A novel snow transport model for analytically investigating effects of wind exposure on flat roof snow load due to saltation

In modern structural codes, the reference value of the snow load on roofs is commonly given as the product of the characteristic value of the ground snow load at the construction site multiplied by the shape coefficient. The shape coefficient is a conversion factor which depends on the roof geometry, its wind exposure, and its thermal properties. In the Eurocodes, the characteristic roof snow load is either defined as the value corresponding to an annual probability of exceedance of 0.02 or as a nominal value. In this paper, an improved methodology to evaluate the roof snow load characterized by a given probability of exceedance (e.g., p=0.02 in one year) is presented based on appropriate probability density functions for ground snow loads and shape coefficients, duly taking into account the influence of the roof’s geometry and its exposure to wind. In that context, the curves for the design values of the shape coefficients are provided as a function of the coefficient of variation (COVg) of the yearly maxima of the snow load on the ground expected at a given site, considering three relevant wind exposure conditions: sheltered or non-exposed, semi-sheltered or normal, and windswept or exposed. The design shape coefficients for flat and pitched roofs, obtained considering roof snow load measurements collected in Europe during the European Snow Load Research Project (ESLRP) and in Norway, are finally compared with the roof snow load provisions given in the relevant existing Eurocode EN1991-1-3:2003 and in the new version being developed (prEN1991-1-3:2020) for the “second generation” of the Eurocodes.

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A snow-transport model for complex terrain

Journal of Glaciology ◽

10.3189/s0022143000002021 ◽

1998 ◽

Vol 44 (148) ◽

pp. 498-516 ◽

Cited By ~ 35

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.

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High resolution modelling of snow transport in complex terrain using downscaled MM5 wind fields

The Cryosphere ◽

10.5194/tc-4-99-2010 ◽

2010 ◽

Vol 4 (1) ◽

pp. 99-113 ◽

Cited By ~ 38

Author(s):

M. Bernhardt ◽

G. E. Liston ◽

U. Strasser ◽

G. Zängl ◽

K. Schulz

Keyword(s):

Snow Cover ◽

Temporal Dynamics ◽

Transport Model ◽

Winter Season ◽

Model Performance ◽

Test Site ◽

High Mountain ◽

Spatial And Temporal Variability ◽

Wind Fields ◽

Snow Transport

Abstract. Snow transport is one of the most dominant processes influencing the snow cover accumulation and ablation in high mountain environments. Hence, the spatial and temporal variability of the snow cover is significantly modified with respective consequences on the total amount of water in the snow pack, on the temporal dynamics of the runoff and on the energy balance of the surface. For the present study we used the snow transport model SnowModel in combination with MM5 (Penn State University – National Center for Atmospheric Research MM5 model) generated wind fields. In a first step the MM5 wind fields were downscaled by using a semi-empirical approach which accounts for the elevation difference of model and real topography, and vegetation. The target resolution of 30 m corresponds to the resolution of the best available DEM and land cover map of the test site Berchtesgaden National Park. For the numerical modelling, data of six automatic meteorological stations were used, comprising the winter season (September–August) of 2003/04 and 2004/05. In addition we had automatic snow depth measurements and periodic manual measurements of snow courses available for the validation of the results. It could be shown that the model performance of SnowModel could be improved by using downscaled MM5 wind fields for the test site. Furthermore, it was shown that an estimation of snow transport from surrounding areas to glaciers becomes possible by using downscaled MM5 wind fields.

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High resolution modelling of snow transport in complex terrain using simulated wind fields

The Cryosphere Discussions ◽

10.5194/tcd-2-513-2008 ◽

2008 ◽

Vol 2 (4) ◽

pp. 513-556 ◽

Cited By ~ 1

Author(s):

M. Bernhardt ◽

U. Strasser ◽

G. E. Liston ◽

W. Mauser

Keyword(s):

Snow Cover ◽

Temporal Dynamics ◽

Transport Model ◽

Winter Season ◽

Spatial And Temporal Variability ◽

Wind Fields ◽

Remotely Sensed Data ◽

Mountain Environments ◽

Penn State ◽

Snow Transport

Abstract. Snow transport is one of the most dominant processes influencing the snow cover accumulation and ablation in high alpine mountain environments. Hence, the spatial and temporal variability of the snow cover is significantly modified with respective consequences on the total amount of water in the snow pack, on the temporal dynamics of the runoff and on the energy balance of the surface. For the presented study we used the snow transport model SnowTran-3D in combination with MM5 (Penn State University – National Center for Atmospheric Research MM5 model) generated wind fields. In a first step the MM5 wind fields were downscaled by using a semi-empirical approach which accounts for the elevation difference of model and real topography, as well as aspect, inclination and vegetation. The target resolution of 30 m corresponds to the resolution of the best available DEM and land cover map. For the numerical modelling, data of six automatic meteorological stations were used, comprising the winter season (September–August) of 2003/04 and 2004/05. In addition we had automatic snow depth measurements and periodic manual measurements of snow courses available for the validation of the results. In this paper we describe the downscaling of the wind fields and discuss the results of the snow transport simulations with respect to the measurements and remotely sensed data.

