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Abstract
As a significant detriment to physical and mental health, millions of motor vehicle crashes occur in the United States each year, with approximately 23% of these crashes linked to adverse weather conditions. This study builds upon a strong knowledge base to provide a deeper understanding of how rainfall intensity influences relative crash risk. Gridded precipitation and temperature data were aggregated to the county level and analyzed alongside motor vehicle crash data for all 146 counties in the Carolinas (North Carolina and South Carolina) for the period 2003–19. A matched-pair analysis routine linked unique time steps of rainfall (daily, 6-h, and hourly) to corresponding dry periods to evaluate relative crash risk across each state. Risk estimates were calculated on the basis of precipitation thresholds (light, moderate, heavy, and very heavy). Results indicate a statistically significant increase in crash risk during periods of rainfall in the Carolinas. As a baseline, the relative risk of experiencing a crash increases by 11.6% during days with accumulating rainfall and as much as 81.0% during heavy rainfall events over a 6-h period. In general, estimates of risk increase relative to the intensity of the rainfall event and the temporal delineation of the matched-pair routine. However, these relationships have unique spatiotemporal patterns indicating that, although hourly risk estimates may be beneficial for urban counties, daily relative risk estimates may be the only way to accurately capture risk in rural areas.
Significance Statement
Each year, more than 1 000 000 motor vehicle crashes in the United States are linked to adverse weather conditions in police reports, with rainfall events being among the largest contributors to increased crash risk. In this study, crash frequencies are evaluated to better understand how the intensity of rainfall events (light vs heavy) influences the risk of experiencing a collision on roadways in North Carolina and South Carolina. The results of statistical analyses revealed that risk increases significantly during rainfall events in both states and that the risk of experiencing a crash is highest during the heaviest rainfall events. However, even during light precipitation events, the risk of experiencing a crash is significantly higher than when driving during dry conditions. These results are helpful to transportation stakeholders and emergency responders in the hope of reducing crash risk in our changing climate.
Abstract
As a significant detriment to physical and mental health, millions of motor vehicle crashes occur in the United States each year, with approximately 23% of these crashes linked to adverse weather conditions. This study builds upon a strong knowledge base to provide a deeper understanding of how rainfall intensity influences relative crash risk. Gridded precipitation and temperature data were aggregated to the county level and analyzed alongside motor vehicle crash data for all 146 counties in the Carolinas (North Carolina and South Carolina) for the period 2003–19. A matched-pair analysis routine linked unique time steps of rainfall (daily, 6-h, and hourly) to corresponding dry periods to evaluate relative crash risk across each state. Risk estimates were calculated on the basis of precipitation thresholds (light, moderate, heavy, and very heavy). Results indicate a statistically significant increase in crash risk during periods of rainfall in the Carolinas. As a baseline, the relative risk of experiencing a crash increases by 11.6% during days with accumulating rainfall and as much as 81.0% during heavy rainfall events over a 6-h period. In general, estimates of risk increase relative to the intensity of the rainfall event and the temporal delineation of the matched-pair routine. However, these relationships have unique spatiotemporal patterns indicating that, although hourly risk estimates may be beneficial for urban counties, daily relative risk estimates may be the only way to accurately capture risk in rural areas.
Significance Statement
Each year, more than 1 000 000 motor vehicle crashes in the United States are linked to adverse weather conditions in police reports, with rainfall events being among the largest contributors to increased crash risk. In this study, crash frequencies are evaluated to better understand how the intensity of rainfall events (light vs heavy) influences the risk of experiencing a collision on roadways in North Carolina and South Carolina. The results of statistical analyses revealed that risk increases significantly during rainfall events in both states and that the risk of experiencing a crash is highest during the heaviest rainfall events. However, even during light precipitation events, the risk of experiencing a crash is significantly higher than when driving during dry conditions. These results are helpful to transportation stakeholders and emergency responders in the hope of reducing crash risk in our changing climate.
