The International Bathymetric Chart of the Arctic Ocean Version 4.0

Martin Jakobsson, Larry A. Mayer, Caroline Bringensparr, Carlos F. Castro, Rezwan Mohammad, Paul Johnson, Tomer Ketter, Daniela Accettella, David Amblas, Lu An, Jan Erik Arndt, Miquel Canals, José Luis Casamor, Nolwenn Chauché, Bernard Coakley, Seth Danielson, Maurizio Demarte, Mary Lynn Dickson, Boris Dorschel, Julian A. DowdeswellSimon Dreutter, Alice C. Fremand, Dana Gallant, John K. Hall, Laura Hehemann, Hanne Hodnesdal, Jongkuk Hong, Roberta Ivaldi, Emily Kane, Ingo Klaucke, Diana W. Krawczyk, Yngve Kristoffersen, Boele R. Kuipers, Romain Millan, Giuseppe Masetti, Mathieu Morlighem, Riko Noormets, Megan M. Prescott, Michele Rebesco, Eric Rignot, Igor Semiletov, Alex J. Tate, Paola Travaglini, Isabella Velicogna, Pauline Weatherall, Wilhelm Weinrebe, Joshua K. Willis, Michael Wood, Yulia Zarayskaya, Tao Zhang, Mark Zimmermann, Karl B. Zinglersen

Research output: Contribution to journalArticleResearchpeer-review

65 Citations (Scopus)

Abstract

Bathymetry (seafloor depth), is a critical parameter providing the geospatial context for a multitude of marine scientific studies. Since 1997, the International Bathymetric Chart of the Arctic Ocean (IBCAO) has been the authoritative source of bathymetry for the Arctic Ocean. IBCAO has merged its efforts with the Nippon Foundation-GEBCO-Seabed 2030 Project, with the goal of mapping all of the oceans by 2030. Here we present the latest version (IBCAO Ver. 4.0), with more than twice the resolution (200 × 200 m versus 500 × 500 m) and with individual depth soundings constraining three times more area of the Arctic Ocean (∼19.8% versus 6.7%), than the previous IBCAO Ver. 3.0 released in 2012. Modern multibeam bathymetry comprises ∼14.3% in Ver. 4.0 compared to ∼5.4% in Ver. 3.0. Thus, the new IBCAO Ver. 4.0 has substantially more seafloor morphological information that offers new insights into a range of submarine features and processes; for example, the improved portrayal of Greenland fjords better serves predictive modelling of the fate of the Greenland Ice Sheet.

Original languageEnglish
Article number176
Number of pages14
JournalScientific data
Volume7
DOIs
Publication statusPublished - 1 Dec 2020

Programme Area

  • Programme Area 5: Nature and Climate

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