Thermal diffusivity of seasonal snow determined from temperature profiles

Abstract

a b s t r a c tThermal diffusivity of snow is an important thermodynamic property associated with key hydrological phenomena such as snow melt and heat and water vapor exchange with the atmosphere. Direct determination of snow thermal diffusivity requires coupled point measurements of thermal conductivity and density, which continually change due to snow metamorphism. Traditional methods for determining these two quantities are generally limited by temporal resolution. In this study we present a method to determine the thermal diffusivity of snow with high temporal resolution using snow temperature profile measurements. High resolution (between 2.5 and 10 cm at 1 min) temperature measurements from the seasonal snow pack at the Plaine-Morte glacier in Switzerland are used as initial conditions and Neumann (heat flux) boundary conditions to numerically solve the one-dimensional heat equation and iteratively optimize for thermal diffusivity. The implementation of Neumann boundary conditions and a ttest, ensuring statistical significance between solutions of varied thermal diffusivity, are important to help constrain thermal diffusivity such that spurious high and low values as seen with Dirichlet (temperature) boundary conditions are reduced. The results show that time resolved thermal diffusivity can be determined from temperature measurements of seasonal snow and support density-based empirical parameterizations for thermal conductivity.

Snow Temperature Changes within a Seasonal Snowpack and Their Relationship to Turbulent Fluxes of Sensible and Latent Heat

“…Though our study does not specifically focus on internal snowpack heat transport processes, in the appendix we calculate a eff from our snow temperature measurements to compare with recently published results by Oldroyd et al (2013). For a snowpack of depth h, where only vertical heat transport is considered and z 5 0 corresponds to ground level, the snowpack energy budget (in W m…”

“…Because the upper portion of the MRC probe protruded above the snow surface, we were concerned with along-probe temperature conduction affecting the MRC snow temperature measurements. Though probes similar to the MRC probe have been used in other snow studies (e.g., Fierz 2011;Oldroyd et al 2013), we chose to check the validity of the MRC probe data using other nearby temperature measurements (Fig. 1).…”

“…Within the snow-science community, much effort has gone toward parameterizations of k eff and a eff with easily measured quantities such as snow density (e.g., Schlatter 1972;Pfeffer and Humphrey 1996;Brandt and Warren 1997;Sturm et al 1997Sturm et al , 2002Andreas et al 2004;Oldroyd et al 2013). Though our study does not specifically focus on internal snowpack heat transport processes, in the appendix we calculate a eff from our snow temperature measurements to compare with recently published results by Oldroyd et al (2013).…”

Thermal conductivity of firn at Lomonosovfonna, Svalbard, derived from subsurface temperature measurements

“…1 m and the associated phase lag and/or amplitude dampening occurring with depth can be used to reconstruct the effective thermal conductivity of seasonal snow (e.g. Sergienko et al, 2008;Osokin and Sosnovsky, 2014). Annual fluctuations penetrate down to ca.…”

Practical considerations for enhanced-resolution coil-wrapped distributed temperature sensing

“…When measuring air temperature, one must also consider the effect of radiation on the probe (e.g. Vercauteren et al, 2008;Oldroyd et al, 2013). Colour of the cable coating and direct exposure to solar radiation can have influence on the temperature measurement up to several degrees (De Jong et al, 2015), and is also relevant underwater (Neilson, 2010).…”