Presence Of Snow Research Articles

Local climate determines vulnerability to camouflage mismatch in snowshoe hares

AbstractAimPhenological mismatches, when life‐events become mistimed with optimal environmental conditions, have become increasingly common under climate change. Population‐level susceptibility to mismatches depends on how phenology and phenotypic plasticity vary across a species’ distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal.LocationNorth America.Time period2010–2017.Major taxa studiedSnowshoe hare (Lepus americanus).MethodsWe used > 5,500 by‐catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high‐resolution climate data. We estimated occurrence of camouflage mismatch between hares’ coat colour and the presence and absence of snow over 7 years of monitoring.ResultsSpatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low‐snow years in regions characterized by shallow, short‐lasting snowpack.Main conclusionsLong‐term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species’ range. Our results underscore the population‐specific susceptibility to climate change‐induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change.

Quantifying Dissolved Organic Carbon Dynamics Using a Three‐Dimensional Terrestrial Ecosystem Model at High Spatial‐Temporal Resolutions

AbstractArctic terrestrial ecosystems are very sensitive to the global climate change due to the large storage of soil organic carbon and the presence of snow, glacier, and permafrost, which respond directly to near surface air temperature that has warmed in the Arctic by almost twice as much as the global average. These ecosystems play a significant role in affecting regional and global carbon cycling, which have been traditionally quantified using biogeochemical models that have not explicitly considered the loss of carbon due to lateral flow of water from land to aquatic ecosystems. Building upon an extant spatially distributed hydrological model and a process‐based biogeochemical model, we have developed a three‐dimensional terrestrial ecosystem model to elucidate how lateral water flow has impacted the regional dissolved organic carbon (DOC) dynamics in the Tanana Flats Basin in central Alaska. The model explicitly simulates the production, consumption, and transport of DOC. Both in situ observational data and remote sensing‐based products were used to calibrate and validate the model. Our simulations show that (1) plant litter DOC leaching exerts significant controls on soil DOC concentration during precipitation and snowmelt events, (2) lateral transport plays an important role in affecting regional DOC dynamics, and (3) DOC export to the Tanana River is approximately 9.6 × 106 kg C year−1. This study provides a modeling framework to adequately quantify the Arctic land ecosystem carbon budget by considering the lateral transport of carbon affected by permafrost degradation. The quantification of the lateral carbon fluxes will also improve future carbon cycle modeling for Arctic aquatic ecosystems.

Modelling ground thermal regime in bordering (dis)continuous permafrost environments

Permafrost controls geomorphological dynamics in maritime Antarctic ecosystems. Here, we analyze and model ground thermal regime in bordering conditions between continuous and discontinuous permafrost to better understand its relationship with the timing of glacial retreat. In February 2017, a transect including 10 sites for monitoring ground temperatures was installed in the eastern fringe of Byers Peninsula (Livingston Island, northern Antarctic Peninsula), together with one station recording air temperatures and snow thickness. The sites were selected following the Mid-Late Holocene deglaciation of the area at a distance ranging from 0.30 to 3.15 km from the current Rotch Dome glacier front. The transect provided data on the effects of topography, snow cover and the timing of ice-free exposure, on the ground thermal regime. From February 2017 to February 2019, the mean annual air temperature was −2.0 °C, which was >0.5 °C higher than 1986–2015 average in the Western Antarctic Peninsula region. Mean annual ground temperature at 10 cm depth varied between 0.3 and −1.1 °C, similar to the modelled Temperatures on the Top of the Permafrost (TTOP) that ranged from 0.06 ± 0.08 °C to −1.33 ± 0.07 °C. The positive average temperatures at the warmest site were related to the long-lasting presence of snow which favoured warmer ground temperatures and may trigger permafrost degradation. The role of other factors (topography, and timing of the deglaciation) explained intersite differences, but the overall effect was not as strong as snow cover.

The effects of experimental oil-contaminated marine snow on meiofauna in a microcosm.

