Show simple item record

dc.contributor.authorPonte, R. M.
dc.contributor.authorWunsch, Carl
dc.contributor.authorForget, Gael
dc.contributor.authorCampin, Jean-Michel
dc.contributor.authorHeimbach, Patrick
dc.contributor.authorHill, Christopher N.
dc.date.accessioned2015-11-02T19:19:34Z
dc.date.available2015-11-02T19:19:34Z
dc.date.issued2015-10
dc.date.submitted2015-08
dc.identifier.issn1991-9603
dc.identifier.issn1991-959X
dc.identifier.urihttp://hdl.handle.net/1721.1/99660
dc.description.abstractThis paper presents the ECCO v4 non-linear inverse modeling framework and its baseline solution for the evolving ocean state over the period 1992–2011. Both components are publicly available and subjected to regular, automated regression tests. The modeling framework includes sets of global conformal grids, a global model setup, implementations of data constraints and control parameters, an interface to algorithmic differentiation, as well as a grid-independent, fully capable Matlab toolbox. The baseline ECCO v4 solution is a dynamically consistent ocean state estimate without unidentified sources of heat and buoyancy, which any interested user will be able to reproduce accurately. The solution is an acceptable fit to most data and has been found to be physically plausible in many respects, as documented here and in related publications. Users are being provided with capabilities to assess model–data misfits for themselves. The synergy between modeling and data synthesis is asserted through the joint presentation of the modeling framework and the state estimate. In particular, the inverse estimate of parameterized physics was instrumental in improving the fit to the observed hydrography, and becomes an integral part of the ocean model setup available for general use. More generally, a first assessment of the relative importance of external, parametric and structural model errors is presented. Parametric and external model uncertainties appear to be of comparable importance and dominate over structural model uncertainty. The results generally underline the importance of including turbulent transport parameters in the inverse problem.en_US
dc.description.sponsorshipUnited States. National Aeronautics and Space Administration. Physical Oceanography Programen_US
dc.language.isoen_US
dc.publisherCopernicus GmbHen_US
dc.relation.isversionofhttp://dx.doi.org/10.5194/gmd-8-3071-2015en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en_US
dc.sourceCopernicus Publicationsen_US
dc.titleECCO version 4: an integrated framework for non-linear inverse modeling and global ocean state estimationen_US
dc.typeArticleen_US
dc.identifier.citationForget, G., J.-M. Campin, P. Heimbach, C. N. Hill, R. M. Ponte, and C. Wunsch. “ECCO Version 4: An Integrated Framework for Non-Linear Inverse Modeling and Global Ocean State Estimation.” Geosci. Model Dev. 8, no. 10 (2015): 3071–3104.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciencesen_US
dc.contributor.mitauthorForget, Gaelen_US
dc.contributor.mitauthorCampin, Jean-Michelen_US
dc.contributor.mitauthorHeimbach, Patricken_US
dc.contributor.mitauthorHill, Christopher N.en_US
dc.relation.journalGeoscientific Model Developmenten_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsForget, G.; Campin, J.-M.; Heimbach, P.; Hill, C. N.; Ponte, R. M.; Wunsch, C.en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-3925-6161
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record