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Abstract
Anthropogenic climate change promises to bring existential changes to human society in the coming years. One such example of these changes is the increasing frequency of extreme weather capable of causing significant damage. Despite this, many Americans are acutely unaware of the relationship between climate change and extreme weather events, perhaps because of a lack of direct messaging about it. This study analyzed the effects of natural disasters on climate change discussion sentiment and volume through news media and Twitter posts. The study hypothesized that specific major natural disasters would lead to increases in the number of climate change–related Twitter posts and news articles, as well as more positive climate sentiment, indicative of belief in the severity of global warming. Through an analysis of almost 35 million climate change–related tweets and 300 000+ news articles, along with the collection of over 130 million natural-disaster-related tweets published in the United States between 2010 and 2020, media volume rose an average of 10% around specific extreme weather events, corroborating the first aspect of the hypothesis. The ratio of positive to negative sentiment tweets, however, decreased, suggesting the tendency of extreme weather to elicit more response from climate change deniers than supporters. Thus, increased climate change discussion around major natural disasters represents a missed opportunity for continuing to drive forward climate change messaging and awareness in the United States.
Significance Statement
Extreme weather events threaten Americans’ lives and livelihoods. In turn, anthropogenic climate change has been shown to amplify the frequency and intensity of these weather events, creating uncertainty for communities across the country. Despite the proven connection between climate change and natural disasters, public messaging often fails to leverage anxiety over extreme weather to drive support for environmental action. This study sought to quantify the media relationships of climate change and natural disasters to inform awareness strategies.
Abstract
Anthropogenic climate change promises to bring existential changes to human society in the coming years. One such example of these changes is the increasing frequency of extreme weather capable of causing significant damage. Despite this, many Americans are acutely unaware of the relationship between climate change and extreme weather events, perhaps because of a lack of direct messaging about it. This study analyzed the effects of natural disasters on climate change discussion sentiment and volume through news media and Twitter posts. The study hypothesized that specific major natural disasters would lead to increases in the number of climate change–related Twitter posts and news articles, as well as more positive climate sentiment, indicative of belief in the severity of global warming. Through an analysis of almost 35 million climate change–related tweets and 300 000+ news articles, along with the collection of over 130 million natural-disaster-related tweets published in the United States between 2010 and 2020, media volume rose an average of 10% around specific extreme weather events, corroborating the first aspect of the hypothesis. The ratio of positive to negative sentiment tweets, however, decreased, suggesting the tendency of extreme weather to elicit more response from climate change deniers than supporters. Thus, increased climate change discussion around major natural disasters represents a missed opportunity for continuing to drive forward climate change messaging and awareness in the United States.
Significance Statement
Extreme weather events threaten Americans’ lives and livelihoods. In turn, anthropogenic climate change has been shown to amplify the frequency and intensity of these weather events, creating uncertainty for communities across the country. Despite the proven connection between climate change and natural disasters, public messaging often fails to leverage anxiety over extreme weather to drive support for environmental action. This study sought to quantify the media relationships of climate change and natural disasters to inform awareness strategies.
Abstract
Decision-makers in climate risk management often face problems of how to reconcile diverse and conflicting sources of information about weather and its impact on human activity, such as when they are determining a quantitative threshold for when to act on satellite data. For this class of problems, it is important to quantitatively assess how severe a year was relative to other years, accounting for both the level of uncertainty among weather indicators and those indicators’ relationship to humanitarian consequences. We frame this assessment as the task of constructing a probability distribution for the relative severity of each year, incorporating both observational data—such as satellite measurements—and prior information on human impact—such as farmers’ reports—the latter of which may be incompletely measured or partially ordered. We present a simple, extensible statistical method to fit a probability distribution of relative severity to any ordinal data, using the principle of maximum entropy. We demonstrate the utility of the method through application to a weather index insurance project in Malawi, in which the model allows us to quantify the likelihood that satellites would correctly identify damaging drought events as reported by farmers, while accounting for uncertainty both within a set of commonly used satellite indicators and between those indicators and farmers’ ranking of the worst drought years. This approach has immediate utility in the design of weather-index insurance schemes and forecast-based action programs, such as assessing their degree of basis risk or determining the probable needs for postseason food assistance.
