Titel
The fractions skill score for ensemble forecast verification
Autor*in
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Abstract
The fractions skill score (FSS) is a neighbourhood verification method originally designed to verify deterministic forecasts of binary events. Previous studies employed different approaches for computing an ensemble-based FSS for probabilistic forecast verification. We show that the formulation of an ensemble-based FSS substantially affects verification results. Comparing four possible approaches, we determine how different ensemble-based FSS variants depend on ensemble size, neighbourhood size, and forecast event frequency of occurrence. We demonstrate that only one ensemble-based FSS, which we call the probabilistic FSS (pFSS), is well behaved and reasonably dependent on ensemble size. Furthermore, we derive a relationship to describe how the pFSS behaves with ensemble size. The proposed relationship is similar to a known result for the Brier skill score. Our study uses high-resolution 1000-member ensemble precipitation forecasts from a high-impact weather period. The large ensemble enables us to study the influence of ensemble and neighbourhood size on forecast skill by deriving probabilistic skilful spatial scales.
Stichwort
brier skill scoreforecast verificationfractions skill scoreneighbourhood methodsnumerical weather predictionprecipitationprobabilistic forecasts
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
phaidra.univie.ac.at/o:2104776
DOI
Erschienen in
Titel
Quarterly Journal of the Royal Meteorological Society
Band
150
Ausgabe
764
ISSN
0035-9009
Erscheinungsdatum
2024
Seitenanfang
4457
Seitenende
4477
Publication
Wiley
Fördergeber
Erscheinungsdatum
2024
Zugänglichkeit
Rechte
Rechteangabe
© 2024 The Author(s)
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