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Accurately projecting mass loss from ice sheets is of critical societal importance. However, despite recent improvements in ice sheet models, our analysis of a recent effort to project Greenland's contribution to future sea-level suggests that few models reproduce historical mass loss accurately, and that they appear much too confident in the spread of predicted outcomes. The inability of models to reproduce historical observations raises concerns about the models' skill at projecting mass loss. Here we suggest that the future sea level contribution from Greenland may well be significantly higher than reported in that study. We propose a roadmap to enable a more realistic accounting of uncertainties associated with such forecasts, and a formal process by which observations of mass change be used to refine projections of mass change. Finally, we note that tremendous government investment and planning affecting 10s to 100s of millions of people is founded on the work of several tens of scientists involved in a significantly volunteer effort. To achieve the goal of credible projections of ice sheet contribution to sea-level, we strongly believe that investment in research must be commensurate with the scale of the challenge.

Here, we present a compilation of 85 ice temperature profiles from 79 boreholes from the Greenland Ice Sheet and peripheral ice caps, as well as local ice caps in the Canadian Arctic. Only 25 profiles (32 %) were previously available in open-access data repositories. The remaining 54 profiles (68 %) are being made digitally available here for the first time. These newly available profiles, which are associated with pre-2010 boreholes, have been submitted by community members or digitized from published graphics and/or data tables. All 85 profiles are now made available in both absolute (meters) and normalized (0 to 1 ice thickness) depth scales, and are accompanied by extensive metadata. This metadata includes a transparent description of data provenance. The ice temperature profiles span 70 years, with the earliest profile being from 1950 at Camp VI, West Greenland. To highlight the value of this database in evaluating ice flow simulations, we compare the ice temperature profiles from the Greenland Ice Sheet with an ice flow simulation by the Parallel Ice Sheet Model (PISM). We find a cold bias in modeled near-surface ice temperatures within the ablation area, a warm bias in modeled basal ice temperatures at inland cold-bedded sites, and an apparent underestimation of deformational heating in high-strain settings. These biases provide process-level insight on simulated ice temperatures., The Cryosphere Discussions, ISSN:1994-0432, ISSN:1994-0440

Changes to the support, culture, and community organization of U.S. glaciology are needed to advance understanding of glacial change and better predict rising seas and other ice loss impacts.

Earth’s topography and bathymetry is shaped by a complex interplay between solid-Earth processes that deform the Earth from within and the surface processes that modify the outer shape of the Earth. At the surface, an ultimate baselevel set by global sea level marks the defining transition from erosion to deposition. Over geological time scales, this baselevel has resulted in a distinct hypsometric distribution (distribution of surface area with elevation), with the highest concentration of surface area focused in a narrow elevation range near present-day sea level.This particular feature in Earth’s hypsometry makes the global land fraction very sensitive to changes in sea level. Indeed, a sea-level change will result in a significant change in the land fraction as dictated by the hypsometric distribution, thereby modulating the very same sea-level change. However, it remains unexplored exactly how sea-level changes have modified the global land fraction over past glacial cycles and into the future.Here we analyse how Earth’s hypsometry has changed over the last glacial cycle as large ice sheets waxed and waned particularly in Scandinavia and North America. These changes in global ice volume resulted in a significant global excursion in sea level, modulated regionally by solid-Earth deformation, gravitational effects, and effects from Earth’s rotation. These changes modified Earth’s hypsometry, and therefore the global land fraction at any given time. Consequently, we can map out how Earth’s hypsometry has influenced global mean sea level (GMSL) over time. To examine this relationship between Earth’s hypsometry and sea level further, we look to the deep future, to a scenario where both the Greenland Ice Sheet and the Antarctic Ice Sheets will melt away completely over multi-millennial timescales. This scenario is not meant to represent a realistic future scenario per se, but it allows us to define the hypsometric GMSL correction needed for any GMSL that the Earth has experienced recently or will experience in the future.

