Dr. Jessica Badgeley is a senior research scientist who studies how ice sheets and glaciers respond to climate shifts – from glacial-interglacial transitions to seasonal cycles to modern and future climate change. She combines observations and numerical models using formal data assimilation methods and model-data comparisons to learn about how ice sheets and glaciers interact with the climate system. By understanding the past and present, she aims to integrate this knowledge into model initializations, physics, and parameterizations to improve future projections of ice sheet and glacier mass change, which ultimately impact sea level and freshwater availability.
Previously, Jessica was a James S. McDonnell Foundation Postdoctoral Fellow at Dartmouth College. Under the mentorship of Dr. Mathieu Morlighem and Dr. Hélène Seroussi, she developed expertise in the Ice-sheet and Sea-level System Model (ISSM) and its variational data assimilation capabilities to model glacier behavior over the historical period, with a particular focus on seasonal glacier dynamics in Greenland. Jessica earned her PhD from the Department of Earth and Space Sciences, University of Washington in 2022. Under the mentorship of Dr. Eric Steig, Dr. Greg Hakim, and many others, Jessica used ensemble Kalman filter data assimilation to reconstruct Greenland climate, worked towards reconstructions of paleo ice sheet evolution during the last deglaciation, and helped develop ice-flow modeling software.
Though Jessica’s research currently leans towards modeling and data analysis, she has spent several seasons of fieldwork in Antarctica (2013, 2016), Greenland (2017), and Alaska (2021, 2022) to study ice sheets and glaciers.
Selected Projects
Greenland Ice Sheet Seasonal Dynamics
“Impact of Seasonal Ice Velocity on the Mass Balance of Greenland Outlet Glaciers”
NASA ROSES 2023, A.15 Cryospheric Science (2025-2028)
Collaborators: Dr. Michalea King
Summary: Outlet glacier velocities in Greenland vary on seasonal timescales, and recent work suggests that capturing this variability in models is important for accurate estimates of present and future mass balance. Ice front positions and subglacial hydrology influence seasonal to interannual ice flow velocities, yet most studies that relate these variables rely on idealized models, observations only, or are limited to individual or small samples of glaciers. These caveats have made it challenging to quantify causal linkages for seasonal glacier dynamics, and most importantly, have limited our understanding and confidence on how seasonal changes in velocity will impact net mass balance of glaciers and the ice sheet in the future.
In this study, we will synergize new modeling approaches with dense observations to better constrain the dominant drivers of outlet glacier seasonality and quantify how this seasonality impacts ice sheet mass balance. Specifically, we will investigate the extent to which ice fronts and subglacial hydrology control seasonal velocities for each glacier in our large study sample, as well as the evolution of the relative contributions of each driver as the climate and ice sheet change. We will leverage these insights to develop and test more informed approaches to incorporating seasonal processes in model simulations and, finally, determine the spatial and temporal scales necessary in models for accurate simulations of mass change.
Juneau Icefield Ice-Atmosphere Interactions
“Quantifying near-surface temperature lapse rates: a path to improved melt estimates for the Juneau Icefield, Alaska”
University of Washington, PCC Climate Science Research Acceleration Fund (2024-2025)
Collaborators: Dr. Mira Berdahl and Daniel Otto
Summary: Alaska’s glaciers are only beginning to retreat due to recent warming and are expected to continue losing mass over the coming decades. To project glacier mass change and melt evolution, most studies downscale or extrapolate temperature to the local topography using near-surface temperature lapse rates – the rate of temperature change with elevation. This assumption is problematic because lapse rates have been shown to vary in space and time. Moreover, glaciated regions are typically not well-observed, and simple assumptions about lapse rates may not hold in this unique environment.
We will directly measure the spatial and temporal variability of temperature lapse rates on the Juneau Icefield, a glacier complex in Alaska. Spring 2025, our team is deploying an extensive array of low-cost temperature sensors across the Juneau Icefield and the surrounding region. This network of sensors will collect data over the entire summer melt season. The goal is to use this dataset to better estimate current and future melt in this critical region and will lead to general insights into the unique meteorological conditions in glacierized regions.