Browse
Abstract
In recent decades, changes in precipitation, temperature, and air circulation patterns have led to increases in the occurrences of extreme weather events. These events can have devastating effects on communities causing destruction to property and croplands, as well as negative impacts on public health. As changes in the climate are projected to continue throughout the remainder of the twenty-first century, the ability for a community to plan for extreme weather events is essential to its survival. In this paper, we introduce a new index for examining the potential impacts of climate extremes on community resilience throughout the conterminous United States at the county level. We use an established disaster resilience index (baseline resilience indicators for communities) together with a revised version of the U.S. climate extremes index to create a combined measure of climate resilience—the climate extremes resilience index (CERI). To demonstrate the index, we test it on the 2021 Pacific Northwest heat wave, a 1000-yr weather event made 150 times as likely by climate change. To promote the use of the index, we also introduce a Google Earth Engine web app to calculate and map the CERI for the CONUS. By developing a web application for calculating the CERI, we expand the use of climate-resilience indices beyond theoretical applications. We anticipate that this tool and the CERI could be useful for policy makers to plan for climate-related disasters, as well as help the public with understanding and visualizing the impacts of extreme climatic events.
Abstract
In recent decades, changes in precipitation, temperature, and air circulation patterns have led to increases in the occurrences of extreme weather events. These events can have devastating effects on communities causing destruction to property and croplands, as well as negative impacts on public health. As changes in the climate are projected to continue throughout the remainder of the twenty-first century, the ability for a community to plan for extreme weather events is essential to its survival. In this paper, we introduce a new index for examining the potential impacts of climate extremes on community resilience throughout the conterminous United States at the county level. We use an established disaster resilience index (baseline resilience indicators for communities) together with a revised version of the U.S. climate extremes index to create a combined measure of climate resilience—the climate extremes resilience index (CERI). To demonstrate the index, we test it on the 2021 Pacific Northwest heat wave, a 1000-yr weather event made 150 times as likely by climate change. To promote the use of the index, we also introduce a Google Earth Engine web app to calculate and map the CERI for the CONUS. By developing a web application for calculating the CERI, we expand the use of climate-resilience indices beyond theoretical applications. We anticipate that this tool and the CERI could be useful for policy makers to plan for climate-related disasters, as well as help the public with understanding and visualizing the impacts of extreme climatic events.
Abstract
Domestic climate migration is likely to increase in the future, but we know little about public perceptions and attitudes about climate migrants and migration. Understanding how perceptions and attitudes are formed is a critical task in assessing public support for assistance policies and developing effective messaging campaigns. In this paper, we aim to better understand how the U.S. public perceives domestic climate migrants. We use novel survey data to identify the relationship between climate change risk perceptions and awareness of “climate migrants,” belief that domestic climate migration is currently happening in the United States, perceived voluntariness of domestic climate migrant relocation, and support for the development of assistance programs for domestic climate migrants. We utilize a large, nationally representative panel of U.S. adults (N = 4074) collected over three waves in 2022. We find that climate change risk perceptions and perceptions of whether migration is voluntary are key drivers of perceptions and attitudes toward domestic climate migrants. We provide key suggestions to policy makers and decision-makers to improve outcomes for host and migrant communities.
Significance Statement
This study illuminates factors that influence the how the public forms perceptions and attitudes about domestic climate migrants in the United States. For the first time, we offer insight into the drivers of public opinion toward domestic climate migrants and migration. Our results indicate that the various perceptions of climate migrants are largely driven by preexisting climate change risk perceptions and respondent characteristics. Our findings create a new connection with the existing literature on climate change risk perceptions and offer an opportunity for decision-makers and policy makers to create effective messaging campaigns on topics related to domestic climate migration in the United States.
Abstract
Domestic climate migration is likely to increase in the future, but we know little about public perceptions and attitudes about climate migrants and migration. Understanding how perceptions and attitudes are formed is a critical task in assessing public support for assistance policies and developing effective messaging campaigns. In this paper, we aim to better understand how the U.S. public perceives domestic climate migrants. We use novel survey data to identify the relationship between climate change risk perceptions and awareness of “climate migrants,” belief that domestic climate migration is currently happening in the United States, perceived voluntariness of domestic climate migrant relocation, and support for the development of assistance programs for domestic climate migrants. We utilize a large, nationally representative panel of U.S. adults (N = 4074) collected over three waves in 2022. We find that climate change risk perceptions and perceptions of whether migration is voluntary are key drivers of perceptions and attitudes toward domestic climate migrants. We provide key suggestions to policy makers and decision-makers to improve outcomes for host and migrant communities.
Significance Statement
This study illuminates factors that influence the how the public forms perceptions and attitudes about domestic climate migrants in the United States. For the first time, we offer insight into the drivers of public opinion toward domestic climate migrants and migration. Our results indicate that the various perceptions of climate migrants are largely driven by preexisting climate change risk perceptions and respondent characteristics. Our findings create a new connection with the existing literature on climate change risk perceptions and offer an opportunity for decision-makers and policy makers to create effective messaging campaigns on topics related to domestic climate migration in the United States.
Abstract
During peak disease transmission in 2021, the compounding threat posed by the pandemic and hurricane season required coastal states to understand evacuation behaviors during a major hurricane to inform the planning process. While research relating to hurricane evacuation behavior and perceptions of risk has increased since the start of the pandemic, there is minimal understanding of how perceptions have changed now the COVID-19 vaccine is available. A total of 1075 individuals across seven U.S. coastal states participated in a study on evacuation intentions postvaccine availability. Findings revealed that most survey participants (50.9%) preferred to stay home if a major hurricane threatened their area, and only 3.9% would evacuate to a public shelter. Approximately half (56.2%) of individuals viewed the risk of being in a shelter as more dangerous than enduring hurricane hazards. When considering shelter use, nearly half of respondents (49.4%) stated they would evacuate to a shelter before the pandemic; now, only one-third (34.3%) would consider evacuating to a shelter during the pandemic. Statistically significant findings include the relationship between those who lived in evacuation zones A or B (25.5%) and the choice to shelter in place at home (40.5%) or evacuate to a hotel (36.9%). There was a statistically significant relationship between the level of education and choosing to evacuate to a hotel. Additionally, the influence of pet ownership on evacuation decision-making was found to be statistically significant. Officials can use the results of this study to strengthen community preparedness and planning strategies across diverse populations.
Abstract
During peak disease transmission in 2021, the compounding threat posed by the pandemic and hurricane season required coastal states to understand evacuation behaviors during a major hurricane to inform the planning process. While research relating to hurricane evacuation behavior and perceptions of risk has increased since the start of the pandemic, there is minimal understanding of how perceptions have changed now the COVID-19 vaccine is available. A total of 1075 individuals across seven U.S. coastal states participated in a study on evacuation intentions postvaccine availability. Findings revealed that most survey participants (50.9%) preferred to stay home if a major hurricane threatened their area, and only 3.9% would evacuate to a public shelter. Approximately half (56.2%) of individuals viewed the risk of being in a shelter as more dangerous than enduring hurricane hazards. When considering shelter use, nearly half of respondents (49.4%) stated they would evacuate to a shelter before the pandemic; now, only one-third (34.3%) would consider evacuating to a shelter during the pandemic. Statistically significant findings include the relationship between those who lived in evacuation zones A or B (25.5%) and the choice to shelter in place at home (40.5%) or evacuate to a hotel (36.9%). There was a statistically significant relationship between the level of education and choosing to evacuate to a hotel. Additionally, the influence of pet ownership on evacuation decision-making was found to be statistically significant. Officials can use the results of this study to strengthen community preparedness and planning strategies across diverse populations.
Abstract
Climate change has negatively affected agricultural productivity in Indonesia. This study conducted a bibliometric analysis of the literature on soil salinity caused by climate change, discussed the impact of soil salinity on Indonesian agriculture, examined various strategies for adaptation to salinity, and delivered some ideas for future research. An analysis of 39 identified Scopus articles related to farmers’ vulnerability, adaptation, and practices was carried out. This study was performed in November 2022 and employed Bibliometrix R package and VOSviewer software. Findings show that salinity has left Indonesia’s agriculture vulnerable to reduced food production, especially for small-scale farmers losing crop yields and land. Various adaptation measures have been initiated, such as restoring soil fertility and using saline-resistant varieties. Irrigation facilities improvements have also been carried out to reduce the risks of soil salinity expansion. Farmers also try social action measures, such as selling assets, borrowing money for daily needs, and even changing jobs. However, for farmers to survive and sustain their businesses, any such measures need to produce satisfactory results. A review of the existing literature reveals a lack of soil salinity studies in Indonesia, which simultaneously points to research gaps not only on the issue of the impact of salinity on income and the vulnerability of small farmers but also on the development of adaptation strategies to address salinity due to climate change.