We give an overview of the Instructed Glacier Model (IGM) -- a new framework to model the evolution of glaciers at any scale by coupling ice dynamics, surface mass balance, and mass conservation. The key novelty of IGM is that it models the ice flow by a Convolutional Neural Network (CNN), which is trained from physical high-order ice flow mechanical models. Doing so has major advantages in both forward and inverse modelling.In forward modelling, the most computationally demanding model component (the ice flow) is substituted by a very cheap CNN emulator. Once trained with representative data, IGM permits to model individual mountain glaciers several orders of magnitude faster than high-order ones on CPU with fidelity levels above 90 % in terms of ice flow solutions leading to nearly identical transient thickness evolution. Switching to Graphics Processing Unit (GPU) permits additional significant speed-ups, especially when modelling large-scale glacier networks and/or high spatial resolutions.In inverse modelling, the substitution by a CNN emulator does not only speed up but facilitates dramatically the data assimilation step, i.e. the search for optimal ice thickness and ice flow parameter spatial distributions that match spatial observations at best (such as ice flow, surface topography or ice thickness profiles) while being consistent with the high-order ice flow mechanics. The reason is that inverting a CNN can take great benefit from the tools used for its training such as automatic differentiation, stochastic gradient methods, and GPU. IGM is an open-source Python code (https://github.com/jouvetg/igm), which deals with two-dimensional gridded input and output data. Together with a companion library of trained ice flow emulators, IGM permits user-friendly, computationally highly-efficient, easy-to-customize, and mechanically state-of-the-art glacier forward and inverse modelling at any scale. We illustrate its potential by replicating a simulation of the great Aletsch Glacier, Switzerland, from 1880 to 2100, based on a Stokes model. The complete workflow (data assimilation and 220 years long forward modelling) at 100 m of resolution takes about 1-2 min on the GPU of a laptop and can be replicated and adapted easily using an online Colab notebook.

The land ice contribution to global mean sea level rise has not yet been predicted 1 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 models 2–8, but primarily used previous-generation scenarios 9 and climate models 10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios 11,12 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.

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.

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.

The Greenland Ice Sheet is the largest land ice contributor to sea level rise. This will continue in the future but at an uncertain rate and observational estimates are limited to the last few decades. Understanding the long-term glacier response to external forcing is key to improving projections. Here we use historical photographs to calculate ice loss from 1880–2012 for Jakobshavn, Helheim, and Kangerlussuaq glacier. We estimate ice loss corresponding to a sea level rise of 8.1 ± 1.1 millimetres from these three glaciers. Projections of mass loss for these glaciers, using the worst-case scenario, Representative Concentration Pathways 8.5, suggest a sea level contribution of 9.1–14.9 mm by 2100. RCP8.5 implies an additional global temperature increase of 3.7 °C by 2100, approximately four times larger than that which has taken place since 1880. We infer that projections forced by RCP8.5 underestimate glacier mass loss which could exceed this worst-case scenario., The Greenland Ice Sheet is the largest land ice contributor to sea level rise and understanding the long-term glacier response to external forcing is key to improved projections. Here the authors show Greenland’s three largest outlet glaciers will likely exceed current worst-case scenario

39 pages, 8 figures, 3 tables.-- Gridded Surface Height Anomalies Version 1801. Ver. 1801 available from NASA JPL PO.DAAC, CA, USA(https://doi.org/10.5067/SLREF-CDRV1). Data are also available through Wiese et al. (2017), Global sea level provides an important indicator of the state of the warming climate, but changes in regional sea level are most relevant for coastal communities around the world. With improvements to the sea‐level observing system, the knowledge of regional sea‐level change has advanced dramatically in recent years. Satellite measurements coupled with in situ observations have allowed for comprehensive study and improved understanding of the diverse set of drivers that lead to variations in sea level in space and time. Despite the advances, gaps in the understanding of contemporary sea‐level change remain and inhibit the ability to predict how the relevant processes may lead to future change. These gaps arise in part due to the complexity of the linkages between the drivers of sea‐level change. Here we review the individual processes which lead to sea‐level change and then describe how they combine and vary regionally. The intent of the paper is to provide an overview of the current state of understanding of the processes that cause regional sea‐level change and to identify and discuss limitations and uncertainty in our understanding of these processes. Areas where the lack of understanding or gaps in knowledge inhibit the ability to provide the needed information for comprehensive planning efforts are of particular focus. Finally, a goal of this paper is to highlight the role of the expanded sea‐level observation network—particularly as related to satellite observations—in the improved scientific understanding of the contributors to regional sea‐level change, The research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The authors acknowledge support from the National Aeronautics and Space Administration under Grants 80NSSC17K0565, 80NSSC170567, 80NSSC17K0566, 80NSSC17K0564, and NNX17AB27G. A. A. acknowledgessupport under GRACE/GRACEFO Science Team Grant (NNH15ZDA001N‐GRACE). T. W. acknowledges support by the National Aeronautics and Space Administration (NASA) under the New (Early Career) Investigator Program in Earth Science (Grant: 80NSSC18K0743). C. G. P was supported by the J. Lamar Worzel Assistant Scientist Fund and the Penzance Endowed Fund in Support of Assistant Scientists at the Woods Hole Oceanographic Institution, With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

