The hazards literature has identified many factors as being influential in the decision making process during high risk, short-notice disasters. Risk perception and previous disaster experience are commonly identified as two of the more influential factors in this complex process. However, few studies adequately address the complex role(s) that these factors play in self-protective decision-making during successive high-risk events. In particular, the role of previous disaster experience during subsequent events is still a matter of considerable discussion and inconsistent findings. This thesis examines two events that occurred in August, 2011 in Goderich, Ontario: an F-3 tornado that struck the community on August 21st and a tornado warning that was posted for the region three days later on August 24th. This case study provided the opportunity to examine the roles of risk perception and previous disaster experience in the decision-making process during successive high-risk events. Semi-structured interviews (n=35) and close-ended questionnaires (n=268) were conducted to learn about the ways that individuals obtained and understood risk information, and to explore whether and how such information guided protective behaviors during the two events. The interviews were analyzed using thematic coding to identify response patterns, and the questionnaires were analyzed using IBM SPSS software. It was found that a sizable portion of the sample population took protective actions on August 24th in ways that were inconsistent with their actions on August 21st. Also, a significant portion of respondents chose not to take any form of protective action on August 24th despite having previously experienced the damaging tornado. The findings of this research suggest that the significance of previous disaster experience in the decision-making process is highly variable and context-dependent. A second significant research finding involves the impact of the tornado on the place attachments of Goderich residents. It was found that the disaster had significant impacts, both positive and negative, on participants' sense of place. These findings have implications for both short- and long-term disaster recovery.

The primary purpose of this research program is to confirm the spontaneous planning behavior in post-disaster operations while at the same time contribute to the development of the concept in a tornado type disaster. An additional goal also includes examining how the process takes place in resolving unanticipated problems as a disaster unfolds. This study uses qualitative methodology which is case study to probe the concept of spontaneous planning behavior to solve unexpected challenges as a disaster develops. Specifically, semi-structured, open-ended questions were utilized to collect data from stakeholders in eleven functional organizations in three impacted cities during the North Texas April 3, 2012, tornadoes. Findings indicate that debris removal and ensuring public safety, search and rescue, securing damaged neighborhoods, activation of emergency operations centers, damage assessment, restoration of communication system, public relations and media, and volunteer and donation management activities appear to have benefited from spontaneous planning behavior. Further findings suggest that the driving forces behind the phenomenon were gathering valuable new information, learning opportunity within the disaster, relative freedom and significant high degree of discretion, response was innovative with flexibility, and solutions waiting for problems features proposed in the integrated decision-making model (IDMM). However, it was uncovered that interview respondents’ answers tend to indicate that mixed organizational structures helped in problem resolutions rather than just flat organizational structure as some decision making literature may suggest. Analysis of this decision-making model expanded the understanding of how spontaneous planning behavior took place in resolving unforeseen problems in post-disaster operations. This research project confirmed the concept of spontaneous planning in the North Texas tornadoes as well as suggesting how it occurred. The research program validates spontaneous planning behavior in tornadoes; advances and develops the concept of spontaneous planning; increases understanding, description, and management of post-disaster operations; improves emergency management operations; promotes spontaneous planning as a key principle among responders and others involved in emergency management; and proposes IDMM as a useful model that explains decision-making behavior during a disaster.

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Severe weather outbreaks are violent weather events that can cause major damage and injury. Unfortunately, forecast models can mistakenly predict the intensity of these events. Frequently, the prediction of outbreaks is inaccurate with regards to their intensity, hindering the efforts of forecasters to confidently inform the public about intensity risks. This research aims to improve outbreak intensity forecasting using severe weather parameters and an outbreak ranking index to predict outbreak intensity. Areal coverage values of gridded severe weather diagnostic variables, computed from the North American Regional Reanalysis (NARR) database for outbreaks spanning 1979 to 2013, will be used as predictors in an artificial intelligence modeling ensemble to predict outbreak intensity. NARR fields will be dynamically downscaled to a National Severe Storms Laboratory-defined WRF 4-km North American domain on which areal coverages will be computed. The research will result in a model that will predict verification information on the model performance.

Scholars from various disciplines have long attempted to identify the variables most closely associated with individual preparedness. Therefore, we now have much more knowledge regarding these factors and their association with individual preparedness behaviors. However, it has not been sufficiently discussed how decisive many of these factors are in encouraging preparedness. In this article, we seek to examine what factors, among the many examined in previous studies, are most central to engendering emergency preparedness in individuals particularly for tornadoes by utilizing a relatively uncommon machine learning technique in disaster management literature. Using unique survey data, we find that in the case of tornado preparedness the most decisive variables are related to personal experiences and economic circumstances rather than basic demographics. Our findings contribute to scholarly endeavors to understand and promote individual tornado preparedness behaviors by highlighting the variables most likely to shape tornado preparedness at an individual level.

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