scholarly journals Influence of Strong Winds on Snow Distribution and Avalanche Activity

1989 ◽  
Vol 13 ◽  
pp. 195-201 ◽  
Author(s):  
R. Meister
Keyword(s):  
Snow Depth ◽  
Transport Model ◽  
Snow Accumulation ◽  
Drift Flux ◽  
Zone Control ◽  
Flux Measurements ◽  
Snow Distribution ◽  
Strong Winds ◽  
Local Range ◽  
Good Agreement

In a local range, crest winds were compared with winds at lower stations to make it possible to initiate a drift-transport model which would predict snow accumulation patterns on leeward slopes. Corrections to the model input were made after consideration of detailed drift-flux measurements in the lowest 2 m above snow surface. Good agreement was found between the total length of large avalanches in a path near the crest, the appropriate wind reading and the corrected snow-depth increments in the rupture zone. Control of medium-sized avalanches likely to cause injury to skiers can be improved with the proposed method.

scholarly journals Influence of Strong Winds on Snow Distribution and Avalanche Activity

1989 ◽  
Vol 13 ◽  
pp. 195-201 ◽  
Author(s):  
R. Meister
Keyword(s):  
Snow Depth ◽  
Transport Model ◽  
Snow Accumulation ◽  
Drift Flux ◽  
Zone Control ◽  
Flux Measurements ◽  
Snow Distribution ◽  
Strong Winds ◽  
Local Range ◽  
Good Agreement

In a local range, crest winds were compared with winds at lower stations to make it possible to initiate a drift-transport model which would predict snow accumulation patterns on leeward slopes. Corrections to the model input were made after consideration of detailed drift-flux measurements in the lowest 2 m above snow surface. Good agreement was found between the total length of large avalanches in a path near the crest, the appropriate wind reading and the corrected snow-depth increments in the rupture zone. Control of medium-sized avalanches likely to cause injury to skiers can be improved with the proposed method.

scholarly journals A snow-transport model for complex terrain

1998 ◽  
Vol 44 (148) ◽  
pp. 498-516 ◽  
Author(s):  
Glen E. Liston ◽  
Matthew Sturm
Keyword(s):  
Snow Depth ◽  
Depth Distribution ◽  
Snow Water Equivalent ◽  
Transport Model ◽  
Vegetation Type ◽  
Cold Season ◽  
Snow Accumulation ◽  
Surface Shear Stress ◽  
Surface Shear ◽  
Snow Transport

AbstractAs part of the winter environment in middle- and high-latitude regions, the interactions between wind, vegetation, topography and snowfall produce snow covers of non-uniform depth and snow water-equivalent distribution. A physically based numerical snow-transport model (SnowTran-3D) is developed and used to simulate this three-dimensional snow-depth evolution over topographically variable terrain. The mass-transport model includes processes related to vegetation snow-holding capacity, topographic modification of wind speeds, snow-cover shear strength, wind-induced surface-shear stress, snow transport resulting from saltation and suspension, snow accumulation and erosion, and sublimation of the blowing and drifting snow. The model simulates the cold-season evolution of snow-depth distribution when forced with inputs of vegetation type and topography, and atmospheric foreings of air temperature, humidity, wind speed and direction, and precipitation. Model outputs include the spatial and temporal evolution of snow depth resulting from variations in precipitation, saltation and suspension transport, and sublimation. Using 4 years of snow-depth distribution observations from the foothills north of the Brooks Range in Arctic Alaska, the model is found to simulate closely the observed snow-depth distribution patterns and the interannual variability.

scholarly journals Multiscale spatial variability of lidar-derived and modeled snow depth on Hardangervidda, Norway

2013 ◽  
Vol 54 (62) ◽  
pp. 273-281 ◽  
Author(s):  
Kjetil Melvold ◽  
Thomas Skaugen
Keyword(s):  
Spatial Variability ◽  
Snow Depth ◽  
Laser Scanning ◽  
Regional Scale ◽  
Local Scale ◽  
Snow Accumulation ◽  
Large Variability ◽  
Airborne Laser ◽  
Snow Distribution ◽  
Snow Model

AbstractThis study presents results from an Airborne Laser Scanning (ALS) mapping survey of snow depth on the mountain plateau Hardangervidda, Norway, in 2008 and 2009 at the approximate time of maximum snow accumulation during the winter. The spatial extent of the survey area is >240 km2. Large variability is found for snow depth at a local scale (2 m2), and similar spatial patterns in accumulation are found between 2008 and 2009. The local snow-depth measurements were aggregated by averaging to produce new datasets at 10, 50, 100, 250 and 500 m2 and 1 km2 resolution. The measured values at 1 km2 were compared with simulated snow depth from the seNorge snow model (www.senorge.no), which is run on a 1 km2 grid resolution. Results show that the spatial variability decreases as the scale increases. At a scale of about 500 m2 to 1 km2 the variability of snow depth is somewhat larger than that modeled by seNorge. This analysis shows that (1) the regional-scale spatial pattern of snow distribution is well captured by the seNorge model and (2) relatively large differences in snow depth between the measured and modeled values are present.

