A mental models study of hurricane forecast and warning production, communication, and decision-making

AMS Citation:
Bostrom, A., R. E. Morss, J. K. Lazo, J. Demuth, H. Lazrus, and R. Hudson, 2016: A mental models study of hurricane forecast and warning production, communication, and decision-making. Weather, Climate, and Society, 8, 111-129, doi:10.1175/WCAS-D-15-0033.1.
Resource Type:article
Title:A mental models study of hurricane forecast and warning production, communication, and decision-making
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.
Peer Review:Refereed
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OpenSky citable URL: ark:/85065/d7sb47bm
Publisher's Version: 10.1175/WCAS-D-15-0033.1
  • Ann Bostrom
  • Rebecca Morss - NCAR/UCAR
  • Jeffrey Lazo - NCAR/UCAR
  • Julie Demuth - NCAR/UCAR
  • Heather Lazrus - NCAR/UCAR
  • Rebecca Hudson
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