Basal motion is the primary mechanism for ice flux in Greenland, yet a widely applicable model for predicting it remains elusive. This is due to the difficulty in both observing small-scale bed properties and predicting a time-varying water pressure on which basal motion putatively depends. We take a Bayesian approach to these problems by coupling models of ice dynamics and subglacial hydrology and conditioning on observations of surface velocity in southwestern Greenland to infer the posterior probability distributions for eight spatially and temporally constant parameters governing the behavior of both the sliding law and hydrologic model. Because the model is computationally expensive, characterization of these distributions using classical Markov Chain Monte Carlo sampling is intractable. We skirt this issue by training a neural network as a surrogate that approximates the model at a sliver of the computational cost. We find that surface velocity observations establish strong constraints on model parameters relative to a prior distribution and also elucidate correlations, while the model explains 60% of observed variance. However, we also find that several distinct configurations of the hydrologic system and stress regime are consistent with observations, underscoring the need for continued data collection and model development.

Most of Earth’s glaciers are retreating, but some tidewater glaciers are advancing despite increasing temperatures and contrary to their neighbors. This can be explained by the coupling of ice and sediment dynamics: a shoal forms at the glacier terminus, reducing ice discharge and causing advance towards an unstable configuration followed by abrupt retreat, in a process known as the tidewater glacier cycle. Here we use a numerical model calibrated with observations to show that interactions between ice flow, glacial erosion, and sediment transport drive these cycles, which occur independent of climate variations. Water availability controls cycle period and amplitude, and enhanced melt from future warming could trigger advance even in glaciers that are steady or retreating, complicating interpretations of glacier response to climate change. The resulting shifts in sediment and meltwater delivery from changes in glacier configuration may impact interpretations of marine sediments, fjord geochemistry, and marine ecosystems., The reason some of the Earth’s tidewater glaciers are advancing despite increasing temperatures is not entirely clear. Here, using a numerical model that simulates both ice and sediment dynamics, the authors show that internal dynamics drive glacier variability independent of climate.

An assessment of past, present and future ice loss from the Greenland ice sheet shows that rates of loss in the twenty‑first century will be much higher than those at any time during the past 11,700 years. Ice-mass loss from the Greenland ice sheet over 12,000 years.

Simulations show that the Greenland Ice Sheet could disappear within a millennium if greenhouse gas emissions continue unabated., The Greenland Ice Sheet holds 7.2 m of sea level equivalent and in recent decades, rising temperatures have led to accelerated mass loss. Current ice margin recession is led by the retreat of outlet glaciers, large rivers of ice ending in narrow fjords that drain the interior. We pair an outlet glacier–resolving ice sheet model with a comprehensive uncertainty quantification to estimate Greenland’s contribution to sea level over the next millennium. We find that Greenland could contribute 5 to 33 cm to sea level by 2100, with discharge from outlet glaciers contributing 8 to 45% of total mass loss. Our analysis shows that uncertainties in projecting mass loss are dominated by uncertainties in climate scenarios and surface processes, whereas uncertainties in calving and frontal melt play a minor role. We project that Greenland will very likely become ice free within a millennium without substantial reductions in greenhouse gas emissions.

