Snow Redistribution Research Articles

ВЛИЯНИЕ СПЕЦИФИЧЕСКОГО РЕЖИМА СНЕЖНЫХ ОТЛОЖЕНИЙ НА ВЕЧНОМЁРЗЛЫE ОСНОВАНИЯ В ГОРОДАХ КРИОЛИТОЗОНЫ (НА ПРИМЕРЕ НОРИЛЬСКОГО РЕГИОНА)

With increasing snowfalls and rising winter temperatures in the Arctic regions of Russia (against the background of almost the same summer values), the role of solid precipitation in the formation of the temperature and humidity regimes of seasonally thawed and upper horizons of permafrost grounds becomes extremely important. No regular observations of snow accumulation in built-up areas were conducted in the Arctic settlements. This article presents for the first time the results of snow measurements in urbanized areas of the Norilsk region, and assesses the warming effect of snow cover on the permafrost grounds and foundations. The problems that arise during the mechanical redistribution of snow are identified. In some areas the thickness of the snow cover (near the city of Norilsk) by the end of March can reach 200 cm; in February, the average monthly value for the last 15 years amounts 69 cm, and in the city the height of snow dumps ranges from 2 to 5 m. The warming effect of snow cover on the permafrost layer enhances as the snow height increases from 0 to 2–2.5 m, and then remains unchanged. Large masses of snow existing for many decades in almost the same places (together with the snow drifts of the air from the ventilated subfields) result in the development of degradation tendencies within the permafrost. A slight temperature rise was noted in grounds under 30–40% of the operated objects (as compared with the design values), which causes deformation of the structures.

The Antarctic sea ice cover from ICESat-2 and CryoSat-2: freeboard, snow depth, and ice thickness

Abstract. We offer a view of the Antarctic sea ice cover from lidar (ICESat-2) and radar (CryoSat-2) altimetry, with retrievals of freeboard, snow depth, and ice thickness that span an 8-month winter between 1 April and 16 November 2019. Snow depths are from freeboard differences. The multiyear ice observed in the West Weddell sector is the thickest, with a mean sector thickness > 2 m. The thinnest ice is found near polynyas (Ross Sea and Ronne Ice Shelf) where new ice areas are exported seaward and entrained in the surrounding ice cover. For all months, the results suggest that ∼ 65 %–70 % of the total freeboard is comprised of snow. The remarkable mechanical convergence in coastal Amundsen Sea, associated with onshore winds, was captured by ICESat-2 and CryoSat-2. We observe a corresponding correlated increase in freeboards, snow depth, and ice thickness. While the spatial patterns in the freeboard, snow depth, and thickness composites are as expected, the observed seasonality in these variables is rather weak. This most likely results from competing processes (snowfall, snow redistribution, snow and ice formation, ice deformation, and basal growth and melt) that contribute to uncorrelated changes in the total and radar freeboards. Evidence points to biases in CryoSat-2 estimates of ice freeboard of at least a few centimeters from high salinity snow (> 10) in the basal layer resulting in lower or higher snow depth and ice thickness retrievals, although the extent of these areas cannot be established in the current data set. Adjusting CryoSat-2 freeboards by 3–6 cm gives a circumpolar ice volume of 17 900–15 600 km3 in October, for an average thickness of ∼ 1.29–1.13 m. Validation of Antarctic sea ice parameters remains a challenge, as there are no seasonally and regionally diverse data sets that could be used to assess these large-scale satellite retrievals.

Predicting Variable Contributing Areas, Hydrological Connectivity, and Solute Transport Pathways for a Canadian Prairie Basin

AbstractIn cold agricultural regions, seasonal snowmelt over frozen soils provides the primary source of runoff and transports large nutrient loads downstream. The postglacial landscape of the Canadian Prairies and Northern Plains of the United States creates challenges for hydrological and water quality modeling. Here, the application of conventional hydrological models is problematic because of cold regions hydrological and chemical processes, the lack of fluvially eroded drainage systems, large noncontributing areas to streamflow and level topography. A new hydrodynamic model was developed to diagnose overland flow from snowmelt in this situation. The model was used to calculate the effect of variable contributing areas on (1) hydrological connectivity and the development of (2) tipping points in streamflow generation and (3) predominant chemical transport pathways. The agricultural Steppler Basin in Manitoba, Canada, was used to evaluate the model and diagnose snowmelt runoff. Relationships were established between contributing area and (1) snowmelt runoff intensity, (2) seasonal snowmelt volumes and duration, and (3) inundated, active and connected areas. Variations in the contributing area depended on terrain and snowmelt characteristics including wind redistribution of snow. Predictors of hydrological response and the size of the contributing area were developed which can be used in larger scale hydrological models of similar regions

