Articles | Volume 15, issue 6
https://doi.org/10.5194/tc-15-2917-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-2917-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Jun 2021
Research article |
| 28 Jun 2021
| 28 Jun 2021
Sensitivity of the Greenland surface mass and energy balance to uncertainties in key model parameters
Department of Earth Science, University of Bergen, Bergen, Norway
Bjerknes Centre for Climate Research, Bergen, Norway
Andreas Born
Department of Earth Science, University of Bergen, Bergen, Norway
Bjerknes Centre for Climate Research, Bergen, Norway
Related authors
Tobias Zolles and Andreas Born
The Cryosphere, 18, 4831–4844, https://doi.org/10.5194/tc-18-4831-2024, https://doi.org/10.5194/tc-18-4831-2024, 2024
Short summary
Short summary
The Greenland ice sheet largely depends on the climate state. The uncertainties associated with the year-to-year variability have only a marginal impact on our simulated surface mass budget; this increases our confidence in projections and reconstructions. Basing the simulations on proxies, e.g., temperature, results in overestimates of the surface mass balance, as climatologies lead to small amounts of snowfall every day. This can be reduced by including sub-monthly precipitation variability.
Katharina M. Holube, Tobias Zolles, and Andreas Born
The Cryosphere, 16, 315–331, https://doi.org/10.5194/tc-16-315-2022, https://doi.org/10.5194/tc-16-315-2022, 2022
Short summary
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.
Heiko Goelzer, Petra M. Langebroek, Andreas Born, Stefan Hofer, Konstanze Haubner, Michele Petrini, Gunter Leguy, William H. Lipscomb, and Katherine Thayer-Calder
Geosci. Model Dev., 18, 7853–7867, https://doi.org/10.5194/gmd-18-7853-2025, https://doi.org/10.5194/gmd-18-7853-2025, 2025
Short summary
Short summary
On the backdrop of observed accelerating ice sheet mass loss over the last few decades, there is growing interest in the role of ice sheet changes in global climate projections. In this regard, we have coupled an Earth system model with an ice sheet model and have produced an initial set of climate projections including an interactive coupling with a dynamic Greenland ice sheet.
Robert G. Bingham, Julien A. Bodart, Marie G. P. Cavitte, Ailsa Chung, Rebecca J. Sanderson, Johannes C. R. Sutter, Olaf Eisen, Nanna B. Karlsson, Joseph A. MacGregor, Neil Ross, Duncan A. Young, David W. Ashmore, Andreas Born, Winnie Chu, Xiangbin Cui, Reinhard Drews, Steven Franke, Vikram Goel, John W. Goodge, A. Clara J. Henry, Antoine Hermant, Benjamin H. Hills, Nicholas Holschuh, Michelle R. Koutnik, Gwendolyn J.-M. C. Leysinger Vieli, Emma J. MacKie, Elisa Mantelli, Carlos Martín, Felix S. L. Ng, Falk M. Oraschewski, Felipe Napoleoni, Frédéric Parrenin, Sergey V. Popov, Therese Rieckh, Rebecca Schlegel, Dustin M. Schroeder, Martin J. Siegert, Xueyuan Tang, Thomas O. Teisberg, Kate Winter, Shuai Yan, Harry Davis, Christine F. Dow, Tyler J. Fudge, Tom A. Jordan, Bernd Kulessa, Kenichi Matsuoka, Clara J. Nyqvist, Maryam Rahnemoonfar, Matthew R. Siegfried, Shivangini Singh, Vjeran Višnjević, Rodrigo Zamora, and Alexandra Zuhr
The Cryosphere, 19, 4611–4655, https://doi.org/10.5194/tc-19-4611-2025, https://doi.org/10.5194/tc-19-4611-2025, 2025
Short summary
Short summary
The ice sheets covering Antarctica have built up over millenia through successive snowfall events which become buried and preserved as internal surfaces of equal age detectable with ice-penetrating radar. This paper describes an international initiative working together on these archival data to build a comprehensive 3-D picture of how old the ice is everywhere across Antarctica and how this is being used to reconstruct past and to predict future ice and climate behaviour.
