Emily Geyman

2021 Hertz Fellow
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Emily Geyman studies perturbations to Earth’s climate across history in order to better predict and understand the climate response to greenhouse emissions in the next century.

Emily has spent the last two years living in the Arctic Circle, Norway, as a Daniel M. Sachs Global Scholar at Princeton University. Using archives of aerial imagery dating back to the 1930s, she has used structure-from-motion techniques to reconstruct changes in the volume and geometry of about 2,000 Arctic glaciers over the last century. Now she is developing geometric and mass balance models—calibrated using her historical record—to simulate how Arctic glaciers will respond to a warmer, wetter climate and contribute to sea level rise in the coming century. She will pursue her research as a PhD student at the California Institute of Technology in fall 2021.

Emily became hooked on geoscience as an undergraduate at Princeton University. For her thesis, she used a combination of field geology and geophysics, satellite remote sensing, and lab geochemistry to understand how sediments accumulating today turn into rock and encode information about Earth’s climate. Her ultimate goal was to build strong translation tools from modern analogue environments so that we can more accurately reconstruct ancient climate dynamics from the geologic record. This work led to five first-authored publications and gave her the opportunity to work on diverse sets of geological questions in the Bahamas, Namibia, Australia, France, Spain, and the Yukon.

A native of Seattle, Emily enjoys ultra-running, ski mountaineering, cross-country skiing, playing soccer, reading, knitting, and baking bread.

"Geocience is special because the observations and laboratory are basically the world that we live in." 
– Emily Geyman

Graduate Studies

California Institute of Technology
Geology, Earth Science

Undergraduate Studies

Princeton University

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2021 Hertz Fellow Emily Geyman studies perturbations to Earth’s climate across history in order to better predict the climate response to greenhouse emissions.