Integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the PalMod 130k marine palaeoclimate data synthesis

International audience Abstract. Palaeoclimate data hold the unique promise of providing a long-term perspective on climate change and as such can serve as an important benchmark for climate models. However, palaeoclimate data have generally been archived with insufficient standardisation and metada...

Full description

Bibliographic Details
Published in:Earth System Science Data
Main Authors: Jonkers, Lukas, Cartapanis, Olivier, Langner, Michael, Mckay, Nick, Mulitza, Stefan, Strack, Anne, Kucera, Michal
Other Authors: Oeschger Centre for Climate Change Research (OCCR), University of Bern, Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Center for Marine Environmental Sciences Bremen (MARUM), Universität Bremen, School of Earth and Sustainability, Northern Arizona University Flagstaff, Bundesministerium fur Bildung und Forschung (PalMod grant) - Swiss National Science FoundationPP00P2-144811
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2020
Subjects:
Online Access:https://hal.inrae.fr/hal-03311934
https://hal.inrae.fr/hal-03311934/document
https://hal.inrae.fr/hal-03311934/file/essd-12-1053-2020.pdf
https://doi.org/10.5194/essd-12-1053-2020
id ftunivnantes:oai:HAL:hal-03311934v1
record_format openpolar
institution Open Polar
collection Université de Nantes: HAL-UNIV-NANTES
op_collection_id ftunivnantes
language English
topic Sea-surface Temperature
Atlantic Deep-water
Eastern Equatorial Pacific
South China Sea
Northern-hemisphere Climate
Millennial-scale Changes
Southeastern New-zealand
Western Iberian Margin
Intermediate Water
Llast Deglaciation
[SDU.STU.AG]Sciences of the Universe [physics]/Earth Sciences/Applied geology
[SDU]Sciences of the Universe [physics]
spellingShingle Sea-surface Temperature
Atlantic Deep-water
Eastern Equatorial Pacific
South China Sea
Northern-hemisphere Climate
Millennial-scale Changes
Southeastern New-zealand
Western Iberian Margin
Intermediate Water
Llast Deglaciation
[SDU.STU.AG]Sciences of the Universe [physics]/Earth Sciences/Applied geology
[SDU]Sciences of the Universe [physics]
Jonkers, Lukas
Cartapanis, Olivier
Langner, Michael
Mckay, Nick
Mulitza, Stefan
Strack, Anne
Kucera, Michal
Integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the PalMod 130k marine palaeoclimate data synthesis
topic_facet Sea-surface Temperature
Atlantic Deep-water
Eastern Equatorial Pacific
South China Sea
Northern-hemisphere Climate
Millennial-scale Changes
Southeastern New-zealand
Western Iberian Margin
Intermediate Water
Llast Deglaciation
[SDU.STU.AG]Sciences of the Universe [physics]/Earth Sciences/Applied geology
[SDU]Sciences of the Universe [physics]
description International audience Abstract. Palaeoclimate data hold the unique promise of providing a long-term perspective on climate change and as such can serve as an important benchmark for climate models. However, palaeoclimate data have generally been archived with insufficient standardisation and metadata to allow for transparent and consistent uncertainty assessment in an automated way. Thanks to improved computation capacity, transient palaeoclimate simulations are now possible, calling for data products containing multi-parameter time series rather than information on a single parameter for a single time slice. Efforts are underway to simulate a complete glacial–interglacial cycle using general circulation models (https://www.palmod.de/, last access: 6 May 2020), and to confront these simulations with palaeoclimate data, we have compiled a multi-parameter marine palaeoclimate data synthesis that contains time series spanning 0 to 130 000 years ago. We present the first version of the data product that focuses exclusively on time series for which a robust chronology based on benthic foraminifera δ18O and radiocarbon dating is available. The product contains 896 time series of eight palaeoclimate parameters from 143 individual sites, each associated with rich metadata, age–depth model ensembles, and information to refine and update the chronologies. This version contains 205 time series of benthic foraminifera δ18O; 169 of benthic foraminifera δ13C; 131 of seawater temperature; 174 and 119 of planktonic foraminifera δ18O and δ13C; and 44, 38 and 16 of carbonate, organic carbon and biogenic silica content, respectively. The data product is available in three formats (R, LiPD and netCDF) facilitating use across different software and operating systems and can be downloaded at https://doi.org/10.1594/PANGAEA.908831 (Jonkers et al., 2019). This data descriptor presents our data synthesis strategy and describes the contents and format of the data product in detail. It ends with a set of recommendations for data ...
author2 Oeschger Centre for Climate Change Research (OCCR)
University of Bern
Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE)
Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Center for Marine Environmental Sciences Bremen (MARUM)
Universität Bremen
School of Earth and Sustainability
Northern Arizona University Flagstaff
Bundesministerium fur Bildung und Forschung (PalMod grant) - Swiss National Science FoundationPP00P2-144811
format Article in Journal/Newspaper
author Jonkers, Lukas
Cartapanis, Olivier
Langner, Michael
Mckay, Nick
Mulitza, Stefan
Strack, Anne
Kucera, Michal
author_facet Jonkers, Lukas
Cartapanis, Olivier
Langner, Michael
Mckay, Nick
Mulitza, Stefan
Strack, Anne
Kucera, Michal
author_sort Jonkers, Lukas
title Integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the PalMod 130k marine palaeoclimate data synthesis
title_short Integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the PalMod 130k marine palaeoclimate data synthesis
