CR1.2

We are using an ice sheet model that explicitly represents individual layers of accumulation that are fixed in time (isochronal). With progressing time, new layers are added on the top, while older layers subside and become thinner as ice flows towards the margins. This approach eliminates unwanted diffusion and faithfully represents the englacial stratification.

The isochronal model is coupled uni-directionally to a full ice sheet model (“host model”), which provides the ice physics and dynamics. Via the isochronal model’s layer tracking, the host model’s output can be evaluated throughout the interior using the radiostratigraphy data set of the Greenland ice sheet.

We investigate the stability and resolution-dependence of this coupled modeling system in simulations of the last glacial cycle with yelmo as the host model. One key question concerns how frequent updates from the host model must be to ensure a reliable simulation. This could enable offline forcing of the isochronal model with output from a range of existing ice sheet models.

The long-term goal is to make the isochronal model flexible and easily adaptable enough to effectively force it with existing full ice sheet models and to provide it to the community as a new way to assess the models’ performance. 

How to cite: Rieckh, T., Born, A., and Robinson, A.: Layer Tracing of the Greenland Ice Sheet Interior: A Coupled Model Approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8432, https://doi.org/10.5194/egusphere-egu22-8432, 2022.

How to cite: Oien, R., Nowicki, S., and Csatho, B.: The pre-industrial digital elevation model of the Greenland Ice Sheet from the 17th and 18th Centuries , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10811, https://doi.org/10.5194/egusphere-egu22-10811, 2022.

We use the diurnal Energy Balance Model (dEBM) in combination with ERA5 reanalysis forcings to simulate the surface mass balance (SMB) of the Greenland Ice Sheet (GrIS). The dEBM (Krebs-Kanzow et al., 2021) is based on the energy balance of glaciated surfaces. In contrast to most empirical schemes, it is physics based and accounts for variations in the radiative forcing due to changes in the Earth's orbit and atmospheric composition. The dEBM scheme only requires monthly atmospheric forcing (precipitation, temperature, shortwave and longwave radiation and cloud cover) and is computationally inexpensive, which makes it particularly suitable to investigate the response of ice sheets to long-term climate change. After calibration and validation, we investigate the contribution of individual climate forcings (temperature, precipitation, clouds and radiation) to the interannual SMB variability.                     

Furthermore, we compare 1979-2016 ERA5 and ERA-Interim with respect to the main atmospheric drivers of the melt season over the GrIS. In summer, ERA5 differs remarkably from ERA-Interim: averaged over the lower parts of the GrIS, the mean near-surface temperature is 1 K lower while mean downward shortwave radiation at the surface is on average 15W/m^2 higher than in ERA-Interim. In consequence those methods which hitherto have estimated the GrIS surface mass balance from the ERA-Interim surface energy balance need to be carefully recalibrated before they can be progressed to ERA5 forcing.

Krebs-Kanzow, U., Gierz, P., Rodehacke, C. B., Xu, S., Yang, H., and Lohmann, G., 2021: The diurnal Energy Balance Model (dEBM): a convenient surface mass balance solution for ice sheets in Earth system modeling, The Cryosphere, 15, 2295–2313, https://doi.org/10.5194/tc-15-2295-2021.

How to cite: Krebs-Kanzow, U., Rodehacke, C., and Lohmann, G.: The 1950-2020 variability of the Greenland Ice Sheet surface mass balance, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9957, https://doi.org/10.5194/egusphere-egu22-9957, 2022.

This study investigates the sensitivity of modeled surface melt and subsurface heating on the Antarctic ice sheet to a new spectral snow albedo and radiative transfer scheme in the Regional Atmospheric Climate Model (RACMO), version 2.3p3 (Rp3). We tune Rp3 to observations by performing several sensitivity experiments and assess the impact on temperature and melt by incrementally changing one parameter at a time. When fully tuned, Rp3 compares well with in situ and remote sensing observations of surface mass and energy balance, melt, near-surface and (sub)surface temperature, albedo and snow grain specific surface area. Near surface snow temperature is especially sensitive to the prescribed fresh snow specific surface area and fresh dry snow metamorphism. These processes, together with the refreezing water grain size and subsurface heating, are important for melt around the margins of the Antarctic ice sheet. Moreover, small changes in the albedo and the aforementioned processes can lead to an order of magnitude overestimation of melt, locally leading to runoff and a reduced surface mass balance.

How to cite: van Dalum, C., van de Berg, W. J., and van den Broeke, M.: Antarctic surface climate in RACMO2.3p3, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12543, https://doi.org/10.5194/egusphere-egu22-12543, 2022.