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Snow-Distribution Modelling in the Ammassalik Region, South East Greenland

Hydrology Research ◽

10.2166/nh.2003.0025 ◽

2003 ◽

Vol 34 (1-2) ◽

pp. 1-16 ◽

Cited By ~ 36

Author(s):

B. Hasholt ◽

G.E. Liston ◽

N.T. Knudsen

Keyword(s):

Snow Water Equivalent ◽

Transport Model ◽

Digital Terrain Model ◽

Climatic Conditions ◽

Blowing Snow ◽

Orographic Effects ◽

Terrain Model ◽

Snow Distribution ◽

Western Side ◽

Snow Transport

The Ammassalik region is characterized by a strong alpine relief, with altitudes up to 1,000 m. Glaciers are located mainly on the western side of ridges. The climate is low arctic, with annual precipitation amounts of more than 1,000 mm, which falls mainly as snow. Furthermore very strong storms occur frequently throughout the region. All together these factors support strong snow redistribution by wind, which likely explains the glacier locations, and also explains the observed regional runoff differences. The aim of this study is to apply the Liston & Sturm snow-transport model (SnowTran-3D) to elucidate the snow distribution according to the actual climatic conditions. A digital terrain model was used to determine the terrain forcing of the wind field. Precipitation data from the Ammassalik meteorological station were corrected for aerodynamic errors and orographic effects. Wind, temperature and humidity were obtained from a station located on a nunatak 515 m.a.s.l. at the equilibrium line on the Mittivakkat Glacier. The recorded winter accumulation (balance) of snow on the glacier was used for model calibration and testing. Significant snow transport from east-facing slopes to west-facing slopes was confirmed by the model. The drift accumulations were greatest at the head of the glacier, just on the lee side of the ridge east of the glacier. In some areas, as much as 10% of the precipitation was returned to the atmosphere by blowing-snow sublimation. An average snow water equivalent of 113 cm was obtained (not including some minor areas having snow depths as great as 4 m). These results compare well with glacier observations of 114 cm collected in May 1998 (during the field survey the 4 m areas are omitted because of crevasse hazards). Future work will use the model to test scenarios that include changes in wind regime. 1

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Land-based remote sensing of snow for the validation of a snow transport model

Cold Regions Science and Technology ◽

10.1016/j.coldregions.2004.03.007 ◽

2004 ◽

Vol 39 (2-3) ◽

pp. 93-104 ◽

Cited By ~ 13

Author(s):

Javier G. Corripio ◽

Yves Durand ◽

Gilbert Guyomarc'h ◽

Laurent Mérindol ◽

Dominique Lecorps ◽

...

Keyword(s):

Remote Sensing ◽

Transport Model ◽

Snow Transport

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Remote monitoring of the snow loads on a roof of buildings

Journal Ice and Snow ◽

10.15356/2076-6734-2016-2-246-252 ◽

2016 ◽

Vol 56 (2) ◽

pp. 246-252

Author(s):

V. A. Lobkina ◽

I. A. Kononov ◽

A. A. Potapov

Keyword(s):

