Anomaly Detection in Paleoclimate Records Using Permutation Entropy
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...
Published in: | Entropy |
---|---|
Main Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI AG
2018
|
Subjects: | |
Online Access: | https://doi.org/10.3390/e20120931 https://doaj.org/article/41cb76ebfe524fcb8316a23ae81618ed |
id |
ftdoajarticles:oai:doaj.org/article:41cb76ebfe524fcb8316a23ae81618ed |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:41cb76ebfe524fcb8316a23ae81618ed 2023-05-15T16:38:48+02:00 Anomaly Detection in Paleoclimate Records Using Permutation Entropy Joshua Garland Tyler R. Jones Michael Neuder Valerie Morris James W. C. White Elizabeth Bradley 2018-12-01T00:00:00Z https://doi.org/10.3390/e20120931 https://doaj.org/article/41cb76ebfe524fcb8316a23ae81618ed EN eng MDPI AG https://www.mdpi.com/1099-4300/20/12/931 https://doaj.org/toc/1099-4300 1099-4300 doi:10.3390/e20120931 https://doaj.org/article/41cb76ebfe524fcb8316a23ae81618ed Entropy, Vol 20, Iss 12, p 931 (2018) paleoclimate permutation entropy ice core anomaly detection Science Q Astrophysics QB460-466 Physics QC1-999 article 2018 ftdoajarticles https://doi.org/10.3390/e20120931 2022-12-30T22:35:19Z 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. Article in Journal/Newspaper ice core Directory of Open Access Journals: DOAJ Articles Entropy 20 12 931 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
paleoclimate permutation entropy ice core anomaly detection Science Q Astrophysics QB460-466 Physics QC1-999 |
spellingShingle |
paleoclimate permutation entropy ice core anomaly detection Science Q Astrophysics QB460-466 Physics QC1-999 Joshua Garland Tyler R. Jones Michael Neuder Valerie Morris James W. C. White Elizabeth Bradley Anomaly Detection in Paleoclimate Records Using Permutation Entropy |
topic_facet |
paleoclimate permutation entropy ice core anomaly detection Science Q Astrophysics QB460-466 Physics QC1-999 |
description |
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. |
format |
Article in Journal/Newspaper |
author |
Joshua Garland Tyler R. Jones Michael Neuder Valerie Morris James W. C. White Elizabeth Bradley |
author_facet |
Joshua Garland Tyler R. Jones Michael Neuder Valerie Morris James W. C. White Elizabeth Bradley |
author_sort |
Joshua Garland |
title |
Anomaly Detection in Paleoclimate Records Using Permutation Entropy |
title_short |
Anomaly Detection in Paleoclimate Records Using Permutation Entropy |
title_full |
Anomaly Detection in Paleoclimate Records Using Permutation Entropy |
title_fullStr |
Anomaly Detection in Paleoclimate Records Using Permutation Entropy |
title_full_unstemmed |
Anomaly Detection in Paleoclimate Records Using Permutation Entropy |
title_sort |
anomaly detection in paleoclimate records using permutation entropy |
publisher |
MDPI AG |
publishDate |
2018 |
url |
https://doi.org/10.3390/e20120931 https://doaj.org/article/41cb76ebfe524fcb8316a23ae81618ed |
genre |
ice core |
genre_facet |
ice core |
op_source |
Entropy, Vol 20, Iss 12, p 931 (2018) |
op_relation |
https://www.mdpi.com/1099-4300/20/12/931 https://doaj.org/toc/1099-4300 1099-4300 doi:10.3390/e20120931 https://doaj.org/article/41cb76ebfe524fcb8316a23ae81618ed |
op_doi |
https://doi.org/10.3390/e20120931 |
container_title |
Entropy |
container_volume |
20 |
container_issue |
12 |
container_start_page |
931 |
_version_ |
1766029143340744704 |