Inverse stochastic–dynamic models for high-resolution Greenland ice core records
International audience 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 δ 18 O and dust records of un...
Published in: | Earth System Dynamics |
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ftecoleponts:oai:HAL:insu-03321824v1 2024-09-15T18:08:55+00:00 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 Laboratoire de Météorologie Dynamique (UMR 8539) (LMD) Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X) Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL) Institute of Geophysics and Planetary Physics Los Angeles (IGPP) University of California Los Angeles (UCLA) University of California (UC)-University of California (UC) Virginia Polytechnic Institute and State University Blacksburg Institute of Applied Physics of RAS Russian Academy of Sciences Moscow (RAS) Lamont-Doherty Earth Observatory (LDEO) Columbia University New York Centre for Ice and Climate Copenhagen Niels Bohr Institute Copenhagen (NBI) Faculty of Science Copenhagen University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH)-Faculty of Science Copenhagen University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH) Oeschger Centre for Climate Change Research (OCCR) Universität Bern = University of Bern = Université de Berne (UNIBE) 2017 https://insu.hal.science/insu-03321824 https://insu.hal.science/insu-03321824/document https://insu.hal.science/insu-03321824/file/DDR_ESD_Boers17.pdf https://doi.org/10.5194/esd-8-1171-2017 en eng HAL CCSD European Geosciences Union info:eu-repo/semantics/altIdentifier/doi/10.5194/esd-8-1171-2017 insu-03321824 https://insu.hal.science/insu-03321824 https://insu.hal.science/insu-03321824/document https://insu.hal.science/insu-03321824/file/DDR_ESD_Boers17.pdf doi:10.5194/esd-8-1171-2017 info:eu-repo/semantics/OpenAccess ISSN: 2190-4979 EISSN: 2190-4987 Earth System Dynamics https://insu.hal.science/insu-03321824 Earth System Dynamics, 2017, 8 (4), pp.1171 - 1190. ⟨10.5194/esd-8-1171-2017⟩ [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology info:eu-repo/semantics/article Journal articles 2017 ftecoleponts https://doi.org/10.5194/esd-8-1171-2017 2024-08-13T23:47:27Z International audience 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 δ 18 O 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 δ 18 O 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 δ 18 O and dust time series, and (iv) non-Markovian contributions that represent short-term memory effects. Article in Journal/Newspaper Greenland Greenland ice core Greenland Ice core Project Greenland ice cores ice core NGRIP North Greenland North Greenland Ice Core Project École des Ponts ParisTech: HAL Earth System Dynamics 8 4 1171 1190 |
institution |
Open Polar |
collection |
École des Ponts ParisTech: HAL |
op_collection_id |
ftecoleponts |
language |
English |
topic |
[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology |
spellingShingle |
[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology Boers, Niklas Chekroun, Mickael, D Liu, Honghu Kondrashov, Dmitri Rousseau, Denis-Didier Svensson, Anders Bigler, Matthias Ghil, Michael Inverse stochastic–dynamic models for high-resolution Greenland ice core records |
topic_facet |
[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology |
description |
International audience 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 δ 18 O 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 δ 18 O 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 δ 18 O and dust time series, and (iv) non-Markovian contributions that represent short-term memory effects. |
author2 |
Laboratoire de Météorologie Dynamique (UMR 8539) (LMD) Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X) Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL) Institute of Geophysics and Planetary Physics Los Angeles (IGPP) University of California Los Angeles (UCLA) University of California (UC)-University of California (UC) Virginia Polytechnic Institute and State University Blacksburg Institute of Applied Physics of RAS Russian Academy of Sciences Moscow (RAS) Lamont-Doherty Earth Observatory (LDEO) Columbia University New York Centre for Ice and Climate Copenhagen Niels Bohr Institute Copenhagen (NBI) Faculty of Science Copenhagen University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH)-Faculty of Science Copenhagen University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH) Oeschger Centre for Climate Change Research (OCCR) Universität Bern = University of Bern = Université de Berne (UNIBE) |
format |
Article in Journal/Newspaper |
author |
Boers, Niklas Chekroun, Mickael, D Liu, Honghu Kondrashov, Dmitri Rousseau, Denis-Didier Svensson, Anders Bigler, Matthias Ghil, Michael |
author_facet |
Boers, Niklas Chekroun, Mickael, D Liu, Honghu Kondrashov, Dmitri Rousseau, Denis-Didier Svensson, Anders Bigler, Matthias Ghil, Michael |
author_sort |
Boers, Niklas |
title |
Inverse stochastic–dynamic models for high-resolution Greenland ice core records |
title_short |
Inverse stochastic–dynamic models for high-resolution Greenland ice core records |
title_full |
Inverse stochastic–dynamic models for high-resolution Greenland ice core records |
title_fullStr |
Inverse stochastic–dynamic models for high-resolution Greenland ice core records |
title_full_unstemmed |
Inverse stochastic–dynamic models for high-resolution Greenland ice core records |
title_sort |
inverse stochastic–dynamic models for high-resolution greenland ice core records |
publisher |
HAL CCSD |
publishDate |
2017 |
url |
https://insu.hal.science/insu-03321824 https://insu.hal.science/insu-03321824/document https://insu.hal.science/insu-03321824/file/DDR_ESD_Boers17.pdf https://doi.org/10.5194/esd-8-1171-2017 |
genre |
Greenland Greenland ice core Greenland Ice core Project Greenland ice cores ice core NGRIP North Greenland North Greenland Ice Core Project |
genre_facet |
Greenland Greenland ice core Greenland Ice core Project Greenland ice cores ice core NGRIP North Greenland North Greenland Ice Core Project |
op_source |
ISSN: 2190-4979 EISSN: 2190-4987 Earth System Dynamics https://insu.hal.science/insu-03321824 Earth System Dynamics, 2017, 8 (4), pp.1171 - 1190. ⟨10.5194/esd-8-1171-2017⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/esd-8-1171-2017 insu-03321824 https://insu.hal.science/insu-03321824 https://insu.hal.science/insu-03321824/document https://insu.hal.science/insu-03321824/file/DDR_ESD_Boers17.pdf doi:10.5194/esd-8-1171-2017 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/esd-8-1171-2017 |
container_title |
Earth System Dynamics |
container_volume |
8 |
container_issue |
4 |
container_start_page |
1171 |
op_container_end_page |
1190 |
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1810446284455149568 |