Snow Drift Research Articles

Case Study of Blowing Snow Impacts on the Antarctic Peninsula Lower Atmosphere and Surface Simulated With a Snow/Ice Enhanced WRF Model

AbstractTo better capture the air‐snow‐ice interaction, a snow/ice enhanced Weather Research and Forecasting (WRF‐ice) model has been developed. This study examines the performance of WRF‐ice and its blowing snow component during a strong cyclone event from October 23 to 27, 2017 over the Antarctic Peninsula, which is characterized by a synoptic cyclone crossing the northern part of the Peninsula and an embodied mesoscale cyclone over the Weddell Sea. Evolution of the cyclone is accurately reproduced in the 5‐km resolution WRF‐ice simulation, and the simulated near‐surface conditions agree well with station and satellite observations. Numerical simulations show that the process of blowing snow sublimation can be prominent within the lower atmosphere when the air is dry, and produces moistening and cooling effects. Over relatively warm and humid areas, cloud enhancement by blowing snow can lead to either colder or warmer surfaces because of competing effects of longwave and shortwave cloud radiative forcings. In particular, additional moisture from blowing snow sublimation can slightly intensify precipitation over the mountains. Surface energy budget analysis indicates that absorbed shortwave (Sa), incoming longwave (Ld), and outgoing longwave (Lu) are dominant components of surface energy budget. When increases in Ld, Lu, and sensible heat flux are combined with decreases in Sa and latent heat flux due to blowing snow effects, a negative surface net heat flux (∼0.5 W/m2) occurs during daytime. A positive domain‐total surface mass balance (∼0.43 Gt) is generated during the simulated cyclone event due to increases in precipitation, decreases in runoff, and decreases in sublimation.

Study of Antarctic Blowing Snow Storms Using MODIS and CALIOP Observations With a Machine Learning Model

AbstractAs a common phenomenon over Antarctica, blowing snow (BLSN), especially the large BLSN storms, play an important role in the Antarctic surface mass balance, radiation budget, and planetary boundary layer processes. This study presents the work on BLSN storm identification and analysis with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite. Spectral analysis shows that BLSN identification is feasible with MODIS daytime data. A random forest machine learning model is developed and observations from the Cloud‐Aerosol Lidar with Orthogonal Polarization are used for training. Model performance results show that machine‐learning based classification can achieve over 90% overall accuracy when classifying MODIS pixels into cloud, clear, and BLSN categories. The machine learning model is applied to MODIS observations during the month of October 2009 for BLSN storm analysis. Results show that the size of BLSN storms has a large spectrum and can reach hundreds of thousands km2. The MODIS based BLSN storm frequency map extends the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations coverage limit from 82°S to the South Pole. A BLSN storm belt, which extends from the South Pole region to the coastal area between 130°E and 160°E along the Transantarctic Mountains, provides a potential pathway of snow transport. These results are important in improving the understanding of BLSN impact on Antarctic surface mass balance and boundary layer processes.

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.

Особенности психологической подготовки военнослужащих к действиям в экстремальной ситуации

There are many examples of crises and catastrophes in the history of mankind. Almost the entire spectrum of natural disasters is possible in Kazakhstan. In particular, earthquakes, floods, fires in forests and steppes, snowstorms, and others. In all mountain and foothill zones, there is a danger of landslides, the threat of snow drift. In addition, there are situations that have arisen for man-made reasons. These catastrophes are the result of human activity. Such extreme situations require the concentration of all physical and psychological capabilities of a person. This is especially important for military personnel who often operate in extreme or critical conditions. Psychological readiness to solve such situations gives the individual confidence in the correctness of their own actions and, in the end, leads to a successful result. The purpose of this article is to present the results of research in the framework of a master's thesis. The main focus is on the analysis of the features of psychological training of military personnel to act in an extreme situation. The studied problem is revealed by the authors from the point of view of modern approaches to the psychological training of military personnel in a critical situation. The research methods used (analysis, generalization, experiment) allowed us to reveal the depth of the problem relevant to military psychology. The research is based on the results of modern research by Kazakh and foreign scientists. Approaches to the interpretation of the essence of the content of the concept "extreme situation" are considered, and the factors that determine the specifics of psychological training of military personnel to act in a crisis are highlighted. The concept of "psychological readiness of military personnel to work in critical (extreme) situations" is defined. Statistical results of the experiment are presented. The experimental activity carried out in the course of experimental work has a high practical significance, since it was successfully tested through the implementation of the work of the military unit 3176 "K" in Pavlodar and can be used in the psychological training of military personnel. The article is devoted to the actual problem of psychology. The results presented in the article may be useful for military psychologists.

