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Lookup NU author(s): Professor Rachel Carr
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 Copernicus Publications. All rights reserved.The Greenland Ice Sheet contributed 10.6 mm to global sea level rise between 1992 and 2018, and it is projected to be the largest glacial contributor to sea level rise by 2100. Here we assess the relative importance of two major sources of uncertainty in 21st century ice loss projections: (1) the choice of sliding law and (2) the surface mass balance (SMB) forecast. Specifically, we used the ice flow model Úa to conduct an ensemble of runs for 48 combinations of sliding law and SMB forecast for three major Greenland outlet glaciers (Kangerlussuaq (KG), Humboldt (HU) and Petermann (PG) glaciers) with differing characteristics and evaluated how the sensitivity to these factors varied between the study glaciers. Overall, our results show that SMB forecasts were responsible for 4.45 mm of the variability in sea level rise by 2100 compared with 0.33 mm sea level equivalent (SLE) due to sliding law. HU had the largest absolute contribution to sea level rise and the largest range (2.16-7.96 mm SLE), followed by PG (0.84-5.42 mm SLE), and these glaciers showed similar patterns of ice loss across the SMB forecasts and sliding laws. KG had the lowest range and absolute values (-0.60 to 3.45 mm SLE) of sea level rise, and the magnitude of mass loss by SMB forecast differed markedly between HU and PG. Our results highlight SMB forecasts as a key focus for improving estimates of Greenland's contribution to 21st century sea level rise.
Author(s): Carr JR, Hill EA, Gudmundsson GH
Publication type: Article
Publication status: Published
Journal: Cryosphere
Year: 2024
Volume: 18
Issue: 6
Pages: 2719-2737
Online publication date: 14/06/2024
Acceptance date: 19/03/2024
Date deposited: 04/07/2024
ISSN (print): 1994-0416
ISSN (electronic): 1994-0424
Publisher: Copernicus Publications
URL: https://doi.org/10.5194/tc-18-2719-2024
DOI: 10.5194/tc-18-2719-2024
Data Access Statement: The model runs were conducted using Úa, which is publicly available via GitHub at https://github.com/GHilmarG/UaSource (last access: February 2023; DOI: https://doi.org/10.5281/zenodo.3706624, Gudmundsson, 2024). We used version 2022 for our experiments.
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