Graduate Project
 

Spatio-temporal patterns and trends in MODIS-retrieved radiative forcing by snow impurities over the Western U.S. from 2001 - 2022

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https://ir.library.oregonstate.edu/concern/graduate_projects/0k225k664

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  • Seasonal mountain snowpack of the western US (WUS) is a key water resource to millions of people. Impurities at the snow surface directly affect snowmelt timing and rate, as they contribute to earlier peak streamflow, snow disappearance, and less water availability in dry months. Predicting the locations, timing, and intensity of impurities is challenging, and little is known concerning how RF has changed over the past decades. Here we contribute a novel analysis of the magnitude and spatio-temporal variability of snow radiative forcing (RF) across the WUS at 3 distinct spatial scales using remotely sensed RF from MODIS data sets (MODSCAG/DRFS) from 2001-2022. To establish spatial patterns, we calculated a single pixel-integrated value of RF from March 1st - June 30th for the 22 years. A Mann-Kendall significance test was used to detect long-term trends, and Theil-Sen's slope analysis was used to determine trend magnitude. We found the greatest snow RF in the Upper Colorado region, with notable RF in less-studied regions, (such as the Great Basin and Pacific Northwest), that watersheds with greater temporal variability tend to have greater spatial variability, and that these watersheds are more associated with arid regions. Trends of snow RF are largely stable in the WUS; only a small percent of mountain ecoregions (0.03-8%) had significant trends in RF, and these were typically negative. All mountain ecoregions exhibited a net decline in RF on snow, with the most ubiquitous and widespread decline seen in the Sierra Nevadas. This study helps inform where and when RF impacts on snowmelt may need to be considered in hydrologic models.
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