Surface mass balance (SMB) is computed from regional climate models (RCM) using reanalysis data. Estimates of the SMB vary between RCMs due to differences such as the model set-up, physical parameterizations, and topography as well as ice mask. The ice mask in a model defines the surface covered by glacier ice. The differences in ice masks appear small, however it is here shown that it leads to important differences in SMB when integrated over the continent. To circumvent this area-dependent bias, intercomparison studies of modelled SMB use a common ice mask (Mottram et al., 2021). The SMB in areas outside the common ice mask is discarded. By comparing the native ice masks with the common ice mask used in Mottram et al. 2021 we find differences in integrated SMB of between 20.1 and 102.4 Gt per year over the grounded ice sheet when compared to the ensemble mean from Mottram et al. 2021. These differences are nearly equivalent to the entire Antarctic ice sheet mass imbalance identified in the IMBIE study.
SMB is particularly essential when estimating the total mass balance of an ice sheet via the input-output method, by subtracting ice discharge from the SMB to derive the mass change. We use the RCM HIRHAM5 to simulate the Antarctic climate and force a newly develop offline subsurface firn model, to simulate the Antarctic SMB from 1980 to 2017. We use discharge estimates from two previously published studies to calculate the regional scale mass budget. To validate the results from the input-output method, we compared the results to the gravimetry-derived mass balance from the GRACE/GRACE-FO mass loss time series, computed for the period 2002–2020. We find good agreement between the two input-output results and GRACE in West Antarctica, however, there are large disagreements between the two input-output methods in East Antarctica and over the Antarctic Peninsula. Over the entire grounded ice sheet, GRACE detects a mass loss of 900 Gt for the period 2002-2017, whereas the two input-output results show a mass gain of 500 Gt and a mass loss of 4000 Gt, depending on which discharge dataset is used. These results are integrated over the native HIRHAM5 ice mask. If we instead integrate over the common ice mask from Mottram et al. 2021, the results change from a mass gain of 500 Gt to a mass loss of 500 Gt, and a mass loss of 4000 Gt to a mass loss of 5000 Gt, over the grounded ice sheet for the period 2002-2017. While the differences in ice discharge remain the largest sources of uncertainty in the Antarctic ice sheet mass budget, our analysis shows that even a small area bias in ice mask can have a huge impact in high precipitation areas and therefore SMB estimates. We conclude there is a pressing need for a common ice mask protocol, to create an accurate harmonized updated ice mask.

How to cite: Hansen, N., Simonsen, S. B., Boberg, F., Forsberg, R., and Mottram, R.: Errors in Mass Balance estimates of Antarctica from ice mask and input-output inconsistencies, pinpointed by GRACE, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3838, https://doi.org/10.5194/egusphere-egu22-3838, 2022.

Full-Stokes (FS) ice sheet models provide the most sophisticated formulation of ice sheet flow. However, their ap- plicability is often limited due to the high computational demand and numerical challenges. To balance computational demand and accuracy, the so-called Blatter-Pattyn (BP) stress regime is frequently used. Here, we explore the dynamic consequences by solving FS and the BP stress regime applied to the Northeast Greenland Ice Stream. To ensure a consistent comparison, we use one single ice sheet model to run the simulations under identical numerical conditions. A sensitivity study to the horizontal grid resolution (from 12.8 down to 0.1 km) reveals that velocity differences between the FS and BP solution emerge below ∼1 km horizontal resolution and continuously increase with resolution. Over the majority of the modelling domain both models reveal similar surface velocity patterns. At the grounding line of 79° North Glacier the simulations unveil considerable differences whereby BP overestimates ice discharge of up to 50% compared to FS. A sensitivity study to the friction type reveals that differences are stronger for a power-law friction than a linear friction law. Model differences are attributed to topographic variability and the basal drag since neglected stress terms in BP become important.

How to cite: Humbert, A., Kleiner, T., and Rückamp, M.: Comparison of ice dynamics using full-Stokes and Blatter-Pattyn approximation: application to the Northeast Greenland Ice Stream, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5459, https://doi.org/10.5194/egusphere-egu22-5459, 2022.

