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Effects of Track and Threat Information on Judgments of Hurricane Strike Probability

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  • Hao‐Che Wu
  • Michael K. Lindell
  • Carla S. Prater
  • Charles D. Samuelson

Abstract

Although evacuation is one of the best strategies for protecting citizens from hurricane threat, the ways that local elected officials use hurricane data in deciding whether to issue hurricane evacuation orders is not well understood. To begin to address this problem, we examined the effects of hurricane track and intensity information in a laboratory setting where participants judged the probability that hypothetical hurricanes with a constant bearing (i.e., straight line forecast track) would make landfall in each of eight 45 degree sectors around the Gulf of Mexico. The results from 162 participants in a student sample showed that the judged strike probability distributions over the eight sectors within each scenario were, unsurprisingly, unimodal and centered on the sector toward which the forecast track pointed. More significantly, although strike probability judgments for the sector in the direction of the forecast track were generally higher than the corresponding judgments for the other sectors, the latter were not zero. Most significantly, there were no appreciable differences in the patterns of strike probability judgments for hurricane tracks represented by a forecast track only, an uncertainty cone only, or forecast track with an uncertainty cone—a result consistent with a recent survey of coastal residents threatened by Hurricane Charley. The study results suggest that people are able to correctly process basic information about hurricane tracks but they do make some errors. More research is needed to understand the sources of these errors and to identify better methods of displaying uncertainty about hurricane parameters.

Suggested Citation

  • Hao‐Che Wu & Michael K. Lindell & Carla S. Prater & Charles D. Samuelson, 2014. "Effects of Track and Threat Information on Judgments of Hurricane Strike Probability," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1025-1039, June.
  • Handle: RePEc:wly:riskan:v:34:y:2014:i:6:p:1025-1039
    DOI: 10.1111/risa.12128
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    References listed on IDEAS

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    1. Simon French & Nikolaos Argyris & Stephanie M. Haywood & Matthew C. Hort & Jim Q. Smith, 2019. "Communicating Geographical Risks in Crisis Management: The Need for Research," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 9-16, January.
    2. Dean Kyne & William Donner, 2018. "Kyne–Donner Model of Authority’s Recommendation and Hurricane Evacuation Decisions: A Study of Hypothetical Hurricane Event in the Rio Grande Valley, Texas," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(6), pages 897-922, December.
    3. Baruch Fischhoff & Gabrielle Wong‐Parodi & Dana Rose Garfin & E. Alison Holman & Roxane Cohen Silver, 2018. "Public Understanding of Ebola Risks: Mastering an Unfamiliar Threat," Risk Analysis, John Wiley & Sons, vol. 38(1), pages 71-83, January.
    4. Hao‐Che Wu & Michael K. Lindell & Carla S. Prater, 2015. "Process Tracing Analysis of Hurricane Information Displays," Risk Analysis, John Wiley & Sons, vol. 35(12), pages 2202-2220, December.
    5. Seyed M. Miran & Chen Ling & Alan Gerard & Lans Rothfusz, 2018. "The effect of providing probabilistic information about a tornado threat on people’s protective actions," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(2), pages 743-758, November.

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