The state and fate of the Antarctic firn layer: a modelling and machine learning study

Publication date

2025-06-18

Authors

Veldhuijsen, Sanne Bouwina MariaISNI 0000000512642825

Editors

Advisors

Supervisors

van den Broeke, MichielORCID 0000-0003-4662-7565ISNI 0000000389564445
van de Berg, Willem-JanORCID 0000-0002-8232-2040ISNI 0000000419423214
Wouters, B.ISNI 0000000080129605

Document Type

Dissertation
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Abstract

The Antarctic ice sheet contains about 70% of the Earth's freshwater, making it the largest freshwater reservoir on the planet. If only 10% of the ice sheet were to melt, it would raise global sea level by approximately 6 m. Currently, mass loss from the Antarctic ice sheet is the largest source of uncertainty in sea level rise projections. To reduce this uncertainty, it is important to enhance our understanding of ice-sheet processes. A key component of the ice sheet is firn, which is the transitional material between snow and ice. Firn covers nearly all the ice sheet as a thick protective blanket, with a thickness up to 100 m. This firn layer acts as a sponge, as it provides pore space, in which currently most of the surface meltwater refreezes. Depletion of the firn pore space can lead to meltwater ponding at the ice sheet surface. This poses a risk, particularly for ice shelves, the floating extensions of the ice sheet that fringe 75% of Antarctica’s coastline. When conditions are unfavorable, meltwater ponding can lead to hydrofracturing and subsequent ice-shelf disintegration. Given that many ice shelves buttress the flow of grounded ice, their collapse can trigger accelerated mass loss from the Antarctic ice sheet. In my thesis, I study the contemporary and future state of the Antarctic firn layer, and develop and improve the methods for its simulation. My main tool is the firn densification model IMAU-FDM. To improve and evaluate the model, I use in-situ and remote sensing measurements. To explore future firn evolution for a broad range of climate scenarios, I also developed a computationally efficient machine learning emulator.

Keywords

firn, emulator, ice slabs, firn aquifers, ijskap, zeespiegelstijging, projecties, klimaatverandering, machine learning, firn, emulator, ice slabs, firn aquifers, ice sheet, sea level rise, projections, climate change, machine learning, SDG 13 - Climate Action

Citation

Veldhuijsen, S B M 2025, 'The state and fate of the Antarctic firn layer : a modelling and machine learning study', Doctor of Philosophy, Universiteit Utrecht. https://doi.org/10.33540/2903