The Effect of Probabilistic Information on Threshold Forecasts

Abstract

The study reported here asks whether the use of probabilistic information indicating forecast uncertainty improves the quality of deterministic weather decisions. Participants made realistic wind speed forecasts based on historical information in a controlled laboratory setting. They also decided whether it was appropriate to post an advisory for winds greater than 20 kt (10.29 m s?1) during the same time intervals and in the same geographic locations. On half of the forecasts each participant also read a color-coded chart showing the probability of winds greater than 20 kt. Participants had a general tendency to post too many advisories in the low probability situations (0%?10%) and too few advisories in very high probability situations (90%?100%). However, the probability product attenuated these biases. When participants used the probability product, they posted fewer advisories when the probability of high winds was low and they posted more advisories when the probability of high winds was high. The difference was due to the probability product alone because the within-subjects design and counterbalancing of forecast dates ruled out alternative explanations. The data suggest that the probability product improved threshold forecast decisions.