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Abstract
Media organizations can quickly disseminate information from official sources to the general population. The media play a vital role before, during, and after a hazard incident or natural disaster by broadcasting early warnings, coordinating emergency management strategies, providing timely updates, and offering advice on protective actions. Therefore, it is important to examine how news media use various framing devices such as story selection, placement, length, and quotations from officials and citizens in their crisis news coverage. We investigate print media coverage of Hurricane Harvey utilizing data from three newspapers: the New York Times (online), the Wall Street Journal (online), and the Houston Chronicle. By examining the use of descriptors, quotes, and wording about Hurricane Harvey, our research explores how media coverage framed and created a tone for the government and private sectors for their roles in response and recovery processes. Findings reveal that the human-interest frame received the most media attention, whereas the morality frame received less attention. For tone, we find that the overall tone for the government response was balanced and less negative. However, the media tone varies among three levels of government: the tone for the federal government was more negative, whereas the tone for the city and state levels of government was slightly positive. For private sectors, we found that the for-profit sector coverage had a strong negative tone, whereas the nonprofit sector received a strong positive tone. By offering a descriptive analysis of framing and tone, our study reveals how print media sources portray actors involved in recovery and rebuilding efforts for Hurricane Harvey.
Abstract
Media organizations can quickly disseminate information from official sources to the general population. The media play a vital role before, during, and after a hazard incident or natural disaster by broadcasting early warnings, coordinating emergency management strategies, providing timely updates, and offering advice on protective actions. Therefore, it is important to examine how news media use various framing devices such as story selection, placement, length, and quotations from officials and citizens in their crisis news coverage. We investigate print media coverage of Hurricane Harvey utilizing data from three newspapers: the New York Times (online), the Wall Street Journal (online), and the Houston Chronicle. By examining the use of descriptors, quotes, and wording about Hurricane Harvey, our research explores how media coverage framed and created a tone for the government and private sectors for their roles in response and recovery processes. Findings reveal that the human-interest frame received the most media attention, whereas the morality frame received less attention. For tone, we find that the overall tone for the government response was balanced and less negative. However, the media tone varies among three levels of government: the tone for the federal government was more negative, whereas the tone for the city and state levels of government was slightly positive. For private sectors, we found that the for-profit sector coverage had a strong negative tone, whereas the nonprofit sector received a strong positive tone. By offering a descriptive analysis of framing and tone, our study reveals how print media sources portray actors involved in recovery and rebuilding efforts for Hurricane Harvey.
Abstract
This paper explores environmental distress (e.g., feeling blue) in a politically conservative (“red”) and predominantly white farming community in the southwestern United States. In such communities across the United States, expressed concern over environmental change—including climate change—tends to be lower. This is understood to have a palliative effect that reduces feelings of ecoanxiety. Using an emotional geographies framework, our study identifies the forms of everyday emotional expressions related to water and environmental change in the context of a vulnerable rural agricultural community in central Arizona. Drawing on long-term participant-observation and stakeholder research, we use data from individual (n = 48) and group (n = 8) interviews with water stakeholders to explore reports of sadness and fear over environmental change using an emotion-focused text analysis. We find that this distress is related to social and material changes related to environmental change rather than to environmental change itself. We discuss implications for research on emotional geographies for understanding reactions to environmental change and uncertainty.
Abstract
This paper explores environmental distress (e.g., feeling blue) in a politically conservative (“red”) and predominantly white farming community in the southwestern United States. In such communities across the United States, expressed concern over environmental change—including climate change—tends to be lower. This is understood to have a palliative effect that reduces feelings of ecoanxiety. Using an emotional geographies framework, our study identifies the forms of everyday emotional expressions related to water and environmental change in the context of a vulnerable rural agricultural community in central Arizona. Drawing on long-term participant-observation and stakeholder research, we use data from individual (n = 48) and group (n = 8) interviews with water stakeholders to explore reports of sadness and fear over environmental change using an emotion-focused text analysis. We find that this distress is related to social and material changes related to environmental change rather than to environmental change itself. We discuss implications for research on emotional geographies for understanding reactions to environmental change and uncertainty.
