Articles | Volume 14, issue 3
https://doi.org/10.5194/esd-14-593-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-14-593-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 May 2023
Research article |
| 16 May 2023
| 16 May 2023
Stable stadial and interstadial states of the last glacial's climate identified in a combined stable water isotope and dust record from Greenland
Keno Riechers
CORRESPONDING AUTHOR
Research Domain IV – Complexity Science, Potsdam Institute for Climate Impact Research,
Telegrafenberg A31, 14473 Potsdam, Germany
Earth System Modelling, School of Engineering & Design, Technical University of Munich, 80333 Munich, Germany
Leonardo Rydin Gorjão
Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway
Institute of Energy and Climate Research, Forschungszentrum Jülich, 52428 Jülich, Germany
Institute for Theoretical Physics, University of Cologne, 50937 Cologne, Germany
Institute of Networked Energy Systems, German Aerospace Center (DLR), 26129 Oldenburg, Germany
Forough Hassanibesheli
Earth System Modelling, Helmholtz Centre Potsdam, GFZ German Research Center for
Geosciences, 14473 Potsdam, Germany
Pedro G. Lind
Department of Computer Science, OsloMet – Oslo Metropolitan University, 0130 Oslo, Norway
NordSTAR – Nordic Center for Sustainable and Trustworthy AI Research, 0166 Oslo, Norway
Artificial Intelligence Lab, Oslo Metropolitan University, 0166 Oslo, Norway
Dirk Witthaut
Institute of Energy and Climate Research, Forschungszentrum Jülich, 52428 Jülich, Germany
Institute for Theoretical Physics, University of Cologne, 50937 Cologne, Germany
Niklas Boers
Earth System Modelling, School of Engineering & Design, Technical University of Munich, 80333 Munich, Germany
Research Domain IV – Complexity Science, Potsdam Institute for Climate Impact Research,
Telegrafenberg A31, 14473 Potsdam, Germany
Global Systems Institute, Department of Mathematics, University of Exeter, EX4 4QF Exeter, UK
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In layer counted proxy records each measurement is accompanied by a timestamp typically measured by counting periodic layers. Knowledge of the uncertainty of this timestamp is important for a rigorous propagation to further analyses. By assuming a Bayesian regression model to the layer increments we express the dating uncertainty by the posterior distribution, from which chronologies can be sampled efficiently. We apply our framework to dating abrupt warming transitions during the last glacial.
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The late Pleistocene glacial cycles are dominated by a 100-kyr periodicity, rather than other major astronomical periods like 19, 23, 41, or 400 kyr. Various models propose distinct mechanisms to explain this, but their diversity may obscure the key factor behind the 100-kyr periodicity. We propose a time-scale matching hypothesis, suggesting that the ice-sheet climate system responds to astronomical forcing at ~100 kyr because its intrinsic timescale is closer to 100 kyr than to other periods.
Clara Hummel, Niklas Boers, and Martin Rypdal
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We revisit early warning signals (EWS) for past abrupt climate changes known as Dansgaard-Oeschger (DO) events. Using advanced statistical methods, we find fewer significant EWS than previously reported. While some signals appear consistent across Greenland ice core records, they are not enough to identify the still unknown physical mechanisms behind DO events. This study highlights the complexity of predicting climate changes and urges caution in interpreting (paleo-)climate data.
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Dansgaard–Oeschger events are a series of abrupt past climate change events during which the atmosphere, sea ice, and ocean in the North Atlantic underwent rapid changes. One current topic of interest is the order in which these different changes occurred, which remains unknown. In this work, we find that the current best method used to investigate this topic is subject to substantial bias. This implies that it is not possible to reliably determine the order of the different changes.
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Recent work has used observations to find statistical signs that the Atlantic Meridional Overturning Circulation (AMOC) may be approaching a collapse. We find that in complex climate models in which the AMOC does not collapse before 2100, the statistical signs that are present in the observations are not found in the 1850–2014 equivalent model time series. This indicates that the observed statistical signs are not prone to false positives.
Takahito Mitsui and Niklas Boers
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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.
Takahito Mitsui, Matteo Willeit, and Niklas Boers
Earth Syst. Dynam., 14, 1277–1294, https://doi.org/10.5194/esd-14-1277-2023, https://doi.org/10.5194/esd-14-1277-2023, 2023
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Maximilian Gelbrecht, Alistair White, Sebastian Bathiany, and Niklas Boers
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Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
Eirik Myrvoll-Nilsen, Keno Riechers, Martin Wibe Rypdal, and Niklas Boers
Clim. Past, 18, 1275–1294, https://doi.org/10.5194/cp-18-1275-2022, https://doi.org/10.5194/cp-18-1275-2022, 2022
Short summary
Short summary
In layer counted proxy records each measurement is accompanied by a timestamp typically measured by counting periodic layers. Knowledge of the uncertainty of this timestamp is important for a rigorous propagation to further analyses. By assuming a Bayesian regression model to the layer increments we express the dating uncertainty by the posterior distribution, from which chronologies can be sampled efficiently. We apply our framework to dating abrupt warming transitions during the last glacial.
Keno Riechers, Takahito Mitsui, Niklas Boers, and Michael Ghil
Clim. Past, 18, 863–893, https://doi.org/10.5194/cp-18-863-2022, https://doi.org/10.5194/cp-18-863-2022, 2022
Short summary
Short summary
Building upon Milancovic's theory of orbital forcing, this paper reviews the interplay between intrinsic variability and external forcing in the emergence of glacial interglacial cycles. It provides the reader with historical background information and with basic theoretical concepts used in recent paleoclimate research. Moreover, it presents new results which confirm the reduced stability of glacial-cycle dynamics after the mid-Pleistocene transition.
Keno Riechers and Niklas Boers
Clim. Past, 17, 1751–1775, https://doi.org/10.5194/cp-17-1751-2021, https://doi.org/10.5194/cp-17-1751-2021, 2021
Short summary
Short summary
Greenland ice core data show that the last glacial cycle was punctuated by a series of abrupt climate shifts comprising significant warming over Greenland, retreat of North Atlantic sea ice, and atmospheric reorganization. Statistical analysis of multi-proxy records reveals no systematic lead or lag between the transitions of proxies that represent different climatic subsystems, and hence no evidence for a potential trigger of these so-called Dansgaard–Oeschger events can be found.
Charlotte Neubacher, Dirk Witthaut, and Jan Wohland
Adv. Geosci., 54, 205–215, https://doi.org/10.5194/adgeo-54-205-2021, https://doi.org/10.5194/adgeo-54-205-2021, 2021
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In our study, we investigate the variability of potential offshore wind power over Europe on time scales of more than 10 years. Detailed spectral analysis of potential offshore wind power capacities over the last century indicates a strong coupling to large climate patterns such as the NAO. Furthermore, combining the wind power potential at the German North Sea and the Portuguese Atlantic coast shows that the variability can be mitigated.
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Short summary
Paleoclimate proxy records show that the North Atlantic climate repeatedly transitioned between two regimes during the last glacial interval. This study investigates a bivariate proxy record from a Greenland ice core which reflects past Greenland temperatures and large-scale atmospheric conditions. We reconstruct the underlying deterministic drift by estimating first-order Kramers–Moyal coefficients and identify two separate stable states in agreement with the aforementioned climatic regimes.
Paleoclimate proxy records show that the North Atlantic climate repeatedly transitioned between...
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