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Abstract
A cool environment is critical for protecting vulnerable populations from the adverse health effects associated with exposure to extreme heat. Although cooling centers are commonly established to provide temporary heat relief to the public, there is limited research exploring the spatial distributions and accessibility of cooling centers across cities in Texas. The intent of this study was to examine the spatial characteristics of cooling center locations throughout the Texas Triangle megaregion and evaluate the proximity of cooling centers to vulnerable populations. Specifically, spatial clustering analysis was used to quantitatively characterize the spatial distributions of cooling centers in San Antonio, Houston, and Dallas, while spatial lag regression was conducted to evaluate the relationships between indicators of socioeconomic vulnerability and proximity to cooling centers. The findings indicated that cooling centers exhibited clustering at short distances, which suggested there were potential spatial redundancies. The distributions of the cooling centers also illustrated possible accessibility issues due to the concentration of the locations in urban cores. The spatial lag regression models highlighted several problematic relationships, as elderly and disabled populations were located at significantly greater distances from cooling centers in San Antonio and Dallas, respectively. However, numerous insignificant relationships were also observed, which suggested that cooling center locations did not consistently marginalize or favor vulnerable populations. Therefore, a higher degree of intentionality that explicitly considers cooling center proximity to the vulnerable populations they aim to serve might be beneficial as planners and emergency managers determine cooling center locations in response to extreme heat.
Abstract
A cool environment is critical for protecting vulnerable populations from the adverse health effects associated with exposure to extreme heat. Although cooling centers are commonly established to provide temporary heat relief to the public, there is limited research exploring the spatial distributions and accessibility of cooling centers across cities in Texas. The intent of this study was to examine the spatial characteristics of cooling center locations throughout the Texas Triangle megaregion and evaluate the proximity of cooling centers to vulnerable populations. Specifically, spatial clustering analysis was used to quantitatively characterize the spatial distributions of cooling centers in San Antonio, Houston, and Dallas, while spatial lag regression was conducted to evaluate the relationships between indicators of socioeconomic vulnerability and proximity to cooling centers. The findings indicated that cooling centers exhibited clustering at short distances, which suggested there were potential spatial redundancies. The distributions of the cooling centers also illustrated possible accessibility issues due to the concentration of the locations in urban cores. The spatial lag regression models highlighted several problematic relationships, as elderly and disabled populations were located at significantly greater distances from cooling centers in San Antonio and Dallas, respectively. However, numerous insignificant relationships were also observed, which suggested that cooling center locations did not consistently marginalize or favor vulnerable populations. Therefore, a higher degree of intentionality that explicitly considers cooling center proximity to the vulnerable populations they aim to serve might be beneficial as planners and emergency managers determine cooling center locations in response to extreme heat.
Abstract
Geovisualizations play a central role in communicating hurricane storm surge risks to the public by connecting information about the hazard to a place. Meanwhile, people connect to places through meaning, functions, and emotional bond, known as a sense of place. The mixed-method approach presented in this paper focuses on the intersection of sense of place, geovisualization, and risk communication. We explored place meaning, scale of place, and place attachment in the coastal communities in Georgia and South Carolina. We conducted cognitive mapping focus groups and developed a series of geovisualizations of storm surge risk with varying representations of place. We then investigated people’s ability to connect visual storm surge information to a place and understand their risk by testing these geovisualizations in a large population survey (n = 1442). We found that a 2D regional-scale map displayed together with a 3D abstract representation of a neighborhood was the most helpful in enabling people to relate to a place, quickly make sense of the information, and understand the risk. Our results showed that while the geovisualizations of storm surge risk can be effective generally, they were less effective in several important and vulnerable groups. We found substantial impacts of race, income, map-reading ability, place attachment, and scale of place on how people connected the storm surge risk shown in the visual to a place. These findings have implications for future research and for considering the way weather forecasters and emergency managers communicate storm surge information with diverse audiences using geovisualizations.
Significance Statement
Weather forecasters and emergency managers often use geovisualizations to communicate hurricane storm surge risks and threats to the public. Despite the important role that geovisualizations play, few studies have empirically investigated their effectiveness in hazardous weather risk communication. With the overarching goal of understanding how geovisualizations enable coastal residents to understand and respond to risk, we use an interdisciplinary approach to create new knowledge about the effectiveness of geovisualizations in storm surge risk communication. Our results show substantial impacts of sociodemographic factors across many of the measures that enable people to connect to a place through visualizations. These findings have implications for communicating geospatially varying risk to diverse audiences.
