How autumn Eurasian snow anomalies affect east asian winter monsoon: a numerical study

Science.gov (United States)

Luo, Xiao; Wang, Bin

2018-03-01

Previous studies have found that snow Eurasian anomalies in autumn can affect East Asian winter monsoon (EAWM), but the mechanisms remain controversial and not well understood. The possible mechanisms by which Eurasian autumn snow anomalies affect EAWM are investigated by numerical experiments with a coupled general circulation model and its atmospheric general circulation model component. The leading empirical orthogonal function mode of the October-November mean Eurasian snow cover is characterized by a uniform anomaly over a broad region of central Eurasia (40°N-65°N, 60°E-140°E). However, the results from a 150-ensemble mean simulation with snow depth anomaly specified in October and November reveal that the Mongolian Plateau and Vicinity (MPV, 40°-55°N, 80°-120°E) is the key region for autumn snow anomalies to affect EAWM. The excessive snow forcing can significantly enhance EAWM and the snowfall over the northwestern China and along the EAWM front zone stretching from the southeast China to Japan. The physical process involves a snow-monsoon feedback mechanism. The excessive autumn snow anomalies over the MPV region can persist into the following winter, and significantly enhance winter snow anomalies, which increase surface albedo, reduce incoming solar radiation and cool the boundary layer air, leading to an enhanced Mongolian High and a deepened East Asian trough. The latter, in turn, strengthen surface northwesterly winds, cooling East Asia and increasing snow accumulation over the MPV region and the southeastern China. The increased snow covers feedback to EAWM system through changing albedo, extending its influence southeastward. It is also found that the atmosphere-ocean coupling process can amplify the delayed influence of Eurasian snow mass anomaly on EAWM. The autumn surface albedo anomalies, however, do not have a lasting "memory" effect. Only if the albedo anomalies are artificially extended into December and January, will the EAWM be

Relationship of deer and moose populations to previous winters' snow

Science.gov (United States)

Mech, L.D.; McRoberts, R.E.; Peterson, R.O.; Page, R.E.

1987-01-01

(1) Linear regression was used to relate snow accumulation during single and consecutive winters with white-tailed deer (Odocoileus virginianus) fawn:doe ratios, mosse (Alces alces) twinning rates and calf:cow ratios, and annual changes in deer and moose populations. Significant relationships were found between snow accumulation during individual winters and these dependent variables during the following year. However, the strongest relationships were between the dependent variables and the sums of the snow accumulations over the previous three winters. The percentage of the variability explained was 36 to 51. (2) Significant relationships were also found between winter vulnerability of moose calves and the sum of the snow accumulations in the current, and up to seven previous, winters, with about 49% of the variability explained. (3) No relationship was found between wolf numbers and the above dependent variables. (4) These relationships imply that winter influences on maternal nutrition can accumulate for several years and that this cumulative effect strongly determines fecundity and/or calf and fawn survivability. Although wolf (Canis lupus L.) predation is the main direct mortality agent on fawns and calves, wolf density itself appears to be secondary to winter weather in influencing the deer and moose populations.

Genetic differentiation between sympatric and allopatric wintering populations of Snow Geese

Science.gov (United States)

Humphries, E.M.; Peters, J.L.; Jonsson, J.E.; Stone, R.; Afton, A.D.; Omland, K.E.

2009-01-01

Blackwater National Wildlife Refuge on the Delmarva Peninsula, Maryland, USA has been the wintering area of a small population of Lesser Snow Geese (Chen caerulescens caerulescens; LSGO) since the 1930s. Snow Geese primarily pair in wintering areas and gene flow could be restricted between this and other LSGO wintering populations. Winter pair formation also could facilitate interbreeding with sympatric but morphologically differentiated Greater Snow Geese (C. c. atlantica; GSGO).We sequenced 658 bp of the mitochondrial DNA control region for 68 Snow Geese from East Coast and Louisiana wintering populations to examine the level of genetic differentiation among populations and subspecies. We found no evidence for genetic differentiation between LSGO populations but, consistent with morphological differences, LSGO and GSGO were significantly differentiated. We also found a lack of genetic differentiation between different LSGO morphotypes from Louisiana. We examined available banding data and found the breeding range of Delmarva LSGO overlaps extensively with LSGO that winter in Louisiana, and documented movements between wintering populations. Our results suggest the Delmarva population of LSGO is not a unique population unit apart from Mid-Continent Snow Geese. ?? 2009 by the Wilson Ornithological Society.

Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014

Science.gov (United States)

Alonso-González, Esteban; López-Moreno, J. Ignacio; Gascoin, Simon; García-Valdecasas Ojeda, Matilde; Sanmiguel-Vallelado, Alba; Navarro-Serrano, Francisco; Revuelto, Jesús; Ceballos, Antonio; Jesús Esteban-Parra, María; Essery, Richard

2018-02-01

We present snow observations and a validated daily gridded snowpack dataset that was simulated from downscaled reanalysis of data for the Iberian Peninsula. The Iberian Peninsula has long-lasting seasonal snowpacks in its different mountain ranges, and winter snowfall occurs in most of its area. However, there are only limited direct observations of snow depth (SD) and snow water equivalent (SWE), making it difficult to analyze snow dynamics and the spatiotemporal patterns of snowfall. We used meteorological data from downscaled reanalyses as input of a physically based snow energy balance model to simulate SWE and SD over the Iberian Peninsula from 1980 to 2014. More specifically, the ERA-Interim reanalysis was downscaled to 10 km × 10 km resolution using the Weather Research and Forecasting (WRF) model. The WRF outputs were used directly, or as input to other submodels, to obtain data needed to drive the Factorial Snow Model (FSM). We used lapse rate coefficients and hygrobarometric adjustments to simulate snow series at 100 m elevations bands for each 10 km × 10 km grid cell in the Iberian Peninsula. The snow series were validated using data from MODIS satellite sensor and ground observations. The overall simulated snow series accurately reproduced the interannual variability of snowpack and the spatial variability of snow accumulation and melting, even in very complex topographic terrains. Thus, the presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism, and risk management. The data presented here are freely available for download from Zenodo (https://doi.org/10.5281/zenodo.854618). This paper fully describes the work flow, data validation, uncertainty assessment, and possible applications and limitations of the database.

Improving snow density estimation for mapping SWE with Lidar snow depth: assessment of uncertainty in modeled density and field sampling strategies in NASA SnowEx

Science.gov (United States)

Raleigh, M. S.; Smyth, E.; Small, E. E.

2017-12-01

The spatial distribution of snow water equivalent (SWE) is not sufficiently monitored with either remotely sensed or ground-based observations for water resources management. Recent applications of airborne Lidar have yielded basin-wide mapping of SWE when combined with a snow density model. However, in the absence of snow density observations, the uncertainty in these SWE maps is dominated by uncertainty in modeled snow density rather than in Lidar measurement of snow depth. Available observations tend to have a bias in physiographic regime (e.g., flat open areas) and are often insufficient in number to support testing of models across a range of conditions. Thus, there is a need for targeted sampling strategies and controlled model experiments to understand where and why different snow density models diverge. This will enable identification of robust model structures that represent dominant processes controlling snow densification, in support of basin-scale estimation of SWE with remotely-sensed snow depth datasets. The NASA SnowEx mission is a unique opportunity to evaluate sampling strategies of snow density and to quantify and reduce uncertainty in modeled snow density. In this presentation, we present initial field data analyses and modeling results over the Colorado SnowEx domain in the 2016-2017 winter campaign. We detail a framework for spatially mapping the uncertainty in snowpack density, as represented across multiple models. Leveraging the modular SUMMA model, we construct a series of physically-based models to assess systematically the importance of specific process representations to snow density estimates. We will show how models and snow pit observations characterize snow density variations with forest cover in the SnowEx domains. Finally, we will use the spatial maps of density uncertainty to evaluate the selected locations of snow pits, thereby assessing the adequacy of the sampling strategy for targeting uncertainty in modeled snow density.

Effects of dirty snow in nuclear winter simulations

International Nuclear Information System (INIS)

Vogelmann, A.M.; Robock, A.; Ellingson, R.G.

1988-01-01

A large-scale nuclear war would inject smoke into the atmosphere from burning forests, cities, and industries in targeted areas. This smoke could fall out onto snow and ice and would lower cryospheric albedos by as much as 50%. A global energy balance climate model is used to investigate the maximum effect these ''dirty snow'' albedos have on the surface temperature in nuclear winter simulations which span several years. These effects are investigated for different nuclear winter scenarios, snow precipitation rates, latitudinal distributions of smoke, and seasonal timings. We find that dirty snow, in general, would have a small temperature effect at mid- and low latitudes but could have a large temperature effect at polar latitudes, particularly if the soot is able to reappear significantly in later summers. Factors which limit the climatic importance of the dirty snow are (1) the dirty snow albedo is lowest when the atmosphere still contains a large amount of light-absorbing smoke; (2) even with dirty snow, sea ice areas can still increase, which helps maintain colder temperatures through the sea ice thermal inertial feedback; (3) the snow and ice areas affected by the dirty snow albedos are largest when there is little seasonal solar insolation; and (4) the area affected by the dirty snow is relatively small under all circumstances. copyright American Geophysical Union 1988

Storing snow for the next winter: Two case studies on the application of snow farming.

Science.gov (United States)

Grünewald, Thomas; Wolfsperger, Fabian

2016-04-01

Snow farming is the conservation of snow during the warm half-year. This means that large piles of snow are formed in spring in order to be conserved over the summer season. Well-insulating materials such as chipped wood are added as surface cover to reduce melting. The aim of snow farming is to provide a "snow guaranty" for autumn or early winter - this means that a specific amount of snow will definitively be available, independent of the weather conditions. The conserved snow can then be used as basis for the preparation of winter sports grounds such as cross-country tracks or ski runs. This helps in the organization of early winter season sport events such as World Cup races or to provide appropriate training conditions for athletes. We present a study on two snow farming projects, one in Davos (Switzerland) and one in the Martell valley of South Tyrol. At both places snow farming has been used for several years. For the summer season 2015, we monitored both snow piles in order to assess the amount of snow conserved. High resolution terrestrial laser scanning was performed to measure snow volumes of the piles at the beginning and at the end of the summer period. Results showed that only 20% to 30 % of the snow mass was lost due to ablation. This mass loss was surprisingly low considering the extremely warm and dry summer. In order to identify the most relevant drivers of snow melt we also present simulations with the sophisticated snow cover models SNOWPACK and Alpine3D. The simulations are driven by meteorological input data recorded in the vicinity of the piles and enable a detailed analysis of the relevant processes controlling the energy balance. The models can be applied to optimize settings for snow farming and to examine the suitability of new locations, configurations or cover material for future snow farming projects.

Why on the snow? Winter emergence strategies of snow-active Chironomidae (Diptera) in Poland.

Science.gov (United States)

Soszyńska-Maj, Agnieszka; Paasivirta, Lauri; Giłka, Wojciech

2016-10-01

A long-term study of adult non-biting midges (Chironomidae) active in winter on the snow in mountain areas and lowlands in Poland yielded 35 species. The lowland and mountain communities differed significantly in their specific composition. The mountain assemblage was found to be more diverse and abundant, with a substantial contribution from the subfamily Diamesinae, whereas Orthocladiinae predominated in the lowlands. Orthocladius wetterensis Brundin was the most characteristic and superdominant species in the winter-active chironomid communities in both areas. Only a few specimens and species of snow-active chironomids were recorded in late autumn and early winter. The abundance of chironomids peaked in late February in the mountain and lowland areas with an additional peak in the mountain areas in early April. However, this second peak of activity consisted mainly of Orthocladiinae, as Diamesinae emerged earliest in the season. Most snow-active species emerged in mid- and late winter, but their seasonal patterns differed between the 2 regions as a result of the different species composition and the duration of snow cover in these regions. Spearman's rank correlation coefficient tests yielded positive results between each season and the number of chironomid individuals recorded in the mountain area. A positive correlation between air temperature, rising to +3.5 °C, and the number of specimens recorded on the snow in the mountain community was statistically significant. The winter emergence and mate-searching strategies of chironomids are discussed in the light of global warming, and a brief compilation of most important published data on the phenomena studied is provided. © 2015 Institute of Zoology, Chinese Academy of Sciences.

Indicative properties on snow cover based on the results of experimental studies in the winter 2011/12 in the central part of the East European Plain

Directory of Open Access Journals (Sweden)

L. M. Kitaev

2013-01-01

Full Text Available Local and regional differences in the snow formation were studied in different landscapes of the central part of the East European Plain – within reserves in the Moscow and Tver’ regions (south-north direction; the study period is the winter 2011/12. The observed increase of snow storage in 1.3–1.5 times in the direction south-north is connected, apparently. The difference in the five-day appearance of snow cover maximum is related to differences in regional winter air temperature. Throughout the snow depth and snow storage in spruce are smaller than in deciduous forest – in the ratio of 0.81 in south area and 0.93 in north area; in spruce the large part of solid precipitation is intercepted by the crowns pine trees. Snow stratigraphy at south areas has four layers, six layers at the north area are more variable in snow density and snow storage. Perhaps, gravitational conversion is more noticeable due to larger snow depth. Snow density and snow storage at the open areas are more heterogeneous than in the forest. This is due to sharp fluctuations in air temperature, wind transport and compaction of snow, evaporation from the snow surface. The stratigraphy of snow also reflects the history of winter changes of air temperature and snow accumulation. Common feature for reserves at south and north is the availability of layers with maximum snow storage in the middle of the snow thickness, which were formed during the air temperature drops to the lowest seasonal values in period with increase of snow depth to maximum. Formation of depth hoar in snow thickness are touched everywhere the bottom and middle layers, respectively, it was formed both before and during the period with minimal air temperature. Thus, the results of experimental studies confirm the significance of the differences of individual components of the landscape setting. Analytical conclusions are largely qualitative in nature due to the lack to date of initial information, and

Establishing Winter Origins of Migrating Lesser Snow Geese Using Stable Isotopes

Directory of Open Access Journals (Sweden)

Viviane Hénaux

2012-06-01

Full Text Available Increases in Snow Goose (Chen caerulescens populations and large-scale habitat changes in North America have contributed to the concentration of migratory waterfowl on fewer wetlands, reducing resource availability, and enhancing risks of disease transmission. Predicting wintering locations of migratory individuals is critical to guide wildlife population management and habitat restoration. We used stable carbon (δ13C, nitrogen (δ15N, and hydrogen (δ2H isotope ratios in muscle tissue of wintering Snow Geese to discriminate four major wintering areas, the Playa Lake Region, Texas Gulf Coast, Louisiana Gulf Coast, and Arkansas, and infer the wintering locations of individuals collected later during the 2007 and 2008 spring migrations in the Rainwater Basin (RWB of Nebraska. We predicted the wintering ground derivation of migrating Snow Geese using a likelihood-based approach. Our three-isotope analysis provided an efficient discrimination of the four wintering areas. The assignment model predicted that 53% [95% CI: 37-69] of our sample of Snow Geese from the RWB in 2007 had most likely originated in Louisiana, 38% [23-54] had wintered on Texas Gulf Coast, and 9% [0-20] in Arkansas; the assessment suggested that 89% [73-100] of our 2008 sample had most likely come from Texas Gulf Coast, 9% [0-27] from Louisiana Gulf Coast, and 2% [0-9] from Arkansas. Further segregation of wintering grounds and additional sampling of spring migrating Snow Geese would refine overall assignment and help explain interannual variations in migratory connectivity. The ability to distinguish origins of northbound geese can support the development of spatially-adaptive management strategies for the midcontinent Snow Goose population. Establishing migratory connectivity using isotope assignment techniques can be extended to other waterfowl species to determine critical habitat, evaluate population energy requirements, and inform waterfowl conservation and management

CREST-SAFE: Snow LST validation, wetness profiler creation, and depth/SWE product development

Science.gov (United States)

Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Khanbilvardi, R.; Munoz Barreto, J.; Yu, Y.

2017-12-01

CREST-SAFE: Snow LST validation, wetness profiler creation, and depth/SWE product development The Field Snow Research Station (also referred to as Snow Analysis and Field Experiment, SAFE) is operated by the NOAA Center for Earth System Sciences and Remote Sensing Technologies (CREST) in the City University of New York (CUNY). The field station is located within the premises of the Caribou Municipal Airport (46°52'59'' N, 68°01'07'' W) and in close proximity to the National Weather Service (NWS) Regional Forecast Office. The station was established in 2010 to support studies in snow physics and snow remote sensing. The Visible Infrared Imager Radiometer Suite (VIIRS) Land Surface Temperature (LST) Environmental Data Record (EDR) and Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (provided by the Terra and Aqua Earth Observing System satellites) were validated using in situ LST (T-skin) and near-surface air temperature (T-air) observations recorded at CREST-SAFE for the winters of 2013 and 2014. Results indicate that T-air correlates better than T-skin with VIIRS LST data and that the accuracy of nighttime LST retrievals is considerably better than that of daytime. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and night-time values. Results indicate that, although all the data sets showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C). Additionally, we created a liquid water content (LWC)-profiling instrument using time-domain reflectometry (TDR) at CREST-SAFE and tested it during the snow melt period (February-April) immediately after installation in 2014. Results displayed high agreement when compared to LWC estimates obtained using empirical formulas developed in previous studies, and minor improvement over wet snow LWC estimates. Lastly, to improve on global snow cover mapping, a snow product capable of estimating snow depth and snow water

Responses of Plant Community Composition to Long-term Changes in Snow Depth at the Great Basin Desert - Sierra Nevada ecotone.

Science.gov (United States)

Loik, M. E.

2015-12-01

Snowfall is the dominant hydrologic input for many high-elevation ecosystems of the western United States. Many climate models envision changes in California's Sierra Nevada snow pack characteristics, which would severely impact the storage and release of water for one of the world's largest economies. Given the importance of snowfall for future carbon cycling in high elevation ecosystems, how will these changes affect seedling recruitment, plant mortality, and community composition? To address this question, experiments utilize snow fences to manipulate snow depth and melt timing at a desert-montane ecotone in eastern California, USA. Long-term April 1 snow pack depth averages 1344 mm (1928-2015) but is highly variable from year to year. Snow fences increased equilibrium drift snow depth by 100%. Long-term changes in snow depth and melt timing are associated with s shift from shurbs to graminoids where snow depth was increased for >50 years. Changes in snow have impacted growth for only three plant species. Moreover, annual growth ring increments of the conifers Pinus jeffreyi and Pi. contorta were not equally sensitive to snow depth. There were over 8000 seedlings of the shrubs Artemisia tridentata and Purshia tridentata found in 6300 m2 in summer 2009, following about 1400 mm of winter snow and spring rain. The frequency of seedlings of A. tridentata and P. tridentata were much lower on increased-depth plots compared to ambient-depth, and reduced-depth plots. Survival of the first year was lowest for A. tridentata. Survival of seedlings from the 2008 cohort was much higher for P. tridentata than A. tridentata during the 2011-2015 drought. Results indicate complex interactions between snow depth and plant community characteristics, and that responses of plants at this ecotone may not respond similarly to increases vs. decreases in snow depth. These changes portend altered carbon uptake in this region under future snowfall scenarios.

Deepened winter snow increases stem growth and alters stem δ13C and δ15N in evergreen dwarf shrub Cassiope tetragona in high-arctic Svalbard tundra

International Nuclear Information System (INIS)

Blok, Daan; Michelsen, Anders; Elberling, Bo; Weijers, Stef; Löffler, Jörg; Welker, Jeffrey M; Cooper, Elisabeth J

2015-01-01

Deeper winter snow is hypothesized to favor shrub growth and may partly explain the shrub expansion observed in many parts of the arctic during the last decades, potentially triggering biophysical feedbacks including regional warming and permafrost thawing. We experimentally tested the effects of winter snow depth on shrub growth and ecophysiology by measuring stem length and stem hydrogen (δ 2 H), carbon (δ 13 C), nitrogen (δ 15 N) and oxygen (δ 18 O) isotopic composition of the circumarctic evergreen dwarf shrub Cassiope tetragona growing in high-arctic Svalbard, Norway. Measurements were carried out on C. tetragona individuals sampled from three tundra sites, each representing a distinct moisture regime (dry heath, meadow, moist meadow). Individuals were sampled along gradients of experimentally manipulated winter snow depths in a six-year old snow fence experiment: in ambient (c. 20 cm), medium (c. 100 cm), and deep snow (c. 150 cm) plots. The deep-snow treatment consistently and significantly increased C. tetragona growth during the 2008–2011 manipulation period compared to growth in ambient-snow plots. Stem δ 15 N and stem N concentration values were significantly higher in deep-snow individuals compared to individuals growing in ambient-snow plots during the course of the experiment, suggesting that soil N-availability was increased in deep-snow plots as a result of increased soil winter N mineralization. Although inter-annual growing season-precipitation δ 2 H and stem δ 2 H records closely matched, snow depth did not change stem δ 2 H or δ 18 O, suggesting that water source usage by C. tetragona was unaltered. Instead, the deep insulating snowpack may have protected C. tetragona shrubs against frost damage, potentially compensating the detrimental effects of a shortened growing season and associated phenological delay on growth. Our findings suggest that an increase in winter precipitation in the High Arctic, as predicted by climate models, has

Airborne Surveys of Snow Depth over Arctic Sea Ice

Science.gov (United States)

Kwok, R.; Panzer, B.; Leuschen, C.; Pang, S.; Markus, T.; Holt, B.; Gogineni, S.

2011-01-01

During the spring of 2009, an ultrawideband microwave radar was deployed as part of Operation IceBridge to provide the first cross-basin surveys of snow thickness over Arctic sea ice. In this paper, we analyze data from three approx 2000 km transects to examine detection issues, the limitations of the current instrument, and the regional variability of the retrieved snow depth. Snow depth is the vertical distance between the air \\snow and snow-ice interfaces detected in the radar echograms. Under ideal conditions, the per echogram uncertainty in snow depth retrieval is approx 4 - 5 cm. The finite range resolution of the radar (approx 5 cm) and the relative amplitude of backscatter from the two interfaces limit the direct retrieval of snow depths much below approx 8 cm. Well-defined interfaces are observed over only relatively smooth surfaces within the radar footprint of approx 6.5 m. Sampling is thus restricted to undeformed, level ice. In early April, mean snow depths are 28.5 +/- 16.6 cm and 41.0 +/- 22.2 cm over first-year and multiyear sea ice (MYI), respectively. Regionally, snow thickness is thinner and quite uniform over the large expanse of seasonal ice in the Beaufort Sea, and gets progressively thicker toward the MYI cover north of Ellesmere Island, Greenland, and the Fram Strait. Snow depth over MYI is comparable to that reported in the climatology by Warren et al. Ongoing improvements to the radar system and the utility of these snow depth measurements are discussed.

Winter snow conditions on Arctic sea ice north of Svalbard during the Norwegian young sea ICE (N-ICE2015) expedition

Science.gov (United States)

Merkouriadi, Ioanna; Gallet, Jean-Charles; Graham, Robert M.; Liston, Glen E.; Polashenski, Chris; Rösel, Anja; Gerland, Sebastian

2017-10-01

Snow is a crucial component of the Arctic sea ice system. Its thickness and thermal properties control heat conduction and radiative fluxes across the ocean, ice, and atmosphere interfaces. Hence, observations of the evolution of snow depth, density, thermal conductivity, and stratigraphy are crucial for the development of detailed snow numerical models predicting energy transfer through the snow pack. Snow depth is also a major uncertainty in predicting ice thickness using remote sensing algorithms. Here we examine the winter spatial and temporal evolution of snow physical properties on first-year (FYI) and second-year ice (SYI) in the Atlantic sector of the Arctic Ocean, during the Norwegian young sea ICE (N-ICE2015) expedition (January to March 2015). During N-ICE2015, the snow pack consisted of faceted grains (47%), depth hoar (28%), and wind slab (13%), indicating very different snow stratigraphy compared to what was observed in the Pacific sector of the Arctic Ocean during the SHEBA campaign (1997-1998). Average snow bulk density was 345 kg m-3 and it varied with ice type. Snow depth was 41 ± 19 cm in January and 56 ± 17 cm in February, which is significantly greater than earlier suggestions for this region. The snow water equivalent was 14.5 ± 5.3 cm over first-year ice and 19 ± 5.4 cm over second-year ice.

Snow cover and extreme winter warming events control flower abundance of some, but not all species in high arctic Svalbard

DEFF Research Database (Denmark)

Semenchuk, Philipp R.; Elberling, Bo; Cooper, Elisabeth J.

2013-01-01

octopetala. However, the affected species were resilient and individuals did not experience any long term effects. In the case of short or cold summers, a subset of species suffered reduced reproductive success, which may affect future plant composition through possible cascading competition effects. Extreme...... winter warming events were shown to expose the canopy to cold winter air. The following summer most of the overwintering flower buds could not produce flowers. Thus reproductive success is reduced if this occurs in subsequent years. We conclude that snow depth influences flower abundance by altering...... events, while Stellaria crassipes responded partly. Snow pack thickness determined whether winter warming events had an effect on flower abundance of some species. Warming events clearly reduced flower abundance in shallow but not in deep snow regimes of Cassiope tetragona, but only marginally for Dryas...

Evaluating UAV and LiDAR Retrieval of Snow Depth in a Coniferous Forest in Arizona

Science.gov (United States)

Van Leeuwen, W. J. D.; Broxton, P.; Biederman, J. A.

2017-12-01

Remote sensing of snow depth and cover in forested environments is challenging. Trees interfere with the remote sensing of snowpack below the canopy and cause large variations in the spatial distribution of the snowpack itself (e.g. between below canopy environments to shaded gaps to open clearings). The distribution of trees and topographic variation make it challenging to monitor the snowpack with in-situ observations. Airborne LiDAR has improved our ability to monitor snowpack over large areas in montane and forested environments because of its high sampling rate and ability to penetrate the canopy. However, these LiDAR flights can be too expensive and time-consuming to process, making it hard to use them for real-time snow monitoring. In this research, we evaluate Structure from Motion (SfM) as an alternative to Airborne LiDAR to generate high-resolution snow depth data in forested environments. This past winter, we conducted a snow field campaign over Arizona's Mogollon Rim where we acquired aerial LiDAR, multi-angle aerial photography from a UAV, and extensive field observations of snow depth at two sites. LiDAR and SFM derived snow depth maps were generated by comparing "snow-on" and "snow-off" LiDAR and SfM data. The SfM- and LiDAR-generated snow depth maps were similar at a site with fewer trees, though there were more discrepancies at a site with more trees. Both compared reasonably well with the field observations at the sparser forested site, with poorer agreement at the denser forested site. Finally, although the SfM produced point clouds with much higher point densities than the aerial LiDAR, the SfM was not able to produce meaningful snow depth estimates directly underneath trees and had trouble in areas with deep shadows. Based on these findings, we are optimizing our UAV data acquisition strategies for this upcoming field season. We are using these data, along with high-resolution hydrological modeling, to gain a better understanding of how

Snow Based Winter Tourism and Kinds of Adaptations to Climate Change

Science.gov (United States)

Breiling, M.

2009-04-01

Austria is the most intensive winter tourism country in the world with some 4% contribution in the national GNP. Snow based winter tourism became the lead economy of mountain areas, covering two thirds of the country and is by far economically more important than agriculture and forestry. While natural snow was the precondition for the establishment of winter tourism, artificial snow is nowadays the precondition to maintain winter tourism in the current economic intensity. Skiing originally low tech, is developing increasingly into high tech. While skiing was comparatively cheap in previous days due to natural snow, skiing is getting more expensive and exclusive for a higher income class due to the relative high production costs. Measures to adapt to a warmer climate can be divided into three principle types: physical adaptation, technical adaptation - where artificial snow production plays a major role - and social adaptation. It will be discussed under which conditions each adaptation type seems feasible in dependence of the level of warming. In particular physical and technical adaptations are related to major investments. Practically every ski resort has to decide about what is an appropriate, economically cost efficient level of adaptation. Adapting too much reduces profits. Adapting too little does not bring enough income. The optimal level is often not clear. In many cases public subsidies help to collect funds for adaptation and to keep skiing profitable. The possibility to adapt on local, regional or on national scales will depend on the degree of warming, the future price of artificial snow production and the public means foreseen to support the winter tourism industry.

Long-term variability in Northern Hemisphere snow cover and associations with warmer winters

Science.gov (United States)

McCabe, Gregory J.; Wolock, David M.

2010-01-01

A monthly snow accumulation and melt model is used with gridded monthly temperature and precipitation data for the Northern Hemisphere to generate time series of March snow-covered area (SCA) for the period 1905 through 2002. The time series of estimated SCA for March is verified by comparison with previously published time series of SCA for the Northern Hemisphere. The time series of estimated Northern Hemisphere March SCA shows a substantial decrease since about 1970, and this decrease corresponds to an increase in mean winter Northern Hemisphere temperature. The increase in winter temperature has caused a decrease in the fraction of precipitation that occurs as snow and an increase in snowmelt for some parts of the Northern Hemisphere, particularly the mid-latitudes, thus reducing snow packs and March SCA. In addition, the increase in winter temperature and the decreases in SCA appear to be associated with a contraction of the circumpolar vortex and a poleward movement of storm tracks, resulting in decreased precipitation (and snow) in the low- to mid-latitudes and an increase in precipitation (and snow) in high latitudes. If Northern Hemisphere winter temperatures continue to warm as they have since the 1970s, then March SCA will likely continue to decrease.

When Models and Observations Collide: Journeying towards an Integrated Snow Depth Product

Science.gov (United States)

Webster, M.; Petty, A.; Boisvert, L.; Markus, T.; Kurtz, N. T.; Kwok, R.; Perovich, D. K.

2017-12-01

Knowledge of snow depth is essential for assessing changes in sea ice mass balance due to snow's insulating and reflective properties. In remote sensing applications, the accuracy of sea ice thickness retrievals from altimetry crucially depends on snow depth. Despite the need for snow depth data, we currently lack continuous observations that capture the basin-scale snow depth distribution and its seasonal evolution. Recent in situ and remote sensing observations are sparse in space and time, and contain uncertainties, caveats, and/or biases that often require careful interpretation. Likewise, using model output for remote sensing applications is limited due to uncertainties in atmospheric forcing and different treatments of snow processes. Here, we summarize our efforts in bringing observational and model data together to develop an approach for an integrated snow depth product. We start with a snow budget model and incrementally incorporate snow processes to determine the effects on snow depth and to assess model sensitivity. We discuss lessons learned in model-observation integration and ideas for potential improvements to the treatment of snow in models.

Biogeochemical Impact of Snow Cover and Cyclonic Intrusions on the Winter Weddell Sea Ice Pack

Science.gov (United States)

Tison, J.-L.; Schwegmann, S.; Dieckmann, G.; Rintala, J.-M.; Meyer, H.; Moreau, S.; Vancoppenolle, M.; Nomura, D.; Engberg, S.; Blomster, L. J.; Hendrickx, S.; Uhlig, C.; Luhtanen, A.-M.; de Jong, J.; Janssens, J.; Carnat, G.; Zhou, J.; Delille, B.

2017-12-01

Sea ice is a dynamic biogeochemical reactor and a double interface actively interacting with both the atmosphere and the ocean. However, proper understanding of its annual impact on exchanges, and therefore potentially on the climate, notably suffer from the paucity of autumnal and winter data sets. Here we present the results of physical and biogeochemical investigations on winter Antarctic pack ice in the Weddell Sea (R. V. Polarstern AWECS cruise, June-August 2013) which are compared with those from two similar studies conducted in the area in 1986 and 1992. The winter 2013 was characterized by a warm sea ice cover due to the combined effects of deep snow and frequent warm cyclones events penetrating southward from the open Southern Ocean. These conditions were favorable to high ice permeability and cyclic events of brine movements within the sea ice cover (brine tubes), favoring relatively high chlorophyll-a (Chl-a) concentrations. We discuss the timing of this algal activity showing that arguments can be presented in favor of continued activity during the winter due to the specific physical conditions. Large-scale sea ice model simulations also suggest a context of increasingly deep snow, warm ice, and large brine fractions across the three observational years, despite the fact that the model is forced with a snowfall climatology. This lends support to the claim that more severe Antarctic sea ice conditions, characterized by a longer ice season, thicker, and more concentrated ice are sufficient to increase the snow depth and, somehow counterintuitively, to warm the ice.

Evaluation of snow cover and snow depth on the Qinghai–Tibetan Plateau derived from passive microwave remote sensing

Directory of Open Access Journals (Sweden)

L. Dai

2017-08-01

Full Text Available Snow cover on the Qinghai–Tibetan Plateau (QTP plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow

Evaluation of SNODAS snow depth and snow water equivalent estimates for the Colorado Rocky Mountains, USA

Science.gov (United States)

Clow, David W.; Nanus, Leora; Verdin, Kristine L.; Schmidt, Jeffrey

2012-01-01

The National Weather Service's Snow Data Assimilation (SNODAS) program provides daily, gridded estimates of snow depth, snow water equivalent (SWE), and related snow parameters at a 1-km2 resolution for the conterminous USA. In this study, SNODAS snow depth and SWE estimates were compared with independent, ground-based snow survey data in the Colorado Rocky Mountains to assess SNODAS accuracy at the 1-km2 scale. Accuracy also was evaluated at the basin scale by comparing SNODAS model output to snowmelt runoff in 31 headwater basins with US Geological Survey stream gauges. Results from the snow surveys indicated that SNODAS performed well in forested areas, explaining 72% of the variance in snow depths and 77% of the variance in SWE. However, SNODAS showed poor agreement with measurements in alpine areas, explaining 16% of the variance in snow depth and 30% of the variance in SWE. At the basin scale, snowmelt runoff was moderately correlated (R2 = 0.52) with SNODAS model estimates. A simple method for adjusting SNODAS SWE estimates in alpine areas was developed that uses relations between prevailing wind direction, terrain, and vegetation to account for wind redistribution of snow in alpine terrain. The adjustments substantially improved agreement between measurements and SNODAS estimates, with the R2 of measured SWE values against SNODAS SWE estimates increasing from 0.42 to 0.63 and the root mean square error decreasing from 12 to 6 cm. Results from this study indicate that SNODAS can provide reliable data for input to moderate-scale to large-scale hydrologic models, which are essential for creating accurate runoff forecasts. Refinement of SNODAS SWE estimates for alpine areas to account for wind redistribution of snow could further improve model performance. Published 2011. This article is a US Government work and is in the public domain in the USA.

Deepened winter snow increases stem growth and alters stem δ13C and δ15N in evergreen dwarf shrub Cassiope tetragona in high-arctic Svalbard tundra

DEFF Research Database (Denmark)

Blok, Daan; Weijers, Stef; Welker, Jeffrey M

2015-01-01

Deeper winter snow is hypothesized to favor shrub growth and may partly explain the shrub expansion observed in many parts of the arctic during the last decades, potentially triggering biophysical feedbacks including regional warming and permafrost thawing. We experimentally tested the effects...... of winter snow depth on shrub growth and ecophysiology by measuring stem length and stem hydrogen ( δ2H), carbon ( δ13C), nitrogen ( δ15N) and oxygen ( δ18O) isotopic composition of the circumarctic evergreen dwarf shrub Cassiope tetragona growing in high-arctic Svalbard, Norway. Measurements were carried...... closely matched, snow depth did not change stem δ 2 H or δ 18 O, suggesting that water source usage by C. tetragona was unaltered. Instead, the deep insulating snowpack may have protected C. tetragona shrubs against frost damage, potentially compensating the detrimental effects of a shortened growing...

Russian Federation Snow Depth and Ice Crust Surveys

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Russian Federation Snow Depth and Ice Crust Surveys, dataset DSI-9808, contains routine snow surveys that run throughout the cold season every 10 days (every five...

Sampling in the Snow: High School Winter Field Experiences Provide Relevant, Real World Connections Between Scientific Practices and Disciplinary Core Ideas

Science.gov (United States)

Hanson, E. W.; Burakowski, E. A.

2014-12-01

For much of the northern United States, the months surrounding the winter solstice are times of increased darkness, low temperatures, and frozen landscapes. It's a time when many high school science educators, who otherwise would venture outside with their classes, hunker down and are wary of the outdoors. However, a plethora of learning opportunities lies just beyond the classroom. Working collaboratively, a high school science teacher and a snow scientist have developed multiple activities to engage students in the scientific process of collecting, analyzing and interpreting the winter world using snow data to (1) learn about the insulative properties of snow, and (2) to learn about the role of snow cover on winter climate through its reflective properties while participating in a volunteer network that collects snow depth, albedo (reflectivity), and density data. These outdoor field-based snow investigations incorporate Next Generation Science Standards (NGSS) and disciplinary core ideas, including ESS2.C: The roles of water in Earth's surface processes and ESS2.D: Weather and Climate. Additionally, the lesson plans presented address Common Core State Standards (CCSS) in Mathematics, including the creation and analysis of bar graphs and time series plots (CCSS.Math.HSS-ID.A.1) and xy scatter plots (CCSS.Math.HSS-ID.B.6). High school students participating in the 2013/2014 snow sampling season described their outdoor learning experience as "authentic" and "hands-on" as compared to traditional class indoors. They emphasized that learning outdoors was essential to their understanding of underlying content and concepts because they "learn through actual experience."

Winter fidelity and apparent survival of lesser snow goose populations in the Pacific flyway

Science.gov (United States)

Williams, C.K.; Samuel, M.D.; Baranyuk, Vasily V.; Cooch, E.G.; Kraege, Donald K.

2008-01-01

The Beringia region of the Arctic contains 2 colonies of lesser snow geese (Chen caerulescens caerulescens) breeding on Wrangel Island, Russia, and Banks Island, Canada, and wintering in North America. The Wrangel Island population is composed of 2 subpopulations from a sympatric breeding colony but separate wintering areas, whereas the Banks Island population shares a sympatric wintering area in California, USA, with one of the Wrangel Island subpopulations. The Wrangel Island colony represents the last major snow goose population in Russia and has fluctuated considerably since 1970, whereas the Banks Island population has more than doubled. The reasons for these changes are unclear, but hypotheses include independent population demographics (survival and recruitment) and immigration and emigration among breeding or wintering populations. These demographic and movement patterns have important ecological and management implications for understanding goose population structure, harvest of admixed populations, and gene flow among populations with separate breeding or wintering areas. From 1993 to 1996, we neckbanded molting birds at their breeding colonies and resighted birds on the wintering grounds. We used multistate mark-recapture models to evaluate apparent survival rates, resighting rates, winter fidelity, and potential exchange among these populations. We also compared the utility of face stain in Wrangel Island breeding geese as a predictor of their wintering area. Our results showed similar apparent survival rates between subpopulations of Wrangel Island snow geese and lower apparent survival, but higher emigration, for the Banks Island birds. Males had lower apparent survival than females, most likely due to differences in neckband loss. Transition between wintering areas was low (exchange between the Banks and northern Wrangel Island populations. Face staining was an unreliable indicator of wintering area. Our findings suggest that northern and southern

Estonian Mean Snow Depth and Duration (1891-1994)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains the number of days of snow cover in days per year, and three 10-day snow depth means per month in centimeters from stations across Estonia....

Variability in snow depth time series in the Adige catchment

Directory of Open Access Journals (Sweden)

Giorgia Marcolini

2017-10-01

New hydrological insights for the region: Stations located above and below 1650 m a.s.l. show different dynamics, with the latter experiencing in the last decades a larger reduction of average snow depth and snow cover duration, than the former. Wavelet analyses show that snow dynamics change with elevation and correlate differently with climatic indices at multiple temporal scales. We also observe that starting from the late 1980s snow cover duration and mean seasonal snow depth are below the average in the study area. We also identify an elevation dependent correlation with the temperature. Moreover, correlation with the Mediterranean Oscillation Index and with the North Atlantic Oscillation Index is identified.

Regime shift of snow days in Switzerland

Science.gov (United States)

Marty, Christoph

2008-06-01

The number of days with a snow depth above a certain threshold is the key factor for winter tourism in an Alpine country like Switzerland. An investigation of 34 long-term stations between 200 and 1800 m asl (above sea level) going back for at least the last 60 years (1948-2007) shows an unprecedented series of low snow winters in the last 20 years. The signal is uniform despite high regional differences. A shift detection analysis revealed a significant step-like decrease in snow days at the end of the 1980's with no clear trend since then. This abrupt change resulted in a loss of 20% to 60% of the total snow days. The stepwise increase of the mean winter temperature at the end of the 1980's and its close correlation with the snow day anomalies corroborate the sensitivity of the mid-latitude winter to the climate change induced temperature increase.

Variability of snow line elevation, snow cover area and depletion in the main Slovak basins in winters 2001–2014

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Krajčí Pavel

2016-03-01

Full Text Available Spatial and temporal variability of snow line (SL elevation, snow cover area (SCA and depletion (SCD in winters 2001–2014 is investigated in ten main Slovak river basins (the Western Carpathians. Daily satellite snow cover maps from MODIS Terra (MOD10A1, V005 and Aqua (MYD10A1, V005 with resolution 500 m are used.

Effects of sowing time on pink snow mould, leaf rust and winter damage in winter rye varieties in Finland

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M. SERENIUS

2008-12-01

Full Text Available Disease infection in relation to sowing time of winter rye (Secale cereale was studied in southern Finland in order to compare overwintering capacity of modern rye varieties and to give recommendations for rye cultivation. This was done by using three sowing times and four rye varieties in field trials conducted at three locations in 1999–2001. The early sown rye (beginning of August was severely affected by diseases caused by Puccinia recondita and Microdochium nivale, whereas postponing sowing for two weeks after the recommended sowing time resulted in considerably less infection. The infection levels of diseases differed among rye varieties. Finnish rye varieties Anna and Bor 7068 were more resistant to snow mould and more winter hardy than the Polish variety Amilo, or the German hybrid varieties Picasso and Esprit. However, Amilo was the most resistant to leaf rust. In the first year snow mould appeared to be the primary cause of winter damage, but in the second year the winter damage was positively correlated with leaf rust. No significant correlation between frit fly infestation and winter damage or disease incidence of snow mould or leaf rust was established. The late sowing of rye (in the beginning of September is recommended in Finland, particularly with hybrid varieties, to minimize the need for chemical plant protection in autumn.;

Winter is losing its cool

Science.gov (United States)

Feng, S.

2017-12-01

Winter seasons have significant societal impacts across all sectors ranging from direct human health to ecosystems, transportation, and recreation. This study quantifies the severity of winter and its spatial-temporal variations using a newly developed winter severity index and daily temperature, snowfall and snow depth. The winter severity and the number of extreme winter days are decreasing across the global terrestrial areas during 1901-2015 except the southeast United States and isolated regions in the Southern Hemisphere. These changes are dominated by winter warming, while the changes in daily snowfall and snow depth played a secondary role. The simulations of multiple CMIP5 climate models can well capture the spatial and temporal variations of the observed changes in winter severity and extremes during 1951-2005. The models are consistent in projecting a future milder winter under various scenarios. The winter severity is projected to decrease 60-80% in the middle-latitude Northern Hemisphere under the business-as-usual scenario. The winter arrives later, ends earlier and the length of winter season will be notably shorter. The changes in harsh winter in the polar regions are weak, mainly because the warming leads to more snowfall in the high latitudes.

Estimating winter survival of winter wheat by simulations of plant frost tolerance

NARCIS (Netherlands)

Bergjord Olsen, A.K.; Persson, T.; Wit, de A.; Nkurunziza, L.; Sindhøj, E.; Eckersten, H.

2018-01-01

Based on soil temperature, snow depth and the grown cultivar's maximum attainable level of frost tolerance (LT50c), the FROSTOL model simulates development of frost tolerance (LT50) and winter damage, thereby enabling risk calculations for winter wheat survival. To explore the accuracy of this

Snow Climatology of Arctic Sea Ice: Comparison of Reanalysis and Climate Model Data with In Situ Measurements

Science.gov (United States)

Chevooruvalappil Chandran, B.; Pittana, M.; Haas, C.

2015-12-01

Snow on sea ice is a critical and complex factor influencing sea ice processes. Deep snow with a high albedo and low thermal conductivity inhibits ice growth in winter and minimizes ice loss in summer. Very shallow or absent snow promotes ice growth in winter and ice loss in summer. The timing of snow ablation critically impacts summer sea ice mass balance. Here we assess the accuracy of various snow on sea ice data products from reanalysis and modeling comparing them with in situ measurements. The latter are based on the Warren et al. (1999) monthly climatology derived from snow ruler measurements between 1954-1991, and on daily snow depth retrievals from few drifting ice mass balance buoys (IMB) with sufficiently long observations spanning the summer season. These were compared with snow depth data from the National Center for Environmental Prediction Department of Energy Reanalysis 2 (NCEP), the Community Climate System Model 4 (CCSM4), and the Canadian Earth System Model 2 (CanESM2). Results are quite variable in different years and regions. However, there is often good agreement between CanESM2 and IMB snow depth during the winter accumulation and spring melt periods. Regional analyses show that over the western Arctic covered primarily with multiyear ice NCEP snow depths are in good agreement with the Warren climatology while CCSM4 overestimates snow depth. However, in the Eastern Arctic which is dominated by first-year ice the opposite behavior is observed. Compared to the Warren climatology CanESM2 underestimates snow depth in all regions. Differences between different snow depth products are as large as 10 to 20 cm, with large consequences for the sea ice mass balance. However, it is also very difficult to evaluate the accuracy of reanalysis and model snow depths due to a lack of extensive, continuous in situ measurements.

Observations of distributed snow depth and snow duration within diverse forest structures in a maritime mountain watershed

Science.gov (United States)

Dickerson-Lange, Susan E.; Lutz, James A.; Gersonde, Rolf; Martin, Kael A.; Forsyth, Jenna E.; Lundquist, Jessica D.

2015-11-01

Spatially distributed snow depth and snow duration data were collected over two to four snow seasons during water years 2011-2014 in experimental forest plots within the Cedar River Municipal Watershed, 50 km east of Seattle, Washington, USA. These 40 × 40 m forest plots, situated on the western slope of the Cascade Range, include unthinned second-growth coniferous forests, variable density thinned forests, forest gaps in which a 20 m diameter (approximately equivalent to one tree height) gap was cut in the middle of each plot, and old-growth forest. Together, this publicly available data set includes snow depth and density observations from manual snow surveys, distributed snow duration observations from ground temperature sensors and time-lapse cameras, meteorological data collected at two open locations and three forested locations, and forest canopy data from airborne light detection and ranging (LiDAR) data and hemispherical photographs. These colocated snow, meteorological, and forest data have the potential to improve understanding of forest influences on snow processes, and provide a unique model-testing data set for hydrological analyses in a forested, maritime watershed. We present empirical snow depletion curves within forests to illustrate an application of these data to improve subgrid representation of snow cover in distributed modeling.

Measurements of seasonal frost depth by frost tube in Japan

Science.gov (United States)

Harada, K.; Yoshikawa, K.; Iwahana, G.; Stanilovskaya, J. V.; Sawada, Y.; Sone, T.

2017-12-01

Since 2011 winter season, frost depths have been measured as an outreach program in Hokkaido, northern part of Japan, where seasonal ground freezing occurs in winter. Frost depths were measured in elementary, junior high and high schools in order to emphasis their interest for earth sciences. At schools, using simple frost tube, measurements were conducted directly once a week by students or teacher during ground freezing under no snow-removal condition. A lecture was made in class and a frost tube was set at schoolyard, as the same tube and protocol as UAF's Permafrost Outreach Program, using clear tube with blue-colored water. In 2011 winter season, we started measurements at three schools, and the number of school extended to 32 in 2016 season, 26 elementary schools, 5 junior high schools and one high school. We visited schools in summer time or just before frost season to talk about the method of measurement, and measurements by students started just after ground freezing. After the end of frozen period, we visited schools again to explain results of each school or another schools in Japan, Alaska, Canada or Russia. The measured frost depths in Hokkaido ranged widely, from only a few centimeter to more than 50 cm. However, some schools had no frost depth due to heavy snow. We confirmed that the frost depth strongly depends on air temperature and snow depth. The lecture was made to student why the frost depth ranged widely, and the effect of snow was explained by using the example of igloo. In order to validate the effect of snow and to compare frost depths, we tried to measure frost depths under snow-removal and no snow-removal conditions at the same elementary school. At the end of December, depths had no significant difference between these conditions, and the difference went to 14 cm after one month, with about 30 cm of snow depth. After these measurements and lectures, students noticed snow has a role as insulator and affects the frost depth.

Estimating snow depth of alpine snowpack via airborne multifrequency passive microwave radiance observations: Colorado, USA

Science.gov (United States)

Kim, R. S.; Durand, M. T.; Li, D.; Baldo, E.; Margulis, S. A.; Dumont, M.; Morin, S.

2017-12-01

This paper presents a newly-proposed snow depth retrieval approach for mountainous deep snow using airborne multifrequency passive microwave (PM) radiance observation. In contrast to previous snow depth estimations using satellite PM radiance assimilation, the newly-proposed method utilized single flight observation and deployed the snow hydrologic models. This method is promising since the satellite-based retrieval methods have difficulties to estimate snow depth due to their coarse resolution and computational effort. Indeed, this approach consists of particle filter using combinations of multiple PM frequencies and multi-layer snow physical model (i.e., Crocus) to resolve melt-refreeze crusts. The method was performed over NASA Cold Land Processes Experiment (CLPX) area in Colorado during 2002 and 2003. Results showed that there was a significant improvement over the prior snow depth estimates and the capability to reduce the prior snow depth biases. When applying our snow depth retrieval algorithm using a combination of four PM frequencies (10.7,18.7, 37.0 and 89.0 GHz), the RMSE values were reduced by 48 % at the snow depth transects sites where forest density was less than 5% despite deep snow conditions. This method displayed a sensitivity to different combinations of frequencies, model stratigraphy (i.e. different number of layering scheme for snow physical model) and estimation methods (particle filter and Kalman filter). The prior RMSE values at the forest-covered areas were reduced by 37 - 42 % even in the presence of forest cover.

Carbon dioxide evolution from snow-covered agricultural ecosystems in Finland

Directory of Open Access Journals (Sweden)

Hiroshi Koizumi

1996-07-01

Full Text Available The release of CO2 from the snow surface in winter and the soil surface in summer was directly or indirectly measured in three different soil types (peat, sand and clay in agricultural ecosystems in Finland. The closed chamber (CC method was used for the direct and Pick’s diffusion model (DM method for the indirect measurements. The winter soil temperatures at 2-cm depth were between 0 and 1°C for each soil type. The concentration of CO2 within the snowpack increased linearly with snow depth. The average fluxes of CO2 calculated from the gradients of CO2 concentration in the snow using the DM method ranged from 10 to 27 mg CO2 m2h-1 and with the CC method from 18 to 27 mg CO2 m2h-1. These results suggest that the snow insulates the soil thermally, allowing CO2 production to continue at soil temperatures slightly above freezing in the winter. Carbon dioxide formed in the soil can move across the snowpack up to the atmosphere. The winter/summer ratio of CO2 evolution was estimated to exceed 4%. Therefore, the snow-covered crop soil served as a source of CO2 in winter, and CO2 evolution constitutes an important part of the annual CO2 budget in snowy regions.

