新一代天气雷达对局地强风暴预警的改善

介绍美国新一代天气雷达 (WSR 88D)与传统天气雷达在探测和预警局地强风暴方面的评分对比。评分系统采用命中率POD、误警率FAR和警报提前时间。这有助于了解正在布网的我国新一代天气雷达可能带来的对局地强对流风暴预警能力的改善程度。     

台风“艾云尼”（2018）外围两次近距离龙卷的环境条件和雷达特征

2018年6月8日在距台风“艾云尼”中心80 km、160 km的广州市南沙区横沥镇、佛山市南海区大沥镇两地罕见地先后出现了龙卷天气。利用X波段双偏振雷达组网、广州S波段双偏振雷达、风廓线雷达和区域加密自动站等观测资料对两次近距离台风龙卷过程的环境条件和雷达特征进行了分析。环境条件分析表明,两次龙卷发生地位于低层西南急流和东南急流辐合区,所处环境为弱的对流有效位能（CAPE）、低的抬升凝结高度和强的低层垂直风切变环境中,0~1 km垂直风切变值超过15×10-3 s-1。中小尺度雷达特征分析表明:（1）两地龙卷由台风外围微型超级单体引起,超级单体在发展强盛阶段有钩状回波、入流缺口、中层回波悬垂等典型特征,最强反射率因子55~60 dBz,强度≥50 dBz强回波发展高度在4 km以下,微型超级单体有水平尺度2~3 km的中气旋,由于速度模糊影响,仅在南海龙卷发生前9 min广州S波段雷达能自动识别中气旋。（2）与南沙龙卷相联系的中气旋核心高度低,强度进一步加强紧缩导致龙卷发生;而与南海龙卷相联系的中气旋从中层发展,中气旋加强紧缩下降到更低导致龙卷发生。（3）两地弱龙卷发生时广州和南海双偏振雷达没能捕捉到龙卷碎片（TDS）特征,南海X波段雷达能提前30 min监测到入流急流,提前27 min探测出钩状回波等特征,并通过分析ZDR弧和KDP弧可判断低层强盛的上升气流和强的垂直风切变利于风暴的发展。（4）佛山四部X波段组网雷达反演的1 km水平风场可分析出小尺度涡旋结构,对应钩状回波尾端有强的风向切变,这对龙卷发生地点的判断和风暴的流场结构有较好指示意义。      

相控阵天气雷达监测预警龙卷风的过程剖析

天气雷达作为龙卷风监测预警的重要手段之一,应用具有超高时空分辨率的X波段双极化相控阵天气雷达系统,较好地捕获并提前预警龙卷风。以2022年6月19日07时发生在广东佛山南海的一次龙卷风为例,详细剖析龙卷生消及雷达监测预警过程。借助雷达智能预警软件,利用X波段双极化相控阵天气雷达的双偏振量和超高时空分辨率数据,实时反演三维风场和分析龙卷碎片(TVS)特征,能够显著提高龙卷风监测预警水平。实例表明,本次成功地提前18分钟预警龙卷,进一步说明了X波段双极化相控阵天气雷达在强对流天气探测方面具有较强的生命力。     

X波段双偏振雷达相态识别与拼图的关键技术

X波段双偏振雷达具有时空分辨率高、易于布网的特点,但散射特性差异和衰减影响使现有S波段雷达的相态识别和拼图算法不适用于X波段双偏振雷达。该文针对X波段相态识别及拼图产品的关键技术开展研究,提出基于准垂直剖面的融化层识别方法、基于数据质量的置信度阈值调整方法、基于统计的隶属函数参数改进方法和基于衰减程度的拼图融合方法。通过对比改进后可有效提升水凝物相态识别结果的可靠性和多雷达拼图结果的合理性。在2016年汛期北京典型个例中,融合后的X波段雷达网与当地S波段业务雷达相比能够提供更精细的回波结构和水凝物相态分布,有效缓解S波段雷达在近处探测能力降低的问题,识别的降雹区与地面观测相符。     

台风山竹(1822)龙卷的双极化相控阵雷达特征

2018年9月17日台风山竹（1822）外围螺旋雨带中发生EF2级龙卷。在高湿度、高不稳定、强垂直风切变的环流背景下,龙卷在台风外围雨带上微型超级单体右后侧钩状回波顶端的弱回波区中发展起来。具有高时空分辨率的广州X波段双极化相控阵雷达,不仅观测到超级单体的发展过程,还呈现出龙卷涡旋演变特征:单体风暴尾端在右后方入流加强作用下,逐渐形成钩状回波形态,此时对流层中低层2~3 km高度附近的中气旋强度率先达到最大,随着旋转强度进一步加强和旋转中心高度逐步下降,低层强旋转特征越来越明显,当低层旋转速度达到峰值（超过21 m·s-1）,旋转直径收缩到1 km范围,地面出现EF2级以上龙卷,旋转速度对区域出现清晰的弱回波龙卷眼区特征。X波段双极化相控阵雷达在龙卷观测中优势显著,弥补了多普勒天气雷达观测的不足。     

