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Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.

Predicting the climate for the future and how it will impact ice sheet evolution requires coupling ice sheet models with climate models. However, before we attempt to develop a realistic coupled setup, we propose, in this study, to first analyse the impact of a model simulated climate on an ice sheet. We undertake this exercise for a set of regional and global climate models. Modelled near surface air temperature and precipitation are provided as upper boundary conditions to the GRISLI (GRenoble Ice Shelf and Land Ice model) hybrid ice sheet model (ISM) in its Greenland configuration. After 20 kyrs of simulation, the resulting ice sheets highlight the differences between the climate models. While modelled ice sheet sizes are generally comparable to the observed one, there are considerable deviations among the ice sheets on regional scales. These deviations can be explained by biases in temperature and precipitation near the coast. This is especially true in the case of global models. But the deviations between the climate models are also due to the differences in the atmospheric general circulation. To account for these differences in the context of coupling ice sheet models with climate models, we conclude that appropriate downscaling methods will be needed. In some cases, systematic corrections of the climatic variables at the interface may be required to obtain realistic results for the Greenland ice sheet (GIS).

Computer models are necessary for understanding and predicting marine ice sheet behaviour. However, there is uncertainty over implementation of physical processes at the ice base, both for grounded and floating glacial ice. Here we implement several sliding relations in a marine ice sheet flow-line model accounting for all stress components and demonstrate that model resolution requirements are strongly dependent on both the choice of basal sliding relation and the spatial distribution of ice shelf basal melting.Sliding relations that reduce the magnitude of the step change in basal drag from grounded ice to floating ice (where basal drag is set to zero) show reduced dependence on resolution compared to a commonly used relation, in which basal drag is purely a power law function of basal ice velocity. Sliding relations in which basal drag goes smoothly to zero as the grounding line is approached from inland (due to a physically motivated incorporation of effective pressure at the bed) provide further reduction in resolution dependence.A similar issue is found with the imposition of basal melt under the floating part of the ice shelf: melt parameterisations that reduce the abruptness of change in basal melting from grounded ice (where basal melt is set to zero) to floating ice provide improved convergence with resolution compared to parameterisations in which high melt occurs adjacent to the grounding line.Thus physical processes, such as sub-glacial outflow (which could cause high melt near the grounding line), impact on capability to simulate marine ice sheets. If there exists an abrupt change across the grounding line in either basal drag or basal melting, then high resolution will be required to solve the problem. However, the plausible combination of a physical dependency of basal drag on effective pressure, and the possibility of low ice shelf basal melt rates next to the grounding line, may mean that some marine ice sheet systems can be reliably simulated at a coarser resolution than currently thought necessary.

Continuing global warming will have a strong impact on the Greenland ice sheet in the coming centuries. During the last decade (2000–2010), both increased melt-water runoff and enhanced ice discharge from calving glaciers have contributed 0.6 ± 0.1 mm yr−1 to global sea-level rise, with a relative contribution of 60 and 40% respectively. Here we use a higher-order ice flow model, spun up to present day, to simulate future ice volume changes driven by both atmospheric and oceanic temperature changes. For these projections, the flow model accounts for runoff-induced basal lubrication and ocean warming-induced discharge increase at the marine margins. For a suite of 10 atmosphere and ocean general circulation models and four representative concentration pathway scenarios, the projected sea-level rise between 2000 and 2100 lies in the range of +1.4 to +16.6 cm. For two low emission scenarios, the projections are conducted up to 2300. Ice loss rates are found to abate for the most favourable scenario where the warming peaks in this century, allowing the ice sheet to maintain a geometry close to the present-day state. For the other moderate scenario, loss rates remain at a constant level over 300 years. In any scenario, volume loss is predominantly caused by increased surface melting as the contribution from enhanced ice discharge decreases over time and is self-limited by thinning and retreat of the marine margin, reducing the ice–ocean contact area. As confirmed by other studies, we find that the effect of enhanced basal lubrication on the volume evolution is negligible on centennial timescales. Our projections show that the observed rates of volume change over the last decades cannot simply be extrapolated over the 21st century on account of a different balance of processes causing ice loss over time. Our results also indicate that the largest source of uncertainty arises from the surface mass balance and the underlying climate change projections, not from ice dynamics.

