Helheim Glacier Research Articles

Velocity of Greenland's Helheim Glacier Controlled Both by Terminus Effects and Subglacial Hydrology With Distinct Realms of Influence

AbstractTwo outstanding questions for the future of the Greenland Ice Sheet are (a) how enhanced meltwater draining beneath the ice will impact the behavior of large tidewater glaciers, and (b) to what extent tidewater glacier velocity is driven by changes at the terminus versus changes in sliding velocity due to meltwater. We present a two‐way coupled framework to simulate the nonlinear feedbacks of evolving subglacial hydrology and ice dynamics using the Subglacial Hydrology And Kinetic, Transient Interactions (SHAKTI) model within the Ice‐sheet and Sea‐level System Model (ISSM). Through coupled simulations of Helheim Glacier, we find that terminus effects dominate the seasonal velocity pattern up to 15 km from the terminus, while hydrology drives the velocity response upstream. With increased melt, the hydrology influence yields seasonal acceleration of several hundred meters per year in the interior, suggesting that hydrology will play an important role in future mass balance of tidewater glaciers.

Forward and Inverse Modeling of Ice Sheet Flow Using Physics‐Informed Neural Networks: Application to Helheim Glacier, Greenland

AbstractPredicting the future contribution of the ice sheets to sea level rise over the next decades presents several challenges due to a poor understanding of critical boundary conditions, such as basal sliding. Traditional numerical models often rely on data assimilation methods to infer spatially variable friction coefficients by solving an inverse problem, given an empirical friction law. However, these approaches are not versatile, as they sometimes demand extensive code development efforts when integrating new physics into the model. Furthermore, this approach makes it difficult to handle sparse data effectively. To tackle these challenges, we use the Physics‐Informed Neural Networks (PINNs) to seamlessly integrate observational data and governing equations of ice flow into a unified loss function, facilitating the solution of both forward and inverse problems within the same framework. We illustrate the versatility of this approach by applying the framework to two‐dimensional problems on the Helheim Glacier in southeast Greenland. By systematically concealing one variable (e.g., ice speed, ice thickness, etc.), we demonstrate the ability of PINNs to accurately reconstruct hidden information. Furthermore, we extend this application to address a challenging mixed inversion problem. We show how PINNs are capable of inferring the basal friction coefficient while simultaneously filling gaps in the sparsely observed ice thickness. This unified framework offers a promising avenue to enhance the predictive capabilities of ice sheet models, reducing uncertainties, and advancing our understanding of poorly constrained physical processes.

Tidally Modulated Glacial Slip and Tremor at Helheim Glacier, Greenland

AbstractNumerical modeling of ice sheet motion and hence projections of global sea level rise require information about the evolving subglacial environment, which unfortunately remains largely unknown due to its difficulty of access. Here we advance such subglacial observations by reporting multi‐year observations of seismic tremor likely associated with glacier sliding at Helheim Glacier. This association is confirmed by correlation analysis between tremor power and multiple environmental forcings on different timescales. Variations of the observed tremor power indicate that different factors affect glacial sliding on different timescales. Effective pressure may control glacial sliding on long (seasonal/annual) timescales, while tidal forcing modulates the sliding rate and tremor power on short (hourly/daily) timescales. Polarization results suggest that the tremor source comes from an upstream subglacial ridge. This observation provides insights on how different factors should be included in ice sheet modeling and how their timescales of variability play an essential role.

Alongshore Winds Force Warm Atlantic Water Toward Helheim Glacier in Southeast Greenland

AbstractEnhanced transport of warm subsurface Atlantic Water (AW) into Greenland fjords has driven glacier mass loss, but the mechanisms transporting AW to the fjords remain poorly characterized. Here, we provide the first direct satellite‐based observations of rapid (∼0.2 m/s) AW intrusion toward Sermilik Fjord abutting Helheim Glacier, one of Greenland's largest glaciers. The intrusions arise when coastal upwelling—through interactions with Sermilik's bathymetric trough on the continental shelf—triggers enhanced AW upwelling and inflow that can travel tens of kilometers along the trough within hours. A weakening or reversal of northeasterly alongshore winds stimulates the intrusions and is often associated with the passing of cyclones and subsequent sea surface lowering. Mooring data show that these intrusions produce subsurface ocean warming both at Sermilik Fjord mouth and within the fjord and that the warming signal in the fjord does not diminish during subsequent coastal downwelling events. Satellite imagery captures near‐synchronous AW intrusions at multiple troughs rimming southeast Greenland suggesting that these wind‐driven processes may play a substantial role in ocean heat transport toward the Greenland Ice Sheet.

Seasonal Flow Types of Glaciers in Sermilik Fjord, Greenland, Over 2016–2021

AbstractGreenland glaciers have three primary seasonal ice flow patterns, or “types”: terminus‐driven, runoff‐driven, and runoff‐adapting. To date, glacier types have been identified by analyzing flow at a single location near the terminus; information at all other locations is discarded. Here, we use principal component (PC)/empirical orthogonal function (EOF) analysis to decompose multi‐year time series of glacier speed, combined from three satellite‐derived products at four glaciers feeding Sermilik Fjord, Greenland. This improves on single‐point methods by yielding spatial patterns (EOFs), which ensure the result reflects data at all locations on the glacier, and associated temporal patterns (PCs), which allow identification of glacier type. We find that the leading EOF is uniformly signed over the entire glacier domain, that this mode explains the majority of the variance in speed, and therefore that glacier type can be inferred from the leading PC. We find that Helheim Glacier was terminus‐driven, Fenris Glacier and Midgard Glacier were runoff‐adapting, and Pourquoi Pas Glacier was runoff‐driven over 2016–2021. Our classification agrees with previous work for Helheim and Midgard Glaciers, but differs at the other two. At all but Fenris Glacier, the leading PC correlates significantly with the speed pattern observed at the single point used in previous analyses. Thus, Fenris Glacier has more complex flow patterns than single‐point analysis can capture, and wider spatial analysis techniques such as EOF/PC are required. We suggest that, due to its low computational cost and inclusion in standard analysis packages, EOF/PC analysis should be used for assessing glacier type.

Subglacial hydrology modeling predicts high winter water pressure and spatially variable transmissivity at Helheim Glacier, Greenland

AbstractWater pressure beneath glaciers influences ice velocity. Subglacial hydrology models are helpful for gaining insight into basal conditions, but models depend on unconstrained parameters, and a current challenge is reproducing elevated water pressures in winter. We eliminate terms related to englacial storage, opening by sliding, and melt due to changes in the pressure-melting-point temperature, to create a minimalist version of the Subglacial Hydrology And Kinetic, Transient Interactions (SHAKTI) model, and apply this model to Helheim Glacier in east Greenland to explore the winter base state of the subglacial drainage system. Our results suggest that meltwater produced at the bed alone supports active winter drainage with large areas of elevated water pressure and preferential drainage pathways, using a continuum approach that allows for transitions between flow regimes. Transmissivity varies spatially over several orders of magnitude from 10−4to 103m2s−1, with regions of weak transmissivity representing poorly connected regions of the system. Bed topography controls the location of primary drainage pathways, and high basal melt rates occur along the steep valley walls. Frictional heat from sliding is a dominant source of basal melt; different approaches for calculating basal shear stress produce significantly different basal melt rates and subglacial discharge.

