A comparison of annual layer thickness model estimates with observational measurements using the Berkner Island ice core, Antarctica

• Published in: Antarctic Science
• Main Authors: Massam, A., Sneed, S.B., Lee, G.P., Tuckwell, R.R., Mulvaney, R., Mayewski, P.A., Whitehouse, P.L.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Cambridge University Press 2017
• Subjects: Antarctic; Berkner Island; Antarc*; Antarctic Science; Antarctica; ice core
• Online Access: http://nora.nerc.ac.uk/id/eprint/516260/; https://nora.nerc.ac.uk/id/eprint/516260/1/Massam.pdf; https://nora.nerc.ac.uk/id/eprint/516260/7/Massametal_AntarcticScience_accepted.pdf; https://doi.org/10.1017/S0954102017000025

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.