Abstract
The changes in climatic conditions and their associated impacts are contributing to a worsening of existing gender inequalities and a heightening of women’s socioeconomic vulnerabilities in South Africa. Using data collected by research methods inspired by the tradition of participatory appraisals, we systematically discuss the impacts of climate change on marginalized women and the ways in which they are actively responding to climate challenges and building their adaptive capacity and resilience in the urban areas of KwaZulu-Natal, South Africa. We argue that changes in climate have both direct and indirect negative impacts on women’s livelihoods and well-being. Less than one-half (37%) of the women reported implementing locally developed coping mechanisms to minimize the impacts of climate-related events, whereas 63% reported lacking any form of formal safety nets to deploy and reduce the impacts of climate-induced shocks and stresses. The lack of proactive and gender-sensitive local climate change policies and strategies creates socioeconomic and political barriers that limit the meaningful participation of women in issues that affect them and marginalize them in the climate change discourses and decision-making processes, thereby hampering their efforts to adapt and reduce existing vulnerabilities. Thus, we advocate for the creation of an enabling environment to develop and adopt progendered, cost-effective, transformative, and sustainable climate change policies and adaptation strategies that are responsive to the needs of vulnerable groups (women) of people in society. This will serve to build their adaptive capacity and resilience to climate variability and climate change–related risks and hazards.
Abstract
The changes in climatic conditions and their associated impacts are contributing to a worsening of existing gender inequalities and a heightening of women’s socioeconomic vulnerabilities in South Africa. Using data collected by research methods inspired by the tradition of participatory appraisals, we systematically discuss the impacts of climate change on marginalized women and the ways in which they are actively responding to climate challenges and building their adaptive capacity and resilience in the urban areas of KwaZulu-Natal, South Africa. We argue that changes in climate have both direct and indirect negative impacts on women’s livelihoods and well-being. Less than one-half (37%) of the women reported implementing locally developed coping mechanisms to minimize the impacts of climate-related events, whereas 63% reported lacking any form of formal safety nets to deploy and reduce the impacts of climate-induced shocks and stresses. The lack of proactive and gender-sensitive local climate change policies and strategies creates socioeconomic and political barriers that limit the meaningful participation of women in issues that affect them and marginalize them in the climate change discourses and decision-making processes, thereby hampering their efforts to adapt and reduce existing vulnerabilities. Thus, we advocate for the creation of an enabling environment to develop and adopt progendered, cost-effective, transformative, and sustainable climate change policies and adaptation strategies that are responsive to the needs of vulnerable groups (women) of people in society. This will serve to build their adaptive capacity and resilience to climate variability and climate change–related risks and hazards.
Abstract
Broadcast meteorologists play an essential role in communicating severe weather information from the National Weather Service to the public. Because of their importance, researchers incorporated broadcast meteorologists in the development of probabilistic hazard information (PHI) in NOAA’s Hazardous Weather Testbed. As part of Forecasting a Continuum of Environmental Threats (FACETs), PHI is meant to bring additional context to severe weather warnings through the inclusion of probability information. Since this information represents a shift in the current paradigm of solely deterministic NWS warnings, understanding end user needs is paramount to create usable and accessible products that result in their intended outcome to serve the public. This paper outlines the establishment of “K-Probabilistic Hazard Information Television” (KPHI-TV), a research infrastructure under the Hazardous Weather Testbed created to study broadcast meteorologists and PHI. A description of the design of KPHI-TV and methods used by researchers are presented, including displaced real-time cases and semistructured interviews. Researchers completed an analysis of the 2018 experiment, using a quantitative analysis of television coverage decisions with PHI, and a thematic analysis of semistructured interviews. Results indicate that no clear probabilistic decision thresholds for PHI emerged among the participants. Other themes arose, including the relationship between PHI and the warning polygon, and communication challenges. Overall, broadcast participants preferred a system that includes PHI over the warning polygon alone, but raised other concerns, suggesting iterative research in the design and implementation of PHI should continue.
Significance Statement
Broadcast meteorologists are the primary source of severe weather warning information for the U.S. public. As a result, researchers at NOAA’s National Severe Storms Laboratory and the Cooperative Institute for Mesoscale Meteorological Studies developed a mock television studio to allow broadcast meteorologists to use and communicate experimental products “on air” as part of the research-and-development process. Feedback provided by broadcasters is incorporated into products through an iterative process. Since 2016, 18 broadcasters have tested probabilistic hazard information at the warning time scale (0–1 h) for severe wind and hail, tornadoes, and lightning.
