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Shannon M. McNeeley and Heather Lazrus

Abstract

The way in which people perceive climate change risk is informed by their social interactions and cultural worldviews comprising fundamental beliefs about society and nature. Therefore, perceptions of climate change risk and vulnerability along with people’s “myths of nature”—that is, how groups of people conceptualize the way nature functions—influence the feasibility and acceptability of climate adaptation planning, policy making, and implementation. This study presents analyses of cultural worldviews that broaden the current treatments of culture and climate change mitigation and adaptation decision making in communities. The authors use insights from community-based climate research and engage the Cultural Theory of Risk conceptual framework to situate community understandings of, and responses to, climate impacts. This study looks at how the issue of climate change manifests socially in four cases in the United States and Tuvalu and how ideas about climate change are produced by the institutional cultural contexts across scales from the local to the global. This approach helps us identify local and regional priorities and support the development of new relationships for adaptation research and planning by helping to diagnose barriers to climate change adaptation, assist improved communication through framing/reframing climate issues based on shared understandings and collective learning, and help move from conflict to cooperation through better negotiation of diverse worldviews.

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Shannon M. McNeeley and Heather Lazrus
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Pamela L. Heinselman, Daphne S. LaDue, and Heather Lazrus

Abstract

Rapid-scan weather radars, such as the S-band phased array radar at the National Weather Radar Testbed in Norman, Oklahoma, improve precision in the depiction of severe storm processes. To explore potential impacts of such data on forecaster warning decision making, 12 National Weather Service forecasters participated in a preliminary study with two control conditions: 1) when radar scan time was similar to volume coverage pattern 12 (4.5 min) and 2) when radar scan time was faster (43 s). Under these control conditions, forecasters were paired and worked a tropical tornadic supercell case. Their decision processes were observed and audio was recorded, interactions with data displays were video recorded, and the products were archived. A debriefing was conducted with each of the six teams independently and jointly, to ascertain the forecaster decision-making process. Analysis of these data revealed that teams examining the same data sometimes came to different conclusions about whether and when to warn. Six factors contributing toward these differences were identified: 1) experience, 2) conceptual models, 3) confidence, 4) tolerance of possibly missing a tornado occurrence, 5) perceived threats, and 6) software issues. The three 43-s teams issued six warnings: three verified, two did not verify, and one event was missed. Warning lead times were the following: tornado, 18.6 and 11.5 min, and severe, 6 min. The three tornado warnings issued by the three 4.5-min teams verified, though warning lead times were shorter: 4.6 and 0 min (two teams). In this case, use of rapid-scan data showed the potential to extend warning lead time and improve forecasters’ confidence, compared to standard operations.

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Ann Bostrom, Rebecca E. Morss, Jeffrey K. Lazo, Julie L. Demuth, Heather Lazrus, and Rebecca Hudson

Abstract

The study reported here explores how to enhance the public value of hurricane forecast and warning information by examining the entire warning process. A mental models research approach is applied to address three risk management tasks critical to warnings for extreme weather events: 1) understanding the risk decision and action context for hurricane warnings, 2) understanding the commonalities and conflicts in interpretations of that context and associated risks, and 3) exploring the practical implications of these insights for hurricane risk communication and management. To understand the risk decision and action context, the study develops a decision-focused model of the hurricane forecast and warning system on the basis of results from individual mental models interviews with forecasters from the National Hurricane Center (n = 4) and the Miami–South Florida Weather Forecast Office (n = 4), media broadcasters (n = 5), and public officials (n = 6), as well as a group decision-modeling session with a subset of the forecasters. Comparisons across professionals reveal numerous shared perceptions, as well as some critical differences. Implications for improving extreme weather event forecast and warning systems and risk communication are threefold: 1) promote thinking about forecast and warning decisions as a system, with informal as well as formal elements; 2) evaluate, coordinate, and consider controlling the proliferation of forecast and warning information products; and 3) further examine the interpretation and representation of uncertainty within the hurricane forecast and warning system as well as for users.

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Heather Lazrus, Betty H. Morrow, Rebecca E. Morss, and Jeffrey K. Lazo

Abstract

Risk communication may accentuate or alleviate the vulnerability of people who have particular difficulties responding to the threat of hazards such as hurricanes. The process of risk communication involves how hazard information is received, understood, and responded to by individuals and groups. Thus, risk communication and vulnerability interact through peoples' knowledge, attitudes, and practices. This study explores risk communication with several groups that may be at particular risk of hurricane impacts: older adults, newer residents, and persons with disabilities. Focus groups conducted in Miami, Florida, examined how members of these groups express their own vulnerability or agency in terms of receiving, interpreting, and responding to hurricane risk information. Findings indicate that people's interactions with risk information are deeply contextual and are facilitated by their individual agency to cope with their vulnerabilities.