Significance Statement
Soil salinization caused by climate change is a disastrous problem in Indonesia’s coastal areas that presents a major challenge to the productivity of rice agriculture and difficulties in addressing sustainable food security. To provide researchers with a clear understanding of the current emphasis and future trends in climate change–induced salinity research, systematically analyzing the relevant literature in the existing research area is necessary. The bibliometric analysis in this study shows that research on salinity due to climate change in Indonesia still needs to be completed. Further comprehensive studies to find a focus for managing coastal soil salinity are urgently required to reduce vulnerability and increase adaptation to salinity due to climate change.
Abstract
Climate change has negatively affected agricultural productivity in Indonesia. This study conducted a bibliometric analysis of the literature on soil salinity caused by climate change, discussed the impact of soil salinity on Indonesian agriculture, examined various strategies for adaptation to salinity, and delivered some ideas for future research. An analysis of 39 identified Scopus articles related to farmers’ vulnerability, adaptation, and practices was carried out. This study was performed in November 2022 and employed Bibliometrix R package and VOSviewer software. Findings show that salinity has left Indonesia’s agriculture vulnerable to reduced food production, especially for small-scale farmers losing crop yields and land. Various adaptation measures have been initiated, such as restoring soil fertility and using saline-resistant varieties. Irrigation facilities improvements have also been carried out to reduce the risks of soil salinity expansion. Farmers also try social action measures, such as selling assets, borrowing money for daily needs, and even changing jobs. However, for farmers to survive and sustain their businesses, any such measures need to produce satisfactory results. A review of the existing literature reveals a lack of soil salinity studies in Indonesia, which simultaneously points to research gaps not only on the issue of the impact of salinity on income and the vulnerability of small farmers but also on the development of adaptation strategies to address salinity due to climate change.
Significance Statement
Soil salinization caused by climate change is a disastrous problem in Indonesia’s coastal areas that presents a major challenge to the productivity of rice agriculture and difficulties in addressing sustainable food security. To provide researchers with a clear understanding of the current emphasis and future trends in climate change–induced salinity research, systematically analyzing the relevant literature in the existing research area is necessary. The bibliometric analysis in this study shows that research on salinity due to climate change in Indonesia still needs to be completed. Further comprehensive studies to find a focus for managing coastal soil salinity are urgently required to reduce vulnerability and increase adaptation to salinity due to climate change.
Abstract
Flash droughts, characterized by rapid onset and intensification, are increasingly occurring as a consequence of climate change and rising temperatures. However, existing hydrometeorological definitions fail to encompass the full range of flash droughts, many of which have distinct local physical attributes. Consequently, these events often go undetected or unforecast in generic global flash drought assessments and are underrepresented in research. To address this gap, we conducted a comprehensive survey to gather information on local nomenclature, characteristics, and impacts of flash droughts worldwide. The survey revealed the widespread occurrence of these phenomena, highlighting their underresearched nature. By analyzing case studies, through literature review often in local languages to unearth elusive studies, we identified five different types of flash droughts based on their specific characteristics. Our study aims to increase awareness about the complexity and diverse impacts of flash droughts, emphasizing the importance of considering regional contexts and the vulnerability of affected populations. The reported impacts underscore the need for better integration of all flash drought types in drought research, monitoring, and management. Monitoring a combination of indicators is crucial for timely detection and response to this emerging and escalating threat.
Significance Statement
This study aims to better understand flash droughts worldwide and their varying characteristics and impacts. We surveyed the experiences of people affected by flash droughts and then examined a wide range of literature, including non-English and nonacademic sources. This helped us understand how flash droughts can differ from those commonly studied in the United States and China. We identified and described five types of flash droughts, some of which may not be detected by current drought measurement methods. It is crucial to include all types of flash droughts in drought monitoring systems and management plans, as they are expected to become more common due to global warming. We can then better prepare for and reduce the impacts of this growing threat.
