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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
Sara E. Harrison, Sally H. Potter, Raj Prasanna, Emma E. H. Doyle, and David Johnston

Abstract

Impact forecasts and warnings (IFW) are key to resilience for hydrometeorological hazards. Communicating the potential social, economic, and environmental hazard impacts allows individuals and communities to adjust their plans and better prepare for the consequences of the hazard. IFW systems require additional knowledge about impacts and underlying vulnerability and exposure. Lack of data or knowledge about impacts, vulnerability, and exposure has been identified as a challenge for IFW implementation. In this study, we begin to address this challenge by developing an understanding of the data needs and uses for IFWs. Using the grounded theory method, we conducted a series of interviews with users and creators of hazard, impact, vulnerability, and exposure data (e.g., warning services, forecasters, meteorologists, hydrologists, emergency managers, data specialists, risk modelers) to understand where these data are needed and used in the warning value chain, a concept used to represent and understand the flow of information among actors in the warning chain. In support of existing research, we found a growing need for creating, gathering, and using impact, vulnerability, and exposure data for IFWs. Furthermore, we identified different approaches for impact forecasting and defining impact thresholds using objective models and subjective impact-oriented discussions depending on the data available. We also provided new insight into a growing need to identify, model, and warn for social and health impacts, which have typically taken a back seat to modeling and forecasting physical and infrastructure impacts. Our findings on the data needs and uses within IFW systems will help guide their development and provide a pathway for identifying specific relevant data sources.

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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Karin Marie Antonsen, Brigt Dale, and Stephanie Mayer

Abstract

In 2018, tourism was the fastest growing sector in the world, accounting for 10% of all jobs worldwide and 10.4% of the world’s gross domestic product. Tourism is often cited as a strategy for future development at national, regional, and local levels. This paper takes a closer look at the Lofoten Islands in northern Norway, where the increase in nature-based tourism over the last two decades has occurred in parallel with the restructuring of the traditional fisheries. Nature-based tourism in rural regions relies heavily on a broad range of ecosystem services (ES). This paper will present how stakeholders in nature-based tourism assess the influence of climate change on ES crucial for their activities and for the destination and will outline and explain how the practitioners perceive their ability to withstand or adapt to these changes. With the aid of models depicting potential future climate scenarios, we initiated discussions with stakeholders and found that tourism actors have only to a minor degree sought to develop strategies to increase adaptive capacity and therefore resilience to climate change. Based on our findings, we discuss how the adaptive capacity of individual actors in nature-based tourism forms the basis for the system’s resilience, and that a general resilience focus also forms the basis for transformational capacity, a capacity needed for future resilience. In light of our findings and analyses, we will conclude by reflecting on overarching systemic transformative tendencies in the wake of coronavirus disease 2019 (COVID-19) and obligations contained in the Paris Agreement on reducing global emissions.

Open access
Keegan Fraser and Jennifer M. Fitchett

Abstract

In an era of globalization, the spread of misinformation is becoming increasingly problematic. The dissemination of inaccurate and conflicting news on events such as tropical cyclones can result in people being placed at increased risk and can negatively influence the amount of aid received by the affected region. This study scrutinizes media articles and, with the use of comparative analysis, uncovers the potential cause of misinformation in disaster journalism. The results of the study found that 59% (n = 80) of the articles reported on wind speed values and 80% (n = 80) of the articles reported on the number of fatalities. Results indicate that 44% (n = 80) of the articles used official sources, uncovering that a potential source of misinformation is not only what is provided to journalists from official sources but also how the various sources can lead to contradicting news articles. The variations in news reports can be attributed to factors such as the influx of different reports and the changing conditions during a disaster, all of which make consistent reporting on a disaster a challenging process.

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Brooke Fisher Liu, Anita Atwell Seate, Ji Youn Kim, Daniel Hawblitzel, Saymin Lee, and Xin Ma

Abstract

This study proposes the concept of quiet weather communication and offers the first framework of quiet weather communication strategies tied to specific public outcomes (e.g., build and maintain organization–public relationships). Most of the risk communication literature focuses on severe weather communication. We posit that through defining and examining quiet weather strategic communication we can better understand how the weather enterprise can prepare communities for future severe weather. Through four virtual focus groups with 28 NWS and broadcast meteorologists, we operationalize quiet weather communication strategies (humanize the organization, provide weather education, share the love of blue skies, and showcase quiet weather trends). We then report meteorologists’ perceptions of the strengths and weaknesses of each strategy and propose future directions for research on quiet weather communication.

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Michael K. Ndegwa, Apurba Shee, Calum Turvey, and Liangzhi You

Abstract

Weather index insurance (WII) has been a promising innovation that protects smallholder farmers against drought risks and provides resilience against adverse rainfall conditions. However, the uptake of WII has been hampered by high spatial and intraseasonal basis risk. To minimize intraseasonal basis risk, the standard approaches to designing WII based on seasonal cumulative rainfall have been shown to be ineffective in some cases because they do not incorporate different water requirements across each phenological stage of crop growth. One of the challenges in incorporating crop phenology in insurance design is to determine the water requirement in crop growth stages. Borrowing from agronomy, crop science, and agrometeorology, we adopt evapotranspiration methods in determining water requirements for a crop to survive in each stage that can be used as a trigger level for a WII product. Using daily rainfall and evapotranspiration data, we illustrate the use of Monte Carlo risk modeling to price an operational WII and WII-linked credit product. The risk modeling approach that we develop includes incorporation of correlation between rainfall and evapotranspiration indices that can minimize significant intertemporal basis risk in WII.

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