Academic Profile
Snow hydrology and geospatial data science for mountain water resources.
I am a snow hydrologist and geospatial data scientist interested in modeling mountain snow accumulation and melt at large scales. My work incorporates satellite remote sensing, numerical weather prediction, and non-linear optimization techniques to create post-processing models to improve our ability to estimate snow water equivalent at high resolution over large domains.
Ultimately, I am interested in how snowpack dynamics respond to climate variability and how we can better represent these processes to support water resource management. I am currently a postdoctoral researcher in the Pavelsky Global Hydrology Lab at the University of North Carolina at Chapel Hill.
Current Focus
Continental-scale SWE estimation
Developing downscaling and post-processing approaches that improve snow water equivalent estimates over large domains and in complex terrain.
Methods
Remote sensing, modeling, and optimization
Combining satellite observations, numerical weather prediction, and optimization techniques to improve large-scale snow estimation workflows.
Audience
Open work for researchers and collaborators
This site collects research themes, publications, datasets, and teaching materials connected to my current work in mountain hydrology and cryosphere science.
Research Themes
Three threads that organize the work
Snow water equivalent in complex terrain
Improving SWE model estimates in complex, mountainous basins where terrain and forcing variability challenge coarse-resolution products.
Scalable remote sensing workflows
Developing scalable methods for snow water equivalent estimation from remote sensing and remote-sensing-constrained snow models.
Climate-sensitive mountain hydrology
Studying how mountain snowpack dynamics respond to climate variability and how those changes shape water resources and cryosphere science.