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Abstract
Media such as Twitter have become platforms for contemporary Americans to express their opinions and allow for reaction to public opinion. Climate change is a topic of ongoing social concern. Machine-automated processing facilitates “big data” analysis and is suitable for analyzing a large corpus of tweets. This paper uses R tools to conduct sentiment calculation and emotion analysis on the tweet corpus from 2015 to 2018 to present the overall tendency of citizens’ attitudes toward climate change topics. The keyword analysis finds that people focus on the message’s source. “Climate change” has often been conflated with “global warming” in the popular consciousness. Supporters of the scientific consensus that human activities drastically affect Earth’s climate system express fear and surprise about extreme weather and opponents’ behavior, whereas opponents of that consensus express multiple emotional responses that include anger, disgust, and sadness toward politicians who, in their view, fabricate stories about climate change about which they have no real feelings. This study also reveals that the automatic annotation tools are still inadequate, with limited emotion lexicon and identification of negation and sarcasm.
Significance Statement
This research aims to perceive people’s emotional expressions on climate change as expressed on Twitter. The distributions of emotions across different opinion groups on climate change can be analyzed by manually annotating the opinion stances. Our first step is to research keywords to identify the main discussion topics. Then, automatic sentiment analysis with R software reveals the prevalent negative positions, and emotion analysis yields the primary emotions and the connection with different opinion groups, which logistic regression models test. These results better reflect the concerns of the population and provide support for climate policy. Future research could subdivide topics and develop field-specialized sentiment and emotion lexicons.
Abstract
Media such as Twitter have become platforms for contemporary Americans to express their opinions and allow for reaction to public opinion. Climate change is a topic of ongoing social concern. Machine-automated processing facilitates “big data” analysis and is suitable for analyzing a large corpus of tweets. This paper uses R tools to conduct sentiment calculation and emotion analysis on the tweet corpus from 2015 to 2018 to present the overall tendency of citizens’ attitudes toward climate change topics. The keyword analysis finds that people focus on the message’s source. “Climate change” has often been conflated with “global warming” in the popular consciousness. Supporters of the scientific consensus that human activities drastically affect Earth’s climate system express fear and surprise about extreme weather and opponents’ behavior, whereas opponents of that consensus express multiple emotional responses that include anger, disgust, and sadness toward politicians who, in their view, fabricate stories about climate change about which they have no real feelings. This study also reveals that the automatic annotation tools are still inadequate, with limited emotion lexicon and identification of negation and sarcasm.
Significance Statement
This research aims to perceive people’s emotional expressions on climate change as expressed on Twitter. The distributions of emotions across different opinion groups on climate change can be analyzed by manually annotating the opinion stances. Our first step is to research keywords to identify the main discussion topics. Then, automatic sentiment analysis with R software reveals the prevalent negative positions, and emotion analysis yields the primary emotions and the connection with different opinion groups, which logistic regression models test. These results better reflect the concerns of the population and provide support for climate policy. Future research could subdivide topics and develop field-specialized sentiment and emotion lexicons.
Abstract
Research has found that people who know the least about a topic are often very overconfident of their knowledge, while those who know the most often underestimate their knowledge. This finding, known as the Dunning–Kruger effect (DKE) has recently been shown to occur in knowledge of severe weather as well. The current study investigated whether being overconfident in one’s knowledge might translate into a tendency to make poorer sheltering decisions when faced with severe weather. Participants took two severe weather quizzes, one of perceived knowledge and one of objective knowledge. Participants also predicted their performance on both quizzes. The participants then saw four wireless emergency tornado warning alerts on a simulated smartphone screen, along with a tornado scenario, and then made two protective action decisions: one about immediately sheltering in place and the other the likelihood they would drive away. The results revealed that the participants did exhibit the DKE: those with the lowest levels of knowledge exhibited the most overconfidence while those with the highest levels of knowledge underestimated their performance. Also, in comparison with individuals with the most knowledge, those with the least knowledge were the most likely to state that they would not shelter immediately and that they would get in their car and drive away. Although more education is needed, the findings suggest a conundrum: those who know the least about severe weather, thinking they know a lot, are probably those individuals least likely to seek out additional education on the topic.