Assessing and modeling precipitation in mountainous areas remains a major challenge in glacier mass balance modeling. Observations are typically scarce and reanalysis data and similar climate products are too coarse to accurately capture orographic effects. Here we use the linear theory of orographic precipitation model (LT model) to downscale winter precipitation from the Weather Research and Forecasting Model (WRF) over the Juneau Icefield, one of the largest ice masses in North America (>4,000 km2), for the period 1979–2013. The LT model is physically-based yet computationally efficient, combining airflow dynamics and simple cloud microphysics. The resulting 1 km resolution precipitation fields show substantially reduced precipitation on the northeastern portion of the icefield compared to the southwestern side, a pattern that is not well captured in the coarse resolution (20 km) WRF data. Net snow accumulation derived from the LT model precipitation agrees well with point observations across the icefield. To investigate the robustness of the LT model results, we perform a series of sensitivity experiments varying hydrometeor fall speeds, the horizontal resolution of the underlying grid, and the source of the meteorological forcing data. The resulting normalized spatial precipitation pattern is similar for all sensitivity experiments, but local precipitation amounts vary strongly, with greatest sensitivity to variations in snow fall speed. Results indicate that the LT model has great potential to provide improved spatial patterns of winter precipitation for glacier mass balance modeling purposes in complex terrain, but ground observations are necessary to constrain model parameters to match total amounts.

Model simulations of the Greenland ice sheet contribution to 21st-century sea-level rise are performed with a state-of-the-art ice-sheet model (Parallel Ice Sheet Model (PISM)). The climate-forcing fields are obtained from the European Union’s Seventh Framework Programme project ice2sea, in which three regional climate models are used to dynamically downscale two scenarios (A1B and E1) from two general circulation models (ECHAM5 and HadCM3). To assess the sensitivity of the projections to the model initial state, four initialization methods are applied. In these experiments, the simulated contribution to sea-level rise by 2100 ranges from an equivalent of 0.2 to 6.8 cm. The largest uncertainties arise from different formulations of the regional climate models (0.8–3.9 cm) and applied scenarios (0.65–1.9 cm), but an important source of uncertainty is the initialization method (0.1–0.8 cm). These model simulations do not account for the recently observed acceleration of ice streams and consequent thinning rates, the changing ice discharge that may result from the spatial and temporal variability of ocean forcing, or the feedback occurring between ice-sheet elevation changes and climate forcing. Thus the results should be considered the lower limit of Greenland ice sheet contributions to sea-level rise, until such processes have been integrated into large-scale ice-sheet models.

Recent observations of the Greenland ice sheet indicate rapid mass loss at an accelerating rate with an increasing contribution to global mean sea level. Ice sheet models are used for projections of such future contributions of ice sheets to sea level, but the quality of projections is difficult to measure directly. Realistic initial states are crucial for accurate simulations. To test initial states we use hindcasting, i.e. forcing a model with known or closely-estimated inputs for past events to see how well the output matches observations. By simulating the recent past of Greenland, and comparing to observations of ice thickness, ice discharge, surface speeds, mass loss and surface elevation changes for validation, we find that the short term model response is strongly influenced by the initial state. We show that the dynamical state can be mis-represented despite a good agreement with some observations, stressing the importance of using multiple observations. Some initial states generate good agreement with measured mass time series in the hindcast period, and good agreement with present-day kinematic fields. We suggest hindcasting as a methodology for careful validation of initial states that can be done before making projections on decadal to century time-scales.

Atmospheric, oceanic, and subglacial forcing scenarios from the Sea-level Response to Ice Sheet Evolution (SeaRISE) project are applied to six three-dimensional thermomechanical ice-sheet models to assess Antarctic ice sheet sensitivity over a 500 year timescale and to inform future modeling and field studies. Results indicate (i) growth with warming, except within low-latitude basins (where inland thickening is outpaced by marginal thinning); (ii) mass loss with enhanced sliding (with basins dominated by high driving stresses affected more than basins with low-surface-slope streaming ice); and (iii) mass loss with enhanced ice shelf melting (with changes in West Antarctica dominating the signal due to its marine setting and extensive ice shelves; cf. minimal impact in the Terre Adelie, George V, Oates, and Victoria Land region of East Antarctica). Ice loss due to dynamic changes associated with enhanced sliding and/or sub-shelf melting exceeds the gain due to increased precipitation. Furthermore, differences in results between and within basins as well as the controlling impact of sub-shelf melting on ice dynamics highlight the need for improved understanding of basal conditions, grounding-zone processes, ocean-ice interactions, and the numerical representation of all three.

