Place, proximity, and perceived harm: extreme weather events and views about climate change

Zanocco, Chad; Boudet, Hilary; Nilson, Roberta S.; Satein, Hannah; Whitley, Hannah; Flora, June A.

doi:10.1007/s10584-018-2251-x

Cited by 124 publications

(68 citation statements)

References 35 publications

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“…Using mixed effects modeling (also known as multilevel modeling) allowed us to account for possible unobserved heterogeneity at different spatial levels (known as random effects), in this case, county (or Canadian district) and state (or Canadian province). A mixed effects modeling approach helps account for similarities (if there are any) between respondents living in the same county/district or state/province [118] and is an increasingly common approach for analyzing spatially-dependent survey data [72,92,[119][120][121][122][123]. We used ordinal logistic regression modeling instead of ordinary least squares linear regression modeling because our dependent variables were categorical and not normally distributed (Supplementary Materials).…”

Section: Discussionmentioning

confidence: 99%

Public Preferences in a Shifting Energy Future: Comparing Public Views of Eight Energy Sources in North America’s Pacific Northwest

Hazboun

Boudet

2020

Energies

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The U.S. and Canada continue to face major changes in energy production. Mounting awareness of the climate crisis has placed increasing importance on developing renewable energy sources, however, advances in fossil fuel extraction technology have opened vast domestic reserves of oil and natural gas. Public preferences for energy policy play a role in determining energy futures, but researchers rarely simultaneously compare public views across multiple renewable and non-renewable energies or across country boundaries. Here, we used a 2019 online survey sample (n = 1500) to compare predictors of support for eight fuel sources for electricity generation in British Columbia, Canada, and Washington and Oregon, USA. Results indicate the highest support overall for renewables (wind, solar, wave/tidal energy, geothermal) and the lowest for fossil fuels (coal and natural gas), nuclear, and hydropower. Mixed-effects regression modeling indicates that views on climate and the balance between environment and economy were consistent predictors of support across most energy types, while political ideology was less consistent. Perceived local importance of both extractive and renewable energy industries were significant predictors of support for some, but not all, energy sources, as were education and gender. Overall, our research suggests that while divisions persist in public energy preferences for both renewable and non-renewable sources, there is the broadest support for renewable energy technologies.

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Section: Discussionmentioning

confidence: 99%

Public Preferences in a Shifting Energy Future: Comparing Public Views of Eight Energy Sources in North America’s Pacific Northwest

Hazboun

Boudet

2020

Energies

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“…However, an earlier UK study [54] finds that flood experiences does not affect climate opinion, and a recent study suggests that coping capacity moderates the negative emotions from a flood event that would motivate opinion change [52]. A recent study in the US [77] surveyed four communities exposed to tornadoes or wildfires and finds that event proximity does not predict climate opinion, as opposed to subjective harm from the event. Similarly, case studies of particular events like a flood event in Boulder, Colorado [78] or a drought in the US Midwest [29] show no effect on climate opinions.…”

Section: The Effect Of Objective Non-temperature Experiences On Climamentioning

confidence: 99%

“…Yet, only a handful of papers covered by this review include fixed or random effects at any level, including regional [20,33,46,68], state [7,9,39,91], or geographies below the state level (e.g. county, city, weather station) [9,22,36,49,65,76,77,79].…”

Section: Causal Identification Of Weather On Perceptionsmentioning

confidence: 99%

“…Some studies forego theoretical groundings and limit their focus to documenting empirical associations (e.g. [10,66,73]), however, many [16,48,59,61,77,83] contextualize their work using one of two psychological theories: dual-process theory [97], which emerged from the cognitive-experiential self theory [98], and construal level theory (CLT) [99].…”

Section: The Need For Theoretical Context and Integrationmentioning

confidence: 99%

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How will climate change shape climate opinion?

Howe

Marlon

Mildenberger

et al. 2019

Environ. Res. Lett.

184

129

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As climate change intensifies, global publics will experience more unusual weather and extreme weather events. How will individual experiences with these weather trends shape climate change beliefs, attitudes, and behaviors? In this article, we review 73 papers that have studied the relationship between climate change experiences and public opinion. Overall, we find mixed evidence that weather shapes climate opinions. Although there is some support for a weak effect of local temperature and extreme weather events on climate opinion, the heterogeneity of independent variables, dependent variables, study populations, and research designs complicate systematic comparison. To advance research on this critical topic, we suggest that future studies pay careful attention to differences between self-reported and objective weather data, causal identification, and the presence of spatial autocorrelation in weather and climate data. Refining research designs and methods in future studies will help us understand the discrepancies in results, and allow better detection of effects, which have important practical implications for climate communication. As the global population increasingly experiences weather conditions outside the range of historical experience, researchers, communicators, and policymakers need to understand how these experiences shape-and are shaped by-public opinions and behaviors.

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“…Thus additional questions arise as to the functionalities of Smart Systems in the advance education, preparation, and warning process. When facing increasing environmental hazards in large population areas [31], the combination of public responses to perceived harm [32]-regardless of the frequency, recurrence, or intensity of a particular hazard [33,34]-creates uncertainty when applied to locations with specific yet variable characteristics.…”

Section: Introductionmentioning

confidence: 99%

Environmental Hazards: A Coverage Response Approach

Croft

2019

Future Internet

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The rapid rise and implementation of Smart Systems (i.e., multi-functional observation and platform systems that depict settings and/or identify situations or features of interest, often in real-time) has inversely paralleled and readily exposed the reduced capacity of human and societal systems to effectively respond to environmental hazards. This overarching review and essay explores the complex set of interactions found among Smart, Societal, and Environmental Systems. The resulting rise in the poorly performing response solutions to environmental hazards that has occurred despite best practices, detailed forecast information, and the use and application of real-time in situ observational platforms are considered. The application of Smart Systems, relevant architectures, and ever-increasing numbers of applications and tools development by individuals as they interact with Smart Systems offers a means to ameliorate and resolve confounding found among all of the interdependent Systems. The interactions of human systems with environmental hazards further expose society’s complex operational vulnerabilities and gaps in response to such threats. An examination of decision-making, the auto-reactive nature of responses before, during, and after environmental hazards; and the lack of scalability and comparability are presented with regard to the prospects of applying probabilistic methods, cross-scale time and space domains; anticipated impacts, and the need to account for multimodal actions and reactions—including psycho-social contributions. Assimilation of these concepts and principles in Smart System architectures, applications, and tools is essential to ensure future viability and functionalities with regard to environmental hazards and to produce an effective set of societal engagement responses. Achieving the promise of Smart Systems relative to environmental hazards will require an extensive transdisciplinary approach to tie psycho-social behaviors directly with non-human components and systems in order to close actionable gaps in response. Pathways to achieve a more comprehensive understanding are given for consideration by the wide diversity of disciplines necessary to move forward in Smart Systems as tied with the societal response to environmental hazards.

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Place, proximity, and perceived harm: extreme weather events and views about climate change

Cited by 124 publications

References 35 publications

Public Preferences in a Shifting Energy Future: Comparing Public Views of Eight Energy Sources in North America’s Pacific Northwest

Public Preferences in a Shifting Energy Future: Comparing Public Views of Eight Energy Sources in North America’s Pacific Northwest

How will climate change shape climate opinion?

Environmental Hazards: A Coverage Response Approach

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