Significance Statement
Tornadoes are common in many states, and the National Weather Service issues tornado warnings in the hopes that individuals will take protective action. Previous research has found that people with low levels of knowledge (such as knowledge of severe weather) are often overconfident of their knowledge. This study explores whether those with low (as compared with high) severe weather knowledge make poorer decisions to a tornado warning. The findings show that those with the lowest knowledge were indeed overconfident and that they were less likely to shelter and more likely to drive away than those with high knowledge. The findings highlight that more severe weather education, although a worthy goal, might be difficult to implement if knowledge confidence is already high.
Abstract
Research has found that people who know the least about a topic are often very overconfident of their knowledge, while those who know the most often underestimate their knowledge. This finding, known as the Dunning–Kruger effect (DKE) has recently been shown to occur in knowledge of severe weather as well. The current study investigated whether being overconfident in one’s knowledge might translate into a tendency to make poorer sheltering decisions when faced with severe weather. Participants took two severe weather quizzes, one of perceived knowledge and one of objective knowledge. Participants also predicted their performance on both quizzes. The participants then saw four wireless emergency tornado warning alerts on a simulated smartphone screen, along with a tornado scenario, and then made two protective action decisions: one about immediately sheltering in place and the other the likelihood they would drive away. The results revealed that the participants did exhibit the DKE: those with the lowest levels of knowledge exhibited the most overconfidence while those with the highest levels of knowledge underestimated their performance. Also, in comparison with individuals with the most knowledge, those with the least knowledge were the most likely to state that they would not shelter immediately and that they would get in their car and drive away. Although more education is needed, the findings suggest a conundrum: those who know the least about severe weather, thinking they know a lot, are probably those individuals least likely to seek out additional education on the topic.
Significance Statement
Tornadoes are common in many states, and the National Weather Service issues tornado warnings in the hopes that individuals will take protective action. Previous research has found that people with low levels of knowledge (such as knowledge of severe weather) are often overconfident of their knowledge. This study explores whether those with low (as compared with high) severe weather knowledge make poorer decisions to a tornado warning. The findings show that those with the lowest knowledge were indeed overconfident and that they were less likely to shelter and more likely to drive away than those with high knowledge. The findings highlight that more severe weather education, although a worthy goal, might be difficult to implement if knowledge confidence is already high.
Abstract
NOAA’s National Weather Service (NWS) provides forecasts, warnings, and decision support to the public for the protection of life and property. The NWS Weather-Ready Nation model describes the process of applying weather information to achieve societal value. However, it is not clear how different racial and socioeconomic groups across the United States receive, understand, and act upon the weather information supplied under this model. There may be barriers that keep important, lifesaving information from the populations at the highest risk of severe weather impacts. This paper estimates the extent of racial and socioeconomic disparities in severe weather risk information reception, comprehension, response, and trust, as well as severe weather preparedness and risk perceptions in the United States. We use data from the University of Oklahoma’s Severe Weather and Society Survey, which is annually completed by a sample of 3000 U.S. adults (age 18+) that is designed to match the characteristics of the U.S. population. We pool data over four years (2017–20) to provide reliable severe weather risk prevalence statistics for adults by race, ethnicity, and socioeconomic characteristics. As a robustness check, we supplement this information with data from the annual FEMA National Household Survey. We find that racial and socioeconomic groups receive, understand, trust, and act upon severe weather information differently. These findings suggest that NWS and their partners should adjust their communication strategies to ensure all populations receive and understand actionable severe weather information.
Significance Statement
It is crucial that severe weather risk communication is received, appropriately interpreted, and trusted by all communities—especially the most vulnerable. Past research has not explained how different racial and socioeconomic groups receive, understand, and act upon NWS forecasts and warnings. This study finds that racial and socioeconomic groups receive, understand, trust, and act upon severe weather information differently. Risk communication strategies should be adjusted to eliminate barriers that keep important, lifesaving information from vulnerable populations.