There are large uncertainties in model predictions of the Antarctic Ice Sheet (AIS) contribution to future sea level rise. One source of model uncertainty is the description of basal friction. Here, we implement a new basal sliding law, developed by Zoet and Iverson (2020), in an updated version of the Community Ice Sheet Model (CISM). The Zoet-Iverson sliding law combines properties of two previously used sliding laws: power-law behavior in areas with slow-moving ice and coulomb-law behavior in fast-moving ice streams and outlet glaciers. We adress the behavior and performance of the Zoet-Iverson law in CISM using AIS spin-up procedures developed for the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We invert a non-dimensional coefficient in the Zoet-Iverson law to match modelled and observed thickness for grounded ice. Ocean temperatures are tuned to nudge ice-shelf thickness via the basal melt rates. These tuning processes are Antarctic-wide, but we focus on the Amundsen Sea region. We then advance the model forward to better represent the present-day Thwaites glacier, by inverting for observed ice velocity and by changing the ocean forcing. The main results from this run are the sub-shelf ocean temperature perturbation, thickness, and velocity profile of Thwaites glacier. Results are compared with different sliding laws to demonstrate the effect of the Zoet-Iverson law on the representation of the ongoing retreat. 

Zoet, L.K. & Iverson, N.R. (2020). A slip law for glaciers on deformable beds. In: Science 368 (6486), pages 76-78. DOI: 10.1126/science.aaz1183

How to cite: van den Akker, T., Lipscomb, W. H., Leguy, G. R., van de Berg, W. J., and van de Wal, R. S. W.: Implementation of the Zoet-Iverson basal sliding law in CISM, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8882, https://doi.org/10.5194/egusphere-egu22-8882, 2022.

Large efforts are engaged to model climate-ice sheet interactions in order to estimate Antarctic and Greenland ice sheets’ contribution to sea level in the next decades to centuries. Here we present a first-order evaluation of CMIP5 and CMIP6 climate models over both polar regions. We focus on large-scale atmospheric fields and surface ocean variables only. Our goal is to provide a first overview of climate model biases in polar regions, in order to use their outputs on an informed basis. We particularly target the use of climate model outputs for forcing ice sheet models and regional atmospheric models.

We consider 9 (non-independent) variables : 850 hPa and 700 hPa annual and summer temperature, annual integrated water vapor, annual sea level pressure, annual 500hPa geopotential height, summer sea surface temperature, and winter sea ice concentration; over the Arctic (> 50°N) and the Antarctic (<40°S) regions. We use the ERA5 reanalysis as a reference, but we also include 5 other reanalyses in the intercomparison in order to estimate uncertainty coming from this choice. We define two sets of metrics. The first set of metrics, called “scaled rmse”, is the spatial root mean square error (RMSE) of time-mean variables for each region, that we divide by the median RMSE among all CMIP models. The second set of metrics, called “implausible fraction”, is the portion of the region where the difference between time-mean CMIP model and time-mean ERA5 is greater than three times the local interannual standard deviation. We find a strong relationship between the two sets of metrics. In addition, using the implausible fraction, we find that CMIP variables are significantly more implausible in the Antarctic than in the Arctic. It might be because of badly resolved processes or because of higher decadal variability in the South. Further work should include estimates of decadal variability in the implausibility computation.

How to cite: Agosta, C., Kittel, C., Amory, C., Edwards, T., and Davrinche, C.: Evaluation of CMIP5 and CMIP6 global climate models in the Arctic and Antarctic regions, atmosphere and surface ocean, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11363, https://doi.org/10.5194/egusphere-egu22-11363, 2022.

Surface Mass Balance (SMB) is the key driver of ice sheet mass budget. It delivers the snow that nourishes ice sheets and the surface melt that balances snowfall and, along with ocean interactions, drives ice flow. We here present alternative future projections for both the Greenland and Antarctic ice sheets, driven by two different earth system models (ESMs), EC-Earth and CESM2, for two different emissions pathways (SSP585, 245) and in the case of EC-Earth for two different CMIP versions (EC-EARTH2 inCMIP5 and EC-EARTH3 in CMIP6).

We use the regional climate model (RCM) HIRHAM5 to downscale the global models to 5.5km resolution over the Greenland ice sheet and 12km resolution over Antarctica. HIRHAM5 output is then used to drive a surface mass budget model for both ice sheets.

The matrix of models and scenarios gives us the opportunity to examine how different factors, including atmospheric circulation indices, model resolution, ocean dynamics, sea ice and SMB components affect mass budget and sea level rise estimates over the course of the 21^st century. About half the difference between CMIP5 and CMIP6 SMB estimates is related to differences in the scenarios compared to the SSPs and about half is related to differences in the driving models. In addition, we compare with other published downscaled SMB estimates from different RCMs (MAR and RACMO) to assess the envelope of likely ice sheet evolution out to 2100. Both CESM2 and EC-EARTH3 have high equilibrium climate sensitivity, and our study correspondingly shows high ice sheet mass loss particularly from Greenland by the end of the century, in line with other published estimates under high emissions scenarios. Melt is increasingly important in both ice sheets, but especially Greenland over the course of the 21^st century and scales by temperature and therefore emissions pathway. All model projections show an increase in precipitation, but internal variability in circulation in the Southern Ocean still dominates the patterns in Antarctica and masks to some extent climate change signal in SMB.

