Articles | Volume 8, issue 4
Earth Syst. Dynam., 8, 1171–1190, 2017
Earth Syst. Dynam., 8, 1171–1190, 2017
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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Cited articles

Andersen, E. B.: Asymptotic properties of conditional maximum-likelihood estimators, J. Roy. Stat. Soc. B Met., 32, 283–301, 1970.
Andersen, K. K., Svensson, A., Johnsen, S. J., Rasmussen, S. O., Bigler, M., Rüthlisberger, R., Ruth, U., Siggaard-Andersen, M. L., Peder Steffensen, J., Dahl-Jensen, D., Vinther, B. M., and Clausen, H. B.: The Greenland Ice Core Chronology 2005, 15–42 ka. Part 1: Constructing the time scale, Quaternary Sci. Rev., 25, 3246–3257,, 2006.
Barnston, A. G., Tippett, M. K., L'Heureux, M. L., Li, S., and Dewitt, D. G.: Skill of real-time seasonal ENSO model predictions during 2002–11: is our capability increasing?, B. Am. Meteorol. Soc., 93, 631–651,, 2012.
Berger, W. H.: The 100-kyr ice-age cycle: Internal oscillation or inclinational forcing?, Int. J. Earth Sci., 88, 305–316,, 1999.
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