Lise Seland Graff, Jerry Tjiputra, Ada Gjermundsen, Andreas Born, Jens Boldingh Debernard, Heiko Goelzer, Yan-Chun He, Petra Margaretha Langebroek, Aleksi Nummelin, Dirk Olivié, Øyvind Seland, Trude Storelvmo, Mats Bentsen, Chuncheng Guo, Andrea Rosendahl, Dandan Tao, Thomas Toniazzo, Camille Li, Stephen Outten, and Michael Schulz
Earth Syst. Dynam., 16, 1671–1698, https://doi.org/10.5194/esd-16-1671-2025, https://doi.org/10.5194/esd-16-1671-2025, 2025
Short summary
Short summary
The magnitude of future Arctic amplification is highly uncertain. Using the Norwegian Earth System Model, we explore the effect of improving the representation of clouds, ocean eddies, the Greenland ice sheet, sea ice, and ozone on the projected Arctic winter warming in a coordinated experiment set. These improvements all lead to enhanced projected Arctic warming, with the largest changes found in the sea ice retreat regions and the largest uncertainty found on the Atlantic side.
Sina Loriani, Yevgeny Aksenov, David I. Armstrong McKay, Govindasamy Bala, Andreas Born, Cristiano Mazur Chiessi, Henk A. Dijkstra, Jonathan F. Donges, Sybren Drijfhout, Matthew H. England, Alexey V. Fedorov, Laura C. Jackson, Kai Kornhuber, Gabriele Messori, Francesco S. R. Pausata, Stefanie Rynders, Jean-Baptiste Sallée, Bablu Sinha, Steven C. Sherwood, Didier Swingedouw, and Thejna Tharammal
Earth Syst. Dynam., 16, 1611–1653, https://doi.org/10.5194/esd-16-1611-2025, https://doi.org/10.5194/esd-16-1611-2025, 2025
Short summary
Short summary
In this work, we draw on palaeo-records, observations, and modelling studies to review tipping points in the ocean overturning circulations, monsoon systems, and global atmospheric circulations. We find indications for tipping in the ocean overturning circulations and the West African monsoon, with potentially severe impacts on the Earth system and humans. Tipping in the other considered systems is regarded as conceivable but is currently not sufficiently supported by evidence.
Charlotte Rahlves, Heiko Goelzer, Andreas Born, and Petra M. Langebroek
EGUsphere, https://doi.org/10.5194/egusphere-2025-2192, https://doi.org/10.5194/egusphere-2025-2192, 2025
Short summary
Short summary
We present a method to better simulate how Greenland’s ice sheet may change over thousands of years in response to climate change. Using a stand-alone ice sheet model, we adjust snowfall and melting patterns based on changes in the ice sheet’s shape. This approach avoids complex coupled models and enables faster testing of many future scenarios to understand the long-term stability of Greenland’s ice.
Sjur Barndon, Robert Law, Andreas Born, Thomas Chudley, and Stefanie Brechtelsbauer
EGUsphere, https://doi.org/10.5194/egusphere-2025-1304, https://doi.org/10.5194/egusphere-2025-1304, 2025
Short summary
Short summary
By simulating a section of the Scandinavian Ice Sheet over a deep fjord, we aim to understand the behaviour of ice sheets over rough landscapes. For perpendicular flow, we find reduced speed within the fjord and reverse flow at its base. Comparing real and smoothed topography shows that low-resolution models fail to capture these effects. Our findings have implications for Greenland ice sheet models, as commonly used bedrock resolutions likely overlook the influence of similar rough landscapes.
