Stanford University
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Woods Seminar | Improving the Understanding of Snow Processes and Hydrometeorology Using Remote Sensing | Laurie Huning, UCI

When:
Monday, Feb 25, 2019 4:15 PM
Where:
Y2E2 Building, Room 299
More Info:
Woods Seminar | Improving the Understanding of Snow Processes and Hydrometeorol…
Audience:
Faculty/Staff, Students
Sponsor:
Stanford Woods Institute for the Environment

Large populations across the western United States depend on seasonal snowmelt derived from mountainous regions for the majority of their water resources. Despite advances in the remote sensing of snow, estimating the amount of water stored in the snowpack, its distribution, and how it is changing over mountainous regions remains a significant challenge for hydrologic and water resources applications. I present work that combines remote sensing and modeling to overcome previous data limitations with a new, high-resolution (90-m, daily) snow reanalysis spanning over three decades across the Sierra Nevada. Using this historical snowpack information, I characterize the climatology and interannual variability of snowfall (e.g., distribution, accumulation rate, orographic relationships, etc.). I also explore climate related questions with a multivariate, probabilistic framework to understand the extent to which the mountain snowpack responds to different levels of atmospheric warming.

Results indicate that the Sierra Nevada snowpack accumulates during a relatively short cold season where a few large snowstorms (e.g., atmospheric rivers) can be the difference between a wet or dry year across the range. Insight into the interannual and spatial variability of snowstorms, snowfall distributions, and snow water equivalent can be used to improve streamflow forecasts, reservoir operations, etc. Potential future directions for quantifying water resources, developing near-real time hydrologic monitoring systems, and improving variability and uncertainty estimates of hydrologic states and land-atmospheric interactions with remote sensing and modeling will be discussed.

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