江淮地区龙卷超级单体风暴及其环境参数分析   总被引：3，自引：1，他引：3  

周后福  刁秀广  夏文梅  王德育  项阳 《气象学报》2014,72(2):306-317

利用多普勒雷达探测资料和NCEP再分析资料,对2003—2010年发生在江淮地区的6个龙卷超级单体风暴及其环境参数进行了分析。研究表明：（1）龙卷超级单体风暴H_BASE平均为1.7 km,H_TOP平均为9.1 km;H多在风暴的下部,近于下部的1/4处。H_BASE平均值比江淮地区各种超级单体的平均值低得多,H_TOP则略低。（2）龙卷超级单体I_VIL平均为25.6 kg/m²,Z_MX平均为54.8 dBz。和江淮地区超级单体相比,龙卷I_VIL要小得多,而龙卷Z_MX略低。（3）龙卷超级单体的中气旋M_BASE、M_TOP和M_SHR平均值分别为1.2 km、3.9 km和14.4×10^-3s^-1,和江淮地区超级单体相比,龙卷M_BASE、M_TOP明显低,而M_SHR略高。（4）TVS参数最强时的V_AD在12—45 m/s,V_LLD多大于30 m/s,V_MXD多超过30 m/s,V_MXD的高度不低于0.8 km,T_DPT在2.4—6.4 km,T_BASE在0.7—1.5 km,T_TOP在2.3—6.4 km,T_MXSHR超过22×10^-3s^-1。TVS参数最强时间与龙卷实际时间基本吻合,平均相差4.2 min;平均而言,TVS出现后6 min有龙卷发生。（5）雷达推算的龙卷超级单体的0—6 km风垂直切变比江淮地区超级单体的风垂直切变平均值高15.2%;龙卷发生前I_CAPE平均为1752 J/kg,I_K为38℃,850 hPa到地面风切变平均超过12 m/s,850—500 hPa温差平均为23.7℃。龙卷发生前能量处在中等到强的状态,大气不稳定性较强,风垂直切变大。  相似文献   

星载测雨雷达探测的夏季亚洲对流与层云降水雨顶高度气候特征   总被引：11，自引：2，他引：9  

傅云飞  曹爱琴  李天奕  冯沙  郑媛媛  刘勇  张爱民 《气象学报》2012,70(3):436-451

利用热带测雨卫星测雨雷达的10年探测结果,对夏季亚洲对流降水与层云降水雨顶高度分布、雨顶高度与地表降水强度的关系、雨顶高度日变化特征进行了研究。结果表明,青藏高原和中国东部平原的多数(70%以上)对流降水雨顶高度分布在8—12和5—10km,其他地区分布在5—9km;陆面对流降水雨顶平均高度高于洋面。洋面和陆面层云降水雨顶高度没有明显差异,多在5—8km。夏季亚洲浅对流降水比例少,而深厚对流主要出现在中国东部平原、西南、印度次大陆西部至伊朗高原东部地区,比例约40%。洋面和陆面的弱对流降水的雨顶平均高度在7—8km,弱层云降水相应的雨顶平均高度多小于7.5km;陆面约90%的强对流降水雨顶平均高度在9km以上,而强层云降水雨顶的平均高度通常不超过8.5km。夏季亚洲对流降水和层云降水的雨顶平均高度均随着地面平均降水率的增大而升高,两者遵从二次函数关系。对流降水及层云降水频次、强度和雨顶高度的日变化峰值分析表明,陆面这些参量的日变化强于洋面,并且三者的日变化基本同步。  相似文献   

The Evolution of a Meso-β-Scale Convective Vortex in the Dabie Mountain Area   总被引：1，自引：0，他引：1       下载免费PDF全文

XU Wenhui  NI Yunqi  WANG Xiaokang  QIU Xuexing 《Acta Meteorologica Sinica》2012,26(5):597-613

