CR1.2

The Antarctic ice sheet has the potential to be a major contributor to future global sea level rise, but this has been difficult to predict, in part due to the combination of expected ice mass loss and snowfall accumulation. A great deal of uncertainty arises from the large variation of atmospheric and oceanic changes across climate models, and sensitivity to ocean changes across ice sheet models, but these uncertainties cannot be fully sampled because the models are too computationally expensive.

Here we make projections of Antarctica’s contribution to global sea level rise based on the simulations of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). Using a Gaussian process emulator, a statistical approximation of expensive computer models, we estimate probability distributions by sampling uncertainties in future climate and ice sheet sensitivity to ocean warming far more thoroughly than the original ISMIP6 ensemble could. We find a sea level contribution of 4 cm (5^th-95th percentile range -5 to 14 cm) sea level equivalent by 2100 under current emissions policies, increasing to 21 cm (5^th-95th percentile range 7 to 43 cm) if we use the subset of climate models, ice sheet models and ice sheet/ocean sensitivity values that lead to the highest sea level contributions.

We then compare the output from this emulator to a linear mixed model emulator, which  incorporates a random effect to represent the variation arising from different ice sheet models. We do this for all three Antarctic regions (West and East Antarctica, and the Peninsula) under two greenhouse emissions scenarios (SSP1-26 and SSP5-85). Both methods produce similar probability distributions of sea level contribution in 2100, demonstrating that differences in statistical models are not dominating the results.

How to cite: Turner, F. and Edwards, T. and the ISMIP6 team and others: Predicting the Antarctic sea level contribution to sea level rise with emulation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7476, https://doi.org/10.5194/egusphere-egu21-7476, 2021.

The future surface mass balance (SMB) will influence the ice dynamics and the contribution of the Antarctic ice sheet (AIS) to the sea-level rise. Most of recent Antarctic SMB projections were based on the 5th phase of the Coupled Model Intercomparison Project (CMIP5). However, new CMIP6 results have revealed a +1.3°C higher mean Antarctic near-surface temperature than in CMIP5 at the end of the 21st century enabling estimations of future SMB in warmer climates. Here, we investigate the AIS sensitivity to different warmings with an ensemble of four simulations performed with the polar regional climate model MAR forced by two CMIP5 and two CMIP6 models over 1981--2100. Statistical extrapolation allows us to expand our results to the whole CMIP5 and CMIP6 ensembles. Our results highlight a contrasting effect on the future grounded ice sheet and the ice shelves. The SMB over grounded ice is projected to increase as a response to stronger snowfall, only partly offset by enhanced meltwater runoff. This leads to a cumulated sea-level rise mitigation (i.e. an increase in surface mass) of the grounded Antarctic surface by 5.1 ± 1.9 cm sea-level equivalent (SLE) in CMIP5-RCP8.5 and 6.3 ± 2.0 cm SLE in CMIP6-ssp585. Additionally, the CMIP6 low-emission ssp126 and intermediate-emission ssp245 scenarios project a stabilised surface mass gain resulting in a lower mitigation to sea-level rise than in ssp585. Over the ice shelves, the strong runoff increase associated with higher temperature is projected to lower the SMB with a stronger decrease in CMIP6-ssp585 compared to CMIP5-RCP8.5. Ice shelves are however predict to have a close-to-present-equilibrium stable SMB under CMIP6 ssp126 and ssp245 scenarios. Future uncertainties are mainly due to the sensitivity to anthropogenic forcing and the timing of the projected warming. Furthermore,  we compare the MAR projected SMB to the ISMIP6-derived SMB, revealing large local and integrated differences between MAR and the respective forcing ESM highlighting the need of additional projections relying on more models including both RCMs and ESMs. While ice shelves should remain at a close-to-equilibrium stable SMB under the Paris Agreements, MAR projects strong SMB decrease for an Antarctic near-surface warming above +2.5°C limiting the warming range before potential irreversible damages on the ice-shelves. Finally, our results reveal the existence of a potential threshold (+7.5°C) that leads to a lower grounded SMB increase. This however has to be confirmed in following studies using more extreme or longer future scenarios.

How to cite: Kittel, C., Amory, C., Agosta, C., Jourdain, N. C., Hofer, S., Delhasse, A., Doutreloup, S., Huot, P.-V., Lang, C., Fichefet, T., and Fettweis, X.: Diverging future surface mass balance between the Antarctic ice shelves and grounded ice sheet, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2160, https://doi.org/10.5194/egusphere-egu21-2160, 2021.