Ten ice-sheet models are used to study sensitivity of the Greenland and Antarctic ice sheets to prescribed changes of surface mass balance, sub-ice-shelf melting and basal sliding. Results exhibit a large range in projected contributions to sea-level change. In most cases, the ice volume above flotation lost is linearly dependent on the strength of the forcing. Combinations of forcings can be closely approximated by linearly summing the contributions from single forcing experiments, suggesting that nonlinear feedbacks are modest. Our models indicate that Greenland is more sensitive than Antarctica to likely atmospheric changes in temperature and precipitation, while Antarctica is more sensitive to increased ice-shelf basal melting. An experiment approximating the Intergovernmental Panel on Climate Change’s RCP8.5 scenario produces additional first-century contributions to sea level of 22.3 and 8.1 cm from Greenland and Antarctica, respectively, with a range among models of 62 and 14 cm, respectively. By 200 years, projections increase to 53.2 and 26.7 cm, respectively, with ranges of 79 and 43 cm. Linear interpolation of the sensitivity results closely approximates these projections, revealing the relative contributions of the individual forcings on the combined volume change and suggesting that total ice-sheet response to complicated forcings over 200 years can be linearized.

The basal thermal state of an ice sheet (frozen or thawed) is an important control upon its evolution, dynamics and response to external forcings. However, this state can only be observed directly within sparse boreholes or inferred conclusively from the presence of subglacial lakes. Here we synthesize spatially extensive inferences of the basal thermal state of the Greenland Ice Sheet to better constrain this state. Existing inferences include outputs from the eight thermomechanical ice-flow models included in the SeaRISE effort. New remote-sensing inferences of the basal thermal state are derived from Holocene radiostratigraphy, modern surface velocity and MODIS imagery. Both thermomechanical modeling and remote inferences generally agree that the Northeast Greenland Ice Stream and large portions of the southwestern ice-drainage systems are thawed at the bed, whereas the bed beneath the central ice divides, particularly their west-facing slopes, is frozen. Elsewhere, there is poor agreement regarding the basal thermal state. Both models and remote inferences rarely represent the borehole-observed basal thermal state accurately near NorthGRIP and DYE-3. This synthesis identifies a large portion of the Greenland Ice Sheet (about one third by area) where additional observations would most improve knowledge of its overall basal thermal state.

We develop a Bayesian model for estimating ice thickness given sparse observations coupled with estimates of surface mass balance, surface elevation change, and surface velocity. These fields are related through mass conservation. We use the Metropolis-Hastings algorithm to sample from the posterior probability distribution of ice thickness for three cases: a synthetic mountain glacier, Storglaciaren, and Jakobshavn Isbrae. Use of continuity in interpolation improves thickness estimates where relative velocity and surface mass balance errors are small, a condition difficult to maintain in regions of slow flow and surface mass balance near zero. Estimates of thickness uncertainty depend sensitively on spatial correlation. When this structure is known, we suggest a thickness measurement spacing of one to two times the correlation length to take best advantage of continuity based interpolation techniques. To determine ideal measurement spacing, the structure of spatial correlation must be better quantified.

The Greenland Ice Sheet is losing mass at an accelerating rate due to increased surface melt and flow acceleration in outlet glaciers. Quantifying future dynamic contributions to sea level requires accurate portrayal of outlet glaciers in ice sheet simulations, but to date poor knowledge of subglacial topography and limited model resolution have prevented reproduction of complex spatial patterns of outlet flow. Here we combine a high-resolution ice-sheet model coupled to uniformly applied models of subglacial hydrology and basal sliding, and a new subglacial topography data set to simulate the flow of the Greenland Ice Sheet. Flow patterns of many outlet glaciers are well captured, illustrating fundamental commonalities in outlet glacier flow and highlighting the importance of efforts to map subglacial topography. Success in reproducing present day flow patterns shows the potential for prognostic modelling of ice sheets without the need for spatially varying parameters with uncertain time evolution., Quantifying Greenland's future contribution to sea level requires accurate portrayal of its outlet glaciers in ice sheet simulations. Here, the authors show that outlet glacier flow can be captured if ice thickness is well constrained and vertical shearing as well as membrane stresses are included in the model.

