Published November 25, 2024 | Version v2

Nonlinear time series analysis of palaeoclimate proxy records

  • 1. Potsdam Institute for Climate Impact Research
  • 2. Magdeburg-Stendal University of Applied Sciences
  • 3. Kadir Has University, Istanbul

Description

Jupyter notebook for nonlinear time series analysis of the palaeoclimate proxy records used in the paper. It calculates the number of potential wells, the entropy of the data, the order pattern (permutation) entropy, the recurrence quantification/network measures, DET, LAM, transitivity, and average path length as well as the visibility graph based irreversibility test statsitics p(k) and p(C).

The repository also contains the data sets used in the analysis in the folder Data.

Published in
N. Marwan, J. F. Donges, R. V. Donner, D. Eroglu: Nonlinear time series analysis of palaeoclimate proxy records, Quaternary Science Reviews, 274, 107245 (2021). DOI:10.1016/j.quascirev.2021.107245

Technical info

Important note on compatibility with newer pyunicorn versions

The analysis was performed with pyunicorn v0.6.1. Since v0.7.0, the way how recurrence plot line structures are handled in the pyunicorn sub-routine recurrence_plot.py (sub-functions diagline_dist and vertline_dist) has changed (see pyunicorn git commit 740f6ca6f891233c0ab952a05d6dba295ff47b31, 2023-12-14). Therefore, we have now added a version test in the sub-function rp_significance in the file nonlinear_timeseries_analysis.py to ensure compatibility with the calculations.

Files

marwan_qsr2021.zip

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Additional details

References

  • Marwan et al., Nonlinear time series analysis of palaeoclimate proxy records, Quaternary Science Reviews 274, 107245, 2021, doi:10.1016/j.quascirev.2021.107245