Mass balance assessments of the East Antarctic ice sheet are highly sensitive to changes in firn thickness resulting from variability in firn compaction rates and surface mass fluxes (snowfall, sublimation, melt). To better constrain uncertainty in firn thickness and in the underlying processes, we develop a model-based ensemble of firn evolution scenarios over 1992-2017. We combine statistical emulation of nine firn-densification models, climatic output from three regional climate models and different assumptions about surface snow density to generate a comprehensive set of 54 model scenarios. The ensemble agrees that firn thickness changes in the interior are minor, but there are pronounced thickening and thinning patterns in coastal areas.  At basin level, model uncertainty in firn thickness change ranges between 0.2–1.0 cm yr^-1 (15–300%). Statistical analysis of the ensemble uncertainty demonstrates that climatic forcing is the primary contributor of model spread on firn thickness estimates. However, in basins characterised by warmer temperatures, high snowfall or increasing snowfall, the contributions of firn compaction and surface snow density can account for up to 46 and 28% of the spread, respectively.

By comparing the ensemble scenarios with satellite measurements of elevation changes over the same 1992-2017 period, we find that these estimates are consistent over a majority of basins. Nonetheless, we identify several basins where model estimates of firn thickness change do not match altimetry measurements. These discrepancies can be explained by different causes: (1) the model ensemble may fail to represent the real firn thickness change over our period of interest, (2) the uncertainty range associated with the altimetry data may not capture the true signal and (3) a component of the elevation change signal may be related to ice dynamical imbalance. As such, our analysis serves to highlight specific areas where further focus on potential sources of errors in model and altimetry results is needed in order to better constrain mass balance assessments in East Antarctica.

How to cite: Verjans, V., Leeson, A., McMillan, M., Stevens, M., van Wessem, J. M., van de Berg, W. J., van den Broeke, M., Kittel, C., Amory, C., Fettweis, X., Hansen, N., Boberg, F., and Mottram, R.: Uncertainty in East Antarctic firn thickness constrained using a model ensemble approach, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-140, https://doi.org/10.5194/egusphere-egu21-140, 2021.

Ice Sheet Models are a powerful tool to project the evolution of the Greenland and Antarctic Ice Sheets, and thus their future contribution to global sea-level changes. Probing the fitness of ice-sheet models to reproduce ongoing and past changes of the Greenland and Antarctic ice cover is a fundamental part of every modelling effort. However, benchmarking ice-sheet model data against real-world observations is a non-trivial process, as observational data comes with spatio-temporal gaps in coverage. Here, we present a new approach to assess the ability of ice-sheet models which makes use of the internal layering of the Antarctic Ice Sheet. We simulate observed isochrone elevations within the Antarctic Ice Sheet via passive Lagrangian tracers, highlighting that a good fit of the model to two dimensional datasets does not guarantee a good match against the three dimensional architecture of the ice-sheet and thus correct evolution over time. We show, that paleoclimate forcing schemes commonly used to drive ice-sheet models work well in the interior of the Antarctic Ice Sheet and especially along ice divides, but fail towards the ice-sheet margin. The comparison to isochronal horizons attempted here reveals, that simple heuristics of basal drag can lead to an overestimation of the vertical interior ice sheet flow especially over subglacial basins. Our model-observation intercomparison approach opens a new avenue to the improvement and tuning of current ice-sheet models via a more rigid constraint on model parameterisations and climate forcing which will benefit model-based estimates of future and past ice-sheet changes.

How to cite: Sutter, J., Fischer, H., and Eisen, O.: Investigating the internal structure of the Antarctic Ice Sheet: the utility of isochrones for spatio-temporal ice sheet model calibration, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9446, https://doi.org/10.5194/egusphere-egu21-9446, 2021.

Glaciers and ice streams channel the majority of ice mass discharge into the ocean, and are modulated by basal slip at the ice-bed interface, deformation within the ice interior, and lateral shear at the margins separating fast- and slow-moving ice. The anisotropy of glacier ice (i.e. ice that deforms preferentially in certain modes and directions) at shear margins greatly facilitates streaming ice, however it is still poorly understood due to a lack of in-situ measurements and is usually incorporated into models as a simple scalar enhancement factor. The resurgence of polarimetric radar techniques to detect bulk fabric anisotropy through exploiting the birefringence of ice crystals has greatly aided quantification of the ice crystal orientation fabric (COF) across the Antarctic Ice Sheet. In our study, we invert these techniques to infer the azimuthal fabric strength at the Eastern Shear Margin of Thwaites Glacier from non-polarimetric airborne radargrams collected during the 2018-19 field season. From these results, we infer the evolution of the crystal orientation fabric across the shear margin, where ice is subjected to varying levels of both pure and simple shear. Our findings suggest the potential of the upper reaches of the ESM having undergone recent inward migration. Together with compatible ground-based polarimetric radar experiments, our study highlights the potential of radar sounding to observe and infer variations in fabric strength from regions of complex flow at multiple spatial scales. Because the bulk COF of ice sheets records the past history of ice sheet deformation and influences present-day ice flow dynamics, accurate measurements of ice fabric strength and orientation not only places constraints on present and past ice flow history, but also aids in the incorporation of anisotropic rheology in ice flow models.

