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Avital Li and James Ford

Abstract

This paper identifies and characterizes vulnerability to climatic change in the Ngöbe-Buglé Indigenous community of Playitas, Panama, using a “trajectories of change” approach. Playitas is a community composed of swidden forest farmers that is undergoing rapid rates of change as a result of demographic shifts, regional development, and climate change. Working in collaboration with a community organization, various methods were used to identify and characterize livelihoods, social-ecological dynamics, environmental change, and behavioral responses to change, with the aim of informing future planning in the community. Qualitative methods included semistructured interviews (n = 26), community workshops, and participant observation. Causal-loop diagrams based on field data and the perceptions of community members were created to model trajectories of change. The research reveals that change is driven by both internal and external factors and that the responses of community members create both reinforcing and balancing feedback loops that overall generate increased stress in agricultural systems, social structures, and environmental components. Although community members historically relied on social relationships, Indigenous knowledge, and remoteness as sources of resilience to external disturbances, climate change is acting as a “multiplier” of their existing vulnerabilities and is undermining their capacity to adapt to current and future climatic changes.

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Abigail Sullivan and Dave D. White

Abstract

Risk perceptions influence individual and collective action related to climate change, and there is an important gap between public and expert perceptions of climate change risk, especially in the United States. Past studies have found that on average 40% of the American public believe climate change will affect them personally. We contribute a study of climate change risk perceptions in the metropolitan areas of three western U.S. cities (Denver, Colorado; Las Vegas, Nevada; Phoenix, Arizona), assessing overall patterns and drivers. A representative mail survey (N = 786) of the general public in these cities revealed that 60% of respondents identified climate change as personally risky, with the perception that it will impact either their family or their city in the next 30 years. Our results indicate that the gap in risk perceptions between the public and experts may be decreasing, although we discuss several limitations and reasons why this result requires further investigation. Using regression models, we analyze factors that are hypothesized to drive risk perceptions and discover that pro-environmental worldview and perceived personal responsibility are the most influential predictors. We discuss the implications of our results for fostering collective action to address climate change in dry, western U.S. metropolitan areas.

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Emily D. Esplin, Jennifer R. Marlon, Anthony Leiserowitz, and Peter D. Howe

Abstract

The risks associated with extreme heat are increasing as heat waves become more frequent and severe across larger areas. As people begin to experience heat waves more often and in more places, how will individuals respond? Measuring experience with heat simply as exposure to extreme temperatures may not fully capture how people subjectively experience those temperatures or their varied impacts on human health. These impacts may also influence an individual’s response to heat and motivate risk-reduction behaviors. If subjectively experiencing negative health effects from extreme heat promotes protective actions, these effects could be used alongside temperature exposure to more accurately measure extreme heat experience and inform risk prevention and communication strategies according to local community needs. Using a multilevel regression model, this study analyzes georeferenced national survey data to assess whether Americans’ exposure to extreme heat and experience with its health effects are associated with self-reported protective behaviors. Subjective experience with heat-related health symptoms strongly predicted all reported protective behaviors while measured heat exposure had a much weaker influence. Risk perception was strongly associated with some behaviors. This study focuses particularly on the practice of checking on family, friends, and neighbors during a heat wave, which can be carried out by many people. For this behavior, age, race/ethnicity, gender, and income, along with subjective experience and risk perception, were important predictors. Results suggest that the subjective experience of extreme heat influences health-related behavioral responses and should therefore be considered when designing or improving local heat protection plans.

