Incorporating satellite-derived albedo into a snow energy balance model changes how we simulate melt in dust-affected headwaters with implications for water supply forecasting.
Commercial satellite stereo imagery can produce 3 meter snow depth maps across consecutive winters with accuracy comparable to airborne lidar, a promising approach for mountain snow monitoring.
We examine characteristic shifts in the days when snow actually accumulates and melts to better understand how storm days are changing in a warming climate and how extreme events affect snowpack.
Great presentations from the SnowHydRO lab at this year’s Joint Eastern/Western Snow Conference in Denver, CO!
Our paper on snow darkening in the Great Salt Lake Basin has been accepted to Water Resources Research
Had a blast presenting our work at the SnowHydro 2026 conference in Jaca, Spain
AGU 2025 conference in New Orleans, LA
Presented at the ASO Inc. Annual Workshop in South Lake Tahoe, CA
Happy to collaborate on work shared in two oral presentations at IGARSS 2025 in Brisbane, Australia
Joined the University of Utah faculty as a Research Assistant Professor
Presented at the Western Snow Conference in Bozeman, MT!
Presented our work on remote sensing informed snow modeling at AGU 2024 conference in Washington DC!
Selected for a 3 year NASA Terrestrial Hydrology Program award to study the role of albedo in snowmelt.
ASO Inc. Annual 2024 Workshop in South Lake Tahoe, CA!
Our paper on surface mass balance of debris-covered glaciers has been accepted to the Journal of Glaciology.
Joined the Snow Hydrology Research-to-Operations Lab as a Postdoctoral Research Associate.
Our dataset supporting Six Seasons of Stereo Snow Depth Maps has been published on NSIDC.
Our paper on Six Seasons of Stereo Snow Depth Maps has been published in Geophysical Research Letters.
Defended my PhD Thesis ‘Quantifying seasonal snow using very-high-resolution stereo optical satellite images’. 🎓
Received the Dr. James E. Church Award for Best Student Presentation at the Western Snow Conference in Flagstaff, AZ.
A systematic evaluation of satellite stereo parameters affecting DEM accuracy and precision over a snow-covered mountain site.
A satellite stereo DEM time series approach estimates surface mass balance for debris-covered glaciers, disentangling elevation change signals from ice flow dynamics to isolate geodetic mass balance.
A regression model using snow depth, day of water year, winter precipitation, and temperature continentality converts depth measurements to SWE estimates at locations without weather instrumentation, outperforming existing bulk density equations.