A multiscale observational case study of an isolated tornadic supercell

This work deals with the analysis of an isolated tornadic supercell thunderstorm that took place on the plain of Friuli Venezia Giulia (Italy) causing several damage. The analysis is performed using different kind of data, looking in the available information for possible signatures that could be helpful in the forecasting and nowcasting procedures. The analysis reveals that rather than a single cause for the tornadic storm development, there is an “interaction” of several effects. In particular, a favorable environment seems to be produced by the interplay between synoptic and mesoscale environments with a fundamental role played by orography. Radar data, in particular Doppler measurements, are fundamental to the recognition and interpretation of the events but in this particular case they could give little useful information for the forecasting and nowcasting procedures. The most robust signals of an environment prone to the onset of severe deep moist convection come from the thermal gradients at the ground and by the vertical profile analysis. The reason why the event took place in that specific place and not in others is still unknown.     

Local housing price index analysis in wind-disaster-prone areas

This study examines the effect of severe wind events on the mean and variance of housing price indices of six metropolitan statistical areas (MSA) that are vulnerable to hurricanes and/or tornadoes. The research focuses on three areas that experienced significant tornado activity (Fort Worth-Arlington, Nashville, and Oklahoma City) and three hurricane-prone areas (Corpus Christi, Miami, and Wilmington, NC). An econometric time series model that captures the housing market responses to severe windstorms is utilized. The model estimates changes in the local housing price index (HPI) as a function of several control variables as well as dichotomous variables that correspond to the tornadoes and hurricanes. As expected, the statistical findings indicate an immediate but short-lived decline in housing prices following a tornado or hurricane. Somewhat surprising is the result that the impact on the housing market is remarkably consistent whether the wind event was a hurricane or a tornado. Hurricanes and tornadoes are vastly different in terms of the point probabilities of a hit, the scope of the affected area and the lead time that supports last minute preparation to mitigate damage. It appears that the market response to destruction of real property does not distinguish between the types of wind event that produced the damage to the region. Results suggest that windstorms result in an immediate one-half to two percent reduction in total MSA housing value. This corresponds to a range of $34 million to $580 million in lost housing value. Estimates indicate some differences in how long market values continue to decline in the periods following the wind event; however, most of the decline occurs within four quarters after the windstorm. These differences can be attributed to the particular time series characteristics of the specific housing markets and their respective housing price indices. The market serves the purpose of integrating and normalizing the losses. In so doing the market provides a metric— a method for calibrating and comparing structural damage caused by different phenomenon.

广东佛山EF3级龙卷超级单体风暴高分辨率数值模拟

本文对2015年10月4日发生于广东佛山地区台风"彩虹"登陆后螺旋云带中的一次强龙卷风过程进行高分辨率（148 m,48 m）数值模拟,结果产生了类龙卷涡旋（Tornado-Like Vortex,TLV）,最接近观测到的龙卷风,并对龙卷超级单体及产生龙卷的TLV系统的三维动热力精细化结构进行诊断分析.结果表明,此次龙卷产生于超级单体右侧边缘,钩状回波显著,伴有明显的中气旋活动.模拟的龙卷超级单体与之前观测研究和理想化建模的龙卷超级单体结构相类似,超级单体后部云墙之下低层水成物呈现狭窄的触地漏斗状结构,对应低层的TLV系统;TLV具有中心气流下沉和周围气流上升的动力结构,对应上宽下窄的强烈涡管.与之前的研究相比,本次台风螺旋云带中的超级单体中后部入流较弱,出流较强,其前部气流上升存在水合物聚集.相对螺旋度（Storm Relative Helicity,SRH）的分析表明,超级单体的发展伴随正负SRH的增大,龙卷发生在SRH正负高值区的交界处.     

Tornado shelter-seeking behavior and tornado shelter options among mobile home residents in the United States

Residents of 401 mobile homes in Georgia, Mississippi, Illinois, and Oklahoma were surveyed after they heard a tornado warning. Most residents (69%) did not seek shelter during the warning. Half of those who sought shelter went to the frame house of a friend, neighbor, or relative, and 25% of those sought shelter in a basement or underground shelter. Some of the places where residents sought shelter were of dubious quality, such as their own mobile home, another mobile home, or in an out-building. Twenty-one percent of mobile home residents believed that they had a basement or underground shelter available as shelter during a tornado warning, and about half of those said they would drive to the shelter. Residents said they would drive if the shelter was more than 200 m away. Fifteen percent actually had a basement or underground shelter suitable as shelter within 200 m of their mobile home, but only 43% of the residents would use those shelters. The most common reason cited for not using the shelters was that they did not know the people who lived there. Likewise, a frame house or other sturdy building was within 200 m of 58% of the mobile homes, but only 35% of the residents stated they would use those houses for shelter. Thirty-one percent of mobile home residents had a ditch that was at least 0.5 m deep within 200 m of the mobile home. However, 44% of these ditches had utility lines overhead, 23% had water in them, and 20% had trees overhead. The limited tornado shelter options among mobile home residents in the United States needs to be incorporated into safety instructions so that residents without nearby shelter are allowed to drive to safer shelter.     