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Kurt B. Waldman, Noemi Vergopolan, Shahzeen Z. Attari, Justin Sheffield, Lyndon D. Estes, Kelly K. Caylor, and Tom P. Evans

Abstract

Given the varying manifestations of climate change over time and the influence of climate perceptions on adaptation, it is important to understand whether farmer perceptions match patterns of environmental change from observational data. We use a combination of social and environmental data to understand farmer perceptions related to rainy season onset. Household surveys were conducted with 1171 farmers across Zambia at the end of the 2015/16 growing season eliciting their perceptions of historic changes in rainy season onset and their heuristics about when rain onset occurs. We compare farmers’ perceptions with satellite-gauge-derived rainfall data from the Climate Hazards Group Infrared Precipitation with Station dataset and hyper-resolution soil moisture estimates from the HydroBlocks land surface model. We find evidence of a cognitive bias, where farmers perceive the rains to be arriving later, although the physical data do not wholly support this. We also find that farmers’ heuristics about rainy season onset influence maize planting dates, a key determinant of maize yield and food security in sub-Saharan Africa. Our findings suggest that policy makers should focus more on current climate variability than future climate change.

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Matthew Berman and Jennifer I. Schmidt

Abstract

We summarize the potential nature and scope of economic effects of climate change in Alaska that have already occurred and are likely to become manifest over the next 30–50 years. We classified potential effects discussed in the literature into categories according to climate driver, type of environmental service affected, certainty and timing of the effects, and potential magnitude of economic consequences. We then described the nature of important economic effects and provided estimates of larger, more certain effects for which data were available. Largest economic effects were associated with costs to prevent damage, relocate, and replace infrastructure threatened by permafrost thaw, sea level rise, and coastal erosion. The costs to infrastructure were offset by a large projected reduction in space heating costs attributable to milder winters. Overall, we estimated that five relatively certain, large effects that could be readily quantified would impose an annual net cost of $340–$700 million, or 0.6%–1.3% of Alaska’s GDP. This significant, but relatively modest, net economic effect for Alaska as a whole obscures large regional disparities, as rural communities face large projected costs while more southerly urban residents experience net gains.

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Juergen Weichselgartner and Berit Arheimer

Abstract

The current landscape of climate services represents a highly diverse and still growing range of programs, projects, and portals involved in developing and/or providing climate services at different administrative levels and spatial–temporal scales. The diversity of service producers, users, and policy arenas has created a highly heterogeneous data- and information-oriented service landscape, and the authors contend that the domain of climate services requires efforts toward agreed structures and forms of conceptualization, operationalization, and evaluation. It is proposed here that qualitative classification be applied into climate change adaptation products, services, and systems to better guide research, policy, and practice with a clear terminology and analysis framework. This differentiation allows the pinpointing of critical challenges associated with the production and application of climate-relevant information, as well as the identification of suitable metrics to assess the impact of climate services. The article concludes with recommendations to advance climate services into knowledge–action systems and increase their sustainability.

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Ernest Agee and Lindsey Taylor

Abstract

The record of tornado fatalities in the United States for over two centuries (1808–2017) and decadal census records have been examined to search for historical trends. Particular attention has been given to the response to population growth and expansion into the tornado-prone regions of the country. The region selected includes the Tornado Alley of the central Great Plains, the Dixie Alley in the southeastern states, and the adjoining states in the Midwest that collectively encompass a 21-state rectangular region. The data record has been divided into two subintervals, Era A (1808–1915) and Era B (1916–2017), each of which consists of three equal-length periods. Era A is characterized by a growing and westward expanding population along with a basic absence of scientific knowledge, technology, and communications (for prediction, detection, and warning). This is followed by a renaissance of discovery and advancement in Era B that contributes to saving lives. The aforementioned periods are defined by a set of notable events that help to define the respective periods. A death per population index (DPI) is used to evaluate the 21 states in each era; there is a rise of mean DPI values to a maximum of 1.50 at the end of Era A and a subsequent fall to 0.21 at the end of Era B. It is also shown for all three periods in Era B that the deadliest tornado states, in ranked order, are Arkansas, Mississippi, Alabama, and Oklahoma. Suggestions are presented for ways to continue the decreasing trend in DPI, which would imply that the death rate increase is not as fast as the rate of population increase (or would even imply a decreasing death rate).