1822号“山竹”台风龙卷过程观测与预警分析

2018年9月17日09:37—10:00,在登陆台风“山竹”外围螺旋雨带中,广东省佛山市三水区到肇庆市四会区发生了EF2级强龙卷,龙卷路径长度18 km,持续时间23 min,平均时速47 km/h,导致不少建筑物损毁。本次过程佛山市进行了龙卷预警试验,提前37 min发布了龙卷预警,龙卷没有造成人员伤亡。利用观测资料对产生强龙卷的环境场特征、地面自动站和雷达观测的中小尺度特征以及龙卷预警试验进行了分析,结果表明:产生龙卷的微型超级单体出现在台风外围和副高边缘之间的强东南急流中,具有低层辐合、高层辐散、水汽充足等典型台风外围龙卷环流形势特征;强的低空0~1 km垂直风切变、大的风暴相对螺旋度和低的抬升凝结高度等环境条件利于龙卷的生成;龙卷影响时,邻近地面自动气象站观测要素表现出明显的信号,瞬时大风和最低气压的极值区呈东南至西北向带状分布,与龙卷路径一致,龙卷过境前后,单站气压“漏斗”明显,5 min降压/升压幅度达-2.5 hPa/+2.1 hPa;广州多普勒天气雷达探测到龙卷母体风暴的低层钩状回波和入流缺口特征,以及低层强中气旋和类TVS特征。预警试验初步表明,对台风龙卷高发区,在环境场有利情况下,若低层出现中等或以上强度中气旋,其底高在1 km以下,可以考虑发布龙卷预警。      

Current Status and Future Challenges of Weather Radar Polarimetry: Bridging the Gap between Radar Meteorology/Hydrology/Engineering and Numerical Weather Prediction

After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.     

基于雷达观测的2021年6月珠江口一次水龙卷过程分析

利用常规地面和探空资料、珠海S波段双偏振多普勒天气雷达和珠海横琴X波段相控阵雷达资料对2021年6月1日发生在珠江口的水龙卷过程进行分析。研究表明:此次水龙卷过程发生在高层强辐散、中层短波槽影响、低层西南风的背景场下;极低的抬升凝结高度、较大的0~1 km风矢量差、超过超级单体发生阈值的风暴相对螺旋度,为龙卷的发生提供了较好的动力条件。两部雷达均观测到超级单体结构特征,最强反射率因子超过65 dBZ。X波段相控阵雷达资料能够清晰展现水龙卷超级单体风暴精细化演变特征,0.9 °仰角首先出现风切变,随后风切变出现高度逐渐增高,并加强为中气旋,切变最高高度达到17.1 °仰角,随后高度逐渐降低,龙卷减弱。三维反射率因子图清楚地反映了龙卷母体风暴穹窿结构形成过程,以及强反射率因子区向上延伸,变细加强,龙卷触及水面后变粗的过程。S波段雷达探测到在龙卷发生前,出现Z_DR低值眼区和ρ_HV弧,这对于预报员提前预警以及识别龙卷具有一定帮助。      

DEVELOPMENT AND ASSESSMENT OF QUANTITATIVE PRECIPITATION ESTIMATION ALGORITHMS FOR S-, C-, AND X-BAND DUAL-POLARIZATION RADARS BASED ON DISDROMETER DATA FROM THREE REGIONS OF CHINA

The accuracy of quantitative precipitation estimation (QPE) for dual-polarization radars can be improved by using a localized rainfall estimation algorithm derived from the raindrop size distribution (DSD). In the present study, DSDs observed at Suzhou City, Jiangsu province; Yangjiang City, Guangdong province; and Naqu City, Tibet are analyzed during the rainy season together with the corresponding polarimetric variables for the above three regions. Most importantly, these DSD data are used to develop optimal “synthetic” QPE algorithms for S-, C-, and X-band dual-polarization radars, which will be built or upgraded in the three regions. Meanwhile, a new piecewise fitting method (PFM) is proposed. It has been found that the number concentration N(D) of small raindrops (D<1mm) is the highest in Suzhou, while that of larger raindrops (D>1mm) is the highest in Yangjiang. The characteristics of the differential reflectivity (ZDR) and specific differential phase (KDP) are significantly different in the three locations, suggesting that different rainfall estimators are needed for different locations. Further performance assessment of the QPE based on DSD data indicates that the PFM QPE algorithm (LDSD) performs better than the conventional fitting method (CFM), and the localized QPE algorithm can improve the QPE accuracy. Observations from S-band dual-polarization radars and rain gauges in the Southern China Monsoon Rainfall Experiment are implemented to verify the performances of the QPE algorithms proposed in the present study. It is found that compared with non-localized algorithms, the localized LDSD algorithm yields the best results with at least 7.66% and 8.43% reductions in the RMSE and NE, respectively, which implies that while polarimetric variables can reflect DSD characteristics, the localized QPE algorithm remains necessary.     