Ecophysiological and ultrastructural characterisation of the circumpolar orange snow alga Sanguina aurantia compared to the cosmopolitan red snow alga Sanguina nivaloides (Chlorophyta)

Red snow caused by spherical cysts can be found worldwide, while an orange snow phenomenon caused by spherical cells is restricted to (Sub-)Arctic climates. Both bloom types, occurring in the same localities at Svalbard, were compared ecophysiologically. Using a combination of molecular markers and light- and transmission electron microscopy, cells were identified as Sanguina nivaloides and Sanguina aurantia (Chlorophyceae). In search for reasons for a cosmopolitan vs. a more restricted distribution of these microbes, significant differences in fatty acid and pigment profiles of field samples were found. S. aurantia accumulated much lower levels of polyunsaturated fatty acids (21% vs. 48% of total fatty acids) and exhibited lower astaxanthin-to-chlorophyll-a ratio (2–8 vs. 12–18). These compounds play an important role in adaptation to extreme conditions at the snow surface and within snow drifts. Accordingly, the performance of photosystem II showed that one third to nearly half of the photosynthetic active irradiation was sufficient in S. aurantia, compared to S. nivaloides, to become light saturated. Furthermore, formation of plastoglobules observed in S. nivaloides but missing in S. aurantia may contribute to photoprotection. The rapid light curves of the two species show to a certain extent the shade-adapted photosynthesis under the light conditions at Svalbard (high α-value 0.16 vs. 0.11, low saturation point Ik 59 vs. 86). These results indicate significant physiological and ultrastructural differences of the two genetically closely related cryoflora species, but the reasons why S. aurantia has not been found at conditions outside (Sub-)Arctic climate types remain unknown.

Industrial electrical heating systems to ensure the safe and uninterrupted operation of enterprises

The article describes modern methods for ensuring the safe operation of technological installations of enterprises and related processes, by introducing industrial electric heating systems based on electric heating cables into their composition. Such systems are widely used in modern industry to protect equipment from freezing, maintain specified technological temperatures, ensure uninterrupted operation, and also to provide a comfortable and safe environment in enterprises reducing (the lost time injures rates by protecting of gutters, roofs and open areas from the negative effects of the environment, such as ice, icicles, snow drifts, etc.)

Comparative Analysis of Effectiveness of Resistance and Induction Turnout Heating

Turnouts are key parts of rail roads and are exposed to adverse weather conditions such as snowfall, snow drifts, low temperatures, or sleet. Effective protection assures good turnout function and contributes to rail traffic efficiency and safety. Presently, resistance heating (RH) is the most common system of turnout heating in Europe. In this study, we attempted to implement energy-saving induction heating (IH) in order to cut costs of operation and electricity. A turnout heating test stand, including a stock-rail and a switch-rail, was executed in a climatic chamber. Air temperature was constant at the time of heating. Active power received by both the systems was identical for any measurement (450 W). Test results enabled an assessment of switch-rail position and variations of climatic chamber air temperature on growth of turnout temperatures. Effects of heating type on correct lubrication of the slide plate surface were compared. Dynamics of heating variations and their impact on effectiveness of snow or ice removal were defined for both heating systems. Turnout’s readiness for switch-rail shifting and lubrication conditions of turnout’s moving parts were compared. An in-depth comparative analysis of efficiency of RH and IH turnout heating was undertaken in the conclusion.

Topographic, edaphic and climate influences on aspen (Populus tremuloides) drought stress on an intermountain bunchgrass prairie

Quaking aspen, Populus tremuloides, has experienced severe declines in recent years in part due to the effects of changing climate and extreme drought. This study set out to investigate these effects by assessing associations of climatic, edaphic and topographic variables with physiological drought stress in aspen. The study took place on the Zumwalt Prairie in northeastern Oregon, a semi-arid bunchgrass prairie where aspen occur in isolated stands associated with riparian areas and late-season persistence of snow drifts. Using a 33-year time series of Landsat imagery to detect associations of aspen stands late-season snow cover and field measurements of soil moisture in aspen stands during 2017, we found while snow dominated stands were associated with greater soil moisture during spring, levels had equilibrated to those of other upland stands by summer. Measurements of predawn and midday stem Ψ in multiple height classes of aspen ramets revealed associations of both shallow soil moisture and vapor pressure deficit with physiological drought stress in aspen. Analysis of soil texture class revealed an important association with midday stem Ψ, with finer textured soils associated with decreased stem Ψ in comparison to coarser textured soils. While neither topographical characteristics nor snow cover were found to be important drivers of drought stress, topographical curvature was found to have a strong influence on summer soil moisture in upland stands. These findings contribute to our understanding of aspen physiology, drought ecology and landscape hydrology toward the xeric margin of aspen’s range. This information can help land managers anticipate and adapt to changing climates and understand their effects on key plant species such as aspen.

