
Fig. 5 Boxplot of mid altitude radial convergence strongest convergence of 401 samples(a), lead time of 47 samples(b), bottom height(c) and top height(d) of 401 samples in straight-line damaging wind producing supercell storms
图 6 致灾大风事件对应的超级单体风暴内253个样本的后侧入流急流强度(a)、底高(b)和顶高(c)以及12个样本的核心高度下降幅度(d)箱线图
Fig. 6 Boxplot of intensity(a), bottom height(b) and top height(c) of 253 rear inflow jet samples, core height decline of 12 rear inflow jet samples(d) in straight-line damaging wind producing supercell storms
图 7 产生致灾大风的超级单体462个样本的风暴顶辐散强度(a)及最强风暴顶辐散所在高度(b)、247个样本的低仰角径向速度大值区强度(c)及其所在高度(d)箱线图
Fig. 7 Boxplot of maximum storm top divergence intensity(a) and its height(b) of 462 samples, strong radial velocity intensity at low elevation(c) and its height(d) of 247 samples in straight-line damaging wind producing supercell storms
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[1] 俞小鼎,王秀明,李万莉,等.雷暴与强对流临近预报.北京:气象出版社,2020.Yu X D, Wang X M, Li W L, et al. The Nowcasting of Thunderstorms and Severe Convective. Beijing: China Meteorological Press, 2020. [2] Johns R H, Doswell C A. Severe local storms forecasting. Wea Forecasting, 1992, 7(4): 588-612. doi: 10.1175/1520-0434(1992)007<0588:SLSF>2.0.CO;2 [3] Browning K. The structure and mechanisms of hailstorms. Amer Meteor Soc Monograph, 1977, 38: 1-36. [4] Fujita T T. Tornadoes and downbursts in the context of generalized planetary scales. J Atmos Sci, 1981, 38(8): 1511-1534. doi: 10.1175/1520-0469(1981)038<1511:TADITC>2.0.CO;2 [5] 郑媛媛, 俞小鼎, 方翀, 等. 一次典型超级单体风暴的多普勒天气雷达观测分析. 气象学报, 2004, 62(3): 317-328. doi: 10.3321/j.issn:0577-6619.2004.03.006Zheng Y Y, Yu X D, Fang C, et al. Analysis of a strong classic supercell storm with Doppler weather radar data. Acta Meteor Sinica, 2004, 62(3): 317-328. doi: 10.3321/j.issn:0577-6619.2004.03.006 [6] 翟丽萍, 农孟松, 梁维亮, 等. 造成临桂极端大风的超级风暴单体观测分析. 暴雨灾害, 2019, 38(4): 346-353. doi: 10.3969/j.issn.1004-9045.2019.04.007Zhai L P, Nong M S, Liang W L, et al. Analysis of the observations for a supercell causing extreme gale in Lingui. Torrential Rain Disasters, 2019, 38(4): 346-353. doi: 10.3969/j.issn.1004-9045.2019.04.007 [7] 马淑萍, 王秀明, 俞小鼎. 极端雷暴大风的环境参量特征. 应用气象学报, 2019, 30(3): 292-301. doi: 10.11898/1001-7313.20190304Ma S P, Wang X M, Yu X D. Environmental parameter characteristics of severe wind with extreme thunderstorm. J Appl Meteor Sci, 2019, 30(3): 292-301. doi: 10.11898/1001-7313.20190304 [8] 陈明轩, 俞小鼎, 谭晓光, 等. 对流天气临近预报技术的发展与研究进展. 应用气象学报, 2004, 15(6): 754-766. doi: 10.3969/j.issn.1001-7313.2004.06.015Chen M X, Yu X D, Tan X G, et al. A brief review on the development of nowcasting for convective storms. J Appl Meteor Sci, 2004, 15(6): 754-766. doi: 10.3969/j.issn.1001-7313.2004.06.015 [9] 俞小鼎, 张爱民, 郑媛媛, 等. 一次系列下击暴流事件的多普勒天气雷达分析. 应用气象学报, 2006, 17(4): 385-393. doi: 10.3969/j.issn.1001-7313.2006.04.001Yu X D, Zhang A M, Zheng Y Y. Doppler radar analysis on a series of downburst events. J Appl Meteor Sci, 2006, 17(4): 385-393. doi: 10.3969/j.issn.1001-7313.2006.04.001 [10] 朱君鉴, 刁秀广, 曲军, 等. 4.28临沂强对流灾害性大风多普勒天气雷达产品分析. 气象, 2008, 34(12): 21-26;129. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX200812004.htmZhu J J, Diao X G, Qu J, et al. Study on the damage wind with Doppler radar products in Linyi, Shandong on 28 April 2006. Meteor Mon, 2008, 34(12): 21-26;129. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX200812004.htm [11] 钱传海, 张金艳, 应冬梅, 等. 2003年4月江西一次强对流天气过程的诊断分析. 