Use of machine learning techniques for modeling of snow depth

Directory of Open Access Journals (Sweden)

G. V. Ayzel

2017-01-01

Full Text Available Snow exerts significant regulating effect on the land hydrological cycle since it controls intensity of heat and water exchange between the soil-vegetative cover and the atmosphere. Estimating of a spring flood runoff or a rain-flood on mountainous rivers requires understanding of the snow cover dynamics on a watershed. In our work, solving a problem of the snow cover depth modeling is based on both available databases of hydro-meteorological observations and easily accessible scientific software that allows complete reproduction of investigation results and further development of this theme by scientific community. In this research we used the daily observational data on the snow cover and surface meteorological parameters, obtained at three stations situated in different geographical regions: Col de Porte (France, Sodankyla (Finland, and Snoquamie Pass (USA.Statistical modeling of the snow cover depth is based on a complex of freely distributed the present-day machine learning models: Decision Trees, Adaptive Boosting, Gradient Boosting. It is demonstrated that use of combination of modern machine learning methods with available meteorological data provides the good accuracy of the snow cover modeling. The best results of snow cover depth modeling for every investigated site were obtained by the ensemble method of gradient boosting above decision trees – this model reproduces well both, the periods of snow cover accumulation and its melting. The purposeful character of learning process for models of the gradient boosting type, their ensemble character, and use of combined redundancy of a test sample in learning procedure makes this type of models a good and sustainable research tool. The results obtained can be used for estimating the snow cover characteristics for river basins where hydro-meteorological information is absent or insufficient.

Rand Corporation Mean Monthly Global Snow Depth

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — All available monthly snow depth climatologies were integrated by the Rand Corporation, in the early 1980s, into one global (excluding Africa and South America)...

The influence of snowmobile trails on coyote movements during winter in high-elevation landscapes.

Directory of Open Access Journals (Sweden)

Eric M Gese

Full Text Available Competition between sympatric carnivores has long been of interest to ecologists. Increased understanding of these interactions can be useful for conservation planning. Increased snowmobile traffic on public lands and in habitats used by Canada lynx (Lynx canadensis remains controversial due to the concern of coyote (Canis latrans use of snowmobile trails and potential competition with lynx. Determining the variables influencing coyote use of snowmobile trails has been a priority for managers attempting to conserve lynx and their critical habitat. During 2 winters in northwest Wyoming, we backtracked coyotes for 265 km to determine how varying snow characteristics influenced coyote movements; 278 km of random backtracking was conducted simultaneously for comparison. Despite deep snow (>1 m deep, radio-collared coyotes persisted at high elevations (>2,500 m year-round. All coyotes used snowmobile trails for some portion of their travel. Coyotes used snowmobile trails for 35% of their travel distance (random: 13% for a mean distance of 149 m (random: 59 m. Coyote use of snowmobile trails increased as snow depth and penetrability off trails increased. Essentially, snow characteristics were most influential on how much time coyotes spent on snowmobile trails. In the early months of winter, snow depth was low, yet the snow column remained dry and the coyotes traveled off trails. As winter progressed and snow depth increased and snow penetrability increased, coyotes spent more travel distance on snowmobile trails. As spring approached, the snow depth remained high but penetrability decreased, hence coyotes traveled less on snowmobile trails because the snow column off trail was more supportive. Additionally, coyotes traveled closer to snowmobile trails than randomly expected and selected shallower snow when traveling off trails. Coyotes also preferred using snowmobile trails to access ungulate kills. Snow compaction from winter recreation influenced

The influence of snowmobile trails on coyote movements during winter in high-elevation landscapes.

Science.gov (United States)

Gese, Eric M; Dowd, Jennifer L B; Aubry, Lise M

2013-01-01

Competition between sympatric carnivores has long been of interest to ecologists. Increased understanding of these interactions can be useful for conservation planning. Increased snowmobile traffic on public lands and in habitats used by Canada lynx (Lynx canadensis) remains controversial due to the concern of coyote (Canis latrans) use of snowmobile trails and potential competition with lynx. Determining the variables influencing coyote use of snowmobile trails has been a priority for managers attempting to conserve lynx and their critical habitat. During 2 winters in northwest Wyoming, we backtracked coyotes for 265 km to determine how varying snow characteristics influenced coyote movements; 278 km of random backtracking was conducted simultaneously for comparison. Despite deep snow (>1 m deep), radio-collared coyotes persisted at high elevations (>2,500 m) year-round. All coyotes used snowmobile trails for some portion of their travel. Coyotes used snowmobile trails for 35% of their travel distance (random: 13%) for a mean distance of 149 m (random: 59 m). Coyote use of snowmobile trails increased as snow depth and penetrability off trails increased. Essentially, snow characteristics were most influential on how much time coyotes spent on snowmobile trails. In the early months of winter, snow depth was low, yet the snow column remained dry and the coyotes traveled off trails. As winter progressed and snow depth increased and snow penetrability increased, coyotes spent more travel distance on snowmobile trails. As spring approached, the snow depth remained high but penetrability decreased, hence coyotes traveled less on snowmobile trails because the snow column off trail was more supportive. Additionally, coyotes traveled closer to snowmobile trails than randomly expected and selected shallower snow when traveling off trails. Coyotes also preferred using snowmobile trails to access ungulate kills. Snow compaction from winter recreation influenced coyote

Effect of snow cover on soil frost penetration

Science.gov (United States)

Rožnovský, Jaroslav; Brzezina, Jáchym

2017-12-01

Snow cover occurrence affects wintering and lives of organisms because it has a significant effect on soil frost penetration. An analysis of the dependence of soil frost penetration and snow depth between November and March was performed using data from 12 automated climatological stations located in Southern Moravia, with a minimum period of measurement of 5 years since 2001, which belong to the Czech Hydrometeorological institute. The soil temperatures at 5 cm depth fluctuate much less in the presence of snow cover. In contrast, the effect of snow cover on the air temperature at 2 m height is only very small. During clear sky conditions and no snow cover, soil can warm up substantially and the soil temperature range can be even higher than the range of air temperature at 2 m height. The actual height of snow is also important - increased snow depth means lower soil temperature range. However, even just 1 cm snow depth substantially lowers the soil temperature range and it can therefore be clearly seen that snow acts as an insulator and has a major effect on soil frost penetration and soil temperature range.

Historical Soviet Daily Snow Depth (HSDSD), Version 2

Data.gov (United States)

National Aeronautics and Space Administration — The Historical Soviet Daily Snow Depth (HSDSD) product is based on observations from 284 World Meteorological Organization (WMO) stations throughout Russia and the...

Snow depth retrieval from L-band satellite measurements on Arctic and Antarctic sea ice

Science.gov (United States)

Maaß, N.; Kaleschke, L.; Wever, N.; Lehning, M.; Nicolaus, M.; Rossmann, H. L.

2017-12-01

The passive microwave mission SMOS provides daily coverage of the polar regions and measures at a low frequency of 1.4 GHz (L-band). SMOS observations have been used to operationally retrieve sea ice thickness up to 1 m and to estimate snow depth in the Arctic for thicker ice. Here, we present how SMOS-retrieved snow depths compare with airborne measurements from NASA's Operation IceBridge mission (OIB) and with AMSR-2 satellite retrievals at higher frequencies, and we show first applications to Antarctic sea ice. In previous studies, SMOS and OIB snow depths showed good agreement on spatial scales from 50 to 1000 km for some days and disagreement for other days. Here, we present a more comprehensive comparison of OIB and SMOS snow depths in the Arctic for 2011 to 2015. We find that the SMOS retrieval works best for cold conditions and depends on auxiliary information on ice surface temperature, here provided by MODIS thermal imagery satellite data. However, comparing SMOS and OIB snow depths is difficult because of the different spatial resolutions (SMOS: 40 km, OIB: 40 m). Spatial variability within the SMOS footprint can lead to different snow conditions as seen from SMOS and OIB. Ideally the comparison is made for uniform conditions: Low lead and open water fraction, low spatial and temporal variability of ice surface temperature, no mixture of multi- and first-year ice. Under these conditions and cold temperatures (surface temperatures below -25°C), correlation coefficients between SMOS and OIB snow depths increase from 0.3 to 0.6. A finding from the comparison with AMSR-2 snow depths is that the SMOS-based maps depend less on the age of the sea ice than the maps derived from higher frequencies. Additionally, we show first results of SMOS snow depths for Antarctic sea ice. SMOS observations are compared to measurements of autonomous snow buoys drifting in the Weddell Sea since 2014. For a better comparability of these point measurements with SMOS data, we use

Quantifying spatial distribution of snow depth errors from LiDAR using Random Forests

Science.gov (United States)

Tinkham, W.; Smith, A. M.; Marshall, H.; Link, T. E.; Falkowski, M. J.; Winstral, A. H.

2013-12-01

There is increasing need to characterize the distribution of snow in complex terrain using remote sensing approaches, especially in isolated mountainous regions that are often water-limited, the principal source of terrestrial freshwater, and sensitive to climatic shifts and variations. We apply intensive topographic surveys, multi-temporal LiDAR, and Random Forest modeling to quantify snow volume and characterize associated errors across seven land cover types in a semi-arid mountainous catchment at a 1 and 4 m spatial resolution. The LiDAR-based estimates of both snow-off surface topology and snow depths were validated against ground-based measurements across the catchment. Comparison of LiDAR-derived snow depths to manual snow depth surveys revealed that LiDAR based estimates were more accurate in areas of low lying vegetation such as shrubs (RMSE = 0.14 m) as compared to areas consisting of tree cover (RMSE = 0.20-0.35 m). The highest errors were found along the edge of conifer forests (RMSE = 0.35 m), however a second conifer transect outside the catchment had much lower errors (RMSE = 0.21 m). This difference is attributed to the wind exposure of the first site that led to highly variable snow depths at short spatial distances. The Random Forest modeled errors deviated from the field measured errors with a RMSE of 0.09-0.34 m across the different cover types. Results show that snow drifts, which are important for maintaining spring and summer stream flows and establishing and sustaining water-limited plant species, contained 30 × 5-6% of the snow volume while only occupying 10% of the catchment area similar to findings by prior physically-based modeling approaches. This study demonstrates the potential utility of combining multi-temporal LiDAR with Random Forest modeling to quantify the distribution of snow depth with a reasonable degree of accuracy. Future work could explore the utility of Terrestrial LiDAR Scanners to produce validation of snow-on surface

Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China

Science.gov (United States)

Huang, Xiaodong; Deng, Jie; Ma, Xiaofang; Wang, Yunlong; Feng, Qisheng; Hao, Xiaohua; Liang, Tiangang

2016-10-01

By combining optical remote sensing snow cover products with passive microwave remote sensing snow depth (SD) data, we produced a MODIS (Moderate Resolution Imaging Spectroradiometer) cloudless binary snow cover product and a 500 m snow depth product. The temporal and spatial variations of snow cover from December 2000 to November 2014 in China were analyzed. The results indicate that, over the past 14 years, (1) the mean snow-covered area (SCA) in China was 11.3 % annually and 27 % in the winter season, with the mean SCA decreasing in summer and winter seasons, increasing in spring and fall seasons, and not much change annually; (2) the snow-covered days (SCDs) showed an increase in winter, spring, and fall, and annually, whereas they showed a decrease in summer; (3) the average SD decreased in winter, summer, and fall, while it increased in spring and annually; (4) the spatial distributions of SD and SCD were highly correlated seasonally and annually; and (5) the regional differences in the variation of snow cover in China were significant. Overall, the SCD and SD increased significantly in south and northeast China, and decreased significantly in the north of Xinjiang province. The SCD and SD increased on the southwest edge and in the southeast part of the Tibetan Plateau, whereas it decreased in the north and northwest regions.

Snowscape Ecology: Linking Snow Properties to Wildlife Movements and Demography

Science.gov (United States)

Prugh, L.; Verbyla, D.; van de Kerk, M.; Mahoney, P.; Sivy, K. J.; Liston, G. E.; Nolin, A. W.

2017-12-01

Snow enshrouds up to one third of the global land mass annually and exerts a major influence on animals that reside in these "snowscapes," (landscapes covered in snow). Dynamic snowscapes may have especially strong effects in arctic and boreal regions where dry snow persists for much of the year. Changes in temperature and hydrology are transforming northern regions, with profound implications for wildlife that are not well understood. We report initial findings from a NASA ABoVE project examining effects of snow properties on Dall sheep (Ovis dalli dalli). We used the MODSCAG snow fraction product to map spring snowline elevations and snow-off dates from 2000-2015 throughout the global range of Dall sheep in Alaska and northwestern Canada. We found a negative effect of spring snow cover on Dall sheep recruitment that increased with latitude. Using meteorological data and a daily freeze/thaw status product derived from passive microwave remote sensing from 1983-2012, we found that sheep survival rates increased in years with higher temperatures, less winter precipitation, fewer spring freeze-thaw events, and more winter freeze-thaw events. To examine the effects of snow depth and density on sheep movements, we used location data from GPS-collared sheep and a snowpack evolution model (SnowModel). We found that sheep selected for shallow, fluffy snow at high elevations, but they selected for denser snow as depth increased. Our field measurements identified a critical snow density threshold of 329 (± 18 SE) kg/m3 to support the weight of Dall sheep. Thus, sheep may require areas of shallow, fluffy snow for foraging, while relying on hard-packed snow for winter travel. These findings highlight the importance of multiple snowscape properties on wildlife movements and demography. The integrated study of snow properties and ecological processes, which we call snowscape ecology, will greatly improve global change forecasting.

Impacts of Synoptic Weather Patterns on Snow Albedo at Sites in New England

Science.gov (United States)

Adolph, A. C.; Albert, M. R.; Lazarcik, J.; Dibb, J. E.; Amante, J.; Price, A. N.

2015-12-01

Winter snow in the northeastern United States has changed over the last several decades, resulting in shallower snow packs, fewer days of snow cover and increasing precipitation falling as rain in the winter. In addition to these changes which cause reductions in surface albedo, increasing winter temperatures also lead to more rapid snow grain growth, resulting in decreased snow reflectivity. We present in-situ measurements and analyses to test the sensitivity of seasonal snow albedo to varying weather conditions at sites in New England. In particular, we investigate the impact of temperature on snow albedo through melt and grain growth, the impact of precipitation event frequency on albedo through snow "freshening," and the impact of storm path on snow structure and snow albedo. Over three winter seasons between 2013 and 2015, in-situ snow characterization measurements were made at three non-forested sites across New Hampshire. These near-daily measurements include spectrally resolved albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density and local meteorological parameters. Combining this information with storm tracks derived from HYSPLIT modeling, we quantify the current sensitivity of northeastern US snow albedo to temperature as well as precipitation type, frequency and path. Our analysis shows that southerly winter storms result in snow with a significantly lower albedo than storms which come from across the continental US or the Atlantic Ocean. Interannual variability in temperature and statewide spatial variability in snowfall rates at our sites show the relative importance of snowfall amount and temperatures in albedo evolution over the course of the winter.

Spatially explicit modeling of conflict zones between wildlife and snow sports: prioritizing areas for winter refuges.

Science.gov (United States)

Braunisch, Veronika; Patthey, Patrick; Arlettaz, Raphaël

2011-04-01

Outdoor winter recreation exerts an increasing pressure upon mountain ecosystems, with unpredictable, free-ranging activities (e.g., ski mountaineering, snowboarding, and snowshoeing) representing a major source of stress for wildlife. Mitigating anthropogenic disturbance requires the spatially explicit prediction of the interference between the activities of humans and wildlife. We applied spatial modeling to localize conflict zones between wintering Black Grouse (Tetrao tetrix), a declining species of Alpine timberline ecosystems, and two free-ranging winter sports (off-piste skiing [including snow-boarding] and snowshoeing). Track data (snow-sports and birds' traces) obtained from aerial photographs taken over a 585-km transect running along the timberline, implemented within a maximum entropy model, were used to predict the occurrence of snow sports and Black Grouse as a function of landscape characteristics. By modeling Black Grouse presence in the theoretical absence of free-ranging activities and ski infrastructure, we first estimated the amount of habitat reduction caused by these two factors. The models were then extrapolated to the altitudinal range occupied by Black Grouse, while the spatial extent and intensity of potential conflict were assessed by calculating the probability of human-wildlife co-occurrence. The two snow-sports showed different distribution patterns. Skiers' occurrence was mainly determined by ski-lift presence and a smooth terrain, while snowshoers' occurrence was linked to hiking or skiing routes and moderate slopes. Wintering Black Grouse avoided ski lifts and areas frequented by free-ranging snow sports. According to the models, Black Grouse have faced a substantial reduction of suitable wintering habitat along the timberline transect: 12% due to ski infrastructure and another 16% when adding free-ranging activities. Extrapolating the models over the whole study area results in an overall habitat loss due to ski infrastructure of

Summer warming and changes in snow depth is reflected in the growth rings of Alaskan tundra shrubs (Toolik Lake)

Science.gov (United States)

Buchwal, A.; Welker, J. M.

2016-12-01

Arctic change is being manifested by shifts in the vegetation composition and abundance throughout many regions of the Arctic. These changes are primarily reflected by increases in shrub growth and density, but the extent to which shrub growth is expressed in greater shrub ring width and the degree to which natural and experimental warming correspond and or whether the secondary effect of deeper snow in winter acts to alter shrub ring growh and or shrub biomass is yet to be determined for Arctic Alaska. In order to explore growth response of arctic shrubs to on-going and predicted temperature and snow depth increase we investigated shrubs' annual growth rings using dendrochronological methods applied to plants growing under control and experimental treatments in Toolik Lake, Northern Alaska. Specifically we evaluated the effects of a 20-year experimental warming (due to open top chambers, OTC's) and snow depth increases on the growth rings pattern of two common shrub species of Northern Alaska, i.e. Betula nana and Salix pulchra. By applying a serial sectioning method patterns of annual growth were investigated across the entire plant including below-ground parts. Moreover this procedure allowed for a complete cross-dating and a detection of irregular radial growth, including common missing and partially missing rings. We found that the natural warming in Alaska occurring over the past 20 years is stimulating shrub ring growth, more so for Betula than for Salix. Experimental warming (simulating conditions in approximately 2030) stimulated the secondary growth ratio; however the allocation pattern between below-ground and above-ground is quite variable between individual shrubs. In addition, annual growth rings analyses were supplemented by quantitative wood anatomy properties, such as vessel size and density. Our findings indicate that there can be differential growth ring responses of deciduous shrubs to natural climate warming, that growth ring increases reflect

The Critical Depth of Freeze-Thaw Soil under Different Types of Snow Cover

Directory of Open Access Journals (Sweden)

Qiang Fu

2017-05-01

Full Text Available Snow cover is the most common upper boundary condition influencing the soil freeze-thaw process in the black soil farming area of northern China. Snow is a porous dielectric cover, and its unique physical properties affect the soil moisture diffusion, heat conduction, freezing rate and other variables. To understand the spatial distribution of the soil water-heat and the variable characteristics of the critical depth of the soil water and heat, we used field data to analyze the freezing rate of soil and the extent of variation in soil water-heat in a unit soil layer under bare land (BL, natural snow (NS, compacted snow (CS and thick snow (TS treatments. The critical depth of the soil water and heat activity under different snow covers were determined based on the results of the analysis, and the variation fitting curve of the difference sequences on the soil temperature and water content between different soil layers and the surface 5-cm soil layer were used to verify the critical depth. The results were as follows: snow cover slowed the rate of soil freezing, and the soil freezing rate under the NS, CS and TS treatments decreased by 0.099 cm/day, 0.147 cm/day and 0.307 cm/day, respectively, compared with that under BL. In addition, the soil thawing time was delayed, and the effect was more significant with increased snow cover. During freeze-thaw cycles, the extent of variation in the water and heat time series in the shallow soil was relatively large, while there was less variation in the deep layer. There was a critical stratum in the vertical surface during hydrothermal migration, wherein the critical depth of soil water and heat change gradually increased with increasing snow cover. The variance in differences between the surface layer and both the soil water and heat in the different layers exhibited “steady-rising-steady” behavior, and the inflection point of the curve is the critical depth of soil freezing and thawing. This critical

Factors Impacting Spatial Patterns of Snow Distribution in a Small Catchment near Nome, AK

Science.gov (United States)

Chen, M.; Wilson, C. J.; Charsley-Groffman, L.; Busey, R.; Bolton, W. R.

2017-12-01

Snow cover plays an important role in the climate, hydrology and ecological systems of the Arctic due to its influence on the water balance, thermal regimes, vegetation and carbon flux. Thus, snow depth and coverage have been key components in all the earth system models but are often poorly represented for arctic regions, where fine scale snow distribution data is sparse. The snow data currently used in the models is at coarse resolution, which in turn leads to high uncertainty in model predictions. Through the DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic, high resolution snow distribution data is being developed and applied in catchment scale models to ultimately improve representation of snow and its interactions with other model components in the earth system models . To improve these models, it is important to identify key factors that control snow distribution and quantify the impacts of those factors on snow distribution. In this study, two intensive snow depth surveys (1 to 10 meters scale) were conducted for a 2.3 km2 catchment on the Teller road, near Nome, AK in the winter of 2016 and 2017. We used a statistical model to quantify the impacts of vegetation types, macro-topography, micro-topography, and meteorological parameters on measured snow depth. The results show that snow spatial distribution was similar between 2016 and 2017, snow depth was spatially auto correlated over small distance (2-5 meters), but not spatially auto correlated over larger distance (more than 2-5 meters). The coefficients of variation of snow depth was above 0.3 for all the snow survey transects (500-800 meters long). Variation of snow depth is governed by vegetation height, aspect, slope, surface curvature, elevation and wind speed and direction. We expect that this empirical statistical model can be used to estimate end of winter snow depth for the whole watershed and will further develop the model using data from other arctic regions to estimate

STUDY ON THE RETRIEVAL OF SNOW DEPTH FROM FY3B/MWRI IN THE ATCTIC

Directory of Open Access Journals (Sweden)

L. Li

2016-06-01

Full Text Available temperatures. Given the high albedo and low thermal conductivity, snow is regarded as one of the key reasons for the amplification of the warming in polar regions. The distributions of sea ice and snow depth are essential to the whole thermal conduction in the Arctic. This study focused on the retrieval of snow depth on sea ice from brightness temperatures of the MicroWave Radiometer Imager (MWRI onboard the FengYun (FY-3B satellite during the period from December 1, 2010 to April 30, 2011. After cross calibrated to the Advanced Microwave Scanning Radiometer–EOS (AMSR-E Level 2A data, the MWRI brightness temperatures were applied to calculate the sea ice concentrations based on the Arctic Radiation and Turbulence Interaction Study Sea Ice (ASI algorithm. According to the proportional relationship between the snow depth and the surface scattering in 18.7 and 36.5 GHz, the snow depths were derived. In order to eliminate the influence of uncertainties in grain sizes of snow as well as sporadic weather effects, the seven-day averaged snow depths were calculated. Then the results were compared with the snow depths from the AMSR-E Level 3 Sea Ice products. The bias of differences between the MWRI and the AMSR-E Level 3 products are ranged between −1.09 and −0.32 cm，while the standard deviations and the correlation coefficients are ranged from 2.47 to 2.88 cm and from 0.78 to 0.90 for different months. As a result, it could be summarized that FY3B/MWRI showed a promising prospect in retrieving snow depth on sea ice.

Slip resistance of winter footwear on snow and ice measured using maximum achievable incline.

Science.gov (United States)

Hsu, Jennifer; Shaw, Robert; Novak, Alison; Li, Yue; Ormerod, Marcus; Newton, Rita; Dutta, Tilak; Fernie, Geoff

2016-05-01

Protective footwear is necessary for preventing injurious slips and falls in winter conditions. Valid methods for assessing footwear slip resistance on winter surfaces are needed in order to evaluate footwear and outsole designs. The purpose of this study was to utilise a method of testing winter footwear that was ecologically valid in terms of involving actual human testers walking on realistic winter surfaces to produce objective measures of slip resistance. During the experiment, eight participants tested six styles of footwear on wet ice, on dry ice, and on dry ice after walking over soft snow. Slip resistance was measured by determining the maximum incline angles participants were able to walk up and down in each footwear-surface combination. The results indicated that testing on a variety of surfaces is necessary for establishing winter footwear performance and that standard mechanical bench tests for footwear slip resistance do not adequately reflect actual performance. Practitioner Summary: Existing standardised methods for measuring footwear slip resistance lack validation on winter surfaces. By determining the maximum inclines participants could walk up and down slopes of wet ice, dry ice, and ice with snow, in a range of footwear, an ecologically valid test for measuring winter footwear performance was established.

Winter warming as an important co-driver for Betula nana growth in western Greenland during the past century

DEFF Research Database (Denmark)

Hollesen, Jørgen; Buchwal, Agata; Rachlewicz, Grzegorz

2015-01-01

Growing season conditions are widely recognized as the main driver for tundra shrub radial growth, but the effects of winter warming and snow remain an open question. Here, we present a more than 100years long Betulanana ring-width chronology from Disko Island in western Greenland that demonstrates...... a highly significant and positive growth response to both summer and winter air temperatures during the past century. The importance of winter temperatures for Betulanana growth is especially pronounced during the periods from 1910-1930 to 1990-2011 that were dominated by significant winter warming....... Data also reveal a clear shift within the last 20years from a period with thick snow depths (1991-1996) and a positive effect on Betulanana radial growth, to a period (1997-2011) with generally very shallow snow depths and no significant growth response towards snow. During this period, winter...

The effect of snow/sea ice type on the response of albedo and light penetration depth (e-folding depth to increasing black carbon

Directory of Open Access Journals (Sweden)

A. A. Marks

2014-09-01

Full Text Available The optical properties of snow/sea ice vary with age and by the processes they were formed, giving characteristic types of snow and sea ice. The response of albedo and light penetration depth (e-folding depth to increasing mass ratio of black carbon is shown to depend on the snow and sea ice type and the thickness of the snow or sea ice. The response of albedo and e-folding depth of three different types of snow (cold polar snow, wind-packed snow and melting snow and three sea ice (multi-year ice, first-year ice and melting sea ice to increasing mass ratio of black carbon is calculated using a coupled atmosphere–snow/sea ice radiative-transfer model (TUV-snow, over the optical wavelengths of 300–800 nm. The snow and sea ice types are effectively defined by a scattering cross-section, density and asymmetry parameter. The relative change in albedo and e-folding depth of each of the three snow and three sea ice types with increasing mass ratio of black carbon is considered relative to a base case of 1 ng g−1 of black carbon. The relative response of each snow and sea ice type is intercompared to examine how different types of snow and sea ice respond relative to each other. The relative change in albedo of a melting snowpack is a factor of four more responsive to additions of black carbon compared to cold polar snow over a black carbon increase from 1 to 50 ng g−1, while the relative change in albedo of a melting sea ice is a factor of two more responsive to additions of black carbon compared to multi-year ice for the same increase in mass ratio of black carbon. The response of e-folding depth is effectively not dependent on snow/sea ice type. The albedo of sea ice is more responsive to increasing mass ratios of black carbon than snow.

Snowfall and Snow Depth for Canada 1943-1982

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Data include monthly snowfall and end-of-month snow depth for 140 stations across Canada. Stations that maintained at least 20 years of data were chosen. The...

Mapping snow depth in alpine terrain with remotely piloted aerial systems and structure-from-motion photogrammetry - first results from a pilot study

Science.gov (United States)

Adams, Marc; Fromm, Reinhard; Bühler, Yves; Bösch, Ruedi; Ginzler, Christian

2016-04-01

Detailed information on the spatio-temporal distribution of seasonal snow in the alpine terrain plays a major role for the hydrological cycle, natural hazard management, flora and fauna, as well as tourism. Current methods are mostly only valid on a regional scale or require a trade-off between the data's availability, cost and resolution. During a one-year pilot study, we investigated the potential of remotely piloted aerial systems (RPAS) and structure-from-motion photogrammetry for snow depth mapping. We employed multi-copter and fixed-wing RPAS, equipped with different low-cost, off-the shelf sensors, at four test sites in Austria and Switzerland. Over 30 flights were performed during the winter 2014/15, where different camera settings, filters and lenses, as well as data collection routines were tested. Orthophotos and digital surface models (DSM) where calculated from the imagery using structure-from-motion photogrammetry software. Snow height was derived by subtracting snow-free from snow-covered DSMs. The RPAS-results were validated against data collected using a variety of well-established remote sensing (i.e. terrestrial laser scanning, large frame aerial sensors) and in-situ measurement techniques. The results show, that RPAS i) are able to map snow depth within accuracies of 0.07-0.15 m root mean square error (RMSE), when compared to traditional in-situ data; ii) can be operated at lower cost, easier repeatability, less operational constraints and higher GSD than large frame aerial sensors on-board manned aircraft, while achieving significantly higher accuracies; iii) are able to acquire meaningful data even under harsh environmental conditions above 2000 m a.s.l. (turbulence, low temperature and high irradiance, low air density). While providing a first prove-of-concept, the study also showed future challenges and limitations of RPAS-based snow depth mapping, including a high dependency on correct co-registration of snow-free and snow-covered height

Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China

Directory of Open Access Journals (Sweden)

X. Huang

2016-10-01

Full Text Available By combining optical remote sensing snow cover products with passive microwave remote sensing snow depth (SD data, we produced a MODIS (Moderate Resolution Imaging Spectroradiometer cloudless binary snow cover product and a 500 m snow depth product. The temporal and spatial variations of snow cover from December 2000 to November 2014 in China were analyzed. The results indicate that, over the past 14 years, (1 the mean snow-covered area (SCA in China was 11.3 % annually and 27 % in the winter season, with the mean SCA decreasing in summer and winter seasons, increasing in spring and fall seasons, and not much change annually; (2 the snow-covered days (SCDs showed an increase in winter, spring, and fall, and annually, whereas they showed a decrease in summer; (3 the average SD decreased in winter, summer, and fall, while it increased in spring and annually; (4 the spatial distributions of SD and SCD were highly correlated seasonally and annually; and (5 the regional differences in the variation of snow cover in China were significant. Overall, the SCD and SD increased significantly in south and northeast China, and decreased significantly in the north of Xinjiang province. The SCD and SD increased on the southwest edge and in the southeast part of the Tibetan Plateau, whereas it decreased in the north and northwest regions.

Winter forest soil respiration controlled by climate and microbial community composition.

Science.gov (United States)

Monson, Russell K; Lipson, David L; Burns, Sean P; Turnipseed, Andrew A; Delany, Anthony C; Williams, Mark W; Schmidt, Steven K

2006-02-09

Most terrestrial carbon sequestration at mid-latitudes in the Northern Hemisphere occurs in seasonal, montane forest ecosystems. Winter respiratory carbon dioxide losses from these ecosystems are high, and over half of the carbon assimilated by photosynthesis in the summer can be lost the following winter. The amount of winter carbon dioxide loss is potentially susceptible to changes in the depth of the snowpack; a shallower snowpack has less insulation potential, causing colder soil temperatures and potentially lower soil respiration rates. Recent climate analyses have shown widespread declines in the winter snowpack of mountain ecosystems in the western USA and Europe that are coupled to positive temperature anomalies. Here we study the effect of changes in snow cover on soil carbon cycling within the context of natural climate variation. We use a six-year record of net ecosystem carbon dioxide exchange in a subalpine forest to show that years with a reduced winter snowpack are accompanied by significantly lower rates of soil respiration. Furthermore, we show that the cause of the high sensitivity of soil respiration rate to changes in snow depth is a unique soil microbial community that exhibits exponential growth and high rates of substrate utilization at the cold temperatures that exist beneath the snow. Our observations suggest that a warmer climate may change soil carbon sequestration rates in forest ecosystems owing to changes in the depth of the insulating snow cover.

Estimating water equivalent snow depth from related meteorological variables

International Nuclear Information System (INIS)

Steyaert, L.T.; LeDuc, S.K.; Strommen, N.D.; Nicodemus, M.L.; Guttman, N.B.

1980-05-01

Engineering design must take into consideration natural loads and stresses caused by meteorological elements, such as, wind, snow, precipitation and temperature. The purpose of this study was to determine a relationship of water equivalent snow depth measurements to meteorological variables. Several predictor models were evaluated for use in estimating water equivalent values. These models include linear regression, principal component regression, and non-linear regression models. Linear, non-linear and Scandanavian models are used to generate annual water equivalent estimates for approximately 1100 cooperative data stations where predictor variables are available, but which have no water equivalent measurements. These estimates are used to develop probability estimates of snow load for each station. Map analyses for 3 probability levels are presented

Independent evaluation of the SNODAS snow depth product using regional-scale lidar-derived measurements

Science.gov (United States)

Hedrick, A.; Marshall, H.-P.; Winstral, A.; Elder, K.; Yueh, S.; Cline, D.

2015-01-01

Repeated light detection and ranging (lidar) surveys are quickly becoming the de facto method for measuring spatial variability of montane snowpacks at high resolution. This study examines the potential of a 750 km2 lidar-derived data set of snow depths, collected during the 2007 northern Colorado Cold Lands Processes Experiment (CLPX-2), as a validation source for an operational hydrologic snow model. The SNOw Data Assimilation System (SNODAS) model framework, operated by the US National Weather Service, combines a physically based energy-and-mass-balance snow model with satellite, airborne and automated ground-based observations to provide daily estimates of snowpack properties at nominally 1 km resolution over the conterminous United States. Independent validation data are scarce due to the assimilating nature of SNODAS, compelling the need for an independent validation data set with substantial geographic coverage. Within 12 distinctive 500 × 500 m study areas located throughout the survey swath, ground crews performed approximately 600 manual snow depth measurements during each of the CLPX-2 lidar acquisitions. This supplied a data set for constraining the uncertainty of upscaled lidar estimates of snow depth at the 1 km SNODAS resolution, resulting in a root-mean-square difference of 13 cm. Upscaled lidar snow depths were then compared to the SNODAS estimates over the entire study area for the dates of the lidar flights. The remotely sensed snow depths provided a more spatially continuous comparison data set and agreed more closely to the model estimates than that of the in situ measurements alone. Finally, the results revealed three distinct areas where the differences between lidar observations and SNODAS estimates were most drastic, providing insight into the causal influences of natural processes on model uncertainty.

Simulating Snow in Canadian Boreal Environments with CLASS for ESM-SnowMIP

Science.gov (United States)

Wang, L.; Bartlett, P. A.; Derksen, C.; Ireson, A. M.; Essery, R.

2017-12-01

The ability of land surface schemes to provide realistic simulations of snow cover is necessary for accurate representation of energy and water balances in climate models. Historically, this has been particularly challenging in boreal forests, where poor treatment of both snow masking by forests and vegetation-snow interaction has resulted in biases in simulated albedo and snowpack properties, with subsequent effects on both regional temperatures and the snow albedo feedback in coupled simulations. The SnowMIP (Snow Model Intercomparison Project) series of experiments or `MIPs' was initiated in order to provide assessments of the performance of various snow- and land-surface-models at selected locations, in order to understand the primary factors affecting model performance. Here we present preliminary results of simulations conducted for the third such MIP, ESM-SnowMIP (Earth System Model - Snow Model Intercomparison Project), using the Canadian Land Surface Scheme (CLASS) at boreal forest sites in central Saskatchewan. We assess the ability of our latest model version (CLASS 3.6.2) to simulate observed snowpack properties (snow water equivalent, density and depth) and above-canopy albedo over 13 winters. We also examine the sensitivity of these simulations to climate forcing at local and regional scales.

The Impact Of Snow Melt On Surface Runoff Of Sava River In Slovenia

Science.gov (United States)

Horvat, A.; Brilly, M.; Vidmar, A.; Kobold, M.

2009-04-01

Snow is a type of precipitation in the form of crystalline water ice, consisting of a multitude of snowflakes that fall from clouds. Snow remains on the ground until it melts or sublimates. Spring snow melt is a major source of water supply to areas in temperate zones near mountains that catch and hold winter snow, especially those with a prolonged dry summer. In such places, water equivalent is of great interest to water managers wishing to predict spring runoff and the water supply of cities downstream. In temperate zone like in Slovenia the snow melts in the spring and contributes certain amount of water to surface flow. This amount of water can be great and can cause serious floods in case of fast snow melt. For this reason we tried to determine the influence of snow melt on the largest river basin in Slovenia - Sava River basin, on surface runoff. We would like to find out if snow melt in Slovenian Alps can cause spring floods and how serious it can be. First of all we studied the caracteristics of Sava River basin - geology, hydrology, clima, relief and snow conditions in details for each subbasin. Furtermore we focused on snow and described the snow phenomenom in Slovenia, detailed on Sava River basin. We collected all available data on snow - snow water equivalent and snow depth. Snow water equivalent is a much more useful measurement to hydrologists than snow depth, as the density of cool freshly fallen snow widely varies. New snow commonly has a density of between 5% and 15% of water. But unfortunately there is not a lot of available data of SWE available for Slovenia. Later on we compared the data of snow depth and river runoff for some of the 40 winter seasons. Finally we analyzed the use of satellite images for Slovenia to determine the snow cover for hydrology reason. We concluded that snow melt in Slovenia does not have a greater influence on Sava River flow. The snow cover in Alps can melt fast due to higher temperatures but the water distributes

Impact of intra- versus inter-annual snow depth variation on water relations and photosynthesis for two Great Basin Desert shrubs.

Science.gov (United States)

Loik, Michael E; Griffith, Alden B; Alpert, Holly; Concilio, Amy L; Wade, Catherine E; Martinson, Sharon J

2015-06-01

Snowfall provides the majority of soil water in certain ecosystems of North America. We tested the hypothesis that snow depth variation affects soil water content, which in turn drives water potential (Ψ) and photosynthesis, over 10 years for two widespread shrubs of the western USA. Stem Ψ (Ψ stem) and photosynthetic gas exchange [stomatal conductance to water vapor (g s), and CO2 assimilation (A)] were measured in mid-June each year from 2004 to 2013 for Artemisia tridentata var. vaseyana (Asteraceae) and Purshia tridentata (Rosaceae). Snow fences were used to create increased or decreased snow depth plots. Snow depth on +snow plots was about twice that of ambient plots in most years, and 20 % lower on -snow plots, consistent with several down-scaled climate model projections. Maximal soil water content at 40- and 100-cm depths was correlated with February snow depth. For both species, multivariate ANOVA (MANOVA) showed that Ψ stem, g s, and A were significantly affected by intra-annual variation in snow depth. Within years, MANOVA showed that only A was significantly affected by spatial snow depth treatments for A. tridentata, and Ψ stem was significantly affected by snow depth for P. tridentata. Results show that stem water relations and photosynthetic gas exchange for these two cold desert shrub species in mid-June were more affected by inter-annual variation in snow depth by comparison to within-year spatial variation in snow depth. The results highlight the potential importance of changes in inter-annual variation in snowfall for future shrub photosynthesis in the western Great Basin Desert.

Winter Arctic sea ice growth: current variability and projections for the coming decades

Science.gov (United States)

Petty, A.; Boisvert, L.; Webster, M.; Holland, M. M.; Bailey, D. A.; Kurtz, N. T.; Markus, T.

2017-12-01

Arctic sea ice increases in both extent and thickness during the cold winter months ( October to May). Winter sea ice growth is an important factor controlling ocean ventilation and winter water/deep water formation, as well as determining the state and vulnerability of the sea ice pack before the melt season begins. Key questions for the Arctic community thus include: (i) what is the current magnitude and variability of winter Arctic sea ice growth and (ii) how might this change in a warming Arctic climate? To address (i), our current best guess of pan-Arctic sea ice thickness, and thus volume, comes from satellite altimetry observations, e.g. from ESA's CryoSat-2 satellite. A significant source of uncertainty in these data come from poor knowledge of the overlying snow depth. Here we present new estimates of winter sea ice thickness from CryoSat-2 using snow depths from a simple snow model forced by reanalyses and satellite-derived ice drift estimates, combined with snow depth estimates from NASA's Operation IceBridge. To address (ii), we use data from the Community Earth System Model's Large Ensemble Project, to explore sea ice volume and growth variability, and how this variability might change over the coming decades. We compare and contrast the model simulations to observations and the PIOMAS ice-ocean model (over recent years/decades). The combination of model and observational analysis provide novel insight into Arctic sea ice volume variability.

Winter ecology of a subalpine grassland: Effects of snow removal on soil respiration, microbial structure and function.

Science.gov (United States)

Gavazov, Konstantin; Ingrisch, Johannes; Hasibeder, Roland; Mills, Robert T E; Buttler, Alexandre; Gleixner, Gerd; Pumpanen, Jukka; Bahn, Michael

2017-07-15

Seasonal snow cover provides essential insulation for mountain ecosystems, but expected changes in precipitation patterns and snow cover duration due to global warming can influence the activity of soil microbial communities. In turn, these changes have the potential to create new dynamics of soil organic matter cycling. To assess the effects of experimental snow removal and advanced spring conditions on soil carbon (C) and nitrogen (N) dynamics, and on the biomass and structure of soil microbial communities, we performed an in situ study in a subalpine grassland in the Austrian Alps, in conjunction with soil incubations under controlled conditions. We found substantial winter C-mineralisation and high accumulation of inorganic and organic N in the topsoil, peaking at snowmelt. Soil microbial biomass doubled under the snow, paralleled by a fivefold increase in its C:N ratio, but no apparent change in its bacteria-dominated community structure. Snow removal led to a series of mild freeze-thaw cycles, which had minor effects on in situ soil CO 2 production and N mineralisation. Incubated soil under advanced spring conditions, however, revealed an impaired microbial metabolism shortly after snow removal, characterised by a limited capacity for C-mineralisation of both fresh plant-derived substrates and existing soil organic matter (SOM), leading to reduced priming effects. This effect was transient and the observed recovery in microbial respiration and SOM priming towards the end of the winter season indicated microbial resilience to short-lived freeze-thaw disturbance under field conditions. Bacteria showed a higher potential for uptake of plant-derived C substrates during this recovery phase. The observed temporary loss in microbial C-mineralisation capacity and the promotion of bacteria over fungi can likely impede winter SOM cycling in mountain grasslands under recurrent winter climate change events, with plausible implications for soil nutrient availability and

Independent evaluation of the SNODAS snow depth product using regional scale LiDAR-derived measurements

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Hedrick, A.; Marshall, H.-P.; Winstral, A.; Elder, K.; Yueh, S.; Cline, D.

2014-06-01

Repeated Light Detection and Ranging (LiDAR) surveys are quickly becoming the de facto method for measuring spatial variability of montane snowpacks at high resolution. This study examines the potential of a 750 km2 LiDAR-derived dataset of snow depths, collected during the 2007 northern Colorado Cold Lands Processes Experiment (CLPX-2), as a validation source for an operational hydrologic snow model. The SNOw Data Assimilation System (SNODAS) model framework, operated by the US National Weather Service, combines a physically-based energy-and-mass-balance snow model with satellite, airborne and automated ground-based observations to provide daily estimates of snowpack properties at nominally 1 km resolution over the coterminous United States. Independent validation data is scarce due to the assimilating nature of SNODAS, compelling the need for an independent validation dataset with substantial geographic coverage. Within twelve distinctive 500 m × 500 m study areas located throughout the survey swath, ground crews performed approximately 600 manual snow depth measurements during each of the CLPX-2 LiDAR acquisitions. This supplied a dataset for constraining the uncertainty of upscaled LiDAR estimates of snow depth at the 1 km SNODAS resolution, resulting in a root-mean-square difference of 13 cm. Upscaled LiDAR snow depths were then compared to the SNODAS-estimates over the entire study area for the dates of the LiDAR flights. The remotely-sensed snow depths provided a more spatially continuous comparison dataset and agreed more closely to the model estimates than that of the in situ measurements alone. Finally, the results revealed three distinct areas where the differences between LiDAR observations and SNODAS estimates were most drastic, suggesting natural processes specific to these regions as causal influences on model uncertainty.

Application of the MODIS “snow cover” product for identification of the snow cover pattern in Gis-Baikal region

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E. A. Istomina

2014-01-01

Full Text Available Validation of remote sensing data MODIS «snow cover» in the period from September to May 2000/01, 2007/08, 2008/09 is realized on the base of weather stations data. Good repeatability of weather stations data and snow cover data is shown (more than 80% when snow depth is exceeds 2 cm. The minimum accuracy is in May and October for the variety of snowfall winters. Remote sensing data give possibility to extend the dot information of hydrometeorological stations network on the spatial snow distribution to the mountainous area of Predbajkalje where ground-based observations are absent. According to remote sensing earlier appearance and later melting of snow in mountain areas were identified. The plains and basins areas are characterized by later appearance and earlier melting of snow.

Effects of Planting of Calluna Vulgaris for Stable Snow Accumulation in Winter

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Ibuki, R.; Harada, K.

2017-12-01

Recent year climate of the winter season is changing and the period of snow accumulation is reduced compared with before. It affects the management of the ski resort. Snowfall had occurred in December 2016, but the snow accumulated after January 2017 at the ski resort located in the Pacific Ocean side of the Northeast region of Japan. This situation is thought to be originated from two reasons, one is snow thawing, another is to be blown away by the strong monsoon wind. We are considering utilizing planting to stabilize snow accumulation. Currently building rock gardens with shrubs, mainly Calluna Vulgaris in the ski resort for attracting customers in the summer. These are difficult to raise in the lowlands of Japan because they are too hot, but because of their good growth in relatively low-temperature highlands, it is rare for local residents to appreciate the value of these. In addition, it is excellent in low temperature resistance, and it will not die even under the snow. We investigated the pressure resistance performance due to snowfall and the appropriateness of growth under the weather conditions of the area. Regarding Calluna Vulgaris, Firefly, the plants were not damaged even under snow more than 1 m. In addition, three years have passed since planting, relatively good growth is shown, and the stock has been growing every year. Based on these results, we plan to stabilize the snow accumulation by carrying out planting of Calluna vulgaris inside the slope. The growth of the Calluna species is gentle and the tree height grows only about 50 cm even if 15 years have passed since planting. Therefore, it is considered that the plant body is hard to put out their head on the snow surface during the ski season. Next season will monitor the snow accumulation around the planting area through the snow season.

Climate Prediction Center (CPC) U.S. Daily Snow Depth Observations

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National Oceanic and Atmospheric Administration, Department of Commerce — Observational reports of current snow depth (at 1200 UTC) are made by members of the NWS Automated Surface Observing Systems (ASOS) network and NWS Cooperative...

Alpine snow cover in a changing climate: a regional climate model perspective

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Steger, Christian; Kotlarski, Sven; Jonas, Tobias; Schär, Christoph

2013-08-01

An analysis is presented of an ensemble of regional climate model (RCM) experiments from the ENSEMBLES project in terms of mean winter snow water equivalent (SWE), the seasonal evolution of snow cover, and the duration of the continuous snow cover season in the European Alps. Two sets of simulations are considered, one driven by GCMs assuming the SRES A1B greenhouse gas scenario for the period 1951-2099, and the other by the ERA-40 reanalysis for the recent past. The simulated SWE for Switzerland for the winters 1971-2000 is validated against an observational data set derived from daily snow depth measurements. Model validation shows that the RCMs are capable of simulating the general spatial and seasonal variability of Alpine snow cover, but generally underestimate snow at elevations below 1,000 m and overestimate snow above 1,500 m. Model biases in snow cover can partly be related to biases in the atmospheric forcing. The analysis of climate projections for the twenty first century reveals high inter-model agreement on the following points: The strongest relative reduction in winter mean SWE is found below 1,500 m, amounting to 40-80 % by mid century relative to 1971-2000 and depending upon the model considered. At these elevations, mean winter temperatures are close to the melting point. At higher elevations the decrease of mean winter SWE is less pronounced but still a robust feature. For instance, at elevations of 2,000-2,500 m, SWE reductions amount to 10-60 % by mid century and to 30-80 % by the end of the century. The duration of the continuous snow cover season shows an asymmetric reduction with strongest shortening in springtime when ablation is the dominant factor for changes in SWE. We also find a substantial ensemble-mean reduction of snow reliability relevant to winter tourism at elevations below about 1,800 m by mid century, and at elevations below about 2,000 m by the end of the century.

Sustainable Block Design Process for High-Rise and High-Density Districts with Snow and Wind Simulations for Winter Cities

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Norihiro Watanabe

2017-11-01

Full Text Available Urban designs that consider regional climatic conditions are one of the most important approaches for developing sustainable cities. In cities that suffer from heavy snow and cold winds in winter, an urban design approach different than that used for warm cities should be used. This study presents a scientific design process (the sustainable design approach that incorporates environmental and energy assessments that use snow and wind simulations to establish guidelines for the design of urban blocks in high-rise and high-density districts so that the impact of snow and wind can be minimized in these cities. A city block in downtown Sapporo, Japan, was used as a case study, and we evaluated four conceptual models. The four models were evaluated for how they impacted the snow and wind conditions in the block as well as the snow removal energy. Based on the results, we were able to identify the design guidelines in downtown Sapporo: an urban block design with higher building height ratio without the mid-rise part can reduce the snowdrifts and lower the snow removal energy. The proposed sustainable urban design approach would be effective in improving the quality of public spaces and reducing snow removal energy in winter cities.

Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data, Version 1

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National Aeronautics and Space Administration — This data set consists of a Northern Hemisphere subset of the Canadian Meteorological Centre (CMC) operational global daily snow depth analysis. Data include daily...

High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

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Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

2017-12-01

Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential

From drones to ASO: Using 'Structure-From-Motion' photogrammetry to quantify variations in snow depth at multiple scales

Science.gov (United States)

Skiles, M.

2017-12-01

The ability to accurately measure and manage the natural snow water reservoir in mountainous regions has its challenges, namely mapping of snowpack depth and snow water equivalent (SWE). Presented here is a scalable method that differentially maps snow depth using Structure from Motion (SfM); a photogrammetric technique that uses 2d images to create a 3D model/Digital Surface Model (DSM). There are challenges with applying SfM to snow, namely, relatively uniform snow brightness can make it difficult to produce quality images needed for processing, and vegetation can limit the ability to `see' through the canopy to map both the ground and snow beneath. New techniques implemented in the method to adapt to these challenges will be demonstrated. Results include a time series at (1) the plot scale, imaged with an unmanned areal vehicle (DJI Phantom 2 adapted with Sony A5100) over the Utah Department of Transportation Atwater Study Plot in Little Cottonwood Canyon, UT, and at (2) the mountain watershed scale, imaged from the RGB camera aboard the Airborne Snow Observatory (ASO), over the headwaters of the Uncompahgre River in the San Juan Mountains, CO. At the plot scale we present comparisons to measured snow depth, and at the watershed scale we present comparisons to the ASO lidar DSM. This method is of interest due to its low cost relative to lidar, making it an accessible tool for snow research and the management of water resources. With advancing unmanned aerial vehicle technology there are implications for scalability to map snow depth, and SWE, across large basins.

Analyses of newly digitised and reconstructed snow series over the last 100+ years in Switzerland

Science.gov (United States)

Scherrer, S. C.; Wüthrich, C.; Croci-Maspoli, M.; Appenzeller, C.

