WorldWideScience

Sample records for winter snow depth

  1. The effects of changes in snow depth on winter recreation

    Czech Academy of Sciences Publication Activity Database

    Zahradníček, Pavel; Rožnovský, J.; Štěpánek, Petr; Farda, Aleš; Brzezina, J.

    2016-01-01

    Roč. 7, č. 1 (2016), s. 44-54 ISSN 1804-2821 R&D Projects: GA MŠk(CZ) LO1415; GA ČR GA13-04291S; GA ČR(CZ) GA14-12262S Institutional support: RVO:67179843 Keywords : new snow * total snow depth * climate change * climate models * winter recreations Subject RIV: EH - Ecology, Behaviour

  2. Monitoring Forsmark. Snow depth, snow water content and ice cover during the winter 2010/2011

    International Nuclear Information System (INIS)

    Wass, Eva

    2011-07-01

    Snow depth and ice cover have been measured and observed during the winter 2010/2011. This type of measurements started in the winter 2002/2003 and has been ongoing since then. In addition to these parameters, the water content of the snow was calculated at each measurement occasion from the weight of a snow sample. Measurements and observations were conducted on a regular basis from the beginning of November 2010 until the middle of April 2011. A persistent snow cover was established in the end of November 2010 and remained until the beginning of April 2011 at the station with longest snow cover duration. The period of ice cover was 160 days in Lake Eckarfjaerden, whereas the sea bay at SFR was ice covered for 135 days

  3. Combined Study of Snow Depth Determination and Winter Leaf Area Index Retrieval by Unmanned Aerial Vehicle Photogrammetry

    Science.gov (United States)

    Lendzioch, Theodora; Langhammer, Jakub; Jenicek, Michal

    2017-04-01

    A rapid and robust approach using Unmanned Aerial Vehicle (UAV) digital photogrammetry was performed for evaluating snow accumulation over different small localities (e.g. disturbed forest and open area) and for indirect field measurements of Leaf Area Index (LAI) of coniferous forest within the Šumava National Park, Czech Republic. The approach was used to reveal impacts related to changes in forest and snowpack and to determine winter effective LAI for monitoring the impact of forest canopy metrics on snow accumulation. Due to the advancement of the technique, snow depth and volumetric changes of snow depth over these selected study areas were estimated at high spatial resolution (1 cm) by subtracting a snow-free digital elevation model (DEM) from a snow-covered DEM. Both, downward-looking UAV images and upward-looking digital hemispherical photography (DHP), and additional widely used LAI-2200 canopy analyser measurements were applied to determine the winter LAI, controlling interception and transmitting radiation. For the performance of downward-looking UAV images the snow background instead of the sky fraction was used. The reliability of UAV-based LAI retrieval was tested by taking an independent data set during the snow cover mapping campaigns. The results showed the potential of digital photogrammetry for snow depth mapping and LAI determination by UAV techniques. The average difference obtained between ground-based and UAV-based measurements of snow depth was 7.1 cm with higher values obtained by UAV. The SD of 22 cm for the open area seemed competitive with the typical precision of point measurements. In contrast, the average difference in disturbed forest area was 25 cm with lower values obtained by UAV and a SD of 36 cm, which is in agreement with other studies. The UAV-based LAI measurements revealed the lowest effective LAI values and the plant canopy analyser LAI-2200 the highest effective LAI values. The biggest bias of effective LAI was observed

  4. Consistent seasonal snow cover depth and duration variability over ...

    Indian Academy of Sciences (India)

    Decline in consistent seasonal snow cover depth, duration and changing snow cover build- up pattern over the WH in recent decades indicate that WH has undergone considerable climate change and winter weather patterns are changing in the WH. 1. Introduction. Mountainous regions around the globe are storehouses.

  5. Scales of snow depth variability in high elevation rangeland sagebrush

    Science.gov (United States)

    Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

    2017-09-01

    In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

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

    Directory of Open Access Journals (Sweden)

    E. E. Stigter

    2017-07-01

    Full Text Available 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 equivalent (SWE. Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF. Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May and decreases during the late melt season (June to September as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

  7. 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)...

  8. CLPX-Ground: ISA Snow Depth Transects

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set is part of the NASA Cold Land Processes Field Experiment (CLPX). Parameters include snow depth, surface wetness, surface roughness, canopy, and soil...

  9. Linking snowfall and snow accumulation to generate spatial maps of SWE and snow depth

    Science.gov (United States)

    Broxton, Patrick D.; Dawson, Nicholas; Zeng, Xubin

    2016-06-01

    It is critically important but challenging to estimate the amount of snow on the ground over large areas due to its strong spatial variability. Point snow data are used to generate or improve (i.e., blend with) gridded estimates of snow water equivalent (SWE) by using various forms of interpolation; however, the interpolation methodologies often overlook the physical mechanisms for the snow being there in the first place. Using data from the Snow Telemetry and Cooperative Observer networks in the western United States, we show that four methods for the spatial interpolation of peak of winter snow water equivalent (SWE) and snow depth based on distance and elevation can result in large errors. These errors are reduced substantially by our new method, i.e., the spatial interpolation of these quantities normalized by accumulated snowfall from the current or previous water years. Our method results in significant improvement in SWE estimates over interpolation techniques that do not consider snowfall, regardless of the number of stations used for the interpolation. Furthermore, it can be used along with gridded precipitation and temperature data to produce daily maps of SWE over the western United States that are comparable to existing estimates (which are based on the assimilation of much more data). Our results also show that not honoring the constraint between SWE and snowfall when blending in situ data with gridded data can lead to the development and propagation of unrealistic errors.

  10. Combining snow depth and innovative skier flow measurements in order to improve snow grooming techniques

    Science.gov (United States)

    Carmagnola, Carlo Maria; Albrecht, Stéphane; Hargoaa, Olivier

    2017-04-01

    In the last decades, ski resort managers have massively improved their snow management practices, in order to adapt their strategies to the inter-annual variability in snow conditions and to the effects of climate change. New real-time informations, such as snow depth measurements carried out on the ski slopes by grooming machines during their daily operations, have become available, allowing high saving, efficiency and optimization gains (reducing for instance the groomer fuel consumption and operation time and the need for machine-made snow production). In order to take a step forward in improving the grooming techniques, it would be necessary to keep into account also the snow erosion by skiers, which depends mostly on the snow surface properties and on the skier attendance. Today, however, most ski resort managers have only a vague idea of the evolution of the skier flows on each slope during the winter season. In this context, we have developed a new sensor (named Skiflux) able to measure the skier attendance using an infrared beam crossing the slopes. Ten Skiflux sensors have been deployed during the 2016/17 winter season at Val Thorens ski area (French Alps), covering a whole sector of the resort. A dedicated software showing the number of skier passages in real time as been developed as well. Combining this new Skiflux dataset with the snow depth measurements from grooming machines (Snowsat System) and the snow and meteorological conditions measured in-situ (Liberty System from Technoalpin), we were able to create a "real-time skiability index" accounting for the quality of the surface snow and its evolution during the day. Moreover, this new framework allowed us to improve the preparation of ski slopes, suggesting new strategies for adapting the grooming working schedule to the snow quality and the skier attendance. In the near future, this work will benefit from the advances made within the H2020 PROSNOW project ("Provision of a prediction system allowing

  11. Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

    Science.gov (United States)

    Wainwright, Haruko M.; Liljedahl, Anna K.; Dafflon, Baptiste; Ulrich, Craig; Peterson, John E.; Gusmeroli, Alessio; Hubbard, Susan S.

    2017-04-01

    This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes and estimated using ground-penetrating radar (GPR) surveys and the photogrammetric detection and ranging (phodar) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE = 2.9 cm), with a spatial sampling of 10 cm along transects. Phodar-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing, while yielding a high precision (RMSE = 6.0 cm) and a fine spatial sampling (4 cm × 4 cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free lidar digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free lidar DEM and multiscale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high-precision estimates of snow depth (RMSE = 6.0 cm), at 0.5 m resolution and over the lidar domain (750 m × 700 m).

  12. Winter survival of Scots pine seedlings under different snow conditions.

    Science.gov (United States)

    Domisch, Timo; Martz, Françoise; Repo, Tapani; Rautio, Pasi

    2018-04-01

    Future climate scenarios predict increased air temperatures and precipitation, particularly at high latitudes, and especially so during winter. Soil temperatures, however, are more difficult to predict, since they depend strongly on the fate of the insulating snow cover. 'Rain-on-snow' events and warm spells during winter can lead to thaw-freeze cycles, compacted snow and ice encasement, as well as local flooding. These adverse conditions could counteract the otherwise positive effects of climatic changes on forest seedling growth. In order to study the effects of different winter and snow conditions on young Scots pine (Pinus sylvestris L.) seedlings, we conducted a laboratory experiment in which 80 1-year-old Scots pine seedlings were distributed between four winter treatments in dasotrons: ambient snow cover (SNOW), compressed snow and ice encasement (ICE), flooded and frozen soil (FLOOD) and no snow (NO SNOW). During the winter treatment period and a 1.5-month simulated spring/early summer phase, we monitored the needle, stem and root biomass of the seedlings, and determined their starch and soluble sugar concentrations. In addition, we assessed the stress experienced by the seedlings by measuring chlorophyll fluorescence, electric impedance and photosynthesis of the previous-year needles. Compared with the SNOW treatment, carbohydrate concentrations were lower in the FLOOD and NO SNOW treatments where the seedlings had almost died before the end of the experiment, presumably due to frost desiccation of aboveground parts during the winter treatments. The seedlings of the ICE treatment showed dead needles and stems only above the snow and ice cover. The results emphasize the importance of an insulating and protecting snow cover for small forest tree seedlings, and that future winters with changed snow patterns might affect the survival of tree seedlings and thus forest productivity.

  13. Rand Corporation Mean Monthly Global Snow Depth, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides monthly snow depth for the entire globe (excluding Africa and South America) from 1950 to 1976. All available monthly snow depth climatologies...

  14. Canadian Meteorological Centre (CMC) Daily Snow Depth Analysis Data

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of Northern Hemisphere snow depth analysis data processed by the Canadian Meteorological Centre (CMC). Snow depth data obtained from surface...

  15. Spatiotemporal variability of snow depth across the Eurasian continent from 1966 to 2012

    Science.gov (United States)

    Zhong, Xinyue; Zhang, Tingjun; Kang, Shichang; Wang, Kang; Zheng, Lei; Hu, Yuantao; Wang, Huijuan

    2018-01-01

    Snow depth is one of the key physical parameters for understanding land surface energy balance, soil thermal regime, water cycle, and assessing water resources from local community to regional industrial water supply. Previous studies by using in situ data are mostly site specific; data from satellite remote sensing may cover a large area or global scale, but uncertainties remain large. The primary objective of this study is to investigate spatial variability and temporal change in snow depth across the Eurasian continent. Data used include long-term (1966-2012) ground-based measurements from 1814 stations. Spatially, long-term (1971-2000) mean annual snow depths of >20 cm were recorded in northeastern European Russia, the Yenisei River basin, Kamchatka Peninsula, and Sakhalin. Annual mean and maximum snow depth increased by 0.2 and 0.6 cm decade-1 from 1966 through 2012. Seasonally, monthly mean snow depth decreased in autumn and increased in winter and spring over the study period. Regionally, snow depth significantly increased in areas north of 50° N. Compared with air temperature, snowfall had greater influence on snow depth during November through March across the former Soviet Union. This study provides a baseline for snow depth climatology and changes across the Eurasian continent, which would significantly help to better understanding climate system and climate changes on regional, hemispheric, or even global scales.

  16. 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...

  17. 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....

  18. 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.

  19. Nimbus-7 SMMR Derived Monthly Global Snow Cover and Snow Depth

    Data.gov (United States)

    National Aeronautics and Space Administration — The data set consists of monthly global snow cover and snow depth derived from Nimbus-7 SMMR data for 1978 through 1987. The SMMR data are interpolated for spatial...

  20. Nimbus-7 SMMR Derived Monthly Global Snow Cover and Snow Depth, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — The data set consists of monthly global snow cover and snow depth derived from Nimbus-7 SMMR data for 1978 through 1987. The SMMR data are interpolated for spatial...

  1. 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" target="_blank">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.

  2. Decadal variability in snow depth anomaly over Eurasia and its association with all India summer monsoon rainfall and seasonal circulations

    CERN Document Server

    Singh, G P

    2003-01-01

    The Historical Soviet Daily Snow Depth (HSDSD) version II data set has been used in the computation of winter and spring snow depth anomalies over west (25 deg. E to 70 deg. E, 35 deg. N to 65 deg. N) and east (70 deg. E to 160 deg. E, 35 deg. N to 65 deg. N) Eurasia. It is noticed that winter snow depth anomaly over east Eurasia is positively correlated while west Eurasia is negatively correlated with subsequent Indian summer monsoon rainfall (ISMR). The DJF snow depth anomaly shows highest and inverse correlation coefficient (CC) with ISMR over a large area of west Eurasia in a recent period of study i.e. 1975-1995. On the basis of standardised winter (mean of December, January and February) snow depth anomaly over west Eurasia, the years 1966, 1968, 1979 and 1986 are identified as high snow years and the years 1961 and 1975 as low snow years. The characteristics of seasonal monsoon circulation features have been studied in detail during contrasting years of less (more) snow depth in winter/spring seasons f...

  3. 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.

  4. 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.

  5. 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

    frequent extreme winter warming events. Flower production of many Arctic plants is dependent on melt out timing, since season length determines resource availability for flower preformation. We erected snow fences to increase snow depth and shorten growing season, and counted flowers of six species over 5......years, during which we experienced two extreme winter warming events. Most species were resistant to snow cover increase, but two species reduced flower abundance due to shortened growing seasons. Cassiope tetragona responded strongly with fewer flowers in deep snow regimes during years without extreme...... 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...

  6. 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.

  7. Consistent seasonal snow cover depth and duration variability over ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Earth System Science; Volume 125; Issue 7. Consistent seasonal ... Consistent seasonal snow cover depth and duration, delay days and early melt days of consistent seasonal snow cover at 11 stations spread across different mountain ranges over the WH were analyzed. Mean, maximum and ...

  8. Consistent seasonal snow cover depth and duration variability over ...

    Indian Academy of Sciences (India)

    of biodiversity, global ecosystem and global hydro- logical cycle (Robinson ... climate change impacts assessment, water resources ...... Brown R D and Braaten R O 1998 Spatial and temporal vari- ability of Canadian monthly snow depths; Atmos. Ocean. 36 37–54. Cayan D R 1996 Interannual climate variability and snow.

  9. 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...

  10. CLPX-Ground: ISA Snow Depth Transects and Related Measurements

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of snow depth data from nine study areas, within three larger-scale areas in northern Colorado (Fraser, North Park, and Rabbit Ears Meso-cell...

  11. 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...

  12. Variability of snow depth at the plot scale: implications for mean depth estimation and sampling strategies

    Directory of Open Access Journals (Sweden)

    J. I. López-Moreno

    2011-08-01

    Full Text Available Snow depth variability over small distances can affect the representativeness of depth samples taken at the local scale, which are often used to assess the spatial distribution of snow at regional and basin scales. To assess spatial variability at the plot scale, intensive snow depth sampling was conducted during January and April 2009 in 15 plots in the Rio Ésera Valley, central Spanish Pyrenees Mountains. Each plot (10 × 10 m; 100 m2 was subdivided into a grid of 1 m2 squares; sampling at the corners of each square yielded a set of 121 data points that provided an accurate measure of snow depth in the plot (considered as ground truth. The spatial variability of snow depth was then assessed using sampling locations randomly selected within each plot. The plots were highly variable, with coefficients of variation up to 0.25. This indicates that to improve the representativeness of snow depth sampling in a given plot the snow depth measurements should be increased in number and averaged when spatial heterogeneity is substantial.

    Snow depth distributions were simulated at the same plot scale under varying levels of standard deviation and spatial autocorrelation, to enable the effect of each factor on snowpack representativeness to be established. The results showed that the snow depth estimation error increased markedly as the standard deviation increased. The results indicated that in general at least five snow depth measurements should be taken in each plot to ensure that the estimation error is <10 %; this applied even under highly heterogeneous conditions. In terms of the spatial configuration of the measurements, the sampling strategy did not impact on the snow depth estimate under lack of spatial autocorrelation. However, with a high spatial autocorrelation a smaller error was obtained when the distance between measurements was greater.

  13. 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.

  14. 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

  15. 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.

  16. Daily snow depth measurements from 195 stations in the United States

    Energy Technology Data Exchange (ETDEWEB)

    Allison, L.J. [ed.] [Oak Ridge National Lab., TN (United States). Carbon Dioxide Information Analysis Center; Easterling, D.R.; Jamason, P.; Bowman, D.P.; Hughes, P.Y.; Mason, E.H. [National Oceanic and Atmospheric Administration, Asheville, NC (United States). National Climatic Data Center

    1997-02-01

    This document describes a database containing daily measurements of snow depth at 195 National Weather Service (NWS) first-order climatological stations in the United States. The data have been assembled and made available by the National Climatic Data Center (NCDC) in Asheville, North Carolina. The 195 stations encompass 388 unique sampling locations in 48 of the 50 states; no observations from Delaware or Hawaii are included in the database. Station selection criteria emphasized the quality and length of station records while seeking to provide a network with good geographic coverage. Snow depth at the 388 locations was measured once per day on ground open to the sky. The daily snow depth is the total depth of the snow on the ground at measurement time. The time period covered by the database is 1893--1992; however, not all station records encompass the complete period. While a station record ideally should contain daily data for at least the seven winter months (January through April and October through December), not all stations have complete records. Each logical record in the snow depth database contains one station`s daily data values for a period of one month, including data source, measurement, and quality flags.

  17. Daily Snow Depth and SWE from GPS Signal-to-Noise Ratios, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of daily snow depths and snow-water equivalents (SWEs) estimated from GPS signal-to-noise ratios (SNRs). Snow depth is determined by...

  18. 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.

  19. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  1. Quantifying the impacts of snow on surface energy balance through assimilating snow cover fraction and snow depth

    Science.gov (United States)

    Meng, Chunlei

    2017-10-01

    Seasonal snow plays an important part in Earth's climate system. Snow cover regulates the land surface energy balance through altering the albedo of the land surface. To utilize the satellite-retrieved snow cover fraction (SCF) and snow depth (SD) data sufficiently and avoid inconsistency, this paper developed a very simple but robust quality control method to assimilate Fengyun satellite-retrieved SCF and SD simultaneously. The results show that the assimilation method which this paper implemented can not only utilize the satellite-retrieved SCF and SD data sufficiently but also avoid the inconsistency of them. Two experiments were designed and performed to quantify the impacts of snow on land surface energy balance using the integrated urban land model. With the increase of the SCF and SD, the net radiation decreased significantly during the day and increased a little at night; the sensible heat flux decreased significantly during the day; the evapotranspiration and ground heat flux decreased during the day too.

  2. Winter precipitation and snow accumulation drive the methane sink or source strength of Arctic tussock tundra.

    Science.gov (United States)

    Blanc-Betes, Elena; Welker, Jeffrey M; Sturchio, Neil C; Chanton, Jeffrey P; Gonzalez-Meler, Miquel A

    2016-08-01

    Arctic winter precipitation is projected to increase with global warming, but some areas will experience decreases in snow accumulation. Although Arctic CH4 emissions may represent a significant climate forcing feedback, long-term impacts of changes in snow accumulation on CH4 fluxes remain uncertain. We measured ecosystem CH4 fluxes and soil CH4 and CO2 concentrations and (13) C composition to investigate the metabolic pathways and transport mechanisms driving moist acidic tundra CH4 flux over the growing season (Jun-Aug) after 18 years of experimental snow depth increases and decreases. Deeper snow increased soil wetness and warming, reducing soil %O2 levels and increasing thaw depth. Soil moisture, through changes in soil %O2 saturation, determined predominance of methanotrophy or methanogenesis, with soil temperature regulating the ecosystem CH4 sink or source strength. Reduced snow (RS) increased the fraction of oxidized CH4 (Fox) by 75-120% compared to Ambient, switching the system from a small source to a net CH4 sink (21 ± 2 and -31 ± 1 mg CH4  m(-2)  season(-1) at Ambient and RS). Deeper snow reduced Fox by 35-40% and 90-100% in medium- (MS) and high- (HS) snow additions relative to Ambient, contributing to increasing the CH4 source strength of moist acidic tundra (464 ± 15 and 3561 ± 97 mg CH4  m(-2)  season(-1) at MS and HS). Decreases in Fox with deeper snow were partly due to increases in plant-mediated CH4 transport associated with the expansion of tall graminoids. Deeper snow enhanced CH4 production within newly thawed soils, responding mainly to soil warming rather than to increases in acetate fermentation expected from thaw-induced increases in SOC availability. Our results suggest that increased winter precipitation will increase the CH4 source strength of Arctic tundra, but the resulting positive feedback on climate change will depend on the balance between areas with more or less snow accumulation than they are currently

  3. Spatiotemporal Variability of Snow Depth across Eurasian Continent from 1966 to 2008

    Science.gov (United States)

    Zhong, X.; Zhang, T.; Wang, K.

    2013-12-01

    Snow depth is one of the important parameters of snow cover, and it affects the surface energy balance, assessment of snow water equivalent, ecosystem, soil temperatures, and water cycle as a whole. In this study, the long-term observed snow depth from 1972 meteorological stations and snow course sites were used to investigate snow depth climatology and its spatiotemporal variations over Eurasian Continent from 1966 to 2008. Preliminary results showed that snow depth was affected by latitude, which in general snow depth increased with the increasing latitude. The higher values of snow depth were found in the northeastern European Russia, the east of western Siberia, the west of central Siberia, Kamchatka Peninsula, and some areas of Sakhalin. While the lower snow accumulation occurred in most areas of China except for the north of Xinjiang Autonomous Region of China, Northeast China, and some regions of the southwestern Tibet. Both of the trends in inter-annual variability of annual mean snow depth and annual maximum snow depth were not significant. However, the long-term monthly mean snow depth had obvious increasing trends from February to May. There were similar spatial distributions of linear trend coefficients of annual mean snow depth and annual maximum snow depth across the former Soviet Union (USSR). The most significant trends of changes in annual mean snow depth and annual maximum snow depth were found between 40° to 70°N. The obvious trends of variability in monthly mean snow depth appeared in the areas between 50° to 60°N. The significant decreasing trends in monthly mean snow depth were observed in most areas of China from February to March. This may be largely influenced by climate change, which leads to an advancing of the end date of snow cover.

  4. Converting Snow Depth to SWE: The Fusion of Simulated Data with Remote Sensing Retrievals and the Airborne Snow Observatory

    Science.gov (United States)

    Bormann, K.; Marks, D. G.; Painter, T. H.; Hedrick, A. R.; Deems, J. S.

    2015-12-01

    Snow cover monitoring has greatly benefited from remote sensing technology but, despite their critical importance, spatially distributed measurements of snow water equivalent (SWE) in mountain terrain remain elusive. Current methods of monitoring SWE rely on point measurements and are insufficient for distributed snow science and effective management of water resources. Many studies have shown that the spatial variability in SWE is largely controlled by the spatial variability in snow depth. JPL's Airborne Snow Observatory mission (ASO) combines LiDAR and spectrometer instruments to retrieve accurate and very high-resolution snow depth measurements at the watershed scale, along with other products such as snow albedo. To make best use of these high-resolution snow depths, spatially distributed snow density data are required to leverage SWE from the measured snow depths. Snow density is a spatially and temporally variable property that cannot yet be reliably extracted from remote sensing techniques, and is difficult to extrapolate to basin scales. However, some physically based snow models have shown skill in simulating bulk snow densities and therefore provide a pathway for snow depth to SWE conversion. Leveraging model ability where remote sensing options are non-existent, ASO employs a physically based snow model (iSnobal) to resolve distributed snow density dynamics across the basin. After an adjustment scheme guided by in-situ data, these density estimates are used to derive the elusive spatial distribution of SWE from the observed snow depth distributions from ASO. In this study, we describe how the process of fusing model data with remote sensing retrievals is undertaken in the context of ASO along with estimates of uncertainty in the final SWE volume products. This work will likely be of interest to those working in snow hydrology, water resource management and the broader remote sensing community.

  5. 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

  6. Tree-Ring Widths and Snow Cover Depth in High Tauern

    Science.gov (United States)

    Falarz, Malgorzata

    2017-12-01

    The aim of the study is to examine the correlation of Norway spruce tree-ring widths and the snow cover depth in the High Tauern mountains. The average standardized tree-ring widths indices for Nowary spruce posted by Bednarz and Niedzwiedz (2006) were taken into account. Increment cores were collected from 39 Norway spruces growing in the High Tauern near the upper limit of the forest at altitude of 1700-1800 m, 3 km from the meteorological station at Sonnblick. Moreover, the maximum of snow cover depth in Sonnblick (3105 m a.s.l.) for each winter season in the period from 1938/39 to 1994/95 (57 winter seasons) was taken into account. The main results of the research are as follows: (1) tree-ring widths in a given year does not reveal statistically significant dependency on the maximum snow cover depth observed in the winter season, which ended this year; (2) however, the tested relationship is statistically significant in the case of correlating of the tree-ring widths in a given year with a maximum snow cover depth in a season of previous year. The correlation coefficient for the entire period of the study is not very high (r=0.27) but shows a statistical significance at the 0.05 level; (3) the described relationship is not stable over time. 30-year moving correlations showed no significant dependencies till 1942 and after 1982 (probably due to the so-called divergence phenomenon). However, during the period of 1943-1981 the values of correlation coefficient for moving 30-year periods are statistically significant and range from 0.37 to 0.45; (4) the correlation coefficient between real and calibrated (on the base of the regression equation) values of maximum snow cover depth is statistically significant for calibration period and not significant for verification one; (5) due to a quite short period of statistically significant correlations and not very strict dependencies, the reconstruction of snow cover on Sonnblick for the period before regular measurements

  7. Understanding Snow Depth Variability with Respect to the Canopy in Multiple Climates Using Airborne LiDAR

    Science.gov (United States)

    Currier, W. R.; Giulia, M.; Pflug, J. M.; Jonas, T.; Jessica, L.

