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Abstract
Effective communication about severe weather requires that providers of weather information disseminate accurate and timely messages and that the intended recipients (i.e., the population at risk) receive and react to these messages. This article contributes to extant research on the second half of this equation by introducing a “real time” measure of public attention to severe weather risk communication based on the growing stream of data that individuals publish on social media platforms, in this case, Twitter. The authors develop a metric that tracks temporal fluctuations in tornado-related Twitter activity between 25 April 2012 and 11 November 2012 and assess the validity of the metric by systematically comparing fluctuations in Twitter activity to the issuance of tornado watches and warnings, which represent basic but important forms of communication designed to elicit, and therefore correlate with, public attention. The assessment finds that the measure demonstrates a high degree of convergent validity, suggesting that social media data can be used to advance our understanding of the relationship between risk communication, attention, and public reactions to severe weather.
Abstract
Effective communication about severe weather requires that providers of weather information disseminate accurate and timely messages and that the intended recipients (i.e., the population at risk) receive and react to these messages. This article contributes to extant research on the second half of this equation by introducing a “real time” measure of public attention to severe weather risk communication based on the growing stream of data that individuals publish on social media platforms, in this case, Twitter. The authors develop a metric that tracks temporal fluctuations in tornado-related Twitter activity between 25 April 2012 and 11 November 2012 and assess the validity of the metric by systematically comparing fluctuations in Twitter activity to the issuance of tornado watches and warnings, which represent basic but important forms of communication designed to elicit, and therefore correlate with, public attention. The assessment finds that the measure demonstrates a high degree of convergent validity, suggesting that social media data can be used to advance our understanding of the relationship between risk communication, attention, and public reactions to severe weather.
Abstract
On 22 May 2011, a massive tornado tore through a densely populated section of Joplin, Missouri, killing 162 people. The EF5 tornado was the deadliest single tornado to occur in the United States since modern record keeping began in 1950, surpassing the tornado of 8 June 1953, which claimed 116 lives in Flint, Michigan. The Joplin tornado death toll was also far higher than the average annual number of deaths caused by tornadoes in the United States between 2000 and 2011. This study analyzed Joplin deaths by damage zone and place of death. Tabular data collected primarily from secondary sources revealed the number of deaths and death rates differ significantly by zone of destruction. The central zone (labeled as “catastrophic”) had the most deaths, with the number decreasing systematically in both directions from the center of that zone. The results of this study further show that more people died in nonresidential buildings in Joplin than is usual in a U.S. tornado event, calling into question how well such structures protect occupants. Finally, the lack of basements in residential and other structures most likely contributed greatly to the high death toll, although the degree remains uncertain. Several recommendations are offered to reduce future U.S. tornado fatalities.
Abstract
On 22 May 2011, a massive tornado tore through a densely populated section of Joplin, Missouri, killing 162 people. The EF5 tornado was the deadliest single tornado to occur in the United States since modern record keeping began in 1950, surpassing the tornado of 8 June 1953, which claimed 116 lives in Flint, Michigan. The Joplin tornado death toll was also far higher than the average annual number of deaths caused by tornadoes in the United States between 2000 and 2011. This study analyzed Joplin deaths by damage zone and place of death. Tabular data collected primarily from secondary sources revealed the number of deaths and death rates differ significantly by zone of destruction. The central zone (labeled as “catastrophic”) had the most deaths, with the number decreasing systematically in both directions from the center of that zone. The results of this study further show that more people died in nonresidential buildings in Joplin than is usual in a U.S. tornado event, calling into question how well such structures protect occupants. Finally, the lack of basements in residential and other structures most likely contributed greatly to the high death toll, although the degree remains uncertain. Several recommendations are offered to reduce future U.S. tornado fatalities.
Abstract
Exposure has amplified rapidly over the past half century and is one of the primary drivers of increases in disaster frequency and consequences. Previous research on exposure change detection has proven limited since the geographic units of aggregation for decennial censuses, the sole measure of accurate historical population and housing counts, vary from one census to the next. To address this shortcoming, this research produces a set of gridded population and housing data for the Chicago, Illinois, region to evaluate the concept of the “expanding bull’s-eye effect.” This effect argues that “targets”—people and their built environments—of geophysical hazards are enlarging as populations grow and spread. A collection of observationally derived synthetic violent tornadoes are transposed across fine-geographic-scale population and housing unit grids at different time stamps to appraise the concept. Results reveal that intensifying and expanding development is placing more people and their possessions in the potential path of tornadoes, increasing the likelihood of tornado disasters. The research demonstrates how different development morphologies lead to varying exposure rates that contribute to the unevenness of potential weather-related disasters across the landscape. In addition, the investigation appraises the viability of using a gridded framework for assessing changes in census-derived exposure data. The creation of uniformly sized grid data on a scale smaller than counties, municipalities, and conventional census geographic units addresses two of the most critical problems assessing historical changes in disaster frequencies and magnitudes—highly variable spatial units of exposure data and the mismatch between spatial scales of population/housing data and hazards.
