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, Michael Ghil

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

21 Citationer (Scopus)
210 Downloads (Pure)

Abstract

Proxy records from Greenland ice cores have been studied for several decades, yet many open questions remain regarding the climate variability encoded therein. Here, we use a Bayesian framework for inferring inverse, stochastic-dynamic models from 18O and dust records of unprecedented, subdecadal temporal resolution. The records stem from the North Greenland Ice Core Project (NGRIP), and we focus on the time interval 59-22 ka b2k. Our model reproduces the dynamical characteristics of both the 18O and dust proxy records, including the millennial-scale Dansgaard-Oeschger variability, as well as statistical properties such as probability density functions, waiting times and power spectra, with no need for any external forcing. The crucial ingredients for capturing these properties are (i) high-resolution training data, (ii) cubic drift terms, (iii) nonlinear coupling terms between the 18O and dust time series, and (iv) non-Markovian contributions that represent short-term memory effects.

OriginalsprogEngelsk
TidsskriftEarth System Dynamics
Vol/bind8
Udgave nummer4
Sider (fra-til)1171-1190
Antal sider20
ISSN2190-4979
DOI
StatusUdgivet - 2017

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