Anomaly Detection in Paleoclimate Records using Permutation Entropy
Authors:
Joshua Garland,
Tyler R. Jones,
Michael Neuder,
Valerie Morris,
James W. C. White,
Elizabeth Bradley
Abstract:
Permutation entropy techniques can be useful in identifying anomalies in paleoclimate data records, including noise, outliers, and post-processing issues. We demonstrate this using weighted and unweighted permutation entropy of water-isotope records in a deep polar ice core. In one region of these isotope records, our previous calculations revealed an abrupt change in the complexity of the traces:…
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Permutation entropy techniques can be useful in identifying anomalies in paleoclimate data records, including noise, outliers, and post-processing issues. We demonstrate this using weighted and unweighted permutation entropy of water-isotope records in a deep polar ice core. In one region of these isotope records, our previous calculations 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 re-analyzing 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 raw 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 re-analysis---and can even be useful in guiding that analysis.
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Submitted 29 November, 2018; v1 submitted 3 November, 2018;
originally announced November 2018.
Climate entropy production recorded in a deep Antarctic ice core
Authors:
Joshua Garland,
Tyler R. Jones,
Elizabeth Bradley,
Michael Neuder,
James W. C. White
Abstract:
Paleoclimate records are extremely rich sources of information about the past history of the Earth system. Information theory, the branch of mathematics capable of quantifying the degree to which the present is informed by the past, provides a new means for studying these records. Here, we demonstrate that estimates of the Shannon entropy rate of the water-isotope data from the West Antarctica Ice…
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Paleoclimate records are extremely rich sources of information about the past history of the Earth system. Information theory, the branch of mathematics capable of quantifying the degree to which the present is informed by the past, provides a new means for studying these records. Here, we demonstrate that estimates of the Shannon entropy rate of the water-isotope data from the West Antarctica Ice Sheet (WAIS) Divide ice core, calculated using weighted permutation entropy (WPE), can bring out valuable new information from this record. We find that WPE correlates with accumulation, reveals possible signatures of geothermal heating at the base of the core, and clearly brings out laboratory and data-processing effects that are difficult to see in the raw data. For example, the signatures of Dansgaard-Oeschger events in the information record are small, suggesting that these abrupt warming events may not represent significant changes in the climate system dynamics. While the potential power of information theory in paleoclimatology problems is significant, the associated methods require careful handling and well-dated, high-resolution data. The WAIS Divide ice core is the first such record that can support this kind of analysis. As more high-resolution records become available, information theory will likely become a common forensic tool in climate science.
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Submitted 7 November, 2018; v1 submitted 20 June, 2018;
originally announced June 2018.