Year of Award

2019

Document Type

Dissertation

Degree Type

Doctor of Philosophy (PhD)

Degree Name

Mathematics

Department or School/College

Mathematical Sciences

Committee Chair

Jesse Johnson

Commitee Members

Jesse Johnson, Joel Harper, John Bardsley, Cory Palmer, Stephen Price

Keywords

glaciology, greenland, modeling

Subject Categories

Partial Differential Equations

Abstract

Warming temperatures have led to accelerating ice loss from the Greenland ice sheet, contributing to global sea level rise. Understanding the stability of the Greenland ice sheet to further warming is crucial to estimating rates of sea level rise over the next century. Estimating sea level rise is complicated by uncertainties in the physical mechanisms governing ice motion as well as uncertainties in the broader Arctic climate system of which the ice sheet is an integral part. In chapter 2, we focus on how surface melt water input to the ice sheet bed influences the rate of basal sliding, which is thought to depend on the seasonal evolution of the subglacial drainage system. Models of subglacial drainage have developed considerably in recent years. However, the recent sublglacial hydrology model intercomparison project (SHMIP), presented in Appendix A, shows that a wide gamut of models underpredict subglacial water pressure in winter when compared to borehole water pressure observations from Greenland. We investigate possible causes for this unphysical model behavior, ranging from poorly constrained model parameters to uncertainties in the physical equations for subglacial drainage. We conclude that the mismatch between modeled and observed winter water pressure can be remedied by dynamically adjusting the hydraulic conductivity parameter, which accounts for missing physics in the models describing seasonal changes in drainage system connectivity. Chapter 3 focuses on contextualizing modern climate change in the Arctic by investigating past changes in temperature and precipitation. In particular, we exploit a new chronology of ice sheet retreat in west Central Greenland, along with a novel data assimilation method based on the unscented transform (UT), to estimate changes in precipitation during the Holocene Thermal Maximum (HTM) -- a period of higher than modern temperatures that occurred some eight-thousand years ago. We demonstrate the effectiveness of the UT as a method for data assimilation and uncertainty quantification and show new evidence that the HTM was associated with greater than modern snowfall, which helped mitigate ice sheet retreat.

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© Copyright 2019 Jacob Zachary Downs