Abstract
Broadcast meteorologists play an essential role in communicating severe weather information from the National Weather Service to the public. Because of their importance, researchers incorporated broadcast meteorologists in the development of probabilistic hazard information (PHI) in NOAA’s Hazardous Weather Testbed. As part of Forecasting a Continuum of Environmental Threats (FACETs), PHI is meant to bring additional context to severe weather warnings through the inclusion of probability information. Since this information represents a shift in the current paradigm of solely deterministic NWS warnings, understanding end user needs is paramount to create usable and accessible products that result in their intended outcome to serve the public. This paper outlines the establishment of “K-Probabilistic Hazard Information Television” (KPHI-TV), a research infrastructure under the Hazardous Weather Testbed created to study broadcast meteorologists and PHI. A description of the design of KPHI-TV and methods used by researchers are presented, including displaced real-time cases and semistructured interviews. Researchers completed an analysis of the 2018 experiment, using a quantitative analysis of television coverage decisions with PHI, and a thematic analysis of semistructured interviews. Results indicate that no clear probabilistic decision thresholds for PHI emerged among the participants. Other themes arose, including the relationship between PHI and the warning polygon, and communication challenges. Overall, broadcast participants preferred a system that includes PHI over the warning polygon alone, but raised other concerns, suggesting iterative research in the design and implementation of PHI should continue.
Significance Statement
Broadcast meteorologists are the primary source of severe weather warning information for the U.S. public. As a result, researchers at NOAA’s National Severe Storms Laboratory and the Cooperative Institute for Mesoscale Meteorological Studies developed a mock television studio to allow broadcast meteorologists to use and communicate experimental products “on air” as part of the research-and-development process. Feedback provided by broadcasters is incorporated into products through an iterative process. Since 2016, 18 broadcasters have tested probabilistic hazard information at the warning time scale (0–1 h) for severe wind and hail, tornadoes, and lightning.
Abstract
This study examines the influences of state and local political affiliation and local exposure to weather-related impacts on local government climate change adaptation efforts in 88 U.S. cities. Although climate adaptation takes place when cities replace critical infrastructure damaged by severe weather events, little is known about the influence of political affiliation and severe weather events on climate adaptation in a broader sense. Using multiple linear regression models, this study analyzes variations in local government climate adaptation efforts as a function of local gross domestic product (as a control variable), historical weather-related factors [i.e., number of extreme weather events, weather-related economic impact due to property damage, and weather-related human impact (injuries and fatalities)], and state and local political affiliation. The findings of this study indicate that local political affiliation significantly influences local government climate adaptation efforts; however, state political affiliation does not. Further, local weather-related impacts do not appear to affect the likelihood of local government to engage in climate adaptation efforts, even when accounting for potential interactions with local political affiliation. These results support the hypothesis that local political affiliation is a strong and robust predictor of local climate adaptation in U.S. cities. This study contributes to literature aimed at addressing the widely acknowledged need for understanding key barriers to U.S. climate adaptation, as well as the role of politics in moderating climate action.
Abstract
This study examines the influences of state and local political affiliation and local exposure to weather-related impacts on local government climate change adaptation efforts in 88 U.S. cities. Although climate adaptation takes place when cities replace critical infrastructure damaged by severe weather events, little is known about the influence of political affiliation and severe weather events on climate adaptation in a broader sense. Using multiple linear regression models, this study analyzes variations in local government climate adaptation efforts as a function of local gross domestic product (as a control variable), historical weather-related factors [i.e., number of extreme weather events, weather-related economic impact due to property damage, and weather-related human impact (injuries and fatalities)], and state and local political affiliation. The findings of this study indicate that local political affiliation significantly influences local government climate adaptation efforts; however, state political affiliation does not. Further, local weather-related impacts do not appear to affect the likelihood of local government to engage in climate adaptation efforts, even when accounting for potential interactions with local political affiliation. These results support the hypothesis that local political affiliation is a strong and robust predictor of local climate adaptation in U.S. cities. This study contributes to literature aimed at addressing the widely acknowledged need for understanding key barriers to U.S. climate adaptation, as well as the role of politics in moderating climate action.
