The fractions skill score for ensemble forecast verification

Autor(en)

Tobias Necker, Ludwig Wolfgruber, Lukas Kugler, Martin Weissmann, Manfred Dorninger, Stefano Serafin

Abstrakt

The Fractions Skill Score (FSS) is a neighbourhood verification method originally designed to verify deterministic forecasts of binary events. Previous studies employed different approaches to computing an ensemble-based FSS for probabilistic forecast verification. We show that the formulation of the ensemble-based FSS substantially affects verification results. Comparing four different approaches, we determine how the ensemble-based FSS depends on ensemble size, neighbourhood size, and frequency of occurrence of the forecast event. Furthermore, we derive an empirical formula for the expected dependence of the FSS on ensemble size. Our results are based on high-resolution 1000-member ensemble precipitation forecasts over Germany for a high-impact weather period. The large ensemble enables us to study the influence of ensemble size on forecast skill in terms of a probabilistic skilful spatial scale. We demonstrate that only one form of ensemble-based FSS, which we refer to as probabilistic FSS, is well-behaved and exhibits a reasonable dependence on ensemble size.

Organisation(en)

Institut für Meteorologie und Geophysik

Journal

Quarterly Journal of the Royal Meteorological Society

Band

150

Seiten

4457-4477

Anzahl der Seiten

21

ISSN

0035-9009

DOI

https://doi.org/10.1002/qj.4824

Publikationsdatum

2024

Peer-reviewed

Ja

ÖFOS 2012

105206 Meteorologie

Schlagwörter

ASJC Scopus Sachgebiete

Atmospheric Science

Link zum Portal

https://ucrisportal.univie.ac.at/de/publications/ff9b5f07-a319-406f-886a-9203d550fe53