Value from Ambiguity in Ensemble Forecasts

Abstract

Abstract This study explores the objective application of ambiguity information, that is, the uncertainty in forecast probability derived from an ensemble. One application approach, called uncertainty folding, merges ambiguity with forecast uncertainty information for subsequent use in standard risk-analysis decision making. Uncertainty folding is found to be of no practical benefit when tested in a low-order, weather forecast simulation. A second approach, called ulterior motives, attempts to use ambiguity information to aid secondary decision factors not considered in the standard risk analysis, while simultaneously maintaining the primary value associated with the probabilistic forecasts. Following ulterior motives, the practical utility of ambiguity information is demonstrated on real-world ensemble forecasts used to support decisions concerning the preparation for freezing temperatures paired with a secondary desire for the reduction in repeat false alarms. Sample products for communicating ambiguity to the user are also presented.