2010-09-01

Snow is an important socio-economic factor in the Swiss Alpine region (tourism, hydro-electricity, drinking water) and responsible for considerable natural hazards such as avalanches. In addition, high-quality long-term snow series can be used as an excellent indicator of climate change. The objectives of this study are threefold. First, suitable long-term snow series from different altitudes and regions in Switzerland have been selected, missing data digitized and the entire series quality checked. Second, the long-term snow series have been used for trend analyses over a time period >100 years. Third, snow depth series have been reconstructed using daily new snow, temperature and precipitation as input variables. This made it possible to analyse snow depth related variables such as days with snow pack. Results show that the snow cover is varying substantially on seasonal and decadal time scales. The analyses of the decadal new snow trends during the last 100 years shows unprecedented low new snow sums in the winter seasons (DJF) of the 1990s. The 100 year trend of days with snow pack reveals a significant decrease for stations below 800 m asl in the winter season (DJF) and for stations around 1800 m asl in spring (MAM). Similar results were found for seasonal new snow sums. The results of the trend analyses are also discussed with respect to temperature and precipitation trends. Finally we will also shortly discuss how especially "precious" snow measurements have been identified and incorporated in a National Basic Climatological Network (NBCN) as well as in the Global Climate Observing System (GCOS).

Climate change in winter versus the growing-season leads to different effects on soil microbial activity in northern hardwood forests

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Sorensen, P. O.; Templer, P. H.; Finzi, A.

2014-12-01

Mean winter air temperatures have risen by approximately 2.5˚ C per decade over the last fifty years in the northeastern U.S., reducing the maximum depth of winter snowpack by approximately 26 cm over this period and the duration of winter snow cover by 3.6 to 4.2 days per decade. Forest soils in this region are projected to experience a greater number of freeze-thaw cycles and lower minimum winter soil temperatures as the depth and duration of winter snow cover declines in the next century. Climate change is likely to result not only in lower soil temperatures during winter, but also higher soil temperatures during the growing-season. We conducted two complementary experiments to determine how colder soils in winter and warmer soils in the growing-season affect microbial activity in hardwood forests at Harvard Forest, MA and Hubbard Brook Experimental Forest, NH. A combination of removing snow via shoveling and buried heating cables were used to induce freeze-thaw events during winter and to warm soils 5˚C above ambient temperatures during the growing-season. Increasing the depth and duration of soil frost via snow-removal resulted in short-term reductions in soil nitrogen (N) production via microbial proteolytic enzyme activity and net N mineralization following snowmelt, prior to tree leaf-out. Declining mass specific rates of carbon (C) and N mineralization associated with five years of snow removal at Hubbard Brook Experimental Forest may be an indication of microbial physiological adaptation to winter climate change. Freeze-thaw cycles during winter reduced microbial extracellular enzyme activity and the temperature sensitivity of microbial C and N mineralization during the growing-season, potentially offsetting nutrient and soil C losses due to soil warming in the growing-season. Our multiple experimental approaches show that winter climate change is likely to contribute to reduced microbial activity in northern hardwood forests.

Validation of MODIS snow cover images over Austria

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J. Parajka

2006-01-01

Full Text Available This study evaluates the Moderate Resolution Imaging Spectroradiometer (MODIS snow cover product over the territory of Austria. The aims are (a to analyse the spatial and temporal variability of the MODIS snow product classes, (b to examine the accuracy of the MODIS snow product against in situ snow depth data, and (c to identify the main factors that may influence the MODIS classification accuracy. We use daily MODIS grid maps (version 4 and daily snow depth measurements at 754 climate stations in the period from February 2000 to December 2005. The results indicate that, on average, clouds obscured 63% of Austria, which may significantly restrict the applicability of the MODIS snow cover images to hydrological modelling. On cloud-free days, however, the classification accuracy is very good with an average of 95%. There is no consistent relationship between the classification errors and dominant land cover type and local topographical variability but there are clear seasonal patterns to the errors. In December and January the errors are around 15% while in summer they are less than 1%. This seasonal pattern is related to the overall percentage of snow cover in Austria, although in spring, when there is a well developed snow pack, errors tend to be smaller than they are in early winter for the same overall percent snow cover. Overestimation and underestimation errors balance during most of the year which indicates little bias. In November and December, however, there appears to exist a tendency for overestimation. Part of the errors may be related to the temporal shift between the in situ snow depth measurements (07:00 a.m. and the MODIS acquisition time (early afternoon. The comparison of daily air temperature maps with MODIS snow cover images indicates that almost all MODIS overestimation errors are caused by the misclassification of cirrus clouds as snow.

The Snow Must Go On: Ground Ice Encasement, Snow Compaction and Absence of Snow Differently Cause Soil Hypoxia, CO2 Accumulation and Tree Seedling Damage in Boreal Forest.

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Martz, Françoise; Vuosku, Jaana; Ovaskainen, Anu; Stark, Sari; Rautio, Pasi

2016-01-01

At high latitudes, the climate has warmed at twice the rate of the global average with most changes observed in autumn, winter and spring. Increasing winter temperatures and wide temperature fluctuations are leading to more frequent rain-on-snow events and freeze-thaw cycles causing snow compaction and formation of ice layers in the snowpack, thus creating ice encasement (IE). By decreasing the snowpack insulation capacity and restricting soil-atmosphere gas exchange, modification of the snow properties may lead to colder soil but also to hypoxia and accumulation of trace gases in the subnivean environment. To test the effects of these overwintering conditions changes on plant winter survival and growth, we established a snow manipulation experiment in a coniferous forest in Northern Finland with Norway spruce and Scots pine seedlings. In addition to ambient conditions and prevention of IE, we applied three snow manipulation levels: IE created by artificial rain-on-snow events, snow compaction and complete snow removal. Snow removal led to deeper soil frost during winter, but no clear effect of IE or snow compaction done in early winter was observed on soil temperature. Hypoxia and accumulation of CO2 were highest in the IE plots but, more importantly, the duration of CO2 concentration above 5% was 17 days in IE plots compared to 0 days in ambient plots. IE was the most damaging winter condition for both species, decreasing the proportion of healthy seedlings by 47% for spruce and 76% for pine compared to ambient conditions. Seedlings in all three treatments tended to grow less than seedlings in ambient conditions but only IE had a significant effect on spruce growth. Our results demonstrate a negative impact of winter climate change on boreal forest regeneration and productivity. Changing snow conditions may thus partially mitigate the positive effect of increasing growing season temperatures on boreal forest productivity.

Linking Changes in Snow Cover with Nitrogen Cycling and Microbial Abundance and Functional Gene Expression in Agricultural Soils

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Goyer, C.; Brin, L.; Zebarth, B.; Burton, D.; Wertz, S.; Chantigny, M.

2016-12-01

In eastern Canada, climate change-related warming and increased precipitation may alter winter snow cover, with potential consequences for soil conditions, microbes, and N2O fluxes. We conducted a two-year field study with snow removal, passive snow addition, and ambient treatments in a potato-barley crop system. We measured in situ greenhouse gas (N2O and CO2) fluxes and belowground gas accumulation, and quantified abundance and expression of denitrifier (nirS, nirK, nosZ) and nitrifier (ammonium oxidizing archaeal (AOA) and bacterial (AOB) amoA) genes. Soil gas accumulated throughout winter, and surface fluxes were greatest during spring thaw. Greatest mid-winter soil N2O accumulation and spring thaw N2O fluxes were associated with snow removal in winter 1 and ambient snow in winter 2. High N2O accumulation and fluxes may have been due to increased substrate availability with increased frost intensity in removal plots in winter 1, but with greatest water content in ambient plots in winter 2. In each winter, greatest abundances of nirS, nirK gene denitrifiers and/or amoA gene of AOA were observed in the treatments with the greatest N2O accumulation and fluxes. Gene expression did not vary with treatment, but highest expression of amoA gene of AOA and AOB, and nosZ gene was measured near 0ºC, indicating activity during periods of stable snow cover and spring thaw. Results suggest that the magnitude of fluxes during spring thaw were related to soil conditions and microbial communities present during the prior winter, and not solely those during thaw. Furthermore, the effects of changing snow cover on microbes and N2O fluxes were not a straightforward effect of snow depth, but were likely mediated by temperature and moisture.

Winter warming as an important co-driver for Betula nana growth in western Greenland during the past century.

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Hollesen, Jørgen; Buchwal, Agata; Rachlewicz, Grzegorz; Hansen, Birger U; Hansen, Marc O; Stecher, Ole; Elberling, Bo

2015-06-01

Growing season conditions are widely recognized as the main driver for tundra shrub radial growth, but the effects of winter warming and snow remain an open question. Here, we present a more than 100 years long Betula nana ring-width chronology from Disko Island in western Greenland that demonstrates a highly significant and positive growth response to both summer and winter air temperatures during the past century. The importance of winter temperatures for Betula nana growth is especially pronounced during the periods from 1910-1930 to 1990-2011 that were dominated by significant winter warming. To explain the strong winter importance on growth, we assessed the importance of different environmental factors using site-specific measurements from 1991 to 2011 of soil temperatures, sea ice coverage, precipitation and snow depths. The results show a strong positive growth response to the amount of thawing and growing degree-days as well as to winter and spring soil temperatures. In addition to these direct effects, a strong negative growth response to sea ice extent was identified, indicating a possible link between local sea ice conditions, local climate variations and Betula nana growth rates. Data also reveal a clear shift within the last 20 years from a period with thick snow depths (1991-1996) and a positive effect on Betula nana radial growth, to a period (1997-2011) with generally very shallow snow depths and no significant growth response towards snow. During this period, winter and spring soil temperatures have increased significantly suggesting that the most recent increase in Betula nana radial growth is primarily triggered by warmer winter and spring air temperatures causing earlier snowmelt that allows the soils to drain and warm quicker. The presented results may help to explain the recently observed 'greening of the Arctic' which may further accelerate in future years due to both direct and indirect effects of winter warming. © 2015 John Wiley & Sons

A novel approach for automatic snow depth estimation using UAV-taken images without ground control points

Science.gov (United States)

Mizinski, Bartlomiej; Niedzielski, Tomasz

2017-04-01

Recent developments in snow depth reconstruction based on remote sensing techniques include the use of photographs of snow-covered terrain taken by unmanned aerial vehicles (UAVs). There are several approaches that utilize visible-light photos (RGB) or near infrared images (NIR). The majority of the methods in question are based on reconstructing the digital surface model (DSM) of the snow-covered area with the use of the Structure-from-Motion (SfM) algorithm and the stereo-vision software. Having reconstructed the above-mentioned DSM it is straightforward to calculate the snow depth map which may be produced as a difference between the DSM of snow-covered terrain and the snow-free DSM, known as the reference surface. In order to use the aforementioned procedure, the high spatial accuracy of the two DSMs must be ensured. Traditionally, this is done using the ground control points (GCPs), either artificial or natural terrain features that are visible on aerial images, the coordinates of which are measured in the field using the Global Navigation Satellite System (GNSS) receiver by qualified personnel. The field measurements may be time-taking (GCPs must be well distributed in the study area, therefore the field experts should travel over long distances) and dangerous (the field experts may be exposed to avalanche risk or cold). Thus, there is a need to elaborate methods that enable the above-mentioned automatic snow depth map production without the use of GCPs. One of such attempts is shown in this paper which aims to present the novel method which is based on real-time processing of snow-covered and snow-free dense point clouds produced by SfM. The two stage georeferencing is proposed. The initial (low accuracy) one assigns true geographic, and subsequently projected, coordinates to the two dense point clouds, while the said initially-registered dense point clouds are matched using the iterative closest point (ICP) algorithm in the final (high accuracy) stage. The

Retrospective forecasts of the upcoming winter season snow accumulation in the Inn headwaters (European Alps)

Science.gov (United States)

Förster, Kristian; Hanzer, Florian; Stoll, Elena; Scaife, Adam A.; MacLachlan, Craig; Schöber, Johannes; Huttenlau, Matthias; Achleitner, Stefan; Strasser, Ulrich

2018-02-01

This article presents analyses of retrospective seasonal forecasts of snow accumulation. Re-forecasts with 4 months' lead time from two coupled atmosphere-ocean general circulation models (NCEP CFSv2 and MetOffice GloSea5) drive the Alpine Water balance and Runoff Estimation model (AWARE) in order to predict mid-winter snow accumulation in the Inn headwaters. As snowpack is hydrological storage that evolves during the winter season, it is strongly dependent on precipitation totals of the previous months. Climate model (CM) predictions of precipitation totals integrated from November to February (NDJF) compare reasonably well with observations. Even though predictions for precipitation may not be significantly more skilful than for temperature, the predictive skill achieved for precipitation is retained in subsequent water balance simulations when snow water equivalent (SWE) in February is considered. Given the AWARE simulations driven by observed meteorological fields as a benchmark for SWE analyses, the correlation achieved using GloSea5-AWARE SWE predictions is r = 0.57. The tendency of SWE anomalies (i.e. the sign of anomalies) is correctly predicted in 11 of 13 years. For CFSv2-AWARE, the corresponding values are r = 0.28 and 7 of 13 years. The results suggest that some seasonal prediction of hydrological model storage tendencies in parts of Europe is possible.

Intercomparison and validation of snow albedo parameterization schemes in climate models

Energy Technology Data Exchange (ETDEWEB)

Pedersen, Christina A.; Winther, Jan-Gunnar [Norwegian Polar Institute, Tromsoe (Norway)

2005-09-01

Snow albedo is known to be crucial for heat exchange at high latitudes and high altitudes, and is also an important parameter in General Circulation Models (GCMs) because of its strong positive feedback properties. In this study, seven GCM snow albedo schemes and a multiple linear regression model were intercompared and validated against 59 years of in situ data from Svalbard, the French Alps and six stations in the former Soviet Union. For each site, the significant meteorological parameters for modeling the snow albedo were identified by constructing the 95% confidence intervals. The significant parameters were found to be: temperature, snow depth, positive degree day and a dummy of snow depth, and the multiple linear regression model was constructed to include these. Overall, the intercomparison showed that the modeled snow albedo varied more than the observed albedo for all models, and that the albedo was often underestimated. In addition, for several of the models, the snow albedo decreased at a faster rate or by a greater magnitude during the winter snow metamorphosis than the observed albedo. Both the temperature dependent schemes and the prognostic schemes showed shortcomings. (orig.)

Application of Low-Cost UASs and Digital Photogrammetry for High-Resolution Snow Depth Mapping in the Arctic

Directory of Open Access Journals (Sweden)

Emiliano Cimoli

2017-11-01

Full Text Available The repeat acquisition of high-resolution snow depth measurements has important research and civil applications in the Arctic. Currently the surveying methods for capturing the high spatial and temporal variability of the snowpack are expensive, in particular for small areal extents. An alternative methodology based on Unmanned Aerial Systems (UASs and digital photogrammetry was tested over varying surveying conditions in the Arctic employing two diverse and low-cost UAS-camera combinations (500 and 1700 USD, respectively. Six areas, two in Svalbard and four in Greenland, were mapped covering from 1386 to 38,410 m2. The sites presented diverse snow surface types, underlying topography and light conditions in order to test the method under potentially limiting conditions. The resulting snow depth maps achieved spatial resolutions between 0.06 and 0.09 m. The average difference between UAS-estimated and measured snow depth, checked with conventional snow probing, ranged from 0.015 to 0.16 m. The impact of image pre-processing was explored, improving point cloud density and accuracy for different image qualities and snow/light conditions. Our UAS photogrammetry results are expected to be scalable to larger areal extents. While further validation is needed, with the inclusion of extra validation points, the study showcases the potential of this cost-effective methodology for high-resolution monitoring of snow dynamics in the Arctic and beyond.

Topographic, meteorologic, and canopy controls on the scaling characteristics of the spatial distribution of snow depth fields

Science.gov (United States)

Ernesto Trujillo; Jorge A. Ramirez; Kelly J. Elder

2007-01-01

In this study, LIDAR snow depths, bare ground elevations (topography), and elevations filtered to the top of vegetation (topography + vegetation) in five 1-km2 areas are used to determine whether the spatial distribution of snow depth exhibits scale invariance, and the control that vegetation, topography, and winds exert on such behavior. The one-dimensional and mean...

Validation and Algorithms Comparative Study for Microwave Remote Sensing of Snow Depth over China

International Nuclear Information System (INIS)

Bin, C J; Qiu, Y B; Shi, L J

2014-01-01

In this study, five different snow algorithms (Chang algorithm, GSFC 96 algorithm, AMSR-E SWE algorithm, Improved Tibetan Plateau algorithm and Savoie algorithm) were selected to validate the accuracy of snow algorithms over China. These algorithms were compared for the accuracy of snow depth algorithms with AMSR-E brightness temperature data and ground measurements on February 10-12, 2010. Results showed that the GSFC 96 algorithm was more suitable in Xinjiang with the RMSE range from 6.85cm to 7.48 cm; in Inner Mongolia and Northeast China. Improved Tibetan Plateau algorithm is superior to the other four algorithms with the RMSE of 5.46cm∼6.11cm and 6.21cm∼7.83cm respectively; due to the lack of ground measurements, we couldn't get valid statistical results over the Tibetan Plateau. However, the mean relative error (MRE) of the selected algorithms was ranging from 37.95% to 189.13% in four study areas, which showed that the accuracy of the five snow depth algorithms is limited over China

Improving the Terrain-Based Parameter for the Assessment of Snow Redistribution in the Col du Lac Blanc Area and Comparisons with TLS Snow Depth Data

Science.gov (United States)

Schön, Peter; Prokop, Alexander; Naaim-Bouvet, Florence; Nishimura, Kouichi; Vionnet, Vincent; Guyomarc'h, Gilbert

2014-05-01

Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns, but has failed to quantitatively describe the snow redistribution, and correlations with measured snow heights were poor. The objective of our research was to a) identify the sources of poor correlations between predicted and measured snow re-distribution and b) improve the parameters ability to qualitatively and quantitatively describe snow redistribution in our research area, the Col du Lac Blanc in the French Alps. The area is at an elevation of 2700 m and particularly suited for our study due to its constant wind direction and the availability of data from a meteorological station. Our work focused on areas with terrain edges of approximately 10 m height, and we worked with 1-2 m resolution digital terrain and snow surface data. We first compared the results of the terrain-based parameter calculations to measured snow-depths, obtained by high-accuracy terrestrial laser scan measurements. The results were similar to previous studies: The parameter was able to reproduce observed patterns in snow distribution, but regression analyses showed poor correlations between terrain-based parameter and measured snow-depths. We demonstrate how the correlations between measured and calculated snow heights improve if the parameter is calculated based on a snow surface model instead of a digital terrain model. We show how changing the parameter's search distance and how raster re-sampling and raster smoothing improve the results. To improve the parameter

Relationship between snow depth and gray wolf predation on white-tailed deer

Science.gov (United States)

Nelson, M.E.; Mech, L.D.

1986-01-01

Survival of 203 yearling and adult white-tailed deer (Odocoileus virginianus) was monitored for 23,441 deer days from January through April 1975-85 in northeastern Minnesota. Gray wolf (Canis lupus) predation was the primary mortality cause, and from year to year during this period, the mean predation rate ranged from 0.00 to 0.29. The sum of weekly snow depths/month explained 51% of the variation in annual wolf predation rate, with the highest predation during the deepest snow.

The Impacts of Pine Tree Die-Off on Snow Accumulation and Distribution at Plot to Catchment Scales

Science.gov (United States)

Biederman, J. A.; Harpold, A. A.; Gutmann, E. D.; Reed, D. E.; Gochis, D. J.; Brooks, P. D.

2011-12-01

Seasonal snow cover is a primary water source throughout much of Western North America, where insect-induced tree die-off is changing the montane landscape. Widespread mortality from insects or drought differs from well-studied cases of fire and logging in that tree mortality is not accompanied by other immediate biophysical changes. Much of the impacted landscape is a mosaic of stands of varying species, structure, management history and health overlain on complex terrain. To address the challenge of predicting the effects of forest die-off on snow water input, we quantified snow accumulation and ablation at scales ranging from individual trees, through forest stands, to nested small catchments. Our study sites in Northern Colorado and Southern Wyoming are dominated by lodgepole pine, but they include forest stands that are naturally developed, managed and clear-cut with varying mortality from Mountain Pine Beetle (MPB). Our record for winters 2010 and 2011 includes continuous meteorological data and snow depth in plots with varying MPB impact as well as stand- to catchment-scale snow surveys mid-winter and near maximal accumulation. At the plot scale, snow depth sensors in healthy stands recorded greater inputs during storms (21-42% of depth) and greater seasonal accumulation (15-40%) in canopy gaps than under trees, whereas no spatial effects of canopy geometry were observed in stands with heavy mortality. Similar patterns were observed in snow surveys near peak accumulation. At both impacted and thinned sites, spatial variability in snow depth was more closely associated with larger scale topography and changes in stand structure than with canopy cover. The role of aspect in ablation was observed to increase in impacted stands as both shading and wind attenuation decreased. Evidence of wind-controlled snow distribution was found 80-100 meters from exposed stand edges in impacted forest as compared to 10-15 meters in healthy forest. Integrating from the scale of

Changes in snow cover over Northern Eurasia in the last few decades

International Nuclear Information System (INIS)

Bulygina, O N; Razuvaev, V N; Korshunova, N N

2009-01-01

Daily snow depth (SD) and snow cover extent around 820 stations are used to analyse variations in snow cover characteristics in Northern Eurasia, a region that encompasses the Russian Federation. These analyses employ nearly five times more stations than in the previous studies and temporally span forty years. A representative judgement on the changes of snow depth over most of Russia is presented here for the first time. The number of days with greater than 50% of the near-station territory covered with snow, and the number of days with the snow depth greater than 1.0 cm, are used to characterize the duration of snow cover (SCD) season. Linear trends of the number of days and snow depth are calculated for each station from 1966 to 2007. This investigation reveals regional features in the change of snow cover characteristics. A decrease in the duration of snow cover is demonstrated in the northern regions of European Russia and in the mountainous regions of southern Siberia. An increase in SCD is found in Yakutia and in the Far East. In the western half of the Russian Federation, the winter-averaged SD is shown to increase, with the maximum trends being observed in Northern West Siberia. In contrast, in the mountainous regions of southern Siberia, the maximum SD decreases as the SCD decreases. While both snow cover characteristics (SCD and SD) play an important role in the hydrological cycle, ecosystems dynamics and societal wellbeing are quite different roles and the differences in their systematic changes (up to differences in the signs of changes) deserve further attention.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Snow Cover/Depth (SCD) Snow Fraction Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Snow Cover/Depth Fraction (SCF) from the Visible Infrared Imaging Radiometer...

Impact of climate change in Switzerland on socioeconomic snow indices

Science.gov (United States)

Schmucki, Edgar; Marty, Christoph; Fierz, Charles; Weingartner, Rolf; Lehning, Michael

2017-02-01

Snow is a key element for many socioeconomic activities in mountainous regions. Due to the sensitivity of the snow cover to variations of temperature and precipitation, major changes caused by climate change are expected to happen. We analyze the evolution of some key snow indices under future climatic conditions. Ten downscaled and postprocessed climate scenarios from the ENSEMBLES database have been used to feed the physics-based snow model SNOWPACK. The projected snow cover has been calculated for 11 stations representing the diverse climates found in Switzerland. For the first time, such a setup is used to reveal changes in frequently applied snow indices and their implications on various socioeconomic sectors. Toward the end of the twenty-first century, a continuous snow cover is likely only guaranteed at high elevations above 2000 m a.s.l., whereas at mid elevations (1000-1700 m a.s.l.), roughly 50 % of all winters might be characterized by an ephemeral snow cover. Low elevations (below 500 m a.s.l.) are projected to experience only 2 days with snowfall per year and show the strongest relative reductions in mean winter snow depth of around 90 %. The range of the mean relative reductions of the snow indices is dominated by uncertainties from different GCM-RCM projections and amounts to approximately 30 %. Despite these uncertainties, all snow indices show a clear decrease in all scenario periods and the relative reductions increase toward lower elevations. These strong reductions can serve as a basis for policy makers in the fields of tourism, ecology, and hydropower.

Optimizing winter/snow removal operations in MoDOT St. Louis district : includes outcome based evaluation of operations.

Science.gov (United States)

2011-10-01

The objective of this project was to develop fleet location, route decision, material selection, and treatment procedures for winter snow removal operations to improve MoDOTs services and lower costs. This work uses a systematic, heuristic-based o...

IOD influence on the early winter tibetan plateau snow cover: diagnostic analyses and an AGCM simulation

Energy Technology Data Exchange (ETDEWEB)

Yuan, Chaoxia; Tozuka, Tomoki; Yamagata, Toshio [The University of Tokyo, Department of Earth and Planetary Science, Graduate School of Science, Tokyo (Japan)

2012-10-15

Using diagnostic analyses and an AGCM simulation, the detailed mechanism of Indian Ocean Dipole (IOD) influence on the early winter Tibetan Plateau snow cover (EWTPSC) is clarified. In early winter of pure positive IOD years with no co-occurrence of El Nino, the anomalous dipole diabatic heating over the tropical Indian Ocean excites the baroclinic response in the tropics. Since both baroclinic and barotropic components of the basic zonal wind over the Arabian Peninsula increase dramatically in early winter due to the equatorward retreat of the westerly jet, the baroclinic mode excites the barotropic Rossby wave that propagates northeastward and induces a barotropic cyclonic anomaly north of India. This enables the moisture transport cyclonically from the northern Indian Ocean toward the Tibetan Plateau. The convergence of moisture over the plateau explains the positive influence of IOD on the EWTPSC. In contrast, the basic zonal wind over the Arabian Peninsula is weak in autumn. This is not favorable for excitation of the barotropic Rossby wave and teleconnection, even though the IOD-related diabatic heating anomaly in autumn similar to that in early winter exists. This result explains the insignificant (significant positive) partial correlation between IOD and the autumn (early winter) Tibetan Plateau snow cover after excluding the influence of ENSO. The sensitivity experiment forced by the IOD-related SST anomaly within the tropical Indian Ocean well reproduces the baroclinic response in the tropics, the teleconnection from the Arabian Peninsula, and the increased moisture supply to the Tibetan Plateau. Also, the seasonality of the atmospheric response to the IOD is simulated. (orig.)

On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data

Science.gov (United States)

Zhou, Lu; Xu, Shiming; Liu, Jiping; Wang, Bin

2018-03-01

The accurate knowledge of sea ice parameters, including sea ice thickness and snow depth over the sea ice cover, is key to both climate studies and data assimilation in operational forecasts. Large-scale active and passive remote sensing is the basis for the estimation of these parameters. In traditional altimetry or the retrieval of snow depth with passive microwave remote sensing, although the sea ice thickness and the snow depth are closely related, the retrieval of one parameter is usually carried out under assumptions over the other. For example, climatological snow depth data or as derived from reanalyses contain large or unconstrained uncertainty, which result in large uncertainty in the derived sea ice thickness and volume. In this study, we explore the potential of combined retrieval of both sea ice thickness and snow depth using the concurrent active altimetry and passive microwave remote sensing of the sea ice cover. Specifically, laser altimetry and L-band passive remote sensing data are combined using two forward models: the L-band radiation model and the isostatic relationship based on buoyancy model. Since the laser altimetry usually features much higher spatial resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS) satellite, there is potentially covariability between the observed snow freeboard by altimetry and the retrieval target of snow depth on the spatial scale of altimetry samples. Statistically significant correlation is discovered based on high-resolution observations from Operation IceBridge (OIB), and with a nonlinear fitting the covariability is incorporated in the retrieval algorithm. By using fitting parameters derived from large-scale surveys, the retrievability is greatly improved compared with the retrieval that assumes flat snow cover (i.e., no covariability). Verifications with OIB data show good match between the observed and the retrieved parameters, including both sea ice thickness and snow depth. With

Spatial and temporal variability in seasonal snow density

KAUST Repository

Bormann, Kathryn J.

2013-03-01

Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

Spatial and temporal variability in seasonal snow density

KAUST Repository

Bormann, Kathryn J.; Westra, Seth; Evans, Jason P.; McCabe, Matthew

2013-01-01

Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

A snow cover climatology for the Pyrenees from MODIS snow products

Science.gov (United States)

Gascoin, S.; Hagolle, O.; Huc, M.; Jarlan, L.; Dejoux, J.-F.; Szczypta, C.; Marti, R.; Sanchez, R.

2015-05-01

The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (w.e.) and 150 mm, respectively, for both MOD10A1 and MYD10A1. κ coefficients are within 0.74 and 0.92 depending on the product and the variable for these thresholds. However, we also find a seasonal trend in the optimal SWE and SD thresholds, reflecting the hysteresis in the relationship between the depth of the snowpack (or SWE) and its extent within a MODIS pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85) for MOD10A1 and 96% (κ = 0.81) for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50% of the

VARIABILITY OF THE WINTER SNOWINESS AT THE SOUTHEAST OF KAMCHATKA PENINSULA

Directory of Open Access Journals (Sweden)

A. A. Grits

2012-01-01

Full Text Available Analyses of the snow cover depth for several years in the southeast ofKamchatkaPeninsulashow some possibilities for development of skiing, tourism and mountaineering. We found four types of winters in 1935–2006: high-snowy, mid-snowy, little-snowy, and unstable snowy. The average depth of snow for 71 years is133 cmwith minimum of60 cmin 1939 and maximum of272 cmin 2005. The exceptional snowiness gives opportunity to use this territory even in summer months. In some years inKamchatka, the mountain-skiing season lasts a round year. The average date of forming the steady snow cover in the lowlands areas is November 12, and the middle date of the highest snow is May 22. The most comfortable time for recreation on the peninsula in wintertime are observed from the middle of March until the middle of April. During this time, we have the maximum snow, large duration of sunshine and air temperature closed to zero degrees.

Statistical downscaling of regional climate scenarios for the French Alps : Impacts on snow cover

Science.gov (United States)

Rousselot, M.; Durand, Y.; Giraud, G.; Mérindol, L.; Déqué, M.; Sanchez, E.; Pagé, C.; Hasan, A.

2010-12-01

Mountain areas are particularly vulnerable to climate change. Owing to the complexity of mountain terrain, climate research at scales relevant for impacts studies and decisive for stakeholders is challenging. A possible way to bridge the gap between these fine scales and those of the general circulation models (GCMs) consists of combining high-resolution simulations of Regional Climate Models (RCMs) to statistical downscaling methods. The present work is based on such an approach. It aims at investigating the impacts of climate change on snow cover in the French Alps for the periods 2021-2050 and 2071-2100 under several IPCC hypotheses. An analogue method based on high resolution atmospheric fields from various RCMs and climate reanalyses is used to simulate local climate scenarios. These scenarios, which provide meteorological parameters relevant for snowpack evolution, subsequently feed the CROCUS snow model. In these simulations, various sources of uncertainties are thus considered (several greenhouse gases emission scenarios and RCMs). Results are obtained for different regions of the French Alps at various altitudes. For all scenarios, temperature increase is relatively uniform over the Alps. This regional warming is larger than that generally modeled at the global scale (IPCC, 2007), and particularly strong in summer. Annual precipitation amounts seem to decrease, mainly as a result of decreasing precipitation trends in summer and fall. As a result of these climatic evolutions, there is a general decrease of the mean winter snow depth and seasonal snow duration for all massifs. Winter snow depths are particularly reduced in the Northern Alps. However, the impact on seasonal snow duration is more significant in the Southern and Extreme Southern Alps, since these regions are already characterized by small winter snow depths at low elevations. Reference : IPCC (2007a). Climate change 2007 : The physical science basis. Contribution of working group I to the

SNOW CLEARING SERVICE WINTER 2001-2002

CERN Multimedia

ST-HM Group; Tel. 72202

2001-01-01

As usual at this time of the year, the snowing clearing service, which comes under the control of the Transport Group (ST-HM), is preparing for the start of snow-clearing operations (timetable, stand-by service, personnel responsible for driving vehicles and machines, preparation of useful and necessary equipment, work instructions, etc.) in collaboration with the Cleaning Service (ST-TFM) and the Fire Brigade (TIS-FB). The main difficulty for the snow-clearing service is the car parks, which cannot be properly cleared because of the presence of CERN and private vehicles parked there overnight in different parts of the parking areas. The ST-HM Transport Group would therefore like to invite you to park vehicles together in order to facilitate the access of the snow ploughs, thus allowing the car parks to be cleared more efficiently before the personnel arrives for work in the mornings.

Surface energy balance of seasonal snow cover for snow-melt ...

Indian Academy of Sciences (India)

This study describes time series analysis of snow-melt, radiation data and energy balance for a seasonal snow cover at Dhundi field station of SASE, which lies in Pir Panjal range of the. N–W Himalaya, for a winter season from 13 January to 12 April 2005. The analysis shows that mean snow surface temperature remains ...

Snow cover and temperature relationships in North America and Eurasia

Science.gov (United States)

Foster, J.; Owe, M.; Rango, A.

1983-01-01

In this study the snow cover extent during the autumn months in both North America and Eurasia has been related to the ensuing winter temperature as measured at several locations near the center of each continent. The relationship between autumn snow cover and the ensuing winter temperatures was found to be much better for Eurasia than for North America. For Eurasia the average snow cover extent during the autumn explained as much as 52 percent of the variance in the winter (December-February) temperatures compared to only 12 percent for North America. However, when the average winter snow cover was correlated with the average winter temperature it was found that the relationship was better for North America than for Eurasia. As much as 46 percent of the variance in the winter temperature was explained by the winter snow cover in North America compared to only 12 percent in Eurasia.

A distributed snow-evolution modeling system (SnowModel)

Science.gov (United States)

Glen E. Liston; Kelly. Elder

2006-01-01

SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D...

Application of Low-Cost UASs and Digital Photogrammetry for High-Resolution Snow Depth Mapping in the Arctic

DEFF Research Database (Denmark)

Cimoli, Emiliano; Marcer, Marco; Vandecrux, Baptiste Robert Marcel

2017-01-01

The repeat acquisition of high-resolution snow depth measurements has important research and civil applications in the Arctic. Currently the surveying methods for capturing the high spatial and temporal variability of the snowpack are expensive, in particular for small areal extents. An alternati...... areal extents. While further validation is needed, with the inclusion of extra validation points, the study showcases the potential of this cost-effective methodology for high-resolution monitoring of snow dynamics in the Arctic and beyond....... methodology based on Unmanned Aerial Systems (UASs) and digital photogrammetry was tested over varying surveying conditions in the Arctic employing two diverse and low-cost UAS-camera combinations (500 and 1700 USD, respectively). Six areas, two in Svalbard and four in Greenland, were mapped covering from......-estimated and measured snow depth, checked with conventional snow probing, ranged from 0.015 to 0.16 m. The impact of image pre-processing was explored, improving point cloud density and accuracy for different image qualities and snow/light conditions. Our UAS photogrammetry results are expected to be scalable to larger...

Multitemporal Accuracy and Precision Assessment of Unmanned Aerial System Photogrammetry for Slope-Scale Snow Depth Maps in Alpine Terrain

Science.gov (United States)

Adams, Marc S.; Bühler, Yves; Fromm, Reinhard

2017-12-01

Reliable and timely information on the spatio-temporal distribution of snow in alpine terrain plays an important role for a wide range of applications. Unmanned aerial system (UAS) photogrammetry is increasingly applied to cost-efficiently map the snow depth at very high resolution with flexible applicability. However, crucial questions regarding quality and repeatability of this technique are still under discussion. Here we present a multitemporal accuracy and precision assessment of UAS photogrammetry for snow depth mapping on the slope-scale. We mapped a 0.12 km2 large snow-covered study site, located in a high-alpine valley in Western Austria. 12 UAS flights were performed to acquire imagery at 0.05 m ground sampling distance in visible (VIS) and near-infrared (NIR) wavelengths with a modified commercial, off-the-shelf sensor mounted on a custom-built fixed-wing UAS. The imagery was processed with structure-from-motion photogrammetry software to generate orthophotos, digital surface models (DSMs) and snow depth maps (SDMs). Accuracy of DSMs and SDMs were assessed with terrestrial laser scanning and manual snow depth probing, respectively. The results show that under good illumination conditions (study site in full sunlight), the DSMs and SDMs were acquired with an accuracy of ≤ 0.25 and ≤ 0.29 m (both at 1σ), respectively. In case of poorly illuminated snow surfaces (study site shadowed), the NIR imagery provided higher accuracy (0.19 m; 0.23 m) than VIS imagery (0.49 m; 0.37 m). The precision of the UASSDMs was 0.04 m for a small, stable area and below 0.33 m for the whole study site (both at 1σ).

Relating C-band Microwave and Optical Satellite Observations as A Function of Snow Thickness on First-Year Sea Ice during the Winter to Summer Transition

Science.gov (United States)

Zheng, J.; Yackel, J.

2015-12-01

The Arctic sea ice and its snow cover have a direct impact on both the Arctic and global climate system through their ability to moderate heat exchange across the ocean-sea ice-atmosphere (OSA) interface. Snow cover plays a key role in the OSA interface radiation and energy exchange, as it controls the growth and decay of first-year sea ice (FYI). However, meteoric accumulation and redistribution of snow on FYI is highly stochastic over space and time, which makes it poorly understood. Previous studies have estimated local-scale snow thickness distributions using in-situ technique and modelling but it is spatially limited and challenging due to logistic difficulties. Moreover, snow albedo is also critical for determining the surface energy balance of the OSA during the critical summer ablation season. Even then, due to persistent and widespread cloud cover in the Arctic at various spatio-temporal scales, it is difficult and unreliable to remotely measure albedo of snow cover on FYI in the optical spectrum. Previous studies demonstrate that only large-scale sea ice albedo was successfully estimated using optical-satellite sensors. However, space-borne microwave sensors, with their capability of all-weather and 24-hour imaging, can provide enhanced information about snow cover on FYI. Daily spaceborne C-band scatterometer data (ASCAT) and MODIS data are used to investigate the the seasonal co-evolution of the microwave backscatter coefficient and optical albedo as a function of snow thickness on smooth FYI. The research focuses on snow-covered FYI near Cambridge Bay, Nunavut (Fig.1) during the winter to advanced-melt period (April-June, 2014). The ACSAT time series (Fig.2) show distinct increase in scattering at melt onset indicating the first occurrence of melt water in the snow cover. The corresponding albedo exhibits no decrease at this stage. We show how the standard deviation of ASCAT backscatter on FYI during winter can be used as a proxy for surface roughness

Monitoring snow cover and its effect on runoff regime in the Jizera Mountains

Science.gov (United States)

Kulasova, Alena

2015-04-01

The Jizera Mountains in the northern Bohemia are known by its rich snow cover. Winter precipitation represents usually a half of the precipitation in the hydrological year. Gradual snow accumulation and melt depends on the course of the particular winter period, the topography of the catchments and the type of vegetation. During winter the snow depth, and especially the snow water equivalent, are affected by the changing character of the falling precipitation, air and soil temperatures and the wind. More rapid snowmelt occurs more on the slopes without forest oriented to the South, while a gradual snowmelt occurs on the locations turned to the North and in forest. Melting snow recharges groundwater and affects water quality in an important way. In case of extreme situation the snowmelt monitoring is important from the point of view of flood protection of communities and property. Therefore the immediate information on the amount of water in snow is necessary. The way to get this information is the continuous monitoring of the snow depth and snow water equivalent. In the Jizera Mountains a regular monitoring of snow cover has been going on since the end of the 19th century. In the 80s of the last century the Jizera Mountains were affected by the increased fallout of pollutants in the air. There followed a gradual dieback of the forest cover and cutting down the upper part of the ridges. In order to get data for the quantification of runoff regime changes in the changing natural environment, the Czech Hydrometeorological Institute (CHMI) founded in the upper part of the Mountains several experimental catchments. One of the activities of the employees of the experimental basis is the regular measurement of snow cover at selected sites from 1982 up to now. At the same time snow cover is being observed using snow pillows, where its mass is monitored with the help of pressure sensors. In order to improve the reliability of the continuous measurement of the snow water

Past and future of the Austrian snow cover - results from the CC-Snow project

Science.gov (United States)

Strasser, Ulrich; Marke, Thomas; Hanzer, Florian; Ragg, Hansjörg; Kleindienst, Hannes; Wilcke, Renate; Gobiet, Andreas

2013-04-01

This study has the goal to simulate the evolution of the Austrian snow cover from 1971 to 2050 by means of a coupled modelling scheme, and to estimate the effect of climate change on the evolution of the natural snow cover. The model outcomes are interepreted with focus on both the future natural snow conditions, and the effects on winter skiing tourism. Therefore the regional temperature-index snow model SNOWREG is applied, providing snow maps with a spatial resolution of 250 m. The model is trained by means of assimilating local measurements and observed natural snow cover patterns. Meteorological forcing consists of the output of four realizations of the ENSEMBLES project for the A1B emission scenario. The meteorological variables are downscaled and error corrected with a quantile based empirical-statistical method on a daily time basis. The control simulation is 1971-2000, and the scenario simulation 2021-2050. Spatial interpolation is performed on the basis of parameter-elevation relations. We compare the four different global/regional climate model combinations and their effect on the snow modelling, and we explain the patterns of the resulting snow cover by means of regional climatological characteristics. The provinces Tirol and Styria serve as test regions, being typical examples for the two climatic subregions of Austria. To support the interpretation of the simulation results we apply indicators which enable to define meaningful measures for the comparison of the different periods and regions. Results show that the mean duration of the snow cover will decrease by 15 to 30 days per winter season, mostly in elevations between 2000 and 2500 m. Above 3000 m the higher winter precipitation can compensate this effect, and mean snow cover duration may even slightly increase. We also investigate the local scale by application of the physically based mountain snow model AMUNDSEN. This model is capable of producing 50 m resolution output maps for indicators

The value of snow cover

Science.gov (United States)

Sokratov, S. A.

2009-04-01

Snow is the natural resource, like soil and water. It has specific properties which allow its use not just for skiing but also for houses cooling in summer (Swedish experience), for air fields construction (Arctic and Antarctic), for dams (north of Russia), for buildings (not only snow-houses of some Polar peoples but artistic hotel attracting tourists in Sweden), and as art material (Sapporo snow festival, Finnish events), etc. "Adjustment" of snow distribution and amount is not only rather common practice (avalanche-protection constructions keeping snow on slopes) but also the practice with long history. So-called "snow irrigation" was used in Russia since XIX century to protect winter crop. What is now named "artificial snow production", is part of much larger pattern. What makes it special—it is unavoidable in present climate and economy situation. 5% of national income in Austria is winter tourism. 50% of the economy in Savoy relay on winter tourism. In terms of money this can be less, but in terms of jobs and income involved this would be even more considerable in Switzerland. As an example—the population of Davos is 14000 in Summer and 50000 in Winter. Skiing is growing business. In present time you can find ski slopes in Turkey and Lebanon. To keep a cite suitable for attracting tourists you need certain amount of sunny days and certain amount of snow. The snow cannons are often the only way to keep a place running. On the other hand, more artificial snow does not necessary attract more tourists, while heavy natural snowfall does attract them. Artificial snow making is costly and requires infrastructure (ponds and electric lines) with very narrow range of weather conditions. Related companies are searching for alternatives and one of them can be "weather regulation" by distribution of some chemical components in clouds. It did not happen yet, but can happen soon. The consequences of such interference in Nature is hardly known. The ski tourism is not the

[Effects of snow pack on soil nitrogen transformation enzyme activities in a subalpine Abies faxioniana forest of western Sichuan, China].

Science.gov (United States)

Xiong, Li; Xu, Zhen-Feng; Wu, Fu-Zhong; Yang, Wan-Qin; Yin, Rui; Li, Zhi-Ping; Gou, Xiao-Lin; Tang, Shi-Shan

2014-05-01

This study characterized the dynamics of the activities of urease, nitrate reductase and nitrite reductase in both soil organic layer and mineral soil layer under three depths of snow pack (deep snowpack, moderate snowpack and shallow snowpack) over the three critical periods (snow formed period, snow stable period, and snow melt period) in the subalpine Abies faxoniana forest of western Sichuan in the winter of 2012 and 2013. Throughout the winter, soil temperature under deep snowpack increased by 46.2% and 26.2%, respectively in comparison with moderate snowpack and shallow snowpack. In general, the three nitrogen-related soil enzyme activities under shallow snowpack were 0.8 to 3.9 times of those under deep snowpack during the winter. In the beginning and thawing periods of seasonal snow pack, shallow snowpack significantly increased the activities of urease, nitrate and nitrite reductase enzyme in both soil organic layer and mineral soil layer. Although the activities of the studied enzymes in soil organic layer and mineral soil layer were observed to be higher than those under deep- and moderate snowpacks in deep winter, no significant difference was found under the three snow packs. Meanwhile, the effects of snowpack on the activities of the measured enzymes were related with season, soil layer and enzyme type. Significant variations of the activities of nitrogen-related enzymes were found in three critical periods over the winter, and the three measured soil enzymes were significantly higher in organic layer than in mineral layer. In addition, the activities of the three measured soil enzymes were closely related with temperature and moisture in soils. In conclusion, the decrease of snow pack induced by winter warming might increase the activities of soil enzymes related with nitrogen transformation and further stimulate the process of wintertime nitrogen transformation in soils of the subalpine forest.

Evaluation of NVE's snow station network; Subreport in R et D project 302H15 Good snow data; Evaluering av NVE sitt snoestasjonsnettverk

Energy Technology Data Exchange (ETDEWEB)

Ree, Bjoerg Lirhus; Landroe, Hilde; Trondsen, Elise; Moeen, Knut M.

2011-03-15

NVE has measured snow water equivalent of snow pillow in forty years. Our snow station network has risen since 1997 from 6 to 25 stations. It was therefore absolutely necessary to do a review and quality assurance of NVE's snow data. This report discusses the snow data measured continuously - snow water equivalent and snow depth. Each station and the parameters it measures are described and evaluated. It is concluded in relation to whether stations should be continued or not. Stations technical solutions are well described, both of NVE's standard stations and the two test stations, Filefjell and Svarttjoernbekken. It has been o importance to bring out what problems the instruments have or may have and provide suggestions for solutions to them. Problems related to measure the water equivalent under Norwegian conditions, with the challenges and winter rain and re-freezing provides, is also reviewed. Alternatives to water equivalent measurements with a snow pillow, which is the traditional way in this country, are presented. Some of the alternative methods NVE tests out, for the others only description and our opinion is given. (Author)

Quantifying small-scale spatio-temporal variability of snow stratigraphy in forests based on high-resolution snow penetrometry

Science.gov (United States)

Teich, M.; Hagenmuller, P.; Bebi, P.; Jenkins, M. J.; Giunta, A. D.; Schneebeli, M.

2017-12-01

Snow stratigraphy, the characteristic layering within a seasonal snowpack, has important implications for snow remote sensing, hydrology and avalanches. Forests modify snowpack properties through interception, wind speed reduction, and changes to the energy balance. The lack of snowpack observations in forests limits our ability to understand the evolution of snow stratigraphy and its spatio-temporal variability as a function of forest structure and to observe snowpack response to changes in forest cover. We examined the snowpack under canopies of a spruce forest in the central Rocky Mountains, USA, using the SnowMicroPen (SMP), a high resolution digital penetrometer. Weekly-repeated penetration force measurements were recorded along 10 m transects every 0.3 m in winter 2015 and bi-weekly along 20 m transects every 0.5 m in 2016 in three study plots beneath canopies of undisturbed, bark beetle-disturbed and harvested forest stands, and an open meadow. To disentangle information about layer hardness and depth variabilities, and to quantitatively compare the different SMP profiles, we applied a matching algorithm to our dataset, which combines several profiles by automatically adjusting their layer thicknesses. We linked spatial and temporal variabilities of penetration force and depth, and thus snow stratigraphy to forest and meteorological conditions. Throughout the season, snow stratigraphy was more heterogeneous in undisturbed but also beneath bark beetle-disturbed forests. In contrast, and despite remaining small diameter trees and woody debris, snow stratigraphy was rather homogenous at the harvested plot. As expected, layering at the non-forested plot varied only slightly over the small spatial extent sampled. At the open and harvested plots, persistent crusts and ice lenses were clearly present in the snowpack, while such hard layers barely occurred beneath undisturbed and disturbed canopies. Due to settling, hardness significantly increased with depth at

Sensitivity Analysis of Snow Patterns in Swiss Ski Resorts to Shifts in Temperature, Precipitation and Humidity Under Condition of Climate Change

Science.gov (United States)

Uhlmann, B.; Goyette, S.; Beniston, M.

2008-12-01

The value of snow as a resource has considerably increased in Swiss mountain regions, in particular in the context of winter tourism. In the perspective of a warming climate, it is thus important to quantify the potential changes in snow amount and duration that could have large repercussions on the economy of ski resorts. Because of the fine spatial variability of snow, the use of a Surface Energy Balance Model (SEBM) is adequate to simulate local snow cover evolution. A perturbation method has been developed to generate plausible future meteorological input data required for SEBM simulations in order to assess the changes in snow cover patterns. Current and future snow depths have also been simulated within the ski areas themselves. The results show a large decrease of the snow depths and duration, even at high elevation in a warmer climate and emphasize the sensitivity of snow to topographical characteristics of the resorts. The study highlights the fact that not only the altitude of a domain but also its exposure, localization inland and slope gradients need to be taken into account when evaluating current and future snow depths. This method enables a precise assessment of the snow pattern over a small area.

Addressing challenges for youths with mobility devices in winter conditions.

Science.gov (United States)

Morales, Ernesto; Lindsay, Sally; Edwards, Geoffrey; Howell, Lori; Vincent, Claude; Yantzi, Nicole; Gauthier, Véronique

2018-01-01

Winter-related research about the experience of navigating in the urban context has mostly focused on the elderly population with physical disabilities. The aim of this project was to explore potential design solutions to enhance young people's mobility devices and the built environment to improve accessibility and participation in winter. A multi-method qualitative design process included the following steps: (1) in-depth interviews; (2) photo elicitation; (3) individual co-design sessions; and (4) group co-design sessions (i.e., focus group). The participants were 13 youths (nine males and four females), aged 12-21, who used a wheelchair (12 power chair users and one manual wheelchair), for some with their parents, others without their parents, according to the parents' willingness to participate or not in the study (n = 13). The first two authors conducted group co-design sessions with mechanical engineers and therapists/clinicians in two Canadian cities to discuss the feasibility of the designs. Results (findings): The youths and their parents reported different winter-related challenges and proposed specific design solutions to enhance their participation and inclusion in winter activities. Seven of these designs were presented at two group co-design sessions of therapists/clinicians and engineers. Two designs were found to be feasible: (1) a traction device for wheelchairs in snow and (2) a mat made of rollers to clean snow and dirt from tires. The results of this research highlight the frustrations and challenges youths who use wheelchairs encounter in winter and a need for new solutions to ensure greater accessibility in winter. Therapists/clinicians and designers should address winter-related accessibility problems in areas with abundant snow. Implications for Rehabilitation Several studies show that current urban contexts do not necessarily respond accurately to the needs of individuals with limited mobility. Winter-related research about the

Reindeer (Rangifer tarandus and climate change: Importance of winter forage

Directory of Open Access Journals (Sweden)

Thrine Moen Heggberget

2002-06-01

climate may cause an altitudinal upward shift in the production of mat-forming lichens in alpine, sub-arctic regions. This is due to an increased potential for lichen growth at high altitudes, combined with increased competition from taller-growing vascular plants at lower altitudes, where the biomass of Betula nana in particular will increase. Matforming lichens dominant on dry, windblown ridges are easily overgrazed at high reindeer densities. This has longterm effects due to lichens’ slow regeneration rate, but may also reduce competition from vascular plants in a long time perspective. Fires may act in a similar way in some forested areas. Accessibility of winter forage depends on plant biomass, snow depth and hardness; ice crusts or exceptionally deep snow may result in starvation and increased animal mortality. Calf recruitment appears to be low and/or highly variable where winter ranges are overgrazed and hard or deep snow is common. Population decline in several Rangifer tarandus spp. has been associated with snow-rich winters. Effects tend to be delayed and cumulative, particularly on calves. This is mainly ascribed to feeding conditions for young animals which later affect age at maturation. Global warming may increase the frequency of deep or hard snow on reindeer ranges in Norway, due to increased precipitation and more frequent mild periods in winter. We hypothesise that potential benefits from increased plant productivity due to global warming will be counteracted by shifts in the distribution of preferred lichen forage, reduction of the areas of suitable winter ranges, and generally reduced forage accessibility in winter.

