Projects:

Climate-resilient machine learning

Climate change shifts natural distributions. This non-stationarity means that our measurements of the natural world may not accurately communicate climate change to us -- can machine learning tools help us adapt to rapidly changing distributions? This work focuses on increasing the speed of representing spatial patterns in management-relevant models.

Climate change impacts on snow drought

We know that climate change affects hydrological systems, but the details of how different regions will be impacted is still an open question. Snow drought, or a lack of snow water storage in a particular area, is expected to increase in the future due to warming temperatures, but snow drought can also be caused by changing precipitation patterns. This project undertakes an exploration of how predictions of statistical ranges of climate and weather will shift our expected distributions of snow drougths in the future. See Cowherd et al., 2023 below for more details.

How do megafires impact snow hydrology?

In the American West, we rely on snow for a large portion of our fresh water supply. The structure of forests in the places where snow falls has a large impact on what happens to snow -- does it sublimate to the atmosphere, get taken up by surrounding vegetation, infiltrate into the soil, or melt and run downstream to cities and agricultural regions in the spring? Large wildfires alter forest structure in the high mountains where snow falls and we do not fully understand how the types of forest change caused by fires will change what happens to snow in the future. We're using remote sensing, modeling, and field work to track and predict forest-snow interactions with a focus on regions where snow is a major water source for people. My work is on two areas of focus: 1) with field work in the Caldor Fire (South Lake Tahoe, California), how does fire change the spatial representativity of monitoring stations? and 2) increasing implementation of ML methods (e.g., LSTMs) to quantify fire's effect on climate-streamflow relationships in snowy basins in the US.

Interactive mapping of satellite fire detections

Geostationary satellites have orbits that keep them in the same location relative to the Earth's surface at all times. This allows the satellite to continuously image the same places. The GOES suite, operated by NASA, focuses on North America and produces as processed fire-detection dataset. In this project, originally a class project for Jeff Chambers's graduate remote sensing course at UC Berkeley, we create an interface through Google Earth Engine for exploring GOES fire detections with animations and almost real-time data updates Check out the map application here.

How do wave-current flows impact cohesive sediment transport?

Coastal erosion in the San Francisco Bay threatens the security of shoreline infrastructure. This field campaign from 2018 to 2020 deployed hydrodynamics instrumentation in the South Bay to measure near-bed flow and sediment concentrations. My work focused on phase decomposition of the wave signal in near-bed velocity profiles during a summer deployment. In this project, we developed a method for identifying instantaneous wave phase from a combined wave-current flow using the Hilbert transform and then tracked the timing of at-bed stress and turbulence over the bottom 1.5 cm of the water. We found that the variations in stress and turbulence during the passage of a single wave are high enough that the instantaneous stress can be much higher than reported by a long-term average and that there is a phase lag between stress and turbulence. See Cowherd et al., 2021 and Egan et al., 2019 below for more details.

Publications:

Cowherd, M. Leung, L.R., and Girotto, M. (2023) Evolution of global snow drought characteristics from 1850 to 2100. Environmental Research Letters.
doi.org/10.1088/1748-9326/acd804

Cowherd, M., Egan, G., Monismith, S., & Fringer, O. (2021). Phase‐resolved wave boundary layer dynamics in a shallow estuary. Geophysical Research Letters.
doi.org/10.1029/2020GL092251

Egan, G., Cowherd, M., Fringer, O., & Monismith, S. (2019). Observations of near-bed shear stress in a shallow, wave- and current-driven flow. Journal of Geophysical Research: Oceans.
doi.org/10.1029/2019JC015165

Undergraduate thesis: "Boundary layer fluid dynamics in South San Francisco Bay" (2019) advised by Oliver Fringer
purl.stanford.edu/wr832gx3390

Eduati, et. al., NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration*. Prediction of human population responses to toxic compounds by a collaborative competition. Nature Biotechnology 33, 933-40 (2015). *Collaborator
doi.org/10.1038/nbt.3299