Abstract
Geovisualizations play a central role in communicating hurricane storm surge risks to the public by connecting information about the hazard to a place. Meanwhile, people connect to places through meaning, functions, and emotional bond, known as a sense of place. The mixed-method approach presented in this paper focuses on the intersection of sense of place, geovisualization, and risk communication. We explored place meaning, scale of place, and place attachment in the coastal communities in Georgia and South Carolina. We conducted cognitive mapping focus groups and developed a series of geovisualizations of storm surge risk with varying representations of place. We then investigated people’s ability to connect visual storm surge information to a place and understand their risk by testing these geovisualizations in a large population survey (n = 1442). We found that a 2D regional-scale map displayed together with a 3D abstract representation of a neighborhood was the most helpful in enabling people to relate to a place, quickly make sense of the information, and understand the risk. Our results showed that while the geovisualizations of storm surge risk can be effective generally, they were less effective in several important and vulnerable groups. We found substantial impacts of race, income, map-reading ability, place attachment, and scale of place on how people connected the storm surge risk shown in the visual to a place. These findings have implications for future research and for considering the way weather forecasters and emergency managers communicate storm surge information with diverse audiences using geovisualizations.
Significance Statement
Weather forecasters and emergency managers often use geovisualizations to communicate hurricane storm surge risks and threats to the public. Despite the important role that geovisualizations play, few studies have empirically investigated their effectiveness in hazardous weather risk communication. With the overarching goal of understanding how geovisualizations enable coastal residents to understand and respond to risk, we use an interdisciplinary approach to create new knowledge about the effectiveness of geovisualizations in storm surge risk communication. Our results show substantial impacts of sociodemographic factors across many of the measures that enable people to connect to a place through visualizations. These findings have implications for communicating geospatially varying risk to diverse audiences.
Abstract
Although decision-making in response to tornado warnings is well researched, most studies do not examine whether individual responses to these warnings vary across different geographical locations and demographic groups. This gap is addressed by using data from a decision experiment that places participants virtually in a simulated tornado warning and asks them to minimize the costs of their decisions. The authors examine the following: 1) what demographic attributes may contribute to choices to minimize costs to protect assets at a specific location in a tornado warning, 2) whether there is a spatial component to how these attributes influence decision-making, and 3) if there are specific U.S. regions where individuals do not make protective decisions that minimize their overall cost. Multilevel regression analysis and poststratification are applied to data from the simulated decision experiment to estimate which demographic attributes and National Weather Service County Warning Areas are most associated with the costliest protective decisions. The results are then analyzed using spatial autocorrelation to identify spatial patterns. Results indicate that sex, race, and ethnicity are important factors that influence protection decisions. Findings also show that people across the southern portions of the United States tend to make more costly protective decisions, as defined in this work.
Significance Statement
Tornadoes, although rare, threaten both life and property. Studies have shown that certain demographic groups are more negatively impacted by disasters than others and are at higher risk of severe weather hazards. We ask if there are demographic characteristics or geographic locations in common among people who are more prone to making protection decisions during tornado warnings to minimize economic costs. Results can help warning providers, such as the National Weather Service, direct resources and education to specific types of decision-makers or locations to improve sheltering decisions.
Abstract
Although decision-making in response to tornado warnings is well researched, most studies do not examine whether individual responses to these warnings vary across different geographical locations and demographic groups. This gap is addressed by using data from a decision experiment that places participants virtually in a simulated tornado warning and asks them to minimize the costs of their decisions. The authors examine the following: 1) what demographic attributes may contribute to choices to minimize costs to protect assets at a specific location in a tornado warning, 2) whether there is a spatial component to how these attributes influence decision-making, and 3) if there are specific U.S. regions where individuals do not make protective decisions that minimize their overall cost. Multilevel regression analysis and poststratification are applied to data from the simulated decision experiment to estimate which demographic attributes and National Weather Service County Warning Areas are most associated with the costliest protective decisions. The results are then analyzed using spatial autocorrelation to identify spatial patterns. Results indicate that sex, race, and ethnicity are important factors that influence protection decisions. Findings also show that people across the southern portions of the United States tend to make more costly protective decisions, as defined in this work.
Significance Statement
Tornadoes, although rare, threaten both life and property. Studies have shown that certain demographic groups are more negatively impacted by disasters than others and are at higher risk of severe weather hazards. We ask if there are demographic characteristics or geographic locations in common among people who are more prone to making protection decisions during tornado warnings to minimize economic costs. Results can help warning providers, such as the National Weather Service, direct resources and education to specific types of decision-makers or locations to improve sheltering decisions.
