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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 models2-8, 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.

Beyond the impact of glacial isostatic adjustment, landscape evolution is typically neglected at large scale when considering the basal boundary condition for ice sheet and climate modelling over past glacial cycles. Erosion and changing sediment loads impact bed elevation, land/sea mask, and basal drag. To date, how the above affects past ice sheet evolution is unclear. Constraining the role that Pliocene regolith may have played in Pleistocene glacial cycle variability requires bounds on the amount of regolith preceding those glacial cycles. However, quantitative bounds on regolith thickness at the spatial scale of the glaciated regions of North America are currently absent in the literature. To address the above, we present an updated sediment production and transport model with dynamically calculated soft sediment mask, isostatic adjustment to dynamical sediment load and bedrock erosion, and a new subglacial hydrology model coupled to the Glacial Systems Model. The coupled model is capable of multi-million year integrations driven only by greenhouse gas concentration and insolation. The model passes a set of verification tests and conserves mass. We assess parametric sensitivity of sediment transport rates. We compare the final sediment solutions in an ensemble of whole-Pleistocene simulations for a range of initial (Pliocene) regolith thicknesses against multiple estimates for present day drift thickness distribution, Quaternary sediment volume in the Atlantic Ocean, and erosion depth estimates. Consistency of modelling and data constraints requires a Pliocene regolith thickness of less than 50 m. [ABSTRACT FROM AUTHOR]

Despite their recognized significance on global climate and extensive research efforts, the mechanism(s) driving Heinrich Events remain(s) a subject of debate. Here, we use the 3D thermo-mechanically coupled Glacial Systems Model (GSM) to examine Hudson Strait ice stream surge cycling as well as the role of 3 factors previously hypothesized to play a critical role in Heinrich events: ice shelves, glacial isostatic adjustment, and sub-surface ocean temperature forcings. In contrast to all previous modeling studies examining HEs, the GSM uses a transient last glacial cycle climate forcing, global visco-elastic glacial isostatic adjustment model, and sub-glacial hydrology model. The results presented here are based on a high-variance sub-ensemble retrieved from North American history matching for the last glacial cycle. Over our comparatively wide sampling of the potential parameter space (52 ensemble parameters for climate forcing and process uncertainties), we find two modes of Hudson Strait ice streaming: classic binge-purge versus near continuous ice streaming with occasional shutdowns and subsequent surge onset overshoot. Our model results indicate that large ice shelves covering the Labrador Sea during the last glacial cycle only occur when extreme calving restrictions are applied. The otherwise minor ice shelves provide insignificant buttressing for the Hudson Strait ice stream. While sub-surface ocean temperature forcing leads to minor differences regarding surge characteristics, glacial isostatic adjustment does have a significant impact. Given input uncertainties, the strongest controls on ice stream surge cycling are the poorly constrained deep geothermal heat flux under Hudson Bay and Hudson Strait and the basal drag law. Decreasing the geothermal heat flux within available constraints and/or using a Coulomb sliding law instead of a Weertman-type power law leads to a shift from the near-continuous streaming mode to the binge-purge mode. [ABSTRACT FROM AUTHOR]

The Marine Isotope Stage 11c (MIS-11c) interglacial is an enigmatic period characterized by a long duration of relatively weak insolation forcing, but it is thought to have been coincident with a large global sea-level rise of 6–13 m. The configuration of the Greenland Ice Sheet during the MIS-11c interglacial highstand is therefore of great interest. Given the constraints of limited data, model-based analysis may be of use but only if model uncertainties are adequately accounted for. A particularly under-addressed issue in coupled climate and ice-sheet modeling is the coupling of surface air temperatures to the ice model. Many studies apply a uniform "lapse rate" accounting for the temperature differences at different altitudes over the ice surface, but this uniformity neglects both regional and seasonal differences in near-surface temperature dependencies on altitude. Herein we provide the first such analysis for MIS-11c Greenland that addresses these uncertainties by comparing one-way coupled Community Earth System Model (CESM) and ice-sheet model results from several different downscaling methodologies. In our study, a spatially and temporally varying temperature downscaling method produced the greatest success rate in matching the constraints of limited paleodata, and it suggests a peak ice volume loss from Greenland during MIS-11c of approximately 50 % compared to present day (∼ 3.9 m contribution to sea-level rise). This result is on the lower bound of existing data- and model-based studies, partly as a consequence of the applied one-way coupling methodology that neglects some feedbacks. Additional uncertainties are examined by comparing two different present-day regional climate analyses for bias correction of temperatures and precipitation, a spread of initialization states and times, and different spatial configurations of precipitation bias corrections. No other factor exhibited greater influence over the simulated Greenland ice sheet than the choice of temperature downscaling scheme. [ABSTRACT FROM AUTHOR]