    2017-12-01

    Snow depth within a typical hydrologic model grid cell (150 m or 1 km) can vary from 0.5 meters to 6 meters, or more. This variability is driven by the meteorological conditions throughout the winter as well as the forest architecture. To better understand this variability, we used airborne LiDAR from Olympic National Park, WA, Yosemite National Park, CA, Jemez Caldera, NM, and Niwot Ridge, CO to determine unique spatial patterns of snow depth in forested regions. Specifically, we compared snow depth distributions along north facing forest edges and south facing forest edges to those in the open or directly under the canopy. When categorizing the north facing and south facing edges based on distance from the canopy, distances relative to tree height, and distances relative to the fraction of the sky that is visible (sky view factor) we found unique snow depth patterns for each of these regions. In all regions besides Olympic National Park, WA, north facing edges contained more snow than open areas, forested areas, or along the south facing edges. These snow distributions were relatively consistent regardless of the metric used to define the forest edge and the size of the domain (150 m through 1 km). The absence of the forest edge effect in Olympic National Park was attributed to the meteorological data and climate conditions, which showed significantly less incoming shortwave radiation and more incoming longwave radiation. Furthermore, this study evaluated the effect that wind speed and direction have on the spatial distribution of snow depth.

  8. 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.

  9. 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.

  10. Decadal variability in snow depth anomaly over Eurasia and its association with all India summer monsoon rainfall and seasonal circulations

    International Nuclear Information System (INIS)

    Singh, G.P.

    2003-05-01

    The Historical Soviet Daily Snow Depth (HSDSD) version II data set has been used in the computation of winter and spring snow depth anomalies over west (25 deg. E to 70 deg. E, 35 deg. N to 65 deg. N) and east (70 deg. E to 160 deg. E, 35 deg. N to 65 deg. N) Eurasia. It is noticed that winter snow depth anomaly over east Eurasia is positively correlated while west Eurasia is negatively correlated with subsequent Indian summer monsoon rainfall (ISMR). The DJF snow depth anomaly shows highest and inverse correlation coefficient (CC) with ISMR over a large area of west Eurasia in a recent period of study i.e. 1975-1995. On the basis of standardised winter (mean of December, January and February) snow depth anomaly over west Eurasia, the years 1966, 1968, 1979 and 1986 are identified as high snow years and the years 1961 and 1975 as low snow years. The characteristics of seasonal monsoon circulation features have been studied in detail during contrasting years of less (more) snow depth in winter/spring seasons followed by excess (deficient) rainfall over India using National Center for Environmental Prediction (NCEP) / National Center for Atmospheric Research (NCAR) reanylised data for the period 1948-1995. The composite difference of temperature, wind, stream function and velocity potential during the years of high and low snow years at upper and lower levels have been studied in detail. The temperature at lower level shows maximum cooling up to 6 deg. C during DJF and this cooling persists up to 500hPa by 2 deg. C which gives rise to anomalous cyclonic circulation over the Caspian Sea and this may be one of the causes of the weakening of the summer monsoon circulation over Indian sub-continent. The stream function difference fields show westerly dominated over Arabian Sea at upper level in weak monsoon years. Velocity potential difference field shows complete phase reversal in the dipole structure from the deficient to excess Indian summer monsoon rainfall. (author)

  11. 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

  12. 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

  13. The Snowtweets Project: communicating snow depth measurements from specialists and non-specialists via mobile communication technologies and social networks

    Science.gov (United States)

    King, J. M.; Cabrera, A. R.; Kelly, R. E.

    2009-12-01

    With the global decline of in situ snow measurements for hydrometeorological applications, there is an evolving need to find alternative ways to collect localized measurements of snow. The Snowtweets Project is an experiment aimed at providing a way for people interested in making snow measurements to quickly broadcast their measurements to the internet. The goal of the project is to encourage specialists and non-specialists alike to share simple snow depth measurements through widely available social networking sites. We are currently using the rapidly growing microblogging site Twitter (www.twitter.com) as a broadcasting vehicle to collect the snow depth measurements. Using 140 characters or less, users "tweet" their snow depth from their location through the Twitter website. This can be done from a computer or smartphone with internet access or through SMS messaging. The project has developed a Snowtweets web application that interrogates Twitter by parsing the 140 character string to obtain a geographic position and snow depth. GeoRSS and KML feeds are available to visualize the tweets in GoogleEarth or they can be viewed in our own visualiser, Snowbird. The emphasis is on achieving wide coverage to increase the number of microblogs. Furthermore, after some quality control filters, the project is able to combine the broadcast snow depths with traditional and objective satellite remote sensing-based observations or hydrologic model estimates. Our site, snowcore.uwaterloo.ca, was launched in July 2009 and is ready for the 2009-2010 northern hemisphere winter. We invite comments from experienced community participation projects to help improve our product.

  14. 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.

  15. Mapping snow depth return levels: smooth spatial modeling versus station interpolation

    Directory of Open Access Journals (Sweden)

    J. Blanchet

    2010-12-01

    Full Text Available For adequate risk management in mountainous countries, hazard maps for extreme snow events are needed. This requires the computation of spatial estimates of return levels. In this article we use recent developments in extreme value theory and compare two main approaches for mapping snow depth return levels from in situ measurements. The first one is based on the spatial interpolation of pointwise extremal distributions (the so-called Generalized Extreme Value distribution, GEV henceforth computed at station locations. The second one is new and based on the direct estimation of a spatially smooth GEV distribution with the joint use of all stations. We compare and validate the different approaches for modeling annual maximum snow depth measured at 100 sites in Switzerland during winters 1965–1966 to 2007–2008. The results show a better performance of the smooth GEV distribution fitting, in particular where the station network is sparser. Smooth return level maps can be computed from the fitted model without any further interpolation. Their regional variability can be revealed by removing the altitudinal dependent covariates in the model. We show how return levels and their regional variability are linked to the main climatological patterns of Switzerland.

  16. Estimating Snow Depth and Snow Water Equivalence Using Repeat-Pass Interferometric SAR in the Northern Piedmont Region of the Tianshan Mountains

    OpenAIRE

    Li, Hui; Wang, Zuo; He, Guangjun; Man, Wang

    2017-01-01

    Snow depth and Snow Water Equivalence (SWE) are important parameters for hydrological applications. In this application, a theoretical method of snow depth estimation with repeat-pass InSAR measurements was proposed, and a preliminary sensitivity analysis of snow phase changes versus the incident angle and snow density was developed. Moreover, the snow density and incident angle parameters were analyzed and calibrated, and the local incident angle was used as a substitute for the satellite in...

  17. 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.

  18. Determining Snow Depth Using Airborne Multi-Pass Interferometric Synthetic Aperture Radar

    Science.gov (United States)

    2013-09-01

    Then, in regions without surface reports, SSMI /S algorithms are used to detect snow. If no snow was previously detected, a value of 0.1m of snow...be representative of the region that SNODEP is trying to describe. To make up for this poor coverage of in- situ observations the SSMIS passive...microwave satellite is used to determine the snow depth everywhere else. SSMIS does this by using a correlation coefficient between the microwave

  19. Estimating Snow Depth and Snow Water Equivalence Using Repeat-Pass Interferometric SAR in the Northern Piedmont Region of the Tianshan Mountains

    Directory of Open Access Journals (Sweden)

    Hui Li

    2017-01-01

    Full Text Available Snow depth and Snow Water Equivalence (SWE are important parameters for hydrological applications. In this application, a theoretical method of snow depth estimation with repeat-pass InSAR measurements was proposed, and a preliminary sensitivity analysis of snow phase changes versus the incident angle and snow density was developed. Moreover, the snow density and incident angle parameters were analyzed and calibrated, and the local incident angle was used as a substitute for the satellite incident angle to improve the snow depth estimation. From the results, the coherence images showed that a high degree of coherence can be found for dry snow, and, apart from the effect of snow, land use/cover change due to a long temporal baseline and geometric distortion due to the rugged terrain were the main constraints for InSAR technique to measure snow depth and SWE in this area. The result of snow depth estimation between July 2008 and February 2009 demonstrated that the average snow depth was about 20 cm, which was consistent with the field survey results. The areal coverage of snow distribution estimated from the snow depth and SWE results was consistent with snow cover obtained from HJ-1A CCD optical data at the same time.

  20. 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

  1. 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.

  2. Soil thermal dynamics, snow cover, and frozen depth under five temperature treatments in an ombrotrophic bog: Constrained forecast with data assimilation

    Science.gov (United States)

    Huang, Yuanyuan; Jiang, Jiang; Ma, Shuang; Ricciuto, Daniel; Hanson, Paul J.; Luo, Yiqi

    2017-08-01

    Accurate simulation of soil thermal dynamics is essential for realistic prediction of soil biogeochemical responses to climate change. To facilitate ecological forecasting at the Spruce and Peatland Responses Under Climatic and Environmental change site, we incorporated a soil temperature module into a Terrestrial ECOsystem (TECO) model by accounting for surface energy budget, snow dynamics, and heat transfer among soil layers and during freeze-thaw events. We conditioned TECO with detailed soil temperature and snow depth observations through data assimilation before the model was used for forecasting. The constrained model reproduced variations in observed temperature from different soil layers, the magnitude of snow depth, the timing of snowfall and snowmelt, and the range of frozen depth. The conditioned TECO forecasted probabilistic distributions of soil temperature dynamics in six soil layers, snow, and frozen depths under temperature treatments of +0.0, +2.25, +4.5, +6.75, and +9.0°C. Air warming caused stronger elevation in soil temperature during summer than winter due to winter snow and ice. And soil temperature increased more in shallow soil layers in summer in response to air warming. Whole ecosystem warming (peat + air warmings) generally reduced snow and frozen depths. The accuracy of forecasted snow and frozen depths relied on the precision of weather forcing. Uncertainty is smaller for forecasting soil temperature but large for snow and frozen depths. Timely and effective soil thermal forecast, constrained through data assimilation that combines process-based understanding and detailed observations, provides boundary conditions for better predictions of future biogeochemical cycles.

  3. Soil thermal dynamics, snow cover, and frozen depth under five temperature treatments in an ombrotrophic bog: Constrained forecast with data assimilation: Forecast With Data Assimilation

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Yuanyuan [Department of Microbiology and Plant Biology, University of Oklahoma, Norman Oklahoma USA; Jiang, Jiang [Department of Microbiology and Plant Biology, University of Oklahoma, Norman Oklahoma USA; Key Laboratory of Soil and Water Conservation and Ecological Restoration in Jiangsu Province, Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province, Nanjing Forestry University, Nanjing China; Ma, Shuang [Department of Microbiology and Plant Biology, University of Oklahoma, Norman Oklahoma USA; Ricciuto, Daniel [Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge Tennessee USA; Hanson, Paul J. [Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge Tennessee USA; Luo, Yiqi [Department of Microbiology and Plant Biology, University of Oklahoma, Norman Oklahoma USA; Department of Earth System Science, Tsinghua University, Beijing China

    2017-08-01

    Accurate simulation of soil thermal dynamics is essential for realistic prediction of soil biogeochemical responses to climate change. To facilitate ecological forecasting at the Spruce and Peatland Responses Under Climatic and Environmental change site, we incorporated a soil temperature module into a Terrestrial ECOsystem (TECO) model by accounting for surface energy budget, snow dynamics, and heat transfer among soil layers and during freeze-thaw events. We conditioned TECO with detailed soil temperature and snow depth observations through data assimilation before the model was used for forecasting. The constrained model reproduced variations in observed temperature from different soil layers, the magnitude of snow depth, the timing of snowfall and snowmelt, and the range of frozen depth. The conditioned TECO forecasted probabilistic distributions of soil temperature dynamics in six soil layers, snow, and frozen depths under temperature treatments of +0.0, +2.25, +4.5, +6.75, and +9.0°C. Air warming caused stronger elevation in soil temperature during summer than winter due to winter snow and ice. And soil temperature increased more in shallow soil layers in summer in response to air warming. Whole ecosystem warming (peat + air warmings) generally reduced snow and frozen depths. The accuracy of forecasted snow and frozen depths relied on the precision of weather forcing. Uncertainty is smaller for forecasting soil temperature but large for snow and frozen depths. Timely and effective soil thermal forecast, constrained through data assimilation that combines process-based understanding and detailed observations, provides boundary conditions for better predictions of future biogeochemical cycles.

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

    Directory of Open Access Journals (Sweden)

    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.;

  5. 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

  6. Disentangling the mechanisms behind winter snow impact on vegetation activity in northern ecosystems.

    Science.gov (United States)

    Wang, Xiaoyi; Wang, Tao; Guo, Hui; Liu, Dan; Zhao, Yutong; Zhang, Taotao; Liu, Qiang; Piao, Shilong

    2018-04-01

    Although seasonal snow is recognized as an important component in the global climate system, the ability of snow to affect plant production remains an important unknown for assessing climate change impacts on vegetation dynamics at high-latitude ecosystems. Here, we compile data on satellite observation of vegetation greenness and spring onset date, satellite-based soil moisture, passive microwave snow water equivalent (SWE) and climate data to show that winter SWE can significantly influence vegetation greenness during the early growing season (the period between spring onset date and peak photosynthesis timing) over nearly one-fifth of the land surface in the region north of 30 degrees, but the magnitude and sign of correlation exhibits large spatial heterogeneity. We then apply an assembled path model to disentangle the two main processes (via changing early growing-season soil moisture, and via changing the growth period) in controlling the impact of winter SWE on vegetation greenness, and suggest that the "moisture" and "growth period" effect, to a larger extent, result in positive and negative snow-productivity associations, respectively. The magnitude and sign of snow-productivity association is then dependent upon the relative dominance of these two processes, with the "moisture" effect and positive association predominating in Central, western North America and Greater Himalaya, and the "growth period" effect and negative association in Central Europe. We also indicate that current state-of-the-art models in general reproduce satellite-based snow-productivity relationship in the region north of 30 degrees, and do a relatively better job of capturing the "moisture" effect than the "growth period" effect. Our results therefore work towards an improved understanding of winter snow impact on vegetation greenness in northern ecosystems, and provide a mechanistic basis for more realistic terrestrial carbon cycle models that consider the impacts of winter snow

  7. 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 (<3%), with equal movement between northern and southern wintering areas for Wrangel Island birds and little evidence of exchange between the Banks and northern Wrangel Island

  8. Frost flower chemical signature in winter snow on Vestfonna ice cap, Nordaustlandet, Svalbard

    Directory of Open Access Journals (Sweden)

    E. Beaudon

    2009-07-01

    Full Text Available The chemistry of snow and ice cores from Svalbard is influenced by variations in local sea ice margin and distance to open water. Snow pits sampled at two summits of Vestfonna ice cap (Nordaustlandet, Svalbard, exhibit spatially heterogeneous soluble ions concentrations despite similar accumulation rates, reflecting the importance of small-scale weather patterns on this island ice cap. The snow pack on the western summit shows higher average values of marine ions and a winter snow layer that is relatively depleted in sulphate. One part of the winter snow pack exhibits a [SO42-/Na+] ratio reduced by two thirds compared with its ratio in sea water. This low sulphate content in winter snow is interpreted as the signature of frost flowers, which are formed on young sea ice when offshore winds predominate. Frost flowers have been described as the dominant source of sea salt to aerosol and precipitation in ice cores in coastal Antarctica but this is the first time their chemical signal has been described in the Arctic. The eastern summit does not show any frost flower signature and we interpret the unusually dynamic ice transport and rapid formation of thin ice on the Hinlopen Strait as the source of the frost flowers.

  9. Snow line analysis in the Romanian Carpathians under the influence of winter warming

    Science.gov (United States)

    Micu, Dana; Cosmin Sandric, Ionut

    2013-04-01

    The Romanian Carpathians are subject to winter warming as statistically proved by station measurements over a 47 year period (1961-2007). Herein, the snow season is considered to last from the 1st of November to the 30th of April, when snowpack usually reaches the highest stability and thickness. This paper investigates the signals of winter temperature and precipitation change at 17 mountain station located above 1,000 m, as being considered the main triggering factors of large fluctuations in snow amount and duration in these mountains. Fewer snowfalls were recorded all over the Romanian Carpathians after the mid 80s and over large mountain areas (including the alpine ones) the frequency of positive temperature extremes became higher (e.g. winter heat waves). Late Fall snowfalls and snowpack onsets (mainly in mid elevation areas, located below 1,700 m) and particularly the shifts towards early Spring snowmelts (at all the sites) were statistically proved to explain the decline of snow cover duration across the Carpathians. However, the sensitivity of snow cover duration to recent winter warming is still blurred in the high elevation areas (above 2,000 m). The trends in winter climate variability observed in the Romanian Carpathians beyond 1,000 m altitude are fairly comparable to those estimated in other European mountain ranges from observational data (e.g. the Swiss Alps, the French Alps and the Tatra Mts.). In relation to the climate change signals derived from observational data provided by low density mountain meteorological network (of about 3.3 stations per km2 in the areas above 1,000 m), the paper analysis the spatial probability and evolution trends of snow line in each winter season across the Romanian Carpathians, based on Landsat satellite data (MSS, TM and ETM+), with sufficiently high spatial (30 to 60 m) and temporal resolutions (850 images), over the 1973-2011 period. The Landsat coverage was considered suitable enough to enable an objective

  10. 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

  11. 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.

  12. 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.

  13. CLPX-Ground: ISA Snow Depth Transects and Related Measurements, Version 2

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of snow depth data from nine study areas, within three larger-scale areas in northern Colorado (Fraser, North Park, and Rabbit Ears Meso-cell...

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

    Data.gov (United States)

    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...

  15. CryoSat-2 Sea Ice Freeboard, Thickness, and Snow Depth Quick Look, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — The NASA CryoSat-2 Sea Ice Freeboard, Thickness, and Snow Depth Quick Look product is an experimental sea ice thickness data set containing derived geophysical data...

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

    Data.gov (United States)

    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...

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

    Science.gov (United States)

    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.

  18. 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

  19. 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.

  20. Statistical modelling of the snow depth distribution in open alpine terrain

    Directory of Open Access Journals (Sweden)

    T. Grünewald

    2013-08-01

    Full Text Available The spatial distribution of alpine snow covers is characterised by large variability. Taking this variability into account is important for many tasks including hydrology, glaciology, ecology or natural hazards. Statistical modelling is frequently applied to assess the spatial variability of the snow cover. For this study, we assembled seven data sets of high-resolution snow-depth measurements from different mountain regions around the world. All data were obtained from airborne laser scanning near the time of maximum seasonal snow accumulation. Topographic parameters were used to model the snow depth distribution on the catchment-scale by applying multiple linear regressions. We found that by averaging out the substantial spatial heterogeneity at the metre scales, i.e. individual drifts and aggregating snow accumulation at the landscape or hydrological response unit scale (cell size 400 m, that 30 to 91% of the snow depth variability can be explained by models that are calibrated to local conditions at the single study areas. As all sites were sparsely vegetated, only a few topographic variables were included as explanatory variables, including elevation, slope, the deviation of the aspect from north (northing, and a wind sheltering parameter. In most cases, elevation, slope and northing are very good predictors of snow distribution. A comparison of the models showed that importance of parameters and their coefficients differed among the catchments. A "global" model, combining all the data from all areas investigated, could only explain 23% of the variability. It appears that local statistical models cannot be transferred to different regions. However, models developed on one peak snow season are good predictors for other peak snow seasons.

  1. Winter climate extremes and their role for priming SOM decomposition under the snow

    Science.gov (United States)

    Gavazov, Konstantin; Bahn, Michael

    2015-04-01

    The central research question of this project is how soil respiration and soil microbial community composition and activity of subalpine grasslands are affected by extreme winter climate events, such as mid-winter snowmelt and subsequent advanced growing season date. In the scope of this talk, focus will be laid on the assumptions that (1) reduced snow cover leads to intensive freeze-thaw cycles in the soil with larger amplitudes of microbial biomass, DOC and soil CO2 production and efflux over the course of winter, and shifts peak microbial activity to deeper soil layers with limited and recalcitrant substrate; (2) causes a shift in microbial community composition towards decreased fungal/bacterial ratios; and (3) results in a stronger incorporation of labile C in microbial biomass and more pronounced priming effects of soil organic matter turnover. Our findings indicate that snow removal, induces a strong and immediate negative effect on the physiology of soil microbes, impairing them in their capacity for turnover of SOM in the presence of labile substances (priming). This effect however is transient and soil microbes recover within the same winter. The reason for that is that snow removal did not produce any measurable (PLFA) changes in soil microbial community composition. The advanced start of the growing season, as a result of snow removal in mid-winter, granted the bacterial part of the microbial community more active in the uptake of labile substrates and the turnover of SOM than the fungal one. This finding is in line with the concept for a seasonal shift towards bacterial-dominated summer microbial community composition and could bring about implications for the plant-microbe competition for resources at the onset of the growing season.

  2. Influence of snow depth and surface flooding on light transmission through Antarctic pack ice

    Science.gov (United States)

    Arndt, Stefanie; Meiners, Klaus M.; Ricker, Robert; Krumpen, Thomas; Katlein, Christian; Nicolaus, Marcel

    2017-03-01

    Snow on sea ice alters the properties of the underlying ice cover as well as associated physical and biological processes at the interfaces between atmosphere, sea ice, and ocean. The Antarctic snow cover persists during most of the year and contributes significantly to the sea-ice mass due to the widespread surface flooding and related snow-ice formation. Snow also enhances the sea-ice surface reflectivity of incoming shortwave radiation and determines therefore the amount of light being reflected, absorbed, and transmitted to the upper ocean. Here, we present results of a case study of spectral solar radiation measurements under Antarctic pack ice with an instrumented Remotely Operated Vehicle in the Weddell Sea in 2013. In order to identify the key variables controlling the spatial distribution of the under-ice light regime, we exploit under-ice optical measurements in combination with simultaneous characterization of surface properties, such as sea-ice thickness and snow depth. Our results reveal that the distribution of flooded and nonflooded sea-ice areas dominates the spatial scales of under-ice light variability for areas smaller than 100 m-by-100 m. However, the heterogeneous and highly metamorphous snow on Antarctic pack ice obscures a direct correlation between the under-ice light field and snow depth. Compared to the Arctic, light levels under Antarctic pack ice are extremely low during spring (<0.1%). This is mostly a result of the distinctly different dominant sea ice and snow properties with seasonal snow cover (including strong surface melt and summer melt ponds) in the Arctic and a year-round snow cover and widespread surface flooding in the Southern Ocean.

  3. Winter stream temperature in the rain-on-snow zone of the Pacific Northwest: influences of hillslope runoff and transient snow cover

    Directory of Open Access Journals (Sweden)

    J. A. Leach

    2014-02-01

    Full Text Available Stream temperature dynamics during winter are less well studied than summer thermal regimes, but the winter season thermal regime can be critical for fish growth and development in coastal catchments. The winter thermal regimes of Pacific Northwest headwater streams, which provide vital winter habitat for salmonids and their food sources, may be particularly sensitive to changes in climate because they can remain ice-free throughout the year and are often located in rain-on-snow zones. This study examined winter stream temperature patterns and controls in small headwater catchments within the rain-on-snow zone at the Malcolm Knapp Research Forest, near Vancouver, British Columbia, Canada. Two hypotheses were addressed by this study: (1 winter stream temperatures are primarily controlled by advective fluxes associated with runoff processes and (2 stream temperatures should be depressed during rain-on-snow events, compared to rain-on-bare-ground events, due to the cooling effect of rain passing through the snowpack prior to infiltrating the soil or being delivered to the stream as saturation-excess overland flow. A reach-scale energy budget analysis of two winter seasons revealed that the advective energy input associated with hillslope runoff overwhelms vertical energy exchanges (net radiation, sensible and latent heat fluxes, bed heat conduction, and stream friction and hyporheic energy fluxes during rain and rain-on-snow events. Historical stream temperature data and modelled snowpack dynamics were used to explore the influence of transient snow cover on stream temperature over 13 winters. When snow was not present, daily stream temperature during winter rain events tended to increase with increasing air temperature. However, when snow was present, stream temperature was capped at about 5 °C, regardless of air temperature. The stream energy budget modelling and historical analysis support both of our hypotheses. A key implication is that

  4. A technigue exploitation about anti-slide tire polyploid on ice-snow road in winter

    Science.gov (United States)

    Xiaojie, Qi; Qiang, Wang; Zhao, Yang; Yunlong, Wang; Guotian, Wang; Degang, Lv

    2017-04-01

    Present studies focus on improving anti-slide property of tyes on ice-snow road by changing material modification of tyre tread and designing groove. However, the basic reason causing starting slide, long braking distance, turning slide slip and so on of tyres used in winter is that tyre tread materials are unitary and homogenous rubber composite which can’t coordinate driving demands of tyres in winter under muti-work condition, and can’t exert their best property when starting, braking and sliding slip. In order to improve comprehensive anti-slide property of tyres, this paper discusses about changing structure, shape and distribution proportion among haploid materials of tyre tread rubber. Polyploid bubber tyre tread technique based on artificial neural network which is in favor of starting, braking and anti-slide slip is optimized and combined. Friction feature and anti-slide mechanism on ice-snow road of polyploid rubber tyre tread are studied using testing technique of low-temperature cabin and computer simulation. A set high anti-slide theories and realizing method systems of polyploid rubber composite formed from basic theory, models and technique method are developped which will be applied into solving anti-slide problem of winter tyres, provide theory instruction for studies on high anti-slide winter tyres, and promote development of application and usage safety of winter tyres.