Abstract
Exposure has amplified rapidly over the past half century and is one of the primary drivers of increases in disaster frequency and consequences. Previous research on exposure change detection has proven limited since the geographic units of aggregation for decennial censuses, the sole measure of accurate historical population and housing counts, vary from one census to the next. To address this shortcoming, this research produces a set of gridded population and housing data for the Chicago, Illinois, region to evaluate the concept of the “expanding bull’s-eye effect.” This effect argues that “targets”—people and their built environments—of geophysical hazards are enlarging as populations grow and spread. A collection of observationally derived synthetic violent tornadoes are transposed across fine-geographic-scale population and housing unit grids at different time stamps to appraise the concept. Results reveal that intensifying and expanding development is placing more people and their possessions in the potential path of tornadoes, increasing the likelihood of tornado disasters. The research demonstrates how different development morphologies lead to varying exposure rates that contribute to the unevenness of potential weather-related disasters across the landscape. In addition, the investigation appraises the viability of using a gridded framework for assessing changes in census-derived exposure data. The creation of uniformly sized grid data on a scale smaller than counties, municipalities, and conventional census geographic units addresses two of the most critical problems assessing historical changes in disaster frequencies and magnitudes—highly variable spatial units of exposure data and the mismatch between spatial scales of population/housing data and hazards.
Abstract
The role of previous disaster experience as a motivating factor for protective action during high-risk events is still a matter of considerable discussion and inconsistent findings in the hazards literature. In this paper, two events that occurred in August 2011 in Goderich, Ontario, Canada, are examined: an F3 tornado that impacted the community on 21 August 2011 and a tornado warning that was posted for the region 3 days later on 24 August 2011. This case study provided the opportunity to examine the roles of previous disaster experience and sociodemographics on the decision-making process during two successive potentially tornadic events. The results of this research are based on close-ended questionnaires completed by individuals who experienced both storms or who experienced only the subsequent storm on 24 August 2011 (n = 177). Physical cues were found to be the primary motivator during the 21 August 2011 tornado, while the tornado warning was the primary motivator during the subsequent storm. Additionally, there was an increase in the percentage of individuals who took protective action on 24 August 2011 regardless of the respondents’ presence or absence during the 21 August 2011 tornado. Finally, none of the tested sociodemographic variables was found to be statistically significant for the 21 August 2011 tornado, while only gender (female) was found to be positively correlated with protective behaviors on 24 August 2011. These findings suggest that previous disaster experience (either direct or indirect) and sociodemographics intersect in a variety of complex ways.
Abstract
The role of previous disaster experience as a motivating factor for protective action during high-risk events is still a matter of considerable discussion and inconsistent findings in the hazards literature. In this paper, two events that occurred in August 2011 in Goderich, Ontario, Canada, are examined: an F3 tornado that impacted the community on 21 August 2011 and a tornado warning that was posted for the region 3 days later on 24 August 2011. This case study provided the opportunity to examine the roles of previous disaster experience and sociodemographics on the decision-making process during two successive potentially tornadic events. The results of this research are based on close-ended questionnaires completed by individuals who experienced both storms or who experienced only the subsequent storm on 24 August 2011 (n = 177). Physical cues were found to be the primary motivator during the 21 August 2011 tornado, while the tornado warning was the primary motivator during the subsequent storm. Additionally, there was an increase in the percentage of individuals who took protective action on 24 August 2011 regardless of the respondents’ presence or absence during the 21 August 2011 tornado. Finally, none of the tested sociodemographic variables was found to be statistically significant for the 21 August 2011 tornado, while only gender (female) was found to be positively correlated with protective behaviors on 24 August 2011. These findings suggest that previous disaster experience (either direct or indirect) and sociodemographics intersect in a variety of complex ways.
