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A new estimator of heat periods for decadal climate predictions - A complex network approach

Weimer, M.; Mieruch, S.; Schädler, G.; Kottmeier, C.

Abstract (englisch):
Regional decadal predictions have emerged in the past few years as a research field with high application potential, especially for extremes like heat and drought periods. However, up to now the prediction skill of decadal hindcasts, as evaluated with standard methods, is moderate and for extreme values even rarely investigated. In this study, we use hindcast data from a regional climate model (CCLM) for eight regions in Europe and quantify the skill of the model alternatively by constructing time-evolving climate networks and use the network correlation threshold (link strength) as a predictor for heat periods. We show that the skill of the network measure to estimate the low-frequency dynamics of heat periods is superior for decadal predictions with respect to the typical approach of using a fixed temperature threshold for estimating the number of heat periods in Europe.

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Volltext §
DOI: 10.5445/IR/1000058958
DOI: 10.5194/npg-23-307-2016
Zitationen: 1
Web of Science
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Fakultät für Physik (PHYSIK)
Institut für Meteorologie und Klimaforschung - Forschungsbereich Troposphäre (IMK-TRO)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2016
Sprache Englisch
Identifikator ISSN: 1023-5809
KITopen-ID: 1000058958
HGF-Programm 12.01.02 (POF III, LK 01)
Proc.res.f.multisc.predictab.of weather
Erschienen in Nonlinear processes in geophysics
Band 23
Heft 4
Seiten 307-317
Nachgewiesen in Web of Science
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