Journal
WEATHER CLIMATE AND SOCIETY
Volume 8, Issue 2, Pages 111-129Publisher
AMER METEOROLOGICAL SOC
DOI: 10.1175/WCAS-D-15-0033.1
Keywords
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Funding
- U.S. National Science Foundation [NSF 0729302, 0729511]
- Eunice Kennedy Shriver National Institute of Child Health and Human Development [R24 HD042828]
- Directorate For Geosciences
- Div Atmospheric & Geospace Sciences [0729511] Funding Source: National Science Foundation
- Divn Of Social and Economic Sciences
- Direct For Social, Behav & Economic Scie [1463492] Funding Source: National Science Foundation
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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-focusedmodel 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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