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Rebecca E. Morss, Julie L. Demuth, Jeffrey K. Lazo, Katherine Dickinson, Heather Lazrus, and Betty H. Morrow

Abstract

This study uses data from a survey of coastal Miami-Dade County, Florida, residents to explore how different types of forecast and warning messages influence evacuation decisions, in conjunction with other factors. The survey presented different members of the public with different test messages about the same hypothetical hurricane approaching Miami. Participants’ responses to the information were evaluated using questions about their likelihood of evacuating and their perceptions of the information and the information source. Recipients of the test message about storm surge height and the message about extreme impacts from storm surge had higher evacuation intentions, compared to nonrecipients. However, recipients of the extreme-impacts message also rated the information as more overblown and the information source as less reliable. The probabilistic message about landfall location interacted with the other textual messages in unexpected ways, reducing the other messages’ effects on evacuation intentions. These results illustrate the importance of considering trade-offs, unintended effects, and information interactions when deciding how to convey weather information. Recipients of the test message that described the effectiveness of evacuation had lower perceptions that the information was overblown, suggesting the potential value of efficacy messaging. In addition, respondents with stronger individualist worldviews rated the information as significantly more overblown and had significantly lower evacuation intentions. This illustrates the importance of understanding how and why responses to weather messages vary across subpopulations. Overall, the analysis demonstrates the potential value of systematically investigating how different people respond to different types of weather risk messages.

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Julie L. Demuth, Rebecca E. Morss, Leysia Palen, Kenneth M. Anderson, Jennings Anderson, Marina Kogan, Kevin Stowe, Melissa Bica, Heather Lazrus, Olga Wilhelmi, and Jen Henderson

Abstract

This article investigates the dynamic ways that people communicate, assess, and respond as a weather threat evolves. It uses social media data, which offer unique records of what people convey about their real-world risk contexts. Twitter narratives from 53 people who were in a mandatory evacuation zone in a New York City neighborhood during Hurricane Sandy in 2012 were qualitatively analyzed. The study provides rich insight into the complex, dynamic information behaviors and risk assessments of people at risk, and it illustrates how social media data can be collected, sampled, and analyzed to help provide this understanding. Results show that this sample of people at significant risk attended to forecast information and evacuation orders as well as multiple types of social and environmental cues. Although many tweeted explicitly about the mandatory evacuation order, forecast information was usually referenced only implicitly. Social and environmental cues grew more important as the threat approached and often triggered heightened risk perceptions or protective actions. The results also reveal the importance of different aspects of people’s cognitive and affective risk perceptions as well as specific emotions (e.g., fear, anger) for understanding risk assessments. People discussed a variety of preparatory and protective behavioral responses and exhibited multiple types of coping responses (e.g., humor) as the threat evolved. People’s risk assessments and responses were closely intertwined, and their risk perceptions were not continuously elevated as the hurricane approached; they exhibited different ways of interpreting, coping, and responding as they accessed and processed evolving information about the threat.

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Rebecca E. Morss, Julie L. Demuth, Heather Lazrus, Leysia Palen, C. Michael Barton, Christopher A. Davis, Chris Snyder, Olga V. Wilhelmi, Kenneth M. Anderson, David A. Ahijevych, Jennings Anderson, Melissa Bica, Kathryn R. Fossell, Jennifer Henderson, Marina Kogan, Kevin Stowe, and Joshua Watts

Abstract

During the last few decades, scientific capabilities for understanding and predicting weather and climate risks have advanced rapidly. At the same time, technological advances, such as the Internet, mobile devices, and social media, are transforming how people exchange and interact with information. In this modern information environment, risk communication, interpretation, and decision-making are rapidly evolving processes that intersect across space, time, and society. Instead of a linear or iterative process in which individual members of the public assess and respond to distinct pieces of weather forecast or warning information, this article conceives of weather prediction, communication, and decision-making as an interconnected dynamic system. In this expanded framework, information and uncertainty evolve in conjunction with people’s risk perceptions, vulnerabilities, and decisions as a hazardous weather threat approaches; these processes are intertwined with evolving social interactions in the physical and digital worlds. Along with the framework, the article presents two interdisciplinary research approaches for advancing the understanding of this complex system and the processes within it: analysis of social media streams and computational natural–human system modeling. Examples from ongoing research are used to demonstrate these approaches and illustrate the types of new insights they can reveal. This expanded perspective together with research approaches, such as those introduced, can help researchers and practitioners understand and improve the creation and communication of information in atmospheric science and other fields.

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Shannon M. McNeeley, Sarah A. Tessendorf, Heather Lazrus, Tanya Heikkila, Ian M. Ferguson, Jennifer S. Arrigo, Shahzeen Z. Attari, Christina M. Cianfrani, Lisa Dilling, Jason J. Gurdak, Stephanie K. Kampf, Derek Kauneckis, Christine J. Kirchhoff, Juneseok Lee, Benjamin R. Lintner, Kelly M. Mahoney, Sarah Opitz-Stapleton, Pallav Ray, Andy B. South, Andrew P. Stubblefield, and Julie Brugger
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