A Method for Determining the Thaw Water Content in a Snow Layer

Heated pavements are used as an alternative to removing snow and ice mechanically and chemically. Usually a heated pavement system is automatically switched on when snowfall starts or when there is a risk of ice formation. Ideally, these systems run based on accurate predictions of surface conditions a couple of hours ahead of time, for which both weather forecasts and reliable surface temperature predictions are needed. The effective thermal conductivity of the snow layer is often described as a function of its density. However the thermal conductivity of a snow layer can vary considerably, not only for snow samples with a different density, but also for snow samples with the same density, but with a variation in the liquid water content. In this paper a physical temperature and surface condition model is described for snow-covered roads. The model is validated for an entire winter season on a heated pavement in Norway. Two different models to describe the thermal conductivity through the snow layer were compared. Results show that the thermal conductivity of the snow layer can be best described as a function of the density for snow with a low liquid water content. For snow with a high water content, the thermal conductivity can be best described as a function of the volume fractions and thermal conductivity of ice, water, and air, in which air and ice are modeled as a series system and water and air/ice in parallel.

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Analysis of characteristic snow parameters and associated factors in a cold region in northeast China

Water Science & Technology Water Supply ◽

10.2166/ws.2018.096 ◽

2018 ◽

Vol 19 (2) ◽

pp. 511-518 ◽

Cited By ~ 1

Author(s):

Qiang Fu ◽

Li Peng ◽

Tianxiao Li ◽

Song Cui ◽

Dong Liu ◽

...

Keyword(s):

Water Content ◽

Liquid Water ◽

Meteorological Factors ◽

Correlation Coefficients ◽

Bottom Layer ◽

Liquid Water Content ◽

Snow Layer ◽

Snow Properties ◽

Positive Correlations ◽

Changing Rate

Abstract Snow characteristics were measured in the comprehensive experimental field and the results of a detailed analysis of physical snow properties indicated that snowpack characteristics are affected by a variety of climate parameters. The average liquid water content of snow increased from 0.5% to 3.5%. The bottom snow layer exhibited larger parameter variations than those in the surface and middle layers. The average snow porosity was 72.3% for the entire snowpack, and the changing rate of porosity ranged from 4% to 19% during the accumulation period and from 7% to 25% during the snowmelt period. The porosity of the bottom layer displayed the fastest decline and the largest range. The air temperature, snow temperature and solar radiation showed significant positive correlations with the liquid water content of the snow, and the calculated correlation coefficients were all above 0.9. In addition, relative humidity and temperature were negatively correlated. All meteorological factors studied affected the melting capacity of snow to varying degrees. This study included the design and implementation of snow experiments on bare land under natural conditions as well as measurements of snow parameters in detailed snowpack layers and explained the characteristics of snow parameters combined with meteorological factors.

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Changes in seasonal snow liquid water content during the snowmelt period in the Western Tianshan Mountains, China

The Cryosphere Discussions ◽

10.5194/tcd-6-4137-2012 ◽

2012 ◽

Vol 6 (5) ◽

pp. 4137-4169 ◽

Cited By ~ 2

Author(s):

H. Lu ◽

W. S. Wei ◽

M. Z. Liu ◽

X. Han ◽

W. Hong

Keyword(s):

Heat Flux ◽

Temporal Variation ◽

Snow Cover ◽

Water Content ◽

Liquid Water ◽

Sensible Heat Flux ◽

Liquid Water Content ◽

Snow Layer ◽

Snowmelt Period ◽

Western Tianshan

Abstract. Snow liquid water content is a very important parameter for snow hydrological processes, avalanche research and snow cover mapping by remote sensing. Snow liquid water content was measured with a portable instrument (Snow Fork) in the Tianshan Station for Snow Cover and Avalanche Research, Chinese Academy of Sciences during the snowmelt period in spring 2010. This study analyzed the temporal and spatial distribution of snow liquid water content in different weather conditions. The average liquid water content of snow in the whole layer exponentially increased and can be calculated using a regression function of prior moving average temperature. The proportion of net radiation, sensible heat flux and latent heat flux in total energy changed in different snowmelt period. During the pre-snowmelt period (0.3% ≤ Wvol < 1%), snow liquid water content and its temporal variation were relatively small, with liquid water accumulated in the coarse snow layer. During the mid-snowmelt period (1% ≤ Wvol < 2.5%), the variation was significant in the upper layer and decreased drastically during the snowfall and the following one to two days. Only the temporal variation decreased after rain or snow (ROS) events. During the late-snowmelt period (Wvol ≥ 2.5%), the distribution and variation of every snow layer showed a~uniform trend, and the effect of ROS events on liquid water content only occurred during rainfall and snowfall.