The control of short-term ice mélange weakening episodes on calving activity at major Greenland outlet glaciers

Abstract. The dense mixture of iceberg of various sizes and sea ice observed in many of Greenland's fjords, called ice mélange (sikussak in Greenlandic), has been shown to have a significant impact on the dynamics of several Greenland tidewater glaciers, mainly through the seasonal support it provides to the glacier terminus in winter. However, a clear understanding of shorter-term ice mélange dynamics is still lacking, mainly due to the high complexity and variability of the processes at play at the ice–ocean boundary. In this study, we use a combination of Sentinel-1 radar and Sentinel-2 optical satellite imagery to investigate in detail intra-seasonal ice mélange dynamics and its link to calving activity at three major outlet glaciers: Kangerdlugssuaq Glacier, Helheim Glacier and Sermeq Kujalleq in Kangia (Jakobshavn Isbræ). In those fjords, we identified recurrent ice mélange weakening (IMW) episodes consisting of the up-fjord propagation of a discontinuity between jam-packed and weaker ice mélange towards the glacier terminus. At a late stage, i.e., when the IMW front approaches the glacier terminus, these episodes were often correlated with the occurrence of large-scale calving events. The IMW process is particularly visible at the front of Kangerdlugssuaq Glacier and presents a cyclic behavior, such that we further analyzed IMW dynamics during the June–November period from 2018 to 2021 at this location. Throughout this period, we detected 30 IMW episodes with a recurrence time of 24 d, propagating over a median distance of 5.9 km and for 17 d, resulting in a median propagation speed of 400 m d−1. We found that 87 % of the IMW episodes occurred prior to a calving event visible in spaceborne observations and that ∼75 % of all detected calving events were preceded by an IMW episode. These results therefore present the IMW process as a clear control on the calving activity of Kangerdlugssuaq Glacier. Finally, using a simple numerical model for ice mélange motion, we showed that a slightly biased random motion of ice floes without fluctuating external forcing can reproduce IMW events and their cyclic influence and explain observed propagation speeds. These results further support our observations in characterizing the IMW process as self-sustained through the existence of an IMW–calving feedback. This study therefore highlights the importance of short-term ice mélange dynamics in the longer-term evolution of Greenland outlet glaciers.

Simulating surface height and terminus position for marine outlet glaciers using a level set method with data assimilation

We implement a data assimilation framework for integrating ice surface and terminus position observations into a numerical ice-flow model. The model uses the well-known shallow shelf approximation (SSA) coupled to a level set method to capture ice motion and changes in the glacier geometry. The level set method explicitly tracks the evolving ice–atmosphere and ice–ocean boundaries for a marine outlet glacier. We use an Ensemble Transform Kalman Filter to assimilate observations of ice surface elevation and lateral ice extent by updating the level set function that describes the ice interface. Numerical experiments on an idealized marine-terminating glacier demonstrate the effectiveness of our data assimilation approach for tracking seasonal and multi-year glacier advance and retreat cycles. The model is also applied to simulate Helheim Glacier, a major tidewater-terminating glacier of the Greenland Ice Sheet that has experienced a recent history of rapid retreat. By assimilating observations from remotely-sensed surface elevation profiles we are able to more accurately track the migrating glacier terminus and glacier surface changes. These results support the use of data assimilation methodologies for obtaining more accurate predictions of short-term ice sheet dynamics.

Hydrologic modeling of a perennial firn aquifer in southeast Greenland

AbstractA conceptual model, based on field observations and assumed physics of a perennial firn aquifer near Helheim Glacier (southeast Greenland), is evaluated via steady-state 2-D simulation of liquid water flow and energy transport with phase change. The simulation approach allows natural representation of flow and energy advection and conduction that occur in vertical meltwater recharge through the unsaturated zone and in lateral flow within the saturated aquifer. Agreement between measured and simulated aquifer geometry, temperature, and recharge and discharge rates confirms that the conceptual field-data-based description of the aquifer is consistent with the primary physical processes of groundwater flow, energy transport and phase change. Factors that are found to control simulated aquifer configuration include surface temperature, meltwater recharge rate, residual total-water saturation and capillary fringe thickness. Simulation analyses indicate that the size of perennial firn aquifers depends primarily on recharge rates from surface snowmelt. Results also imply that the recent aquifer expansion, likely due to a warming climate, may eventually produce lakes on the ice-sheet surface that would affect the surface energy balance.

