Wind Redistribution Of Snow Research Articles

Snow Loss Into Leads in Arctic Sea Ice: Minimal in Typical Wintertime Conditions, but High During a Warm and Windy Snowfall Event

AbstractThe amount of snow on Arctic sea ice impacts the ice mass budget. Wind redistribution of snow into open water in leads is hypothesized to cause significant wintertime snow loss. However, there are no direct measurements of snow loss into Arctic leads. We measured the snow lost in four leads in the Central Arctic in winter 2020. We find, contrary to expectations, that under typical winter conditions, minimal snow was lost into leads. However, during a cyclone that delivered warm air temperatures, high winds, and snowfall, 35.0 ± 1.1 cm snow water equivalent (SWE) was lost into a lead (per unit lead area). This corresponded to a removal of 0.7–1.1 cm SWE from the entire surface—∼6%–10% of this site's annual snow precipitation. Warm air temperatures, which increase the length of time that wintertime leads remain unfrozen, may be an underappreciated factor in snow loss into leads.

Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV lidar

Abstract. Accurate knowledge of snow depth distributions in forested regions is crucial for applications in hydrology and ecology. In such a context, understanding and assessing the effect of vegetation and topographic conditions on snow depth variability is required. In this study, the spatial distribution of snow depth in two agro-forested sites and one coniferous site in eastern Canada was analyzed for topographic and vegetation effects on snow accumulation. Spatially distributed snow depths were derived by unmanned aerial vehicle light detection and ranging (UAV lidar) surveys conducted in 2019 and 2020. Distinct patterns of snow accumulation and erosion in open areas (fields) versus adjacent forested areas were observed in lidar-derived snow depth maps at all sites. Omnidirectional semi-variogram analysis of snow depths showed the existence of a scale break distance of less than 10 m in the forested area at all three sites, whereas open areas showed comparatively larger scale break distances (i.e., 11–14 m). The effect of vegetation and topographic variables on the spatial variability in snow depths at each site was investigated with random forest models. Results show that the underlying topography and the wind redistribution of snow along forest edges govern the snow depth variability at agro-forested sites, while forest structure variability dominates snow depth variability in the coniferous environment. These results highlight the importance of including and better representing these processes in physically based models for accurate estimates of snowpack dynamics.

Toward a Novel Laser-Based Approach for Estimating Snow Interception

Forests reduce snow accumulation on the ground through canopy interception and subsequent evaporative losses. To understand snow interception and associated hydrological processes, studies have typically relied on resource-intensive point scale measurements derived from weighed trees or indirect measurements that compared snow accumulation between forested sites and nearby clearings. Weighed trees are limited to small or medium-sized trees, and indirect comparisons can be confounded by wind redistribution of snow, branch unloading, and clearing size. A potential alternative method could use terrestrial lidar (light detection and ranging) because three-dimensional lidar point clouds can be generated for any size tree and can be utilized to calculate volume of the intercepted snow. The primary objective of this study was to provide a feasibility assessment for estimating snow interception volume with terrestrial laser scanning (TLS), providing information on challenges and opportunities for future research. During the winters of 2017 and 2018, intercepted snow masses were continuously measured for two model trees suspended from load-cells. Simultaneously, autonomous terrestrial lidar scanning (ATLS) was used to develop volumetric estimates of intercepted snow. Multiplying ATLS volume estimates by snow density estimates (derived from empirical models based on air temperature) enabled the comparison of predicted vs. measured snow mass. Results indicate agreement between predicted and measured values (R2 ≥ 0.69, RMSE ≥ 0.91 kg, slope ≥ 0.97, intercept ≥ −1.39) when multiplying TLS snow interception volume with a constant snow density estimate. These results suggest that TLS might be a viable alternative to traditional approaches for mapping snow interception, potentially useful for estimating snow loads on large trees, collecting data in difficult to access terrain, and calibrating snow interception models to new forest types around the globe.

Monitoring snowbank processes and cornice fall avalanches with time-lapse photography