  5. 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...

  6. Snow cover detection and snow depth algorithms for the Global Change Observation Mission (GCOM) AMSR2 instrument using AMSR-E/AMSR2 measurements

    Science.gov (United States)

    Lee, Y. K.; Kongoli, C.; Key, J. R.

    2014-12-01

    Snow is one of the most dynamic hydrological variables on the Earth surface playing a key role in the global energy and water budget. The ability to detect global snow cover and measure snow depth in near all weather conditions has been demonstrated with satellite microwave measurements. The Advanced Microwave Scanning Radiometer 2 (AMSR2), launched on May 18, 2012 onboard SHIZUKU, is included in A-train group of satellites and will replace the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) instrument. The similarity of channels between AMSR-E and AMSR2 makes AMSR2 instrument a successor of AMSR-E instrument. This study will evaluate the suite of AMSR2 algorithms that are being developed for the operational retrieval of snow cover detection and snow depth using AMSR-E and AMSR2 data. AMSR-E data spans 10 years from June 2002 to September 2011; AMSR2 data spans 2 years from August 2012 to May 2014. The snow cover detection algorithm is based on the operational NOAA's heritage microwave algorithm with snow climatology tests and wet snow filtering as new enhancements. The SD algorithm is adopted from the current version of the operational NASA AMSR-E SWE algorithm. The 24- and 4-km IMS snow cover and in-situ SYNOP and COOP snow depth are used as references for the evaluation. More details about the reference data and evaluation results will be discussed.

  7. 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

  8. Wet and full-depth glide snow avalanche onset monitoring and detection with ground based Ku-band radar

    Science.gov (United States)

    Lucas, Célia; Bühler, Yves; Leinss, Silvan; Hajnsek, Irena

    2017-04-01

    Wet and full-depth glide snow avalanches can be of considerable danger for people and infrastructure in alpine regions. In Switzerland avalanche hazard predictions are performed by the Institute for Snow and Avalanche Research SLF. However these predictions are issued on regional scale and do not yield information about the current status of particular slopes of interest. To investigate the potential of radar technology for avalanche prediction on the slope scale, we performed the following experiment. During the winter seasons 2015/2016 and 2016/2017, a ground-based Ku-band radar was placed in the vicinity of Davos (GR) in order to monitor the Dorfberg slope with 4-minute measurement intervals [1]. With Differential Interferometry [2] line of sight movements on the order of a fraction of the radar wavelength (1.7 cm) can be measured. Applying this technique to the Dorfberg scenario, it was possible to detect snowpack displacement of up to 0.4 m over 3 days in the avalanche release area prior to a snow avalanche event. A proof of concept of this approach was previously made by [3-5]. The analysis of the snowpack displacement history of such release areas shows that an avalanche is generally released after several cycles of acceleration and deceleration of a specific area of the snowpack, followed by an abrupt termination of the movement at the moment of the avalanche release. The acceleration and deceleration trends are related to thawing and refreezing of the snowpack induced by the daily temperature variations. The proposed method for the detection of snowpack displacements as indication for potential wet and full-depth glide snow avalanches is a promising tool to increase avalanche safety on specific slopes putting infrastructure or people at risk. The identification of a singular signature to discriminate the time window immediately prior to the release is still under investigation, but the ability to monitor snowpack displacement allows for mapping of zones

  9. Novel Snow Depth Retrieval Method Using Time Series Ssmi Passive Microwave Imagery

    Science.gov (United States)

    Nikraftar, Z.; Hasanlou, M.; Esmaeilzadeh, M.

    2016-06-01

    The Special Sensor Microwave Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSM/IS) are satellites that work in passive microwave range. The SSM/I has capability to measure geophysical parameters which these parameters are key to investigate the climate and hydrology condition in the world. In this research the SSMI passive microwave data is used to study the feasibility of monitoring snow depth during snowfall month from 2010 to 2015 using an algorithm in conjunction with ground depth measured at meteorological stations of the National Centre for Environmental Information (NCEI). The previous procedures for snow depth retrieval algorithms uses only one or two passive bands for modelling snow depth. This study enable us to use of a nonlinear multidimensional regression algorithm which incorporates all channels and their related weighting coefficients for each band. Higher value of these coefficients are indicator of the importance of each band in the regression model. All channels and their combination were used in support of the vector algorithm combined with genetic algorithm (GA) for feature selection to estimate snow depth. The results were compared with those algorithms developed by recent researchers and the results clearly shows the superiority of proposed method (R2 = 0.82 and RMSE = 6.3 cm).

  10. NOVEL SNOW DEPTH RETRIEVAL METHOD USING TIME SERIES SSMI PASSIVE MICROWAVE IMAGERY

    Directory of Open Access Journals (Sweden)

    Z. Nikraftar

    2016-06-01

    Full Text Available The Special Sensor Microwave Imager (SSM/I and the Special Sensor Microwave Imager Sounder (SSM/IS are satellites that work in passive microwave range. The SSM/I has capability to measure geophysical parameters which these parameters are key to investigate the climate and hydrology condition in the world. In this research the SSMI passive microwave data is used to study the feasibility of monitoring snow depth during snowfall month from 2010 to 2015 using an algorithm in conjunction with ground depth measured at meteorological stations of the National Centre for Environmental Information (NCEI. The previous procedures for snow depth retrieval algorithms uses only one or two passive bands for modelling snow depth. This study enable us to use of a nonlinear multidimensional regression algorithm which incorporates all channels and their related weighting coefficients for each band. Higher value of these coefficients are indicator of the importance of each band in the regression model. All channels and their combination were used in support of the vector algorithm combined with genetic algorithm (GA for feature selection to estimate snow depth. The results were compared with those algorithms developed by recent researchers and the results clearly shows the superiority of proposed method (R2 = 0.82 and RMSE = 6.3 cm.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    K. Förster

    2018-02-01

    Full Text Available 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.

  13. Design and development of a wireless sensor network to monitor snow depth in multiple catchments in the American River basin, California: hardware selection and sensor placement techniques

    Science.gov (United States)

    Kerkez, B.; Rice, R.; Glaser, S. D.; Bales, R. C.; Saksa, P. C.

    2010-12-01

    A 100-node wireless sensor network (WSN) was designed for the purpose of monitoring snow depth in two watersheds, spanning 3 km2 in the American River basin, in the central Sierra Nevada of California. The network will be deployed as a prototype project that will become a core element of a larger water information system for the Sierra Nevada. The site conditions range from mid-elevation forested areas to sub-alpine terrain with light forest cover. Extreme temperature and humidity fluctuations, along with heavy rain and snowfall events, create particularly challenging conditions for wireless communications. We show how statistics gathered from a previously deployed 60-node WSN, located in the Southern Sierra Critical Zone Observatory, were used to inform design. We adapted robust network hardware, manufactured by Dust Networks for highly demanding industrial monitoring, and added linear amplifiers to the radios to improve transmission distances. We also designed a custom data-logging board to interface the WSN hardware with snow-depth sensors. Due to the large distance between sensing locations, and complexity of terrain, we analyzed network statistics to select the location of repeater nodes, to create a redundant and reliable mesh. This optimized network topology will maximize transmission distances, while ensuring power-efficient network operations throughout harsh winter conditions. At least 30 of the 100 nodes will actively sense snow depth, while the remainder will act as sensor-ready repeaters in the mesh. Data from a previously conducted snow survey was used to create a Gaussian Process model of snow depth; variance estimates produced by this model were used to suggest near-optimal locations for snow-depth sensors to measure the variability across a 1 km2 grid. We compare the locations selected by the sensor placement algorithm to those made through expert opinion, and offer explanations for differences resulting from each approach.

  14. 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.)

  15. Pre-ABoVE: Vegetation, NDVI, Snow and Thaw Depths, in North Slope, Alaska and NWT, CA

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset includes vegetation cover maps, Normalized Difference Vegetation Index (NDVI) maps, snow depth and thaw depth data that were obtained as part of a...

  16. 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...

  17. 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...

  18. 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.

  19. 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

  20. Some relationships among air, snow, and soil temperatures and soil frost

    Science.gov (United States)

    George Hart; Howard W. Lull

    1963-01-01

    Each winter gives examples of the insulating properties of snow cover. Seeds and soil fauna are protected from the cold by snow. Underground water pipes are less likely to freeze under snow cover. And, according to many observers, the occurrence, penetration, and thaw of soil frost are affected by snow cover. The depth of snow necessary to protect soil from freezing...

  1. 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

  2. Differential ecophysiological response of deciduous shrubs and a graminoid to long-term experimental snow reductions and additions in moist acidic tundra, northern Alaska

    Science.gov (United States)

    Robert R. Pattison; Jeffrey M. Welker

    2014-01-01

    Changes in winter precipitation that include both decreases and increases in winter snow are underway across the Arctic. In this study, we used a 14-year experiment that has increased and decreased winter snow in the moist acidic tussock tundra of northern Alaska to understand impacts of variation in winter snow depth on summer leaf-level ecophysiology of two deciduous...

  3. Lessons learned from the snow emergency management of winter season 2008-2009 in Piemonte

    Science.gov (United States)

    Bovo, Dr.; Pelosini, Dr.; Cordola, Dr.

    2009-09-01

    The winter season 2008-2009 has been characterized by heavy snowfalls over the whole Piemonte, in the Western Alps region. The snowfalls have been exceptional because of their earliness, persistence and intensity. The impact on the regional environment and territory has been relevant, also from the economical point of view, as well as the effort of the people involved in the forecasting, prevention and fighting actions. The environmental induced effects have been shown until late spring. The main critical situations have been arisen from the snowfalls earliness in season, the several snow precipitation events over the plains, the big amount of snow accumulation on the ground, as well as the anomaly with respect to the last 30 years climatic trend of snow conditions in Piemonte. The damage costs to the public property caused by the snowfalls have been estimated by the Regione Piemonte to be 470 million euros, giving evidence of the real emergency dimension of the event, never occurred during the last 20 years. The technical support from the Regional Agency for Environmental Protection of Regione Piemonte (Arpa Piemonte) to the emergency management allowed to analyse and highlight the direct and induced effects of the heavy snowfalls, outlining risk scenarios characterized by different space and time scales. The risk scenarios deployment provided a prompt recommendation list, both for the emergency management and for the natural phenomena evolution surveillance planning to assure the people and property safety. The risk scenarios related to the snow emergency are different according to the geographical and anthropic territory aspects. In the mountains, several natural avalanche releases, characterized frequently by a large size, may affect villages, but they may also interrupt the main and secondary roads both down in the valleys and small villages road access, requiring a long time for the complete and safe snow removal and road re-opening. The avalanches often

  4. 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

  5. Evaluation of forest snow processes models (SnowMKIP2)

    Science.gov (United States)

    Nick Rutter; Richard Essery; John Pomeroy; Nuria Altimir; Kostas Andreadis; Ian Baker; Alan Barr; Paul Bartlett; Aaron Boone; Huiping Deng; Herve Douville; Emanuel Dutra; Kelly Elder; others

    2009-01-01

    Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation...

  6. 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

    ; 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......Changing climate is expected to alter precipitation patterns in the Arctic, with consequences for subsurface temperature and moisture conditions, community structure, and nutrient mobilization through microbial belowground processes. Here, we address the effect of increased snow depth...... 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...

  7. Boreal Forest Permafrost Sensitivity Ecotypes to changes in Snow Depth and Soil Moisture

    Science.gov (United States)

    Dabbs, A.; Romanovsky, V. E.; Kholodov, A. L.

    2017-12-01

    Changes in the global climate, pronounced especially in polar regions due to their accelerated warming, are expected by many global climate models to have large impacts on the moisture budget throughout the world. Permafrost extent and the soil temperature regime are both strongly dependent on soil moisture and snow depth because of their immense effects on the thermal properties of the soil column and surface energy balance respectively. To assess how the ground thermal regime at various ecotypes may react to a change in the moisture budget, we performed a sensitivity analysis using the Geophysical Institute Permafrost Laboratory model, which simulates subsurface temperature dynamics by solving a one-dimensional nonlinear heat equation with phase change. We used snow depth and air temperature data from the Fairbanks International Airport meteorological station as forcing for this sensitivity analysis. We looked at five different ecotypes within the boreal forest region of Alaska: mixed, deciduous and black forests, willow shrubs and tundra. As a result of this analysis, we found that ecotypes with higher soil moisture contents, such as willow shrubs, are most sensitive to changes in snow depth due to the larger amount of latent heat trapped underneath the snow during the freeze up of active layer. In addition, soil within these ecotypes has higher thermal conductivity due to high saturation degree allowing for deeper seasonal freezing. Also, we found that permafrost temperatures were most sensitive to changes in soil moisture in ecotypes that were not completely saturated such as boreal forest. These ecotypes lacked complete saturation because of thick organic layers that have very high porosities or partially drained mineral soils. Contrarily, tundra had very little response to changes in soil moisture due to its thin organic layer and almost completely saturated soil column. This difference arises due to the disparity between the frozen and unfrozen thermal

  8. 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

    -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......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...

  9. 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).

  10. Recharge of an Unconfined Pumice Aquifer: Winter Rainfall Versus Snow Pack, South-central Oregon

    Science.gov (United States)

    Cummings, M. L.; Weatherford, J. M.; Eibert, D.

    2015-12-01

    Walker Rim study area, an uplifted fault block east of the Cascade Range, south-central Oregon, exceeds 1580 m elevation and includes Round Meadow-Sellers Marsh closed basin, and headwaters of Upper Klamath Basin, Deschutes Basin, and Christmas Lake Valley in the Great Basin. The water-bearing unit is 2.8 to 3.0 m thick Plinian pumice fall from the Holocene eruption of Mount Mazama, Cascade Range. The perched pumice aquifer is underlain by low permeability regolith and bedrock. Disruption of the internal continuity of the Plinian pumice fall by fluvial and lacustrine processes resulted in hydrogeologic environments that include fens, wet meadows, and areas of shallow water table. Slopes are low and surface and groundwater pathways follow patterns inherited from the pre-eruption landscape. Discharge for streams and springs and depth to water table measured in open-ended piezometers slotted in the pumice aquifer have been measured between March and October, WY 2011 through WY2015. Yearly occupation on same date has been conducted for middle April, June 1st, and end of October. WY2011 and WY2012 received more precipitation than the 30 year average while WY2014 was the third driest year in 30 years of record. WY2014 and WY2015 provide an interesting contrast. Drought conditions dominated WY2014 while WY2015 was distinct in that the normal cold-season snow pack was replaced by rainfall. Cumulative precipitation exceeded the 30-year average between October and March. The pumice aquifer of wet meadows and areas of shallow water table experienced little recharge in WY2015. Persistence of widespread diffuse discharge from fens declined by middle summer as potentiometric surfaces lowered into confining peat layers or in some settings into the pumice aquifer. Recharge of the perched pumice aquifer in rain-dominated WY2015 was similar to or less than in the snow-dominated drought of WY2014. Rain falling on frozen ground drove runoff rather than aquifer recharge.

  11. 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.

  12. Comparison of snow depth retrieval algorithm in Northeastern China based on AMSR2 and FY3B-MWRI data

    Science.gov (United States)

    Fan, Xintong; Gu, Lingjia; Ren, Ruizhi; Zhou, Tingting

    2017-09-01

    Snow accumulation has a very important influence on the natural environment and human activities. Meanwhile, improving the estimation accuracy of passive microwave snow depth (SD) retrieval is a hotspot currently. Northeastern China is a typical snow study area including many different land cover types, such as forest, grassland and farmland. Especially, there is relatively stable snow accumulation in January every year. The brightness temperatures which are observed by the Advanced Microwave Scanning Radiometer 2 (AMSR2) on GCOM-W1 and FengYun3B Microwave Radiation Imager (FY3B-MWRI) in the same period in 2013 are selected as the study data in the research. The results of snow depth retrieval using AMSR2 standard algorithm and Jiang's FY operational algorithm are compared in the research. Moreover, to validate the accuracy of the two algorithms, the retrieval results are compared with the SD data observed at the national meteorological stations in Northeastern China. Furthermore, the retrieval SD is also compared with AMSR2 and FY standard SD products, respectively. The root mean square errors (RMSE) results using AMSR2 standard algorithms and FY operational algorithm are close in the forest surface, which are 6.33cm and 6.28cm, respectively. However, The FY operational algorithm shows a better result than the AMSR2 standard algorithms in the grassland and farmland surface. The RMSE results using FY operational algorithm in the grassland and farmland surface are 2.44cm and 6.13cm, respectively.

  13. Intercomparison of snow depth retrievals over Arctic sea ice from radar data acquired by Operation IceBridge

    Science.gov (United States)

    Kwok, Ron; Kurtz, Nathan T.; Brucker, Ludovic; Ivanoff, Alvaro; Newman, Thomas; Farrell, Sinead L.; King, Joshua; Howell, Stephen; Webster, Melinda A.; Paden, John; Leuschen, Carl; MacGregor, Joseph A.; Richter-Menge, Jacqueline; Harbeck, Jeremy; Tschudi, Mark

    2017-11-01

    Since 2009, the ultra-wideband snow radar on Operation IceBridge (OIB; a NASA airborne mission to survey the polar ice covers) has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Progressive improvements in radar hardware and data processing methodologies have led to improved data quality for subsequent retrieval of snow depth. Existing retrieval algorithms differ in the way the air-snow (a-s) and snow-ice (s-i) interfaces are detected and localized in the radar returns and in how the system limitations are addressed (e.g., noise, resolution). In 2014, the Snow Thickness On Sea Ice Working Group (STOSIWG) was formed and tasked with investigating how radar data quality affects snow depth retrievals and how retrievals from the various algorithms differ. The goal is to understand the limitations of the estimates and to produce a well-documented, long-term record that can be used for understanding broader changes in the Arctic climate system. Here, we assess five retrieval algorithms by comparisons with field measurements from two ground-based campaigns, including the BRomine, Ozone, and Mercury EXperiment (BROMEX) at Barrow, Alaska; a field program by Environment and Climate Change Canada at Eureka, Nunavut; and available climatology and snowfall from ERA-Interim reanalysis. The aim is to examine available algorithms and to use the assessment results to inform the development of future approaches. We present results from these assessments and highlight key considerations for the production of a long-term, calibrated geophysical record of springtime snow thickness over Arctic sea ice.

  14. 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

  15. Optimizing Observations of Sea Ice Thickness and Snow Depth in the Arctic

    Science.gov (United States)

    2015-09-30

    high proportion of multi-year ice (MYI), such as north of Greenland and Ellesmere Island. Over much of the Beaufort Sea, Canada Basin and central ...2015), Perspectives: Remote Sensing of Snow on Sea Ice, Snow on Sea Ice Processes Workshop, National Center for Atmospheric Research – Mesa Lab

  16. Inter-calibrating SMMR, SSM/I and SSMI/S to improve the consistency of snow depth data products in China

    Science.gov (United States)

    DAI, Liyun; Che, Tao

    2015-04-01

    The long time series of passive microwave snow depth/snow water equivalent (SWE) products were the fundamental data for climate and hydrological researches. However, the temporal continuity of the products was influenced by the update or supersede of passive microwave sensors or platforms. In this study, we inter-calibrated the brightness temperatures from Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMI/S), and evaluated the consistency of snow cover area (SCA) and snow depth derived from the Scanning Multichannel Microwave Radiometer (SMMR), SSM/I and SSMI/S. The results presented that the spatial pattern of SCA derived from SMMR and SSM/I showed more consistent after calibration than before calibration; the relative bias of SCA and snow depth in China between SSM/I and SSMI/S declined from 42.42% to 1.65% and from 66.18% to -1.5%, respectively; the SCA and snow depth derived from SSM/I carried on F08, F11 and F13 presented high consistency. In a word, to obtain consistent snow depth and SCA remote sensing products, the inter-sensor calibrations between SMMR and SSM/I, SSM/I and SSMI/S are important, while the SCA and snow depth derived from SSM/I sensors carried on F08, F11 and F13 presented no significant differences.

  17. The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise

    DEFF Research Database (Denmark)

    Kern, S.; Khvorostovsky, K.; Skourup, H.

    2015-01-01

    sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer (AMSR-E) and the Warren climatology (Warren et al., 1999). We compare the different data sets in spatiotemporal scales where satellite radar altimetry yields meaningful results. An inter-comparison of the snow...

  18. Inter-Calibrating SMMR, SSM/I and SSMI/S Data to Improve the Consistency of Snow-Depth Products in China

    Directory of Open Access Journals (Sweden)

    Liyun Dai

    2015-06-01

    Full Text Available Long-term snow depth/snow water equivalent (SWE products derived from passive microwave remote sensing data are fundamental for climatological and hydrological studies. However, the temporal continuity of the products is affected by the updating or replacement of passive microwave sensors or satellite platforms. In this study, we inter-calibrated brightness temperature (Tb data obtained from the Special Sensor Microwave Imager (SSM/I and the Special Sensor Microwave Imager/Sounder (SSMI/S. Then, we evaluated the consistency of the snow cover area (SCA and snow depth derived from the Scanning Multichannel Microwave Radiometer (SMMR, SSM/I and SSMI/S. The results indicated that (1 the spatial pattern of the SCA derived from the SMMR and SSM/I data was more consistent after calibration than before; (2 the relative biases in the SCA and snow depth in China between the SSM/I and SSMI/S data decreased from 42.42% to 1.65% and from 66.18% to −1.5%, respectively; and (3 the SCA and snow depth derived from the SSM/I data carried on F08, F11 and F13 were highly consistent. To obtain consistent snow depth and SCA products, inter-sensor calibrations between SMMR, SSM/I and SSMI/S are important. In consideration of the snow data product continuation, we suggest that the brightness temperature data from all sensors be calibrated based on SSMI/S.

  19. AFSC/RACE/GAP/Nichol: Archival tag depth and temperature data from snow crab

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Seasonal migration of commercial-size (=102 mm carapace width [CW]), morphometrically mature (MM) snow crabs (Chionoecetes opilio) from the eastern Bering Sea was...

  20. 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.

  1. Snow cover - characteristics and trends for the meteorological mountain stations in Romania

    Science.gov (United States)

    Manea, A.; Ralita, I.; Dumitrescu, Al.; Boroneant, C.

    2009-04-01

    Snow cover represents an important climatological parameter for the specialized analysis because it can provide useful information regarding the climatological evolution of one region, taking into account the variability of the climate. The latest years brought milder winters for Romania. The number of days with snow cover and the depth of snow cover are very important factors for the mountain tourism and the winter sports. This paper presents the trends of the number of days with snow cover and the snow depth over the 1961-2007 period for 18 mountain meteorological stations in Romania. In this case, "mountain station" refers to a station located at an altitude higher than 1000 m.

  2. 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

  3. Assessment of the Performance of Several Roadway Mixes under Rain, Snow, and Winter Maintenance Activities

    OpenAIRE

    Flintsch, Gerardo W.

    2004-01-01

    The purpose of this study was to assess the relative functional performance, including skid resistance and splash and spray, of five hot-mix-asphalt (HMA) surfaces and a tinned portland cement concrete highway surface during controlled wet and wintry weather events. The study compared the way that these surfaces respond to various deicing and anti-icing snow removal and ice control techniques under artificial wintry conditions. In addition, the splash and spray characteristics of the surfaces...

  4. 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.

  5. Partial least regression approach to forecast the East Asian winter monsoon using Eurasian snow cover and sea surface temperature

    Science.gov (United States)

    Yu, Lulu; Wu, Zhiwei; Zhang, Renhe; Yang, Xin

    2017-06-01

    Seasonal prediction of the East Asian (EA) winter monsoon (EAWM) is of great significance yet a challenging issue. In this study, three statistical seasonal prediction models for the EAWM are established using three leading modes of the Eurasian snow cover (ESC), the first leading mode of sea surface temperature (SST) and the four leading modes of the combination of the ESC and SST in preceding autumn, respectively. These leading modes are identified by the partial-least square (PLS) regression. The first PLS (PLS1) mode for the ESC features significantly anomalous snow cover in Siberia and Tibetan Plateau regions. The ESC second PLS (PLS2) mode corresponds to large areas of snow cover anomalies in the central Siberia, whereas the third PLS (PLS3) mode a meridional seesaw pattern of ESC. The SST PLS1 mode basically exhibits an El Niño-Southern Oscillation developing phase in equatorial eastern Pacific and significant SST anomalies in North Atlantic. A strong EAWM tends to emerge in a La Niña year concurrent with cold SST anomalies in the North Atlantic, and vice versa. After a 35-year training period (1967-2001), three PLS seasonal prediction models are constructed and the 11-year hindcast is performed for the period of 2002-2012, respectively. The PLS model based on combination of the autumn ESC and SST exhibits the best hindcast skill among the three models, its correlation coefficient between the observation and the hindcast reaching 0.86. This indicates that this physical-based PLS model may provide another practical tool for the EAWM. In addition, the relative contribution of the ESC and SST is also examined by assessing the hindcast skills of the other two PLS models constructed solely by the ESC or SST. Possible physical mechanisms are also discussed.

