Modeling blowing snow accumulation downwind of an obstruction: The Ohara Eulerian particle distribution equation

2017 ◽  
Vol 53 (5) ◽  
pp. 3557-3564
Author(s):  
N. J. Kinar
Keyword(s):  
Particle Distribution ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Distribution Equation

scholarly journals The importance of wind-blown snow redistribution to snow accumulation on Bellingshausen Sea ice

2011 ◽  
Vol 52 (57) ◽  
pp. 271-278 ◽  
Author(s):  
Katherine C. Leonard ◽  
Ted Maksym
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Wind Speeds ◽  
Antarctic Sea Ice ◽  
Drifting Snow ◽  
Bellingshausen Sea ◽  
Ice Mass Balance ◽  
High Winds

AbstractSnow distribution is a dominating factor in sea-ice mass balance in the Bellingshausen Sea, Antarctica, through its roles in insulating the ice and contributing to snow-ice production. the wind has long been qualitatively recognized to influence the distribution of snow accumulation on sea ice, but the relative importance of drifting and blowing snow has not been quantified over Antarctic sea ice prior to this study. the presence and magnitude of drifting snow were monitored continuously along with wind speeds at two sites on an ice floe in the Bellingshausen Sea during the October 2007 Sea Ice Mass Balance in the Antarctic (SIMBA) experiment. Contemporaneous precipitation measurements collected on board the RVIB Nathaniel B. Palmer and accumulation measurements by automated ice mass-balance buoys (IMBs) allow us to document the proportion of snowfall that accumulated on level ice surfaces in the presence of high winds and blowing-snow conditions. Accumulation on the sea ice during the experiment averaged <0.01 m w.e. at both IMB sites, during a period when European Centre for Medium-Range Weather Forecasts analyses predicted >0.03 m w.e. of precipitation on the ice floe. Accumulation changes on the ice floe were clearly associated with drifting snow and high winds. Drifting-snow transport during the SIMBA experiment was supply-limited. Using these results to inform a preliminary study using a blowing-snow model, we show that over the entire Southern Ocean approximately half of the precipitation over sea ice could be lost to leads.

scholarly journals Radar measurements of blowing snow off a mountain ridge

2020 ◽  
Vol 14 (6) ◽  
pp. 1779-1794
Author(s):  
Benjamin Walter ◽  
Hendrik Huwald ◽  
Josué Gehring ◽  
Yves Bühler ◽  
Michael Lehning
Keyword(s):  
Wind Velocity ◽  
Order Approximation ◽  
Sonic Anemometer ◽  
Snow Accumulation ◽  
Travel Distance ◽  
Storm Event ◽  
Height Distribution ◽  
Blowing Snow ◽  
Mountain Ridge ◽  
Mountainous Regions

Abstract. Modelling and forecasting wind-driven redistribution of snow in mountainous regions with its implications on avalanche danger, mountain hydrology or flood hazard is still a challenging task often lacking in essential details. Measurements of drifting and blowing snow for improving process understanding and model validation are typically limited to point measurements at meteorological stations, providing no information on the spatial variability of horizontal mass fluxes or even the vertically integrated mass flux. We present a promising application of a compact and low-cost radar system for measuring and characterizing larger-scale (hundreds of metres) snow redistribution processes, specifically blowing snow off a mountain ridge. These measurements provide valuable information of blowing snow velocities, frequency of occurrence, travel distances and turbulence characteristics. Three blowing snow events are investigated, two in the absence of precipitation and one with concurrent precipitation. Blowing snow velocities measured with the radar are validated by comparison against wind velocities measured with a 3D ultra-sonic anemometer. A minimal blowing snow travel distance of 60–120 m is reached 10–20 % of the time during a snow storm, depending on the strength of the storm event. The relative frequency of transport distances decreases exponentially above the minimal travel distance, with a maximum measured distance of 280 m. In a first-order approximation, the travel distance increases linearly with the wind velocity, allowing for an estimate of a threshold wind velocity for snow particle entrainment and transport of 7.5–8.8 m s−1, most likely depending on the prevailing snow cover properties. Turbulence statistics did not allow a conclusion to be drawn on whether low-level, low-turbulence jets or highly turbulent gusts are more effective in transporting blowing snow over longer distances, but highly turbulent flows are more likely to bring particles to greater heights and thus influence cloud processes. Drone-based photogrammetry measurements of the spatial snow height distribution revealed that increased snow accumulation in the lee of the ridge is the result of the measured local blowing snow conditions.

scholarly journals Blowing snow in coastal Adélie Land, Antarctica: three atmospheric-moisture issues

