Abstract
Abstract The possible economic value of the quantification of uncertainty in future ensemble-based surface weather forecasts is investigated using a formal, idealized decision model. Current, or baseline, weather forecasts are represented by probabilistic forecasts of moderate accuracy, as measured by the ranked probability score. Hypothetical ensemble-based forecasts are constructed by supplementing the baseline set of probabilistic forecasts with lower- and higher-skill forecasts. These are chosen in such a way that mixtures of the forecasts including the lower- and higher-skill subsets with equal frequency exhibit the same accuracy overall as the moderately accurate (conventional, baseline) forecasts. For both simple one-time decisions (static situation) and related sequences of decisions (dynamic situation), these hypothetical ensemble-based forecasts are found to lead to greater economic value in the idealized decision problem when protective actions are relatively inexpensive, corresponding to real-...
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