Abstract
Multiday severe weather outlooks can inform planning beyond the hour-to-day windows of warnings and watches. Outlooks can be complex to visualize, as they represent large-scale weather phenomena overlapping across several days at varying levels of uncertainty. Here, we present the results of a survey (n = 417) that explores how visual variables affect comprehension, inferences, and intended decision-making in a hypothetical scenario with the New Zealand MetService Severe Weather Outlook. We propose that visualization of the time window, forecast area, icons, and uncertainty can influence perceptions and decision-making based on four key findings. First, composite-style outlooks that depict multiple days of weather on one map can lead to biased perceptions of the forecast. When responding to questions about a day for which participants accurately reported there was no severe weather forecast, those who viewed a composite outlook reported higher likelihoods of severe weather occurring, higher levels of concern about travel, and higher likelihoods of changing plans compared to those who viewed outlooks that showed weather for each day on a separate map, suggesting that they perceived the forecast to underrepresent the likelihood of severe weather on that day. Second, presenting uncertainty in an extrinsic way (e.g., “low”) can lead to more accurate estimates of likelihood than intrinsic formats (e.g., hue variation). Third, shaded forecast areas may lead to higher levels of confidence in the forecast than outlined forecast areas. Fourth, inclusion of weather icons can improve comprehension in some conditions. The results demonstrate how visualization can affect decision-making about severe weather and support several evidence-based considerations for effective design of long-term forecasts.
Significance Statement
Severe weather outlook forecasts can be hard to clearly communicate because they show multiple weather patterns across multiple days and regions with varying uncertainty. The purpose of this study is to explore how visual elements of outlook design affect the way that people understand this complex content. We had three separate groups respond to the same series of questions while viewing different modified versions of the MetService Severe Weather Outlook in Aotearoa New Zealand and compared their responses. We find that the way the outlooks’ time window, forecast area, icons, and uncertainty are visualized can influence how people understand outlooks and make inferences and decisions about severe weather. We discuss how these influences may impact communication and action and present several evidence-based considerations for effective outlook design.
Abstract
Multiday severe weather outlooks can inform planning beyond the hour-to-day windows of warnings and watches. Outlooks can be complex to visualize, as they represent large-scale weather phenomena overlapping across several days at varying levels of uncertainty. Here, we present the results of a survey (n = 417) that explores how visual variables affect comprehension, inferences, and intended decision-making in a hypothetical scenario with the New Zealand MetService Severe Weather Outlook. We propose that visualization of the time window, forecast area, icons, and uncertainty can influence perceptions and decision-making based on four key findings. First, composite-style outlooks that depict multiple days of weather on one map can lead to biased perceptions of the forecast. When responding to questions about a day for which participants accurately reported there was no severe weather forecast, those who viewed a composite outlook reported higher likelihoods of severe weather occurring, higher levels of concern about travel, and higher likelihoods of changing plans compared to those who viewed outlooks that showed weather for each day on a separate map, suggesting that they perceived the forecast to underrepresent the likelihood of severe weather on that day. Second, presenting uncertainty in an extrinsic way (e.g., “low”) can lead to more accurate estimates of likelihood than intrinsic formats (e.g., hue variation). Third, shaded forecast areas may lead to higher levels of confidence in the forecast than outlined forecast areas. Fourth, inclusion of weather icons can improve comprehension in some conditions. The results demonstrate how visualization can affect decision-making about severe weather and support several evidence-based considerations for effective design of long-term forecasts.
Significance Statement
Severe weather outlook forecasts can be hard to clearly communicate because they show multiple weather patterns across multiple days and regions with varying uncertainty. The purpose of this study is to explore how visual elements of outlook design affect the way that people understand this complex content. We had three separate groups respond to the same series of questions while viewing different modified versions of the MetService Severe Weather Outlook in Aotearoa New Zealand and compared their responses. We find that the way the outlooks’ time window, forecast area, icons, and uncertainty are visualized can influence how people understand outlooks and make inferences and decisions about severe weather. We discuss how these influences may impact communication and action and present several evidence-based considerations for effective outlook design.
