Articles | Volume 6, issue 4
https://doi.org/10.5194/gchron-6-503-2024
https://doi.org/10.5194/gchron-6-503-2024
Research article
 | 
15 Oct 2024
Research article |  | 15 Oct 2024

Towards the construction of regional marine radiocarbon calibration curves: an unsupervised machine learning approach

Ana-Cristina Mârza, Laurie Menviel, and Luke C. Skinner

Model code and software

acmarza/ocean_data_clusters: v0.1-alpha (v0.1-alpha) A.-C. Marza https://doi.org/10.5281/zenodo.13846995

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Short summary
Radiocarbon serves as a powerful dating tool, but the calibration of marine radiocarbon dates presents significant challenges because the whole surface ocean cannot be represented by a single calibration curve. Here we use climate model outputs and data to assess a novel method for developing regional marine calibration curves. Our results are encouraging and point to a way forward for solving the marine radiocarbon age calibration problem without relying on model simulations of the past.