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

Content Provider	Springer Nature Link
Author	Bröcker, Jochen
Copyright Year	2011
Abstract	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.
Starting Page	655
Ending Page	667
Page Count	13
File Format	PDF
ISSN	09307575
Journal	Climate Dynamics
Volume Number	39
Issue Number	3-4
e-ISSN	14320894
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-10-02
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Probability forecasts Scoring rules Reliability Resolution Forecast evaluation Geophysics/Geodesy Meteorology/Climatology Oceanography
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science

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