Environmental risk perception from visual cues: the psychophysics of tornado risk perception. (8th December 2015)

• Record Type: Journal Article
• Authors: Dewitt, Barry; Fischhoff, Baruch; Davis, Alexander; Broomell, Stephen B
• Is Part Of: Environmental research letters. Volume 10:Number 12(2015:Dec.)
• Publication Date: 2015-12-08
• Subjects: decision-making -- risk perception -- risk communication -- signal detection theory -- multidimensional scaling; Environmental sciences -- Periodicals; Human ecology -- Research -- Periodicals; Environmental health -- Periodicals; 333.7
• DOI: 10.1088/1748-9326/10/12/124009
• Languages: English
• ISSNs: 1748-9326

Abstract

Abstract: Lay judgments of environmental risks are central to both immediate decisions (e.g., taking shelter from a storm) and long-term ones (e.g., building in locations subject to storm surges). Using methods from quantitative psychology, we provide a general approach to studying lay perceptions of environmental risks. As a first application of these methods, we investigate a setting where lay decisions have not taken full advantage of advances in natural science understanding: tornado forecasts in the US and Canada. Because official forecasts are imperfect, members of the public must often evaluate the risks on their own, by checking environmental cues (such as cloud formations) before deciding whether to take protective action. We study lay perceptions of cloud formations, demonstrating an approach that could be applied to other environmental judgments. We use signal detection theory to analyse how well people can distinguish tornadic from non-tornadic clouds, and multidimensional scaling to determine how people make these judgments. We find that participants ( N = 400 recruited from Amazon Mechanical Turk) have heuristics that generally serve them well, helping participants to separate tornadic from non-tornadic clouds, but which also lead them to misjudge the tornado risk of certain cloud types. The signal detection task revealed confusion regarding shelf clouds, mammatus clouds, and clouds with upper- and mid-level tornadic features, which the multidimensional scaling task suggested was the result of participants focusing on the darkness of the weather scene and the ease of discerning its features. We recommend procedures for training (e.g., for storm spotters) and communications (e.g., tornado warnings) that will reduce systematic misclassifications of tornadicity arising from observers' reliance on otherwise useful heuristics.