Abstract
One commonly proposed strategy for reducing urban air pollution is transitioning from single-occupancy vehicle (SOV) travel to alternative transportation (AT) modes, such as walking, biking, and using public transportation. While many studies have addressed the benefits of switching from SOV to AT, fewer studies have examined the potential for negative outcomes due to increased exposure to heat when using AT modes. This work uses Maricopa County, Arizona, home to the metropolitan Phoenix area, as a test case to examine the potential impacts of heat on commuters who utilize AT. First, regions of the county with the most candidates for switching from SOV to AT were identified and used to develop an AT candidate index. This index was based on both the current rates of AT use and the number of SOV commuters with the shortest commuting times in the dataset (<10 min). Next, typical weather conditions during warnings for high ozone (O3) pollution were examined. From 2017 to 2020, over one-quarter of all days with an O3 warning also were subject to an excessive heat warning. Last, land surface temperature data were used to determine the potential for increased heat exposure during AT commuting at both the ZIP code and AT infrastructure (public transit stops and bikeways) scales. Although this work focuses on Maricopa County, the issues presented here are increasingly relevant for cities across the world that are subject to poor air quality, hotter temperatures, and heat waves.
Abstract
One commonly proposed strategy for reducing urban air pollution is transitioning from single-occupancy vehicle (SOV) travel to alternative transportation (AT) modes, such as walking, biking, and using public transportation. While many studies have addressed the benefits of switching from SOV to AT, fewer studies have examined the potential for negative outcomes due to increased exposure to heat when using AT modes. This work uses Maricopa County, Arizona, home to the metropolitan Phoenix area, as a test case to examine the potential impacts of heat on commuters who utilize AT. First, regions of the county with the most candidates for switching from SOV to AT were identified and used to develop an AT candidate index. This index was based on both the current rates of AT use and the number of SOV commuters with the shortest commuting times in the dataset (<10 min). Next, typical weather conditions during warnings for high ozone (O3) pollution were examined. From 2017 to 2020, over one-quarter of all days with an O3 warning also were subject to an excessive heat warning. Last, land surface temperature data were used to determine the potential for increased heat exposure during AT commuting at both the ZIP code and AT infrastructure (public transit stops and bikeways) scales. Although this work focuses on Maricopa County, the issues presented here are increasingly relevant for cities across the world that are subject to poor air quality, hotter temperatures, and heat waves.
Abstract
Climate perception is a growing area of study in the social sciences and one that has implications on the tools and strategies we use to communicate climate change risk information. However, the range of climate perception studies remains limited, focused primarily on perceptions of day-to-day weather, sudden-onset severe events, or long-term permanent change. Phenomena situated between these extremes (e.g., annual- to decadal-scale variability) are largely missing from social science of climate research. Whether this is due to limited perception by research participants, is due to limited research attention, or is a reflection of the methods commonly applied to human dimensions of climate research, this gap precludes analysis of the full range of complex climate experiences and their influence on climate perception and understanding. In this paper, we offer a proof of concept for the climate autobiography timeline (CAT), a visual timeline tool developed to assess climate perception while prompting an ordered consideration of time, with the goal of eliciting insights into complex and long-term climate experiences such as low-frequency climate variability. Results are based off a preliminary application of the CAT across focus groups conducted in Newfoundland and Labrador, a province of Canada that is subject to low-frequency climate variability and frequent high-impact weather. Results reveal three key findings: 1) weather and climate narratives are commonly anchored to two time periods, potentially obscuring perceptions of variability; 2) narratives focus on socially important weather and climate phenomena; and 3) the social and visual coconstruction of weather and climate narratives may yield more holistic representations of local climate knowledge.
Significance Statement
The purpose of this work is to highlight the utility of timeline research methods to the study of climate perception research. Specifically, the climate autobiography timeline (CAT) serves as a tool that can address limitations of research tools commonly applied to the study of climate perceptions, notably the inability for current methods to elicit and organize complex climate experiences. Failure to capture these experiences may prevent a holistic and socially grounded understanding of climate perceptions. Drawing from a preliminary application of CATs in the province of Newfoundland and Labrador in Canada, we highlight how the tool can provide information complementary to, but distinct from, data collected through more commonly used methods such as interviews or surveys. This approach holds promise for analyses of long-term climate history, impacts of historical severe events, and cultural impact of weather and climate.