Abstract
Because flash drought is a relatively new phenomenon in drought research, defining the concept is critical for scientists and decision-makers. Having detrimental impacts on many sectors, it is important to have a consistent definition and understanding of flash drought, between experts and stakeholders, to provide early warning to the community. This study focuses on onset and progression of conditions and demonstrates the difference in flash drought identification for 15 events across six quantitative definitions of flash drought that use the U.S. Drought Monitor (USDM). Five flash drought events have been studied in the literature while 10 additional events have been perceived as flash drought by stakeholders. The results show that two of six definitions consistently capture the earliest onset of flash drought and include a large percent area in the identification. A qualitative analysis of management challenges and needs determined by stakeholders was completed using survey data. The results found that managing impacts and better communication and education were the top challenges and more data and enhanced and efficient communication as the top needs to better monitor, manage, and respond to flash droughts. The results demonstrate the need for assessing the characteristics of the definitions to enhance communication and monitoring strategies for large and small-scale flash droughts.
Significance Statement
The purpose of this study is to better understand how different numerical flash drought definitions characterize multiple flash drought events and how these definitions are useful in addressing the needs and challenges of stakeholders. This is important because definitions may capture different areas in flash droughts, which can impact how end users identify a flash drought. Further, this study uses events identified by the literature and by people familiar with drought monitoring. From these findings, definitions that capture flash drought earliest would help address the challenge of rapid onset and the need of quicker data. Further, definitions by sector would be beneficial to address the scale of impacts. This study identifies the importance of definitions for early warning systems.
Abstract
Because flash drought is a relatively new phenomenon in drought research, defining the concept is critical for scientists and decision-makers. Having detrimental impacts on many sectors, it is important to have a consistent definition and understanding of flash drought, between experts and stakeholders, to provide early warning to the community. This study focuses on onset and progression of conditions and demonstrates the difference in flash drought identification for 15 events across six quantitative definitions of flash drought that use the U.S. Drought Monitor (USDM). Five flash drought events have been studied in the literature while 10 additional events have been perceived as flash drought by stakeholders. The results show that two of six definitions consistently capture the earliest onset of flash drought and include a large percent area in the identification. A qualitative analysis of management challenges and needs determined by stakeholders was completed using survey data. The results found that managing impacts and better communication and education were the top challenges and more data and enhanced and efficient communication as the top needs to better monitor, manage, and respond to flash droughts. The results demonstrate the need for assessing the characteristics of the definitions to enhance communication and monitoring strategies for large and small-scale flash droughts.
Significance Statement
The purpose of this study is to better understand how different numerical flash drought definitions characterize multiple flash drought events and how these definitions are useful in addressing the needs and challenges of stakeholders. This is important because definitions may capture different areas in flash droughts, which can impact how end users identify a flash drought. Further, this study uses events identified by the literature and by people familiar with drought monitoring. From these findings, definitions that capture flash drought earliest would help address the challenge of rapid onset and the need of quicker data. Further, definitions by sector would be beneficial to address the scale of impacts. This study identifies the importance of definitions for early warning systems.
Abstract
Arctic communities are experienced with severe weather, but impacts can still be serious, particularly when the intensity or persistence of hazardous conditions is extreme. Such was the case for the community of Clyde River (Kangiqtugaapik), Nunavut, Canada, which experienced 33 blizzard days during winter 2021/22—likely the most at Clyde River since at least 1978/79. Blizzard conditions resulted from unusually frequent high winds rather than excessive snowfall. The most severe stretch included eight blizzard days over an 11-day period, with top wind gusts of 98 km h−1. Winds caused severe drifting, covering homes and blocking streets. Broken heavy equipment, including snow-clearing machines, compounded the impacts, leaving homes without essential services like water delivery and sewage pump-out for days. Residents reported the storms and resulting impacts as some of the worst in memory. The drifting and volume of snow, combined with the lack of available resources to manage it, obliged the community to declare a state of emergency. Projections of increased Arctic precipitation and extreme weather events points to the need for communities to have proper resources and supports, including preparedness and adaptation and mitigation strategies, so they can be better equipped to handle storm and blizzard impacts such as those experienced at Clyde River in the winter of 2021/22. Additional steps that can be implemented to better support and prepare communities include investing in preparedness planning, expanded and enhanced weather information and services, community land-based programming to transfer Inuit knowledge and skills, assessing the usefulness of current forecasts, and new approaches to community planning.
