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Abstract
Unlike the scientific definition of global warming (GW), public discussion often links the existence of GW to daily temperatures rather than long-term averages. Previous research found that daily weather is perceived as personal experiences with GW. Additionally, prior beliefs about GW can affect interpretations of such experiences as evidence for the existence of GW. However, previous studies demonstrating that beliefs affect interpretations of experiences were based on correlational designs—limiting causal inferences—and relied only on self-reports of remembered personal experiences instead of direct interpretations of weather. The authors present the first randomized experiment investigating how people interpret daily temperatures in terms of the evidence that it provides about GW, clarifying the psychological causes for different interpretations of the same experiences across individuals. They test the influence of knowledge about (and beliefs in) GW on the interpretation of daily temperatures across two framing conditions labeled weather (interpreting a temperature as abnormal weather) and climate (interpreting a temperature as evidence of GW). The authors use signal detection theory to measure the decision-maker's (a) ability to discriminate between temperatures, called sensitivity, and (b) threshold for describing a temperature as abnormal, called the decision threshold. The results replicate previous research finding a motivational distortion in interpreting temperatures as evidence of GW and further find belief-consistent distortions in decision thresholds while observing no measurable change in sensitivity. In other words, people know when temperatures are abnormally hot, but classify ambiguous events (i.e., less extreme abnormalities) differently based on their beliefs in GW.

AbstractReducing fatalities from tornadoes in the southeastern United States requires considering multiple societal factors, including the risk perceptions that influence how people interpret tornado forecasts and warnings and make protective decisions. This study investigates perceptions of tornado risk in the southeastern United States, operationalized as judgments of tornado likelihood. While it is possible that residents of the Southeast could learn about tornado likelihood in their region from observing the local environment, cognitive-ecological theory from psychology suggests that such judgments of likelihood can be inaccurate, even if other aspects of local knowledge are accurate. This study analyzes data from a survey that elicited different groups' judgments of tornado likelihood associated with different seasons, times of day, and storm system types. Results are presented from a representative sample of Southeastern residents and are compared with a sample of tornado experts (who have extensive knowledge about the likelihood of Southeastern tornadoes) and a representative sample of Great Plains residents. Overall, the analysis finds that many members of the Southeastern public deviate from the expert sample on tornado likelihood, especially for winter and overnight tornadoes. These deviations from expert opinion mimic the judgments of the Great Plains public. This study demonstrates how psychological theory and a decision science approach can be used to identify potential gaps in public knowledge about hazardous weather risks, and it reveals several such potential gaps. Further research is needed to understand the reasons for deviations between public and expert judgments, evaluate their effects on protective decision-making, and develop strategies to address them.

We investigate optimal group member configurations for producing a maximally accurate group forecast. Our approach accounts for group members that may be biased in their forecasts and/or have errors that correlate with the criterion values being forecast. We show that for large forecasting groups, the diversity of individual forecasts linearly trades off with forecaster accuracy when determining optimal group composition.