Advances in tornado and storm research in the United Kingdom and Europe: the role of the Tornado and Storm Research Organisation

The Tornado and Storm Research Organisation (TORRO) was formed in the UK in 1974 in order to determine realistic spatial, temporal and intensity distributions of tornadoes in the UK and, eventually, throughout Europe. Currently, TORRO's databases contain nearly 2000 tornadoes and over 550 waterspouts for the UK alone. In 1972, TORRO's founder, Terence Meaden, devised the Tornado Intensity Scale. This scale enables the wind speeds of tornadoes to be rated on a scale from T0 to T10, or more (since it is an open-ended scale). Using this scale, estimates have been made of the statistical return periods of differing intensities of UK tornadoes. TORRO's research into understanding the conditions of tornado development is ultimately intended to lead to issuing forecasts of tornadoes. In 1991, TORRO issued the first tornado watch in the UK for 12 November and this proved to be accurate—not only did three property-damaging tornadoes strike East Anglia but the forecast maximum intensity of T5 was attained. In 1975, TORRO expanded its activities to include conventional thunderstorm reporting and investigations. In 1982, TORRO incorporated the British and Irish thunderstorm data-collection organisation, the Thunderstorm Census Organisation (TCO), which was established in 1924. By the early 1980s, TORRO's network of voluntary thunderstorm observers, located throughout the UK and Ireland and increasingly in other European countries, numbered around 350 and the network continues to grow. In addition to TORRO's early focus on tornadoes and thunderstorms, its data collection and research has expanded to consider other whirlwinds (such as waterspouts and land devils), hailstorms, lightning (including ball lightning) and blizzards/heavy snowfalls. In 1996, TORRO began providing easy access to its databases (e.g. post-1995 UK and European severe weather events, especially tornadoes and hailstorms) and other information via its internet site at http://www.torro.org.uk/. Building on over 25 years of experience—and of the half a century of the TCO before it—TORRO continues to expand its European role in severe weather data collection and research, helped by the on-going appointment of European representatives and its increasing European membership.     

Experimental results on rainfall estimation in complex terrain with a mobile X-band polarimetric weather radar

In this work the capability of reliable rainfall measurements with small weather radars in complex terrain for flood forecasting purposes is examined. Rain measurements were carried out during winter–spring 2007 with a mobile X-band dual-polarization radar in the northwestern mountainous part of the island of Crete in Greece. In this area a 2D-video disdrometer and a network of raingauges was installed for radar calibration and evaluation of rainfall measurements, respectively. The complex terrain of the experimental site may significantly reduce the performance of rain measurements due to ground clutter and partial or total beam blockage. A beam blockage algorithm using high resolution terrain data was applied in order to find areas with significant terrain effects and estimate correction of the radar measurements. Rain attenuation correction was based on modern sophisticated algorithms using differential phase measurements. The accuracy of rainfall estimation from standard or polarimetric algorithms at plan position indicator (PPI) scans was examined for high-temporal resolution (1 min) rainfall rates and accumulated rainfall values for winter and spring time rain events. For high elevation measurements, which were required in order to avoid terrain effects in large areas of interest, a correction for the vertical-profile-of-reflectivity (VPR) was also applied to the radar data. An average VPR model used in the corresponding correction of reflectivity was constructed based on range–height indicator (RHI) scans. It was concluded that quantitative high resolution X-band radar observations of rainfall in complex terrain is possible after careful application of all the above processing steps.     