Isotope composition of winter precipitation and snow cover in the foothills of the Altai

Directory of Open Access Journals (Sweden)

N. S. Malygina

2017-01-01

Full Text Available Over the past three decades, several general circulation models of the atmosphere and ocean (atmospheric and oceanic general circulation models  – GCMs have been improved by modeling the hydrological cycle with the use of isotopologues (isotopes of water HDO and H2 18O. Input parameters for the GCM models taking into account changes in the isotope composition of atmospheric precipitation were, above all, the results obtained by the network GNIP – Global Network of Isotopes in Precipitation. At different times, on the vast territory of Russia there were only about 40 simultaneously functioning stations where the sampling of atmospheric precipitation was performed. In this study we present the results of the isotope composition of samples taken on the foothills of the Altai during two winter seasons of 2014/15 and 2015/16. Values of the isotope composition of precipitation changed in a wide range and their maximum fluctuations were 25, 202 and 18‰ for δ18О, dexc and δD, respectively. The weighted-mean values of δ18О and δD of the precipitation analyzed for the above two seasons were close to each other (−21.1 and −158.1‰ for the first season and −21.1 and −161.9‰ for the second one, while dexc values differed significantly. The comparison of the results of isotope analysis of the snow cover integral samples with the corresponding in the time interval the weighted-mean values of precipitation showed high consistency. However, despite the similarity of values of δ18О and δD, calculated for precipitation and snow cover, and the results, interpolated in IsoMAP (from data of the GNIP stations for 1960–2010, the dexc values were close to mean annual values of IsoMAP for only the second winter season. According to the trajectory analysis (the HYSPLIT model, the revealed differences between both, the seasons, and the long-term average values of IsoMAP, were associated with a change of main regions where the air masses

Enhanced hemispheric-scale snow mapping through the blending of optical and microwave satellite data

Science.gov (United States)

Armstrong, R. L.; Brodzik, M. J.; Savoie, M.; Knowles, K.

2003-04-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. Global snow cover fluctuation can now be monitored over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere weekly snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible satellite data and the visible data typically show higher monthly variability. Decadal trends and their significance are compared for the two data types. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as throughout the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the

Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

NARCIS (Netherlands)

Stigter, Emmy E.; Wanders, Niko; Saloranta, Tuomo M.; Shea, Joseph M.; Bierkens, M.F.P.; Immerzeel, W.W.

2017-01-01

Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water

Unexpected Patterns in Snow and Dirt

Science.gov (United States)

Ackerson, Bruce J.

2018-01-01

For more than 30 years, Albert A. Bartlett published "Thermal patterns in the snow" in this journal. These are patterns produced by heat sources underneath the snow. Bartlett's articles encouraged me to pay attention to patterns in snow and to understanding them. At winter's end the last snow becomes dirty and is heaped into piles. This…

Scaling precipitation input to spatially distributed hydrological models by measured snow distribution

Directory of Open Access Journals (Sweden)

Christian Vögeli

2016-12-01

Full Text Available Accurate knowledge on snow distribution in alpine terrain is crucial for various applicationssuch as flood risk assessment, avalanche warning or managing water supply and hydro-power.To simulate the seasonal snow cover development in alpine terrain, the spatially distributed,physics-based model Alpine3D is suitable. The model is typically driven by spatial interpolationsof observations from automatic weather stations (AWS, leading to errors in the spatial distributionof atmospheric forcing. With recent advances in remote sensing techniques, maps of snowdepth can be acquired with high spatial resolution and accuracy. In this work, maps of the snowdepth distribution, calculated from summer and winter digital surface models based on AirborneDigital Sensors (ADS, are used to scale precipitation input data, with the aim to improve theaccuracy of simulation of the spatial distribution of snow with Alpine3D. A simple method toscale and redistribute precipitation is presented and the performance is analysed. The scalingmethod is only applied if it is snowing. For rainfall the precipitation is distributed by interpolation,with a simple air temperature threshold used for the determination of the precipitation phase.It was found that the accuracy of spatial snow distribution could be improved significantly forthe simulated domain. The standard deviation of absolute snow depth error is reduced up toa factor 3.4 to less than 20 cm. The mean absolute error in snow distribution was reducedwhen using representative input sources for the simulation domain. For inter-annual scaling, themodel performance could also be improved, even when using a remote sensing dataset from adifferent winter. In conclusion, using remote sensing data to process precipitation input, complexprocesses such as preferential snow deposition and snow relocation due to wind or avalanches,can be substituted and modelling performance of spatial snow distribution is improved.

Integration of snow management practices into a detailed snow pack model

Science.gov (United States)

Spandre, Pierre; Morin, Samuel; Lafaysse, Matthieu; Lejeune, Yves; François, Hugues; George-Marcelpoil, Emmanuelle

2016-04-01

The management of snow on ski slopes is a key socio-economic and environmental issue in mountain regions. Indeed the winter sports industry has become a very competitive global market although this economy remains particularly sensitive to weather and snow conditions. The understanding and implementation of snow management in detailed snowpack models is a major step towards a more realistic assessment of the evolution of snow conditions in ski resorts concerning past, present and future climate conditions. Here we describe in a detailed manner the integration of snow management processes (grooming, snowmaking) into the snowpack model Crocus (Spandre et al., Cold Reg. Sci. Technol., in press). The effect of the tiller is explicitly taken into account and its effects on snow properties (density, snow microstructure) are simulated in addition to the compaction induced by the weight of the grooming machine. The production of snow in Crocus is carried out with respect to specific rules and current meteorological conditions. Model configurations and results are described in detail through sensitivity tests of the model of all parameters related to snow management processes. In-situ observations were carried out in four resorts in the French Alps during the 2014-2015 winter season considering for each resort natural, groomed only and groomed plus snowmaking conditions. The model provides realistic simulations of the snowpack properties with respect to these observations. The main uncertainty pertains to the efficiency of the snowmaking process. The observed ratio between the mass of machine-made snow on ski slopes and the water mass used for production was found to be lower than was expected from the literature, in every resort. The model now referred to as "Crocus-Resort" has been proven to provide realistic simulations of snow conditions on ski slopes and may be used for further investigations. Spandre, P., S. Morin, M. Lafaysse, Y. Lejeune, H. François and E. George

Impact of the snow cover scheme on snow distribution and energy budget modeling over the Tibetan Plateau

Science.gov (United States)

Xie, Zhipeng; Hu, Zeyong; Xie, Zhenghui; Jia, Binghao; Sun, Genhou; Du, Yizhen; Song, Haiqing

2018-02-01

This paper presents the impact of two snow cover schemes (NY07 and SL12) in the Community Land Model version 4.5 (CLM4.5) on the snow distribution and surface energy budget over the Tibetan Plateau. The simulated snow cover fraction (SCF), snow depth, and snow cover days were evaluated against in situ snow depth observations and a satellite-based snow cover product and snow depth dataset. The results show that the SL12 scheme, which considers snow accumulation and snowmelt processes separately, has a higher overall accuracy (81.8%) than the NY07 (75.8%). The newer scheme performs better in the prediction of overall accuracy compared with the NY07; however, SL12 yields a 15.1% underestimation rate while NY07 overestimated the SCF with a 15.2% overestimation rate. Both two schemes capture the distribution of the maximum snow depth well but show large positive biases in the average value through all periods (3.37, 3.15, and 1.48 cm for NY07; 3.91, 3.52, and 1.17 cm for SL12) and overestimate snow cover days compared with the satellite-based product and in situ observations. Higher altitudes show larger root-mean-square errors (RMSEs) in the simulations of snow depth and snow cover days during the snow-free period. Moreover, the surface energy flux estimations from the SL12 scheme are generally superior to the simulation from NY07 when evaluated against ground-based observations, in particular for net radiation and sensible heat flux. This study has great implications for further improvement of the subgrid-scale snow variations over the Tibetan Plateau.

Snow Cover Maps from MODIS Images at 250 m Resolution, Part 2: Validation

Directory of Open Access Journals (Sweden)

Marc Zebisch

2013-03-01

Full Text Available The performance of a new algorithm for binary snow cover monitoring based on Moderate Resolution Imaging Spectroradiometer (MODIS satellite images at 250 m resolution is validated using snow cover maps (SCA based on Landsat 7 ETM+ images and in situ snow depth measurements from ground stations in selected test sites in Central Europe. The advantages of the proposed algorithm are the improved ground resolution of 250 m and the near real-time availability with respect to the 500 m standard National Aeronautics and Space Administration (NASA MODIS snow products (MOD10 and MYD10. It allows a more accurate snow cover monitoring at a local scale, especially in mountainous areas characterized by large landscape heterogeneity. The near real-time delivery makes the product valuable as input for hydrological models, e.g., for flood forecast. A comparison to sixteen snow cover maps derived from Landsat ETM/ETM+ showed an overall accuracy of 88.1%, which increases to 93.6% in areas outside of forests. A comparison of the SCA derived from the proposed algorithm with standard MODIS products, MYD10 and MOD10, indicates an agreement of around 85.4% with major discrepancies in forested areas. The validation of MODIS snow cover maps with 148 in situ snow depth measurements shows an accuracy ranging from 94% to around 82%, where the lowest accuracies is found in very rugged terrain restricted to in situ stations along north facing slopes, which lie in shadow in winter during the early morning acquisition.

Decontamination and winter conditions

International Nuclear Information System (INIS)

Quenild, C.; Tveten, U.

1984-12-01

The report deals with two decontamonation experiments under winter conditions. A snow-covered parking lot was contaminated, and the snow was subsequently removed using standard snow-moving equipment. The snow left behind was collected and the content of contaminant was determined. A non-radioactive contaminant was used. A decontamination factor exceeding 100 was obtained. Although the eksperimental conditions were close to ideal, it is reason to believe that extremely efficient removal of deposited materials on a snow surface is achivable. In another investigation, run-off from agricultural surface, contaminated while covered with snow, was measured A lycimeter was used in this experiment. A stable layer of ice and snow was allowed to form before contamination. The run-off water was collected at each thaw period until all snow and ice was gone. Cs-134 was used as contaminant. Roughly 30% of the Cs-134 with which the area was contaminated ran off with the melt water. Following a reactor accident situation, this would have given a corresponding reduction in the long term doses. Both of these experiments show that consequence calculation assumptions, as they are currently applied to large accident assessment, tend to overestimate the consequences resulting from accidents taking place under winter conditions

Simulation of Wind-Driven Snow Redistribution at a High-Elevation Alpine Site Using a Meso-Scale Atmospheric Model

Science.gov (United States)

Vionnet, V.; Martin, E.; Masson, V.; Guyomarc'h, G.; Naaim-Bouvet, F.; Prokop, A.; Durand, Y.; Lac, C.

2012-12-01

In alpine regions, blowing snow events strongly influence the temporal and spatial evolution of the snow depth distribution throughout the winter season. We recently developed a new simulation system to gain understanding on the complex processes that drive the redistribution of snow by the wind in complex terrain. This new system couples directly the detailed snow-pack model Crocus with the meso-scale atmospheric model Meso-NH. A blowing snow scheme allows Meso-NH to simulate the transport of snow particles in the atmosphere. We used the coupled system to study a blowing snow event with snowfall that occurred in February 2011 in the Grandes Rousses range (French Alps). Three nested domains at an horizontal resolution of 450, 150 and 50 m allow the model to simulate the complex 3D precipitation and wind fields around our experimental site (2720 m a.s.l.) during this 22-hour event. Wind-induced snow transport is activated over the domains of higher resolution (150 and 50 m). We firstly assessed the ability of the model to reproduce atmospheric flows at high resolution in alpine terrain using a large dataset of observations (meteorological data, vertical profile of wind speed). Simulated blowing snow fluxes are then compared with measurements from SPC and mechanical snow traps. Finally a map of snow erosion and accumulation produced by Terrestrial Laser measurements allows to evaluate the quality of the simulated snow depth redistribution.

Modelling technical snow production for skiing areas in the Austrian Alps with the physically based snow model AMUNDSEN

Science.gov (United States)

Hanzer, F.; Marke, T.; Steiger, R.; Strasser, U.

2012-04-01

Tourism and particularly winter tourism is a key factor for the Austrian economy. Judging from currently available climate simulations, the Austrian Alps show a particularly high vulnerability to climatic changes. To reduce the exposure of ski areas towards changes in natural snow conditions as well as to generally enhance snow conditions at skiing sites, technical snowmaking is widely utilized across Austrian ski areas. While such measures result in better snow conditions at the skiing sites and are important for the local skiing industry, its economic efficiency has also to be taken into account. The current work emerges from the project CC-Snow II, where improved future climate scenario simulations are used to determine future natural and artificial snow conditions and their effects on tourism and economy in the Austrian Alps. In a first step, a simple technical snowmaking approach is incorporated into the process based snow model AMUNDSEN, which operates at a spatial resolution of 10-50 m and a temporal resolution of 1-3 hours. Locations of skiing slopes within a ski area in Styria, Austria, were digitized and imported into the model environment. During a predefined time frame in the beginning of the ski season, the model produces a maximum possible amount of technical snow and distributes the associated snow on the slopes, whereas afterwards, until to the end of the ski season, the model tries to maintain a certain snow depth threshold value on the slopes. Due to only few required input parameters, this approach is easily transferable to other ski areas. In our poster contribution, we present first results of this snowmaking approach and give an overview of the data and methodology applied. In a further step in CC-Snow, this simple bulk approach will be extended to consider actual snow cannon locations and technical specifications, which will allow a more detailed description of technical snow production as well as cannon-based recordings of water and energy

Natural variations in snow cover do not affect the annual soil CO2 efflux from a mid-elevation temperate forest.

Science.gov (United States)

Schindlbacher, Andreas; Jandl, Robert; Schindlbacher, Sabine

2014-02-01

Climate change might alter annual snowfall patterns and modify the duration and magnitude of snow cover in temperate regions with resultant impacts on soil microclimate and soil CO2 efflux (Fsoil ). We used a 5-year time series of Fsoil measurements from a mid-elevation forest to assess the effects of naturally changing snow cover. Snow cover varied considerably in duration (105-154 days) and depth (mean snow depth 19-59 cm). Periodically shallow snow cover (soil freezing or increased variation in soil temperature. This was mostly not reflected in Fsoil which tended to decrease gradually throughout winter. Progressively decreasing C substrate availability (identified by substrate induced respiration) likely over-rid the effects of slowly changing soil temperatures and determined the overall course of Fsoil . Cumulative CO2 efflux from beneath snow cover varied between 0.46 and 0.95 t C ha(-1)  yr(-1) and amounted to between 6 and 12% of the annual efflux. When compared over a fixed interval (the longest period of snow cover during the 5 years), the cumulative CO2 efflux ranged between 0.77 and 1.18 t C ha(-1) or between 11 and 15% of the annual soil CO2 efflux. The relative contribution (15%) was highest during the year with the shortest winter. Variations in snow cover were not reflected in the annual CO2 efflux (7.44-8.41 t C ha(-1) ) which did not differ significantly between years and did not correlate with any snow parameter. Regional climate at our site was characterized by relatively high amounts of precipitation. Therefore, snow did not play a role in terms of water supply during the warm season and primarily affected cold season processes. The role of changing snow cover therefore seems rather marginal when compared to potential climate change effects on Fsoil during the warm season. © 2013 The Authors. Global Change Biology published by John Wiley & Sons Ltd.

Snow reliability in ski resorts considering artificial snowmaking

Science.gov (United States)

Hofstätter, M.; Formayer, H.; Haas, P.

2009-04-01

Snow reliability is the key factor to make skiing on slopes possible and to ensure added value in winter tourism. In this context snow reliability is defined by the duration of a snowpack on the ski runs of at least 50 mm snow water equivalent (SWE), within the main season (Dec-Mar). Furthermore the snowpack should form every winter and be existent early enough in season. In our work we investigate the snow reliability of six Austrian ski resorts. Because nearly all Austrian resorts rely on artificial snowmaking it is of big importance to consider man made snow in the snowpack accumulation and ablation in addition to natural snow. For each study region observed weather data including temperature, precipitation and snow height are used. In addition we differentiate up to three elevations on each site (valley, intermediate, mountain top), being aware of the typical local winter inversion height. Time periods suitable for artificial snow production, for several temperature threshold (-6,-4 or -1 degree Celsius) are calculated on an hourly base. Depending on the actual snowpack height, man made snow can be added in the model with different defined capacities, considering different technologies or the usage of additives. To simulate natural snowpack accumulation and ablation we a simple snow model, based on daily precipitation and temperature. This snow model is optimized at each site separately through certain parameterization factors. Based on the local observations and the monthly climate change signals from the climate model REMO-UBA, we generate long term time series of temperature and precipitation, using the weather generator LARS. Thereby we are not only able to simulate the snow reliability under current, but also under future climate conditions. Our results show significant changes in snow reliability, like an increase of days with insufficient snow heights, especially at mid and low altitudes under natural snow conditions. Artificial snowmaking can partly

Modelling snow accumulation and snow melt in a continuous hydrological model for real-time flood forecasting

International Nuclear Information System (INIS)

Stanzel, Ph; Haberl, U; Nachtnebel, H P

2008-01-01

Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.

Modelling snow accumulation and snow melt in a continuous hydrological model for real-time flood forecasting

Energy Technology Data Exchange (ETDEWEB)

Stanzel, Ph; Haberl, U; Nachtnebel, H P [Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Applied Life Sciences, Muthgasse 18, 1190 Vienna (Austria)], E-mail: philipp.stanzel@boku.ac.at

2008-11-01

Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.

Water losses during technical snow production

Science.gov (United States)

Grünewald, Thomas; Wolfsperger, Fabian

2017-04-01

These days, the production of technical snow can be seen as a prerequisite for winter tourism. Huge amounts of water are used for technical snow production by ski resorts, especially in the beginning of the winter season. The aim is to guarantee an appropriate amount of snow to reliably provide optimal ski runs until the date of season opening in early December. Technical snow is generated by pumping pressurized water through the nozzles of a snow machine and dispersing the resulting spray of small water droplets which freeze during their travel to the ground. Cooling and freezing of the droplets can only happen if energy is emitted to the air mass surrounding the droplets. This heat transfer is happening through convective cooling and though evaporation and sublimation of water droplets and ice particles. This means that also mass is lost from the droplets and added in form of vapor to the air. It is important to note that not all water that is pumped through the snow machine is converted to snow distributed on the ground. Significant amounts of water are lost due to wind drift, sublimation and evaporation while droplets are traveling through the air or to draining of water which is not fully frozen when arriving at the ground. Studies addressing this question are sparse and the quantity of the water losses is still unclear. In order to assess this question in more detail, we obtained several systematic field observations at a test site near Davos, Switzerland. About a dozen of snow making tests had been performed during the last winter seasons. We compare the amount of water measured at the intake of the snow machine with the amount of snow accumulating at the ground during a night of snow production. The snow mass was calculated from highly detailed repeated terrestrial laser scanning measurements in combination with manually gathered snow densities. In addition a meteorological station had been set up in the vicinity observing all relevant meteorological

Evaluation of air-soil temperature relationships simulated by land surface models during winter across the permafrost region

Science.gov (United States)

Wang, Wenli; Rinke, Annette; Moore, John C.; Ji, Duoying; Cui, Xuefeng; Peng, Shushi; Lawrence, David M.; McGuire, A. David; Burke, Eleanor J.; Chen, Xiaodong; Delire, Christine; Koven, Charles; MacDougall, Andrew; Saito, Kazuyuki; Zhang, Wenxin; Alkama, Ramdane; Bohn, Theodore J.; Ciais, Philippe; Decharme, Bertrand; Gouttevin, Isabelle; Hajima, Tomohiro; Krinner, Gerhard; Lettenmaier, Dennis P.; Miller, Paul A.; Smith, Benjamin; Sueyoshi, Tetsuo

2016-01-01

 A realistic simulation of snow cover and its thermal properties are important for accurate modelling of permafrost. We analyze simulated relationships between air and near-surface (20 cm) soil temperatures in the Northern Hemisphere permafrost region during winter, with a particular focus on snow insulation effects in nine land surface models and compare them with observations from 268 Russian stations. There are large across-model differences as expressed by simulated differences between near-surface soil and air temperatures, (ΔT), of 3 to 14 K, in the gradients between soil and air temperatures (0.13 to 0.96°C/°C), and in the relationship between ΔT and snow depth. The observed relationship between ΔT and snow depth can be used as a metric to evaluate the effects of each model's representation of snow insulation, and hence guide improvements to the model’s conceptual structure and process parameterizations. Models with better performance apply multi-layer snow schemes and consider complex snow processes. Some models show poor performance in representing snow insulation due to underestimation of snow depth and/or overestimation of snow conductivity. Generally, models identified as most acceptable with respect to snow insulation simulate reasonable areas of near-surface permafrost (12–16 million km2). However, there is not a simple relationship between the quality of the snow insulation in the acceptable models and the simulated area of Northern Hemisphere near-surface permafrost, likely because several other factors such as differences in the treatment of soil organic matter, soil hydrology, surface energy calculations, and vegetation also provide important controls on simulated permafrost distribution.

Ectomycorrhizal and saprotrophic fungi respond differently to long-term experimentally increased snow depth in the High Arctic

DEFF Research Database (Denmark)

Mundra, Sunil; Halvorsen, Rune; Kauserud, Håvard

2016-01-01

on the variation in species richness and community structure of ectomycorrhizal (ECM) and saprotrophic fungi. Soil samples were collected weekly from mid-July to mid-September in both control and deep snow plots. Richness of ECM fungi was lower, while saprotrophic fungi was higher in increased snow depth plots...... relative to controls. [Correction added on 23 September 2016 after first online publication: In the preceding sentence, the richness of ECM and saprotrophic fungi were wrongly interchanged and have been fixed in this current version.] ECM fungal richness was related to soil NO3-N, NH4-N, and K......; and saprotrophic fungi to NO3-N and pH. Small but significant changes in the composition of saprotrophic fungi could be attributed to snow treatment and sampling time, but not so for the ECM fungi. Delayed snow melt did not influence the temporal variation in fungal communities between the treatments. Results...

Hydrologic response across a snow persistence gradient on the west and east slopes of the Rocky Mountains in Colorado

Science.gov (United States)

Richard, G. A.; Hammond, J. C.; Kampf, S. K.; Moore, C. D.; Eurich, A.

2017-12-01

Snowpack trend analyses and modeling studies suggest that lower elevation snowpacks in mountain regions are most sensitive to drought and warming temperatures, however, in Colorado, most snow monitoring occurs in the high elevations where snow lasts throughout the winter and most streamflow monitoring occurs at lower elevations. The lack of combined snow and streamflow monitoring in watersheds along the transition from intermittent to persistent snow creates a gap in our understanding of snowmelt and runoff within the intermittent-persistent snow transition. Expanded hydrologic monitoring that spans the gradient of snow conditions in Colorado can help improve streamflow prediction and inform land and water managers. This study established hydrologic monitoring watersheds in intermittent, transitional, and persistent snow zones on the east slope and west slope of the Rocky Mountains in Colorado, and uses this monitoring network to improve understanding of how snow accumulation and melt affect soil moisture and streamflow generation under different snow conditions. We monitored six small watersheds (three west slope, three east slope) (0.8 to 3.9 km2) that drain intermittent, transitional, and persistent snow zones. At each site, we measured: streamflow, snow depth, soil moisture, precipitation, air temperature, and snow water equivalent (SWE). In our first season of monitoring, the west slope persistent and transitional sites had more mid-winter melt and infiltration, shorter snowpack duration, and lower peak SWE than the east slope sites. Snow cover remained at the east slope persistent site into June, whereas much of the snow at the persistent site on the west slope had already melted by early June. The difference in soil water input likely has consequences for streamflow response that we will continue to examine in future years. At the west slope intermittent site, the stream did not flow during the entire first year of monitoring, while at the east slope

SNOW THICKNESS ON AUSTRE GRØNFJORDBREEN, SVALBARD, FROM RADAR MEASUREMENTS AND STANDARD SNOW SURVEYS

Directory of Open Access Journals (Sweden)

I. I. Lavrentiev

2018-01-01

Full Text Available Summary Comparison of two methods of measurements of snow cover thickness on the glacier Austre Grønfjordbreen, Svalbard was performed in the spring of 2014. These methods were the radar (500 MHz observations and standard snow surveys. Measurements were conducted in 77 different points on the surface of the glacier. A good correlation (R2 = 0.98 was revealed. In comparison with the data of snow surveys, the radar measurements show a similar but more detailed pattern of the distribution of the snow cover depth. The discrepancy between the depths of snow cover on maps plotted from data of both methods did not exceed 30 cm in most parts of the glacier. The standard error of interpolation of the radar data onto the entire glacier surface amounts, on average, to 18 cm. This corresponds to the error of radar measurements of 18.8% when an average snow depth is about 160 cm and 9.4% at its maximum thickness of 320 cm. The distance between the measurement points at which the spatial covariance of the snow depth disappears falls between 236 and 283 m along the glacier, and between 117 and 165 m across its position. We compared the results of radar measurements of the pulse-delay time of reflections from the base of the snow cover with the data of manual probe measurements at 10 points and direct measurements of snow depth and average density in 12 snow pits. The average speed of radio waves propagation in the snow was determined as Vcr = 23.4±0.2 cm ns−1. This magnitude and the Looyenga and Kovacs formulas allowed estimating the average density of snow cover ρL = 353.1±13.1 kg m−3 and ρK = 337.4±12.9 kg m−3. The difference from average density measured in 12 pits ρav.meas = 387.4±12.9 kg m−3 amounts to −10.8% and −14.8%. In 2014, according to snow and radar measurements, altitudinal gradient of snow accumulation on the glacier Austre Grønfjordbreen was equal to 0.21 m/100 m, which is smaller than the

CREST-Snow Field Experiment: analysis of snowpack properties using multi-frequency microwave remote sensing data

Directory of Open Access Journals (Sweden)

T. Y. Lakhankar

2013-02-01

Full Text Available The CREST-Snow Analysis and Field Experiment (CREST-SAFE was carried out during January–March 2011 at the research site of the National Weather Service office, Caribou, ME, USA. In this experiment dual-polarized microwave (37 and 89 GHz observations were accompanied by detailed synchronous observations of meteorology and snowpack physical properties. The objective of this long-term field experiment was to improve understanding of the effect of changing snow characteristics (grain size, density, temperature under various meteorological conditions on the microwave emission of snow and hence to improve retrievals of snow cover properties from satellite observations. In this paper we present an overview of the field experiment and comparative preliminary analysis of the continuous microwave and snowpack observations and simulations. The observations revealed a large difference between the brightness temperature of fresh and aged snowpack even when the snow depth was the same. This is indicative of a substantial impact of evolution of snowpack properties such as snow grain size, density and wetness on microwave observations. In the early spring we frequently observed a large diurnal variation in the 37 and 89 GHz brightness temperature with small depolarization corresponding to daytime snowmelt and nighttime refreeze events. SNTHERM (SNow THERmal Model and the HUT (Helsinki University of Technology snow emission model were used to simulate snowpack properties and microwave brightness temperatures, respectively. Simulated snow depth and snowpack temperature using SNTHERM were compared to in situ observations. Similarly, simulated microwave brightness temperatures using the HUT model were compared with the observed brightness temperatures under different snow conditions to identify different states of the snowpack that developed during the winter season.

Snow management practices in French ski resorts

Science.gov (United States)

Spandre, Pierre; Francois, Hugues; George-Marcelpoil, Emmanuelle; Morin, Samuel

2016-04-01

Winter tourism plays a fundamental role in the economy of French mountain regions but also in other countries such as Austria, USA or Canada. Ski operators originally developed grooming methods to provide comfortable and safe skiing conditions. The interannual variability of snow conditions and the competition with international destinations and alternative tourism activities encouraged ski resorts to mitigate their dependency to weather conditions through snowmaking facilities. However some regions may not be able to produce machine made snow due to inadequate conditions and low altitude resorts are still negatively impacted by low snow seasons. In the meantime, even though the operations of high altitude resorts do not show any dependency to the snow conditions they invest in snowmaking facilities. Such developments of snowmaking facilities may be related to a confused and contradictory perception of climate change resulting in individualistic evolutions of snowmaking facilities, also depending on ski resorts main features such as their altitude and size. Concurrently with the expansion of snowmaking facilities, a large range of indicators have been used to discuss the vulnerability of ski resorts such as the so-called "100 days rule" which was widely used with specific thresholds (i.e. minimum snow depth, dates) and constraints (i.e. snowmaking capacity). The present study aims to provide a detailed description of snow management practices and major priorities in French ski resorts with respect to their characteristics. We set up a survey in autumn 2014, collecting data from 56 French ski operators. We identify the priorities of ski operators and describe their snowmaking and grooming practices and facilities. The operators also provided their perception of the ski resort vulnerability to snow and economic challenges which we could compare with the actual snow conditions and ski lift tickets sales during the period from 2001 to 2012.

Unexpected Patterns in Snow and Dirt

Science.gov (United States)

Ackerson, Bruce J.

2018-01-01

For more than 30 years, Albert A. Bartlett published "Thermal patterns in the snow" in this journal. These are patterns produced by heat sources underneath the snow. Bartlett's articles encouraged me to pay attention to patterns in snow and to understanding them. At winter's end the last snow becomes dirty and is heaped into piles. This snow comes from the final clearing of sidewalks and driveways. The patterns observed in these piles defied my intuition. This melting snow develops edges where dirt accumulates, in contrast to ice cubes, which lose sharp edges and become more spherical upon melting. Furthermore, dirt absorbs more radiation than snow and yet doesn't melt and round the sharp edges of snow, where dirt accumulates.

Estimation of the condition of snow cover in Voronezh according to the chemical analysis of water from melted snow

OpenAIRE

Prozhorina Tatyana Ivanovna; Bespalova Elena Vladimirovna; Yakunina Nadezhda

2014-01-01

Snow cover possesses high sorption ability and represents informative object to identify technogenic pollution of an urban environment. In this article the investigation data of a chemical composition of snow fallen in Voronezh during the winter period of 2014 are given. Relationships between existence of pollutants in snow and the level of technogenic effect are analyzed.

A Distributed Snow Evolution Modeling System (SnowModel)

Science.gov (United States)

Liston, G. E.; Elder, K.

2004-12-01

A spatially distributed snow-evolution modeling system (SnowModel) has been specifically designed to be applicable over a wide range of snow landscapes, climates, and conditions. To reach this goal, SnowModel is composed of four sub-models: MicroMet defines the meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowMass simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. While other distributed snow models exist, SnowModel is unique in that it includes a well-tested blowing-snow sub-model (SnowTran-3D) for application in windy arctic, alpine, and prairie environments where snowdrifts are common. These environments comprise 68% of the seasonally snow-covered Northern Hemisphere land surface. SnowModel also accounts for snow processes occurring in forested environments (e.g., canopy interception related processes). SnowModel is designed to simulate snow-related physical processes occurring at spatial scales of 5-m and greater, and temporal scales of 1-hour and greater. These include: accumulation from precipitation; wind redistribution and sublimation; loading, unloading, and sublimation within forest canopies; snow-density evolution; and snowpack ripening and melt. To enhance its wide applicability, SnowModel includes the physical calculations required to simulate snow evolution within each of the global snow classes defined by Sturm et al. (1995), e.g., tundra, taiga, alpine, prairie, maritime, and ephemeral snow covers. The three, 25-km by 25-km, Cold Land Processes Experiment (CLPX) mesoscale study areas (MSAs: Fraser, North Park, and Rabbit Ears) are used as SnowModel simulation examples to highlight model strengths, weaknesses, and features in forested, semi-forested, alpine, and shrubland environments.

Calculation of new snow densities from sub-daily automated snow measurements

Science.gov (United States)

Helfricht, Kay; Hartl, Lea; Koch, Roland; Marty, Christoph; Lehning, Michael; Olefs, Marc

2017-04-01

In mountain regions there is an increasing demand for high-quality analysis, nowcasting and short-range forecasts of the spatial distribution of snowfall. Operational services, such as for avalanche warning, road maintenance and hydrology, as well as hydropower companies and ski resorts need reliable information on the depth of new snow (HN) and the corresponding water equivalent (HNW). However, the ratio of HNW to HN can vary from 1:3 to 1:30 because of the high variability of new snow density with respect to meteorological conditions. In the past, attempts were made to calculate new snow densities from meteorological parameters mainly using daily values of temperature and wind. Further complex statistical relationships have been used to calculate new snow densities on hourly to sub-hourly time intervals to drive multi-layer snow cover models. However, only a few long-term in-situ measurements of new snow density exist for sub-daily time intervals. Settling processes within the new snow due to loading and metamorphism need to be considered when computing new snow density. As the effect of these processes is more pronounced for long time intervals, a high temporal resolution of measurements is desirable. Within the pluSnow project data of several automatic weather stations with simultaneous measurements of precipitation (pluviometers), snow water equivalent (SWE) using snow pillows and snow depth (HS) measurements using ultrasonic rangers were analysed. New snow densities were calculated for a set of data filtered on the basis of meteorological thresholds. The calculated new snow densities were compared to results from existing new snow density parameterizations. To account for effects of settling of the snow cover, a case study based on a multi-year data set using the snow cover model SNOWPACK at Weissfluhjoch was performed. Measured median values of hourly new snow densities at the different stations range from 54 to 83 kgm-3. This is considerably lower than a 1

Uncertainty in solid precipitation and snow depth prediction for Siberia using the Noah and Noah-MP land surface models

Science.gov (United States)

Suzuki, Kazuyoshi; Zupanski, Milija

2018-01-01

In this study, we investigate the uncertainties associated with land surface processes in an ensemble predication context. Specifically, we compare the uncertainties produced by a coupled atmosphere-land modeling system with two different land surface models, the Noah- MP land surface model (LSM) and the Noah LSM, by using the Maximum Likelihood Ensemble Filter (MLEF) data assimilation system as a platform for ensemble prediction. We carried out 24-hour prediction simulations in Siberia with 32 ensemble members beginning at 00:00 UTC on 5 March 2013. We then compared the model prediction uncertainty of snow depth and solid precipitation with observation-based research products and evaluated the standard deviation of the ensemble spread. The prediction skill and ensemble spread exhibited high positive correlation for both LSMs, indicating a realistic uncertainty estimation. The inclusion of a multiple snowlayer model in the Noah-MP LSM was beneficial for reducing the uncertainties of snow depth and snow depth change compared to the Noah LSM, but the uncertainty in daily solid precipitation showed minimal difference between the two LSMs. The impact of LSM choice in reducing temperature uncertainty was limited to surface layers of the atmosphere. In summary, we found that the more sophisticated Noah-MP LSM reduces uncertainties associated with land surface processes compared to the Noah LSM. Thus, using prediction models with improved skill implies improved predictability and greater certainty of prediction.

Mapping snow depth in complex alpine terrain with close range aerial imagery - estimating the spatial uncertainties of repeat autonomous aerial surveys over an active rock glacier

Science.gov (United States)

Goetz, Jason; Marcer, Marco; Bodin, Xavier; Brenning, Alexander

2017-04-01

Snow depth mapping in open areas using close range aerial imagery is just one of the many cases where developments in structure-from-motion and multi-view-stereo (SfM-MVS) 3D reconstruction techniques have been applied for geosciences - and with good reason. Our ability to increase the spatial resolution and frequency of observations may allow us to improve our understanding of how snow depth distribution varies through space and time. However, to ensure accurate snow depth observations from close range sensing we must adequately characterize the uncertainty related to our measurement techniques. In this study, we explore the spatial uncertainties of snow elevation models for estimation of snow depth in a complex alpine terrain from close range aerial imagery. We accomplish this by conducting repeat autonomous aerial surveys over a snow-covered active-rock glacier located in the French Alps. The imagery obtained from each flight of an unmanned aerial vehicle (UAV) is used to create an individual digital elevation model (DEM) of the snow surface. As result, we obtain multiple DEMs of the snow surface for the same site. These DEMs are obtained from processing the imagery with the photogrammetry software Agisoft Photoscan. The elevation models are also georeferenced within Photoscan using the geotagged imagery from an onboard GNSS in combination with ground targets placed around the rock glacier, which have been surveyed with highly accurate RTK-GNSS equipment. The random error associated with multi-temporal DEMs of the snow surface is estimated from the repeat aerial survey data. The multiple flights are designed to follow the same flight path and altitude above the ground to simulate the optimal conditions of repeat survey of the site, and thus try to estimate the maximum precision associated with our snow-elevation measurement technique. The bias of the DEMs is assessed with RTK-GNSS survey observations of the snow surface elevation of the area on and surrounding

Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation

Science.gov (United States)

Kwon, Yonghwan; Yang, Zong-Liang; Zhao, Long; Hoar, Timothy J.; Toure, Ally M.; Rodell, Matthew

2016-01-01

This paper addresses continental-scale snow estimates in North America using a recently developed snow radiance assimilation (RA) system. A series of RA experiments with the ensemble adjustment Kalman filter are conducted by assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature T(sub B) at 18.7- and 36.5-GHz vertical polarization channels. The overall RA performance in estimating snow depth for North America is improved by simultaneously updating the Community Land Model, version 4 (CLM4), snow/soil states and radiative transfer model (RTM) parameters involved in predicting T(sub B) based on their correlations with the prior T(sub B) (i.e., rule-based RA), although degradations are also observed. The RA system exhibits a more mixed performance for snow cover fraction estimates. Compared to the open-loop run (0.171m RMSE), the overall snow depth estimates are improved by 1.6% (0.168m RMSE) in the rule-based RA whereas the default RA (without a rule) results in a degradation of 3.6% (0.177mRMSE). Significant improvement of the snow depth estimates in the rule-based RA as observed for tundra snow class (11.5%, p < 0.05) and bare soil land-cover type (13.5%, p < 0.05). However, the overall improvement is not significant (p = 0.135) because snow estimates are degraded or marginally improved for other snow classes and land covers, especially the taiga snow class and forest land cover (7.1% and 7.3% degradations, respectively). The current RA system needs to be further refined to enhance snow estimates for various snow types and forested regions.

Rapid responses of permafrost and vegetation to experimentally increased snow cover in sub-arctic Sweden

International Nuclear Information System (INIS)

Johansson, Margareta; Bosiö, Julia; Akerman, H Jonas; Jackowicz-Korczynski, Marcin; Christensen, Torben R; Callaghan, Terry V

2013-01-01

Increased snow depth already observed, and that predicted for the future are of critical importance to many geophysical and biological processes as well as human activities. The future characteristics of sub-arctic landscapes where permafrost is particularly vulnerable will depend on complex interactions between snow cover, vegetation and permafrost. An experimental manipulation was, therefore, set up on a lowland peat plateau with permafrost, in northernmost Sweden, to simulate projected future increases in winter precipitation and to study their effects on permafrost and vegetation. After seven years of treatment, statistically significant differences between manipulated and control plots were found in mean winter ground temperatures, which were 1.5 ° C higher in manipulated plots. During the winter, a difference in minimum temperatures of up to 9 ° C higher could be found in individual manipulated plots compared with control plots. Active layer thicknesses increased at the manipulated plots by almost 20% compared with the control plots and a mean surface subsidence of 24 cm was recorded in the manipulated plots compared to 5 cm in the control plots. The graminoid Eriophorum vaginatum has expanded in the manipulated plots and the vegetation remained green longer in the season. (letter)

Hydrological Implications of Covering Wind-Blown Snow Accumulations with Geotextiles on Mount Aragats, Armenia

Directory of Open Access Journals (Sweden)

Alexander Nestler

2014-07-01

Full Text Available Snow is an excellent water reservoir, naturally storing large quantities of water at time scales from a few days to several months. In summer-dry countries, like Armenia, runoff due to snow melt from mountain regions is highly important for a sustained water supply (irrigation, hydropower. Snow fields on Mount Aragats, Armenia’s highest peak, often persist until July, providing vital amounts of melt water. Artificially managing these wind-driven snow accumulations as a natural water reservoir might have considerable potential. In the context of the Swiss-Armenian joint venture, Freezwater, snow fields are covered with geotextiles in order to delay snow melt long enough to provide additional melt water in the dry season of the year. In this study, we analyze the hydrological effectiveness of the artificial management of the natural snow cover on Mount Aragats based on various field measurements acquired over a three-year period and numerical modeling. Over the winter season, partly more than five meter-thick snow deposits are formed supported by snow redistribution by strong wind. Repeated mappings of snow fields indicate that snow cover patterns remain highly consistent over time. Measurements of ablation below manually applied geotextiles show a considerable reduction of melt rates by more than 50%. Simulations with an energy-balance model and a distributed temperature-index model allow assessing the hydrological effect of artificial snow management for different initial snow depths and elevations and suggest that coverage is needed at a large scale in order to generate a significant impact on discharge.

Snowpack snow water equivalent measurement using the attenuation of cosmic gamma radiation

International Nuclear Information System (INIS)

Osterhuber, R.; Condreva, K.

1998-01-01

Incoming, background cosmic radiation constantly fluxes through the earth's atmosphere. The high energy gamma portion of this radiation penetrates many terrestrial objects, including the winter snowpack. The attenuation of this radiation is exponentially related to the mass of the medium through which it penetrates. For the past three winters, a device measuring cosmic gamma radiation--and its attenuation through snow--has been installed at the Central Sierra Snow Laboratory, near Donner Pass, California. This gamma sensor, measuring energy levels between 5 and 15 MeV, has proved to be an accurate, reliable, non-invasive, non-mechanical instrument with which to measure the total snow water equivalent of a snowpack. This paper analyzes three winters' worth of data and discusses the physics and practical application of the sensor for the collection of snow water equivalent data from a remote location

AMSR-E/Aqua Daily L3 12.5 km Tb, Sea Ice Conc., & Snow Depth Polar Grids V002

Data.gov (United States)

National Aeronautics and Space Administration — The AMSR-E/Aqua Level 3 12.5 km daily sea ice product includes 18.7 - 89.0 GHz TBs, sea ice concentration averages (asc & desc), and 5-day snow depth over sea...

Altitudinal gradients, midwinter melt, and wind effects on snow accumulation in semiarid midlatitude Andes under La Niña conditions

Science.gov (United States)

Ayala, A.; McPhee, J.; Vargas, X.

2014-04-01

The Andes Cordillera remains a sparsely monitored and studied snow hydrology environment in comparison to similar mountain ranges in the Northern Hemisphere. In order to uncover some of the key processes driving snow water equivalent (SWE) spatial variability, we present and analyze a distributed SWE data set, sampled at the end of accumulation season 2011. Three representative catchments across the region were monitored, obtaining measurements in an elevation range spanning 2000 to 3900 m asl and from 32.4° to 34.0°S in latitude. Climatic conditions during this season corresponded to a moderate La Niña phenomenon, which is generally correlated with lower-than normal accumulation. Collected measurements can be described at the regional and watershed extents by altitudinal gradients that imply an increase by a factor of two in snow depth between 2200 and 3000 m asl, though with significant variability at the upper sites. In these upper sites, we found north-facing, wind-sheltered slopes showing 25% less average SWE values than south-facing, wind-exposed ones. This suggests that under these conditions, solar radiation dominated wind transport effects in controlling end-of-winter variability. Nevertheless, we found clusters of snow depth measurements above 3000 m asl that can be explained by wind exposure differences. This is the first documented snow depth data set of this spatial extent for this region, and it is framed within an ongoing research effort aimed at improving understanding and modeling of snow hydrology in the extratropical Andes Cordillera.

Optimizing placements of ground-based snow sensors for areal snow cover estimation using a machine-learning algorithm and melt-season snow-LiDAR data

Science.gov (United States)

Oroza, C.; Zheng, Z.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2016-12-01

We present a structured, analytical approach to optimize ground-sensor placements based on time-series remotely sensed (LiDAR) data and machine-learning algorithms. We focused on catchments within the Merced and Tuolumne river basins, covered by the JPL Airborne Snow Observatory LiDAR program. First, we used a Gaussian mixture model to identify representative sensor locations in the space of independent variables for each catchment. Multiple independent variables that govern the distribution of snow depth were used, including elevation, slope, and aspect. Second, we used a Gaussian process to estimate the areal distribution of snow depth from the initial set of measurements. This is a covariance-based model that also estimates the areal distribution of model uncertainty based on the independent variable weights and autocorrelation. The uncertainty raster was used to strategically add sensors to minimize model uncertainty. We assessed the temporal accuracy of the method using LiDAR-derived snow-depth rasters collected in water-year 2014. In each area, optimal sensor placements were determined using the first available snow raster for the year. The accuracy in the remaining LiDAR surveys was compared to 100 configurations of sensors selected at random. We found the accuracy of the model from the proposed placements to be higher and more consistent in each remaining survey than the average random configuration. We found that a relatively small number of sensors can be used to accurately reproduce the spatial patterns of snow depth across the basins, when placed using spatial snow data. Our approach also simplifies sensor placement. At present, field surveys are required to identify representative locations for such networks, a process that is labor intensive and provides limited guarantees on the networks' representation of catchment independent variables.

Snow loads in a changing climate: new risks?

Directory of Open Access Journals (Sweden)

U. Strasser

2008-01-01

Full Text Available In January/February 2006, heavy snowfalls in Bavaria (Germany lead to a series of infrastructural damage of catastrophic nature. Since on many collapsed roofs the total snow load was not exceptional, serious engineering deficiencies in roof construction and a sudden rise in the total snow load were considered to be the trigger of the events. An analysis of the then meteorological conditions reveals, that the early winter of 2005/2006 was characterised by an exceptional continuous snow cover, temperatures remained around the freezing point and no significant snowmelt was evident. The frequent freezing/thawing cycles were followed by a general compaction of the snow load. This resulted in a re-distribution and a new concentration of the snow load on specific locations on roofs. With respect to climate change, the question arises as to whether the risks relating to snow loads will increase. The future probability of a continuous snow cover occurrence with frequent freezing/thawing cycles will probably decline due to predicted higher temperatures. However, where temperatures remain low, an increase in winter precipitation will result in increased snow loads. Furthermore, the variability of extremes is predicted to increase. If heavy snowfall events are more frequent, the risk of a trigger event will likely increase. Finally, an attempt will be made here in this paper to outline a concept for an operational warning system for the Bavarian region. This system envisages to predict the development and risk of critical snow loads for a 3-day time period, utilising a combination of climate and snow modelling data and using this together with a snow pillow device (located on roofs and the results of which.

Experimental measurement and modeling of snow accumulation and snowmelt in a mountain microcatchment

Science.gov (United States)

Danko, Michal; Krajčí, Pavel; Hlavčo, Jozef; Kostka, Zdeněk; Holko, Ladislav

2016-04-01

Fieldwork is a very useful source of data in all geosciences. This naturally applies also to the snow hydrology. Snow accumulation and snowmelt are spatially very heterogeneous especially in non-forested, mountain environments. Direct field measurements provide the most accurate information about it. Quantification and understanding of processes, that cause these spatial differences are crucial in prediction and modelling of runoff volumes in spring snowmelt period. This study presents possibilities of detailed measurement and modeling of snow cover characteristics in a mountain experimental microcatchment located in northern part of Slovakia in Western Tatra mountains. Catchment area is 0.059 km2 and mean altitude is 1500 m a.s.l. Measurement network consists of 27 snow poles, 3 small snow lysimeters, discharge measurement device and standard automatic weather station. Snow depth and snow water equivalent (SWE) were measured twice a month near the snow poles. These measurements were used to estimate spatial differences in accumulation of SWE. Snowmelt outflow was measured by small snow lysimeters. Measurements were performed in winter 2014/2015. Snow water equivalent variability was very high in such a small area. Differences between particular measuring points reached 600 mm in time of maximum SWE. The results indicated good performance of a snow lysimeter in case of snowmelt timing identification. Increase of snowmelt measured by the snow lysimeter had the same timing as increase in discharge at catchment's outlet and the same timing as the increase in air temperature above the freezing point. Measured data were afterwards used in distributed rainfall-runoff model MIKE-SHE. Several methods were used for spatial distribution of precipitation and snow water equivalent. The model was able to simulate snow water equivalent and snowmelt timing in daily step reasonably well. Simulated discharges were slightly overestimated in later spring.

Climatic change and tourism. Research into the consequences of climatic change on winter tourism in the Swiss alps; Klimaaenderung und Tourismus. Klimafolgenforschung am Beispiel des Wintertourismus in den schweizer Alpen

Energy Technology Data Exchange (ETDEWEB)

Abegg, B.

1996-12-31

Swiss winter tourism is highly dependent on the ski industry and therefore relies on favourable snow conditions. An investigation of the snow-deficient winters at the end of the 1980`s indicated that lack of snow severely impacts the industry. Climate change (global warming) is a new challenge for Swiss winter tourism. It is demonstrated that a rising snowline would have a wide range of serious consequences. Under current climate conditions, ski fields higher than 1200 m are considered to be snow abundant. Assuming that temperatures increase by about 2{sup o}C, this line of snow-reliability would rise by 300 m up to 1500 m. Today 85% of Swiss ski areas are snow reliable. If climate change occurred as outlined above, the number of snow reliable ski areas would drop to 63%. The number of suitable days for skiing, defined as days with a snow depth of {>=} 30 cm, would also decrease - in Einsiedeln (910 m) for example, from today`s average of 51 days to 24 days in the future. Furthermore it is possible that the frequency and distribution of the weather patterns would change. If the currently observed trends (increasing occurrence of high pressure systems in winter) continue, negative effects on ski tourism have to be expected. A survey undertaken in the canton of Grisons shows that climate change is perceived as a potential problem for tourism. The tourism managers are well aware of the relationships between the snow conditions and their businesses, and they can imagine what the consequences of increasingly poor snow conditions would be. With regard to the projected climate change, tourism managers are not destined to play an inactive role. There is a whole set of strategies, especially in the short term, that can help sustain ski tourism. Best known is the increased use of artificial snow. Others are a better snow management or the development of new facilities in higher areas. In the medium and long term however, more sophisticated strategies need to be taken into

Merging a Terrain-Based Parameter and Snow Particle Counter Data for the Assessment of Snow Redistribution in the Col du Lac Blanc Area

Science.gov (United States)

Schön, Peter; Prokop, Alexander; Naaim-Bouvet, Florence; Vionnet, Vincent; Guyomarc'h, Gilbert; Heiser, Micha; Nishimura, Kouichi

2015-04-01

Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns. It does not, however, provide a quantitative estimate of changes in snow depths. The objective of our research was to introduce a new parameter to quantify changes in snow depths in our research area, the Col du Lac Blanc in the French Alps. The area is at an elevation of 2700 m and particularly suited for our study due to its consistently bi-modal wind directions. Our work focused on two pronounced, approximately 10 m high terrain breaks, and we worked with 1 m resolution digital snow surface models (DSM). The DSM and measured changes in snow depths were obtained with high-accuracy terrestrial laser scan (TLS) measurements. First we calculated the terrain-based parameter Sx on a digital snow surface model and correlated Sx with measured changes in snow-depths (Δ SH). Results showed that Δ SH can be approximated by Δ SHestimated = α * Sx, where α is a newly introduced parameter. The parameter α has shown to be linked to the amount of snow deposited influenced by blowing snow flux. At the Col du Lac Blanc test side, blowing snow flux is recorded with snow particle counters (SPC). Snow flux is the number of drifting snow particles per time and area. Hence, the SPC provide data about the duration and intensity of drifting snow events, two important factors not accounted for by the terrain parameter Sx. We analyse how the SPC snow flux data can be used to estimate the magnitude of the new variable parameter α . To simulate the development

Impacts of Recent Climatic Wetting on Distributed Snow and Streamflow Responses in a Terminal Lake Basin.