During an oil spill, a marine oil snow sedimentation and flocculent accumulation (MOSSFA) event can transport oil residue to the seafloor. Microcosm experiments were used to test the effects of oil residues on meiofaunal abundance and the nematode:copepod ratio under different oil concentrations and in the presence and absence of marine snow. Total meiofaunal abundance was 1.7 times higher in the presence of snow regardless of oil concentration. The nematode:copepod ratio was 13.9 times lower in the snow treatment regardless of the oil concentration. Copepod abundance was 24.3 times higher in marine snow treatments and 4.3 times higher at the highest oil concentration. Nematode abundance was 1.7 times lower at the highest oil concentration. The result of the experiment was an enrichment effect. The lack of a toxic response in the experiments may be attributable to relatively low oil concentrations, weathering processes, and the absence of chemically dispersed oil.

IN-YOLO: Real-Time Detection of Outdoor High Voltage Insulators Using UAV Imaging

The high voltage insulator requires continuous monitoring and inspection to prevent failures and emergencies. Manual inspections are costly as it requires covering a large geographical area where insulators are often subjected to harsh weather conditions. Automatic detection of insulators from aerial images is the first step towards performing real-time classification of insulator conditions using Unmanned Aerial Vehicle (UAV). In this paper, we provide a cost-effective solution for detecting insulators under the conditions of an uncluttered background, varied object resolution and illumination conditions using You Only Look Once (YOLO) deep learning neural network model from aerial images. We apply data augmentation to avoid overfitting with a training set size of 56000 image samples. It is demonstrated experimentally that this method can accurately locate insulator on UAV based real-time image data. The detected insulator images are then successfully subjected to insulator surface condition assessment for the presence of ice, snow and water using different classifiers.

Near surface air temperature lapse rates over complex terrain: a WRF based analysis of controlling factors and processes for the central Himalayas

Various environmental processes are strongly controlled by spatio-temporal variations of surface air temperature (hereafter temperature) in complex terrain. However, the usually scarce network of observations in high mountain regions does not allow for an investigation of the relevant micro-meteorological processes that result in complex temperature fields. Climate impact studies often utilize a constant lapse rate of temperature (LRT hereafter) in order to generate spatially distributed temperature data, although it is well acknowledged that LRTs feature a pronounced variability at spatial, seasonal, and diurnal scales. In this study, the Weather Research and Forecasting (WRF) model is used to understand the factors and processes influencing temperature and LRT in the Khumbu and Rolwaling regions of the central Himalayas. A high resolution simulation is performed for one complete year (June 2014–May 2015) in order to capture the entire seasonal cycle. To test the model response to land cover and terrain characteristics, additional simulations with adjusted surface conditions are conducted. Our results demonstrate the capability of WRF to reproduce the processes controlling LRT, although an LRT bias is detected during non-monsoon seasons. The simulated temperature fields feature two LRT minima (i.e. low temperature decrease with elevation) during Nov–Dec and monsoon season, and two LRT maxima (strong temperature decrease with elevation) during the early post-monsoon and pre-monsoon seasons. A steeper LRT (i.e. a rapid decrease of temperature with elevation) is found at high elevations (> 4500 m) while shallower LRT values (i.e. a slower decrease or even increase of temperature with elevation) are apparent at lower elevations. During the pre-monsoon season, high net insolation rates and a reduced latent heat loss from snow free surfaces cause strong sensible heating at low elevations, while the presence of snow at high elevations leads to reduced sensible heating. This strong contrast results in steeper LRT values. Early post-monsoon shows similar characteristics but with a reduced magnitude. The shallow LRT during monsoon season is shown to be caused by the large-scale moisture supply and the associated latent heat release at the Himalayan slopes. This effect is further intensified due to strong up-valley winds which contribute to a well-mixed troposphere. Temperature inversions associated with cold air pooling cause shallow LRT values in lower river valleys during Nov–Dec. The results suggest that the identified processes should be considered for downscaling applications, particularly if distributed temperature fields are required for climate impact investigations.

Editorial for Special Issue: “Remote Sensing of Environmental Changes in Cold Regions”

Cold regions, characterized by the presence of permafrost and extensive snow and ice cover, are significantly affected by changing climate [...]

Light Permeates Seasonally Through Arctic Sea Ice

The transmission of sunlight through Arctic sea ice depends on the presence of ice, snow, and melt ponds, data collected over 6 years reveal.

Impact of Snow Initialization in Subseasonal‐to‐Seasonal Winter Forecasts With the Norwegian Climate Prediction Model

AbstractSnow initialization has been previously investigated as a potential source of predictability at the subseasonal‐to‐seasonal (S2S) timescale in winter and spring, through its local radiative, thermodynamical, and hydrological feedbacks. However, previous studies were conducted with low‐top models over short periods only. Furthermore, the potential role of the land surface‐stratosphere connection upon the S2S predictability had remained unclear. To this end, we have carried out twin 30‐member ensembles of 2‐month (November and December) retrospective forecasts over the period 1985–2016, with either realistic or degraded snow initialization. A high‐top version of the Norwegian Climate Prediction Model is used, based on the Whole Atmosphere Community Climate Model, to insure improved coupling with the stratosphere. In a composite difference of high versus low initial Eurasian snow, the surface temperature is strongly impacted by the presence of snow, and wave activity fluxes into the stratosphere are enhanced at a 1‐month lag, leading to a weakened polar vortex. Focusing further on 7 years characterized by a strongly negative phase of the Arctic Oscillation, we find a weak snow feedback contributing to the maintenance of the negative Arctic Oscillation. By comparing the twin forecasts, we extracted the predictive skill increment due to realistic snow initialization. The prediction of snow itself is greatly improved, and there is increased skill in surface temperature over snow‐covered land in the first 10 days, and localized skill increments in the mid‐latitude transition regions on the southern flanks of the snow‐covered land areas, at lead times longer than 30 days.

Detecting intercepted snow on mountain needleleaf forest canopies using satellite remote sensing

Snow interception in cold regions needleleaf forest canopies is a crucial process that controls local snow accumulation and redistribution over >20% of the Earth's land surface. Various ground-based methods exist to measure intercepted snow load, however all are based on single-tree measurements and are difficult to implement. No research has focussed on detecting large areal intercepted snow loads and no studies have assessed the use of satellite observations. In this study, four remote sensing indices (NDSI, NDVI, albedo, and land surface temperature (LST)) were retrieved from Landsat images to study their sensitivity to canopy intercepted snow and the possibility of using them to detect the presence of intercepted snow. The results indicate that presence of intercepted snow on canopy increased NDSI and albedo, but decreased NDVI. Intercepted snow presence also decreased the areal variability of NDSI and NDVI while increasing that of albedo. For these three indices, the differences between snow-free and snowcovered canopies were correlated to topography and forest canopy cover. Of these indices, NDSI changed the greatest. Intercepted snow noticeably decreased the LST difference between forest and open areas in springtime while the influence in wintertime was relatively smaller. An intercepted snow detection approach that uses both NDSI and NDVI to classify pixels into either snowcovered canopy or other (snow-free canopy and non-forest areas) is proposed here. A case study applying this approach compared remote sensing detection to simulations by the snow interception and sublimation model implemented in the Cold Regions Hydrological Modelling platform (CRHM). This used local meteorological observations from the pine, spruce and fir forest covered Marmot Creek Research Basin in the Canadian Rockies. The remote sensing detection of intercepted snow agreed well with CRHM simulations for continuous forests (83%) and less well for sparse forests (72%) and clearings with small trees (70%). Therefore, the approach is suitable for intercepted snow detection over continuous evergreen canopies. This technique provides a new capability for large-scale snow interception model validation and data assimilation to cold regions hydrological forecasting models.

Geomorphological Evidence of Localized Stagnant Ice Deposits in Terra Cimmeria, Mars