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Heat flow from wet to dry snowpack layers and associated faceting

Annals of Glaciology ◽

10.3189/172756404781814762 ◽

2004 ◽

Vol 38 ◽

pp. 187-194 ◽

Cited By ~ 5

Author(s):

Bruce Jamieson ◽

Charles Fierz

Keyword(s):

Approximate Solution ◽

Heat Flow ◽

Snow Cover ◽

Water Content ◽

Latent Heat ◽

Basic Equation ◽

Freezing Time ◽

Snow Layer ◽

Wet Snow ◽

Good Agreement

AbstractLayers of faceted crystals adjacent to crusts form the failure layers for some unexpected dry-slab avalanches. This paper focuses on the case of facets that form when dry snow overlies wet snow. From a basic equation for heat flow in solids, the approximate freezing time of the wet layer is derived. Seven experiments are described in which a wet layer was placed between two dry-snowlayers in a cold laboratory. Measured freezing times are comparable to the freezing times from the approximate solution assuming that latent heat from the irreducible water content flowed up. In four of the experiments, evidence of faceting was observed at the base of the upper dry snow layer within 5 hours and before the wet layer froze. In all seven experiments faceting was observed in the upper dry layer after the wet layer froze. Simulations performed with the snow-cover model SNOWPACK yield freezing times that agree reasonably with the approximate solution and allow the influence of various parameters on the results to be explored. In addition, simulated temperatures and grain evolution are compared with observations, showing good agreement.

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An implicit physical water percolation model

10.5194/egusphere-egu2020-11824 ◽

2020 ◽

Author(s):

Willem Jan van de Berg

Keyword(s):

Water Content ◽

Preferential Flow ◽

Climate Models ◽

Numerical Models ◽

Pore Space ◽

Equation Model ◽

Implicit Time ◽

Snow Layer ◽

First Results ◽

The Impact

<p>The parametrization in numerical models of the behavior of water in snow is either oversimplified - the bucket method &#8211; or hugely complicated &#8211; the Richardson equation. The latter faithfully resembles the general behavior of water in snow, when a dual domain approach, representing slow matrix and fast preferential flow, is taken. However, this type of models are unsuitable for application in climate models due to their high computation costs.</p><p>Therefore, an implicit Richardson equation model is developed, which is able to run on time steps of several minutes, typical for climate models, and snow layer thickness down to a few centimeters. In order to reach to a differentiable governing equation, required for iterative implicit time stepping, with as few as possible discontinuities in the derivatives, favorable for convergence, modifications are made in the governing equations when the water content approaches the irreducible water content or water almost fills the available pore space. Here, we show the first results of this model, with a focus on the impact of parameterization choices on the modelled water flow, refreezing profile and melt water buffering capacity.</p>

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Characterization of frozen hydrated biological specimens by low-loss EELS

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100132492 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1572-1573

Author(s):

Songquan Sun ◽

Richard D. Leapman

Keyword(s):

Water Content ◽

Direct Method ◽

Internal Standard ◽

Dry Weight ◽

Dark Field ◽

Protein Solutions ◽

Subcellular Compartment ◽

Differential Shrinkage ◽

Electron Energy Loss

Analyses of ultrathin cryosections are generally performed after freeze-drying because the presence of water renders the specimens highly susceptible to radiation damage. The water content of a subcellular compartment is an important quantity that must be known, for example, to convert the dry weight concentrations of ions to the physiologically more relevant molar concentrations. Water content can be determined indirectly from dark-field mass measurements provided that there is no differential shrinkage between compartments and that there exists a suitable internal standard. The potential advantage of a more direct method for measuring water has led us to explore the use of electron energy loss spectroscopy (EELS) for characterizing biological specimens in their frozen hydrated state.We have obtained preliminary EELS measurements from pure amorphous ice and from cryosectioned frozen protein solutions. The specimens were cryotransfered into a VG-HB501 field-emission STEM equipped with a 666 Gatan parallel-detection spectrometer and analyzed at approximately −160 C.

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STEM measurement of subcellular water distributions

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100148678 ◽

1993 ◽

Vol 51 ◽

pp. 568-569

Author(s):

R.D. Leapman ◽

S.Q. Sun ◽

S-L. Shi ◽

R.A. Buchanan ◽

S.B. Andrews

Keyword(s):

Water Content ◽

Internal Standard ◽

Dry Weight ◽

Dry Mass ◽

Scanning Transmission Electron Microscope ◽

Dark Field ◽

Bulk Water ◽

Inelastic Electron ◽

Scanning Transmission ◽

Annular Dark Field

Recent advances in rapid-freezing and cryosectioning techniques coupled with use of the quantitative signals available in the scanning transmission electron microscope (STEM) can provide us with new methods for determining the water distributions of subcellular compartments. The water content is an important physiological quantity that reflects how fluid and electrolytes are regulated in the cell; it is also required to convert dry weight concentrations of ions obtained from x-ray microanalysis into the more relevant molar ionic concentrations. Here we compare the information about water concentrations from both elastic (annular dark-field) and inelastic (electron energy loss) scattering measurements.In order to utilize the elastic signal it is first necessary to increase contrast by removing the water from the cryosection. After dehydration the tissue can be digitally imaged under low-dose conditions, in the same way that STEM mass mapping of macromolecules is performed. The resulting pixel intensities are then converted into dry mass fractions by using an internal standard, e.g., the mean intensity of the whole image may be taken as representative of the bulk water content of the tissue.

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