Published February 27, 2019 | Version v1
Dataset Open

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

  • 1. Georges Lemaître Centre for Earth and Climate Research (TECLIM), Earth and Life Institute (ELI), Université catholique de Louvain (UCL), Belgium
  • 2. Research School of Earth Sciences, Australian National University, Canberra ACT 2601, Australia
  • 3. Australian Antarctic Division, 203 Channel Highway, Kingston, Tasmania 7050, Australia
  • 4. Laboratoire des Sciences du Climat et de l'Environnement (IPSL/CEA-CNRS-UVSQ UMR 8212), CEA Saclay, 91191 Gif-sur-Yvette CEDEX, France
  • 5. University of Bern, Oeschger Centre for Climate Change Research & Institute of Geography, 3012 Bern, Switzerland
  • 6. Department of Geology – Quaternary Science, Lund University, Sölvegatan 12, 223 62, Lund, Sweden
  • 7. Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, USA
  • 8. Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Venice, Italy
  • 9. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 27570 Bremerhaven, Germany

Description

This dataset contains data assimilation-based temperature and δ18O 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:

  1. d18O_DA_ECHAM5-MPI-OM_1-2015.nc: data assimilation-based δ18O reconstructions using the model ensemble derived from ECHAM5-MPI-OM
  2. ts_DA_ECHAM5-MPI-OM_1-2015.nc: data assimilation-based surface temperature reconstructions using the model ensemble derived from ECHAM5-MPI-OM
  3. d18O_DA_ECHAM5-wiso_1-2015.nc: data assimilation-based δ18O reconstructions using the model ensemble derived from ECHAM5-wiso
  4. 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 δ18O). 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 δ18O). 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.

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