While subglacial hydrology is known to play a role in glacial dynamics on sub-annual to decadal scales, it remains unclear whether subglacial hydrology plays a critical role in ice sheet evolution on centennial or longer timescales. Furthermore, several drainage systems have been inferred, but it is unclear which is most applicable at the continental/glacial scale. More fundamentally, it is even unclear if the structural choice of subglacial hydrology truly matters for this context. Here we compare the contribution to the surge behaviour of an idealized Hudson Strait-like ice stream from three subglacial hydrology systems. We use the newly updated BAsal Hydrology Model – BrAHMs2.0 – and provide model verification tests. BrAHMs2.0 incorporates two process-based representations of inefficient drainage dominant in the literature (linked cavity and poro-elastic) and a non-mass-conserving zero-dimensional form (herein termed leaky bucket) coupled to an ice sheet systems model (the Glacial Systems Model, GSM). The linked-cavity and poro-elastic configurations include an efficient drainage scheme while the leaky bucket does not. All three systems have a positive feedback on ice velocity, whereby faster basal velocities increase melt supply. The poro-elastic and leaky-bucket systems have diagnostic effective pressure relationships – only the linked-cavity system has an additional negative feedback, whereby faster basal ice velocities increase the dynamical effective pressure due to higher cavity opening rates. We examine the contribution of mass transport, efficient drainage, and the linked-cavity negative feedback to surging. We also assess the likely bounds on poorly constrained subglacial hydrology parameters and adopt an ensemble approach to study their impact and interactions within those bounds. We find that subglacial hydrology is an important system inductance for realistic ice stream surging but that the three formulations all exhibit similar surge behaviour within parametric uncertainties. Even a detail as fundamental as mass-conserving transport of subglacial water is not necessary for simulating a full range of surge frequency and amplitude. However, one difference is apparent: the combined positive and negative feedbacks of the linked-cavity system yield longer duration surges and a broader range of effective pressures than its poro-elastic and leaky-bucket counterparts. [ABSTRACT FROM AUTHOR]

Models of glacial isostatic adjustment (GIA) play a central role in the interpretation of various geologic and geodetic data to understand and simulate past and future changes in ice sheets and sea level, and infer rheological properties of the deep Earth. A relatively recent advance has been the development of models that include 3D Earth structure, as opposed to 1D, spherically symmetric structure. However, a major limitation in employing 3D GIA models is their high computational expense. As such, we have developed a method using artificial neural networks (ANNs) and the Tensorflow library to emulate the influence of 3D Earth models with the goal of more affordably constraining the parameter space of these models: specifically the radial (1D) viscosity profile upon which the lateral variations are added. This study provides an initial "proof of concept" assessment of using ANNs to emulate the influence of lateral Earth structure on GIA model output. Our goal is to test whether the fast surrogate model can accurately predict the difference in these outputs (i.e., RSL and uplift rates) for the 3D case relative to the SS case. If so, the surrogate model can be used with a computationally efficient SS (Earth) GIA model to generate output that reproduces output from a 3D (Earth) GIA model. Evaluation of the surrogate model performance for deglacial RSL indicates that it is able to provide useful estimates of this field throughout the parameter space when trained on only ≈ 15 % (≈ 50) of the parameter vectors considered (330 in total). Our results indicate that the ANN:model misfits, while not negligible, are of a scale such that useful predictions of deglacial RSL changes can be made. We applied the surrogate model in a model:data comparison exercise using RSL data distributed along the North American coasts from the Canadian Arctic to the US Gulf coast. We find that the surrogate model is able to successfully reproduce the data:model misfit values such that the region of minimum misfit either overlaps the 3D GIA model results, or is within two increments in the parameter space. The surrogate model can, therefore, be used to accurately explore this aspect of the 3D Earth model parameter space. While the 3D Earth models can outperform the SS Earth models for some regional subsets of the RSL data set, the SS Earth models still produce better fits overall. In summary, this work demonstrates the utility of machine learning in 3D Earth GIA modelling and so future work to expand on this analysis is warranted. [ABSTRACT FROM AUTHOR]

