Snow interception modelling: Isolated observations have led to many land surface models lacking appropriate temperature sensitivities

Abstract

When formulating a hydrologic model, scientists rely on parameterizations of multiple processes based on field data, but literature review suggests that more frequently people select parameterizations that were included in pre-existing models rather than reevaluating the underlying field experiments. Problems arise when limited field data exist, when "trusted" approaches do not get reevaluated, and when sensitivities fundamentally change in different environments. The physics and dynamics of snow interception by

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

“…As noted above, the sway‐based estimate is likely overestimated (due to exceeding the 1:1 line), but provides a reference value that can be refined. Additionally, maximum interception capacity varies with temperature in models, with two common parameterizations showing opposing temperature sensitivities, due to the processes discussed above (Lundquist et al., 2021). The canopy‐to‐mass data could guide selection and development of an interception parameterization that is most realistic for particular conditions.…”

“…A low‐cost and minimally disruptive approach that can be applied across climates would provide new opportunities to describe dynamics in canopy snow storage and advance model development. Improved descriptions of canopy snow storage dynamics across sites are important to our efforts to mitigate climate change impacts, as most model representations of snow interception are attributed to two field studies in vastly different snow climates (cold boreal forest, Hedstrom & Pomeroy, 1998; warm maritime forest, Storck et al., 2002) which diverge when estimating snow interception capacity with warming temperature (Lundquist et al., 2021). Representation of interception and unloading is a main factor leading to snow model divergence in forested areas (Rutter et al., 2009).…”

Evaluating Multiple Canopy‐Snow Unloading Parameterizations in SUMMA With Time‐Lapse Photography Characterized by Citizen Scientists

“…It also resulted in differences in the canopy albedo feedback to the atmosphere. Due to lack of observations (Lundquist et al., 2021), these processes are often overlooked in hydrology. Remote time‐lapse cameras and citizen science provide one path for new observations and new understanding.…”

“…While often overlooked, snow unloading is a complex physical process. Once snow accumulates in the canopy, it can melt out as water dripping onto the snowpack below, unload as snow from the canopy onto the snowpack below, or sublimate back to the atmosphere (Lundquist et al., 2021). Additional complexity is added when rime ice forms on the canopy, impacting the physical properties of the intercepted snow (Whiteman & Garibotti, 2013).…”

“…Snow unloading through these mechanisms often results in a large, and sometimes sudden, decrease in land surface albedo. In addition, this complex process is difficult to parametrize due to limited observations, making existing model formulations difficult to evaluate (Lundquist et al., 2021). Thus, the goal of this work is to evaluate the performance of three widely used canopy‐snow‐unloading parameterizations, using a modular snow model that holds all other processes constant, combined with time‐lapse photographs from several climates, interpreted by citizen scientists.…”