Abstract
Recent improvements in weather observation and monitoring have increased the precision of tornado warnings. The National Weather Service currently issues storm-based tornado warnings, and even more geographically specific warnings that include probability information are under development. At the same time, the widespread proliferation of smartphone and mobile computing technology supports the rapid dissemination of graphical weather warning information. Some broadcasters and private companies have already begun using probabilistic-style tornado warning graphics. However, the development of these new types of warnings has occurred with limited research on how users interpret probabilistic visualizations.
This study begins filling this void by examining responses to color scheme and relative position using probabilistic tornado warning designs. A survey of university students is used to measure the level of perceived fear and likelihood of protective action for a series of hypothetical warning scenarios. Central research questions investigate 1) differences in responses across warning designs, 2) clustering of extreme responses in each design, 3) trends in responses with respect to probability levels, 4) differences in responses inside versus outside the warnings, and 5) differences in responses near the edges of the warning designs. Results suggest a variety of trade-offs in viewer responses to tornado warnings based on visual design choices. These findings underscore the need for more comprehensive research on visualizations in weather hazard communication that can aid meteorologists in effectively warning the public and spur appropriate tornado protection behaviors in a timely manner.
Abstract
Recent improvements in weather observation and monitoring have increased the precision of tornado warnings. The National Weather Service currently issues storm-based tornado warnings, and even more geographically specific warnings that include probability information are under development. At the same time, the widespread proliferation of smartphone and mobile computing technology supports the rapid dissemination of graphical weather warning information. Some broadcasters and private companies have already begun using probabilistic-style tornado warning graphics. However, the development of these new types of warnings has occurred with limited research on how users interpret probabilistic visualizations.
This study begins filling this void by examining responses to color scheme and relative position using probabilistic tornado warning designs. A survey of university students is used to measure the level of perceived fear and likelihood of protective action for a series of hypothetical warning scenarios. Central research questions investigate 1) differences in responses across warning designs, 2) clustering of extreme responses in each design, 3) trends in responses with respect to probability levels, 4) differences in responses inside versus outside the warnings, and 5) differences in responses near the edges of the warning designs. Results suggest a variety of trade-offs in viewer responses to tornado warnings based on visual design choices. These findings underscore the need for more comprehensive research on visualizations in weather hazard communication that can aid meteorologists in effectively warning the public and spur appropriate tornado protection behaviors in a timely manner.
Abstract
Very little empirical work has been done on disaster aid in the United States. This paper examines postdisaster grants to households from the Federal Emergency Management Agency in the state of Missouri in 2008, when the state experienced flooding, storms, and tornadoes. The paper answers the following questions: What was the aid for? How much was given? How many people applied for aid? How many households received aid and how many were denied? Why were some applicants denied aid? Is there any relationship between aid received and socioeconomic or demographic characteristics of communities? The paper finds that the majority of aid grants are for very small amounts of money, on the order of a few thousand dollars. Over half of aid applications are denied, often because of ineligible or insufficient damage. The paper provides some important basic information on the nature of disaster grants to households and also generates several hypotheses for future research.
Abstract
Very little empirical work has been done on disaster aid in the United States. This paper examines postdisaster grants to households from the Federal Emergency Management Agency in the state of Missouri in 2008, when the state experienced flooding, storms, and tornadoes. The paper answers the following questions: What was the aid for? How much was given? How many people applied for aid? How many households received aid and how many were denied? Why were some applicants denied aid? Is there any relationship between aid received and socioeconomic or demographic characteristics of communities? The paper finds that the majority of aid grants are for very small amounts of money, on the order of a few thousand dollars. Over half of aid applications are denied, often because of ineligible or insufficient damage. The paper provides some important basic information on the nature of disaster grants to households and also generates several hypotheses for future research.
Abstract
This paper contributes to existing knowledge on factors that influence adoption of hazards adjustments for tornadoes. The Protective Action Decision Model provides the theoretical basis for the study, which was conducted after the 2011 disaster in DeKalb County, Alabama. Most of the 124 survey participants had received public safety information on how to prepare for a tornado, understood the definition of a tornado warning, had participated in a tornado drill, and had a plan for seeking shelter. Few owned a NOAA weather radio or had a tornado-resistant shelter on the premises. Demographic analysis found that older residents (60+ yr) and households without children were significantly less likely to have participated in a tornado drill, lower income residents were significantly less likely to have a tornado-resistant shelter on the premises or a plan for seeking shelter, and mobile home residents were significantly less likely to have a plan for seeking shelter. Locus of control and past experience were not significantly associated with adoption of hazards adjustments, but suspected reasons for these results are discussed. Many plans that involved evacuating to another location included excessively long travel distances, and several mobile home residents planned to seek shelter inside their residence. Failure to adopt effective preparedness actions in each of these areas could serve as a situational impediment to making an appropriate protective action decision when a tornado threatens the household. The results identify aspects of household preparedness where there is opportunity for improvement, which would reduce vulnerability and enhance community resilience.
