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dc.contributor.authorKimmritz, Madlen
dc.contributor.authorCounillon, Francois
dc.contributor.authorSmedsrud, Lars H.
dc.contributor.authorBethke, Ingo
dc.contributor.authorKeenlyside, Noel
dc.contributor.authorOgawa, Fumiaki
dc.contributor.authorWang, Yiguo
dc.PublishedKimmritz M, Counillon F, Smedsrud LH, Bethke I, Keenlyside N, Ogawa F, Wang Y. Impact of ocean and sea ice initialisation on seasonal prediction skill in the Arctic. Journal of Advances in Modeling Earth Systems. 2019;11:4147–4166eng
dc.description.abstractThere is a growing demand for skillful prediction systems in the Arctic. Using the Norwegian Climate Prediction Model (NorCPM) that combines the fully-coupled Norwegian Earth System Model and the Ensemble Kalman filter, we present a system that performs both, weakly-coupled data assimilation (wCDA) when assimilating ocean hydrogaphy (by updating the ocean alone) and strongly-coupled data assimilation (sCDA) when assimilating sea ice concentration (SIC) (by jointly updating the sea ice and ocean). We assess the seasonal prediction skill of this version of NorCPM, the first climate prediction system using sCDA, by performing retrospective predictions (hindcasts) for the period 1985 to 2010. To better understand origins of the prediction skill of Arctic sea ice, we compare this version with a version that solely performs wCDA of ocean hydrography. The reanalysis that assimilates just ocean data, exhibits a skillful hydrography in the upper Arctic ocean, and features an improved sea ice state, such as improved summer SIC in the Barents Sea, or reduced biases in sea ice thickness. Skillful prediction of SIE up to 10-12 lead months are only found during winter in regions of a relatively deep ocean mixed layer outside the Arctic basin. Additional DA of SIC data notably further corrects the initial sea ice state, confirming the applicability of the results of Kimmritz et al. (2018) in a historical setting. The resulting prediction skill of SIE is widely enhanced compared to predictions initialised through wCDA of only ocean data. Particularly high skill is found for July-initialised autumn SIE predictions.en_US
dc.publisherAmerican Geophysical Unionen_US
dc.rightsAttribution CC BYeng
dc.titleImpact of ocean and sea ice initialisation on seasonal prediction skill in the Arcticen_US
dc.typePeer reviewed
dc.typeJournal article
dc.rights.holderCopyright 2019 The Authorsen_US
dc.source.journalJournal of Advances in Modeling Earth Systems
dc.relation.projectNotur/NorStore: ns9039k
dc.relation.projectNotur/NorStore: nn9602k
dc.relation.projectNordforsk: 81512
dc.relation.projectNordforsk: 76654
dc.relation.projectNotur/NorStore: ns9602k
dc.relation.projectNorges forskningsråd: 275268
dc.relation.projectNotur/NorStore: nn9039k
dc.relation.projectNorges forskningsråd: 270733
dc.relation.projectTrond Mohn stiftelse: BFS2018TMT01
dc.relation.projectEC/H2020: 727890
dc.relation.projectNotur/NorStore: NS9039K
dc.relation.projectNotur/NorStore: NN9602K
dc.relation.projectNotur/NorStore: NS9602K
dc.relation.projectNotur/NorStore: NN9039K

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