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Abstract
Carbon monoxide (CO) is a colorless, odorless gas that can cause injury or death if inhaled. CO is a frequent secondary hazard induced by the aftereffects of natural hazards as individuals, families, and communities often seek alternative power sources for heating, cooking, lighting, and cleanup during the emergency and recovery phases of a disaster. These alternative power sources—such as portable generators, petroleum-based heaters, and vehicles—exhaust CO that can ultimately build to toxic levels in enclosed areas. Ever-increasing environmental and societal changes combined with an aging infrastructure are growing the odds of power failures during hazardous weather events, which, in turn, are increasing the likelihood of CO exposure, illness, and death. This study analyzed weather-related CO fatalities from 2000 to 2019 in the United States using death-certificate data, providing one of the longest assessments of this mortality. Results reveal that over 8300 CO fatalities occurred in the United States during the 20-yr study period, with 17% of those deaths affiliated with weather perils. Cool-season perils such as ice storms, snowstorms, and extreme cold were the leading hazards that led to situations causing CO fatalities. States in the Southeast and Northeast had the highest CO fatality rates, with winter having the greatest seasonal mortality. In general, these preventable CO poisoning influxes are related to a deficiency of knowledge on generator safety and the absence of working detectors and alarms in the enclosed locations where poisonings occur. Education and prevention programs that target the most vulnerable populations will help prevent future weather-related CO fatalities.
Significance Statement
Carbon monoxide exposure is common after weather disasters when individuals, families, and communities seek alternative power sources—such as portable generators, petroleum-based heaters, and vehicles—that exhaust this deadly, colorless, and odorless gas. Initially, we catalog carbon monoxide fatalities associated with weather events in the United States over two decades; thereafter, we illustrate the characteristics and patterns affiliated with these deaths. Results will assist public officials, first responders, and individuals in their decision-making and response before, during, and after weather events so that these deaths may be prevented in the future.
Abstract
Carbon monoxide (CO) is a colorless, odorless gas that can cause injury or death if inhaled. CO is a frequent secondary hazard induced by the aftereffects of natural hazards as individuals, families, and communities often seek alternative power sources for heating, cooking, lighting, and cleanup during the emergency and recovery phases of a disaster. These alternative power sources—such as portable generators, petroleum-based heaters, and vehicles—exhaust CO that can ultimately build to toxic levels in enclosed areas. Ever-increasing environmental and societal changes combined with an aging infrastructure are growing the odds of power failures during hazardous weather events, which, in turn, are increasing the likelihood of CO exposure, illness, and death. This study analyzed weather-related CO fatalities from 2000 to 2019 in the United States using death-certificate data, providing one of the longest assessments of this mortality. Results reveal that over 8300 CO fatalities occurred in the United States during the 20-yr study period, with 17% of those deaths affiliated with weather perils. Cool-season perils such as ice storms, snowstorms, and extreme cold were the leading hazards that led to situations causing CO fatalities. States in the Southeast and Northeast had the highest CO fatality rates, with winter having the greatest seasonal mortality. In general, these preventable CO poisoning influxes are related to a deficiency of knowledge on generator safety and the absence of working detectors and alarms in the enclosed locations where poisonings occur. Education and prevention programs that target the most vulnerable populations will help prevent future weather-related CO fatalities.
Significance Statement
Carbon monoxide exposure is common after weather disasters when individuals, families, and communities seek alternative power sources—such as portable generators, petroleum-based heaters, and vehicles—that exhaust this deadly, colorless, and odorless gas. Initially, we catalog carbon monoxide fatalities associated with weather events in the United States over two decades; thereafter, we illustrate the characteristics and patterns affiliated with these deaths. Results will assist public officials, first responders, and individuals in their decision-making and response before, during, and after weather events so that these deaths may be prevented in the future.
Abstract
Prior research suggests that climate stories are rarely reported by local news outlets in the United States. As part of the Climate Matters in the Newsroom project—a program for climate-reporting resources designed to help journalists report local climate stories—we conducted a series of local climate-reporting workshops for journalists to support such reporting. Here, we present the impacts of eight workshops conducted in 2018 and 2019—including participant assessments of the workshop, longitudinal changes in their climate-reporting self-efficacy, and the number and proportion of print and digital climate stories reported. We learned that participants found value in the workshops and experienced significant increases in their climate-reporting self-efficacy in response to the workshops, which were largely sustained over the next 6 months. We found only limited evidence that participants reported more frequently on climate change after the workshops—possibly, in part, due to the impact of coronavirus disease 2019 (COVID-19) on the news industry. These findings suggest that local climate-reporting workshops can be a useful but not necessarily sufficient strategy for supporting local climate change reporting. Further research is needed to illuminate how to support local climate reporting most effectively.
Significance Statement
As part of an NSF-funded project to support local climate change news reporting, we conducted a series of eight journalist workshops. Here we evaluate their impacts. Participants gave the workshops strong positive ratings and experienced significant increases in climate-reporting self-efficacy. There was only limited evidence, however, that the workshops led to more frequent reporting on climate change—a conclusion muddied by the impacts of coronavirus disease 2019 (COVID-19) on the news industry. These findings suggest that local climate-reporting workshops may be a useful strategy but that additional research is needed to strengthen the approach.
Abstract
Prior research suggests that climate stories are rarely reported by local news outlets in the United States. As part of the Climate Matters in the Newsroom project—a program for climate-reporting resources designed to help journalists report local climate stories—we conducted a series of local climate-reporting workshops for journalists to support such reporting. Here, we present the impacts of eight workshops conducted in 2018 and 2019—including participant assessments of the workshop, longitudinal changes in their climate-reporting self-efficacy, and the number and proportion of print and digital climate stories reported. We learned that participants found value in the workshops and experienced significant increases in their climate-reporting self-efficacy in response to the workshops, which were largely sustained over the next 6 months. We found only limited evidence that participants reported more frequently on climate change after the workshops—possibly, in part, due to the impact of coronavirus disease 2019 (COVID-19) on the news industry. These findings suggest that local climate-reporting workshops can be a useful but not necessarily sufficient strategy for supporting local climate change reporting. Further research is needed to illuminate how to support local climate reporting most effectively.
Significance Statement
As part of an NSF-funded project to support local climate change news reporting, we conducted a series of eight journalist workshops. Here we evaluate their impacts. Participants gave the workshops strong positive ratings and experienced significant increases in climate-reporting self-efficacy. There was only limited evidence, however, that the workshops led to more frequent reporting on climate change—a conclusion muddied by the impacts of coronavirus disease 2019 (COVID-19) on the news industry. These findings suggest that local climate-reporting workshops may be a useful strategy but that additional research is needed to strengthen the approach.
Abstract
Millions of people attend Major League Baseball games every year, during a season that is played primarily outdoors at the peak of the U.S. lightning season. In recent years, social media photographs and baseball game television broadcasts have revealed lightning within proximity of several baseball games without the game being delayed. Lightning data from the U.S. National Lightning Detection Network within 12.8 km of 9717 Major League Baseball games between 2016 and 2019 were examined to find the extent to which lightning is a threat to games, players, staff, and fans: 717 games were found to have lightning within 12.8 km, with more than 175 000 in-cloud and cloud-to-ground lightning discharges detected during those games. The distribution of games with lightning was not uniform and is related to the annual average lightning density of each ballpark. Despite the significant risk of a lightning-related incident at Major League Baseball games, existing work from other organizations like the National Collegiate Athletics Association and the National Athletics Trainers Association can be leveraged to improve lightning safety at professional baseball games.
Significance Statement
Nearly one of every 14 Major League Baseball games has lightning within what lightning safety experts would consider an unsafe distance. The potential for a lightning casualty incident is high because most games are played outdoors and millions of people are at baseball games every year. Although frameworks that can improve lightning safety at the thousands of professional baseball games that are played every year exist, it is unclear how frequently they are implemented.
Abstract
Millions of people attend Major League Baseball games every year, during a season that is played primarily outdoors at the peak of the U.S. lightning season. In recent years, social media photographs and baseball game television broadcasts have revealed lightning within proximity of several baseball games without the game being delayed. Lightning data from the U.S. National Lightning Detection Network within 12.8 km of 9717 Major League Baseball games between 2016 and 2019 were examined to find the extent to which lightning is a threat to games, players, staff, and fans: 717 games were found to have lightning within 12.8 km, with more than 175 000 in-cloud and cloud-to-ground lightning discharges detected during those games. The distribution of games with lightning was not uniform and is related to the annual average lightning density of each ballpark. Despite the significant risk of a lightning-related incident at Major League Baseball games, existing work from other organizations like the National Collegiate Athletics Association and the National Athletics Trainers Association can be leveraged to improve lightning safety at professional baseball games.
Significance Statement
Nearly one of every 14 Major League Baseball games has lightning within what lightning safety experts would consider an unsafe distance. The potential for a lightning casualty incident is high because most games are played outdoors and millions of people are at baseball games every year. Although frameworks that can improve lightning safety at the thousands of professional baseball games that are played every year exist, it is unclear how frequently they are implemented.
Abstract
Because many viral respiratory diseases show seasonal cycles, weather conditions could affect the spread of coronavirus disease 2019 (COVID-19). Although many studies pursued this possible link early in the pandemic, their results were inconsistent. Here, we assembled 158 quantitative empirical studies examining the link between weather and COVID-19. A metaregression analysis was performed on their 4793 correlation coefficients to explain these inconsistent results. We found four principal findings. First, 80 of the 158 studies did not state the time lag between infection and reporting, rendering these studies ineffective in determining the weather–COVID-19 relationship. Second, the research outcomes depended on the statistical analysis methods employed in each study. Specifically, studies using correlation tests produced outcomes that were functions of the geographical locations of the data from the original studies, whereas studies using linear regression produced outcomes that were functions of the analyzed weather variables. Third, Asian countries had more positive associations for air temperature than other regions, possibly because the air temperature was undergoing its seasonal increase from winter to spring during the rapid outbreak of COVID-19 in these countries. Fourth, higher solar energy was associated with reduced COVID-19 spread, regardless of statistical analysis method and geographical location. These results help to interpret the inconsistent results and motivate recommendations for best practices in future research. These recommendations include calculating the effects of a time lag between the weather and COVID-19, using regression analysis models, considering nonlinear effects, increasing the time period considered in the analysis to encompass more variety of weather conditions and to increase sample size, and eliminating multicollinearity between weather variables.
Significance Statement
Many respiratory viruses have seasonal cycles, and COVID-19 may, too. Many studies have tried to determine the effects of weather on COVID-19, but results are often inconsistent. We try to understand this inconsistency through statistics. For example, half of the 158 studies we examined did not account for the time lag between infection and reporting a COVID-19 case, which would make these studies flawed. Other studies showed that more COVID-19 cases occurred at higher temperatures in Asian countries, likely because the season was changing from winter to spring as the pandemic spread. We conclude with recommendations for future studies to avoid these kinds of pitfalls and better inform decision-makers about how the pandemic will evolve in the future.
Abstract
Because many viral respiratory diseases show seasonal cycles, weather conditions could affect the spread of coronavirus disease 2019 (COVID-19). Although many studies pursued this possible link early in the pandemic, their results were inconsistent. Here, we assembled 158 quantitative empirical studies examining the link between weather and COVID-19. A metaregression analysis was performed on their 4793 correlation coefficients to explain these inconsistent results. We found four principal findings. First, 80 of the 158 studies did not state the time lag between infection and reporting, rendering these studies ineffective in determining the weather–COVID-19 relationship. Second, the research outcomes depended on the statistical analysis methods employed in each study. Specifically, studies using correlation tests produced outcomes that were functions of the geographical locations of the data from the original studies, whereas studies using linear regression produced outcomes that were functions of the analyzed weather variables. Third, Asian countries had more positive associations for air temperature than other regions, possibly because the air temperature was undergoing its seasonal increase from winter to spring during the rapid outbreak of COVID-19 in these countries. Fourth, higher solar energy was associated with reduced COVID-19 spread, regardless of statistical analysis method and geographical location. These results help to interpret the inconsistent results and motivate recommendations for best practices in future research. These recommendations include calculating the effects of a time lag between the weather and COVID-19, using regression analysis models, considering nonlinear effects, increasing the time period considered in the analysis to encompass more variety of weather conditions and to increase sample size, and eliminating multicollinearity between weather variables.