  6. Joint DEnKF-albedo assimilation scheme that considers the common land model subgrid heterogeneity and a snow density-based observation operator for improving snow depth simulations

    Science.gov (United States)

    Xu, Jianhui; Zhang, Feifei; Zhao, Yi; Shu, Hong; Zhong, Kaiwen

    2016-07-01

    For the large-area snow depth (SD) data sets with high spatial resolution in the Altay region of Northern Xinjiang, China, we present a deterministic ensemble Kalman filter (DEnKF)-albedo assimilation scheme that considers the common land model (CoLM) subgrid heterogeneity. In the albedo assimilation of DEnKF-albedo, the assimilated albedos over each subgrid tile are estimated with the MCD43C1 bidirectional reflectance distribution function (BRDF) parameters product and CoLM calculated solar zenith angle. The BRDF parameters are hypothesized to be consistent over all subgrid tiles within a specified grid. In the SCF assimilation of DEnKF-albedo, a DEnKF combining a snow density-based observation operator considers the effects of the CoLM subgrid heterogeneity and is employed to assimilate MODIS SCF to update SD states over all subgrid tiles. The MODIS SCF over a grid is compared with the area-weighted sum of model predicted SCF over all the subgrid tiles within the grid. The results are validated with in situ SD measurements and AMSR-E product. Compared with the simulations, the DEnKF-albedo scheme can reduce errors of SD simulations and accurately simulate the seasonal variability of SD. Furthermore, it can improve simulations of SD spatiotemporal distribution in the Altay region, which is more accurate and shows more detail than the AMSR-E product.

  7. Inter-calibrating SMMR, SSM/I and SSMI/S data to improve the consistency of snow-depth products in China

    Science.gov (United States)

    Dai, L.

    2015-12-01

    Long-term snow depth/snow water equivalent (SWE) products derived from passive microwave remote sensing data are fundamental for climatological and hydrological studies. However, the temporal continuity of the products is affected by the updating or replacement of passive microwave sensors or satellite platforms. In this study, we inter-calibrated brightness temperature (Tb) data obtained from the Special Sensor Microwave Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMI/S). Then, we evaluated the consistency of the snow cover area (SCA) and snow depth derived from the Scanning Multichannel Microwave Radiometer (SMMR), SSM/I and SSMI/S. The results indicated that (1) the spatial pattern of the SCA derived from the SMMR and SSM/I data was more consistent after calibration than before; (2) the relative biases in the SCA and snow depth in China between the SSM/I and SSMI/S data decreased from 42.42% to 1.65% and from 66.18% to -1.5%, respectively; and (3) the SCA and snow depth derived from the SSM/I data carried on F08, F11 and F13 were highly consistent. The relative bias of SCA and snow depth between F08 and F11 were -5.8% and -3.73%, respectively, and they are 3.31% and 1.85% between F13 and F11. To obtain consistent snow depth and SCA products, inter-sensor calibrations between SMMR, SSM/I and SSMI/S are important. In consideration of the snow data product continuation, we suggest that the brightness temperature data from all sensors be calibrated based on SSMI/S.

  8. Aerosol optical depth retrieval in the Arctic region using MODIS data over snow

    NARCIS (Netherlands)

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

    2013-01-01

    The Arctic is vulnerable to the long-term transport of aerosols because they affect the surface albedo when particles are deposited on snow and ice. However, aerosol observations for this area are sparse and hence there is considerable uncertainty in the knowledge on the properties of the Arctic

  9. 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.

  10. Retrieval of the ultraviolet effective snow albedo during 1998 winter campaign in the French Alps.

    Science.gov (United States)

    Smolskaia, Irina; Masserot, Dominique; Lenoble, Jacqueline; Brogniez, Colette; de la Casinière, Alain

    2003-03-20

    A measurement campaign was carried out in February 1998 at Briançon Station, French Alps (44.9 degrees N, 6.65 degrees E, 1,310 m above sea level) in order to determine the UV effective snow albedo that was retrieved for both erythemal and UV-A irradiances from measurements and modeling enhancement factors. The results are presented for 15 cloudless days with very variable snow cover and a small snowfall in the middle of the campaign. Erythemal irradiance enhancement due to the surface albedo was found to decrease from approximately +15% to +5% with a jump to +22% after the snowfall, whereas UV-A irradiance enhancement decreased from 7% to 5% and increased to 15% after the snowfall. Thesevalues fit to effective surface albedos of 0.4, 0.1, and 0.5 for erythemal, and to effective albedos of 0.25, 0.1, and 0.4 for UV-A irradiances, respectively. An unexpected difference between the effective albedos retrieved in the two wavelength regions can be explained by the difference of the environment contribution.

  11. Study on Assessment Model of Classification for Snow Disasters in Tibet Plateau

    Science.gov (United States)

    Jia, L., Sr.; Xiao, T.; Wang, C.; Du, J.; Chen, D.; Zhou, Z.

    2017-12-01

    Based on Tibetan Plateau snow observation data from 39 meteorological stations during 1979-2013, we found 4 indexes for assessment model, as snow depth, the max snow depth, snow cover areas and snow duration respectively. The recurrence period of snow disasters and event distance function were calculated by normal probability density function. And the assessment model classification for snow disasters was also studied. The main contents of this research are summarized as follows: (1) The assessment model of classification for Snow Disasters was build. The snow depth, the max snow depth, snow cover areas and snow duration were selected as indexes for model, and the standard of Classification was found. The four indexes form the evaluation vector, thus euclidean distance was calculated to classify the snow disasters form the first to fifth class snow disaster. (2) The assessment of snow disasters was studied. In 370 cases of heavy snowfall in four seasons, the first class snow disaster occurred 257 times, and 69.46% of the whole cases. The second to fourth class snow disaster occurred 22.44%, 4.05% respectively. The probability of snow disaster is highest in spring, and the probability is similar in autumn and winter. (3) The average of snow depth in the fourth class snow disaster was 2.56cm, the max of snow depth is 7.45cm, the snow cover areas is 0.17 and snow duration is 57.2d. There are 4, 7, 4 times of the fourth class snow disaster in 1980s, 1990s, 2000s respectively, and 9 times occurred in winter. In December 1981, there was the fourth class snow disaster lasted for three months. During 2006-2013, up to the third class snow disaster were occurred every year, and the fourth class snow disaster occurred 4 times. In 21st century, although the times of the class snow disaster was descend, but it still has hugely damages at plateau areas. Key words: Snow Disasters; Tibet plateau; Classification; Assessment Model Acknowledgements: This study was supported by

  12. Improving Surface Mass Balance Over Ice Sheets and Snow Depth on Sea Ice

    Science.gov (United States)

    Koenig, Lora Suzanne; Box, Jason; Kurtz, Nathan

    2013-01-01

    Surface mass balance (SMB) over ice sheets and snow on sea ice (SOSI) are important components of the cryosphere. Large knowledge gaps remain in scientists' abilities to monitor SMB and SOSI, including insufficient measurements and difficulties with satellite retrievals. On ice sheets, snow accumulation is the sole mass gain to SMB, and meltwater runoff can be the dominant single loss factor in extremely warm years such as 2012. SOSI affects the growth and melt cycle of the Earth's polar sea ice cover. The summer of 2012 saw the largest satellite-recorded melt area over the Greenland ice sheet and the smallest satellite-recorded Arctic sea ice extent, making this meeting both timely and relevant.

  13. 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.

  14. 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

  15. COMPARISON OF DIGITAL SURFACE MODELS FOR SNOW DEPTH MAPPING WITH UAV AND AERIAL CAMERAS

    Directory of Open Access Journals (Sweden)

    R. Boesch

    2016-06-01

    Full Text Available Photogrammetric workflows for aerial images have improved over the last years in a typically black-box fashion. Most parameters for building dense point cloud are either excessive or not explained and often the progress between software releases is poorly documented. On the other hand, development of better camera sensors and positional accuracy of image acquisition is significant by comparing product specifications. This study shows, that hardware evolutions over the last years have a much stronger impact on height measurements than photogrammetric software releases. Snow height measurements with airborne sensors like the ADS100 and UAV-based DSLR cameras can achieve accuracies close to GSD * 2 in comparison with ground-based GNSS reference measurements. Using a custom notch filter on the UAV camera sensor during image acquisition does not yield better height accuracies. UAV based digital surface models are very robust. Different workflow parameter variations for ADS100 and UAV camera workflows seem to have only random effects.

  16. Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

    Science.gov (United States)

    Molthan, Andrew; Haynes, John M.; Jedlovec, Gary J.; Lapenta, William M.

    2009-01-01

    Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud

  17. Snow Depth Estimation Using Time Series Passive Microwave Imagery via Genetically Support Vector Regression (case Study Urmia Lake Basin)

    Science.gov (United States)

    Zahir, N.; Mahdi, H.

    2015-12-01

    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.

  18. 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.

  19. 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

  20. CO2 snow depth and subsurface water-ice abundance in the northern hemisphere of Mars.

    Science.gov (United States)

    Mitrofanov, I G; Zuber, M T; Litvak, M L; Boynton, W V; Smith, D E; Drake, D; Hamara, D; Kozyrev, A S; Sanin, A B; Shinohara, C; Saunders, R S; Tretyakov, V

    2003-06-27

    Observations of seasonal variations of neutron flux from the high-energy neutron detector (HEND) on Mars Odyssey combined with direct measurements of the thickness of condensed carbon dioxide by the Mars Orbiter Laser Altimeter (MOLA) on Mars Global Surveyor show a latitudinal dependence of northern winter deposition of carbon dioxide. The observations are also consistent with a shallow substrate consisting of a layer with water ice overlain by a layer of drier soil. The lower ice-rich layer contains between 50 and 75 weight % water, indicating that the shallow subsurface at northern polar latitudes on Mars is even more water rich than that in the south.

  1. How Well Are We Measuring Snow? The NOAA/FAA/NCAR Winter Precipitation Test Bed

    Science.gov (United States)

    Baker, B.; Rasmussen, R.; Kochendorfer, J.; Meyers, T.; Nitu, R.; Paul, J.; Smith, C.; Yang, D.

    2012-04-01

    Precipitation is one of the most important atmospheric variables for ecosystems, hydrologic systems, climate, and weather forecasting. Despite its importance, accurate measurement remains challenging, and the lack of recent and complete inter-comparisons leads researchers to discount the importance and severity of measurement errors. These errors are exacerbated for the automated measurement of solid precipitation and underestimates of 20-50% are common. While solid precipitation measurements have been the subject of many studies, there have been only a limited number of coordinated assessments on the accuracy, reliability, and repeatability of automatic precipitation measurements. The most recent comprehensive study, the "WMO Solid Precipitation Measurement Inter-comparison" focused on manual techniques of solid precipitation measurement. Precipitation gauge technology has changed considerably in the last 12 years and the focus has shifted to automated techniques. Given the strong need for automated solid precipitation data from both the climate and weather communities, and the widely varying catch efficiencies of the various instruments, inter-comparison studies are needed. The World Meteorological Organization Committee on Meteorological Instruments and Observations (WMO-CIMO) is organizing a Solid Precipitation Inter-comparison Experiment (WMO-SPICE) focused on automatic precipitation gauges and their configurations, in various climate conditions, building on the significant efforts currently underway in many countries. The inter-comparison will aim at understanding and improving our ability to reliably measure solid precipitation using automatic gauges. The study will take place starting in 2012 at sites around the world including the US, Norway, China, Canada, Japan, Switzerland, Russia, Finland and New Zealand. The NOAA /FAA/NCAR precipitation test bed in Marshall, CO. in partnership with Environment Canada will collect data during the winter of 2011/2012 to

  2. Dominance of grain size impacts on seasonal snow albedo at open sites in New Hampshire

    Science.gov (United States)

    Adolph, Alden C.; Albert, Mary R.; Lazarcik, James; Dibb, Jack E.; Amante, Jacqueline M.; Price, Andrea

    2017-01-01

    Snow cover serves as a major control on the surface energy budget in temperate regions due to its high reflectivity compared to underlying surfaces. Winter in the northeastern United States has changed over the last several decades, resulting in shallower snowpacks, fewer days of snow cover, and increasing precipitation falling as rain in the winter. As these climatic changes occur, it is imperative that we understand current controls on the evolution of seasonal snow albedo in the region. Over three winter seasons between 2013 and 2015, snow characterization measurements were made at three open sites across New Hampshire. These near-daily measurements include spectral albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density, black carbon content, local meteorological parameters, and analysis of storm trajectories using the Hybrid Single-Particle Lagrangian Integrated Trajectory model. Using analysis of variance, we determine that land-based winter storms result in marginally higher albedo than coastal storms or storms from the Atlantic Ocean. Through multiple regression analysis, we determine that snow grain size is significantly more important in albedo reduction than black carbon content or snow density. And finally, we present a parameterization of albedo based on days since snowfall and temperature that accounts for 52% of variance in albedo over all three sites and years. Our improved understanding of current controls on snow albedo in the region will allow for better assessment of potential response of seasonal snow albedo and snow cover to changing climate.

  3. Long-range atmospheric transport of terrestrial biomarkers by the Asian winter monsoon: Evidence from fresh snow from Sapporo, northern Japan

    Science.gov (United States)

    Yamamoto, Shinya; Kawamura, Kimitaka; Seki, Osamu

    2011-07-01

    Molecular distributions of terrestrial biomarkers were investigated in fresh snow samples from Sapporo, northern Japan, to better understand the long-range atmospheric transport of terrestrial organic matter by the Asian winter monsoon. Stable carbon (δ 13C) and hydrogen (δD) isotope ratios of C 22-C 28n-alkanoic acids were also measured to decipher their source regions. The snow samples are found to contain higher plant-derived n-alkanes, n-alkanols and n-alkanoic acids as major components. Relative abundances of these three biomarker classes suggest that they are likely derived from higher plants in the Asian continent. The C 27/C 31 ratios of terrestrial n-alkanes in the snow samples range from 1.3 to 5.5, being similar to those of the plants growing in the latitudes >40°N of East Asia. The δ 13C values of the n-alkanoic acids in the snow samples (-33.4 to -27.6‰) are similar to those of typical C 3 gymnosperm from Sapporo (-34.9 to -29.3‰). However, the δD values of the n-alkanoic acids (-208 to -148‰) are found to be significantly depleted with deuterium (by ˜72‰) than those of plant leaves from Sapporo. Such depletion can be most likely interpreted by the long-range atmospheric transport of the n-alkanoic acids from vegetation in the latitudes further north of Sapporo because the δD values of terrestrial higher plants tend to decrease northward in East Asia reflecting the δD of precipitation. Together with the results of backward trajectory analyses, this study suggests that the terrestrial biomarkers in the Sapporo snow samples are likely transported from Siberia, Russian Far East and northeast China to northern Japan by the Asian winter monsoon.

  4. 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

  5. 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...

  6. 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...

  7. Snow-atmosphere coupling and its impact on temperature variability and extremes over North America

    Science.gov (United States)

    Diro, G. T.; Sushama, L.; Huziy, O.

    2017-07-01

    The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981-2010 period are performed, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 40-60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating

  8. Snow-atmosphere coupling and its impact on temperature variability and extremes over North America

    Science.gov (United States)

    Diro, G. T.; Sushama, L.; Huziy, O.

    2018-04-01

    The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981-2010 period are performed, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 40-60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating

  9. Seasonal Evolution of Thermal Conductivity of Snow and its Impact on Surface Temperature Regimes

    Science.gov (United States)

    Alexeev, V. A.; Kholodov, A. L.

    2017-12-01

    Snow acts as an insulating blanket for permafrost in the winter. Thermal conductivity properties of snowpack in the winter will greatly impact the temperature regimes of the underlaying permafrost. Fourier analysis and other techniques are applied to data obtained from a set of observational sites in Fairbanks, AK with temperature and moisture measured within the snowpack throughout the entire winter in order to estimate thermal conductivity of snow and fluxes through the snow. These data are analyzed in order to understand the variations of soil temperature as a function of snow properties and weather conditions. Thermal diffusion coefficients, snow depth and density data are compared with other available sources. Results obtained will be used for further development of a snow-permafrost model.

  10. An observation-based assessment of the influences of air temperature and snow depth on soil temperature in Russia

    International Nuclear Information System (INIS)

    Park, Hotaek; Sherstiukov, Artem B; Fedorov, Alexander N; Polyakov, Igor V; Walsh, John E

    2014-01-01

    This study assessed trends in the variability of soil temperature (T SOIL ) using spatially averaged observation records from Russian meteorological land stations. The contributions of surface air temperature (SAT) and snow depth (SND) to T SOIL variation were quantitatively evaluated. Composite time series of these data revealed positive trends during the period of 1921–2011, with accelerated increases since the 1970s. The T SOIL warming rate over the entire period was faster than the SAT warming rate in both permafrost and non-permafrost regions, suggesting that SND contributes to T SOIL warming. Statistical analysis revealed that the highest correlation between SND and T SOIL was in eastern Siberia, which is underlain by permafrost. SND in this region accounted for 50% or more of the observed variation in T SOIL . T SOIL in the non-permafrost region of western Siberia was significantly correlated with changes in SAT. Thus, the main factors associated with T SOIL variation differed between permafrost and non-permafrost regions. This finding underscores the importance of including SND data when assessing historical and future variations and trends of permafrost in the Northern Hemisphere. (letter)

  11. 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

  12. 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.

  13. Researches on snow distribution Correlation Based on Arctic Oscillation and over Qinghai-Tibet Plateau

    Science.gov (United States)

    Xiao, T.; Wang, C.; Jia, L.; Du, J.; Chen, Q.

    2017-12-01

    Based on Qinghai-Tibetan Plateau observation data and reanalysis data, the characteristics of snow cover days and depth were analyzed. The relationship between Arctic Oscillation and Qinghai-Tibet Plateau snow cover and its reasons were analyzed. The relationship between Arctic Oscillation and warm and cold climate's temperature and snow cover were also analyzed. And last, the influence of Arctic Oscillation and El Nino Southern Oscillation on the distribution of snow cover days in the Tibetan Plateau was also analyzed. The main contents of this paper are summarized as follows: (1) The interdecadal change of annual snow depth and cover days had a "less-more-less" trend, and both the abrupt change year was 1998. The significant cycle of snow depth is 2 3 years, and snow cover days is 1 3 years. The distribution of large value both snow depths and cover day were same. (2) The Arctic oscillation is significantly related to the number of snow cover days and temperatures in the Tibetan Plateau, but the relationship between AO and the snow cover depth is not significant. The Arctic Oscillation can affect the temperature in Tibetan Plateau by the atmospheric circulation field, thus affecting the Tibetan Plateau snow days in winter. (3). In the past 35 years, warm winter events increased, and cold winter events decreased, and the warming effect of the Qinghai-Tibet Plateau is significant. When the Arctic oscillation index is positive, the plateau is prone to regional cold winter events, and the temperature is less, then the snow cover days increase. The snow cover day also has the relationship with ENSO. When Nino3 index is positive, the Qinghai-Tibet Plateau snow days seem to increase, when the Nino3 index is negative, most of the snow days reduced. Key words: Arctic Oscillation Qinghai-Tibetan Plateau; Snow distribution; Cold and Warm Winter. ENSO Acknowledgements. This study was supported by National Natural Science Foundation of China Fund Project (91337215

  14. Simulation of emergence of winter wheat in response to soil temperature, water potential and planting depth

    Science.gov (United States)

    Seedling emergence is a critical stage in the establishment of dryland wheat. Soil temperature, soil water potential and planting depth are important factors influencing emergence. These factors have considerable spatio-temporal variation making it difficult to predict the timing and percentage of w...

  15. Distribution of VOCs between air and snow at the Jungfraujoch high alpine research station, Switzerland, during CLACE 5 (winter 2006

    Directory of Open Access Journals (Sweden)

    E. Starokozhev

    2009-05-01

    Full Text Available Volatile organic compounds (VOCs were analyzed in air and snow samples at the Jungfraujoch high alpine research station in Switzerland as part of CLACE 5 (CLoud and Aerosol Characterization Experiment during February/March 2006. The fluxes of individual compounds in ambient air were calculated from gas phase concentrations and wind speed. The highest concentrations and flux values were observed for the aromatic hydrocarbons benzene (14.3 μg.m−2 s−1, 1,3,5-trimethylbenzene (5.27 μg.m−2 s−1, toluene (4.40 μg.m−2 −1, and the aliphatic hydrocarbons i-butane (7.87 μg.m−2 s−1, i-pentane (3.61 μg.m−2 s−1 and n-butane (3.23 μg.m−2 s−1. The measured concentrations and fluxes were used to calculate the efficiency of removal of VOCs by snow, which is defined as difference between the initial and final concentration/flux values of compounds before and after wet deposition. The removal efficiency was calculated at −24°C (−13.7°C and ranged from 37% (35% for o-xylene to 93% (63% for i-pentane. The distribution coefficients of VOCs between the air and snow phases were derived from published poly-parameter linear free energy relationship (pp-LFER data, and compared with distribution coefficients obtained from the simultaneous measurements of VOC concentrations in air and snow at Jungfraujoch. The coefficients calculated from pp-LFER exceeded those values measured in the present study, which indicates more efficient snow scavenging of the VOCs investigated than suggested by theoretical predictions.

  16. Validation of MODIS snow cover images over Austria

    Directory of Open Access Journals (Sweden)

    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.

  17. Distributed calibrating snow models using remotely sensed snow cover information

    Science.gov (United States)

    Li, H.

    2015-12-01

    Distributed calibrating snow models using remotely sensed snow cover information Hongyi Li1, Tao Che1, Xin Li1, Jian Wang11. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China For improving the simulation accuracy of snow model, remotely sensed snow cover data are used to calibrate spatial parameters of snow model. A physically based snow model is developed and snow parameters including snow surface roughness, new snow density and critical threshold temperature distinguishing snowfall from precipitation, are spatially calibrated in this study. The study region, Babaohe basin, located in northwestern China, have seasonal snow cover and with complex terrain. The results indicates that the spatially calibration of snow model parameters make the simulation results more reasonable, and the simulated snow accumulation days, plot-scale snow depth are more better than lumped calibration.

  18. Wind drifted snow influence on the water and mass balance in the mountainous catchment "Modry potok", the Giant Mountains, Czech Republic.

    Science.gov (United States)

    Dvorak, I. J.; Fottova, D.; Tesar, M.; Kocianova, M.; Harcarik, J.

    2009-04-01

    There are very specific components of the water balance in the mountain headwater regions. Beside the point of cloud- and fog-water deposition it is mainly accumulation of water in the snow cover drifted into the watershed by the wind. Uneven distribution of the snow cover over the mountainous terrain is a well known phenomenon in all alpine and arctic areas. The result of this uneveness is a mosaic of microhabitats with various snow depths, different melting dates and snow free periods. Wire probes can be reliably used up to snow depths of 3 m only. To get more realistic data, two digital models using kinematic carrier phase-based GPS measurements were developed: (1) a model for snow surface data, applied at the end of winter seasons from 2000 to 2008, and (2) a model for the underlying snow free ground surface, applied after the snow melting in August 2000. These two models, overlaid in the GIS environment, have identified snow depths. For the creation of digital elevation models (DEMs), the TOPOGRID command in ArcInfo was used, which generated a grid of elevations from 3-D point, line, and polygon data. The snow depths were obtained and snow maps constructed accordingly. These "snow" results can be used for more realistic estimation of water content of snow in the watershed, distribution of snow depth during the winter seasons and define the water and mass balance more precisely. The objectives of this study were to highlight water storage in the snow-beds and show the GPS kinematic measurements as a contribution to understand more the snow accumulating and melting processes in the Modry potok catchment (2,62 km2, 1010 - 1554 m a.s.l.) in the Giant Mts. The research is supported by the Ministry of the Environment of the Czech Republic (SP/1a6/151/07) and by the Krkonose National Park Administration in Vrchlabi.

  19. High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

    Science.gov (United States)

    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

  20. Effect of summer throughfall exclusion, summer drought, and winter snow cover on methane fluxes in a temperate forest soil

    Science.gov (United States)

    Borken, W.; Davidson, E.A.; Savage, K.; Sundquist, E.T.; Steudler, P.

