Research Areas

Breakthroughs in understanding cryospheric change will come from integrating methodologies across disciplines. However, in glaciology, observational and modeling studies often occur in isolation, and there are inadequate crossovers between glaciologists, oceanographers, and climate scientists.

My research challenges these divisions. With my background in glaciology, geophysics, and climate science, I apply this broad knowledge to develop new methods that combine ice sheet models and geophysical observations, work that has been funded by NOAA and the NSF. I also collaborate with planetary radio science experts to address terrestrial radioglaciology challenges, and I work with oceanographers to explore the interactions between Southern Ocean forcing and the stability of the Antarctic ice sheet. Additionally, my undergraduate work in Atmospheric Science included Arctic climatology research. My interdisciplinary approach gives me a unique perspective for understanding ice sheet dynamics and the broader impacts of climate change.

One of my areas of expertise is utilizing numerical models to simulate ice sheet dynamics. These models are essential for predicting future cryospheric changes via simulating how ice sheets might respond to various environmental factors, particularly climate change. For instance, my work with the Ice-Sheet and Sea-Level System Model (ISSM) has uncovered a potential vulnerability of the Antarctic ice sheet due to climate warming—the impact of thawing at the ice-bed interface on ice-sheet mass loss. In regions where the bed is currently frozen but close to thawing, just a slight increase in basal temperature could significantly reduce basal friction, leading to additional mass loss from the Antarctic ice sheet. You can find out more about this work here.

I am also focused on the characterization of englacial and subglacial ice sheet conditions through radar sounding observations. Radar sounding can provide powerful observational constraints on the englacial material properties and thermal and hydrologic conditions of the bed. However, quantitative analysis of radar sounding data remains relatively rare. Statistical and machine learning approaches will be at the forefront of future radar sounding data analysis and can unlock new subsurface ice sheet insights. For example, I developed a novel statistical approach applied to radar data near the outflow of Wilkes Subglacial Basin in East Antarctica to locate regions where the bed is frozen and thawed, along with levels of confidence in the thermal state classifications. Not only did this analysis reveal variable basal thermal conditions in areas controlling the regions stability, but it also comprised the first radar-based assessment of subglacial thermal conditions. This work shows that novel methodological approaches can make it possible to observationally classify frozen and thawed bed, thereby laying the groundwork to use radar-inferred thermal state observations as model constraints.