Abstract
Flash droughts, characterized by rapid onset and intensification, are increasingly occurring as a consequence of climate change and rising temperatures. However, existing hydrometeorological definitions fail to encompass the full range of flash droughts, many of which have distinct local physical attributes. Consequently, these events often go undetected or unforecast in generic global flash drought assessments and are underrepresented in research. To address this gap, we conducted a comprehensive survey to gather information on local nomenclature, characteristics, and impacts of flash droughts worldwide. The survey revealed the widespread occurrence of these phenomena, highlighting their underresearched nature. By analyzing case studies, through literature review often in local languages to unearth elusive studies, we identified five different types of flash droughts based on their specific characteristics. Our study aims to increase awareness about the complexity and diverse impacts of flash droughts, emphasizing the importance of considering regional contexts and the vulnerability of affected populations. The reported impacts underscore the need for better integration of all flash drought types in drought research, monitoring, and management. Monitoring a combination of indicators is crucial for timely detection and response to this emerging and escalating threat.
Significance Statement
This study aims to better understand flash droughts worldwide and their varying characteristics and impacts. We surveyed the experiences of people affected by flash droughts and then examined a wide range of literature, including non-English and nonacademic sources. This helped us understand how flash droughts can differ from those commonly studied in the United States and China. We identified and described five types of flash droughts, some of which may not be detected by current drought measurement methods. It is crucial to include all types of flash droughts in drought monitoring systems and management plans, as they are expected to become more common due to global warming. We can then better prepare for and reduce the impacts of this growing threat.
Abstract
National Weather Service (NWS) forecasters have many roles and responsibilities, including communication with core partners throughout the forecast and warning process to ensure that the information they are providing is relevant, understandable, and actionable. Although the NWS communicates to many groups, members of the emergency management community are among the most critical partners. However, little is known about the diverse population of emergency managers (EMs) and how they receive, process, and use forecast information. The Extreme Weather and Emergency Management Survey (WxEM) aims to fill this knowledge gap by 1) building a nationwide panel of EMs and 2) fielding routine surveys that include questions of relevance to NWS operations. The panel was built by creating a database with contact information from more than 4000 EMs across the country. An enrollment survey was sent to the list, and over 700 EMs agreed to participate in the project. Following enrollment, WxEM panelists receive surveys three–four times per year that address how EMs use NWS forecast information. These surveys cover a variety of subjects, with the goal of working with other researchers to develop surveys that address their research needs. By collaborating with other research groups to design short, focused surveys, the WxEM project will reduce the research burden on EMs and, at the same time, increase the quality and comparability of research data in the weather enterprise. The results will be shared with the NWS and the research community, and all data gathered from these surveys will be publicly available.
Significance Statement
The Extreme Weather and Emergency Management Survey aims to better understand how emergency managers use National Weather Service (NWS) forecast information via a series of surveys regularly distributed to a panel of emergency managers across the country. By collaborating with other researchers, these surveys will cover broad topics and should limit the number of participation requests sent to emergency managers. Results will be distributed to participants, researchers, and NWS forecasters. All data will be publicly available.
Abstract
National Weather Service (NWS) forecasters have many roles and responsibilities, including communication with core partners throughout the forecast and warning process to ensure that the information they are providing is relevant, understandable, and actionable. Although the NWS communicates to many groups, members of the emergency management community are among the most critical partners. However, little is known about the diverse population of emergency managers (EMs) and how they receive, process, and use forecast information. The Extreme Weather and Emergency Management Survey (WxEM) aims to fill this knowledge gap by 1) building a nationwide panel of EMs and 2) fielding routine surveys that include questions of relevance to NWS operations. The panel was built by creating a database with contact information from more than 4000 EMs across the country. An enrollment survey was sent to the list, and over 700 EMs agreed to participate in the project. Following enrollment, WxEM panelists receive surveys three–four times per year that address how EMs use NWS forecast information. These surveys cover a variety of subjects, with the goal of working with other researchers to develop surveys that address their research needs. By collaborating with other research groups to design short, focused surveys, the WxEM project will reduce the research burden on EMs and, at the same time, increase the quality and comparability of research data in the weather enterprise. The results will be shared with the NWS and the research community, and all data gathered from these surveys will be publicly available.