    2006-01-01

    Soil moisture strongly controls the uptake of atmospheric methane by limiting the diffusion of methane into the soil, resulting in a negative correlation between soil moisture and methane uptake rates under most non-drought conditions. However, little is known about the effect of water stress on methane uptake in temperate forests during severe droughts. We simulated extreme summer droughts by exclusion of 168 mm (2001) and 344 mm (2002) throughfall using three translucent roofs in a mixed deciduous forest at the Harvard Forest, Massachusetts, USA. The treatment significantly increased CH4 uptake during the first weeks of throughfall exclusion in 2001 and during most of the 2002 treatment period. Low summertime CH4 uptake rates were found only briefly in both control and exclusion plots during a natural late summer drought, when water contents below 0.15 g cm-3 may have caused water stress of methanotrophs in the A horizon. Because these soils are well drained, the exclusion treatment had little effect on A horizon water content between wetting events, and the effect of water stress was smaller and more brief than was the overall treatment effect on methane diffusion. Methane consumption rates were highest in the A horizon and showed a parabolic relationship between gravimetric water content and CH4 consumption, with maximum rate at 0.23 g H2O g-1 soil. On average, about 74% of atmospheric CH4 was consumed in the top 4-5 cm of the mineral soil. By contrast, little or no CH4 consumption occurred in the O horizon. Snow cover significantly reduced the uptake rate from December to March. Removal of snow enhanced CH4 uptake by about 700-1000%, resulting in uptake rates similar to those measured during the growing season. Soil temperatures had little effect on CH4 uptake as long as the mineral soil was not frozen, indicating strong substrate limitation of methanotrophs throughout the year. Our results suggest that the extension of snow periods may affect the annual rate

  1. Spatial and temporal variation in snow accumulation in the Central Spanish Pyrenees

    Science.gov (United States)

    López-Moreno, I.; Beguería, S.; García-Ruiz, J. M.

    2003-04-01

    Water stored in winter snowpack represents a valuable resource in mountainous regions. The distribution of the snow determines the availability of water resources during snowmelt period, as well as the development of the economy based on winter sports. This work analyses the main factors that explain the variation in snow accumulation in the Central Spanish Pyrenees. Data about evolution of snowpack is provided by the measurement of 106 sticks installed in the study area from 1985. The snow depth is measured in two moments of the year, at the beginning of March and at the end of April or beginning of May. Snow depth, of both measurements moments, has been mapped using linear regression between snow depth and different topographic and geographic variables derived from the digital terrain model. In order to improve the estimation interpolated residuals values have been subtracted. The variability of the interannual snow distribution has been analysed with a factorial analysis in order to obtain different annual patterns of snowpack distribution. Relation between the dominant winter weather-type and the different patterns, provided by the factorial analysis, has been studied. The weather-type classification has been obtained using the Jenkinson and Collison system based on daily series of sea level atmospheric pressure measured around the Iberian Peninsula with a 5º x 10º scale. Thus, it is possible to know the influence of the prevailing winter synoptic situations in the snowpack distribution. The results show that topographic and geographic variables have a high capacity to explain the spatial distribution of the average snow cover during the study period. Nevertheless, the annual snow accumulation is the result of the arrival of frontal disturbances that come from different directions. By that, it is complex to relate the different snow distribution patterns to the main winter synoptic conditions of each year.

  2. 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).

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. 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…

  6. The ringed seal's last refuge and the importance of snow cover

    Science.gov (United States)

    Kelly, B. P.; Bitz, C. M.

    2010-12-01

    Ringed seals are strongly adapted to inhabiting seasonal ice cover throughout the Arctic Ocean, marginal seas, and some freshwater lakes. Their distribution has expanded and contracted with northern hemisphere ice cover and is expected to mirror declining ice cover in coming decades. Ringed seals require snow cover to provide shelter from extreme cold and from predators, and the southern extent of their range corresponds to the latitudes to which snow cover—sufficient to form and maintain subnivean lairs—extends. The lairs are especially critical to the survival of pups born and nursed under the snow in late March through May. Snow drifts 50 cm or deeper are necessary for lair occupation, and field measurements indicate that such drifting occurs only where average snow depths (on flat ice) exceed 20 cm. When snow depths are less, ringed seal pups freeze in their lairs and are vulnerable to predation by carnivores and birds. As the climate warms, winter precipitation is expected to increase in the Arctic Ocean, potentially favoring formation and occupation of lairs. At the same time, increasingly late ice formation is expected to decrease the overall accumulation of snow, an effect exacerbated by the high fraction of annual snow fall that occurs in autumn. Early snow melts also contribute to pup mortality and are likely to increase as the climate warms. We forecast April snow depths on Arctic sea ice through the year 2100 in seven runs of CCSM3. Despite predicted increases in winter precipitation in the Arctic, the model forecasted that the accumulation of snow on sea ice will decrease by almost 50% in this century. The timing of the onset of snow melt changes little in the projections, but the shallower snow pack will melt more quickly in the warmer climate. In almost all portions of the range, average snow depths are expected to be less than 20 cm and inadequate for successful rearing of ringed seal young by the end of the century and—in many locations

  7. Influence of snow-cover properties on avalanche dynamics

    Science.gov (United States)

    Steinkogler, W.; Sovilla, B.; Lehning, M.

    2012-04-01

    Snow avalanches with the potential of reaching traffic routes and settlements are a permanent winter threat for many mountain communities. Snow safety officers have to take the decision whether to close a road, a railway line or a ski slope. Those decisions are often very difficult as they demand the ability to interpret weather forecasts, to establish their implication for the stability and the structure of the snow cover and to evaluate the influence of the snow cover on avalanche run-out distances. In the operational programme 'Italy-Switzerland, project STRADA' we focus on the effects of snow cover on avalanche dynamics, and thus run-out distance, with the aim to provide a better understanding of this influence and to ultimately develop tools to support snow safety officers in their decision process. We selected five avalanches, measured at the Vallée de la Sionne field site, with similar initial mass and topography but different flow dynamics and run-out distances. Significant differences amongst the individual avalanches could be observed for front and internal velocities, impact pressures, flow regimes, deposition volumes and run-out distances. For each of these avalanches, the prevailing snow conditions at release were reconstructed using field data from local snowpits or were modeled with SNOWPACK. Combining flow dynamical data with snow cover properties shows that erodible snow depth, snow density and snow temperature in the snow pack along the avalanche track are among the decisive variables that appear to explain the observed differences. It is further discussed, how these influencing factors can be quantified and used for improved predictions of site and time specific avalanche hazard.

  8. 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

  9. 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

    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...

  10. 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.

  11. Snow Fun.

    Science.gov (United States)

    Finlay, Joy

    1988-01-01

    Describes several learning activities that can be done with children in the snow. Includes shake paintings, snow sculpture, snow "snakes," snow-ball contests, an igloo experience, and how to make snowshoes. (TW)

  12. 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.

  13. Seedling establishment at the alpine tree line - Can there be too much winter protection?

    Science.gov (United States)

    Lett, S.; Wardle, D.; Nilsson, M. C.; Dorrepaal, E.

    2014-12-01

    Alpine and arctic tree line expansion relies on tree seedling survival above the tree line, where the environment is harsh and protection by snow during winter is essential. Above the tree line, bryophytes are dominant; they may act as thermal insulators but their insulating ability differs between species. Apart from these positive effects, both snow and bryophytes may have negative effects on seedlings via shortening of the growing season or competition, respectively. Snow depth and duration are expected to change due to climate change, leading in some places to more snow and in others to less. What is the role of bryophytes insulating properties for seedling establishment under changing winter conditions at the alpine tree line? We hypothesized that protecting effects of snow and bryophytes would be more important for seedling survival in harsh climate (high elevation) than in milder climate (low elevation) (interactions: bryophyte*elevation and snow*elevation) and that negative effects of less snow would be ameliorated by well-insulating bryophytes (interaction: bryophyte*snow). To test this, we transplanted cores of three bryophyte species of differing insulation capacity and bare soil (control) from the subarctic tree line (~600m asl.) to 700 and 350 m asl. We transplanted 10 seedlings of two common tree line tree species (Betula pubescens and Pinus sylvestris) into each core in late summer. Cores were subjected to one of three snow treatments: autumn and spring snow removal or addition, or no manipulation. After the winter we scored seedling survival. The snow treatments had different effects at the two elevations (elevation* snow: Pbryophytes did not (elevation*bryophyte: n.s). In the harsh climate, snow addition generally enhanced seedling survival. In contrast, at the milder climate site, snow addition only increased survival in the bare soil treatment but decreased survival of seedlings in the bryophyte cores (bryophyte*snow: P=0.053). Our data show that

  14. Influence of Dust and Black Carbon on the Snow Albedo in the NASA Goddard Earth Observing System Version 5 Land Surface Model

    Science.gov (United States)

    Yasunari, Teppei J.; Koster, Randal D.; Lau, K. M.; Aoki, Teruo; Sud, Yogesh C.; Yamazaki, Takeshi; Motoyoshi, Hiroki; Kodama, Yuji

    2011-01-01

    Present-day land surface models rarely account for the influence of both black carbon and dust in the snow on the snow albedo. Snow impurities increase the absorption of incoming shortwave radiation (particularly in the visible bands), whereby they have major consequences for the evolution of snowmelt and life cycles of snowpack. A new parameterization of these snow impurities was included in the catchment-based land surface model used in the National Aeronautics and Space Administration Goddard Earth Observing System version 5. Validation tests against in situ observed data were performed for the winter of 2003.2004 in Sapporo, Japan, for both the new snow albedo parameterization (which explicitly accounts for snow impurities) and the preexisting baseline albedo parameterization (which does not). Validation tests reveal that daily variations of snow depth and snow surface albedo are more realistically simulated with the new parameterization. Reasonable perturbations in the assigned snow impurity concentrations, as inferred from the observational data, produce significant changes in snowpack depth and radiative flux interactions. These findings illustrate the importance of parameterizing the influence of snow impurities on the snow surface albedo for proper simulation of the life cycle of snow cover.

  15. 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.

  16. Forcing the snow-cover model SNOWPACK with forecasted weather data

    Directory of Open Access Journals (Sweden)

    S. Bellaire

    2011-12-01

    Full Text Available Avalanche danger is often estimated based on snow cover stratigraphy and snow stability data. In Canada, single forecasting regions are very large (>50 000 km2 and snow cover data are often not available. To provide additional information on the snow cover and its seasonal evolution the Swiss snow cover model SNOWPACK was therefore coupled with a regional weather forecasting model GEM15. The output of GEM15 was compared to meteorological as well as snow cover data from Mt. Fidelity, British Columbia, Canada, for five winters between 2005 and 2010. Precipitation amounts are most difficult to predict for weather forecasting models. Therefore, we first assess the capability of the model chain to forecast new snow amounts and consequently snow depth. Forecasted precipitation amounts were generally over-estimated. The forecasted data were therefore filtered and used as input for the snow cover model. Comparison between the model output and manual observations showed that after pre-processing the input data the snow depth and new snow events were well modelled. In a case study two key factors of snow cover instability, i.e. surface hoar formation and crust formation were investigated at a single point. Over half of the relevant critical layers were reproduced. Overall, the model chain shows promising potential as a future forecasting tool for avalanche warning services in Canadian data sparse areas and could thus well be applied to similarly large regions elsewhere. However, a more detailed analysis of the simulated snow cover structure is still required.

  17. Evaluating controls on snow distribution in the eastern Chugach Mountains, Alaska

    Science.gov (United States)

    Wolken, G. J.; Wikstrom Jones, K.

    2017-12-01

    A detailed understanding of the spatial and temporal variability of alpine snow depth is important because of its strong influence on water resources, regional economies, and public safety. However, in complex terrain, strong orographic gradients and complicated topography-influenced wind fields produce complex accumulation patterns that are difficult to accurately quantify using traditional in situ and satellite-based approaches, and are challenging to model. In this study, we use repeat airborne photogrammetry, Structure from Motion (SfM) processing methods, and field-based measurements to produce continuous and accurate maps of end-of-winter snow depth and snow water equivalence (SWE) in the eastern Chugach Mountains, Alaska, during the period 2015-2017. We validate photogrammetry-derived snow depth maps using simultaneously acquired snow depth measurements recorded by project and citizen scientists. Patterns of snow distribution in the study area are largely controlled by orographic forcing, however, these patterns are strongly modulated by persistent synoptic weather systems that serve to weaken the climatological snow distribution pattern.

  18. Snow multivariable data assimilation for hydrological predictions in Alpine sites

    Science.gov (United States)

    Piazzi, Gaia; Thirel, Guillaume; Campo, Lorenzo; Gabellani, Simone; Stevenin, Hervè

    2017-04-01

    Snowpack dynamics (snow accumulation and ablation) strongly impacts on hydrological processes in Alpine areas. During the winter season the presence of snow cover (snow accumulation) reduces the drainage in the basin with a resulting lower watershed time of concentration in case of possible rainfall events. Moreover, the release of the significant water volume stored in winter (snowmelt) considerably contributes to the total discharge during the melting period. Therefore when modeling hydrological processes in snow-dominated catchments the quality of predictions deeply depends on how the model succeeds in catching snowpack dynamics. The integration of a hydrological model with a snow module allows improving predictions of river discharges. Besides the well-known modeling limitations (uncertainty in parameterizations; possible errors affecting both meteorological forcing data and initial conditions; approximations in boundary conditions), there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine several independent snow-related data sources (model simulations, ground-based measurements and remote sensed observations) in order to obtain the most likely estimate of snowpack state. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model strengthened by a multivariable DA framework for hydrological purposes. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity

  19. Long-term increases in snow pack elevate leaf N and photosynthesis in Salix arctica: responses to a snow fence experiment in the High Arctic of NW Greenland

    Science.gov (United States)

    Leffler, A. Joshua; Welker, Jeffery M.

    2013-06-01

    We examine the influence of altered winter precipitation on a High Arctic landscape with continuous permafrost. Gas exchange, leaf tissue element and isotopic composition (N, δ13C, δ15N), and plant water sources derived from stem and soil water δ18O were examined in Salix arctica (arctic willow) following a decade of snow-fence-enhanced snow pack in NW Greenland. Study plots in ambient and +snow conditions were sampled in summer 2012. Plants experiencing enhanced snow conditions for 10 years had higher leaf [N], photosynthetic rate, and more enriched leaf δ15N. Enhanced snow did not influence stomatal conductance or depth of plant water use. We attribute the higher photosynthetic rate in S. arctica exposed to deeper snow pack to altered biogeochemical cycles which yielded higher leaf [N] rather than to enhanced water availability. These data demonstrate the complexity of High Arctic plant responses to changes in winter conditions. Furthermore, our data depict the intricate linkages between winter and summer conditions as they regulate processes such as leaf gas exchange that may control water vapor and CO2 feedbacks between arctic tundra and the surrounding atmosphere.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Snow Cover/Depth (SCD) Binary Map 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 Binary Snow Cover (BSC) from the Visible Infrared Imaging Radiometer Suite...

  7. Origin of elemental carbon in snow from western Siberia and northwestern European Russia during winter-spring 2014, 2015 and 2016

    Science.gov (United States)

    Evangeliou, Nikolaos; Shevchenko, Vladimir P.; Espen Yttri, Karl; Eckhardt, Sabine; Sollum, Espen; Pokrovsky, Oleg S.; Kobelev, Vasily O.; Korobov, Vladimir B.; Lobanov, Andrey A.; Starodymova, Dina P.; Vorobiev, Sergey N.; Thompson, Rona L.; Stohl, Andreas

    2018-01-01

    Short-lived climate forcers have been proven important both for the climate and human health. In particular, black carbon (BC) is an important climate forcer both as an aerosol and when deposited on snow and ice surface because of its strong light absorption. This paper presents measurements of elemental carbon (EC; a measurement-based definition of BC) in snow collected from western Siberia and northwestern European Russia during 2014, 2015 and 2016. The Russian Arctic is of great interest to the scientific community due to the large uncertainty of emission sources there. We have determined the major contributing sources of BC in snow in western Siberia and northwestern European Russia using a Lagrangian atmospheric transport model. For the first time, we use a recently developed feature that calculates deposition in backward (so-called retroplume) simulations allowing estimation of the specific locations of sources that contribute to the deposited mass. EC concentrations in snow from western Siberia and northwestern European Russia were highly variable depending on the sampling location. Modelled BC and measured EC were moderately correlated (R = 0.53-0.83) and a systematic region-specific model underestimation was found. The model underestimated observations by 42 % (RMSE = 49 ng g-1) in 2014, 48 % (RMSE = 37 ng g-1) in 2015 and 27 % (RMSE = 43 ng g-1) in 2016. For EC sampled in northwestern European Russia the underestimation by the model was smaller (fractional bias, FB > -100 %). In this region, the major sources were transportation activities and domestic combustion in Finland. When sampling shifted to western Siberia, the model underestimation was more significant (FB model calculations was also evaluated using two independent datasets of BC measurements in snow covering the entire Arctic. The model underestimated BC concentrations in snow especially for samples collected in springtime.

  8. Central Asian Snow Cover from Hydrometeorological Surveys, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides observations of end of month snow depth, snow density, and snow water equivalent from three river basins in Central Asia: Amu Darya, Sir...

  9. 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)

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

    Science.gov (United States)

    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.

  11. Interannual changes in snow cover and its impact on ground surface temperatures in Livingston Island (Antarctica)

    Science.gov (United States)

    Nieuwendam, Alexandre; Ramos, Miguel; Vieira, Gonçalo

    2015-04-01

    In permafrost areas the seasonal snow cover is an important factor on the ground thermal regime. Snow depth and timing are important in ground insulation from the atmosphere, creating different snow patterns and resulting in spatially variable ground temperatures. The aim of this work is to characterize the interactions between ground thermal regimes and snow cover and the influence on permafrost spatial distribution. The study area is the ice-free terrains of northwestern Hurd Peninsula in the vicinity of the Spanish Antarctic Station "Juan Carlos I" and Bulgarian Antarctic Station "St. Kliment Ohridski". Air and ground temperatures and snow thickness data where analysed from 4 sites along an altitudinal transect in Hurd Peninsula from 2007 to 2012: Nuevo Incinerador (25 m asl), Collado Ramos (110 m), Ohridski (140 m) and Reina Sofia Peak (275 m). The data covers 6 cold seasons showing different conditions: i) very cold with thin snow cover; ii) cold with a gradual increase of snow cover; iii) warm with thick snow cover. The data shows three types of periods regarding the ground surface thermal regime and the thickness of snow cover: a) thin snow cover and short-term fluctuation of ground temperatures; b) thick snow cover and stable ground temperatures; c) very thick snow cover and ground temperatures nearly constant at 0°C. a) Thin snow cover periods: Collado Ramos and Ohridski sites show frequent temperature variations, alternating between short-term fluctuations and stable ground temperatures. Nuevo Incinerador displays during most of the winter stable ground temperatures; b) Cold winters with a gradual increase of the snow cover: Nuevo Incinerador, Collado Ramos and Ohridski sites show similar behavior, with a long period of stable ground temperatures; c) Thick snow cover periods: Collado Ramos and Ohridski show long periods of stable ground, while Nuevo Incinerador shows temperatures close to 0°C since the beginning of the winter, due to early snow cover

  12. CLPX-Ground: Snow Measurements at the Local Scale Observation Site (LSOS), Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set presents snow depth, snow water equivalence (SWE), snow wetness data, and snow pit data from two pine sites and a small clearing at the Local Scale...

  13. CLPX-Ground: Snow Measurements at the Local Scale Observation Site (LSOS)

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set presents snow depth, snow water equivalence (SWE), snow wetness data, and snow pit data from two pine sites and a small clearing at the Local Scale...

  14. Validation of NOAA-Interactive Multisensor Snow and Ice Mapping System (IMS by Comparison with Ground-Based Measurements over Continental United States

    Directory of Open Access Journals (Sweden)

    Reza Khanbilvardi

    2012-04-01

    Full Text Available In this study, daily maps of snow cover distribution and sea ice extent produced by NOAA’s interactive multisensor snow and ice mapping system (IMS were validated using in situ snow depth data from observing stations obtained from NOAA’s National Climatic Data Center (NCDC for calendar years 2006 to 2010. IMS provides daily maps of snow and sea ice extent within the Northern Hemisphere using data from combination of geostationary and polar orbiting satellites in visible, infrared and microwave spectrums. Statistical correspondence between the IMS and in situ point measurements has been evaluated assuming that ground measurements are discrete and continuously distributed over a 4 km IMS snow cover maps. Advanced Very High Resolution Radiometer (AVHRR land and snow classification data are supplemental datasets used in the further analysis of correspondence between the IMS product and in situ measurements. The comparison of IMS maps with in situ snow observations conducted over a period of four years has demonstrated a good correspondence of the data sets. The daily rate of agreement between the products mostly ranges between 80% and 90% during the Northern Hemisphere through the winter seasons when about a quarter to one third of the territory of continental US is covered with snow. Further, better agreement was observed for stations recording higher snow depth. The uncertainties in validation of IMS snow product with stationed NCDC data were discussed.

  15. 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.

  16. 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 ...

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

    Science.gov (United States)

    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.

  18. 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

  19. Snow melt water use and tundra plant gas exchange: An ecohydrological perspective on vegetation changes in the Arctic

    Science.gov (United States)

    Jespersen, R. G.; Leffler, A. J.; Welker, J. M.

    2016-12-01

    Understanding the ecohydrological effects of changing snow cover in the arctic is particularly important as it may be a driver of arctic shrub expansion. Previous studies have focused mostly on relationships between snow cover and biogeochemical processes, with less attention given to plant and soil water relations and the ecophysiology of tundra plant life forms. Here we examined the ecophysiological consequences of different snow depth regimes in moist acidic tundra in the Alaskan Arctic, with a particular focus on the role of snowmelt water in plant ecophysiological processes. Using a 20+ year snowfence experiment featuring shallow, control, and deep winter snow conditions, we combined leaf-level gas exchange measurements with isotopic characterization of soil water, stem water, and leaves to clarify water use patterns in the four dominant plant species. Thus far, our leaf-level data reveal striking differences in how species respond to deep or shallow snow scenarios. In the deep snow zone, Salix pulchra, Betula nana, and Eriophorum vaginatum have all demonstrated at least 20% increases in maximum net photosynthesis (Amax) and stomatal conductance (gs) relative to the control and shallow snow zones throughout the early and mid-summer, with the strongest response to deep snow being seen in Salix (>50% increase in both Amax and gs). Both Betula and Eriophorum also demonstrated at least 25% reductions in Amax and gs in the shallow snow zone relative to control conditions during one of the early or mid-summer measurement periods. In contrast, Ledum palustre has responded haphazardly to changes in winter snow depth, with no consistent directional changes in Amax or gs across snow depths. We anticipate that accompanying isotopic data will reveal differences among species in the timing of water use from particular depths and sources. Thus far, our data suggest that Salix pulchra, Betula nana, and Eriophorum vaginatum are physiologically capable of exploiting the

  20. Snow Leopard

    Indian Academy of Sciences (India)

    the Central Asian mountains and the Indian Himalayan re- gion. Owing to their ... ographical range and associated ecological, social, and cultural ... Central Asia. Snow Leopard: Morphology. The ability of snow leopards to camouflage with the surrounding landscape of rocks, sparse low vegetation, and snow is crucial for.

  1. Snow depth and vegetation pattern in a late-melting snowbed analyzed by GPS and GIS in the Giant Mountains, Czech Republic

    Czech Academy of Sciences Publication Activity Database

    Hejcman, M.; Dvořák, I.J.; Kociánová, M.; Pavlů, V.; Nežerková, P.; Vítek, O.; Rauch, Ota; Jeník, Jan

    2006-01-01

    Roč. 38, č. 1 (2006), s. 90-98 ISSN 1523-0430 R&D Projects: GA ČR GA526/03/0528 Institutional research plan: CEZ:AV0Z60050516 Keywords : Snow bed * GPS * vegetation Subject RIV: DO - Wilderness Conservation Impact factor: 0.931, year: 2006

  2. 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

  3. Temporal and spectral cloud screening of polar winter aerosol optical depth (AOD: impact of homogeneous and inhomogeneous clouds and crystal layers on climatological-scale AODs

    Directory of Open Access Journals (Sweden)

    N. T. O'Neill

    2016-10-01

    Full Text Available We compared star-photometry-derived, polar winter aerosol optical depths (AODs, acquired at Eureka, Nunavut, Canada, and Ny-Ålesund, Svalbard, with GEOS-Chem (GC simulations as well as ground-based lidar and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization retrievals over a sampling period of two polar winters. The results indicate significant cloud and/or low-altitude ice crystal (LIC contamination which is only partially corrected using temporal cloud screening. Spatially homogeneous clouds and LICs that remain after temporal cloud screening represent an inevitable systematic error in the estimation of AOD: this error was estimated to vary from 78 to 210 % at Eureka and from 2 to 157 % at Ny-Ålesund. Lidar analysis indicated that LICs appeared to have a disproportionately large influence on the homogeneous coarse-mode optical depths that escape temporal cloud screening. In principle, spectral cloud screening (to yield fine-mode or submicron AODs reduces pre-cloud-screened AODs to the aerosol contribution if one assumes that coarse-mode (super-micron aerosols are a minor part of the AOD. Large, low-frequency differences between these retrieved values and their GC analogue appeared to be often linked to strong, spatially extensive planetary boundary layer events whose presence at either site was inferred from CALIOP profiles. These events were either not captured or significantly underestimated by the GC simulations. High-frequency AOD variations of GC fine-mode aerosols at Ny-Ålesund were attributed to sea salt, while low-frequency GC variations at Eureka and Ny-Ålesund were attributable to sulfates. CALIOP profiles and AODs were invaluable as spatial and temporal redundancy support (or, alternatively, as insightful points of contention for star photometry retrievals and GC estimates of AOD.