AbstractThe presence of snow and ice at midlatitudes of Mars cannot be explained by current climatic conditions, as surface ice is unstable. However, a large variety of debris‐covered glaciers have been observed at both midlatitudes. Here, we report the presence of local, small‐scale, and debris‐covered stagnant ice deposits on the floor of a valley system in Terra Cimmeria. These deposits, termed valley fill deposits (VFD), have a distribution that is restricted to the host valley floor and to the extent of the ejecta blanket associated with Tarq impact crater. The VFD are characterized by convex‐upward morphology, various crevasses, sublimation pits, an average area of a few square kilometers, and occasional ejecta streaks on their surface. Our model age estimation points to two possible time frames for the Tarq impact event; thus, we suggest two formation scenarios for VFD: (I) distribution of ice due to impact into shallow ice during the Middle Amazonian and (II) post‐impact deposition of VFD due to precipitation. In both scenarios, ice preservation is most likely due to a lag of dust and debris deposited in the valley's topographic lows. Scenario I is more consistent with our geomorphological observation of the VFD being overlain by ejecta streaks. Our results highlight the importance of local geological events and conditions in the distribution and preservation of buried ice deposits on Mars and suggest that more small‐scale and debris‐covered ice deposits may exist in the midlatitudes than previously thought. These deposits are of high importance for future human exploration missions to Mars.

Changing snow depth in the Great Lakes basin (USA): Implications and trends

Abstract In the Great Lakes basin of North America, snow plays a critical role in the regional hydroclimate, where snow ablation events can serve both as a resource and a hazard. The frequency and magnitude of an ablation event is governed by the availability of meteorological conditions to ablate snow, and the physical presence of snow to be ablated. While the meteorological conditions leading to ablation have been well documented, examining changes in atmospheric conditions alone have been unable to completely explain observed ablation trends. As such, this study applies a gridded snow depth dataset to evaluate snow depth variability, while speaking to the implications of such variability on ablation frequency and water resources. Snow cover is present in the basin from November – April, with the more northerly regions (Lake Superior and Lake Huron basins) exhibiting a deeper and more seasonally-persistent snowpack. Seasonal basin-wide snow depth decreased by approximately 25% from 1960 to 2009, with some of the most significant decreases occurring north of Lake Superior. Surface air temperatures are negatively associated snow depth, and warming temperatures are likely contributing to snow depth declines. These regional decreases in snow depth spatially corroborate previously observed decreases in the frequency of ablation events in the basin, and highlight the importance of examining both snow cover and meteorological conditions when seeking to explain snow ablation variability. The results from this study can be applied to inform water resource management decisions in the region.

Performance of a snow blower prototype mounted on different vehicles type

All transportation sectors, in many countries of the world have shown problems related to the presence of snow on roads. The purpose of this work was to evaluate the performances of a snow blower prototype that can be attached in front of different commercial vehicle types (quad-bike, car, and small tractor) specifically developed for urban areas and private use. The prototype was tested using three different pavement types (bare soil, concrete, and asphalt) and with different snow layer thickness (50, 100, 150, 200, 250, and 300 mm). The highest forward speed (2.51 km h–1) was obtained using the car on asphalt pavement working with a snow layer thickness of 50 mm. In contrast, the lowest forward speed (0.28 km h–1) was observed when the prototype was fixed to the quad-bike and it worked on concrete base with a snow depth of 300 mm. The forward speed, and consequently also the productivity, varied only as a function of snow thickness. The prototype has demonstrated functional quality in all testing conditions leaving only a snow residue after its passage of about 0.18 dm3 on 100 meter of road. The hourly fuel consumption varied between 6.56 and 6.68 litres highlighting an average specific fuel consumption of 319.5 g kWh–1. The snow blower prototype, as it demonstrated good performance in all tested working conditions, seems to be a valid solution in snow-removal especially in private areas where the equipment versatility plays a fundamental rule.

Surface radiation balance and weather conditions on a non-glaciated coastal area in the Antarctic region

Meteorological measurements were performed on the non-glaciated coastal area of the Ferraz Station, the Brazilian Antarctic Station, at King George Island. Near the Station there are different topographic attributes, such as sea, glacier and hill, in addition to the intermittent presence of snow. The local atmospheric characteristics depend on wind direction, which is related in small scale to the local features and in large scale to the synoptic systems acting over the region. Westerly winds were the most frequent, with relatively lower speed and higher temperature and humidity values compared to the also frequent easterly winds, related to the coolest and driest winds. The average monthly barometric pressure and wind speed were higher during winter, associated with the presence of high-pressure systems. The radiation balance, measured for the first time in Ferraz Station, evidenced the presence of clouds throughout the year, especially during summer months, associated with the frequent synoptic systems of the region. During nighttimes (daytimes) and in winter (summer) months, the surface lost (gained) energy mainly by net longwave (shortwave) radiation. Reflected shortwave radiation was higher during spring months because of the its relatively higher albedo values combined with the already increased magnitude of the incident shortwave radiation.