Significance Statement
Many respiratory viruses have seasonal cycles, and COVID-19 may, too. Many studies have tried to determine the effects of weather on COVID-19, but results are often inconsistent. We try to understand this inconsistency through statistics. For example, half of the 158 studies we examined did not account for the time lag between infection and reporting a COVID-19 case, which would make these studies flawed. Other studies showed that more COVID-19 cases occurred at higher temperatures in Asian countries, likely because the season was changing from winter to spring as the pandemic spread. We conclude with recommendations for future studies to avoid these kinds of pitfalls and better inform decision-makers about how the pandemic will evolve in the future.
Abstract
Tornadoes are nature’s most violent storm and annually cause billions of dollars in damage along with the threat of fatalities and injuries. To improve tornado warnings, the National Weather Service is considering a change from a deterministic to a probabilistic paradigm. While studies have been conducted on how individual behavior may change with the new warnings, no study of which we are aware has considered the effect this change may have on businesses. This project is a response to the Weather Research and Forecasting Innovation Act of 2017, House of Representatives (H.R.) bill 353, which calls for the use of social and behavioral science to study and improve storm warning systems. The goal is to discuss business response to probabilistic tornado warnings through descriptive and regression-based statistics using a survey administered to businesses in north Texas. Prior to release, the survey was vetted by a focus group composed of businesses in Grayson County, Texas, who assisted in the creation of a behavior ranking scale. The scale ranked behaviors from low to high effort. Responses allowed for determining whether the business reacted to the warning in a passive or active manner. Returned surveys came from large and small businesses in north Texas and represent a wide variety of industries. Regression analysis explores which variables have the greatest influence on the behavior of businesses and show that, beyond increases in probability from the probabilistic warnings, trust in the warning provides the most significant change to behavior.
Abstract
Tornadoes are nature’s most violent storm and annually cause billions of dollars in damage along with the threat of fatalities and injuries. To improve tornado warnings, the National Weather Service is considering a change from a deterministic to a probabilistic paradigm. While studies have been conducted on how individual behavior may change with the new warnings, no study of which we are aware has considered the effect this change may have on businesses. This project is a response to the Weather Research and Forecasting Innovation Act of 2017, House of Representatives (H.R.) bill 353, which calls for the use of social and behavioral science to study and improve storm warning systems. The goal is to discuss business response to probabilistic tornado warnings through descriptive and regression-based statistics using a survey administered to businesses in north Texas. Prior to release, the survey was vetted by a focus group composed of businesses in Grayson County, Texas, who assisted in the creation of a behavior ranking scale. The scale ranked behaviors from low to high effort. Responses allowed for determining whether the business reacted to the warning in a passive or active manner. Returned surveys came from large and small businesses in north Texas and represent a wide variety of industries. Regression analysis explores which variables have the greatest influence on the behavior of businesses and show that, beyond increases in probability from the probabilistic warnings, trust in the warning provides the most significant change to behavior.
Abstract
Extreme heat events pose a threat to human health. Forecasting and warning strategies have been developed to mitigate heat-health hazards. Yet, studies have found that the public lacks knowledge about their heat-health risks and preventive actions to take to reduce risks. Local governmental websites are an important means to communicate preparedness to the public. The purpose of this study is to examine information provided to the public on municipal government web pages of the 10 most populous U.S. cities. A two-level document and content analyses were conducted. A direct content analysis was conducted using federal government websites and documents to create the Extreme Heat Event Public Response Rubric. The rubric contains two broad categories of populations and actions that are further specified. The rubric was then used to examine local government extreme heat event websites for the 10 most populous cities in the United States. The examination of the local government sites found that information included on the websites failed to identify the breadth of populations at greater risk for adverse heat-health outcomes and omitted some recommended actions designed to prevent adverse heat-health events. Local governments often communicated concrete and simple content to the public but more complex information was not included on their websites.
