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Joseph T. Ripberger, Makenzie J. Krocak, Wesley W. Wehde, Jinan N. Allan, Carol Silva, and Hank Jenkins-Smith

Abstract

Social criteria are important to achieving the mission of the National Weather Service. Accordingly, researchers and administrators at the NWS increasingly recognize a need to supplement verification statistics with complementary data about society in performance management and evaluation. This will require significant development of new capacities to both conceptualize relevant criteria and measure them using consistent, transparent, replicable, and reliable measures that permit generalizable inference to populations of interest. In this study, we contribute to this development by suggesting three criteria that require measurement (forecast and warning reception, comprehension, and response) and demonstrating a methodology that allows us to measure these concepts in a single information domain—tornado warnings. The methodology we employ improves upon previous research in multiple ways. It provides a more generalizable approach to measurement using a temporally consistent set of survey questions that are applicable across the United States; it relies on a more robust set of psychometric tests to analytically demonstrate the reliability of the measures; and it is more transparent and replicable than previous research because the data and methods (source code) are publicly available. In addition to describing and assessing the reliability of the measures, we explore the sensitivity of the measures to geographic and demographic variation to identify significant differences that require attention in measurement. We close by discussing the implications of this study and the next steps toward development and use of social criteria in performance management and evaluation.

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Andrea L. Taylor, Astrid Kause, Barbara Summers, and Melanie Harrowsmith

Abstract

In the United Kingdom, the Met Office issues regionally calibrated impact-based weather warnings. These aim to reduce harm to people and property. To decrease risk from severe weather, it is important to understand how members of the U.K. public interpret and act on these warnings. This paper addresses this through a postevent survey (n = 552) conducted following Storm Doris, a 2017 winter storm during which wind warnings were issued across much of the United Kingdom. Survey questions examined 1) understanding of impact-based wind warnings, 2) interpretation of local warning level, 3) predictors of perceived local risk (likelihood, impact severity, concern) implied by warnings, 4) predictors of trust in the forecast, and 5) predictors of recalled and anticipated action. Our findings indicate that U.K. residents generally understand that weather warnings are based on potential weather impacts, although many do not realize warnings are regionally calibrated. We also find that while local warning levels are rarely underestimated, they may sometimes be overestimated. Institutional trust in the Met Office and perceived vulnerability to weather predict both perceived risk and behavioral response, while warning “understandability” is linked to greater trust in the forecast. Strikingly, while differences in local warning levels influenced risk perception, they did not affect recalled or intended behavioral response. This study highlights the importance of institutional trust in the effective communication of severe weather warnings, and a need for education on impact-based weather warnings. Above all, it demonstrates the need for further exploration of the effect of weather warnings on protective behavior.

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S. Ziaja

Abstract

Climate adaptation relies on theoretical frameworks of coproduced science and knowledge networks to produce acceptable outcomes for politically contentious resources. As adaptation moves from theory to implementation, there is a need for positive case studies to use as benchmarks. Building from literature on actionable science this paper presents one such positive case—the development of a hydropower and reservoir decision-support tool. The focus of this history is on the multiple phases of interaction (and noninteraction) between researchers and a semidefined community of stakeholders. The lessons presented from the Integrated Forecast and Reservoir Management (INFORM) system project stress that collaborations between managers and researchers were crucial to the success of the project by building knowledge networks, which could outlast formal processes, and by incorporating policy preferences of end users into the model. The history also provides examples of how even successful collaborative projects do not always follow the usual expectations for coproduced science and shows that, even when those guidelines are followed, external circumstances can threaten the adoption of research products. Ultimately, this paper argues for the importance of building strong knowledge networks alongside more formal processes—like those in boundary organizations—for effective collaborative engagement.