The evolution of a mesoscale convective system (MCS) that caused strong precipitation in the northern area of Dabie Mountain during 21-22 June 2008 is analyzed, along with the evolution of the associated meso-β-scale convective vortex (MCV). The mesoscale reanalysis data generated by the Local Analysis and Prediction System (LAPS) at a 3-km horizontal resolution and a 1-h time resolution during the South China Heavy Rainfall Experiment (SCHeREX) were utilized. The results show that two processes played key roles in the enhancement of convective instability. First, the mesoscale low-level jet strengthened and shifted eastward, leading to the convergence of warm-wet airflow and increasing convective instability at middle and low levels. Second, the warm-wet airflow interacted with the cold airflow from the north, causing increased vertical vorticity in the vicinity of steeply sloping moist isentropic surfaces. The combined action of these two processes caused the MCS to shift progressively eastward. Condensation associated with the MCS released latent heat and formed a layer of large diabatic heating in the middle troposphere, increasing the potential vorticity below this layer. This increase in potential vorticity created favorable conditions for the development of a low-level vortex circulation. The vertical motion associated with this low-level vortex further promoted the development of convection, creating a positive feedback between the deep convection and the low-level vortex circulation. This feedback mechanism not only promoted the maturation of the MCS, but also played the primary role in the evolution of the MCV. The MCV formed and developed due to the enhancement of the positive feedback that accompanied the coming together of the center of the vortex and the center of the convection. The positive feedback peaked and the MCV matured when these two centers converged. The positive feedback weakened and the MCV began to decay as the two centers separated and diverged.  相似文献   

长生命史飑线在强、弱对流降水过程中的异同点分析   总被引：5，自引：0，他引：5  

姚晨  郑媛媛  张雪晨 《高原气象》2012,31(5):1366-1375

利用常规气象资料、自动站资料、NCEP再分析资料和多普勒雷达资料,对发生在我国中纬度地区不同对流环境下两次长生命史飑线过程的物理机制和中尺度特征进行了分析。结果表明:(1)飑线在近地面层有较强的水汽辐合,但强对流降水过程中的飑线湿层深厚,水汽辐合的层次更为深广、强度更强,存在较低的抬升凝结高度。(2)高层强冷平流与低层暖平流的叠加是飑线的共同特征之一;不同之处在于弱对流降水过程中飑线不稳定层结的建立更多地依靠高层冷平流的作用,有更高的温度直减率,具有弱降水超级单体的一些特征;强对流降水过程中飑线低层暖平流的加强也是造成大气不稳定的重要原因,θse在中层呈现出湿中性层结特征,存在更大的热力不稳定度,是典型的强降水超级单体特性。(3)长生命史飑线的发展离不开强环境风垂直风切变;强对流降水过程中垂直风切变主要是风速随高度变化而产生的,弱对流降水过程中垂直风切变主要表现为风向随高度的变化。(4)飑线沿着出流边界和引导气流方向移动。(5)飑线在雷达回波上的共同点:都出现典型弓形回波,减弱的标志亦是阵风锋逐渐远离回波主体,弓形回波逐渐断裂,强回波后侧的层状云回波面积开始增大;不同点在于弓形回波的演变方式不同,弱对流降水过程中的弓形回波有超级单体风暴的典型结构,而强对流降水过程中弓形回波的形成是由强降水超级单体的发展而来,单体结构明显不同于经典超级单体中非降水或弱降水超级单体。(6)速度场上低层存在着径向速度的大值区,中低层有辐合,并伴有中气旋存在,中层存在明显的MARC(Mid-Altitude Radial Convergence)。1km高度以下的径向速度大值区、MARC和中气旋对地面灾害性大风有提前预警作用。  相似文献   

Application and Verification of Joint Probability Method in Potential Forecast for Severe Convective Weather in Anhui Province     

Yuejia Zhu  Rui Xing  Mingjia Zhu  Dongyong Wang  Xuexing Qiu 《地球科学进展》2019,34(7):731-746