Robert Law, Andreas Born, Philipp Voigt, Joseph A. MacGregor, and Claire Marie Guimond
EGUsphere, https://doi.org/10.48550/arXiv.2411.18779, https://doi.org/10.48550/arXiv.2411.18779, 2025
Short summary
Short summary
Convection has been previously, yet contentiously, suggested for ice sheets, but never before comprehensively explored using numerical models. We use mantle dynamics code to test the hypothesis that convection gives rise to enigmatic plume-like features observed in radio-stratigraphy observations of the Greenland Ice Sheet. Our results provide very good agreement with field observations, but could imply that ice in northern Greenland is significantly softer than commonly thought.
Charlotte Rahlves, Heiko Goelzer, Andreas Born, and Petra M. Langebroek
The Cryosphere, 19, 1205–1220, https://doi.org/10.5194/tc-19-1205-2025, https://doi.org/10.5194/tc-19-1205-2025, 2025
Short summary
Short summary
Mass loss from the Greenland ice sheet significantly contributes to rising sea levels, threatening coastal communities globally. To improve future sea-level projections, we simulated ice sheet behavior until 2100, initializing the model with observed geometry and using various climate models. Predictions indicate a sea-level rise of 32 to 228 mm by 2100, with climate model uncertainty being the main source of variability in projections.
Konstanze Haubner, Heiko Goelzer, and Andreas Born
EGUsphere, https://doi.org/10.5194/egusphere-2024-3785, https://doi.org/10.5194/egusphere-2024-3785, 2025
Short summary
Short summary
We add a new dynamic component – an ice sheet model simulating the Greenland ice sheet – to an Earth system model that already captures the global climate evolution including ocean, atmosphere, land and sea ice. Under a strong warming scenario, the global warming of 10 °C over 250 yrs is dominating the climate evolution. Changes from the ice-climate interaction are mainly local yet impacting the evolution of the Greenland ice sheet. Hence, ice-climate feedbacks should be considered beyond 2100.
Thi-Khanh-Dieu Hoang, Aurélien Quiquet, Christophe Dumas, Andreas Born, and Didier M. Roche
Clim. Past, 21, 27–51, https://doi.org/10.5194/cp-21-27-2025, https://doi.org/10.5194/cp-21-27-2025, 2025
Short summary
Short summary
To improve the simulation of surface mass balance (SMB) that influences the advance–retreat of ice sheets, we run a snow model, the BErgen Snow SImulator (BESSI), with transient climate forcing obtained from an Earth system model, iLOVECLIM, over Greenland and Antarctica during the Last Interglacial (LIG; 130–116 ka). Compared to the simple existing SMB scheme of iLOVECLIM, BESSI gives more details about SMB processes with higher physics constraints while maintaining a low computational cost.
Tobias Zolles and Andreas Born
The Cryosphere, 18, 4831–4844, https://doi.org/10.5194/tc-18-4831-2024, https://doi.org/10.5194/tc-18-4831-2024, 2024
Short summary
Short summary
The Greenland ice sheet largely depends on the climate state. The uncertainties associated with the year-to-year variability have only a marginal impact on our simulated surface mass budget; this increases our confidence in projections and reconstructions. Basing the simulations on proxies, e.g., temperature, results in overestimates of the surface mass balance, as climatologies lead to small amounts of snowfall every day. This can be reduced by including sub-monthly precipitation variability.
Therese Rieckh, Andreas Born, Alexander Robinson, Robert Law, and Gerrit Gülle
Geosci. Model Dev., 17, 6987–7000, https://doi.org/10.5194/gmd-17-6987-2024, https://doi.org/10.5194/gmd-17-6987-2024, 2024
Short summary
Short summary
We present the open-source model ELSA, which simulates the internal age structure of large ice sheets. It creates layers of snow accumulation at fixed times during the simulation, which are used to model the internal stratification of the ice sheet. Together with reconstructed isochrones from radiostratigraphy data, ELSA can be used to assess ice sheet models and to improve their parameterization. ELSA can be used coupled to an ice sheet model or forced with its output.