How to cite: Young, T. J., Jordan, T. M., Martín, C., Schroeder, D. M., Christoffersen, P., Tulaczyk, S. M., Culberg, R., and Bienert, N. L.: Polarimetric radar-sounding to infer and quantify shear margin ice fabric anisotropy, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2107, https://doi.org/10.5194/egusphere-egu21-2107, 2021.

Airborne ice-penetrating radar surveys around the Ellsworth Subglacial Highlands (ESH) have mapped and dated englacial ice sheet layers, hereafter referred to as ‘Internal Reflection Horizons’ (IRHs). The geometry and internal structure of IRHs can reveal the cumulative effects of surface mass balance, strain, basal melt and ice dynamics, to improve understanding of the glacial history of West Antarctic Ice Sheet (WAIS). Despite the airborne-surveyed IRHs however, international efforts to develop a continental-wide scale coverage of IRHs (i.e. AntArchitecture), are limited by a lack of data in the critical regions between the upper reach of Pine Island Glacier (PIG), Rutford Ice Stream (RIS) and Institute Ice Stream (IIS). This region is important because any significant collapse of WAIS or reorganisation of ice flow would likely be felt in the ESH because it hosts deep subglacial troughs (Ellsworth Trough and CECs Trough), that represent a potential connection between the Weddell and Amundsen Seas. Using an extensive ground-based ice radar dataset acquired by Centro de Estudios Científicos (CECs) we bridge this regional gap by mapping IRHs across the Amundsen-Weddell divide of the WAIS. This work links airborne-derived IRH datasets across PIG and IIS, to develop an extensive layer characterisation across a large area of West Antarctica. We present the regional internal structure of the ice sheet, gridded paleo ice surfaces, and identify areas with complex IRH structures, and evaluate the possible glaciological processes responsible. We then compare our results with modelled outputs of ice sheet geometry and outline our current understanding of the past ice flow behaviour of the ESH, and the implications for WAIS glacial history. We consider our results in the context of the characterisation of ‘old-ice’ in WAIS and in relation to the upcoming plans for accessing subglacial Lake CECs in order to determine its history.

How to cite: Napoleoni, F., Ross, N., Bentley, M. J., Jamieson, S. S. R., Smith, A. M., Uribe, J.-A., Zamora, R., and Brisbourne, A. M.: Englacial stratigraphy in Ellsworth Subglacial Highlands, West Antarctica, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3366, https://doi.org/10.5194/egusphere-egu21-3366, 2021.

Dome A is the summit of the East Antarctic Ice Sheet (EAIS), underlain by the rugged Gamburtsev Subglacial Mountains (GSM).  The rugged basal topography produces a complex hydrological system featuring basal melt, water transport and storage, and freeze-on.  Here, we present the results of an inverse model used to infer the spatial distributions of geothermal heat flow (GHF) and accumulation rate that best fit a variety of observational constraints.  Our model agrees well with the observed water bodies and freeze-on structures, while also predicting a significant amount of unobserved water and suggesting a change in stratigraphic interpretation that reduces the volume of the freeze-on units.  Our model stratigraphy agrees well with observations, and we predict that there will be two distinct patches of ice up to 1.5 Ma suitable for ice coring underneath the divide.  Past divide migration could have interrupted stratigraphic continuity at the old ice patches, but various indirect lines of evidence suggest that the divide has been stable for about the last one and a half glacial cycles, which is a hopeful but by no means definitive sign for stability in the longer term.  Finally, our GHF estimate is higher than previous estimates for this region, but consistent with possible heterogeneity in crustal heat production.     

How to cite: Wolovick, M., Moore, J., and Zhao, L.: Joint Inversion for Surface Accumulation and Geothermal Heat Flow from Ice-Penetrating Radar Observations at Dome A, East Antarctica., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13492, https://doi.org/10.5194/egusphere-egu21-13492, 2021.