Abstract
NOAA’s National Weather Service (NWS) provides forecasts, warnings, and decision support to the public for the protection of life and property. The NWS Weather-Ready Nation model describes the process of applying weather information to achieve societal value. However, it is not clear how different racial and socioeconomic groups across the United States receive, understand, and act upon the weather information supplied under this model. There may be barriers that keep important, lifesaving information from the populations at the highest risk of severe weather impacts. This paper estimates the extent of racial and socioeconomic disparities in severe weather risk information reception, comprehension, response, and trust, as well as severe weather preparedness and risk perceptions in the United States. We use data from the University of Oklahoma’s Severe Weather and Society Survey, which is annually completed by a sample of 3000 U.S. adults (age 18+) that is designed to match the characteristics of the U.S. population. We pool data over four years (2017–20) to provide reliable severe weather risk prevalence statistics for adults by race, ethnicity, and socioeconomic characteristics. As a robustness check, we supplement this information with data from the annual FEMA National Household Survey. We find that racial and socioeconomic groups receive, understand, trust, and act upon severe weather information differently. These findings suggest that NWS and their partners should adjust their communication strategies to ensure all populations receive and understand actionable severe weather information.
Significance Statement
It is crucial that severe weather risk communication is received, appropriately interpreted, and trusted by all communities—especially the most vulnerable. Past research has not explained how different racial and socioeconomic groups receive, understand, and act upon NWS forecasts and warnings. This study finds that racial and socioeconomic groups receive, understand, trust, and act upon severe weather information differently. Risk communication strategies should be adjusted to eliminate barriers that keep important, lifesaving information from vulnerable populations.
Abstract
A radar display is a tool that depicts meteorological data over space and time; therefore, an individual must think spatially and temporally in addition to drawing on their own meteorological knowledge and past weather experiences. We aimed to understand how the construal of situational risks and outcomes influences the perceived usefulness of a radar display and to explore how radar users interpret distance, time, and meteorological attributes using hypothetical scenarios in the Tampa Bay area (Florida). Ultimately, we wanted to understand how and why individuals use weather radar and to discover what makes it a useful tool. To do this, construal level theory and geospatial thinking guided the mixed methods used in this study to investigate four research objectives. Our findings show that radar is used most often by our participants to anticipate what will happen in the near future in their area. Participants described in their own words what they were viewing while using a radar display and reported what hazards they expected at the study location. Many participants associated the occurrence of lightning or strong winds with “red” and “orange” reflectivity values on a radar display. Participants provided valuable insight into what was and was not found useful about certain radar displays. We also found that most participants overestimated the amount of time they would have before precipitation would begin at their location. Overall, weather radar was found to be a very useful tool; however, judging spatial and temporal proximity became difficult when storm motion/direction was not easily identifiable.
Significance Statement
The purpose of this study is to understand how and why individuals use weather radar and to discover what makes radar a useful tool. We were particularly interested to explore how distance and time are thought about when using radar. We found that radar is generally a useful tool for decision-making except when a storm event was stationary. Participants use their personal experiences and knowledge of past weather events when they use a radar display. We also discovered that deciding how much time is available before rain occurs is often overestimated. These findings are helpful to understand how individuals use weather radar to make decisions that may help us to better understand protective action behavior.
Abstract
A radar display is a tool that depicts meteorological data over space and time; therefore, an individual must think spatially and temporally in addition to drawing on their own meteorological knowledge and past weather experiences. We aimed to understand how the construal of situational risks and outcomes influences the perceived usefulness of a radar display and to explore how radar users interpret distance, time, and meteorological attributes using hypothetical scenarios in the Tampa Bay area (Florida). Ultimately, we wanted to understand how and why individuals use weather radar and to discover what makes it a useful tool. To do this, construal level theory and geospatial thinking guided the mixed methods used in this study to investigate four research objectives. Our findings show that radar is used most often by our participants to anticipate what will happen in the near future in their area. Participants described in their own words what they were viewing while using a radar display and reported what hazards they expected at the study location. Many participants associated the occurrence of lightning or strong winds with “red” and “orange” reflectivity values on a radar display. Participants provided valuable insight into what was and was not found useful about certain radar displays. We also found that most participants overestimated the amount of time they would have before precipitation would begin at their location. Overall, weather radar was found to be a very useful tool; however, judging spatial and temporal proximity became difficult when storm motion/direction was not easily identifiable.
