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dc.date.accessioned2018-09-04T10:33:37Z
dc.date.available2018-09-04T10:33:37Z
dc.date.created2017-10-18T15:11:21Z
dc.date.issued2017
dc.identifier.citationFarinotti, Daniel Brinkerhoff, Douglas J. Clarke, Garry K.C. Fürst, Johannes J. Frey, Holger Gantayat, Prateek Gillet-Chaulet, Fabien Girard, Claire Huss, Matthias Leclercq, Paul Willem Linsbauer, Andreas Machguth, Horst Martin, Carlos Maussion, Fabien Morlighem, Mathieu Mosbeux, Cyrille Pandit, Ankur Portmann, Andrea Rabatel, Antoine Ramsankaran, Raaj A.A.J. Reerink, Thomas J. Sanchez, Olivier Stentoft, Peter A. Singh Kumari, Sangita van Pelt, Ward J.J. Anderson, Brian Benham, Toby Binder, Daniel Dowdeswell, Julian A. Fischer, Andrea Helfricht, Kay Kutuzov, Stanislav Lavrentiev, Ivan McNabb, Robert Whitfield Gudmundsson, G. Hilmar Li, Huilin Andreassen, Liss Marie . How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment. The Cryosphere. 2017, 11(2), 949-970
dc.identifier.urihttp://hdl.handle.net/10852/64100
dc.description.abstractKnowledge of the ice thickness distribution of glaciers and ice caps is an important prerequisite for many glaciological and hydrological investigations. A wealth of approaches has recently been presented for inferring ice thickness from characteristics of the surface. With the Ice Thickness Models Intercomparison eXperiment (ITMIX) we performed the first coordinated assessment quantifying individual model performance. A set of 17 different models showed that individual ice thickness estimates can differ considerably – locally by a spread comparable to the observed thickness. Averaging the results of multiple models, however, significantly improved the results: on average over the 21 considered test cases, comparison against direct ice thickness measurements revealed deviations on the order of 10 ± 24 % of the mean ice thickness (1σ estimate). Models relying on multiple data sets – such as surface ice velocity fields, surface mass balance, or rates of ice thickness change – showed high sensitivity to input data quality. Together with the requirement of being able to handle large regions in an automated fashion, the capacity of better accounting for uncertainties in the input data will be a key for an improved next generation of ice thickness estimation approaches.en_US
dc.languageEN
dc.publisherNational Snow and Ice Data Center
dc.rightsAttribution 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/
dc.titleHow accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperimenten_US
dc.typeJournal articleen_US
dc.creator.authorFarinotti, Daniel
dc.creator.authorBrinkerhoff, Douglas J.
dc.creator.authorClarke, Garry K.C.
dc.creator.authorFürst, Johannes J.
dc.creator.authorFrey, Holger
dc.creator.authorGantayat, Prateek
dc.creator.authorGillet-Chaulet, Fabien
dc.creator.authorGirard, Claire
dc.creator.authorHuss, Matthias
dc.creator.authorLeclercq, Paul Willem
dc.creator.authorLinsbauer, Andreas
dc.creator.authorMachguth, Horst
dc.creator.authorMartin, Carlos
dc.creator.authorMaussion, Fabien
dc.creator.authorMorlighem, Mathieu
dc.creator.authorMosbeux, Cyrille
dc.creator.authorPandit, Ankur
dc.creator.authorPortmann, Andrea
dc.creator.authorRabatel, Antoine
dc.creator.authorRamsankaran, Raaj A.A.J.
dc.creator.authorReerink, Thomas J.
dc.creator.authorSanchez, Olivier
dc.creator.authorStentoft, Peter A.
dc.creator.authorSingh Kumari, Sangita
dc.creator.authorvan Pelt, Ward J.J.
dc.creator.authorAnderson, Brian
dc.creator.authorBenham, Toby
dc.creator.authorBinder, Daniel
dc.creator.authorDowdeswell, Julian A.
dc.creator.authorFischer, Andrea
dc.creator.authorHelfricht, Kay
dc.creator.authorKutuzov, Stanislav
dc.creator.authorLavrentiev, Ivan
dc.creator.authorMcNabb, Robert Whitfield
dc.creator.authorGudmundsson, G. Hilmar
dc.creator.authorLi, Huilin
dc.creator.authorAndreassen, Liss Marie
cristin.unitcode185,15,22,0
cristin.unitnameInstitutt for geofag
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.cristin1505653
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=The Cryosphere&rft.volume=11&rft.spage=949&rft.date=2017
dc.identifier.jtitleThe Cryosphere
dc.identifier.volume11
dc.identifier.issue2
dc.identifier.startpage949
dc.identifier.endpage970
dc.identifier.doihttp://dx.doi.org/10.5194/tc-11-949-2017
dc.identifier.urnURN:NBN:no-66643
dc.type.documentTidsskriftartikkelen_US
dc.type.peerreviewedPeer reviewed
dc.source.issn1994-0416
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/64100/2/tc-11-949-2017.pdf
dc.type.versionPublishedVersion


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