Impact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6–LIM3 global ocean–sea ice model

dc.contributor.authorMoreno Chamarro, Eduardo
dc.contributor.authorOrtega Montilla, Pablo
dc.contributor.authorMassonnet, François
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2020-10-06T16:06:21Z
dc.date.available2020-10-06T16:06:21Z
dc.date.issued2020-10-05
dc.description.abstractThis study assesses the impact of different sea ice thickness distribution (ITD) discretizations on the sea ice concentration (SIC) variability in ocean stand-alone NEMO3.6–LIM3 simulations. Three ITD discretizations with different numbers of sea ice thickness categories and boundaries are evaluated against three different satellite products (hereafter referred to as “data”). Typical model and data interannual SIC variability is characterized by K-means clustering both in the Arctic and Antarctica between 1979 and 2014. We focus on two seasons, winter (January–March) and summer (August–October), in which correlation coefficients across clusters in individual months are largest. In the Arctic, clusters are computed before and after detrending the series with a second-degree polynomial to separate interannual from longer-term variability. The analysis shows that, before detrending, winter clusters reflect the SIC response to large-scale atmospheric variability at both poles, while summer clusters capture the negative and positive trends in Arctic and Antarctic SIC, respectively. After detrending, Arctic clusters reflect the SIC response to interannual atmospheric variability predominantly. The cluster analysis is complemented with a model–data comparison of the sea ice extent and SIC anomaly patterns. The single-category discretization shows the worst model–data agreement in the Arctic summer before detrending, related to a misrepresentation of the long-term melting trend. Similarly, increasing the number of thin categories reduces model–data agreement in the Arctic, due to a poor representation of the summer melting trend and an overly large winter sea ice volume associated with a net increase in basal ice growth. In contrast, more thin categories improve model realism in Antarctica, and more thick ones improve it in central Arctic regions with very thick ice. In all the analyses we nonetheless identify no optimal discretization. Our results thus suggest that no clear benefit in the representation of SIC variability is obtained from increasing the number of sea ice thickness categories beyond the current standard with five categories in NEMO3.6–LIM3.
dc.description.peerreviewedPeer Reviewed
dc.description.sponsorshipThis research has been supported by the European Commission's Horizon 2020 APPLICATE project (grant no. GA 727862) and the European Commission's Horizon 2020 PRIMAVERA project (grant no. GA 641727).
dc.description.versionPostprint (published version)
dc.format.extent15 p.
dc.identifier.citationMoreno Chamarro, E.; Ortega Montilla, P.; Massonnet, F. Impact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6–LIM3 global ocean–sea ice model. "Geoscientific Model Development (GMD)", 5 Octubre 2020, vol. 13, núm. 10, p. 4773-4787.
dc.identifier.doi10.5194/gmd-13-4773-2020
dc.identifier.issn1991959X
dc.identifier.urihttps://hdl.handle.net/2117/329910
dc.language.isoeng
dc.publisherCopernicus Publications
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/727862/EU/Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE change/APPLICATE
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/641727/EU/PRocess-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment/PRIMAVERA
dc.relation.publisherversionhttps://gmd.copernicus.org/articles/13/4773/2020/
dc.relation.urihttps://gmd.copernicus.org/articles/13/4773/2020/gmd-13-4773-2020-supplement.pdf
dc.rights.accessOpen Access
dc.rights.licensenameAttribution 3.0 Spain
dc.rights.licensenameAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectÀrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia
dc.subject.lcshComputer simulation
dc.subject.lcshSea ice--Arctic regions
dc.subject.lcshArtificial satellites in earth sciences
dc.subject.lemacSimulació per ordinador
dc.subject.lemacSatèl·lits artificials en ciències de la terra
dc.subject.otherSea ice model
dc.subject.otherNEMO3.6–LIM3
dc.subject.otherIce thickness distribution
dc.subject.otherClimate models
dc.subject.otherSatellite observations
dc.subject.otherSimulations
dc.titleImpact of the ice thickness distribution discretization on the sea ice concentration variability in the NEMO3.6–LIM3 global ocean–sea ice model
dc.typeArticle
dspace.entity.typePublication
local.citation.endingPage4787
local.citation.number10
local.citation.publicationNameGeoscientific Model Development (GMD)
local.citation.startingPage4773
local.citation.volume13

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