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Entropy 2018, 20(12), 931;

Anomaly Detection in Paleoclimate Records Using Permutation Entropy

Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
Institute for Arctic and Alpine Research, University of Colorado Boulder, Boulder, CO 80309, USA
Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309, USA
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Received: 3 November 2018 / Revised: 29 November 2018 / Accepted: 4 December 2018 / Published: 5 December 2018
(This article belongs to the Special Issue Applications of Information Theory in the Geosciences II)
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Permutation entropy techniques can be useful for identifying anomalies in paleoclimate data records, including noise, outliers, and post-processing issues. We demonstrate this using weighted and unweighted permutation entropy with water-isotope records containing data from a deep polar ice core. In one region of these isotope records, our previous calculations (See Garland et al. 2018) revealed an abrupt change in the complexity of the traces: specifically, in the amount of new information that appeared at every time step. We conjectured that this effect was due to noise introduced by an older laboratory instrument. In this paper, we validate that conjecture by reanalyzing a section of the ice core using a more advanced version of the laboratory instrument. The anomalous noise levels are absent from the permutation entropy traces of the new data. In other sections of the core, we show that permutation entropy techniques can be used to identify anomalies in the data that are not associated with climatic or glaciological processes, but rather effects occurring during field work, laboratory analysis, or data post-processing. These examples make it clear that permutation entropy is a useful forensic tool for identifying sections of data that require targeted reanalysis—and can even be useful for guiding that analysis. View Full-Text
Keywords: paleoclimate; permutation entropy; ice core; anomaly detection paleoclimate; permutation entropy; ice core; anomaly detection

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Garland, J.; Jones, T.R.; Neuder, M.; Morris, V.; White, J.W.C.; Bradley, E. Anomaly Detection in Paleoclimate Records Using Permutation Entropy. Entropy 2018, 20, 931.

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