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The Antarctic ice sheet's contribution to global sea level rise over the 21st century is of primary societal importance and remains largely uncertain as of yet. In particular, in the recent literature, the contribution of the Antarctic ice sheet by 2100 can be negative (sea level fall) by a few centimetres or positive (sea level rise), with some estimates above 1 m. The Ice Sheet Model Intercomparison Project for the Coupled Model Intercomparison Project – phase 6 (ISMIP6) aimed at reducing the uncertainties in the fate of the ice sheets in the future by gathering various ice sheet models in a common framework. Here, we present the GRISLI-LSCE (Grenoble Ice Sheet and Land Ice model of the Laboratoire des Sciences du Climat et de l'Environnement) contribution to ISMIP6-Antarctica. We show that our model is strongly sensitive to the climate forcing used, with a contribution of the Antarctic ice sheet to global sea level rise by 2100 that ranges from -50 to +150 mm sea level equivalent (SLE). Future oceanic warming leads to a decrease in thickness of the ice shelves, resulting in grounding-line retreat, while increased surface mass balance partially mitigates or even overcompensates the dynamic ice sheet contribution to global sea level rise. Most of the ice sheet changes over the next century are dampened under low-greenhouse-gas-emission scenarios. Uncertainties related to sub-ice-shelf melt rates induce large differences in simulated grounding-line retreat, confirming the importance of this process and its representation in ice sheet models for projections of the Antarctic ice sheet's evolution. [ABSTRACT FROM AUTHOR]

Polar amplification will result in amplified temperature changes in the Arctic with respect to the rest of the globe, making the Greenland ice sheet particularly vulnerable to global warming. While the ice sheet has been showing an increased mass loss in the past decades, its contribution to global sea level rise in the future is of primary importance since it is at present the largest single-source contribution after the thermosteric contribution. The question of the fate of the Greenland and Antarctic ice sheets for the next century has recently gathered various ice sheet models in a common framework within the Ice Sheet Model Intercomparison Project for the Coupled Model Intercomparison Project – phase 6 (ISMIP6). While in a companion paper we present the GRISLI-LSCE (Grenoble Ice Sheet and Land Ice model of the Laboratoire des Sciences du Climat et de l'Environnement) contribution to ISMIP6-Antarctica, we present here the GRISLI-LSCE contribution to ISMIP6-Greenland. We show an important spread in the simulated Greenland ice loss in the future depending on the climate forcing used. The contribution of the ice sheet to global sea level rise in 2100 can thus be from as low as 20 mm sea level equivalent (SLE) to as high as 160 mm SLE. Amongst the models tested in ISMIP6, the Coupled Model Intercomparison Project – phase 6 (CMIP6) models produce larger ice sheet retreat than their CMIP5 counterparts. Low-emission scenarios in the future drastically reduce the ice mass loss. The oceanic forcing contributes to about 10 mm SLE in 2100 in our simulations. In addition, the dynamical contribution to ice thickness change is small compared to the impact of surface mass balance. This suggests that mass loss is mostly driven by atmospheric warming and associated ablation at the ice sheet margin. With additional sensitivity experiments we also show that the spread in mass loss is only weakly affected by the choice of the ice sheet model mechanical parameters. [ABSTRACT FROM AUTHOR]

In the context of global warming, growing attention is paid to the evolution of the Greenland ice sheet (GrIS) and its contribution to sea-level rise at the centennial timescale. Atmosphere–GrIS interactions, such as the temperature–elevation and the albedo feedbacks, have the potential to modify the surface energy balance and thus to impact the GrIS surface mass balance (SMB). In turn, changes in the geometrical features of the ice sheet may alter both the climate and the ice dynamics governing the ice sheet evolution. However, changes in ice sheet geometry are generally not explicitly accounted for when simulating atmospheric changes over the Greenland ice sheet in the future. To account for ice sheet–climate interactions, we developed the first two-way synchronously coupled model between a regional atmospheric model (MAR) and a 3-D ice sheet model (GRISLI). Using this novel model, we simulate the ice sheet evolution from 2000 to 2150 under a prolonged representative concentration pathway scenario, RCP8.5. Changes in surface elevation and ice sheet extent simulated by GRISLI have a direct impact on the climate simulated by MAR. They are fed to MAR from 2020 onwards, i.e. when changes in SMB produce significant topography changes in GRISLI. We further assess the importance of the atmosphere–ice sheet feedbacks through the comparison of the two-way coupled experiment with two other simulations based on simpler coupling strategies: (i) a one-way coupling with no consideration of any change in ice sheet geometry; (ii) an alternative one-way coupling in which the elevation change feedbacks are parameterized in the ice sheet model (from 2020 onwards) without taking into account the changes in ice sheet topography in the atmospheric model. The two-way coupled experiment simulates an important increase in surface melt below 2000 m of elevation, resulting in an important SMB reduction in 2150 and a shift of the equilibrium line towards elevations as high as 2500 m, despite a slight increase in SMB over the central plateau due to enhanced snowfall. In relation with these SMB changes, modifications of ice sheet geometry favour ice flux convergence towards the margins, with an increase in ice velocities in the GrIS interior due to increased surface slopes and a decrease in ice velocities at the margins due to decreasing ice thickness. This convergence counteracts the SMB signal in these areas. In the two-way coupling, the SMB is also influenced by changes in fine-scale atmospheric dynamical processes, such as the increase in katabatic winds from central to marginal regions induced by increased surface slopes. Altogether, the GrIS contribution to sea-level rise, inferred from variations in ice volume above floatation, is equal to 20.4 cm in 2150. The comparison between the coupled and the two uncoupled experiments suggests that the effect of the different feedbacks is amplified over time with the most important feedbacks being the SMB–elevation feedbacks. As a result, the experiment with parameterized SMB–elevation feedback provides a sea-level contribution from GrIS in 2150 only 2.5 % lower than the two-way coupled experiment, while the experiment with no feedback is 9.3 % lower. The change in the ablation area in the two-way coupled experiment is much larger than those provided by the two simplest methods, with an underestimation of 11.7 % (14 %) with parameterized feedbacks (no feedback). In addition, we quantify that computing the GrIS contribution to sea-level rise from SMB changes only over a fixed ice sheet mask leads to an overestimation of ice loss of at least 6 % compared to the use of a time variable ice sheet mask. Finally, our results suggest that ice-loss estimations diverge when using the different coupling strategies, with differences from the two-way method becoming significant at the end of the 21st century. In particular, even if averaged over the whole GrIS the climatic and ice sheet fields are relatively similar; at the local and regional scale there are important differences, highlighting the importance of correctly representing the interactions when interested in basin scale changes. [ABSTRACT FROM AUTHOR]

The article presents study which examines the sensitivity of Greenland ice sheet (GSI) model to atmospheric forcing fields. It states that modelled precipitation and near surface air temperature is provided as upper boundary conditions to the GRenoble Ice Shelf and Land Ice model (GRISLI) hybrid ice sheet model (ISM) in Greenland. Results show that the model is much more sensitive to surface mass balance than to the dynamic parameters.