Tidewater-glacier response to supraglacial lake drainage

The flow speed of the Greenland Ice Sheet changes dramatically in inland regions when surface meltwater drains to the bed. But ice-sheet discharge to the ocean is dominated by fast-flowing outlet glaciers, where the effect of increasing surface melt on annual discharge is unknown. Observations of a supraglacial lake drainage at Helheim Glacier, and a consequent velocity pulse propagating down-glacier, provide a natural experiment for assessing the impact of changes in injected meltwater, and allow us to interrogate the subglacial hydrological system. We find a highly efficient subglacial drainage system, such that summertime lake drainage has little net effect on ice discharge. Our results question the validity of common remote-sensing approaches for inferring subglacial conditions, knowledge of which is needed for improved projections of sea-level rise.

Helheim Glacier ice velocity variability responds to runoff and terminus position change at different timescales

The Greenland Ice Sheet discharges ice to the ocean through hundreds of outlet glaciers. Recent acceleration of Greenland outlet glaciers has been linked to both oceanic and atmospheric drivers. Here, we leverage temporally dense observations, regional climate model output, and newly developed time series analysis tools to assess the most important forcings causing ice flow variability at one of the largest Greenland outlet glaciers, Helheim Glacier, from 2009 to 2017. We find that ice speed correlates most strongly with catchment-integrated runoff at seasonal to interannual scales, while multi-annual flow variability correlates most strongly with multi-annual terminus variability. The disparate time scales and the influence of subglacial topography on Helheim Glacier’s dynamics highlight different regimes that can inform modeling and forecasting of its future. Notably, our results suggest that the recent terminus history observed at Helheim is a response to, rather than the cause of, upstream changes.

Inferring Mass Loss by Measuring Contemporaneous Deformation around the Helheim Glacier, Southeastern Greenland, Using Sentinel-1 InSAR

The elastic response of solid earth to glacier and ice sheet melting, the most important consequences of climate change, is a contemporaneous uplift. Here, we use interferometric synthetic aperture radar (InSAR) measurements to detect crustal deformation and mass loss near the Helheim glacier, one of the largest glaciers in southeastern Greenland. The InSAR time series of Sentinel-1 data between April 2016 and July 2020 suggest that there is a maximum cumulative displacement of ~6 cm in the line of sight (LOS) direction from the satellite to the ground near Helheim. We use an exponentially decreasing model of the thinning rate, which assumes that the mass loss starts at the lower-elevation terminal region of the glacier and continues to the higher-elevation interior. A linear inversion of the derived crustal uplift in the vicinity of bedrock using this model for surface loading in an elastic half-space suggests a mass loss of 8.33 Gt/year, which agrees with the results from other studies.

Inferring time-dependent calving dynamics at Helheim Glacier

AbstractWe perform Bayesian inference of the parameters of a time-dependent model of ice flow and calving at Helheim Glacier, East Greenland. We find that, while a time-independent calving parameterization can recover the mean observed terminus position, such a model is unable to recover sub-annual variability, even when forced with seasonally varying climate. To address this, we develop a simple stochastic model relating surface runoff rates and calving threshold. Again inferring model parameters from observations, we find that this parameterization is able to reproduce observations with respect to both mean position and characteristic temporal variability. This result demonstrates the importance of considering potential sub-annual controls on calving rates in numerical models, which may include variable undercutting rates or surface runoff-dependent surface crevasse propagation.

Variational inference at glacier scale

We characterize the joint Bayesian posterior distribution over spatially-varying basal traction and ice rheology of an ice sheet model from observations of surface speed using stochastic variational inference, the first application of such methods to large-scale fluid simulations subject to real-world observations. Assuming a low-rank Gaussian process posterior, we use natural gradient descent to minimize the Kullback-Leibler divergence between this assumed distribution and the true posterior. By also placing a Gaussian process prior over traction and rheology, and by casting the problem in terms of eigenfunctions of a kernel, we gain substantial control over prior assumptions on parameter smoothness and length scale, while also rendering the inference tractable. In a synthetic example, we find that this method recovers known parameters and accounts for situations of parameter indeterminacy. We also apply the method to Helheim Glacier in Southeast Greenland and show that the proposed method is computationally scalable to catchment-sized problems. We find that observations of fast flow provide substantial information gain relative to a prior distribution, however even precise observations offer little information in slow-flowing regions. The approach described here is a road-map towards robust and scalable Bayesian inference in a wide array of physics-informed problems.