Abstract
Considering the widespread and cross-cultural effects of climate on various production sectors, environmental factors, and human societies, drought is nowadays regarded as one of the most important environmental challenges of the current century. Because of their close relationship with the natural environment and their limited opportunities, rural communities have long been exposed to drought, and farmers in dry and semiarid regions have been applying measures to adapt to and cope with it. The main purpose of this study was to investigate and identify farmers’ native methods to reduce the effects of drought. The research method was phenomenological and survey based. The population included villagers in Kangavar County, Kermanshah Province, in Iran. Sampling was done by the targeted and snowflake method. The data collection instrument was an in-depth interview in the qualitative section and a self-designed questionnaire in the quantitative section. The results showed that farmers used different measures for coping with and adapting to drought, including using no-tillage farming; uprooting trees with high water demands; hope and oblation; mulching; reducing, changing, and/or mixing livestock types (reaction behaviors); diversifying the sources of livelihoods; changing cropping patterns; correcting irrigation practices; changing planting time; seeding before the drought; and using water storage techniques (fractional behaviors). In addition, farmers had a weaker capability to cope with the environmental, economic, and social vulnerabilities than with drought. This presented the vulnerability of farmers to drought in all economic, social, and environmental spheres.
Abstract
Considering the widespread and cross-cultural effects of climate on various production sectors, environmental factors, and human societies, drought is nowadays regarded as one of the most important environmental challenges of the current century. Because of their close relationship with the natural environment and their limited opportunities, rural communities have long been exposed to drought, and farmers in dry and semiarid regions have been applying measures to adapt to and cope with it. The main purpose of this study was to investigate and identify farmers’ native methods to reduce the effects of drought. The research method was phenomenological and survey based. The population included villagers in Kangavar County, Kermanshah Province, in Iran. Sampling was done by the targeted and snowflake method. The data collection instrument was an in-depth interview in the qualitative section and a self-designed questionnaire in the quantitative section. The results showed that farmers used different measures for coping with and adapting to drought, including using no-tillage farming; uprooting trees with high water demands; hope and oblation; mulching; reducing, changing, and/or mixing livestock types (reaction behaviors); diversifying the sources of livelihoods; changing cropping patterns; correcting irrigation practices; changing planting time; seeding before the drought; and using water storage techniques (fractional behaviors). In addition, farmers had a weaker capability to cope with the environmental, economic, and social vulnerabilities than with drought. This presented the vulnerability of farmers to drought in all economic, social, and environmental spheres.
Abstract
We study how seasonal climate affects influenza–pneumonia (I-P) mortality using monthly health and climate data over the past 20 years, reduced to mean annual cycle and statistically correlated. Results show that I-P deaths are inversely related to temperature, humidity, and net solar radiation in the United States, South Africa, and Puerto Rico (r < −0.93) via transmission and immune system response. The I-P mortality is 3–10 times as high in winter as in summer, with sharp transitions in autumn and spring. Public health management can rely on seasonal climate-induced fluctuations of I-P mortality to promote healthy lifestyle choices and guide efforts to mitigate epidemic impacts.
Abstract
We study how seasonal climate affects influenza–pneumonia (I-P) mortality using monthly health and climate data over the past 20 years, reduced to mean annual cycle and statistically correlated. Results show that I-P deaths are inversely related to temperature, humidity, and net solar radiation in the United States, South Africa, and Puerto Rico (r < −0.93) via transmission and immune system response. The I-P mortality is 3–10 times as high in winter as in summer, with sharp transitions in autumn and spring. Public health management can rely on seasonal climate-induced fluctuations of I-P mortality to promote healthy lifestyle choices and guide efforts to mitigate epidemic impacts.