The basal topography is largely unknown beneath most glaciers and ice caps, and many attempts have been made to estimate a thickness field from other more accessible information at the surface. Here, we present a two-step reconstruction approach for ice thickness that solves mass conservation over single or several connected drainage basins. The approach is applied to a variety of test geometries with abundant thickness measurements including marine- and land-terminating glaciers as well as a 2400 km2 ice cap on Svalbard. The input requirements are kept to a minimum for the first step. In this step, a geometrically controlled, non-local flux solution is converted into thickness values relying on the shallow ice approximation (SIA). In a second step, the thickness field is updated along fast-flowing glacier trunks on the basis of velocity observations. Both steps account for available thickness measurements. Each thickness field is presented together with an error-estimate map based on a formal propagation of input uncertainties. These error estimates point out that the thickness field is least constrained near ice divides or in other stagnant areas. Withholding a share of the thickness measurements, error estimates tend to overestimate mismatch values in a median sense. We also have to accept an aggregate uncertainty of at least 25 % in the reconstructed thickness field for glaciers with very sparse or no observations. For Vestfonna ice cap (VIC), a previous ice volume estimate based on the same measurement record as used here has to be corrected upward by 22 %. We also find that a 13 % area fraction of the ice cap is in fact grounded below sea level. The former 5 % estimate from a direct measurement interpolation exceeds an aggregate maximum range of 6–23 % as inferred from the error estimates here.

Combined records of snow accumulation rate, δ18O and deuterium excess were produced from several shallow ice cores and snow pits at NEEM (North Greenland Eemian Ice Drilling), covering the period from 1724 to 2007. They are used to investigate recent climate variability and characterise the isotope–temperature relationship. We find that NEEM records are only weakly affected by inter-annual changes in the North Atlantic Oscillation. Decadal δ18O and accumulation variability is related to North Atlantic sea surface temperature and is enhanced at the beginning of the 19th century. No long-term trend is observed in the accumulation record. By contrast, NEEM δ18O shows multidecadal increasing trends in the late 19th century and since the 1980s. The strongest annual positive δ18O values are recorded at NEEM in 1928 and 2010, while maximum accumulation occurs in 1933. The last decade is the most enriched in δ18O (warmest), while the 11-year periods with the strongest depletion (coldest) are depicted at NEEM in 1815–1825 and 1836–1846, which are also the driest 11-year periods. The NEEM accumulation and δ18O records are strongly correlated with outputs from atmospheric models, nudged to atmospheric reanalyses. Best performance is observed for ERA reanalyses. Gridded temperature reconstructions, instrumental data and model outputs at NEEM are used to estimate the multidecadal accumulation–temperature and δ18O–temperature relationships for the strong warming period in 1979–2007. The accumulation sensitivity to temperature is estimated at 11 ± 2 % °C−1 and the δ18O–temperature slope at 1.1 ± 0.2 ‰ °C−1, about twice as large as previously used to estimate last interglacial temperature change from the bottom part of the NEEM deep ice core.

We apply a new parameterisation of the Greenland ice sheet (GrIS) feedback between surface mass balance (SMB: the sum of surface accumulation and surface ablation) and surface elevation in the MAR regional climate model (Edwards et al., 2014) to projections of future climate change using five ice sheet models (ISMs). The MAR (Modèle Atmosphérique Régional: Fettweis, 2007) climate projections are for 2000–2199, forced by the ECHAM5 and HadCM3 global climate models (GCMs) under the SRES A1B emissions scenario. The additional sea level contribution due to the SMB–elevation feedback averaged over five ISM projections for ECHAM5 and three for HadCM3 is 4.3% (best estimate; 95% credibility interval 1.8–6.9%) at 2100, and 9.6% (best estimate; 95% credibility interval 3.6–16.0%) at 2200. In all results the elevation feedback is significantly positive, amplifying the GrIS sea level contribution relative to the MAR projections in which the ice sheet topography is fixed: the lower bounds of our 95% credibility intervals (CIs) for sea level contributions are larger than the "no feedback" case for all ISMs and GCMs. Our method is novel in sea level projections because we propagate three types of modelling uncertainty – GCM and ISM structural uncertainties, and elevation feedback parameterisation uncertainty – along the causal chain, from SRES scenario to sea level, within a coherent experimental design and statistical framework. The relative contributions to uncertainty depend on the timescale of interest. At 2100, the GCM uncertainty is largest, but by 2200 both the ISM and parameterisation uncertainties are larger. We also perform a perturbed parameter ensemble with one ISM to estimate the shape of the projected sea level probability distribution; our results indicate that the probability density is slightly skewed towards higher sea level contributions.