Significance Statement
The purpose of this study is to understand how and why individuals use weather radar and to discover what makes radar a useful tool. We were particularly interested to explore how distance and time are thought about when using radar. We found that radar is generally a useful tool for decision-making except when a storm event was stationary. Participants use their personal experiences and knowledge of past weather events when they use a radar display. We also discovered that deciding how much time is available before rain occurs is often overestimated. These findings are helpful to understand how individuals use weather radar to make decisions that may help us to better understand protective action behavior.
Abstract
Machine learning was applied to predict evacuation rates for all census tracts affected by Hurricane Laura. The evacuation ground truth was derived from cellular telephone–based mobility data. Twitter data, census data, geographical data, COVID-19 case rates, the social vulnerability index from the Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease Registry (ATSDR), and relevant weather and physical data were used to do the prediction. Random forests were found to perform well, with a mean absolute percent error of 4.9% on testing data. Feature importance for prediction was analyzed using Shapley additive explanations and it was found that previous evacuation, rainfall forecasts, COVID-19 case rates, and Twitter data rank highly in terms of importance. Social vulnerability indices were also found to show a very consistent relationship with evacuation rates, such that higher vulnerability consistently implies lower evacuation rates. These findings can help with hurricane evacuation preparedness and planning as well as real-time assessment.
Significance Statement
This study evaluates the usefulness of Twitter data, COVID-19 case rates, and the social vulnerability index from the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry in predicting evacuation rates during Hurricane Laura, in the context of other relevant geographic, and weather-related variables. All three are found to be useful, to different extents, and this work suggests important directions for future research in understanding the reasons behind their relevance to predicting evacuation rates.
Abstract
Machine learning was applied to predict evacuation rates for all census tracts affected by Hurricane Laura. The evacuation ground truth was derived from cellular telephone–based mobility data. Twitter data, census data, geographical data, COVID-19 case rates, the social vulnerability index from the Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease Registry (ATSDR), and relevant weather and physical data were used to do the prediction. Random forests were found to perform well, with a mean absolute percent error of 4.9% on testing data. Feature importance for prediction was analyzed using Shapley additive explanations and it was found that previous evacuation, rainfall forecasts, COVID-19 case rates, and Twitter data rank highly in terms of importance. Social vulnerability indices were also found to show a very consistent relationship with evacuation rates, such that higher vulnerability consistently implies lower evacuation rates. These findings can help with hurricane evacuation preparedness and planning as well as real-time assessment.
Significance Statement
This study evaluates the usefulness of Twitter data, COVID-19 case rates, and the social vulnerability index from the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry in predicting evacuation rates during Hurricane Laura, in the context of other relevant geographic, and weather-related variables. All three are found to be useful, to different extents, and this work suggests important directions for future research in understanding the reasons behind their relevance to predicting evacuation rates.
Abstract
Indigenous Peoples’ advocacy has enabled them to position themselves in global debates on climate change. Although the international community progressively acknowledges Indigenous Peoples’ contributions to climate action, their effective recognition in national climate governance remains marginal. This article analyses Indigenous Peoples’ recognition in the climate governance of Latin American states based on a document analysis of the Nationally Determined Contributions (NDCs) submitted between 2016 and March 2022. A content analysis and a frequency analysis were conducted on 30 documents. Mentions related to Indigenous Peoples in the NDCs are increasing; nevertheless, this recognition reproduces the multicultural approach that has characterized Latin American states’ legislations and thereby undermines the coherence of climate policy. The references mainly allude to cultural diversity and climatic vulnerability without addressing the ongoing territorial conflicts that mediate the relationship between Indigenous Peoples and states. Nor do the NDCs recognize the right of Indigenous Peoples to participate at the different levels of climate change decision-making processes. Intercultural recognition of Indigenous Peoples and better standards of participation in climate change governance are mandatory. However, states must first promote institutional transformations to address the historical and institutional factors that have produced Indigenous Peoples’ climate vulnerability and generate the necessary mechanisms to implement the recognition committed to in the NDCs.