2014 ◽  
Vol 8 (5) ◽  
pp. 1905-1919 ◽  
Author(s):  
H. Barral ◽  
C. Genthon ◽  
A. Trouvilliez ◽  
C. Brun ◽  
C. Amory
Keyword(s):  
Moisture Content ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Atmospheric Moisture ◽  
Atmospheric Models ◽  
Moisture Fluxes ◽  
Measurement Uncertainties ◽  
Strong Winds ◽  
The Impact ◽  
Atmospheric Moisture Content

Abstract. A total of 3 years of blowing-snow observations and associated meteorology along a 7 m mast at site D17 in coastal Adélie Land are presented. The observations are used to address three atmospheric-moisture issues related to the occurrence of blowing snow, a feature which largely affects many regions of Antarctica: (1) blowing-snow sublimation raises the moisture content of the surface atmosphere close to saturation, and atmospheric models and meteorological analyses that do not carry blowing-snow parameterizations are affected by a systematic dry bias; (2) while snowpack modelling with a parameterization of surface-snow erosion by wind can reproduce the variability of snow accumulation and ablation, ignoring the high levels of atmospheric-moisture content associated with blowing snow results in overestimating surface sublimation, affecting the energy budget of the snowpack; (3) the well-known profile method of calculating turbulent moisture fluxes is not applicable when blowing snow occurs, because moisture gradients are weak due to blowing-snow sublimation, and the impact of measurement uncertainties are strongly amplified in the case of strong winds.

A Distributed Snow-Evolution Modeling System (SnowModel)

2006 ◽  
Vol 7 (6) ◽  
pp. 1259-1276 ◽  
Author(s):  
Glen E. Liston ◽  
Kelly Elder
Keyword(s):  
Forest Canopy ◽  
Snow Water Equivalent ◽  
Vegetation Type ◽  
Atmospheric Model ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Canopy Interception ◽  
Meteorological Forcing ◽  
Spatially Distributed ◽  
Evolution Modeling

Abstract SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. Since each of these submodels was originally developed and tested for nonforested conditions, details describing modifications made to the submodels for forested areas are provided. SnowModel was created to run on grid increments of 1 to 200 m and temporal increments of 10 min to 1 day. It can also be applied using much larger grid increments, if the inherent loss in high-resolution (subgrid) information is acceptable. Simulated processes include snow accumulation; blowing-snow redistribution and sublimation; forest canopy interception, unloading, and sublimation; snow-density evolution; and snowpack melt. Conceptually, SnowModel includes the first-order physics required to simulate snow evolution within each of the global snow classes (i.e., ice, tundra, taiga, alpine/mountain, prairie, maritime, and ephemeral). The required model inputs are 1) temporally varying fields of precipitation, wind speed and direction, air temperature, and relative humidity obtained from meteorological stations and/or an atmospheric model located within or near the simulation domain; and 2) spatially distributed fields of topography and vegetation type. SnowModel’s ability to simulate seasonal snow evolution was compared against observations in both forested and nonforested landscapes. The model closely reproduced observed snow-water-equivalent distribution, time evolution, and interannual variability patterns.

scholarly journals Cloud and precipitation properties from ground-based remote sensing instruments in East Antarctica

2014 ◽  
Vol 8 (4) ◽  
pp. 4195-4241 ◽  
Author(s):  
I. V. Gorodetskaya ◽  
S. Kneifel ◽  
M. Maahn ◽  
K. Van Tricht ◽  
J. H. Schween ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Bimodal Distribution ◽  
Snow Accumulation ◽  
East Antarctica ◽  
Blowing Snow ◽  
Precipitation Radar ◽  
Radiative Fluxes ◽  
Near Surface ◽  
Surface Mass ◽  
Meteorological Observatory