Science.gov (United States)

Van Hoy, D.; Mahmood, T. H.; Jeannotte, T.; Todhunter, P. E.

2017-12-01

The recent shift in hydroclimatic conditions in the Northern Great Plains (NGP) has led to an increase in precipitation, rainfall rate, and wetland connectivity over the last few decades. These changes yield an integrated response resulting in high mean annual streamflow and subsequent flooding in many NGP basins such as the terminal Devils Lake Basin (DLB). In this study, we investigate the impacts of recent climatic wetting on distributed hydrologic responses such as snow processes and streamflow using a field-tested and physically-based cold region hydrologic model (CRHM). CHRM is designed for cold prairie regions and has modules to simulate major processes such as blowing snow transport, sublimation, interception, frozen soil infiltration, snowmelt and subsequent streamflow generation. Our modeling focuses on a tributary basin of the DLB known as the Mauvais Coulee Basin (MCB). Since there were no snow observations in the MCB, we conducted a detailed snow survey at distributed locations estimating snow depth, density, and snow water equivalent (SWE) using a prairie snow tube four times during winter of 2016-17. The MCB model was evaluated against distributed snow observations and streamflow measured at the basin outlet (USGS) for the year 2016-2017. Preliminary results indicate that the simulated SWEs at distributed locations and streamflow (NSE ≈ 0.70) are in good agreement with observations. The simulated SWE maps exhibit large spatiotemporal variation during 2016-17 winter due to spatial variability in precipitation, snow redistribution from stubble field to wooded areas, and snow accumulations in small depressions across the subbasins. The main source of snow appears to be the hills and ridges of the eastern and western edges of the basin, while the main sink is the large flat central valleys. The model will be used to examine the effect of recent changes to precipitation and temperature on snow processes and subsequent streamflow for 2004-2017 season. We

Obtaining sub-daily new snow density from automated measurements in high mountain regions

Science.gov (United States)

Helfricht, Kay; Hartl, Lea; Koch, Roland; Marty, Christoph; Olefs, Marc

2018-05-01

The density of new snow is operationally monitored by meteorological or hydrological services at daily time intervals, or occasionally measured in local field studies. However, meteorological conditions and thus settling of the freshly deposited snow rapidly alter the new snow density until measurement. Physically based snow models and nowcasting applications make use of hourly weather data to determine the water equivalent of the snowfall and snow depth. In previous studies, a number of empirical parameterizations were developed to approximate the new snow density by meteorological parameters. These parameterizations are largely based on new snow measurements derived from local in situ measurements. In this study a data set of automated snow measurements at four stations located in the European Alps is analysed for several winter seasons. Hourly new snow densities are calculated from the height of new snow and the water equivalent of snowfall. Considering the settling of the new snow and the old snowpack, the average hourly new snow density is 68 kg m-3, with a standard deviation of 9 kg m-3. Seven existing parameterizations for estimating new snow densities were tested against these data, and most calculations overestimate the hourly automated measurements. Two of the tested parameterizations were capable of simulating low new snow densities observed at sheltered inner-alpine stations. The observed variability in new snow density from the automated measurements could not be described with satisfactory statistical significance by any of the investigated parameterizations. Applying simple linear regressions between new snow density and wet bulb temperature based on the measurements' data resulted in significant relationships (r2 > 0.5 and p ≤ 0.05) for single periods at individual stations only. Higher new snow density was calculated for the highest elevated and most wind-exposed station location. Whereas snow measurements using ultrasonic devices and snow

Twenty-four year record of Northern Hemisphere snow cover derived from passive microwave remote sensing

Science.gov (United States)

Armstrong, Richard L.; Brodzik, Mary Jo

2003-04-01

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Seasonal snow can cover more than 50% of the Northern Hemisphere land surface during the winter resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. Passive microwave satellite remote sensing can augment measurements based on visible satellite data alone because of the ability to acquire data through most clouds or during darkness as well as to provide a measure of snow depth or water equivalent. It is now possible to monitor the global fluctuation of snow cover over a 24 year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR) 1978-1987 and Special Sensor Microwave/Imager (SSM/I), 1987-present). Evaluation of snow extent derived from passive microwave algorithms is presented through comparison with the NOAA Northern Hemisphere snow extent data. For the period 1978 to 2002, both passive microwave and visible data sets show a smiliar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible statellite data and the visible data typically show higher monthly variability. During shallow snow conditions of the early winter season microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) does not provide a scattering signal of sufficient strength to be detected by the algorithms. As the snow cover continues to build during the months of January through March, as well as on into the melt season, agreement between the two data types continually improves. This occurs because as the snow becomes deeper and the layered structure more complex, the negative spectral gradient driving the passive microwave algorithm

Impact of a reduced winter snowpack on litter arthropod abundance and diversity in a northern hardwood forest ecosystem

Science.gov (United States)

Pamela H. Templer; Andrew F. Schiller; Nathan W. Fuller; Anne M. Socci; John L. Campbell; John E. Drake; Thomas H. Kunz

2012-01-01

Projected changes in climate for the northeastern USA over the next 100 years include a reduction in the depth and duration of the winter snowpack, which could affect soil temperatures and frost regimes. We conducted a snow-removal experiment in a northern hardwood forest at the Hubbard Brook Experimental Forest in central New Hampshire over 2 years to induce soil...

Regional variation in the chemical composition of winter snow pack and terricolous lichens in relation to sources of acid emissions in the Usa river basin, northeast European Russia

International Nuclear Information System (INIS)

Walker, T.R.; Crittenden, P.D.; Young, S.D.

2003-01-01

The chemistry of winter snow pack and terricolous lichens indicate pollution distribution in Arctic Russia. - The chemical composition of snow and terricolous lichens was determined along transects through the Subarctic towns of Vorkuta (130 km west-east), Inta (240 km south-north) and Usinsk (140 km, southwest-northeast) in the Usa river basin, northeast European Russia. Evidence of pollution gradients was found on two spatial scales. First, on the Inta transect, northward decreases in concentrations of N in the lichen Cladonia stellaris (from 0.57 mmol N g -1 at 90 km south to 0.43 mmol N g -1 at 130 km north of Inta) and winter deposition of non-sea salt sulphate (from 29.3 to 12.8 mol ha -1 at 90 km south and 110 km north of Inta, respectively) were attributed to long range transport of N and S from lower latitudes. Second, increased ionic content (SO 4 2- , Ca 2+ , K + ) and pH of snow, and modified N concentration and the concentration ratios K + :Mg 2+ and K + : (Mg 2+ +Ca 2+ ) in lichens (Cladonia arbuscula and Flavocetraria cucullata) within ca. 25-40 km of Vorkuta and Inta were largely attributed to local deposition of alkaline coal ash. Total sulphate concentrations in snow varied from ca. 5 μmol l -1 at remote sites to ca. 19 μmol l -1 near Vorkuta. Nitrate concentration in snow (typically ca. 9 μmol l -1 ) did not vary with proximity to perceived pollution sources

A long-term assessment of the variability in winter use of dense conifer cover by female white-tailed deer.

Directory of Open Access Journals (Sweden)

Glenn D Delgiudice

Full Text Available Long-term studies allow capture of a wide breadth of environmental variability and a broader context within which to maximize our understanding of relationships to specific aspects of wildlife behavior. The goal of our study was to improve our understanding of the biological value of dense conifer cover to deer on winter range relative to snow depth and ambient temperature.We examined variation among deer in their use of dense conifer cover during a 12-year study period as potentially influenced by winter severity and cover availability. Female deer were fitted with a mixture of very high frequency (VHF, n = 267 and Global Positioning System (GPS, n = 24 collars for monitoring use of specific cover types at the population and individual levels, respectively. We developed habitat composites for four study sites. We fit multinomial response models to VHF (daytime data to describe population-level use patterns as a function of snow depth, ambient temperature, and cover availability. To develop alternative hypotheses regarding expected spatio-temporal patterns in the use of dense conifer cover, we considered two sets of competing sub-hypotheses. The first set addressed whether or not dense conifer cover was limiting on the four study sites. The second set considered four alternative sub-hypotheses regarding the potential influence of snow depth and ambient temperature on space use patterns. Deer use of dense conifer cover increased the most with increasing snow depth and most abruptly on the two sites where it was most available, suggestive of an energy conservation strategy. Deer use of dense cover decreased the most with decreasing temperatures on the sites where it was most available. At all four sites deer made greater daytime use (55 to >80% probability of use of open vegetation types at the lowest daily minimum temperatures indicating the importance of thermal benefits afforded from increased exposure to solar radiation. Date

Drones application on snow and ice surveys in alpine areas

Science.gov (United States)

La Rocca, Leonardo; Bonetti, Luigi; Fioletti, Matteo; Peretti, Giovanni

2015-04-01

scientific point of view. All flight was performed by remote controlled aero models with high resolution camera. Aero models were able to take off and to ground on snow covered or icy surfaces since the specific aerodynamic configuration and specific engine used to. All winter surveys were executed flying low to obtain a tridimensional reconstruction of an High resolution Digital Elevation Model (DEM) of snow cover and ice cover and on summer as been developed the DEM were snow amass in the maximum avalanche risk period. The difference between winter and summer DEM (difference between two point clouds) let to individuate the snow depth, and it was used as input data for the snow avalanche model for the Aprica site (Bergamo - Italy).

Snow mechanics and avalanche formation: field experiments on the dynamic response of the snow cover

Science.gov (United States)

Schweizer, Jürg; Schneebeli, Martin; Fierz, Charles; Föhn, Paul M. B.

1995-11-01

Knowledge about snow mechanics and snow avalanche formation forms the basis of any hazard mitigation measures. The crucial point is the snow stability. The most relevant mechanical properties - the compressive, tensile and shear strength of the individual snow layers within the snow cover - vary substantially in space and time. Among other things the strength of the snow layers depends strongly on the state of stress and the strain rate. The evaluation of the stability of the snow cover is hence a difficult task involving many extrapolations. To gain insight in the release mechanism of slab avalanches triggered by skiers, the skier's impact is measured with a load cell at different depths within the snow cover and for different snow conditions. The study focused on the effects of the dynamic loading and of the damping by snow compaction. In accordance with earlier finite-element (FE) calculations the results show the importance of the depth of the weak layer or interface and the snow conditions, especially the sublayering. In order to directly measure the impact force and to study the snow properties in more detail, a new instrument, called rammrutsch was developed. It combines the properties of the rutschblock with the defined impact properties of the rammsonde. The mechanical properties are determined using (i) the impact energy of the rammrutsch and (ii) the deformations of the snow cover measured with accelerometers and digital image processing of video sequences. The new method is well suited to detect and to measure the mechanical processes and properties of the fracturing layers. The duration of one test is around 10 minutes and the method seems appropriate for determining the spatial variability of the snow cover. A series of experiments in a forest opening showed a clear difference in the snow stability between sites below trees and ones in the free field of the opening.

Acid Rain and Snow in Kashiwazaki City.

OpenAIRE

小野寺, 正幸; 富永, 禎秀; 竹園, 恵; 大金, 一二; Onodera, Masayuki; Tominaga, Yoshihide; Takesono, Satoshi; Oogane, Katsuji

2002-01-01

This paper described the actual condition of acid rain and snow and their influence of a winter monsoon in Kashiwazaki city. For 7 months from September in 2001 to March in 2002, the pH value was measured in rain or snow. The minimum of pH value observed was 3.9 for the 7 months. The day which observed pH

Technical snow production in skiing areas: conditions, practice, monitoring and modelling. A case study in Mayrhofen/Austria

Science.gov (United States)

Strasser, Ulrich; Hanzer, Florian; Marke, Thomas; Rothleitner, Michael

2017-04-01

The production of technical snow today is a self-evident feature of modern alpine skiing resort management. Millions of Euros are invested every year for the technical infrastructure and its operation to produce a homogeneous and continuing snow cover on the skiing slopes for the winter season in almost every larger destination in the Alps. In Austria, skiing tourism is a significant factor of the national economic structure. We present the framing conditions of technical snow production in the mid-size skiing resort of Mayrhofen (Zillertal Alps/Austria, 136 km slopes, elevation range 630 - 2.500 m a.s.l.). Production conditions are defined by the availability of water, the planned date for the season opening, and the climatic conditions in the weeks before. By means of an adapted snow production strategy an attempt is made to ecologically and economically optimize the use of water and energy resources. Monitoring of the snow cover is supported by a network of low-cost sensors and mobile snow depth recordings. Finally, technical snow production is simulated with the spatially distributed, physically based hydroclimatological model AMUNDSEN. The model explicitly considers individual snow guns and distributes the produced snow along the slopes. The amount of simulated snow produced by each device is a function of its type, of actual wet-bulb temperature at the location, of ski area infrastructure (in terms of water supply and pumping capacity), and of snow demand.

Seasonal variation in the input of atmospheric selenium to northwestern Greenland snow

Energy Technology Data Exchange (ETDEWEB)

Lee, Khanghyun; Hong, Sang-Bum [Korea Polar Research Institute, 26 Songdomirae-ro, Yeonsu-gu, Incheon 406–840 (Korea, Republic of); Lee, Jeonghoon [Department of Science Education, Ewha womans University, 52 Ewhayeodae-gil, Seodaemun-gu, Seoul 120-750 (Korea, Republic of); Chung, Jiwoong; Hur, Soon-Do [Korea Polar Research Institute, 26 Songdomirae-ro, Yeonsu-gu, Incheon 406–840 (Korea, Republic of); Hong, Sungmin, E-mail: smhong@inha.ac.kr [Department of Ocean Sciences, Inha University, 100 Inharo, Nam-gu, Incheon 402-751 (Korea, Republic of)

2015-09-01

Oxygen isotope ratio (δ{sup 18}O) and concentrations of Al, Na{sup +}, methanesulfonic acid (MSA), SO{sub 4}{sup 2−}, and selenium (Se) in a continuous series of 70 snow samples from a 3.2-m snow pit at a site in northwestern Greenland were determined using ultraclean procedures. Well-defined depth profiles of δ{sup 18}O, Al, and sea-salt-Na{sup +} allowed the determination of chronology of the snow pit that spanned approximately 6 years from spring 2003 to summer 2009. Se concentrations were at a low pg/g level, ranging from 7.2 to 45 pg/g, and exhibited high variability with generally higher values during winter and spring and lower values during summer and fall. Very high crustal enrichment factors (EF{sub c}) of Se averaging approximately 26,600 for the entire time period indicate a small contribution from crust dust. High Se/MSA ratios are generally observed in the winter and spring snow layers, in which the Se concentrations were relatively high (> 20 pg/g). This suggests that a significant component of the Se present in the snow layers is of anthropogenic origin. During the summer season, however, high EF{sub c} values are accompanied with low Se/MSA, indicating an increased contribution of marine biogenic sources. Significant correlations between Se, Al, and non-sea-salt SO{sub 4}{sup 2−} highlight that significant inputs of Se to the snow are likely controlled by the seasonality in the transport efficiency of anthropogenic Se from the source regions to the site. Based on the seasonal changes in Se concentrations, Se/MSA, and Se/S ratios observed in the samples, the input of anthropogenic Se to the site appears to be governed by the long-range transportation of Se emitted from coal combustion in East Asian countries, especially in China. - Highlights: • The first comprehensive seasonal variation of Se in Greenland snow is presented. • Data exhibit pronounced seasonality in the fallout of Se to Greenland. • High Se/MSA ratios indicate a

Seasonal variation in the input of atmospheric selenium to northwestern Greenland snow

International Nuclear Information System (INIS)

Lee, Khanghyun; Hong, Sang-Bum; Lee, Jeonghoon; Chung, Jiwoong; Hur, Soon-Do; Hong, Sungmin

2015-01-01

Oxygen isotope ratio (δ 18 O) and concentrations of Al, Na + , methanesulfonic acid (MSA), SO 4 2− , and selenium (Se) in a continuous series of 70 snow samples from a 3.2-m snow pit at a site in northwestern Greenland were determined using ultraclean procedures. Well-defined depth profiles of δ 18 O, Al, and sea-salt-Na + allowed the determination of chronology of the snow pit that spanned approximately 6 years from spring 2003 to summer 2009. Se concentrations were at a low pg/g level, ranging from 7.2 to 45 pg/g, and exhibited high variability with generally higher values during winter and spring and lower values during summer and fall. Very high crustal enrichment factors (EF c ) of Se averaging approximately 26,600 for the entire time period indicate a small contribution from crust dust. High Se/MSA ratios are generally observed in the winter and spring snow layers, in which the Se concentrations were relatively high (> 20 pg/g). This suggests that a significant component of the Se present in the snow layers is of anthropogenic origin. During the summer season, however, high EF c values are accompanied with low Se/MSA, indicating an increased contribution of marine biogenic sources. Significant correlations between Se, Al, and non-sea-salt SO 4 2− highlight that significant inputs of Se to the snow are likely controlled by the seasonality in the transport efficiency of anthropogenic Se from the source regions to the site. Based on the seasonal changes in Se concentrations, Se/MSA, and Se/S ratios observed in the samples, the input of anthropogenic Se to the site appears to be governed by the long-range transportation of Se emitted from coal combustion in East Asian countries, especially in China. - Highlights: • The first comprehensive seasonal variation of Se in Greenland snow is presented. • Data exhibit pronounced seasonality in the fallout of Se to Greenland. • High Se/MSA ratios indicate a significant contribution from anthropogenic sources. �

Summertime Minimum Streamflow Elasticity to Antecendent Winter Precipitation, Peak Snow Water Equivalent and Summertime Evaporative Demand in the Western US Maritime Mountains

Science.gov (United States)

Schaperow, J.; Cooper, M. G.; Cooley, S. W.; Alam, S.; Smith, L. C.; Lettenmaier, D. P.

2017-12-01

As climate regimes shift, streamflows and our ability to predict them will change, as well. Elasticity of summer minimum streamflow is estimated for 138 unimpaired headwater river basins across the maritime western US mountains to better understand how climatologic variables and geologic characteristics interact to determine the response of summer low flows to winter precipitation (PPT), spring snow water equivalent (SWE), and summertime potential evapotranspiration (PET). Elasticities are calculated using log log linear regression, and linear reservoir storage coefficients are used to represent basin geology. Storage coefficients are estimated using baseflow recession analysis. On average, SWE, PET, and PPT explain about 1/3 of the summertime low flow variance. Snow-dominated basins with long timescales of baseflow recession are least sensitive to changes in SWE, PPT, and PET, while rainfall-dominated, faster draining basins are most sensitive. There are also implications for the predictability of summer low flows. The R2 between streamflow and SWE drops from 0.62 to 0.47 from snow-dominated to rain-dominated basins, while there is no corresponding increase in R2 between streamflow and PPT.

Collaborative Research: Snow Accumulation and Snow Melt in a Mixed Northern Hardwood-Conifer Forest, Version 1

Data.gov (United States)

National Aeronautics and Space Administration — This data set contains snow depth, Snow Water Equivalent (SWE), and forest cover characteristics for sites at the Hubbard Brook Experimental Forest in northern New...

[Contribution of soil water at various depths to water consumption of rainfed winter wheat in the Loess tableland, China].

Science.gov (United States)

Cheng, Li Ping; Liu, Wen Zhao

2017-07-18

Soil water and stem water were collected in jointing and heading stages of the rainfed winter wheat in the Changwu Loess tableland, and the stable isotopic compositions of hydrogen and oxygen in water samples were measured to analyze the contribution of soil water at various depths to water consumption of winter wheat. The results showed that the isotopes were enriched in soil and wheat stem water in comparison with that in precipitation. Under the condition of no dry layer in soil profile, the contributions to wheat water consumption in jointing and heading stages were 5.4% and 2.6% from soil water at 0-30 cm depth, 73.4% and 67.3% at 60-90 cm depth (the main water source for winter wheat), and 7.9% and 13.5% below 120 cm depth, respectively. With the wheat growth, the contribution of soil water below the depth of 90 cm increased. It was concluded that soil evaporation mainly consumed soil water in 0-30 cm depth and wheat transpiration mainly consumed soil water below 60 cm depth in the experimental period. In the production practice, it is necessary to increase rainwater storage ratio during the summer fallow period, and apply reasonable combination of nitrogen and phosphorus fertilizers in order to increase soil moisture before wheat sowing, promote the wheat root developing deep downwards and raise the deep soil water utilization ratio.

Snow Drift Management: Summit Station Greenland

Science.gov (United States)

2016-05-01

management Snow surveys Transport analysis Winds -- Speed 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF...that about 25% of the estimated snow that the wind transports to Summit each winter is deposited and forms drifts, mostly in close proxim- ity to...the structures. This analysis demonstrates that weather data ( wind speed and direction) and a transport analysis can aid in estimating the vol- ume of

Analysis of Light Absorbing Aerosols in Northern Pakistan: Concentration on Snow/Ice, their Source Regions and Impacts on Snow Albedo

Science.gov (United States)

Gul, C.; Praveen, P. S.; Shichang, K.; Adhikary, B.; Zhang, Y.; Ali, S.

2016-12-01

Elemental carbon (EC) and light absorbing organic carbon (OC) are important particulate impurities in snow and ice which significantly reduce the albedo of glaciers and accelerate their melting. Snow and ice samples were collected from Karakorum-Himalayan region of North Pakistan during the summer campaign (May-Jun) 2015 and only snow samples were collected during winter (Dec 2015- Jan 2016). Total 41 surface snow/ice samples were collected during summer campaign along different elevation ranges (2569 to 3895 a.m.s.l) from six glaciers: Sachin, Henarche, Barpu, Mear, Gulkin and Passu. Similarly 18 snow samples were collected from Sust, Hoper, Tawas, Astore, Shangla, and Kalam regions during the winter campaign. Quartz filters were used for filtering of melted snow and ice samples which were then analyzed by thermal optical reflectance (TOR) method to determine the concentration of EC and OC. The average concentration of EC (ng/g), OC (ng/g) and dust (ppm) were found as follows: Passu (249.5, 536.8, 475), Barpu (1190, 397.6, 1288), Gulkin (412, 793, 761), Sachin (911, 2130, 358), Mear (678, 2067, 83) and Henarche (755, 1868, 241) respectively during summer campaign. Similarly, average concentration of EC (ng/g), OC (ng/g) and dust (ppm) was found in the samples of Sust (2506, 1039, 131), Hoper (646, 1153, 76), Tawas (650, 1320, 16), Astore (1305, 2161, 97), Shangla (739, 2079, 31) and Kalam (107, 347, 5) respectively during winter campaign. Two methods were adopted to identify the source regions: one coupled emissions inventory with back trajectories, second with a simple region tagged chemical transport modeling analysis. In addition, CALIPSO subtype aerosol composition indicated that frequency of smoke in the atmosphere over the region was highest followed by dust and then polluted dust. SNICAR model was used to estimate the snow albedo reduction from our in-situ measurements. Snow albedo reduction was observed to be 0.3% to 27.6%. The derived results were used

Seasonal rhythms of body temperature in the free-ranging raccoon dog (Nyctereutes procyonoides) with special emphasis on winter sleep.

Science.gov (United States)

Mustonen, Anne-Mari; Asikainen, Juha; Kauhala, Kaarina; Paakkonen, Tommi; Nieminen, Petteri

2007-01-01

The raccoon dog (Nyctereutes procyonoides) is the only canid with passive overwintering in areas with cold winters, but the depth and rhythmicity of wintertime hypothermia in the wild raccoon dog are unknown. To study the seasonal rhythms of body temperature (T(b)), seven free-ranging animals were captured and implanted with intra-abdominal T(b) loggers and radio-tracked during years 2004-2006. The average size of the home ranges was 306+/-26 ha, and the average 24 h T(b) was 38.0+/-dogs were hypothermic for 5 h in the morning (06:00-11:00 h), whereas the highest T(b) values were recorded between 16:00-23:00 h. The range of the 24 h oscillations increased by approximately 0.6 degrees C, and the rhythmicity was more pronounced than in the snow-free period. The ambient temperature and depth of snow cover were important determinants of the seasonal T(b) rhythms. The overwintering strategy of the raccoon dog resembled the patterns of winter sleep in bears and badgers, but the wintertime passivity of the species was more intermittent and the decrease in the T(b) less pronounced.

Simultaneous retrieval of sea ice thickness and snow depth using concurrent active altimetry and passive L-band remote sensing data

Science.gov (United States)

Zhou, L.; Xu, S.; Liu, J.

2017-12-01

The retrieval of sea ice thickness mainly relies on satellite altimetry, and the freeboard measurements are converted to sea ice thickness (hi) under certain assumptions over snow loading. The uncertain in snow depth (hs) is a major source of uncertainty in the retrieved sea ice thickness and total volume for both radar and laser altimetry. In this study, novel algorithms for the simultaneous retrieval of hi and hs are proposed for the data synergy of L-band (1.4 GHz) passive remote sensing and both types of active altimetry: (1) L-band (1.4GHz) brightness temperature (TB) from Soil Moisture Ocean Salinity (SMOS) satellite and sea ice freeboard (FBice) from radar altimetry, (2) L-band TB data and snow freeboard (FBsnow) from laser altimetry. Two physical models serve as the forward models for the retrieval: L-band radiation model, and the hydrostatic equilibrium model. Verification with SMOS and Operational IceBridge (OIB) data is carried out, showing overall good retrieval accuracy for both sea ice parameters. Specifically, we show that the covariability between hs and FBsnow is crucial for the synergy between TB and FBsnow. Comparison with existing algorithms shows lower uncertainty in both sea ice parameters, and that the uncertainty in the retrieved sea ice thickness as caused by that of snow depth is spatially uncorrelated, with the potential reduction of the volume uncertainty through spatial sampling. The proposed algorithms can be applied to the retrieval of sea ice parameters at basin-scale, using concurrent active and passive remote sensing data based on satellites.

Seasonal evolution of the effective thermal conductivity of the snow and the soil in high Arctic herb tundra at Bylot Island, Canada

Science.gov (United States)

Domine, Florent; Barrere, Mathieu; Sarrazin, Denis

2016-11-01

The values of the snow and soil thermal conductivity, ksnow and ksoil, strongly impact the thermal regime of the ground in the Arctic, but very few data are available to test model predictions for these variables. We have monitored ksnow and ksoil using heated needle probes at Bylot Island in the Canadian High Arctic (73° N, 80° W) between July 2013 and July 2015. Few ksnow data were obtained during the 2013-2014 winter, because little snow was present. During the 2014-2015 winter ksnow monitoring at 2, 12 and 22 cm heights and field observations show that a depth hoar layer with ksnow around 0.02 W m-1 K-1 rapidly formed. At 12 and 22 cm, wind slabs with ksnow around 0.2 to 0.3 W m-1 K-1 formed. The monitoring of ksoil at 10 cm depth shows that in thawed soil ksoil was around 0.7 W m-1 K-1, while in frozen soil it was around 1.9 W m-1 K-1. The transition between both values took place within a few days, with faster thawing than freezing and a hysteresis effect evidenced in the thermal conductivity-liquid water content relationship. The fast transitions suggest that the use of a bimodal distribution of ksoil for modelling may be an interesting option that deserves further testing. Simulations of ksnow using the snow physics model Crocus were performed. Contrary to observations, Crocus predicts high ksnow values at the base of the snowpack (0.12-0.27 W m-1 K-1) and low ones in its upper parts (0.02-0.12 W m-1 K-1). We diagnose that this is because Crocus does not describe the large upward water vapour fluxes caused by the temperature gradient in the snow and soil. These fluxes produce mass transfer between the soil and lower snow layers to the upper snow layers and the atmosphere. Finally, we discuss the importance of the structure and properties of the Arctic snowpack on subnivean life, as species such as lemmings live under the snow most of the year and must travel in the lower snow layer in search of food.

Canopy structure and topography effects on snow distribution at a catchment scale: Application of multivariate approaches

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Jenicek Michal

2018-03-01

Full Text Available The knowledge of snowpack distribution at a catchment scale is important to predict the snowmelt runoff. The objective of this study is to select and quantify the most important factors governing the snowpack distribution, with special interest in the role of different canopy structure. We applied a simple distributed sampling design with measurement of snow depth and snow water equivalent (SWE at a catchment scale. We selected eleven predictors related to character of specific localities (such as elevation, slope orientation and leaf area index and to winter meteorological conditions (such as irradiance, sum of positive air temperature and sum of new snow depth. The forest canopy structure was described using parameters calculated from hemispherical photographs. A degree-day approach was used to calculate melt factors. Principal component analysis, cluster analysis and Spearman rank correlation were applied to reduce the number of predictors and to analyze measured data. The SWE in forest sites was by 40% lower than in open areas, but this value depended on the canopy structure. The snow ablation in large openings was on average almost two times faster compared to forest sites. The snow ablation in the forest was by 18% faster after forest defoliation (due to the bark beetle. The results from multivariate analyses showed that the leaf area index was a better predictor to explain the SWE distribution during accumulation period, while irradiance was better predictor during snowmelt period. Despite some uncertainty, parameters derived from hemispherical photographs may replace measured incoming solar radiation if this meteorological variable is not available.

Sublimation From Snow in Northern Environments

Science.gov (United States)

Pomeroy, J. W.

2002-12-01

Sublimation from snow is an often neglected component of water and energy balances. Research under the Mackenzie GEWEX Study has attempted to understand the snow and atmospheric processes controlling sublimation and to estimate the magnitude of sublimation in high latitude catchments. Eddy correlation units were used to measure vertical water vapour fluxes from a high latitude boreal forest, snow-covered tundra and shrub-covered tundra in Wolf Creek Research Basin, near Whitehorse Yukon, Territory Canada. Over Jan-Apr. water vapour fluxes from the forest canopy amounted to 18.3 mm, a significant loss from winter snowfall of 54 mm. Most of this loss occurred when the canopy was snow-covered. The weight of snow measured on a suspended, weighed tree indicates that this flux is dominated by sublimation of intercepted snow. In the melt period (April), water vapour fluxes were uniformly small ranging from 0.21 mm/day on the tundra slope, 0.23 mm/day for the forest and 0.27 mm/day for the shrub-tundra. During the melt period the forest and shrub canopies was snow-free and roots were frozen, so the primary source of water vapour from all sites was the surface snow.

Improving Snow Modeling by Assimilating Observational Data Collected by Citizen Scientists

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Crumley, R. L.; Hill, D. F.; Arendt, A. A.; Wikstrom Jones, K.; Wolken, G. J.; Setiawan, L.

2017-12-01

Modeling seasonal snow pack in alpine environments includes a multiplicity of challenges caused by a lack of spatially extensive and temporally continuous observational datasets. This is partially due to the difficulty of collecting measurements in harsh, remote environments where extreme gradients in topography exist, accompanied by large model domains and inclement weather. Engaging snow enthusiasts, snow professionals, and community members to participate in the process of data collection may address some of these challenges. In this study, we use SnowModel to estimate seasonal snow water equivalence (SWE) in the Thompson Pass region of Alaska while incorporating snow depth measurements collected by citizen scientists. We develop a modeling approach to assimilate hundreds of snow depth measurements from participants in the Community Snow Observations (CSO) project (www.communitysnowobs.org). The CSO project includes a mobile application where participants record and submit geo-located snow depth measurements while working and recreating in the study area. These snow depth measurements are randomly located within the model grid at irregular time intervals over the span of four months in the 2017 water year. This snow depth observation dataset is converted into a SWE dataset by employing an empirically-based, bulk density and SWE estimation method. We then assimilate this data using SnowAssim, a sub-model within SnowModel, to constrain the SWE output by the observed data. Multiple model runs are designed to represent an array of output scenarios during the assimilation process. An effort to present model output uncertainties is included, as well as quantification of the pre- and post-assimilation divergence in modeled SWE. Early results reveal pre-assimilation SWE estimations are consistently greater than the post-assimilation estimations, and the magnitude of divergence increases throughout the snow pack evolution period. This research has implications beyond the

Snow cover and snowfall impact corticosterone and immunoglobulin a levels in a threatened steppe bird.

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Liu, Gang; Hu, Xiaolong; Kessler, Aimee Elizabeth; Gong, Minghao; Wang, Yihua; Li, Huixin; Dong, Yuqiu; Yang, Yuhui; Li, Linhai

2018-05-15

Birds use both the corticosterone stress response and immune system to meet physiological challenges during exposure to adverse climatic conditions. To assess the stress level and immune response of the Asian Great Bustard during conditions of severe winter weather, we measured fecal corticosterone (CORT) and Immunoglobulin A (IgA) before and after snowfall in a low snow cover year (2014) and a high snow cover year (2015). A total of 239 fecal samples were gathered from individuals in Tumuji Nature Reserve, located in eastern Inner Mongolia, China. We observed high CORT levels that rose further after snowfall both in high and low snow cover years. IgA levels increased significantly after snowfall in the low snow cover year, but decreased after snowfall in the high snow cover year. These results suggest that overwintering Asian Great Bustards are subjected to climatic stress during severe winter weather, and the hypothalamic-pituitary-adrenal axis and immune system react to this challenge. Extreme levels of stress, such as snowfall in already prolonged and high snow cover conditions may decrease immune function. Supplemental feeding should be considered under severe winter weather conditions for this endangered subspecies. Copyright © 2018 Elsevier Inc. All rights reserved.

Air–snow exchange of nitrate: a modelling approach to investigate physicochemical processes in surface snow at Dome C, Antarctica

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J. Bock

2016-10-01

Full Text Available Snowpack is a multiphase (photochemical reactor that strongly influences the air composition in polar and snow-covered regions. Snowpack plays a special role in the nitrogen cycle, as it has been shown that nitrate undergoes numerous recycling stages (including photolysis in the snow before being permanently buried in the ice. However, the current understanding of these physicochemical processes remains very poor. Several modelling studies have attempted to reproduce (photochemical reactions inside snow grains, but these have relied on strong assumptions to characterise snow reactive properties, which are not well defined. Air–snow exchange processes such as adsorption, solid-state diffusion, or co-condensation also affect snow chemical composition. Here, we present a physically based model of these processes for nitrate. Using as input a 1-year-long time series of atmospheric nitrate concentration measured at Dome C, Antarctica, our model reproduces with good agreement the nitrate measurements in the surface snow. By investigating the relative importance of the main exchange processes, this study shows that, on the one hand, the combination of bulk diffusion and co-condensation allows a good reproduction of the measurements (correlation coefficient r = 0.95, with a correct amplitude and timing of summer peak concentration of nitrate in snow. During winter, nitrate concentration in surface snow is mainly driven by thermodynamic equilibrium, whilst the peak observed in summer is explained by the kinetic process of co-condensation. On the other hand, the adsorption of nitric acid on the surface of the snow grains, constrained by an already existing parameterisation for the isotherm, fails to fit the observed variations. During winter and spring, the modelled concentration of adsorbed nitrate is respectively 2.5 and 8.3-fold higher than the measured one. A strong diurnal variation driven by the temperature cycle and a peak occurring in early

Occurrence of blowing snow events at an alpine site over a 10-year period: Observations and modelling

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Vionnet, V.; Guyomarc'h, G.; Naaim Bouvet, F.; Martin, E.; Durand, Y.; Bellot, H.; Bel, C.; Puglièse, P.

2013-05-01

Blowing snow events control the evolution of the snow pack in mountainous areas and cause inhomogeneous snow distribution. The goal of this study is to identify the main features of blowing snow events at an alpine site and assess the ability of the detailed snowpack model Crocus to reproduce the occurrence of these events in a 1D configuration. We created a database of blowing snow events observed over 10 years at our experimental site. Occurrences of blowing snow events were divided into cases with and without concurrent falling snow. Overall, snow transport is observed during 10.5% of the time in winter and occurs with concurrent falling snow 37.3% of the time. Wind speed and snow age control the frequency of occurrence. Model results illustrate the necessity of taking the wind-dependence of falling snow grain characteristics into account to simulate periods of snow transport and mass fluxes satisfactorily during those periods. The high rate of false alarms produced by the model is investigated in detail for winter 2010/2011 using measurements from snow particle counters.

Effects of multilayer snow scheme on the simulation of snow: Offline Noah and coupled with NCEP CFSv2

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Saha, Subodh Kumar; Sujith, K.; Pokhrel, Samir; Chaudhari, Hemantkumar S.; Hazra, Anupam

2017-03-01

The Noah version 2.7.1 is a moderately complex land surface model (LSM), with a single layer snowpack, combined with vegetation and underlying soil layer. Many previous studies have pointed out biases in the simulation of snow, which may hinder the skill of a forecasting system coupled with the Noah. In order to improve the simulation of snow by the Noah, a multilayer snow scheme (up to a maximum of six layers) is introduced. As Noah is the land surface component of the Climate Forecast System version 2 (CFSv2) of the National Centers for Environmental Prediction (NCEP), the modified Noah is also coupled with the CFSv2. The offline LSM shows large improvements in the simulation of snow depth, snow water equivalent (SWE), and snow cover area during snow season (October to June). CFSv2 with the modified Noah reveals a dramatic improvements in the simulation of snow depth and 2 m air temperature and moderate improvements in SWE. As suggested in the previous diagnostic and sensitivity study, improvements in the simulation of snow by CFSv2 have lead to the reduction in dry bias over the Indian subcontinent (by a maximum of 2 mm d-1). The multilayer snow scheme shows promising results in the simulation of snow as well as Indian summer monsoon rainfall and hence this development may be the part of the future version of the CFS.

The engineering approach to winter sports

CERN Document Server

Cheli, Federico; Maldifassi, Stefano; Melzi, Stefano; Sabbioni, Edoardo

2016-01-01

The Engineering Approach to Winter Sports presents the state-of-the-art research in the field of winter sports in a harmonized and comprehensive way for a diverse audience of engineers, equipment and facilities designers, and materials scientists. The book examines the physics and chemistry of snow and ice with particular focus on the interaction (friction) between sports equipment and snow/ice, how it is influenced by environmental factors, such as temperature and pressure, as well as by contaminants and how it can be modified through the use of ski waxes or the microtextures of blades or ski soles. The authors also cover, in turn, the different disciplines in winter sports:  skiing (both alpine and cross country), skating and jumping, bob sledding and skeleton, hockey and curling, with attention given to both equipment design and on the simulation of gesture and  track optimization.

Energy expenditure and clearing snow: a comparison of shovel and snow pusher.

Science.gov (United States)

Smolander, J; Louhevaara, V; Ahonen, E; Polari, J; Klen, T

1995-04-01

In order to assess the energy demands of manual clearing of snow, nine men did snow clearing work for 15 min with a shovel and a snow pusher. The depth of the snowcover was 400-600 mm representing a very heavy snowfall. Heart rate (HR), oxygen consumption (VO2), pulmonary ventilation (VE), respiratory exchange ratio (R), and rating of perceived exertion (RPE) were determined during the work tasks. HR, VE, R, and RPE were not significantly different between the shovel and snow pusher. HR averaged (+/- SD) 141 +/- 20 b min-1 with the shovel, and 142 +/- 19 beats.min-1 with the snow pusher. VO2 was 2.1 +/- 0.41.min-1 (63 +/- 12%VO2 max) in shovelling and 2.6 +/- 0.51.min-1 (75 +/- 14%VO2max) in snow pushing (p < 0.001). In conclusion manual clearing of snow in conditions representing heavy snowfalls was found to be strenuous physical work, not suitable for persons with cardiac risk factors, but which may serve as a mode of physical training in healthy adults.

Warming, soil moisture, and loss of snow increase Bromus tectorum’s population growth rate

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Aldo Compagnoni

2014-01-01

Full Text Available Abstract Climate change threatens to exacerbate the impacts of invasive species. In temperate ecosystems, direct effects of warming may be compounded by dramatic reductions in winter snow cover. Cheatgrass (Bromus tectorum is arguably the most destructive biological invader in basins of the North American Intermountain West, and warming could increase its performance through direct effects on demographic rates or through indirect effects mediated by loss of snow. We conducted a two-year experimental manipulation of temperature and snow pack to test whether 1 warming increases cheatgrass population growth rate and 2 reduced snow cover contributes to cheatgrass’ positive response to warming. We used infrared heaters operating continuously to create the warming treatment, but turned heaters on only during snowfalls for the snowmelt treatment. We monitored cheatgrass population growth rate and the vital rates that determine it: emergence, survival and fecundity. Growth rate increased in both warming and snowmelt treatments. The largest increases occurred in warming plots during the wettest year, indicating that the magnitude of response to warming depends on moisture availability. Warming increased both fecundity and survival, especially in the wet year, while snowmelt contributed to the positive effects of warming by increasing survival. Our results indicate that increasing temperature will exacerbate cheatgrass impacts, especially where warming causes large reductions in the depth and duration of snow cover.

Comparison of seasonal soil microbial process in snow-covered temperate ecosystems of northern China.

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Xinyue Zhang

Full Text Available More than half of the earth's terrestrial surface currently experiences seasonal snow cover and soil frost. Winter compositional and functional investigations in soil microbial community are frequently conducted in alpine tundra and boreal forest ecosystems. However, little information on winter microbial biogeochemistry is known from seasonally snow-covered temperate ecosystems. As decomposer microbes may differ in their ability/strategy to efficiently use soil organic carbon (SOC within different phases of the year, understanding seasonal microbial process will increase our knowledge of biogeochemical cycling from the aspect of decomposition rates and corresponding nutrient dynamics. In this study, we measured soil microbial biomass, community composition and potential SOC mineralization rates in winter and summer, from six temperate ecosystems in northern China. Our results showed a clear pattern of increased microbial biomass C to nitrogen (N ratio in most winter soils. Concurrently, a shift in soil microbial community composition occurred with higher fungal to bacterial biomass ratio and gram negative (G- to gram positive (G+ bacterial biomass ratio in winter than in summer. Furthermore, potential SOC mineralization rate was higher in winter than in summer. Our study demonstrated a distinct transition of microbial community structure and function from winter to summer in temperate snow-covered ecosystems. Microbial N immobilization in winter may not be the major contributor for plant growth in the following spring.

Concentrations and source regions of light-absorbing particles in snow/ice in northern Pakistan and their impact on snow albedo

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Gul, Chaman; Praveen Puppala, Siva; Kang, Shichang; Adhikary, Bhupesh; Zhang, Yulan; Ali, Shaukat; Li, Yang; Li, Xiaofei

2018-04-01

Black carbon (BC), water-insoluble organic carbon (OC), and mineral dust are important particles in snow and ice which significantly reduce albedo and accelerate melting. Surface snow and ice samples were collected from the Karakoram-Himalayan region of northern Pakistan during 2015 and 2016 in summer (six glaciers), autumn (two glaciers), and winter (six mountain valleys). The average BC concentration overall was 2130 ± 1560 ng g-1 in summer samples, 2883 ± 3439 ng g-1 in autumn samples, and 992 ± 883 ng g-1 in winter samples. The average water-insoluble OC concentration overall was 1839 ± 1108 ng g-1 in summer samples, 1423 ± 208 ng g-1 in autumn samples, and 1342 ± 672 ng g-1 in winter samples. The overall concentration of BC, OC, and dust in aged snow samples collected during the summer campaign was higher than the concentration in ice samples. The values are relatively high compared to reports by others for the Himalayas and the Tibetan Plateau. This is probably the result of taking more representative samples at lower elevation where deposition is higher and the effects of ageing and enrichment are more marked. A reduction in snow albedo of 0.1-8.3 % for fresh snow and 0.9-32.5 % for aged snow was calculated for selected solar zenith angles during daytime using the Snow, Ice, and Aerosol Radiation (SNICAR) model. The daily mean albedo was reduced by 0.07-12.0 %. The calculated radiative forcing ranged from 0.16 to 43.45 W m-2 depending on snow type, solar zenith angle, and location. The potential source regions of the deposited pollutants were identified using spatial variance in wind vector maps, emission inventories coupled with backward air trajectories, and simple region-tagged chemical transport modeling. Central, south, and west Asia were the major sources of pollutants during the sampling months, with only a small contribution from east Asia. Analysis based on the Weather Research and Forecasting (WRF-STEM) chemical transport model identified a

Vancouver winters: Environmental influences on inpatient adult orthopaedic trauma demographics

International Nuclear Information System (INIS)

Noordin, S.; Masri, B. A.

2014-01-01

Objective: To compare the pattern of adult inpatient orthopaedic injuries admitted at three Vancouver hospitals following one of the worst winter snowstorms in the region with the preceding control winter period. Methods: The surveillance study was conducted at the University of British Columbia, Vancouver, Canada, 2007 to 2010. Inpatient adult admissions for orthopaedic injuries at three hospitals were recorded, including age, gender, anatomic location of injury, type of fracture (open or closed), fixation method (internal versus external fixation), and length of acute care hospital stay. Comparisons between admissions during this weather pattern and admission during a previous winter with minimal snow were made. SPSS 19 was used for statistical analysis. Results: Of the 511 patients admitted under Orthopaedic trauma service during the significant winter snowstorms of December 2008 - January 2009, 100 (19.6%) (CI: 16.2%-23.2%) were due to ice and snow, whereas in the preceding mild winter only 18 of 415 (4.3%) (CI: 2.5%-6.8%) cases were related to snow (p<0.05). Ankle and wrist fractures were the most frequent injuries during the index snow storm period (p<0.05). At all the three institutions, 97 (96.5%) fractures were closed during the snowstorm as opposed to 17 (95%) during the control winter period. Internal fixation in 06 (89%) fractures as opposed to external fixation in 12 (11%) patients was the predominant mode of fixation across the board during both time periods. Conclusion: The study demonstrated a significantly higher inpatient orthopaedic trauma volume during the snowstorm more rigorous prospective studies need to be designed to gain further insight to solving these problems from a public health perspective. (author)

Cloud-based Computing and Applications of New Snow Metrics for Societal Benefit

Science.gov (United States)

Nolin, A. W.; Sproles, E. A.; Crumley, R. L.; Wilson, A.; Mar, E.; van de Kerk, M.; Prugh, L.

2017-12-01

Seasonal and interannual variability in snow cover affects socio-environmental systems including water resources, forest ecology, freshwater and terrestrial habitat, and winter recreation. We have developed two new seasonal snow metrics: snow cover frequency (SCF) and snow disappearance date (SDD). These metrics are calculated at 500-m resolution using NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data (MOD10A1). SCF is the number of times snow is observed in a pixel over the user-defined observation period. SDD is the last date of observed snow in a water year. These pixel-level metrics are calculated rapidly and globally in the Google Earth Engine cloud-based environment. SCF and SDD can be interactively visualized in a map-based interface, allowing users to explore spatial and temporal snowcover patterns from 2000-present. These metrics are especially valuable in regions where snow data are sparse or non-existent. We have used these metrics in several ongoing projects. When SCF was linked with a simple hydrologic model in the La Laguna watershed in northern Chile, it successfully predicted summer low flows with a Nash-Sutcliffe value of 0.86. SCF has also been used to help explain changes in Dall sheep populations in Alaska where sheep populations are negatively impacted by late snow cover and low snowline elevation during the spring lambing season. In forest management, SCF and SDD appear to be valuable predictors of post-wildfire vegetation growth. We see a positive relationship between winter SCF and subsequent summer greening for several years post-fire. For western US winter recreation, we are exploring trends in SDD and SCF for regions where snow sports are economically important. In a world with declining snowpacks and increasing uncertainty, these metrics extend across elevations and fill data gaps to provide valuable information for decision-making. SCF and SDD are being produced so that anyone with Internet access and a Google

Water and life from snow: A trillion dollar science question

Science.gov (United States)

Sturm, Matthew; Goldstein, Michael A.; Parr, Charles

2017-05-01

Snow provides essential resources/services in the form of water for human use, and climate regulation in the form of enhanced cooling of the Earth. In addition, it supports a thriving winter outdoor recreation industry. To date, the financial evaluation of the importance of snow is incomplete and hence the need for accelerated snow research is not as clear as it could be. With snow cover changing worldwide in several worrisome ways, there is pressing need to determine global, regional, and local rates of snow cover change, and to link these to financial analyses that allow for rational decision making, as risks related to those decisions involve trillions of dollars.

COSMO-SkyMed Image Investigation of Snow Features in Alpine Environment

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Simonetta Paloscia

2017-01-01

Full Text Available In this work, X band images acquired by COSMO-SkyMed (CSK on alpine environment have been analyzed for investigating snow characteristics and their effect on backscattering variations. Preliminary results confirmed the capability of simultaneous optical and Synthetic Aperture Radar (SAR images (Landsat-8 and CSK in separating snow/no-snow areas and in detecting wet snow. The sensitivity of backscattering to snow depth has not always been confirmed, depending on snow characteristics related to the season. A model based on Dense Media Radiative Transfer theory (DMRT-QMS was applied for simulating the backscattering response on the X band from snow cover in different conditions of grain size, snow density and depth. By using DMRT-QMS and snow in-situ data collected on Cordevole basin in Italian Alps, the effect of grain size and snow density, beside snow depth and snow water equivalent, was pointed out, showing that the snow features affect the backscatter in different and sometimes opposite ways. Experimental values of backscattering were correctly simulated by using this model and selected intervals of ground parameters. The relationship between simulated and measured backscattering for the entire dataset shows slope >0.9, determination coefficient, R2 = 0.77, and root mean square error, RMSE = 1.1 dB, with p-value <0.05.

Improvement of a snow albedo parameterization in the Snow-Atmosphere-Soil Transfer model: evaluation of impacts of aerosol on seasonal snow cover

Science.gov (United States)

Zhong, Efang; Li, Qian; Sun, Shufen; Chen, Wen; Chen, Shangfeng; Nath, Debashis

2017-11-01

The presence of light-absorbing aerosols (LAA) in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take this into consideration. To better represent the snow process and to evaluate the impacts of LAA on snow, this study presents an improved snow albedo parameterization in the Snow-Atmosphere-Soil Transfer (SAST) model, which includes the impacts of LAA on snow. Specifically, the Snow, Ice and Aerosol Radiation (SNICAR) model is incorporated into the SAST model with an LAA mass stratigraphy scheme. The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot (SASP), Colorado, USA. Results show that the snow albedo and snow depth are better reproduced than those in the original SAST, particularly during the period of snow ablation. Furthermore, the impacts of LAA on snow are estimated in the coupled model through case comparisons of the snowpack, with or without LAA. The LAA particles directly absorb extra solar radiation, which accelerates the growth rate of the snow grain size. Meanwhile, these larger snow particles favor more radiative absorption. The average total radiative forcing of the LAA at the SASP is 47.5 W m-2. This extra radiative absorption enhances the snowmelt rate. As a result, the peak runoff time and "snow all gone" day have shifted 18 and 19.5 days earlier, respectively, which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.

