Lay Detection of Unusual Patterns in the Frequency of Hurricanes

An increase in the severity of extreme weather is arguably one of the most important consequences of climate change with immediate and potentially devastating impacts. Recent events, like Hurricane Harvey, stimulated public discourse surrounding the role of climate change in amplifying, or otherwise modifying, the patterns of such events. Within the scientific community, recent years have witnessed considerable progress on “climate attribution”—the use of statistical techniques to assess the probability that climate change is influencing the character of some extreme weather events. Using a novel application of signal detection theory, this article assesses when, and to what extent, laypeople attribute changes in hurricanes to climate change and whether and how certain characteristics predict this decision. The results show that people attribute hurricanes to climate change based on their preexisting climate beliefs and numeracy. Respondents who were more dubious about the existence of climate change (and more numerate) required a greater degree of evidence (i.e., a more extreme world) before they were willing to suggest that an unusual hurricane season might be influenced by climate change. However, those who have doubts were still willing to make these attributions when hurricane behavior becomes sufficiently extreme. In general, members of the public who hold different prior views about climate change are not in complete disagreement about the evidence they perceive, which leaves the possibility for future work to explore ways to bring such judgments back into alignment.