Repeated exposure to tornado events in “Dixie Alley” over the years with often fatal outcomes has led to vibrant discussion in the weather enterprise. Two areas of focus for research are socio-economic factors which increase vulnerability for individuals, and the communication channels used by individuals during tornado events. Understanding what individuals know and how their background and experiences play a role in weather knowledge can help communicators reach at-risk groups more effectively and efficiently not only in the moments that matter, but also when education can play a role in the weeks and months before a potential tornado event. Through a comprehensive survey, socio-economic factors were analyzed with public perception and tornado alert knowledge. Individuals in Mississippi and Alabama have a firm grasp in tornado knowledge and can perceive vulnerability based on several factors.

A majority of tornado research focuses on the Great Plains region of the United States. Knowledge of tornado environments outside of the Great Plains is limited; this is especially true for the Southeast U.S. In addition, little is known about the role of the lower troposphere on tornadogenesis. Therefore, this study examines low-level thermodynamic parameters associated with tornadoes in the Southeast U.S between 1960 and 2002. Previous studies have shown that higher values of CAPE, 0-3 km CAPE, 0-1 and 0-3 km SRH, and 0-1 and 0-1 km EHI are more likely associated with significant tornadoes. Similar studies have shown that decreasing LCL, LFC heights, and CIN are common with significant tornadoes. This study supports that higher values of shear and instability/shear and lower CIN values are associated with significant tornadoes in the Southeast. However, this study indicates that instability, LCL, and LFC heights may be poor tornado strength discriminators.

Disaster damage assessments are a critical component to response and recovery operations. In recent years, the field of remote sensing has seen innovations in automated damage assessments and UAS collection capabilities. However, little work has been done to explore the intersection of automated methods and UAS photogrammetry to detect tornado damage. UAS imagery, combined with Structure from Motion (SfM) output, can directly be used to train models to detect tornado damage. In this research, we develop a CNN that can classify tornado damage in forests using SfM-derived orthophotos and digital surface models. The findings indicate that a CNN approach provides a higher accuracy than random forest classification, and that DSM-based derivatives add predictive value over the use of the orthophoto mosaic alone. This method has the potential to fill a gap in tornado damage assessment, as tornadoes that occur in wooded areas are typically difficult to survey on the ground and in the field; an improved record of tornado damage in these areas will improve our understanding of tornado climatology. / Master of Science / Disaster damage assessments are a critical component to response and recovery operations. In recent years, the field of remote sensing has seen innovations in automated damage assessments and Unmanned Aerial System (UAS) collection capabilities. However, little work has been done to explore the intersection of automated methods and UAS imagery to detect tornado damage. UAS imagery, combined with 3D models, can directly be used to train machine learning models to automatically detect tornado damage. In this research, we develop a machine learning model that can classify tornado damage in forests using UAS imagery and 3D derivatives. The findings indicate that the machine learning model approach provides a higher accuracy than traditional techniques. In addition, the 3D derivatives add value over the use of only the UAS imagery. This method has the potential to fill a gap in tornado damage assessment, as tornadoes that occur in wooded areas are typically difficult to survey on the ground and in the field; an improved record of tornado damage in these areas will improve our understanding of tornado climatology.

Thesis (Ph.D.)--University of Delaware, 2007. / Principal faculty advisor: Havidan Rodriguez, Dept. of Sociology & Criminal Justice. Includes bibliographical references.

The southeast United States is prone to severe weather throughout the year. Despite technological advances, some severe weather events occasionally remain unwarned in this part of the country. Past studies examined the relationship between cloud-to-ground (CG) lightning and warm season severe weather episodes. The present study examined the relationship between cool season tornadoes and CG lightning, with a focus over the southeastern United States, where most cool season tornadoes occur. Data from the Storm Prediction Center and National Lightning Detection Network (NLDN) were used to investigate CG lightning properties within 50 km and one hour before tornado touchdown. This was completed over a period of 13 cool seasons from October 1989 through March 2002. Of 3325 tornado events, 2358 contained at least one NLDN-detectable flash. CG lightning attributes of peak current, multiplicity, and flash density compared well with those of prior warm season lightning research. Overall event frequency appeared to be lower than in the warm season. Almost all Central Plains events were accompanied by at least one NLDN-detectable flash. Up to 70% of tornado events near the Gulf of Mexico and Atlantic coasts contained no NLDN-detectable lightning. Although it is not known why this trend was observed, it is speculated that NLDN detection efficiency and/or storm structure differences may play a role in these observations. Warm season studies have correlated tornadoes with predominantly positive (>50% positive CG lightning), or PPCG storms. Gridded maps showed the greatest percentage and highest frequency of cool season PPCG storms across Kansas and Nebraska, with up to 70% of events associated with PPCG lightning. A secondary, albeit lower, frequency maximum extended 1° to 2° inland across Louisiana into North Carolina. This study also subjectively defined a storm with “enhanced” positive cloud-to-ground (EPCG) lightning as one containing >25% positive cloud-to-ground lightning, which corresponds to approximately the 75th percentile of all cool season tornadoes. This has lead to speculation that EPCG criterion may be a better indicator of the possibility of severe weather than the traditional PPCG criterion.

