Articles | Volume 20, issue 3
https://doi.org/10.5194/cp-20-683-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-20-683-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Mar 2024
Research article |
| 22 Mar 2024
| 22 Mar 2024
Statistical precursor signals for Dansgaard–Oeschger cooling transitions
Earth System Modelling, School of Engineering & Design, Technical University of Munich, Munich, Germany
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 6012 03, 14412 Potsdam, Germany
Niklas Boers
Earth System Modelling, School of Engineering & Design, Technical University of Munich, Munich, Germany
Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 6012 03, 14412 Potsdam, Germany
Department of Mathematics and Global Systems Institute, University of Exeter, Exeter, UK
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Short summary
In general, the variance and short-lag autocorrelations of the fluctuations increase in a system approaching a critical transition. Using these indicators, we identify statistical precursor signals for the Dansgaard–Oeschger cooling events recorded in two climatic proxies of three Greenland ice core records. We then provide a dynamical systems theory that bridges the gap between observing statistical precursor signals and the physical precursor signs empirically known in paleoclimate research.
In general, the variance and short-lag autocorrelations of the fluctuations increase in a system...