QVP方法在双偏振雷达冬季降水观测中的应用

双偏振雷达是研究降水微物理过程的重要探测设备,为研究我国东部沿海地区冬季降水的微物理特性,选取2019—2020年不同天气背景下（包含相态转换）影响上海的冬季降水过程,基于上海南汇WSR-88D双偏振雷达资料,采用准垂直廓线（QVP）方法反演3次降水过程的反射率因子Z_H、差分反射率Z_DR和相关系数ρ_hv的高度-时间廓线。基于QVP,结合探空、再分析资料、地面自动气象站和雨滴谱数据,分析过程时段内融化层高度变化、云中粒子微物理特征,同时借助云雷达观测比对QVP方法的实际效果。结果表明:QVP方法反演的廓线可以体现贝吉龙过程的发生以及融化层高度的变化,并能够有效区分过程时段内的凇附和聚合过程。与此同时,对于非连续性或非均匀性质的降水系统,有针对性地选择方位利用QVP方法进行处理可准确获取重点关注区域降水云系中的微物理过程变化。综上所述,QVP方法反演的高度-时间廓线能够用于降水相态的快速诊断及降水粒子从空中到地面演变的微物理过程分析,为冬季降水相态短时临近预报提供依据。     

基于随机森林的组网雷达龙卷检测算法

近年来我国极端灾害性天气频发,造成了重大人员伤亡和财产损失,随着防灾减灾工作的推进,龙卷等中小尺度强对流灾害性天气的预警预报工作的关注度正逐步提升。现有龙卷检测算法基于对新一代天气雷达基数据在多个仰角和体积扫描中进行阈值判断得到龙卷涡旋特征TVS,在自适应协同观测背景下表现为自适应策略同步较慢,预警预报准确率不高,提前预警时间短。使用机器学习算法结合龙卷在雷达反射率、径向速度和速度谱宽的多重特征能有效提高龙卷识别的准确率和预警时间,能提高组网雷达的协同观测能力。基于随机森林的龙卷检测算法（TDA-RF）,使用CINRAD雷达历史龙卷数据作为训练集,通过随机森林算法对训练集进行分类学习得到龙卷预测模型,使用预测模型对实时雷达数据进行龙卷检测。试验结果表明,TDARF算法能有效识别不同强度的龙卷,较TVS龙卷检测算法能给出龙卷区域的分类概率值,无需对龙卷特征时空连续性进行判断;TDA-RF算法对多个特征进行综合判断具有较好的抗干扰能力,使基于组网雷达的龙卷预警时间最高可达18分钟。     

基于X波段双偏振相控阵雷达的超级单体风暴观测分析

为了研究X波段双偏振相控阵雷达对超级单体风暴的探测能力,利用X波段双偏振相控阵雷达和S波段双偏振天气雷达资料,分析了一次发生在华南地区的超级单体风暴在成熟阶段的精细结构观测特征,结果表明：X波段双偏振相控阵雷达较高的时空分辨率有利于精细监测超级单体快速演变过程,但同时受衰减影响明显,超级单体核心区后侧出现明显的“V”型缺口;超级单体的低层观测到CC谷和ZDR弧,中层观测到ZDR环和CC环,高层高ZH区对应较小的ZDR和CC,这些都是超级单体发展旺盛的重要特征;垂直方向上观测到ZDR柱,ZDR柱与上升气流密切相关。降雹前ZDR柱迅速增加,冰雹降落后ZDR柱高度迅速降低。冰雹降落到地面后会部分融化,导致含水量显著增加,因此在近地层出现KDP大值区,冰雹与降水的混合相态则使得CC降低,这对冰雹的临近预警和识别冰雹在地面的降落位置具有很好的指示意义。研究结果可为X波段双偏振相控阵雷达在强对流天气监测预警中的应用提供参考。     

X 波段双极化雷达对云中水凝物粒子的相态识别

人工影响天气研究需对云中降水粒子的相态和分布结构进行准确识别,以便提高人工影响天气作业效率.中国科学院大气物理研究所的车载X波段双极化雷达可提供与云中降水粒子大小、形状、相态等特征密切相关的4个极化参数:反射率因子、差分反射率、差分相移率、水平和垂直极化相关系数.利用这4个极化参数加上环境温度作为5个输入参量,建立了降水粒子相态模糊逻辑识别算法,识别的降水粒子有10种:毛毛雨、雨、湿霰、干霰、小雹、大雹、雨加雹、湿雪、干雪、冰晶.利用此雷达的实际观测资料,并与地面和飞机空中实测资料对照,对我国南、北方地区观测的降水天气过程进行分析,结果表明:建立的模糊逻辑算法对云内水凝物粒子的相态识别分类合理.     

