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Abstract
Lightning around the world poses a significant threat to life, infrastructure, and economic sectors. This study evaluates lightning risk at the municipal level in Mexico, recognizing the interplay of hazard and vulnerability in risk estimation. Despite declining lightning-related fatalities, possibly attributed to demographic shifts and improved urban infrastructure, persistent social vulnerability exists, particularly among rural populations engaged in labor-intensive agriculture with lower education levels. We estimate a risk map for lightning-related fatality risk in Mexico, where we identify high-risk regions along the Sierra Madre Occidental, the Pacific coast, and central and southeastern Mexico, marked by elevated lightning days and social vulnerability. The risk map integrates hazard and social vulnerability, capturing the distribution of fatality incidents, and it reveals that 82.1% of incidents occurred in municipalities categorized as “high” or “very high” risk. This result emphasizes the need to consider both physical hazard and social vulnerability for a comprehensive assessment of lightning risk. This study contributes to understanding lightning risk in Mexico, providing crucial insights at the municipality level for informing policymaking and targeting risk mitigation strategies. By highlighting the interrelation of hazard and social vulnerability, this research aligns with broader goals of enhancing local resilience and safety in the face of natural hazards, highlighting the ongoing need for disaster risk reduction efforts.
Significance Statement
This study provides a comprehensive evaluation of the risk of death by lightning at the municipality level in Mexico, considering the intricate interplay between hazard and social vulnerability. By analyzing both the physical hazard of lightning and the social vulnerability of exposed populations, the study provides a map estimating the risk level for each municipality. The risk map, capturing the interrelation of hazard and vulnerability, provides a powerful tool for policymakers and emergency responders. With 82.1% of lightning fatalities concentrated in municipalities with “high” and “very high” risk, this work underscores the need for comprehensive risk assessment strategies. This research contributes knowledge for informed decision-making, targeted interventions, and the ongoing pursuit of enhancing community resilience to lightning-related hazards.
Abstract
Lightning around the world poses a significant threat to life, infrastructure, and economic sectors. This study evaluates lightning risk at the municipal level in Mexico, recognizing the interplay of hazard and vulnerability in risk estimation. Despite declining lightning-related fatalities, possibly attributed to demographic shifts and improved urban infrastructure, persistent social vulnerability exists, particularly among rural populations engaged in labor-intensive agriculture with lower education levels. We estimate a risk map for lightning-related fatality risk in Mexico, where we identify high-risk regions along the Sierra Madre Occidental, the Pacific coast, and central and southeastern Mexico, marked by elevated lightning days and social vulnerability. The risk map integrates hazard and social vulnerability, capturing the distribution of fatality incidents, and it reveals that 82.1% of incidents occurred in municipalities categorized as “high” or “very high” risk. This result emphasizes the need to consider both physical hazard and social vulnerability for a comprehensive assessment of lightning risk. This study contributes to understanding lightning risk in Mexico, providing crucial insights at the municipality level for informing policymaking and targeting risk mitigation strategies. By highlighting the interrelation of hazard and social vulnerability, this research aligns with broader goals of enhancing local resilience and safety in the face of natural hazards, highlighting the ongoing need for disaster risk reduction efforts.
Significance Statement
This study provides a comprehensive evaluation of the risk of death by lightning at the municipality level in Mexico, considering the intricate interplay between hazard and social vulnerability. By analyzing both the physical hazard of lightning and the social vulnerability of exposed populations, the study provides a map estimating the risk level for each municipality. The risk map, capturing the interrelation of hazard and vulnerability, provides a powerful tool for policymakers and emergency responders. With 82.1% of lightning fatalities concentrated in municipalities with “high” and “very high” risk, this work underscores the need for comprehensive risk assessment strategies. This research contributes knowledge for informed decision-making, targeted interventions, and the ongoing pursuit of enhancing community resilience to lightning-related hazards.
