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  • 1
    Online Resource
    Online Resource
    Cambridge :Cambridge University Press,
    Keywords: Mass budget (Geophysics). ; Electronic books.
    Description / Table of Contents: Land and sea ice combined form the largest part of the Earth's cryosphere, responding to climate change over timescales ranging from seasons to millennia. This is a detailed and comprehensive overview of the observation and modelling of present and predicted future trends in the mass balance of ice on Earth.
    Type of Medium: Online Resource
    Pages: 1 online resource (664 pages)
    Edition: 1st ed.
    ISBN: 9780511187636
    DDC: 551.31
    Language: English
    Note: Cover -- Half-title -- Title -- Copyright -- Contents -- Contributors -- Foreword -- Preface -- 1 Introduction and background -- 1.1 Aims and objectives of the book -- 1.2 Importance of the cryosphere in the Earth system -- 1.2.1 Sea level -- 1.2.2 Ice-ocean-atmosphere feedbacks -- 1.3 Timescales of variability -- 1.4 Geographical context -- References -- Part I Observational techniques and methods -- 2 In situ measurement techniques: land ice -- 2.1 Introduction -- 2.2 Mass balance equations -- 2.3 Direct measurement of surface elevation change -- 2.3.1 Traditional surveying methods -- 2.3.2 Cartographic method: comparison of topographic maps from different years -- 2.3.3 Repeated altitude profiles by GPS -- 2.3.4 Coffee-can method -- 2.4 Measurement of mass balance components -- 2.4.1 Accumulation and ablation rate -- Stake readings -- Index methods -- Pit studies, firn and ice cores -- Annual cycles - oxygen isotopes, dust, chemistry -- Reference layers -- Automatic registrations -- Ground-penetrating radar (GPR) -- 2.4.2 Superimposed ice and internal accumulation -- 2.4.3 Error analysis -- 2.4.4 Balance velocity -- 2.4.5 Calving -- 2.4.6 Bottom mass balance (floating glaciers and ice shelves) -- Upward-pointing echo sounder -- Thickness change in bore holes, combined with strain-rate and surface balance measurements -- Mass flux divergence calculations -- The cavity beneath the glacier -- 2.5 Local mass balance equation -- 2.6 Conclusion -- References -- 3 In situ measurement techniques: sea ice -- 3.1 Current techniques -- 3.1.1 Submarine sonar profiling -- 3.1.2 Moored upward sonars -- 3.1.3 Airborne laser profilometry -- 3.1.4 Airborne electromagnetic techniques -- 3.1.5 Drilling -- 3.2 Possible future techniques -- 3.2.1 Sonar on AUVs and floats -- 3.2.2 Acoustic tomography -- 3.2.3 The use of microwave sensors -- References. , 4 Remote-sensing techniques -- 4.1 Introduction -- 4.2 Electromagnetic theory and basic principles -- 4.3 Satellites and sensors -- 4.3.1 Visible and infra-red sensors -- Landsat -- SPOT -- ASTER -- AVHRR -- 4.3.2 Synthetic aperture radars and scatterometers -- 4.3.3 Satellite altimetry -- Atmospheric corrections -- Orbits -- CryoSat -- The ice, clouds and elevation satellite, ICESat -- 4.3.4 Passive microwave radiometers (PMRs) -- 4.4 Land-ice mass balance -- 4.4.1 Direct measurement of volume changes -- Radar altimetry -- Laser altimetry -- Other methods of determining volume change -- 4.4.2 Measurement of mass balance components: budget approach -- Accumulation rates -- Ablation -- Iceberg calving -- Bottom mass balance of floating ice -- Grounding-line fluxes -- Determination of ice thickness -- Velocity and grounding-line estimation -- 4.4.3 Balance velocities and fluxes -- 4.5 Sea-ice mass balance: introduction -- 4.5.1 Sea-ice coverage - extent, concentration and type -- Retrieval of ice concentration and extent -- Ice types -- Ice types from passive microwave data -- Ice types from active microwave data -- 4.5.2 Sea-ice motion and deformation -- Retrieval of sea-ice motion -- High resolution ice motion from SAR -- Small-scale ice motion and deformation -- 4.5.3 Sea-ice thickness -- Radar altimetry -- Seasonal ice-thickness estimates from kinematics -- Ice surface temperature and ice thickness -- 4.6 Summary -- References -- Part II Modelling techniques and methods -- 5 Modelling land-ice surface mass balance -- 5.1 Introduction -- 5.2 The surface energy balance -- 5.2.1 Introduction -- 5.2.2 The incoming short-wave radiative flux -- 5.2.3 Surface albedo -- 5.2.4 The incoming long-wave radiative flux -- 5.2.5 The outgoing long-wave radiative flux -- 5.2.6 The fluxes of sensible and latent heat -- 5.2.7 The heat flux supplied by rain. , 5.2.8 Subsurface processes -- 5.3 The degree-day approach -- 5.4 The mass balance in ablation models -- 5.5 Introduction to modelling the mass balance at the scale of glaciers -- 5.6 Ablation models -- 5.6.1 Grids and forcing -- 5.6.2 Validation -- 5.7 Atmospheric models -- 5.7.1 Introduction -- 5.7.2 Global and regional atmospheric circulation models -- 5.7.3 Atmospheric and surface physics in the models -- 5.7.4 Scales, resolution and computing cost -- 5.7.5 Model performances and biasses -- 5.7.6 Meteorological analyses and short-term forecasts -- 5.8 Regression models -- 5.9 Comparison of the different types of models -- 5.10 List of symbols -- References -- 6 Modelling land-ice dynamics -- 6.1 Introduction -- 6.2 Glacier dynamics -- 6.2.1 Force balance -- Driving stress -- Resistive stresses -- Force balance in the horizontal direction -- Force balance in the vertical direction -- 6.2.2 Flow law -- 6.2.3 Velocities and strain rates -- 6.2.4 Thermodynamics -- 6.2.5 Continuity -- 6.2.6 Basal sliding and bed deformation -- 6.3 Hierarchy of models -- 6.3.1 Introduction -- 6.3.2 Lamellar flow -- 6.3.3 Including lateral drag -- 6.3.4 Ice-shelf spreading -- 6.3.5 Ice shelf/ice sheet interaction -- 6.4 Evaluating terrestrial ice-mass models -- 6.4.1 Terminology -- 6.4.2 Types of ice-mass models -- Prognostic models -- Diagnostic models -- 6.4.3 Model validation -- The EISMINT inter-comparison -- EISMINT levels one and two -- EISMINT level three -- Conclusions -- 6.4.4 Model calibration and confirmation -- Confirming models of ice velocity -- Confirming models of ice-mass temperature -- The use of RES data to confirm models of glacier flow -- 6.5 List of symbols -- References -- 7 Modelling the dynamic response of sea ice -- 7.1 Introduction -- 7.2 Selected observational sea-ice motion: mechanical and physical characteristics. , 7.2.1 Sea-ice drift, deformation and pressure ridges -- 7.2.2 Ice stress and physical properties -- 7.3 Modelling sea-ice drift and deformation -- 7.3.1 Equations of motion -- 7.3.2 Deformation scaling of momentum equations -- 7.4 Sea-ice mechanics -- 7.4.1 Aggregate isotropic sea-ice constitutive laws -- 7.4.2 Coulombic and fracture-based isotropic models -- 7.4.3 Effect of plastic ice interaction on modelled ice drift -- A mechanistic one-dimensional plastic system -- Comparison of large-scale simulated plastic drift and deformation characteristics -- Improvement of simulations by including 'inertial imbedding' -- The effect of rheology on outflow -- 7.5 Sea-ice thermodynamics -- 7.5.1 Idealized growth: the Stefan problem -- 7.5.2 Empirical analytic sea-ice growth models for seasonal ice -- 7.5.3 Full heat budget thermodynamic models -- 7.5.4 Effects of internal brine pockets and variable conductivity -- 7.6 Ice-thickness distribution theory: dynamic thermodynamic coupling -- 7.6.1 Evolution equations for the ice-thickness distribution -- 7.6.2 Consistency of isotropic plastic models with ridge building -- 7.6.3 Characteristics of thickness distribution models coupled to specified deformation -- 7.6.4 Two-level ice-thickness distribution -- 7.6.5 Relative characteristics of two-level and multi-level models in numerical simulations -- 7.6.6 Thickness strength coupling: kinematic waves and inertial variability -- Kinematic waves in sea ice -- Inertial variability in sea-ice deformation -- Ice arching with growth and advection -- 7.6.7 Ice-tide interaction and stationary shore fast ice -- 7.7 