Future work will extend the ensemble of SMB estimate with a direct statistically based method, that allows fast downscaling of ESM output directly to SMB using the Copenhagen Ice Sheet Surface Energy and Mass Balance modEL (CISSEMBEL) and we also present some early preliminary results comparing different downscaling techniques.

How to cite: Mottram, R., Boberg, F., Hansen, N., Langen, P., Yang, S., Larsen, M., and Rodehacke, C.: A Tale of Two Ice Sheets, SSPs, CMIPs and global models: future climate and surface mass balance projections for Greenland and Antarctica, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4154, https://doi.org/10.5194/egusphere-egu22-4154, 2022.

Mass loss from the Greenland Ice Sheet ice sheet has increased sixfold since the 1990s. With accelerated ice mass loss rates, it could become the largest contributor to sea-level rise in the 21^stcentury. Both the surface mass balance and outlet glacier retreat control this ice mass loss. The latter is decomposed between ice flow changes in the lower trunks of outlet glaciers (discharge) and calving of marine-terminating outlet glaciers. Partitioning between SMB and retreat contributors evolved through the last decade. It is uncertain how much they will contribute individually in the future. While a coupled RCM-ice sheet model helps to improve the SMB contribution, future glacier retreat contribution modelling is in its early stages. Using the RCM MAR, fully coupled to the GISM ice sheet model, we investigate the impact of the surrounding ocean on the outlet glaciers. Our parameterization, based on oceanic basins temperature and subglacial ice sheet runoff changes, simulates individual outlet glacier retreat rate. By forcing our atmosphere – GrIS – ocean-retreat-like model by several CMIP6 GCM models, we assess the 21^stcentury Greenland ice mass loss. Partitioning between mass loss from SMB and outlet glacier retreat forced by various CMIP6 SSP scenarios is estimated both at the regional and large Greenland scale.

How to cite: Le clec'h, S., Fettweis, X., and Huybrechts, P.: Quantifying 21st century Greenland ice mass loss from outlet glacier retreat and surface mass balance changes from coupled MAR-GISM simulations., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7883, https://doi.org/10.5194/egusphere-egu22-7883, 2022.

With a sea-level rise potential of 58 m sea-level equivalent, the future evolution of the Antarctic Ice Sheet under progressing warming is of importance for coastal communities, ecosystems and the global economy. Short-term projections of the sea-level contribution from Antarctica in the recent ice sheet model intercomparison ISMIP6 range from a slight mass gain (-7.8 cm) to a mass loss of up to 30.0 cm sea-level equivalent at the end of the century under Representative Concentration Pathway 8.5 (Seroussi et al., 2020, Edwards et al., 2021). However, due to high inertia of the system, the ice sheet response to perturbations in its climatic boundary conditions are rather slow. Consequences of potentially triggered unstable ice loss due to positive feedback mechanisms may therefore play out over long timescales (on the order of millennia).  Projections of the committed sea-level change at a given point in time, that is the sea-level change which arises by fixing the climatic boundary conditions and letting the ice sheet evolve over several millennia, might differ substantially from the sea-level change expected at that point in time (Winkelmann et al., 2022).

Previous assessments of the long-term contribution to sea-level rise from the Antarctic Ice Sheet have been primarily restricted to a single model and have rarely explored the full range of intra- and inter-model parameter uncertainties. Here, we determine the long-term, multi-millennial sea level contribution from mass balance changes of the Antarctic Ice Sheet by means of two ice sheet models, the Parallel Ice Sheet Model (PISM) and the fast Elementary Thermomechanical Ice Sheet (f.ETISh) model. More specifically, we assess the response of the Antarctic Ice Sheet to atmospheric and oceanic forcing conditions derived from state-of-the-art climate model projections available from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) under the Shared Socioeconomic Pathways SSP5-8.5 and SSP1-2.6 available until the year 2300. The sea-level commitment from the Antarctic Ice Sheet is quantified by branching off at regular intervals in time and running the ice sheet models for several millennia under fixed climate conditions. Key uncertainties related to ice dynamics as well as to interactions with the bed, atmosphere and ocean are taken into account in an ensemble approach.

How to cite: Klose, A. K., Coulon, V., Pattyn, F., and Winkelmann, R.: The long-term sea-level commitment from Antarctica, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7964, https://doi.org/10.5194/egusphere-egu22-7964, 2022.