雷暴大风与龙卷的预报预警和灾害现场调查
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摘要
近年来强雷暴大风与龙卷导致的灾害事件引发广泛关注。在总结雷暴大风和龙卷机理、短期预报技术和天气形势特征基础上,给出了这两类天气的监测和短时临近预报预警技术,最后简要总结了灾后现场调查工作和风灾强度评估方法。雷暴大风多数是由对流风暴内强烈下沉气流产生;而龙卷一类由中气旋产生,另一类由辐合线上的中小尺度涡旋和快速发展对流风暴中的强上升气流共同作用形成。但归根结底,巨大的静力不稳定能量是产生强雷暴大风与龙卷(热带气旋龙卷除外)的必要条件。新一代天气雷达观测是雷暴大风与龙卷的监测和临近预警主要手段。自动气象站观测风场能够相当程度上监测大风天气,地球静止气象卫星和自动气象站变压、变温等观测资料也能够辅助监测雷暴大风天气,但龙卷监测尚无法直接使用这两类资料。对这两类天气所致灾害的现场调查工作依然必不可少。快速更新或者集合的高时空分辨率数值模式预报及其后处理是这两类天气短时预报的主要途径。
In recent years, the disasters, which were caused by convectively driven high winds and tornadoes, attracted more attention in China. This paper firstly summarizes the mechanisms, short-range forecasting techniques and synoptic situations of convectively driven high winds and tornadoes, then presents techniques of monitoring and warning on them, finally gives brief summary of damage survey and wind estimation methodology for them. Most of convectively driven high winds are caused by strong rear downdrafts of convective storms. However, one type of tornadoes was generated from mesocyclones, another type of tornadoes was caused by the combining effect of mesovortices and strong updrafts of convective storms in convergence line. Massive convective available potential energy is one of the necessary conditions favorable for convectively driven high winds and tornadoes(except for tropical cyclone tornadoes). Monitoring and warning convectively driven high winds and tornadoes depend on the observations by new generation weather radar network. Observational winds from automatic weather station(AWS) can monitor convectively driven high winds to a great extent, and observations from geostationary meteorological satellites and pressure tendency and temperature tendency from AWS are also useful to monitor convectively driven high winds, but these data cannot directly be used to monitor tornadoes. Damage survey for the disasters caused by these two types of weather is still necessary. Short-term forecasting these two types of weather depends mainly upon a rapid update high-resolution(ensemble) numerical model and post-processing.
In recent years, the disasters, which were caused by convectively driven high winds and tornadoes, attracted more attention in China. This paper firstly summarizes the mechanisms, short-range forecasting techniques and synoptic situations of convectively driven high winds and tornadoes, then presents techniques of monitoring and warning on them, finally gives brief summary of damage survey and wind estimation methodology for them. Most of convectively driven high winds are caused by strong rear downdrafts of convective storms. However, one type of tornadoes was generated from mesocyclones, another type of tornadoes was caused by the combining effect of mesovortices and strong updrafts of convective storms in convergence line. Massive convective available potential energy is one of the necessary conditions favorable for convectively driven high winds and tornadoes(except for tropical cyclone tornadoes). Monitoring and warning convectively driven high winds and tornadoes depend on the observations by new generation weather radar network. Observational winds from automatic weather station(AWS) can monitor convectively driven high winds to a great extent, and observations from geostationary meteorological satellites and pressure tendency and temperature tendency from AWS are also useful to monitor convectively driven high winds, but these data cannot directly be used to monitor tornadoes. Damage survey for the disasters caused by these two types of weather is still necessary. Short-term forecasting these two types of weather depends mainly upon a rapid update high-resolution(ensemble) numerical model and post-processing.
引文
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(1)郑媛媛,2017.雷暴大风和龙卷短临预报预警.2017年强对流天气汛前预报技术准备会。
[2]Meng Z,Yao D,Bai L,et al.W ind estimation around the shipwreck of Oriental Star based on field damage surveys and radar observations.Science Bulletin,2016,61(4):330-337.