Abstract
Climate perception is a growing area of study in the social sciences and one that has implications on the tools and strategies we use to communicate climate change risk information. However, the range of climate perception studies remains limited, focused primarily on perceptions of day-to-day weather, sudden-onset severe events, or long-term permanent change. Phenomena situated between these extremes (e.g., annual- to decadal-scale variability) are largely missing from social science of climate research. Whether this is due to limited perception by research participants, is due to limited research attention, or is a reflection of the methods commonly applied to human dimensions of climate research, this gap precludes analysis of the full range of complex climate experiences and their influence on climate perception and understanding. In this paper, we offer a proof of concept for the climate autobiography timeline (CAT), a visual timeline tool developed to assess climate perception while prompting an ordered consideration of time, with the goal of eliciting insights into complex and long-term climate experiences such as low-frequency climate variability. Results are based off a preliminary application of the CAT across focus groups conducted in Newfoundland and Labrador, a province of Canada that is subject to low-frequency climate variability and frequent high-impact weather. Results reveal three key findings: 1) weather and climate narratives are commonly anchored to two time periods, potentially obscuring perceptions of variability; 2) narratives focus on socially important weather and climate phenomena; and 3) the social and visual coconstruction of weather and climate narratives may yield more holistic representations of local climate knowledge.
Significance Statement
The purpose of this work is to highlight the utility of timeline research methods to the study of climate perception research. Specifically, the climate autobiography timeline (CAT) serves as a tool that can address limitations of research tools commonly applied to the study of climate perceptions, notably the inability for current methods to elicit and organize complex climate experiences. Failure to capture these experiences may prevent a holistic and socially grounded understanding of climate perceptions. Drawing from a preliminary application of CATs in the province of Newfoundland and Labrador in Canada, we highlight how the tool can provide information complementary to, but distinct from, data collected through more commonly used methods such as interviews or surveys. This approach holds promise for analyses of long-term climate history, impacts of historical severe events, and cultural impact of weather and climate.
Abstract
Scientists at NOAA are testing a new tool that allows forecasters to communicate estimated probabilities of severe hazards (tornadoes, severe wind, and hail) as part of the Forecasting a Continuum of Environmental Threats (FACETs) framework. In this study, we employ the embedded systems theory (EST)—a communication framework that analyzes small group workplace practices as products of group, organizational, and local dynamics—to understand how probabilistic hazard information (PHI) is produced and negotiated among multiple NWS weather forecast offices in an experimental setting. Gathering feedback from NWS meteorologists who participated in the 2020 Hazard Services (HS)-PHI Interoffice Collaboration experiment, we explored implications of local and interoffice collaboration while using this experimental tool. By using a qualitative thematic analysis, it was found that differing probability thresholds, forecasting styles, social dynamics, and workload will be social factors that developers should consider as they bring PHI toward operational readiness. Warning operations in this new paradigm were also implemented into the EST model to create a communication ecosystem for future weather hazard communication research.
Significance Statement
Meteorologists are currently exploring how to use probabilities to communicate life-saving information. From tornadoes to hail, a new type of probabilistic hazard information could fundamentally change the way that NWS meteorologists collaborate with one another when issuing weather products, especially near and along the boundaries of County Warning Areas. To explore potential collaboration challenges and solutions, we applied a communication framework and explored perceptions that NWS meteorologists had while using this new tool in an experimental setting. NWS meteorologists expressed that differing ways of communicating hazard information between each office, along with forecasting styles and workload, would change the way they go about producing critical hazard information to the public.
Abstract
Scientists at NOAA are testing a new tool that allows forecasters to communicate estimated probabilities of severe hazards (tornadoes, severe wind, and hail) as part of the Forecasting a Continuum of Environmental Threats (FACETs) framework. In this study, we employ the embedded systems theory (EST)—a communication framework that analyzes small group workplace practices as products of group, organizational, and local dynamics—to understand how probabilistic hazard information (PHI) is produced and negotiated among multiple NWS weather forecast offices in an experimental setting. Gathering feedback from NWS meteorologists who participated in the 2020 Hazard Services (HS)-PHI Interoffice Collaboration experiment, we explored implications of local and interoffice collaboration while using this experimental tool. By using a qualitative thematic analysis, it was found that differing probability thresholds, forecasting styles, social dynamics, and workload will be social factors that developers should consider as they bring PHI toward operational readiness. Warning operations in this new paradigm were also implemented into the EST model to create a communication ecosystem for future weather hazard communication research.
Significance Statement
Meteorologists are currently exploring how to use probabilities to communicate life-saving information. From tornadoes to hail, a new type of probabilistic hazard information could fundamentally change the way that NWS meteorologists collaborate with one another when issuing weather products, especially near and along the boundaries of County Warning Areas. To explore potential collaboration challenges and solutions, we applied a communication framework and explored perceptions that NWS meteorologists had while using this new tool in an experimental setting. NWS meteorologists expressed that differing ways of communicating hazard information between each office, along with forecasting styles and workload, would change the way they go about producing critical hazard information to the public.