Significance Statement
We present a novel statistical method for synthesizing many indicators of drought into a probability distribution of how bad an agricultural season was likely to have been. This is important because climate risk analysts face problems of how to reconcile diverse and conflicting sources of information about drought—such as determining a quantitative threshold for when to act on satellite data, having only limited, ordinal information on past droughts to validate it. Our new method allows us to construct a probability distribution for the relative severity of a year, incorporating both kinds of data. This allows us to quantify the likelihood that satellites would have missed major humanitarian droughts due to, for example, mistimed observations or unobserved heterogeneity in impacts.
Abstract
Decision-makers in climate risk management often face problems of how to reconcile diverse and conflicting sources of information about weather and its impact on human activity, such as when they are determining a quantitative threshold for when to act on satellite data. For this class of problems, it is important to quantitatively assess how severe a year was relative to other years, accounting for both the level of uncertainty among weather indicators and those indicators’ relationship to humanitarian consequences. We frame this assessment as the task of constructing a probability distribution for the relative severity of each year, incorporating both observational data—such as satellite measurements—and prior information on human impact—such as farmers’ reports—the latter of which may be incompletely measured or partially ordered. We present a simple, extensible statistical method to fit a probability distribution of relative severity to any ordinal data, using the principle of maximum entropy. We demonstrate the utility of the method through application to a weather index insurance project in Malawi, in which the model allows us to quantify the likelihood that satellites would correctly identify damaging drought events as reported by farmers, while accounting for uncertainty both within a set of commonly used satellite indicators and between those indicators and farmers’ ranking of the worst drought years. This approach has immediate utility in the design of weather-index insurance schemes and forecast-based action programs, such as assessing their degree of basis risk or determining the probable needs for postseason food assistance.
Significance Statement
We present a novel statistical method for synthesizing many indicators of drought into a probability distribution of how bad an agricultural season was likely to have been. This is important because climate risk analysts face problems of how to reconcile diverse and conflicting sources of information about drought—such as determining a quantitative threshold for when to act on satellite data, having only limited, ordinal information on past droughts to validate it. Our new method allows us to construct a probability distribution for the relative severity of a year, incorporating both kinds of data. This allows us to quantify the likelihood that satellites would have missed major humanitarian droughts due to, for example, mistimed observations or unobserved heterogeneity in impacts.
Abstract
When a tornado hits, there is little time to think through mental checklists for needed items. This study attempted to understand what information sources those in the path of tornados utilized for preparation and how those sources influence people to act. Results from the study indicate that television and radio are the top two information sources, and that some visual graphics—gauged via heat maps to understand higher levels of severe weather preparation—were reported as useful. Contrary to meteorological intentions, results showed that participants were less likely to prepare for impending weather when radar displayed tornado locations and intensity. In addition, those who identified as having more interest in weather-related information in the study were significantly more likely to prepare, along with those who fear future tornadoes. Each variable explored is underpinned by the theory of planned behavior and the risk information seeking and processing (RISP) model to better understand behavioral intentions and actions. This study offers two new concepts of general weather that have not previously been explored: interest and general versus specific storm preparation.
Significance Statement
The purpose of this work is to learn more about how individuals gather information and obtain weather warnings, primarily during tornado events. In particular, the study seeks to understand how individuals view and interpret visual graphics with information about the location and details about the event. Further, results suggest some differences between those who generally prepare for storm season versus those who only prepare for a specific event. Researchers may also be interested to know how weather enthusiasts may differ in their preparatory activities in comparison with nonweather enthusiasts. All of this information will help meteorologists and media professionals to better target their messages during severe weather.
Abstract
When a tornado hits, there is little time to think through mental checklists for needed items. This study attempted to understand what information sources those in the path of tornados utilized for preparation and how those sources influence people to act. Results from the study indicate that television and radio are the top two information sources, and that some visual graphics—gauged via heat maps to understand higher levels of severe weather preparation—were reported as useful. Contrary to meteorological intentions, results showed that participants were less likely to prepare for impending weather when radar displayed tornado locations and intensity. In addition, those who identified as having more interest in weather-related information in the study were significantly more likely to prepare, along with those who fear future tornadoes. Each variable explored is underpinned by the theory of planned behavior and the risk information seeking and processing (RISP) model to better understand behavioral intentions and actions. This study offers two new concepts of general weather that have not previously been explored: interest and general versus specific storm preparation.
Significance Statement
The purpose of this work is to learn more about how individuals gather information and obtain weather warnings, primarily during tornado events. In particular, the study seeks to understand how individuals view and interpret visual graphics with information about the location and details about the event. Further, results suggest some differences between those who generally prepare for storm season versus those who only prepare for a specific event. Researchers may also be interested to know how weather enthusiasts may differ in their preparatory activities in comparison with nonweather enthusiasts. All of this information will help meteorologists and media professionals to better target their messages during severe weather.
Abstract
Nearly one-half of the residents of North and South Carolina use decentralized or onsite wastewater treatment systems (OWTS). As the climate changes, coastal communities relying on OWTS are particularly vulnerable, as soil-based wastewater treatment may be reduced by water inundation from storm surge, sea level rise and associated groundwater rise, and heavy rainfall. Despite the vulnerabilities of OWTS to increased precipitation and sea level rise, there is little known about how onsite wastewater managers are responding to current and future climate risks. We conducted interviews with wastewater operators and installers and health regulators to understand the functioning, management, and regulation of OWTS in the current climate, challenges with rising sea levels and increases in extreme weather events, and what adaptation strategies could be implemented to mitigate negative impacts. Our results indicate that heavy precipitation and storm surges cause malfunctions for conventional septic systems where traditional site variables (e.g., soil type or groundwater level) are undesirable. Weather and climate are not required regulatory factors to consider in system selection and site approval, but many OWTS managers are aware of their impacts on the functioning of systems, and some are preemptively taking action to mitigate those impacts. Our findings suggest that filling gaps in the current communication structure between regulators and homeowners relying on OWTS is critical for coastal communities in the Carolinas to build climate resilience into decentralized wastewater infrastructure.
Significance Statement
This research aims to understand the functioning, management, and regulation of onsite wastewater treatment systems in the current climate, the challenges to these systems caused by rising sea levels and increases in extreme weather events, and the adaptation strategies that can be implemented to mitigate negative climate impacts. These results can be used by state government agencies, municipalities, and private sector wastewater managers to improve the resiliency of onsite wastewater treatment systems.
Abstract
Nearly one-half of the residents of North and South Carolina use decentralized or onsite wastewater treatment systems (OWTS). As the climate changes, coastal communities relying on OWTS are particularly vulnerable, as soil-based wastewater treatment may be reduced by water inundation from storm surge, sea level rise and associated groundwater rise, and heavy rainfall. Despite the vulnerabilities of OWTS to increased precipitation and sea level rise, there is little known about how onsite wastewater managers are responding to current and future climate risks. We conducted interviews with wastewater operators and installers and health regulators to understand the functioning, management, and regulation of OWTS in the current climate, challenges with rising sea levels and increases in extreme weather events, and what adaptation strategies could be implemented to mitigate negative impacts. Our results indicate that heavy precipitation and storm surges cause malfunctions for conventional septic systems where traditional site variables (e.g., soil type or groundwater level) are undesirable. Weather and climate are not required regulatory factors to consider in system selection and site approval, but many OWTS managers are aware of their impacts on the functioning of systems, and some are preemptively taking action to mitigate those impacts. Our findings suggest that filling gaps in the current communication structure between regulators and homeowners relying on OWTS is critical for coastal communities in the Carolinas to build climate resilience into decentralized wastewater infrastructure.