Abstract
Catastrophic disasters disrupt the structural and social aspects of housing, which can lead to varying lengths of displacement and housing instability for affected residents. Stable housing is a critical aspect of postdisaster recovery, which makes it important to understand how much time passes before displaced residents are able to find stable housing. Using the Gulf Coast Child and Family Health Study, a longitudinal cohort of Mississippi and Louisiana residents exposed to Hurricane Katrina (n = 1079), we describe patterns of stable housing by identifying protective and prohibitive factors that affect time to stable housing in the 13 years following the storm. Survival analyses reveal that median time to stable housing was 1082 days—over 3 years after Katrina. Age, housing tenure, marital status, income, and social support each independently affected time to stable housing. Findings suggest that postdisaster housing instability is similar to other forms of housing instability, including eviction, frequent moves, and homelessness.
Significance Statement
Climate change is expected to increase gradual-onset events like sea level rise, as well as the frequency and intensity of acute disasters like hurricanes. Such events when coupled with population growth, coastline development, and increasing inequality will lead to high levels of displacement and housing instability. Using longitudinal data, we wanted to understand how much time passed until residents who were displaced by Hurricane Katrina were able to find permanent and stable housing and identify factors that either prolonged or accelerated respondents’ time to stable housing. Addressing this gap can help to improve resident recovery and create targeted postdisaster housing policy, especially as displacement from disasters becomes increasingly common among those living in regions susceptible to the effects of climate change.
Abstract
Catastrophic disasters disrupt the structural and social aspects of housing, which can lead to varying lengths of displacement and housing instability for affected residents. Stable housing is a critical aspect of postdisaster recovery, which makes it important to understand how much time passes before displaced residents are able to find stable housing. Using the Gulf Coast Child and Family Health Study, a longitudinal cohort of Mississippi and Louisiana residents exposed to Hurricane Katrina (n = 1079), we describe patterns of stable housing by identifying protective and prohibitive factors that affect time to stable housing in the 13 years following the storm. Survival analyses reveal that median time to stable housing was 1082 days—over 3 years after Katrina. Age, housing tenure, marital status, income, and social support each independently affected time to stable housing. Findings suggest that postdisaster housing instability is similar to other forms of housing instability, including eviction, frequent moves, and homelessness.
Significance Statement
Climate change is expected to increase gradual-onset events like sea level rise, as well as the frequency and intensity of acute disasters like hurricanes. Such events when coupled with population growth, coastline development, and increasing inequality will lead to high levels of displacement and housing instability. Using longitudinal data, we wanted to understand how much time passed until residents who were displaced by Hurricane Katrina were able to find permanent and stable housing and identify factors that either prolonged or accelerated respondents’ time to stable housing. Addressing this gap can help to improve resident recovery and create targeted postdisaster housing policy, especially as displacement from disasters becomes increasingly common among those living in regions susceptible to the effects of climate change.
Abstract
Timely communication of warnings is essential to protection of lives and properties during tornado outbreaks. Both official and personal channels of communication prove to have considerable impact on the overall outcome. In this study, an agent-based model is developed to simulate warning’s reception–dissemination process in which a person is exposed to, receives, and sends information while interacting with others. The model is applied to an EF5 tornado (EF indicates enhanced Fujita scale) that struck Moore, Oklahoma, in 2013. The parameters are calibrated using publicly available data or a poststorm telephone survey or were derived from literature reviews, expert judgement, and sensitivity analysis. The result shows a reasonable agreement between modeled and observed reception rates for older and younger adults and for different channels, with errors of less than 20 percentage points. Similar agreement is also seen for the average numbers of warning sources. The subsequent simulation indicates that, in the absence of tornado sirens, the overall reception rates for younger and older adults would drop from the baseline by 17 and 6 percentage points, respectively. Concurrently, there is a large decline in the number of warning sources. When a persons’ social network is enlarged, the reception rate for older adults improves from 77% to 80%, whereas for younger adults it stays unchanged. The impact of increased connectivity is more pronounced when people are not watching television or a tornado siren is not available.