The Greenland ice sheet (GrIS) is one of the largest contributors to global mean sea-level rise today and is expected to continue losing mass in the future under increasing Arctic warming. Mass loss in the future is caused by the thinning and retreat of marine-terminating outlet glaciers and to a larger extent by decreasing surface mass balance (SMB) due to increased surface meltwater runoff. In this paper we study the relative importance of changes in SMB and outlet glacier retreat by means of model simulations that have been performed as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). The effect of the two forcing mechanisms can be separated based on a comparison between full projections and single forcing experiments up to year 2100 for a number of ice sheet models, driving General Circulation Models and two forcing scenarios (RCP2.6 and RCP8.5). We can confirm earlier findings for the high forcing scenario that a compensation between the two processes renders the sea-level contribution from the full experiment lower than the sum of the single forcing experiments.

How to cite: Goelzer, H. and the The ISMIP6 team: Relative importance of surface mass balance and outlet glacier forcing in ISMIP6 Greenland ice sheet sea-level projections, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11177, https://doi.org/10.5194/egusphere-egu21-11177, 2021.

Mass loss from the Greenland Ice Sheet (GrIS) can be partitioned between surface mass balance (SMB) 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 an instantaneous response in velocity and mass loss, but also 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 realised. Here we model the committed response of the GrIS to recent observed changes in terminus position, neglecting any future climate perturbations. Our simulations quantify the sea level contribution that is locked in due to the slow dynamic response of the ice. Using the Ice Sheet System Model (ISSM), we run forward simulations starting from an initial state representative of the 2007 ice sheet. We apply perturbations to the marine-terminating glacier termini that represent recent observed changes, and simulate the response over the 21^st Century, holding the climate forcing constant. The sensitivity of the ice sheet response to model parameter uncertainty is explored with in an ensemble framework, and GRACE data is used to constrain the results. We find that terminus retreat observed between 2007 and 2015 results in approximately 6 mm of sea level rise by 2100, with retreat having a lasting impact on velocity and mass loss. Our results complement the ISMIP6 projections, which report the ice sheet response to future forcing, excluding the background committed response. In this way, we can obtain estimates of Greenland’s total contribution to sea level rise by 2100.

How to cite: Nias, I., Nowicki, S., and Felikson, D.: Recent retreat of Greenland's marine terminating glaciers has a lasting impact on velocity and mass loss during the 21st Century, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9908, https://doi.org/10.5194/egusphere-egu21-9908, 2021.

Accelerated surface melt of the Greenland ice sheet (GrIS) is currently a large contributor to sea level rise, and the primary process of GrIS mass loss. Projections of future GrIS melt are limited by the lack of explicit melt calculations within most global climate models and the high computational cost of dynamical downscaling with regional models. To translate global climate evolution to GrIS surface melt, we train artificial neural networks (ANNs) with the output of the explicit melt calculation of the Community Earth System Model 2.1 (CESM2). ANNs are well suited for this task, as they are capable of learning complex, non-linear relationships, and they are fast to run.

Our results show that the ANNs accurately project GrIS surface melt when evaluated against regional climate simulations. Further, the ANNs recognize patterns already established in litterature as important for surface melt, and use bases the projections on these patterns. Using the global climate simulations from the CMIP6 archive, the ANNs project a GrIS surface melt increase ranging from 414 Gt yr^-1 to 1,378 Gt yr^-1 by the end of the 21^st century. The main source of projection uncertainty throughout the 21^st century is due to the spread in the models’ climate sensitivity.

How to cite: Sellevold, R. and Vizcaino, M.: Projecting 21st century GrIS surface melt using artificial neural networks, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9540, https://doi.org/10.5194/egusphere-egu21-9540, 2021.

Lack of observation is one of the main limitations for improving model prediction in glaciology. However, over the past few years, the amount of observations from satellites has increased at a phenomenal rate. Hopefully, this amount of data will allow to validate the models and their parameterizations. In addition, data assimilation seems to be an optimal method to combine the model and these frequent observations, allowing to reduce the uncertainties of the model and thus potentially improve the projections. While inverse methods are now common in glaciology to infer uncertain parameters from observed surface velocities acquired at a given date, transient data assimilation algorithms are still under development. Recently, the performance of an Ensemble Kalman Filter has been studied on a synthetic case. Here, the goal of this study is to investigate the feasibility of applying this assimilation scheme on a real case : evolution of Upernavik Isstrøm since 1985 using the open source finite element software Elmer/Ice. To do so, we first need to generate an ensemble of simulations that sample the model uncertainties and to evaluate this ensemble against available observations.

We first assemble a set of observations that will serve for model setup and validation. In this sense, we have collected ice velocity measurements, from optical and radar source, surface elevation and bed topography, ice front position and surface mass balance that give us a fairly good a priori knowledge of the evolution of Upernavik Isstrøm between 1985 and 2020. These datasets are divided into two parts : one is used to better characterize and set up the initial state of the system, and the other is used to evaluate model outputs.

