基于雷达回波拼图资料的风暴单体和中尺度对流系统识别、跟踪及预报技术

以中国气象科学研究院灾害天气国家重点实验室的区域雷达组网三维数字产品作为数据输入,在雷达基数据的SCIT(The Strom Cell Identification and Tracking)算法基础上,完成了三维格点风暴单体识别、追踪和预报,用Davis发展的客观诊断评估方法识别雷达拼图资料中的中尺度对流系统,实现了雷达数据的中尺度对流系统识别、跟踪和预报,并利用这两种方法对多个强天气过程进行风暴和中尺度对流系统识别、跟踪及预报.在单雷达区域内用原SCIT和修改后的SCIT算法做了风暴单体定量识别检验.结果表明,(1)修改后的SCIT算法能够实现三维风暴的自动识别、跟踪和预报,在单雷达区域内与原算法识别风暴数量大体相当,中尺度对流系统识别方法能够实现中尺度对流系统的自动识别,并完成跟踪和预报;(2)SCIT算法预报误差较小,中尺度对流系统算法预报误差相对较大,它们的预报误差随时间延长而增大.     

改进的SCIT算法在人工防雹作业中的应用分析

基于新一代天气雷达三维组网产品,利用改进后的对流风暴跟踪(SCIT)算法,对2013年3月22日发生在江西省北部地区的一次降雹天气过程进行冰雹回波识别和跟踪分析。选用能反映冰雹云特征的6个基于雷达反射率三维拼图的人工防雹作业指标,借助经验阈值形成人工防雹作业条件的模糊逻辑判断方法。以地面降雹实况记录为检验标准,对改进后的SCIT算法的识别结果进行检验。结果表明,改进后的SCIT算法共识别出可实施人工作业的冰雹云对流单体4个,不仅多于观测到的地面降雹站点数(3个),也多于未改进的SCIT算法识别出的冰雹云回波单体数,且识别出的位置与实况完全一致,表明应用改进后的SCIT算法有助于增强人工防雹作业的准确率。     

基于数学形态学的三维风暴体自动识别方法研究

基于雷达数据的风暴体识别、追踪及预警方法是重要的临近预报技术之一,其中准确的风暴体自动识别是进行风暴体自动追踪和预警的前提。在风暴体识别中常会碰到的两个问题是:虚假合并和从风暴簇中分离出相距较近的风暴单体。美国国家大气科学研究中心提出的TITAN(Thunderstorm Identification,Tracking,Analysis,and Nowcasting)算法使用单阈值进行识别,容易将相邻的多单体回波识别为一个风暴体。美国国家强风暴实验室提出的SCIT(Storm Cell Identification and Tracking)算法使用7个反射率因子阈值进行识别,可以较好地分离出风暴簇中的风暴单体,但它直接抛弃了低阈值的识别结果,导致风暴体内部结构信息的丢失。SCIT的这种识别策略可能会使处于初生阶段、强度较低的风暴体被错误地抛弃掉。TITAN和SCIT都无法完全识别出相邻风暴的虚假合并。为了解决这两个问题,文章提出了基于数学形态学的识别方法。该方法首先使用第1级阈值进行单阈值识别;其次,对识别得到的风暴体执行基于动态卷积模板的腐蚀操作,以消除虚假合并;然后,使用高一级阈值进行识别,并对识别得到的风暴体进行膨胀操作,当风暴体的边界在膨胀的过程中相互之间接触,或接触到了原来较低阈值识别的风暴体的边界时,则停止膨胀过程;最后,逐次使用更高级别的阈值进行识别,并在每一级阈值的识别过程中执行腐蚀和膨胀操作。试验结果表明,通过在多阈值识别的过程中综合使用膨胀和腐蚀操作,基于数学形态学的三维风暴体识别方法不仅能够成功地识别出风暴体的虚假合并,同时还能在从风暴簇中分离出相距较近的风暴单体时,尽可能多地保留风暴单体的内部结构信息。     

一次副高影响下的局地强风暴触发及维持机制探析

利用自动站观测资料、FY-2G卫星资料和多普勒雷达等资料,对发生在副热带高压影响下的重庆局地强风暴过程进行了观测和数值模拟分析,探讨了其中尺度对流系统(MCS)演变,抬升触发和维持机制。结果表明:(1)在副热带高压影响下,重庆处于高温、高湿气团中,大气层结极不稳定;(2)此次局地风暴抬升触发的关键因子是地面附近浅薄边界层中尺度辐合线,辐合线由川渝盆地中西部MCS的雷暴高压与重庆地面热低压共同作用形成;(3)中尺度辐合线触发的对流风暴形成小范围冷池出流与环境风场形成新的辐合线,加强对流风暴发展,并再次触发新的对流单体。承载层平均风为偏南风,使得对流单体向北缓慢移动,冷池出流和边界层辐合线共同作用使得风暴单体向西向北传播和长时间维持。     

