Snow Transport Model Research Articles

Development of Eulerian–Lagrangian simulation for snow transport in the presence of obstacles

The aim of this study is to develop a wind-induced snow transport model in a turbulent atmospheric boundary layer with the multiphase particle-in-cell (MP-PIC) approach. The airflow is treated as a continuum (Eulerian phase), and the snow is treated as discrete particles (Lagrangian phase). The momentum exchange between airflow and snow particles is considered, as well as the drag force of fluctuation velocity on particles, the turbulence damping near the snow-airflow interface, and the inter-particle collisions. The validation comprised wind-induced snow transport on flat terrain and around the roadbed, with the typical Eulerian–Eulerian approach serving as a control. The Eulerian–Lagrangian approach yields a better agreement with the experimental observations, especially in the presence of obstacles. On the contrary, considerable discrepancies with the experimental data are detected when utilizing the Eulerian–Eulerian approach. The Eulerian–Lagrangian approach is thought to have the advantages of independent snow momentum-governing equations and a precise snow-airflow momentum exchange model, which could be beneficial for snow transport prediction in urban environments.

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

Abstract. The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

Probabilistic study of snow loads on flat roofs considering the effects of wind at representative sites in China

Based on meteorological data, this paper simulates the evolution of ground and roof snow loads over time in winter. The snowmelt model is used to simulate the ground snow load, and the snow transport model is employed in cooperation with the snowmelt model to simulate the flat roof snow load. Through the simulations, samples of annual maximum ground snow loads, annual maximum roof snow loads, and ground-to-roof conversion factors for at least 60 years at 50 representative snowy sites in China are obtained. First, the statistical characteristics of the above samples are analysed. Then, the probabilistic models with different parameter estimation methods are used to fit the samples, and each model's goodness of fit is evaluated by using K-S test, Akaike information criterion (AIC), and Q-Q plot. The results show that the Generalized Extreme Value (GEV) distribution based on Maximum Likelihood Estimation (MLE) of parameters is the preferred probabilistic model for snow loads both on the ground and roofs. However, none of the models selected in this paper can accurately describe the ground-to-roof conversion factor. Therefore, this paper recommends using the R-year ground and roof snow loads obtained by the probabilistic model for calculating the ground-to-roof conversion factor. Finally, the ground-to-roof conversion factor is found to be quite scattered for the most of the studied sites, thus it could be more reasonable to use site-specific values estimated by the method proposed in this paper rather than a uniform value in consideration of safety and economy of the structure.

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

This paper introduces a novel snow transport model for the analytical simulation of wind-induced snow transport on flat roofs. In the novel model, the differences between precipitation and deposited snow particles on roofs, including the differences in threshold friction velocity and fetch distance for saturated drifting state, are considered. Thus, snow drifting on a roof is divided into drifting without and during snowfall. The effects of terrain category and roof height are also considered using the friction velocity on roofs to compute snow transport rate instead of directly using the wind speed data reported by weather stations. Parametric analysis and case study are conducted to explain the novel model in detail and compare the results with those obtained from the model developed by O’Rourke et al. (2005). The estimated fetch distance for saturated snow drifting by the proposed approach in this study ranges from zero to thousands of meters, which is consistent with field measurement results and more reasonable than the use of constant values. Results of the case study indicate that the proposed snow transport model might be more reasonable because the effects of more factors are considered.

Drifting-snow statistics from multiple-year autonomous measurements in Adélie Land, East Antarctica

Abstract. Drifting snow is a widespread feature over the Antarctic ice sheet, whose climatological and hydrological significance at the continental scale have been consequently investigated through modelling and satellite approaches. While field measurements are needed to evaluate and interpret model and satellite products, most drifting-snow observation campaigns in Antarctica involved data collected at a single location and over short time periods. With the aim of acquiring new data relevant to the observation and modelling of drifting snow in Antarctic conditions, two remote locations in coastal Adélie Land (East Antarctica) that are 100 km apart were instrumented in January 2010 with meteorological and second-generation IAV Engineering acoustic FlowCapt™ sensors. The data, provided nearly continuously so far, constitute the longest dataset of autonomous near-surface (i.e. within 2 m) measurements of drifting snow currently available over the Antarctic continent. This paper presents an assessment of drifting-snow occurrences and snow mass transport from up to 9 years (2010–2018) of half-hourly observational records collected in one of the Antarctic regions most prone to snow transport by wind. The dataset is freely available to the scientific community and can be used to complement satellite products and evaluate snow-transport models close to the surface and at high temporal frequency.