Helheim Glacier's Terminus Position Controls Its Seasonal and Inter‐Annual Ice Flow Variability

AbstractOver the past decade, one of the largest contributors to total ice discharge across the Greenland ice sheet, Helheim Glacier, has experienced large fluctuations in ice velocity. In this study, we simulate the dynamics of Helheim, from 2007 to 2020, using the Ice‐sheet and Sea‐level System Model to identify the drivers of these large changes in ice discharge. By quantifying the impact of individual external forcing and model parameters on Helheim's modeled velocity, we find that the position of the calving front alone explains the dynamic variability of the glacier, as it has a direct and large impact on Helheim's ice velocity. The seasonal to inter‐annual variability of Helheim Glacier is, however, relatively insensitive to the choice of friction law or ice rheology factor. This study shows that more research on calving dynamics and ice–ocean interactions is required to project the future of this sector of Greenland.

Meltwater drainage and iceberg calving observed in high-spatiotemporal resolution at Helheim Glacier, Greenland

AbstractMarine-terminating glaciers lose mass through melting and iceberg calving, and we find that meltwater drainage systems influence calving timing at Helheim Glacier, a tidewater glacier in East Greenland. Meltwater feeds a buoyant subglacial discharge plume at the terminus of Helheim Glacier, which rises along the glacial front and surfaces through the mélange. Here, we use high-resolution satellite and time-lapse imagery to observe the surface expression of this meltwater plume and how plume timing and location compare with that of calving and supraglacial meltwater pooling from 2011 to 2019. The plume consistently appeared at the central terminus even as the glacier advanced and retreated, fed by a well-established channelized drainage system with connections to supraglacial water. All full-thickness calving episodes, both tabular and non-tabular, were separated from the surfacing plume by either time or by space. We hypothesize that variability in subglacial hydrology and basal coupling drive this inverse relationship between subglacial discharge plumes and full-thickness calving. Surfacing plumes likely indicate a low-pressure subglacial drainage system and grounded terminus, while full-thickness calving occurrence reflects a terminus at or close to flotation. Our records of plume appearance and full-thickness calving therefore represent proxies for the grounding state of Helheim Glacier through time.

Helheim Glacier Poised for Dramatic Retreat

AbstractHelheim Glacier, one of the largest marine‐terminating outlet glaciers draining the Greenland Ice Sheet, underwent significant retreat and acceleration in the early 2000s, accounting for an appreciable proportion of the ice sheet's mass loss during that period. Using a range of remotely sensed datasets, we show that despite a subsequent readvance, the glacier has continued to lose mass and thin, and has retreated inland of the retracted position occupied in 2005. Critically, the near‐terminus is up to 100 m thinner than during 2005, and the front 5 km is within 25–50 m of flotation, with retrograde bed slopes extending several kilometers inland of the terminus. The neighboring Fenris and Midgard Glaciers have both undergone recent large‐scale and rapid retreat once their near‐terminus regions began to float, suggesting that under projected climate warming and associated glacier thinning, Helheim Glacier is poised to pass a threshold whereby the near‐terminus region will retreat rapidly.