Abstract
This paper contributes to existing knowledge on factors that influence adoption of hazards adjustments for tornadoes. The Protective Action Decision Model provides the theoretical basis for the study, which was conducted after the 2011 disaster in DeKalb County, Alabama. Most of the 124 survey participants had received public safety information on how to prepare for a tornado, understood the definition of a tornado warning, had participated in a tornado drill, and had a plan for seeking shelter. Few owned a NOAA weather radio or had a tornado-resistant shelter on the premises. Demographic analysis found that older residents (60+ yr) and households without children were significantly less likely to have participated in a tornado drill, lower income residents were significantly less likely to have a tornado-resistant shelter on the premises or a plan for seeking shelter, and mobile home residents were significantly less likely to have a plan for seeking shelter. Locus of control and past experience were not significantly associated with adoption of hazards adjustments, but suspected reasons for these results are discussed. Many plans that involved evacuating to another location included excessively long travel distances, and several mobile home residents planned to seek shelter inside their residence. Failure to adopt effective preparedness actions in each of these areas could serve as a situational impediment to making an appropriate protective action decision when a tornado threatens the household. The results identify aspects of household preparedness where there is opportunity for improvement, which would reduce vulnerability and enhance community resilience.
Abstract
Tornado–hazard assessment is hampered by a population bias in the available data. Here, the authors demonstrate a way to statistically quantify this bias using the ratio of city to country report densities. The expected report densities come from a model of the number of reports as a function of distance from the nearest city center. On average since 1950, reports near cities with populations of at least 1000 in a 5.5° latitude × 5.5° longitude region centered on Russell, Kansas, exceed those in the country by 70% [54%, 84%; 95% confidence interval (CI)]. The model is applied to 10-yr moving windows to show that the percentage is decreasing with time. Over the most recent period (2002–11), the tornado report density in the city is slightly fewer than 3 reports (100 km2)−1 (100 yr)−1, and this value is statistically indistinguishable from the report density in the country. On average, the population bias is less pronounced for Fujita (F) scale F0 tornadoes, but the bias disappears more quickly over time for the F1 and stronger tornadoes. The authors show evidence that this decline could be related in part to an increase in the number of storm chasers. The population-bias model can enhance the usefulness of the Storm Prediction Center's tornado database and help create more meaningful spatial climatologies.
Abstract
Tornado–hazard assessment is hampered by a population bias in the available data. Here, the authors demonstrate a way to statistically quantify this bias using the ratio of city to country report densities. The expected report densities come from a model of the number of reports as a function of distance from the nearest city center. On average since 1950, reports near cities with populations of at least 1000 in a 5.5° latitude × 5.5° longitude region centered on Russell, Kansas, exceed those in the country by 70% [54%, 84%; 95% confidence interval (CI)]. The model is applied to 10-yr moving windows to show that the percentage is decreasing with time. Over the most recent period (2002–11), the tornado report density in the city is slightly fewer than 3 reports (100 km2)−1 (100 yr)−1, and this value is statistically indistinguishable from the report density in the country. On average, the population bias is less pronounced for Fujita (F) scale F0 tornadoes, but the bias disappears more quickly over time for the F1 and stronger tornadoes. The authors show evidence that this decline could be related in part to an increase in the number of storm chasers. The population-bias model can enhance the usefulness of the Storm Prediction Center's tornado database and help create more meaningful spatial climatologies.
Abstract
U.S. government officials are focusing their attention on how to deliver timely and effective warning information to the public, especially given the devastating weather-related events that have occurred in recent years. With the increase of cell phones (and in particular, web-capable smartphones), weather warnings sent through various cellular technologies represent one way for officials to quickly notify an increasingly mobile public. Cellular technology innovations also make it possible for officials to broadcast information-rich media like graphics to cell phones. Whether warning messages must include such “rich” media to be effective remains an open question. The current study investigates the effectiveness of National Weather Service (NWS) warning messages sent either in plain text or in text that includes a radar image of the storm. The research protocol was modeled after the interactive National Weather Service (iNWS) messaging service currently available to NWS core partners. In the study, participants read full-text NWS warnings of tornadoes or flash floods that either did or did not include a radar image of the storm. The researchers timed participants' ability to decide if a critical town was in the warning area, and then probed their understanding of the message content. Results show that participants' decision times to the town question did not differ between the graphic and no-graphic conditions. None of the other message content measures differed as a function of message condition. The results have potential implications for the federal government's new Wireless Emergency Alert (WEA) system, which, as yet, is limited to text-only warnings.