Modelling polar bear maternity den habitat in east Svalbard

We evaluated a novel tool that predicts possible maternity den habitat of the polar bear (Ursus maritimus) based on a physical snow transport model, a digital terrain model and weather data. We observed and compared den locations in three important denning areas in east Svalbard (Kongsøya, n = 288; Svenskøya, n = 86; Hopen, n = 115) with modelled snowdrift distributions for 24 years. Accounting for a likely position uncertainty of 100 m, 69% of all dens were located within year-specific modelled snowdrifts. These covered on average 1.8%, 2.1% and 24.7% of the three study islands, respectively. Our snowdrift model accurately predicted maternity den positions (R2 = 0.42, area under the receiving operating characteristic curve [AUC] = 0.85). A model based on slope and altitude, also predicted den positions reasonably well (R2 = 0.35, AUC = 0.88). Habitat maps identifying both current and future areas for maternity denning will become important in managing the Barents Sea population as well as other Arctic populations where changes in sea-ice conditions alter the accessibility to traditional denning areas.

雪粒子の空気輸送モデルによる地吹雪メカニズムの解明 －その5 間欠性から連続性への輸送形態の変化－

雪粒子の空気輸送モデルによる地吹雪メカニズムの解明 －その5 間欠性から連続性への輸送形態の変化－

雪粒子の空気輸送モデルによる地吹雪メカニズムの解明 －その4 ハイスピードカメラによるスプラッシュ過程の把握－

雪粒子の空気輸送モデルによる地吹雪メカニズムの解明 －その4 ハイスピードカメラによるスプラッシュ過程の把握－

Development of a large-eddy simulation coupled with Lagrangian snow transport model

The aim of this study is to develop a large-eddy simulation (LES)-coupled Lagrangian snow transport model. This model consists of an LES for turbulent flow fields, and a particle transport simulation model based on Newton's equations of motion. Particles are treated as point masses for turbulent flow fields in this study. The interactions of momentum exchange between a fluid and particles are considered. The particle transport simulation includes three physical sub-processes on the snow surface: aerodynamic entrainment, rebound, and splash. Then, we simulated particle transport within a turbulent boundary layer under the low-wind condition in which saltation intermittently occurs. This simulation was calculated with high frequency and high resolution to capture the fine turbulent structures. The initial stage of saltation mainly related to sweeps, and particles were ejected through the process of aerodynamic entrainment. These ejected particle induced more saltating particles, and the number of saltating particles transported through the processes of splash and rebound increased and became dominant as time proceeds. In such processes of splash and rebound under low-wind conditions, the particle transport might be unaffected by turbulent structures.

雪粒子の空気輸送モデルによる地吹雪メカニズムの解明 －その1 ラージ・エディ・シミュレーションに基づくラグランジュ型雪粒子輸送モデルの構築－

雪粒子の空気輸送モデルによる地吹雪メカニズムの解明 －その1 ラージ・エディ・シミュレーションに基づくラグランジュ型雪粒子輸送モデルの構築－

雪粒子の空気輸送モデルによる地吹雪メカニズムの解明 －その2 数値計算による境界層中の非定常な地吹雪の再現－

雪粒子の空気輸送モデルによる地吹雪メカニズムの解明 －その2 数値計算による境界層中の非定常な地吹雪の再現－

ラージ・エディ・シミュレーションに基づくラグランジュ型飛雪モデルの開発

ラージ・エディ・シミュレーションに基づくラグランジュ型飛雪モデルの開発

A conceptual, distributed snow redistribution model

Abstract. When applying conceptual hydrological models using a temperature index approach for snowmelt to high alpine areas often accumulation of snow during several years can be observed. Some of the reasons why these "snow towers" do not exist in nature are vertical and lateral transport processes. While snow transport models have been developed using grid cell sizes of tens to hundreds of square metres and have been applied in several catchments, no model exists using coarser cell sizes of 1 km2, which is a common resolution for meso- and large-scale hydrologic modelling (hundreds to thousands of square kilometres). In this paper we present an approach that uses only gravity and snow density as a proxy for the age of the snow cover and land-use information to redistribute snow in alpine basins. The results are based on the hydrological modelling of the Austrian Inn Basin in Tyrol, Austria, more specifically the Ötztaler Ache catchment, but the findings hold for other tributaries of the river Inn. This transport model is implemented in the distributed rainfall–runoff model COSERO (Continuous Semi-distributed Runoff). The results of both model concepts with and without consideration of lateral snow redistribution are compared against observed discharge and snow-covered areas derived from MODIS satellite images. By means of the snow redistribution concept, snow accumulation over several years can be prevented and the snow depletion curve compared with MODIS (Moderate Resolution Imaging Spectroradiometer) data could be improved, too. In a 7-year period the standard model would lead to snow accumulation of approximately 2900 mm SWE (snow water equivalent) in high elevated regions whereas the updated version of the model does not show accumulation and does also predict discharge with more accuracy leading to a Kling–Gupta efficiency of 0.93 instead of 0.9. A further improvement can be shown in the comparison of MODIS snow cover data and the calculated depletion curve, where the redistribution model increased the efficiency (R2) from 0.70 to 0.78 (calibration) and from 0.66 to 0.74 (validation).