Glacier facies characterization using optical satellite data: Impacts of radiometric resolution, seasonality, and surface morphology

The spectral characterization of geographic landscapes is vital for their accurate mapping using remote sensing data. This can be done through spectral profiling, as demonstrated here, to characterize the surface facies of the Gangotri and neighbouring glaciers, central Himalaya. The satellite-derived reflectance curves were compared with the in-situ and published (validation) data. The study attempts to understand the influence of certain parameters such as the satellite sensor’s radiometric resolution, timing of data acquisition (seasonality), and surface morphology on glacier/snow–ice facies identification. Results show that the first two parameters complement each other in identifying the snow–ice facies accurately. High radiometric resolution (HRR) data concurred closely with the validation dataset and had higher mean entropy values over the glaciated areas than low radiometric resolution (LRR) ablation data. Presence of seasonal snow and degree of surface melting show considerable influence on satellite-derived reflectances of glacier facies. Our findings assert the usage of HRR ablation data in appraising the interannual and seasonal variability of glacier facies. While HRR post-ablation data overestimates the reflectance of snow–ice facies, LRR post-ablation data have limitations in their discrimination. Certain morphology and resultant features, such as crevasses and shadows, induce underestimation of the satellite-derived reflectances, creating confusion among the snow and ice facies. This spectral confusion can, however, be resolved by the use of ancillary data. Elevation, temperature, and band ratios/spectral indices are helpful in segregating snow–ice facies, while slope, band ratios, temperature, and texture measures effectively discriminate the other facies.

Weather and Temporal Factors Associated with Use of Emergency Medical Services

Background: Fluctuations in emergency medical services (EMS) responses can have a substantial impact on the ability of agencies to meet resource needs within an EMS system. We aimed to identify weather characteristics as potentially predictable factors associated with EMS responses. Methods: We reviewed hourly counts of scene responses documented by 24 EMS agencies in Western Pennsylvania from January 1, 2014 to December 31, 2017 and compared rates of responses to weather characteristics. Responses to counties nonadjacent to the studied weather reporting station and interfacility/scheduled transports were excluded. We identified the mean temperature, meters visibility, dew point, wind speed, total millimeters of precipitation, and presence of rain or snow in 6-hour windows prior to dispatch, in addition to temporal factors of time of day and weekend vs. weekday. Analysis was performed using multivariable linear regression of a negative binomial distribution, reporting incidence rate ratios (IRR) with 95% confidence intervals (CI). Secondary analyses were performed for transports to the hospital and cases involving transports for traumatic complaints and pediatric patients (age <18 years). Results: We included 529,058 responses (54.8% female, mean age 57.2 ± SD 24.7 years). In our multivariable model, responses were associated with (IRR, 95% CI) rain (1.10, 1.08–1.11) snow (1.07, 1.05–1.09), and both rain and snow (1.15, 1.11–1.19). A lower incidence of responses occurred on weekends (0.84, 0.83–0.85) and at night (0.62, 0.61–0.62). Increasing temperature in 5 °C increments was associated with an increase in responses across seasons with an effect that varied between 1.16 (1.15–1.17) in winter to 1.31 (1.28–1.33) in summer. Windy weather was associated with increased responses from light breeze (1.10, 1.09–1.11) to fresh breeze or greater (1.23, 1.16–1.30). Transports occurred in a similar pattern to responses. Trauma transports (n = 64,235) occurred more during weekends (1.04, 1.02–1.06). Pediatric transports (n = 21,880) were not significantly associated with precipitation or season. Conclusion: EMS responses increased with rising temperature and following rain and snow. These findings may assist in planning by EMS agencies and emergency departments to identify periods of greatest resource utilization.