风暴单体识别与跟踪(SCIT)算法评估

利用兴义新一代多普勒天气雷达复合体扫资料及WSR-88D提供的风暴单体识别与跟踪(SCIT)算法对2007-2008年发生在贵州省黔西南地区的40次天气过程个例进行验证、分析,分别从单体识别、单体跟踪评估、单体位置预报、单体算法评估效果与季节关系分析、单体算法评估效果与距离关系分析、冰雹暴雨评估对比分析6个方面进行评估、分析。在充分考虑了当地地理环境、气候背景的前提下对算法评估不太理想的情况进行了误差分析,并进行了算法补偿,提出了解决的办法,一是降低识别阈值,将SCIT的7个反射率阈值降低一个等级,二是提取反射率因子垂直梯度,用上述两个改进方法对2007-2008年的40次天气过程重新进行评估,并与算法改进前的评估效果进行对比检验,结果表明,算法改进后评估效果有所提高。     

基于动态模板函数的线状中尺度对流系统自动识别

在中尺度对流系统(mesoscale convective systems,MCSs)自动识别、跟踪基础上,根据拟合椭圆长轴设计动态模板和得分函数,完成了雷达拼图资料上的线状MCSs自动识别。并利用不同类型中尺度天气过程对算法进行检验,分析结果表明:(1)算法能够实现对线状MCSs的自动识别,由于对流系统分裂与合并造成的回波形态"突变",得分值结果能得到较好的反映;(2)算法能够实现对线状MCSs天气的跟踪,一般情况下跟踪效果较好,在分裂或者合并发生的时刻跟踪效果较差。     

中尺度对流系统和闪电

1.引言每年春夏时节美国包括大平原和东南地区在内的广大地区的总降水量与中尺度对流系统(Mesoscale Convective Systems,以下简称MCS)过境有关.MCS定义为持续时间至少几小时且在生命史内具有明显对流活动的大范围降水系统(水平尺度为100-500km).根据定义,MCS包括超级单体雷暴,伴有层状云降水区的飑线以及中尺度对流复合体(MCC).MCC是根据云顶最低温度和特定温度阈值的覆盖范围来定义的(Maddox,1980).MCC中的对流单体的分布较为     

风暴的多普勒雷达自动识别

3种基于雷达的风暴自动识别方法:(1)美国WSR-88D Build 7.0风暴算法,它利用多个预设阈值来检验回波的强度和连续性,以构造具有三维连续结构的风暴,该方法在风暴合并、分裂以及多个单体相距较近时误差较大。(2)为美国WSR-88D Biuld 9.0风暴算法(B9SI),它用7个反射率因子识别阈值替代此前唯一的一个反射率因子阈值,增加了特征核抽取和相近单体处理技术,并保留远距离上的强的2D分量。该方法在面对成串或成簇多单体时,能够识别出多个单体核,并准确定位。B9SI没有考虑反射率因子纹理结构和空间梯度的变化,也没有利用径向速度资料,因此无法描述风暴对流的发展状况。(3)CSI方法,它在降低B9SI反射率因子识别阈值的基础上,利用模糊逻辑技术对B9SI输出结果和雷达基资料做进一步的处理,以计算描述风暴对流发展强弱的对流指数。CSI首先提取一组最能描述风暴对流性特征的物理量,包括反射率因子纹理结构、反射率因子空间变化率、垂直积分含水量和径向速度标准方差,并分配权重;其次,利用每一个物理量的统计结果,结合其物理意义,设计出相应的隶属函数,以计算风暴与该物理量描述的对流性特征相匹配的概率;最后对多个概率值进行加权平均即得对流指数。此外,计算了2004年8月11日发生在广州的超级单体演变过程中的对流指数,分析表明:对流指数两次加大对应了超级单体的合并增长和辐合增长过程;风暴最强盛时对流指数为0.744;随后对流指数减小,雷达观测到的最大反射率因子对应高度明显降低,地面上开始出现大范围的强降水。     