Abstract
This study explores the correlation between weather and the perception of urban cleanliness across the 47 largest cities in Spain. Utilizing survey data conducted by the national Consumers and Users Organization (OCU) in 2015, 2019, and 2023 to assess cleanliness perceptions, we analyze potential associations with precipitation and temperature recorded by weather stations of the Spanish Meteorological Agency. Additionally, we consider computed values of the De Martonne aridity index. The OCU data reveal regional disparities in perceived cleanliness quality. Higher cleanliness scores are obtained in cities located in the northern and north-central regions of Spain, characterized by humid and superhumid climates according to the De Martonne index. Conversely, lower cleanliness ratings are given to cities in the southern and eastern regions of Spain, where a Mediterranean climate and lower aridity index values prevail. In conducting a statistical analysis on the perception of cleanliness and variables related to precipitation and temperature, the results of the chi-square and linear correlation tests found no strong statistical correlation, although a tendency is observed. Cities with higher annual precipitation and lower values of average annual temperature tend to receive better cleanliness ratings, while drier and warmer cities exhibit the worst values of perceived urban cleanliness. Furthermore, our findings indicate that the Gompertz model effectively captures a strong statistical correlation in the relationship between cleanliness perception and the De Martonne index: As aridity increases, cleanliness perception decreases. These results are relevant for the development of future cleaning methods and systems, particularly in light of the climate change scenarios that are anticipated in the Mediterranean region due to warmer and drier conditions and, consequently, an increase in aridity.
Abstract
This study explores the correlation between weather and the perception of urban cleanliness across the 47 largest cities in Spain. Utilizing survey data conducted by the national Consumers and Users Organization (OCU) in 2015, 2019, and 2023 to assess cleanliness perceptions, we analyze potential associations with precipitation and temperature recorded by weather stations of the Spanish Meteorological Agency. Additionally, we consider computed values of the De Martonne aridity index. The OCU data reveal regional disparities in perceived cleanliness quality. Higher cleanliness scores are obtained in cities located in the northern and north-central regions of Spain, characterized by humid and superhumid climates according to the De Martonne index. Conversely, lower cleanliness ratings are given to cities in the southern and eastern regions of Spain, where a Mediterranean climate and lower aridity index values prevail. In conducting a statistical analysis on the perception of cleanliness and variables related to precipitation and temperature, the results of the chi-square and linear correlation tests found no strong statistical correlation, although a tendency is observed. Cities with higher annual precipitation and lower values of average annual temperature tend to receive better cleanliness ratings, while drier and warmer cities exhibit the worst values of perceived urban cleanliness. Furthermore, our findings indicate that the Gompertz model effectively captures a strong statistical correlation in the relationship between cleanliness perception and the De Martonne index: As aridity increases, cleanliness perception decreases. These results are relevant for the development of future cleaning methods and systems, particularly in light of the climate change scenarios that are anticipated in the Mediterranean region due to warmer and drier conditions and, consequently, an increase in aridity.
Abstract
Extreme weather, including heat waves, poses a significant threat to ecosystems and human health. As global temperatures continue to rise, the frequency and severity of heat waves will increase. Because of this, communicating heat-related risks to the public is increasingly important. One commonly used communication tool is the Climate Shift Index (CSI), which establishes how much more likely an extreme weather event, such as a heat wave, has been made by climate change. To test the impact of the CSI on people’s understanding of the links between climate change and extreme weather, we conducted an experiment informing 3902 American adults that climate change made the July 2023 heat wave in the United States at least 5 times more likely. In addition to this standard CSI wording and two control messages, we also explored the effectiveness of reframing magnitude as a percentage and whether mechanistic and attribution explanations of the relationship between climate change and heat waves further increase understanding. All treatments increased the belief that climate change made the July 2023 heat wave more likely and is making heat waves in general more likely as well. Additionally, we found that expressing the magnitude as a percentage was more effective than the standard CSI framing. We also found that just talking about the heat wave, without mentioning climate change, was enough to change beliefs.
