Recent satellite and ground-based remote sensing are based on the analysis of microwave radiation reflected at the Earth’s surface in comparison to a signal directly received at an antenna above the ground. More gentle, non-destructive methods are based on the changes of spectral reflectance in the NIR region (920–1650 nm) of snow bearing different water contents and ground-penetrating radar, by which an electromagnetic signal is generated and the reflected wavefield is measured, from which it is possible to map the values of θ w in the sampled region. Thus, no successive tests can be made at a given site since the snowpack is irreversibly altered at every measurement. The main drawbacks of such techniques are the large amount of snow and the long time necessary to perform a measurement. Several in-situ, more or less invasive techniques to measure θ w were reviewed in the past and include centrifugal, dielectric, calorimetric or dilution approaches. Indeed, associated with θ w changes are sudden, non-linear alterations of snowpack properties and of the outflow of meltwater. To take into account the space–time evolution of meltwater outflow that is correlated with the snowpack stability, continuous recording of θ w is required. Measuring θ w is admittedly difficult and demanding. Indeed, albedo is higher in snow with smaller grains and vice versa. The fate of the snowpack is further affected by the lowered surface albedo of snow progressively impregnated with water since considerable liquid phase amounts favor the formation of ice clusters that act similar to big grains, being more efficient than small crystallites in absorbing light.
SNOW WAGER TIMES FULL
This can be full depth when water reaches the ground behind the snow cover, or, since the shear strength of snow reduces exponentially with increasing the volumetric water content, when a wet, buried snow layer becomes the preferential sliding surface of the avalanche. Accelerated melting under strong Sun irradiation, as well as heavy rain on snow, lead to increased θ w values and can result in a flood, possibly associated with severe runoff or wet avalanche release.
As such, θ w in snow is a marker of snowmelt and snow mechanical stability. This results mostly when melted snow or rainwater infiltrates into the snow, changing its wetness alternatively, the presence of thermal gradients through the snowpack may drive changes of θ w in snow layers at specific depths. Ī relevant property of a snowpack is the liquid water content θ w. In the laboratory, strict control of ambient temperature and supersaturation allows us to produce natural-like snow crystals with a degree of perfection higher than that of spontaneously grown crystals. The size and shape of the constituting snow grains concurrently evolve. Sun irradiation, temperature gradients, humidity and wind are the leading factors that concur with the evolution of the layers that progressively accumulate upon successive snowfalls and build up the snowpack. After its deposition, natural snow undergoes extensive metamorphism that consists of grain sintering under mechanical compression and thermal gradients through the snowpack thickness due to mass and thermal energy fluxes, driven by the weather conditions it experiences.
SNOW WAGER TIMES FREE
The initial shape of the crystallites formed in a cloud include plates, needles, hollow columns, dendrites, depending on the combinations of temperature and water vapor supersaturation values they experience along their free fall down to the ground, where they progressively accumulate. Snow is a granular, porous material made of a mixture of ice crystals with a variety of forms, a fraction of liquid water and water vapor in thermodynamic equilibrium. As a result, we exploited continuous, qualitative monitoring of the evolution of the liquid water content as reflected by the fitting coefficient c. We progressively charged snow with liquid water from dry snow up to soaked snow. The obtained snow spectra are well fitted by a linear combination of the spectra typical of liquid water and ice. We performed experiments on both fine- and coarse-grained snow. We reproduced water percolation in the laboratory, and used Raman spectroscopy to detect the presence of the liquid phase in controlled snow samples. Liquid water does not spread homogeneously through a snowpack because different snow layers have different permeabilities therefore, it is important to track sudden changes in the amount of liquid water within a specific layer. Knowledge of the content of the liquid phase in snow is critical to estimate the snowmelt runoff and to forecast the release of wet avalanches. The relative abundance of the three phases drives snow grain metamorphism and affects the physical properties of the snowpack. In snow, water coexists in solid, liquid and vapor states.
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