Data assimilation-based surface temperature reconstructions over the last two millennia over Antarctica

This dataset contains data assimilation-based temperature and δ 18 O reconstructions in 10 Antarctic regions over the last two millennia, presented in : Klein, F., Abram, N. J., Curran, M. A. J., Goosse, H., Goursaud, S., Masson-Delmotte, V., Moy, A., Neukom, R., Orsi, A., Sjolte, J., Steiger, N., S...

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Main Authors: Klein, François, Abram, Nerilie J., Curran, Mark A. J., Goosse, Hugues, Goursaud, Sentia, Masson-Delmotte, Valérie, Moy, Andrew, Neukom, Raphael, Orsi, Anaïs, Sjolte, Jesper, Steiger, Nathan, Stenni, Barbara, Werner, Martin
Format: Dataset
Language:unknown
Published: Zenodo 2019
Subjects:
Dee
Online Access:https://dx.doi.org/10.5281/zenodo.2579203
https://zenodo.org/record/2579203
id ftdatacite:10.5281/zenodo.2579203
record_format openpolar
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Climate reconstruction
Data assimilation
Water isotopes
Paleoclimate
spellingShingle Climate reconstruction
Data assimilation
Water isotopes
Paleoclimate
Klein, François
Abram, Nerilie J.
Curran, Mark A. J.
Goosse, Hugues
Goursaud, Sentia
Masson-Delmotte, Valérie
Moy, Andrew
Neukom, Raphael
Orsi, Anaïs
Sjolte, Jesper
Steiger, Nathan
Stenni, Barbara
Werner, Martin
Data assimilation-based surface temperature reconstructions over the last two millennia over Antarctica
topic_facet Climate reconstruction
Data assimilation
Water isotopes
Paleoclimate
description This dataset contains data assimilation-based temperature and δ 18 O reconstructions in 10 Antarctic regions over the last two millennia, presented in : Klein, F., Abram, N. J., Curran, M. A. J., Goosse, H., Goursaud, S., Masson-Delmotte, V., Moy, A., Neukom, R., Orsi, A., Sjolte, J., Steiger, N., Stenni, B., and Werner, M.: Assessing the robustness of Antarctic temperature reconstructions over the past two millennia using pseudoproxy and data assimilation experiments, Clim. Past Discuss., https://doi.org/10.5194/cp-2018-90, in review, 2018. We use a new database of stable oxygen isotopes in ice cores compiled in the framework of Antarctica2k (Stenni et al., 2017) to constrain model ensembles derived from two simulations: one performed using ECHAM5-MPI-OM that covers the period 800-1999 CE with a horizontal resolution of 3.75° by 3.75° (Sjolte et al., 2018), and the other performed with ECHAM5-wiso, spanning 1871-2011 CE at 1.125° spatial resolution (Steiger et al., 2017). This latter simulation is available here. Four netCDF files are available: d18O_DA_ECHAM5-MPI-OM_1-2015.nc: data assimilation-based δ 18 O reconstructions using the model ensemble derived from ECHAM5-MPI-OM ts_DA_ECHAM5-MPI-OM_1-2015.nc: data assimilation-based surface temperature reconstructions using the model ensemble derived from ECHAM5-MPI-OM d18O_DA_ECHAM5-wiso_1-2015.nc: data assimilation-based δ 18 O reconstructions using the model ensemble derived from ECHAM5-wiso ts_DA_ECHAM5-wiso_1-2015.nc: data assimilation-based surface temperature reconstructions using the model ensemble derived from ECHAM5-wiso The variables included in the NetCDF files are: region: integers from 1 to 10 corresponding to the ID of the ten reconstructions targets, that were defined in Stenni et al. (2017): 1: East Antarctic Plateau 2: Wilkes Land Coast 3: Weddell Sea Coast 4: Antarctic Peninsula 5: West Antarctic Ice Sheet 6: Victoria Land Coast-Ross Sea 7: Dronning Maud Land Coast 8: West Antarctica 9: East Antarctica 10: Antarctica time: integers from 1 to 2015, corresponding to the years CE covered by the reconstructions DA_ts (or DA_d18O): data assimilation-based reconstructed surface temperature (or δ 18 O). The values are annual means and are given in anomalies computed over full period. The units are degrees celsius (or permil). DA_ts_std (or DA_d18O_std): Weighted standard deviation of the particles used for reconstructing temperature (or δ 18 O). The units are degrees celsius (or permil). For a detailed description of the experimental design, please see the associated publication (Klein et al., 2018). Don't hesitate to contact François Klein for more information. References Klein, F., Abram, N. J., Curran, M. A. J., Goosse, H., Goursaud, S., Masson-Delmotte, V., Moy, A., Neukom, R., Orsi, A., Sjolte, J., Steiger, N., Stenni, B., and Werner, M.: Assessing the robustness of Antarctic temperature reconstructions over the past two millennia using pseudoproxy and data assimilation experiments, Clim. Past Discuss., https://doi.org/10.5194/cp-2018-90, in review, 2018. Sjolte, J., Sturm, C., Adolphi, F., Vinther, B. M., Werner, M., Lohmann, G., and Muscheler, R.: Solar and volcanic forcing of North Atlantic climate inferred from a process-based reconstruction, Climate of the Past, 14, 1179–1194, https://doi.org/10.5194/cp-14-1179-2018, 2018. Steiger, N. J., Steig, E. J., Dee, S. G., Roe, G. H., and Hakim, G. J.: Climate reconstruction using data assimilation of water isotope ratios from ice cores, Journal of Geophysical Research: Atmospheres, 122, 1545–1568, https://doi.org/10.1002/2016JD026011, 2017. Stenni, B., Curran, M. A. J., Abram, N. J., Orsi, A., Goursaud, S., Masson-Delmotte, V., Neukom, R., Goosse, H., Divine, D., van Ommen, T., Steig, E. J., Dixon, D. A., Thomas, E. R., Bertler, N. A. N., Isaksson, E., Ekaykin, A., Werner, M., and Frezzotti, M.: Antarctic climate variability on regional and continental scales over the last 2000 years, Climate of the Past, 13, 1609–1634, https://doi.org/10.5194/cp-13-1609-2017, 2017.
