Snow Interception Modeling: Isolated Observations have led to Land
Surface Models Lacking Appropriate Climate 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
re-evaluating the underlying field experiments. Problems arise when
limited field data exist, when “trusted” approaches do not get
reevaluated, and when processes fundamentally change in different
environments. The physics and dynamics of snow interception by conifers,
including both loading and unloading of snow, is just such a case. The
most commonly used interception parameterization is based on data from
four trees from one site, but field study results are not directly
transferable between environments. The process varies dramatically
between locations with relatively warmer versus colder winters. Here, we
combine a comprehensive literature review with a model to demonstrate
essential improvements to model representations of snow interception. We
recommend that, as a first and essential step, all models include
increased loading due to increased adhesion and cohesion when
temperatures rise from -3 and 0°C. The commonly used parameters of a
fixed maximum value for loading and an e-folding time for unloading are
not supported by observations or physical understanding and are not
necessary to reproduce observations. In addition to unloading based on
physical processes, such as wind or canopy warming, all models must
represent melting of in-canopy snow so that it can be unloaded in liquid
form. As a second step, we propose field experiments across climates and
forest types to investigate: a) a representation of the force balance
between adhesion and cohesion versus gravity for both interception
efficiency and rates of unloading, b) wind effects during and between
storms, and c) lubrication when snow melts. For greatest impact, this
framework requires dedicated field measurements. These processes are
essential for models to accurately represent the impacts of dynamically
changing forest cover and snow cover on both global albedo and water
supplies.