[3]郑永光,朱文剑,姚聃,等.风速等级标准与2016年6月23日阜宁龙卷强度估计.气象,2016,42(11):1289-1303.
[4]张小玲,杨波,朱文剑,等.2016年6月23日江苏阜宁EF4级龙卷天气分析.气象,2016,42(11):1304-1314.
[5]Xue M,Zhao K,Wang M,et al.Recent significant tornadoes in China.Advances in Atmospheric Sciences,2016,33(11):1209-1217.
[6]范雯杰,俞小鼎.中国龙卷的时空分布特征.气象,2015,41(7):793-805.
[7]俞小鼎,周小刚,王秀明.雷暴与强对流临近天气预报技术进展.气象学报,2012,70(3):311-337.
[8]郑永光,陶祖钰,俞小鼎.强对流天气预报的一些基本问题.气象,2017,43(6):641-652.
[9]郑永光,朱文剑,田付友.2015年“东方之星”翻沉事件和2016年阜宁EF4级龙卷对流风暴环境条件、结构特征和机理.气象科技进展,2018,8(2):44-54.
[10]Fujita T T,Wakimoto R M.Five scales of airflow associated with a series of downbursts on 16 July 1980.Monthly Weather Review,1981,109(7):1438-1456.
[11]高玉春.气象业务发展对新一代天气雷达技术性能提升的要求.气象科技进展,2017,7(3):16-21.
[12]郑永光,张小玲,周庆亮,等.强对流天气短时临近预报业务技术进展与挑战.气象,2010,36(7):33-42.
[13]郑永光,林隐静,朱文剑,等.强对流天气综合监测业务系统建设.气象,2013,39(2):234-240.
[14]张涛,蓝渝,毛冬艳,等.国家级中尺度天气分析业务技术进展Ⅰ:对流天气环境场分析业务技术规范的改进与产品集成系统支撑技术.气象,2013,39(7):894-900.
[15]蓝渝,张涛,郑永光,等.国家级中尺度天气分析业务技术进展Ⅱ:对流天气中尺度过程分析规范和支撑技术.气象,2013,39(7):901-910.
[16]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.
[17]杨波,郑永光,蓝渝,等.国家级强对流天气综合业务支撑体系建设.气象,2017,43(7):845-855.
[18]Johns R H,Doswell III C A.Severe local storms forecasting.Weather and Forecasting,1992,7(4):588-612.
[19]Wakimoto R M,Kessinger C J,Kingsmill D E.Kinematic,thermodynamic,and visual structure of low-reflectivity microbursts.Monthly Weather Review,1994,122(1):72-92.
[20]Wilson J W,Wakimoto R M.The discovery of the downburst:T.T.Fujita’s contribution.Bulletin of the American Meteorological Society,2001,82(1):49-62.
[21]Ellrod G P.Environmental conditions associated with the Dallas microburst storm determined from satellite soundings.Weather and Forecasting,1989,4(4):469-484.
[22]Mc Cann D W.WINDEX:a new index for forecasting microburst potential.Weather and Forecasting,1994,9(4):532-541.
[23]Atkins N T,Wakimoto R M.Wet microburst activity over the southeastern United States:implications for forecasting.Weather and Forecasting,1991,6(4):470-482.
[24]Ellrod G P.Experimental microburst image products derived from GOES sounder data.Preprints,16th Conferenceon Weather Analysis and Forecasting,Phoenix,AZ,American Meteorological Society,1998,16:43-45.
[25]Pryor K L,Ellrod G P.Recent improvements to the GOESmicroburst products.Weather and Forecasting,2004,19:582-594.
[26]Pr yor K L,Ellrod G P.WMSI:a new index for forecasting wetmicroburst severit y.Electronic Journal of Operational Meteorology,2004.
[27]Pryor K L.Progress and developments of downburst prediction applications of GOES.Weather and Forecasting,2015,30(5):1182-1200.