Time-lapse photography was employed to monitor a snowbank at 3640 m above sea level in the Uinta Mountains, Utah, USA. The snowbank forms against a 35-m high, east-facing escarpment and is nourished by wind redistribution of snow from an alpine plateau. The snowbank is capped by a large cornice, and its central core persists through the summer in most years. An automated, solar-powered digital camera was deployed between October 2016 and June 2017, and programmed to capture 5 photographs each day between 8:00 and 16:00, local time. Although cold temperatures affected the batteries during the winter, a total of 812 photographs were collected, for an overall average of 3.4 per day. These images were combined in an animation displaying the growth of the snowbank and associated cornice over the course of the winter. The debris fields resulting from nineteen cornice fall avalanches were noted in the sequence of photographs. Data collected at a nearby automated weather station reveal that 12 avalanches (between early December and early April) were preceded by significant increases in snow depth, snow water equivalent, and precipitation, with sustained windspeeds above the winter average. In contrast, six of the last seven events (between late April and early June) occurred in the absence of new snowfall, but were associated with rapid rises in temperature and notable decreases in snow water equivalent. The average interval between recorded avalanches is 10 days, with a maximum of 29 days and a minimum of 2 h. Recurrence intervals were shorter in December/January, in late March/early April, and in late April/early May. Only one avalanche occurred in the 56 days between 27 January and 24 March. Time-lapse photography is a powerful tool for monitoring nival processes.

The climatic mass balance of Svalbard glaciers: a 10-year simulation with a coupled atmosphere–glacier mass balance model

Abstract. In this study we simulate the climatic mass balance of Svalbard glaciers with a coupled atmosphere–glacier model with 3 km grid spacing, from September 2003 to September 2013. We find a mean specific net mass balance of −257 mm w.e. yr−1, corresponding to a mean annual mass loss of about 8.7 Gt, with large interannual variability. Our results are compared with a comprehensive set of mass balance, meteorological, and satellite measurements. Model temperature biases of 0.19 and −1.9 °C are found at two glacier automatic weather station sites. Simulated climatic mass balance is mostly within about 100 mm w.e. yr−1 of stake measurements, and simulated winter accumulation at the Austfonna ice cap shows mean absolute errors of 47 and 67 mm w.e. yr−1 when compared to radar-derived values for the selected years 2004 and 2006. Comparison of modeled surface height changes from 2003 to 2008, and satellite altimetry reveals good agreement in both mean values and regional differences. The largest deviations from observations are found for winter accumulation at Hansbreen (up to around 1000 mm w.e. yr−1), a site where sub-grid topography and wind redistribution of snow are important factors. Comparison with simulations using 9 km grid spacing reveal considerable differences on regional and local scales. In addition, 3 km grid spacing allows for a much more detailed comparison with observations than what is possible with 9 km grid spacing. Further decreasing the grid spacing to 1 km appears to be less significant, although in general precipitation amounts increase with resolution. Altogether, the model compares well with observations and offers possibilities for studying glacier climatic mass balance on Svalbard both historically as well as based on climate projections.

Assessing uncertainty and sensor biases in passive microwave data across High Mountain Asia

Abstract Snowfall comprises a significant percentage of the annual water budget in High Mountain Asia (HMA), but snow-water equivalent (SWE) is poorly constrained due to lack of in-situ measurements and complex terrain that limits the efficacy of modeling and observations. Over the past few decades, SWE has been estimated with passive microwave (PM) sensors with generally good results in wide, flat, terrain, and lower reliability in densely forested, complex, or high-elevation areas. In this study, we use raw swath data from five satellite sensors — the Special Sensor Microwave/Imager (SSMI) and Special Sensor Microwave Imager/Sounder (SSMIS) (1987–2015, F08, F11, F13, F17), Advanced Microwave Scanning Radiometer — Earth Observing System (AMSR-E, 2002–2011), AMSR2 (2012–2015), and the Global Precipitation Measurement (GPM, 2014–2015) — in order to understand the spatial and temporal structure of native sensor, topographic, and land cover biases in SWE estimates in HMA. We develop a thorough understanding of the uncertainties in our SWE estimates by examining the impacts of topographic parameters (aspect, relief, hillslope angle, and elevation), land cover, native sensor biases, and climate parameters (precipitation, temperature, and wind speed). HMA, with its high seasonality, large topographic gradients and low relief at high elevations provides an excellent context to examine a wide range of climatic, land-cover, and topographic settings to better constrain SWE uncertainties and potential sensor bias. Using a multi-parameter regression, we compare long-term SWE variability to forest fraction, maximal multi-year snow depth, topographic parameters, and long-term average wind speed across both individual sensor time series and a merged multi-sensor dataset. In regions where forest cover is extensive, it is the strongest control on SWE variability. In those regions where forest density is low ( While forest cover and elevation have been integrated into many SWE algorithms, wind speed and long-term maximal snow depth have not. Our results show that wind redistribution of snow can have impacts on SWE, especially over large, flat, areas. Using our regression results, we have developed an understanding of sensor-specific SWE uncertainties and their spatial patterns. The uncertainty maps developed in this study provide a first-order approximation of SWE-estimate reliability for much of HMA, and imply that high-fidelity SWE estimates can be produced for many high-elevation areas.

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.