Warm-air entrainment and advection during alpine blowing snow events

Abstract. Blowing snow transport has considerable impact on the hydrological cycle in alpine regions both through the redistribution of the seasonal snowpack and through sublimation back into the atmosphere. Alpine energy and mass balances are typically modeled with time-averaged approximations of sensible and latent heat fluxes. This oversimplifies nonstationary turbulent mixing in complex terrain and may overlook important exchange processes for hydrometeorological prediction. To determine if specific turbulent motions are responsible for warm- and dry-air advection during blowing snow events, quadrant analysis and variable interval time averaging was used to investigate turbulent time series from the Fortress Mountain Snow Laboratory alpine study site in the Canadian Rockies, Alberta, Canada, during the winter of 2015–2016. By analyzing wind velocity and sonic temperature time series with concurrent blowing snow, such turbulent motions were found to supply substantial sensible heat to near-surface wind flows. These motions were responsible for temperature fluctuations of up to 1 ∘C, a considerable change for energy balance estimation. A simple scaling relationship was derived that related the frequency of dominant downdraft and updraft events to their duration and local variance. This allows for the first parameterization of entrained or advected energy for time-averaged representations of blowing snow sublimation and suggests that advection can strongly reduce thermodynamic feedbacks between blowing snow sublimation and the near-surface atmosphere. The downdraft and updraft scaling relationship described herein provides a significant step towards a more physically based blowing snow sublimation model with more realistic mixing of atmospheric heat. Additionally, calculations of return frequencies and event durations provide a field-measurement context for recent findings of nonstationarity impacts on sublimation rates.

Observing and Modeling the Isotopic Evolution of Snow Meltwater on the Southeastern Tibetan Plateau

AbstractObserving the isotopic evolution of snow meltwater helps in understanding the process of snow melting but remains a challenge to acquire in the field. In this study, we monitored the melting of two snowpacks near Baishui Glacier No. 1, a typical temperate glacier on the southeastern Tibetan Plateau. We employed a physically based isotope model (PBIM) to calculate the isotopic composition of meltwater draining from natural snowpacks. The initial condition of the PBIM was revised to account for natural conditions, i.e., the initial δ18O stratigraphy of snow layers before melting. Simulations revealed that the initial heterogeneity of δ18O in snow layers as well as ice‐liquid isotopic exchange were responsible for most variations of δ18O in snow meltwater, whereas new snow and wind drift could result in sudden changes of the isotopic composition of the meltwater. The fraction of ice involved in the isotopic exchange (f) was the most sensitive parameter for the model output. The initial δ18O in the snowpack is mirrored in meltwater in case of small f and is smoothed with a large exchange fraction f. The other unknown parameter of the PBIM is the dimensionless rate constant of isotopic exchange, which depends on water percolation and initial snow depth. The successful application of the PBIM in the field might not only be useful for understanding snow melting process but might also provide the possibility of predicting the isotopic composition of snow meltwater and improve the accuracy of hydrograph separation.

Importance of Blowing Snow During Cloudy Conditions in East Antarctica: Comparison of Ground-Based and Space-Borne Retrievals Over Ice-Shelf and Mountain Regions

