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

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

doi:https://doi.org/10.5194/esd-8-1171-2017

Articles | Volume 8, issue 4

Earth Syst. Dynam., 8, 1171–1190, 2017

https://doi.org/10.5194/esd-8-1171-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Earth Syst. Dynam., 8, 1171–1190, 2017

https://doi.org/10.5194/esd-8-1171-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

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 et al.

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Final revised paper (published on 15 Dec 2017)
Preprint (discussion started on 24 Jan 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Review Boers et al.', Anonymous Referee #1, 01 Feb 2017
- AC1: 'Response to Anonymous Referee #1:', Niklas Boers, 22 May 2017
RC2: 'Interactive comment on “Inverse stochastic-dynamic models for high-resolution Greenland ice-core records” by Niklas Boers et al.', Takahito Mitsui, 05 May 2017
- AC2: 'Responses to Takahito Mitsui', Niklas Boers, 22 May 2017

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.