In consideration of large uncertainties in severe convective weather forecast, ensemble forecasting is a dynamic method developed to quantitatively estimate forecast uncertainty. Based on ensemble output, joint probability is a post-processing method to delineate key areas where weather event may actually occur by taking account of the uncertainty of several important physical parameters. An investigation of the environments of little rainfall convection and strong rainfall convection from April to September (warm season) during 2009-2015 was presented using daily disastrous weather data, precipitation data of 80 stations in Anhui province and NCEP Final Analysis (FNL) data. Through ingredients-based forecasting methodology and statistical analysis,four convective parameters characterizing two types of convection were obtained, respectively, which were used to establish joint probability forecasting together with their corresponding thresholds. Using the ECMWF ensemble forecast and observations from April to September during 2016-2017, systematic verification mainly based on ROC and case study of different weather processes were conducted. The results demonstrate that joint probability method is capable of discriminating little rainfall convection and non-convection with comparable performance for different lead times, which is more favorable to identifying the occurrence of strong rainfall convection. The joint probability of little rainfall convection is a good indication for the occurrence of regional or local convection, but may produce some false alarms. The joint probability of strong rainfall convection is good at indicating regional concentrated short-term heavy precipitation as well as local heavy rainfall. There are also individual missing reports in this method, and in practice, 10% can be roughly used as joint probability threshold to achieve relative high TS score. Overall, ensemble-based joint probability method can provide practical short-term probabilistic guidance for severe convective weather.  相似文献   

1961～2017年雅鲁藏布江河谷地区夏季气候暖干化趋势     

赤曲  周顺武  多典洛珠  王传辉  孙阳 《气候与环境研究》2020,25(3):281-291

基于1961～2017年青藏高原腹地雅鲁藏布江河谷地区4个站（拉萨、日喀则、泽当和江孜）夏季（6～8月）月平均气温、降水和相对湿度等观测资料,分析了该地区夏季气候年际和年代际演变特征,并探讨了气温、降水和相对湿度在年际和年代际时间尺度上的相互关系以及与总云量和地面水汽压的联系。结果表明:（1）1961～2017年该地区夏季气候出现了暖干化趋势。气温（相对湿度）显著升高（下降）,降水趋势变化不明显;本世纪初气温（相对湿度）均发生了显著的突变。（2）该地区夏季气候因子间在年际和年代际时间尺度上存在密切关系:气温与相对湿度和降水均存在明显的负相关,降水与相对湿度为正相关。（3）该地区夏季气候因子间的年际和年代际变化与同期总云量和地面水汽变化有关。1961～2017年总云量持续减少是气温显著升高的主要原因之一,气温的显著升高和降水变化不明显又造成了相对湿度的显著下降。  相似文献   

2013年春季一次强飑线过程中尺度特征研究     

吴瑞姣  黎玥君  林永辉 《热带气象学报》2023,(4):522-535

运用多种观测数据,结合WRF模式分析了2013年3月19日发生在黔湘地区一次飑线形成期的中尺度特征。（1）此次飑线发生在高空500 hPa槽前的西南气流中,地面冷锋附近。环境风为西南向,且垂直于飑线长轴的分量小于沿着飑线长轴的分量。（2）飑线东、西两段存在显著差异：东段所在环境干燥,下沉对流有效位能DCAPE大,故雷暴大风强而短时强降水弱,对流单体初始于锋区及冷空气一侧,呈碎块状分布;西段环境湿润,短时强降水和冰雹集中,对流单体出现于地面锋区附近中尺度辐合线内,辐合线持久,其上辐合中心处不断有单体新生。（3）此次过程有重力波作用,且飑线西段重力波特征更明显。急流中的波动与中尺度辐合线相交,波动上升气流叠加辐合线上升运动,引起对流发生并迅猛发展,使得对流单体趋向于沿着波动等振幅面排列成带状,进而形成飑线。（4）旧单体南、北两侧均有新对流单体发生：北侧新单体高、低层重力波反相位叠加,对流受到抑制;南侧的新单体高、低层波动同相,上升气流加强,对流得以发展;新旧单体不断迭代更新,飑线整体向东南传播。  相似文献   