Abstract
Extreme weather, including heat waves, poses a significant threat to ecosystems and human health. As global temperatures continue to rise, the frequency and severity of heat waves will increase. Because of this, communicating heat-related risks to the public is increasingly important. One commonly used communication tool is the Climate Shift Index (CSI), which establishes how much more likely an extreme weather event, such as a heat wave, has been made by climate change. To test the impact of the CSI on people’s understanding of the links between climate change and extreme weather, we conducted an experiment informing 3902 American adults that climate change made the July 2023 heat wave in the United States at least 5 times more likely. In addition to this standard CSI wording and two control messages, we also explored the effectiveness of reframing magnitude as a percentage and whether mechanistic and attribution explanations of the relationship between climate change and heat waves further increase understanding. All treatments increased the belief that climate change made the July 2023 heat wave more likely and is making heat waves in general more likely as well. Additionally, we found that expressing the magnitude as a percentage was more effective than the standard CSI framing. We also found that just talking about the heat wave, without mentioning climate change, was enough to change beliefs.
Abstract
This paper analyzes findings from semistructured interviews and focus groups with 31 farmers in the Willamette Valley in which farmers were asked about their needs for climate data and about the usability of a range of outputs from the Community Earth System Model, version 2 (CESM2), for their soil management practices. Findings indicate that climate and soils data generated from CESM and other Earth system models (ESMs), despite their coarse spatial scale resolutions, can inform farmers’ long-term decisions, but that the data would be more usable if the outputs were provided in a format that allowed farmers to choose the variables and thresholds relevant to their particular needs and if ESMs incorporated farmer practices including residue removal, cover cropping, and tillage levels into the model operations so that farmers could better understand the impacts of their decisions. Findings also suggest that although there is a significant gap in the spatial resolution at which these global ESMs generate data and the spatial resolution needed by farmers to make most decisions, farmers are adept at making scalar adjustments to apply coarse-resolution data to the specifics of their own farm’s microclimate. Thus, our findings suggest that, to support agricultural decision-making, development priorities for ESMs should include developing better representations of agricultural management practices within the models and creating interactive data dashboards or platforms.
Abstract
This paper analyzes findings from semistructured interviews and focus groups with 31 farmers in the Willamette Valley in which farmers were asked about their needs for climate data and about the usability of a range of outputs from the Community Earth System Model, version 2 (CESM2), for their soil management practices. Findings indicate that climate and soils data generated from CESM and other Earth system models (ESMs), despite their coarse spatial scale resolutions, can inform farmers’ long-term decisions, but that the data would be more usable if the outputs were provided in a format that allowed farmers to choose the variables and thresholds relevant to their particular needs and if ESMs incorporated farmer practices including residue removal, cover cropping, and tillage levels into the model operations so that farmers could better understand the impacts of their decisions. Findings also suggest that although there is a significant gap in the spatial resolution at which these global ESMs generate data and the spatial resolution needed by farmers to make most decisions, farmers are adept at making scalar adjustments to apply coarse-resolution data to the specifics of their own farm’s microclimate. Thus, our findings suggest that, to support agricultural decision-making, development priorities for ESMs should include developing better representations of agricultural management practices within the models and creating interactive data dashboards or platforms.
Abstract
A violent tornado occurred in Czechia on 24 June 2021, killing six and causing at least 576 injuries. There were more indirect than direct injuries. The tornado was rated 4 on the international Fujita scale (IF4) using a draft version of the IF scale. This was the first violent tornado in Czechia and one of only 17 violent, i.e., (I)F4 or higher, tornadoes that occurred in Europe since 1950. The tornado reached a width of 3.5 km, the widest on record in Europe. The case presents an important opportunity to investigate the impacts of such a strong tornado in the area, where they are rare, no tornado warnings are issued, and where the building standards are different from the typically investigated tornadoes in the United States. We discuss challenges in organizing the damage survey, which took 3 days and involved meteorologists from three countries. A wind damage survey guide to aid mitigating these was written by the European Severe Storms Laboratory and initiated the development of a wind damage surveying app. The damage survey showed that most of the inhabited buildings built using heavy masonry and rigid ceilings did not collapse in IF2/3 winds, but only with IF4 winds. Eyewitness reports collected after the tornado show that many people were not aware of the risk associated with the tornado. Eventually, most people tried to shelter in the most secure part of the house, but it was often too late. This case highlights the need for better communication of tornado risk to the public in Europe.
