Decision-making based on warning design: How individuals infer uncertainty and choose to respond

When forecasters issue warnings, they consider a complex array of decision factors, including but not limited to forecast quality parameters such as POD (probability of detection) and FAR (false alarm rate), and lead-time goals geared toward providing as much value as possible to the end-user. Tradeoffs between these factors are unavoidable given constraints of technology and the present state of the science. Some research has explored the relationship between warning lead-time and behavioral responses, including both qualitative post-event case studies of vulnerability and aggregate statistical analyses of morbidity and mortality in an attempt to showcase the temporal dimension of forecast value for these particular hazardous events. While these studies are revealing, this dimension alone does not form a complete basis from which to consider problems such as repeated false alarm effects, to consider advancements in warning displays or even to have the assurance that those in the area of the warning understand their relationship to the hazard. Such issues implicitly involve deeper study of spatiality and spatial perception. This research thus aims to expand previous research to include consideration of the spatial.

Using theories of spatial cognition and cognitive decision theory, experiments are designed to reveal effects of storm-relative location and cartographic design on certainty and warning judgment. This presentation will highlight recent findings from these experiments, describing how different warning maps elicit different interpretations, carrying implications for effective lead-time and warning decision-making. The presentation aims to generate discussion about the tools available to the forecaster for communicating hazard information to the public, and debating what might be most effective.