Continuous measurements of blowing snow are scarce, both in time and space. Satellites now provide the opportunity to derive blowing snow occurrences, transport and sublimation rates over Antarctica. These products are extremely valuable and offer a continental-wide assessment of blowing snow, which is an important but unknown component of the surface mass balance of the Antarctic ice sheet. However, little ground truth is available to validate these retrievals. The recent application of ceilometers for detection of blowing snow frequencies provides an opportunity to validate the satellite retrievals of blowing snow frequencies at the Princess Elisabeth and Neumayer stations, East Antarctica for the 2011-2016 time period. A routine to detect blowing snow occurrence from remote sensing ceilometers has been developed at those locations. Thanks to their ground-based location, ceilometers are able to detect blowing snow events in the presence of clouds and precipitation, which can be missed by the satellite, since optically thick clouds impede the penetration of the signal. This is important, since the proportion of events missed by the CALIPSO and ICESat-2 satellites due to the presence of cloud decks is currently unknown. Over coastal areas, up to 90% of blowing snow happens under cloudy conditions and represent 30%of all cloudy conditions at both Neumayer and Princess Elisabeth stations. Although both detection methods have their limitations, 10% (4%) of the measurements at Princess Elisabeth (and Neumayer) are identified as blowing snow by the satellite but not by the ceilometer, likely due to differences in sensors, limitation of the surface identification by the satellite, or the spatial inhomogeneity of the blowing snow event. While the satellite blowing snow retrieval is a useful product, further investigation is needed to reduce the uncertainties on blowing snow frequencies associated with clouds.

Present and future changes in winter climate indices relevant for access disruptions in Troms, northern Norway

Abstract. A number of seaside communities in Troms, northern Norway, are vulnerable to sudden weather-induced access disruptions due to high-impact weather and dependency on one or few roads. In this paper we study changes in winter weather known to potentially cause access disruptions in Troms, for the present climate (1958–2017) and two future periods (2041–2070; 2071–2100). We focus on climate indices associated with snow avalanches and weather that may lead to for example slippery road conditions. In two focus areas, the most important results show larger snow amounts now compared to 50 years ago, and heavy snowfall has become more intense and frequent. This trend is expected to turn in the future, particularly at low elevations where snow cover during winter might become a rarity by 2100. Strong snow drift, due to a combination of snowfall and wind speed, has slightly increased in the two focus areas, but a strong decrease is expected in the future due to less snow. Events of heavy rain during winter are rather infrequent in the present winter climate of Troms, but we show that these events are likely to occur much more often in all regions in the future.

A Dynamic Bayesian Network model for ship-ice collision risk in the Arctic waters

Extreme weather conditions of the Arctic and its icy waters pose high-risk potential for a range of marine accidents in the region. Ship-ice collision is the focus of this paper. A large number of vessels operating in the Arctic waters are at risk of ice damage due to ship-ice collisions. The damage may vary from a minor hull deformation to ruptures that could put the lives, assets, and environment at risk. To minimize the risk of ship-ice collision in Arctic waters, a simple yet robust model to make routine safety-driven operational decisions could help. The present study proposes a Dynamic Bayesian Network (DBN) model to fill this gap. The model assesses the operational risk of ship-ice collision in an ice prone region using the hypothetical form of observations. Low temperatures, Weather, Ice, Fog, Darkness, Blowing snow, Poor visibility, Ice strength, Ice drift, Types of ice, Ice concentration and Speed of the vessel are considered as the primary risk factors in the region. The estimated collision risk would provide an easy to use indicator for decisions concerning safe operations in ice such as maneuvering, route selection, and safe speed. A case study of an oil tanker navigating across the Barents Sea is presented to explain the proposed model.

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.

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.

Winter Wind Parameter for Snow Drifts

AbstractThe relationships in ASCE 7 for the determination of roof snow drift size are functions of the ground snow load and the upwind fetch of the snow source area. In a 2019 paper, O’Rourke and C...

GOES-16 Observations of Blowing Snow in Horizontal Convective Rolls on 24 February 2019

Abstract On 24 February 2019, strong winds behind an Arctic cold front led to widespread blowing snow across the northern Great Plains including areas in eastern North/South Dakota and western Minnesota. Impacts of the event ranged from blizzard conditions in northwest Minnesota to sporadic, minor reductions in visibility across the region. This study documents the event using remotely sensed observations from platforms including geostationary and polar-orbiting satellites, an S-band radar, and time-lapse images from a camera located at the University of North Dakota in Grand Forks, North Dakota. Blowing snow is observed as plumes that resemble horizontal convective rolls (HCRs). Variations in near-infrared imagery are documented, and supporting observations suggest this is due to the occurrence or absence of clouds on top of the blowing snow layer. While lack of in situ observations preclude further investigation of physical differences between plumes, the utility of the Geostationary Operational Environmental Satellite-16 (GOES-16) satellite to operational forecasters is discussed. Improvements to spatial, radiometric, and temporal resolution courtesy of the Advanced Baseline Imager (ABI) on board GOES-16 allows for daytime detection of blowing snow events that previously, was only possible with instruments on board polar-orbiting satellites. This has improved Impact-Based Decision Support Services (IDSS) at National Weather Service offices that deal with the hazard of blowing snow.