Abstract
A violent tornado occurred in Czechia on 24 June 2021, killing six and causing at least 576 injuries. There were more indirect than direct injuries. The tornado was rated 4 on the international Fujita scale (IF4) using a draft version of the IF scale. This was the first violent tornado in Czechia and one of only 17 violent, i.e., (I)F4 or higher, tornadoes that occurred in Europe since 1950. The tornado reached a width of 3.5 km, the widest on record in Europe. The case presents an important opportunity to investigate the impacts of such a strong tornado in the area, where they are rare, no tornado warnings are issued, and where the building standards are different from the typically investigated tornadoes in the United States. We discuss challenges in organizing the damage survey, which took 3 days and involved meteorologists from three countries. A wind damage survey guide to aid mitigating these was written by the European Severe Storms Laboratory and initiated the development of a wind damage surveying app. The damage survey showed that most of the inhabited buildings built using heavy masonry and rigid ceilings did not collapse in IF2/3 winds, but only with IF4 winds. Eyewitness reports collected after the tornado show that many people were not aware of the risk associated with the tornado. Eventually, most people tried to shelter in the most secure part of the house, but it was often too late. This case highlights the need for better communication of tornado risk to the public in Europe.
Abstract
Climate and weather-related disasters in California illustrate the need for immediate climate change action—both mitigation to reduce impacts and adaptation to protect our communities, relatives, and the ecosystems we depend upon. Indigenous frontline communities face even greater threats from climate impacts due to historical and political legacies of environmental injustice. Climate change adaptation actions have proven challenging to implement as communities struggle to access necessary climate data at appropriate scales, identify effective strategies that address community priorities, and obtain resources to act at a whole-community level. In this paper, we present three examples of Indigenous communities in California that have used a climate justice approach to climate change adaptation. These communities are drawing upon community knowledge and expertise to address the challenges of adaptation planning and taking actions that center community priorities. The three cases address emergency preparation and response, cultural burning and fire management, and community organizing and social cohesion. Across these spheres, they illustrate the ways in which a community-based and climate justice-focused approach to adaptation can be effective in addressing current threats while also addressing the legacy of imposed, socially constructed vulnerability and environmental injustices. Because we recognize the need for multiple knowledges and skills in adaptation actions, we include recommendations that have emerged based on what has been learned through these long-standing and engaged participatory research collaborations for climate scientists who wish to contribute to climate justice-focused adaptation efforts by using scientific data to support—not supplant—community efforts, target funding toward genuine community engagement and adaptation actions, and become aware of the historical and political legacies that created the climate vulnerabilities and injustices evident today.
Abstract
Climate and weather-related disasters in California illustrate the need for immediate climate change action—both mitigation to reduce impacts and adaptation to protect our communities, relatives, and the ecosystems we depend upon. Indigenous frontline communities face even greater threats from climate impacts due to historical and political legacies of environmental injustice. Climate change adaptation actions have proven challenging to implement as communities struggle to access necessary climate data at appropriate scales, identify effective strategies that address community priorities, and obtain resources to act at a whole-community level. In this paper, we present three examples of Indigenous communities in California that have used a climate justice approach to climate change adaptation. These communities are drawing upon community knowledge and expertise to address the challenges of adaptation planning and taking actions that center community priorities. The three cases address emergency preparation and response, cultural burning and fire management, and community organizing and social cohesion. Across these spheres, they illustrate the ways in which a community-based and climate justice-focused approach to adaptation can be effective in addressing current threats while also addressing the legacy of imposed, socially constructed vulnerability and environmental injustices. Because we recognize the need for multiple knowledges and skills in adaptation actions, we include recommendations that have emerged based on what has been learned through these long-standing and engaged participatory research collaborations for climate scientists who wish to contribute to climate justice-focused adaptation efforts by using scientific data to support—not supplant—community efforts, target funding toward genuine community engagement and adaptation actions, and become aware of the historical and political legacies that created the climate vulnerabilities and injustices evident today.
