Currently Pine Island Glacier (PIG) is responsible for 20% of the total ice loss offdischarge from the West Antarctic Ice Sheet (WAIS) ([22]; [30]). The accelerated thinning observed since the 1980s has essentially been attributed to enhanced sub-ice shelf melting [21] induced by the recent alteration of Circumpolar Deep Water circulation [10]. This has reduced the buttressing exerted by the ice shelf, leading to the acceleration of the ice stream and the ongoing retreat of the grounding line (GL) along the glacier's trunk observed since 1992 [17]. Today the GL lies over bedrock that has a steep retrograde slope [29] (Figure 1c) raising the possibility that PIG may already be engaged in an irrevocable retreat. ProvidedAssuming that ice flow is dominated * durand@lgge.obs.ujf-grenoble.fr 2 by basal sliding and lateral variation can be ignored, grounding lines located on retrograde slopes are always unstable [24,3], but in realistic, three-dimensional geometries lateral drag and buttressing in the ice shelf can act to prevent unstable retreat [9]. Assessing the stability of PIG therefore requires numerical models that accurately represent these additional forces.Models designed to study the evolution of PIG have been reported, though limited to flowline geometries [7] or extreme forcings [11]. Overall, the short-term behaviour of PIG is not well understood, and projections vary wildly, ranging from modest retreat to almost full collapse of the main trunk within a century [11,7].Here, we evaluate the potential instability of PIG and its short-term contribution to sea-level rise (SLR) using state-of-the-art ice flow models. To decide whether PIG is subject to Marine Ice Sheet Instability (MISI) at present, we must answer two questions: (i) to what extent is the dynamic response of PIG to changes in its ice shelf dictated by the bedrock topography rather than the type and amplitude of the perturbation, and, (ii) can the GL be stabilized on the retrograde slope? Confidence in the answers we propose is of course affected by the accuracy of both the physics implemented in the models that we use and our estimates of poorly constrained parameters. We addressed these questions using three different ice-flow models: the full Stokes For all three models, the geometry is relaxed over 15 years to remove unphysical surface undulations induced by remaining uncertainties in the model initial conditions [6]. Surface accumu-3 lation is given by the regional atmospheric model RACMO (1980RACMO ( -2004) and sub-ice shelf melting is imposed as a piecewise linear function of the lower surface elevationwater depth with a maximum melting rate of 100 m a −1 below -800 m depth, linearly decreasing to no melt above -400 m. This melt-rate parametrisation, which we will refer to as m0 control, is in reason- The recent retreat of PIG is now firmly attributed to acceleration of the glacier in response to sub-ice shelf melting. To evaluate the consequences of melting on PIG dynamics, fivefour different melt-rate perturbations are tested. These ar...

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Predictions of marine ice-sheet behaviour require models able to simulate grounding-line migration. We present results of an intercomparison experiment for plan-view marine ice-sheet models. Verification is effected by comparison with approximate analytical solutions for flux across the grounding line using simplified geometrical configurations (no lateral variations, no buttressing effects from lateral drag). Perturbation experiments specifying spatial variation in basal sliding parameters permitted the evolution of curved grounding lines, generating buttressing effects. The experiments showed regions of compression and extensional flow across the grounding line, thereby invalidating the boundary layer theory. Steady-state grounding-line positions were found to be dependent on the level of physical model approximation. Resolving grounding lines requires inclusion of membrane stresses, a sufficiently small grid size (<500 m), or subgrid interpolation of the grounding line. The latter still requires nominal grid sizes of <5 km. For larger grid spacings, appropriate parameterizations for ice flux may be imposed at the grounding line, but the short-time transient behaviour is then incorrect and different from models that do not incorporate grounding-line parameterizations. The numerical error associated with predicting grounding-line motion can be reduced significantly below the errors associated with parameter ignorance and uncertainties in future scenarios.

Abstract. Coupled ice sheet–ocean models capable of simulating moving grounding lines are just becoming available. Such models have a broad range of potential applications in studying the dynamics of marine ice sheets and tidewater glaciers, from process studies to future projections of ice mass loss and sea level rise. The Marine Ice Sheet–Ocean Model Intercomparison Project (MISOMIP) is a community effort aimed at designing and coordinating a series of model intercomparison projects (MIPs) for model evaluation in idealized setups, model verification based on observations, and future projections for key regions of the West Antarctic Ice Sheet (WAIS). Here we describe computational experiments constituting three interrelated MIPs for marine ice sheet models and regional ocean circulation models incorporating ice shelf cavities. These consist of ice sheet experiments under the Marine Ice Sheet MIP third phase (MISMIP+), ocean experiments under the Ice Shelf-Ocean MIP second phase (ISOMIP+) and coupled ice sheet–ocean experiments under the MISOMIP first phase (MISOMIP1). All three MIPs use a shared domain with idealized bedrock topography and forcing, allowing the coupled simulations (MISOMIP1) to be compared directly to the individual component simulations (MISMIP+ and ISOMIP+). The experiments, which have qualitative similarities to Pine Island Glacier Ice Shelf and the adjacent region of the Amundsen Sea, are designed to explore the effects of changes in ocean conditions, specifically the temperature at depth, on basal melting and ice dynamics. In future work, differences between model results will form the basis for the evaluation of the participating models.