scholarly journals Topographic control of snowpack distribution in a small catchment in the central Spanish Pyrenees: intra- and inter-annual persistence

2014 ◽  
Vol 8 (2) ◽  
pp. 1937-1972 ◽  
Author(s):  
J. Revuelto ◽  
J. I. López-Moreno ◽  
C. Azorin-Molina ◽  
S. M. Vicente-Serrano
Keyword(s):  
Snow Depth ◽  
Depth Distribution ◽  
Laser Scanner ◽  
Climatic Conditions ◽  
Snow Accumulation ◽  
Small Catchment ◽  
Explanatory Variables ◽  
Spanish Pyrenees ◽  
Snow Distribution ◽  
Variance Explained

Abstract. In this study we analyzed the relations between terrain characteristics and snow depth distribution in a small alpine catchment located in the central Spanish Pyrenees. Twelve field campaigns were conducted during 2012 and 2013, which were years characterized by very different climatic conditions. Snow depth was measured using a long range terrestrial laser scanner and analyses were performed at a spatial resolution of 5 m. Pearson's r correlation, multiple linear regressions and binary regression trees were used to analyze the influence of topography on the snow depth distribution. The analyses were used to identify the topographic variables that better explain the snow distribution in this catchment, and to assess whether their contributions were variable over intra- and inter-annual time scales. The topographic position index, which has rarely been used in these types of studies, most accurately explained the distribution of snow accumulation. Other variables affecting the snow depth distribution included the maximum upwind slope, elevation, and northing (or potential incoming solar radiation). The models developed to predict snow distribution in the basin for each of the 12 survey days were similar in terms of the most explanatory variables. However, the variance explained by the overall model and by each topographic variable, especially those making a lesser contribution, differed markedly between a year in which snow was abundant (2013) and a~year when snow was scarce (2012), and also differed between surveys in which snow accumulation or melting conditions dominated in the preceding days. The total variance explained by the models clearly decreased for those days on which the snow pack was thinner and more patchily distributed. Despite the differences in climatic conditions in the 2012 and 2013 snow seasons, some similarities in snow accumulation patterns were observed.

Snow Distribution at a High Arctic Site at Svalbard

2001 ◽  
Vol 32 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Oddbjørn Bruland ◽  
Knut Sand ◽  
Ånund Killingtveit
Keyword(s):  
Snow Depth ◽  
High Arctic ◽  
The Arctic ◽  
Major Influence ◽  
Differential Gps ◽  
Detailed Measurement ◽  
Distribution Mapping ◽  
Survey System ◽  
Snow Distribution ◽  
Strong Winds

In the Arctic regions snow cover has a major influence on the environment both in a hydrological and ecological context. Due to strong winds and open terrain the snow is heavily redistributed and the snow depth is quite variable. This has a significant influence on the duration of the melting season, on the possibilities of greenhouse gas exchange, the plant growing season and therefore the arctic terrestrial fauna. The aim of this study is to describe the snow depth variability by detailed measurement of snow distribution in a 3 km2 site near to Ny-Ålesund at 79° north of Svalbard and to link this to topography and climate at the location. The measurements were carried out in a grid of 100 m by 100 m cells using the SIR-2 Georadar from Geophysical Survey System Inc. (GSSI). Differential GPS was used to create a detailed Digital Elevation Model (DEM) and the snow depth data were correlated to topographic data. The average snowdepth in the area was about 70 cm with a standard deviation of 40 cm. Statistical distribution and spatial correlation for the snow depths were found. The method was found acceptable for snow distribution mapping. The main observation was the major accumulation in the west facing slopes due to easterly winds that are dominant in this area.

scholarly journals LiDAR measurement of seasonal snow accumulation along an elevation gradient in the southern Sierra Nevada, California

2014 ◽  
Vol 18 (10) ◽  
pp. 4261-4275 ◽  
Author(s):  
P. B. Kirchner ◽  
R. C. Bales ◽  
N. P. Molotch ◽  
J. Flanagan ◽  
Q. Guo
Keyword(s):  
Sierra Nevada ◽  
Snow Depth ◽  
Elevation Gradient ◽  
Precipitable Water ◽  
Snow Accumulation ◽  
Lapse Rate ◽  
Lidar Measurement ◽  
Regression Residuals ◽  
Snow Distribution ◽  
Scanning Lidar

