Extreme floods in Europe: going beyond observations using reforecast ensemble pooling

Abstract < 0.25  average correlation across lead times). The resulting large ensemble (130 time series instead of 1) enables the analyses of very extreme events which occur less than twice a century. We demonstrate that such ensemble pooling produces more robust estimates with considerably reduced uncertainty bounds (by ∼ 80 % on average) than observation-based estimates but may equally introduce biases arising from the simulated meteorology and hydrological model. Our results show that, for a given return period, specific floods are highest in steep, cold, and wet regions and are comparably low in regions with strong flow regulation through dams. Furthermore, our pooled flood estimates indicate that the probability of regional flooding is higher in Central Europe and Great Britain than in Scandinavia. We conclude that reforecast ensemble pooling is an efficient approach to increase sample size and to derive robust local and regional flood estimates in regions with good hydrological model performance.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Extreme floods in Europe: going beyond observations using reforecast ensemble pooling ; volume:26 ; number:2 ; year:2022 ; pages:469-482 ; extent:14 ; Hydrology and earth system sciences ; 26, Heft 2 (2022), 469-482 (gesamt 14)

Beteiligte, Orts- und Zeitangaben

• Urheber: Brunner, Manuela Irene ; Slater, Louise J.

Weitere Informationen

• DOI: 10.5194/hess-26-469-2022
• URN: urn:nbn:de:101:1-2022020304210769872058
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:35 MESZ