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
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 51 Scimago H index 51
Volume 8, issue 10 | Copyright
Geosci. Model Dev., 8, 3071-3104, 2015
https://doi.org/10.5194/gmd-8-3071-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 06 Oct 2015

Model description paper | 06 Oct 2015

ECCO version 4: an integrated framework for non-linear inverse modeling and global ocean state estimation

G. Forget et al.
Viewed
Total article views: 5,121 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,730 1,869 522 5,121 490 173 190
  • HTML: 2,730
  • PDF: 1,869
  • XML: 522
  • Total: 5,121
  • Supplement: 490
  • BibTeX: 173
  • EndNote: 190
Views and downloads (calculated since 05 May 2015)
Cumulative views and downloads (calculated since 05 May 2015)
Cited
Saved (final revised paper)
Saved (discussion paper)
Discussed (final revised paper)
Discussed (discussion paper)
No discussed metrics found.
Latest update: 20 Sep 2018
Publications Copernicus
Download
Short summary
The ECCO v4 non-linear inverse modeling framework and its reference solution are made publicly available. The inverse estimate of ocean physics and atmospheric forcing yields a dynamically consistent and global state estimate without unidentified sources of heat and salt that closely fits in situ and satellite data. Any user can reproduce it accurately. Parametric and external model uncertainties are of comparable magnitudes and generally exceed structural model uncertainties.
The ECCO v4 non-linear inverse modeling framework and its reference solution are made publicly...
Citation
Share