Isabel Nias

Iceberg calving from tidewater glaciers has contributed more than half of the total mass loss of the Greenland Ice Sheet over the past four decades, and observations have shown that episodes of increased iceberg discharge have coincided with rising air temperatures and/or the occurrence of warmer coastal waters into fjords within which they discharge. Despite significant advances in understanding over the last two decades, major uncertainties still remain in understanding how sensitive iceberg calving rates are to climate-induced exchanges of heat and freshwater around marine terminating ice sheet margins. This is partly because we do not know the long-term, multi-decadal to centuries historical context of the ice-ocean system that links our understanding of contemporary process with longer term glacier response to climate. In this study, we use the Ice-sheet and Sea-level System Model (ISSM) to simulate the advance and retreat of a fast-flowing tidewater glacier in southwest Greenland, Kangiata Nunata Sermia, over the last 1000 years to indentify the drivers of advance and retreat and evaluate calving-parameter choices against observed long-term ice-margin variability. While models have successfully reproduced observed recent retreat, their parameters are rarely tested against centennial- to millennial-scale records of advance. We explore the parameter space governing calving-front advance, focusing on submarine melt rates and von Mises calving-law stress thresholds for grounded and floating ice and validate model ensembles against a well-constrained millennial-scale record of advance and retreat. Using Latin Hypercube Sampling, we assess two criteria: whether the calving front advances at all, and whether it can reach the reconstructed Little Ice Age (LIA) position. We find that advance can occur across the full tested range of submarine melt rates, up to 1.5 m d⁻¹. However, successful advance to the LIA position is more tightly constrained by the von Mises stress thresholds. In several simulations, the calving front advances only as far as a widening in the fjord, unless the calving rate is reduced by setting a sufficiently high stress thresholds. Our results highlight a strong interaction between calving physics and fjord geometry in controlling long-term advance. This project contributes to improving confidence in multi-decadal to centennial projections of ice sheet behaviour through validating model performance over similar timescales including prolonged episodes of both glacier advance and retreat.

50% of mass loss from the Greenland Ice Sheet in recent decades is due to calving from tidewater glaciers (TWG). However, the relationship between climate and calving remains uncertain. While calving parameters in glacier models can replicate observed glacier retreat, they need validation against longer-term records of ice margin advance and retreat. By contextualizing both the advance and retreat of a Greenlandic TWG, Kangiata Nunaata Sermia, KNS, over centennial to millennial timescales, we can minimize the impact of short-term climate variations and assess if modelled climate-glacier interactions are biased toward retreat due to processes operating over decadal timescales. Our model is validated against a well-constrained millennial-scale record of advance and retreat from a fast-flowing TWG in southwest Greenland. Our key research questions are: How do calving laws perform when modelling the advance of a grounded Greenlandic TWG? And how do calving law tuning parameters relate to physical processes, such as climate and fjord geometry? By comparing four calving laws and exploring a physical basis for glacier-specific tunning, we aim to better constrain calving fronts in glacier models and improve the capacity for predictive calving modelling.A previous Greenland wide study suggested that the von Mises law better replicates decadal retreat, but our results show it lacks sensitivity to advance and, to avoid numerical instability, requires transient tuning for retreat. We further investigate the sensitivity of other calving laws, including eigen calving, height-above-buoyancy, and crevasse-water-depth.

Subglacial lakes beneath the Antarctic Ice Sheet were first identified using airborne radio-echo sounding (RES) surveys from the 1960s. In Antarctica, 20% of 675 currently identified subglacial lakes are “active,” exhibiting draining and filling behaviour as water flows through them. Clusters of active subglacial lakes often form in networks, connected by subglacial hydrological pathways which enable transfer of water between lakes themselves. Signals of this hydrological activity at the ice base can be detected in height changes at the ice sheet surface. Despite efforts to observe and understand this component of ice sheet mechanics, triggers of lake drainage events, in addition to drainage mechanisms and their variability are currently unresolved. An ongoing challenge lies in accurately identifying the location and extent of subglacial lakes.We present a new dataset of locations and boundaries for over 100 newly identified subglacial lakes in Antarctica. Using 10 years of CryoSat-2 swath-processed altimetry data, from 2011-2021, we identify localised regions of ice surface uplift and subsidence associated with subglacial lake filling and draining cycles. We use a new method to manually delineate subglacial lake maximum extent boundaries for individual filling and drainage periods. These results provide insights into new areas of subglacial hydrological activity in Antarctica and their evolution over time, which are vital to resolve in order to understand their impacts on Antarctic Ice Sheet stability.