Combining niche and game theories to address interspecific cooperation in ecological communities

Incorporating cooperative interspecific interactions into the classical Niche Theory has been identified as a big challenge of population and community ecology. Attempting to fill this gap I present the Lotka-Volterra Niche Game Model (LVNGM), resulting from the marriage between the classical Niche Theory and Game Theory. I use this new framework to analyze the effects of including cooperative interspecific interactions on two global properties of a community, its aggregate biomass or total yield and its biodiversity, measured by the Shannon equitability. I consider different dilemma games, games for which neither pure competition nor pure cooperation are dominant/optimal strategies, which are popular in biology: the Prisoner's Dilemma (PD), the Snowdrift (SD) and the Stag-Hunt (SH) games. The main result is that these games lead to a higher total yield—which is maximum for the SD, followed by the PD and the SH in third place—and, generally, to a higher biodiversity than pure competition. LVNGM allows gaining insights into niche construction/engineering. Examples in which LVNGM can be applied range from several single-trophic natural communities, in which positive interactions have been detected, to overyielding of artificial polycultures and plant-pollinator networks.

Interaction of wind and cold‐season hydrologic processes on erosion from complex topography following wildfire in sagebrush steppe

AbstractWildfire is a natural component of sagebrush (Artemisia spp.) steppe rangelands that induces temporal shifts in plant community physiognomy, ground surface conditions, and erosion rates. Fire alteration of the vegetation structure and ground cover in these ecosystems commonly amplifies soil losses by wind‐ and water‐driven erosion. Much of the fire‐related erosion research for sagebrush steppe has focused on either erosion by wind over gentle terrain or water‐driven erosion under high‐intensity rainfall on complex topography. However, many sagebrush rangelands are geographically positioned in snow‐dominated uplands with complex terrain in which runoff and sediment delivery occur primarily in winter months associated with cold‐season hydrology. Current understanding is limited regarding fire effects on the interaction of wind‐ and cold‐season hydrologic‐driven erosion processes for these ecosystems. In this study, we evaluated fire impacts on vegetation, ground cover, soils, and erosion across spatial scales at a snow‐dominated mountainous sagebrush site over a 2‐year period post‐fire. Vegetation, ground cover, and soil conditions were assessed at various plot scales (8 m2 to 3.42 ha) through standard field measures. Erosion was quantified through a network of silt fences (n = 24) spanning hillslope and side channel or swale areas, ranging from 0.003 to 3.42 ha in size. Sediment delivery at the watershed scale (129 ha) was assessed by suspended sediment samples of streamflow through a drop‐box v‐notch weir. Wildfire consumed nearly all above‐ground live vegetation at the site and resulted in more than 60% bare ground (bare soil, ash, and rock) in the immediate post‐fire period. Widespread wind‐driven sediment loading of swales was observed over the first month post‐fire and extensive snow drifts were formed in these swales each winter season during the study. In the first year, sediment yields from north‐ and south‐facing aspects averaged 0.99–8.62 t ha−1 at the short‐hillslope scale (~0.004 ha), 0.02–1.65 t ha−1 at the long‐hillslope scale (0.02–0.46 ha), and 0.24–0.71 t ha−1 at the swale scale (0.65–3.42 ha), and watershed scale sediment yield was 2.47 t ha−1. By the second year post fire, foliar cover exceeded 120% across the site, but bare ground remained more than 60%. Sediment yield in the second year was greatly reduced across short‐ to long‐hillslope scales (0.02–0.04 t ha−1), but was similar to first‐year measures for swale plots (0.24–0.61 t ha−1) and at the watershed scale (3.05 t ha−1). Nearly all the sediment collected across all spatial scales was delivered during runoff events associated with cold‐season hydrologic processes, including rain‐on‐snow, rain‐on‐frozen soils, and snowmelt runoff. Approximately 85–99% of annual sediment collected across all silt fence plots each year was from swales. The high levels of sediment delivered across hillslope to watershed scales in this study are attributed to observed preferential loading of fine sediments into swale channels by aeolian processes in the immediate post‐fire period and subsequent flushing of these sediments by runoff from cold‐season hydrologic processes. Our results suggest that the interaction of aeolian and cold‐season hydrologic‐driven erosion processes is an important component for consideration in post‐fire erosion assessment and prediction and can have profound implications for soil loss from these ecosystems. © 2019 John Wiley & Sons, Ltd.

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.