This release contains the ISMIP6 Elmer/Ice configuration code, sif and the scripts to run the simulation of the paper :

Caillet, J., Jourdain, N. C., Mathiot, P., Gillet-Chaulet, F., Urruty, B., Burgard, C., Amory, C., Kittel, C., and Chekki, M.: Uncertainty in the projected Antarctic contribution to sea level due to internal climate variability, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-128, 2024.

This a copy of the 2023.v0 release.

ISMIP6 Antarctica 2300 Projections read me file

  Main Contributor name : Justine Caillet, Pierre Mathiot, Fabien Gillet-Chaulet email: justine.caillet at univ-grenoble-alpes.fr, pierre.mathiot at univ-grenoble-alpes.fr, fabien.gillet-chaulet at univ-grenoble-alpes.fr, affiliation: Université Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, Grenoble, France

Collaborators: Nicolas Jourdain, Benoit Urruty, Christoph Kittel, Clara Burgard, Mondher Chekki Date of submission to ISMIP6: 28/02/2023

1.     Describe the technique that you used to create an initial condition for projections of the ice sheet to  2300 in general terms, in particular does it assimilate observations of the present-day ice sheet or  spin the ice sheet up over a longer (glacial-interglacial) period, or another method?

The initial geometry (topography and ice thickness) corresponds to the second version of the BedMachineAntarctica dataset (Morlighem et al., 2020), slightly modified as Lake Vostok is not considered. Initial viscosity and friction parameter are inferred using inverse methods (Gillet-Chaulet et al., 2012, Brondex et al., 2019) to match the 2015-2016 surface ice velocities described in Mouginot et al., 2019. The historical run covers the period 1995-2014 and corresponds to the relaxation phase following the inversion of viscosity and friction coefficients. The role of this step is to reduce the inconsistencies between input data and inverted data when we switch from a diagnostic to a prognostic simulation (Gillet-Chaulet et al., 2012), which results in artificial high surface elevation rate of change. These anomalies usually disappear within a few years. During this phase, we also corrected both the ocean temperature to match the range of the 1994-2018 melt estimate from Adusumilli et al., 2020 and the friction to match the rates of ice-sheet mass change estimated by the IMBIE team (The IMBIE Team, 2018).

2.     Did you participate in ISMIP6 Antarctica Projections? In this case what is the corresponding  submission and were there any changes made since the submission?

No participation. Initialization methods

3.     Describe the initialization method used, including assimilation of data, spin-up, or any other  method.

Initial viscosity and friction parameter are inferred using inverse methods (Gillet-Chaulet et al., 2012, Brondex et al., 2019) to match the 2015-2016 surface ice velocities described in Mouginot et al., 2019.

4.     What are the tuning targets, constraints and outputs of your initialization procedure?

The objective of initialization is to define the viscosity and friction fields. Inverse methods are based on minimizing a cost function that calculate the mismatch between modeled and observed surface velocities. A smoothness constraint is added to the cost function under the form of a regularisation term (Gillet-Chaulet et al., 2012) to avoid overfitting of the data and improve the conditioning of the problem. This process results in spatial distribution of basal drag coefficient and viscosity enhancement factor.

5.     What procedures do you use to validate the initial conditions, or tests that you apply to the final  state of your initialization method?

During the ralaxation phase (historical run), we applied two types of correction :

• a uniform reduction of 10% of friction coefficient is applied to ensure that the model drift is limited with the current forcing and is consistent with the rates of ice-sheet mass change estimated by the IMBIE team for both West and East Antarctica (The IMBIE Team, 2018). This fixed correction is applied to all runs.
• an ocean temperature correction is applied in individual basins to ensure that the mean basal melt rates are within the range of the 1994-2018 estimates from Adusumilli et al., (2020). The temperature corrections range from -1.8° to 0.6° with respect to the ISMIP6 present-day ocean forcing. This fixed temperature correction is applied to all runs.

