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Estimating reliability and resolution of probability forecasts through decomposition of the empirical score

Broecker, J. (2012) Estimating reliability and resolution of probability forecasts through decomposition of the empirical score. Climate Dynamics, 39 (3-4). pp. 655-667. ISSN 0930-7575

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To link to this article DOI: 10.1007/s00382-011-1191-1

Abstract/Summary

References (20)Cited By (1)Export CitationAboutAbstract Proper scoring rules provide a useful means to evaluate probabilistic forecasts. Independent from scoring rules, it has been argued that reliability and resolution are desirable forecast attributes. The mathematical expectation value of the score allows for a decomposition into reliability and resolution related terms, demonstrating a relationship between scoring rules and reliability/resolution. A similar decomposition holds for the empirical (i.e. sample average) score over an archive of forecast–observation pairs. This empirical decomposition though provides a too optimistic estimate of the potential score (i.e. the optimum score which could be obtained through recalibration), showing that a forecast assessment based solely on the empirical resolution and reliability terms will be misleading. The differences between the theoretical and empirical decomposition are investigated, and specific recommendations are given how to obtain better estimators of reliability and resolution in the case of the Brier and Ignorance scoring rule.

Item Type:Article
Refereed:Yes
Divisions:No Reading authors. Back catalogue items
Faculty of Science > School of Mathematical and Physical Sciences > Department of Mathematics and Statistics
Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
ID Code:29162
Uncontrolled Keywords:probability forecasting, scoring rules, reliability, resolution, forecast evaluation
Publisher:Springer

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