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Predicting climate extremes - a complex network approach

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

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 8 regions in Europe to construct 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 predict the low frequency dynamics of heat periods is similar to the one of the standard approach, with the potential of being even better in some regions.

Volltext §
DOI: 10.5445/IR/1000052507
DOI: 10.5194/npgd-2-1481-2015
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 2015
Sprache Englisch
Identifikator ISSN: 2198-5634
KITopen-ID: 1000052507
HGF-Programm 12.01.02 (POF III, LK 01) Proc.res.f.multisc.predictab.of weather
Erschienen in Nonlinear Processes in Geophysics Discussions
Verlag European Geosciences Union (EGU)
Band 2
Heft 5
Seiten 1481-1505
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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