Abstract. A new comprehensive cloud-precipitation-meteorological observatory has been established at Princess Elisabeth base, located in the escarpment zone of Dronning Maud Land, East Antarctica. The observatory consists of a set of ground-based remote sensing instruments (ceilometer, infrared pyrometer and vertically profiling precipitation radar) combined with automatic weather station measurements of near-surface meteorology, radiative fluxes, and snow accumulation. In this paper, the observatory is presented and the potential for studying the evolution of clouds and precipitating systems is illustrated by case studies. It is shown that the synergetic use of the set of instruments allows for distinguishing ice, mixed-phase and precipitating clouds, including some information on their vertical extent. In addition, wind-driven blowing snow events can be distinguished from deeper precipitating systems. Cloud properties largely affect the surface radiative fluxes, with liquid-containing clouds dominating the radiative impact. A statistical analysis of all measurements (in total 14 months mainly occurring in summer/autumn) indicates that these liquid-containing clouds occur during as much as 20% of the cloudy periods. The cloud occurrence shows a strong bimodal distribution with clear sky conditions 51% of the time and complete overcast conditions 35% of the time. Snowfall occurred 17% of the cloudy periods with a predominance of light precipitation and only rare events with snowfall > 1 mm h−1 water equivalent (w.e.). Three of such intensive snowfall events occurred during 2011 contributing to anomalously large annual snow accumulation. This is the first deployment of a precipitation radar in Antarctica allowing to assess the contribution of the snowfall to the local surface mass balance. It is shown that on the one hand large accumulation events (>10 mm w.e. day−1) during the measurement period of 26 months were always associated with snowfall, but that on the other hand snowfall did not always lead to accumulation. In general, this promising set of robust instrumentation allows for improved insight in cloud and precipitation processes in Antarctica and can be easily deployed at other Antarctic stations.

scholarly journals Field-scale water balance closure in seasonally frozen conditions

2017 ◽  
Vol 21 (11) ◽  
pp. 5401-5413 ◽  
Author(s):  
Xicai Pan ◽  
Warren Helgason ◽  
Andrew Ireson ◽  
Howard Wheater
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Snow Accumulation ◽  
Frozen Soil ◽  
Blowing Snow ◽  
Soil Drainage ◽  
Field Scale ◽  
Significant Term ◽  
The Common ◽  
Precipitation Gauge

Abstract. Hydrological water balance closure is a simple concept, yet in practice it is uncommon to measure every significant term independently in the field. Here we demonstrate the degree to which the field-scale water balance can be closed using only routine field observations in a seasonally frozen prairie pasture field site in Saskatchewan, Canada. Arrays of snow and soil moisture measurements were combined with a precipitation gauge and flux tower evapotranspiration estimates. We consider three hydrologically distinct periods: the snow accumulation period over the winter, the snowmelt period in spring, and the summer growing season. In each period, we attempt to quantify the residual between net precipitation (precipitation minus evaporation) and the change in field-scale storage (snow and soil moisture), while accounting for measurement uncertainties. When the residual is negligible, a simple 1-D water balance with no net drainage is adequate. When the residual is non-negligible, we must find additional processes to explain the result. We identify the hydrological fluxes which confound the 1-D water balance assumptions during different periods of the year, notably blowing snow and frozen soil moisture redistribution during the snow accumulation period, and snowmelt runoff and soil drainage during the melt period. Challenges associated with quantifying these processes, as well as uncertainties in the measurable quantities, caution against the common use of water balance residuals to estimate fluxes and constrain models in such a complex environment.

scholarly journals Impact of Future Climate and Vegetation on the Hydrology of an Arctic Headwater Basin at the Tundra–Taiga Transition

2019 ◽  
Vol 20 (2) ◽  
pp. 197-215 ◽  
Author(s):  
Sebastian A. Krogh ◽  
John W. Pomeroy
Keyword(s):  
Climate Change ◽  
Snow Accumulation ◽  
Future Climate ◽  
The Arctic ◽  
Climate Projections ◽  
Mean Annual Temperature ◽  
Permafrost Degradation ◽  
Blowing Snow ◽  
Projected Changes ◽  
The Impact

Abstract The rapidly warming Arctic is experiencing permafrost degradation and shrub expansion. Future climate projections show a clear increase in mean annual temperature and increasing precipitation in the Arctic; however, the impact of these changes on hydrological cycling in Arctic headwater basins is poorly understood. This study investigates the impact of climate change, as represented by simulations using a high-resolution atmospheric model under a pseudo-global-warming configuration, and projected changes in vegetation, using a spatially distributed and physically based Arctic hydrological model, on a small headwater basin at the tundra–taiga transition in northwestern Canada. Climate projections under the RCP8.5 emission scenario show a 6.1°C warming, a 38% increase in annual precipitation, and a 19 W m−2 increase in all-wave annual irradiance over the twenty-first century. Hydrological modeling results suggest a shift in hydrological processes with maximum peak snow accumulation increasing by 70%, snow-cover duration shortening by 26 days, active layer deepening by 0.25 m, evapotranspiration increasing by 18%, and sublimation decreasing by 9%. This results in an intensification of the hydrological regime by doubling discharge volume, a 130% increase in spring runoff, and earlier and larger peak streamflow. Most hydrological changes were found to be driven by climate change; however, increasing vegetation cover and density reduced blowing snow redistribution and sublimation, and increased evaporation from intercepted rainfall. This study provides the first detailed investigation of projected changes in climate and vegetation on the hydrology of an Arctic headwater basin, and so it is expected to help inform larger-scale climate impact studies in the Arctic.

