The fractions skill score for ensemble forecast verification
- Author(s)
- Tobias Necker, Ludwig Wolfgruber, Lukas Kugler, Martin Weissmann, Manfred Dorninger, Stefano Serafin
- 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.
- Organisation(s)
- Department of Meteorology and Geophysics
- Journal
- Quarterly Journal of the Royal Meteorological Society
- Volume
- 150
- Pages
- 4457-4477
- No. of pages
- 21
- ISSN
- 0035-9009
- DOI
- https://doi.org/10.1002/qj.4824
- Publication date
- 2024
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 105206 Meteorology
- Keywords
- ASJC Scopus subject areas
- Atmospheric Science
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/ff9b5f07-a319-406f-886a-9203d550fe53