Massam, A. and Sneed, S. and Lee, G. and Tuckwell, R. and Mulvaney, R. and Mayewski, P.A. and Whitehouse, P. (2017) 'A comparison of annual layer thickness model estimates with observational measurements using the Berkner Island ice core, Antarctica.', Antarctic science. .
Abstract
A model to estimate the annual layer thickness of deposited snowfall at a deep ice core site, compacted by vertical strain with respect to depth, is assessed using ultra-high-resolution laboratory analytical techniques. A recently established technique of high-resolution direct chemical analysis of ice using ultra-violet laser ablation inductively-coupled plasma mass spectrometry (LA ICP-MS) has been applied to ice from the Berkner Island ice core, and compared with results from lower resolution techniques conducted on parallel sections of ice. The results from both techniques have been analysed in order to assess the capability of each technique to recover seasonal cycles from deep Antarctic ice. Results do not agree with the annual layer thickness estimates from the age–depth model for individual samples <1 m long as the model cannot reconstruct the natural variability present in annual accumulation. However, when compared with sections >4 m long, the deviation between the modelled and observational layer thicknesses is minimized to within two standard deviations. This confirms that the model is capable of successfully estimating mean annual layer thicknesses around analysed sections. Furthermore, our results confirm that the LA ICP-MS technique can reliably recover seasonal chemical profiles beyond standard analytical resolution.
Item Type: | Article |
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Full text: | (AM) Accepted Manuscript Download PDF (555Kb) |
Status: | Peer-reviewed |
Publisher Web site: | https://doi.org/10.1017/S0954102017000025 |
Publisher statement: | This article has been published in a revised form in Antarctic science https://doi.org/10.1017/S0954102017000025. This version is free to view and download for private research and study only. Not for re-distribution, re-sale or use in derivative works. © Antarctic Science Ltd 2017 |
Date accepted: | 25 January 2017 |
Date deposited: | 20 February 2017 |
Date of first online publication: | 14 February 2017 |
Date first made open access: | 14 August 2017 |
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