Gustav Jungdal-Olesen, Jane Lund Andersen, Andreas Born, and Vivi Kathrine Pedersen
The Cryosphere, 18, 1517–1532, https://doi.org/10.5194/tc-18-1517-2024, https://doi.org/10.5194/tc-18-1517-2024, 2024
Short summary
Short summary
We explore how the shape of the land and underwater features in Scandinavia affected the former Scandinavian ice sheet over time. Using a computer model, we simulate how the ice sheet evolved during different stages of landscape development. We discovered that early glaciations were limited in size by underwater landforms, but as these changed, the ice sheet expanded more rapidly. Our findings highlight the importance of considering landscape changes when studying ice-sheet history.
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
Short summary
In the observational period, spatially coherent sea surface temperatures characterize the northern North Atlantic at multidecadal timescales. We show that spatially non-coherent temperature patterns are seen both in further projections and a past warm climate period with a CO2 level comparable to the future low-emission scenario. Buoyancy forcing is shown to be important for northern North Atlantic temperature patterns.
Katharina M. Holube, Tobias Zolles, and Andreas Born
The Cryosphere, 16, 315–331, https://doi.org/10.5194/tc-16-315-2022, https://doi.org/10.5194/tc-16-315-2022, 2022
Short summary
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.
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
Short summary
Ice penetrating radar reflections from the Greenland ice sheet are the best available record of past accumulation and how these layers have been deformed over time by the flow of ice. Direct simulations of this archive hold great promise for improving our models and for uncovering details of ice sheet dynamics that neither models nor data could achieve alone. We present the first three-dimensional ice sheet model that explicitly simulates individual layers of accumulation and how they deform.
Cited articles
Amante, C. and Eakins, B.: ETOPO1 1 Arc-Minute Global Relief Model:
Procedures, Data Sources and Analysis [data], https://doi.org/10.7289/V5C8276M, 2009. a
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, Science Advances, 5, 12 pp.,
https://doi.org/10.1126/sciadv.aav9396, 2019. a, b
Beven, K.: Changing ideas in hydrology – The case of physically-based models,
J. Hydrol., 105, 157–172, https://doi.org/10.1016/0022-1694(89)90101-7,
1989. a
Bintanja, R., Van de Wal, R., and Oerlemans, J.: Global ice volume variations
through the last glacial cycle simulated by a 3-D ice-dynamical model,
Quatern. Int., 95, 11–23, https://doi.org/10.1016/S1040-6182(02)00023-X,
2002. a
Box, J. E. and Steffen, K.: Sublimation on the Greenland ice sheet from
automated station observations, J. Geophys. Res., 106,
965–981, https://doi.org/10.1029/2001JD900219, 2001. a, b
Box, J. E., Bromwich, D. H., and Bai, L. S.: Greenland ice sheet surface mass
balance 1991–2000: Application of Polar MM5 mesoscale model and in situ
data, J. Geophys. Res.-Atmos., 109, 1–21,
https://doi.org/10.1029/2003JD004451, 2004. a, b
Brady, E. C., Otto-Bliesner, B. L., Kay, J. E., and Rosenbloom, N.: Sensitivity
to glacial forcing in the CCSM4, J. Climate, 26, 1901–1925,
https://doi.org/10.1175/JCLI-D-11-00416.1, 2013. a
Braithwaite, R. J.: Calculation of sensible-heat flux over a melting ice
surface using simple climate data and daily measurements of ablation, Ann.
