Articles | Volume 8, issue 10
https://doi.org/10.5194/gmd-8-3071-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-3071-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
ECCO version 4: an integrated framework for non-linear inverse modeling and global ocean state estimation
G. Forget
CORRESPONDING AUTHOR
Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
J.-M. Campin
Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
P. Heimbach
Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
Jackson School of Geosciences, The University of Texas at Austin, Austin, TX 78712, USA
C. N. Hill
Dept. of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
R. M. Ponte
Atmospheric and Environmental Research, Inc., Lexington, MA 02421, USA
C. Wunsch
Dept. of Earth and Planetary Sciences, Harvard University, Cambridge, MA 02139, USA
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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...