We present a new parameterisation that relates surface mass balance (SMB: the sum of surface accumulation and surface ablation) to changes in surface elevation of the Greenland ice sheet (GrIS) for the MAR (Modèle Atmosphérique Régional: Fettweis, 2007) regional climate model. The motivation is to dynamically adjust SMB as the GrIS evolves, allowing us to force ice sheet models with SMB simulated by MAR while incorporating the SMB–elevation feedback, without the substantial technical challenges of coupling ice sheet and climate models. This also allows us to assess the effect of elevation feedback uncertainty on the GrIS contribution to sea level, using multiple global climate and ice sheet models, without the need for additional, expensive MAR simulations. We estimate this relationship separately below and above the equilibrium line altitude (ELA, separating negative and positive SMB) and for regions north and south of 77° N, from a set of MAR simulations in which we alter the ice sheet surface elevation. These give four "SMB lapse rates", gradients that relate SMB changes to elevation changes. We assess uncertainties within a Bayesian framework, estimating probability distributions for each gradient from which we present best estimates and credibility intervals (CI) that bound 95% of the probability. Below the ELA our gradient estimates are mostly positive, because SMB usually increases with elevation: 0.56 (95% CI: −0.22 to 1.33) kg m−3 a−1 for the north, and 1.91 (1.03 to 2.61) kg m−3 a−1 for the south. Above the ELA, the gradients are much smaller in magnitude: 0.09 (−0.03 to 0.23) kg m−3 a−1 in the north, and 0.07 (−0.07 to 0.59) kg m−3 a−1 in the south, because SMB can either increase or decrease in response to increased elevation. Our statistically founded approach allows us to make probabilistic assessments for the effect of elevation feedback uncertainty on sea level projections (Edwards et al., 2014).

To estimate the sea level rise (SLR) originating from changes in surface mass balance (SMB) of the Greenland ice sheet (GrIS), we present 21st century climate projections obtained with the regional climate model MAR (Modèle Atmosphérique Régional), forced by output of three CMIP5 (Coupled Model Intercomparison Project Phase 5) general circulation models (GCMs). Our results indicate that in a warmer climate, mass gain from increased winter snowfall over the GrIS does not compensate mass loss through increased meltwater run-off in summer. Despite the large spread in the projected near-surface warming, all the MAR projections show similar non-linear increase of GrIS surface melt volume because no change is projected in the general atmospheric circulation over Greenland. By coarsely estimating the GrIS SMB changes from GCM output, we show that the uncertainty from the GCM-based forcing represents about half of the projected SMB changes. In 2100, the CMIP5 ensemble mean projects a GrIS SMB decrease equivalent to a mean SLR of +4 ± 2 cm and +9 ± 4 cm for the RCP (Representative Concentration Pathways) 4.5 and RCP 8.5 scenarios respectively. These estimates do not consider the positive melt–elevation feedback, although sensitivity experiments using perturbed ice sheet topographies consistent with the projected SMB changes demonstrate that this is a significant feedback, and highlight the importance of coupling regional climate models to an ice sheet model. Such a coupling will allow the assessment of future response of both surface processes and ice-dynamic changes to rising temperatures, as well as their mutual feedbacks.

We present an updated and quality controlled surface mass balance (SMB) database for the Antarctic ice sheet. Importantly, the database includes formatted metadata, such as measurement technique, elevation, time covered, etc, which allows any user to filter out the data. Here, we discard data with limited spatial and temporal representativeness, too small measurement accuracy, or lack of quality control. Applied to the database, this filtering process gives four times more reliable data than when applied to previously available databases. New data with high spatial resolution are now available over long traverses, and at low elevation in some areas. However, the quality control led to a considerable reduction in the spatial density of data in several regions, particularly over West Antarctica. Over interior plateaus, where the SMB is low, the spatial density of measurements remains high. This quality controlled dataset was compared to results from ERA-Interim reanalysis to assess whether field data allow us to reconstruct an accurate description of the main SMB distribution features in Antarctica. We identified large areas where data gaps impede model validation: except for very few areas (e. g., Adelie Land), measurements in the elevation range between 200 m and 1000 m above sea level are not regularly distributed and do not allow a thorough validation of models in such regions with complex topography, where the highest scattering of SMB values is reported. Clearly, increasing the spatial density of field measurements at low elevations, in the Antarctic Peninsula and in West Antarctica is a scientific priority.