This study expands the pool of verification methods for probabilistic weather and climate predictions by a decomposition of the quantile score (QS). The QS is a proper score function and evaluates predictive quantiles on a set of forecast–observation pairs. We introduce a decomposition of the QS in reliability, resolution and uncertainty and discuss the biases of the decomposition. Further, a reliability diagram for quantile forecasts is presented. Verification with the QS and its decomposition is illustrated on precipitation forecasts derived from the mesoscale weather prediction ensemble COSMO-DE-EPS of the German Meteorological Service. We argue that the QS is ready to become as popular as the Brier score in forecast verification.
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Bentzien et al. (2013) studied this question.
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