Wind speed dependences of fracture and accumulation of snowflakes on snow surface

Sato, Takeshi; Kosugi, Ken’ichirou; Mochizuki, Shigeto; Nemoto, Masaki

doi:10.1016/j.coldregions.2007.05.004

Cited by 50 publications

(37 citation statements)

References 6 publications

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“…First of all, during drifting snow events, snow particles become smaller due to collisions and enhanced sublimation. These effects have been frequently observed, but not often quantified (Sato et al, 2008). The smaller particles may then pack closer together or fill gaps between unaffected, larger ones that are already immobilized, increasing the density.…”

Section: Introductionmentioning

confidence: 99%

Event-driven deposition of snow on the Antarctic Plateau: analyzing field measurements with SNOWPACK

Zwaaftink

Cagnati²,

Crepaz³

et al. 2013

The Cryosphere

103

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Abstract. Antarctic surface snow has been studied by means of continuous measurements and observations over a period of 3 yr at Dome C. Snow observations include solid deposits in form of precipitation, diamond dust, or hoar, snow temperatures at several depths, records of deposition and erosion on the surface, and snow profiles. Together with meteorological data from automatic weather stations, this forms a unique dataset of snow conditions on the Antarctic Plateau. Large differences in snow amounts and density exist between solid deposits measured 1 m above the surface and deposition at the surface. We used the snow-cover model SNOWPACK to simulate the snow-cover evolution for different deposition parameterizations. The main adaptation of the model described here is a new event-driven deposition scheme. The scheme assumes that snow is added to the snow cover permanently only during periods of strong winds. This assumption followed from the comparison between observations of solid deposits and daily records of changes in snow height: solid deposits could be observed on tables 1 m above the surface on 94 out of 235 days (40 %) while deposition at the surface occurred on 59 days (25 %) during the same period, but both happened concurrently on 33 days (14 %) only. This confirms that precipitation is not necessarily the driving force behind non-temporary snow height changes. A comparison of simulated snow height to stake farm measurements over 3 yr showed that we underestimate the total accumulation by at least 33 %, when the total snow deposition is constrained by the measurements of solid deposits on tables 1 m above the surface. During shorter time periods, however, we may miss over 50 % of the deposited mass. This suggests that the solid deposits measured above the surface and used to drive the model, even though comparable to ECMWF forecasts in its total magnitude, should be seen as a lower boundary. As a result of the new deposition mechanism, we found a good agreement between model results and measurements of snow temperatures and recorded snow profiles. In spite of the underestimated deposition, the results thus suggest that we can obtain quite realistic simulations of the Antarctic snow cover by the introduction of event-driven snow deposition.

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Section: Introductionmentioning

confidence: 99%

Event-driven deposition of snow on the Antarctic Plateau: analyzing field measurements with SNOWPACK

Zwaaftink

Cagnati²,

Crepaz³

et al. 2013

The Cryosphere

103

View full text Add to dashboard Cite

show abstract

“…Mechanical dismantling and cracking of snow crystals in the air and subsequently at the snow surface increases snow density (e.g. Sato et al, 2008). We cannot relate density differences to crystal types or size from the presented data set.…”

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confidence: 74%

Obtaining sub-daily new snow density from automated measurements in high mountain regions

Hartl¹,

Koch²,

Marty³

et al. 2017

Preprint

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Abstract. The density of new snow is sometimes monitored by meteorological or hydrological services at daily time intervals, or occasionally measured in local field studies. However, meteorological conditions and thus settling of the freshly deposited snow rapidly alter the new snow density until measurement. Physically based snow models and now-casting 10 applications make use of hourly weather data to determine the water equivalent of the snowfall and snow depth. In previous studies, a number of empirical parameterizations were developed to approximate the new snow density by meteorological parameters. These parameterizations are largely based on new snow measurements derived from local in-situ measurements.In this study a data set of automated snow measurements at four stations located in the European Alps is analysed for several winter seasons. Hourly new snow densities are calculated from the height of new snow and the water equivalent of snowfall. 15Considering the settling of the new snow and the old snow pack, the average hourly new snow density is 68 kgm -3 with a standard deviation of 9 kgm -3 . Seven existing parameterizations for estimating new snow densities were tested against these data, and most calculations overestimate the hourly automated measurements. Two of the tested parameterizations were capable of simulating low new snow densities observed at sheltered inner-alpine stations. The observed variability in new snow density from the automated measurements could not be described with satisfactory statistical significance by any of the 20 investigated parameterizations, but relationships between new snow density and wet bulb temperature are partly visible in the automated measurements data. Wind speed is a crucial parameter for the inter-station variability of new snow density, with higher new snow density at more windy locations. Whereas snow measurements using ultrasonic devices and snow pillows are appropriate for calculating station mean new snow densities, we recommend instruments with higher accuracy e.g. optical devices for better investigations of the variability of new snow densities on sub daily intervals. 25Hydrol. Earth Syst. Sci. Discuss., https://doi

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“…Snow grains are fragmented by snow drift (e.g. Sato et al, 2008), and thus more packed into the layer of new snow during windy conditions even over the course of only 1 h. The Kühtai station shows the lowest ρ HN , and the difference of the mean ρ HN is 17 kg m −3 between Weissfluhjoch and Kühtai stations for period 1. Median ρ HN and median T w of the different periods show a relationship between the periods at Kühtai station, with a higher ρ HN for a higher T w (Fig.…”

Section: Station-dependent Differencesmentioning

confidence: 99%

Obtaining sub-daily new snow density from automated measurements in high mountain regions

Hartl

Koch

Marty³

et al. 2018

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The density of new snow is operationally monitored by meteorological or hydrological services at daily time intervals, or occasionally measured in local field studies. However, meteorological conditions and thus settling of the freshly deposited snow rapidly alter the new snow density until measurement. Physically based snow models and nowcasting applications make use of hourly weather data to determine the water equivalent of the snowfall and snow depth. In previous studies, a number of empirical parameterizations were developed to approximate the new snow density by meteorological parameters. These parameterizations are largely based on new snow measurements derived from local in situ measurements. In this study a data set of automated snow measurements at four stations located in the European Alps is analysed for several winter seasons. Hourly new snow densities are calculated from the height of new snow and the water equivalent of snowfall. Considering the settling of the new snow and the old snowpack, the average hourly new snow density is 68 kg m −3 , with a standard deviation of 9 kg m −3 . Seven existing parameterizations for estimating new snow densities were tested against these data, and most calculations overestimate the hourly automated measurements. Two of the tested parameterizations were capable of simulating low new snow densities observed at sheltered inner-alpine stations. The observed variability in new snow density from the automated measurements could not be described with satisfactory statistical significance by any of the investigated parameterizations. Applying simple linear regressions between new snow density and wet bulb temperature based on the measurements' data resulted in significant relationships (r 2 > 0.5 and p ≤ 0.05) for single periods at individual stations only. Higher new snow density was calculated for the highest elevated and most wind-exposed station location. Whereas snow measurements using ultrasonic devices and snow pillows are appropriate for calculating station mean new snow densities, we recommend instruments with higher accuracy e.g. optical devices for more reliable investigations of the variability of new snow densities at sub-daily intervals.

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Wind speed dependences of fracture and accumulation of snowflakes on snow surface

Cited by 50 publications

References 6 publications

Event-driven deposition of snow on the Antarctic Plateau: analyzing field measurements with SNOWPACK

Event-driven deposition of snow on the Antarctic Plateau: analyzing field measurements with SNOWPACK

Obtaining sub-daily new snow density from automated measurements in high mountain regions

Obtaining sub-daily new snow density from automated measurements in high mountain regions

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