format Dataset
author Klein, François
Abram, Nerilie J.
Curran, Mark A. J.
Goosse, Hugues
Goursaud, Sentia
Masson-Delmotte, Valérie
Moy, Andrew
Neukom, Raphael
Orsi, Anaïs
Sjolte, Jesper
Steiger, Nathan
Stenni, Barbara
Werner, Martin
author_facet Klein, François
Abram, Nerilie J.
Curran, Mark A. J.
Goosse, Hugues
Goursaud, Sentia
Masson-Delmotte, Valérie
Moy, Andrew
Neukom, Raphael
Orsi, Anaïs
Sjolte, Jesper
Steiger, Nathan
Stenni, Barbara
Werner, Martin
author_sort Klein, François
title Data assimilation-based surface temperature reconstructions over the last two millennia over Antarctica
title_short Data assimilation-based surface temperature reconstructions over the last two millennia over Antarctica
title_full Data assimilation-based surface temperature reconstructions over the last two millennia over Antarctica
title_fullStr Data assimilation-based surface temperature reconstructions over the last two millennia over Antarctica
title_full_unstemmed Data assimilation-based surface temperature reconstructions over the last two millennia over Antarctica
title_sort data assimilation-based surface temperature reconstructions over the last two millennia over antarctica
publisher Zenodo
publishDate 2019
url https://dx.doi.org/10.5281/zenodo.2579203
https://zenodo.org/record/2579203
long_lat ENVELOPE(-59.767,-59.767,-62.433,-62.433)
ENVELOPE(162.967,162.967,-71.050,-71.050)
ENVELOPE(120.000,120.000,-69.000,-69.000)
geographic Antarctic
Antarctic Peninsula
Dee
Dronning Maud Land
East Antarctica
Ross Sea
Sturm
Victoria Land
Weddell
Weddell Sea
West Antarctic Ice Sheet
West Antarctica
Wilkes Land
geographic_facet Antarctic
Antarctic Peninsula
Dee
Dronning Maud Land
East Antarctica
Ross Sea
Sturm
Victoria Land
Weddell
Weddell Sea
West Antarctic Ice Sheet
West Antarctica
Wilkes Land
genre Antarc*
Antarctic
Antarctic Peninsula
Antarctica
Dronning Maud Land
East Antarctica
Ice Sheet
North Atlantic
Ross Sea
Victoria Land
Weddell Sea
West Antarctica
Wilkes Land
genre_facet Antarc*
Antarctic
Antarctic Peninsula
Antarctica
Dronning Maud Land
East Antarctica
Ice Sheet
North Atlantic
Ross Sea
Victoria Land
Weddell Sea
West Antarctica
Wilkes Land
op_relation https://dx.doi.org/10.5281/zenodo.2579204
op_rights Open Access
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5281/zenodo.2579203
https://doi.org/10.5281/zenodo.2579204
_version_ 1766256067904274432
spelling ftdatacite:10.5281/zenodo.2579203 2023-05-15T13:51:58+02:00 Data assimilation-based surface temperature reconstructions over the last two millennia over Antarctica Klein, François Abram, Nerilie J. Curran, Mark A. J. Goosse, Hugues Goursaud, Sentia Masson-Delmotte, Valérie Moy, Andrew Neukom, Raphael Orsi, Anaïs Sjolte, Jesper Steiger, Nathan Stenni, Barbara Werner, Martin 2019 https://dx.doi.org/10.5281/zenodo.2579203 https://zenodo.org/record/2579203 unknown Zenodo https://dx.doi.org/10.5281/zenodo.2579204 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY Climate reconstruction Data assimilation Water isotopes Paleoclimate dataset Dataset 2019 ftdatacite https://doi.org/10.5281/zenodo.2579203 https://doi.org/10.5281/zenodo.2579204 2021-11-05T12:55:41Z This dataset contains data assimilation-based temperature and δ 18 O reconstructions in 10 Antarctic regions over the last two millennia, presented in : Klein, F., Abram, N. J., Curran, M. A. J., Goosse, H., Goursaud, S., Masson-Delmotte, V., Moy, A., Neukom, R., Orsi, A., Sjolte, J., Steiger, N., Stenni, B., and Werner, M.: Assessing the robustness of Antarctic temperature reconstructions over the past two millennia using pseudoproxy and data assimilation experiments, Clim. Past Discuss., https://doi.org/10.5194/cp-2018-90, in review, 2018. We use a new database of stable oxygen isotopes in ice cores compiled in the framework of Antarctica2k (Stenni et al., 2017) to constrain model ensembles derived from two