Significance Statement
Extreme heat is the leading weather-related cause of mortality in the United States annually. Public response to extreme heat events requires that the public understand their risk and know the actions to take to mitigate that risk. The public seeks information from local government websites. Our results found that many local government websites did not provide the information to the public on the array of conditions and factors that put people at a greater risk for an adverse heat-health event, nor did the websites include information on the variety of actions that the public should take in response to an extreme heat event in order to reduce their risks. Addressing the omission of the information on these websites may improve public response to extreme heat events.
Abstract
Extreme heat events pose a threat to human health. Forecasting and warning strategies have been developed to mitigate heat-health hazards. Yet, studies have found that the public lacks knowledge about their heat-health risks and preventive actions to take to reduce risks. Local governmental websites are an important means to communicate preparedness to the public. The purpose of this study is to examine information provided to the public on municipal government web pages of the 10 most populous U.S. cities. A two-level document and content analyses were conducted. A direct content analysis was conducted using federal government websites and documents to create the Extreme Heat Event Public Response Rubric. The rubric contains two broad categories of populations and actions that are further specified. The rubric was then used to examine local government extreme heat event websites for the 10 most populous cities in the United States. The examination of the local government sites found that information included on the websites failed to identify the breadth of populations at greater risk for adverse heat-health outcomes and omitted some recommended actions designed to prevent adverse heat-health events. Local governments often communicated concrete and simple content to the public but more complex information was not included on their websites.
Significance Statement
Extreme heat is the leading weather-related cause of mortality in the United States annually. Public response to extreme heat events requires that the public understand their risk and know the actions to take to mitigate that risk. The public seeks information from local government websites. Our results found that many local government websites did not provide the information to the public on the array of conditions and factors that put people at a greater risk for an adverse heat-health event, nor did the websites include information on the variety of actions that the public should take in response to an extreme heat event in order to reduce their risks. Addressing the omission of the information on these websites may improve public response to extreme heat events.
Abstract
Climate change is an increasingly pressing concern because it generates individual and societal vulnerability in many places in the world and also because it potentially threatens political stability. Aside from sea level rise, climate change is typically manifested in local temperature and precipitation extremes that generate other hazards. In this study, we investigated whether certain kinds of governance strategies were more common in societies whose food supply had been threatened by such natural hazards—specifically, floods, droughts, and locust infestations. We coded and analyzed ethnographic data from the Human Relations Area Files on 26 societies regarding dominant political, economic, and ideological behaviors of leaders in each society for a specified time period. Leaders in societies experiencing food-destroying disasters used different political economic strategies for maintaining power than did leaders in societies that face fewer disasters or that did not face such disasters. In nondisaster settings, leaders were more likely to have inward-focused cosmological and collectivistic strategies; conversely, when a society had experienced food-destroying disasters, leaders were more likely to have exclusionary tribal/family-based and externally focused strategies. This apparent difficulty in maintaining order and coherence of leadership in disaster settings may apply more to politically complex societies than to polities governed solely at the community level. Alternatively, it could be that exclusionary leaders help set up the conditions for disastrous consequences of hazards for the populace. Exceptions to the pattern of exclusionary political economic strategies in disaster settings indicate that workarounds do exist that allow leaders with corporate governance approaches to stay in power.
