Please use this identifier to cite or link to this item: https://oar.tib.eu/jspui/handle/123456789/5118
Title: Abrupt transitions in time series with uncertainties
Authors: Goswami, B.Boers, N.Rheinwalt, A.Marwan, N.Heitzig, J.Breitenbach, S.F.M.Kurths, J.
Publishers Version: https://doi.org/10.1038/s41467-017-02456-6
Issue Date: 2018
Published in: Nature Communications Vol. 9 (2018), No. 1
Publisher: London : Nature Publishing Group
Abstract: Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Niño-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.
Keywords: ice; detection method; El Nino-Southern Oscillation; Holocene; ice rafting; identification method; network analysis; Pacific Decadal Oscillation; probability density function; summer; time series; uncertainty analysis; Article; Asian; climate; community structure; El Nino; Holocene; human; summer; time series analysis; transition temperature; uncertainty; Atlantic Ocean; Atlantic Ocean (North)
DDC: 510
License: CC BY 4.0 Unported
Link to License: https://creativecommons.org/licenses/by/4.0/
Appears in Collections:Mathematik



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