Significance Statement
The decisions of the Conference of the Parties of the UN Framework Convention on Climate Change progressively encourage the participation of Indigenous Peoples and consider their knowledge in decision-making processes. Our article explores how this recommendation is assumed in Latin America through the analysis of Nationally Determined Contributions (NDCs)—the national pledges in the context of the Paris Agreement for the reduction of greenhouse gas emissions and adaptation to climate change. Our findings reveal that the mentions and recognition of Indigenous Peoples in NDCs are increasing. This recognition is not matched by promoting full and meaningful intercultural participation. In addition to generating mechanisms for effective participation, addressing the multiple historical and institutional drivers of Indigenous Peoples’ climate vulnerability is necessary.
Abstract
Indigenous Peoples’ advocacy has enabled them to position themselves in global debates on climate change. Although the international community progressively acknowledges Indigenous Peoples’ contributions to climate action, their effective recognition in national climate governance remains marginal. This article analyses Indigenous Peoples’ recognition in the climate governance of Latin American states based on a document analysis of the Nationally Determined Contributions (NDCs) submitted between 2016 and March 2022. A content analysis and a frequency analysis were conducted on 30 documents. Mentions related to Indigenous Peoples in the NDCs are increasing; nevertheless, this recognition reproduces the multicultural approach that has characterized Latin American states’ legislations and thereby undermines the coherence of climate policy. The references mainly allude to cultural diversity and climatic vulnerability without addressing the ongoing territorial conflicts that mediate the relationship between Indigenous Peoples and states. Nor do the NDCs recognize the right of Indigenous Peoples to participate at the different levels of climate change decision-making processes. Intercultural recognition of Indigenous Peoples and better standards of participation in climate change governance are mandatory. However, states must first promote institutional transformations to address the historical and institutional factors that have produced Indigenous Peoples’ climate vulnerability and generate the necessary mechanisms to implement the recognition committed to in the NDCs.
Significance Statement
The decisions of the Conference of the Parties of the UN Framework Convention on Climate Change progressively encourage the participation of Indigenous Peoples and consider their knowledge in decision-making processes. Our article explores how this recommendation is assumed in Latin America through the analysis of Nationally Determined Contributions (NDCs)—the national pledges in the context of the Paris Agreement for the reduction of greenhouse gas emissions and adaptation to climate change. Our findings reveal that the mentions and recognition of Indigenous Peoples in NDCs are increasing. This recognition is not matched by promoting full and meaningful intercultural participation. In addition to generating mechanisms for effective participation, addressing the multiple historical and institutional drivers of Indigenous Peoples’ climate vulnerability is necessary.
Abstract
It is now widely acknowledged that climate change will have a considerable impact on various aspects of human existence, and this includes happiness and satisfaction with life. This study adds to the existing literature on the contribution of climate to well-being by exploring the interaction of various climate variables at the national and local levels while controlling for socioeconomic factors. Using climate data covering a 20-yr period and demographic data from the Household Income Labor Dynamics in Australia surveys, several ordinary least squares (OLS) models of interaction are developed to test the proposition that climate does influence life satisfaction. Geographically weighted regression is then applied to explore how the relationship between explanatory variables and life satisfaction varies across different regions of Australia. We find that overall rainfall, temperature, and sunshine have a small but significant effect on individual life satisfaction. The spatial analysis reveals a high level of nonstationarity in the way climate variables impact life satisfaction, suggesting that regional climate type may be an important element influencing the relationship. The understanding of this relationship may assist policy makers who develop resilience and adaptation strategies as we face the impacts of climate change.