  4. Assessing the efficiency of machine made snow production using observations in ski resorts

    Science.gov (United States)

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

    2016-04-01

    The interannual variability of snow conditions has encouraged ski resorts to mitigate their dependency to weather conditions through snowmaking facilities. However the efficiency of the method i.e. the ratio of water actually converted into snow on ski fields to the water used for production may highly differ depending on meteorological conditions and is still poorly known. Previous investigations of water losses accounting for sublimation and evaporation estimated that 5 to 10% of the water was lost during the snowmaking process. A recent study consisting in a field campaign on four distinct sites (2014-2015 winter season) estimated that water losses may exceed 50% and speculated this to be due to a combination of wind effects (suspension, further sublimation and transport beyond ski slopes limits) and trapping by the vegetation. The present study introduces a method we set up to assess water losses during the snowmaking process by using differential GPS measurements on machine made snow piles: snow depth observations are interpolated on a regular spatial grid from the originally variable grid. Snow and water volumes are deduced thanks to complementary density measurements. The uncertainty of the interpolation method was assessed using a high-resolution laser scanner of a given snow pile and with respect to a digital terrain. Uncertainties on snow depth, snow density and the resulting water equivalent volume are presented and discussed. The method provided relevant measurements of water volumes within a 20 to 30 m distance to the snowgun. Beyond this distance, the relative error due to increasing interpolation error and decreasing snow depth highlighted the limits of the method. However water volumes were derived in several occasions during the season and confirmed that a significant ratio of the water volume either falls beyond a 30 m distance to the snowgun or is lost due to sublimation and evaporation.

  5. The magnitude of the snow-sourced reactive nitrogen flux to the boundary layer in the Uintah Basin, Utah, USA

    Directory of Open Access Journals (Sweden)

    M. Zatko

    2016-11-01

    Full Text Available Reactive nitrogen (Nr  =  NO, NO2, HONO and volatile organic carbon emissions from oil and gas extraction activities play a major role in wintertime ground-level ozone exceedance events of up to 140 ppb in the Uintah Basin in eastern Utah. Such events occur only when the ground is snow covered, due to the impacts of snow on the stability and depth of the boundary layer and ultraviolet actinic flux at the surface. Recycling of reactive nitrogen from the photolysis of snow nitrate has been observed in polar and mid-latitude snow, but snow-sourced reactive nitrogen fluxes in mid-latitude regions have not yet been quantified in the field. Here we present vertical profiles of snow nitrate concentration and nitrogen isotopes (δ15N collected during the Uintah Basin Winter Ozone Study 2014 (UBWOS 2014, along with observations of insoluble light-absorbing impurities, radiation equivalent mean ice grain radii, and snow density that determine snow optical properties. We use the snow optical properties and nitrate concentrations to calculate ultraviolet actinic flux in snow and the production of Nr from the photolysis of snow nitrate. The observed δ15N(NO3− is used to constrain modeled fractional loss of snow nitrate in a snow chemistry column model, and thus the source of Nr to the overlying boundary layer. Snow-surface δ15N(NO3− measurements range from −5 to 10 ‰ and suggest that the local nitrate burden in the Uintah Basin is dominated by primary emissions from anthropogenic sources, except during fresh snowfall events, where remote NOx sources from beyond the basin are dominant. Modeled daily averaged snow-sourced Nr fluxes range from 5.6 to 71  ×  107 molec cm−2 s−1 over the course of the field campaign, with a maximum noontime value of 3.1  ×  109 molec cm−2 s−1. The top-down emission estimate of primary, anthropogenic NOx in Uintah and Duchesne counties is at least 300 times higher than

  6. 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.

  7. Influence of snowpack internal structure on snow metamorphism and melting intensity on Hansbreen, Svalbard

    Directory of Open Access Journals (Sweden)

    Laska Michał

    2016-06-01

    Full Text Available This paper presents a detailed study of melting processes conducted on Hansbreen – a tidewater glacier terminating in the Hornsund fjord, Spitsbergen. The fieldwork was carried out from April to July 2010. The study included observations of meltwater distribution within snow profiles in different locations and determination of its penetration time to the glacier ice surface. In addition, the variability of the snow temperature and heat transfer within the snow cover were measured. The main objective concerns the impact of meltwater on the diversity of physical characteristics of the snow cover and its melting dynamics. The obtained results indicate a time delay between the beginning of the melting processes and meltwater reaching the ice surface. The time necessary for meltwater to percolate through the entire snowpack in both, the ablation zone and the equilibrium line zone amounted to c. 12 days, despite a much greater snow depth at the upper site. An elongated retention of meltwater in the lower part of the glacier was caused by a higher amount of icy layers (ice formations and melt-freeze crusts, resulting from winter thaws, which delayed water penetration. For this reason, a reconstruction of rain-on-snow events was carried out. Such results give new insight into the processes of the reactivation of the glacier drainage system and the release of freshwater into the sea after the winter period.

  8. Annual Soil Temperature Wave at Four Depths in Southwestern Wisconsin

    Science.gov (United States)

    Richard S. Sartz

    1967-01-01

    Soil temperature was measured for a year on a southeast-facing slope of 25 percent, latitude 43 degrees 50 minutes N. The spring-summer cover was unmowed alfalfa-bluegrass meadow, the fall-winter cover, meadow stubble. Snow cover was light or absent. The soil was Fayette silt loam, valley phase. The annual temperature wave at all depths followed the air temperature...

  9. 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.

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

    Science.gov (United States)

    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

  11. NASA Airborne Snow Observatory: Measuring Spatial Distribution of Snow Water Equivalent and Snow Albedo

    Science.gov (United States)

    Joyce, M.; Painter, T. H.; Bormann, K. J.; Berisford, D. F.; Lai-Norling, J.

    2017-12-01

    The two most critical properties for understanding snowmelt runoff and timing are the spatial and temporal distributions of snow water equivalent (SWE) and snow albedo. Despite their importance in controlling volume and timing of runoff, snowpack albedo and SWE are still largely unquantified in the US and not at all in most of the globe, leaving runoff models poorly constrained. NASA Jet Propulsion Laboratory, in partnership with the California Department of Water Resources, has developed the Airborne Snow Observatory (ASO), an imaging spectrometer and scanning LiDAR system, to quantify SWE and snow albedo, generate unprecedented knowledge of snow properties for cutting edge cryospheric science, and provide complete, robust inputs to water management models and systems of the future. This poster will describe the NASA Airborne Snow Observatory, its outputs and their uses and applications, along with recent advancements to the system and plans for the project's future. Specifically, we will look at how ASO uses its imaging spectrometer to quantify spectral albedo, broadband albedo, and radiative forcing by dust and black carbon in snow. Additionally, we'll see how the scanning LiDAR is used to determine snow depth against snow-free acquisitions and to quantify snow water equivalent when combined with in-situ constrained modeling of snow density.

  12. 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.

  13. 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

  14. Snow Matters

    DEFF Research Database (Denmark)

    Gyimóthy, Szilvia; Jensen, Martin Trandberg

    2018-01-01

    attribute of high altitude mountain destinations. Hitherto, researchers mostly engaged with snowclad landscapes as a backstage; trying to deconstruct the complex symbolism and representational qualities of this elusive substance. Despite snow being a strategically crucial condition for tourism in the Alps......This chapter explores the performative potential of snow for Alpine tourism, by drawing attention to its material and nonrepresentational significance for tourism practices. European imagination has been preoccupied with snow since medieval times and even today, snow features as the sine que non...

  15. 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).

  16. Coupled long-term summer warming and deeper snow alters species composition and stimulates gross primary productivity in tussock tundra.

    Science.gov (United States)

    Leffler, A Joshua; Klein, Eric S; Oberbauer, Steven F; Welker, Jeffrey M

    2016-05-01

    Climate change is expected to increase summer temperature and winter precipitation throughout the Arctic. The long-term implications of these changes for plant species composition, plant function, and ecosystem processes are difficult to predict. We report on the influence of enhanced snow depth and warmer summer temperature following 20 years of an ITEX experimental manipulation at Toolik Lake, Alaska. Winter snow depth was increased using snow fences and warming was accomplished during summer using passive open-top chambers. One of the most important consequences of these experimental treatments was an increase in active layer depth and rate of thaw, which has led to deeper drainage and lower soil moisture content. Vegetation concomitantly shifted from a relatively wet system with high cover of the sedge Eriophorum vaginatum to a drier system, dominated by deciduous shrubs including Betula nana and Salix pulchra. At the individual plant level, we observed higher leaf nitrogen concentration associated with warmer temperatures and increased snow in S. pulchra and B. nana, but high leaf nitrogen concentration did not lead to higher rates of net photosynthesis. At the ecosystem level, we observed higher GPP and NEE in response to summer warming. Our results suggest that deeper snow has a cascading set of biophysical consequences that include a deeper active layer that leads to altered species composition, greater leaf nitrogen concentration, and higher ecosystem-level carbon uptake.

  17. A Refined Methodology for Modelling Climate Change Impacts on Snow Sports Tourism

    Science.gov (United States)

    Demiroglu, O. Cenk; Turp, M. Tufan; Ozturk, Tugba; An, Nazan; Kurnaz, M. Levent

    2015-04-01

    Nature-based tourism is one of the most vulnerable sectors of the economy against climate change. Among its types, winter tourism stands out as the most critical due to the relatively high exposure and sensitivity of snow cover to the anthropogenic warming trends. In this study, we aim at improving previous works by Ozturk et al. where snow reliability of ski resorts have been examined through projections based on regional climate model outputs downscaled from various GCMs. Major improvements to these studies will be related to increasing the resolution, obtaining snow depth values from snow-water equivalent outputs, and hourly, instead of the daily, calculations of wet bulb temperatures. Daily snow depth values will be utilized for 100-days rule that looks for at least 100 days of snow cover at a minimum of 30 cm in order for a ski resort to be viable, whereas the wet bulb temperatures below -7 oC will indicate the snowmaking capacity. The domain of analysis will be the Balkans, the Middle East and the Caucasus. Therefore the spatial gap in the mostly Euro- and Amero-centric literature will also be improved. The domain will be modelled through RegCM 4.4.2 of the International Centre for Theoretical Physics basing its resolution on MPI-ESM-MR of Max Planck Institut für Meteorologie and the concentration scenario RCP 4.5 for a realistic tourism development future of 2020-2050.

  18. A Framework for Thinking about the Spatial Variability of Snow across Multiple Scales and Climate Zones (Invited)

    Science.gov (United States)

    Sturm, M.

    2010-12-01

    It is well known that snow on the ground (or on lake and sea ice) varies at a myriad of scales ranging from millimeters to hundreds of kilometers. Many studies have focused directly, or in part, on snow heterogeneity at one or more of these scales, but a consistent broad framework within which these studies can be placed has yet to be developed. Consequently, the overall approach to scaling issues and snow variability is disjoint and inefficient. Nevertheless, strong common threads unite these issues. At the finest scale within-layer variations always arise from vapor transport and snow metamorphism. Layer properties vary based on weather during deposition and following snowfall (winter history). At plot to landscape scales, micro and macro topography and vegetation interact with wind, solar irradience, melt water percolation, and gravity to produce lateral variations in depth and snow water equivalent. At the coarsest scales, synoptic and climate gradients produce facies changes in both layers and bulk snow cover characteristics that vary in predictable ways. Here a preliminary multi-scale framework for snow variations is suggested and its utility discussed. At the largest scale, the framework uses the snow climate classification as a first discriminator. These classes are divided into wind-affected vs. non-wind-affected snow. Landscape and local variations in topography are then superimposed on these coarser-scale variations. Because vegetation varies with both climate and topography, it correlates with, as well as drives variations snow property variations; it becomes the third discriminator. Using these discriminators, similarities in snow variations and critical inherent length scales of several types of snow covers are explored.

  19. Snow density climatology across the former USSR

    Science.gov (United States)

    Zhong, X.; Zhang, T.; Wang, K.

    2014-04-01

    Snow density is one of the basic properties used to describe snow cover characteristics, and it is a key factor for linking snow depth and snow water equivalent, which are critical for water resources assessment and modeling inputs. In this study, we used long-term data from ground-based measurements to investigate snow density (bulk density) climatology and its spatiotemporal variations across the former Soviet Union (USSR) from 1966 to 2008. The results showed that the long-term monthly mean snow density was approximately 0.22 ± 0.05 g cm-3 over the study area. The maximum and minimum monthly mean snow density was about 0.33 g cm-3 in June, and 0.14 g cm-3 in October, respectively. Maritime and ephemeral snow had the highest monthly mean snow density, while taiga snow had the lowest. The higher values of monthly snow density were mainly located in the European regions of the former USSR, on the coast of Arctic Russia, and the Kamchatka Peninsula, while the lower snow density occurred in central Siberia. Significant increasing trends of snow density from September through June of the next year were observed, however, the rate of the increase varied with different snow classes. The long-term (1966-2008) monthly and annual mean snow densities had significant decreasing trends, especially during the autumn months. Spatially, significant positive trends in monthly mean snow density lay in the southwestern areas of the former USSR in November and December and gradually expanded in Russia from February through April. Significant negative trends mainly lay in the European Russia and the southern Russia. There was a high correlation of snow density with elevation for tundra snow and snow density was highly correlated with latitude for prairie snow.

  20. Snow Leopard

    Indian Academy of Sciences (India)

    Owing to their secretive nature and inaccessible habitat,little is known about its ecology and distribution. Due toits endangered status and high aesthetic value, the snow leopardis considered as an 'umbrella species' for wildlife conservationin the Indian Himalayas. This article summarizes thecurrent knowledge on snow ...

  1. Snow Leopard

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 22; Issue 7. Snow Leopard: Ecology and Conservation Issues in India. Abhishek Ghoshal. General Article Volume 22 Issue 7 July 2017 pp 677- ... Keywords. Ecology, carnivore, conservation, Himalayas, mammal, snow leopard, Panthera uncia, wildlife.

  2. SnowClim: Snow climate monitoring for Europe

    Science.gov (United States)

    Bissolli, P.; Maier, U.

    2009-09-01

    Snow cover, particularly its depth and its frequency, is a very essential climate element. It influences the earth's surface radiation budget considerably due to its reflectivity properties and also it has large impact on economy and daily life (e.g. traffic, tourism). Although a lot of research and many national activities of snow monitoring have been done, there are very few products describing an integrated snow monitoring for whole Europe. In the light of a foreseen future Regional Climate Centre on Climate Monitoring (RCC-CM), the German Meteorological Service (Deutscher Wetterdienst, DWD) has established some first operational snow climate monitoring activities for the WMO Region VI (Europe and the Middle East). First selected key elements are the number of snowdays with a snow cover > 1 cm, the mean and the maximum snow depth per month. Results are presented in form of monthly and climatological maps, tables and diagrams of time series starting in 1981. Data presently are taken from observations at synoptical stations, received by the Global Telecommunication System. A first quality control based on threshold tests has been developed. The snow climate monitoring products are currently under further development. New evaluations will be carried out also on a daily data basis, additional satellite data, and also the quality control procedure will be extended. Some operational SnowClim products are available on the DWD web site: www.dwd.de/snowclim

  3. 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.

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

    Science.gov (United States)

    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

  5. 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

  6. Inter-Calibration of Passive Microwave Satellite Brightness Temperatures Observed by F13 SSM/I and F17 SSMIS for the Retrieval of Snow Depth on Arctic First-Year Sea Ice

    Directory of Open Access Journals (Sweden)

    Qingquan Liu

    2017-12-01

    Full Text Available Passive microwave satellite brightness temperatures (TB that were observed by the F13 Special Sensor Microwave/Imager (SSM/I and the subsequent F17 Special Sensor Microwave Imager/Sounder (SSMIS were inter-calibrated using empirical relationship models during their overlap period. Snow depth (SD on the Arctic first-year sea ice was further retrieved. The SDs derived from F17 TB and F13C TB which were calibrated F17 TB using F13 TB as the baseline were then compared and evaluated against in situ SD measurements based on the Operational IceBridge (OIB airborne observations from 2009 to 2013. Results show that Cavalieri inter-calibration models (CA models perform smaller root mean square error (RMSE than Dai inter-calibration models (DA models, and the standard deviation of OIB SDs in the 25 km pixels is around 6 cm on first-year sea ice. Moreover, the SDs derived from the calibrated F17 TB using F13 TB as the baseline were in better agreement than the F17 SDs as compared with OIB SDs, with the biases of −2 cm (RMSE of 5 cm and −9 cm (RMSE of 10 cm, respectively. We conclude that TB observations from F17 SSMIS calibrated to F13 SSM/I as the baseline should be recommended when performing the sensors’ biases correction for SD purpose based on the existing algorithm. These findings could serve as a reference for generating more consistent and reliable TB, which could help to improve the retrieval and analysis of long-term snow depth on the Arctic first-year sea ice.

  7. Measurements for winter road maintenance

    OpenAIRE

    Riehm, Mats

    2012-01-01

    Winter road maintenance activities are crucial for maintaining the accessibility and traffic safety of the road network at northerly latitudes during winter. Common winter road maintenance activities include snow ploughing and the use of anti-icing agents (e.g. road salt, NaCl). Since the local weather is decisive in creating an increased risk of slippery conditions, understanding the link between local weather and conditions at the road surface is critically important. Sensors are commonly i...

  8. 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.

    Directory of Open Access Journals (Sweden)

    Françoise Martz

    Full Text Available 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.

  9. Sensitivity Analysis of Snow Cover to Climate Change Scenarios and Their Impact on Plant Habitats in Alpine Terrain

    Energy Technology Data Exchange (ETDEWEB)

    Keller, F.; Goyette, S.; Beniston, M. [Department of Geosciences, Geography, Fribourg (Switzerland)

    2005-10-01

    In high altitude areas snow cover duration largely determines the length of the growing season of the vegetation. A sensitivity study of snow cover to various scenarios of temperature and precipitation has been conducted to assess how snow cover and vegetation may respond for a very localized area of the high Swiss Alps (2050-2500 m above sea level). A surface energy balance model has been upgraded to compute snow depth and duration, taking into account solar radiation geometry over complex topography. Plant habitat zones have been defined and 23 species, whose photoperiodic preferences were documented in an earlier study, were grouped into each zone. The sensitivity of snowmelt to a change in mean, minimum and maximum temperature alone and a change in mean temperature combined with a precipitation change of +10% in winter and -10% in summer is investigated. A seasonal increase in the mean temperature of 3 to 5 K reduces snow cover depth and duration by more than a month on average. Snow melts two months earlier in the rock habitat zone with the mean temperature scenario than under current climate conditions. This allows the species in this habitat to flower earlier in a warmer climate, but not all plants are able to adapt to such changes.

  10. 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

  11. 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...

  12. Snow clearance

    CERN Multimedia

    Mauro Nonis

    2005-01-01

    In reply to the numerous questions received, we should like to inform you of the actions and measures taken in an effort to maintain the movements of vehicles and pedestrians since the heavy snow fall on Sunday 23 January. Our contractor's employees began clearing the snow during the morning of Sunday 23 January on the main CERN sites (Meyrin, Prévessin), but an accident prevented them from continuing. The vehicle in question was repaired by Monday morning when two other vehicles joined it to resume snow clearing; priority was given to access points to the main sites and the LHC sites, as well as to the main roads inside the sites. The salt sprinklers were also brought into action that same day; the very low temperature during the night from Monday to Tuesday prevented the snow from melting and compacted the ice; the continuing cold during the day on Tuesday (-6°C at 10:00 on the Meyrin site) meant that all efforts to remove the ice were doomed to failure. In order to ensure more efficie...

  13. Snow Matters

    DEFF Research Database (Denmark)

    Gyimóthy, Szilvia; Jensen, Martin Trandberg

    2018-01-01

    attribute of high altitude mountain destinations. Hitherto, researchers mostly engaged with snowclad landscapes as a backstage; trying to deconstruct the complex symbolism and representational qualities of this elusive substance. Despite snow being a strategically crucial condition for tourism in the Alps...

  14. Snow Leopard

    Indian Academy of Sciences (India)

    around the same time in Kinnaur district. Studies on snow leop- ard habitats over the past two decades show that the economy of the region has rapidly shifted from traditional agro-pastoralism to market-driven agriculture. Consequently, human population growth, agricultural expanse, and excessive livestock grazing (Fig-.

  15. 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

  16. A triple-moment blowing snow-atmospheric model and its application in computing the seasonal wintertime snow mass budget

    Directory of Open Access Journals (Sweden)

    J. Yang

    2010-06-01

    Full Text Available Many field studies have shown that surface sublimation and blowing snow transport and sublimation have significant influences on the snow mass budget in many high latitude regions. We developed a coupled triple-moment blowing snow-atmospheric modeling system to study the influence of these processes on a seasonal time scale over the Northern Hemisphere. Two simulations were performed. The first is a 5 month simulation for comparison with snow survey measurements over a Saskatchewan site to validate the modeling system. The second simulation covers the 2006/2007 winter period to study the snow mass budget over the Northern Hemisphere. The results show that surface sublimation is significant in Eurasian Continent and the eastern region of North America, reaching a maximum value of 200 mm SWE (Snow Water Equivalent. Over the Arctic Ocean and Northern Canada, surface deposition with an average value of 30 mm SWE was simulated. Blowing snow sublimation was found to return up to 50 mm SWE back to the atmosphere over the Arctic Ocean, while the divergence of blowing snow transport contributes only a few mm SWE to the change in snow mass budget. The results were further stratified in 10 degree latitudinal bands. The results show that surface sublimation decreases with an increase in latitude while blowing snow sublimation increases with latitude. Taken together, the surface sublimation and blowing snow processes was found to distribute 23% to 52% of winter precipitation over the three month winter season.

  17. 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.

  18. Using tube rhizotrons to measure variation in depth penetration rate among modern North-European winter wheat (Triticum aestivum L.) cultivars

    DEFF Research Database (Denmark)

    Ytting, Nanna Karkov; Andersen, Sven Bode; Thorup-Kristensen, Kristian

    2014-01-01

    Deeper plant root systems are desired for improved water and nitrogen uptake in leaching environments. However, phenotyping for deep roots requires methods that enable plants to develop deep roots under realistic conditions. Winter cereals raise further complications as early growth occurs under ...

  19. 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.

  20. Sensing winter soil respiration dynamics in near-real time

    Science.gov (United States)

    Contosta, A.; Burakowski, E. A.; Varner, R. K.; Frey, S. D.

    2014-12-01

    Some of the largest reductions in seasonal snow cover are projected to occur in temperate latitudes. Limited measurements from these ecosystems indicate that winter soil respiration releases as much as 30% of carbon fixed during the previous growing season. This respiration is possible with a snowpack that insulates soil from ambient fluctuations in climate. However, relationships among snowpack, soil temperature, soil moisture, and winter soil respiration in temperate regions are not well-understood. Most studies have infrequently sampled soil respiration and its drivers, and most measurements have been limited to the soil surface. We made near-real time, continuous measurements of temperature, moisture, and CO2 fluxes from the soil profile, through the snowpack, and into the atmosphere in a deciduous forest of New Hampshire, USA. We coupled these data with daily sampling of snow depth and snow water equivalent (SWE). Our objectives were to continuously measure soil CO2 production (Psoil) and CO2 flux through the snowpack (Fsnow) and to compare Fsnow and Psoil with environmental drivers. We found that Fsnow was more dynamic than Psoil, changing as much as 30% over several days with shifting environmental conditions. Multiple regression indicated that SWE, air temperature, surface soil temperature, surface soil CO2 concentrations, and soil moisture at 15 cm were significant predictors of Fsnow. The transition of surface temperature from below to above 0°C was particularly important as it represented a phase change from ice to liquid water. Only air temperature and soil moisture at 15 cm were significant drivers of Psoil, where higher moisture at 15 cm resulted in lower Psoil rates. Time series analysis showed that Fsnow lagged 40 days behind Psoil. This lag may be due to slow CO2 diffusion through soil to overlying snow under high moisture conditions. Our results suggest that surface soil CO2 losses are driven by rapid changes in snow cover, surface temperature

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Validation of the operational MSG-SEVIRI snow cover product over Austria

    Science.gov (United States)

    Surer, S.; Parajka, J.; Akyurek, Z.

    2014-02-01

    The objective of this study is to evaluate the mapping accuracy of the MSG-SEVIRI operational snow cover product over Austria. The SEVIRI instrument is aboard the geostationary Meteosat Second Generation (MSG) satellite. The snow cover product provides 32 images per day, with a relatively low spatial resolution of 5 km over Austria. The mapping accuracy is examined at 178 stations with daily snow depth observations and compared with the daily MODIS-combined (Terra + Aqua) snow cover product for the period April 2008-June 2012. The results show that the 15 min temporal sampling allows a significant reduction of clouds in the snow cover product. The mean annual cloud coverage is less than 30% in Austria, as compared to 52% for the combined MODIS product. The mapping accuracy for cloud-free days is 89% as compared to 94% for MODIS. The largest mapping errors are found in regions with large topographical variability. The errors are noticeably larger at stations with elevations that differ greatly from those of the mean MSG-SEVIRI pixel elevations. The median of mapping accuracy for stations with absolute elevation difference less than 50 m and more than 500 m is 98.9 and 78.2%, respectively. A comparison between the MSG-SEVIRI and MODIS products indicates an 83% overall agreement. The largest disagreements are found in Alpine valleys and flatland areas in the spring and winter months, respectively.

  3. 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.

  4. 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.