Significance Statement
Every year, tornadoes cause significant property damage and numerous casualties in the United States. This study aims to understand how tornado warnings reach the at-risk public through various communication channels. Using the agent-based model and simulation, we are able to reconstruct the dynamic patterns of warning’s reception–dissemination process for older and younger adults within a historical EF5 tornado. Further analysis confirms the importance of tornado sirens in not only alerting more residents about the dangerous weather condition but also prompting protective actions. In the meantime, an increase in social connectivity among residents would compensate for the lack of exposure to television and tornado siren. Future work should investigate the robustness of this model and its parameters when applied to other tornado outbreaks.
Abstract
Timely communication of warnings is essential to protection of lives and properties during tornado outbreaks. Both official and personal channels of communication prove to have considerable impact on the overall outcome. In this study, an agent-based model is developed to simulate warning’s reception–dissemination process in which a person is exposed to, receives, and sends information while interacting with others. The model is applied to an EF5 tornado (EF indicates enhanced Fujita scale) that struck Moore, Oklahoma, in 2013. The parameters are calibrated using publicly available data or a poststorm telephone survey or were derived from literature reviews, expert judgement, and sensitivity analysis. The result shows a reasonable agreement between modeled and observed reception rates for older and younger adults and for different channels, with errors of less than 20 percentage points. Similar agreement is also seen for the average numbers of warning sources. The subsequent simulation indicates that, in the absence of tornado sirens, the overall reception rates for younger and older adults would drop from the baseline by 17 and 6 percentage points, respectively. Concurrently, there is a large decline in the number of warning sources. When a persons’ social network is enlarged, the reception rate for older adults improves from 77% to 80%, whereas for younger adults it stays unchanged. The impact of increased connectivity is more pronounced when people are not watching television or a tornado siren is not available.
Significance Statement
Every year, tornadoes cause significant property damage and numerous casualties in the United States. This study aims to understand how tornado warnings reach the at-risk public through various communication channels. Using the agent-based model and simulation, we are able to reconstruct the dynamic patterns of warning’s reception–dissemination process for older and younger adults within a historical EF5 tornado. Further analysis confirms the importance of tornado sirens in not only alerting more residents about the dangerous weather condition but also prompting protective actions. In the meantime, an increase in social connectivity among residents would compensate for the lack of exposure to television and tornado siren. Future work should investigate the robustness of this model and its parameters when applied to other tornado outbreaks.
Abstract
The Electric Reliability Council of Texas (ERCOT) manages the electric power across most of Texas. They make short-term assessments of electricity demand on the basis of historical weather over the last two decades, thereby ignoring the effects of climate change and the possibility of weather variability outside the recent historical range. In this paper, we develop an empirical method to predict the impact of weather on energy demand. We use that with a large ensemble of climate model runs to construct a probability distribution of power demand on the ERCOT grid for summer and winter 2021. We find that the most severe weather events will use 100% of available power—if anything goes wrong, as it did during the 2021 winter, there will not be sufficient available power. More quantitatively, we estimate a 5% chance that maximum power demand would be within 4.3 and 7.9 GW of ERCOT’s estimate of best-case available resources during summer and winter 2021, respectively, and a 20% chance it would be within 7.1 and 17 GW. The shortage of power on the ERCOT grid is partially hidden by the fact that ERCOTs seasonal assessments, which are based entirely on historical weather, are too low. Prior to the 2021 winter blackout, ERCOT forecast an extreme peak load of 67 GW. In reality, we estimate hourly peak demand was 82 GW, 22% above ERCOT’s most extreme forecast and about equal to the best-case available power. Given the high stakes, ERCOT should develop probabilistic estimates using modern scientific tools to predict the range of power demand more accurately.