Ecotoxicological benthic impacts of experimental oil-contaminated marine snow deposition

Marine Oil Snow Sedimentation and Flocculent Accumulation (MOSSFA) can pose serious threats to the marine benthic ecosystem as it results in a deposition of oil contaminated marine snow on the sediment surface. In a microcosm experiment we investigated the effects of oil in combination with artificial marine snow or kaolin clay on two benthic invertebrate species and benthic meiofauna. The amphipod showed a dose-dependent decrease in survival for both oil-contaminated clay and oil-contaminated marine snow. The gastropod was only affected by the highest concentration of oil-contaminated marine snow and had internal concentrations of PAHs with a similar distribution as oil-contaminated marine snow. Benthic copepods showed higher survival in presence of marine snow. This study revealed that marine snow on the sediment after oil spills affects organisms in a trait-dependent way and that it can be a vector for introducing oil into the food web.

Estimating Contributions of Sea Ice and Land Snow to Climate Feedback

AbstractIn this study, we use the National Center for Atmospheric Research Community Earth System Model to investigate the contribution of sea ice and land snow to the climate sensitivity in response to increased atmospheric carbon dioxide content. We focus on the overall effect arising from the presence or absence of sea ice and/or land snow. We analyze our results in terms of the radiative forcing and climate feedback parameter. We find that the presence of sea ice and land snow decreases the climate feedback parameter (and thus increases climate sensitivity). Adjusted radiative forcing from added carbon dioxide is comparatively less sensitive to the presence of sea ice or land snow. The effect of sea ice on the climate feedback parameter decreases as sea ice cover diminishes at higher CO2 concentration. However, the influence of both sea ice and land snow on the climate feedback parameter remains substantial under the CO2 concentration range considered here (to eight times preindustrial CO2 content). Approximately, one quarter of the effect of sea ice and land snow on the climate feedback parameter is a consequence of the effect of these components on longwave feedback that is mainly associated with cloud change. Polar warming in response to added CO2 is approximately doubled by the presence of sea ice and land snow. Relative to the case in which sea ice and land snow are absent in the model, in response to increased CO2 concentrations, the presence of sea ice and land snow results in an increase in global mean warming by over 40%.

Risk of pedestrian falls in Oslo, Norway: Relation to age, gender and walking surface condition

The risk of pedestrian falls in Oslo, Norway, is analysed. Injury data were collected during 2016 by the municipal emergency medical clinic. A total of 6309 injured pedestrians were recorded. 6109 were injured in falls in which no other road user was involved. The risk of falling per million kilometres walked varies by age, gender and surface condition. Women have a higher risk than men. Risk has a J-shaped variation with age for both genders, being highest among the oldest. The presence of snow or ice on the walking surface is associated with more than a doubling of risk. There are few comparable previous studies of the risk of pedestrian falls. However, to the extent comparisons can be made, pedestrian risk of injury by falling is higher in Oslo than in other cities or countries. The preventability of falls is discussed.

Study of the influence of surface reinforcement on the bearing capacity of ice

Practical experience shows that the physical and mechanical properties of the ice cover are unreliable and can strongly depend on various external factors (the presence of snow and wind at the time of freezing, the ambient temperature), if it is reinforced by traditional methods. In this connection, the problem of increasing the bearing capacity of ice by alternative methods, e.g. by introducing reinforcing elements into the ice, is an urgent problem today. The aim of this work is to determine the effect of various reinforcing materials on the carrying capacity of the ice cover. First, a comparison was made between the results of experimental and numerical studies obtained for the maximum deflections and the carrying capacity of ice samples strengthened with steel reinforcement according to the proposed scheme. Secondly, numerical investigation of the strength of ice upon reinforcement with various composite materials was performed. Experiments on strengthening ice samples with A400 steel reinforcement were carried out on a setup specially designed for simulating pure bending conditions. The destruction of the ice cover occurs under the action of pure bending when the vehicle is moving along it. In numerical experiments, the samples were reinforced with surface reinforcing frames with different physical and mechanical properties. Numerical calculations of the stress-strain characteristics of the ice cover were performed in terms of the physically nonlinear deformation model using the FE software package. The paper gives a qualitative and quantitative assessment of the effectiveness of the use of various composite materials as reinforcing elements. It is shown that the application of reinforcing materials to strengthen the ice cover significantly increases its bearing capacity.