Airflow over low-sloped gable roof buildings: Wind tunnel experiment and CFD simulations

In this study, the impact of roof slope on the flow characteristics over low-sloped gable roofs was investigated using steady computational fluid dynamics (CFD) simulations based on a k-ω SST turbulence model. A measurement database of the flow field over a scaled model of 15° was created using particle image velocimetry (PIV). Sensitivity analyses for the grid resolutions and turbulence models were performed. Among the three common Reynolds-averaged Navier-Stokes equations (RANS) models, the k-ω SST model exhibited a better performance, followed by the RNG model and then the realizable k- model. Next, the flow properties over the differently sloped (0° to 25°) building models were determined. It was found that the effect of roof slope on the flow characteristics was identified by changing the position and size of the separation bubbles, 15° was found to be approximately the sensitive slope at which the distribution of the separation bubbles changed significantly. Additionally, it is suggested additional attention focused on the distributions of the negative pressure on the windward surfaces (especially 5° and 10° roofs) and the possible snow redistribution on the leeward surfaces.

Slope processes connected with snow patches in semi-arid ice-free areas of James Ross Island, Antarctic Peninsula

In this study, we aim to describe geomorphological processes related to snow patches in the ice-free environment of James Ross Island located in Maritime Antarctica. The area of interest for this study is situated on Cape Lachman and consists of an approximately 1500 m long and 300 m wide oval-shaped depression with two shallow lakes at the bottom. Due to the varied aspect of the slopes, large snow accumulations form in the southern part of the depression, where the slopes exhibit a lee aspect towards the prevailing southwestern wind. Within the semi-arid conditions of James Ross Island, the redistribution of snow by wind and the availability of moisture from the melting snow play a key role in shaping of the landscape. Via repeated UAV surveys, field campaigns and construction of a digital terrain model of the study area, we were able to identify the specific landforms that have been shaped by nival processes, such as winnowing of the fine material and its subsequent transport downslope; and mass-wasting, resulting from slumping of the meltwater-saturated active layer. We developed a three-step model of landscape evolution throughout the Holocene, which helps to explain how snow-related processes contribute to landscape shaping within the ice-free environment of James Ross Island.

CFD simulation of snow redistribution on a bridge deck: Effect of barriers with different porosities

Snow redistribution caused by snowdrift may worsen the traffic condition of bridge decks in snowy regions, hence it needs to be considered in bridge designs. In this study, a quasi-steady numerical method is adopted to simulate snowdrift on a typical bridge deck with barriers. The whole process of snowdrift on bridge decks is divided into several phases to simulate the variation in profile of snowpack, and a two-dimensional (2D) steady Computational Fluid Dynamics (CFD) simulation method is employed in each phase. To investigate the effect of barriers on the snow redistribution on bridge decks, the simulation results of wind velocity field, wall friction velocity, snow concentration field and snow redistributions are analyzed in detail. Generally, as the barrier porosity decreases, the total amount of snow erosion decreases due to the blocking effect of the barrier, but the decrease is limited when the barrier porosity is below 37.5%. Heavy snow accumulation mainly occurs behind the windward barrier when the barrier porosity is below 62.5%. To avoid snow accumulation, barrier porosity above 75% is suggested as the optimal choice for improving the traffic condition of bridge decks.

Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys

Abstract. We use repeat high-resolution airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery acquired in 2014, 2016, and 2017 to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88∘ S, an elevation bias validation site for ICESat-2 and potential validation site for CryoSat-2. We find significant small-scale variability (<10 km) in snow accumulation based on the snow radar subsurface stratigraphy, indicating areas of strong wind redistribution are prevalent at 88∘ S. In general, highs in snow accumulation rate correspond with topographic lows, resulting in a negative correlation coefficient of r2=-0.32 between accumulation rate and MSWD (mean slope in the mean wind direction). This relationship is strongest in areas where the dominant wind direction is parallel to the survey profile, which is expected as the geophysical surveys only capture a two-dimensional cross section of snow redistribution. Variability in snow accumulation appears to correlate with variability in MSWD. The correlation coefficient between the standard deviations of accumulation rate and MSWD is r2=0.48, indicating a stronger link between the standard deviations than the actual parameters. Our analysis shows that there is no simple relationship between surface slope, wind direction, and snow accumulation rates for the overall survey area. We find high variability in surface roughness derived from laser altimetry measurements on length scales smaller than 10 km, sometimes with very distinct and sharp transitions. Some areas also show significant temporal variability over the course of the 3 survey years. Ultimately, there is no statistically significant slope-independent relationship between surface roughness and accumulation rates within our survey area. The observed correspondence between the small-scale temporal and spatial variability in surface roughness and backscatter, as evidenced by Ku-band radar signal strength retrievals, will make it difficult to develop elevation bias corrections for radar altimeter retrieval algorithms.

Temporal and spatial variabilities in surface mass balance at the EGRIP site, Greenland from 2009 to 2017

Temporal variability in surface mass balance (SMB) on the Greenland ice sheet is important for understanding the mass balance of the ice sheet. Additionally, knowledge of the spatial variability in SMB at ice core drilling sites helps to interpret the spatial representativeness of SMB data obtained from a single ice core. In this study, to investigate the spatiotemporal variability in recent SMB in the East Greenland Ice Core Project (EGRIP) area in the northeastern Greenland ice sheet, pit observations were made at six sites in the summers of 2016–2018. In all pits, depth profiles of water isotope ratios showed clear seasonal variations. The annual SMB differed from site to site, which is probably due to post-depositional redistribution of snow caused by wind erosion and snowdrift. However, the multiple-site averages of annual SMBs, which ranged from 134 to 157 mm w. e. yr−1 (average 146 mm w. e. yr−1) during 2009–2017, were very similar. This indicates that annual SMBs in the EGRIP area were nearly constant in this period. The seasonal SMBs in the EGRIP area tended to be larger in the summer–winter period than in the winter–summer period.

Mechanisms of Cold Region Hydrologic Change to Recent Wetting in a Northern Glaciated Landscape

AbstractThe Northern Great Plains (NGP) experienced a transition from a long drought cycle to a deluge cycle in the late 1900s. Embedded within this long‐term transition were shorter‐term decadal‐scale dry and wet periods. A recent NGP drought (1999–2004) was followed in 2005 by a wet period that continues to present day. However, how surface hydrology in a northern glaciated landscape responds to increased precipitation is poorly understood and a physically based modeling framework is needed to clarify the underlying processes. This study utilizes a physically based hydrologic model to investigate the impacts of increased precipitation on the water budget by examining its partition into intermediate processes from 2004–2017 in the Mauvais Coulee Basin (MCB). The MCB model evaluations against snow observations (2016–2017) and outlet streamflow observations (2004–2017) imply strong model performance. Simulated snow exhibits high spatiotemporal variation due to variability in precipitation, snow redistribution from stubble fields to wooded areas, and snow accumulation in small depressions. Our modeling results identify two major phases (before and after 2011) exhibiting different hydrologic responses. The period before 2011 is dominated by streamflow and evapotranspiration (ET), while extreme ET dominance is observed after 2011. This switch is due to climatic conditions involving changes in the vapor density difference and depressional and subsurface storage by intermediate processes. A clear contrast in the prewinter soil moisture‐streamflow relationship between before and after 2011 is reported. Our findings help illuminate the important influences of increased precipitation upon the intermediate processes in controlling streamflow in a northern glaciated prairie landscape.

Radar measurements of blowing snow off a mountain ridge

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.