Abstract
The Electric Reliability Council of Texas (ERCOT) manages the electric power across most of Texas. They make short-term assessments of electricity demand on the basis of historical weather over the last two decades, thereby ignoring the effects of climate change and the possibility of weather variability outside the recent historical range. In this paper, we develop an empirical method to predict the impact of weather on energy demand. We use that with a large ensemble of climate model runs to construct a probability distribution of power demand on the ERCOT grid for summer and winter 2021. We find that the most severe weather events will use 100% of available power—if anything goes wrong, as it did during the 2021 winter, there will not be sufficient available power. More quantitatively, we estimate a 5% chance that maximum power demand would be within 4.3 and 7.9 GW of ERCOT’s estimate of best-case available resources during summer and winter 2021, respectively, and a 20% chance it would be within 7.1 and 17 GW. The shortage of power on the ERCOT grid is partially hidden by the fact that ERCOTs seasonal assessments, which are based entirely on historical weather, are too low. Prior to the 2021 winter blackout, ERCOT forecast an extreme peak load of 67 GW. In reality, we estimate hourly peak demand was 82 GW, 22% above ERCOT’s most extreme forecast and about equal to the best-case available power. Given the high stakes, ERCOT should develop probabilistic estimates using modern scientific tools to predict the range of power demand more accurately.
Abstract
This research explores a data-driven methodological framework to quantify the effect of rainfall and visibility on travel time reliability (TTR) by considering selected road segments in North Carolina. The framework includes capturing, processing, and integrating weather-related information and travel time data for the selected road segments. Various TTR indices were computed for the selected road segments under different rainfall and visibility ranges by day of the week (DOW) and time of the day (TOD). The TTR indices were computed for one week before and after (same DOW and TOD) under the normal weather condition and compared with those obtained under different intensities of rainfall and visibility. The variability in travel time patterns due to other events is expected to be marginal when considering the same DOW and TOD for comparison purposes. The results indicate that poor visibility with different rainfall intensities has the maximum adverse effect on the TTR. The outcomes from the data-driven methodological framework help the transportation planners in developing weather-responsive traffic management strategies and assessing their effectiveness using TTR indices.
Significance Statement
Travel time reliability (TTR) generally refers to the level of consistency or dependability in transportation service. It is considered as a measure of road operational performance. Ensuring higher levels of reliability is critical for efficient transportation system management along with mobility and accessibility needs. However, factors such as weather condition have a negative effect on the TTR. A data-driven methodological framework is proposed by integrating weather information and travel time data to quantify the effect of common weather conditions like rainfall and visibility on the TTR. The results indicated that heavy rain and poor visibility have an adverse effect on the TTR. These results are useful for agencies to better manage the traffic under different weather conditions.
Abstract
This research explores a data-driven methodological framework to quantify the effect of rainfall and visibility on travel time reliability (TTR) by considering selected road segments in North Carolina. The framework includes capturing, processing, and integrating weather-related information and travel time data for the selected road segments. Various TTR indices were computed for the selected road segments under different rainfall and visibility ranges by day of the week (DOW) and time of the day (TOD). The TTR indices were computed for one week before and after (same DOW and TOD) under the normal weather condition and compared with those obtained under different intensities of rainfall and visibility. The variability in travel time patterns due to other events is expected to be marginal when considering the same DOW and TOD for comparison purposes. The results indicate that poor visibility with different rainfall intensities has the maximum adverse effect on the TTR. The outcomes from the data-driven methodological framework help the transportation planners in developing weather-responsive traffic management strategies and assessing their effectiveness using TTR indices.
Significance Statement
Travel time reliability (TTR) generally refers to the level of consistency or dependability in transportation service. It is considered as a measure of road operational performance. Ensuring higher levels of reliability is critical for efficient transportation system management along with mobility and accessibility needs. However, factors such as weather condition have a negative effect on the TTR. A data-driven methodological framework is proposed by integrating weather information and travel time data to quantify the effect of common weather conditions like rainfall and visibility on the TTR. The results indicated that heavy rain and poor visibility have an adverse effect on the TTR. These results are useful for agencies to better manage the traffic under different weather conditions.