6. What dataset is used for the SMB climatology?

The SMB climatology is the average output of the atmospheric model RACMO2.3 (v2.3p2) over the period 1995-2014. The RACMO configuration used here is described and evaluated in van Wessem et al. (2018). It is forced by ERA-Interim (Dee et al. 2011), has a resolution of 27 km and topography is based on the DEM from Bamber et al. (2009). Model parameters

7. Do you apply corrections, such as SMB corrections? Please provide a description.

  A few adjustments were needed to ensure that all the simulations converged. These included adjusting the time step (between 0.625 day and 2.5 days) and removing the isolated ice islands (less than 7-35 cells – variable temporal frequency) during the disintegration of the ice shelves in the most critical scenarios in terms of surface loss.

8. How is ocean-induced melt parameterized at the bottom of floating ice? How is melting applied to  partially floating cells (if applicable)?

No melt is applied to grounded or partially floating mesh elements.

9. What parameterization is used to migrate the grounding line? How are partially floating cells  treated?

The grounding line position is determined using a flotation criterion and a sub-grid scheme is applied for the friction in partially floating elements (SEP3 in Seroussi et al., 2014).

10. How is ice front migration treated? What calving law or calving rate are used?

A fixed front is considered, which means that the calving flux is assumed to be the opposite of the ice flux at the front. We nonetheless impose a minimum ice-shelf thickness of 1 m and areas of 1m-thick are considered to be unglaciated in the outputs. Projections Please detail what is applied in both the open and standard experiments when modeling choices differ.

11. How many experiments did you perform? List them according to the list of experiments.

We ran the Tier 1 Experiments (control run and projection runs from 1 to 6) over the period 2015-2300 as well as one historical run (1995-2014), i.e., 8 simulations.

12. How was your "historical simulation" performed? What forcing dataset did you use to bring your ice  sheet model from initialization date to the end of historical (end of December 2014)?

The historical run covers the period 1995-2014 and corresponds to the relaxation phase following the inversion of viscosity and friction coefficients from 2015-2016 surface ice velocities described in Mouginot et al., 2019 and ice surface height of seconde version of the BedMachineAntarctica dataset (Morlighem et al., 2020). The role of this step is to reduce the inconsistencies between input data and inverted data when we switch from a diagnostic to a prognostic simulation (Gillet-Chaulet et al., 2012), which results in artificial high surface elevation rate of change. These anomalies usually disappear within a few years. For this run, we chose :

• the reference atmospheric forcing : The reference SMB is the average output of the atmospheric model RACMO2.3 (v2.3p2) over the period 1995-2014. A conservative interpolation on the Elmer grid is used to ensure the conservation of the fluxes. The RACMO configuration used here is described and evaluated in van Wessem et al. (2018). It is forced by ERA-Interim (Dee et al. 2011), has a resolution of 27 km and topography is based on the DEM from Bamber et al. (2009),
• the average ISMIP6 ocean forcing (T, S) over the period 1995-2014 (Jourdain et al., 2020). A temperature correction is added to ensure that the historical basal melt rates are realistic (see answer to question 7).

13. What parameterization did you use to compute the ocean induced melt under the ice shelves?  Explain parameterizations used for both the open and standard experiments.

Basal melt rate is estimated using the PICO parameterization (Reese et al., 2018). PICO parameterizes the vertical overturning circulation in ice-shelf cavities and includes a formulation of the ice-ocean boundary layer. For each of these processes, PICO has one parameter, which is constant across all Antarctic ice shelves. The parameter C influences the strength of the vertical overturning circulation, and the parameter γT describes the vertical heat exchange coefficient at the ice-ocean interface, which in reality depends on the ocean velocity and the ice roughness (Reese et al., 2022 (subm)). We kept the PICO configuration used in Urruty et al. (subm). The γT and C parameters are those estimated in Reese et al. (subm) (i.e., C = 2 Svm3.kg-1 and γT = 5.5.10-5 m.s-1) and the number of boxes (fixed at 5 maximum) depends on the distance to the front and the grounding line. The ocean temperature and salinity correspond to the sea-floor temperature and salinity values averaged over the 50 km area in front of the ice shelf as described in Burgard et al. (subm). A single bottom salinity and temperature are considered for each basin according to the division described in Reese et al., (2018), i.e., 19 basins. In order to make the historical state as realistic as possible, a temperature correction per basin is added as described in the previous answer.