[28]Wakimoto R M,Wilson J W.Non-supercell tornadoes.Monthly Weather Review,1989,117(6):1113-1140.
[29]Markowski P,Richardson Y.Mesoscale Meteorlogy in Midlatitudes.Chichester:John Wiley and Sons Ltd,2010:245-260.
[30]Agee E,Jones E.Proposed conceptual taxonomy for proper identification and classification of tornado events.Weather and Forecasting,2009,24(2):609-617.
[31]Davies-Jones R,Trapp R J,Bluestein H B.Tornadoes and tornadic storms.Severe Convective Storms.Meteor Monogr,American Meteorological Society,2001,28(50):167-221.
[32]Trapp R J,Stumpf G J,Manross K L.A reassessment of the percentage of tornadicmesocyclones.Weather and Forecasting,2005,20(4):680-687.
[33]Brooks H E,Lee J W,Craven J P.The spatial distribution of severe thunderstorm and tornado environments from global reanalysis data.Atmospheric Research,2003,67:73-94.
[34]Craven J P,Brooks H E.Baseline climatology of sounding derived parameters associated with deep moist convection.National Weather Digest,2004,28(1):13-24.
[35]Grams J S,Thompson R L,Snively D V,et al.A climatology and comparison of parameters for significant tornado events in the United States.Weather and Forecasting,2012,27(1):106-123.
[36]Mc Caul E W.Buoyancy and shear characteristics of hurricanetornado environments.Monthly Weather Review,1991,119(8):1954-1978.
[37]郑媛媛,张备,王啸华,等.台风龙卷的环境背景和雷达回波结构分析.气象,2015,41(8):942-952.
[38]Bluestein H B.Severe Convective Storms and Tornadoes:Observations and Dynamics.Heidelberg:Springer-Praxis,2013:307-360.
[39]Atkins N T,Bouchard C S,Przybylinski R W,et al.Damaging surface wind mechanisms within the 10 June 2003 Saint Louis bow echo during BAMEX.Monthly Weather Review,2005,133(8):2275-2296.
[40]Doswell C A,Burgess D W.Tornadoes and tornadic storms:a review of conceptual models.The Tornado:Its Structure,Dynamics,Prediction,and Hazards.Washington DC:American Geophysical Union,1993:161-172.
[41]Schultz D M,Richardson Y P,Markowski P M,et al.Tornadoes in the Central United States and the“Clash of Air Masses”.Bulletin of the American Meteorological Society,2014,95(11):1704-1712.
[42]Markowski P M,Straka J M,Rasmussen E N.Direct surface thermodynamic observations within the rear-flank downdrafts of nontornadic and tornadicsupercells.Monthly Weather Review,2002,130(7):1692-1721.
[43]樊李苗,俞小鼎.中国短时强对流天气的若干环境参数特征分析.高原气象,2013,32(1):156-165.
[44]Tian F,Zheng Y,Zhang T,et al.Statistical characteristics of environmental parameters for warm season short-duration heavy rainfall over central and eastern China.Journal of Meteorological Research,2015,29(3):370-384.
[45]Bright D R,Weiss S J,Levit J J,et al.The evolution of multiscale ensemble guidance in the prediction of convective and severe convective storms at the Storm Prediction Center.Preprints,24th Conference Severe Local Storms,Savannah GA,2008.
[46]Guyer J L,Bright D R.Utility of SPC short-range ensemble forecast(SREF)guidance for forecasting the development of severe convection.Preprints,24th Conference Severe Local Storms,Savannah GA,2008.
[47]Du J,Dimego G,Toth Z,et al.NCEP short-range ensemble forecast(SREF)system upgrade in 2009.19th Conference on NWP and 23rd Conference on WAF,2009.
[48]Schmocker G K,Przybylinski R W,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.Preprints,15th Conference on Weather Analysis and Forecasting,Norfolk,American Meteorological Society,1996:306-311.
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