The fate of percolating surface meltwater encountering ‘impermeable’ ice layers is uncertain in the accumulation zone of the Greenland Ice Sheet (GrIS). Often, ice layers are considered to retard meltwater and cause lateral runoff. However, modelled and field-based observations in the percolation zone of the GrIS have suggested ice layers are not necessarily impermeable and meltwater can breakthrough, percolating to deeper depths of snow/firn and consequently inferring a greater refreezing capacity within the accumulation zone. The physical and thermal conditions which control the permeability of ice layers remain unclear and effective parameterisation of these processes is lacking for snow/firn modelling of melt, refreezing and runoff. Here we present repeat cold-laboratory experiments which seek to understand how meltwater interacts with thin ice layers (5 to 20 mm) for two differing thermal regime contexts whereby the surrounding snow/firn thermal regime is either (i) below or (ii) at the melting point.We find that under extreme melt regimes, ice layers continually retard wetted fronts of percolating meltwater when the thermal regime of the snowpack is below the melting point. This barrier results in the snowpack at depth remaining at least ~1oC cooler than snow above the ice layer which is saturated with meltwater. We also find that the ice layer forces ~35% of the percolating meltwater to runoff, cooling the overlying snow and increasing the refreezing capacity of the snow closer to the snowpack surface. The remaining ~65% of meltwater ponds and later refreezes on the ice layer, thickening the impenetrable surface.When the thermal regime of the surrounding snow/firn is at the melting point, we find that meltwater is able to pond without refreezing, resulting in the ice layer failing and allowing deeper percolation into the snowpack. These findings suggest that the thermal regime of a snowpack is crucial for the structural integrity of an ice layer and thus the permeability of a snowpack.Consequently, these findings have implications for parameterising meltwater runoff and ice layer integrity in snow and firn models which incorporate ‘impermeable’ barriers in their domains. Future work will continue to explore similar experiments with thicker ice layers (~60 mm) to determine whether ice layer breakthrough is primarily a function of snow/firn thermal regime and/or ice layer thickness.

Mass loss from the Antarctic and Greenland Ice Sheets could lead to a rise in global mean sea level of 0.25 m by 2100 and several metres by 2300 if greenhouse gas emissions remain unmitigated. Uncertainties in these estimates are strongly related to ocean-driven ice melt, which can lead to grounding line retreat, thinning and acceleration of the fast-flowing regions of both Antarctica and Greenland. The processes of ocean-driven ice melt on large spatial and temporal scales are imperfectly known, and measurements are sparse, impacting the accuracy of ice sheet and ocean model projection studies. The Joint Commission on Ice-Ocean Interactions (JCIOI) hosted the first community workshop in October 2022 with the aims to: (1) identify critical knowledge gaps surrounding processes that govern ocean-driven melt of ice sheets across a range of spatio-temporal scales; and (2) identify options to address the knowledge gaps through observing, parameterising, and modelling ice-ocean interactions, and their impacts on ice mass loss and ocean dynamics. Community discussions from the workshop highlighted the need for concurrent and sustained measurements of ice, ocean and atmosphere properties at the ice sheet-ocean interface, and making best use of existing observations to improve models, capture observed changes, better understand physical mechanisms and improve future projections. Building on the workshop outputs, we propose to develop a framework for ice-ocean observations that details the essential measurements that need to be collected, and the temporal and spatial scales on which to measure. This framework will require widespread community engagement on key scientific questions, agreement and coordination, including protocols for data collection, processing, and sharing.

Determining reliable probability distributions for ice sheet mass change over the coming century is critical to refining uncertainties in sea-level rise projections. Bayesian calibration, a method for constraining projection uncertainty using observations, has been previously applied to ice sheet projections but the impact of the chosen observation type on the calibrated posterior probability distributions has not been quantified. Here, we perform three separate Bayesian calibrations to constrain uncertainty in Greenland Ice Sheet (GrIS) simulations of the committed mass loss in 2100 under the current climate, using observations of velocity change, dynamic ice thickness change, and mass change. Comparing the posterior probability distributions shows that the median ice sheet mass change can differ by 119 % for the particular model ensemble that we used, depending on the observation type used in the calibration. More importantly for risk-averse sea-level planning, posterior probabilities of high-end mass change scenarios are highly sensitive to the observation selected for calibration. Furthermore, we show that using mass change observations alone may result in model simulations that overestimate flow acceleration and underestimate dynamic thinning around the margin of the ice sheet. Finally, we look ahead and present ideas for ways to improve Bayesian calibration of ice sheet projections.