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Adam J. Kalkstein, Miloslav Belorid, P. Grady Dixon, Kyu Rang Kim, and Keith A. Bremer

Abstract

South Korea has among the highest rates of suicide in the world, and previous research suggests that suicide frequency increases with anomalously high temperatures, possibly as a result of increased sunshine. However, it is unclear whether this temperature–suicide association exists throughout the entire year. Using distributed lag nonlinear modeling, which effectively controls for nonlinear and delayed effects, we examine temperature–suicide associations for both a warm season (April–September) and a cool season (October–March) for three cities across South Korea: Seoul, Daegu, and Busan. We find consistent, statistically significant, mostly linear relationships between relative risk of suicide and daily temperature in the cool season but few associations in the warm season. This seasonal signal of statistically significant temperature–suicide associations only in the cool season exists among all age segments, but especially for those 35 and older, along with both males and females. We further use distributed lag nonlinear modeling to examine cloud cover–suicide associations and find few significant relationships. This result suggests that that high daily temperatures in the cool season, and not exposure to sun, are responsible for the strong temperature–suicide associations found in South Korea.

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Bogdan Antonescu, David M. Schultz, Hugo M. A. M. Ricketts, and Dragoş Ene

Abstract

Tornadoes and waterspouts have long fascinated humankind through their presence in myths and popular beliefs and originally were believed to have supernatural causes. The first theories explaining weather phenomena as having natural causes were proposed by ancient Greek natural philosophers. Aristotle was one of the first natural philosophers to speculate about the formation of tornadoes and waterspouts in Meteorologica (circa 340 BCE). Aristotle believed that tornadoes and waterspouts were associated with the wind trapped inside the cloud and moving in a circular motion. When the wind escapes the cloud, its descending motion carries the cloud with it, leading to the formation of a typhon (i.e., tornado or waterspout). His theories were adopted and further nuanced by other Greek philosophers such as Theophrastus and Epicurus. Aristotle’s ideas also influenced Roman philosophers such as Lucretius, Seneca, and Pliny the Elder, who further developed his ideas and also added their own speculations (e.g., tornadoes do not need a parent cloud). Almost ignored, Meteorologica was translated into Latin in the twelfth century, initially from an Arabic version, leading to much greater influence over the next centuries and into the Renaissance. In the seventeenth century, the first book-length studies on tornadoes and waterspouts were published in Italy and France, marking the beginning of theoretical and observational studies on these phenomena in Europe. Even if speculations about tornadoes and waterspouts proposed by Greek and Roman authors were cited after the nineteenth century only as historical pieces, core ideas of modern theories explaining these vortices can be traced back to this early literature.

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Yoko Kusunose, Lala Ma, and David Van Sanford

Abstract

Weather and climate forecasts can help agricultural producers improve management choices in anticipation of uncertain growing conditions. Current literature conjectures that the extent to which forecasts are useful depends on their accuracy, that is, the probability with which a forecasted event, such as precipitation, is projected to occur. Too little accuracy can potentially render forecasts effectively useless, even if they convey some form of information. In this study, we collect farmer-based data through a questionnaire and a framed field experiment to test for the existence of an accuracy threshold for forecasts, below which forecasts do not induce any behavioral changes. We do this in the context of a very specific management choice—the timing and amount of nitrogen that Kentucky farmers apply to their wheat in early spring—in response to randomly generated 6-to-10-day forecasts of rainfall conditions. We find that forecasts provide economically significant value to decision-makers only when they depart dramatically from what is normally expected. These results have implications that extend beyond the nitrogen-application decision for winter wheat: if this type of behavior is widespread, at current accuracy levels, other types of forecasts may be of little value to decision-makers and therefore go unheeded.

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Maya K. Buchanan, Michael Oppenheimer, and Adam Parris

Abstract

Sea level rise amplifies flooding from tides and storms for coastal communities around the globe. Although the characterization of these physical hazards has improved, it is people’s behavior that will ultimately determine the impact on communities. This study adds to our understanding of how people may respond to various adaptation options and policies, using a household survey in New York City, New York, neighborhoods affected by Hurricane Sandy. We investigate previously overlooked factors that may influence intended household adaptive behavior, such as single-action bias, a cognitive trade-off that households make between adaptation options, whereby taking a small (and often less effective measure) may strongly discourage uptake of a more protective measure. Through a novel application of discrete choice experiments in the coastal adaptation context, we simulate plausible future conditions to assess potential adaptation under climatic and nonclimatic stressors. Our findings suggest that single-action bias plays a substantial role in intended coastal adaptation, whereby the odds of homeowners who have already implemented a modest-cost measure to insure and relocate in the future are 66% and 80% lower, respectively. The odds of homeowners to relocate are also ~1.9, ~2.2, and ~3.1 times as great if their peers relocate, nuisance flooding becomes a frequent occurrence, and property values fall substantially, respectively. We find that renters’ motivation to relocate is largely driven more by external issues such as crime, gentrification, and economic security than by flood hazard.