On the behaviour of dynamic contributing areas and flood frequency curves in North American Prairie watersheds

Summary This statistical study examines the impact of storage upon the frequency and magnitude of runoff in the hummocky glacially transformed landscape of the Canadian Prairies. When runoff production is unaffected by depressions, the shape of the runoff frequency curve resembles the shape of the precipitation frequency curve, adjusted for the effects of infiltration, evaporation, sublimation, and wind redistribution of snow. However, the shape and slope of the runoff frequency curve can be affected by storage thresholds associated with hillslope and wetland depressions, and reflect the number, size and spatial distribution of depressions in the catchment. A comparison of runoff frequency curves from catchments with or without depressions provides a useful indicator of the amount of water retained by surface depressions without recourse to detailed topographic mapping of the basins. Results obtained from this study provide valuable insights into the complex function of closed and intermittently contributing drainage basins.

Variability of snow and ice thermal, physical and optical properties pertinent to sea ice algae biomass during spring

Changes in the thermal, physical and optical properties of the snow–sea ice system and feedbacks between various temporal and spatial scales affect accumulation of microalgae at the sea ice bottom and are the focus of this research. During the spring transition period, May 4 to June 9, 2002, we closely monitored atmospheric conditions and properties of the snow–sea ice system, including thermal, physical and optical properties of the snow cover (e.g., temperature, grain size, light attenuation), ice thickness and salinity, and biomass of bottom ice algae. Results show that snowdrift size averaged 31.2 by 10.6 m with a depth range of 2 to 45 cm. Snowpacks also varied in age, distinguished by coincident peaks of snow salinity and grain size and a lower PAR extinction coefficient. Spatial variability of the snowpack was superimposed by temporal variability associated with seasonal snow–ice melt and wind redistribution of snow. Maximum biomass of ice algae was observed under intermediate snow covers. Under thin snow covers, algae biomass declined steadily coincident with seasonal warming and desalination of the ice cover. Under thick snow covers, algae biomass was negatively correlated with snow depth. These results suggest that thin snow covers were associated with a thermal effect causing sloughing of algae, whereas under deep snow, algae were still light limited and thermally insulated from the warming atmosphere. Our results highlight the importance of snow cover history on the sea ice system operating below. Furthermore, in the context of current climate change scenarios, shifts in snow depth would result in decreases of ice algae biomass.

Variability in accumulation rates from GPR profiling on the West Antarctic plateau

AbstractIsochronal layers in firn detected with ground-penetrating radar (GPR) and dated using results from ice-core analyses are used to calculate accumulation rates along a 100 km across-flow profile in West Antarctica. Accumulation rates are shown to be highly variable over short distances. Elevation measurements from global positioning system surveys show that accumulation rates derived from shallow horizons correlate well with surface undulations, which implies that wind redistribution of snow is the leading cause of this variability. Temporal changes in accumulation rate over 25–185 year intervals are smoothed to along-track length scales comparable to surface undulations in order to identify trends in accumulation that are likely related to changes in climate. Results show that accumulation rates along this profile have decreased in recent decades, which is consistent with core-derived time series of annual accumulation rates measured at the two ends of the radar profile. These results suggest that temporal variability observed in accumulation-rate records from ice cores and GPR profiles can be obscured by spatial influences, although it is possible to resolve temporal signals if the effects of local topography and ice flow are quantified and removed.

Analysis of ERS Tandem SAR coherence from glaciers, valleys, and fjord ice on Svalbard

Interferometric satellite synthetic aperture radar (SAR) data was acquired from an area on Spitsbergen, Svalbard, during the European remote sensing satellite (ERS) Tandem mission in 1995-1996. Analyzing these data sets shows that the estimated SAR coherence is highly dependent on the satellite baseline length, and that corrections for this decorrelation effect is necessary if the baseline is a few hundred meters or more. Meteorological recordings are compared to SAR coherence estimates made at different seasons and surface categories: glaciers in motion, glacial forefields dominated by ice-cored moraines, lakes, rivers, and flat valleys with fine moraine materials like gravel and sand. It was found that temporal decorrelation effects are mainly due to changing surface conditions caused by precipitation and temperature variations around freezing, but that wind redistribution of snow also may play a role. Structures and cracks in the fjord ice as well as boundaries of lakes, rivers, and coastlines can be detected in SAR coherence images because of the contrast between high and low coherence areas. Low coherence is observed from those parts of moving glaciers that experience deformations shear, or zones of relative high velocity. The usefulness of 35-days interferometric SAR (e.g., the foreseen ENVISAT configuration) will be limited, even in sparsely vegetated areas like Svalbard, as compared to the ERS Tandem configuration.