Abstract
As Arctic open water increases, shipping activity to and from mid- and western Russian Arctic ports to points south has notably increased. A number of Arctic municipalities hope increased vessel traffic will create opportunities to become a major transshipment hub. However, even with more traffic passing these ports, it might still be economically cheaper to offload cargo at a more southern port, which may also result in lower emissions. Ultimately, the question of whether to use a transshipment in the Arctic versus an established major European port is determined by the relative costs (or emissions) of sea versus land travel. This study calculates the relative competitiveness of six Norwegian coastal cities as multimodal hubs for shipments. We quantify the relative prices and CO2 emissions for sea and land travel for routes starting at the Norwegian–Russian sea border with an ultimate destination in central Europe and find that all existing routes are not competitive with routes using the major existing Port of Rotterdam (Netherlands); even with investments in port expansion and modernization, they would be underutilized regardless of an increase in vessel traffic destined for central Europe. We then examine under what relative prices (emissions) these routes become economically viable or result in lower emissions than using existing southern ports. Notably, the cheapest routes generally produce the lowest emissions, and the most expensive routes tend to have the largest emissions. Communities should consider relative competitiveness prior to making large infrastructure investments. While some choices are physically possible, they may not be economically viable.
Significance Statement
Climate change, while disruptive, can also create new opportunities. Many Arctic cities hope to become a major transshipping hub as declining sea ice opens new shipping routes from western and mid-Russian Arctic ports to European ports. This paper quantifies the relative competitiveness of six Norwegian coastal cities as multimodal transportation hubs and finds that they are uncompetitive with the more southern port in Rotterdam (Netherlands). We also show that the most economically competitive routes have lower direct emissions. Thus, while Arctic ports provide critical services in support of local and regional economic activity, even with year-round Arctic navigation Arctic ports’ development into major transshipment hubs for cargo destined for more distant locations may be neither economically viable nor desirable.
Abstract
As Arctic open water increases, shipping activity to and from mid- and western Russian Arctic ports to points south has notably increased. A number of Arctic municipalities hope increased vessel traffic will create opportunities to become a major transshipment hub. However, even with more traffic passing these ports, it might still be economically cheaper to offload cargo at a more southern port, which may also result in lower emissions. Ultimately, the question of whether to use a transshipment in the Arctic versus an established major European port is determined by the relative costs (or emissions) of sea versus land travel. This study calculates the relative competitiveness of six Norwegian coastal cities as multimodal hubs for shipments. We quantify the relative prices and CO2 emissions for sea and land travel for routes starting at the Norwegian–Russian sea border with an ultimate destination in central Europe and find that all existing routes are not competitive with routes using the major existing Port of Rotterdam (Netherlands); even with investments in port expansion and modernization, they would be underutilized regardless of an increase in vessel traffic destined for central Europe. We then examine under what relative prices (emissions) these routes become economically viable or result in lower emissions than using existing southern ports. Notably, the cheapest routes generally produce the lowest emissions, and the most expensive routes tend to have the largest emissions. Communities should consider relative competitiveness prior to making large infrastructure investments. While some choices are physically possible, they may not be economically viable.
Significance Statement
Climate change, while disruptive, can also create new opportunities. Many Arctic cities hope to become a major transshipping hub as declining sea ice opens new shipping routes from western and mid-Russian Arctic ports to European ports. This paper quantifies the relative competitiveness of six Norwegian coastal cities as multimodal transportation hubs and finds that they are uncompetitive with the more southern port in Rotterdam (Netherlands). We also show that the most economically competitive routes have lower direct emissions. Thus, while Arctic ports provide critical services in support of local and regional economic activity, even with year-round Arctic navigation Arctic ports’ development into major transshipment hubs for cargo destined for more distant locations may be neither economically viable nor desirable.