A selected hierarchy of dynamic thermodynamic simulations of the evolution of sea ice -- 7.7.1 Selected characteristics of ice-ocean circulation models -- 7.7.2 Multiple equilibrium states of mechanistic dynamic thermodynamic sea-ice models. , 7.7.3 Arctic Basin variable thickness simulations -- Ridged ice and sensitivity to mechanical parameters -- The relative role of dynamics and thermodynamics in historical variability -- 7.7.4 The response of sea ice to climate change: the effect of ice dynamics -- 7.8 Concluding remarks -- References -- Part III The mass balance of sea ice -- 8 Sea-ice observations -- 8.1 Introduction -- 8.2 Sea-ice observations -- 8.3 Sea-ice observations: the pre-satellite era -- 8.4 Sea-ice cover: the post-satellite era -- 8.5 Mean ice thickness and its variability -- 8.6 Current evidence for change -- 8.7 Consequences of change -- 8.8 Future prospects -- References -- 9 Sea-ice modelling -- 9.1 Brief overview of sea-ice models -- 9.1.1 Momentum equation -- 9.1.2 Thermodynamics -- 9.1.3 Conservation equations -- 9.2 Mean thickness -- 9.2.1 Spatial and temporal variability -- 9.2.2 Ice export -- 9.2.3 Sensitivity to model parameterizations -- 9.3 Modelling future changes in sea-ice mass balance -- 9.4 Summary and conclusions -- References -- Part IV The mass balance of the ice sheets -- 10 Greenland: recent mass balance observations -- 10.1 Introduction -- 10.1.1 The polar ice sheets -- 10.1.2 Greenland and sea-level change -- 10.1.3 Program for Arctic Regional Climate Assessment (PARCA) -- 10.2 Components of ice-sheet mass balance -- 10.2.1 Accumulation -- 10.2.2 Surface ablation -- 10.2.3 Ice discharge -- 10.3 PARCA measurements -- 10.3.1 Snow-accumulation rates -- Shallow ice coring -- Accumulation rates from satellite microwave data -- Accumulation rates from atmospheric analyses -- 10.3.2 Ice depth sounding and layer tracking -- 10.3.3 Ice velocities and glacier grounding lines from SAR interferometry -- 10.3.4 Ice-surface characteristics from satellite data -- Summer melt zones -- Surface temperature and albedo -- Snow facies. , 10.3.5 Automatic weather station (AWS) network and meteorological observations.
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  • 2
    Publication Date: 2024-03-23
    Description: The dataset described in this document has been put together for the purposes of numerical ice sheet modelling of the Antarctic Ice Sheet (AIS), containing data on the ice sheet configuration (e.g. ice surface and ice thickness) and boundary conditions, such as the surface air temperature and accumulation. It is now possible to download a community ice sheet model (e.g. Glimmer-CISM, Rutt et al., 2009 doi:10.1029/2008JF001015), but without adequate data it is difficult to utilise such models. More specifically, ice sheet models that are initialised and run forward from the present day ice sheet configuration, need input data to represent the present-day ice sheet configuration as closely as possible (unlike those spun-up from ice free conditions, which only require the bed/bathymetry). Whilst the BEDMAP dataset (Lythe et al., 2001) was a step forward when it was made, there are a number of inconsistencies within the dataset (see Section 3), and since its release, more data has become available. The dataset described here incorporates some major new datasets (e.g. AGASEA/BBAS ice thickness, Nitsche et al. (2006) bathymetry doi:10.1029/2007GC001694), but by no means incorporates all the new data available. This considerable task is left for a 'BEDMAP2', (an updated version of BEDMAP), however, the processing carried out in this document illustrates the requirements of a dataset for the purpose of high resolution ice sheet modelling, and bridges the gap until a BEDMAP2 is published. It is envisaged, however, that updated versions of the data set will be made available periodically when new regional data sets become available and can be readily incorporated.