Image classification of marine-terminating outlet glaciers in Greenland using deep learning methods

Abstract. A wealth of research has focused on elucidating the key controls on mass loss from the Greenland and Antarctic ice sheets in response to climate forcing, specifically in relation to the drivers of marine-terminating outlet glacier change. The manual methods traditionally used to monitor change in satellite imagery of marine-terminating outlet glaciers are time-consuming and can be subjective, especially where mélange exists at the terminus. Recent advances in deep learning applied to image processing have created a new frontier in the field of automated delineation of glacier calving fronts. However, there remains a paucity of research on the use of deep learning for pixel-level semantic image classification of outlet glacier environments. Here, we apply and test a two-phase deep learning approach based on a well-established convolutional neural network (CNN) for automated classification of Sentinel-2 satellite imagery. The novel workflow, termed CNN-Supervised Classification (CSC) is adapted to produce multi-class outputs for unseen test imagery of glacial environments containing marine-terminating outlet glaciers in Greenland. Different CNN input parameters and training techniques are tested, with overall F1 scores for resulting classifications reaching up to 94 % for in-sample test data (Helheim Glacier) and 96 % for out-of-sample test data (Jakobshavn Isbrae and Store Glacier), establishing a state of the art in classification of marine-terminating glaciers in Greenland. Predicted calving fronts derived using optimal CSC input parameters have a mean deviation of 56.17 m (5.6 px) and median deviation of 24.7 m (2.5 px) from manually digitised fronts. This demonstrates the transferability and robustness of the deep learning workflow despite complex and seasonally variable imagery. Future research could focus on the integration of deep learning classification workflows with free cloud-based platforms, to efficiently classify imagery and produce datasets for a range of glacial applications without the need for substantial prior experience in coding or deep learning.

Accuracy evaluation of digital elevation models derived from Terrestrial Radar Interferometer over Helheim Glacier, Greenland

Glaciers in polar regions are sensitive to climate and ocean changes and can thin rapidly as a consequence of global warming. Digital Elevation Models (DEMs) from remote sensing observations have been widely used to detect changes in polar glaciers. DEMs from Terrestrial Radar Interferometer (TRI) have recently been used for high frequency glacier change and glacier-ocean interaction studies. However, it is unclear whether TRI DEM over a large study area can be combined directly with remote sensing observations to investigate glacier changes as well as the accuracy of TRI DEM at far range. In this study, we deployed a TRI close to Helheim Glacier, East Greenland and generated DEMs using TRI and satellite laser altimetry. We analyzed the accuracy of the TRI DEM using theoretical calculations, comparisons based on repeat observations, and comparisons with a high accurate ArcticDEM. The validation results suggest that for stable ground surfaces, the uncertainty (standard deviation) is <5 m at range < 9.8 km. Averaging across time (e.g. one hour) decreases the uncertainty almost linearly with range, over 0.5 m to 1.2 m when the range increases from 7.0 km to 10.0 km. Increasing the correlation coefficient threshold for phase unwrapping does not significantly reduce uncertainty. TRI DEMs are influenced by systematic error at far range primarily due to coarse azimuth resolution and phase unwrapping difficulties in discontinuous interferograms. As the absolute accuracy of TRI DEMs is not uniformly distributed in the range direction (farther points have worse uncertainty), our findings indicate that TRI DEMs within range of 10 km can reach <5 m uncertainty, which can be compared with DEMs obtained from remote sensing satellites to detect glacier thinning.

Estimating Ice Discharge at Greenland's Three Largest Outlet Glaciers Using Local Bedrock Uplift

AbstractWe present a novel method to estimate dynamic ice loss of Greenland's three largest outlet glaciers: Jakobshavn Isbræ, Kangerlussuaq Glacier, and Helheim Glacier. We use Global Navigation Satellite System (GNSS) stations attached to bedrock to measure elastic displacements of the solid Earth caused by dynamic thinning near the glacier terminus. When we compare our results with discharge, we find a time lag between glacier speedup/slowdown and onset of dynamic thinning/thickening. Our results show that dynamic thinning/thickening on Jakobshavn Isbræ occurs 0.87 ± 0.07 years before speedup/slowdown. This implies that using GNSS time series we are able to predict speedup/slowdown of Jakobshavn Isbræ by up to 10.4 months. For Kangerlussuaq Glacier the lag between thinning/thickening and speedup/slowdown is 0.37 ± 0.17 years (4.4 months). Our methodology and results could be important for studies that attempt to model and understand mechanisms controlling short‐term dynamic fluctuations of outlet glaciers in Greenland.