Abstract

Methods that combine in-situ measurements, statistical methods, and model simulations with remotely sensed data provide a pathway for improving the robustness of surface flux products. For this research, we acquired eddy-covariance fluxes along a five-tower transect in a snowy montane forest over three consecutive winters to characterize near-field variability of the subcanopy environment. The novel experiment design enabled discriminating near-field evaposublimation sources. Boosted regression trees reveal that the predictive capacity of state variables change with season and storm cycle frequency. High rates of post-storm evaposublimation of canopy-intercepted snow at this site were constrained by short residence time of snow in the canopy due to throughfall and melt. The snow melt-out date for open vs. closed canopy conditions depended on total snowfall accumulation. Compared with low accumulation years, the snow melt-out date under the dense canopy during the high accumulation winter was later than for the open area, as shading became more important later in the season. The field experiments informed an environmental response function that was used to integrate ERA5-Land latent heat flux data at 20-km nominal resolution with USFS Tree Canopy Fraction data at 30-m resolution and showed near-field flux variability that was not resolved in model simulations. Previous evaposublimation results from experiments in alpine and subalpine environments do not directly translate to a montane forest due to differences in process rates.

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