Diagnosis of future changes in hydrology for a Canadian Rockies headwater basin

Abstract. Climate change is anticipated to impact the hydrology of the Saskatchewan River, which originates in the Canadian Rockies mountain range. To better understand the climate change impacts in the mountain headwaters of this basin, a physically based hydrological model was developed for this basin using the Cold Regions Hydrological Modelling platform (CRHM) for Marmot Creek Research Basin (∼9.4 km2), located in the Front Ranges of the Canadian Rockies. Marmot Creek is composed of ecozones ranging from montane forests to alpine tundra and alpine exposed rock and includes both large and small clearcuts. The model included blowing and intercepted snow redistribution, sublimation, energy-balance snowmelt, slope and canopy effects on melt, Penman–Monteith evapotranspiration, infiltration to frozen and unfrozen soils, hillslope hydrology, streamflow routing, and groundwater components and was parameterised without calibration from streamflow. Near-surface outputs from the 4 km Weather Research and Forecasting (WRF) model were bias-corrected using the quantile delta mapping method with respect to meteorological data from five stations located from low-elevation montane forests to alpine ridgetops and running over October 2005–September 2013. The bias-corrected WRF outputs during a current period (2005–2013) and a future pseudo global warming period (PGW, 2091–2099) were used to drive model simulations to assess changes in Marmot Creek's hydrology. Under a “business-as-usual” forcing scenario, Representative Concentration Pathway 8.5 (RCP8.5) in PGW, the basin will warm up by 4.7 ∘C and receive 16 % more precipitation, which will lead to a 40 mm decline in seasonal peak snowpack, 84 mm decrease in snowmelt volume, 0.2 mm d−1 slower melt rate, and 49 d shorter snow-cover duration. The alpine snow season will be shortened by almost 1.5 months, but at some lower elevations there will be large decreases in peak snowpack (∼45 %) in addition to a shorter snow season. Declines in the peak snowpack will be much greater in clearcuts than under mature forest canopies. In alpine and treeline ecozones, blowing snow transport and sublimation will be suppressed by higher-threshold wind speeds for transport, in forest ecozones, sublimation losses from intercepted snow will decrease due to faster unloading and drip, and throughout the basin, evapotranspiration will increase due to a longer snow-free season and more rainfall. Runoff will begin earlier in all ecozones, but, as a result of variability in surface and subsurface hydrology, forested and alpine ecozones will generate the greatest runoff volumetric increases, ranging from 12 % to 25 %, whereas the treeline ecozone will have a small (2 %) decrease in runoff volume due to decreased melt volumes from smaller snowdrifts. The shift in timing in streamflow will be notable, with 236 % higher flows in spring months and 12 % lower flows in summer and 13 % higher flows in early fall. Overall, Marmot Creek's annual streamflow discharge will increase by 18 % with PGW, without a change in its streamflow generation efficiency, despite its basin shifting from primarily snowmelt runoff towards rainfall-dominated runoff generation.

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.

The seasonal evolution of albedo across glaciers and the surrounding landscape of Taylor Valley, Antarctica

Abstract. The McMurdo Dry Valleys (MDVs) of Antarctica are a polar desert ecosystem consisting of alpine glaciers, ice-covered lakes, streams, and expanses of vegetation-free rocky soil. Because average summer temperatures are close to 0 ∘C, the MDV ecosystem in general, and glacier melt dynamics in particular, are both closely linked to the energy balance. A slight increase in incoming radiation or change in albedo can have large effects on the timing and volume of meltwater. However, the seasonal evolution or spatial variability of albedo in the valleys has yet to fully characterized. In this study, we aim to understand the drivers of landscape albedo change within and across seasons. To do so, a box with a camera, GPS, and shortwave radiometer was hung from a helicopter that flew transects four to five times a season along Taylor Valley. Measurements were repeated over three seasons. These data were coupled with incoming radiation measured at six meteorological stations distributed along the valley to calculate the distribution of albedo across individual glaciers, lakes, and soil surfaces. We hypothesized that albedo would decrease throughout the austral summer with ablation of snow patches and increasing sediment exposure on the glacier and lake surfaces. However, small snow events (<6 mm water equivalent) coupled with ice whitening caused spatial and temporal variability of albedo across the entire landscape. Glaciers frequently followed a pattern of increasing albedo with increasing elevation, as well as increasing albedo moving from east to west laterally across the ablation zone. We suggest that spatial patterns of albedo are a function of landscape morphology trapping snow and sediment, longitudinal gradients in snowfall magnitude, and wind-driven snow redistribution from east to west along the valley. We also compare our albedo measurements to the MODIS albedo product and found that overall the data have reasonable agreement. The mismatch in spatial scale between these two datasets results in variability, which is reduced after a snow event due to albedo following valley-scale gradients of snowfall magnitude. These findings highlight the importance of understanding the spatial and temporal variability in albedo and the close coupling of climate and landscape response. This new understanding of landscape albedo can constrain landscape energy budgets, better predict meltwater generation on from MDV glaciers, and how these ecosystems will respond to changing climate at the landscape scale.