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Kieran M. Findlater, Milind Kandlikar, Terre Satterfield, and Simon D. Donner

Abstract

Despite long-standing assertions that climate change creates new risk management challenges, the climate change adaptation literature persists in assuming, both implicitly and explicitly, that weather and climate variability are suitable proxies for climate change in evaluating farmers’ risk perceptions and predicting their adaptive responses. This assumption persists in part because there is surprisingly little empirical evidence either way, although case studies suggest that there may be important differences. Here, we use a national survey of South Africa’s commercial grain farmers (n = 389)—similar to their peers in higher-income countries (e.g., North America, Europe, Australia), but without subsidies—to show that they treat weather and climate change risks quite differently. We find that their perceptions of climate change risks are distinct from and, in many regards, oppositional to their perceptions of weather risks. While there seems to be a temporal element to this distinction (i.e., differing concern for short-term vs long-term risks), there are other differences that are better understood in terms of normalcy (i.e., normal vs abnormal relative to historical climate) and permanency (i.e., temporary vs permanent changes). We also find an interaction effect of education and political identity on concern for climate change that is at odds with the well-publicized cultural cognition thesis based on surveys of the American public. Overall, studies that use weather and climate variability as unqualified proxies for climate change are likely to mislead researchers and policymakers about how farmers perceive, interpret, and respond to climate change stimuli.

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Kerstin K. Zander, Simon Moss, and Stephen T. Garnett

Abstract

There is mounting evidence that climate change impacts compromise people’s well-being. Many regions of Australia have experienced record hot temperatures and more frequent and longer heat waves with substantial consequences for people, economies, and ecosystems. Using data from an Australia-wide online survey with 1101 respondents, we investigated the relationship between self-reported measures of heat stress and different dimensions of subjective well-being. After controlling for socioeconomic factors known to affect well-being, we found that heat stress was linked to people’s certainty about and planning for their future but not to their life satisfaction, happiness, social state, capabilities, or purpose in life. This result indicates that, while heat is not associated with present well-being, many people worry about the effect that increased heat will have on their future well-being. People who were uncertain about their future were also more likely than those who did not feel uncertain to think that heat compromised their productivity. People who agreed that they were competent and capable in their activities rated their heat stress–related productivity loss lower than those who disagreed. The findings are relevant for future studies using life-satisfaction approaches to assess consequences of climate change impacts and to studies in “happiness economics.” We recommend that future research on the impact of climate change on well-being go beyond simply life satisfaction and happiness and test multiple dimensions of well-being.

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Erik Løhre, Marie Juanchich, Miroslav Sirota, Karl Halvor Teigen, and Theodore G. Shepherd

Abstract

The use of interval forecasts allows climate scientists to issue predictions with high levels of certainty even for areas fraught with uncertainty, since wide intervals are objectively more likely to capture the truth than narrow intervals. However, wide intervals are also less informative about what the outcome will be than narrow intervals, implying a lack of knowledge or subjective uncertainty in the forecaster. In six experiments, we investigate how laypeople perceive the (un)certainty associated with wide and narrow interval forecasts, and find that the preference for accuracy (seeing wide intervals as “objectively” certain) versus informativeness (seeing wide intervals as indicating “subjective” uncertainty) is influenced by contextual cues (e.g., question formulation). Most important, we find that people more commonly and intuitively associate wide intervals with uncertainty than with certainty. Our research thus challenges the wisdom of using wide intervals to construct statements of high certainty in climate change reports.

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