Abstract. We present results from snow-on and snow-off airborne-scanning LiDAR measurements over a 53 km2 area in the southern Sierra Nevada. We found that snow depth as a function of elevation increased approximately 15 cm per 100 m, until reaching an elevation of 3300 m, where depth sharply decreased at a rate of 48 cm per 100 m. Departures from the 15 cm per 100 m trend, based on 1 m elevation-band means of regression residuals, showed slightly less steep increases below 2050 m; steeper increases between 2050 and 3300 m; and less steep increases above 3300 m. Although the study area is partly forested, only measurements in open areas were used. Below approximately 2050 m elevation, ablation and rainfall are the primary causes of departure from the orographic trend. From 2050 to 3300 m, greater snow depths than predicted were found on the steeper terrain of the northwest and the less steep northeast-facing slopes, suggesting that ablation, aspect, slope and wind redistribution all play a role in local snow-depth variability. At elevations above 3300 m, orographic processes mask the effect of wind deposition when averaging over large areas. Also, terrain in this basin becomes less steep above 3300 m. This suggests a reduction in precipitation from upslope lifting and/or the exhaustion of precipitable water from ascending air masses. Our results suggest a cumulative precipitation lapse rate for the 2100–3300 m range of about 6 cm per 100 m elevation for the accumulation period of 3 December 2009 to 23 March 2010. This is a higher gradient than the widely used PRISM (Parameter-elevation Relationships on Independent Slopes Model) precipitation products, but similar to that from reconstruction of snowmelt amounts from satellite snow-cover data. Our findings provide a unique characterization of the consistent, steep average increase in precipitation with elevation in snow-dominated terrain, using high-resolution, highly accurate data and highlighs the importance of solar radiation, wind redistribution and mid-winter melt with regard to snow distribution.

scholarly journals Snowfall and snow accumulation processes during the MOSAiC winter and spring season

2021 ◽  
Author(s):  
David N. Wagner ◽  
Matthew D. Shupe ◽  
Ola G. Persson ◽  
Taneil Uttal ◽  
Markus M. Frey ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Temporal Dynamics ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Drifting Snow ◽  
Snow Water ◽  
Abstract Data ◽  
Good Agreement

Abstract. Data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition allowed us to investigate the temporal dynamics of snowfall, snow accumulation, and erosion in great detail for almost the whole accumulation season (November 2019 to May 2020). We computed cumulative snow water equivalent (SWE) over the sea ice based on snow depth (HS) and density retrievals from a SnowMicroPen (SMP) and approximately weekly-measured snow depths along fixed transect paths. Hence, the computed SWE considers surface heterogeneities over an average path length of 1469 m. We used the SWE from the snow cover to compare with precipitation sensors installed during MOSAiC. The data were compared with ERA5 reanalysis snowfall rates for the drift track. Our study shows that the simple fitted HS-SWE function can well be used to compute SWE along a transect path based on SMP SWE retrievals and snow-depth measurements. We found an accumulated snow mass of 34 mm SWE until 26 April 2020. Further, we found that the Vaisala Present Weather Detector 22 (PWD22), installed on a railing on the top deck of research vessel Polarstern was least affected by blowing snow and showed good agreements with SWE retrievals along the transect, however, it also systematically underestimated snowfall. The OTT Pluvio2 and the OTT Parsivel2 were largely affected by wind and blowing snow, leading to higher measured precipitation rates, but when eliminating drifting snow periods, especially the OTT Pluvio2 shows good agreements with ground measurements. A comparison with ERA5 snowfall data reveals a good timing of the snowfall events and good agreement with ground measurements but also a tendency towards overestimation. Retrieved snowfall from the ship-based Ka-band ARM Zenith Radar (KAZR) shows good agreements with SWE of the snow cover and comparable differences as ERA5. Assuming the KAZR derived snowfall as an upper limit and PWD22 as a lower limit of a cumulative snowfall range, we estimate 72 to 107 mm measured between 31 October 2019 and 26 April 2020. For the same period, we estimate the precipitation mass loss along the transect due to erosion and sublimation as between 53 and 68 %. Until 7 May 2020, we suggest a cumulative snowfall of 98–114 mm.

scholarly journals LiDAR measurement of seasonal snow accumulation along an elevation gradient in the southern Sierra Nevada, California

2014 ◽  
Vol 11 (5) ◽  
pp. 5327-5365 ◽  
Author(s):  
P. B. Kirchner ◽  
R. C. Bales ◽  
N. P. Molotch ◽  
J. Flanagan ◽  
Q. Guo
Keyword(s):  
Sierra Nevada ◽  
Snow Depth ◽  
Elevation Gradient ◽  
Precipitable Water ◽  
Snow Accumulation ◽  
Lapse Rate ◽  
Lidar Measurement ◽  
Regression Residuals ◽  
Snow Distribution ◽  
Scanning Lidar

