{"refrec":{"BRefID":216858,"RR":"<b>Franco, B.; Fettweis, X.; Lang, C.; Erpicum, M.</b> (2012). Impact of spatial resolution on the modelling of the Greenland ice sheet surface mass balance between 1990–2010, using the regional climate model MAR. <i>Cryosphere 6(3)</i>: 695-711. <a href=\"http://dx.doi.org/10.5194/tc-6-695-2012\" target=\"_blank\">http://dx.doi.org/10.5194/tc-6-695-2012</a>","BEntID":208607,"PublicFlag":1,"CheckedFlag":1,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>Cryosphere 6(3)</i>: 695-711. <a href=\"https://dx.doi.org/10.5194/tc-6-695-2012\" target=\"_blank\">https://dx.doi.org/10.5194/tc-6-695-2012</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Franco, B.; Fettweis, X.; Lang, C.; Erpicum, M.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Franco, B. <i>et al.</i>","Englishabstract":"With the aim to force an ice dynamical model, the Greenland ice sheet (GrIS) surface mass balance (SMB) was modelled at different spatial resolutions (15–50 km) for the period 1990–2010, using the regional climate model MAR (Modèle Atmosphérique Régional) forced by the ERA-INTERIM reanalysis. This comparison revealed that (i) the inter-annual variability of the SMB components is consistent within the different spatial resolutions investigated, (ii) the MAR model simulates heavier precipitation on average over the GrIS with decreasing spatial resolution, and (iii) the SMB components (except precipitation) can be derived from a simulation at lower resolution with an “intelligent” interpolation. This interpolation can also be used to approximate the SMB components over another topography/ice sheet mask of the GrIS. These results are important for the forcing of an ice dynamical model needed to enable future projections of the GrIS contribution to sea level rise over the coming centuries.","AbstractOtherLang":null,"BibLvlCode":"AS","StandardTitle":"Impact of spatial resolution on the modelling of the Greenland ice sheet surface mass balance between 1990–2010, using the regional climate model MAR","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2024-12-10 01:33:17.368041","timezone_type":1,"timezone":"+01:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":null,"OtherDescriptors":null,"Notes":null,"AnaPub":2012,"MonPub":null,"DateUpdate":"2018-02-13","DateCreate":"2012-07-18","SecASFANote":null,"ConfID":null,"PeerRev":1,"VlizCoreFlag":1,"WoScode":"WOS:000305831000007","VABBcode":null,"OpenAcc":1,"DOI":"10.5194/tc-6-695-2012"},"refs":null,"anarec":{"AnaID":216858,"PubliDate":2012,"Pagination":"695-711","XtraPublOfAnaID":null,"ISBN":null,"Volume":"6","Issue":"3","BRefMon":null,"BRefMonRR":null,"BRefXtra":null,"BRefXtraRR":null,"SerBRefID":216569,"SerRR":"The Cryosphere. 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