Significance Statement
This research aims to understand the functioning, management, and regulation of onsite wastewater treatment systems in the current climate, the challenges to these systems caused by rising sea levels and increases in extreme weather events, and the adaptation strategies that can be implemented to mitigate negative climate impacts. These results can be used by state government agencies, municipalities, and private sector wastewater managers to improve the resiliency of onsite wastewater treatment systems.
Abstract
Climate change increases the probability and intensity of disaster and brings adverse impacts on social and economic activities. This paper presents the impact of climate risk on the cost of equity capital (COE) and sheds light on the influence mechanisms and moderating factors between climate disaster shocks and the COE in a developing country. We first explain how climate risk represented by drought impacts the COE theoretically. Using the sample data listed in A-share market from 2004 to 2019, we find that drought leads to the rise of the COE due to the deterioration of information environment and the rise of business risk. Specifically, the influence mechanism is tested, and the results show that 1) drought increases firms’ real earnings management 2) and drought has a negative impact on the firms’ return on asset (ROA). Namely, the influence mechanism of drought on the COE is that drought changes the firms’ information environment and business activities. Further analysis shows that the impact of drought on the COE is different in a heterogeneous firm. The drought has a significant impact on the COE in firms with low-ability managers, state-owned enterprises, and politically connected firms, but the impact is not significant in firms with high-ability managers, non-state-owned enterprises, and nonpolitically connected firms. Our research helps people to understand the consequences of climate change from the microeconomic-level firm’s perspective.
Abstract
Climate change increases the probability and intensity of disaster and brings adverse impacts on social and economic activities. This paper presents the impact of climate risk on the cost of equity capital (COE) and sheds light on the influence mechanisms and moderating factors between climate disaster shocks and the COE in a developing country. We first explain how climate risk represented by drought impacts the COE theoretically. Using the sample data listed in A-share market from 2004 to 2019, we find that drought leads to the rise of the COE due to the deterioration of information environment and the rise of business risk. Specifically, the influence mechanism is tested, and the results show that 1) drought increases firms’ real earnings management 2) and drought has a negative impact on the firms’ return on asset (ROA). Namely, the influence mechanism of drought on the COE is that drought changes the firms’ information environment and business activities. Further analysis shows that the impact of drought on the COE is different in a heterogeneous firm. The drought has a significant impact on the COE in firms with low-ability managers, state-owned enterprises, and politically connected firms, but the impact is not significant in firms with high-ability managers, non-state-owned enterprises, and nonpolitically connected firms. Our research helps people to understand the consequences of climate change from the microeconomic-level firm’s perspective.
Abstract
The likelihood of threatening events is often simplified for members of the public and presented as risk categories such as the “watches” and “warnings” currently issued by National Weather Service in the United States. However, research (e.g., Joslyn and LeClerc) suggests that explicit numeric uncertainty information—for example, 30%—improves people’s understanding as well as their decisions. Whether this benefit extends to dynamic situations in which users must process multiple forecast updates is as yet unknown. It may be that other likelihood expressions, such as color coding, are required under those circumstances. The experimental study reported here compared the effect of the categorical expressions “watches” and “warnings” with both color-coded and numeric percent chance expressions of the likelihood of a tornado in a situation with multiple updates. Participants decided whether and when to take shelter to protect themselves from a tornado on each of 40 trials, each with seven updated tornado forecasts. Understanding, decision quality, and trust were highest in conditions that provided percent chance information. Color-coded likelihood information inspired the least trust and led to the greatest overestimation of likelihood and confusion with severity information of all expressions.
Abstract
The likelihood of threatening events is often simplified for members of the public and presented as risk categories such as the “watches” and “warnings” currently issued by National Weather Service in the United States. However, research (e.g., Joslyn and LeClerc) suggests that explicit numeric uncertainty information—for example, 30%—improves people’s understanding as well as their decisions. Whether this benefit extends to dynamic situations in which users must process multiple forecast updates is as yet unknown. It may be that other likelihood expressions, such as color coding, are required under those circumstances. The experimental study reported here compared the effect of the categorical expressions “watches” and “warnings” with both color-coded and numeric percent chance expressions of the likelihood of a tornado in a situation with multiple updates. Participants decided whether and when to take shelter to protect themselves from a tornado on each of 40 trials, each with seven updated tornado forecasts. Understanding, decision quality, and trust were highest in conditions that provided percent chance information. Color-coded likelihood information inspired the least trust and led to the greatest overestimation of likelihood and confusion with severity information of all expressions.