冷涡背景下MCS的统计分析

文章首先给出冷涡的定义,根据冷涡的定义识别出冷涡,2005—2011年4—9月7年共识别出60个冷涡,主要形成在蒙古和我国的东北地区。然后根据中尺度对流系统(MCS)的标准按尺度大小将MCS分类为α中尺度对流系统（MαCS）和β中尺度对流系统（MβCS）,又按MCS的形状将MαCS分类为中尺度对流复合体（MCC）和持续拉长状对流系统（PECS）,MβCS分类为β中尺度对流复合体（MβCC）和β中尺度持续拉长状对流系统（MβECS）。利用FY 2C(2005—2009年)和FY 2E（2010—2011年）的TBB资料对60个冷涡背景下的MCS进行识别并对其时空分布特征及其与冷涡的关系进行统计分析。结果表明：(1) 60个冷涡过程识别出61个MCS,MCS通常产生在我国东北和华北,MCC和PECS生成较分散;MβCC主要集中在华北和东北地区;MβECS主要集中在东北地区。(2) 6月生成的MCS最多,有16个,9月最少。MCS大多形成于当地的下午和晚上,此时对流发展旺盛,有利于中尺度对流系统的产生,到了夜间MCS发展成熟,至凌晨—日出时分消散。(3) 冷涡背景下的MCS的移动路径多数是从西向东偏北的,其生成后主要向东移动,这和我国中纬度西风带天气系统的移动路径基本一致,但由于受冷涡等天气系统的影响,会出现不同的移动方向。位于冷涡东侧且距离冷涡中心距离较近的MCS有向东偏北方向移动的趋势;位于冷涡南侧且距离中心较远的MCS有向东偏南方向移动的趋势。(4) 冷涡背景下的MCS主要产生在冷涡的发展阶段,成熟和消散阶段相对较少。(5) 冷涡背景下的MCS主要形成在冷涡的东南部,西南部也有一小部分。(6) MβCS系统发展较MαCS系统快,持续的时间也较MαCS短。     

"雨燕"中风暴算法与新一代雷达SCIT产品的对比分析

利用2008年广州地区强对流资料,在构建风暴预报位置客观评分模块的基础上,统计分析了三种风暴算法(分别简称为SCIT、雨燕2006、雨燕2008)的预报误差.SCIT在30和60分钟预报时效,分别识别出5 124和2 203个风暴,预报位置绝对平均距离误差为12.9和23.7 km.雨燕2006识别为4 975和2 1...     

Analysis of mesoscale convective systems in Catalonia using meteorological radar for the period 1996–2000

The aim of this paper is to show a climatology of Mesoscale Convective Systems (MCS) in the NE of the Iberian Peninsula, on the basis of meteorological radar observations. Special attention was paid to those cases that have produced heavy rainfalls during the period 1996–2000. Identification of the MCS was undertaken using two procedures. Firstly, the precipitation structures at the lowest level were recognised by means of a 2D algorithm that distinguishes between convective and non-convective contribution. Secondly, the convective cells were identified using a 3D procedure quite similar to the SCIT (Storm Cell Identification and Tracking) algorithm that looks for the reflectivity cores in each radar volume. Finally, the convective cells (3D) were associated with the 2D structures (convective rainfall areas), in order to characterize the complete MCS. Once this methodology was presented the paper offers a proposal for classifying the precipitation systems, and particularly the MCS. 57 MCS structures were classified: 49% of them were identified as linearly well-organised systems, called TS (39%), LS (18%) and NS (43%). In addition to the classification, the following items were analysed for each MCS found: duration, season, time of day, area affected and direction of movement, and main radar parameters related with convection. The average features of those MCS show an area of about 25000 km², Z_max values of 47 dBz, an echotop of 12 km, the maximum frequency at 12 UTC and early afternoon and a displacement towards E-NE. The study was completed by analysing the field at surface, the presence of a mesoscale low near the system and the quasi-stationary features of three cases related with heavy rainfalls. Maximum rainfall (more then 200 mm in 6 h) was related with the presence of a cyclone in combination with the production of a convective train effect.     

