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Henry P. Huntington, Emma Archer, Walker S. Ashley, Susan L. Cutter, Michael A. Goldstein, Carla Roncoli, and Tanya L. Spero
Open access
Ana Raquel Nunes

Abstract

Extreme temperatures impact human health and well-being. Yet, very little empirical evidence exists on what determines human resilience, both in general and in relation to specified extreme temperatures. This paper addresses this serious gap in knowledge by developing a quantitative measure of general resilience (i.e., the resilience of individuals to all daily life circumstances). This is complemented with qualitative elicitations of specified resilience (i.e., the resilience of individuals to a particular type of threat, stress, or event), which in this study are extreme heat and extreme cold. This research uses the “sense of coherence” (SOC) approach (i.e., Orientation to Life Questionnaire—SOC-13 scale) to develop a general resilience index (GRI) using a composite index approach and to develop assessments of heat-related resilience (HRR) and cold-related resilience (CRR) using primary data from mixed-method interviews with 52 older people living in Lisbon, Portugal. The findings show that most participants exhibited high levels of general resilience but low levels of specified resilience. In particular, resilience to cold was lower than resilience to heat. Sources of general and specified resilience were found to be dependent on cognitive, behavioral, and motivational factors in older people’s lives. The findings reveal that believing threats (e.g., extreme temperatures) are structured and ordered, perceiving that assets are available to respond to them, and feeling it is worth responding are sources of resilience. Concrete policy recommendations can be generated from this study by both central and local governments to strengthen resilience. These can take the form of programs, plans, and actions that support individuals and enable them to better deal with challenging life events such as extreme temperatures and to improve both general and specified resilience.

Free access
Stephen B. Broomell, Gabrielle Wong-Parodi, Rebecca E. Morss, and Julie L. Demuth

Abstract

Reducing fatalities from tornadoes in the southeastern United States requires considering multiple societal factors, including the risk perceptions that influence how people interpret tornado forecasts and warnings and make protective decisions. This study investigates perceptions of tornado risk in the southeastern United States, operationalized as judgments of tornado likelihood. While it is possible that residents of the Southeast could learn about tornado likelihood in their region from observing the local environment, cognitive-ecological theory from psychology suggests that such judgments of likelihood can be inaccurate, even if other aspects of local knowledge are accurate. This study analyzes data from a survey that elicited different groups’ judgments of tornado likelihood associated with different seasons, times of day, and storm system types. Results are presented from a representative sample of Southeastern residents and are compared with a sample of tornado experts (who have extensive knowledge about the likelihood of Southeastern tornadoes) and a representative sample of Great Plains residents. Overall, the analysis finds that many members of the Southeastern public deviate from the expert sample on tornado likelihood, especially for winter and overnight tornadoes. These deviations from expert opinion mimic the judgments of the Great Plains public. This study demonstrates how psychological theory and a decision science approach can be used to identify potential gaps in public knowledge about hazardous weather risks, and it reveals several such potential gaps. Further research is needed to understand the reasons for deviations between public and expert judgments, evaluate their effects on protective decision-making, and develop strategies to address them.

Free access
David Samuel Williams

Abstract

Participatory modeling is commonly applied in climate change adaptation research to integrate stakeholder knowledge, beliefs, values, and norms into modeling processes. However, participation is not neutral, and current climate change adaptation research is tailored toward those with sufficient resources to adapt, as opposed to those most in need of adaptation. These are commonly marginalized stakeholder groups who remain on the social, economic, and political periphery, driving their vulnerability to climate change impacts. This paper presents the concept of autonomy in the context of multilevel governance for climate change adaptation before examining past participatory modeling approaches, illustrating the lack of application as an emancipatory tool for increasing the autonomy of marginalized stakeholder groups. Therefore, a list of 10 necessary conditions is presented for conducting participatory modeling for increasing the autonomy of marginalized stakeholder groups, strengthening multilevel governance for climate change adaptation. These theoretical foundations are intended to guide public policy and increase the societal impact of participatory modeling.

Significance Statement

Responding to climate change impacts requires the strengthening of multilevel governance. An important aspect is that multilevel governance is dependent on local actors having sufficient autonomy to carry out climate change adaptation actions. Participatory climate change adaptation research can contribute to enhancing autonomy for climate change adaptation in applying participatory modeling. This paper explains why this is important, how participatory modelers need to design their research, and in what way this could contribute to strengthening multilevel governance and the wider societal response to climate change impacts.

