Seasonal and diurnal cycles of liquid water in snow—Measurements and modeling

Abstract

Evaluating and improving snow models and outflow predictions for hydrological applications is hindered by the lack of continuous data on bulk volumetric liquid water content ( w ) and storage capacity of the melting snowpack. The combination of upward looking ground-penetrating radar and conventional snow height sensors enable continuous, nondestructive determinations of w in natural snow covers from first surficial wetting until shortly before melt out. We analyze diurnal and seasonal cycles of w for 4 years in a flat study site and for three melt seasons on slopes and evaluate model simulations for two different water transport schemes in the snow cover model SNOWPACK. Observed maximum increases in w during a day are below 1.7 vol % (90th percentile) at the flat site. Concerning seasonal characteristics of w , less than 10% of recorded data exceed 5 vol % at the flat site and 3.5 vol % at slopes. Both water transport schemes in SNOWPACK underestimate maximum w at the flat site systematically for all observed melt seasons, while simulated w maxima on slopes are accurate. Implementing observed changes in w per day in outflow predictions increases model performance toward higher agreement with lysimeter measurements. Hence, continuously monitoring w improves our understanding of liquid water percolation and retention in snow, which is highly relevant for several aspects of the cryosphere such as avalanche formation, catchment hydrology, and ice sheet mass balances.

Experimental measurements for improved understanding and simulation of snowmelt events in the Western Tatra Mountains

“…Snow wetness is not commonly measured in snow hydrology research although several recent papers presented the development of some new devices and modeling of liquid water content of snowpack (Avanzi et al, 2014(Avanzi et al, , 2015. Examples of other new devices are Heilig et al (2015), or Kinar and Pomeroy (2015), while Hirashima et al (2014) or Wever et al (2014) discuss the new modeling methods. In this study we have used the Snow Fork in snow pits.…”

Seasonal monitoring of melt and accumulation within the deep percolation zone of the Greenland Ice Sheet and comparison with simulations of regional climate modeling

“…For cold conditions with snow and firn temperatures below 0°C (θ w = 0), the bulk density above the antennas can easily be determined. In contrast to conditions in seasonal snow described by Heilig et al (2015), melting snow and firn on cold ice sheets can rapidly refreeze due to the underlying cold content. As a consequence, the assumption of a constant ice volume fraction after initial melt is invalid for ice sheets.…”

“…reaching L 15,x , the three phase mixing formula is underdetermined (c.f., Heilig et al, 2015). Hence, to solve for θ w , we used the same assumption as Heilig et al (2015) that θ i remains constant after initial percolation into L 15,x .…”

“…The third term in equation (5), F 15,x corresponds to the gravitational liquid water content of L 15,x , which can easily be converted from θ w if the imaged radar volume is known. We used the same approach as described by Heilig et al (2015). To assess the imaged radar volume for this layer, we applied the known radiation characteristics of the radar system.…”

“…assumptions and equations (Heilig et al, 2009(Heilig et al, , 2010Schmid et al, 2014;Heilig et al, 2015): we used the three phase mixing formula postulated by e.g. Roth et al (1990) or Wilhelms (2005) with the exponent β = 0.5 and the assumption of only three contributing volume fractions (air, ice and water: θ a + θ i + θ w = 1).…”