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    A noisy-input generalized additive model for relative sea-level change along the Atlantic coast of North America


    Upton, Maeve and Parnell, Andrew and Kemp, Andrew and Ashe, Erica and McCarthy, Gerard and Cahill, Niamh (2024) A noisy-input generalized additive model for relative sea-level change along the Atlantic coast of North America. Journal of the Royal Statistical Society Series C: Applied Statistics. ISSN 0035-9254

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    Official URL: https://doi.org/10.1093/jrsssc/qlae044


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    Abstract

    We propose a Bayesian, noisy-input, spatial–temporal generalized additive model to examine regional relative sea-level (RSL) changes over time. The model provides probabilistic estimates of component drivers of regional RSL change via the combination of a univariate spline capturing a common regional signal over time, random slopes and intercepts capturing site-specific (local), long-term linear trends and a spatial– temporal spline capturing residual, non-linear, local variations. Proxy and instrumental records of RSL and corresponding measurement errors inform the model and a noisy-input method accounts for proxy temporal uncertainties. Results highlight the decomposition of regional RSL changes over 3,000 years along North America’s Atlantic coast. The physical process glacial isostatic adjustment prevailed before 1800 CE, with anthropogenic forcing dominating after 1900 CE.

    Item Type: Article
    Keywords: Bayesian; sea level; generalized additive models; uncertainty;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Item ID: 18914
    Identification Number: https://doi.org/10.1093/jrsssc/qlae044
    Depositing User: Andrew Parnell
    Date Deposited: 24 Sep 2024 08:36
    Journal or Publication Title: Journal of the Royal Statistical Society Series C: Applied Statistics
    Publisher: The Royal Statistical Society
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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