Some Measurements of Settlement in a Rocky Mountains Snow Cover

Bergen, James D.

doi:10.3189/s0022143000198041

Cited by 9 publications

(5 citation statements)

References 4 publications

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“…All of these processes can be treated together by making the assumption that the snow behaves as a viscous fluid with an “effective” compactive viscosity, η c (Keeler, 1967; Kojima, 1967; Bergen, 1978; Qin Dahe, 1990): where h is the thickness of the layer, t is time, ρ is density and σ is the load. Values of η c have been determined from observations of the settlement of natural snow layers, from uniaxial-strain compressive tests and from depth-density profiles on glaciers and ice sheets.…”

Section: Calculating Time-density Curves Using a Viscous Modelmentioning

confidence: 99%

Differences in compaction behavior of three climate classes of snow

Sturm

Holmgren

1998

Ann. Glaciol.

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In a recent paper (Sturm and others, 1995), a global seasonal snow-cover classification system was developed with each class defined by snow properties like grain-size and type. Here, characteristic bulk density vs time curves are assigned to three classes using snow-course data from Alaskan and Canadian sites. Within each class, curves have similar slopes and intercepts but between classes they are different. The relationship between slope, intercept and snow rheology has been investigated using a finite-difference model in which snow layers are assumed to behave as viscous fluids. Using observed slopes, the density-dependent compactive viscosity of each class has been determined. These are consistent with published values. Results indicate that load and load history are less important to the compaction behavior than grain and bond characteristics, snow temperature and wetness. The study suggests that differences in compaction behavior arise primarily from differences in rheology, the result of climatically controlled differences in the character of the snow. This finding explains why regional snow densities have been successfully predicted from air temperature and wind speed alone, without considering snow depth.

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Section: Calculating Time-density Curves Using a Viscous Modelmentioning

confidence: 99%

Differences in compaction behavior of three climate classes of snow

Sturm

Holmgren

1998

Ann. Glaciol.

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“…It was concluded that under these conditions natural densification of a snow cover is determined primarily by the load, and not by metamorphism of the snow grains. Bergen (1978) noted that in a dry, annual snow-cover settlement is a strong function of rate ofloading, thermal regime, and sample density. While this study primarily involved fine-grained snow (grain sizes in the vicinity of 1.0 mm) the author did note an apparent tendency for viscosity to increase with grain-size.…”

Section: Introductionmentioning

confidence: 99%

An analysis of compressive strain in adjacent temperature-gradient and equi-temperature layers in a natural snow cover

Armstrong¹

1980

J. Glaciol.

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Compressive strain-rates in discrete layers of a sub-alpine snow cover are analyzed. Individual layers are identified according to density and the dominant type of metamorphism which contributed to their formation. Data were collected during four winter seasons at the Institute of Arctic and Alpine Research (INSTAAR) snow-study site (3 400 m), Red Mountain Pass, south-western Colorado, U.S.A. At average densities of less than 250 kg m₋3the influence of metamorphism on strain-rate is not apparent. However, at densities greater than 250 kg m₋3, two separate relationships emerge for strain as a function of crystal type and density. While two adjacent layers may exhibit comparable densities, a layer of sintered, fine grained (ET) snow indicates a strain-rate approximately one order of magnitude greater than an adjacent layer of cohesionless, coarse-grained (TG) snow.

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“…Viscosity can be calculated from compaction rate and expressed in terms of congealation of snow grain crystals (Keeler, 1967;Kojima, 1974;Bergen, 1978;Sturm and Holmgren, 1998) as:…”

Section: Compaction Parameters Of Fresh Snowmentioning

confidence: 99%

Change in fresh snow density in Tianshan Mountains, China

2010

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The fresh snow density was observed with snow analyzer (Snow Fork) at Tianshan Station for Snowcover and Avalanche Research, Chinese Academy of Sciences from February 21 to March 5, 2009. Results show that fresh snow density increases from the 5th h to the 291st h after the snowfall, with an average rate of increase of 4.0×10 -4 g/(cm 3 ·h) (R 2 = 0.943). Analysis shows that fresh snow density is negatively correlated with the compaction rate of fresh snow (R 2 = -0.960). Inversely, it is positively correlated with fresh snow viscosity (R 2 = 0.896). In relation to meteorological factors, ground temperature rising at a depth of 40 cm is the major driving factor of snow density increase. The temperature increase in fresh snow layer and the decrease in depth hoar layer have the most prominent impacts on the snow density increase in the afternoon. Principal component analysis shows that the determinant factors of fresh snow density change can be grouped into 3 types as follows: 1) dynamic factor contributes about 69.71% to fresh snow density change, with a significant effect from the 5th h to the 106th h after the snowfall; 2) exogenous energy factor contributes about 20.91% to it, with a significant effect at the 130th h; and c) endogenous energy factor contributes about 9.38% to it, with a significant effect at the 130th h and the 195th h.

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Some Measurements of Settlement in a Rocky Mountains Snow Cover

Cited by 9 publications

References 4 publications

Differences in compaction behavior of three climate classes of snow

Differences in compaction behavior of three climate classes of snow

An analysis of compressive strain in adjacent temperature-gradient and equi-temperature layers in a natural snow cover

Change in fresh snow density in Tianshan Mountains, China

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