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.Comment: 15 pages, 7 figure