A Comparison of the SNICAR Radiative Transfer Model to In Situ Snow Characterization Measurements at Sites in New England, USA

Science.gov (United States)

Adolph, A. C.; Albert, M. R.; Dibb, J. E.; Lazarcik, J.; Amante, J.

2016-12-01

As a highly reflective material, snow serves as an important control on surface energy balance. Given the current changes in climate and the sensitivity of snow cover to rising temperatures, it is critical that we understand the role of snow and its associated feedbacks in the climate system. Much of snow albedo research has focused on polar or high altitude snow packs, but rapid changes are also occurring in temperate regions; in the northeastern United States of America, changing climate has resulted in shallower snow packs and fewer days of snow cover. As these changes occur and we seek to understand the associated implications for snow albedo within climate dynamics, it is imperative that we are able to accurately represent snow in models. The SNow, ICe, and Aerosol Radiation model (SNICAR), developed by Flanner and Zender (2005) and used in the IPCC assessments, provides upward and downward radiative fluxes of one or many snow layers based on the following inputs: snow depth, density, grain size, and impurity content; solar zenith angle; lighting conditions; and albedo of the surface beneath the snowpack. To our knowledge, the SNICAR model has not been validated with data from a mid-latitude temperate region. Through a measurement campaign that occurred from winter 2013-2016, we have collected over 400 independent observations of a suite of snow characterization measurements and spectral snow albedo from three different sites in New Hampshire, USA. Comparison of our spectral albedo measurements to the SNICAR albedo derived from measured snow properties and illumination conditions will allow for validation of the model or recommendations for improvement based on the sensitivities found in the data.

Merging datasets from NASA SnowEx to better understand how snow falls and moves.

Science.gov (United States)

Gongora, J. A.; Marshall, H. P.; Glenn, N. F.

2017-12-01

A modelers ability to estimated snow depth and snow water equivalent (SWE) for mountain snow depends strongly on their understanding of snowpack spatial distribution and the soundness of the models initial conditions. This work focuses on the application of data science and efficient algorithms to find optimal locations in mountainous terrain to act as initital conditions for machine driven interpolation methods. By using graphs, collections of pairwise relationships between objects, to describe our data we were able to efficiently search, partition, and understand snowpack from the persepetive of this data structure.

Blowing snow detection in Antarctica, from space borne and ground-based remote sensing

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Gossart, A.; Souverijns, N.; Lhermitte, S.; Lenaerts, J.; Gorodetskaya, I.; Schween, J. H.; Van Lipzig, N. P. M.

2017-12-01

Surface mass balance (SMB) strongly controls spatial and temporal variations in the Antarctic Ice Sheet (AIS) mass balance and its contribution to sea level rise. Currently, the scarcity of observational data and the challenges of climate modelling over the ice sheet limit our understanding of the processes controlling AIS SMB. Particularly, the impact of blowing snow on local SMB is not yet constrained and is subject to large uncertainties. To assess the impact of blowing snow on local SMB, we investigate the attenuated backscatter profiles from ceilometers at two East Antarctic locations in Dronning Maud Land. Ceilometers are robust ground-based remote sensing instruments that yield information on cloud base height and vertical structure, but also provide information on the particles present in the boundary layer. We developed a new algorithm to detect blowing snow (snow particles lifted by the wind from the surface to substantial height) from the ceilometer attenuated backscatter. The algorithm successfully allows to detect strong blowing snow signal from layers thicker than 15 m at the Princess Elisabeth (PE, (72°S, 23°E)) and Neumayer (70°S, 8° W) stations. Applying the algorithm to PE, we retrieve the frequency and annual cycle of blowing snow as well as discriminate between clear sky and overcast conditions during blowing snow. We further apply the blowing snow algorithm at PE to evaluate the blowing snow events detection by satellite imagery (Palm et al., 2011): the near-surface blowing snow layers are apparent in lidar backscatter profiles and enable snowdrift events detection (spatial and temporal frequency, height and optical depth). These data are processed from CALIPSO, at a high resolution (1x1 km digital elevation model). However, the remote sensing detection of blowing snow events by satellite is limited to layers of a minimal thickness of 20-30 m. In addition, thick clouds, mostly occurring during winter storms, can impede drifting snow

Changes in late-winter snowpack depth, water equivalent, and density in Maine, 1926-2004

Science.gov (United States)

Hodgkins, Glenn A.; Dudley, Robert W.

2006-03-01

Twenty-three snow-course sites in and near Maine, USA, with records spanning at least 50 years through to 2004 were tested for changes over time in snowpack depth, water equivalent, and density in March and April. Of the 23 sites, 18 had a significant decrease (Mann-Kendall test, p 1950s and 1960s, and densities peaked in the most recent decade. Previous studies in western North America also found a water-equivalent peak in the third quarter of the 20th century. Published in 2006 by John Wiley & Sons, Ltd.Received: 14 June 2005; Accepted: 7 October 2005

Characteristics of black carbon in snow from Laohugou No. 12 glacier on the northern Tibetan Plateau.

Science.gov (United States)

Zhang, Yulan; Kang, Shichang; Li, Chaoliu; Gao, Tanguang; Cong, Zhiyuan; Sprenger, Michael; Liu, Yajun; Li, Xiaofei; Guo, Junming; Sillanpää, Mika; Wang, Kun; Chen, Jizu; Li, Yang; Sun, Shiwei

2017-12-31

Black carbon (BC) emitted from the incomplete combustion of biomass and fossil fuel impacts the climate system, cryospheric change, and human health. This study documents black carbon deposition in snow from a benchmark glacier on the northern Tibetan Plateau. Significant seasonality of BC concentrations indicates different input or post-depositional processes. BC particles deposited in snow had a mass volume median diameter slightly larger than that of black carbon particles typically found in the atmosphere. Also, unlike black carbon particles in the atmosphere, the particles deposited in snow did not exhibit highly fractal morphology by Scanning Transmission Electron Microscope. Footprint analysis indicated BC deposited on the glacier in summer originated mainly from Central Asia; in winter, the depositing air masses generally originated from Central Asia and Pakistan. Anthropogenic emissions play an important role on black carbon deposition in glacial snow, especially in winter. The mass absorption efficiency of BC in snow at 632nm exhibited significantly seasonality, with higher values in summer and lower values in winter. The information on black carbon deposition in glacial snow provided in this study could be used to help mitigate the impacts of BC on glacier melting on the northern Tibetan Plateau. Copyright © 2017 Elsevier B.V. All rights reserved.

A Citizen Science Campaign to Validate Snow Remote-Sensing Products

Science.gov (United States)

Wikstrom Jones, K.; Wolken, G. J.; Arendt, A. A.; Hill, D. F.; Crumley, R. L.; Setiawan, L.; Markle, B.

2017-12-01

The ability to quantify seasonal water retention and storage in mountain snow packs has implications for an array of important topics, including ecosystem function, water resources, hazard mitigation, validation of remote sensing products, climate modeling, and the economy. Runoff simulation models, which typically rely on gridded climate data and snow remote sensing products, would be greatly improved if uncertainties in estimates of snow depth distribution in high-elevation complex terrain could be reduced. This requires an increase in the spatial and temporal coverage of observational snow data in high-elevation data-poor regions. To this end, we launched Community Snow Observations (CSO). Participating citizen scientists use Mountain Hub, a multi-platform mobile and web-based crowdsourcing application that allows users to record, submit, and instantly share geo-located snow depth, snow water equivalence (SWE) measurements, measurement location photos, and snow grain information with project scientists and other citizen scientists. The snow observations are used to validate remote sensing products and modeled snow depth distribution. The project's prototype phase focused on Thompson Pass in south-central Alaska, an important infrastructure corridor that includes avalanche terrain and the Lowe River drainage and is essential to the City of Valdez and the fisheries of Prince William Sound. This year's efforts included website development, expansion of the Mountain Hub tool, and recruitment of citizen scientists through a combination of social media outreach, community presentations, and targeted recruitment of local avalanche professionals. We also conducted two intensive field data collection campaigns that coincided with an aerial photogrammetric survey. With more than 400 snow depth observations, we have generated a new snow remote-sensing product that better matches actual SWE quantities for Thompson Pass. In the next phase of the citizen science portion of

Snow cover setting-up dates in the north of Eurasia: relations and feedback to the macro-scale atmospheric circulation

Directory of Open Access Journals (Sweden)

V. V. Popova

2014-01-01

Full Text Available Variations of snow cover onset data in 1950–2008 based on daily snow depth data collected at first-order meteorological stations of the former USSR compiled at the Russia Institute of Hydrometeorological Information are analyzed in order to reveal climatic norms, relations with macro-scale atmospheric circulation and influence of snow cover anomalies on strengthening/weakening of westerly basing on observational data and results of simulation using model Planet Simulator, as well. Patterns of mean snow cover setting-up data and their correlation with temperature of the Northern Hemisphere extra-tropical land presented in Fig. 1 show that the most sensible changes observed in last decade are caused by temperature trend since 1990th. For the most portion of the studied territory variations of snow cover setting-up data may be explained by the circulation indices in the terms of Northern Hemisphere Teleconnection Patterns: Scand, EA–WR, WP and NAO (Fig. 2. Role of the Scand and EA–WR (see Fig. 2, а, в, г is recognized as the most significant.Changes of snow cover extent calculated on the base of snow cover onset data over the Russia territory, and its western and eastern parts as well, for the second decade of October (Fig. 3 demonstrate significant difference in variability between eastern and western regions. Eastern part of territory essentially differs by lower both year-to-year and long-term variations in the contrast to the western part, characterized by high variance including long-term tendencies: increase in 1950–70th and decrease in 1970–80 and during last six years. Nevertheless relations between snow cover anomalies and Arctic Oscillation (AO index appear to be significant exceptionally for the eastern part of the territory. In the same time negative linear correlation revealed between snow extent and AO index changes during 1950–2008 from statistically insignificant values (in 1950–70 and 1996–2008 to coefficient

Snow melting system with electric heating using photovoltaic power generation; Solar yusetsuko

Energy Technology Data Exchange (ETDEWEB)

Sasaki, M; Fujita, S; Kaga, T; Koyama, N [Hachinohe Institute of Technology, Aomori (Japan)

1996-10-27

This paper clarifies the solar characteristics in Hachinohe district, to investigate a possibility of the snow melting system with electric heating using solar energy. Power demand for snow melting, power generated by the photovoltaic (PV) array, area of PV array, and working conditions of the system, as to temperature, precipitation and snowfall, were investigated. The percentage of sunshine is 44% in Hachinohe district, which has more fortunate natural condition for utilizing solar radiation compared with that of 20% in Aomori prefecture. The intensity of solar radiation in winter from December to March is around 500 W/m{sup 2} in average, which is equivalent to the quantity of solar radiation, around 2 kWh/m{sup 2} a day. When assuming that snow on the road surface is frozen at the snowfall under the air temperature below -3{degree}C, the occurrence frequency is 50% during January and February in Hachinohe district, which means one frozen day for two days and is equivalent to the occurrence frequency of frozen days, 34% in average during winter. The electric application ratio is 0.34 at the maximum in winter. That is, days of 34% for one month are required for snow melting. 3 figs., 3 tabs.

Improving automated disturbance maps using snow-covered landsat time series stacks

Science.gov (United States)

Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen

2012-01-01

Snow-covered winter Landsat time series stacks are used to develop a nonforest mask to enhance automated disturbance maps produced by the Vegetation Change Tracker (VCT). This method exploits the enhanced spectral separability between forested and nonforested areas that occurs with sufficient snow cover. This method resulted in significant improvements in Vegetation...

Snow Precipitation and Snow Cover Climatic Variability for the Period 1971–2009 in the Southwestern Italian Alps: The 2008–2009 Snow Season Case Study

Directory of Open Access Journals (Sweden)

Simona Fratianni

2010-10-01

Full Text Available Snow cover greatly influences the climate in the Alpine region and is one of the most relevant parameters for the climate change analysis. Nevertheless, snow precipitation variability is a relatively underexplored field of research because of the lack of long-term, continuous and homogeneous time series. After a historical research aiming to recover continuous records, three high quality time series of snow precipitation and snow depth recorded in the southwestern Italian Alps were analyzed. The comparison between the climatological indices over the 30 years reference period 1971–2000 and the decade 2000–2009 outlined a general decrease in the amount of snow precipitation, and a shift in the seasonal distribution of the snow precipitation in the most recent period. In the analysis of the last decade snow seasons characteristics, the attention was focused on the heavy snowfalls that occurred in Piedmont during the 2008–2009 snow season: MODerate resolution Imager Spectroradiometer (MODIS snow cover products were used to evaluate snow cover extension at different times during the snow season, and the results were set in relation to the temperatures.

Machine Learning on Images: Combining Passive Microwave and Optical Data to Estimate Snow Water Equivalent

Science.gov (United States)

Dozier, J.; Tolle, K.; Bair, N.

2014-12-01

We have a problem that may be a specific example of a generic one. The task is to estimate spatiotemporally distributed estimates of snow water equivalent (SWE) in snow-dominated mountain environments, including those that lack on-the-ground measurements. Several independent methods exist, but all are problematic. The remotely sensed date of disappearance of snow from each pixel can be combined with a calculation of melt to reconstruct the accumulated SWE for each day back to the last significant snowfall. Comparison with streamflow measurements in mountain ranges where such data are available shows this method to be accurate, but the big disadvantage is that SWE can only be calculated retroactively after snow disappears, and even then only for areas with little accumulation during the melt season. Passive microwave sensors offer real-time global SWE estimates but suffer from several issues, notably signal loss in wet snow or in forests, saturation in deep snow, subpixel variability in the mountains owing to the large (~25 km) pixel size, and SWE overestimation in the presence of large grains such as depth and surface hoar. Throughout the winter and spring, snow-covered area can be measured at sub-km spatial resolution with optical sensors, with accuracy and timeliness improved by interpolating and smoothing across multiple days. So the question is, how can we establish the relationship between Reconstruction—available only after the snow goes away—and passive microwave and optical data to accurately estimate SWE during the snow season, when the information can help forecast spring runoff? Linear regression provides one answer, but can modern machine learning techniques (used to persuade people to click on web advertisements) adapt to improve forecasts of floods and droughts in areas where more than one billion people depend on snowmelt for their water resources?

Estimation of Snow Particle Model Suitable for a Complex and Forested Terrain: Lessons from SnowEx

Science.gov (United States)

Gatebe, C. K.; Li, W.; Stamnes, K. H.; Poudyal, R.; Fan, Y.; Chen, N.

2017-12-01

SnowEx 2017 obtained consistent and coordinated ground and airborne remote sensing measurements over Grand Mesa in Colorado, which feature sufficient forested stands to have a range of density and height (and other forest conditions); a range of snow depth/snow water equivalent (SWE) conditions; sufficiently flat snow-covered terrain of a size comparable to airborne instrument swath widths. The Cloud Absorption Radiometer (CAR) data from SnowEx are unique and can be used to assess the accuracy of Bidirectional Reflectance-Distribution Functions (BRDFs) calculated by different snow models. These measurements provide multiple angle and multiple wavelength data needed for accurate surface BRDF characterization. Such data cannot easily be obtained by current satellite remote sensors. Compared to ground-based snow field measurements, CAR measurements minimize the effect of self-shading, and are adaptable to a wide variety of field conditions. We plan to use the CAR measurements as the validation data source for our snow modeling effort. By comparing calculated BRDF results from different snow models to CAR measurements, we can determine which model best explains the snow BRDFs, and is therefore most suitable for application to satellite remote sensing of snow parameters and surface energy budget calculations.

Snow chemistry of high altitude glaciers in the French Alps

OpenAIRE

MAUPETIT, FRANÇOIS; DELMAS, ROBERT J.

2011-01-01

Snow samples were collected as snowcores in the accumulation zone of four high altitude glaciers (2980–3540 m.a.s.l.) from each of the 4 highest mountain areas of the French Alps, during 3 consecutive years: 1989, 1990 and 1991. Sampling was performed in spring (∼ May), before the onset of late spring–summer percolation. The accumulated snow therefore reflects winter and spring conditions. A complementary sampling of fresh-snow was performed on an event basis, on one of the studied glaciers, ...

Use of gamma surveys from the aircraft for hydrological forecasts on the area with irregular snow pack

Energy Technology Data Exchange (ETDEWEB)

Vershinina, L K

1979-01-01

Gamma snow surveys from the aircraft based on the measurements of the attenuation of gamma-radiation of soils by the snow pack are discussed. Radiation rate depends on the amount of water on the soil surface and in the top layer 30 to 40 cm deep. Therefore, if measurements are made twice (without snow and with snow pack available) water equivalent of snow cover may be determined only when soil moisture content changes do not occur during the period between the dates of gamma surveys. In the areas with frequent winter thaws, standard land snow surveys do not provide snow storage evaluation with the accuracy sufficient for spring flow prediction. It is shown that when gamma-radiation of absolutely dry soils determined at the laboratory is known as well as of naturally moistened soils during the periods of gamma surveys of the snow pack from the aircraft, and when data is available on soil moisture content obtained from the measurements at the base land network, then a reliable estimation of snow storage on the watershed surfaces in the regions with irregular snow cover is quite possible. This ensures a significant accuracy increase of spring snow melt flood forecasting, particularly concerning winters with little snow.

Use of gamma surveys from the airraft for hydrological forecasts on the area with irregular snow pack

Energy Technology Data Exchange (ETDEWEB)

Vershinina, L K [State Hydrological Institute, Leningrad (USSR)

1979-01-01

Gamma snow surveys from aircraft based on the measurement of the attenuation of gamma-radiation of soils by the snow pack are discussed. Radiation rate depends on the amount of water on the soil surface and in the top layer 30 to 40 cm deep. Therefore, if measurements are made twice (without snow and with snow pack available) the water equivalent of the snow cover may be determined only in cases when soil moisture content changes do not occur during the period between the dates of gamma surveys. In areas with frequent winter thaws standard land snow surveys do not provide snow storage evaluation with accuracy sufficient for spring flow prediction. It is shown that when gamma-radiation of absolutely dry soils determined at the laboratory is known, as well as of naturally moistened soils during the periods of gamma surveys of the snow pack from aircraft, and when data is available on soil moisture content obtained from measurements at the base land network, then a reliable estimation of snow storage on the watershed surfaces in regions with irregular snow cover is quite possible. This ensures a significant accuracy increase in spring snow melt flood forecasting, in particular during winters with little snow.

Relocation of major ions in snow along the tundra-taiga ecotone

Energy Technology Data Exchange (ETDEWEB)

Pomeroy, J.W.; Marsh, P. (Environment Canada, Saskatoon (Canada)); Lesack, L. (Simon Fraser Univeristy, Burnaby, (Canada))

1993-01-01

The chemistry of seasonal snowcovers north of Unuvik, Northwest Territories, Canada was stratified by biophysical landscape. In this region, deposition of ions in winter occurs largely through the redistribution of wind-blown snow with accumulations in forest-edges and valley sides 8 to 12 times that of the open tundra. While dominated by this snow redistribution, the loading of most ions, except for SO[sub 4][sup 2-], does not scale exactly with that of snow, there being several mechanisms by which ion concentrations become relatively enriched or depleted in various landscape units. Vaporisation during temperature-gradient metamorphism in shallow-snow and uptake during either photochemical reactions or gaseous scavenging to well-exposed snow transformed concentrations of NO[sub 3][sup -] by 50%. Dry deposition of aerosols to forested terrain and valley bottoms enriched Cl[sup -], Na[sup +], Mg[sup 2]-[sup +], K[sup +] and Ca[sup 2+] concentrations up to more than two-fold, however scavenging of aerosols to blowing snow particles contributed an additional 40% to the sea-salt enrichment and 20% to the Ca[sup 2+] enrichment in wind-blown treeline forests. It is concluded that central measurements of snow chemistry in the Arctic cannot be reliably extrapolated without reference to changes caused by over-winter physical and chemical metamorphic processes. Associating the physical/chemical changes with readily identifiable Arctic landscape units suggests a simple and robust method for spatial extrapolation. (au) (26 refs.)

Physiochemical characterization of insoluble residues in California Sierra Nevada snow

Science.gov (United States)

Creamean, Jessie; Axson, Jessica; Bondy, Amy; Craig, Rebecca; May, Nathaniel; Shen, Hongru; Weber, Michael; Warner, Katy; Pratt, Kerri; Ault, Andrew

2015-04-01

The effects atmospheric aerosols have on cloud particle formation are dependent on both the aerosol physical and chemical characteristics. For instance, larger, irregular-shaped mineral dusts efficiently form cloud ice crystals, enhancing precipitation, whereas small, spherical pollution aerosols have the potential to form small cloud droplets that delay the autoconversion of cloudwater to precipitation. Thus, it is important to understand the physiochemical properties and sources of aerosols that influence cloud and precipitation formation. We present an in-depth analysis of the size, chemistry, and sources of soluble and insoluble residues found in snow collected at three locations in the California Sierra Nevada Mountains during the 2012/2013 winter season. For all sites, February snow samples contained high concentrations of regional pollutants such as ammonium nitrate and biomass burning species, while March snow samples were influenced by mineral dust. The snow at the lower elevation sites in closer proximity to the Central Valley of California were heavily influenced by agricultural and industrial emissions, whereas the highest elevation site was exposed to a mixture of Central Valley pollutants in addition to long-range transported dust from Asia and Africa. Further, air masses likely containing transported dust typically traveled over cloud top heights at the low elevation sites, but were incorporated into the cold (-28°C, on average) cloud tops more often at the highest elevation site, particularly in March, which we hypothesize led to enhanced ice crystal formation and thus the observation of dust in the snow collected at the ground. Overall, understanding the spatial and temporal dependence of aerosol sources is important for remote mountainous regions such as the Sierra Nevada where snowpack provides a steady, vital supply of water.

Evaluation of alternative snow plow cutting edges.

Science.gov (United States)

2009-05-01

With approximately 450 snow plow trucks, the Maine Department of Transportation (MaineDOT) uses in : excess of 10,000 linear feet of plow cutting edges each winter season. Using the 2008-2009 cost per linear : foot of $48.32, the Departments total co...

Constraining snowmelt in a temperature-index model using simulated snow densities

KAUST Repository

Bormann, Kathryn J.

2014-09-01

Current snowmelt parameterisation schemes are largely untested in warmer maritime snowfields, where physical snow properties can differ substantially from the more common colder snow environments. Physical properties such as snow density influence the thermal properties of snow layers and are likely to be important for snowmelt rates. Existing methods for incorporating physical snow properties into temperature-index models (TIMs) require frequent snow density observations. These observations are often unavailable in less monitored snow environments. In this study, previous techniques for end-of-season snow density estimation (Bormann et al., 2013) were enhanced and used as a basis for generating daily snow density data from climate inputs. When evaluated against 2970 observations, the snow density model outperforms a regionalised density-time curve reducing biases from -0.027gcm-3 to -0.004gcm-3 (7%). The simulated daily densities were used at 13 sites in the warmer maritime snowfields of Australia to parameterise snowmelt estimation. With absolute snow water equivalent (SWE) errors between 100 and 136mm, the snow model performance was generally lower in the study region than that reported for colder snow environments, which may be attributed to high annual variability. Model performance was strongly dependent on both calibration and the adjustment for precipitation undercatch errors, which influenced model calibration parameters by 150-200%. Comparison of the density-based snowmelt algorithm against a typical temperature-index model revealed only minor differences between the two snowmelt schemes for estimation of SWE. However, when the model was evaluated against snow depths, the new scheme reduced errors by up to 50%, largely due to improved SWE to depth conversions. While this study demonstrates the use of simulated snow density in snowmelt parameterisation, the snow density model may also be of broad interest for snow depth to SWE conversion. Overall, the

Constraining snowmelt in a temperature-index model using simulated snow densities

KAUST Repository

Bormann, Kathryn J.; Evans, Jason P.; McCabe, Matthew

2014-01-01

Current snowmelt parameterisation schemes are largely untested in warmer maritime snowfields, where physical snow properties can differ substantially from the more common colder snow environments. Physical properties such as snow density influence the thermal properties of snow layers and are likely to be important for snowmelt rates. Existing methods for incorporating physical snow properties into temperature-index models (TIMs) require frequent snow density observations. These observations are often unavailable in less monitored snow environments. In this study, previous techniques for end-of-season snow density estimation (Bormann et al., 2013) were enhanced and used as a basis for generating daily snow density data from climate inputs. When evaluated against 2970 observations, the snow density model outperforms a regionalised density-time curve reducing biases from -0.027gcm-3 to -0.004gcm-3 (7%). The simulated daily densities were used at 13 sites in the warmer maritime snowfields of Australia to parameterise snowmelt estimation. With absolute snow water equivalent (SWE) errors between 100 and 136mm, the snow model performance was generally lower in the study region than that reported for colder snow environments, which may be attributed to high annual variability. Model performance was strongly dependent on both calibration and the adjustment for precipitation undercatch errors, which influenced model calibration parameters by 150-200%. Comparison of the density-based snowmelt algorithm against a typical temperature-index model revealed only minor differences between the two snowmelt schemes for estimation of SWE. However, when the model was evaluated against snow depths, the new scheme reduced errors by up to 50%, largely due to improved SWE to depth conversions. While this study demonstrates the use of simulated snow density in snowmelt parameterisation, the snow density model may also be of broad interest for snow depth to SWE conversion. Overall, the

Ecosystem CO2 production during winter in a Swedish subarctic region: the relative importance of climate and vegetation type

DEFF Research Database (Denmark)

Grogan, Paul; Jonasson, Sven Evert

2006-01-01

General circulation models consistently predict that regional warming will be most rapid in the Arctic, that this warming will be predominantly in the winter season, and that it will often be accompanied by increasing snowfall. Paradoxically, despite the strong cold season emphasis in these predi...... will respond to climate change during winter because they indicate a threshold (~1 m) above which there would be little effect of increased snow accumulation on wintertime biogeochemical cycling....... in these predictions, we know relatively little about the plot and landscape-level controls on tundra biogeochemical cycling in wintertime as compared to summertime. We investigated the relative influence of vegetation type and climate on CO2 production rates and total wintertime CO2 release in the Scandinavian...... subarctic. Ecosystem respiration rates and a wide range of associated environmental and substrate pool size variables were measured in the two most common vegetation types of the region (birch understorey and heath tundra) at four paired sites along a 50 km transect through a strong snow depth gradient...

Ice fishing by wintering Bald Eagles in Arizona

Science.gov (United States)

Teryl G. Grubb; Roy G. Lopez

1997-01-01

Northern Arizona winters vary within and between years with occasional heavy snows (up to 0.6 m) and extreme cold (overnight lows -18 to -29°C) interspersed with dry periods, mild temperatures (daytime highs reaching 10°C), and general loss of snow cover at all but highest elevations. Lakes in the area may freeze and thaw partially or totally several times during a...

Impacts of extreme winter warming events on plant physiology in a sub-Arctic heath community.

Science.gov (United States)

Bokhorst, Stef; Bjerke, Jarle W; Davey, Matthew P; Taulavuori, Kari; Taulavuori, Erja; Laine, Kari; Callaghan, Terry V; Phoenix, Gareth K

2010-10-01

Insulation provided by snow cover and tolerance of freezing by physiological acclimation allows Arctic plants to survive cold winter temperatures. However, both the protection mechanisms may be lost with winter climate change, especially during extreme winter warming events where loss of snow cover from snow melt results in exposure of plants to warm temperatures and then returning extreme cold in the absence of insulating snow. These events cause considerable damage to Arctic plants, but physiological responses behind such damage remain unknown. Here, we report simulations of extreme winter warming events using infrared heating lamps and soil warming cables in a sub-Arctic heathland. During these events, we measured maximum quantum yield of photosystem II (PSII), photosynthesis, respiration, bud swelling and associated bud carbohydrate changes and lipid peroxidation to identify physiological responses during and after the winter warming events in three dwarf shrub species: Empetrum hermaphroditum, Vaccinium vitis-idaea and Vaccinium myrtillus. Winter warming increased maximum quantum yield of PSII, and photosynthesis was initiated for E. hermaphroditum and V. vitis-idaea. Bud swelling, bud carbohydrate decreases and lipid peroxidation were largest for E. hermaphroditum, whereas V. myrtillus and V. vitis-idaea showed no or less strong responses. Increased physiological activity and bud swelling suggest that sub-Arctic plants can initiate spring-like development in response to a short winter warming event. Lipid peroxidation suggests that plants experience increased winter stress. The observed differences between species in physiological responses are broadly consistent with interspecific differences in damage seen in previous studies, with E. hermaphroditum and V. myrtillus tending to be most sensitive. This suggests that initiation of spring-like development may be a major driver in the damage caused by winter warming events that are predicted to become more

Impacts of +2 °C global warming on winter tourism demand in Europe

NARCIS (Netherlands)

Damm, Andrea; Greuell, Wouter; Landgren, Oskar; Prettenthaler, Franz

2017-01-01

Increasing temperatures and snow scarce winter seasons challenge the winter tourism industry. In this study the impacts of +2 °C global warming on winter tourism demand in Europe's ski tourism related NUTS-3 regions are quantified. Using time series regression models, the relationship between

Simulating snow maps for Norway: description and statistical evaluation of the seNorge snow model

Directory of Open Access Journals (Sweden)

T. M. Saloranta

2012-11-01

Full Text Available Daily maps of snow conditions have been produced in Norway with the seNorge snow model since 2004. The seNorge snow model operates with 1 × 1 km resolution, uses gridded observations of daily temperature and precipitation as its input forcing, and simulates, among others, snow water equivalent (SWE, snow depth (SD, and the snow bulk density (ρ. In this paper the set of equations contained in the seNorge model code is described and a thorough spatiotemporal statistical evaluation of the model performance from 1957–2011 is made using the two major sets of extensive in situ snow measurements that exist for Norway. The evaluation results show that the seNorge model generally overestimates both SWE and ρ, and that the overestimation of SWE increases with elevation throughout the snow season. However, the R²-values for model fit are 0.60 for (log-transformed SWE and 0.45 for ρ, indicating that after removal of the detected systematic model biases (e.g. by recalibrating the model or expressing snow conditions in relative units the model performs rather well. The seNorge model provides a relatively simple, not very data-demanding, yet nonetheless process-based method to construct snow maps of high spatiotemporal resolution. It is an especially well suited alternative for operational snow mapping in regions with rugged topography and large spatiotemporal variability in snow conditions, as is the case in the mountainous Norway.

Studies of diffuse and direct solar radiation over snow

International Nuclear Information System (INIS)

Wesely, M.L.; Everett, R.G.

1976-01-01

Two interesting questions can be addressed by examination of solar radiation records obtained while the surface is covered with snow. One concerns the extent to which airborne particulate matter affects solar radiation received at the surface during winter conditions that are typical of those in the northeastern quarter of the United States. The other relates to the importance of complicated light scatterng in the earth-atmosphere system when the surface albedo is large. With the snow surface reflecting 50% or more of the incident radiation, it is likely that a significant addition to diffuse radiation would result from light that is reflected from the surface and then scattered back to the earth by the atmosphere. Preliminary data from measurements made during the winter of 1975 to 1976 are reported

Characteristics of Heavy Snowfall and Snow Crystal Habits in the ESSAY (Experiment on Snow Storms At Yeongdong) Campaign in Korea

Science.gov (United States)

Koh, D.

2016-12-01

The Yeongdong region in Korea has frequent heavy snowfall in winter, which usually results in societal and economic damages such as collapses of the greenhouse and the temporary building due to heavy snowfall weights and traffic accidents due to snow-slippery road condition. Therefore we have conducted an intensive measurement campaign of `Experiment on Snow Storms At Yeongdong (ESSAY)' using radiosonde soundings, several remote sensors and a digital camera with a magnifier for taking a photograph of snowfall crystals in the region. The analysis period is mainly limited to every winter from 2014 to 2016The typical synoptic situation for the heavy snowfall is Low pressure system passing by the far South of the Korean peninsula along with the Siberian High extending to northern Japan, leading to the northeasterly or easterly flows frequently accompanied by the long-lasting snowfall in the Yeongdong region. The snow crystal habits observed in the ESSAY campaign are mainly dendrite, consisting of about 70% of the entire habits, indicative of relatively warmer East Sea effect. Meanwhile, the rimed habits are frequently captured specifically when two-layered clouds are observed. The homogeneous habit such as dendrite is shown in case of shallow clouds with its thickness below 500 m, whereas various habits are captured such as graupel, dendrites, rimed dendrites, etc in the thicker cloud with its thickness greater than 1.5 km. The association of snow crystal habits with temperature and supersaturation in the cloud will be more discussed.

Velocity distribution in snow avalanches

Science.gov (United States)

Nishimura, K.; Ito, Y.

1997-12-01

In order to investigate the detailed structure of snow avalanches, we have made snow flow experiments at the Miyanomori ski jump in Sapporo and systematic observations in the Shiai-dani, Kurobe Canyon. In the winter of 1995-1996, a new device to measure static pressures was used to estimate velocities in the snow cloud that develops above the flowing layer of avalanches. Measurements during a large avalanche in the Shiai-dani which damaged and destroyed some instruments indicate velocities increased rapidly to more than 50 m/s soon after the front. Velocities decreased gradually in the following 10 s. Velocities of the lower flowing layer were also calculated by differencing measurement of impact pressure. Both recordings in the snow cloud and in the flowing layer changed with a similar trend and suggest a close interaction between the two layers. In addition, the velocity showed a periodic change. Power spectrum analysis of the impact pressure and the static pressure depression showed a strong peak at a frequency between 4 and 6 Hz, which might imply the existence of either ordered structure or a series of surges in the flow.

SWEAT: Snow Water Equivalent with AlTimetry

Science.gov (United States)

Agten, Dries; Benninga, Harm-Jan; Diaz Schümmer, Carlos; Donnerer, Julia; Fischer, Georg; Henriksen, Marie; Hippert Ferrer, Alexandre; Jamali, Maryam; Marinaci, Stefano; Mould, Toby JD; Phelan, Liam; Rosker, Stephanie; Schrenker, Caroline; Schulze, Kerstin; Emanuel Telo Bordalo Monteiro, Jorge

2017-04-01

To study how the water cycle changes over time, satellite and airborne remote sensing missions are typically employed. Over the last 40 years of satellite missions, the measurement of true water inventories stored in sea and land ice within the cryosphere have been significantly hindered by uncertainties introduced by snow cover. Being able to determine the thickness of this snow cover would act to reduce such error, improving current estimations of hydrological and climate models, Earth's energy balance (albedo) calculations and flood predictions. Therefore, the target of the SWEAT (Snow Water Equivalent with AlTimetry) mission is to directly measure the surface Snow Water Equivalent (SWE) on sea and land ice within the polar regions above 60°and below -60° latitude. There are no other satellite missions currently capable of directly measuring SWE. In order to achieve this, the proposed mission will implement a novel combination of Ka- and Ku-band radioaltimeters (active microwave sensors), capable of penetrating into the snow microstructure. The Ka-band altimeter (λ ≈ 0.8 cm) provides a low maximum snow pack penetration depth of up to 20 cm for dry snow at 37 GHz, since the volume scattering of snow dominates over the scattering caused by the underlying ice surface. In contrast, the Ku-band altimeter (λ ≈ 2 cm) provides a high maximum snowpack penetration depth of up to 15 m in high latitudes regions with dry snow, as volume scattering is decreased by a factor of 55. The combined difference in Ka- and Ku-band signal penetration results will provide more accurate and direct determination of SWE. Therefore, the SWEAT mission aims to improve estimations of global SWE interpreted from passive microwave products, and improve the reliability of numerical snow and climate models.

Aerosol optical depth retrieval over snow using AATSR data

NARCIS (Netherlands)

Mei, L.; Xue, Y.; Kokhanovsky, A.A.; Hoyningen-Huene, W. von; Istomina, L.; Leeuw, G. de; Burrows, J.P.; Guang, J.; Jing, Y.

2013-01-01

Aerosol observations over the Arctic are important because of the effects of aerosols on Arctic climate, such as their direct and indirect effects on the Earth's radiation balance and on snow albedo. Although information on aerosol properties is available from ground-based measurements, passive

Spatiotemporal variability of snow cover and snow water equivalent in the last three decades over Eurasia

Science.gov (United States)

Zhang, Yinsheng; Ma, Ning

2018-04-01

Changes in the extent and amount of snow cover in Eurasia are of great interest because of their vital impacts on the global climate system and regional water resource management. This study investigated the spatial and temporal variability of the snow cover extent (SCE) and snow water equivalent (SWE) of the continental Eurasia using the Northern Hemisphere Equal-Area Scalable Earth Grid (EASE-Grid) Weekly SCE data for 1972-2006 and the Global Monthly EASE-Grid SWE data for 1979-2004. The results indicated that, in general, the spatial extent of snow cover significantly decreased during spring and summer, but varied little during autumn and winter over Eurasia in the study period. The date at which snow cover began to disappear in spring has significantly advanced, whereas the timing of snow cover onset in autumn did not vary significantly during 1972-2006. The snow cover persistence period declined significantly in the western Tibetan Plateau as well as partial area of Central Asia and northwestern Russia, but varied little in other parts of Eurasia. "Snow-free breaks" (SFBs) with intermittent snow cover in the cold season were principally observed in the Tibetan Plateau and Central Asia, causing a low sensitivity of snow cover persistence period to the timings of snow cover onset and disappearance over the areas with shallow snow. The averaged SFBs were 1-14 weeks during the study period and the maximum intermittence could even reach 25 weeks in certain years. At a seasonal scale, SWE usually peaked in February or March, but fell gradually since April across Eurasia. Both annual mean and annual maximum SWE decreased significantly during 1979-2004 in most parts of Eurasia except for eastern Siberia as well as northwestern and northeastern China. The possible cross-platform inconsistencies between two passive microwave radiometers may cause uncertainties in the detected trends of SWE here, suggesting an urgent need of producing a long-term, more homogeneous SWE

ULUDAĞ WINTER TOURISM and ITS IMPORTANCE IN THE ECONOMIC DEVELOPMENT

Directory of Open Access Journals (Sweden)

Sema AY

2016-08-01

Full Text Available Tourism that is a regional means of development is closely related with the local economic development. Winter tourism is a set of activities and relationships composed of trips made to the regions which are located in the heart of ski sports and accordingly with slopes and snow, accommodations and other services. Since winter tourism mainly consists of a number of activities depending on snowy environments, it requires locations with certain height and slope which will also allow the execution of other nature sports such as walking, climbing etc. besides skiing and snowboarding. Uludağ, the most popular winter sports center that is 30 km away from the Bursa city center has significant natural advantages in terms of winter tourism. However, with the recently changing tourism demands in winter tourism, developments have been taking place in the types of tourism. Uludağ having natural advantages have not been able to sufficiently benefit from these advantages and cannot make use of its existing potential. Besides the countries having sucessful snow resorts of Europe such as Austria, France, Switzerland, Italy and Andorra, Romania and Bulgaria are also increasing their competitiveness in the international markets in recent years with ambitious investments. When Uludağ that is in the location of the largest snow resort in Turkey is compared with these resorts, it is thought that there is a way to go in the field of winter tourism. Starting from this idea, in the research, it is aimed to identify the contribution of Uludağ to the local economic development and the potentials for increasing this contribution. Towards the mentioned aim, the study will be carried out based on field research. In the conclusion of the study, it is planned to submit the proposals focused on policy and strategy to be followed in terms of having Uludağ use its potential in the most efficient way and provide more contribution to the local economy. In addition, its

Analysis of the Lake Superior Watershed Seasonal Snow Cover

National Research Council Canada - National Science Library

Daly, Steven F; Baldwin, Timothy B; Weyrick, Patricia

2007-01-01

Daily estimates of the snow water equivalent (SWE) distribution for the period from 1 December through 30 April for each winter season from 1979 80 through 2002 03 were calculated for the entire Lake Superior watershed...

Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10): a World Weather Research Programme Project

Science.gov (United States)

Isaac, G. A.; Joe, P. I.; Mailhot, J.; Bailey, M.; Bélair, S.; Boudala, F. S.; Brugman, M.; Campos, E.; Carpenter, R. L.; Crawford, R. W.; Cober, S. G.; Denis, B.; Doyle, C.; Reeves, H. D.; Gultepe, I.; Haiden, T.; Heckman, I.; Huang, L. X.; Milbrandt, J. A.; Mo, R.; Rasmussen, R. M.; Smith, T.; Stewart, R. E.; Wang, D.; Wilson, L. J.

2014-01-01

A World Weather Research Programme (WWRP) project entitled the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) was developed to be associated with the Vancouver 2010 Olympic and Paralympic Winter Games conducted between 12 February and 21 March 2010. The SNOW-V10 international team augmented the instrumentation associated with the Winter Games and several new numerical weather forecasting and nowcasting models were added. Both the additional observational and model data were available to the forecasters in real time. This was an excellent opportunity to demonstrate existing capability in nowcasting and to develop better techniques for short term (0-6 h) nowcasts of winter weather in complex terrain. Better techniques to forecast visibility, low cloud, wind gusts, precipitation rate and type were evaluated. The weather during the games was exceptionally variable with many periods of low visibility, low ceilings and precipitation in the form of both snow and rain. The data collected should improve our understanding of many physical phenomena such as the diabatic effects due to melting snow, wind flow around and over terrain, diurnal flow reversal in valleys associated with daytime heating, and precipitation reductions and increases due to local terrain. Many studies related to these phenomena are described in the Special Issue on SNOW-V10 for which this paper was written. Numerical weather prediction and nowcast models have been evaluated against the unique observational data set now available. It is anticipated that the data set and the knowledge learned as a result of SNOW-V10 will become a resource for other World Meteorological Organization member states who are interested in improving forecasts of winter weather.

Estimating snow water equivalent (SWE) using interferometric synthetic aperture radar (InSAR)

Science.gov (United States)

Deeb, Elias J.

Since the early 1990s, radar interferometry and interferometric synthetic aperture radar (InSAR) have been used extensively to measure changes in the Earth's surface. Previous research has presented theory for estimating snow properties, including potential for snow water equivalent (SWE) retrieval, using InSAR. The motivation behind using remote sensing to estimate SWE is to provide a more complete, continuous set of "observations" to assist in water management operations, climate change studies, and flood hazard forecasting. The research presented here primarily investigates the feasibility of using the InSAR technique at two different wavelengths (C-Band and L-Band) for SWE retrieval of dry snow within the Kuparuk watershed, North Slope, Alaska. Estimating snow distribution around meteorological towers on the coastal plain using a three-day repeat orbit of C-Band InSAR data was successful (Chapter 2). A longer wavelength L-band SAR is evaluated for SWE retrievals (Chapter 3) showing the ability to resolve larger snow accumulation events over a longer period of time. Comparisons of InSAR estimates and late spring manual sampling of SWE show a R2 = 0.61 when a coherence threshold is used to eliminate noisy SAR data. Qualitative comparisons with a high resolution digital elevation model (DEM) highlight areas of scour on windward slopes and areas of deposition on leeward slopes. When compared to a mid-winter transect of manually sampled snow depths, the InSAR SWE estimates yield a RMSE of 2.21cm when a bulk snow density is used and corrections for bracketing the satellite acquisition timing is performed. In an effort to validate the interaction of radar waves with a snowpack, the importance of the "dry snow" assumption for the estimation of SWE using InSAR is tested with an experiment in Little Cottonwood Canyon, Alta, Utah (Chapter 5). Snow wetness is shown to have a significant effect on the velocity of propagation within the snowpack. Despite the radar

Extraordinary blowing snow transport events in East Antarctica

Energy Technology Data Exchange (ETDEWEB)

Scarchilli, Claudio; Agnoletto, Lucia [ENEA, Rome (Italy); Universita di Siena, Dipartimento di Scienze della Terra, Siena (Italy); Frezzotti, Massimo; Grigioni, Paolo; Silvestri, Lorenzo de [ENEA, Rome (Italy); Dolci, Stefano [CNR, Rome (Italy); Consorzio P.N.R.A. S.C.r.l., Rome (Italy)

2010-06-15

In the convergence slope/coastal areas of Antarctica, a large fraction of snow is continuously eroded and exported by wind to the atmosphere and into the ocean. Snow transport observations from instruments and satellite images were acquired at the wind convergence zone of Terra Nova Bay (East Antarctica) throughout 2006 and 2007. Snow transport features are well-distinguished in satellite images and can extend vertically up to 200 m as first-order quantitatively estimated by driftometer sensor FlowCapt trademark. Maximum snow transportation occurs in the fall and winter seasons. Snow transportation (drift/blowing) was recorded for {proportional_to}80% of the time, and 20% of time recorded, the flux is >10{sup -2} kg m{sup -2} s{sup -1} with particle density increasing with height. Cumulative snow transportation is {proportional_to}4 orders of magnitude higher than snow precipitation at the site. An increase in wind speed and transportation ({proportional_to}30%) was observed in 2007, which is in agreement with a reduction in observed snow accumulation. Extensive presence of ablation surface (blue ice and wind crust) upwind and downwind of the measurement site suggest that the combine processes of blowing snow sublimation and snow transport remove up to 50% of the precipitation in the coastal and slope convergence area. These phenomena represent a major negative effect on the snow accumulation, and they are not sufficiently taken into account in studies of surface mass balance. The observed wind-driven ablation explains the inconsistency between atmospheric model precipitation and measured snow accumulation value. (orig.)

Warmer and wetter winters: characteristics and implications of an extreme weather event in the High Arctic

International Nuclear Information System (INIS)

Hansen, Brage B; Isaksen, Ketil; Benestad, Rasmus E; Kohler, Jack; Pedersen, Åshild Ø; Loe, Leif E; Coulson, Stephen J; Larsen, Jan Otto; Varpe, Øystein

2014-01-01

One predicted consequence of global warming is an increased frequency of extreme weather events, such as heat waves, droughts, or heavy rainfalls. In parts of the Arctic, extreme warm spells and heavy rain-on-snow (ROS) events in winter are already more frequent. How these weather events impact snow-pack and permafrost characteristics is rarely documented empirically, and the implications for wildlife and society are hence far from understood. Here we characterize and document the effects of an extreme warm spell and ROS event that occurred in High Arctic Svalbard in January–February 2012, during the polar night. In this normally cold semi-desert environment, we recorded above-zero temperatures (up to 7 °C) across the entire archipelago and record-breaking precipitation, with up to 98 mm rainfall in one day (return period of >500 years prior to this event) and 272 mm over the two-week long warm spell. These precipitation amounts are equivalent to 25 and 70% respectively of the mean annual total precipitation. The extreme event caused significant increase in permafrost temperatures down to at least 5 m depth, induced slush avalanches with resultant damage to infrastructure, and left a significant ground-ice cover (∼5–20 cm thick basal ice). The ground-ice not only affected inhabitants by closing roads and airports as well as reducing mobility and thereby tourism income, but it also led to high starvation-induced mortality in all monitored populations of the wild reindeer by blocking access to the winter food source. Based on empirical-statistical downscaling of global climate models run under the moderate RCP4.5 emission scenario, we predict strong future warming with average mid-winter temperatures even approaching 0 °C, suggesting increased frequency of ROS. This will have far-reaching implications for Arctic ecosystems and societies through the changes in snow-pack and permafrost properties. (letter)

Warmer and wetter winters: characteristics and implications of an extreme weather event in the High Arctic

Science.gov (United States)

Hansen, Brage B.; Isaksen, Ketil; Benestad, Rasmus E.; Kohler, Jack; Pedersen, Åshild Ø.; Loe, Leif E.; Coulson, Stephen J.; Larsen, Jan Otto; Varpe, Øystein

2014-11-01

One predicted consequence of global warming is an increased frequency of extreme weather events, such as heat waves, droughts, or heavy rainfalls. In parts of the Arctic, extreme warm spells and heavy rain-on-snow (ROS) events in winter are already more frequent. How these weather events impact snow-pack and permafrost characteristics is rarely documented empirically, and the implications for wildlife and society are hence far from understood. Here we characterize and document the effects of an extreme warm spell and ROS event that occurred in High Arctic Svalbard in January-February 2012, during the polar night. In this normally cold semi-desert environment, we recorded above-zero temperatures (up to 7 °C) across the entire archipelago and record-breaking precipitation, with up to 98 mm rainfall in one day (return period of >500 years prior to this event) and 272 mm over the two-week long warm spell. These precipitation amounts are equivalent to 25 and 70% respectively of the mean annual total precipitation. The extreme event caused significant increase in permafrost temperatures down to at least 5 m depth, induced slush avalanches with resultant damage to infrastructure, and left a significant ground-ice cover (˜5-20 cm thick basal ice). The ground-ice not only affected inhabitants by closing roads and airports as well as reducing mobility and thereby tourism income, but it also led to high starvation-induced mortality in all monitored populations of the wild reindeer by blocking access to the winter food source. Based on empirical-statistical downscaling of global climate models run under the moderate RCP4.5 emission scenario, we predict strong future warming with average mid-winter temperatures even approaching 0 °C, suggesting increased frequency of ROS. This will have far-reaching implications for Arctic ecosystems and societies through the changes in snow-pack and permafrost properties.

rboricultural aspects of snow-damage in the citz of Ljubljana in the winter 1999

OpenAIRE

Marion, Leon; Torelli, Niko; Oven, Primož

2005-01-01

As a result of heavy snow in February 1999, trees were damaged in the City of Ljubljana, Slovenia. Of the investigated 624 trees, 195 (31%) were damaged by snow. On average, 1.7 branch and top per tree were broken. Snow damaged 17 tree species, affecting particularly Aesculus hippocastanum L. and, to a lesser extent, Betula pendula ROTH. and Salix x sepulcralis SIMONK. Decay was the most frequent defect at the failure location and was often associated withincluded bark and vicinity of old mec...

Analysis of the snow-atmosphere energy balance during wet-snow instabilities and implications for avalanche prediction

Directory of Open Access Journals (Sweden)

C. Mitterer

2013-02-01

Full Text Available Wet-snow avalanches are notoriously difficult to predict; their formation mechanism is poorly understood since in situ measurements representing the thermal and mechanical evolution are difficult to perform. Instead, air temperature is commonly used as a predictor variable for days with high wet-snow avalanche danger – often with limited success. As melt water is a major driver of wet-snow instability and snow melt depends on the energy input into the snow cover, we computed the energy balance for predicting periods with high wet-snow avalanche activity. The energy balance was partly measured and partly modelled for virtual slopes at different elevations for the aspects south and north using the 1-D snow cover model SNOWPACK. We used measured meteorological variables and computed energy balance and its components to compare wet-snow avalanche days to non-avalanche days for four consecutive winter seasons in the surroundings of Davos, Switzerland. Air temperature, the net shortwave radiation and the energy input integrated over 3 or 5 days showed best results in discriminating event from non-event days. Multivariate statistics, however, revealed that for better predicting avalanche days, information on the cold content of the snowpack is necessary. Wet-snow avalanche activity was closely related to periods when large parts of the snowpack reached an isothermal state (0 °C and energy input exceeded a maximum value of 200 kJ m⁻² in one day, or the 3-day sum of positive energy input was larger than 1.2 MJ m⁻². Prediction accuracy with measured meteorological variables was as good as with computed energy balance parameters, but simulated energy balance variables accounted better for different aspects, slopes and elevations than meteorological data.