title_full Integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the PalMod 130k marine palaeoclimate data synthesis
title_fullStr Integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the PalMod 130k marine palaeoclimate data synthesis
title_full_unstemmed Integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the PalMod 130k marine palaeoclimate data synthesis
title_sort integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the palmod 130k marine palaeoclimate data synthesis
publisher HAL CCSD
publishDate 2020
url https://hal.inrae.fr/hal-03311934
https://hal.inrae.fr/hal-03311934/document
https://hal.inrae.fr/hal-03311934/file/essd-12-1053-2020.pdf
https://doi.org/10.5194/essd-12-1053-2020
geographic New Zealand
Pacific
geographic_facet New Zealand
Pacific
genre Planktonic foraminifera
genre_facet Planktonic foraminifera
op_source ISSN: 1866-3508
Earth System Science Data
https://hal.inrae.fr/hal-03311934
Earth System Science Data, 2020, 12 (2), pp.1053-1081. ⟨10.5194/essd-12-1053-2020⟩
op_relation info:eu-repo/semantics/altIdentifier/doi/10.5194/essd-12-1053-2020
hal-03311934
https://hal.inrae.fr/hal-03311934
https://hal.inrae.fr/hal-03311934/document
https://hal.inrae.fr/hal-03311934/file/essd-12-1053-2020.pdf
doi:10.5194/essd-12-1053-2020
WOS: 000531893900001
op_rights http://creativecommons.org/licenses/by/
info:eu-repo/semantics/OpenAccess
op_doi https://doi.org/10.5194/essd-12-1053-2020
container_title Earth System Science Data
container_volume 12
container_issue 2
container_start_page 1053
op_container_end_page 1081
_version_ 1766170535438319616
spelling ftunivnantes:oai:HAL:hal-03311934v1 2023-05-15T18:01:11+02:00 Integrating palaeoclimate time series with rich metadata for uncertainty modelling: strategy and documentation of the PalMod 130k marine palaeoclimate data synthesis Jonkers, Lukas Cartapanis, Olivier Langner, Michael Mckay, Nick Mulitza, Stefan Strack, Anne Kucera, Michal Oeschger Centre for Climate Change Research (OCCR) University of Bern Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE) Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) Center for Marine Environmental Sciences Bremen (MARUM) Universität Bremen School of Earth and Sustainability Northern Arizona University Flagstaff Bundesministerium fur Bildung und Forschung (PalMod grant) - Swiss National Science FoundationPP00P2-144811 2020 https://hal.inrae.fr/hal-03311934 https://hal.inrae.fr/hal-03311934/document https://hal.inrae.fr/hal-03311934/file/essd-12-1053-2020.pdf https://doi.org/10.5194/essd-12-1053-2020 en eng HAL CCSD Copernicus Publications info:eu-repo/semantics/altIdentifier/doi/10.5194/essd-12-1053-2020 hal-03311934 https://hal.inrae.fr/hal-03311934 https://hal.inrae.fr/hal-03311934/document https://hal.inrae.fr/hal-03311934/file/essd-12-1053-2020.pdf doi:10.5194/essd-12-1053-2020 WOS: 000531893900001 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 1866-3508 Earth System Science Data https://hal.inrae.fr/hal-03311934 Earth System Science Data, 2020, 12 (2), pp.1053-1081. ⟨10.5194/essd-12-1053-2020⟩ Sea-surface Temperature Atlantic Deep-water Eastern Equatorial Pacific South China Sea Northern-hemisphere Climate Millennial-scale Changes Southeastern New-zealand Western Iberian Margin Intermediate Water Llast Deglaciation [SDU.STU.AG]Sciences of the Universe [physics]/Earth Sciences/Applied geology [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2020 ftunivnantes https://doi.org/10.5194/essd-12-1053-2020 2023-02-22T03:07:35Z International audience Abstract. Palaeoclimate data hold the unique promise of providing a long-term perspective on climate change and as such can serve as an important benchmark for climate models. However, palaeoclimate data have generally been archived with insufficient standardisation and metadata to allow for transparent and consistent uncertainty assessment in an automated way. Thanks to improved computation capacity, transient palaeoclimate simulations are now possible, calling for data products containing multi-parameter time series rather than information on a single parameter for a single time slice. Efforts are underway to simulate a complete glacial–interglacial cycle using general circulation models (https://www.palmod.de/, last access: 6 May 2020), and to confront these simulations with palaeoclimate data, we have compiled a multi-parameter marine palaeoclimate data synthesis that contains time series spanning 0 to 130 000 years ago. We present the first version of the data product that focuses exclusively on time series for which a robust chronology based on benthic foraminifera δ18O and radiocarbon dating is available. The product contains 896 time series of eight palaeoclimate parameters from 143 individual sites, each associated with rich metadata, age–depth model ensembles, and information to refine and update the chronologies. This version contains 205 time series of benthic foraminifera δ18O; 169 of benthic foraminifera δ13C; 131 of seawater temperature; 174 and 119 of planktonic foraminifera δ18O and δ13C; and 44, 38 and 16 of carbonate, organic carbon and biogenic silica content, respectively. The data product is available in three formats (R, LiPD and netCDF) facilitating use across different software and operating systems and can be downloaded at https://doi.org/10.1594/PANGAEA.908831 (Jonkers et al., 2019). This data descriptor presents our data synthesis strategy and describes the contents and format of the data product in detail. It ends with a set of recommendations for data ... Article in Journal/Newspaper Planktonic foraminifera Université de Nantes: HAL-UNIV-NANTES New Zealand Pacific Earth System Science Data 12 2 1053 1081