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

Weimer, M. 1; Mieruch, S. 1; Schädler, G. 1; Kottmeier, C. 1
1 Institut für Meteorologie und Klimaforschung (IMK), Karlsruher Institut für Technologie (KIT)

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.


Volltext §
DOI: 10.5445/IR/1000058958
Originalveröffentlichung
DOI: 10.5194/npg-23-307-2016
Scopus
Zitationen: 3
Dimensions
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Forschungsbereich Troposphäre (IMK-TRO)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2016
Sprache Englisch
Identifikator ISSN: 1023-5809
urn:nbn:de:swb:90-589584
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
Verlag European Geosciences Union (EGU)
Band 23
Heft 4
Seiten 307-317
Nachgewiesen in Dimensions
Scopus
Web of Science
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