Abstract
Weather risk management products can be critical for supporting effective humanitarian actions to mitigate and prevent disasters; however, to be truly actionable, they must be based in an understanding of how weather contributes to disaster risk, informed by humanitarians’ decision-making context. Our paper seeks to identify considerations for weather risk management products to support disaster risk management, through analysis of humanitarian perceptions of the factors and processes that contribute to weather-influenced disasters, taking Somalia as a case study. We carry out semistructured interviews with humanitarian actors familiar with using weather information in their work, and we apply social cascades and disaster risk creation as conceptual tools in our analysis. Our study finds that humanitarian actors perceive historically influenced social networks, livelihood dependence on seasonality, terrorist territorial control, public capacities to manage disasters, and household-level factors related to asset control and coping mechanisms contribute to weather-influenced disasters in Somalia. These factors and processes are part of humanitarians’ dynamic decision-making context. Key insights from our study concern the importance of understanding local geographies of marginalization to design weather risk management products with the context specificity necessary for effective humanitarian actions. Also, assessing weather effects on livelihood calendars can help identify those seasonal weather conditions most responsible for detrimental livelihood impacts. Consideration of livelihood calendars can also promote accurate assessment of the effects of consecutive weather-related hazards on coping capacities and resiliency.
Abstract
Weather risk management products can be critical for supporting effective humanitarian actions to mitigate and prevent disasters; however, to be truly actionable, they must be based in an understanding of how weather contributes to disaster risk, informed by humanitarians’ decision-making context. Our paper seeks to identify considerations for weather risk management products to support disaster risk management, through analysis of humanitarian perceptions of the factors and processes that contribute to weather-influenced disasters, taking Somalia as a case study. We carry out semistructured interviews with humanitarian actors familiar with using weather information in their work, and we apply social cascades and disaster risk creation as conceptual tools in our analysis. Our study finds that humanitarian actors perceive historically influenced social networks, livelihood dependence on seasonality, terrorist territorial control, public capacities to manage disasters, and household-level factors related to asset control and coping mechanisms contribute to weather-influenced disasters in Somalia. These factors and processes are part of humanitarians’ dynamic decision-making context. Key insights from our study concern the importance of understanding local geographies of marginalization to design weather risk management products with the context specificity necessary for effective humanitarian actions. Also, assessing weather effects on livelihood calendars can help identify those seasonal weather conditions most responsible for detrimental livelihood impacts. Consideration of livelihood calendars can also promote accurate assessment of the effects of consecutive weather-related hazards on coping capacities and resiliency.
Abstract
Understanding when weather information is required by the public is essential for evaluating and improving user-oriented weather services. Because of the popularity of smartphones, most people can easily access weather information via smartphone applications. In this study, we analyzed usage data for the Moji Weather smartphone application in 2017 and 2018 and devised a demand index to determine how often the weather information was used by the public under different weather conditions. Using hourly observations of surface temperature, wind intensity, precipitation, and visibility, we quantified the relationship between the demand for weather information and weather conditions in different regions of China. In general, the demand index increased with increases in local hourly precipitation or surface wind intensity in all regions; however, there were notable regional differences in the increasing trends. Extreme hot weather was found to increase the demand index in Northern China, Xinjiang, and the Sichuan Basin while in Southern China it increased more in response to extreme cold weather. We quantified the relationships between the demand index and weather conditions by performing a polynomial regression analysis for each weather element and region. The high-demand thresholds were found to vary among regions, suggesting the need for customized weather services for users in different geographical regions. The study also revealed the contribution of weather warnings to weather information demand in two megacities and showed that warnings were effective for conveying information about weather-related risks.
Abstract
Understanding when weather information is required by the public is essential for evaluating and improving user-oriented weather services. Because of the popularity of smartphones, most people can easily access weather information via smartphone applications. In this study, we analyzed usage data for the Moji Weather smartphone application in 2017 and 2018 and devised a demand index to determine how often the weather information was used by the public under different weather conditions. Using hourly observations of surface temperature, wind intensity, precipitation, and visibility, we quantified the relationship between the demand for weather information and weather conditions in different regions of China. In general, the demand index increased with increases in local hourly precipitation or surface wind intensity in all regions; however, there were notable regional differences in the increasing trends. Extreme hot weather was found to increase the demand index in Northern China, Xinjiang, and the Sichuan Basin while in Southern China it increased more in response to extreme cold weather. We quantified the relationships between the demand index and weather conditions by performing a polynomial regression analysis for each weather element and region. The high-demand thresholds were found to vary among regions, suggesting the need for customized weather services for users in different geographical regions. The study also revealed the contribution of weather warnings to weather information demand in two megacities and showed that warnings were effective for conveying information about weather-related risks.