simulations: one performed using ECHAM5-MPI-OM that covers the period 800-1999 CE with a horizontal resolution of 3.75° by 3.75° (Sjolte et al., 2018), and the other performed with ECHAM5-wiso, spanning 1871-2011 CE at 1.125° spatial resolution (Steiger et al., 2017). This latter simulation is available here. Four netCDF files are available: d18O_DA_ECHAM5-MPI-OM_1-2015.nc: data assimilation-based δ 18 O reconstructions using the model ensemble derived from ECHAM5-MPI-OM ts_DA_ECHAM5-MPI-OM_1-2015.nc: data assimilation-based surface temperature reconstructions using the model ensemble derived from ECHAM5-MPI-OM d18O_DA_ECHAM5-wiso_1-2015.nc: data assimilation-based δ 18 O reconstructions using the model ensemble derived from ECHAM5-wiso ts_DA_ECHAM5-wiso_1-2015.nc: data assimilation-based surface temperature reconstructions using the model ensemble derived from ECHAM5-wiso The variables included in the NetCDF files are: region: integers from 1 to 10 corresponding to the ID of the ten reconstructions targets, that were defined in Stenni et al. (2017): 1: East Antarctic Plateau 2: Wilkes Land Coast 3: Weddell Sea Coast 4: Antarctic Peninsula 5: West Antarctic Ice Sheet 6: Victoria Land Coast-Ross Sea 7: Dronning Maud Land Coast 8: West Antarctica 9: East Antarctica 10: Antarctica time: integers from 1 to 2015, corresponding to the years CE covered by the reconstructions DA_ts (or DA_d18O): data assimilation-based reconstructed surface temperature (or δ 18 O). The values are annual means and are given in anomalies computed over full period. The units are degrees celsius (or permil). DA_ts_std (or DA_d18O_std): Weighted standard deviation of the particles used for reconstructing temperature (or δ 18 O). The units are degrees celsius (or permil). For a detailed description of the experimental design, please see the associated publication (Klein et al., 2018). Don't hesitate to contact François Klein for more information. References Klein, F., Abram, N. J., Curran, M. A. J., Goosse, H., Goursaud, S., Masson-Delmotte, V., Moy, A., Neukom, R., Orsi, A., Sjolte, J., Steiger, N., Stenni, B., and Werner, M.: Assessing the robustness of Antarctic temperature reconstructions over the past two millennia using pseudoproxy and data assimilation experiments, Clim. Past Discuss., https://doi.org/10.5194/cp-2018-90, in review, 2018. Sjolte, J., Sturm, C., Adolphi, F., Vinther, B. M., Werner, M., Lohmann, G., and Muscheler, R.: Solar and volcanic forcing of North Atlantic climate inferred from a process-based reconstruction, Climate of the Past, 14, 1179–1194, https://doi.org/10.5194/cp-14-1179-2018, 2018. Steiger, N. J., Steig, E. J., Dee, S. G., Roe, G. H., and Hakim, G. J.: Climate reconstruction using data assimilation of water isotope ratios from ice cores, Journal of Geophysical Research: Atmospheres, 122, 1545–1568, https://doi.org/10.1002/2016JD026011, 2017. Stenni, B., Curran, M. A. J., Abram, N. J., Orsi, A., Goursaud, S., Masson-Delmotte, V., Neukom, R., Goosse, H., Divine, D., van Ommen, T., Steig, E. J., Dixon, D. A., Thomas, E. R., Bertler, N. A. N., Isaksson, E., Ekaykin, A., Werner, M., and Frezzotti, M.: Antarctic climate variability on regional and continental scales over the last 2000 years, Climate of the Past, 13, 1609–1634, https://doi.org/10.5194/cp-13-1609-2017, 2017. Dataset Antarc* Antarctic Antarctic Peninsula Antarctica Dronning Maud Land East Antarctica Ice Sheet North Atlantic Ross Sea Victoria Land Weddell Sea West Antarctica Wilkes Land DataCite Metadata Store (German National Library of Science and Technology) Antarctic Antarctic Peninsula Dee ENVELOPE(-59.767,-59.767,-62.433,-62.433) Dronning Maud Land East Antarctica Ross Sea Sturm ENVELOPE(162.967,162.967,-71.050,-71.050) Victoria Land Weddell Weddell Sea West Antarctic Ice Sheet West Antarctica Wilkes Land ENVELOPE(120.000,120.000,-69.000,-69.000)