Glaciol., 50, 9–15, https://doi.org/10.3189/172756409787769726, 2009. a, b, c
Bulthuis, K., Arnst, M., Sun, S., and Pattyn, F.: Uncertainty quantification of the multi-centennial response of the Antarctic ice sheet to climate change, The Cryosphere, 13, 1349–1380, https://doi.org/10.5194/tc-13-1349-2019, 2019. a
Busetto, M., Lanconelli, C., Mazzola, M., Lupi, A., Petkov, B., Vitale, V.,
Tomasi, C., Grigioni, P., and Pellegrini, A.: Parameterization of clear sky
effective emissivity under surface-based temperature inversion at Dome C and
South Pole, Antarctica, Antarct. Sci., 25, 697–710,
https://doi.org/10.1017/S0954102013000096, 2013. a
Cullen, N. J., Mölg, T., Conway, J. P., and Steffen, K.: Assessing the
role of sublimation in the dry snow zone of the Greenland ice sheet in a
warming world, J. Geophys. Res.-Atmos., 119, 1–15,
https://doi.org/10.1002/2014JD021557, 2014. a, b
Fettweis, X.: Reconstruction of the 1979–2006 Greenland ice sheet surface mass balance using the regional climate model MAR, The Cryosphere, 1, 21–40, https://doi.org/10.5194/tc-1-21-2007, 2007. a
Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C. J., Born, A., Box, J. E., Delhasse, A., Fujita, K., Gierz, P., Goelzer, H., Hanna, E., Hashimoto, A., Huybrechts, P., Kapsch, M.-L., King, M. D., Kittel, C., Lang, C., Langen, P. L., Lenaerts, J. T. M., Liston, G. E., Lohmann, G., Mernild, S. H., Mikolajewicz, U., Modali, K., Mottram, R. H., Niwano, M., Noël, B., Ryan, J. C., Smith, A., Streffing, J., Tedesco, M., van de Berg, W. J., van den Broeke, M., van de Wal, R. S. W., van Kampenhout, L., Wilton, D., Wouters, B., Ziemen, F., and Zolles, T.: GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet, The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, 2020. a
Gallet, J.-C., Domine, F., Savarino, J., Dumont, M., and Brun, E.: The growth of sublimation crystals and surface hoar on the Antarctic plateau, The Cryosphere, 8, 1205–1215, https://doi.org/10.5194/tc-8-1205-2014, 2014. a
Greuell, W. and Konzelmann, T.: Numerical modelling of the energy balance and
the englacial temperature of the Greenland Ice Sheet. Calculations for the
ETH-Camp location (West Greenland, 1155 m a.s.l.), Global Planet.
Change, 9, 91–114, https://doi.org/10.1016/0921-8181(94)90010-8, 1994. a
Greuell, W. and Smeets, P.: Variations with elevation in the surface energy
balance on the Pasterze (Austria), J. Geophys. Res., 106,
31717, https://doi.org/10.1029/2001JD900127, 2001. a
Hofer, S., Tedstone, A. J., Fettweis, X., and Bamber, J. L.: Decreasing cloud
cover drives the recent mass loss on the Greenland Ice Sheet, Science
Advances, 3, e1700584, https://doi.org/10.1126/sciadv.1700584, 2017. a
Klok, E. J. and Oerlemans, J.: Modelled climate sensitivity of the mass
balance of Morteratschgletscher and its dependence on albedo
parameterization, Int. J. Climatol., 24, 231–245,
https://doi.org/10.1002/joc.994, 2004. a
Krapp, M., Robinson, A., and Ganopolski, A.: SEMIC: an efficient surface energy and mass balance model applied to the Greenland ice sheet, The Cryosphere, 11, 1519–1535, https://doi.org/10.5194/tc-11-1519-2017, 2017. a
Krebs-Kanzow, U., Gierz, P., and Lohmann, G.: Brief communication: An ice surface melt scheme including the diurnal cycle of solar radiation, The Cryosphere, 12, 3923–3930, https://doi.org/10.5194/tc-12-3923-2018, 2018. a
Lehning, M., Bartelt, P., Brown, B., and Fierz, C.: A physical SNOWPACK model
for the Swiss avalanche warning: Part III: Meteorological forcing, thin layer
formation and evaluation, Cold Reg. Sci. Technol., 35, 169–184,
https://doi.org/10.1016/S0165-232X(02)00072-1, 2002. a
Listion, G. E. and Elder, K.: A Meteorological Distribution System for
High-Resolution Terrestrial Modeling (MicroMet), J.