Modelled sensitivity of the snow regime to topography, shrub fraction and shrub height

Abstract. Recent studies show that shrubs are colonizing higher latitudes and altitudes in the Arctic. Shrubs affect the wind transport, accumulation and melt of snow, but there have been few sensitivity studies of how shrub expansion might affect snowmelt rates and timing. Here, a three-source energy balance model (3SOM), which calculates vertical and horizontal energy fluxes – thus allowing within-cell advection – between the atmosphere, snow, snow-free ground and vegetation, is introduced. The three-source structure was specifically adopted to investigate shrub–tundra processes associated with patchy snow cover that single- or two-source models fail to address. The ability of the model to simulate the snow regime of an upland tundra valley is evaluated; a blowing snow transport and sublimation model is used to simulate premelt snow distributions and 3SOM is used to simulate melt. Some success at simulating turbulent fluxes in point simulations and broad spatial pattern in distributed runs is shown even if the lack of advection between cells causes melt rates to be underestimated. The models are then used to investigate the sensitivity of the snow regime in the valley to varying shrub cover and topography. Results show that, for domain average shrub fractional cover ≤0.4, topography dominates the pre- and early melt energy budget but has little influence for higher shrub cover. The increase in domain average sensible heat fluxes and net radiation with increasing shrub cover is more marked without topography where shrubs introduce wind-induced spatial variability of snow and snow-free patches. As snowmelt evolves, differences in the energy budget between simulations with and without topography remain relatively constant and are independent of shrub cover. These results suggest that, to avoid overestimating the effect of shrub expansion on the energy budget of the Arctic, future large-scale investigations should consider wind redistribution of snow, shrub bending and emergence, and sub-grid topography as they affect the variability of snow cover.

Drifting snow sublimation: A high-resolution 3-D model with temperature and moisture feedbacks

The snow transport model of Alpine3D is augmented with a drifting snow sublimation routine. Contrary to other three-dimensional high-resolution snow transport models, Alpine3D now accounts for feedback mechanisms on the air temperature, humidity, and snow mass concentration in three dimensions. Results show that the negative feedbacks of sublimation on the snow mass concentration, temperature, and humidity are, in general, small but relevant on the slope scale. We analyzed the deposition on a leeward slope for simulations including sublimation and compared these to a reference simulation of the model without sublimation. Including sublimation, but neglecting sublimation feedbacks, leads to a reduction in deposition of approximately 12% on this slope. In a simulation including sublimation and its feedbacks, the reduction in snow deposition on the same slope was 10%. The feedbacks thus reduced the loss of snow due to sublimation by 2%. The sublimation process is therefore quite important for a leeward slope influenced by drifting snow. However, we also show that the spatial variability is large and that drifting snow sublimation will mainly affect small regions within a catchment. Averaged over our model domain (2.4 km(2)) in the Swiss Alps, drifting snow sublimation causes a reduction in deposition of 2.3% during a 43 h test period, which is comparable to the sublimation loss from the snow cover during the same time.

The atmospheric snow-transport model: SnowDrift3D

AbstractSnowDrift3D, a high-resolution, atmospheric snow-transport model, is presented for the first time. In contrast to most state-of-the-art snowdrift models, atmospheric particle transport, i.e. saltation and suspension, is accounted for by one passive transport equation. The model uses unsteady wind fields (spatial resolution of up to 2 m) computed with an atmospheric computational fluid dynamics model that is directly connected to the numerical weather prediction model ALADIN. Sensitivity runs show that (1) the saltation mass flux is a function of cubic shear velocity, , (2) the model is marginally sensitive to the grid spacing at high resolutions (up to 2 m), (3) the model computes the redistribution of snow at high resolution in real time on dual core personal computers and (4) the changing topography of the snow cover should be included in cases of local erosion or deposition of a large amount of snow. Finally, we present a comparison of modeled and measured snow distributions obtained by terrestrial laser scanning showing area-wide linear correlation up to R = 0.33.

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

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.