Abstract
This study examines risk perceptions and evacuation planning for those residents affected by Hurricane Laura—the first major hurricane evacuation during the COVID-19 pandemic—and Hurricane Sally, prior to the widespread availability of vaccines. Research on hurricane evacuation behavior and risk perceptions during a pandemic is critical for quantifying the intersect of these compounding threats. Analyses captured how people perceive public shelters and whether evacuation choices changed in light of the pandemic. Many study participants considered themselves vulnerable to COVID-19 (39.4%), and two-thirds believed it would be “very serious” if they or their loved ones contracted COVID-19, but this had no impact on their actual evacuation decision-making. Approximately 75% of the sample stayed at home during Hurricanes Laura or Sally, and, of these, just over 80% indicated that COVID-19 was a somewhat important deciding factor. This reflects the partial role that COVID-19 played in balancing individual and household protective action decision-making during complex disasters, whereas 15.5% wanted to evacuate but waited until it was too late. For those who evacuated to a hotel, many found that staff and guests wore masks and socially distanced in common spaces. Of particular interest is that individuals have a continued negative perception of public shelters’ ability to safeguard against COVID-19 that was coupled with a significant decrease in the number of respondents that would potentially use shelters in 2020 as compared with before the COVID-19 pandemic. These results have informed and will inform future hazard mitigation planning during the current pandemic or future pandemics or infectious disease outbreaks.
Abstract
This study examines risk perceptions and evacuation planning for those residents affected by Hurricane Laura—the first major hurricane evacuation during the COVID-19 pandemic—and Hurricane Sally, prior to the widespread availability of vaccines. Research on hurricane evacuation behavior and risk perceptions during a pandemic is critical for quantifying the intersect of these compounding threats. Analyses captured how people perceive public shelters and whether evacuation choices changed in light of the pandemic. Many study participants considered themselves vulnerable to COVID-19 (39.4%), and two-thirds believed it would be “very serious” if they or their loved ones contracted COVID-19, but this had no impact on their actual evacuation decision-making. Approximately 75% of the sample stayed at home during Hurricanes Laura or Sally, and, of these, just over 80% indicated that COVID-19 was a somewhat important deciding factor. This reflects the partial role that COVID-19 played in balancing individual and household protective action decision-making during complex disasters, whereas 15.5% wanted to evacuate but waited until it was too late. For those who evacuated to a hotel, many found that staff and guests wore masks and socially distanced in common spaces. Of particular interest is that individuals have a continued negative perception of public shelters’ ability to safeguard against COVID-19 that was coupled with a significant decrease in the number of respondents that would potentially use shelters in 2020 as compared with before the COVID-19 pandemic. These results have informed and will inform future hazard mitigation planning during the current pandemic or future pandemics or infectious disease outbreaks.
Abstract
Although there is clear evidence that proximity to a tornado or forecast tornado increases an individual’s risk perception, the specific relationships between risk personalization and spatial variables are unclear. It has also been established that one’s own evaluation of distance does not always match objective measurement. This study sought to explain the differences in the distance at which an individual would personalize the risk from a tornado across personally relevant geospatial factors such as the distance between places frequented (e.g., home and work), urban/rural classification of the area, and the length of residence in the county. A survey of 1023 respondents across eight states (Alabama, Arkansas, Georgia, Kentucky, Louisiana, Mississippi, Missouri, and Tennessee) was used to obtain risk personalization distances, which were distinguished as “worry distances” (the distances at which one would worry about their house or loved ones, or take protective action) and “confirmation distances” (the distances at which one would expect to see, hear, or feel the effects of a tornado). We found that individuals who traveled greater distances and traveled more frequently to the grocery store and another location, those who self-defined their area as urban, and those with advanced degrees had increased risk personalization distances. Lengthier residency in the county influenced these distances as well. Future research is required to better comprehend the relationship of place, risk perception, and geographic mobility on protective action when a tornado occurs.
