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The Northeast Greenland Ice Stream (NEGIS) currently drains more than 10 % of the Greenland Ice Sheet area and has recently undergone significant dynamic changes. It is therefore critical to accurately represent this feature when assessing the future contribution of Greenland to sea level rise. At present, NEGIS is reproduced in ice sheet models by inferring basal conditions using observed surface velocities. This approach helps estimate conditions at the base of the ice sheet but cannot be used to estimate the evolution of basal drag in time, so it is not a good representation of the evolution of the ice sheet in future climate warming scenarios. NEGIS is suggested to be initiated by a geothermal heat flux anomaly close to the ice divide, left behind by the movement of Greenland over the Icelandic plume. However, the heat flux underneath the ice sheet is largely unknown, except for a few direct measurements from deep ice core drill sites. Using the Ice Sheet System Model (ISSM), with ice dynamics coupled to a subglacial hydrology model, we investigate the possibility of initiating NEGIS by inserting heat flux anomalies with various locations and intensities. In our model experiment, a minimum heat flux value of 970 mW m−2 located close to the East Greenland Ice-core Project (EGRIP) is required locally to reproduce the observed NEGIS velocities, giving basal melt rates consistent with previous estimates. The value cannot be attributed to geothermal heat flux alone and we suggest hydrothermal circulation as a potential explanation for the high local heat flux. By including high heat flux and the effect of water on sliding, we successfully reproduce the main characteristics of NEGIS in an ice sheet model without using data assimilation.

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).

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).

Four high-resolution regional climate models (RCMs) have been set up for the area of Greenland, with the aim of providing future projections of Greenland ice sheet surface mass balance (SMB), and its contribution to sea level rise, with greater accuracy than is possible from coarser-resolution general circulation models (GCMs). This is the first time an intercomparison has been carried out of RCM results for Greenland climate and SMB. Output from RCM simulations for the recent past with the four RCMs is evaluated against available observations. The evaluation highlights the importance of using a detailed snow physics scheme, especially regarding the representations of albedo and meltwater refreezing. Simulations with three of the RCMs for the 21st century using SRES scenario A1B from two GCMs produce trends of between −5.5 and −1.1 Gt yr−2 in SMB (equivalent to +0.015 and +0.003 mm sea level equivalent yr−2), with trends of smaller magnitude for scenario E1, in which emissions are mitigated. Results from one of the RCMs whose present-day simulation is most realistic indicate that an annual mean near-surface air temperature increase over Greenland of ~ 2°C would be required for the mass loss to increase such that it exceeds accumulation, thereby causing the SMB to become negative, which has been suggested as a threshold beyond which the ice sheet would eventually be eliminated.