Abstract
Although many people believe their pain fluctuates with weather conditions, both weather and pain may be associated with time spent outside. For example, pleasant weather may mean that people spend more time outside doing physical activity and are exposed to the weather, leading to more (or less) pain, and poor weather or severe pain may keep people inside, sedentary, and not exposed to the weather. We conducted a smartphone study where participants with chronic pain reported daily pain severity, as well as time spent outside. We address the relationship between four weather variables (temperature, dewpoint temperature, pressure, and wind speed) and pain by proposing a three-step approach to untangle their effects: (i) propose a set of plausible directed acyclic graphs (DAGs) that account for potential roles of time spent outside (e.g., collider, effect modifier, mediator); (ii) analyze the compatibility of the observed data with the assumed model; and (iii) identify the most plausible model by combining evidence from the observed data and domain-specific knowledge. We found that the data do not support time spent outside as a collider or mediator of the relationship between weather variables and pain. On the other hand, time spent outside modifies the effect between temperature and pain, as well as wind speed and pain, with the effect being absent on days that participants spent inside and present if they spent some or all of the day outside. Our results show the utility of using directed acyclic graphs for studying causal inference.
Significance Statement
Three-quarters of people living with chronic pain believe that weather influences their pain. However, people staying inside would not be exposed to the weather outside, and good weather may mean that people are more active outside, leading to more or less pain. To obtain data to calculate how the amount of time spent outside affects the weather–pain relationship, we conducted a 15-month smartphone study collecting daily pain reports and nearby weather for nearly 5000 participants in the United Kingdom. We found that time spent outside modifies the relationship between temperature/wind speed and pain, showing the importance of accounting for other factors when investigating the association between weather and chronic pain, which could guide future research into pain mitigation and management.
Abstract
Although many people believe their pain fluctuates with weather conditions, both weather and pain may be associated with time spent outside. For example, pleasant weather may mean that people spend more time outside doing physical activity and are exposed to the weather, leading to more (or less) pain, and poor weather or severe pain may keep people inside, sedentary, and not exposed to the weather. We conducted a smartphone study where participants with chronic pain reported daily pain severity, as well as time spent outside. We address the relationship between four weather variables (temperature, dewpoint temperature, pressure, and wind speed) and pain by proposing a three-step approach to untangle their effects: (i) propose a set of plausible directed acyclic graphs (DAGs) that account for potential roles of time spent outside (e.g., collider, effect modifier, mediator); (ii) analyze the compatibility of the observed data with the assumed model; and (iii) identify the most plausible model by combining evidence from the observed data and domain-specific knowledge. We found that the data do not support time spent outside as a collider or mediator of the relationship between weather variables and pain. On the other hand, time spent outside modifies the effect between temperature and pain, as well as wind speed and pain, with the effect being absent on days that participants spent inside and present if they spent some or all of the day outside. Our results show the utility of using directed acyclic graphs for studying causal inference.
Significance Statement
Three-quarters of people living with chronic pain believe that weather influences their pain. However, people staying inside would not be exposed to the weather outside, and good weather may mean that people are more active outside, leading to more or less pain. To obtain data to calculate how the amount of time spent outside affects the weather–pain relationship, we conducted a 15-month smartphone study collecting daily pain reports and nearby weather for nearly 5000 participants in the United Kingdom. We found that time spent outside modifies the relationship between temperature/wind speed and pain, showing the importance of accounting for other factors when investigating the association between weather and chronic pain, which could guide future research into pain mitigation and management.