Hydrometeorol., 7, 217–234, https://doi.org/10.1175/JHM486.1, 2006. a
Noël, B., van de Berg, W. J., van Wessem, J. M., van Meijgaard, E., van As, D., Lenaerts, J. T. M., Lhermitte, S., Kuipers Munneke, P., Smeets, C. J. P. P., van Ulft, L. H., van de Wal, R. S. W., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016), The Cryosphere, 12, 811–831, https://doi.org/10.5194/tc-12-811-2018, 2018. a, b
Ohmura, A.: Physical Basis for the Temperature-Based Melt-Index Method,
J. Appl. Meteorol., 40, 753–761,
https://doi.org/10.1175/1520-0450(2001)040<0753:PBFTTB>2.0.CO;2, 2001. a
Peltier, W., Argus, D., and Drummond, R.: Space geodesy constrains ice-age
terminal deglaciation: The global ICE-6G_C (VM5a) model., J. Geophys. Res.-Sol. Ea., 120, 450–487, https://doi.org/10.1002/2014JB011176, 2015. a
Plach, A., Nisancioglu, K. H., Langebroek, P. M., Born, A., and Le clec'h, S.: Eemian Greenland ice sheet simulated with a higher-order model shows strong sensitivity to surface mass balance forcing, The Cryosphere, 13, 2133–2148, https://doi.org/10.5194/tc-13-2133-2019, 2019. a, b
Robinson, A., Calov, R., and Ganopolski, A.: Greenland ice sheet model parameters constrained using simulations of the Eemian Interglacial, Clim. Past, 7, 381–396, https://doi.org/10.5194/cp-7-381-2011, 2011. a
Rolstad, C. and Oerlemans, J.: The residual method for determination of the
turbulent exchange coefficient applied to automatic weather station data from
Iceland, Switzerland and West Greenland, Ann. Glaciol., 42, 367–372,
https://doi.org/10.3189/172756405781813041, 2005. a, b, c, d
Saltelli, A., Campolongo, F., and Tarantola, S.: Sensitivity Anaysis as an
Ingredient of Modeling, Stat. Sci., 15, 377–395,
https://doi.org/10.1214/ss/1009213004, 2000. a, b
Saltelli, A., Ratto, M., Tarantola, S., and Campolongo, F.: Sensitivity
analysis practices: Strategies for model-based inference, Reliab.
Eng. Syst. Safe., 91, 1109–1125,
https://doi.org/10.1016/j.ress.2005.11.014, 2006. a, b
Saltelli, A., Annoni, P., Azzini, I., Campolongo, F., Ratto, M., and Tarantola,
S.: Variance based sensitivity analysis of model output. Design and
estimator for the total sensitivity index, Comput. Phys. Commun.,
181, 259–270, https://doi.org/10.1016/j.cpc.2009.09.018, 2010. a, b, c, d
Sauter, T. and Obleitner, F.: Assessing the uncertainty of glacier mass-balance simulations in the European Arctic based on variance decomposition, Geosci. Model Dev., 8, 3911–3928, https://doi.org/10.5194/gmd-8-3911-2015, 2015. a, b
Sobol, I., Tarantola, S., Gatelli, D., Kucherenko, S., and Mauntz, W.:
Estimating the approximation error when fixing unessential factors in global
sensitivity analysis, Reliab. Eng. Syst. Safe., 92, 957–960, https://doi.org/10.1016/j.ress.2006.07.001, 2007. a, b, c, d
Uppala, S. M., Healy, S. B., Balmaseda, M. A., de Rosnay, P., Isaksen, L.,
van de Berg, L., Geer, A. J., McNally, A. P., Matricardi, M., Haimberger, L.,
Dee, D. P., Dragani, R., Bormann, N., Hersbach, H., Vitart, F., Kobayashi,
S., Andrae, U., Beljaars, A. C. M., Poli, P., Monge-Sanz, B. M., Peubey, C.,
Thépaut, J.-N., Delsol, C., Hólm, E. V., Simmons, A. J.,
Köhler, M., Bechtold, P., Berrisford, P., Balsamo, G., Park, B.-K.,
Fuentes, M., Bidlot, J., Bauer, P., Tavolato, C., Kållberg, P., and
Morcrette, J.-J.: The ERA-Interim reanalysis: configuration and performance
of the data assimilation system, Q. J. Roy.
Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
van de Berg, W. J., van den Broeke, M., Ettema, J., van Meijgaard, E., and
Kaspar, F.: Significant contribution of insolation to Eemian melting of the
Greenland ice sheet, Nat. Geosci., 4, 679–683, https://doi.org/10.1038/ngeo1245,
2011. a
Van Den Berg, J., van de Wal, R., and Oerlemans, H.: A mass balance model for
the Eurasian Ice Sheet for the last 120,000 years, Global Planet.
Change, 61, 194–208, https://doi.org/10.1016/j.gloplacha.2007.08.015, 2008. a
van den Broeke, M., Smeets, P., Ettema, J., van der Veen, C., van de Wal, R., and Oerlemans, J.: Partitioning of melt energy and meltwater fluxes in the ablation zone of the west Greenland ice sheet, The Cryosphere, 2, 179–189, https://doi.org/10.5194/tc-2-179-2008, 2008. a
Van Tricht, K., Lhermitte, S., Lenaerts, J. T., Gorodetskaya, I. V.,
L'Ecuyer, T. S., Noël, B., van den Broeke, M. R., Turner, D. D., and
van Lipzig, N. P.: Clouds enhance Greenland ice sheet meltwater runoff,
Nat. Commun., 7, 10266, https://doi.org/10.1038/ncomms10266, 2016. a
van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E., Amory, C., Birnbaum, G., Jakobs, C. L., Krüger, K., Lenaerts, J. T. M., Lhermitte, S., Ligtenberg, S. R. M., Medley, B., Reijmer, C. H., van Tricht, K., Trusel, L. D., van Ulft, L. H., Wouters, B., Wuite, J., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016), The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, 2018. a
Zemp, M., Huss, M., Thibert, E., Eckert, N., McNabb, R., Huber, J., Barandun,
M., Machguth, H., Nussbaumer, S., Gärtner-Roer, I., Thomson, L., Paul, F., Maussion, F., Kutuzov, S., and Cogley, J. G.: Global
glacier mass changes and their contributions to sea-level rise from 1961 to
2016, Nature, 568, 382–386, https://doi.org/10.1038/s41586-019-1071-0,
2019. a
Zolles, T. and Born, A.: Sensitivity of the Greenland surface mass and energy balance to uncertainties in key model parameters: Supplement and Model code, Zenodo [code], https://doi.org/10.5281/zenodo.4310370, 2020.
a
Zolles, T., Maussion, F., Galos, S. P., Gurgiser, W., and Nicholson, L.: Robust uncertainty assessment of the spatio-temporal transferability of glacier mass and energy balance models, The Cryosphere, 13, 469–489, https://doi.org/10.5194/tc-13-469-2019, 2019. a, b, c
Short summary
We investigate the sensitivity of a glacier surface mass and the energy balance model of the Greenland ice sheet for the cold period of the Last Glacial Maximum (LGM) and the present-day climate. The results show that the model sensitivity changes with climate. While for present-day simulations inclusions of sublimation and hoar formation are of minor importance, they cannot be neglected during the LGM. To simulate the surface mass balance over long timescales, a water vapor scheme is necessary.
We investigate the sensitivity of a glacier surface mass and the energy balance model of the...
