Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year
    4.890
  • CiteScore value: 4.49 CiteScore
    4.49
  • SNIP value: 1.539 SNIP 1.539
  • IPP value: 4.28 IPP 4.28
  • SJR value: 2.404 SJR 2.404
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 51 Scimago H
    index 51
  • h5-index value: 40 h5-index 40
Volume 9, issue 5
Geosci. Model Dev., 9, 1697-1723, 2016
https://doi.org/10.5194/gmd-9-1697-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 9, 1697-1723, 2016
https://doi.org/10.5194/gmd-9-1697-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Methods for assessment of models 04 May 2016

Methods for assessment of models | 04 May 2016

Large ensemble modeling of the last deglacial retreat of the West Antarctic Ice Sheet: comparison of simple and advanced statistical techniques

David Pollard et al.
Download
Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by David Pollard on behalf of the Authors (16 Feb 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (21 Mar 2016) by Philippe Huybrechts
RR by Nicholas Golledge (24 Mar 2016)
ED: Publish as is (10 Apr 2016) by Philippe Huybrechts
Publications Copernicus
Download
Short summary
Computer modeling of variations of the Antarctic Ice Sheet help to understand the ice sheet's sensitivity to climate change. We apply a numerical model to its retreat over the last 20 000 years, from its maximum glacial extent to modern. An ensemble of 625 simulations is performed with systematic combinations of uncertain model parameter values. Results are analyzed using (1) simple averaging, and (2) advanced statistical techniques, and reasonable agreement is found between the two.
Computer modeling of variations of the Antarctic Ice Sheet help to understand the ice sheet's...
Citation
Share