Determining reliable probability distributions for ice sheet mass change over the coming century is critical to improving uncertainties in sea-level rise projections. Bayesian calibration, a method for constraining projection uncertainty using observations, has been previously applied to ice sheet projections but the impact of the chosen observation type on the calibrated posterior probability distributions has not been quantified. Here, we perform three separate Bayesian calibrations to constrain uncertainty in Greenland Ice Sheet projections using observations of velocity change, dynamic thickness change, and mass change. Comparing the posterior probability distributions shows that the maximum a posteriori ice sheet mass change can differ by 130 % for the particular model ensemble that we used, depending on the observation type used in the calibration. More importantly for risk-averse sea level planning, posterior probabilities of high-end mass change scenarios are highly sensitive to the observation selected for calibration. Finally, we show that using mass change observations alone may result in projections that overestimate flow acceleration and underestimate dynamic thinning around the margin of the ice sheet.

Determining reliable probability distributions for ice sheet mass change over the coming century is critical to improving uncertainties in sea-level rise projections. Bayesian calibration, a method for constraining projection uncertainty using observations, has been previously applied to ice sheet projections but the impact of the chosen observation type on the calibrated posterior probability distributions has not been quantified. Here, we perform three separate Bayesian calibrations to constrain uncertainty in Greenland Ice Sheet projections using observations of velocity change, dynamic thickness change, and mass change. Comparing the posterior probability distributions shows that the maximum a posteriori ice sheet mass change can differ by 130 % for the particular model ensemble that we used, depending on the observation type used in the calibration. More importantly for risk-averse sea level planning, posterior probabilities of high-end mass change scenarios are highly sensitive to the observation selected for calibration. Finally, we show that using mass change observations alone may result in projections that overestimate flow acceleration and underestimate dynamic thinning around the margin of the ice sheet.

Mass loss from the Greenland Ice Sheet can be partitioned between surface mass balance and discharge due to ice dynamics through its marine‐terminating outlet glaciers. A perturbation to a glacier terminus (e.g., a calving event) results in both an instantaneous response in velocity and mass loss and a diffusive response due to the evolution of ice thickness over time. This diffusive response means the total impact of a retreat event can take decades to be fully realized. Here we model the committed response of the Greenland Ice Sheet by applying perturbations to the marine‐terminating glacier termini that represent recent observed changes, and simulating the response over the 21st century, while holding the climate forcing constant. The sensitivity of the ice sheet response to model parameter uncertainty is explored within an ensemble framework, and Gravity Recovery and Climate Experiment data is used to constrain the results using a Bayesian calibration approach. We find that the Greenland Ice Sheet's committed contribution to 21st century sea level rise is at least 33.5 [17.5 52.4] mm (25th and 75th percentiles in brackets), with at least 6 mm being attributable directly to terminus retreat that occurred between 2007 and 2015. The spread in our projections is driven by uncertainty in the basal friction coefficient. Our results complement the ISMIP6 Greenland projections, which report the ice sheet response to future forcing, excluding the background response. In this way, we can obtain estimates of Greenland's total contribution to sea level rise in 2100.

Determining reliable probability distributions for ice sheet mass change over the coming century is critical to improving uncertainties in sea-level rise projections. Bayesian calibration, a method for constraining projection uncertainty using observations, has been previously applied to ice sheet projections but the impact of the chosen observation type on the calibrated posterior probability distributions has not been quantified. Here, we perform three separate Bayesian calibrations to constrain uncertainty in Greenland Ice Sheet projections using observations of velocity change, dynamic thickness change, and mass change. Comparing the posterior probability distributions shows that the maximum a posteriori ice sheet mass change can differ by 130 % for the particular model ensemble that we used, depending on the observation type used in the calibration. More importantly for risk-averse sea level planning, posterior probabilities of high-end mass change scenarios are highly sensitive to the observation selected for calibration. Finally, we show that using mass change observations alone may result in projections that overestimate flow acceleration and underestimate dynamic thinning around the margin of the ice sheet.