Abstract
Climate information services can build the resilience of African farmers to address the increasing threats associated with climate change. This study used household surveys with 200 farmers and focus group discussions to identify the types of climate information services available to farming households in two selected districts (Tolon and Nanton) in the Northern Region of Ghana. The study also identified the dissemination channels and the barriers faced by farmers in their access and use of climate information services for building climate resilience in Ghanaian farming systems. Multinomial logistic regression analysis was used to evaluate the determinants of farmers’ access to climate information services. Results show that 70% of the surveyed farmers had access to varied forms of climate information services. The most prevalent meteorological variables accessible to them were rainfall, temperature, and windstorms in the form of daily and weekly weather forecasts, with only very limited availability and use of seasonal climate forecasts. Radio, television, and advice from extension agents were reported as the major dissemination channels by study respondents. A majority of the farmers reported lack of communication devices, mistrust in weather and climate forecasts, and lack of visual representations in the forecasts as major barriers to access and use of climate information services. The results highlight the importance of timely and reliable access to climate information services in enhancing farmers’ decision-making capacities and the need for training and recruitment of more extension agents to work with farmers on linking climate information services to targeted actions on crop and land management.
Abstract
Climate information services can build the resilience of African farmers to address the increasing threats associated with climate change. This study used household surveys with 200 farmers and focus group discussions to identify the types of climate information services available to farming households in two selected districts (Tolon and Nanton) in the Northern Region of Ghana. The study also identified the dissemination channels and the barriers faced by farmers in their access and use of climate information services for building climate resilience in Ghanaian farming systems. Multinomial logistic regression analysis was used to evaluate the determinants of farmers’ access to climate information services. Results show that 70% of the surveyed farmers had access to varied forms of climate information services. The most prevalent meteorological variables accessible to them were rainfall, temperature, and windstorms in the form of daily and weekly weather forecasts, with only very limited availability and use of seasonal climate forecasts. Radio, television, and advice from extension agents were reported as the major dissemination channels by study respondents. A majority of the farmers reported lack of communication devices, mistrust in weather and climate forecasts, and lack of visual representations in the forecasts as major barriers to access and use of climate information services. The results highlight the importance of timely and reliable access to climate information services in enhancing farmers’ decision-making capacities and the need for training and recruitment of more extension agents to work with farmers on linking climate information services to targeted actions on crop and land management.
Abstract
Probabilistic forecast information is rapidly spreading in the weather enterprise. Many scientists agree that this is a positive development, but incorporating probability information into risk communication can be challenging because communicators have little guidance about the most effective way to present it. This project endeavors to create such guidance by initiating a “living systematic review” of research studies that empirically examine the impact of risk messages that use probability information on protective action decision-making, intentions, and behaviors. In this article, we explain how we began the review, map the current state of the literature, synthesize core findings, provide actionable recommendations to assist forecasters in risk communication, and introduce an online platform that scholars and forecasters can use to interact with the data from the review. We conclude with two key points from the review that necessitate emphasis: the research literature strongly suggests that 1) average people can make sense of and use probability information if consideration is given to information presentation and 2) assuming appropriate presentation, probability information generally improves decision quality.
Significance Statement
Probability information is increasingly common in weather forecasts, but forecasters have relatively little guidance on the most effective way to communicate this information to members of the public. This project synthesizes the research literature to provide actionable recommendations to assist forecasters who are working to include probability information in risk communication messages.
Abstract
Probabilistic forecast information is rapidly spreading in the weather enterprise. Many scientists agree that this is a positive development, but incorporating probability information into risk communication can be challenging because communicators have little guidance about the most effective way to present it. This project endeavors to create such guidance by initiating a “living systematic review” of research studies that empirically examine the impact of risk messages that use probability information on protective action decision-making, intentions, and behaviors. In this article, we explain how we began the review, map the current state of the literature, synthesize core findings, provide actionable recommendations to assist forecasters in risk communication, and introduce an online platform that scholars and forecasters can use to interact with the data from the review. We conclude with two key points from the review that necessitate emphasis: the research literature strongly suggests that 1) average people can make sense of and use probability information if consideration is given to information presentation and 2) assuming appropriate presentation, probability information generally improves decision quality.
Significance Statement
Probability information is increasingly common in weather forecasts, but forecasters have relatively little guidance on the most effective way to communicate this information to members of the public. This project synthesizes the research literature to provide actionable recommendations to assist forecasters who are working to include probability information in risk communication messages.