Significance Statement
In this study, we consider the winter of 2021/22, during which the community of Clyde River (Kangiqtugaapik), Nunavut experienced 33 days with blizzard conditions—more than any other year since at least 1978/79. Blizzards are characterized by strong winds and blowing snow. Low visibility impedes travel, and drifting snow blocks roads and can bury equipment and buildings. In this case, broken snow-clearing equipment and other infrastructure challenges also hampered the community’s ability to respond, and residents went days without essential services. Several studies suggest that extreme winds will become more common in the Baffin Bay region in the future. This study demonstrates the need for proper resourcing of communities for preparedness, response, and adaptation strategies, especially with the possibility of extreme winter weather becoming more common.
Abstract
Arctic communities are experienced with severe weather, but impacts can still be serious, particularly when the intensity or persistence of hazardous conditions is extreme. Such was the case for the community of Clyde River (Kangiqtugaapik), Nunavut, Canada, which experienced 33 blizzard days during winter 2021/22—likely the most at Clyde River since at least 1978/79. Blizzard conditions resulted from unusually frequent high winds rather than excessive snowfall. The most severe stretch included eight blizzard days over an 11-day period, with top wind gusts of 98 km h−1. Winds caused severe drifting, covering homes and blocking streets. Broken heavy equipment, including snow-clearing machines, compounded the impacts, leaving homes without essential services like water delivery and sewage pump-out for days. Residents reported the storms and resulting impacts as some of the worst in memory. The drifting and volume of snow, combined with the lack of available resources to manage it, obliged the community to declare a state of emergency. Projections of increased Arctic precipitation and extreme weather events points to the need for communities to have proper resources and supports, including preparedness and adaptation and mitigation strategies, so they can be better equipped to handle storm and blizzard impacts such as those experienced at Clyde River in the winter of 2021/22. Additional steps that can be implemented to better support and prepare communities include investing in preparedness planning, expanded and enhanced weather information and services, community land-based programming to transfer Inuit knowledge and skills, assessing the usefulness of current forecasts, and new approaches to community planning.
Significance Statement
In this study, we consider the winter of 2021/22, during which the community of Clyde River (Kangiqtugaapik), Nunavut experienced 33 days with blizzard conditions—more than any other year since at least 1978/79. Blizzards are characterized by strong winds and blowing snow. Low visibility impedes travel, and drifting snow blocks roads and can bury equipment and buildings. In this case, broken snow-clearing equipment and other infrastructure challenges also hampered the community’s ability to respond, and residents went days without essential services. Several studies suggest that extreme winds will become more common in the Baffin Bay region in the future. This study demonstrates the need for proper resourcing of communities for preparedness, response, and adaptation strategies, especially with the possibility of extreme winter weather becoming more common.
Abstract
This study quantified greenhouse gas emissions from indirect activities along the whole value chain of supermarket retailing to derive mitigation measures. Both direct and indirect greenhouse gas emission sources of a supermarket retailing value chain were identified and calculated using the national guidelines for estimating the carbon footprint for organizations, based on a total area of 13 248 m2 and operating 12 h per day. A scoring matrix was applied that considered the magnitude of emissions, the level of influence, and the risks or opportunities associated with business operations. The scoring results indicated a major contribution from value chain activities that should be included in any greenhouse gas analysis. The calculation revealed that the greenhouse gas emissions from the value chain activities were 33 784 t CO2 emitted yr−1 or 94% of total emissions. The key contributors were linked to the production of purchased goods and the management of food waste. Thus, value chain activities should not be overlooked in developing efficient greenhouse gas management strategies. Furthermore, purchased products and services carrying a carbon-reduction label should be given priority, and the application of artificial intelligence and innovation could be considered to reduce the amount of food waste from expired goods.
Abstract
This study quantified greenhouse gas emissions from indirect activities along the whole value chain of supermarket retailing to derive mitigation measures. Both direct and indirect greenhouse gas emission sources of a supermarket retailing value chain were identified and calculated using the national guidelines for estimating the carbon footprint for organizations, based on a total area of 13 248 m2 and operating 12 h per day. A scoring matrix was applied that considered the magnitude of emissions, the level of influence, and the risks or opportunities associated with business operations. The scoring results indicated a major contribution from value chain activities that should be included in any greenhouse gas analysis. The calculation revealed that the greenhouse gas emissions from the value chain activities were 33 784 t CO2 emitted yr−1 or 94% of total emissions. The key contributors were linked to the production of purchased goods and the management of food waste. Thus, value chain activities should not be overlooked in developing efficient greenhouse gas management strategies. Furthermore, purchased products and services carrying a carbon-reduction label should be given priority, and the application of artificial intelligence and innovation could be considered to reduce the amount of food waste from expired goods.
