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  Ocean circulation, ice shelf, and sea ice interactions explain Dansgaard-Oeschger cycles

Boers, N., Ghil, M., Rousseau, D.-D. (2018): Ocean circulation, ice shelf, and sea ice interactions explain Dansgaard-Oeschger cycles. - Proceedings of the National Academy of Sciences of the United States of America (PNAS), 115, 47, E11005-E11014.
https://doi.org/10.1073/pnas.1802573115

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 Creators:
Boers, Niklas1, Author              
Ghil, M.2, Author
Rousseau, D.-D.2, Author
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Abstract: The last glacial interval experienced abrupt climatic changes called Dansgaard–Oeschger (DO) events. These events manifest themselves as rapid increases followed by slow decreases of oxygen isotope ratios in Greenland ice core records. Despite promising advances, a comprehensive theory of the DO cycles, with their repeated ups and downs of isotope ratios, is still lacking. Here, based on earlier hypotheses, we introduce a dynamical model that explains the DO variability by rapid retreat and slow regrowth of thick ice shelves and thin sea ice in conjunction with changing subsurface water temperatures due to insulation by the ice cover. Our model successfully reproduces observed features of the records, such as the sawtooth shape of the DO cycles, waiting times between DO events across the last glacial, and the shifted antiphase relationship between Greenland and Antarctic ice cores. Our results show that these features can be obtained via internal feedbacks alone. Warming subsurface waters could have also contributed to the triggering of Heinrich events. Our model thus offers a unified framework for explaining major features of multimillennial climate variability during glacial intervals.

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 Dates: 2018
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1073/pnas.1802573115
PIKDOMAIN: Transdisciplinary Concepts & Methods - Research Domain IV
eDoc: 8404
Research topic keyword: Tipping Elements
Research topic keyword: Paleoclimate
Model / method: Machine Learning
Model / method: Nonlinear Data Analysis
Regional keyword: Arctic & Antarctica
Organisational keyword: RD4 - Complexity Science
Organisational keyword: FutureLab - Artificial Intelligence in the Anthropocene
Working Group: Development of advanced time series analysis techniques
Working Group: Network- and machine-learning-based prediction of extreme events
 Degree: -

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Title: Proceedings of the National Academy of Sciences of the United States of America (PNAS)
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 115 (47) Sequence Number: - Start / End Page: E11005 - E11014 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals410