variability of sulfate signal in ice core records based on five replicate cores

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ID: 187412
2016
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Ranked #78 of 96 articles by views in proceedings - 16th ieee/acis international conference on computer and information science, icis 2017

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Abstract
Current volcanic reconstructions based on ice core analysis have significantly improved over the past few decades by incorporating multiple-core analyses with a high temporal resolution from different parts of the polar regions into a composite common volcanic eruption record. Regional patterns of volcanic deposition are based on composite records, built from cores taken at both poles. However, in many cases only a single record at a given site is used for these reconstructions. This assumes that transport and regional meteorological patterns are the only source of the dispersion of the volcanic products. Here we evaluate the local-scale variability of a sulfate profile in a low-accumulation site (Dome C, Antarctica), in order to assess the representativeness of one core for such a reconstruction. We evaluate the variability with depth, statistical occurrence, and sulfate flux deposition variability of volcanic eruptions detected in five ice cores, drilled 1 m apart from each other. Local-scale variability, essentially attributed to snow drift and surface roughness at Dome C, can lead to a non-exhaustive record of volcanic events when a single core is used as the site reference, with a bulk probability of 30 % of missing volcanic events and close to 65 % uncertainty on one volcanic flux measurement (based on the standard deviation obtained from a five-core comparison). Averaging n records reduces the uncertainty of the deposited flux mean significantly (by a factor 1∕ n); in the case of five cores, the uncertainty of the mean flux can therefore be reduced to 29 %.
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gautier2016climatevariability Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;E. Gautier;J. Savarino;J. Erbland;A. Lanciki;P. Possenti
Journal proceedings - 16th ieee/acis international conference on computer and information science, icis 2017
Year 2016
DOI
10.5194/cp-12-103-2016
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