Impacts of Degrading Ice‐Wedges on Ground Temperatures in a High Arctic Polar Desert System

AbstractIce‐wedge ice is the most widespread type of massive ice found in the continuous permafrost zone. Polygonal networks of ice‐wedges drive environmental changes and feedback that will likely be exacerbated with future climate change. Recent decadal‐scale observations have shown that ice‐wedges are degrading rapidly within the entire Circum‐Arctic Region but observations of feedback associated with ground temperature regimes are still lacking in many areas. We present over a year's worth of field observations from an area with cold (−16.5°C), thick (>500 m) continuous permafrost and a mean annual air temperature of −19.7°C in the Canadian high Arctic. Topographic surveys, thaw depths, vegetation cover, soil moisture, and annual shallow (12 cm) ground temperature measurements were collected for seven ice‐wedge troughs and two polygon centers in a high‐centered polygon system. We show that geomorphic changes caused by ice‐wedge degradation generate new responses in soil moisture, vegetation cover, and snow distribution that create a mosaic of ground temperatures that range by 5.1°C for mean annual, 2.5°C in summer, and 15.2°C in winter between polygon‐centers and ice‐wedge troughs. Our results show that snow redistribution due to wind induces the cooling of polygon centers, thus promoting new thermal contraction cracking and ice‐wedge formation. We provide an example based on high‐resolution remote sensing data on how these ice‐wedge trough densities vary spatially in our study area. Capturing these fine scale geomorphic differences and resulting ground temperatures will be critical to accurately assess future changes of these common Arctic landscapes.

Pan-Antarctic map of near-surface permafrost temperatures at 1 km2 scale

Abstract. Permafrost is present within almost all of the Antarctic's ice-free areas, but little is known about spatial variations in permafrost temperatures except for a few areas with established ground temperature measurements. We modelled a temperature at the top of the permafrost (TTOP) for all the ice-free areas of the Antarctic mainland and Antarctic islands at 1 km2 resolution during 2000–2017. The model was driven by remotely sensed land surface temperatures and downscaled ERA-Interim climate reanalysis data, and subgrid permafrost variability was simulated by variable snow cover. The results were validated against in situ-measured ground temperatures from 40 permafrost boreholes, and the resulting root-mean-square error was 1.9 ∘C. The lowest near-surface permafrost temperature of −36 ∘C was modelled at Mount Markham in the Queen Elizabeth Range in the Transantarctic Mountains. This is the lowest permafrost temperature on Earth, according to global-scale modelling results. The temperatures were most commonly modelled between −23 and −18 ∘C for mountainous areas rising above the Antarctic Ice Sheet and between −14 and −8 ∘C for coastal areas. The model performance was good where snow conditions were modelled realistically, but errors of up to 4 ∘C occurred at sites with strong wind-driven redistribution of snow.

A Finite Volume Blowing Snow Model for Use With Variable Resolution Meshes

AbstractBlowing snow is ubiquitous in cold, windswept environments. In some regions, blowing snow sublimation losses can ablate a notable fraction of the seasonal snowfall. It is advantageous to predict alpine snow regimes at the spatial scale of snowdrifts (≈1 to 100 m) because of the role of snow redistribution in governing the duration and volume of snowmelt. However, blowing snow processes are often neglected due to computational costs. Here, a three‐dimensional blowing snow model is presented that is spatially discretized using a variable resolution unstructured mesh. This represents the heterogeneity of the surface explicitly yet, for the case study reported, gained a 62% reduction in computational elements versus a fixed‐resolution mesh and resulted in a 44% reduction in total runtime. The model was evaluated for a subarctic mountain basin using transects of measured snow water equivalent (SWE) in a tundra valley. Including blowing snow processes improved the prediction of SWE by capturing inner‐annual snowdrift formation, more than halved the total mean bias error, and increased the coefficient of variation of SWE from 0.04 to 0.31 better matching the observed CV (0.41). The use of a variable resolution mesh did not dramatically degrade the model performance. Comparison with a constant resolution mesh showed a similar CV and RMSE as the variable resolution mesh. The constant resolution mesh had a smaller mean bias error. A sensitivity analysis showed that snowdrift locations and immediate up‐wind sources of blowing snow are the most sensitive areas of the landscape to wind speed variations.