Significance Statement
Greater tornado risk personalization distances were associated with self-defining as urban, having an advanced degree, and driving farther and more frequently to the grocery store and to another location. Longer length of residence was associated with shorter risk personalization distances. With rural participants expressing shorter tornado risk personalization distances, warning communicators with the ability to tailor messages to multiple communities may wish to adjust messages no the basis of whether they are targeted to rural communities or to urban communities.
Abstract
Although there is clear evidence that proximity to a tornado or forecast tornado increases an individual’s risk perception, the specific relationships between risk personalization and spatial variables are unclear. It has also been established that one’s own evaluation of distance does not always match objective measurement. This study sought to explain the differences in the distance at which an individual would personalize the risk from a tornado across personally relevant geospatial factors such as the distance between places frequented (e.g., home and work), urban/rural classification of the area, and the length of residence in the county. A survey of 1023 respondents across eight states (Alabama, Arkansas, Georgia, Kentucky, Louisiana, Mississippi, Missouri, and Tennessee) was used to obtain risk personalization distances, which were distinguished as “worry distances” (the distances at which one would worry about their house or loved ones, or take protective action) and “confirmation distances” (the distances at which one would expect to see, hear, or feel the effects of a tornado). We found that individuals who traveled greater distances and traveled more frequently to the grocery store and another location, those who self-defined their area as urban, and those with advanced degrees had increased risk personalization distances. Lengthier residency in the county influenced these distances as well. Future research is required to better comprehend the relationship of place, risk perception, and geographic mobility on protective action when a tornado occurs.
Significance Statement
Greater tornado risk personalization distances were associated with self-defining as urban, having an advanced degree, and driving farther and more frequently to the grocery store and to another location. Longer length of residence was associated with shorter risk personalization distances. With rural participants expressing shorter tornado risk personalization distances, warning communicators with the ability to tailor messages to multiple communities may wish to adjust messages no the basis of whether they are targeted to rural communities or to urban communities.
Abstract
This paper explores the internal migration of fishers from coastal communities of Bangladesh in response to extreme weather events. It also assesses the vulnerabilities to extreme weather events of these coastal areas, in general, and of targeted fishing communities, in particular. This qualitative study employs a combination of methods, semistructured interviews and observations, in two villages located in the eastern part of Kalapara Upazila, Patuakhali district of Bangladesh. The results indicate that the participants of the study are susceptible to the vulnerability of extreme weather events due to their households’ socioeconomic and geographical location. This study shows that most people from the fishing communities do not migrate to other places to escape from the vulnerabilities as they have high dependency on fish-related activities. Also, there are various socioeconomic and cultural factors that hinder their migration, including the Mohajon–Dadon system, migration costs, lack of skills and resources, and fear of income insecurity. Instead of migrating, they develop their own traditional adaptation mechanisms to ensure their survival. These people remain underrepresented and are not adequately recorded in national or regional migration data.
Abstract
This paper explores the internal migration of fishers from coastal communities of Bangladesh in response to extreme weather events. It also assesses the vulnerabilities to extreme weather events of these coastal areas, in general, and of targeted fishing communities, in particular. This qualitative study employs a combination of methods, semistructured interviews and observations, in two villages located in the eastern part of Kalapara Upazila, Patuakhali district of Bangladesh. The results indicate that the participants of the study are susceptible to the vulnerability of extreme weather events due to their households’ socioeconomic and geographical location. This study shows that most people from the fishing communities do not migrate to other places to escape from the vulnerabilities as they have high dependency on fish-related activities. Also, there are various socioeconomic and cultural factors that hinder their migration, including the Mohajon–Dadon system, migration costs, lack of skills and resources, and fear of income insecurity. Instead of migrating, they develop their own traditional adaptation mechanisms to ensure their survival. These people remain underrepresented and are not adequately recorded in national or regional migration data.
