A strategy to represent impacts of subgrid-scale topography on snow evolution in the Canadian Land Surface Scheme

Abstract

This sensitivity study applies the offline Canadian Land Surface Scheme (CLASS) version 3.6 to simulate snowpack evolution in idealized topography using observations at Likely, British Columbia, Canada over 1 July 2008 to 30 June 2009. A strategy for a subgrid-scale snow (SSS) parameterization is developed to incorporate two key features: ten elevation bands at 100 m intervals to capture air temperature lapse rates, and five slope angles on four aspects to resolve solar radiation impacts on the evolution of snow depth and SWE. Simulations reveal strong elevational dependencies of snow depth and SWE when adjusting temperatures using a moist adiabatic lapse rate with elevation, with 26% peak SWE differences between that at the average elevation versus the mean of the remainder of the elevation bands. Differences in peak SWE on north- and south-facing slopes increase from 3.0 mm at 10° slope to 17.9 mm at 50° slope. When applied to elevation, slope and aspect combinations derived from a high-resolution digital elevation model, elevation dominates the control of peak SWE values. Inclusion of the range of SSS effects into a regional climate model will improve snowpack and hydrological simulations of western North America's snow-dominated, mountainous watersheds.

The Cariboo Alpine Mesonet: sub-hourly hydrometeorological observations of British Columbia's Cariboo Mountains and surrounding area since 2006

“…. Data from these weather stations have supported modelling studies of seasonal snowpack evolution (Younas et al, 2017), blowing snow fluxes , turbulent fluxes on a mountain glacier (Radić et al, 2017), glacial retreat (Beedle et al, 2009(Beedle et al, , 2015 and pro-glacial sediment transport dynamics (Leggat et al, 2015;Stott et al, 2016). These data have also been used to validate remote sensing products of snow (Tong et al, 2009a(Tong et al, , b, 2010, gridded meteorological datasets (Sharma and Déry, 2016) and output from numerical weather prediction models over complex terrain (Schirmer and Jamieson, 2015).…”

Effect of digital elevation model resolution on the simulation of the snow cover evolution in the High Atlas

“…Other strategies (than changing the model grid resolution) were proposed to account for terrain heterogeneity on topographic-driven meteorological forcing while keeping low computational requirements. These approaches can be classified into two categories: (i) the subgrid approach (Essery & Marks, 2007;Gagnon et al, 2013;Müller & Scherer, 2005) and (ii) the semidistributed approach (Revuelto et al, 2017;Younas et al, 2017). The first approach was used to represent forcing variables as probabilistic distributions (instead of a single mean value) at the grid cell scale.…”

Sensitivity testing for the effects of sub-grid scale topography on snow evolution in the Canadian land surface scheme

“…Snow-vegetation exchanges (e.g., Bartlett et al, 2003), snowcover fraction and non-uniform snow distribution (Liston, 2004;Nitta et al, 2014), variability in snow depletion curves inferred from air temperature (Luce et al, 1999) and snow specific surface area (Roy et al, 2013) have added complexity to snow processes in land surface models. Parameterizations of topographic controls on snow derived from physical snow modelling include topography and vegetation effects on the energy balance (Wigmosta et al, 1994), and the effect of topography on wind and snow processes (Marks & Dozier, 1992;Déry et al, 2004;Déry et al, 2010;Younas et al, 2017). Additional sub-grid parameterizations affecting snow include stepped hydrological response units (Pomeroy et al, 2007), power law for elevationdependent snow scaled with a sky view factor (Helbig & Herwignen, 2017), and a multiresolution snow modelling scheme based on surface heterogeneity (Baldo & Margulis, 2017).…”

“…Cyclonic low-pressure systems are the predominant driver of snowstorms in western Canada, while lake-effect snow can also result in substantial snowfall in close proximity to large inland lakes. Topography, wind and vegetation are smaller-scale governing factors determining snow accumulation in heterogeneous terrain (Armstrong & Brun, 2008;Gray & Male, 1981;Ganji et al, 2017a;Younas et al, 2017). Snow depth and SWE are two parameters used to measure snow volume and the meltwater contained within the seasonal snowpack.…”

“…The turbulent fluxes of sensible and latent heat are denoted by s and L , while P is the heat flux from precipitation and blowing snow, and is the ground heat flux. The CLASS model (Verseghy, 2012) currently has limitations in its representation of snow ablation and evolution processes at the sub-grid scale partly due to the absence of including a range of sub-grid topographical values: slope, aspect and elevation that control air temperature, solar radiation and therefore snow distribution (Ganji et al, 2017b;Younas et al, 2017). CLASS currently assumes each model grid cell covers a horizontal surface, with a single value for topographical features within that cell.…”