07 Sep 2022
 | 07 Sep 2022

Bayesian age models and stacks: Combining age inferences from radiocarbon and benthic δ18O stratigraphic alignment

Taehee Lee, Devin Rand, Lorraine E. Lisiecki, Geoffrey Gebbie, and Charles E. Lawrence

Abstract. Previously developed software packages that generate probabilistic age models for ocean sediment cores are designed to use either age proxies (e.g., radiocarbon or tephra layers) or stratigraphic alignment (e.g., of benthic δ18O) and cannot combine age inferences from both techniques. Furthermore, many radiocarbon dating packages are not specifically designed for marine sediment cores and default settings may not accurately reflect the probability of sedimentation rate variability in the deep ocean, requiring subjective tuning of parameter settings. Here we present a new technique for generating Bayesian age models and stacks using ocean sediment core radiocarbon and benthic δ18O data, implemented in a software package named BIGMACS (Bayesian Inference Gaussian Process regression and Multiproxy Alignment of Continuous Signals). BIGMACS constructs multiproxy age models by combining age inferences from both radiocarbon ages and benthic δ18O stratigraphic alignment and constrains sedimentation rates using an empirically derived prior model based on 37 14C-dated ocean sediment cores (Lin et al., 2014). BIGMACS also constructs continuous benthic δ18O stacks via a Gaussian process regression, which requires a smaller number of cores than previous stacking methods. This feature allows users to construct stacks for a region that shares a homogeneous deep water δ18O signal, while leveraging radiocarbon dates across multiple cores. Thus, BIGMACS efficiently generates local or regional stacks with smaller uncertainties in both age and δ18O than previously available techniques. We present two example regional benthic δ18O stacks and demonstrate that the multiproxy age models produced by BIGMACS are more precise than their single proxy counterparts.

Taehee Lee et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-734', Anonymous Referee #1, 06 Oct 2022
  • RC2: 'Comment on egusphere-2022-734', Tim Heaton, 28 Dec 2022
  • EC1: 'Comment on egusphere-2022-734', Luke Skinner, 10 Jan 2023

Taehee Lee et al.

Model code and software

BIGMACS software package Taehee Lee, Devin Rand, Lorraine E. Lisiecki, Geoffrey Gebbie, Charles E. Lawrence

Taehee Lee et al.


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Short summary
Understanding of past climate change depends, in part, on how accurately we can estimate the ages of events recorded in geologic archives. Here we present a new software package, called BIGMACS, to improve age estimates for paleoclimate data from ocean sediment cores. BIGMACS creates “multiproxy” age estimates that reduce age uncertainty by probabilistically combining information from direct age estimates, such as radiocarbon dates, and alignment of regional paleoclimate time series.