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Comparison of three techniques to adjust daily precipitation biases from regional climate models over Germany

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-262064
  • This study compares the performance of three bias correction (BC) techniques in adjusting simulated precipitation estimates over Germany. The BC techniques are the multivariate quantile delta mapping (MQDM) where the grids are used as variables to incorporate the spatial dependency structure of precipitation in the bias correction; empirical quantile mapping (EQM) and, the linear scaling (LS) approach. Several metrics that include first to fourth moments and extremes characterized by the frequency of heavy wet days and return periods duringThis study compares the performance of three bias correction (BC) techniques in adjusting simulated precipitation estimates over Germany. The BC techniques are the multivariate quantile delta mapping (MQDM) where the grids are used as variables to incorporate the spatial dependency structure of precipitation in the bias correction; empirical quantile mapping (EQM) and, the linear scaling (LS) approach. Several metrics that include first to fourth moments and extremes characterized by the frequency of heavy wet days and return periods during boreal summer were applied to score the performance of the BC techniques. Our results indicate a strong dependency of the relative performances of the BC techniques on the choice of the regional climate model (RCM), the region, the season, and the metrics of interest. Hence, each BC technique has relative strengths and weaknesses. The LS approach performs well in adjusting the first moment but tends to fall short for higher moments and extreme precipitation during boreal summer. Depending on the season, the region and the RCM considered, there is a trade-off between the relative performances of the EQM and the MQDM in adjusting the simulated precipitation biases. However, the MQDM performs well across all considered metrics. Overall, the MQDM outperforms the EQM in improving the higher moments and in capturing the observed return level of extreme summer precipitation, averaged over Germany.zeige mehrzeige weniger

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Autor(en): Chibuike Chiedozie Ibebuchi, Daniel Schönbein, Muralidhar Adakudlu, Elena Xoplaki, Heiko Paeth
URN:urn:nbn:de:bvb:20-opus-262064
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Philosophische Fakultät (Histor., philolog., Kultur- und geograph. Wissensch.) / Institut für Geographie und Geologie
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):Water
ISSN:2073-4441
Erscheinungsjahr:2022
Band / Jahrgang:14
Heft / Ausgabe:4
Aufsatznummer:600
Originalveröffentlichung / Quelle:Water (2022) 14:4, 600. doi:10.3390/w14040600
DOI:https://doi.org/10.3390/w14040600
Allgemeine fachliche Zuordnung (DDC-Klassifikation):5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 551 Geologie, Hydrologie, Meteorologie
Freie Schlagwort(e):Germany; bias correction; empirical quantile mapping; linear scaling; multivariate quantile delta mapping; precipitation
Datum der Freischaltung:01.02.2023
Datum der Erstveröffentlichung:16.02.2022
Sammlungen:Open-Access-Publikationsfonds / Förderzeitraum 2022
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International