Devising quality assurance procedures for assessment of legacy geochronological data relating to deglaciation of the last British-Irish Ice Sheet

This contribution documents the process of assessing the quality of data within a compilation of legacy geochronological data relating to the last British-Irish Ice Sheet, a task undertaken as part of a larger community-based project (BRITICE-CHRONO) that aims to improve understanding of the ice she...

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Bibliographic Details
Published in:Earth-Science Reviews
Main Authors: Small, D., Clark, C.D., Chiverrell, R.C., Smedley, R.K., Bateman, M.D., Duller, G.A.T., Ely, J.C., Fabel, D., Medialdea, A., Moreton, S.G.
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2017
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Online Access:https://eprints.whiterose.ac.uk/109852/
https://eprints.whiterose.ac.uk/109852/1/1-s2.0-S0012825216304408-main.pdf
https://doi.org/10.1016/j.earscirev.2016.11.007
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Summary:This contribution documents the process of assessing the quality of data within a compilation of legacy geochronological data relating to the last British-Irish Ice Sheet, a task undertaken as part of a larger community-based project (BRITICE-CHRONO) that aims to improve understanding of the ice sheet's deglacial evolution. As accurate reconstructions depend on the quality of the available data, some form of assessment is needed of the reliability and suitability of each given age(s) in our dataset. We outline the background considerations that informed the quality assurance procedures devised given our specific research question. We describe criteria that have been used to make an objective assessment of the likelihood that an age is influenced by the technique specific sources of geological uncertainty. When these criteria were applied to an existing database of all geochronological data relating to the last British-Irish Ice Sheet they resulted in a significant reduction in data considered suitable for synthesis. The assessed data set was used to test a Bayesian approach to age modelling ice stream retreat and we outline our procedure that allows us to minimise the influence of potentially erroneous data and maximise the accuracy of the resultant age models.