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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

Title:
Inverse stochastic–dynamic models for high-resolution Greenland ice core records
Author(s):
Boers, Niklas
Chekroun, Mickael D.
Liu, Honghu
Kondrashov, Dmitri
Rousseau, Denis-Didier
Svensson, Anders
Bigler, Matthias
Ghil, Michael
Date:
Type:
Articles
Department(s):
Lamont-Doherty Earth Observatory
Volume:
8
Persistent URL:
Book/Journal Title:
Earth System Dynamics
Geographic Area:
Greenland
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 δ¹⁸O 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 δ¹⁸O 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 δ¹⁸O and dust time series, and (iv) non-Markovian contributions that represent short-term memory effects.
Subject(s):
Paleoclimatology
Stochastic models
Dynamics
Climatic changes
Dust
Publisher DOI:
https://doi.org/10.5194/esd-8-1171-2017
Item views
9
Metadata:
text | xml
Suggested Citation:
Niklas Boers, Mickael D. Chekroun, Honghu Liu, Dmitri Kondrashov, Denis-Didier Rousseau, Anders Svensson, Matthias Bigler, Michael Ghil, , Inverse stochastic–dynamic models for high-resolution Greenland ice core records, Columbia University Academic Commons, .

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