Abstract
U.S. government officials are focusing their attention on how to deliver timely and effective warning information to the public, especially given the devastating weather-related events that have occurred in recent years. With the increase of cell phones (and in particular, web-capable smartphones), weather warnings sent through various cellular technologies represent one way for officials to quickly notify an increasingly mobile public. Cellular technology innovations also make it possible for officials to broadcast information-rich media like graphics to cell phones. Whether warning messages must include such “rich” media to be effective remains an open question. The current study investigates the effectiveness of National Weather Service (NWS) warning messages sent either in plain text or in text that includes a radar image of the storm. The research protocol was modeled after the interactive National Weather Service (iNWS) messaging service currently available to NWS core partners. In the study, participants read full-text NWS warnings of tornadoes or flash floods that either did or did not include a radar image of the storm. The researchers timed participants' ability to decide if a critical town was in the warning area, and then probed their understanding of the message content. Results show that participants' decision times to the town question did not differ between the graphic and no-graphic conditions. None of the other message content measures differed as a function of message condition. The results have potential implications for the federal government's new Wireless Emergency Alert (WEA) system, which, as yet, is limited to text-only warnings.
Abstract
Memories, both semantic, or learned knowledge, and episodic, or personal experiences, play an important role in an individual’s decision making under risk. In addition, varying levels of knowledge and experience exist in each individual. These memories enable individuals to make informed decisions based on previous knowledge or experience, and ultimately influence one’s behavior under risk. In this study, 49 undergraduate students participated in a 1-h, classroom-based experiment focusing on decision making. The sample contained n = 23 “episodic” participants, referred to as “high episodic,” who reported having personally experienced a tornado and n = 24 participants, referred to as “low episodic,” who had no reported tornado experience. Incomplete data reported by the remaining participants were not included in this study. All participants completed a decision-making task both before and after viewing a 5-min slideshow stimulus related to tornadoes and associated damage. This decision-making task prompted participants to describe the actions they would anticipate taking during an actual tornado warning. Prior to the stimulus, high episodic participants exhibited a marginally higher tendency to ignore a tornado warning than those participants without episodic (low episodic) memories. After the tornado stimulus, all participants reported a greater likelihood to engage in precautionary action than reported prior to the stimulus. It is also found that 1) those participants with low episodic memory showed greater precaution than the high episodic memory group, and 2) participants with greater knowledge of tornadoes showed the greatest gains in anticipated precautionary behavior. This study suggests that increasing a population’s general knowledge of tornadoes could result in greater individual precaution and overall safety during a tornadic event.
Abstract
Memories, both semantic, or learned knowledge, and episodic, or personal experiences, play an important role in an individual’s decision making under risk. In addition, varying levels of knowledge and experience exist in each individual. These memories enable individuals to make informed decisions based on previous knowledge or experience, and ultimately influence one’s behavior under risk. In this study, 49 undergraduate students participated in a 1-h, classroom-based experiment focusing on decision making. The sample contained n = 23 “episodic” participants, referred to as “high episodic,” who reported having personally experienced a tornado and n = 24 participants, referred to as “low episodic,” who had no reported tornado experience. Incomplete data reported by the remaining participants were not included in this study. All participants completed a decision-making task both before and after viewing a 5-min slideshow stimulus related to tornadoes and associated damage. This decision-making task prompted participants to describe the actions they would anticipate taking during an actual tornado warning. Prior to the stimulus, high episodic participants exhibited a marginally higher tendency to ignore a tornado warning than those participants without episodic (low episodic) memories. After the tornado stimulus, all participants reported a greater likelihood to engage in precautionary action than reported prior to the stimulus. It is also found that 1) those participants with low episodic memory showed greater precaution than the high episodic memory group, and 2) participants with greater knowledge of tornadoes showed the greatest gains in anticipated precautionary behavior. This study suggests that increasing a population’s general knowledge of tornadoes could result in greater individual precaution and overall safety during a tornadic event.