Abstract
Climate change is an increasingly pressing concern because it generates individual and societal vulnerability in many places in the world and also because it potentially threatens political stability. Aside from sea level rise, climate change is typically manifested in local temperature and precipitation extremes that generate other hazards. In this study, we investigated whether certain kinds of governance strategies were more common in societies whose food supply had been threatened by such natural hazards—specifically, floods, droughts, and locust infestations. We coded and analyzed ethnographic data from the Human Relations Area Files on 26 societies regarding dominant political, economic, and ideological behaviors of leaders in each society for a specified time period. Leaders in societies experiencing food-destroying disasters used different political economic strategies for maintaining power than did leaders in societies that face fewer disasters or that did not face such disasters. In nondisaster settings, leaders were more likely to have inward-focused cosmological and collectivistic strategies; conversely, when a society had experienced food-destroying disasters, leaders were more likely to have exclusionary tribal/family-based and externally focused strategies. This apparent difficulty in maintaining order and coherence of leadership in disaster settings may apply more to politically complex societies than to polities governed solely at the community level. Alternatively, it could be that exclusionary leaders help set up the conditions for disastrous consequences of hazards for the populace. Exceptions to the pattern of exclusionary political economic strategies in disaster settings indicate that workarounds do exist that allow leaders with corporate governance approaches to stay in power.
Abstract
The human and economic costs of severe weather damage can be mitigated by appropriate preparation. Despite the benefits, researchers have only begun to examine if known decision-making frameworks apply to severe weather–related decisions. Using experiments, we found that a hyperbolic discounting function accurately described participant decisions to prepare for, and respond to, severe weather, although only delays of 1 month or longer significantly changed decisions to evacuate, suggesting that severe weather that is not imminent does not affect evacuation decisions. In contrast, the probability that a storm would impact the participant influenced evacuation and resource allocation decisions. To influence people’s evacuation decisions, weather forecasters and community planners should focus on disseminating probabilistic information when focusing on short-term weather threats (e.g., hurricanes); delay information appears to affect people’s evacuation decision only for longer-term threats, which may hold promise for climate change warnings.
Abstract
The human and economic costs of severe weather damage can be mitigated by appropriate preparation. Despite the benefits, researchers have only begun to examine if known decision-making frameworks apply to severe weather–related decisions. Using experiments, we found that a hyperbolic discounting function accurately described participant decisions to prepare for, and respond to, severe weather, although only delays of 1 month or longer significantly changed decisions to evacuate, suggesting that severe weather that is not imminent does not affect evacuation decisions. In contrast, the probability that a storm would impact the participant influenced evacuation and resource allocation decisions. To influence people’s evacuation decisions, weather forecasters and community planners should focus on disseminating probabilistic information when focusing on short-term weather threats (e.g., hurricanes); delay information appears to affect people’s evacuation decision only for longer-term threats, which may hold promise for climate change warnings.
Abstract
This study explored people’s perceptions of climate change by conducting interviews and focus-group discussions with local residents of three ecological regions of Nepal, i.e., mountain, midhills, and lowland. Climatic measurements from meteorological stations of the regions were acquired for the period from 1988 to 2018. We compared the people’s perception with trends and variabilities of observed temperature and rainfall patterns. The results showed that, over the last three decades, temperature and precipitation trends and variability between regions varied, largely corroborating the local experiences. The temperature increased in mountain, midhills, and lowland by 0.061°, 0.063°, and 0.017°C yr−1, respectively. In contrast, rainfall decreased by −9.7, −3.6, and −0.04 mm yr−1 for the regions, respectively. Although the amount of rainfall decrease observed in the mountain was highest, its variability was found to be relatively low, and vice versa in lowland. Approximately 88% of interviewees perceived temperature rise, and 74% noticed rainfall decline. Local residents linked these changes with their livelihood activities, as exemplified by, for example, crop’s quality and quantity and birds’ migration. The results indicate that local understandings complement the scarce observational data and provide a reliable and additional foundation to determine changes in climatic variables. Moreover, the result infers that small changes in climate variables have noticeable implications on human behavior change. Therefore, besides active participation of local communities, integrating local understanding is crucial in developing climate change–related policies and strategies at local and national levels.
