Articles | Volume 16, issue 1
https://doi.org/10.5194/tc-16-315-2022
https://doi.org/10.5194/tc-16-315-2022
Research article
 | 
25 Jan 2022
Research article |  | 25 Jan 2022

Sources of uncertainty in Greenland surface mass balance in the 21st century

Katharina M. Holube, Tobias Zolles, and Andreas Born

Related authors

The influence of glacial landscape evolution on Scandinavian Ice Sheet dynamics and dimensions
Gustav Jungdal-Olesen, Vivi Kathrine Pedersen, Jane Lund Andersen, and Andreas Born
EGUsphere, https://doi.org/10.5194/egusphere-2023-2207,https://doi.org/10.5194/egusphere-2023-2207, 2023
Short summary
Buoyancy forcing: a key driver of northern North Atlantic sea surface temperature variability across multiple timescales
Bjørg Risebrobakken, Mari F. Jensen, Helene R. Langehaug, Tor Eldevik, Anne Britt Sandø, Camille Li, Andreas Born, Erin Louise McClymont, Ulrich Salzmann, and Stijn De Schepper
Clim. Past, 19, 1101–1123, https://doi.org/10.5194/cp-19-1101-2023,https://doi.org/10.5194/cp-19-1101-2023, 2023
Short summary
How does a change in climate variability impact the Greenland ice-sheet surface mass balance?
Tobias Zolles and Andreas Born
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-379,https://doi.org/10.5194/tc-2021-379, 2022
Revised manuscript under review for TC
Short summary
Modeling the Greenland englacial stratigraphy
Andreas Born and Alexander Robinson
The Cryosphere, 15, 4539–4556, https://doi.org/10.5194/tc-15-4539-2021,https://doi.org/10.5194/tc-15-4539-2021, 2021
Short summary
Sensitivity of the Greenland surface mass and energy balance to uncertainties in key model parameters
Tobias Zolles and Andreas Born
The Cryosphere, 15, 2917–2938, https://doi.org/10.5194/tc-15-2917-2021,https://doi.org/10.5194/tc-15-2917-2021, 2021
Short summary

Related subject area

Discipline: Ice sheets | Subject: Greenland
Seasonal evolution of the supraglacial drainage network at Humboldt Glacier, northern Greenland, between 2016 and 2020
Lauren D. Rawlins, David M. Rippin, Andrew J. Sole, Stephen J. Livingstone, and Kang Yang
The Cryosphere, 17, 4729–4750, https://doi.org/10.5194/tc-17-4729-2023,https://doi.org/10.5194/tc-17-4729-2023, 2023
Short summary
Choice of observation type affects Bayesian calibration of Greenland Ice Sheet model simulations
Denis Felikson, Sophie Nowicki, Isabel Nias, Beata Csatho, Anton Schenk, Michael J. Croteau, and Bryant Loomis
The Cryosphere, 17, 4661–4673, https://doi.org/10.5194/tc-17-4661-2023,https://doi.org/10.5194/tc-17-4661-2023, 2023
Short summary
Effects of extreme melt events on ice flow and sea level rise of the Greenland Ice Sheet
Johanna Beckmann and Ricarda Winkelmann
The Cryosphere, 17, 3083–3099, https://doi.org/10.5194/tc-17-3083-2023,https://doi.org/10.5194/tc-17-3083-2023, 2023
Short summary
Precursor of disintegration of Greenland's largest floating ice tongue
Angelika Humbert, Veit Helm, Niklas Neckel, Ole Zeising, Martin Rückamp, Shfaqat Abbas Khan, Erik Loebel, Jörg Brauchle, Karsten Stebner, Dietmar Gross, Rabea Sondershaus, and Ralf Müller
The Cryosphere, 17, 2851–2870, https://doi.org/10.5194/tc-17-2851-2023,https://doi.org/10.5194/tc-17-2851-2023, 2023
Short summary
Evaluating different geothermal heat flow maps as basal boundary conditions during spin up of the Greenland ice sheet
Tong Zhang, William Colgan, Agnes Wansing, Anja Løkkegaard, Gunter Leguy, William Lipscomb, and Cunde Xiao
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-102,https://doi.org/10.5194/tc-2023-102, 2023
Revised manuscript accepted for TC
Short summary

Cited articles

Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis, NOAA National Geophysical Data Center [data set], https://doi.org/10.7289/V5C8276M, 2009. a, b, c
Aschwanden, A., Fahnestock, M. A., Truffer, M., Brinkerhoff, D. J., Hock, R., Khroulev, C., Mottram, R., and Khan, S. A.: Contribution of the Greenland Ice Sheet to sea level over the next millennium, Sci. Adv., 5, eeav9396, https://doi.org/10.1126/sciadv.aav9396, 2019. a
Beyer, R., Krapp, M., and Manica, A.: An empirical evaluation of bias correction methods for palaeoclimate simulations, Clim. Past, 16, 1493–1508, https://doi.org/10.5194/cp-16-1493-2020, 2020. a
Born, A., Imhof, M. A., and Stocker, T. F.: An efficient surface energy–mass balance model for snow and ice, The Cryosphere, 13, 1529–1546, https://doi.org/10.5194/tc-13-1529-2019, 2019. a, b, c, d, e
Bougamont, M., Bamber, J. L., and Greuell, W.: A surface mass balance model for the Greenland Ice Sheet, J. Geophys. Res.-Earth, 110, F04018, https://doi.org/10.1029/2005JF000348, 2005. a, b
Download
Short summary
We simulated the surface mass balance of the Greenland Ice Sheet in the 21st century by forcing a snow model with the output of many Earth system models and four greenhouse gas emission scenarios. We quantify the contribution to uncertainty in surface mass balance of these two factors and the choice of parameters of the snow model. The results show that the differences between Earth system models are the main source of uncertainty. This effect is localised mostly near the equilibrium line.