应用气象学报, 2007, 18(4): 460-467. doi: 10.3969/j.issn.1001-7313.2007.04.006Qian C H, Zhang J Y, Ying D M, et al. A severe convection weather of Jiangxi in April 2003. J Appl Meteor Sci, 2007, 18(4): 460-467. doi: 10.3969/j.issn.1001-7313.2007.04.006 [12] 谢健标, 林良勋, 颜文胜, 等. 广东2005年"3·22"强飑线天气过程分析. 应用气象学报, 2007, 18(3): 321-329. doi: 10.3969/j.issn.1001-7313.2007.03.008Xie J B, Lin L X, Yan W S, et al. Dynamic diagnosis of an infrequent squall line in Guangdong on March 22, 2005. J Appl Meteor Sci, 2007, 18(3): 321-329. doi: 10.3969/j.issn.1001-7313.2007.03.008 [13] 王秀明, 俞小鼎, 周小刚, 等. "6.3"区域致灾雷暴大风形成及维持原因分析. 高原气象, 2012, 31(2): 504-514. https://www.cnki.com.cn/Article/CJFDTOTAL-GYQX201202025.htmWang X M, Yu X D, Zhou X G, et al. Study on the formation and evolution of '6.3' damage wind. Plateau Meteor, 2012, 31(2): 504-514. https://www.cnki.com.cn/Article/CJFDTOTAL-GYQX201202025.htm [14] 王福侠, 俞小鼎, 裴宇杰, 等. 河北省雷暴大风的雷达回波特征及预报关键点. 应用气象学报, 2016, 27(3): 342-351. doi: 10.11898/1001-7313.20160309Wang F X, Yu X D, Pei Y J, et al. Radar echo characteristics of thunderstorm gales and forecast key points in Hebei Province. J Appl Meteor Sci, 2016, 27(3): 342-351. doi: 10.11898/1001-7313.20160309 [15] 程月星, 孙继松, 戴高菊, 等. 2016年北京地区一次雷暴大风的观测研究. 气象, 2018, 44(12): 1529-1541. doi: 10.7519/j.issn.10000526.2018.12.003Cheng Y X, Sun J S, Dai G J, et al. Study on a thunderstorm event over Beijing in 2016. Meteor Mon, 2018, 44(12): 1529-1541. doi: 10.7519/j.issn.10000526.2018.12.003 [16] 刁秀广, 张新华, 朱君鉴. CINRAD/SA雷达风暴趋势产品在冰雹和大风预警中的应用. 气象科技, 2009, 37(2): 230-233;259-260. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200902023.htmDiao X G, Zhang X H, Zhu J J. Application of CINRAD/SA storm-trend products to warning of hail and violent winds. Meteor Sci Technol, 2009, 37(2): 230-233;259-260. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200902023.htm [17] 王黉, 李英, 文永仁. 川藏高原一次混合型强对流天气的观测特征. 应用气象学报, 2021, 32(5): 567-579. doi: 10.11898/1001-7313.20210505Wang H, Li Y, Wen Y R. Observational characteristics of a hybrid severe convective event in the Sichuan-Tibet Region. J Appl Meteor Sci, 2021, 32(5): 567-579. doi: 10.11898/1001-7313.20210505 [18] 段亚鹏, 王东海, 刘英. "东方之星"翻沉事件强对流天气分析及数值模拟. 应用气象学报, 2017, 28(6): 666-677. doi: 10.11898/1001-7313.20170603Duan Y P, Wang D H, Liu Y. Radar analysis and numerical simulation of strong convective weather for "Oriental Star" depression. J Appl Meteor Sci, 2017, 28(6): 666-677. doi: 10.11898/1001-7313.20170603 [19] Lemon L R. The flanking line, a severe thunderstorm intensification source. J Atmos Sci, 1976, 33(4): 686-694. [20] 郑永光, 田付友, 周康辉, 等. 雷暴大风与龙卷的预报预警和灾害现场调查. 气象科技进展, 2018, 8(2): 55-61. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKZ201802013.htmZheng Y G, Tian F Y, Zhou K H, et al. Forecasting techniques and damage survey of convectively driven high winds and tornadoes. Adv Meteor Sci Tech, 2018, 8(2): 55-61. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKZ201802013.htm [21] 龙柯吉, 康岚, 罗辉, 等. 四川盆地雷暴大风雷达回波特征统计分析. 气象, 2020, 46(2): 212-222. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX202002007.htmLong K J, Kang L, Luo H, et al. Statistical analysis of radar echo characteristics of thunderstorm gales in Sichuan Basin. Meteor Mon, 2020, 46(2): 212-222. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX202002007.htm [22] 郑永光, 周康辉, 盛杰, 等. 强对流天气监测预报预警技术进展. 