The thesis begins with a review of the literature dealing with the incentives and disincentives for pursuing defence co-production policies in Western Europe. Political, economic and military aspects are each dealt with in turn, and their relative importance assessed. Following this section is a case study of the Panavia Multi-Role Combat Aircraft - the 'Tornado' - now in service with the air forces of West Germany, Britain and Italy. The study traces the progress of the MRCA programme from its initial conception through to production. The main theme of the case study is how the concerns of military-operational performance, cost-saving benefits, and programme efficiency were all secondary to government pursuit of wider political objectives. While the general literature was found to focus upon cost-savings in collaborative procurement, such savings are seen to be constrained or even determined by the outcome of frequently unrelated political decisions. Although set within the broad framework of national economic performance and the demands of social needs upon limited public expenditure budgets, these decisions are based upon government preferences rather than industrial or other lobby-group pressures. A cursory evaluation of the MRCA programme and the aircraft itself is included in the conclusion. The project is seen to have achieved mixed success, but with significant problems. / Arts, Faculty of / Political Science, Department of / Graduate

This research discusses how the design of a tornado forward error correcting channel code (FEC) sends digital data stream profiles to the receiver. The complete design was based on the Tornado channel code, binary phase shift keying (BPSK) modulation on a Gaussian channel (AWGN). The communication link was simulated by using Matlab, which shows the theoretical systems efficiency. Then the data stream was input as data to be simulated communication systems using Matlab. The purpose of this paper is to introduce the audience to a simulation technique that has been successfully used to determine how well a FEC expected to work when transferring digital data streams. The goal is to use this data to show how FEC optimizes a digital data stream to gain a better digital communications systems. The results conclude by making comparisons of different possible styles for the Tornado FEC code.

It is quite astonishing that most homes being built today fail to adequately respond to natural disasters. Looking within the last decade, the data indicates that these disasters are more frequent than they once were, and are affecting a larger geographical area. Many believe that these patterns will only escalate. The magnitude and frequency of these tornadoes and hurricanes are hard to ignore. The power and destruction inflicted has affected most Americans in a multitude of ways. We simply cannot continue to build homes using typical methods of construction in these disaster-prone areas. To re-build a home in the same manner on top of a post-disaster site is the definition of insanity. This thesis aims to bridge the gap and merge the benefits of the safety associated with living in a concrete bunker and the perception of quality of space associated with living in a glass home. An analysis of feasibility and difficulty of construction, and cost will help set parameters early on in the design phase. The goal is that the resultant home could be deployed in both pre and post disaster areas. The challenge, I am addressing, is designing a home that is impervious to tornado and hurricane while offering a delightful space of dwelling.

Tornadoes are one of the most frequent and destructive disasters in the United States. Like other environmental calamities, tornadoes too act as push factors for migration. The objectives of this study are to define tornado hot spots in the US, to analyze migration effectiveness in the tornado hot spots and non-hot spots, and to explore how tornado and other socio-economic factors influence migration decision. Both quantitative and qualitative methods were used. Internal revenue service migration data, SPC tornado data, and Census Bureau data were used in the study. The results indicate that there are significant differences between migration patterns in the tornado hot spots and rest of the country: tornado hot spots are losing population to other regions. The results also indicated that along with the traditional socio-economic push and pull factors of migration, tornado occurrences also influenced people’s migration decision in the United States.

Many studies have suggested that the tornado database is biased by the concentration of human observers. Some studies have shown a possible 66% decrease in tornado reporting can be directly attributed to population density. This study examines whether or not such biases exist throughout the United States. Population data are compared to the historical tornado database in order to better understand the relationship(s) between each variable. Various statistical and spatial techniques are implemented in order to better identify relationships. As expected, weak (F0-F1) tornadoes show a correlation to both population patterns and travel routes. However, not all regions of the United States share the same relationships during the study period. Therefore, any meaningful adjustment to the tornado climatology cannot be made because of the variation in both spatial and temporal changes.