Challenges and Capabilities in Estimating Snow Mass Intercepted in Conifer Canopies With Tree Sway Monitoring

Raleigh, Mark S.; Gutmann, Ethan D.; Van Stan II, John T.; Burns, Sean P.; Blanken, Peter D.; Small, Eric E.

doi:10.1029/2021wr030972

Challenges and Capabilities in Estimating Snow Mass Intercepted in Conifer Canopies With Tree Sway Monitoring

Journal Article · Wed Mar 02 00:00:00 EST 2022 · Water Resources Research

DOI:https://doi.org/10.1029/2021wr030972· OSTI ID:1982083

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Oregon State University, Corvallis, OR (United States)
National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
Cleveland State University, Cleveland, OH (United States)
National Center for Atmospheric Research (NCAR), Boulder, CO (United States); University of Colorado, Boulder, CO (United States)
University of Colorado, Boulder, CO (United States)
Department of Geological Sciences University of Colorado Boulder CO USA

Snowpack accumulation in forested watersheds depends on the amount of snow intercepted in the canopy and its partitioning into sublimation, unloading, and melt. A lack of canopy snow measurements limits our ability to evaluate models that simulate canopy processes and predict snowpack. We tested whether monitoring changes in wind-induced tree sway is a viable technique for detecting snow interception and quantifying canopy snow water equivalent (SWE). Over a 6 year period in Colorado, we monitored hourly sway of two conifers, each instrumented with an accelerometer sampling at 12 Hz. We developed an approach to distinguish changes in sway frequency due to thermal effects on tree rigidity versus intercepted snow mass. Over 60% of days with canopy snow had a sway signal that could not be distinguished from thermal effects. However, larger changes in tree sway could not generally be attributed to thermal effects, and canopy snow was present 93%–95% of the time, as confirmed with classified PhenoCam imagery. Using sway tests, we converted changes in sway to canopy SWE, which were correlated with total snowstorm amounts from a nearby SNOTEL site (Spearman r = 0.72 to 0.80, p < 0.001). Greater canopy SWE was associated with storm temperatures between -7°C and 0°C and wind speeds less than 4 m s^-1. Lower canopy SWE prevailed in storms with lower temperatures and higher wind speeds. Monitoring tree sway is a viable approach for quantifying canopy SWE, but challenges remain in converting changes in sway to mass and distinguishing thermal and snow mass effects on tree sway.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). AmeriFlux

Sponsoring Organization:: National Science Foundation (NSF); USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1982083

Journal Information:: Water Resources Research, Journal Name: Water Resources Research Journal Issue: 3 Vol. 58; ISSN 0043-1397

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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