    Type: Dataset
    Format: application/zip, 15.1 MBytes
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  • 3
    Publication Date: 2019-07-17
    Repository Name: EPIC Alfred Wegener Institut
    Type: PANGAEA Documentation , notRev
    Format: application/pdf
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  • 4
    Publication Date: 2019-07-16
    Description: A flowline ice sheet model is coupled to a box model for cavity circulation and configured for the Pine Island Glacier. An ensemble of 5000 simulations are carried out from 1900 to 2200 with varying inputs and parameters, forced by ocean temperatures predicted by a regional ocean model under the A1B ‘business as usual’ emissions scenario. Comparison is made against recent observations to provide a calibrated prediction in the form of a 95% confidence set. Predictions are for monotonic (apart from some small scale fluctuations in a minority of cases) retreat of the grounding line over the next 200 yr with huge uncertainty in the rate of retreat. Full collapse of the main trunk of the PIG during the 22nd century remains a possibility.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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  • 5
    Publication Date: 2022-09-26
    Description: The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2,3,4,5,6,7,8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 6
    Publication Date: 2022-09-26
    Description: Projections of the sea level contribution from the Greenland and Antarctic ice sheets (GrIS and AIS) rely on atmospheric and oceanic drivers obtained from climate models. The Earth System Models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) generally project greater future warming compared with the previous Coupled Model Intercomparison Project phase 5 (CMIP5) effort. Here we use four CMIP6 models and a selection of CMIP5 models to force multiple ice sheet models as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We find that the projected sea level contribution at 2100 from the ice sheet model ensemble under the CMIP6 scenarios falls within the CMIP5 range for the Antarctic ice sheet but is significantly increased for Greenland. Warmer atmosphere in CMIP6 models results in higher Greenland mass loss due to surface melt. For Antarctica, CMIP6 forcing is similar to CMIP5 and mass gain from increased snowfall counteracts increased loss due to ocean warming.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 7
    Publication Date: 2022-09-26
    Description: Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between −7.8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to present-day conditions over the same period. The simulated evolution of the West 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 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28 mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 8
    Publication Date: 2024-03-14
    Description: The Antarctic Ice Sheet represents the largest source of uncertainty in future sea level rise projections, with a contribution to sea level by 2100 ranging from −5 to 43 cm of sea level equivalent under high carbon emission scenarios estimated by the recent Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). ISMIP6 highlighted the different behaviors of the East and West Antarctic ice sheets, as well as the possible role of increased surface mass balance in offsetting the dynamic ice loss in response to changing oceanic conditions in ice shelf cavities. However, the detailed contribution of individual glaciers, as well as the partitioning of uncertainty associated with this ensemble, have not yet been investigated. Here, we analyze the ISMIP6 results for high carbon emission scenarios, focusing on key glaciers around the Antarctic Ice Sheet, and we quantify their projected dynamic mass loss, defined here as mass loss through increased ice discharge into the ocean in response to changing oceanic conditions. We highlight glaciers contributing the most to sea level rise, as well as their vulnerability to changes in oceanic conditions. We then investigate the different sources of uncertainty and their relative role in projections, for the entire continent and for key individual glaciers. We show that, in addition to Thwaites and Pine Island glaciers in West Antarctica, Totten and Moscow University glaciers in East Antarctica present comparable future dynamic mass loss and high sensitivity to ice shelf basal melt. The overall uncertainty in additional dynamic mass loss in response to changing oceanic conditions, compared to a scenario with constant oceanic conditions, is dominated by the choice of ice sheet model, accounting for 52 % of the total uncertainty of the Antarctic dynamic mass loss in 2100. Its relative role for the most dynamic glaciers varies between 14 % for MacAyeal and Whillans ice streams and 56 % for Pine Island Glacier at the end of the century. The uncertainty associated with the choice of climate model increases over time and reaches 13 % of the uncertainty by 2100 for the Antarctic Ice Sheet but varies between 4 % for Thwaites Glacier and 53 % for Whillans Ice Stream. The uncertainty associated with the ice–climate interaction, which captures different treatments of oceanic forcings such as the choice of melt parameterization, its calibration, and simulated ice shelf geometries, accounts for 22 % of the uncertainty at the ice sheet scale but reaches 36 % and 39 % for Institute Ice Stream and Thwaites Glacier, respectively, by 2100. Overall, this study helps inform future research by highlighting the sectors of the ice sheet most vulnerable to oceanic warming over the 21st century and by quantifying the main sources of uncertainty.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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  • 9
    Publication Date: 2018-12-17
    Description: Earlier large-scale Greenland ice sheet sea-level projections (e.g. those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions have a large effect on the projections and give rise to important uncertainties. The goal of this initMIP-Greenland intercomparison exercise is to compare, evaluate, and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties in modelled mass changes. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6), which is the primary activity within the Coupled Model Intercomparison Project Phase 6 (CMIP6) focusing on the ice sheets. Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of (1) the initial present-day state of the ice sheet and (2) the response in two idealised forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly); they should not be interpreted as sea-level projections. We present and discuss results that highlight the diversity of data sets, boundary conditions, and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to surface mass balance changes in areas where the simulated ice sheets overlap but differences arising from the initial size of the ice sheet. The model drift in the control experiment is reduced for models that participated in earlier intercomparison exercises.
    Type: Article , PeerReviewed
    Format: text
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  • 10
    Publication Date: 2021-01-08
    Description: Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between −7.8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to present-day conditions over the same period. The simulated evolution of the West 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 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28 mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica.
    Type: Article , PeerReviewed
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