Processes governing snow ablation in alpine terrain – detailed measurements from the Canadian Rockies

Abstract. The spatial distribution of snow water equivalent (SWE) and melt are important for estimating areal melt rates and snow-cover depletion (SCD) dynamics but are rarely measured in detail during the late ablation period. This study contributes results from high-resolution observations made using large numbers of sequential aerial photographs taken from an unmanned aerial vehicle on an alpine ridge in the Fortress Mountain Snow Laboratory in the Canadian Rocky Mountains from May to July in 2015. Using structure-from-motion and thresholding techniques, spatial maps of snow depth, snow cover and differences in snow depth (dHS) during ablation were generated in very high resolution as proxies for spatial SWE, spatial ablation rates and SCD. The results indicate that the initial distribution of snow depth was highly variable due to overwinter snow redistribution; thus, the subsequent distribution of dHS was also variable due to albedo, slope/aspect and other unaccountable differences. However, the initial distribution of snow depth was 5 times more variable than that of the subsequent dHS values, which varied by a factor of 2 between the north and south aspects. dHS patterns were somewhat spatially persistent over time but had an insubstantial impact on SCD curves, which were overwhelmingly governed by the initial distribution of snow depth. The reason for this is that only a weak spatial correlation developed between the initial snow depth and dHS. Previous research has shown that spatial correlations between SWE and ablation rates can strongly influence SCD curves. Reasons for the lack of a correlation in this study area were analysed and a generalisation to other regions was discussed. The following questions were posed: what is needed for a large spatial correlation between initial snow depth and dHS? When should snow depth and dHS be taken into account to correctly model SCD? The findings of this study suggest that hydrological and atmospheric models need to incorporate realistic distributions of SWE, melt energy and cold content; therefore, they must account for realistic correlations (i.e. not too large or too small) between SWE and melt in order to accurately model SCD.

Evaluation of SNODAS Snow Water Equivalent in Western Canada and Assimilation Into a Cold Region Hydrological Model

AbstractSnow water equivalent (SWE) is one of the most hydrologically important physical properties of a snowpack. The U.S. National Weather Service's Snow Data Assimilation System (SNODAS) provides snow products at high spatial (~1 km2) and temporal (daily) resolution for the contiguous United States and southern Canada. This study evaluated the SNODAS SWE product in the boreal forest, prairie, and Canadian Rockies of western Canada against extensive snow survey measurements. SNODAS was found to work well in sheltered environments, to overestimate SWE under needle‐leaf forests, and to be unable to capture the spatial variation of SWE in windswept prairie and alpine environments. Results indicate that SNODAS SWE accuracy is strongly influenced by the missing blowing snow redistribution and canopy energetics and snow interception and sublimation processes in the mass balance calculations of the SNODAS model and by erroneous precipitation data forcing the model. To demonstrate how errors caused by missing processes can be corrected in areas with low assimilation frequency, SNODAS data were assimilated into a physically based hydrological model created using the modular Cold Region Hydrological Modelling (CRHM) platform that includes blowing and intercepted snow redistribution and subcanopy melt energetic processes. This approach decreased the overestimation of SWE compared to SNODAS from 135 to 79% in the study area and suggests that snow assimilation modeled SWE quality can be improved if snow redistribution, sublimation, and subcanopy melt processes are incorporated.

Significant Spatial Variability in Radar‐Derived West Antarctic Accumulation Linked to Surface Winds and Topography

AbstractAcross the Antarctic Ice Sheet, accumulation heavily influences firn compaction and surface height changes. Therefore, accumulation varies over short distances (<25 km), complicating the derivation of ice sheet mass changes from altimetry and reducing how accurately field measurements can be spatially extrapolated. However, current atmospheric reanalyses have grid spacings (>25 km) that are too coarse to resolve this variability. To address this limitation, we construct a fine‐scale accumulation product from airborne snow radar observations by superimposing along‐track fluctuations in accumulation onto an atmospheric reanalysis product. Our resulting airborne product reflects large‐scale (>25 km) orographic precipitation patterns while providing robust and unprecedented insight into Antarctic accumulation variability on subgrid scales. On these smaller scales, we find significant, regionally dependent accumulation variability (σrelative>40%). This variability in accumulation is correlated with variability in topographic surface slope in the wind direction (p<0.01), confirming that subgrid‐scale accumulation variability is driven by snow redistribution by wind.

CFD simulation of wind-induced snow redistribution on gable roofs

CFD simulation of wind-induced snow redistribution on gable roofs