Show simple item record

dc.contributor.authorLoose, Nora
dc.contributor.authorHeimbach, Patrick
dc.contributor.authorPillar, H.R.
dc.contributor.authorNisancioglu, Kerim Hestnes
dc.date.accessioned2021-03-15T11:14:51Z
dc.date.available2021-03-15T11:14:51Z
dc.date.created2020-08-31T16:01:12Z
dc.date.issued2020
dc.identifier.issn2169-9275
dc.identifier.urihttps://hdl.handle.net/11250/2733383
dc.description.abstractOceanic quantities of interest (QoIs), for example, ocean heat content or transports, are often inaccessible to direct observation, due to the high cost of instrument deployment and logistical challenges. Therefore, oceanographers seek proxies for undersampled or unobserved QoIs. Conventionally, proxy potential is assessed via statistical correlations, which measure covariability without establishing causality. This paper introduces an alternative method: quantifying dynamical proxy potential. Using an adjoint model, this method unambiguously identifies the physical origins of covariability. A North Atlantic case study illustrates our method within the ECCO (Estimating the Circulation and Climate of the Ocean) state estimation framework. We find that wind forcing along the eastern and northern boundaries of the Atlantic drives a basin‐wide response in North Atlantic circulation and temperature. Due to these large‐scale teleconnections, a single subsurface temperature observation in the Irminger Sea informs heat transport across the remote Iceland‐Scotland ridge (ISR), with a dynamical proxy potential of 19%. Dynamical proxy potential allows two equivalent interpretations: Irminger Sea subsurface temperature (i) shares 19% of its adjustment physics with ISR heat transport and (ii) reduces the uncertainty in ISR heat transport by 19% (independent of the measured temperature value), if the Irminger Sea observation is added without noise to the ECCO state estimate. With its two interpretations, dynamical proxy potential is simultaneously rooted in (i) ocean dynamics and (ii) uncertainty quantification and optimal observing system design, the latter being an emerging branch in computational science. The new method may therefore foster dynamics‐based, quantitative ocean observing system design in the coming years.en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.relation.urihttps://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020JC016112
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleQuantifying Dynamical Proxy Potential Through Shared Adjustment Physics in the North Atlanticen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2020. The Authors.en_US
dc.source.articlenumbere2020JC016112en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.doi10.1029/2020JC016112
dc.identifier.cristin1826307
dc.source.journalJournal of Geophysical Research (JGR): Oceansen_US
dc.source.40125
dc.relation.projectNorges forskningsråd: 246929en_US
dc.relation.projectNotur/NorStore: NN4659Ken_US
dc.relation.projectNorges forskningsråd: 610055en_US
dc.identifier.citationJournal of Geophysical Research: Oceans. 2020, 125 (9), e2020JC016112.en_US
dc.source.volume125en_US
dc.source.issue9en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal