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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/npg-2019-41
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-2019-41
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 09 Sep 2019

Submitted as: research article | 09 Sep 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Nonlinear Processes in Geophysics (NPG).

Detecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysis

Jaqueline Lekscha1,2 and Reik V. Donner1,3 Jaqueline Lekscha and Reik V. Donner
  • 1Potsdam Institute for Climate Impact Research (PIK) – Member of the Leibniz Association, 14473 Potsdam, Germany
  • 2Department of Physics, Humboldt University, 12489 Berlin, Germany
  • 3Department of Water, Environment, Construction and Safety, Magdeburg-Stendal University of Applied Sciences, 39114 Magdeburg, Germany

Abstract. Analysing palaeoclimate proxy time series using windowed recurrence network analysis (wRNA) has been shown to provide valuable information on past climate variability. In turn, it has also been found that the robustness of the obtained results differs among proxies from different palaeoclimate archives. To systematically test the suitability of wRNA for studying different types of palaeoclimate proxy time series, we use the framework of forward proxy modelling. For this, we create artificial input time series with different properties and, in a first step, compare the time series properties of the input and the model output time series. In a second step, we compare the areawise significant anomalies detected using wRNA. For proxies from tree and lake archives, we find that significant anomalies present in the input time series are sometimes missed in the input time series after the nonlinear filtering by the corresponding models. For proxies from speleothems, we observe falsely identified significant anomalies that are not present in the input time series. Finally, for proxies from ice cores, the wRNA results show the best correspondence with those for the input data. Our results contribute to improve the interpretation of windowed recurrence network analysis results obtained from real-world palaeoclimate time series.

Jaqueline Lekscha and Reik V. Donner
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Status: open (until 04 Nov 2019)
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Jaqueline Lekscha and Reik V. Donner
Jaqueline Lekscha and Reik V. Donner
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