皖北一次特大暴雨过程中边界层急流日变化特征 及其对暴雨形成的影响分析     

刘高平  刘俏  邱学兴  陶玮  周晓晔  杨祖祥 《气象科学》2022,42(5):591-601

利用多普勒雷达风廓线产品、ERA5再分析资料和WRF模式,分析了2018年6月27日皖北一次特大暴雨过程中边界层急流的日变化特征及其对特大暴雨形成的作用。结果表明:特大暴雨发生期间存在边界层急流,急流最强达到了18 m·s^-1,强降水主要发生在急流快速增强的时段;急流前部的边界层辐合线是对流的触发因子,强降水落区位于急流核前部。急流为对流系统加强提供水汽和能量,且边界层急流和雷暴高压对峙使对流系统稳定少动,在对流系统西侧激发新的对流单体,有利于特大暴雨的发生;此次过程中天气系统的影响时间主要决定了强降水的落区,而边界层急流的日变化决定了强降水发生的时间段;边界层急流在夜间具有超地转特征,午后具有次地转特征,地转偏差和水平平流作用是导致夜间边界层急流增强的主要原因。  相似文献   

安徽省不同等级雾和重度霾时空分布特征及地面气象条件比较     

石春娥  李耀孙  张浩  杨关盈  周建平 《气象学报》2021,79(5):828-840

雾和霾都是低能见度天气,生成条件相似。利用安徽78个地面站逐时观测资料,基于雾、霾发生物理条件,建立了不同等级雾日和重度霾日的观测诊断方法,重建了不同等级雾和重度霾的时序资料。根据各站强浓雾发生的同步性,将安徽分为5个雾、霾分布特征不同的区域,探讨了各区域不同等级雾及重度霾出现时地面气象条件的异同。结果表明:（1）安徽省强浓雾主要是辐射雾。强浓雾、浓雾和大雾空间分布形势大体一致,淮河以北东、西部和江南都属于强浓雾高发区,但各地强浓雾的时、空分布特征和影响系统不同;重度霾有明显的北多、南少、山区最少的分布特征。（2）强浓雾年变化呈双峰型分布,峰值在1月和4月,日变化为单峰型,峰值在06时;而重度霾年变化为单峰型,峰值在1月,日变化为双峰型。（3）在强浓雾的高发时段（02—08时）,强浓雾时降温幅度最大,比重度霾平均高1℃,风速显著偏低,超过75%的样本风速低于1.5 m/s,且无明显主导风向;而重度霾时,风速比雾时明显要大,个别区域有超过75%的样本风速大于1.5 m/s,且以西北风到东北风为主。说明重度霾能否演变为强浓雾的关键地面气象因子是风速、风向和降温幅度。   相似文献   

High-Resolution Mesoscale Analysis Data from the South China Heavy Rainfall Experiment (SCHeREX): Data Generation and Quality Evaluation          下载免费PDF全文

NI Yunqi  CUI Chunguang  LI Hongli  PENG Juxiang  QIU Xuexing  ZHANG Yanxi  XU Xiaolin  GAO Mei  JIE Lianshu  ZHANG Wenhua 《Acta Meteorologica Sinica》2011,25(4):478-493

In this study,the observational data acquired in the South China Heavy Rainfall Experiment (SCHeREX)from May to July 2008 and 2009 were integrated and assimilated with the US National Oceanic and Atmospheric Administration's (NOAA) Local Analysis and Prediction System (LAPS; information available online at http://laps.fsl.noaa.gov).A high-resolution mesoscale analysis dataset was then generated at a spatial resolution of 5 km and a temporal resolution of 3 h in four observational areas:South China,Central China,Jianghuai area,and Yangtze River Delta area.The quality of this dataset was evaluated as follows.First,the dataset was qualitatively compared with radar reflectivity and TBB image for specific heavy rainfall events so as to examine its capability in reproduction of mesoscale systems.The results show that the SCHeREX analysis dataset has a strong capability in capturing severe mesoscale convective systems.Second,the mean deviation and root mean square error of the SCHeREX mesoscale analysis fields were analyzed and compared with radiosonde data.The results reveal that the errors of geopotential height,temperature,relative humidity,and wind of the SCHeREX analysis were within the acceptable range of observation errors.In particular,the average error was 45 m for geopotential height between 700 and 925 hPa,1.0-1.1℃ for temperature,less than 20％ for relative humidity,1.5-2.0 m s-1 for wind speed,and 20°-25° for wind direction.The above results clearly indicate that the SCHeREX mesoscale analysis dataset is of high quality and sufficient reliability,and it is applicable to refined mesoscale weather studies.  相似文献