Change in snow strength caused by rain

Ito, Yoichi M.; Matsushita, Hiroki; Hirashima, Hiroyuki; Ito, Yasuaki; Noro, Takeshi

doi:10.3189/2012aog61a027

Cited by 6 publications

(3 citation statements)

References 15 publications

(16 reference statements)

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“…The water ponding process is generally considered to be an important factor in wet snow avalanche formation [e.g., Kattelmann, 1984;Fierz and Föhn, 1994;Mitterer et al, 2011;Takeuchi and Hirashima, 2013], and the presence of capillary barriers has been statistically linked to wet snow avalanche activity [Baggi and Schweizer, 2009]. Based on field experiments, it is generally considered that snow strength is strongly reduced once volumetric liquid water content (LWC) exceeds 5-7% [Brun and Rey, 1987;Bhutiyani, 1996;Yamanoi and Endo, 2002;Ito et al, 2012]. As the typical LWC of snow in the absence of gradients in capillary suction is below this value [Coléou and Lesaffre, 1998;Heilig et al, 2015], ponding inside the snow cover seems to be an important prerequisite to reduce the stability of a wet snowpack.…”

Section: Introductionmentioning

confidence: 99%

Assessing wet snow avalanche activity using detailed physics based snowpack simulations

Wever

Valero²,

Fierz³

2016

Geophysical Research Letters

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Water accumulating on microstructural transitions inside a snowpack is often considered a prerequisite for wet snow avalanches. Recent advances in numerical snowpack modeling allow for an explicit simulation of this process. We analyze detailed snowpack simulations driven by meteorological stations in three different climate regimes (Alps, Central Andes, and Pyrenees), with accompanying wet snow avalanche activity observations. Predicting wet snow avalanche activity based on whether modeled water accumulations inside the snowpack locally exceed 5–6% volumetric liquid water content is providing a higher prediction skill than using thresholds for daily mean air temperature, or the daily sum of the positive snow energy balance. Additionally, the depth of the maximum water accumulation in the simulations showed a significant correlation with observed avalanche size. Direct output from detailed snow cover models thereby is able to provide a better regional assessment of dangerous slope aspects and potential avalanche size than traditional methods.

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Section: Introductionmentioning

confidence: 99%

Assessing wet snow avalanche activity using detailed physics based snowpack simulations

Wever

Valero²,

Fierz³

2016

Geophysical Research Letters

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“…Furthermore, grain growth and subsequent changes in pore sizes and pore size distribution under wet conditions decrease snow strength (Wakahama, 1968;Raymond and Tsushima, 1979;Colbeck, 1983;Brun and Ray, 1987;Marsh, 1987;Brun et al, 1989;Lehning et al, 2002;Yamanoi and Endo, 2002;Ito et al, 2012) and can lead to wet snow avalanches (Kattelmann, 1984;Fierz and Föhn, 1994;Baggi and Schweizer, 2008;Mitterer et al, 2011;Mitterer and Schweizer, 2013;Takeuchi and Hirashima, 2013;Wever et al, 2016a). Liquid water movement through the snowpack also controls the lag between rain events or snowmelt and water arrival at the snow base.…”

Section: Introductionmentioning

confidence: 99%

Liquid water infiltration into a layered snowpack: evaluation of a 3-D water transport model with laboratory experiments

Hirashima

Avanzi

Yamaguchi

2017

Hydrol. Earth Syst. Sci.

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Abstract. The heterogeneous movement of liquid water through the snowpack during precipitation and snowmelt leads to complex liquid water distributions that are important for avalanche and runoff forecasting. We reproduced the formation of capillary barriers and the development of preferential flow through snow using a three-dimensional water transport model, which was then validated using laboratory experiments of liquid water infiltration into layered, initially dry snow. Three-dimensional simulations assumed the same column shape and size, grain size, snow density, and water input rate as the laboratory experiments. Model evaluation focused on the timing of water movement, thickness of the upper layer affected by ponding, water content profiles and wet snow fraction. Simulation results showed that the model reconstructs relevant features of capillary barriers, including ponding in the upper layer, preferential infiltration far from the interface, and the timing of liquid water arrival at the snow base. In contrast, the area of preferential flow paths was usually underestimated and consequently the averaged water content in areas characterized by preferential flow paths was also underestimated. Improving the representation of preferential infiltration into initially dry snow is necessary to reproduce the transition from a dry-snow-dominant condition to a wet-snow-dominant one, especially in long-period simulations.

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“…In terms of stability, the presence of liquid water in the starting zone along with isothermal conditions is necessary to trigger a wet snow avalanche (Schweizer et al, 2015;Fierz and Föhn, 1994;Mitterer et al, 2013). More specifically, it was shown that the increase in LWC to 5%-7% will considerably decrease the cohesive forces in snow (Brun, 1989;Ito et al, 2012). Gravitational forces dominate infiltration (Waldner et al, 2004;Techel and Pielmeier, 2011), leading to rapid changes in grain size and shape (Brun, 1989) and density (Jordan et al, 2008).…”

Section: Lwc In Snow a Context For Snow Stabilitymentioning

confidence: 99%

Investigation into percolation and liquid water content in a multi-layered snow model for wet snow instabilities in Glacier National Park, Canada

Madore

Fierz²,

Langlois

2022

Front. Earth Sci.

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Water percolation in snow plays a crucial role in the avalanche risk assessment. Liquid water content and wetting front are hard to measure in the field; hence, accurate simulation of the phenomena can be of great help to forecasters. This study was the first to evaluate water percolation simulations with the SNOWPACK model using Richards’ scheme on Mount Fidelity, Glacier National Park, Canada. The study highlights that, at this site, an updated configuration on precipitation phase transition and new snow density can significantly improve simulations of the snow cover, and water percolation in particular, which can be relevant in an era of an increased occurrence of rain-on-snow (ROS) events. More specifically, emphasis was put on the quality of the input data and parameters. The analysis of the precipitation phase temperature threshold showed that a value of 1.4°C was the best suited to track the rain/snow transition on site. A 10-year analysis of 24-h precipitation measured using the rain gauge and 24-h new snow water equivalent showed an excellent correlation. New snow density sub-models were evaluated using the 24-h new snow density values taken by the park technicians. The BELLAIRE model performed best and was used to drive the snow simulations. Two SNOWPACK snow simulations were evaluated using 1) rain gauge precipitation amount (PCPM) and 2) automatic snow height measurement (HS) at the same site. Both runs simulated the main snowpack layers observed during the dry season (i.e., before spring percolation was observed), and both simulated the snow properties with good accuracy. The water equivalent of snow cover, used as a proxy for a first-order characterization of the simulations generated by both simulations, was slightly underestimated compared with four manual measurements taken on-site during the winter. Nevertheless, the comparison of both measured density and modeled bulk density showed great correspondence. The percolation timing and wetting front depth were evaluated using field measurements from field campaigns and continuous observations from on-site instruments. The main percolation events were correctly simulated and were coincident with the observed wet avalanche cycles. The results highlight the need for accurate input data on valid simulation of the wetting front and percolation timing on site. Good percolation information generated using the SNOWPACK model and Richards’ scheme could be used to assess the snowpack stability by forecasters in areas where such data are available.

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Change in snow strength caused by rain

Cited by 6 publications

References 15 publications

Assessing wet snow avalanche activity using detailed physics based snowpack simulations

Assessing wet snow avalanche activity using detailed physics based snowpack simulations

Liquid water infiltration into a layered snowpack: evaluation of a 3-D water transport model with laboratory experiments

Investigation into percolation and liquid water content in a multi-layered snow model for wet snow instabilities in Glacier National Park, Canada

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