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Seth P. Howard, Alison P. Boehmer, Kevin M. Simmons, and Kim E. Klockow-Mcclain

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.

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Eric C. Jones, Corinne Ong, and Jessica Haynes

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.

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David J. Cox, Joy E. Losee, and Gregory D. Webster

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.

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Kumar Bahadur Darjee, Prem Raj Neupane, and Michael Köhl

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.

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William Turner IV and Terrence R. Nathan

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.

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Camilla Risvoll, Grete K. Hovelsrud, and Jan Åge Riseth

Abstract

Rapid and interacting change poses an increasing threat to livelihoods and food production, and pastoralists in Nordland, northern Norway, are at a crossroads both economically and culturally. Some of these changes are localized and pertain to changing weather and grazing conditions caused by climate change and land fragmentation. Others, driven by national management policies and governance specifically related to predators, are poorly adjusted for the different and localized contexts. The pastoralists are inherently adaptive and have a long history of responding well to variable changing conditions. This is now changing with the continued increasing pressures from many directions. The central government systematically ignores pastoralists’ traditional knowledge and enforces narrow sector policies to be implemented at regional and local levels. We address the effect of how institutional, physical, and societal constraints challenge pastoralists’ prospects for sustainable adaptation. Our results show how pastoralists’ livelihoods become compromised and potentially threatened because they are forced to respond in ways that they know are counterproductive in the long run. Adaptation outcomes are affected by different approaches and epistemologies that are situated across scale and context in terms of regional and national regulations versus local empirical reality among the pastoral communities. This study concludes that radical change is needed toward a more holistic governance in which multiple knowledge systems are integrated to ensure sustainable adaptation at all levels. This study is based on extensive and long-term fieldwork among reindeer herders and sheep farmers in Nordland, through a collaborative process of knowledge coproduction.

Open access
Traoré Amadou, Gatien N. Falconnier, Kouressy Mamoutou, Serpantié Georges, B. A. Alassane, Affholder François, Giner Michel, and Sultan Benjamin

Abstract

Adaptation of the agricultural sector to climate change is crucial to avoid food insecurity in sub-Saharan Africa. Farmers’ perception of climate change is a crucial element in adaptation process. The aim of this study was (i) to compare farmers’ perception of climate change with actual weather data recorded in central Mali, (ii) to identify changes in agricultural practices implemented by farmers to adapt to climate change, and (iii) to investigate the link between farmers’ perception of climate change and implementation of adaptation practices. Focus group discussions and individual surveys were conducted to identify climate-related changes perceived by farmers and agricultural adaptation strategies they consider relevant to cope with these changes. A majority (>50%) of farmers perceived an increase in temperature, decrease in rainfall, shortening of growing season, early cessation of rainfall, and increase in the frequency of dry spells at the beginning of the growing season. In line with farmers’ perception, analysis of climate data indicated (i) an increase in mean annual temperature and minimum growing season temperature and (ii) a decrease in total rainfall. Farmers’ perception of early cessation of rainfall and more-frequent drought periods were not detected by climate data analysis. To cope with the decrease in rainfall and late start of the growing season, farmers used drought-tolerant cultivars and implemented water-saving technologies. Despite a perceived warming, no specific adaptation to heat stress was mentioned by farmers. We found evidence of a link between farmers’ perception of climate change and the implementation of some adaptation options. Our study highlights the need for a dialogue between farmers and researchers to develop new strategies to compensate for the expected negative impacts of heat stress on agricultural productivity.

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Ilan Noy and Eric Strobl

Abstract

This study investigates whether extreme heat episodes (heat waves) have contributed to the development of air conditioning (AC) technology in the United States. To this end, we use weather data to identify days at which heat and relative humidity were above levels comfortable to the human body, and match these with patent data at the county level for nearly a hundred years. We find that in the 2 years after a county has experienced extreme heat AC patents increase. Overall, average extreme heat exposure results in an increase of 7.5% greater innovation. We find no similar increase in the frequency of non-AC-related patent filings, and therefore conclude that heat waves result in innovation targeting their mitigation.

Significance Statement

The possibility of more extreme heat because of global warming has raised the question of whether society will be able to invent new technology to adapt to the likely greater frequency and severity of heat waves. The purpose of this paper is to consider the development of air conditioning in the United States and investigate whether extreme heat has indeed driven innovation in cooling technology. It is shown that, in counties with episodes of extreme heat, the number of air conditioning patents filed increased in the aftermath of these episodes, but that this increase was short-lived.

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Ling Tan and David M. Schultz

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.

Open access
David A. Call and Guy A. Flynt

Abstract

Snow has numerous effects on traffic, including reduced traffic volumes, greater crash risk, and increased travel times. This research examines how snow affects crash risk, traffic volume, and toll revenue on the New York State Thruway. Daily data from January for a 10-yr period (2010–19) were analyzed for the Thruway from the Pennsylvania state line in western New York to Syracuse. Anywhere from 35% to 50% of crashes are associated with inclement weather, with smaller impacts, proportionally, in areas with greater traffic volumes. As expected, snow was almost always involved when weather was a factor. “Unsafe speed” was the most common cause of crashes in inclement weather with all other factors (e.g., animals, drowsiness) much less likely to play a role. The percentage of crashes resulting in an injury did not change significantly with inclement conditions when compared with crashes occurring in fair conditions, and there were too few fatal crashes to make any inferences about them. Daily snowfall rates predicted about 30% of the variation in crash numbers, with every 5.1 cm of snowfall resulting in an additional crash, except in Buffalo where 5.1 cm of snow resulted in an additional 2.6 crashes. Confirming earlier results, daily snowfall had a large impact on passenger vehicle counts whereas commercial vehicle counts were less affected. Revenue data showed a similar pattern, with passenger revenue typically decreasing by 3%–5% per 2.5 cm of snow, whereas commercial revenue decreases were 1%–4% per 2.5 cm of snow.

Significance Statement

While it seems obvious that snowfall increases the number of crashes, decreases traffic volume, and reduces toll revenues, research is limited to support these assumptions, especially the latter two. This study involved an analysis of such items for the New York State Thruway. We found that increasing amounts of snow did cause more crashes. While traffic counts decreased, most of the decrease was in the number of passenger vehicles; commercial vehicle traffic was much less affected. Every 2.5 cm of snow costs the New York State Thruway approximately $1300 at each toll barrier and about $331 at each exit. These findings are helpful to law enforcement, emergency responders, and highway managers.

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