Significance Statement
To the best of our knowledge, this study is the first investigation of contributions of a wide range of climate factors to individual life satisfaction across a continent-size country that provides a novel spatial analysis of the variations in climate factor impact. The study shows that in regions with climatic conditions of high temperatures and prolonged dry periods, additional heat will adversely affect individual well-being. In view of the anticipated effects of climate change, this finding does not bode well for residents of areas that already have a hot and dry climate, as increasing temperatures and potentially longer droughts are likely to compromise their well-being. This study can inform policy making that considers adaptive climate change strategies for community well-being.
Abstract
It is now widely acknowledged that climate change will have a considerable impact on various aspects of human existence, and this includes happiness and satisfaction with life. This study adds to the existing literature on the contribution of climate to well-being by exploring the interaction of various climate variables at the national and local levels while controlling for socioeconomic factors. Using climate data covering a 20-yr period and demographic data from the Household Income Labor Dynamics in Australia surveys, several ordinary least squares (OLS) models of interaction are developed to test the proposition that climate does influence life satisfaction. Geographically weighted regression is then applied to explore how the relationship between explanatory variables and life satisfaction varies across different regions of Australia. We find that overall rainfall, temperature, and sunshine have a small but significant effect on individual life satisfaction. The spatial analysis reveals a high level of nonstationarity in the way climate variables impact life satisfaction, suggesting that regional climate type may be an important element influencing the relationship. The understanding of this relationship may assist policy makers who develop resilience and adaptation strategies as we face the impacts of climate change.
Significance Statement
To the best of our knowledge, this study is the first investigation of contributions of a wide range of climate factors to individual life satisfaction across a continent-size country that provides a novel spatial analysis of the variations in climate factor impact. The study shows that in regions with climatic conditions of high temperatures and prolonged dry periods, additional heat will adversely affect individual well-being. In view of the anticipated effects of climate change, this finding does not bode well for residents of areas that already have a hot and dry climate, as increasing temperatures and potentially longer droughts are likely to compromise their well-being. This study can inform policy making that considers adaptive climate change strategies for community well-being.
Abstract
Studying the population’s perception of coastal erosion is essential and is increasingly used by coastal administrators, especially because it strongly influences the acceptance of coastal adaptation strategies. This article explores the population’s perception of coastal risk on the Atlantic coast of France (Pays de la Loire region) that is an at-risk territory historically affected by erosion and is particularly sensitive to coastal flooding. The major goal of the paper is to collect data in terms of risk perception by carrying out a field survey on three territorial collectivities, with the aim to enhance the feasibility of the managed retreat operations that will be implemented on this coast in the next years. A total of 700 surveys were collected and several original results can be drawn: the population has a good knowledge of erosion in the area where they live, and this knowledge is key because the territory is vulnerable. Similarly, the respondents have a good knowledge of protection measures, but some are more important than others: for example, the reinforcement of coastal defenses is the most commonly cited strategy to deal with coastal hazards whereas relocation is the second-most-known but least-popular scenario. Several factors influence people’s perception of risk: for example, time spent in the residence and age of residents are two elements contributing to place attachment that must be taken into account before starting to implement any climate adaptation policies.
Abstract
Studying the population’s perception of coastal erosion is essential and is increasingly used by coastal administrators, especially because it strongly influences the acceptance of coastal adaptation strategies. This article explores the population’s perception of coastal risk on the Atlantic coast of France (Pays de la Loire region) that is an at-risk territory historically affected by erosion and is particularly sensitive to coastal flooding. The major goal of the paper is to collect data in terms of risk perception by carrying out a field survey on three territorial collectivities, with the aim to enhance the feasibility of the managed retreat operations that will be implemented on this coast in the next years. A total of 700 surveys were collected and several original results can be drawn: the population has a good knowledge of erosion in the area where they live, and this knowledge is key because the territory is vulnerable. Similarly, the respondents have a good knowledge of protection measures, but some are more important than others: for example, the reinforcement of coastal defenses is the most commonly cited strategy to deal with coastal hazards whereas relocation is the second-most-known but least-popular scenario. Several factors influence people’s perception of risk: for example, time spent in the residence and age of residents are two elements contributing to place attachment that must be taken into account before starting to implement any climate adaptation policies.
