Wind tunnel experiments on natural snow drift

Near-surface snow particle dynamics from particle tracking velocimetry and turbulence measurements during alpine blowing snow storms

“…Particle number flux concentration profiles fit an exponential decrease model with increasing accuracy as height decreased and flow density increased, as predicted in many 3058 N. O. Aksamit and J. W. Pomeroy: Near-surface snow PTV other sand and snow studies (Maeno et al, 1980;Nishimura and Hunt, 2000;Creyssels et al, 2009;Ellis et al, 2009;Ho et al, 2011;Lü et al, 2012). A direct comparison of decay length (l v ) between recordings and other experiments was impractical because large variations in surface concentration (ν 0 ) skewed the decay length, making it a poor analogue for saltation height.…”

“…The fractional number flux fits an exponential decrease of the form ν (z) = ν 0 exp(−z/l v ) with increasing accuracy as one approaches the densest flow at the surface, similar to sand and snow saltation profiles seen elsewhere (e.g., Maeno et al, 1980;Nishimura and Hunt, 2000;Creyssels et al, 2009;Ellis et al, 2009;Ho et al, 2011;Lü et al, 2012), with ν 0 and l v being fitted parameters, the latter referred to as the decay length. The number flux decay length l v indicated how quickly the number flux concentration approached zero ( Fig.…”

“…PTV measurements were calculated by DaVis 8 (LaVision) software and estimated individual snow particle velocities using tracking algorithms that match discrete particles in subsequent frames imaged by the high-speed camera. Particle velocimetry techniques are normally used for wind tunnel studies (e.g., Zhang et al, 2007;Creyssels et al, 2009;Ho et al, 2011Ho et al, , 2012Lü et al, 2012;Tominaga et al, 2012;Groot Zwaaftink et al, 2014;Paterna et al, 2016), with few applications, in any discipline, in an outdoor setting (e.g., Morris et al, 2007;Zhu et al, 2007;Rosi et al, 2014;Toloui et al, 2014). This is the first known application of PTV for boundary-layer blowing snow studies in a natural environment.…”

“…In laboratories, several wind tunnel studies have examined drifting snow with particle image velocimetry (PIV) (Lü et al, 2012;Tominaga et al, 2012), shadowgraphy (Gromke et al, 2014), and shadowgraphic particle tracking velocimetry (PTV) (Groot Zwaaftink et al, 2014;Paterna et al, 2016), providing valuable insights into saltating snow velocity distributions, average relative wind and saltating snow velocities, particle size distributions, qualitative comparisons to transport driven by large eddy simulation, and equilibrium wind-blowing snow decoupling. Blowing snow transport model development continues to address small-scale variability (e.g., Nemoto and Nishimura, 2004;Groot Zwaaftink et al, 2014) and requires advanced measurement techniques to understand the physics driving such multiscale heterogeneities as well as evaluate the uncertainties and assumptions inherent in proposed models.…”

A New Formula for Estimating the Threshold Wind Speed for Snow Movement

“…They concluded that the observed threshold wind speed at 10 m height was from 4 to 11 m/s (friction speed about 0.1-1.0 m/s with the roughness length 5 0.005 m) for dry snow, and the average threshold 10 m wind speed was 7.7 m/s. The majority of existing studies assumed a constant threshold wind speed for snow movement either from experiments and field observations (L€ u et al, 2012;Ryan & Crissman, 1990) or steady state theories (Li & Pomeroy, 1997;Liston et al, 2007). Schmidt (1980) derived an equation for the threshold condition of snow movement using the snow particle bonding parameterization.…”