Significance Statement
The Extreme Weather and Emergency Management Survey aims to better understand how emergency managers use National Weather Service (NWS) forecast information via a series of surveys regularly distributed to a panel of emergency managers across the country. By collaborating with other researchers, these surveys will cover broad topics and should limit the number of participation requests sent to emergency managers. Results will be distributed to participants, researchers, and NWS forecasters. All data will be publicly available.
Abstract
Weather index insurance (WII) has long been advertised as a viable alternative to crop yield insurance. WII products were first developed to assist climate-vulnerable farmers from developing countries where establishing a well-structured crop insurance market is expressively difficult due to the poor transport infrastructure and the prevalence of sparsely distributed small-scale farms. In Brazil, the semiarid region stands out as the one that concentrates the ideal conditions for the implementation of a WII product since it houses thousands of climate-vulnerable farmers. With this in mind, we designed and priced a WII product for farmers from the semiarid region of Brazil and posteriorly investigated its risk efficiency. To do so, we first investigated crop yield responses to aridity, enabling the selection of locations for which the WII product was posteriorly assessed. Second, we grouped selected locations into specific contracts according to geographical proximity and evaluated each of these contracts to attest the risk efficiency of the proposed WII product using the method of stochastic efficiency with respect to a function (SERF), which identifies utility efficient alternatives for a range of risk attitudes. Our results show that the WII product may be effective in protecting farmers from adverse variations in production revenue, possibly being attractive for utility-maximizer farmers that are sufficiently risk averse.
Abstract
Weather index insurance (WII) has long been advertised as a viable alternative to crop yield insurance. WII products were first developed to assist climate-vulnerable farmers from developing countries where establishing a well-structured crop insurance market is expressively difficult due to the poor transport infrastructure and the prevalence of sparsely distributed small-scale farms. In Brazil, the semiarid region stands out as the one that concentrates the ideal conditions for the implementation of a WII product since it houses thousands of climate-vulnerable farmers. With this in mind, we designed and priced a WII product for farmers from the semiarid region of Brazil and posteriorly investigated its risk efficiency. To do so, we first investigated crop yield responses to aridity, enabling the selection of locations for which the WII product was posteriorly assessed. Second, we grouped selected locations into specific contracts according to geographical proximity and evaluated each of these contracts to attest the risk efficiency of the proposed WII product using the method of stochastic efficiency with respect to a function (SERF), which identifies utility efficient alternatives for a range of risk attitudes. Our results show that the WII product may be effective in protecting farmers from adverse variations in production revenue, possibly being attractive for utility-maximizer farmers that are sufficiently risk averse.
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
This study used a model to calculate the proportional drop for every vehicle class based on 266 climate patterns consisting of seven temperature groups and varied snowfalls. The winter traffic models use weigh-in-motion (WIM) traffic collected on the commuter roadway for 5 years. The marginal impact and combined effect of meteorological conditions on the proportional decrease in winter traffic volume are evaluated. The predicted percentage decrease in traffic for all three vehicle classes increases as temperature decreases and snowfall increases. Mathematical functions are fitted for the decreased patterns for the considered vehicle type. Roadway authorities may utilize traffic percentage decrease to identify weather-related traffic changes when planning winter highway operation and maintenance.
Abstract
This study used a model to calculate the proportional drop for every vehicle class based on 266 climate patterns consisting of seven temperature groups and varied snowfalls. The winter traffic models use weigh-in-motion (WIM) traffic collected on the commuter roadway for 5 years. The marginal impact and combined effect of meteorological conditions on the proportional decrease in winter traffic volume are evaluated. The predicted percentage decrease in traffic for all three vehicle classes increases as temperature decreases and snowfall increases. Mathematical functions are fitted for the decreased patterns for the considered vehicle type. Roadway authorities may utilize traffic percentage decrease to identify weather-related traffic changes when planning winter highway operation and maintenance.
