Snow Accumulation and Firn Properties Across The Antarctic Ice Sheet

Keenan, Eric

Graduate Thesis Or Dissertation

Snow Accumulation and Firn Properties Across The Antarctic Ice Sheet Public Deposited

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Citations

Citeable URL: https://scholar.colorado.edu/concern/graduate_thesis_or_dissertations/w0892c48r

Abstract

As anthropogenic climate change accelerates, the stability of the Antarctic Ice Sheet has come under increased scrutiny. Being Earth's largest body of frozen water, Antarctica sequesters enough ice that if melted entirely, would raise global sea level by more than 58 m. Glaciologists quantify Antarctica's past and present contribution to sea level rise by calculating its mass balance, which is defined as the rate of change of mass per unit time. One of our primary tools for calculating mass balance is repeat satellite altimetry, which entails converting observed changes in ice sheet surface elevation (and thus volume) into changes in mass. Unfortunately, this conversion is confounded by the spatially heterogeneous, vertically evolving, and time-variant density of Antarctica's thick (10s to 100s of meters) firn layer which covers ~99% of the ice sheet. In this dissertation, we develop models designed to simulate Antarctic firn properties with the goal of improving Antarctic mass balance estimates. We first demonstrate improved modeled firn density simulations by adapting an existing one-dimensional snow model to account for drifting snow, which is a ubiquitous feature of the Antarctic surface climate. Next, we improve our understanding of the spatial patterns of Antarctic snow accumulation by incorporating our single-column model's snow redistribution module into a distributed, three-dimensional modeling framework. Finally, we further constrain Antarctic mass balance by leveraging machine learning techniques to scale our improved physics-based firn models across the entire ice sheet. Overall, our improved models and process understanding help to contextualize past and present Antarctic Ice Sheet mass balance, which is essential for informing future projections.

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