Abstract
This study utilizes hourly land surface temperature (LST) data from the Geostationary Operational Environmental Satellite (GOES) to analyze the seasonal and diurnal characteristics of surface urban heat island intensity (SUHII) across 120 largest U.S. cities and their surroundings. Distinct patterns emerge in the classification of seasonal daytime SUHII and nighttime SUHII. Specifically, the enhanced vegetation index (EVI) and albedo (ALB) play pivotal roles in influencing these temperature variations. The diurnal cycle of SUHII further reveals different trends, suggesting that climate conditions, urban and nonurban land covers, and anthropogenic activities during nighttime hours affect SUHII peaks. Exploring intracity LST dynamics, the study reveals a significant correlation between urban intensity (UI) and LST, with LST rising as UI increases. Notably, populations identified as more vulnerable by the social vulnerability index (SVI) are found in high UI regions. This results in discernible LST inequality, where the more vulnerable communities are under higher LST conditions, possibly leading to higher heat exposure. This comprehensive study accentuates the significance of tailoring city-specific climate change mitigation strategies, illuminating LST variations and their intertwined societal implications.
Abstract
This study utilizes hourly land surface temperature (LST) data from the Geostationary Operational Environmental Satellite (GOES) to analyze the seasonal and diurnal characteristics of surface urban heat island intensity (SUHII) across 120 largest U.S. cities and their surroundings. Distinct patterns emerge in the classification of seasonal daytime SUHII and nighttime SUHII. Specifically, the enhanced vegetation index (EVI) and albedo (ALB) play pivotal roles in influencing these temperature variations. The diurnal cycle of SUHII further reveals different trends, suggesting that climate conditions, urban and nonurban land covers, and anthropogenic activities during nighttime hours affect SUHII peaks. Exploring intracity LST dynamics, the study reveals a significant correlation between urban intensity (UI) and LST, with LST rising as UI increases. Notably, populations identified as more vulnerable by the social vulnerability index (SVI) are found in high UI regions. This results in discernible LST inequality, where the more vulnerable communities are under higher LST conditions, possibly leading to higher heat exposure. This comprehensive study accentuates the significance of tailoring city-specific climate change mitigation strategies, illuminating LST variations and their intertwined societal implications.
Abstract
The use of oral histories in social scientific approaches to climate change has enabled richly detailed explorations of the situated, meaning-laden dimensions of local experiences and knowledge. But “big data” approaches have been increasingly advocated as a means to scale up understandings from individual projects, through better utilizing large collections of qualitative data sources. This article considers the issues raised by such secondary analysis, using the NOAA Voices Oral History Archives, an online database with a focus on coastal communities and groups thought especially vulnerable to climatic changes. Coupling larger-scale methods such as text mining with more traditional methods such as close reading reveals variations across time and space in the ways people talk about environmental changes, underscoring how memories and experiences shape understandings and the subtlety with which these differences are articulated and culturally inscribed. Looking across multiple collections illuminates those shared understandings, points of contention, and differences between communities that might be obscured if decontextualized, showing the importance of “small data” approaches to big data to fully understand the deeply cultural understandings, perceptions, and histories of environmental changes such as climate change.
Abstract
The use of oral histories in social scientific approaches to climate change has enabled richly detailed explorations of the situated, meaning-laden dimensions of local experiences and knowledge. But “big data” approaches have been increasingly advocated as a means to scale up understandings from individual projects, through better utilizing large collections of qualitative data sources. This article considers the issues raised by such secondary analysis, using the NOAA Voices Oral History Archives, an online database with a focus on coastal communities and groups thought especially vulnerable to climatic changes. Coupling larger-scale methods such as text mining with more traditional methods such as close reading reveals variations across time and space in the ways people talk about environmental changes, underscoring how memories and experiences shape understandings and the subtlety with which these differences are articulated and culturally inscribed. Looking across multiple collections illuminates those shared understandings, points of contention, and differences between communities that might be obscured if decontextualized, showing the importance of “small data” approaches to big data to fully understand the deeply cultural understandings, perceptions, and histories of environmental changes such as climate change.