Abstract
This study explored people’s perceptions of climate change by conducting interviews and focus-group discussions with local residents of three ecological regions of Nepal, i.e., mountain, midhills, and lowland. Climatic measurements from meteorological stations of the regions were acquired for the period from 1988 to 2018. We compared the people’s perception with trends and variabilities of observed temperature and rainfall patterns. The results showed that, over the last three decades, temperature and precipitation trends and variability between regions varied, largely corroborating the local experiences. The temperature increased in mountain, midhills, and lowland by 0.061°, 0.063°, and 0.017°C yr−1, respectively. In contrast, rainfall decreased by −9.7, −3.6, and −0.04 mm yr−1 for the regions, respectively. Although the amount of rainfall decrease observed in the mountain was highest, its variability was found to be relatively low, and vice versa in lowland. Approximately 88% of interviewees perceived temperature rise, and 74% noticed rainfall decline. Local residents linked these changes with their livelihood activities, as exemplified by, for example, crop’s quality and quantity and birds’ migration. The results indicate that local understandings complement the scarce observational data and provide a reliable and additional foundation to determine changes in climatic variables. Moreover, the result infers that small changes in climate variables have noticeable implications on human behavior change. Therefore, besides active participation of local communities, integrating local understanding is crucial in developing climate change–related policies and strategies at local and national levels.
Abstract
The relationship between El Niño–Southern Oscillation (ENSO) and the transatlantic slave trade (TAST) is examined using the Slave Voyages dataset and several reconstructed ENSO indices. The ENSO indices are used as a proxy for West African rainfall and temperature. In the Sahel, the El Niño (warm) phase of ENSO is associated with less rainfall and warmer temperatures, whereas the La Niña (cold) phase of ENSO is associated with more rainfall and cooler temperatures. The association between ENSO and the TAST is weak but statistically significant at a 2-yr lag. In this case, El Niño (drier and warmer) years are associated with a decrease in the export of enslaved Africans. The response of the TAST to El Niño is explained in terms of the societal response to agricultural stresses brought on by less rainfall and warmer temperatures. ENSO-induced changes to the TAST are briefly discussed in light of climate-induced movements of peoples in centuries past and the drought-induced movement of peoples in the Middle East today.
Significance Statement
The transatlantic slave trade was driven by economic and political forces, subject to the vagaries of the weather; it spanned two hemispheres and four continents and lasted more than 400 years. In this study we show that El Niño–Southern Oscillation, and its proxy association with West African rainfall and temperature, are significantly associated with the number of enslaved Africans that were transported from West Africa to the Americas. Lessons learned from the effects of weather and climate on the transatlantic slave trade reverberate today: extreme weather and climate change will continue to catalyze and amplify human conflict and migrations.
Abstract
The relationship between El Niño–Southern Oscillation (ENSO) and the transatlantic slave trade (TAST) is examined using the Slave Voyages dataset and several reconstructed ENSO indices. The ENSO indices are used as a proxy for West African rainfall and temperature. In the Sahel, the El Niño (warm) phase of ENSO is associated with less rainfall and warmer temperatures, whereas the La Niña (cold) phase of ENSO is associated with more rainfall and cooler temperatures. The association between ENSO and the TAST is weak but statistically significant at a 2-yr lag. In this case, El Niño (drier and warmer) years are associated with a decrease in the export of enslaved Africans. The response of the TAST to El Niño is explained in terms of the societal response to agricultural stresses brought on by less rainfall and warmer temperatures. ENSO-induced changes to the TAST are briefly discussed in light of climate-induced movements of peoples in centuries past and the drought-induced movement of peoples in the Middle East today.
Significance Statement
The transatlantic slave trade was driven by economic and political forces, subject to the vagaries of the weather; it spanned two hemispheres and four continents and lasted more than 400 years. In this study we show that El Niño–Southern Oscillation, and its proxy association with West African rainfall and temperature, are significantly associated with the number of enslaved Africans that were transported from West Africa to the Americas. Lessons learned from the effects of weather and climate on the transatlantic slave trade reverberate today: extreme weather and climate change will continue to catalyze and amplify human conflict and migrations.