Spatial Patterns of Snow Accumulation in the Alpine Terrain

AbstractA model, relating spatial patterns of snow accumulation in the alpine belt of major mountain ranges to the angular relationship which exists among terrain features such as cirque basins, mean storm-path trajectories, and incident solar radiation, is presented together with a limited amount of relevant empirical data. It is suggested that an “orientation gradient” exists in both the temporal and spatial variation of accumulation and ablation in the alpine terrain, the importance of which varies as some function of the relative control exerted by wind redistribution of snow and of direct incident solar radiation on the accumulation and ablation processes. The data obtained to date suggest that the importance of the orientation gradient varies widely among the mountain ranges studied, being a good predictor of snow distribution patterns in the Front Range of the Colorado Rockies and the Snowy Range in southern Wyoming, both of which are relatively windswept, while in the much less windy Bridger Range, in south-western Montana, both orientation and elevation appear to contribute on an almost equal basis. An indirect method of estimating relative amounts of annual mass turnover, using eleven glaciers located in the Wind River of west central Wyoming, is presented.

Spatial Patterns of Snow Accumulation in the Alpine Terrain

Abstract A model, relating spatial patterns of snow accumulation in the alpine belt of major mountain ranges to the angular relationship which exists among terrain features such as cirque basins, mean storm-path trajectories, and incident solar radiation, is presented together with a limited amount of relevant empirical data. It is suggested that an “orientation gradient” exists in both the temporal and spatial variation of accumulation and ablation in the alpine terrain, the importance of which varies as some function of the relative control exerted by wind redistribution of snow and of direct incident solar radiation on the accumulation and ablation processes. The data obtained to date suggest that the importance of the orientation gradient varies widely among the mountain ranges studied, being a good predictor of snow distribution patterns in the Front Range of the Colorado Rockies and the Snowy Range in southern Wyoming, both of which are relatively windswept, while in the much less windy Bridger Range, in south-western Montana, both orientation and elevation appear to contribute on an almost equal basis. An indirect method of estimating relative amounts of annual mass turnover, using eleven glaciers located in the Wind River of west central Wyoming, is presented.

Strong Snow-Storms, their Effect on Snow Cover and Snow Accumulation

AbstractSnow-drifts have been studied by many researchers both in field and laboratory conditions, however these investigations have been carried out mostly at wind speeds up to 20 m/s whereas in many areas of our planet snow-storms occur at winds up to 40 m/s and more. During the winter seasons of 1972-76 the authors carried out a great number of experiments with an artificial snow-storm in a special wind tunnel 27 m long. The wind speeds reached 40 m/s (60-65 m/s at the 10 m anemometer height). The existing theories and hypotheses of snow-drifting, and in particular the “diffusion" model, were tested in a series of the experiments. These have not confirmed the assumption of the Australian scientists on the decisive role of diffusion in drift mechanism at large wind speeds. The problem of strong snow-storm effect on snow accumulation on avalanche-danger slopes, in particular, wind redistribution of snow is no less important.The results obtained may be used for the determination of snow accumulation in avalanche starting zones due to deflation. This is especially important for forecasting very dangerous and frequently-occurring avalanches due to snow-storms. The investigations performed enable us to estimate the snow deposition produced by strong and superstrong snow-storms, to account for the peculiarities of such snow-storms and the means of protection, to forecast snow distribution in mountainous regions, and to define the role of snow-storms in glacier mass balance.

Strong Snow-Storms, their Effect on Snow Cover and Snow Accumulation

Abstract Snow-drifts have been studied by many researchers both in field and laboratory conditions, however these investigations have been carried out mostly at wind speeds up to 20 m/s whereas in many areas of our planet snow-storms occur at winds up to 40 m/s and more. During the winter seasons of 1972-76 the authors carried out a great number of experiments with an artificial snow-storm in a special wind tunnel 27 m long. The wind speeds reached 40 m/s (60-65 m/s at the 10 m anemometer height). The existing theories and hypotheses of snow-drifting, and in particular the “diffusion" model, were tested in a series of the experiments. These have not confirmed the assumption of the Australian scientists on the decisive role of diffusion in drift mechanism at large wind speeds. The problem of strong snow-storm effect on snow accumulation on avalanche-danger slopes, in particular, wind redistribution of snow is no less important. The results obtained may be used for the determination of snow accumulation in avalanche starting zones due to deflation. This is especially important for forecasting very dangerous and frequently-occurring avalanches due to snow-storms. The investigations performed enable us to estimate the snow deposition produced by strong and superstrong snow-storms, to account for the peculiarities of such snow-storms and the means of protection, to forecast snow distribution in mountainous regions, and to define the role of snow-storms in glacier mass balance.