Glacier Geophysics

I use geophysical observations, mainly radar sounding, to reveal the physical state of ice sheets from surface to bed. Radar data can capture variations in ice properties and basal thermal and hydrologic conditions, yet quantitative analyses remain uncommon. My work advances these capabilities by applying statistical and machine learning approaches to extract robust physical insight from radar echoes.

For example, I developed a statistical framework to classify frozen and thawed bed conditions beneath the outflow of the Wilkes Subglacial Basin in East Antarctica, along with confidence estimates for each classification. This analysis not only revealed variable basal conditions in a region critical to East Antarctica's stability but also marked the first radar-based assessment of subglacial thermal state in this region. These findings were covered in Stanford Engineering News. By turning radar observations into physically interpretable classifications, this work opens the door to using thermal state maps as direct constraints in ice sheet models.