安徽龙卷发生的环境条件和临近预警

利用1960—2009年气象观测资料,对安徽省128次龙卷的气候特征和环流背景进行了分析,结果表明,龙卷多发于4-9月平原丘陵地带的江淮东部,而山区极少,20世纪80年代以后龙卷明显减少;建立了安徽出现龙卷的4种概念模型。同时,利用日本JMA 20km×20km高分辨率数值预报再分析产品对比分析了龙卷、冰雹及雷雨大风的环境场,发现龙卷与冰雹、雷雨大风在4个方面存在明显差异,即中低层比湿、中低层垂直风切变、风暴相对螺旋度和0℃层以下的对流有效位能与整层对流有效位能比值,前3个均是龙卷最大,龙卷是冰雹和雷雨大风的2倍～3倍,对流有效位能主要集中在0℃层以下,而冰雹和雷雨大风主要集中在0℃层以上。基于龙卷临近预警和安徽6次龙卷的雷达特征显示,龙卷涡旋TVS的底部达到雷达最低仰角探测高度的中气旋及其后龙卷涡旋特征是识别龙卷的主要依据,龙卷触地前中气旋的最大速度差增强,其强度与龙卷强度呈正相关。而雷达距离的选取也直接影响龙卷的临近预警,距离龙卷20～100km处的雷达较为理想,200km以外的雷达资料对龙卷预警几乎没有意义。     

海门一次F1级龙卷的多普勒天气雷达特征分析

用多普勒天气雷达、常规观测和地面加密观测资料对2011年7月13日发生在江苏南通海门市树勋镇的龙卷风过程进行了详细分析。得出:较长时间的不稳定层结的存在,较低的抬升凝结高度,较强的水平和垂直风切变以及地面干线的存在为龙卷风的发生发展提供很好的动力条件;底层冷空气的切入,较强的风切变易使单体发展更加旺盛。强回波中心高度和垂直积分液态含水量的下降,径向速度风场中气旋性涡旋的迅速发展是对龙卷风提前警戒的很好指标。龙卷风进行过程中,此系统为低位质心的对流系统,产生的天气是龙卷,伴随大风,与冰雹的高位质心对流系统有明显的区别。中气旋高度,最大切变高度的骤降,中气旋尺度的急剧收缩预示着龙卷的发生,为我们今后的龙卷风预警提供有利的参考。     

江苏省龙卷风灾害易损性分析

在分析江苏省龙卷风气候特征的基础上,利用主成分分析方法对江苏省龙卷风灾害易损性进行了综合评估,得到了江苏省各市的龙卷风灾害易损度,并利用聚类分析对各市易损度进行了分级区划。表明徐州为龙卷风灾害极高易损区,泰州、南通、苏州为高易损区,盐城、镇江、扬州为中易损区,淮安、宿迁、南京、无锡、常州和连云港为低易损区     

The climatology of tornadoes and waterspouts in Italy

In this work 10 years of reports collected by weather amateurs are used to define a preliminary climatology of tornadoes and waterspouts in Italy. The results show behaviors different from those observed in other countries. Generally, tornadoes and waterspouts are more frequent in late summer and autumn than in the other seasons. The seasonality of tornadoes and waterspouts appears different for different Italian zones, in particular in the Po Valley and Friulian plain and coast (south to the Alps) tornadoes and waterspouts are more frequent in spring and early summer while in the Tirrenian and Ionian coasts (western and southern Italy), tornadoes and waterspouts are more frequent in late summer and autumn. As observed in other studies (Brooks, H., E. and Doswell, C. A. III, 2001. Some aspects of the international climatology of tornadoes by damage classification. Atmos. Res., 56, 191–201.) Italian tornadoes and waterspouts are statistically weaker than in other countries but this difference cannot be completely ascribed to the presence of waterspouts. The “CAPE Storm-Relative-Helicity diagrams” and “Shear Magnitude diagrams” obtained for Italian tornadoes and waterspouts show different characteristics than those obtained for US. The cause of these differences is still unknown, it can rely in the sample selection (problems with the concept of proximity sounding) or in a real climatic effect.     

Sounding-derived parameters associated with large hail and tornadoes in the Netherlands

A study is presented focusing on the potential value of parameters derived from radiosonde data or data from numerical atmospheric models for the forecasting of severe weather associated with convective storms. Parameters have been derived from soundings in the proximity of large hail, tornadoes (including tornadoes over water: waterspouts) and thunderstorms in the Netherlands. 66,365 radiosonde soundings from six stations in and around the Netherlands between 1 Dec. 1975 to 31 Aug. 2003 were classified as being associated or not associated with these weather phenomena using observational data from voluntary observers, the Dutch National Meteorological Institute (KNMI) and lightning data from the U.K. Met. Office. It was found that instability as measured by the Lifted Index or CAPE and 0–6 km wind shear independently have considerable skill in distinguishing environments of large hail and of non-hail-producing thunderstorms. It was also found that CAPE released below 3 km above ground level is on average high near waterspouts and weak tornadoes that mostly occur with low shear in the lowest 1 km above the Earth's surface. On the other hand, low-level shear is strong in environments of stronger (F1 and F2) tornadoes and increases with increasing F-scale. This is consistent with the notion that stretching of pre-existing vertical vorticity is the most important mechanism for the formation of weak tornadoes while the tilting of vorticity is more important with stronger tornadoes. The presented results may assist forecasters to assess the likelihood of severe hail or tornadoes.     

Spatial dependencies in wind-related housing damage

This article examines the spatial dependence among housing losses due to tornadoes using data from the May 1999 Oklahoma City tornado. In order to examine the existence of spatial dependence and its impacts on the damage analysis, we compare an estimation based on a traditional ordinary least square model with the general spatial model. The results show that housing damage in this disaster area is highly correlated. Monetary losses not only depend on the tornado that struck residences, but are related to the damage magnitudes of neighboring houses. Average losses as well as the loss ratio increase with the Fujita Scale damage rating. We conclude that the general spatial model provides unbiased estimates compared to the ordinary least square model. In order to construct appropriate home insurance policies for tornado disasters or to improve the damage resistance capabilities of houses, it is necessary for insurance underwriters and builders to consider spatial correlation of tornado damage.