Uncertainties in the model comes from different sources: (i) the model parameters, (ii) the initial topography as the surface elevation in 1985 is only partially known, and (iii) the forcings (i.e. the surface mass balance, the ice front position).
For the model parameters we take into account uncertainties in the ice rheology by perturbing the Glen’s enhancement factor and by generating an ensemble of friction coefficients for different friction laws using a set of inversions that has been performed for the whole Greenland using present day observations. Using these perturbed parameters and a set of surface mass balance representative of the period we generate and evaluate an ensemble of initial topographies for 1985.

With this ensemble of initial states, we perform transient simulations where the position of glacier terminus and a set of perturbed SMB are prescribed each year. Each simulation is scored with specifically designed metrics in terms of dynamics and geometry using the observations described previously. This analysis allows to evaluate the impact of different sources of uncertainty on the transient simulation. Using the results of this study, we will discuss the capacity of Elmer/Ice to reconstruct the trend of the evolution of Upernavik Isstrøm and the possibility to perform transient data assimilation.

How to cite: Jager, E., Gillet-Chaulet, F., and Mouginot, J.: Data assimilation and ensemble method applied to Upernavik Isstrom, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5752, https://doi.org/10.5194/egusphere-egu21-5752, 2021.

Greenland’s future response to climate change will be determined partly by various phenomena controlling ice flow. For the land-terminating sectors, the water lubricating the glacier's base is considered as a major control on the ice motion. For instance, the seasonal modulations of water input induced by summer melt can cause glacier speed-up up to +200-300% compared to the winter mean. Thus, a comprehensive understanding of variations in the basal conditions, which are at the origin of the glacier flow fluctuations, plays a key role for the climate projections.

While the in-situ measurements stay a local and hard approach to investigate the basal conditions, ice flow modeling offers the possibility to invert for them over the large area based on observations of surface glacier speed and topography. During the last decade, the number of available satellite observations has increased significantly, allowing for far more frequent measurements of the glacier speed and precise reconstruction of the seasonal fluctuations. Here, we investigate the possibility of applying this satellite-derived time-series of surface ice velocity to reconstruct the annual behavior of the basal conditions with 2 weeks temporal resolution using an ice flow model.

The area of this study is Russell glacier located on the southwest coast of Greenland. A time series of surface velocity dataset was created by merging measurements from Sentinel-1&2 and Landsat-8, covering an area up to 100 km inland with 150 m/pix spatial resolution and 2-weeks temporal resolution (Derkacheva et al. 2020). The 3D Full-Stokes ice flow model Elmer/Ice is used to invert for the effective basal friction coefficient for each time step.  Usage of a friction law that has been derived for hard beds (Gagliardini et al., 2007) allows to constrain the variation of the basal effective pressure. Overall, the results from the model inversions give access to the evolution of the basal ice speed, friction, effective and water pressure, floatation fraction throughout a complete year. The results are compared with in-situ measurements in terms of absolute values and show a good agreement. The impact of the flow model setup, regularization, assumptions for the ice rheology, and the impact of noise in the speed data are also examined and compared with in-situ measurements.

How to cite: Derkacheva, A., Gillet-Chaulet, F., and Mouginot, J.: Modeling of the Russell glacier's basal conditions at seasonal time scale using the satellite observations of surface ice speed, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4672, https://doi.org/10.5194/egusphere-egu21-4672, 2021.

Most of the existing work on solving inverse problems in glaciology has assumed that the observational data used to constrain the model are spatially dense. This assumption is very convenient because it means that the model-data misfit term in the objective functional can be written as an integral. In many scenarios, however, the computational mesh can locally be much finer than the observational grid, or the observations can have large patches of missing data. Moreover, pretending as if the observations are a globally-defined continuous field obscures valuable information about the number of independent measurements we have. It is then impossible to apply a posteriori sanity checks on the expected model-data misfit from regression theory. Here we'll describe some recent work we've done on assimilating sparse point data into ice flow models and how this allows us to be more rigorous about the statistical interpretation of our results. For now we are focusing on the kinds of inverse problems that have been solved in the glaciology literature for a long time -- inferring rheology and basal friction from surface velocities. But these developments open up the possibility of assimilating new sources of data, such as measurements from strain gauges or ice cores.

How to cite: Shapero, D. and Nixon-Hill, R.: Assimilating sparse data in glaciological inverse problems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3506, https://doi.org/10.5194/egusphere-egu21-3506, 2021.