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Adaptation and application of the large LAERTES-EU regional climate model ensemble for modeling hydrological extremes: a pilot study for the Rhine basin

Ehmele, Florian 1; Kautz, Lisa-Ann; Feldmann, Hendrik 1; He, Yi; Kadlec, Martin; Kelemen, Fanni D.; Lentink, Hilke S.; Ludwig, Patrick ORCID iD icon 1; Manful, Desmond; Pinto, Joaquim G.
1 Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO), Karlsruher Institut für Technologie (KIT)

Abstract:

Enduring and extensive heavy precipitation events associated with widespread river floods are among the main natural hazards affecting central Europe. Since such events are characterized by long return periods, it is difficult to adequately quantify their frequency and intensity solely based on the available observations of precipitation. Furthermore, long-term observations are rare, not homogeneous in space and time, and thus not suitable to running hydrological models (HMs) with respect to extremes. To overcome this issue, we make use of the recently introduced LAERTES-EU (LArge Ensemble of Regional climaTe modEl Simulations for EUrope) data set, which is an ensemble of regional climate model simulations providing over 12 000 simulated years. LAERTES-EU is adapted for use in an HM to calculate discharges for large river basins by applying quantile mapping with a parameterized gamma distribution to correct the mainly positive bias in model precipitation. The Rhine basin serves as a pilot area for calibration and validation. The results show clear improvements in the representation of both precipitation (e.g., annual cycle and intensity distributions) and simulated discharges by the HM after the bias correction. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000143561
Veröffentlicht am 08.03.2022
Originalveröffentlichung
DOI: 10.5194/nhess-22-677-2022
Dimensions
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung Troposphärenforschung (IMKTRO)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 1684-9981
KITopen-ID: 1000143561
HGF-Programm 12.11.35 (POF IV, LK 01) Tailored information for users and stakeholders
Weitere HGF-Programme 12.11.33 (POF IV, LK 01) Regional Climate and Hydrological Cycle
Erschienen in Natural Hazards and Earth System Sciences
Verlag European Geosciences Union (EGU)
Band 22
Heft 2
Seiten 677–692
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Vorab online veröffentlicht am 03.03.2022
Nachgewiesen in Web of Science
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