Influence of snow cover distribution on soil temperature and nutrient dynamics in alpine pedoenvironments

Directory of Open Access Journals (Sweden)

Ermanno Zanini

Full Text Available In Alpine sites snow is present on the ground from six to eight months per year in relation to elevation and exposure. Water is therefore immobilized into the solid state for the greater part of the winter season and released to the ground in a short period during spring snowmelt. In these areas, snow distribution exercises a fundamental role in influencing soil temperature and nutrient dynamics, in particular of nitrogen, with great consequences on plant nutrition. The dormant vegetation period, the low temperatures and the persistent snow cover suggest that soil biological activity is only concentrated during summer. As a matter of fact, soils covered with a consistent snow cover are isolated from the air temperature and can not freeze during winter. A snowpack of sufficient thickness, accumulated early in winter, insulates the ground from the surrounding atmosphere maintaining soil temperature closed to 0 °C during the whole winter season. The elevation of the snow line and the shorter permanence of snow on the ground, as a result of global warming (IPCC, 1996, 2001, might reduce the insulation effect of the snowpack, exposing soils of the mountain belt to lower temperatures and to a greater frequency of freeze/thaw cycles, which might alter organic matter dynamics and soil nutrient availability. Such thermal stresses may determine the lysis of microbial cells and the consequent increase of nitrogen and carbon mineralization by the survived microorganisms. Moreover, the freeze/thaw cycles can determine the exposure of exchange surfaces not available before, with release of organic matter of non-microbial origin, which may become available to surviving microorganisms for respiration. The reduced or absent microbial immobilization may cause the accumulation of remarkable amounts of inorganic nitrogen in soil, potentially leachable during spring snowmelt, when plants have not still started the growing season. Changes of snow distribution in

Surveying wolves without snow: a critical review of the methods used in Spain

OpenAIRE

Blanco, Juan Carlos; Cortés, Yolanda

2011-01-01

Wolves (Canis lupus) are difficult to survey, and in most countries, snow is used for identifying the species, counting individuals, recording movements and determining social position. However, in the Iberian peninsula and other southern regions of its gobal range, snow is very scarce in winter, so wolves must be surveyed without snow. In Spain and Portugal, wolves are surveyed through estimating number of wolf packs in summer by means of locating litters of pups when they are at rendezvous ...

Three-dimensional structural image analysis and mechanics of snow

OpenAIRE

Theile, Thiemo

2011-01-01

Summary This work deals with the problem of predicting the mechanical behaviour of dry snow based on the geometries and properties of its constituents. This approach is known as homogenisation. The main constituents of dry snow are ice and air. Their geometry, i.e. the microstructure, varies widely depending on the type of snow. The shape of individual, sintered snow grains varies and may take the form of stellar crystals, rounded and facetted grains or depth hoar crystals. ...

Snow as an accumulator of air pollutants

Science.gov (United States)

Robert T. Brown

1976-01-01

Using simple analytical techniques, the amounts of air pollutants accumulated in winter snow were determined and the results correlated with lichen survival on trees. Pollutants measured were particulate matter, sulfate, and chloride. An inverse relationship was found between amounts of each of these pollutants and the abundance of various lichens.

The Snowcloud System: Architecture and Algorithms for Snow Hydrology Studies

Science.gov (United States)

Skalka, C.; Brown, I.; Frolik, J.

2013-12-01

Snowcloud is an embedded data collection system for snow hydrology field research campaigns conducted in harsh climates and remote areas. The system combines distributed wireless sensor network technology and computational techniques to provide data at lower cost and higher spatio-temporal resolution than ground-based systems using traditional methods. Snowcloud has seen multiple Winter deployments in settings ranging from high desert to arctic, resulting in over a dozen node-years of practical experience. The Snowcloud system architecture consists of multiple TinyOS mesh-networked sensor stations collecting environmental data above and, in some deployments, below the snowpack. Monitored data modalities include snow depth, ground and air temperature, PAR and leaf-area index (LAI), and soil moisture. To enable power cycling and control of multiple sensors a custom power and sensor conditioning board was developed. The electronics and structural systems for individual stations have been designed and tested (in the lab and in situ) for ease of assembly and robustness to harsh winter conditions. Battery systems and solar chargers enable seasonal operation even under low/no light arctic conditions. Station costs range between 500 and 1000 depending on the instrumentation suite. For remote field locations, a custom designed hand-held device and data retrieval protocol serves as the primary data collection method. We are also developing and testing a Gateway device that will report data in near-real-time (NRT) over a cellular connection. Data is made available to users via web interfaces that also provide basic data analysis and visualization tools. For applications to snow hydrology studies, the better spatiotemporal resolution of snowpack data provided by Snowcloud is beneficial in several aspects. It provides insight into snowpack evolution, and allows us to investigate differences across different spatial and temporal scales in deployment areas. It enables the

Local Variability in Firn Layering and Compaction Rates Using GPR Data, Depth-Density Profiles, and In-Situ Reflectors in the Dry Snow Zone Near Summit Station, Greenland

Science.gov (United States)

Lines, A.; Elliott, J.; Ray, L.; Albert, M. R.

2017-12-01

Understanding the surface mass balance (SMB) of the Greenland ice sheet is critical to evaluating its response to a changing climate. A key factor in translating satellite and airborne elevation measurements of the ice sheet to SMB is understanding natural variability of firn layer depth and the relative compaction rate of these layers. A site near Summit Station, Greenland was chosen to investigate the variation in layering across a 100m by 100m grid using a 900 MHz and a 2.6 GHz ground penetrating radar (GPR) antenna. These radargrams were ground truthed by taking depth density profiles of five 2m snow pits and five 5m firn cores within the 100m by 100m grid. Combining these measurements with the accumulation data from the nearby ICECAPS weekly bamboo forest measurements, it's possible to see how the snow deposition from individual storm events can vary over a small area. Five metal reflectors were also placed on the surface of the snow in the bounds of the grid to serve as reference reflectors for similar measurements that will be taken in the 2018 field season at Summit Station. This will assist in understanding how one year of accumulation in the dry snow zone impacts compaction and how this rate can vary over a small area.

Dynamic-stochastic modeling of snow cover formation on the European territory of Russia

Directory of Open Access Journals (Sweden)

A. N. Gelfan

2014-01-01

Full Text Available A dynamic-stochastic model, which combines a deterministic model of snow cover formation with a stochastic weather generator, has been developed. The deterministic snow model describes temporal change of the snow depth, content of ice and liquid water, snow density, snowmelt, sublimation, re-freezing of melt water, and snow metamorphism. The model has been calibrated and validated against the long-term data of snow measurements over the territory of the European Russia. The model showed good performance in simulating time series of the snow water equivalent and snow depth. The developed weather generator (NEsted Weather Generator, NewGen includes nested generators of annual, monthly and daily time series of weather variables (namely, precipitation, air temperature, and air humidity. The parameters of the NewGen have been adjusted through calibration against the long-term meteorological data in the European Russia. A disaggregation procedure has been proposed for transforming parameters of the annual weather generator into the parameters of the monthly one and, subsequently, into the parameters of the daily generator. Multi-year time series of the simulated daily weather variables have been used as an input to the snow model. Probability properties of the snow cover, such as snow water equivalent and snow depth for return periods of 25 and 100 years, have been estimated against the observed data, showing good correlation coefficients. The described model has been applied to different landscapes of European Russia, from steppe to taiga regions, to show the robustness of the proposed technique.

"no snow - no skiing excursion - consequences of climatic change?"

Science.gov (United States)

Neunzig, Thilo

2014-05-01

Climatology and climate change have become central topics in Geography at our school. Because of that we set up a climatological station at our school. The data are an important basis to observe sudden changes in the weather. The present winter (2013/2014) shows the importance of climate change in Alzey / Germany. In winter many students think of the yearly skiing trip to Schwaz / Austria which is part of our school programme. Due to that the following questions arise: Will skiing still be possible if climate change accelerates? How are the skiing regions in the Alpes going to change? What will happen in about 20 years? How does artificial snow change the landscape and the skiing sport? Students have to be aware of the ecological damage of skiing trips. Each class has to come up with a concept how these trips can be as environmentally friendly as possible. - the trip is for a restricted number of students only (year 8 only) - a small skiing region is chosen which is not overcrowded - snow has to be guaranteed in the ski area to avoid the production of artificial snow (avoidance of high water consumption) - the bus arrives with a class and returns with the one that had been there before These are but a few ideas of students in order to make their trip as environmentally friendly as possible. What is missing is only what is going to happen in the future. What will be the effect of climate change for skiing regions in the secondary mountains? How is the average temperature for winter going to develop? Are there possibilities for summer tourism (e.g. hiking) instead of skiing in winter? The students are going to try to find answers to these questions which are going to be presented on a poster on the GIFT-Workshop in Vienna.

Pollution from the 2014-15 Bárðarbunga eruption monitored by snow cores from the Vatnajökull glacier, Iceland

Science.gov (United States)

Galeczka, Iwona; Eiriksdottir, Eydis Salome; Pálsson, Finnur; Oelkers, Eric; Lutz, Stefanie; Benning, Liane G.; Stefánsson, Andri; Kjartansdóttir, Ríkey; Gunnarsson-Robin, Jóhann; Ono, Shuhei; Ólafsdóttir, Rósa; Jónasdóttir, Elín Björk; Gislason, Sigurdur R.

2017-11-01

The chemical composition of Icelandic rain and snow is dominated by marine aerosols, however human and volcanic activity can also affect these compositions. The six month long 2014-15 Bárðarbunga volcanic eruption was the largest in Iceland for more than 200 years and it released into the atmosphere an average of 60 kt/day SO2, 30 kt/day CO2, 500 t/day HCl and 280 t/day HF. To study the effect of this eruption on the winter precipitation, snow cores were collected from the Vatnajökull glacier and the highlands northeast of the glacier. In addition to 29 bulk snow cores from that precipitated from September 2014 until March 2015, two cores were sampled in 21 and 44 increments to quantify the spatial and time evolution of the chemical composition of the snow. The pH and chemical compositions of melted snow samples indicate that snow has been affected by the volcanic gases emitted during the Bárðarbunga eruption. The pH of the melted bulk snow cores ranged from 4.41 to 5.64 with an average value of 5.01. This is four times greater H+ activity than pure water saturated with the atmospheric CO2. The highest concentrations of volatiles in the snow cores were found close to the eruption site as predicted from CALPUFF SO2 gas dispersion quality model. The anion concentrations (SO4, Cl, and F) were higher and the pH was lower compared to equivalent snow samples collected during 1997-2006 from the unpolluted Icelandic Langjökull glacier. Higher SO4 and Cl concentrations in the snow compared with the unpolluted rainwater of marine origin confirm the addition of a non-seawater SO4 and Cl. The δ34S isotopic composition confirms that the sulphur addition is of volcanic aerosol origin. The chemical evolution of the snow with depth reflects changes in the lava effusion and gas emission rates. Those rates were the highest at the early stage of the eruption. Snow that fell during that time, represented by samples from the deepest part of the snow cores, had the lowest pH and

Winter carbon dioxide effluxes from Arctic ecosystems: An overview and comparison of methodologies

DEFF Research Database (Denmark)

Björkman, M.P.; Morgner, E.; Cooper, E.J.

2010-01-01

removal, (3) diffusion measurements, F2-point, within the snowpack, and (4) a trace gas technique, FSF6, with multiple gas sampling within the snowpack. According to measurements collected from shallow and deep snow cover in High Arctic Svalbard and subarctic Sweden during the winter of 2007......The winter CO2 efflux from subnivean environments is an important component of annual C budgets in Arctic ecosystems and consequently makes prediction and estimations of winter processes as well as incorporations of these processes into existing models important. Several methods have been used......, Fsoil is assumed to measure soil production, whereas FSF6, Fsnow, and F2-point are considered better approaches for quantifying exchange processes between the soil, snow, and the atmosphere. This study indicates that estimates of winter CO2 emissions may vary more as a result of the method used than...

Projected changes of snow conditions and avalanche activity in a warming climate: a case study in the French Alps over the 2020-2050 and 2070-2100 periods

Science.gov (United States)

Castebrunet, H.; Eckert, N.; Giraud, G.; Durand, Y.; Morin, S.

2014-01-01

Projecting changes in snow cover due to climate warming is important for many societal issues, including adaptation of avalanche risk mitigation strategies. Efficient modeling of future snow cover requires high resolution to properly resolve the topography. Here, we detail results obtained through statistical downscaling techniques allowing simulations of future snowpack conditions for the mid- and late 21st century in the French Alps under three climate change scenarios. Refined statistical descriptions of snowpack characteristics are provided with regards to a 1960-1990 reference period, including latitudinal, altitudinal and seasonal gradients. These results are then used to feed a statistical model of avalanche activity-snow conditions-meteorological conditions relationships, so as to produce the first prognoses at annual/seasonal time scales of future natural avalanche activity eventually based on past observations. The resulting statistical indicators are fundamental for the mountain economy in terms of changes anticipation. At all considered spatio-temporal scales, whereas precipitations are expected to remain quite stationary, temperature increase interacting with topography will control snow-related variables, for instance the rate of decrease of total and dry snow depths, and the successive increase/decrease of the wet snow pack. Overall, with regards to the reference period, changes are strong for the end of the 21st century, but already significant for the mid-century. Changes in winter are somewhat less important than in spring, but wet snow conditions will appear at high elevations earlier in the season. For a given altitude, the Southern French Alps will not be significantly more affected than the Northern French Alps, so that the snowpack characteristics will be preserved more lately in the southern massifs of higher mean altitude. Regarding avalanche activity, a general -20-30% decrease and interannual variability is forecasted, relatively strong

Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss

Directory of Open Access Journals (Sweden)

Yurong Cui

2016-06-01

Full Text Available Snow water equivalent (SWE is a key parameter in the Earth’s energy budget and water cycle. It has been demonstrated that SWE can be retrieved using active microwave remote sensing from space. This necessitates the development of forward models that are capable of simulating the interactions of microwaves and the snow medium. Several proposed models have described snow as a collection of sphere- or ellipsoid-shaped ice particles embedded in air, while the microstructure of snow is, in reality, more complex. Natural snow usually forms a sintered structure following mechanical and thermal metamorphism processes. In this research, the bi-continuous vector radiative transfer (bi-continuous-VRT model, which firstly constructs snow microstructure more similar to real snow and then simulates the snow backscattering signal, is used as the forward model for SWE estimation. Based on this forward model, a parameterization scheme of snow volume backscattering is proposed. A relationship between snow optical thickness and single scattering albedo at X and Ku bands is established by analyzing the database generated from the bi-continuous-VRT model. A cost function with constraints is used to solve effective albedo and optical thickness, while the absorption part of optical thickness is obtained from these two parameters. SWE is estimated after a correction for physical temperature. The estimated SWE is correlated with the measured SWE with an acceptable accuracy. Validation against two-year measurements, using the SnowScat instrument from the Nordic Snow Radar Experiment (NoSREx, shows that the estimated SWE using the presented algorithm has a root mean square error (RMSE of 16.59 mm for the winter of 2009–2010 and 19.70 mm for the winter of 2010–2011.

Investigating the Relationships between Canopy Characteristics and Snow Depth Distribution at Fine Scales: Preliminary Results from the SnowEX TLS Campaign

Science.gov (United States)

Glenn, N. F.; Uhlmann, Z.; Spaete, L.; Tennant, C.; Hiemstra, C. A.; McNamara, J.

2017-12-01

Predicting changes in forested seasonal snowpacks under altered climate scenarios is one of the most pressing hydrologic challenges facing today's society. Airborne- and satellite-based remote sensing methods hold the potential to transform measurements of terrestrial water stores in snowpack, improve process representations of snowpack accumulation and ablation, and to generate high quality predictions that inform potential strategies to better manage water resources. While the effects of forest on snowpack are well documented, many of the fine-scale processes influenced by the forest-canopy are not directly accounted for because most snow models don't explicitly represent canopy structure and canopy heterogeneity. This study investigates the influence of forest canopy on snowpack distribution at fine scales and quantifies the influence of canopy heterogeneity on snowpack accumulation and ablation processes. We use terrestrial laser scanning (TLS) data collected during the SnowEX campaign to discover how the relationships between canopy and snow distributions change across scales. Our sample scales range from individual trees to patches of trees across the Grand Mesa, CO, SnowEx site.

An electrostatic charge measurement of blowing snow particles focusing on collision frequency to the snow surface

Science.gov (United States)

Omiya, S.; Sato, A.

2010-12-01

Blowing snow particles are known to have an electrostatic charge. This charge may be a contributing factor in the formation of snow drifts and snow cornices and changing of the trajectory of blowing snow particles. These formations and phenomena can cause natural disaster such as an avalanche and a visibility deterioration, and obstruct transportation during winter season. Therefore, charging phenomenon of the blowing snow particles is an important issue in terms of not only precise understanding of the particle motion but disaster prevention. The primary factor of charge accumulation to the blowing snow particles is thought to be due to “saltation” of them. The “saltation” is one of movement forms of blowing snow: when the snow particles are transported by the wind, they repeat frictional collisions with the snow surface. In previous studies, charge-to-mass ratios measured in the field were approximately -50 to -10 μC/kg, and in the wind tunnel were approximately -0.8 to -0.1 μC/kg. While there were qualitatively consistent in sign, negative, there were huge gaps quantitatively between them. One reason of those gaps is speculated to be due to differences in fetch. In other words, the difference of the collision frequency of snow particles to the snow surface has caused the gaps. But it is merely a suggestion and that has not been confirmed. The purpose of this experiment is to measure the charge of blowing snow particles focusing on the collision frequency and clarify the relationship between them. Experiments were carried out in the cryogenic wind tunnel of Snow and Ice Research Center (NIED, JAPAN). A Faraday cage and an electrometer were used to measure the charge of snow particles. These experiments were conducted over the hard snow surface condition to prevent the erosion of the snow surface and the generation of new snow particles from the surface. The collision frequency of particle was controlled by changing the wind velocity (4.5 to 7 m/s) under

Seasonal snow of arctic Alaska R4D investigations. Final report

Energy Technology Data Exchange (ETDEWEB)

Benson, C.S.

1993-02-01

Seasonal snow is present on the Arctic Slope of Alaska for nine months each year. Its presence or absence determines whether 80% of the solar radiation is reflected or absorbed, respectively. Although life on the Arctic Slope is adapted to, and in some cases dependent upon seasonal snow, little is known about it from a scientific point of view. Its quantity has been grossly underestimated, and knowledge of its distribution and the extent of wind transport and redistribution is very limited. This research project dealt with the amount, regional distribution and physical properties of wind blown snow and its biological role in the R4D area of the Arctic Slope. Physical processes which operate within the snow that were studied included the flux of heat and vapor and the fractionation of stable isotopes through it during fall and winter, and the complex heat and mass transfer within the snow and between snow, its substrate and the overlying atmosphere during the melt period.

Quantifying forest mortality with the remote sensing of snow

Science.gov (United States)

Baker, Emily Hewitt

Greenhouse gas emissions have altered global climate significantly, increasing the frequency of drought, fire, and pest-related mortality in forests across the western United States, with increasing area affected each year. Associated changes in forests are of great concern for the public, land managers, and the broader scientific community. These increased stresses have resulted in a widespread, spatially heterogeneous decline of forest canopies, which in turn exerts strong controls on the accumulation and melt of the snowpack, and changes forest-atmosphere exchanges of carbon, water, and energy. Most satellite-based retrievals of summer-season forest data are insufficient to quantify canopy, as opposed to the combination of canopy and undergrowth, since the signals of the two types of vegetation greenness have proven persistently difficult to distinguish. To overcome this issue, this research develops a method to quantify forest canopy cover using winter-season fractional snow covered area (FSCA) data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) snow covered area and grain size (MODSCAG) algorithm. In areas where the ground surface and undergrowth are completely snow-covered, a pixel comprises only forest canopy and snow. Following a snowfall event, FSCA initially rises, as snow is intercepted in the canopy, and then falls, as snow unloads. A select set of local minima in a winter F SCA timeseries form a threshold where canopy is snow-free, but forest understory is snow-covered. This serves as a spatially-explicit measurement of forest canopy, and viewable gap fraction (VGF) on a yearly basis. Using this method, we determine that MODIS-observed VGF is significantly correlated with an independent product of yearly crown mortality derived from spectral analysis of Landsat imagery at 25 high-mortality sites in northern Colorado. (r =0.96 +/-0.03, p =0.03). Additionally, we determine the lag timing between green-stage tree mortality and

Seasonal snow accumulation in the mid-latitude forested catchment

Czech Academy of Sciences Publication Activity Database

Šípek, Václav; Tesař, Miroslav

2014-01-01

Roč. 69, č. 11 (2014), s. 1562-1569 ISSN 0006-3088 R&D Projects: GA TA ČR TA02021451 Institutional support: RVO:67985874 Keywords : snow depth * snow water equivalent * forested catchment Subject RIV: DA - Hydrology ; Limnology Impact factor: 0.827, year: 2014

NOAA's National Snow Analyses

Science.gov (United States)

Carroll, T. R.; Cline, D. W.; Olheiser, C. M.; Rost, A. A.; Nilsson, A. O.; Fall, G. M.; Li, L.; Bovitz, C. T.

2005-12-01

NOAA's National Operational Hydrologic Remote Sensing Center (NOHRSC) routinely ingests all of the electronically available, real-time, ground-based, snow data; airborne snow water equivalent data; satellite areal extent of snow cover information; and numerical weather prediction (NWP) model forcings for the coterminous U.S. The NWP model forcings are physically downscaled from their native 13 km2 spatial resolution to a 1 km2 resolution for the CONUS. The downscaled NWP forcings drive an energy-and-mass-balance snow accumulation and ablation model at a 1 km2 spatial resolution and at a 1 hour temporal resolution for the country. The ground-based, airborne, and satellite snow observations are assimilated into the snow model's simulated state variables using a Newtonian nudging technique. The principle advantages of the assimilation technique are: (1) approximate balance is maintained in the snow model, (2) physical processes are easily accommodated in the model, and (3) asynoptic data are incorporated at the appropriate times. The snow model is reinitialized with the assimilated snow observations to generate a variety of snow products that combine to form NOAA's NOHRSC National Snow Analyses (NSA). The NOHRSC NSA incorporate all of the available information necessary and available to produce a "best estimate" of real-time snow cover conditions at 1 km2 spatial resolution and 1 hour temporal resolution for the country. The NOHRSC NSA consist of a variety of daily, operational, products that characterize real-time snowpack conditions including: snow water equivalent, snow depth, surface and internal snowpack temperatures, surface and blowing snow sublimation, and snowmelt for the CONUS. The products are generated and distributed in a variety of formats including: interactive maps, time-series, alphanumeric products (e.g., mean areal snow water equivalent on a hydrologic basin-by-basin basis), text and map discussions, map animations, and quantitative gridded products

Aircraft gamma-ray spectrometry in snow-water equivalent measurement

International Nuclear Information System (INIS)

Kuittinen, R.; Vironmaeki, J.

1979-01-01

During the winter periods 1976-1977 and 1977-1978 the Hydrological Office at the National Board of Waters and the Geological Survey of Finland carried out a joint study to evaluate usefuluess of gamma-ray spectrometry in snow-water equivalent measurement. A multichannel gamma-ray spectrometer was fitted in a DC-3 aircraft. Fourteen snow courses were operated using both the gravimetric method and the gamma-ray method. The snow courses were located in southern Finland in forest, swamp and agricultural land. The results shows that the gamma ray method can be considered suitable for use in Finnish conditions and the accuracy of the gamma-ray method is almost of the same magnitude as the accuracy of the gravimetric method. (Auth.)

Aircraft gamma-ray spectrometry in snow-water equivalent measurement

Energy Technology Data Exchange (ETDEWEB)

Kuittinen, R [National Board of Waters (Finland); Vironmaeki, J [Geological Survey of Finland

1979-01-01

During the winter periods 1976-1977 and 1977-1978 the Hydrological Office at the National Board of Waters and the Geological Survey of Finland carried out a joint study to evaluate usefuluess of gamma-ray spectrometry in snow-water equivalent measurement. A multichannel gamma-ray spectrometer was fitted in a DC-3 aircraft. Fourteen snow courses were operated using both the gravimetric method and the gamma-ray method. The snow courses were located in southern Finland in forest, swamp and agricultural land. The results shows that the gamma ray method can be considered suitable for use in Finnish conditions and the accuracy of the gamma-ray method is almost of the same magnitude as the accuracy of the gravimetric method.

Survival of rapidly fluctuating natural low winter temperatures by High Arctic soil invertebrates

DEFF Research Database (Denmark)

Convey, Peter; Abbandonato, Holly; Bergan, Frode

2015-01-01

The extreme polar environment creates challenges for its resident invertebrate communities and the stress tolerance of some of these animals has been examined over many years. However, although it is well appreciated that standard air temperature records often fail to describe accurately conditions...... microhabitats. To assess survival of natural High Arctic soil invertebrate communities contained in soil and vegetation cores to natural winter temperature variations, the overwintering temperatures they experienced were manipulated by deploying cores in locations with varying snow accumulation: No Snow...... and did not decrease below -12. °C. Those under deep snow were even more stable and did not decline below -2. °C. Despite these striking differences in winter thermal regimes, there were no clear differences in survival of the invertebrate fauna between treatments, including oribatid, prostigmatid...

Mass balance re-analysis of Findelengletscher, Switzerland; benefits of extensive snow accumulation measurements

Directory of Open Access Journals (Sweden)

Leo eSold

2016-02-01

Full Text Available A re-analysis is presented here of a 10-year mass balance series at Findelengletscher, a temperate mountain glacier in Switzerland. Calculating glacier-wide mass balance from the set of glaciological point balance observations using conventional approaches, such as the profile or contour method, resulted in significant deviations from the reference value given by the geodetic mass change over a five-year period. This is attributed to the sparsity of observations at high elevations and to the inability of the evaluation schemes to adequately estimate accumulation in unmeasured areas. However, measurements of winter mass balance were available for large parts of the study period from snow probings and density pits. Complementary surveys by helicopter-borne ground-penetrating radar (GPR were conducted in three consecutive years. The complete set of seasonal observations was assimilated using a distributed mass balance model. This model-based extrapolation revealed a substantial mass loss at Findelengletscher of -0.43m w.e. a^-1 between 2004 and 2014, while the loss was less pronounced for its former tributary, Adlergletscher (-0.30m w.e. a^-1. For both glaciers, the resulting time series were within the uncertainty bounds of the geodetic mass change. We show that the model benefited strongly from the ability to integrate seasonal observations. If no winter mass balance measurements were available and snow cover was represented by a linear precipitation gradient, the geodetic mass balance was not matched. If winter balance measurements by snow probings and snow density pits were taken into account, the model performance was substantially improved but still showed a significant bias relative to the geodetic mass change. Thus the excellent agreement of the model-based extrapolation with the geodetic mass change was owed to an adequate representation of winter accumulation distribution by means of extensive GPR measurements.

Limited dietary overlap amongst resident Arctic herbivores in winter: complementary insights from complementary methods.

Science.gov (United States)

Schmidt, Niels M; Mosbacher, Jesper B; Vesterinen, Eero J; Roslin, Tomas; Michelsen, Anders

2018-04-26

Snow may prevent Arctic herbivores from accessing their forage in winter, forcing them to aggregate in the few patches with limited snow. In High Arctic Greenland, Arctic hare and rock ptarmigan often forage in muskox feeding craters. We therefore hypothesized that due to limited availability of forage, the dietary niches of these resident herbivores overlap considerably, and that the overlap increases as winter progresses. To test this, we analyzed fecal samples collected in early and late winter. We used molecular analysis to identify the plant taxa consumed, and stable isotope ratios of carbon and nitrogen to quantify the dietary niche breadth and dietary overlap. The plant taxa found indicated only limited dietary differentiation between the herbivores. As expected, dietary niches exhibited a strong contraction from early to late winter, especially for rock ptarmigan. This may indicate increasing reliance on particular plant resources as winter progresses. In early winter, the diet of rock ptarmigan overlapped slightly with that of muskox and Arctic hare. Contrary to our expectations, no inter-specific dietary niche overlap was observed in late winter. This overall pattern was specifically revealed by combined analysis of molecular data and stable isotope contents. Hence, despite foraging in the same areas and generally feeding on the same plant taxa, the quantitative dietary overlap between the three herbivores was limited. This may be attributable to species-specific consumption rates of plant taxa. Yet, Arctic hare and rock ptarmigan may benefit from muskox opening up the snow pack, thereby allowing them to access the plants.

Modeling snow accumulation and ablation processes in forested environments

Science.gov (United States)

Andreadis, Konstantinos M.; Storck, Pascal; Lettenmaier, Dennis P.

2009-05-01

The effects of forest canopies on snow accumulation and ablation processes can be very important for the hydrology of midlatitude and high-latitude areas. A mass and energy balance model for snow accumulation and ablation processes in forested environments was developed utilizing extensive measurements of snow interception and release in a maritime mountainous site in Oregon. The model was evaluated using 2 years of weighing lysimeter data and was able to reproduce the snow water equivalent (SWE) evolution throughout winters both beneath the canopy and in the nearby clearing, with correlations to observations ranging from 0.81 to 0.99. Additionally, the model was evaluated using measurements from a Boreal Ecosystem-Atmosphere Study (BOREAS) field site in Canada to test the robustness of the canopy snow interception algorithm in a much different climate. Simulated SWE was relatively close to the observations for the forested sites, with discrepancies evident in some cases. Although the model formulation appeared robust for both types of climates, sensitivity to parameters such as snow roughness length and maximum interception capacity suggested the magnitude of improvements of SWE simulations that might be achieved by calibration.

Effect assessment of Future Climate Change on Water Resource and Snow Quality in cold snowy regions in Japan

Science.gov (United States)

Taniguchi, Y.; Nakatsugawa, M.; Kudo, K.

2017-12-01

It is predicted that the effects of global warming on everyday life will be clearly seen in cold, snowy regions such as Hokkaido. In relation to climate change, there is the concern that the warmer climate will affect not only water resources, but also local economies, in snowy areas, when air temperature increases and snowfall decreases become more marked in the future. Communities whose economies are greatly dependent on snow as a tourism resource, such as for winter sports and snow events, will lose large numbers of visitors because of the shortened winter season. This study was done as a basic study to provide basic ideas for planning adaptation strategies against climate change based on the local characteristics of a cold, snowy region. By taking dam catchment basins in Hokkaido as the subject areas and by using the climate change prediction data that correspond to IPCCAR5, the local-level influence of future climate change on snowfall and snow quality in relation to water resources and winter sports was quantitatively assessed. The water budget was examined for a dam catchment basin in Hokkaido under the present climate (September 1984 to August 2004) and under the future climate (September 2080 to August 2100) by using rainfall, snowfall and evapotranspiration estimated by the LoHAS heat and water balance analysis model.The examination found that, under the future climate, the net annual precipitation will decrease by up to 200 mm because of decreases in precipitation and in runoff height that will result from increased evapotranspiration. The predicted decrease in annual hydro potential of snowfall was considered to greatly affect the dam reservoir operation during the snowmelt season. The snow quality analysis by SNOWPACK revealed that the future snow would become granular earlier than it does at present. Most skiers' snow preferences, from best to worst, are light dry snow (i.e., fresh snow), lightly compacted snow, compacted snow and, finally, granular

Winter: Public Enemy #1 for Accessibility EXPLORING NEW SOLUTIONS

Directory of Open Access Journals (Sweden)

Ernesto Morales

2014-05-01

Full Text Available Abstract: Winter is expensive. For countries situated in the northern hemisphere, closer to the north pole, such as Canada, Russia and Scandinavia, winter requires the acquisition of special clothing, car tires, and sports equipment, snow removal or plowing from the streets, and is associated with the presence of ice patches, along with accidents and illnesses associated with cold weather. Fall-related injuries due to winter conditions have been estimated to cost the Canadian health care system $ 2.8 billion a year. However, the greatest cost snow entails every year is the social isolation of seniors as well as wheelchair and walker users. This results from the lack of accessibility, as it is difficult to circulate on snow-covered streets even for the able-bodied. Social isolation has been associated with other negative consequences such as depression and even suicide. This exploratory pilot study aimed at finding possible and feasible design solutions for improving the accessibility of sidewalks during winter conditions. For this project we used a Co-Design methodology. Stakeholders (City of Quebec representatives, designers, urban planners, occupational therapists, and adults with motor, visual and aural disabilities were invited to participate in the design process. In order to meet the objectives, two main steps were carried out: 1. Conception of the design solutions (through Co-design sessions in a Focus-group format with seniors, designers and researchers; and 2. Validation of the design solutions (consultation with experts and stakeholders. The results are a wide variety of possible and feasible solutions, including the reorganisation of the snow-removal procedure and the development of heated curb cuts. This project was funded by the City of Quebec in partnership with the Centre interdisciplinaire de recherche en réadaptation et intégration sociale (CIRRIS. Ultimately, the project sought to explore possible solutions to be implemented

Prevalence of Pure Versus Mixed Snow Cover Pixels across Spatial Resolutions in Alpine Environments

Directory of Open Access Journals (Sweden)

David J. Selkowitz

2014-12-01

Full Text Available Remote sensing of snow-covered area (SCA can be binary (indicating the presence/absence of snow cover at each pixel or fractional (indicating the fraction of each pixel covered by snow. Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days

Development of probabilistic risk assessment methodology against extreme snow for sodium-cooled fast reactor

Energy Technology Data Exchange (ETDEWEB)

Yamano, Hidemasa, E-mail: yamano.hidemasa@jaea.go.jp; Nishino, Hiroyuki; Kurisaka, Kenichi

2016-11-15

Highlights: • Snow PRA methodology was developed. • Snow hazard category was defined as the combination of daily snowfall depth (speed) and snowfall duration. • Failure probability models of snow removal action, manual operation of the air cooler dampers and the access route were developed. • Snow PRA showed less than 10{sup −6}/reactor-year of core damage frequency. - Abstract: This paper describes snow probabilistic risk assessment (PRA) methodology development through external hazard and event sequence evaluations mainly in terms of decay heat removal (DHR) function of a sodium-cooled fast reactor (SFR). Using recent 50-year weather data at a typical Japanese SFR site, snow hazard categories were set for the combination of daily snowfall depth (snowfall speed) and snowfall duration which can be calculated by dividing the snow depth by the snowfall speed. For each snow hazard category, the event sequence was evaluated by event trees which consist of several headings representing the loss of DHR. Snow removal action and manual operation of the air cooler dampers were introduced into the event trees as accident managements. Access route failure probability model was also developed for the quantification of the event tree. In this paper, the snow PRA showed less than 10{sup −6}/reactor-year of core damage frequency. The dominant snow hazard category was the combination of 1–2 m/day of snowfall speed and 0.5–0.75 day of snowfall duration. Importance and sensitivity analyses indicated a high risk contribution of the securing of the access routes.

Development of probabilistic risk assessment methodology against extreme snow for sodium-cooled fast reactor

International Nuclear Information System (INIS)

Yamano, Hidemasa; Nishino, Hiroyuki; Kurisaka, Kenichi

2016-01-01

Highlights: • Snow PRA methodology was developed. • Snow hazard category was defined as the combination of daily snowfall depth (speed) and snowfall duration. • Failure probability models of snow removal action, manual operation of the air cooler dampers and the access route were developed. • Snow PRA showed less than 10"−"6/reactor-year of core damage frequency. - Abstract: This paper describes snow probabilistic risk assessment (PRA) methodology development through external hazard and event sequence evaluations mainly in terms of decay heat removal (DHR) function of a sodium-cooled fast reactor (SFR). Using recent 50-year weather data at a typical Japanese SFR site, snow hazard categories were set for the combination of daily snowfall depth (snowfall speed) and snowfall duration which can be calculated by dividing the snow depth by the snowfall speed. For each snow hazard category, the event sequence was evaluated by event trees which consist of several headings representing the loss of DHR. Snow removal action and manual operation of the air cooler dampers were introduced into the event trees as accident managements. Access route failure probability model was also developed for the quantification of the event tree. In this paper, the snow PRA showed less than 10"−"6/reactor-year of core damage frequency. The dominant snow hazard category was the combination of 1–2 m/day of snowfall speed and 0.5–0.75 day of snowfall duration. Importance and sensitivity analyses indicated a high risk contribution of the securing of the access routes.

Cartographic modelling of aerotechnogenic pollution in snow cover in the landscapes of the Kola Peninsula.

Science.gov (United States)

Ratkin, N E; Asming, V E; Koshkin, V V

2001-01-01

The goal of this work was to develop computational techniques for sulphates, nickel and copper accumulation in the snow in the local pollution zone. The main task was to reveal the peculiarities of formation and pollution of snow cover on the region with complex cross-relief. A digital cartographic model of aerotechnogenic pollution of snow cover in the landscapes of the local zone has been developed, based on five-year experimental data. Data regarding annual emissions from the industrial complex, information about distribution of wind and the sum of precipitation from meteostation "Nikel" for the winter period, allowed the model to ensure: * material presentation in the form of maps of water capacity and accumulation of sulphates, nickel and copper in the snow over any winter period in retrospective; * calculation of water capacity and accumulation of pollutants for watersheds and other natural-territorial complexes; * solution of the opposite problem about the determination of the emissions of sulphates, nickel and copper from the enterprise by measuring snow pollution in datum points. The model can be used in other northern regions of the Russian Federation with similar physical-geographical and climatic conditions. The relationships between the sum of precipitation and water capacity in the landscapes of the same type and also the relationships between pollution content in snow and relief, pollution content in snow and distance from the source of emissions, were used as the basis for the model.

Measurement of snow interception and canopy effects on snow accumulation and melt in a mountainous maritime climate, Oregon, United States

Science.gov (United States)

Storck, Pascal; Lettenmaier, Dennis P.; Bolton, Susan M.

2002-11-01

The results of a 3 year field study to observe the processes controlling snow interception by forest canopies and under canopy snow accumulation and ablation in mountain maritime climates are reported. The field study was further intended to provide data to develop and test models of forest canopy effects on beneath-canopy snowpack accumulation and melt and the plot and stand scales. Weighing lysimeters, cut-tree experiments, and manual snow surveys were deployed at a site in the Umpqua National Forest, Oregon (elevation 1200 m). A unique design for a weighing lysimeter was employed that allowed continuous measurements of snowpack evolution beneath a forest canopy to be taken at a scale unaffected by variability in canopy throughfall. Continuous observations of snowpack evolution in large clearings were made coincidentally with the canopy measurements. Large differences in snow accumulation and ablation were observed at sites beneath the forest canopy and in large clearings. These differences were not well described by simple relationships between the sites. Over the study period, approximately 60% of snowfall was intercepted by the canopy (up to a maximum of about 40 mm water equivalent). Instantaneous sublimation rates exceeded 0.5 mm per hour for short periods. However, apparent average sublimation from the intercepted snow was less than 1 mm per day and totaled approximately 100 mm per winter season. Approximately 72 and 28% of the remaining intercepted snow was removed as meltwater drip and large snow masses, respectively. Observed differences in snow interception rate and maximum snow interception capacity between Douglas fir (Pseudotsuga menziesii), white fir (Abies concolor), ponderosa pine (Pinus ponderosa), and lodgepole pine (Pinus contorta) were minimal.

Dynamic-stochastic modeling of snow cover formation on the European territory of Russia

OpenAIRE

A. N. Gelfan; V. M. Moreido

2014-01-01

A dynamic-stochastic model, which combines a deterministic model of snow cover formation with a stochastic weather generator, has been developed. The deterministic snow model describes temporal change of the snow depth, content of ice and liquid water, snow density, snowmelt, sublimation, re-freezing of melt water, and snow metamorphism. The model has been calibrated and validated against the long-term data of snow measurements over the territory of the European Russia. The model showed good ...

How much of stream and groundwater comes from snow? A stable isotope perspective in the Swiss Alps

Science.gov (United States)

Beria, H.; Schaefli, B.; Ceperley, N. C.; Michelon, A.; Larsen, J.

2017-12-01

Precipitation which once fell as snow is predicted to fall more often as liquid rain now that climate is, and continues, warming. Within snow dominated areas, preferential winter groundwater recharge has been observed, however a shorter winter season and smaller snow fraction results in earlier snowmelt and thinner snowpacks. This has the potential to change the supply of snow water sources to both streams and groundwater, which has important implications for flow regimes and water resources. Stable isotopes of water (2H and 18O) allow us to discriminate rain vs snow signatures within water flowing in the stream or the subsurface. Using one year of isotope data collected in a Swiss Alpine catchment (Vallon de Nant, Vaud), we developed novel forward Bayesian mixing models, based on statistical and empirical likelihoods, to quantify source contributions and uncertainty estimates. To account for the spatial heterogeneity in precipitation isotopes, we parameterized the model accounting for elevation effects on isotopes, calculated using the network of GNIP stations in Switzerland. Instead of sampling meltwater, we sampled snowpack throughout the season and across a steep elevation gradient (1241m to 2455m) to infer the snowmelt transformation factor. Due to continuous mixing within the snowpack, the snowmelt water shows much lower variability in its isotopic range which is reflected in the snow transformation factor. Snowmelt yield to groundwater recharge per unit amount of precipitation was found to be greater than rainfall in Vallon de Nant, suggesting strongly preferential winter recharge. Seasonal dynamics of stream responses to rain-on-snow events, fog deposition, snowmelt and summer rain were also explored. Innovative monitoring and sampling with tools such as stable isotopes and forward Bayesian mixing models are key to improved comprehension of global recharge mechanisms.

Assessing the spatial variability of mountain precipitation in California's Sierra Nevada using the Airborne Snow Observatory

Science.gov (United States)

Brandt, T.; Deems, J. S.; Painter, T. H.; Dozier, J.

2016-12-01

In California's Sierra Nevada, 10 or fewer winter storms are responsible for most of the annual precipitation, which falls mostly as snow. Presently, surface stations are used to measure the dynamics of mountain precipitation. However, even in places like the Sierra Nevada—one of the most gauged regions in the world—the paucity of surface stations can lead to large errors in precipitation thereby biasing both total water year and short-term streamflow forecasts. Remotely sensed snow depth and water equivalent, at a time scale that resolves storms, might provide a novel solution to the problems of: (1) quantifying the spatial variability of mountain precipitation; and (2) assessing gridded precipitation products that are mostly based on surface station interpolation. NASA's Airborne Snow Observatory (ASO), an imaging spectrometer and LiDAR system, has measured snow in the Tuolumne River Basin in California's Sierra Nevada for the past four years, 2013-2016; and, measurements will continue. Principally, ASO monitors the progression of melt for water supply forecasting, nonetheless, a number of flights bracketed storms allowing for estimates of snow accumulation. In this study we examine a few of the ASO recorded storms to determine both the basin and subbasin orographic effect as well as the spatial patterns in total precipitation. We then compare these results to a number of gridded climate products and weather models including: Daymet, the Parameter-elevation Regressions on Independent Slopes Model (PRISM), the North American Land Data Assimilation System (NLDAS-2), and the Weather Research and Forecasting (WRF) model. Finally, to put each ASO recorded storm into context, we use a climatology produced from snow pillows and the North American Regional Reanalysis (NARR) for 2014-2016 to examine key accumulation events, and classify storms based on their integrated water vapor flux.

Forest Fires Darken Snow for Years following Disturbance: Magnitude, Duration, and Composition of Light Absorbing Impurities in Seasonal Snow across a Chronosequence of Burned Forests in the Colorado River Headwaters

Science.gov (United States)

Gleason, K. E.; Arienzo, M. M.; Chellman, N.; McConnell, J.

2017-12-01

Charred forests shed black carbon and burned debris, which accumulates and concentrates on winter snowpack, reducing snow surface albedo, and subsequently increasing snowmelt rates, and advancing the date of snow disappearance. Forest fires have occurred across vast areas of the seasonal snow zone in recent decades, however we do not understand the long-term implications of burned forests in montane headwaters to snow hydrology and downstream water resources. Across a chronosequence of nine burned forests in the Colorado River Headwaters, we sampled snow throughout the complete snowpack profile to conserve the composition, properties, and vertical stratigraphy of impurities in the snowpack during maximum snow accumulation. Using state-of-the-art geochemical analyses, we determined the magnitude, composition, and particle size distribution of black carbon, dust, and other impurities in the snowpack relative to years-since fire. Forest fires continue to darken snow for many years following fire, however the magnitude, composition, and particle size distribution of impurities change through time, altering the post-fire radiative forcing on snow as a burned forest ages.

New Perspectives on Blowing Snow Transport, Sublimation, and Layer Thermodynamic Structure over Antarctica

Science.gov (United States)

Palm, Steve; Kayetha, Vinay; Yang, Yuekui; Pauly, Rebecca M.

2017-01-01

Blowing snow over Antarctica is a widespread and frequent event. Satellite remote sensing using lidar has shown that blowing snow occurs over 70% of the time over large areas of Antarctica in winter. The transport and sublimation of blowing snow are important terms in the ice sheet mass balance equation and the latter is also an important part of the hydrological cycle. Until now the only way to estimate the magnitude of these processes was through model parameterization. We present a technique that uses direct satellite observations of blowing snow and model (MERRA-2) temperature and humidity fields to compute both transport and sublimation of blowing snow over Antarctica for the period 2006 to 2016. The results show a larger annual continent-wide integrated sublimation than current published estimates and a significant transport of snow from continent to ocean. The talk will also include the lidar backscatter structure of blowing snow layers that often reach heights of 200 to 300 m as well as the first dropsonde measurements of temperature, moisture and wind through blowing snow layers.

Shielding effect of snow cover on indoor exposure due to terrestrial gamma radiation

International Nuclear Information System (INIS)

Fujimoto, Kenzo; Kobayashi, Sadayoshi

1988-01-01

Many people in the world live in high latitude region where it snows frequently in winter. When snow covers the ground, it considerably reduces the external exposure from the radiation sources in the ground. Therefore, the evaluation of snow effect on exposure due to terrestrial gamma radiation is necessary to obtain the population dose as well as the absorbed dose in air in snowy regions. Especially the shielding effect on indoor exposure is essentially important in the assessment of population dose since most individuals spend a large portion of their time indoors. The snow effect, however, has been rather neglected or assumed to be the same both indoors and outdoors in the population dose calculation. Snow has been recognized only as a cause of temporal variation of outdoor exposure rate due firstly to radon daughters deposition with snow fall and secondly to the shielding effect of snow cover. This paper describes an approach to the evaluation of shielding effect of snow cover on exposure and introduces population dose calculation as numerical example for the people who live in wooden houses in Japan

Spatiotemporal variability in surface energy balance across tundra, snow and ice in Greenland

DEFF Research Database (Denmark)

Lund, Magnus; Stiegler, Christian; Abermann, Jakob

2017-01-01

The surface energy balance (SEB) is essential for understanding the coupled cryosphere–atmosphere system in the Arctic. In this study, we investigate the spatiotemporal variability in SEB across tundra, snow and ice. During the snow-free period, the main energy sink for ice sites is surface melt....... For tundra, energy is used for sensible and latent heat flux and soil heat flux leading to permafrost thaw. Longer snow-free period increases melting of the Greenland Ice Sheet and glaciers and may promote tundra permafrost thaw. During winter, clouds have a warming effect across surface types whereas during...

Investigation of some regularities of the contamination of the surface snow in the ChAPP region in January-February 1987

International Nuclear Information System (INIS)

Glazunov, V.O.; Amosov, M.M.; Eldashev, V.V.; Draj, O.N.; Pashevich, V.I.

1989-01-01

The data on the surface snow radioactivity inspection obtained in winter 1987 are analyzed. A share of individual radionuclides in the general pollution of surface snow is considered. Changes in general and individual nuclide contamination dependent of the azimuth and distance are presented. A disperse content of contaminants in the surface snow is analyzed. The sampling techniques and snow sample preparation for γ-spectrometry are reported. 5 refs., 8 figs., 7 tabs

Identification and evaluation of slip and fall risk on ice and snow

OpenAIRE

Gao, Chuansi

2001-01-01

Roads and pavements covered with ice and snow during winter in the Nordic and other cold regions are slippery, which result in the prevalence of slip and fall accidents among not only the public, but also outdoor workers. Literature and injury statistics revealed that the most frequently specified contributory factor for occupational slip, trip and fall accidents in Sweden is snow and ice. Road accident research showed that the largest numbers of traffic casualties occurred during walking, fo...

Using idealized snow forcing to test teleconnections with the Indian summer monsoon in the Hadley Centre GCM

Energy Technology Data Exchange (ETDEWEB)

Turner, A.G. [University of Reading, NCAS-Climate, Walker Institute for Climate System Research, Department of Meteorology, Reading (United Kingdom); Slingo, J.M. [University of Reading, NCAS-Climate, Walker Institute for Climate System Research, Department of Meteorology, Reading (United Kingdom); Met Office, Exeter (United Kingdom)

2011-05-15

Anomalous heavy snow during winter or spring has long been regarded as a possible precursor of deficient Indian monsoon rainfall during the subsequent summer. However previous work in this field is inconclusive, in terms of the mechanism that communicates snow anomalies to the monsoon summer, and even the region from which snow has the most impact. In this study we explore these issues in coupled and atmosphere-only versions of the Hadley Centre model. A 1050-year control integration of the HadCM3 coupled model, which well represents the seasonal cycle of snow cover over the Eurasian continent, is analysed and shows evidence for weakened monsoons being preceded by strong snow forcing (in the absence of ENSO) over either the Himalaya/Tibetan Plateau or north/west Eurasia regions. However, empirical orthogonal function (EOF) analysis of springtime interannual variability in snow depth shows the leading mode to have opposite signs between these two regions, suggesting that competing mechanisms may be possible. To determine the dominant region, ensemble integrations are carried out using HadAM3, the atmospheric component of HadCM3, and a variety of anomalous snow forcing initial conditions obtained from the control integration of the coupled model. Forcings are applied during spring in separate experiments over the Himalaya/Tibetan Plateau and north/west Eurasia regions, in conjunction with climatological SSTs in order to avoid the direct effects of ENSO. With the aid of idealized forcing conditions in sensitivity tests, we demonstrate that forcing from the Himalaya region is dominant in this model via a Blanford-type mechanism involving reduced surface sensible heat and longwave fluxes, reduced heating of the troposphere over the Tibetan Plateau and consequently a reduced meridional tropospheric temperature gradient which weakens the monsoon during early summer. Snow albedo is shown to be key to the mechanism, explaining around 50% of the perturbation in sensible

Snow and ice blocking of tunnels

Energy Technology Data Exchange (ETDEWEB)

Lia, Leif

1998-12-31

Hydroelectric power development in cold regions causes much concern about operational reliability and dam safety. This thesis studies the temperature distribution in tunnels by means of air temperature measurements in six tunnel spillways and five diversion tunnels. The measurements lasted for two consecutive winters. The air through flow tunnel is used as it causes cooling of both rock and water. In open spillway tunnels, frost reaches the entire tunnel. In spillway tunnels with walls, the frost zones reach about 100 m from the downstream end. In mildly-inclined diversion tunnels, a frost free zone is located in the middle of the tunnel and snow and ice problems were only observed in the inlet and outlet. Severe aufeis is accumulation is observed in the frost zones. The heat transfer from rock to air, water and ice is calculated and used in a prediction model for the calculation of aufeis build-up together with local field observation data. The water penetration of snow plugs is also calculated, based on the heat balance. It takes 20 to 50 days for water to enter the blocked tunnel. The empirical values are 30 to 60 days, but only 1 day if the temperature of the snow pack is 0{sup o}C. Sensitivity analyses are carried out for temperature variations in rock, snow, water and ice. Systematic field observation shows that it is important for hydropower companies to know about the effects of snow and ice blocking in an area. A risk analysis of dam safety is presented for a real case. Finally, the thesis proposes solutions which can reduce the snow and ice problems. 79 refs., 63 figs., 11 tabs.