应用气象学报, 2015, 26(6): 641-657. doi: 10.11898/1001-7313.20150601Zheng Y G, Zhou K H, Sheng J, et al. Advances in techniques of monitoring, forecasting and warning of severe convective weather. J Appl Meteor Sci, 2015, 26(6): 641-657. doi: 10.11898/1001-7313.20150601 [23] 吴翠红, 韦惠红, 牛奔. 湖北东部雷暴大风雷达回波特征分析. 大气科学学报, 2012, 35(1): 64-72. https://www.cnki.com.cn/Article/CJFDTOTAL-NJQX201201006.htmWu C H, Wei H H, Niu B. Radar echo characteristics analysis for thunderstorm gale in eastern Hubei Province. Trans Atmos Sci, 2012, 35(1): 64-72. https://www.cnki.com.cn/Article/CJFDTOTAL-NJQX201201006.htm [24] 杨璐, 韩丰, 陈明轩, 等. 基于支持向量机的雷暴大风识别方法. 应用气象学报, 2018, 29(6): 680-689. doi: 10.11898/1001-7313.20180604Yang L, Han Feng, Chen M X, et al. Thunderstorm gale identification method based on support vector machine. J Appl Meteor Sci, 2018, 29(6): 680-689. doi: 10.11898/1001-7313.20180604 [25] Lemon L R. Severe Thunderstorm Radar Identification Techniques and Warning Criteria. Kansas City: NOAA Tech Memo NWSNSSFC-3, 1980. [26] Lee R R, White A. Improvement of the WSR-88D mesocyclone algorithm. Wea Forecasting, 1998, 13(2): 341-351. [27] 俞小鼎, 姚秀萍, 熊延南, 等. 多普勒天气雷达原理与业务应用. 北京: 气象出版社, 2006.Yu X D, Yao X P, Xiong Y N, et al. Principle and Application of Doppler Weather Radar. Beijing: China Meteorological Press, 2006. [28] Roberts R D, Wilson J W. A proposed microburst nowcasting procedure using single-Doppler radar. J Appl Meteor, 1989, 28(4): 285-303. [29] Schmid W, Schiesser H, Bauer-Messmer B. Supercell storms in Switzerland: Case studies and implications for nowcasting severe winds with Doppler radar. Meteor Appl, 1997, 4(1): 49-67. [30] Eilts M D, Johnson J T, Mitchell E D, et al. Damaging Downburst Prediction and Detection Algorithm for the WSR-88D. Amer Meteor Soc, 1996: 541-545. [31] Przybylinski R W. The bow echo: Observations, numerical simulations, and severe weather detection methods. Wea Forecasting, 1995, 10(2): 203-218. [32] Schmocker G K, Lin Y J. Forecasting the Initial Onset of Damaging Downburst Winds Associated with a Mesoscale Convective System(MCS) Using the Mid-altitude Radial Convergence(MARC) Signature. 15th Conf on Weather Analysis and Forecasting, 1996. [33] Yu X D, Wang X M, Zhao J. Investigation of Supercells in China-Environmental and Storm Characteristics. 26th Conf on Severe Local Storms. Amer Meteor Soc, 2012. [34] 东高红, 吴涛. 垂直积分液态水含量在地面大风预报中的应用. 气象科技, 2007, 35(6): 877-881;910. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200706026.htmDong G H, Wu T. Application of vertically integrated liquid(VIL)water in disastrous wind nowcasting. Meteor Sci Technol, 2007, 35(6): 877-881;910. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200706026.htm [35] 王易, 郑媛媛, 孙康远, 等. 南京雷达中气旋产品特征值统计分析. 气象学报, 2018, 76(2): 266-278. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201802008.htmWang Y, Zheng Y Y, Sun K Y, et al. A statistical analysis of characteristics of mesocyclone products from Nanjing radar. Acta Meteor Sinica, 2018, 76(2): 266-278. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201802008.htm [36] Smith T M, Elmore K L, Dulin S A. A damaging downburst prediction and detection algorithm for the WSR-88D. Wea Forecasting, 2004, 19(2): 240. [37] Witt A, Nelson S P. The use of single-Doppler radar for estimating maximum hailstone size. J Appl Meteor Climatol, 1991, 30(4): 425-431. -
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