Abstract. We present results from snow-on and snow-off airborne-scanning LiDAR measurements over a 53-km2 area in the southern Sierra Nevada. We found that snow depth as a function of elevation increased approximately 15 cm 100 m-1, until reaching an elevation of 3300 m, where depth sharply decreased at a rate of 48 cm 100 m-1. Departures from the 15 cm 100 m-1 trend, based on 1-m elevation-band means of regression residuals, showed slightly less-steep increases below 2050 m; steeper increases between 2050–3300 m; and less-steep increases above 3300 m. Although the study area is partly forested, only measurements in open areas were used. Below approximately 2050 m elevation, ablation and rainfall are the primary causes of departure from the orographic trend. From 2050 to 3300 m, greater snow depths than predicted were found on the steeper terrain of the northwest and the less-steep northeast-facing slopes, suggesting that ablation, aspect, slope and wind redistribution all play a role in local snow-depth variability. At elevations above 3300 m orographic processes mask the effect of wind deposition when averaging over large areas. Also, terrain in this basin becomes less steep above 3300 m. This suggests a reduction in precipitation from upslope lifting, and/or the exhaustion of precipitable water from ascending air masses. Our results suggest a precipitation lapse rate for the 2100–3300 m range of about 6 cm 100 m-1 elevation. This is a higher gradient than the widely used PRISM (Parameter-elevation Relationships on Independent Slopes Model) precipitation products, but similar to that from reconstruction of snowmelt amounts from satellite snowcover data. Our findings provide a unique characterization of the consistent, steep average increase in precipitation with elevation in snow-dominated terrain, using high-resolution, highly-accurate data, as well as the importance of solar radiation, wind redistribution and mid-winter melt with regard to snow distribution.

Snow Distribution on Forest Clearcuts in the Swedish Mountains

1987 ◽  
Vol 18 (3) ◽  
pp. 185-192 ◽  
Author(s):  
Kurt-Åke Zakrisson
Keyword(s):  
Snow Cover ◽  
Systematic Study ◽  
Snow Depth ◽  
Field Data ◽  
Snow Accumulation ◽  
Slight Excess ◽  
Open Land ◽  
Snow Distribution ◽  
Forest Boundary ◽  
Melting Season

The paper is focused on the problem of choosing observation localities at the margin of forests for snow surveys. A systematic study was made of differences in snow depth and water equivalents of snow accumulation near the boundaries between forests and open land. The field data were collected during the winter seasons 1983-84 and 1984-85. The study involves sounding snow depths and calculating water equivalents of the snow cover from profiles crossing distinct boundaries between forests and clearcuts. The snow accumulation was found to be relatively large in a zone up to 40 m just outside the forest boundary. The accumulation up to 15 m just inside the forest boundary was relatively small as compared to the forest in general. A slight excess of snow in the forest compared to the clearcuts, established at the beginning of the snow accumulation season, gradually turns into a small deficit in April. During most of the melting season the amount of snow in the forest is considerably bigger than in the clearcuts.

scholarly journals Snow distribution patterns on Svalbard glaciers derived from radio-echo soundings

2011 ◽  
Vol 32 (4) ◽  
pp. 393-421 ◽  
Author(s):  
Mariusz Grabiec ◽  
Dariusz Puczko ◽  
Tomasz Budzik ◽  
Grzegorz Gajek
Keyword(s):  
Snow Depth ◽  
Distribution Patterns ◽  
Snow Accumulation ◽  
Complex Pattern ◽  
Precipitation Pattern ◽  
Accumulation Pattern ◽  
Local Factors ◽  
Ice Cap ◽  
Glacier Ice ◽  
Snow Distribution

Snow distribution patterns on Svalbard glaciers derived from radio-echo soundings The spatial distribution of snow thickness on glaciers is driven by a set of climatological, meteorological, topographical and orographic conditions. This work presents results of snow accumulation studies carried out from 2006 to 2009 on glaciers of different types: valley glacier, ice plateau and ice cap. In order to determine snow depth, a shallow radio echo-sounding method was used. Based on the results, the following snow distribution patterns on Svalbard glaciers have been distinguished: precipitation pattern, precipitation-redistribution pattern, redistribution pattern and complex pattern. The precipitation pattern assumes that the snow distribution on glaciers follows the altitudinal gradient. If the accumulation gradient is significantly modified by local factors like wind erosion and redeposition, or local variability of precipitation, the accumulation pattern turns into the precipitation-redistribution pattern. In the redistribution pattern, local factors play a crucial role in the spatial variability of snow depth. The complex pattern, however, demonstrates the co-existence of different snow distribution patterns on a single glacial object (glacier/icecap/ice field).

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