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Effects of Track and Threat Information on Judgments of Hurricane Strike Probability
Author(s) -
Wu HaoChe,
Lindell Michael K.,
Prater Carla S.,
Samuelson Charles D.
Publication year - 2014
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/risa.12128
Subject(s) - track (disk drive) , landfall , sample (material) , meteorology , storm track , tropical cyclone , storm , environmental science , operations research , computer science , statistics , geography , engineering , mathematics , chemistry , chromatography , operating system
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.

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