Polythermal conditions are ubiquitous among glaciers, from small valley glaciers to ice sheets. Conventional temperature-based ‘cold-ice’ models of such ice masses cannot account for that portion of the internal energy which is latent heat of liquid water within temperate ice, so such schemes are not energy-conserving when temperate ice is present. Temperature and liquid water fraction are, however, functions of a single enthalpy variable: a small enthalpy change in cold ice is a change in temperature, while a small enthalpy change in temperate ice is a change in liquid water fraction. The unified enthalpy formulation described here models the mass and energy balance for the threedimensional ice fluid, for the surface runoff layer and for the subglacial hydrology layer, together in a single energy-conserving theoretical framework. It is implemented in the Parallel Ice Sheet Model. Results for the Greenland ice sheet are compared with those from a cold-ice scheme. This paper is intended to be an accessible foundation for enthalpy formulations in glaciology.

Observations over the past two decades show substantial ice loss associated with the speedup of marine terminating glaciers in Greenland. Here we use a regional 3-D outlet glacier model to simulate the behaviour of Jakobshavn Isbræ (JI) located in west Greenland. Using atmospheric and oceanic forcing we tune our model to reproduce the observed frontal changes of JI during 1990–2014. We identify two major accelerations. The first occurs in 1998, and is triggered by moderate thinning prior to 1998. The second acceleration, which starts in 2003 and peaks in summer 2004, is triggered by the final breakup of the floating tongue, which generates a reduction in buttressing at the JI terminus. This results in further thinning, and as the slope steepens inland, sustained high velocities have been observed at JI over the last decade. As opposed to other regions on the Greenland Ice Sheet (GrIS), where dynamically induced mass loss has slowed down over recent years, both modelled and observed results for JI suggest a continuation of the acceleration in mass loss. Further, we find that our model is not able to capture the 2012 peak in the observed velocities. Our analysis suggests that the 2012 acceleration of JI is likely the result of an exceptionally long melt season dominated by extreme melt events. Considering that such extreme surface melt events are expected to intensify in the future, our findings suggest that the 21st century projections of the GrIS mass loss and the future sea level rise may be larger than predicted by existing modelling results.

Greenland’s main outlet glaciers have more than doubled their contribution to global sea‐level rise over the past decade through acceleration of ice discharge. Jakobshavn Isbræ (JI) in west Greenland is the largest outlet glacier in terms of drainage area. Here we use a 3-D modeling approach to study the mechanisms controlling dynamic changes at the terminus of JI over a period of 220 years. Over 100 simulations are performed with different sets of parameters where the calving fronts and the grounding lines are free to evolve in time under atmospheric and oceanic forcing. We find that the thinning and the retreat that starts at the calving front and then propagates upstream is mostly controlled by a loss of resistive stresses at the terminus through glacier dynamics induced calving rather than by changes in oceanic temperatures. Three major accelerations are identified in 1928, 1998 and in the summer of 2003. The acceleration which started in 1928 slowly faded by 1948, while the accelerations in 1998 and 2003 sustain the high velocities observed at JI in the last decade. Further, we find that under atmospheric RCP 4.5 and RCP 8.5 forcing (no RCP ocean forcing included), an increase in ocean temperatures of just 0.7 °C (relative to 1880-2012) is enough to trigger a collapse of the JI’s southern tributary by 2050 which further destabilizes JI and unleashes a major glacial collapse of ~25 km. JI’s contribution to SLR is found to be ~2.8 mm (~1014 Gt) for the period 1880 to 2014, from which the contribution between 1997 to 2014 represents 27 %. By the end of the century contributions to SLR as high as ~11 mm (~4000 Gt under RCP 8.5 and almost 300% increase relative to 1880-2014) can be expected from Jakobshavn Isbræ only. Our choice of ice sheet model comprises the Parallel Ice Sheet Model (PISM).