If you’re a scholar who studies the social impacts of climate change and you aren’t somehow an activist what are you really?—Professor Kian Goh, University of California, Los Angeles

Open access
Teresa A. Myers, Edward W. Maibach, Bernadette Woods Placky, Kimberly L. Henry, Michael D. Slater, and Keith L. Seitter

Abstract

Climate Matters is a localized climate change reporting resources program developed to support television (TV) weathercasters across the United States. Developed as a pilot test in one media market in 2010, it launched nationwide in 2013; in the autumn of 2019 more than 797 weathercasters were participating in the program. In this paper we present evidence of the impact of the Climate Matters program on Americans’ science-based understanding of climate change. We analyzed three sets of data in a multilevel model: 20 nationally representative surveys of American adults conducted biannually since 2010 (n = 23 635), data on when and how frequently Climate Matters stories were aired in each U.S. media market, and data describing the demographic, economic, and climatic conditions in each media market. We hypothesized that 1) reporting about climate change by TV weathercasters will increase science-based public understanding of climate change and 2) this effect will be stronger for people who pay more attention to local weather forecasts. Our results partially support the first hypothesis: controlling for market-level factors (population size, temperature, political ideology, and economic prosperity) and individual-level factors (age, education, income, gender, and political ideology), there is a significant positive association between the amount of Climate Matters reporting and some key indicators of science-based understanding (including that climate change is occurring, is primarily human caused, and causes harm). However, there was no evidence for the second hypothesis. These findings suggest that climate reporting by TV weathercasters, as enabled by the Climate Matters program, may be increasing the climate literacy of the American people.

Open access
Yujie Wang, Lianchun Song, Chris Hewitt, Nicola Golding, and Zili Huang

Abstract

The primary needs for climate services in China, in the form of climate information for decision-making, are to better prepare for and manage meteorological-related disasters, adaptation to climate change, and sustainable development. In this paper, the vision, structure, content, and governance of the China Framework for Climate Services, which is designed to respond to these primary needs, is described. This paper reflects on practice, lessons, and experience developing and delivering climate services in China for disaster risk reduction, agriculture, water, energy, urbanization, and major engineering projects. Four key aspects of successful climate services are highlighted: the transition of climate research to operational climate services; delivering relevant, tailored, and usable climate information; effective engagement between users and providers of climate services; and building interdisciplinary professional teams. Key challenges and opportunities for climate services are recognized in this paper: a growing gap between climate science and services capability and societal need, a lack of awareness in user communities of the climate service value for their activities, and the important need for closer and more meaningful interactions between users and providers of climate services. The delivery and uptake of high-quality, relevant, usable, and effective climate services will facilitate climate-smart decisions that will reduce climate risks and improve Chinese societal resilience.

Open access
Shannon Osaka, James Painter, Peter Walton, and Abby Halperin

Abstract

Extreme event attribution (EEA) is a relatively new branch of climate science combining weather observations and modeling to assess and quantify whether and to what extent anthropogenic climate change altered extreme weather events (such as heat waves, droughts, and floods). Such weather events are frequently depicted in the media, which enhances the potential of EEA coverage to serve as a tool to communicate on-the-ground climate impacts to the general public. However, few academic papers have systematically analyzed EEA’s media representation. This paper helps to fill this literature gap through a comprehensive analysis of media coverage of the 2011–17 California drought, with specific attention to the types of attribution and uncertainty represented. Results from an analysis of five U.S. media outlets between 2014 and 2015 indicate that the connection between the drought and climate change was covered widely in both local and national news. However, legitimate differences in the methods underpinning the attribution studies performed by different researchers often resulted in a frame of scientific uncertainty or disagreement in the media coverage. While this case study shows substantial media interest in attribution science, it also raises important challenges for scientists and others communicating the results of multiple attribution studies via the media.

Open access
Jun-Jie Chang, Yi-Ming Wei, Xiao-Chen Yuan, Hua Liao, and Bi-Ying Yu

Abstract

China, the second largest economy in the world, covers a large area spanning multiple climate zones, with varying economic conditions across regions. Given this variety in climate and economic conditions, global warming is expected to have heterogeneous economic impacts across the country. This study uses annual average temperature to conduct an empirical research from a top-down perspective to evaluate the nonlinear impacts of temperature change on aggregate economic output in China. We find that there is an inverted U-shaped relationship between temperature and economic growth at the provincial level, with a turning point at 12.2°C. The regional and national economic impacts are projected under the shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs). As future temperature rises, the economic impacts are positive in the northeast, north, and northwest regions but negative in the south, east, central, and southwest regions. Based on SSP5, the decrement in the GDP per capita of China would reach 16.0% under RCP2.6 and 27.0% under RCP8.5.

Free access
Henry P. Huntington and Gary M. Lackmann
Open access
Corey Davis, Heather Aldridge, Ryan Boyles, Karen S. McNeal, Lindsay Maudlin, and Rachel Atkins

Abstract

While there is growing demand for use of climate model projections to understand the potential impacts of future climate on resources, there is a lack of effective visuals that convey the range of possible climates across spatial scales and with uncertainties that potential users need to inform their impact assessments and studies. We use usability testing including eye tracking to explore how a group of resource professionals (foresters) interpret and understand a series of graphical representations of future climate change, housed within a web-based decision support system (DSS), that address limitations identified in other tools. We find that a three-map layout effectively communicates the spread of future climate projections spatially, that location-specific information is effectively communicated if depicted both spatially on a map and temporally on a time series plot, and that model error metrics may be useful for communicating uncertainty and in demonstrating the utility of these future climate datasets.

Open access