  5. Arctic moisture source for Eurasian snow cover variations in autumn

    Science.gov (United States)

    Wegmann, Martin; Orsolini, Yvan; Vázquez Dominguez, Marta; Gimeno Presa, Luis; Nieto, Raquel; Buligyna, Olga; Jaiser, Ralf; Handorf, Dörthe; Rinke, Anette; Dethloff, Klaus; Sterin, Alexander; Brönnimann, Stefan

    2015-04-01

    Global warming is enhanced at high northern latitudes where the Arctic surface air temperature has risen at twice the rate of the global average in recent decades - a feature called Arctic amplification. This recent Arctic warming signal likely results from several factors such as the albedo feedback due to a diminishing cryosphere, enhanced poleward atmospheric and oceanic transport, and change in humidity. The reduction in Arctic sea ice is without doubt substantial and a key factor. Arctic summer sea-ice extent has declined by more than 10% per decade since the start of the satellite era (e.g. Stroeve et al., 2012), culminating in a new record low in September 2012, with the long-term trend largely attributed to anthropogenic global warming. Eurasian snow cover changes have been suggested as a driver for changes in the Arctic Oscillation and might provide a link between sea ice decline in the Arctic during summer and atmospheric circulation in the following winter. However, the mechanism connecting snow cover in Eurasia to sea ice decline in autumn is still under debate. Our analysis focuses at sea ice decline in the Barents-Kara Sea region, which allows us to specify regions of interest for FLEXPART forward and backwards moisture trajectories. Based on Eularian and Lagrangian diagnostics from ERA-INTERIM, we can address the origin and cause of late autumn snow depth variations in a dense (snow observations from 820 land stations), unutilized observational datasets over the Commonwealth of Independent States. Open waters in the Barents and Kara Sea have been shown to increase the diabatic heating of the atmosphere, which amplifies baroclinic cyclones and might induce a remote atmospheric response by triggering stationary Rossby waves (Honda et al. 2009). In agreement with these studies, our results show enhanced storm activity originating at the Barents and Kara with disturbances entering the continent through a small sector from the Barents and Kara Seas

  6. 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...

  7. Relationships between climate and winter cereal grain quality in Finland and their potential for forecasting

    Directory of Open Access Journals (Sweden)

    P. D. HOLLINS

    2008-12-01

    Full Text Available Many studies have demonstrated the effects of climate on cereal yield, but there has been little work carried out examining the relationships between climate and cereal grain quality on a national scale. In this study national mean hectolitre weight for both rye and winter wheat in Finland was modelled using monthly gridded accumulated snow depth, precipitation rate, solar radiation and temperature over the period 1971 to 2001. Variables with significant relationships in correlation analysis both before and after difference detrending were further investigated using forward stepwise regression. For rye, March snow depth, and June and July solar radiation accounted for 66% of the year-to-year variance in hectolitre weight, and for winter wheat January snow depth, June solar radiation and August temperature accounted for 62% of the interannual variance in hectolitre weight. Further analysis of national variety trials and weather station data was used to support proposed biological mechanisms. Finally a cross validation technique was used to test forecast models with those variables available by early July by making predictions of above or below the mean hectolitre weight. Analysis of the contingency tables for these predictions indicated that national hectolitre weight forecasts are feasible for both cereals in advance of harvest.;

  8. Historical Soviet Daily Snow Depth (HSDSD)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The HSDSD product is based on observations from 284 World Meteorological Organization (WMO) stations throughout Russia and the former Soviet Union. The area covered...

  9. Historical Soviet Daily Snow Depth (HSDSD)

    Data.gov (United States)

    National Aeronautics and Space Administration — The HSDSD product is based on observations from 284 World Meteorological Organization (WMO) stations throughout Russia and the former Soviet Union. The area covered...

  10. 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.

  11. Building a Cloud-based Global Snow Observatory

    Science.gov (United States)

    Li, X.; Coll, J. M.

    2016-12-01

    Snow covers some 40 percent of Earth's land masses year in and year out and constitutes a vitally important variable for the planet's climate, hydrology, and biosphere due to its high albedo and insulation. It affects atmospheric circulation patterns, permafrost, glacier mass balance, river discharge, and groundwater recharge (Dietz et al. 2015). Snow is also nature's igloo where species from microscopic fungi to 800-pound moose survive the winter each in its own way (Pauli et al. 2013; Petty et al. 2015). Many studies have found that snow in high elevation regions is particularly sensitive to global climate change and is considered as sentinel of change. For human beings, about one-sixth of the world's population depends on seasonal snow and glaciers for their water supply (Barnett et al. 2005) and more than 50% of mountainous areas have an essential or supportive role for downstream regions (Viviroli et al. 2007). Large snowstorms also have a major impact on society in terms of human life, economic loss, and disruption (Squires et al. 2014). Remote sensing provides a practical approach of monitoring global snow and ice cover change. Based on our comprehensive validation and assessment on MODIS snow products, we build a cloud-based Global Snow Observatory (GSO) using Google Earth Engine (GEE) to serve as a platform for global researchers and the general public to access, visualize, and analyze snow data and to build snowmelt runoff models for mountain watersheds. Specifically, we build the GSO to serve global MODIS daily snow cover data and their analyses through GEE on Google App Engine. The GSO provides users the functions of accessing and extracting cloud-gap-filled snow data and interactive snow cover change exploration. In addition to snow cover frequency (SCF), we also plan to develop several other snow cover parameters, including snow cover duration/days, snow cover onset dates, and snow cover melting dates, and to study the shift and trend of global snow

  12. Winter and spring mixing depths affect the trophic status and composition of phytoplankton in the northern meromictic basin of Lake Lugano

    Directory of Open Access Journals (Sweden)

    Marco SIMONA

    2003-08-01

    Full Text Available The trophic state of Lake Lugano is still too high to be acceptable, despite extensive recovery measures undertaken in recent decades which have resulted in a reduction of the external phosphorus load to the deepest of the lake's basins (northern basin; Zmax=286 m to fairly acceptable values. Since meromixis was established in the middle of last century, the deep hypolimnion of the northern basin (the layer between ca 100 m and the bottom has contained high quantities of nutrients (especially phosphorus which are a major potential source of internal load. When there are particularly strong winter mixing events, a portion of this phosphorus reserve is redistributed along the upper water column (0-100 m. The impact of meteo-climatic conditions on the plankton biocenosis were analysed using data collected in the northern basin (Gandria station during the three-year period 1998-2000. The phytoplankton composition, which is typical of eutrophicated waters, shows marked interannual variations, also depending on the degree of mixing of the waters at the start of the vegetative period. Though there is no steady pattern of typical dominant species / master species in the lake, there is a seasonal succession characterised by a marked development of diatoms in spring, and a predominance of chlorophyceans and cyanobacteria in summer and autumn. Under present conditions, the mechanisms of internal replenishment of nutrients towards the euphotic layer, due to the phenomena of late winter and spring mixing, constitute a significant source of nutrients for the spring and summer growth of phytoplankton. On the other hand, pronounced mixing phenomena, like those occurring in the two-year period 1999-2000, can reduce the hypolimnetic nutrient reserves and cause a decrease in the trophic potential of the basin, contrasting with an increase in algal biomass in the euphotic zone.

  13. Snow and Vegetation Interactions at Boundaries in Alaska's Boreal Forest

    Science.gov (United States)

    Hiemstra, C. A.; Sturm, M.

    2012-12-01

    There has been increased attention on snow-vegetation interactions in Arctic tundra because of rapid climate-driven changes affecting that snow-dominated ecosystem. Yet, far less attention is paid to boreal forest snow-vegetation interactions even though climatic conditions are changing there as well. Further, it is the prevalent terrestrial biome on the planet. The forest is a variable patchwork of trees, shrubs, grasses, and forbs shaped by wind, fire, topography, water drainage, and permafrost. These patches and their boundaries have a corresponding effect on boreal snow distributions; however, measurements characterizing boreal snow are sparse and focus within patches (vs. between patches). Unfortunately, remote sensing approaches in such forested areas frequently fall short due to coarse footprint size and dense canopy cover. Over the last several years we have been examining the characteristics of snow cover within and across boundaries in the boreal forest, seeking to identify gradients in snow depth due to snow-vegetation interactions as well identifying methods whereby boreal forest surveys could be improved. Specifically, we collected end-of-season snow measurements in the Alaska boreal forest during long-distance traverses in the Tanana Basin in 2010 (26 sites) and within the Yukon Flats National Wildlife Refuge in 2011 (26 sites). At each site (all relatively flat), hundreds of snow depths were collected using a GPS-equipped Magnaprobe, which is an automated tool for measuring and locating individual snow depths. Corresponding canopy properties included NDVI determined from high-resolution satellite imagery; canopy properties were variable among the 1ha sites and some areas had recently burned. Among sites, NDVI had the largest correlation with snow depths; elevation was not significant. Vegetation transition zones play important roles in explaining observed snow depth. Similar to treeline work showing nutrient and energy gradients are influenced by

  14. ALBEDO MODELS FOR SNOW AND ICE ON A FRESHWATER LAKE. (R824801)

    Science.gov (United States)

    AbstractSnow and ice albedo measurements were taken over a freshwater lake in Minnesota for three months during the winter of 1996¯1997 for use in a winter lake water quality model. The mean albedo of new snow was measured as 0.83±0.028, while the...

  15. Snow and ice control at extreme temperatures.

    Science.gov (United States)

    2011-04-25

    As expected, most state and provincial DOTs that we spoke with are using traditional methods to prevent and : remove snow and ice at very low temperatures. In addition to a review of current research, we spoke with six winter : maintenance profession...

  16. 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...

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. 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

  2. Andes Mountain Snow Distribution, Properties, and Trend: 1979-2014

    Science.gov (United States)

    Mernild, Sebastian H.; Liston, Glen E.; Hiemstra, Christopher A.

    2015-04-01

    Andes snow presence, absence, properties, and water amount are key components of Earth's changing climate system that incur far-reaching physical ramifications. Modeling developments permit relatively high-resolution (4-km horizontal grid; 3-h time step) Andes snow estimates for 1979-2014. SnowModel, in conjunction with land cover, topography, and 35-years of NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) atmospheric reanalysis data, was used to create a spatially distributed, time-evolving, snow-related dataset that included air temperature, snow precipitation, snow-season timing and length, maximum snow water equivalent depth, and average snow density. Regional variability is a dominant feature of the modeled snow-property trends from an area northeast of Quito (latitude: 2.65°S to 0.23°N) to Patagonia (latitude: 52.15°S to 46.44°S). For example, the Quito area annual snow cover area changed -45%, -43% around Cusco (latitude: 14.75°S to 12.52°S), -5% east of Santiago (including the Olivares Basin), and 25% in Patagonia. The annual snow covered area for the entire Andes decreased 13%, mainly in the elevation band between 4,000-5,000 m a.s.l. In spite of strong regional variability, the data clearly show a general positive trend in mean annual air temperature and precipitation, and a decreasing trend in snow precipitation, snow precipitation days, and snow density. Also, the snow-cover onset is later and the snow-cover duration - the number of snow cover days - decreased.

  3. Snow Data Assimilation System (SNODAS) Data Products at NSIDC, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains snow pack properties, such as depth and snow water equivalent (SWE), from the NOAA National Weather Service's National Operational Hydrologic...

  4. Winter Weather

    Science.gov (United States)

    ... Education Centers Harwood Training Grants Videos E-Tools Winter Storms Plan. Equip. Train To prevent injuries, illnesses and Fatalities during winter storms. This page requires that javascript be enabled ...

  5. ESA GlobSnow Snow Water Equivalent (SWE)

    Data.gov (United States)

    National Aeronautics and Space Administration — The European Space Agency (ESA) Global Snow Monitoring for Climate Research (GlobSnow) snow water equivalent (SWE) v2.0 data record contains snow information derived...

  6. Winter MVC

    OpenAIRE

    Castellón Gadea, Pasqual

    2013-01-01

    Winter MVC és un framework de presentació basat en Spring MVC que simplifica la metodologia de configuracions. Winter MVC es un framework de presentación basado en Spring MVC que simplifica la metodología de configuraciones. Winter MVC is a presentation framework that simplifies Spring MVC configuration methodology.

  7. The surface energy balance of a polygonal tundra site in northern Siberia – Part 2: Winter

    Directory of Open Access Journals (Sweden)

    J. Boike

    2011-06-01

    Full Text Available In this study, we present the winter time surface energy balance at a polygonal tundra site in northern Siberia based on independent measurements of the net radiation, the sensible heat flux and the ground heat flux from two winter seasons. The latent heat flux is inferred from measurements of the atmospheric turbulence characteristics and a model approach. The long-wave radiation is found to be the dominant factor in the surface energy balance. The radiative losses are balanced to about 60 % by the ground heat flux and almost 40 % by the sensible heat fluxes, whereas the contribution of the latent heat flux is small. The main controlling factors of the surface energy budget are the snow cover, the cloudiness and the soil temperature gradient. Large spatial differences in the surface energy balance are observed between tundra soils and a small pond. The ground heat flux released at a freezing pond is by a factor of two higher compared to the freezing soil, whereas large differences in net radiation between the pond and soil are only observed at the end of the winter period. Differences in the surface energy balance between the two winter seasons are found to be related to differences in snow depth and cloud cover which strongly affect the temperature evolution and the freeze-up at the investigated pond.

  8. 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.

  9. 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

  10. 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

  11. Snow instability patterns at the scale of a small basin

    Science.gov (United States)

    Reuter, Benjamin; Richter, Bettina; Schweizer, Jürg

    2016-02-01

    Spatial and temporal variations are inherent characteristics of the alpine snow cover. Spatial heterogeneity is supposed to control the avalanche release probability by either hindering extensive crack propagation or facilitating localized failure initiation. Though a link between spatial snow instability variations and meteorological forcing is anticipated, it has not been quantitatively shown yet. We recorded snow penetration resistance profiles with the snow micropenetrometer at an alpine field site during five field campaigns in Eastern Switzerland. For each of about 150 vertical profiles sampled per day a failure initiation criterion and the critical crack length were calculated. For both criteria we analyzed their spatial structure and predicted snow instability in the basin by external drift kriging. The regression models were based on terrain and snow depth data. Slope aspect was the most prominent driver, but significant covariates varied depending on the situation. Residual autocorrelation ranges were shorter than the ones of the terrain suggesting external influences possibly due to meteorological forcing. To explore the causes of the instability patterns we repeated the geostatistical analysis with snow cover model output as covariate data for one case. The observed variations of snow instability were related to variations in slab layer properties which were caused by preferential deposition of precipitation and differences in energy input at the snow surface during the formation period of the slab layers. Our results suggest that 3-D snow cover modeling allows reproducing some of the snow property variations related to snow instability, but in future work all relevant micrometeorological spatial interactions should be considered.

  12. 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.

  13. 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.

  14. 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

  15. Modelling the snow distribution at two high arctic sites at Svalbard, Norway, and at an alpine site in central Norway

    NARCIS (Netherlands)

    Bruland, Oddbjørn; Liston, Glen E.; Vonk, Jorien; Sand, Knut; Killingtveit, Anund

    2004-01-01

    In Arctic regions snow cover has a major influence on the environment both in a hydrological and ecological context. Due to strong winds and open terrain the snow is heavily redistributed and the snow depth is quite variable. This has a significant influence on the snow cover depletion and the

  16. 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 Impact factor: 0.759, year: 2016

  17. 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

  18. Modelling of snow exceedances

    Science.gov (United States)

    Jordanova, Pavlina K.; Sadovský, Zoltán; Stehlík, Milan

    2017-07-01

    Modelling of snow exceedances is of great importance and interest for ecology, civil engineering and general public. We suggest the favorable fit for exceedances related to the exceptional snow loads from Slovakia, assuming that the data is driven by Generalised Pareto Distribution or Generalized Extreme Value Distribution. Further, the statistical dependence between the maximal snow loads and the corresponding altitudes is studied.

  19. Snow snake performance monitoring.

    Science.gov (United States)

    2008-12-01

    A recent study, Three-Dimensional Roughness Elements for Snow Retention (FHWA-WY-06/04F) (Tabler 2006), demonstrated : positive evidence for the effectiveness of Snow Snakes, a new type of snow fence suitable for use within the highway right-of...

  20. Drought and Snow: Analysis of Drivers, Processes and Impacts of Streamflow Droughts in Snow-Dominated Regions

    Science.gov (United States)

    Van Loon, Anne; Laaha, Gregor; Van Lanen, Henny; Parajka, Juraj; Fleig, Anne; Ploum, Stefan

    2016-04-01

    Around the world, drought events with severe socio-economic impacts seem to have a link with winter snowpack. That is the case for the current California drought, but analysing historical archives and drought impact databases for the US and Europe we found many impacts that can be attributed to snowpack anomalies. Agriculture and electricity production (hydropower) were found to be the sectors that are most affected by drought related to snow. In this study, we investigated the processes underlying hydrological drought in snow-dominated regions. We found that drought drivers are different in different regions. In Norway, more than 90% of spring streamflow droughts were preceded by below-average winter precipitation, while both winter air temperature and spring weather were indifferent. In Austria, however, spring streamflow droughts could only be explained by a combination of factors. For most events, winter and spring air temperatures were above average (70% and 65% of events, respectively), and winter and spring precipitation was below average (75% and 80%). Because snow storage results from complex interactions between precipitation and temperature and these variables vary strongly with altitude, snow-related drought drivers have a large spatial variability. The weather input is subsequently modified by land properties. Multiple linear regression between drought severity variables and a large number of catchment characteristics for 44 catchments in Austria showed that storage influences both drought duration and deficit volume. The seasonal storage of water in snow and glaciers was found to be a statistically important variable explaining streamflow drought deficit. Our drought impact analysis in Europe also showed that 40% of the selected drought impacts was caused by a combination of snow-related and other drought types. For example, the combination of a winter drought with a preceding or subsequent summer drought was reported to have a large effect on

  1. 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

  2. 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.

  3. 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

  4. Snow measurement system for airborne snow surveys (GPR system from helicopter) in high mountian areas.

    Science.gov (United States)

    Sorteberg, Hilleborg K.

    2010-05-01

    In the hydropower industry, it is important to have precise information about snow deposits at all times, to allow for effective planning and optimal use of the water. In Norway, it is common to measure snow density using a manual method, i.e. the depth and weight of the snow is measured. In recent years, radar measurements have been taken from snowmobiles; however, few energy supply companies use this method operatively - it has mostly been used in connection with research projects. Agder Energi is the first Norwegian power producer in using radar tecnology from helicopter in monitoring mountain snow levels. Measurement accuracy is crucial when obtaining input data for snow reservoir estimates. Radar screening by helicopter makes remote areas more easily accessible and provides larger quantities of data than traditional ground level measurement methods. In order to draw up a snow survey system, it is assumed as a basis that the snow distribution is influenced by vegetation, climate and topography. In order to take these factors into consideration, a snow survey system for fields in high mountain areas has been designed in which the data collection is carried out by following the lines of a grid system. The lines of this grid system is placed in order to effectively capture the distribution of elevation, x-coordinates, y-coordinates, aspect, slope and curvature in the field. Variation in climatic conditions are also captured better when using a grid, and dominant weather patterns will largely be captured in this measurement system.

  5. Satellite Snow-Cover Mapping: A Brief Review

    Science.gov (United States)

    Hall, Dorothy K.

    1995-01-01

    Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow

  6. 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

  7. Assessment of Northern Hemisphere Snow Water Equivalent Datasets in ESA SnowPEx project

    Science.gov (United States)

    Luojus, Kari; Pulliainen, Jouni; Cohen, Juval; Ikonen, Jaakko; Derksen, Chris; Mudryk, Lawrence; Nagler, Thomas; Bojkov, Bojan

    2016-04-01

    Reliable information on snow cover across the Northern Hemisphere and Arctic and sub-Arctic regions is needed for climate monitoring, for understanding the Arctic climate system, and for the evaluation of the role of snow cover and its feedback in climate models. In addition to being of significant interest for climatological investigations, reliable information on snow cover is of high value for the purpose of hydrological forecasting and numerical weather prediction. Terrestrial snow covers up to 50 million km² of the Northern Hemisphere in winter and is characterized by high spatial and temporal variability. Therefore satellite observations provide the best means for timely and complete observations of the global snow cover. There are a number of independent SWE products available that describe the snow conditions on multi-decadal and global scales. Some products are derived using satellite-based information while others rely on meteorological observations and modelling. What is common to practically all the existing hemispheric SWE products, is that their retrieval performance on hemispherical and multi-decadal scales are not accurately known. The purpose of the ESA funded SnowPEx project is to obtain a quantitative understanding of the uncertainty in satellite- as well as model-based SWE products through an internationally coordinated and consistent evaluation exercise. The currently available Northern Hemisphere wide satellite-based SWE datasets which were assessed include 1) the GlobSnow SWE, 2) the NASA Standard SWE, 3) NASA prototype and 4) NSIDC-SSM/I SWE products. The model-based datasets include: 5) the Global Land Data Assimilation System Version 2 (GLDAS-2) product 6) the European Centre for Medium-Range Forecasts Interim Land Reanalysis (ERA-I-Land) which uses a simple snow scheme 7) the Modern Era Retrospective Analysis for Research and Applications (MERRA) which uses an intermediate complexity snow scheme; and 8) SWE from the Crocus snow scheme, a

  8. Improving Snow Modeling by Assimilating Observational Data Collected by Citizen Scientists

    Science.gov (United States)

    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

  9. COSMO-SkyMed Image Investigation of Snow Features in Alpine Environment

    Directory of Open Access Journals (Sweden)

    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.

  10. Snow observations in Mount Lebanon (2011–2016

    Directory of Open Access Journals (Sweden)

    A. Fayad

    2017-08-01

    Full Text Available 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

  11. Observations of atmospheric chemical deposition to high Arctic snow

    Science.gov (United States)

    Macdonald, Katrina M.; Sharma, Sangeeta; Toom, Desiree; Chivulescu, Alina; Hanna, Sarah; Bertram, Allan K.; Platt, Andrew; Elsasser, Mike; Huang, Lin; Tarasick, David; Chellman, Nathan; McConnell, Joseph R.; Bozem, Heiko; Kunkel, Daniel; Duan Lei, Ying; Evans, Greg J.; Abbatt, Jonathan P. D.

    2017-05-01

    Rapidly rising temperatures and loss of snow and ice cover have demonstrated the unique vulnerability of the high Arctic to climate change. There are major uncertainties in modelling the chemical depositional and scavenging processes of Arctic snow. To that end, fresh snow samples collected on average every 4 days at Alert, Nunavut, from September 2014 to June 2015 were analyzed for black carbon, major ions, and metals, and their concentrations and fluxes were reported. Comparison with simultaneous measurements of atmospheric aerosol mass loadings yields effective deposition velocities that encompass all processes by which the atmospheric species are transferred to the snow. It is inferred from these values that dry deposition is the dominant removal mechanism for several compounds over the winter while wet deposition increased in importance in the fall and spring, possibly due to enhanced scavenging by mixed-phase clouds. Black carbon aerosol was the least efficiently deposited species to the snow.

  12. The Infrared Sensor Suite for SnowEx 2017

    Science.gov (United States)

    Hall, D. K.; Chickadel, C. C.; Crawford, C. J.; DeMarco, E. L.; Jennings, D. E.; Jhabvala, M. D.; Kim, E. J.; Lundquist, J. D.; Lunsford, A. W.

    2017-01-01

    SnowEx is a winter airborne and field campaign designed to measure snow-water equivalent in forested landscapes. A major focus of Year 1 (2016-17) of NASA's SnowEx campaign will be an extensive field program involving dozens of participants from U.S. government agencies and from many universities and institutions, both domestic and foreign. Along with other instruments, two infrared (IR) sensors will be flown on a Naval Research Laboratory P-3 aircraft. Surface temperature is a critical input to hydrologic models and will be measured during the SnowEx mission. A Quantum Well Infrared Photodetector (QWIP) IR imaging camera system will be flown along with a KT-15 remote thermometer to aid in the calibration of the IR image data. Together, these instruments will measure surface temperature of snow and ice targets to an expected accuracy of less than 1C.

  13. 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, ...

  14. A Comparison of Sea Ice Type, Sea Ice Temperature, and Snow Thickness Distributions in the Arctic Seasonal Ice Zones with the DMSP SSM/I

    Science.gov (United States)

    St.Germain, Karen; Cavalieri, Donald J.; Markus, Thorsten

    1997-01-01

    Global climate studies have shown that sea ice is a critical component in the global climate system through its effect on the ocean and atmosphere, and on the earth's radiation balance. Polar energy studies have further shown that the distribution of thin ice and open water largely controls the distribution of surface heat exchange between the ocean and atmosphere within the winter Arctic ice pack. The thickness of the ice, the depth of snow on the ice, and the temperature profile of the snow/ice composite are all important parameters in calculating surface heat fluxes. In recent years, researchers have used various combinations of DMSP SSMI channels to independently estimate the thin ice type (which is related to ice thickness), the thin ice temperature, and the depth of snow on the ice. In each case validation efforts provided encouraging results, but taken individually each algorithm gives only one piece of the information necessary to compute the energy fluxes through the ice and snow. In this paper we present a comparison of the results from each of these algorithms to provide a more comprehensive picture of the seasonal ice zone using passive microwave observations.

  15. 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.

  16. Basic Snow Pressure Calculation

    Science.gov (United States)

    Hao, Shouzhi; Su, Jian

    2018-03-01

    As extreme weather rising in recent years, the damage of large steel structures caused by weather is frequent in China. How to consider the effect of wind and snow loads on the structure in structural design has become the focus of attention in engineering field. In this paper, based on the serious snow disasters in recent years and comparative analysis of some scholars, influence factors and the value of the snow load, the probability model are described.

