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The Antarctic ice sheet (AIS) will be a dominant contributor to global mean sea level rise in the 21st century but remains a major source of uncertainty. The Ice Sheet Model Intercomparison for CMIP6 (ISMIP6) is an ensemble of continental‐scale models for studying the evolution of the AIS and projecting its future contribution to sea level. Due to their complexity and computational cost, ISMIP6 simulations are sparse and generated infrequently. Emulators are smaller‐scale models that approximate ISMs and enable experimentation and exploration into the drivers of sea level change. We introduce a neural network (NN) emulator to approximate the ISMIP6 ensemble, using a variational Long Short‐Term Memory (LSTM) with Monte Carlo dropout to quantify single‐projection uncertainty. The proposed NN emulator is compared to a Gaussian Process (GP) emulator on four criteria: accuracy of point estimates and predictive distributions of individual model projections, approximation of the ensemble projections, and model training time. The NN predicts more accurately on single projections, with a mean absolute error of 0.46 mm Sea Level Equivalent (SLE) versus 0.73 mm SLE for the GP, and has more accurate uncertainty estimates. The NN emulator also better approximates the ensemble distribution of ISMIP6 model projections, with a Kullback‐Leibler divergence of 18.26 versus 199.14 for GP at the projection year 2100. The NN enables more accurate experimentation with a reduced runtime, offering a new tool for understanding the important role of regional precipitation, ice sheet drainage systems, and interannual and longer timescale dynamics.

 

Sea-level rise projections rely on accurate predictions of ice mass loss from Antarctica. Climate change promotes greater mass loss by destabilizing ice shelves and accelerating the discharge of upstream grounded ice. Mass loss is further exacerbated by mechanisms such as the Marine Ice Sheet Instability and the Marine Ice Cliff Instability. However, the effect of basal thermal state changes of grounded ice remains largely unexplored. Here, we use numerical ice sheet modeling to investigate how warmer basal temperatures could affect the Antarctic ice sheet mass balance. We find increased mass loss in response to idealized basal thawing experiments run over 100 years. Most notably, frozen-bed patches could be tenuously sustaining the current ice configuration in parts of George V, Adélie, Enderby, and Kemp Land regions of East Antarctica. With less than 5 degrees of basal warming, these frozen patches may begin to thaw, producing new loci of mass loss.

 

Abstract. Time-dependent simulations of ice sheets require two equations to be solved:the mass transport equation, derived from the conservation of mass, and thestress balance equation, derived from the conservation of momentum. The masstransport equation controls the advection of ice from the interior of the icesheet towards its periphery, thereby changing its geometry. Because it isbased on an advection equation, a stabilization scheme needs to beemployed when solved using the finite-element method. Several stabilizationschemes exist in the finite-element method framework, but their respectiveaccuracy and robustness have not yet been systematically assessed forglaciological applications. Here, we compare classical schemes used in thecontext of the finite-element method: (i) artificial diffusion, (ii)streamline upwinding, (iii) streamline upwind Petrov–Galerkin, (iv)discontinuous Galerkin, and (v) flux-corrected transport. We also look at thestress balance equation, which is responsible for computing the ice velocitythat “advects” the ice downstream. To improve the velocity computationaccuracy, the ice-sheet modeling community employs several sub-elementparameterizations of physical processes at the grounding line, the point wherethe grounded ice starts to float onto the ocean. Here, we introduce a newsub-element parameterization for the driving stress, the force that drives theice-sheet flow. We analyze the response of each stabilization scheme byrunning transient simulations forced by ice-shelf basal melt. The simulationsare based on an idealized ice-sheet geometry for which there is no influenceof bedrock topography. We also perform transient simulations of the AmundsenSea Embayment, West Antarctica, where real bedrock and surface elevations areemployed. In both idealized and real ice-sheet experiments, stabilizationschemes based on artificial diffusion lead systematically to a bias towardsmore mass loss in comparison to the other schemes and therefore should beavoided or employed with a sufficiently high mesh resolution in the vicinityof the grounding line. We also run diagnostic simulations to assess theaccuracy of the driving stress parameterization, which, in combination with anadequate parameterization for basal stress, provides improved numericalconvergence in ice speed computations and more accurate results. 