Remote Monitoring ◽

Winter Season ◽

Snow Accumulation ◽

Snow Melting ◽

Snow Load ◽

Load Change ◽

Load Cells ◽

Snow Loads ◽

Flat Roof ◽

Snow Loading

Obtaining actual data on a change in the value of snow load for a snowfall is an important task the solution of which is usually neglected. The purpose of the work was to obtain a data on dynamics of the snow load change on a roof for a snowfall. A system for remote monitoring of the snow load was developed for this purpose. This system allows continuous gathering and transmission of the data on the snow load change from a unit of area. Obtaining this information gives an indication of the size of snow loading and dynamics of the snow accumulation during snowfall. The developed system provides continuous collection and transmission of data about the changing snow load per unit area. This information makes possible judging values of the snow load and its dynamics during a snowfall. Using of this system allows monitoring of snow accumulation during a snowfall. Discreteness of the system is 1 minute, and the sensitivity to the load change is 50 g. The platform is designed for a load less than 100 kg. When a snowfall ends the platform should be cleaned. In 2015, the system has been just tested, but in future we plan to use the system without cleaning for the whole snow season. In this connection, the more powerful sensors will be used. The system consists of a rectangular platform with an area of 1 m2, and it is equipped with four load cells «TOQUES» BBA at the corners. It was used for two months from late January to mid-March. In total, nine snowfalls were observed. In the winter season of 2014/15, increases of snow loads changed within the range of 10–100 kg/m2. Analysis of the data shows that the maximum snow load exerted on the roof takes place at a snowfall peak, after that it decreases under the influence of external factors. Three main factors influencing formation of the snow loads on a flat roof are as follows: the quantity of solid precipitation, the snow melting, and redistribution of snow by wind. Using of the system allows obtaining actual values of snow load on roofs of buildings instead of data calculated from the snow weight on the ground. These values can be then used to correct standards for the snow loads.

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Snow and blue-ice distribution patterns on the coastal Antarctic Ice Sheet

Antarctic Science ◽

10.1017/s0954102000000109 ◽

2000 ◽

Vol 12 (1) ◽

pp. 69-79 ◽

Cited By ~ 47

Author(s):

Glen E. Liston ◽

Jan-Gunnar Winther ◽

Oddbjørn Bruland ◽

Hallgeir Elvehøy ◽

Knut Sand ◽

...

Keyword(s):

Transport Model ◽

Distribution Patterns ◽

Snow Accumulation ◽

Horizontal Distance ◽

Topographic Features ◽

Dronning Maud Land ◽

Screen Height ◽

Topography Model ◽

Surface Patterns ◽

Snow Transport

Surface patterns of alternating snow and blue-ice bands are found in the Jutulgryta area of Dronning Maud Land, Antarctica. The snow-accumulation regions exist in the lee of blue-ice topographic ridges aligned perpendicular to winter winds. The snow bands are c. 500–2000 m wide and up to several kilometres long. In Jutulgryta, these features cover c. 5000 km2. These alternating snow and blue-ice bands are simulated using a snow transport and redistribution model, SnowTran-3D, that is driven with a winter cycle of observed daily screen-height air temperature, humidity, and wind speed and direction. The snow-transport model is coupled to a wind model that simulates wind flow over the relatively complex topography. Model results indicate that winter winds interact with the ice topographic features to produce alternating surface patterns of snow accumulation and erosion. In addition, model sensitivity simulations suggest that subtle topographic variations, on the order of 5m elevation change over a horizontal distance of 1 to 1.5 km, can lead to snow-accumulation variations that differ by a factor of six. This result is expected to have important consequences regarding the choice of sites for ice-coring efforts in Antarctica and elsewhere.

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Experimental Study of Interference Effects of a High-Rise Building on the Snow Load on a Low-Rise Building with a Flat Roof

Applied Sciences ◽

10.3390/app112311163 ◽

2021 ◽

Vol 11 (23) ◽

pp. 11163

Author(s):

Qingwen Zhang ◽

Yu Zhang ◽

Ziang Yin ◽

Guolong Zhang ◽

Huamei Mo ◽

...

Keyword(s):

Wind Tunnel ◽

Snow Accumulation ◽

Interference Effects ◽

Wind Tunnel Tests ◽

Snow Load ◽

Building Roof ◽

High Rise ◽

High Rise Building ◽

Snow Distribution ◽

Flat Roof

To explore the interference effects of a high-rise building on the snow load on a low-rise building with a flat roof, a series of wind tunnel tests were carried out with fine silica sand as a substitute for snow particles. The effects of the height of the interfering building and the distance between buildings on the snow distribution of the target building under three different wind directions were studied. The snow depth on the target building roof and the mass of particles blown off from the target building were measured during the wind tunnel tests, and the results showed that the snow distribution of the target building roof tends to be uniform when the interfering building is located upstream of the target building due to the shelter effect. When the interfering building is on the side of the target building, the snow distribution of the target building tends to be more uneven, because the interfering building increases the friction velocity on the target building roof near the interfering building. However, when the interfering building is located downstream of the target building, there will be an amplification effect of snow accumulation, and the snow distribution on the target building roof is nearly the same as that of the isolated condition. Under each wind direction, the interference effect of the snow load increases with the increase of the building height and the decrease of the building spacing. Therefore, the influence of the surrounding buildings on the snow distribution of the building roof cannot be ignored and should be considered in the structure design.

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