Perceptions and expected immediate reactions to tornado warning polygons Academic Article uri icon


  • 2015, Springer Science+Business Media Dordrecht. To provide people with more specific information about tornado threats, the National Weather Service has replaced its county-wide warnings with smaller warning polygons that more specifically indicate the risk area. However, tornado warning polygons do not have a standardized definition regarding tornado strike probabilities (ps) so it is unclear how warning recipients interpret them. To better understand this issue, 155 participants responded to 15 hypothetical warning polygons. After viewing each polygon, they rated the likelihood of a tornado striking their location and the likelihood that they would take nine different response actions ranging from continuing normal activities to getting in a car and driving somewhere safer. The results showed participants inferred that the ps was highest at the polygons centroid, lower just inside the edges of the polygon, still lower (but not zero) just outside the edges of the polygon, and lowest in locations beyond that. Moreover, higher ps values were associated with lower expectations of continuing normal activities and higher expectations of seeking information from social sources (but not environmental cues) and higher expectations of seeking shelter (but not evacuating in their cars). These results indicate that most people make some errors in their ps judgments but are likely to respond appropriately to the ps they infer from the warning polygons. Overall, the findings from this study and other research can help meteorologists to better understand how people interpret the uncertainty associated with warning polygons and, thus, improve tornado warning systems.

published proceedings


altmetric score

  • 15.5

author list (cited authors)

  • Lindell, M. K., Huang, S., Wei, H., & Samuelson, C. D.

citation count

  • 53

complete list of authors

  • Lindell, Michael K||Huang, Shih-Kai||Wei, Hung-Lung||Samuelson, Charles D

publication date

  • January 2016