Freshwater, in the form of terrestrial runoff, is hypothesized to have played a critical role in past centennial to millennial scale climate variability by suppressing the production of deep-water in the North Atlantic. It may also play a central role in future climate change as ice sheet and glacier melt accelerates under anthropogenic climate change. In model studies of both past and future climate change, freshwater Hosing (i.e. injection across wide bands in the North Atlantic) is typically used as a means-to-an-end by inducing a strong thermohaline circulation and climate response, with little regard for the other roles that freshwater plays in a complex coupled climate environment. Herein, we evaluate the realism of Hosing relative to two more sophisticated freshwater injection methods, all under glacial boundary conditions: regional injection (allowing the relatively coarse-resolution climate model to transport the freshwater) and a novel freshwater fingerprint method. The latter approach distributes freshwater into an eddy-parametrizing ocean model based upon where it is transported to in a higher resolution eddy-permitting model. Here the COSMOS Earth system model is used as the eddy-parametrizing model, and a configuration of the MITgcm model as the eddy-permitting model. This analysis address three primary questions. Firstly, where is freshwater routed at moderate versus eddy-permitting resolution? Secondly, does the freshwater fingerprint method allow the coarser resolution model to reproduce the net-results of eddy-permitting behaviour? Thirdly, how do climate impacts vary between different forms of freshwater injection? Of the four outlets tested, we find that freshwater released at the Mackenzie River (MAK) outlet results in the most similar freshwater transport patterns at both the eddy-parametrizing and the eddy-permitting resolutions. However at eddy-permitting resolution there is a greater freshening of the contemporary Labrador Sea deep water formation region and mixing of freshwater into the Icelandic Sea. Similarly, Fennoscandian (FEN) freshwater discharge at eddy-permitting resolution results in more freshening of the Greenland-Iceland-Norwegian (GIN) Seas. Freshwater released from within the Gulf of St. Lawrence (GSL) demonstrates large-scale differences between coarse-resolution versus eddy-permitting distributions over the whole North Atlantic. At eddy-permitting resolution, GSL-sourced freshwater freshens the North Atlantic (specifically deep water formation regions important during cold glacial periods) more effectively than at eddy-parametrizing resolution. In COSMOS, freshwater deposited into the GOM results in a larger salinity anomaly at sites of deep-water formation in the northern North Atlantic than freshwater deposited into the GSL, whereas this relationship is reversed in MITgcm. When instead the freshwater fingerprint method is used in COSMOS, the relative strengths of GOM and GSL salinity anomalies in this deep-water formation region align with the eddy-permitting responses. However, for all injection locations considered, the pattern of MITgcm salinity anomalies are best matched by the COSMOS regional injection simulations and not the fingerprint injection simulations. Hosing the North Atlantic in COSMOS results in stronger and earlier sea ice growth and surface cooling versus either regional injection or the fingerprint methods. Comparing regional injections to their respective fingerprint counterparts, injecting freshwater at the outlets results in earlier, but not faster, climate changes in the GIN Seas, mainland Europe, and GRIP ice core regions for the MAK and FEN regions relative to the fingerprint methods. For these injections, regional simulations show both a stronger and faster initial AMOC reduction than the fingerprint simulations. In short, for at least the COSMOS model, both the hosing and fingerprint methodologies are inferior to regional injection when considering salinity distributions alone but when considering AMOC and freshening of deep-water formation regions the fingerprint method corrects the response of the GSL and GOM outlets. [ABSTRACT FROM AUTHOR]