scholarly journals Hydrological response unit-based blowing snow modelling over an alpine ridge

2010 ◽  
Vol 7 (1) ◽  
pp. 1167-1208 ◽  
Author(s):  
M. K. MacDonald ◽  
J. W. Pomeroy ◽  
A. Pietroniro
Keyword(s):  
Wind Speed ◽  
Land Surface ◽  
Large Scale ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Hydrological Response ◽  
Wind Speeds ◽  
Response Unit ◽  
Winter Snow ◽  
Hydrological Response Unit

Abstract. Snow redistribution by wind and the resulting accumulation regimes were simulated for two winters over an alpine ridge transect located in the Canada Rocky Mountains. Simulations were performed using physically based blowing snow and snowmelt models. A hydrological response unit (HRU)-based spatial discretization was used rather than a more computationally expensive fully-distributed one. The HRUs were set up to follow an aerodynamic sequence, whereby eroded snow was transported from windswept, upwind HRUs to drift accumulating, downwind HRUs. HRUs were selected by examining snow accumulation patterns from manual snow depth measurements. Simulations were performed using two sets of wind speed forcing: (1) station observed wind speed, and (2) modelled wind speed from a widely applied empirical, terrain-based windflow model. Best results were obtained when using the site meteorological station wind speed data. The windflow model performed poorly when comparing the magnitude of modelled and observed wind speeds, though over-winter snow accumulation results obtained when using the modelled wind speeds were reasonable. However, there was a notable discrepancy (17%) between blowing snow sublimation quantities estimated when using the modelled and observed wind speeds. As a result, the end-of-winter snow accumulation was considerably underestimated (32%) when using the modelled wind speeds. That snow redistribution by wind can be adequately simulated in computationally efficient HRUs over this alpine ridge has important implications for representing snow transport in large-scale hydrology models and land surface schemes. Snow redistribution by wind was shown to significantly impact snow accumulation regimes in mountainous environments as snow accumulation was reduced to less than one-third of snowfall on windswept landscapes and nearly doubled in certain lee slope and treeline areas. Blowing snow sublimation losses were shown to be significant (approximately one-quarter of snowfall or greater).

scholarly journals Snowdrift modelling for Vestfonna ice cap, north-eastern Svalbard

2013 ◽  
Vol 7 (1) ◽  
pp. 709-741 ◽  
Author(s):  
T. Sauter ◽  
M. Möller ◽  
R. Finkelnburg ◽  
M. Grabiec ◽  
D. Scherer ◽  
...  
Keyword(s):  
Mass Balance ◽  
Snow Accumulation ◽  
Glacier Mass Balance ◽  
Blowing Snow ◽  
Glacier Surface ◽  
Accumulation Pattern ◽  
Surface Mass ◽  
Ice Cap ◽  
Drifting Snow ◽  
Snow Mass

Abstract. The redistribution of snow by drifting and blowing snow frequently leads to an inhomogeneous snow mass distribution on larger ice caps. Together with the thermodynamic impact of drifting snow sublimation on the lower atmospheric boundary layer, these processes affect the glacier surface mass balance. This study provides a first quantification of snowdrift and sublimation of blowing and drifting snow on Vestfonna ice cap (Svalbard) by using the specifically designed "snow2blow" snowdrift model. The model is forced by atmospheric fields from the Weather Research and Forecasting model and resolves processes on a spatial resolution of 250 m. Comparison with radio-echo soudings and snow-pit measurements show that important local scale processes are resolved by the model and the overall snow accumulation pattern is reproduced. The findings indicate that there is a significant redistribution of snow mass from the interior of the ice cap to the surrounding areas and ice slopes. Drifting snow sublimation of suspended snow is found to be stronger during winter. It is concluded that both processes are strong enough to have a significant impact on glacier mass balance.

Spatial Snowdrift Modeling for an Open Natural Terrain using a Physically‐based Linear Particle Distribution Equation

2022 ◽  
Author(s):  
Noriaki Ohara ◽  
Siwei He ◽  
Andrew D. Parsekian ◽  
Benjamin M. Jones ◽  
Rodrigo C. Rangel ◽  
...  
Keyword(s):  
Particle Distribution ◽  
Physically Based ◽  
Natural Terrain ◽  
Distribution Equation
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