Evolution passée des glaciers du massif du Mont-Blanc

Stage de 5-6 mois entre février 2022 et juin-juillet 2022

General context

Mountain glaciers represent an important part of the global cryosphere and, historically, have been the largest ice contributor to sea-level rise as their smaller volume and more marginal locations makes them more vulnerable to warming temperatures. Establishing their evolution over time is therefore key to a more accurate understanding of the impacts of climate change. Making predictions about these glaciers is challenging, however, when their past state is not well-known, as this affects the initial conditions of any prognostic model. In theory, a well-calibrated model should be able to project backwards as well as forwards in time, and allow us to better understand these past states.

Key points

For the first time, a robust workflow has been applied to all glaciers of the Mont-Blanc region to simulate their evolution for the coming next century. This calibrated model now allows us to look backwards in time and thus investigate the past extent of glaciation in this massif, using the optimal set of parameters derived as part of this new workflow. This provides an opportunity for a master student to research the past extent of glaciation in the Mont-Blanc area and to test whether the present-day parameterisations are valid through time, or are very specific to present-day conditions, by comparing model results to available historical observations. This will allow better understanding of temporal variations in glacial dynamics in the Mont-Blanc area and help refine modelling best-practice for Alpine glaciers with consequent improvements in predictions of sea-level rise.

Main objective

The student will use historical datasets of glacier geometry and local climate to force simulations in two models : OGGM (Open Global Glacier Model) and Elmer/Ice. These two models include different levels of complexity of glacier dynamics - OGGM is simpler (1D vertically integrated flowline), Elmer/Ice is more complex (3D full-Stokes) - and the student will also investigate whether one model or the other is more sensitive to any temporal changes in parameter values. This will provide additional useful information to the scientific community about possible biases in existing predictions of glacier volume change in mountainous areas across the world.

How to apply

To apply, please send us a CV and a motivation letter. Internship location is at the glaciology laboratory on the Saint-Martin d’Hères campus (IGE) and the duration is around 5-6 months.

References

1. Farinotti, D., Brinkerhoff, D.J., Fürst, J.J., Gantayat, P., Gillet-Chaulet, F., Huss, M., Leclercq, P.W., Maurer, H., Morlighem, M., Pandit, A., Rabatel, A., Ramsankaran, R., Reerink, T.J., Robo, E., Rouges, E., Tamre, E., van Pelt, W.J.J., Werder, M.A., Azam, M.F., Li, H., Andreassen, L.M., 2021. Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2). Front. Earth Sci. 8. https://doi.org/10.3389/feart.2020.571923

2. Peyaud V., C. Bouchayer, O. Gagliardini, C. Vincent, F. Gillet-Chaulet, D. Six and O. Laarman, 2020. Numerical modeling of the dynamics of the Mer de Glace glacier, French Alps : comparison with past observations and forecasting of near-future evolution, The Cryosphere, 14, 3979–3994, doi:10.5194/tc-14-3979-2020

3. Gillet-Chaulet, F., 2020. Assimilation of surface observations in a transient marine ice sheet model using an ensemble Kalman filter, The Cryosphere 14, 811–832, doi:10.5194/tc-14-811-2020

4. Farinotti D., H. Matthias, J. Fürst, J. Landmann, H. Machguth, F. Maussion and A. Pandit, 2019. A consensus estimate for the ice thickness distribution of all glaciers on Earth, Nature Geoscience, doi:10.1038/s41561-019-0300-3

5. Maussion, F., Butenko, A., Champollion, N., Dusch, M., Eis, J., Fourteau, K., Gregor, P., Jarosch, A. H., Landmann, J., Oesterle, F., Recinos, B., Rothenpieler, T., Vlug, A., Wild, C. T., and Marzeion, B. : The Open Global Glacier Model (OGGM) v1.1, Geosci. Model Dev., 12, 909–931, https://doi.org/10.5194/gmd-12-909-2019, 2019.

6. Zekollari, H., Huss, M., and Farinotti, D. : Modelling the future evolution of glaciers in the European Alps under the EURO-CORDEX RCM ensemble, The Cryosphere, 13, 1125–1146, https://doi.org/10.5194/tc-13-1125-2019, 2019.

7. Marzeion, B., Hock, R., Anderson, B., Bliss, A., Champollion, N., Fujita, K., Huss, M., Immerzeel, W., Kraaijenbrink, P., Malles, J., Maussion, F., Radić, V., Rounce, D. R., Sakai, A., Shannon, S., Wal, R. and Zekollari, H. : Partitioning the Uncertainty of Ensemble Projections of Global Glacier Mass Change, Earth’s Futur., 8(7), doi:10.1029/2019ef001470, 2020.

8. Eis J, van der Laan L, Maussion F and Marzeion B (2021) Reconstruction of Past Glacier Changes with an Ice-Flow Glacier Model : Proof of Concept and Validation. Front. Earth Sci. 9:595755. doi : 10.3389/feart.2021.595755.