珠江三角洲台风龙卷的活动特征及环境条件分析

利用常规观测、自动气象站、多普勒雷达等资料分析珠江三角洲台风龙卷的活动特征及其产生的环境条件。结果表明:台风龙卷发生在6—10月,时间多为10—20时,出现在台风登陆后1.3～21.3 h的时段内;多数龙卷位于台风中心的东北象限,台风中心在广东湛江一广西东南部或北部湾附近时是珠江三角洲龙卷发生的高风险期。高层辐散、低层辐合及中低空强东南急流在珠江口附近叠加是龙卷产生的有利环流背景。强或弱龙卷环境条件的共同特征为低抬升凝结高度、强深层和低层垂直风切变及较大风暴相对螺旋度(SRH),主要差异是强龙卷的深层和低层垂直风切变与SRH更大;相似台风路径下,有/无龙卷环境条件的明显差异在于0～1 km低层垂直风切变和SRH,两值越大出现超级单体或中气旋的可能性越大,龙卷发生概率也就越高。台风龙卷风暴母体属于低质心的微型超级单体风暴;低层有强或中等强度中气旋,有时强中气旋中心伴有龙卷涡旋特征(TVS);龙卷出现在钩状回波顶端或TVS附近。与西风带超级单体龙卷相比,台风龙卷中气旋的尺度更小、垂直伸展高度更低。     

我国近30年龙卷风研究进展

从3方面总结了龙卷风研究成果:①研究概况,最初的龙卷风灾后调查到开展天气气候特征分析至近年来开展龙卷风本体结构、产生机制的探讨,获得了丰硕成果;②研究方法提高,从事实调查到利用统计方法,从利用台站常规观测资料到运用卫星、多普勒雷达、风廓线仪等非常规资料开展分析,近年数值模式WRF、ARPS等也被用来研究龙卷风,研究的方法手段不断得到改进;③龙卷风研究、预报面临的困难和未来展望。     

冷涡背景下辽宁龙卷气候特征和环境条件

为了研究冷涡与辽宁龙卷的关系,揭示冷涡背景下辽宁龙卷发生的特征,利用1951—2020年辽宁省龙卷观测和灾情数据以及欧洲中期天气预报中心ERA5大气再分析资料,收集整理冷涡背景下辽宁龙卷个例,对比冷涡背景下EF2—4级(EF2+)和EF0—1级(EF1?)龙卷物理量参数的差异.结果表明:(1)冷涡背景下辽宁龙卷主要出现...     

Climate analysis of tornadoes in China

Based on analysis of historical tornado observation data provided by the primary network of national weather stations in China for the period from 1960 to 2009,it is found that most tornadoes in China(85%)occurred over plains.Specifically,large numbers of tornado occurrences are found in the Northeast Plain,the North China Plain,the middle-lower Yangtze Plain,and the Pearl River Delta Plain.A flat underlying surface is conducive to tornado occurrence,while the latitudal variation of tornado occurrence in China is not so obvious.Tornadoes mainly occur in summer,and the highest frequency is in July.Note that the beginning and the time span of tornado outbreaks are different in North and South China.Tornadoes occur during May-September in South China(south of 25°N),June-September in Northeast China(north of 40°N),July-September in the middle-lower Yangtze Plain,and July-August in North China(between25°and 40°N).More than 80%of total tornadoes occurred during the above periods for the specific regions.The 1960s and 1970s have seen about twice the average number of tornadoes(7.5 times per year)compared to the mean for 1960-2009.The most frequent occurrence of tornado was in the early and mid 1960s;there were large fluctuations in the 1970s;and the number of tornadoes in the 1980s approached the 50-yr average.Tornado occurrences gradually decreased in the late 1980s,and an abrupt change with dramatic decrease occurred in 1994.The decrease in the tornado occurrence frequency is consistent with the simultaneous climatic change in the meteorological elements that are favorable for tornado formation.Tornado formation requires large vertical wind shear and sufficient atmospheric moisture content near the ground.Changes in the vertical wind shear at both 0-1 and 0-6 km appear to be one important factor that results in the decrease in tornado formation.The changing tendency of relative humidity also has contributed to the decrease in tornado formation in China.     

2003年7月8日安徽系列龙卷的新一代天气雷达分析

利用合肥新一代天气雷达资料对2003年7月8日夜间发生在安徽庐江和无为县的龙卷过程进行了简要的分析。7月8日夜间至9日凌晨，与一条自西向东移动的、被包裹在大片层状雨区中的带状对流(飑线)相联系，先后有4个径向速度场上明显的小尺度涡旋特征出现在飑线的前沿。其中一个小尺度涡旋特征持续了大约2小时30分，先后在庐江和无为县产生了龙卷。特别是在无为产生的龙卷，造成了严重的生命和财产损失，其级别为F2～F3，属于较强龙卷。分析表明，此次龙卷为非超级单体龙卷，在反射率因子图上几乎没有任何特征，而在径向速度图上呈现为明显的小尺度涡旋特征，说明新一代天气雷达的使用大大增强了对龙卷的探测能力。