A MASCOTTE-based characterization of MCSs over Spain, 2000–2002

A 3-year Mesoscale Convective Systems (MCSs) database, which extends from 2000 to 2002, has been built for the Iberian Peninsula and the Balearic Islands using the objective method MASCOTTE (MAximum Spatial COrrelation Technique). It was originally developed to track the evolution of convective systems over the Amazon region; after modifications, it is able to track MCS evolution even with an hour and a half of missed images and provides essential information of both dynamical and morphological characteristics of MCSs. MASCOTTE is tested against a visual and subjective method, and is found to offer advantages such as automation and a simple and efficient operation that make it very useful for building large MCS databases.Thirty-five MCSs were found between June and October, most of them originated along the Mediterranean coast and near the Pyrenees, showing an increasing occurrence from June to September, when the maximum is found. The regions most influenced by MCS occurrences are Balearic Islands, Valencia, Catalonia, Murcia and the Basque Country. The MCSs tend to be small, short-lived and linear, usually moving eastward or northeastward with low velocities.The MCSs-associated precipitation presents high variability, ranging from 80 to 0 mm h⁻¹ as maximum hourly records. Two different convective regions are identified based on MCS behavior in extreme precipitation events: Northern Spain (the Basque Country) with abundant and continuous precipitation regime but little MCS influence, and the Mediterranean coast, where precipitation is sporadic but much more intense.     

3-D Storm Automatic Identification Based on Mathematical Morphology

The strom identification, tracking, and forecasting method is one of the important nowcasting techniques. Accurate storm identification is a prerequisite for successful storm tracking and forecasting. Storm identification faces two difficulties: one is false merger and the other is failure to isolate adjacent storms within a cluster of storms. The TITAN (Thunderstorm Identification, Tracking, Analysis, and Nowcasting) algorithm is apt to identify adjacent storm cells as one storm because it uses a single reflectivity threshold. The SCIT (Storm Cell Identification and Tracking) algorithm uses seven reflectivity thresholds and therefore is capable of isolating adjacent storm cells, but it discards the results identified by the lower threshold, leading to the loss of the internal structure information of storms. Both TITAN and SCIT have the problem of failing to satisfactorily identify false merger. To overcome these shortcomings, this paper proposes a novel approach based on mathematical morphology. The approach first applies the single threshold identification followed by implementing an erosion process to mitigate the false merger problem. During multi-threshold identification stages, dilation operation is performed against the storm cells which are just obtained by the higher threshold identification, until the storm edges touch each other or touch the edges of the previous storms identified by the lower threshold. The results of experiment show that by combining the strengths of the dilation and erosion operations, this approach is able to mitigate the false merger problem as well as maintain the internal structure of sub-storms when isolating storms within a cluster of storms.     

利用SCIT算法分析江淮地区对流云特征

本文设计了一种运用SCIT算法提取雷达拼图中对流云特征量的方法:用SCIT算法识别并追踪云体,算法中只用一个反射率阈值识别对流单体、云体边界;使用模糊逻辑法区分层状云和对流云,提取对流云雷达特征量。使用该方法提取了2013—2015年江淮地区夏季对流云的雷达特征量,并对雷达特征量与降水量分布的关系进行统计分析。结果表明:江淮地区夏季对流云中生命史为13～30 min的对流云比较多,约占总数的60%;生命史大于30 min的对流云较少,并具有平均回波强度、VIL、冷层厚度较大的特征,其最大回波强度和VIL与降水量的相关性较好。     

A warm season climatology of mesoscale convective systems in the Mediterranean basin using satellite data

A 3-year climatology of isolated warm season mesoscale convective systems (MCSs) was built for the Mediterranean basin using Meteosat Second Generation infrared imagery and an objective identification and tracking algorithm. A dataset of 4,718 MCS trajectories was constructed for the warm season of the period 2005–2007, which in turn was split into two subsets (deep and weak convective) according to the intensity of convection using a discriminant parameter in the MCS properties. Several parameters related to geographical, temporal, radiative, morphological, and motion related properties were calculated for each MCS. The majority of MCSs are mainly continental and strongly correlated with orography showing an increased formation from April to June when maximum is found. Initiation and dissipation time revealed a distinct diurnal cycle having a strong correlation with the typical diurnal heating cycle of the atmosphere. On average, a typical isolated MCS in the Mediterranean basin initiates between 14:00 and 17:00 local solar time, tends to be small with elongated shape, short-lived, usually moving toward northeast to southeast with a mean velocity of 36 km/h. When comparing the two MCS subsets, some notable differences were revealed. Weak convective MCSs initiate earlier, move faster, travel longer, tend to reach slightly smaller sizes, are more linear, present higher cloud top temperatures, and have lower fractions of convective cloud type areas than deep convective systems.     

