期刊
NATURE COMMUNICATIONS
卷 9, 期 -, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41467-017-02456-6
关键词
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资金
- DFG/FAPESP [IRTG 1740/TRP 2011/50151-0]
- DFG project IUCLiD [DFG MA4759/8]
- Alexander von Humboldt Foundation
- German Federal Ministry for Education and Research
- DFG
- Government of the Russian Federation [14.Z50.31.0033]
- European Unions Horizon Research and Innovation programme under the Marie Sklodowska-Curie grant [691037]
- MWFK Brandenburg
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 Nino-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.
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