ENGS 88 Honors Thesis (AB Students)

Degree Program

A.B.

Year of Graduation

2021

Faculty Advisor

Colin Meyer

Document Type

Thesis (Senior Honors)

Publication Date

Spring 6-7-2021

Abstract

Climate change is rapidly melting ice and snow worldwide, increasing the production of meltwater on ice sheets and glaciers. Depending on temperature, porosity, and saturation conditions, meltwater may move horizontally as runoff, refreeze into ice, or be stored as a liquid within the snow. When water is stored in the snow for multiple years, it is considered a perennial firn aquifer. These aquifers have received recent attention due to their potential to act as a buffer against sea level rise. Though it is still unclear if this connection truly exists, these features remain of interest to scientists trying to understand the dynamics of ice sheets and glaciers. This paper employs a MATLAB model from Meyer and Hewitt (2017) to examine the impact of future conditions on the temperature of the firn and the presence of perennial firn aquifers. The main conditions that determine the presence or absence of firn aquifers are accumulation rate and surface energy forcing, so this paper uses the model to test a wide range of both of these variables. The values tested were based on plausible future projections, making the plot a roadmap for the impacts of climate change. Increasing radiation is shown to reduce firn aquifer formation, but if accumulation rate also increases, this could counteract that effect. This paper then examines the impact of surface porosity on firn aquifer formation, determining that porosity does not have a large impact due to small future changes predicted and only minor differences between plots. Lastly, Meyer and Hewitt’s model outputs are compared with data collected by Miller et al., validating the model as a close approximation of real data. There were some small differences between plots, most notably in the transition between winter and summer. Therefore, in the future, the model should be modified to better match the sharp transition that occurs in Miller et al.’s data.

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