14. What SMB corrections (e.g., surface elevation feedback) do you apply in the open and standard  experiments?

No correction.

15. Do you include bedrock adjustments? How?

No.

16. How are tributary glaciers treated following ice shelves collapse?

We did not run the optional collapse experiment.

17. Please list any additional details, papers or reports that document your procedure, or model.

The 365-day calendar is used and the reference date is set to 01/01/1995 (start date of the historical run). The finite element model Elmer/Ice (Gagliardini et al., 2013) is used in a global configuration of the Antarctic ice sheet (version v9.0). The detailed description of the configuration is available in Urruty et al. (subm). The ice flow velocity is computed solving the Shallow Shelf Approximation (SSA) of the Stokes equations, assuming an isotropic rheology following Glen's flow law. In floating areas, the friction parameter cannot be inverted. A default value is set to 1 Pa.m-1.y  in case of grounding line advance. The ice viscosity is constant, i.e. not affected by potential changes in temperature or damage.

18. Please complete the following Model Characteristic Table:

|Characteristic | Sample answer ||Reference, if  applicable | |:--- | :--- | :---| :---| |Numerical Method | Triangular finite, element, Arbitrary  Lagrangian eulerian | Triangular finite element (unstructured mesh)|| |Native Grid (horizontal and  vertical) | H: anisotropic  (between 1km on fast  ice stream to 15km in  the interior) V: 17 layers (terrain  following)| H : An anisotropic mesh adaptation scheme provides a refined mesh along the directions of highest curvature of observed ice velocities and ice thickness with an additional criterion function of the distance to the grounding line. The resulting mesh contains ~500 000 nodes and ~1 000 000 linear elements and the size varies from 1 km close to the grounding line to 50 km in the ice sheet interior. || | Native Projection | same as Bamber 2001| Polar stereographic || |Interpolation method to diagnostic grid | ISMIP6 suggested procedure | ISMIP6 suggested procedure || | Time step | 2 months | 1.25 days or 2.5 days || | Ice Flow Mechanics | Higher order (Blatter Pattyn) | Shallow Shelf Approximation SSA || | Basal Sliding | Weertman sliding law  (m=3) | Weertman sliding law  (m=1) || | Basal Hydrology | None | None || | Ice shelves | Yes | Yes || | Advance and Retreat | Freely evolving, grounded ice margin,  grounding line, and  calving front | Freely evolving  grounded ice margin and grounding line. Fixed calving front. We impose a minimum ice-shelf thickness of 1 m. || | Grounding Line:  Determination,  Parameterization | floating criterion | floating criterion || |Calving | calving occurs if thickness falls below  threshold of 50m | Fixed front. No calving || | Initial Surface Mass  Balance | Positive degree day  (Reeh, 1991) with  temperature  dependent factors  following Tarasov and  Peltier | average output of the atmospheric model RACMO2.3 (v2.3p2) over the period 1995-2014 (van Wessem et al. (2018)) || | Year (or range of  years) assigned to  initial condition | 2000 | 1995 || | Parameters for ice  and water density  (rho_i, rho_w),  gravitational  acceleration (g), etc | rho_i= 900kg m-3, rho_w= 1000kg m-3 and g = 9.8 m s-2| rho_i = 9917kg m-3, rho_fw = 1000 kg m-3  (freshwater), rho_sw = 1028 kg m-3  (sea water), g = 9.81 m s-2 || | Variable in data  request not included  and reason | None | See below || | Other comments | None | See below || The area of minimum ice-shelf thickness (1 m thick) are considered to be unglaciated in the different masks (i.e., equal to 0) and were assigned a zero flux. All output variables are masked except for the bedrock (topg). Some data are omitted:

• hfgeoubed, litemptop, litempbotgr, litempbotfl: the thermodynamic aspect is neglected by considering a stationary temperature,
• xvelsurf, yvelsurf, zvelsurf, xvelbase, yvelbase, zvelbase: the ice flow velocity is computed solving the Shallow Shelf Approximation (SSA) of the Stokes equations (vertically integrated field), so by assumption the horizontal velocities are uniform across the whole ice column and equal the mean horizontal velocity,
• licalvf, tendlicalvf: the calving is neglected by considering a fixed front.

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