Forest Canopy Density Effects on Snowpack Across the Climate Gradients of the Western United States Mountain Ranges

Journal Article · 05 January 2022 · Water Resources Research

DOI: https://doi.org/10.1029/2020wr029194 · OSTI ID:1908324

Sun, Ning  ^[1]; Yan, Hongxiang  ^[1]; Wigmosta, Mark S.  ^[2]; Lundquist, Jessica  ^[3]; Dickerson‐Lange, Susan  ^[4]; Zhou, Tian  ^[1]

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1. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
2. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); University of Washington, Seattle, WA (United States)
3. University of Washington, Seattle, WA (United States)
4. Natural Systems Design, Seattle, WA (United States)

Limitations inherent to field studies such as limited spatial and temporal coverage has made it very challenging, if not impossible, to explicitly disentangle the effect of canopy density from climate on snowpack dynamics. Hence, our understanding of how variations in canopy density can affect snow processes under diverse climate conditions has been limited. To address this knowledge gap, this study uses a physics-based modeling approach to represent most key processes that drive snow accumulation and melt in the open and forest with varied forest density, across the climate gradients of the Western U.S. mountain ranges, as represented by 228 Snow Telemetry (SNOTEL) locations. Simulations suggest that, under most winter climate conditions, canopy density exerts a strong influence on under-canopy snowpack dynamics and their controlling processes. Changing canopy density can shift the direction of the modeled differential peak snow accumulation and snow disappearance date (SDD) between the open and forest. For example, while simulated snowpack lasts longer in the open than the high-density forest at most wet/warm and dry/cold locations by up to 55 days, about 90% of all locations show a longer snow duration in the low-density forest by up to 27 days as compared to the open. Interannual variability in climate can also change the magnitude and direction of canopy impact on snow processes. By comparing model simulations to published field observations, and we also identify conditions that require additional field observations to improve process-scale understanding of forest-snow interaction.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Bioenergy Technologies Office
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 1908324
• Report Number(s): PNNL-SA-158006
• Journal Information: Water Resources Research, Journal Name: Water Resources Research Journal Issue: 1 Vol. 58; ISSN 0043-1397
• Publisher: American Geophysical Union (AGU)Copyright Statement
• Country of Publication: United States
• Language: English