新一代天气雷达海浪回波特征分析和识别方法研究

海浪回波是影响沿海雷达定量降水估测和其他产品的重要因素,根据福州、温州的SA多普勒雷达收集的海浪回波资料,按出现时间关系将其分为两类。第1类海浪回波强度一般较强,主要出现在非台风期间降水过程的前后;第2类海浪回波强度较弱且均匀,仅在台风期间的雷达位置的近海域出现。通过分析资料得到两类海浪回波不同于对应降水回波的各种特征,确定识别海浪回波的最佳隶属函数。针对第1类海浪回波,考虑到海浪回波很少与降水回波混合,采用了基于回波分块和模糊逻辑的海浪回波识别方法,首先利用算法预处理条件判断是否执行算法识别,然后采用风暴单体识别与跟踪(SCIT)算法将回波组合成块,计算每个独立回波块的属性值,对符合要求的回波块和离散回波点再进行基于模糊逻辑的逐点识别,借鉴了刘黎平等2007年提出的分步式回波识别方法并加以改进来实现回波点的动态阈值识别。针对第2类海浪回波,直接采用了基于模糊逻辑的分步式海浪回波识别方法。分析表明,两种识别方法能分别对应识别出大部分海浪回波,回波分块和分步式方法对海浪回波的识别效果有明显的改善,有效地降低了降水回波被误判为海浪回波的概率。     

STATISTIC CHARACTERISTICS OF MCSS OVER ASIA AND WESTERN PACIFIC REGION

Mesoscale convective systems (MCSs) are severe disaster-producing weather systems. Previous attempts of MCS census are made by examining infrared satellite imageries artificially, with subjectivity involved in the process unavoidably. This method is also inefficient and time-consuming. The disadvantages make it impossible to do MCS census over Asia and western Pacific region (AWPR) with an extended span of time, which is not favorable for gaining a deeper insight into these systems. In this paper, a fire-new automatic MCS identification (AMI) method is used to capture four categories of MCSs with different sizes and shapes from numerical satellite infrared data. 47,468 MCSs are identified over Asia and western Pacific region during the warm season (May to October) from 1995 to 2008. Based on this database, MCS characteristics such as shape, size, duration, velocity, geographical distribution, intermonthly variation, and lifecycle are studied. Results indicate that the number of linear MCSs is 2.5 times that of circular MCSs. The former is of a larger size while the latter is of a longer duration. The 500 hPa steering flow plays an important role in the MCS movement. MCSs tend to move faster after they reach the maximum extent. Four categories of MCS have similar characteristics of geographical distribution and intermonthly variation. Basically, MCSs are zonally distributed, with three zones weakening from south to north. The intermonthly variation of MCSs is related to the seasonal adjustment of the large-scale circulation. As to the MCSs over China, they have different lifecycle characteristics over different areas. MCSs over plateaus and hill areas, with only one peak in their lifecycle curves, tend to form in the afternoon, mature at nightfall, and dissipate at night. On the other hand, MCSs over plains, which have several peaks in their lifecycle curves, may form either in the afternoon or at night, whereas MCSs over the oceans tend to form at midnight. Affected by the sea-land breeze circulation, MCSs over coastal areas of Guangdong and Guangxi always come into being at about 1500 or 1600 (local time), while MCSs over the Sichuan Basin, affected by the mountain-valley breeze circulation, generally initiate nocturnally.     

S波段多普勒天气雷达非降水气象回波识别

在气象条件为晴空或有云但无降水的情况下,在雷达站附近经常可观测到大面积的非降水气象回波,这些回波对定量估测降水和雷达资料同化效果产生重要影响。为了有效识别这些非降水回波,该文发展了基于模糊逻辑识别和回波分块的非降水气象回波识别算法 (NPMDA)。该文首先利用地面和卫星资料为标准,提出了非降水回波的确定标准,并利用北京SA雷达,对非降水气象回波特性进行了统计分析,得到了隶属函数。在非降水回波识别时首先采用SCIT算法将回波组合成片,然后对整个PPI进行初步的判断。对不能初步判断为降水的PPI,采用模糊逻辑的方法计算成片回波的属性值,依据成片回波的属性值得到片内回波逐点识别时的阈值,从而实现了回波的动态阈值识别。结果表明:对大部分非降水气象回波识别效果较好,对较强降水回波误判较少,弱降水回波有时会出现一定的误判。与NCAR使用的ICADA方法相比,NPMDA方法能明显提高非降水回波的识别率,减少降水回波的误判率。