Abstract
Residents in the Southeast region of the United States are frequently threatened by tornadoes. Previous research indicates that it is important to study the experience of tornado victims to better understand individual risk perception, preparedness, protective action, response, and recovery strategies that contribute to overall community resilience. In this study, we employ an oral-history approach and analyze the lived experience of survivors of an EF3 (on the enhanced Fujita scale) tornado in Jacksonville, Alabama. Using snowball sampling, we conducted in-depth interviews of 25 residents of Jacksonville, Alabama, who experienced the EF3 tornado on 19 March 2018. The recorded interviews were analyzed using qualitative software. Most of the participants described the support system and the range of resources accessible through the network of relations as the critical factors that facilitated recovery and contributed to resilience. The majority also emphasized the importance of being prepared and proactive when addressing future storms, but some of their actions revealed that they were also used to being reactive. The participants were either long-term residents (homeowners) or transient college students (renters), and the data gave insight into different recovery paths and challenges. Further, findings revealed ongoing trauma and recovery challenges due to the extensive, unexpected damage and the lack of temporary housing and contractor availability often associated with small, rural towns. This research aims to provide a scientific basis for improved efforts in preparedness and protective actions as well as in response and recovery strategies in tornado events and for identifying factors of community resilience in tornado-prone areas.
Significance Statement
Grounded in the narratives and reflections of the participants on their tornado experiences, the oral-history interviews generated important insights into psychological–behavioral responses to a disaster, as well as key building blocks of resilience, adding to the body of research surrounding disaster impact and vulnerability, especially for small, rural towns. The preserved voices, stories, and social memory are expected to benefit current and future generations of the community facing similar threats. The findings of this study will further help to inform better practice of local emergency managers and government officials for promoting public awareness of tornadoes and other weather-related risks so as to be more prepared for future extreme weather events.
Abstract
Residents in the Southeast region of the United States are frequently threatened by tornadoes. Previous research indicates that it is important to study the experience of tornado victims to better understand individual risk perception, preparedness, protective action, response, and recovery strategies that contribute to overall community resilience. In this study, we employ an oral-history approach and analyze the lived experience of survivors of an EF3 (on the enhanced Fujita scale) tornado in Jacksonville, Alabama. Using snowball sampling, we conducted in-depth interviews of 25 residents of Jacksonville, Alabama, who experienced the EF3 tornado on 19 March 2018. The recorded interviews were analyzed using qualitative software. Most of the participants described the support system and the range of resources accessible through the network of relations as the critical factors that facilitated recovery and contributed to resilience. The majority also emphasized the importance of being prepared and proactive when addressing future storms, but some of their actions revealed that they were also used to being reactive. The participants were either long-term residents (homeowners) or transient college students (renters), and the data gave insight into different recovery paths and challenges. Further, findings revealed ongoing trauma and recovery challenges due to the extensive, unexpected damage and the lack of temporary housing and contractor availability often associated with small, rural towns. This research aims to provide a scientific basis for improved efforts in preparedness and protective actions as well as in response and recovery strategies in tornado events and for identifying factors of community resilience in tornado-prone areas.
Significance Statement
Grounded in the narratives and reflections of the participants on their tornado experiences, the oral-history interviews generated important insights into psychological–behavioral responses to a disaster, as well as key building blocks of resilience, adding to the body of research surrounding disaster impact and vulnerability, especially for small, rural towns. The preserved voices, stories, and social memory are expected to benefit current and future generations of the community facing similar threats. The findings of this study will further help to inform better practice of local emergency managers and government officials for promoting public awareness of tornadoes and other weather-related risks so as to be more prepared for future extreme weather events.
