Greenland mass trends from airborne and satellite altimetry during 2011–2020

We use satellite and airborne altimetry to estimate annual mass changes of the Greenland Ice Sheet. We estimate ice loss corresponding to a sea-level rise of 6.9±0.4 millimeters from April 2011 to April 2020, with the highest annual ice loss rate of 1.4 mm/yr sea-level equivalent from April 2019 to...

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Bibliographic Details
Main Authors: Khan, Shfaqat Abbas, Bamber, Jonathan L., Rignot, Eric, Helm, Veit, Aschwanden, Andy, Holland, David M., van den Broeke, Michiel R., King, Michalea, Noël, Brice, Truffer, Martin, Humbert, Angelika, Colgan, William, Vijay, Saurabh, Kuipers Munneke, Peter
Format: Other/Unknown Material
Language:unknown
Published: Zenodo 2022
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Online Access:https://doi.org/10.5061/dryad.h70rxwdj5
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Summary:We use satellite and airborne altimetry to estimate annual mass changes of the Greenland Ice Sheet. We estimate ice loss corresponding to a sea-level rise of 6.9±0.4 millimeters from April 2011 to April 2020, with the highest annual ice loss rate of 1.4 mm/yr sea-level equivalent from April 2019 to April 2020 . On a regional scale, our annual mass loss timeseries reveals 10-15 m/yr dynamic thickening at the terminus of Jakobshavn Isbræ from April 2016 to April 2018, followed by a return to dynamic thinning. We observe contrasting patterns of mass loss acceleration in different basins across the ice sheet. Our gridded satellite altimetry data and surface mass balance (SMB), along with corrections due to firn compaction are available for download. Here, we provide: (1) Annual (April to April) elevation change rates of the Greenland Ice Sheet from April 2011 to April 2020 from CryoSat-2, ICESat-2 and NASA's ATM flights. 1x1 km grid. (2) Annual (April to April) elevation change rates due to SMB anomalies. 1x1 km grid. (3) Ice-sheet wide annual corrections due to firn compaction. Funding provided by: Danmarks Frie Forskningsfond Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100004836 Award Number: 1026-00085B Funding provided by: H2020 European Research Council Award Number: 694188 (GlobalMass)