Abstract
Our goal is to tie climate-scale meteorology to regional physics and ecosystem changes and demonstrate a few resulting impacts to which regional peoples are having to respond in the Alaskan Bering Strait region. The sea ice loss events in the winters of 2017/18 and 2018/19 initiated a series of marine environmental, ecological, and industrial changes through a chain of connected events from jet-stream meanders, storms, southerly winds, warmer sea temperatures, and minimum sea ice cover. Resulting impacts continue as coastal communities respond to ongoing nutritional, cultural, and economic challenges. Global warming potentially initiated these events through a weakened atmospheric Arctic Front. Ecological shifts included a transition/reorganization of the Bering Strait regional marine ecosystem. Subsequent changes included shifts in zooplankton species, increases in large-bodied, predatory fish species moving northward, an ice seal unusual mortality event, and seven consecutive years of multispecies seabird die-offs. These changes in the marine ecosystem create a serious food security concern. Ongoing impacts include large, toxic harmful algal blooms and coastal erosion. Recent changes to the maritime industries of the transboundary waters of the Bering Strait include increased industrial ship traffic, planned development of the Port of Nome, and northward proximity of foreign fishing activity. Projections for the next decades are for an increasing frequency of low sea ice years and continuing ecosystem and industrial transitions that contribute to increasing economic and food security concerns for the 16 coastal communities that compose the Bering Strait region.
Significance Statement
Extreme events in the atmosphere/oceans and resultant record sea ice minimums in 2018 and 2019 were manifested in marine ecosystem transitions and maritime industry impacts. This led to ongoing concerns over the food safety and food security of marine resources essential to the nutritional, cultural, and economic well-being of Alaskan coastal communities of the Bering Strait region. Persistent weakening of the Arctic Front may signal an increased frequency of low sea ice events into the next decades.
Abstract
Our goal is to tie climate-scale meteorology to regional physics and ecosystem changes and demonstrate a few resulting impacts to which regional peoples are having to respond in the Alaskan Bering Strait region. The sea ice loss events in the winters of 2017/18 and 2018/19 initiated a series of marine environmental, ecological, and industrial changes through a chain of connected events from jet-stream meanders, storms, southerly winds, warmer sea temperatures, and minimum sea ice cover. Resulting impacts continue as coastal communities respond to ongoing nutritional, cultural, and economic challenges. Global warming potentially initiated these events through a weakened atmospheric Arctic Front. Ecological shifts included a transition/reorganization of the Bering Strait regional marine ecosystem. Subsequent changes included shifts in zooplankton species, increases in large-bodied, predatory fish species moving northward, an ice seal unusual mortality event, and seven consecutive years of multispecies seabird die-offs. These changes in the marine ecosystem create a serious food security concern. Ongoing impacts include large, toxic harmful algal blooms and coastal erosion. Recent changes to the maritime industries of the transboundary waters of the Bering Strait include increased industrial ship traffic, planned development of the Port of Nome, and northward proximity of foreign fishing activity. Projections for the next decades are for an increasing frequency of low sea ice years and continuing ecosystem and industrial transitions that contribute to increasing economic and food security concerns for the 16 coastal communities that compose the Bering Strait region.
Significance Statement
Extreme events in the atmosphere/oceans and resultant record sea ice minimums in 2018 and 2019 were manifested in marine ecosystem transitions and maritime industry impacts. This led to ongoing concerns over the food safety and food security of marine resources essential to the nutritional, cultural, and economic well-being of Alaskan coastal communities of the Bering Strait region. Persistent weakening of the Arctic Front may signal an increased frequency of low sea ice events into the next decades.
