Articles | Volume 8, issue 4
Research article
15 Dec 2017
Research article |  | 15 Dec 2017

Inverse stochastic–dynamic models for high-resolution Greenland ice core records

Niklas Boers, Mickael D. Chekroun, Honghu Liu, Dmitri Kondrashov, Denis-Didier Rousseau, Anders Svensson, Matthias Bigler, and Michael Ghil


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: Reconsider after major revisions (30 May 2017) by Anders Levermann
AR by Niklas Boers on behalf of the Authors (19 Jun 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (20 Jun 2017) by Anders Levermann
RR by Takahito Mitsui (04 Jul 2017)
ED: Publish subject to technical corrections (12 Nov 2017) by Anders Levermann
AR by Niklas Boers on behalf of the Authors (12 Nov 2017)  Author's response    Manuscript
Short summary
We use a Bayesian approach for inferring inverse, stochastic–dynamic models from northern Greenland (NGRIP) oxygen and dust records of subdecadal resolution for the interval 59 to 22 ka b2k. Our model reproduces the statistical and dynamical characteristics of the records, including the Dansgaard–Oeschger variability, with no need for external forcing. The crucial ingredients are cubic drift terms, nonlinear coupling terms between the oxygen and dust time series, and non-Markovian contributions.
Final-revised paper