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# On the timescales and length scales of the Arctic sea ice thickness anomalies: a study based on 14 reanalyses

Ponsoni, Leandro; Massonnet, François; Fichefet, Thierry; Chevallier, Matthieu; Docquier, David

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<identifier identifierType="URL">https://zenodo.org/record/2571613</identifier>
<creators>
<creator>
<creatorName>Ponsoni, Leandro</creatorName>
<givenName>Leandro</givenName>
<familyName>Ponsoni</familyName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-2218-271X</nameIdentifier>
<affiliation>Georges Lemaître Centre for Earth and Climate Research (TECLIM), Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium</affiliation>
</creator>
<creator>
<creatorName>Massonnet, François</creatorName>
<givenName>François</givenName>
<familyName>Massonnet</familyName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-4697-5781</nameIdentifier>
<affiliation>Georges Lemaître Centre for Earth and Climate Research (TECLIM), Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium</affiliation>
</creator>
<creator>
<creatorName>Fichefet, Thierry</creatorName>
<givenName>Thierry</givenName>
<familyName>Fichefet</familyName>
<affiliation>Georges Lemaître Centre for Earth and Climate Research (TECLIM), Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium</affiliation>
</creator>
<creator>
<creatorName>Chevallier, Matthieu</creatorName>
<givenName>Matthieu</givenName>
<familyName>Chevallier</familyName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-2033-166X</nameIdentifier>
<affiliation>Centre National de Recherches Météorologiques (CNRM), Météo France/CNRS UMR3589, Toulouse, France</affiliation>
</creator>
<creator>
<creatorName>Docquier, David</creatorName>
<givenName>David</givenName>
<familyName>Docquier</familyName>
<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-5720-4253</nameIdentifier>
<affiliation>Georges Lemaître Centre for Earth and Climate Research (TECLIM), Earth and Life Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium</affiliation>
</creator>
</creators>
<titles>
<title>On the timescales and length scales of the Arctic sea ice thickness anomalies: a study based on 14 reanalyses</title>
</titles>
<publisher>Zenodo</publisher>
<publicationYear>2019</publicationYear>
<subjects>
<subject>Arctic sea ice thickness</subject>
<subject>timescale</subject>
<subject>length scale</subject>
<subject>reanalyses</subject>
</subjects>
<dates>
<date dateType="Issued">2019-02-14</date>
</dates>
<language>en</language>
<resourceType resourceTypeGeneral="Text">Journal article</resourceType>
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<alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/2571613</alternateIdentifier>
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<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.5194/tc-13-521-2019</relatedIdentifier>
<relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/applicate</relatedIdentifier>
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<rightsList>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
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<descriptions>
<description descriptionType="Abstract">&lt;p&gt;The ocean&amp;ndash;sea ice reanalyses are one of the main sources of Arctic sea ice thickness data both in terms of spatial and temporal resolution, since observations are still sparse in time and space. In this work, we first aim at comparing how the sea ice thickness from an ensemble of 14 reanalyses compares with different sources of observations, such as moored upward-looking sonars, submarines, airbornes, satellites, and ice boreholes. Second, based on the same reanalyses, we intend to characterize the timescales (persistence) and length scales of sea ice thickness anomalies. We investigate whether data assimilation of sea ice concentration by the reanalyses impacts the realism of sea ice thickness as well as its respective timescales and length scales. The results suggest that reanalyses with sea ice data assimilation do not necessarily perform better in terms of sea ice thickness compared with the reanalyses which do not assimilate sea ice concentration. However, data assimilation has a clear impact on the timescales and length scales: reanalyses built with sea ice data assimilation present shorter timescales and length scales. The mean timescales and length scales for reanalyses with data assimilation vary from 2.5 to 5.0 months and 337.0 to 732.5 km, respectively, while reanalyses with no data assimilation are characterized by values from 4.9 to 7.8 months and 846.7 to 935.7 km, respectively.&lt;/p&gt;</description>
</descriptions>
<fundingReferences>
<fundingReference>
<funderName>European Commission</funderName>
<funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
<awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/641727/">641727</awardNumber>
<awardTitle>PRocess-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment</awardTitle>
</fundingReference>
<fundingReference>
<funderName>European Commission</funderName>
<funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
<awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/727862/">727862</awardNumber>
<awardTitle>Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE change</awardTitle>
</fundingReference>
</fundingReferences>
</resource>

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