Articles | Volume 12, issue 2
Clim. Past, 12, 525–542, 2016
Clim. Past, 12, 525–542, 2016

Research article 29 Feb 2016

Research article | 29 Feb 2016

A Bayesian hierarchical model for reconstructing relative sea level: from raw data to rates of change

Niamh Cahill et al.


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (review by Editor) (17 Jan 2016) by Eduardo Zorita
AR by Niamh Cahill on behalf of the Authors (24 Jan 2016)  Author's response
ED: Publish as is (02 Feb 2016) by Eduardo Zorita
Short summary
We propose a Bayesian model for the reconstruction and analysis of former sea levels. The model provides a single, unifying framework for reconstructing and analyzing sea level through time with fully quantified uncertainty. We illustrate our approach using a case study of Common Era (last 2000 years) sea levels from New Jersey.