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  Event synchrony measures for functional climate network analysis: A case study on South American rainfall dynamics

Wolf, F., Bauer, J., Boers, N., Donner, R. V. (2020): Event synchrony measures for functional climate network analysis: A case study on South American rainfall dynamics. - Chaos, 30, 3, 033102.
https://doi.org/10.1063/1.5134012

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 Urheber:
Wolf, Frederik1, Autor              
Bauer, J.2, Autor
Boers, Niklas1, Autor              
Donner, Reik V.1, Autor              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Zusammenfassung: Understanding spatiotemporal patterns of climate extremes has gained considerable relevance in the context of ongoing climate change. With enhanced computational capacity, data driven methods such as functional climate networks have been proposed and have already contributed to significant advances in understanding and predicting extreme events, as well as identifying interrelations between the occurrences of various climatic phenomena. While the (in its basic setting) parameter free event synchronization (ES) method has been widely applied to construct functional climate networks from extreme event series, its original definition has been realized to exhibit problems in handling events occurring at subsequent time steps, which need to be accounted for. Along with the study of this conceptual limitation of the original ES approach, event coincidence analysis (ECA) has been suggested as an alternative approach that incorporates an additional parameter for selecting certain time scales of event synchrony. In this work, we compare selected features of functional climate network representations of South American heavy precipitation events obtained using ES and ECA without and with the correction for temporal event clustering. We find that both measures exhibit different types of biases, which have profound impacts on the resulting network structures. By combining the complementary information captured by ES and ECA, we revisit the spatiotemporal organization of extreme events during the South American Monsoon season. While the corrected version of ES captures multiple time scales of heavy rainfall cascades at once, ECA allows disentangling those scales and thereby tracing the spatiotemporal propagation more explicitly.

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 Datum: 2020
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
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 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1063/1.5134012
PIKDOMAIN: RD4 - Complexity Science
eDoc: 8954
MDB-ID: yes
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Extremes
Research topic keyword: Monsoon
Model / method: Nonlinear Data Analysis
Regional keyword: South America
Organisational keyword: RD4 - Complexity Science
 Art des Abschluß: -

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Titel: Chaos
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 30 (3) Artikelnummer: 033102 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808