Abstract. Climate model projections have previously been used to compute ice shelf basal melt rates in ice sheet models, but the strategies employed – e.g., ocean input, parameterization, calibration technique, and corrections – have varied widely and are often ad hoc. Here, a methodology is proposed for the calculation of circum-Antarctic basal melt rates for floating ice, based on climate models, that is suitable for ISMIP6, the Ice Sheet Model Intercomparison Project for CMIP6 (6th Coupled Model Intercomparison Project). The past and future evolution of ocean temperature and salinity is derived from a climate model by estimating anomalies with respect to the modern day, which are added to a present-day climatology constructed from existing observational datasets. Temperature and salinity are extrapolated to any position potentially occupied by a simulated ice shelf. A simple formulation is proposed for a basal melt parameterization in ISMIP6, constrained by the observed temperature climatology, with a quadratic dependency on either the nonlocal or local thermal forcing. Two calibration methods are proposed: (1) based on the mean Antarctic melt rate (MeanAnt) and (2) based on melt rates near Pine Island's deep grounding line (PIGL). Future Antarctic mean melt rates are an order of magnitude greater in PIGL than in MeanAnt. The PIGL calibration and the local parameterization result in more realistic melt rates near grounding lines. PIGL is also more consistent with observations of interannual melt rate variability underneath Pine Island and Dotson ice shelves. This work stresses the need for more physics and less calibration in the parameterizations and for more observations of hydrographic properties and melt rates at interannual and decadal timescales. 

Abstract. Projection of the contribution of ice sheets to sea level change as part ofthe Coupled Model Intercomparison Project Phase 6 (CMIP6) takes the formof simulations from coupled ice sheet–climate models and stand-alone icesheet models, overseen by the Ice Sheet Model Intercomparison Project forCMIP6 (ISMIP6). This paper describes the experimental setup forprocess-based sea level change projections to be performed with stand-aloneGreenland and Antarctic ice sheet models in the context of ISMIP6. TheISMIP6 protocol relies on a suite of polar atmospheric and oceanicCMIP-based forcing for ice sheet models, in order to explore the uncertaintyin projected sea level change due to future emissions scenarios, CMIPmodels, ice sheet models, and parameterizations for ice–ocean interactions.We describe here the approach taken for defining the suite of ISMIP6stand-alone ice sheet simulations, document the experimental framework andimplementation, and present an overview of the ISMIP6 forcing to beused by participating ice sheet modeling groups. 

Abstract. Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution inresponse to different climate scenarios and assess the mass loss that would contribute tofuture sea level rise. However, there is currently no consensus on estimates of the future massbalance of the ice sheet, primarily because of differences in the representation of physicalprocesses, forcings employed and initial states of ice sheet models. This study presentsresults from ice flow model simulations from 13 international groups focusing on the evolutionof the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet ModelIntercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from theCoupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climatemodel results. Simulations of the Antarctic ice sheet contribution to sea level rise in responseto increased warming during this period varies between −7.8 and 30.0 cm of sea level equivalent(SLE) under Representative ConcentrationPathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment withconstant climate conditions and should therefore be added to the mass loss contribution underclimate conditions similar to present-day conditions over the same period. The simulated evolution of theWest Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica mass change varies between −6.1 and8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighingthe increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelfcollapse, here assumed to be caused by large amounts of liquid water ponding at the surface ofice shelves, yields an additional simulated mass loss of 28 mm compared to simulations without iceshelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, thecalibration of these melt rates based on oceanic conditions taken outside of ice shelf cavitiesand the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario basedon two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared tosimulations done under present-day conditions for the two CMIP5 forcings used and displaylimited mass gain in East Antarctica.