Open access
Mengqi Ye, Jidong Wu, Cailin Wang, and Xin He

Abstract

Tropical cyclones (TCs) can wreak havoc on the landscape and overwhelm communities. Since economic exposure is an important factor in damage function, an evaluation of economic exposure is essential because the characteristics of TC-related hazards are changing under accelerating economic development patterns. Here, we first reconstructed the wind and rainfall fields of historical TCs through an extensive database to extract the economic exposure to TC-prone areas on the mainland of China. We found that rainfall is an important factor in determining the affected extent of a TC event and that economic exposure will be misestimated when considering only the wind field. The results reveal that economic exposure to TCs has increased considerably from 1990 to 2015 and will continue to increase until the year 2100 under shared socioeconomic pathways (SSPs). We found that 66.7% of China’s gross domestic product [GDP; CNY 48.6 trillion (7.8 trillion U.S. dollars)] and 63.9% of China’s asset value [CNY 139.5 trillion (22.4 trillion U.S. dollars)] were concentrated in TC-prone areas in 2015 and increased at an average annual rate of 10.6% and 13.9%, respectively. Projections of GDP scenarios under SSPs revealed continued growth in the early twenty-first century, and the range of GDP and asset value in TC-prone areas by 2100 varied. Further detailed studies are needed to provide a detailed damage function for TC loss assessments under climate change and to consider how TC hazards will interact under changes in exposure and vulnerability related to economic development and social change.

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Allison Engblom, Kristin Timm, Raphael Mazzone, David Perkins, Teresa Myers, and Edward Maibach

Abstract

Most Americans misperceive climate change as distant risk; TV weathercasters can help correct this misperception by reporting on the current local impacts of climate change. Some weathercasters, however, are concerned that such reporting may alienate skeptical viewers. The goal of this study was to develop a better understanding of how viewers respond to climate change information delivered by weathercasters. Interviews were conducted with 30 local TV news viewers in Virginia with divergent views about climate change, categorized as engaged, disengaged, and unconvinced. During the interview, participants were shown two graphics and two videos about the local impacts of climate change. Most participants in all groups [21/30 (70%)] expressed interest in learning about climate change from weathercasters, particularly local and national impacts. Most participants in all three groups understood the key points and responded positively to both the graphics and the videos. Several unconvinced participants (6/10) were disinterested in seeing climate change information in the weather segment, but they were not opposed to it; they felt the weather segment was too short to adequately explain the information. These preliminary findings suggest that most of the local TV news viewers interviewed in this study—even those unconvinced that human-caused climate change is happening—respond positively to TV weathercasters as local climate educators. These findings are consistent with the reports of TV weathercasters who say that when they report on climate change, they receive far more positive than negative feedback from viewers.

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Katie A. Wilson, Pamela L. Heinselman, Patrick S. Skinner, Jessica J. Choate, and Kim E. Klockow-McClain

Abstract

During the 2017 Spring Forecasting Experiment in NOAA’s Hazardous Weather Testbed, 62 meteorologists completed a survey designed to test their understanding of forecast uncertainty. Survey questions were based on probabilistic forecast guidance provided by the NSSL Experimental Warn-on-Forecast System for ensembles (NEWS-e). A mix of 20 multiple-choice and open-ended questions required participants to explain basic probability and percentile concepts, extract information using graphical representations of uncertainty, and determine what type of weather scenario the graphics depicted. Multiple-choice questions were analyzed using frequency counts, and open-ended questions were analyzed using thematic coding methods. Of the 18 questions that could be scored, 60%–96% of the participants’ responses aligned with the researchers’ intended response. Some of the most challenging questions proved to be those requiring qualitative explanations, such as to explain what the 70th-percentile value of accumulated rainfall represents in an ensemble-based probabilistic forecast. Additionally, participants providing answers not aligning with the intended response oftentimes appeared to consider the given information with a deterministic rather than probabilistic mindset. Applications of a deterministic mindset resulted in tendencies to focus on the worst-case scenario and to modify understanding of probabilistic concepts when presented with different variables. The findings from this survey support the need for improved basic and applied training for the development, interpretation, and use of probabilistic ensemble forecast guidance. Future work should collect data for a larger sample size to examine the knowledge gaps across specific user groups and to guide development of probabilistic forecast training tools.

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