Winter climate variability and classification in the Bulgarian Mountainous Regions

International Nuclear Information System (INIS)

Petkova, Nadezhda; Koleva, Ekaterina

2004-01-01

The problems of snowiness and thermal conditions of winters are of high interest of investigations because of the more frequent droughts, occurred in the region. In the present study an attempt to reveal tendencies existing during the last 70 years of 20 th century in the course winter precipitation and,temperature as well as in some of the snow cover parameters. On the base of mean winter air temperature winters in the Bulgarian mountains were analyzed and classified. The main results of the study show that winter precipitation has decrease tendencies more significant in the highest parts of the mountains. On the other hand winter air temperature increases. It shows a relatively well-established maximum at the end of the studied period. In the Bulgarian mountains normal winters are about 35-40% of all winters. (Author)

UAS applications in high alpine, snow-covered terrain

Science.gov (United States)

Bühler, Y.; Stoffel, A.; Ginzler, C.

2017-12-01

Access to snow-covered, alpine terrain is often difficult and dangerous. Hence parameters such as snow depth or snow avalanche release and deposition zones are hard to map in situ with adequate spatial and temporal resolution and with spatial continuous coverage. These parameters are currently operationally measured at automated weather stations and by observer networks. However such isolated point measurements are not able to capture the information spatial continuous and to describe the high spatial variability present in complex mountain topography. Unmanned Aerial Systems (UAS) have the potential to fill this gap by frequently covering selected high alpine areas with high spatial resolution down to ground resolutions of even few millimeters. At the WSL Institute for Snow and Avalanche Research SLF we test different photogrammetric UAS with visual and near infrared bands. During the last three years we were able to gather experience in more than 100 flight missions in extreme terrain. By processing the imagery applying state-of-the-art structure from motion (SfM) software, we were able to accurately document several avalanche events and to photogrammetrically map snow depth with accuracies from 1 to 20 cm (dependent on the flight height above ground) compare to manual snow probe measurements. This was even possible on homogenous snow surfaces with very little texture. A key issue in alpine terrain is flight planning. We need to cover regions at high elevations with large altitude differences (up to 1 km) with high wind speeds (up to 20 m/s) and cold temperatures (down to - 25°C). Only a few UAS are able to cope with these environmental conditions. We will give an overview on our applications of UAS in high alpine terrain that demonstrate the big potential of such systems to acquire frequent, accurate and high spatial resolution geodata in high alpine, snow covered terrain that could be essential to answer longstanding questions in avalanche and snow hydrology

SNOW DEPTH ESTIMATION USING TIME SERIES PASSIVE MICROWAVE IMAGERY VIA GENETICALLY SUPPORT VECTOR REGRESSION (CASE STUDY URMIA LAKE BASIN

Directory of Open Access Journals (Sweden)

N. Zahir

2015-12-01

Full Text Available Lake Urmia is one of the most important ecosystems of the country which is on the verge of elimination. Many factors contribute to this crisis among them is the precipitation, paly important roll. Precipitation has many forms one of them is in the form of snow. The snow on Sahand Mountain is one of the main and important sources of the Lake Urmia’s water. Snow Depth (SD is vital parameters for estimating water balance for future year. In this regards, this study is focused on SD parameter using Special Sensor Microwave/Imager (SSM/I instruments on board the Defence Meteorological Satellite Program (DMSP F16. The usual statistical methods for retrieving SD include linear and non-linear ones. These methods used least square procedure to estimate SD model. Recently, kernel base methods widely used for modelling statistical problem. From these methods, the support vector regression (SVR is achieved the high performance for modelling the statistical problem. Examination of the obtained data shows the existence of outlier in them. For omitting these outliers, wavelet denoising method is applied. After the omission of the outliers it is needed to select the optimum bands and parameters for SVR. To overcome these issues, feature selection methods have shown a direct effect on improving the regression performance. We used genetic algorithm (GA for selecting suitable features of the SSMI bands in order to estimate SD model. The results for the training and testing data in Sahand mountain is [R²_TEST=0.9049 and RMSE= 6.9654] that show the high SVR performance.

Snow cover dynamics in Andean watersheds of Chile (32.0-39.5° S) during the years 2000-2016

Science.gov (United States)

Stehr, Alejandra; Aguayo, Mauricio

2017-10-01

Andean watersheds present important snowfall accumulation mainly during the winter, which melts during the spring and part of the summer. The effect of snowmelt on the water balance can be critical to sustain agriculture activities, hydropower generation, urban water supplies and wildlife. In Chile, 25 % of the territory between the region of Valparaiso and Araucanía comprises areas where snow precipitation occurs. As in many other difficult-to-access regions of the world, there is a lack of hydrological data of the Chilean Andes related to discharge, snow courses, and snow depths, which complicates the analysis of important hydrological processes (e.g. water availability). Remote sensing provides a promising opportunity to enhance the assessment and monitoring of the spatial and temporal variability of snow characteristics, such as the snow cover area (SCA) and snow cover dynamic (SCD). With regards to the foregoing questions, the objective of the study is to evaluate the spatiotemporal dynamics of the SCA at five watersheds (Aconcagua, Rapel, Maule, Biobío and Toltén) located in the Chilean Andes, between latitude 32.0 and 39.5° S, and to analyse its relationship with the precipitation regime/pattern and El Niño-Southern Oscillation (ENSO) events. Those watersheds were chosen because of their importance in terms of their number of inhabitants, and economic activities depending on water resources. The SCA area was obtained from MOD10A2 for the period 2000-2016, and the SCD was analysed through a number of statistical tests to explore observed trends. In order to verify the SCA for trend analysis, a validation of the MOD10A2 product was done, consisting of the comparison of snow presence predicted by MODIS with ground observations. Results indicate that there is an overall agreement of 81 to 98 % between SCA determined from ground observations and MOD10A2, showing that the MODIS snow product can be taken as a feasible remote sensing tool for SCA estimation in

Snow and Ice Crust Changes over Northern Eurasia since 1966

Science.gov (United States)

Bulygina, O.; Groisman, P. Y.; Razuvaev, V.; Radionov, V.

2009-12-01

When temperature of snow cover reaches zero Celsius first time since its establishment, snowmelt starts. In many parts of the world this process can be lengthy. The initial amount of heat that “arrives” to the snowpack might be insufficient for complete snowmelt, during the colder nights re-freeze of the melted snow may occur (thus creating the ice crust layers), and a new cold front (or the departure of the warm front that initiated melt) can decrease temperatures below the freezing point again and stop the snowmelt completely. It well can be that first such snowmelt occurs in winter (thaw day) and for several months thereafter snowpack stays on the ground. However, even the first such melt initiates a process of snow metamorphosis on its surface changing snow albedo and generating snow crust as well as on its bottom generating ice crust. Once emerged, the crusts will not disappear until the complete snowmelt. Furthermore, these crusts have numerous pathways of impact on the wild birds and animals in the Arctic environment as well as on domesticated reindeers. In extreme cases, the crusts may kill some wild species and prevent reindeers’ migration and feeding. Ongoing warming in high latitudes created situations when in the western half of Eurasian continent days with thaw became more frequent. Keeping in mind potential detrimental impacts of winter thaws and associated with them snow/ice crust development, it is worthwhile to study directly what are the major features of snow and ice crust over Eurasia and what is their dynamics. For the purpose of this study, we employed the national snow survey data set archived at the Russian Institute for Hydrometeorological Information. The dataset has routine snow surveys run throughout the cold season each decade (during the intense snowmelt, each 5 days) at all meteorological stations of the former USSR, thereafter, in Russia since 1966. Prior to 1966 snow surveys are also available but the methodology of

Travel in adverse winter weather conditions by blind pedestrians.

Science.gov (United States)

2015-08-31

Winter weather creates many orientation and mobility (O&M) challenges for people who are visually impaired. Getting the cane tip stuck is one of the noticeable challenges when traveling in snow, particularly when the walking surface is covered in dee...

Snow conditions and usability value of pastureland for semi-domesticated reindeer (Rangifer tarandus tarandus in northern boreal forest area

Directory of Open Access Journals (Sweden)

Jouko Kumpula

2009-01-01

Full Text Available We studied variation in snow conditions and selection of pasture area according to altitude by semi-domesticated reindeer (Rangifer tarandus tarandus during 1999 - 2002 in a pine forest area utilised by forest industry in the Ivalo reindeer herding district, northern Finland. Snow conditions were measured over the course of three winters along equilateral triangles (side 3.5 km for three times per winter. The altitudinal selection of pasture area by reindeer was studied using GPS tracking data (10 977 locations from 29 female reindeer. We observed that interannual weather variation mostly affected the depth, density and hardness of snow in the study area. At the forest landscape level, snow depth and density increased with altitude. Thinnest and deepest snow cover occurred on western and northern slopes, respectively. In contrast, forest harvesting did not seem to affect snow conditions. From spring to autumn, reindeer mainly used higher altitudes in pastures. In early and mid-winter, when snow conditions were easy or moderate reindeer still preferred higher altitudes, but in late winter when snow conditions and food accession were at their most difficult, they preferred lower altitudes. We conclude that especially the use of high elevation forestland pastures may become more difficult for reindeer if the global climatic change causes higher winter precipitation to the northern boreal forest area. In general, the low-elevation forestland areas have primary winter grazing value for reindeer but these areas are also intensively used by forest industry.Abstract in Finnish / Tiivistelmä:Lumiolosuhteet ja laidunten käyttöarvo poronhoidossa pohjoisella havumetsäaluella Lumiolosuhteiden vaihtelua ja porojen (Rangifer tarandus tarandus laidunalueen valintaa maaston korkeuden perusteella tutkittiin vuosina 1999–2002 metsätalouden hyödyntämällä mäntymetsäalueella Ivalon paliskunnassa, Pohjois-Suomessa. Lumiolosuhteet mitattiin kolme kertaa

Snow Dunes: A Controlling Factor of Melt Pond Distribution on Arctic Sea Ice

Science.gov (United States)

Petrich, Chris; Eicken, Hajo; Polashenski, Christopher M.; Sturm, Matthew; Harbeck, Jeremy P.; Perovich, Donald K.; Finnegan, David C.

2012-01-01

The location of snow dunes over the course of the ice-growth season 2007/08 was mapped on level landfast first-year sea ice near Barrow, Alaska. Landfast ice formed in mid-December and exhibited essentially homogeneous snow depths of 4-6 cm in mid-January; by early February distinct snow dunes were observed. Despite additional snowfall and wind redistribution throughout the season, the location of the dunes was fixed by March, and these locations were highly correlated with the distribution of meltwater ponds at the beginning of June. Our observations, including ground-based light detection and ranging system (lidar) measurements, show that melt ponds initially form in the interstices between snow dunes, and that the outline of the melt ponds is controlled by snow depth contours. The resulting preferential surface ablation of ponded ice creates the surface topography that later determines the melt pond evolution.

Meteorological and snow distribution data in the Izas Experimental Catchment (Spanish Pyrenees) from 2011 to 2017

Science.gov (United States)

Revuelto, Jesús; Azorin-Molina, Cesar; Alonso-González, Esteban; Sanmiguel-Vallelado, Alba; Navarro-Serrano, Francisco; Rico, Ibai; López-Moreno, Juan Ignacio

2017-12-01

This work describes the snow and meteorological data set available for the Izas Experimental Catchment in the Central Spanish Pyrenees, from the 2011 to 2017 snow seasons. The experimental site is located on the southern side of the Pyrenees between 2000 and 2300 m above sea level, covering an area of 55 ha. The site is a good example of a subalpine environment in which the evolution of snow accumulation and melt are of major importance in many mountain processes. The climatic data set consists of (i) continuous meteorological variables acquired from an automatic weather station (AWS), (ii) detailed information on snow depth distribution collected with a terrestrial laser scanner (TLS, lidar technology) for certain dates across the snow season (between three and six TLS surveys per snow season) and (iii) time-lapse images showing the evolution of the snow-covered area (SCA). The meteorological variables acquired at the AWS are precipitation, air temperature, incoming and reflected solar radiation, infrared surface temperature, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface), and soil temperature; all were taken at 10 min intervals. Snow depth distribution was measured during 23 field campaigns using a TLS, and daily information on the SCA was also retrieved from time-lapse photography. The data set (https://doi.org/10.5281/zenodo.848277) is valuable since it provides high-spatial-resolution information on the snow depth and snow cover, which is particularly useful when combined with meteorological variables to simulate snow energy and mass balance. This information has already been analyzed in various scientific studies on snow pack dynamics and its interaction with the local climatology or topographical characteristics. However, the database generated has great potential for understanding other environmental processes from a hydrometeorological or ecological perspective in which snow dynamics play a

Design of a High Resolution Open Access Global Snow Cover Web Map Service Using Ground and Satellite Observations

Science.gov (United States)

Kadlec, J.; Ames, D. P.

2014-12-01

The aim of the presented work is creating a freely accessible, dynamic and re-usable snow cover map of the world by combining snow extent and snow depth datasets from multiple sources. The examined data sources are: remote sensing datasets (MODIS, CryoLand), weather forecasting model outputs (OpenWeatherMap, forecast.io), ground observation networks (CUAHSI HIS, GSOD, GHCN, and selected national networks), and user-contributed snow reports on social networks (cross-country and backcountry skiing trip reports). For adding each type of dataset, an interface and an adapter is created. Each adapter supports queries by area, time range, or combination of area and time range. The combined dataset is published as an online snow cover mapping service. This web service lowers the learning curve that is required to view, access, and analyze snow depth maps and snow time-series. All data published by this service are licensed as open data; encouraging the re-use of the data in customized applications in climatology, hydrology, sports and other disciplines. The initial version of the interactive snow map is on the website snow.hydrodata.org. This website supports the view by time and view by site. In view by time, the spatial distribution of snow for a selected area and time period is shown. In view by site, the time-series charts of snow depth at a selected location is displayed. All snow extent and snow depth map layers and time series are accessible and discoverable through internationally approved protocols including WMS, WFS, WCS, WaterOneFlow and WaterML. Therefore they can also be easily added to GIS software or 3rd-party web map applications. The central hypothesis driving this research is that the integration of user contributed data and/or social-network derived snow data together with other open access data sources will result in more accurate and higher resolution - and hence more useful snow cover maps than satellite data or government agency produced data by

CHEMICAL COMPOSITION CHANGE OF SUBSURFACE SNOW IN EAST ANTARCTICA WITH DISTANCE FROM THE COAST

Directory of Open Access Journals (Sweden)

L. P. Golobokova

2012-01-01

Full Text Available The paper presents data on chemical composition of snow in theAntarcticasampled along the first tractor traverse during the 53th Russian Antarctic Expedition from Station Progress (the sea coast to Station Vostok (1,276 kmfrom Progress. Specific features of horizontal and depth distribution of chemical components in snow revealed differences in conditions of formation of snow cover along the traverse in both spatial and time scales. Chemical composition of snow depends on the sources of admixture inputs onto the surface of the ice sheet (marine, continental and volcanic. The influence of sea factor decreases with the distance from the coast. Calculated factor of element enrichment indicated that some ions in snow cover were of continental origin in the middle of the traverse. Elevated concentrations of sulphate ions were recorded in snow-firn cores at 130–150 cmfrom the surface. They were attributed to signals of the Pinatubo volcano eruption (1991. Accumulation rate of snow was calculated for the traverse sites based on the depth of the Pinatubo layer.

Snow measurement Using P-Band Signals of Opportunity Reflectometry

Science.gov (United States)

Shah, R.; Yueh, S. H.; Xu, X.; Elder, K.

2017-12-01

Snow water storage in land is a critical parameter of the water cycle. In this study, we develop methods for estimating reflectance from bistatic scattering of digital communication Signals of Opportunity (SoOp) across the available microwave spectrum from VHF to Ka band and show results from proof-of-concept experiments at the Fraser Experimental Forest, Colorado to acquire measurements to relate the SoOp phase and reflectivity to a snow-covered soil surface. The forward modeling of this scenario will be presented and multiple sensitivities were conducted. Available SoOp receiver data along with a network of in situ sensor measurements collected since January 2016 will be used to validate theoretical modeling results. In the winter season of 2016 and 2017, we conducted a field experiment using VHF/UHF-band illuminating sources to detect SWE and surface reflectivity. The amplitude of the reflectivity showed sensitivity to the wetness of snow pack and ground reflectivity while the phase showed sensitivity to SWE. This use of this concept can be helpful to measure the snow water storage in land globally.

Influence of winter season climate variability on snow-precipitation ratio in the western United States

Science.gov (United States)

Mohammad Safeeq; Shraddhanand Shukla; Ivan Arismendi; Gordon E. Grant; Sarah L. Lewis; Anne Nolin

2015-01-01

In the western United States, climate warming poses a unique threat to water and snow hydrology because much of the snowpack accumulates at temperatures near 0 °C. As the climate continues to warm, much of the region's precipitation is expected to switch from snow to rain, causing flashier hydrographs, earlier inflow to reservoirs, and reduced spring and summer...

Evaluation of the Viking-Cives towplow for winter maintenance.

Science.gov (United States)

2014-01-01

To maximize efficiency while minimizing costs within ODOTs winter maintenance budget, ODOT is : evaluating new methods of snow and ice removal. One method is the use of the Viking-Cives TowPlow. The : TowPlow is pulled behind a tandem axle truck a...

SWANN: The Snow Water Artificial Neural Network Modelling System

Science.gov (United States)

Broxton, P. D.; van Leeuwen, W.; Biederman, J. A.

2017-12-01

Snowmelt from mountain forests is important for water supply and ecosystem health. Along Arizona's Mogollon Rim, snowmelt contributes to rivers and streams that provide a significant water supply for hydro-electric power generation, agriculture, and human consumption in central Arizona. In this project, we are building a snow monitoring system for the Salt River Project (SRP), which supplies water and power to millions of customers in the Phoenix metropolitan area. We are using process-based hydrological models and artificial neural networks (ANNs) to generate information about both snow water equivalent (SWE) and snow cover. The snow-cover data is generated with ANNs that are applied to Landsat and MODIS satellite reflectance data. The SWE data is generated using a combination of gridded SWE estimates generated by process-based snow models and ANNs that account for variations in topography, forest cover, and solar radiation. The models are trained and evaluated with snow data from SNOTEL stations as well as from aerial LiDAR and field data that we collected this past winter in northern Arizona, as well as with similar data from other sites in the Southwest US. These snow data are produced in near-real time, and we have built a prototype decision support tool to deliver them to SRP. This tool is designed to provide daily-to annual operational monitoring of spatial and temporal changes in SWE and snow cover conditions over the entire Salt River Watershed (covering 17,000 km2), and features advanced web mapping capabilities and watershed analytics displayed as graphical data.

Using wireless sensor networks to improve understanding of rain-on-snow events across the Sierra Nevada

Science.gov (United States)

Maurer, T.; Avanzi, F.; Oroza, C.; Malek, S. A.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2017-12-01

We use data gathered from Wireless Sensor Networks (WSNs) between 2008 and 2017 to investigate the temporal/spatial patterns of rain-on-snow events in three river basins of California's Sierra Nevada. Rain-on-snow transitions occur across a broad elevation range (several hundred meters), both between storms and within a given storm, creating an opportunity to use spatially and temporally dense data to forecast and study them. WSNs collect snow depth; meteorological data; and soil moisture and temperature data across relatively dense sensor clusters. Ten to twelve measurement nodes per cluster are placed across 1-km2 areas in locations representative of snow patterns at larger scales. Combining precipitation and snow data from snow-pillow and climate stations with an estimation of dew-point temperature from WSNs, we determine the frequency, timing, and geographic extent of rain-on-snow events. We compare these results to WSN data to evaluate the impact of rain-on-snow events on snowpack energy balance, density, and depth as well as on soil moisture. Rain-on-snow events are compared to dry warm-weather days to identify the relative importance of rain and radiation as the primary energy input to the snowpack for snowmelt generation. An intercomparison of rain-on-snow events for the WSNs in the Feather, American, and Kings River basins captures the behavior across a 2° latitudinal range of the Sierra Nevada. Rain-on-snow events are potentially a more important streamflow generation mechanism in the lower-elevation Feather River basin. Snowmelt response to rain-on-snow events changes throughout the wet season, with later events resulting in more melt due to snow isothermal conditions, coarser grain size, and more-homogeneous snow stratigraphy. Regardless of snowmelt response, rain-on-snow events tend to result in decreasing snow depth and a corresponding increase in snow density. Our results demonstrate that strategically placed WSNs can provide the necessary data at

Decrease in hydroclimatic conditions generating floods in the southeast of Belgium over the last 50 years resulting from changes in seasonal snow cover and extreme precipitation events

Science.gov (United States)

Wyard, Coraline; Fettweis, Xavier

2016-04-01

As a consequence of climate change, several studies concluded that winter flood occurrence could increase in the future in many rivers of northern and western Europe in response to an increase in extreme precipitation events. This study aims to determine if trends in extreme hydroclimatic events generating floods can already be detected over the last century. In particular, we focus on the Ourthe River (southeast of Belgium) which is one of the main tributaries of the Meuse River with a catchment area of 3500 km². In this river, most of the floods occur during winter and about 50% of them are due to rainfall events associated with the melting of the snow which covers the Ardennes during winter. In this study, hydroclimatic conditions favorable to flooding were reconstructed over the 20th century using the regional climate model MAR ("Modèle Atmosphérique Régional") forced by the following reanalyses: the ERA-20C, the ERA-Interim and the NCEP/NCAR-v1. The use of the MAR model allows to compute precipitation, snow depth and run-off resulting from precipitation events and snow melting in any part of the Ourthe river catchment area. Therefore, extreme hydroclimatic events, namely extreme run-off events, which could potentially generate floods, can be reconstructed using the MAR model. As validation, the MAR results were compared to weather station-based data. A trend analysis was then performed in order to study the evolution of conditions favorable to flooding in the Ourthe River catchment. The results show that the MAR model allows the detection of more than 95% of the hydroclimatic conditions which effectively generated observed floods in the Ourthe River over the 1974-2014 period. Conditions favorable to flooding present a negative trend over the last 50 years as a result of a decrease in snow accumulation and in extreme precipitation events. However, significance of these trends depends on the reanalysis used to force the regional climate model as well as the

Research of Snow-Melt Process on a Heated Platform

Directory of Open Access Journals (Sweden)

Vasilyev Gregory P.

2016-01-01

Full Text Available The article has shown the results of experimental researches of the snow-melt on a heated platform-near building heat-pump snow-melt platform. The near-building (yard heat pump platforms for snow melt with the area up to 10-15 m2 are a basis of the new ideology of organization of the street cleaning of Moscow from snow in the winter period which supposes the creation in the megalopolis of the «distributed snow-melt system» (DSMS using non-traditional energy sources. The results of natural experimental researches are presented for the estimation of efficiency of application in the climatic conditions of Moscow of heat pumps in the snow-melt systems. The researches were conducted on a model sample of the near-building heat-pump platform which uses the low-potential thermal energy of atmospheric air. The conducted researches have confirmed experimentally in the natural conditions the possibility and efficiency of using of atmospheric air as a source of low-potential thermal energy for evaporation of the snow-melt heat pump systems in the climatic conditions of Moscow. The results of laboratory researches of snow-melt process on a heated horizontal platform are presented. The researches have revealed a considerable dependence of efficiency of the snow-melt process on its piling mode (form-building and the organization of the process of its piling mode (form-building and the organization of the process of its (snow mass heat exchange with the surface of the heated platform. In the process of researches the effect of formation of an «ice dome» under the melting snow mass called by the fact that in case of the thickness of snow loaded on the platform more than 10 cm the water formed from the melting snow while the contact with the heating surface don’t spread on it, but soaks into the snow, wets it due to capillary effect and freezes. The formation of «ice dome» leads to a sharp increase of snow-melt period and decreases the operating

The effects of studded tires on fatal crashes with passenger cars and the benefits of electronic stability control (ESC) in Swedish winter driving.

Science.gov (United States)

Strandroth, Johan; Rizzi, Matteo; Olai, Maria; Lie, Anders; Tingvall, Claes

2012-03-01

This study set out to examine the effects of studded tires on fatal crashes on roads covered with ice or snow in Sweden and also to investigate the extra benefits of electronic stability control (ESC) during the winter months. Two different studies are presented in this paper. Both studies used an induced exposure approach. In the main study, 369 in-depth studies of fatal crashes with passenger cars were analyzed to determine whether loss-of-control (LOC) had been a major component or not. Only crashes involving cars without ESC and equipped with approved studded or non-studded winter tires were analyzed. The additional study used police-reported crashes that occurred during the winter seasons 2003-2010, involving passenger cars with and without ESC. While police records in Sweden do not include any tire information, it was assumed that most cars involved in crashes during the winter period would be equipped with studded tires. Findings in the main study showed that in 64% of the fatal crashes on roads covered with ice or snow LOC had been a major component. Furthermore, in 82% of LOC crashes, the passenger car over-steered prior to collision. Studded tires were found to have a statistically significant effect of 42% in terms of fatal crash reduction on roads covered with ice or snow, compared to non-studded winter tires. The effect on dry or wet roads in the winter was negative, although statistically non-significant. In the additional study, it was found that ESC further reduced crashes with injuries by 29%. The benefits on severe and fatal crashes were slightly greater (32%), although the lower 95% confidence limit was lower. Although studded tires were shown to reduce the risk of fatal crash involvement, compared to non-studded winter tires, the proportion of LOC and over-steering among cars with studded tires was large (59% and 49%, respectively). It was therefore concluded that studded tires do not prevent all LOC crashes, while ESC has benefits in those

Terra Data Confirm Warm, Dry U.S. Winter

Science.gov (United States)

2002-01-01

New maps of land surface temperature and snow cover produced by NASA's Terra satellite show this year's winter was warmer than last year's, and the snow line stayed farther north than normal. The observations confirm earlier National Oceanic and Atmospheric Administration reports that the United States was unusually warm and dry this past winter. (Click to read the NASA press release and to access higher-resolution images.) For the last two years, a new sensor aboard Terra has been collecting the most detailed global measurements ever made of our world's land surface temperatures and snow cover. The Moderate-resolution Imaging Spectroradiometer (MODIS) is already giving scientists new insights into our changing planet. Average temperatures during December 2001 through February 2002 for the contiguous United States appear to have been unseasonably warm from the Rockies eastward. In the top image the coldest temperatures appear black, while dark green, blue, red, yellow, and white indicate progressively warmer temperatures. MODIS observes both land surface temperature and emissivity, which indicates how efficiently a surface absorbs and emits thermal radiation. Compared to the winter of 2000-01, temperatures throughout much of the U.S. were warmer in 2001-02. The bottom image depicts the differences on a scale from dark blue (colder this year than last) to red (warmer this year than last). A large region of warm temperatures dominated the northern Great Plains, while the area around the Great Salt Lake was a cold spot. Images courtesy Robert Simmon, NASA GSFC, based upon data courtesy Zhengming Wan, MODIS Land Science Team member at the University of California, Santa Barbara's Institute for Computational Earth System Science

Estimating the snow water equivalent on a glacierized high elevation site (Forni Glacier, Italy)

Science.gov (United States)

Senese, Antonella; Maugeri, Maurizio; Meraldi, Eraldo; Verza, Gian Pietro; Azzoni, Roberto Sergio; Compostella, Chiara; Diolaiuti, Guglielmina

2018-04-01

We present and compare 11 years of snow data (snow depth and snow water equivalent, SWE) measured by an automatic weather station (AWS) and corroborated by data from field campaigns on the Forni Glacier in Italy. The aim of the analysis is to estimate the SWE of new snowfall and the annual SWE peak based on the average density of the new snow at the site (corresponding to the snowfall during the standard observation period of 24 h) and automated snow depth measurements. The results indicate that the daily SR50 sonic ranger measurements and the available snow pit data can be used to estimate the mean new snow density value at the site, with an error of ±6 kg m-3. Once the new snow density is known, the sonic ranger makes it possible to derive SWE values with an RMSE of 45 mm water equivalent (if compared with snow pillow measurements), which turns out to be about 8 % of the total SWE yearly average. Therefore, the methodology we present is interesting for remote locations such as glaciers or high alpine regions, as it makes it possible to estimate the total SWE using a relatively inexpensive, low-power, low-maintenance, and reliable instrument such as the sonic ranger.

Arctic Sea Ice, Eurasia Snow, and Extreme Winter Haze in China

Science.gov (United States)

Zou, Y.; Wang, Y.; Xie, Z.; Zhang, Y.; Koo, J. H.

2017-12-01

Eastern China is experiencing more severe haze pollution in winter during recent years. Though the environmental deterioration in this region is usually attributed to the high intensity of anthropogenic emissions and large contributions from secondary aerosol formation, the impact of climate variability is also indispensable given its significant influence on regional weather systems and pollution ventilation. Here we analyzed the air quality related winter meteorological conditions over Eastern China in the last four decades and showed a worsening trend in poor regional air pollutant ventilation. Such variations increased the probability of extreme air pollution events, which is in good agreement with aerosol observations of recent years. We further identified the key circulation pattern that is conducive to the weakening ventilation and investigated the relationship between synoptic circulation changes and multiple climate forcing variables. Both statistical analysis and numerical sensitivity experiments suggested that the poor ventilation condition is linked to boreal cryosphere changes including Arctic sea ice in preceding autumn and Eurasia snowfall in earlier winter. We conducted comprehensive dynamic diagnosis and proposed a physical mechanism to explain the observed and simulated circulation changes. At last, we examined future projections of winter extreme stagnation events based on the CMIP5 projection data.

The origin of sea salt in snow on Arctic sea ice and in coastal regions

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F. Domine

2004-01-01

Full Text Available Snow, through its trace constituents, can have a major impact on lower tropospheric chemistry, as evidenced by ozone depletion events (ODEs in oceanic polar areas. These ODEs are caused by the chemistry of bromine compounds that originate from sea salt bromide. Bromide may be supplied to the snow surface by upward migration from sea ice, by frost flowers being wind-blown to the snow surface, or by wind-transported aerosol generated by sea spray. We investigate here the relative importance of these processes by analyzing ions in snow near Alert and Ny-Ålesund (Canadian and European high Arctic in winter and spring. Vertical ionic profiles in the snowpack on sea ice are measured to test upward migration of sea salt ions and to seek evidence for ion fractionation processes. Time series of the ionic composition of surface snow layers are investigated to quantify wind-transported ions. Upward migration of unfractionated sea salt to heights of at least 17cm was observed in winter snow, leading to Cl- concentration of several hundred µM. Upward migration thus has the potential to supply ions to surface snow layers. Time series show that wind can deposit aerosols to the top few cm of the snow, leading also to Cl- concentrations of several hundred µM, so that both diffusion from sea ice and wind transport can significantly contribute ions to snow. At Ny-Ålesund, sea salt transported by wind was unfractionated, implying that it comes from sea spray rather than frost flowers. Estimations based on our results suggest that the marine snowpack contains about 10 times more Na+ than the frost flowers, so that both the marine snowpack and frost flowers need to be considered as sea salt sources. Our data suggest that ozone depletion chemistry can significantly enhance the Br- content of snow. We speculate that this can also take place in coastal regions and contribute to propagate ODEs inland. Finally, we stress the need to measure snow physical parameters

Weak layer fracture: facets and depth hoar

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I. Reiweger

2013-09-01

Full Text Available Understanding failure initiation within weak snow layers is essential for modeling and predicting dry-snow slab avalanches. We therefore performed laboratory experiments with snow samples containing a weak layer consisting of either faceted crystals or depth hoar. During these experiments the samples were loaded with different loading rates and at various tilt angles until fracture. The strength of the samples decreased with increasing loading rate and increasing tilt angle. Additionally, we took pictures of the side of four samples with a high-speed video camera and calculated the displacement using a particle image velocimetry (PIV algorithm. The fracture process within the weak layer could thus be observed in detail. Catastrophic failure started due to a shear fracture just above the interface between the depth hoar layer and the underlying crust.

Snow Cover Monitoring Using MODIS Data in Liaoning Province, Northeastern China

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Yu Lu

2010-03-01

Full Text Available This paper presents the results of snow cover monitoring studies in Liaoning Province, northeastern China, using MODIS data. Snow cover plays an important role in both the regional water balance and soil moisture properties during the early spring in northeastern China. In addition, heavy snowfalls commonly trigger hazards such as flooding, caused by rapid snow melt, or crop failure, resulting from fluctuations in soil temperature associated with changes in the snow cover. The latter is a function of both regional, or global, climatic changes, as well as fluctuations in the albedo resulting from variations in the Snow Covered Area (SCA. These impacts are crucial to human activities, especially to those living in middle-latitude areas such as Liaoning Province. Thus, SCA monitoring is currently an important tool in studies of global climate change, particularly because satellite remote sensing data provide timely and efficient snow cover information for large areas. In this study, MODIS L1B data, MODIS Daily Snow Products (MOD10A1 and MODIS 8-day Snow Products (MOD10A2 were used to monitor the SCA of Liaoning Province over the winter months of November–April, 2006–2008. The effects of cloud masking and forest masking on the snow monitoring results were also assessed. The results show that the SCA percentage derived from MODIS L1B data is relatively consistent, but slightly higher than that obtained from MODIS Snow Products. In situ data from 25 snow stations were used to assess the accuracy of snow cover monitoring from the SCA compared to the results from MODIS Snow Products. The studies found that the SCA results were more reliable than MODIS Snow Products in the study area.

Impacts of microtopographic snow redistribution and lateral subsurface processes on hydrologic and thermal states in an Arctic polygonal ground ecosystem: a case study using ELM-3D v1.0

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G. Bisht

2018-01-01

Full Text Available Microtopographic features, such as polygonal ground, are characteristic sources of landscape heterogeneity in the Alaskan Arctic coastal plain. Here, we analyze the effects of snow redistribution (SR and lateral subsurface processes on hydrologic and thermal states at a polygonal tundra site near Barrow, Alaska. We extended the land model integrated in the E3SM to redistribute incoming snow by accounting for microtopography and incorporated subsurface lateral transport of water and energy (ELM-3D v1.0. Multiple 10-year-long simulations were performed for a transect across a polygonal tundra landscape at the Barrow Environmental Observatory in Alaska to isolate the impact of SR and subsurface process representation. When SR was included, model predictions better agreed (higher R2, lower bias and RMSE with observed differences in snow depth between polygonal rims and centers. The model was also able to accurately reproduce observed soil temperature vertical profiles in the polygon rims and centers (overall bias, RMSE, and R2 of 0.59 °C, 1.82 °C, and 0.99, respectively. The spatial heterogeneity of snow depth during the winter due to SR generated surface soil temperature heterogeneity that propagated in depth and time and led to ∼ 10 cm shallower and  ∼ 5 cm deeper maximum annual thaw depths under the polygon rims and centers, respectively. Additionally, SR led to spatial heterogeneity in surface energy fluxes and soil moisture during the summer. Excluding lateral subsurface hydrologic and thermal processes led to small effects on mean states but an overestimation of spatial variability in soil moisture and soil temperature as subsurface liquid pressure and thermal gradients were artificially prevented from spatially dissipating over time. The effect of lateral subsurface processes on maximum thaw depths was modest, with mean absolute differences of ∼ 3 cm. Our integration of three-dimensional subsurface hydrologic and

The History of Winter: teachers as scientists

Science.gov (United States)

Koenig, L.; Courville, Z.; Wasilewski, P. J.; Gow, T.; Bender, K. J.

2013-12-01

The History of Winter (HOW) is a NASA Goddard Space Flight Center-funded teacher enrichment program that was started by Dr. Peter Wasilewski (NASA), Dr. Robert Gabrys (NASA) and Dr. Tony Gow (Cold Regions Research and Engineering Laboratory, or CRREL) in 2001 and continues with support and involvement of scientists from both the NASA Cryospheric Sciences Laboratory and CREEL. The program brings educators mostly from middle and high schools but also from state parks, community colleges and other institutions from across the US to the Northwood School (a small, private boarding school) in Lake Placid, NY for one week to learn about several facets of winter, polar, and snow research, including the science and history of polar ice core research, lake ice formation and structure, snow pack science, winter ecology, and remote sensing including current and future NASA cryospheric missions. The program receives support from the Northwood School staff to facilitate the program. The goal of the program is to create 'teachers as scientists' which is achieved through several hands-on field experiences in which the teachers have the opportunity to work with polar researchers from NASA, CRREL and partner Universities to dig and sample snow pits, make ice thin sections from lake ice, make snow shelters, and observe under-ice lake ecology. The hands-on work allows the teachers to use the same tools and techniques used in polar research while simultaneously introducing science concepts and activities to support their classroom work. The ultimate goal of the program is to provide the classroom teachers with the opportunity to learn about current and timely cryospheric research as well as to engage in real fieldwork experiences. The enthusiasm generated during the week-long program is translated into classroom activities with guidance from scientists, teachers and educational professionals. The opportunity to engage with polar researchers, both young investigators and renowned

Numerical modeling of a snow cover on Hooker Island (Franz Josef Land archipelago

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V. S. Sokratov

2013-01-01

Full Text Available Results obtained by simulating snow characteristics with a numerical model of surface heat and moisture exchange SPONSOR are presented. The numerical experiments are carried out for Franz Josef Land with typical Arctic climate conditions. The blizzard evaporation parameter is shown to have great influence on snow depth on territories with high wind speed. This parameter significantly improves the simulation quality of the numerical model. Some discrepancies between evaluated and observed snow depth values can be explained by inaccuracies in precipitation measurements (at least in certain cases and errors in calculations of incoming radiation, mostly due to low accuracy in the cloudiness observations.

State of Arctic Sea Ice North of Svalbard during N-ICE2015

Science.gov (United States)

Rösel, Anja; King, Jennifer; Gerland, Sebastian

2016-04-01

The N-ICE2015 cruise, led by the Norwegian Polar Institute, was a drift experiment with the research vessel R/V Lance from January to June 2015, where the ship started the drift North of Svalbard at 83°14.45' N, 21°31.41' E. The drift was repeated as soon as the vessel drifted free. Altogether, 4 ice stations where installed and the complex ocean-sea ice-atmosphere system was studied with an interdisciplinary Approach. During the N-ICE2015 cruise, extensive ice thickness and snow depth measurements were performed during both, winter and summer conditions. Total ice and snow thickness was measured with ground-based and airborne electromagnetic instruments; snow depth was measured with a GPS snow depth probe. Additionally, ice mass balance and snow buoys were deployed. Snow and ice thickness measurements were performed on repeated transects to quantify the ice growth or loss as well as the snow accumulation and melt rate. Additionally, we collected independent values on surveys to determine the general ice thickness distribution. Average snow depths of 32 cm on first year ice, and 52 cm on multi-year ice were measured in January, the mean snow depth on all ice types even increased until end of March to 49 cm. The average total ice and snow thickness in winter conditions was 1.92 m. During winter we found a small growth rate on multi-year ice of about 15 cm in 2 months, due to above-average snow depths and some extraordinary storm events that came along with mild temperatures. In contrast thereto, we also were able to study new ice formation and thin ice on newly formed leads. In summer conditions an enormous melt rate, mainly driven by a warm Atlantic water inflow in the marginal ice zone, was observed during two ice stations with melt rates of up to 20 cm per 24 hours. To reinforce the local measurements around the ship and to confirm their significance on a larger scale, we compare them to airborne thickness measurements and classified SAR-satellite scenes. The

Process-level model evaluation: a snow and heat transfer metric

Science.gov (United States)

Slater, Andrew G.; Lawrence, David M.; Koven, Charles D.

2017-04-01

Land models require evaluation in order to understand results and guide future development. Examining functional relationships between model variables can provide insight into the ability of models to capture fundamental processes and aid in minimizing uncertainties or deficiencies in model forcing. This study quantifies the proficiency of land models to appropriately transfer heat from the soil through a snowpack to the atmosphere during the cooling season (Northern Hemisphere: October-March). Using the basic physics of heat diffusion, we investigate the relationship between seasonal amplitudes of soil versus air temperatures due to insulation from seasonal snow. Observations demonstrate the anticipated exponential relationship of attenuated soil temperature amplitude with increasing snow depth and indicate that the marginal influence of snow insulation diminishes beyond an effective snow depth of about 50 cm. A snow and heat transfer metric (SHTM) is developed to quantify model skill compared to observations. Land models within the CMIP5 experiment vary widely in SHTM scores, and deficiencies can often be traced to model structural weaknesses. The SHTM value for individual models is stable over 150 years of climate, 1850-2005, indicating that the metric is insensitive to climate forcing and can be used to evaluate each model's representation of the insulation process.

Influence of Western Tibetan Plateau Summer Snow Cover on East Asian Summer Rainfall

Science.gov (United States)

Wang, Zhibiao; Wu, Renguang; Chen, Shangfeng; Huang, Gang; Liu, Ge; Zhu, Lihua

2018-03-01

The influence of boreal winter-spring eastern Tibetan Plateau snow anomalies on the East Asian summer rainfall variability has been the focus of previous studies. The present study documents the impacts of boreal summer western and southern Tibetan Plateau snow cover anomalies on summer rainfall over East Asia. Analysis shows that more snow cover in the western and southern Tibetan Plateau induces anomalous cooling in the overlying atmospheric column. The induced atmospheric circulation changes are different corresponding to more snow cover in the western and southern Tibetan Plateau. The atmospheric circulation changes accompanying the western Plateau snow cover anomalies are more obvious over the midlatitude Asia, whereas those corresponding to the southern Plateau snow cover anomalies are more prominent over the tropics. As such, the western and southern Tibetan Plateau snow cover anomalies influence the East Asian summer circulation and precipitation through different pathways. Nevertheless, the East Asian summer circulation and precipitation anomalies induced by the western and southern Plateau snow cover anomalies tend to display similar distribution so that they are more pronounced when the western and southern Plateau snow cover anomalies work in coherence. Analysis indicates that the summer snow cover anomalies over the Tibetan Plateau may be related to late spring snow anomalies due to the persistence. The late spring snow anomalies are related to an obvious wave train originating from the western North Atlantic that may be partly associated with sea surface temperature anomalies in the North Atlantic Ocean.

Application of radar polarimetry techniques for retrieval snow and rain characteristics in remote sensing

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M. Darvishi

2013-09-01

Full Text Available The presence of snow cover has significant impacts on the both global and regional climate and water balance on earth. The accurate estimation of snow cover area can be used for forecasting runoff due to snow melt and output of hydroelectric power. With development of remote sensing techniques at different scopes in earth science, enormous algorithms for retrieval hydrometeor parameters have been developed. Some of these algorithms are used to provide snow cover map such as NLR with AVHRR/MODIS sensor for Norway, Finnish with AVHRR sensor for Finland and NASA with MODIS sensor for global maps. Monitoring snow cover at different parts of spectral electromagnetic is detectable (visible, near and thermal infrared, passive and active microwave. Recently, specific capabilities of active microwave remote sensing such as snow extent map, snow depth, snow water equivalent (SWE, snow state (wet/dry and discrimination between rain and snow region were given a strong impetus for using this technology in snow monitoring, hydrology, climatology, avalanche research and etc. This paper evaluates the potentials and feasibility of polarimetric ground microwave measurements of snow in active remote sensing field. We will consider the behavior co- and cross-polarized backscattering coefficients of snowpack response with polarimetric scatterometer in Ku and L band at the different incident angles. Then we will show how to retrieve snow cover depth, snow permittivity and density parameters at the local scale with ground-based SAR (GB-SAR. Finally, for the sake of remarkable significant the transition region between rain and snow; the variables role of horizontal reflectivity (ZHH and differential reflectivity (ZDR in delineation boundary between snow and rain and some others important variables at polarimetric weather radar are presented.

Snow sublimation in mountain environments and its sensitivity to forest disturbance and climate warming

Science.gov (United States)

Sexstone, Graham A.; Clow, David W.; Fassnacht, Steven R.; Liston, Glen E.; Hiemstra, Christopher A.; Knowles, John F.; Penn, Colin A.

2018-01-01

Snow sublimation is an important component of the snow mass balance, but the spatial and temporal variability of this process is not well understood in mountain environments. This study combines a process‐based snow model (SnowModel) with eddy covariance (EC) measurements to investigate (1) the spatio‐temporal variability of simulated snow sublimation with respect to station observations, (2) the contribution of snow sublimation to the ablation of the snowpack, and (3) the sensitivity and response of snow sublimation to bark beetle‐induced forest mortality and climate warming across the north‐central Colorado Rocky Mountains. EC‐based observations of snow sublimation compared well with simulated snow sublimation at stations dominated by surface and canopy sublimation, but blowing snow sublimation in alpine areas was not well captured by the EC instrumentation. Water balance calculations provided an important validation of simulated sublimation at the watershed scale. Simulated snow sublimation across the study area was equivalent to 28% of winter precipitation on average, and the highest relative snow sublimation fluxes occurred during the lowest snow years. Snow sublimation from forested areas accounted for the majority of sublimation fluxes, highlighting the importance of canopy and sub‐canopy surface sublimation in this region. Simulations incorporating the effects of tree mortality due to bark‐beetle disturbance resulted in a 4% reduction in snow sublimation from forested areas. Snow sublimation rates corresponding to climate warming simulations remained unchanged or slightly increased, but total sublimation losses decreased by up to 6% because of a reduction in snow covered area and duration.

Measurement of the reduction of terrestrial gamma-ray dose rates by the snow cover using TL-dosimeters

International Nuclear Information System (INIS)

Sakamoto, Ryuichi; Saito, Kimiaki; Nagaoka, Toshi; Tsutsumi, Masahiro; Moriuchi, Shigeru

1990-12-01

The objective of the investigation is to make clear the effect of the snow cover on environmental gamma-ray field. The reduction in the natural terrestrial gamma-ray dose rate due to snow cover was measured by TL-dosimeters. The measurements were performed in autumn before snowfall and in winter from September 1987 through March 1988 in Nagaoka city, Niigata prefecture. The dosimeters were set at four points, both outside and inside of the houses, for three months. The penetration factors (ratios of terrestrial gamma-ray dose accumulated during snow covered period to those during snow free period) were 0.54-0.67 in the open field, and 0.73-0.95 in the houses. According to theoretical calculation by the Monte Carlo method and the published snowfall data, the corresponding penetration factor was estimated at 0.54 in an ideal open field. As a result, the measured penetration factors were larger than calculated one by 24 % at maximum. The variation of dose rate inside houses by the difference of the amount of snow fall has been investigated. In general, though the amount of snow fall changes every year, dose rates inside the house were proved to be affected little by them. And, the optimum value of snow density which adapted for inference of penetration factor was found to be 0.3 g/cm 3 . The penetration factors inferred from snowdepth data for the year distributed between 0.6 and 1.0 in winter from November 1985 through April 1986 in Niigata prefecture. (author)

Coupling of snow and permafrost processes using the Basic Modeling Interface (BMI)

Science.gov (United States)

Wang, K.; Overeem, I.; Jafarov, E. E.; Piper, M.; Stewart, S.; Clow, G. D.; Schaefer, K. M.

2017-12-01

We developed a permafrost modeling tool based by implementing the Kudryavtsev empirical permafrost active layer depth model (the so-called "Ku" component). The model is specifically set up to have a basic model interface (BMI), which enhances the potential coupling to other earth surface processes model components. This model is accessible through the Web Modeling Tool in Community Surface Dynamics Modeling System (CSDMS). The Kudryavtsev model has been applied for entire Alaska to model permafrost distribution at high spatial resolution and model predictions have been verified by Circumpolar Active Layer Monitoring (CALM) in-situ observations. The Ku component uses monthly meteorological forcing, including air temperature, snow depth, and snow density, and predicts active layer thickness (ALT) and temperature on the top of permafrost (TTOP), which are important factors in snow-hydrological processes. BMI provides an easy approach to couple the models with each other. Here, we provide a case of coupling the Ku component to snow process components, including the Snow-Degree-Day (SDD) method and Snow-Energy-Balance (SEB) method, which are existing components in the hydrological model TOPOFLOW. The work flow is (1) get variables from meteorology component, set the values to snow process component, and advance the snow process component, (2) get variables from meteorology and snow component, provide these to the Ku component and advance, (3) get variables from snow process component, set the values to meteorology component, and advance the meteorology component. The next phase is to couple the permafrost component with fully BMI-compliant TOPOFLOW hydrological model, which could provide a useful tool to investigate the permafrost hydrological effect.

Snow observations in Mount Lebanon (2011-2016)

Science.gov (United States)

Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; Fanise, Pascal; Drapeau, Laurent; Somma, Janine; Fadel, Ali; Bitar, Ahmad Al; Escadafal, Richard

2017-08-01

We present a unique meteorological and snow observational dataset in Mount Lebanon, a mountainous region with a Mediterranean climate, where snowmelt is an essential water resource. The study region covers the recharge area of three karstic river basins (total area of 1092 km2 and an elevation up to 3088 m). The dataset consists of (1) continuous meteorological and snow height observations, (2) snowpack field measurements, and (3) medium-resolution satellite snow cover data. The continuous meteorological measurements at three automatic weather stations (MZA, 2296 m; LAQ, 1840 m; and CED, 2834 m a.s.l.) include surface air temperature and humidity, precipitation, wind speed and direction, incoming and reflected shortwave irradiance, and snow height, at 30 min intervals for the snow seasons (November-June) between 2011 and 2016 for MZA and between 2014 and 2016 for CED and LAQ. Precipitation data were filtered and corrected for Geonor undercatch. Observations of snow height (HS), snow water equivalent, and snow density were collected at 30 snow courses located at elevations between 1300 and 2900 m a.s.l. during the two snow seasons of 2014-2016 with an average revisit time of 11 days. Daily gap-free snow cover extent (SCA) and snow cover duration (SCD) maps derived from MODIS snow products are provided for the same period (2011-2016). We used the dataset to characterize mean snow height, snow water equivalent (SWE), and density for the first time in Mount Lebanon. Snow seasonal variability was characterized with high HS and SWE variance and a relatively high snow density mean equal to 467 kg m-3. We find that the relationship between snow depth and snow density is specific to the Mediterranean climate. The current model explained 34 % of the variability in the entire dataset (all regions between 1300 and 2900 m a.s.l.) and 62 % for high mountain regions (elevation 2200-2900 m a.s.l.). The dataset is suitable for the investigation of snow dynamics and for the forcing

Influence of beech and spruce sub-montane forests on snow cover in Poľana Biosphere Reserve

Czech Academy of Sciences Publication Activity Database

Šatala, T.; Tesař, Miroslav; Hanzelová, M.; Bartík, M.; Šípek, Václav; Škvarenina, J.; Minďáš, J.; Waldhauserová, P.D.

2017-01-01

Roč. 72, č. 8 (2017), s. 854-861 ISSN 0006-3088 R&D Projects: GA ČR GA16-05665S Institutional support: RVO:67985874 Keywords : snow water equivalent * snow depth * snow accumulation * snow melting Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Hydrology Impact factor: 0.759, year: 2016

Canadian snow and sea ice: historical trends and projections