Preprints
https://doi.org/10.5194/egusphere-2024-862
https://doi.org/10.5194/egusphere-2024-862
23 Apr 2024
 | 23 Apr 2024
Status: this preprint is open for discussion.

The future of Upernavik Isstrøm through ISMIP6 framework: Sensitivity analysis and Bayesian calibration of ensemble prediction

Eliot Jager, Fabien Gillet-Chaulet, Nicolas Champollion, Romain Millan, Heiko Goelzer, and Jérémie Mouginot

Abstract. This study investigates the uncertain future contributions to sea-level rise in response to global warming of Upernavik Isstrøm, a tidewater glacier in Greenland. We analyze multiple sources of uncertainty, including shared socio-economic pathways (SSPs), climate models (global and regional), ice-ocean interactions, and ice sheet model parameters (ISM). We use weighting methods based on spatio-temporal velocity and elevation data to reduce ice flow model uncertainty, and evaluate their ability to prevent overconfidence. Our developed initialization method demonstrates the capability of Elmer/Ice to accurately replicate the historical mass loss of Upernavik Isstrøm. This provides confidence in the model's ability to project the future evolution of this region. Future mass loss predictions range from a contribution to sea level rise from 1.5 to 7.2 mm, with an already committed sea-level contribution projection from 0.6 to 1.3 mm. While all sources of uncertainty contribute at least 15 % to uncertainty until the end of the century, SSP-related uncertainty dominates at 40 %. We find that calibration does not reduce uncertainty of the future mass loss between today and 2100 of Upernavik Isstrøm (+2 %) but significantly reduces uncertainty in the historical mass loss of Upernavik Isstrøm between 1985 and 2015 (-32 to -61 % depending on the weighting method). Combining calibration of the ice sheet model with SSP weighting yields uncertainty reductions of future mass loss in 2050 (-1.5 %) and in 2100 (-32 %).

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Eliot Jager, Fabien Gillet-Chaulet, Nicolas Champollion, Romain Millan, Heiko Goelzer, and Jérémie Mouginot

Status: open (until 22 Jun 2024)

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Eliot Jager, Fabien Gillet-Chaulet, Nicolas Champollion, Romain Millan, Heiko Goelzer, and Jérémie Mouginot

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The future of Upernavik Isstrøm : Sensitivity analysis and Bayesian calibration of ensemble prediction Eliot Jager https://doi.org/10.5281/zenodo.10794469

Eliot Jager, Fabien Gillet-Chaulet, Nicolas Champollion, Romain Millan, Heiko Goelzer, and Jérémie Mouginot

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Short summary
Our study projects uncertainties through ISMIP6 framework for Upernavik Isstrøm, a tidewater Greenlandic glacier. We validate our ice sheet model against past data and quantify uncertainties in SSPs, climate models, ice-ocean interactions, and parameters. We highlight that future CO2 emissions via SSPs is the major uncertainty source at the end of the century. Finally, we show how uncertainties can be reduced using Bayesian calibration, the robustness of which is verified by cross-validation.