Using wind fields from a high‐resolution atmospheric model for simulating snow dynamics in mountainous terrain

AbstractWind‐induced snow transport has remarkable effects on the snow cover spatial variability and on the temporal dynamics of snowmelt runoff. For accurate snow cover modelling, valid atmospheric forcing fields are essential. Since it is impossible to generate appropriate wind fields by a simple spatial interpolation of station data, a new approach was developed: A modified version of the Penn State University‐National Centre for Atmospheric Research (MM5) model was used to generate wind fields with 200‐m resolution. Because of the high computational costs of MM5, it was not practicable to include the wind field generation as an operational part of the snow cover modelling. Therefore, an archive consisting of 220 wind fields was generated prior to the simulation of the snow transport processes. These fields represent the most relevant synoptic situations for wind‐induced snow transport occurring at our test site. The criteria to generate which wind field to use in a specific snow model time step are mean wind speed and direction at the 700 hPa level derived from German Weather Service/Deutscher Wetterdienst (DWD) Lokalmodell (LM) analysis data. The wind field library provided physically derived wind speed and direction fields that were used to drive a snow transport model (SnowTran‐3D) in a high Alpine area in the Berchtesgaden National Park, Germany. In complex Alpine terrain, the procedure provides an alternative to simple interpolation methods, yielding improved physical realism at reasonable computational expense. Copyright © 2008 John Wiley & Sons, Ltd.

Distributed energy-balance modeling of snow-cover evolution and melt in rugged terrain: Tobacco Root Mountains, Montana, USA

Summary A distributed energy-balance model was developed for simulating snowpack evolution and melt in rugged terrain. The model, which was applied to a 43-km 2 watershed in the Tobacco Root Mountains, Montana, USA, used measured ambient data from nearby weather stations to drive energy-balance calculations and to constrain the model of Liston and Sturm [Liston, G.E., Sturm, M., 1998. A snow-transport model for complex terrain. Journal of Glaciology 44 (148), 498–516] for calculating the initial snowpack thickness. Simulated initial snow-water equivalent ranged between 1 cm and 385 cm w.e. (water equivalent) with high values concentrated on east-facing slopes below tall summits. An interpreted satellite image of the snowcover distribution on May 6, 1998, closely matched the simulated distribution with the greatest discrepancy occurring in the floor of the main trunk valley. Model simulations indicated that snowmelt commenced early in the melt season, but rapid meltout of snow cover did not occur until after the average energy balance of the entire watershed became positive about 45 days into the melt season. Meltout was fastest in the lower part of the watershed where warmer temperatures and tree cover enhanced the energy income of the underlying snow. An interpreted satellite image of the snowcover distribution on July 9, 1998 compared favorably with the simulated distribution, and melt curves for modeled canopy-covered cells mimicked the trends measured at nearby snow pillow stations. By the end of the simulation period (August 3), 28% of the watershed remained snow covered, most of which was concentrated in the highest parts of the watershed where initially thick accumulations had been shaded by surrounding summits. The results of this study provide further demonstration of the critical role that topography plays in the timing and magnitude of snowmelt from high mountain watersheds.

Observing, modelling, and validating snow redistribution by wind in a Wyoming upper treeline landscape

Redistribution of snow by wind is a defining feature of the physical environment in high-elevation upper treeline and alpine landscapes where most precipitation is snow and wind speeds are frequently high. In these landscapes, snow, wind, topography, and vegetation interact to produce a pattern of snow deposition where wind-driven snow is eroded from exposed areas and deposited on the lee sides of hills, trees, rocks, and other obstructions. During winters on Libby Flats, a broad, high-elevation ridge located in southeastern Wyoming, USA, snow is heterogeneously distributed with snow depths ranging from 0.1 to 7 m over a lateral span of a few meters. Snow depth variations are principally controlled by the aerodynamic influence of trees on wind, with the deepest drifts forming on the lee sides of krummholz patches and ribbon forests. While precipitation varied from year to year, spatial patterns of snow scouring, drifting, and snowmelt were nearly identical. This characteristic and chronic pattern alters ecosystem structure (e.g., plant species distributions and soil characteristics) and function (e.g., decomposition, primary production, nutrient cycling, and water balance). To better comprehend and predict how ecosystem structure and function change with respect to snow distribution in treeline ecotones, an understanding of the snow transport process, ablation, and subsequent water distribution is required. Since snow accumulation and melt are difficult to observe spatially, we adapted and validated snow transport and land surface models to simulate the heterogeneous snow distributions produced during three consecutive water years (1998–2000). Comparisons of field measurements with model predictions indicate that the linked models generally mimicked the temporal and spatial characteristics of snow accumulation, redistribution, and ablation on Libby Flats. However, considerable modelled and observed discrepancies were associated with shallow or deep snow depths. Model agreement with observations could be improved with higher temporal resolution meteorological data, better resolved terrain and vegetation data, and model improvements.