Characterizing Maritime Snow Canopy Interception in Forested Mountains

Abstract

Abstract Air temperature ( T air ) plays an important role in determining how a canopy intercepts snow and apart from event size is the single most important micrometeorological variable found to adequately influence interception rates and magnitude. We present results from a 6‐year study on snow‐forest interactions. This data set reveals the central role T air plays in how a forest intercepts snow and the need to effectively incorporate this within snow process models. Warm temperature events show a higher canopy interception efficiency ( CIE ) for all sites across the study period, while colder T air events demonstrated a lower corresponding CIE . Additionally, there is a structural component of the forest itself that plays a role in the ability of canopy to intercept snow. Recognizing the physical vertical structure of a forest as nontrivial, we present a simple canopy interception model that includes a novel three‐dimensional forest metric that captures canopy complexity, G z , combined with event size and T air to adequately predict event‐based interception. Low complexity forests decrease interception capacity from the outset, whereas a highly complex or diverse forest increases interception potential and leads to a nonlinear increase in temperature‐based canopy interception due to more surface area able to intercept falling snow. Essentially, forest structure sets the boundary condition of the potential to intercept, while event size and T air determines the rate or amount of interception. We develop a simple canopy snow interception model from these data and compare modeled output against three commonly used interception models in both a maritime and continental snow climate. Partitioning the relative importance of snow‐forest interactions on canopy interception will help provide the information to accurately model snow‐forest interactions and also aid in our water resources predictive capabilities now and into the future.