  17. The Alaska Lake Ice and Snow Observatory Network (ALISON): Hands-on Experiential K- 12 Learning in the North

    Science.gov (United States)

    Morris, K.; Jeffries, M.

    2008-12-01

    The Alaska Lake Ice and Snow Observatory Network (ALISON) was initiated by Martin Jeffries (UAF polar scientist), Delena Norris-Tull (UAF education professor) and Ron Reihl (middle school science teacher, Fairbanks North Star Borough School District). The snow and ice measurement protocols were developed in 1999-2000 at the Poker Flat Research Range (PFRR) by Geophysical Institute, University of Alaska scientists and tested by home school teacher/students in winter 2001-2002 in Fairbanks, AK. The project was launched in 2002 with seven sites around the state (PFRR, Fairbanks, Barrow, Mystic Lake, Nome, Shageluk and Wasilla). The project reached its broadest distribution in 2005-2006 with 22 sites. The schools range from urban (Wasilla) to primarily Alaska native villages (Shageluk). They include public schools, charter schools, home schooled students and parents, informal educators and citizen scientists. The grade levels range from upper elementary to high school. Well over a thousand students have participated in ALISON since its inception. Equipment is provided to the observers at each site. Measurements include ice thickness (with a hot wire ice thickness gauge), snow depth and snow temperature (surface and base). Snow samples are taken and snow density derived. Snow variables are used to calculate the conductive heat flux through the ice and snow cover to the atmosphere. All data are available on the Web site. The students and teachers are scientific partners in the study of lake ice processes, contributing to new scientific knowledge and understanding while also learning science by doing science with familiar and abundant materials. Each autumn, scientists visit each location to work with the teachers and students, helping them to set up the study site, showing them how to make the measurements and enter the data into the computer, and discussing snow, ice and polar environmental change. A number of 'veteran' teachers are now setting up the study sites on

  18. Monitoring and projecting snow on Hawaii Island

    Science.gov (United States)

    Zhang, Chunxi; Hamilton, Kevin; Wang, Yuqing

    2017-05-01

    The highest mountain peaks on Hawaii Island are snow covered for part of almost every year. This snow has aesthetic and recreational value as well as cultural significance for residents and visitors. Thus far there have been almost no systematic observations of snowfall, snow cover, or snow depth in Hawaii. Here we use satellite observations to construct a daily index of Hawaii Island snow cover starting from 2000. The seasonal mean of our index displays large interannual variations that are correlated with the seasonal mean freezing level and frequency of trade wind inversions as determined from nearby balloon soundings. Our snow cover index provides a diagnostic for monitoring climate variability and trends within the extensive area of the globe dominated by the North Pacific trade wind meteorological regime. We have also conducted simulations of the Hawaii climate with a regional atmospheric model. Retrospective simulations for 1990-2015 were run with boundary conditions prescribed from gridded observational analyses. Simulations for the end of 21st century employed boundary conditions based on global climate model projections that included standard scenarios for anticipated anthropogenic climate forcing. The future projections indicate that snowfall will nearly disappear by the end of the current century.

  19. Blowing snow detection from ground-based ceilometers: application to East Antarctica

    Science.gov (United States)

    Gossart, Alexandra; Souverijns, Niels; Gorodetskaya, Irina V.; Lhermitte, Stef; Lenaerts, Jan T. M.; Schween, Jan H.; Mangold, Alexander; Laffineur, Quentin; van Lipzig, Nicole P. M.

    2017-12-01

    Blowing snow impacts Antarctic ice sheet surface mass balance by snow redistribution and sublimation. However, numerical models poorly represent blowing snow processes, while direct observations are limited in space and time. Satellite retrieval of blowing snow is hindered by clouds and only the strongest events are considered. Here, we develop a blowing snow detection (BSD) algorithm for ground-based remote-sensing ceilometers in polar regions and apply it to ceilometers at Neumayer III and Princess Elisabeth (PE) stations, East Antarctica. The algorithm is able to detect (heavy) blowing snow layers reaching 30 m height. Results show that 78 % of the detected events are in agreement with visual observations at Neumayer III station. The BSD algorithm detects heavy blowing snow 36 % of the time at Neumayer (2011-2015) and 13 % at PE station (2010-2016). Blowing snow occurrence peaks during the austral winter and shows around 5 % interannual variability. The BSD algorithm is capable of detecting blowing snow both lifted from the ground and occurring during precipitation, which is an added value since results indicate that 92 % of the blowing snow is during synoptic events, often combined with precipitation. Analysis of atmospheric meteorological variables shows that blowing snow occurrence strongly depends on fresh snow availability in addition to wind speed. This finding challenges the commonly used parametrizations, where the threshold for snow particles to be lifted is a function of wind speed only. Blowing snow occurs predominantly during storms and overcast conditions, shortly after precipitation events, and can reach up to 1300 m a. g. l. in the case of heavy mixed events (precipitation and blowing snow together). These results suggest that synoptic conditions play an important role in generating blowing snow events and that fresh snow availability should be considered in determining the blowing snow onset.

  20. Blowing snow detection from ground-based ceilometers: application to East Antarctica

    Directory of Open Access Journals (Sweden)

    A. Gossart

    2017-12-01

    Full Text Available Blowing snow impacts Antarctic ice sheet surface mass balance by snow redistribution and sublimation. However, numerical models poorly represent blowing snow processes, while direct observations are limited in space and time. Satellite retrieval of blowing snow is hindered by clouds and only the strongest events are considered. Here, we develop a blowing snow detection (BSD algorithm for ground-based remote-sensing ceilometers in polar regions and apply it to ceilometers at Neumayer III and Princess Elisabeth (PE stations, East Antarctica. The algorithm is able to detect (heavy blowing snow layers reaching 30 m height. Results show that 78 % of the detected events are in agreement with visual observations at Neumayer III station. The BSD algorithm detects heavy blowing snow 36 % of the time at Neumayer (2011–2015 and 13 % at PE station (2010–2016. Blowing snow occurrence peaks during the austral winter and shows around 5 % interannual variability. The BSD algorithm is capable of detecting blowing snow both lifted from the ground and occurring during precipitation, which is an added value since results indicate that 92 % of the blowing snow is during synoptic events, often combined with precipitation. Analysis of atmospheric meteorological variables shows that blowing snow occurrence strongly depends on fresh snow availability in addition to wind speed. This finding challenges the commonly used parametrizations, where the threshold for snow particles to be lifted is a function of wind speed only. Blowing snow occurs predominantly during storms and overcast conditions, shortly after precipitation events, and can reach up to 1300 m a. g. l.  in the case of heavy mixed events (precipitation and blowing snow together. These results suggest that synoptic conditions play an important role in generating blowing snow events and that fresh snow availability should be considered in determining the blowing snow onset.

  1. Multi-component ensembles of future meteorological and natural snow conditions for 1500 m altitude in the Chartreuse mountain range, Northern French Alps

    Science.gov (United States)

    Verfaillie, Deborah; Lafaysse, Matthieu; Déqué, Michel; Eckert, Nicolas; Lejeune, Yves; Morin, Samuel

    2018-04-01

    This article investigates the climatic response of a series of indicators for characterizing annual snow conditions and corresponding meteorological drivers at 1500 m altitude in the Chartreuse mountain range in the Northern French Alps. Past and future changes were computed based on reanalysis and observations from 1958 to 2016, and using CMIP5-EURO-CORDEX GCM-RCM pairs spanning historical (1950-2005) and RCP2.6 (4), RCP4.5 and RCP8.5 (13 each) future scenarios (2006-2100). The adjusted climate model runs were used to drive the multiphysics ensemble configuration of the detailed snowpack model Crocus. Uncertainty arising from physical modeling of snow accounts for 20 % typically, although the multiphysics is likely to have a much smaller impact on trends. Ensembles of climate projections are rather similar until the middle of the 21st century, and all show a continuation of the ongoing reduction in average snow conditions, and sustained interannual variability. The impact of the RCPs becomes significant for the second half of the 21st century, with overall stable conditions with RCP2.6, and continued degradation of snow conditions for RCP4.5 and 8.5, the latter leading to more frequent ephemeral snow conditions. Changes in local meteorological and snow conditions show significant correlation with global temperature changes. Global temperature levels 1.5 and 2 °C above preindustrial levels correspond to a 25 and 32 % reduction, respectively, of winter mean snow depth with respect to the reference period 1986-2005. Larger reduction rates are expected for global temperature levels exceeding 2 °C. The method can address other geographical areas and sectorial indicators, in the field of water resources, mountain tourism or natural hazards.

  2. A New Operational Snow Retrieval Algorithm Applied to Historical AMSR-E Brightness Temperatures

    Directory of Open Access Journals (Sweden)

    Marco Tedesco

    2016-12-01

    Full Text Available Snow is a key element of the water and energy cycles and the knowledge of spatio-temporal distribution of snow depth and snow water equivalent (SWE is fundamental for hydrological and climatological applications. SWE and snow depth estimates can be obtained from spaceborne microwave brightness temperatures at global scale and high temporal resolution (daily. In this regard, the data recorded by the Advanced Microwave Scanning Radiometer—Earth Orbiting System (EOS (AMSR-E onboard the National Aeronautics and Space Administration’s (NASA AQUA spacecraft have been used to generate operational estimates of SWE and snow depth, complementing estimates generated with other microwave sensors flying on other platforms. In this study, we report the results concerning the development and assessment of a new operational algorithm applied to historical AMSR-E data. The new algorithm here proposed makes use of climatological data, electromagnetic modeling and artificial neural networks for estimating snow depth as well as a spatio-temporal dynamic density scheme to convert snow depth to SWE. The outputs of the new algorithm are compared with those of the current AMSR-E operational algorithm as well as in-situ measurements and other operational snow products, specifically the Canadian Meteorological Center (CMC and GlobSnow datasets. Our results show that the AMSR-E algorithm here proposed generally performs better than the operational one and addresses some major issues identified in the spatial distribution of snow depth fields associated with the evolution of effective grain size.

  3. Frontal Dynamics of Powder Snow Avalanches

    Science.gov (United States)

    Louge, M. Y.; Carroll, C. S.; Turnbull, B.

    2012-04-01

    We model the dynamics of the head of dilute powder snow avalanches sustained by a massive frontal blow-out, arising as a weakly cohesive snow cover is fluidized by the very pore pressure gradients that the avalanche induces within the snow pack. Such material eruption just behind the front acts as a source of denser fluid thrust into a uniform ambient air flow at high Reynolds number. In such "eruption current", fluidization depth is inversely proportional to a bulk Richardson number representing avalanche height. By excluding situations in which the snow cover is not fluidized up to its free surface, we derive a criterion combining snow pack friction and density indicating which avalanches can produce a sustainable powder cloud. A mass balance involving snow cover and powder cloud sets avalanche height and mean density. By determining which solution of the mass balance is stable, we find that avalanches reach constant growth and acceleration rates for fixed slope and avalanche width. Under these conditions, we calculate the fraction of the fluidized cover that is actually scoured and blown-out into the cloud, and deduce from a momentum balance on the head that the avalanche accelerates at a rate only 14% of the gravitational component along the flow. We also calculate how far a powder cloud travels until its mean density becomes constant. Finally, we show that the dynamics of powder snow avalanches are crucially affected by the rate of change of their width, for example by reaching an apparent steady speed as their channel widens. If such widening is rapid, or if slope inclination vanishes, we calculate where and how powder clouds collapse. Predictions agree well with observations of powder snow avalanches carried out at the Vallee de la Sionne (Switzerland).

  4. 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

  5. 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...

  6. Famine Winter.

    Science.gov (United States)

    Schultz, James Willard; Reyhner, Jon Allan, Ed.

    Written for the students at Heart Butte School on the Blackfeet Reservation, the booklet tells a story about Old Sun, a Blackfeet medicine man, and how terribly unkind the country of the far north can be. Old Sun had a dream of a bear with long, soft fur and white as snow. He was advised by his secret helper to get the bear's skin for a sacrifice…

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

    Science.gov (United States)

    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.

  8. Improving the snow physics of WEB-DHM and its point evaluation at the SnowMIP sites

    Directory of Open Access Journals (Sweden)

    M. Shrestha

    2010-12-01

    Full Text Available In this study, the snow physics of a distributed biosphere hydrological model, referred to as the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM is significantly improved by incorporating the three-layer physically based energy balance snowmelt model of Simplified Simple Biosphere 3 (SSiB3 and the Biosphere-Atmosphere Transfer Scheme (BATS albedo scheme. WEB-DHM with improved snow physics is hereafter termed WEB-DHM-S. Since the in-situ observations of spatially-distributed snow variables with high resolution are currently not available over large regions, the new distributed system (WEB-DHM-S is at first rigorously tested with comprehensive point measurements. The stations used for evaluation comprise the four open sites of the Snow Model Intercomparison Project (SnowMIP phase 1 with different climate characteristics (Col de Porte in France, Weissfluhjoch in Switzerland, Goose Bay in Canada and Sleepers River in USA and one open/forest site of the SnowMIP phase 2 (Hitsujigaoka in Japan. The comparisons of the snow depth, snow water equivalent, surface temperature, snow albedo and snowmelt runoff at the SnowMIP1 sites reveal that WEB-DHM-S, in general, is capable of simulating the internal snow process better than the original WEB-DHM. Sensitivity tests (through incremental addition of model processes are performed to illustrate the necessity of improvements over WEB-DHM and indicate that both the 3-layer snow module and the new albedo scheme are essential. The canopy effects on snow processes are studied at the Hitsujigaoka site of the SnowMIP2 showing that the snow holding capacity of the canopy plays a vital role in simulating the snow depth on ground. Through these point evaluations and sensitivity studies, WEB-DHM-S has demonstrated the potential to address basin-scale snow processes (e.g., the snowmelt runoff, since it inherits the distributed hydrological framework from the WEB-DHM (e.g., the slope-driven runoff

  9. Loropetalum chinense 'Snow Panda'

    Science.gov (United States)

    A new Loropetalum chinense, ‘Snow Panda’, developed at the U.S. National Arboretum is described. ‘Snow Panda’ (NA75507, PI660659) originated from seeds collected near Yan Chi He, Hubei, China in 1994 by the North America-China Plant Exploration Consortium (NACPEC). Several seedlings from this trip w...

  10. 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

  11. 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.

  12. 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.

  13. Evaluation and Economic Value of Winter Weather Forecasts

    OpenAIRE

    Snyder, Derrick William

    2014-01-01

    State and local highway agencies spend millions of dollars each year to deploy winter operation teams to plow snow and de-ice roadways. Accurate and timely weather forecast information is critical for effective decision making. Students from Purdue University partnered with the Indiana Department of Transportation to create an experimental winter weather forecast service for the 2012-2013 winter season in Indiana to assist in achieving these goals. One forecast product, an hourly timeline of ...

  14. 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.

  15. 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)

  16. 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

  17. 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

  18. Snow impact on groundwater recharge in Table Mountain Group ...

    African Journals Online (AJOL)

    Snowmelt in the mountainous areas of the Table Mountain Group (TMG) in South Africa is believed to be one of sources of groundwater recharge in some winter seasons. This paper provides a scientific assessment of snow impact on groundwater recharge in Table Mountain Group Aquifer Systems for the first time.

  19. Modelling of stream flow in snow dominated Budhigandaki ...

    Indian Academy of Sciences (India)

    60

    at the downstream part of the basin. The catchment area experiences short winter monsoon between. Nov-Feb. Relative humidity reaches maximum during the monsoon season. The Himalayan zone contributes to the stream flow in the dry season by snow and ice melt. The Central Mahabharata zone, which account for the ...

  20. 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

  1. Winter Wonderlands

    Science.gov (United States)

    Coy, Mary

    2011-01-01

    Listening to people complain about the hardships of winter and the dreariness of the nearly constant gray sky prompted the author to help her sixth graders recognize and appreciate the beauty that surrounds them for nearly five months of the year in western New York. The author opines that if students could see things more artistically, the winter…

  2. On the importance of sublimation to an alpine snow mass balance in the Canadian Rocky Mountains

    Directory of Open Access Journals (Sweden)

    M. K. MacDonald

    2010-07-01

    Full Text Available A modelling study was undertaken to evaluate the contribution of sublimation to an alpine snow mass balance in the Canadian Rocky Mountains. Snow redistribution and sublimation by wind, snowpack sublimation and snowmelt were simulated for two winters over an alpine ridge transect located in the Canada Rocky Mountains. The resulting snowcover regimes were compared to those from manual snow surveys. Simulations were performed using physically based blowing snow (PBSM and snowpack ablation (SNOBAL models. A hydrological response unit (HRU-based spatial discretization was used rather than a more computationally expensive fully-distributed one. The HRUs were set up to follow an aerodynamic sequence, whereby eroded snow was transported from windswept, upwind HRUs to drift accumulating, downwind HRUs. That snow redistribution by wind can be adequately simulated in computationally efficient HRUs over this ridge has important implications for representing snow transport in large-scale hydrology models and land surface schemes. Alpine snow sublimation losses, in particular blowing snow sublimation losses, were significant. Snow mass losses to sublimation as a percentage of cumulative snowfall were estimated to be 20–32% with the blowing snow sublimation loss amounting to 17–19% of cumulative snowfall. This estimate is considered to be a conservative estimate of the blowing snow sublimation loss in the Canadian Rocky Mountains because the study transect is located in the low alpine zone where the topography is more moderate than the high alpine zone and windflow separation was not observed. An examination of the suitability of PBSM's sublimation estimates in this environment and of the importance of estimating blowing snow sublimation on the simulated snow accumulation regime was conducted by omitting sublimation calculations. Snow accumulation in HRUs was overestimated by 30% when neglecting blowing snow sublimation calculations.

  3. Regional distribution and variability of model-simulated Arctic snow on sea ice

    Science.gov (United States)

    Castro-Morales, Karel; Ricker, Robert; Gerdes, Rüdiger

    2017-09-01

    Numerical models face the challenge of representing the present-day spatiotemporal distribution of snow on sea ice realistically. We present modeled Arctic-wide snow depths on sea ice (hs_mod) obtained with the MITgcm configured with a single snow layer that accumulates proportionally to the thickness of sea ice. When compared to snow depths derived from radar measurements (NASA Operation IceBridge, 2009-2013), the model snow depths are overestimated on first-year ice (2.5 ± 8.1 cm) and multiyear ice (0.8 ± 8.3 cm). The large variance between model and observations lies mainly in the limitations of the model snow scheme and the large uncertainties in the radar measurements. In a temporal analysis, during the peak of snowfall accumulation (April), hs_mod show a decline between 2000 and 2013 associated to long-term reduction of summer sea ice extent, surface melting and sublimation. With the aim of gaining knowledge on how to improve hs_mod, we investigate the contribution of the explicitly modeled snow processes to the resulting hs_mod. Our analysis reveals that this simple snow scheme offers a practical solution to general circulation models due to its ability to replicate robustly the distribution of the large-scale Arctic snow depths. However, benefit can be gained from the integration of explicit wind redistribution processes to potentially improve the model performance and to better understand the interaction between sources and sinks of contemporary Arctic snow.

  4. Sustainability of winter tourism in a changing climate over Kashmir Himalaya.

    Science.gov (United States)

    Dar, Reyaz Ahmad; Rashid, Irfan; Romshoo, Shakil Ahmad; Marazi, Asif

    2014-04-01

    Mountain areas are sensitive to climate change. Implications of climate change can be seen in less snow, receding glaciers, increasing temperatures, and decreasing precipitation. Climate change is also a severe threat to snow-related winter sports such as skiing, snowboarding, and cross-country skiing. The change in climate will put further pressure on the sensitive environment of high mountains. Therefore, in this study, an attempt has been made to know the impact of climate change on the snow precipitation, water resources, and winter tourism in the two famous tourist resorts of the Kashmir Valley. Our findings show that winters are getting prolonged with little snow falls on account of climate change. The average minimum and maximum temperatures are showing statistically significant increasing trends for winter months. The precipitation is showing decreasing trends in both the regions. A considerable area in these regions remains under the snow and glacier cover throughout the year especially during the winter and spring seasons. However, time series analysis of LandSat MODIS images using Normalized Difference Snow Index shows a decreasing trend in snow cover in both the regions from past few years. Similarly, the stream discharge, comprising predominantly of snow- and glacier-melt, is showing a statistically significant declining trend despite the melting of these glaciers. The predicted futuristic trends of temperature from Predicting Regional Climates for Impact Studies regional climate model are showing an increase which may enhance snow-melting in the near future posing a serious threat to the sustainability of winter tourism in the region. Hence, it becomes essential to monitor the changes in temperature and snow cover depletion in these basins in order to evaluate their effect on the winter tourism and water resources in the region.

  5. Titan's Emergence from Winter

    Science.gov (United States)

    Flasar, F. Michael; Achterberg, Richard; Jennings, Donald; Schinder, Paul

    2011-01-01

    We summarize the changes in Titans thermal structure derived from Cassini CIRS and radio-occultation data during the transition from winter to early spring. Titan's surface, and middle atmosphere show noticeable seasonal change, whereas that in most of the troposphere is mated. This can be understood in terms of the relatively small radiative relaxation time in the middle atmosphere and much larger time scale in the troposphere. The surface exhibits seasonal change because the heat capacity in an annual skin depth is much smaller than that in the lowest scale height of the troposphere. Surface temperatures rise 1 K at raid and high latitudes in the winter northern hemisphere and cool in the southern hemisphere. Changes in in the middle atmosphere are more complicated. Temperatures in the middle stratosphere (approximately 1 mbar) increase by a few kelvin at mid northern latitudes, but those at high latitudes first increase as that region moves out of winter shadow, and then decrease. This probably results from the combined effect of increased solar heating as the suit moves higher in the sky and the decreased adiabatic warming as the sinking motions associated with the cross-equatorial meridional cell weaken. Consistent with this interpretation, the warm temperatures observed higher up at the winter polar stratopause cool significantly.

  6. Sound absorption of snow

    OpenAIRE

    Maysenhölder, W.; Schneebeli, M.; Zhou, X.; Zhang, T.; Heggli, M.

    2008-01-01

    Recently fallen snow possesses good sound-absorbing properties. This fact is well-known and confirmed by measurements. Is the filigree structure of snowflakes decisive? In principle we know that the sound-absorbing capacity of a porous material is dependent on its structure. But until now the question as to which structural characteristics are significant has been insufficiently answered. Detailed investigations of snow are to explain this fact by precise measurements of the sound absorption,...

  7. Transformations of snow chemistry in the boreal forest: Accumulation and volatilization

    Science.gov (United States)

    Pomeroy, J.W.; Davies, T.D.; Jones, H.G.; Marsh, P.; Peters, N.E.; Tranter, M.

    1999-01-01

    This paper examines the processes and dynamics of ecologically-important inorganic chemical (primarily NO3-N) accumulation and loss in boreal forest snow during the cold winter period at a northern and southern location in the boreal forest of western Canada. Field observations from Inuvik, Northwest Territories and Waskesiu, Saskatchewan, Canada were used to link chemical transformations and physical processes in boreal forest snow. Data on the disposition and overwinter transformation of snow water equivalent, NO3-, SO42- and other major ions were examined. No evidence of enhanced dry deposition of chemical species to intercepted snow was found at either site except where high atmospheric aerosol concentrations prevailed. At Inuvik, concentrations of SO42- and Cl- were five to six times higher in intercepted snow than in surface snow away from the trees. SO4-S and Cl loads at Inuvik were correspondingly enhanced three-fold within the nearest 0.5 m to individual tree stems. Measurements of snow affected by canopy interception without rapid sublimation provided no evidence of ion volatilization from intercepted snow. Where intercepted snow sublimation rates were significant, ion loads in sub-canopy snow suggested that NO3- volatized with an efficiency of about 62% per snow mass sublimated. Extrapolating this measurement from Waskesiu to sublimation losses observed in other southern boreal environments suggests that 19-25% of snow inputs of NO3- can be lost during intercepted snow sublimation. The amount of N lost during sublimation may be large in high-snowfall, high N load southern boreal forests (Quebec) where 0.42 kg NO3-N ha-1 is estimated as a possible seasonal NO3- volatilization. The sensitivity of the N fluxes to climate and forest canopy variation and implications of the winter N losses for N budgets in the boreal forest are discussed.This paper examines the processes and dynamics of ecologically-important inorganic chemical (primarily NO3-N) accumulation

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Darvishi, M.; Ahmadi, Gh. R.

    2013-09-01

    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.

  10. 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.

  11. Snow hydrology in Mediterranean mountain regions: A review

    Science.gov (United States)

    Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; López-Moreno, Juan Ignacio; Drapeau, Laurent; Page, Michel Le; Escadafal, Richard

    2017-08-01

    Water resources in Mediterranean regions are under increasing pressure due to climate change, economic development, and population growth. Many Mediterranean rivers have their headwaters in mountainous regions where hydrological processes are driven by snowpack dynamics and the specific variability of the Mediterranean climate. A good knowledge of the snow processes in the Mediterranean mountains is therefore a key element of water management strategies in such regions. The objective of this paper is to review the literature on snow hydrology in Mediterranean mountains to identify the existing knowledge, key research questions, and promising technologies. We collected 620 peer-reviewed papers, published between 1913 and 2016, that deal with the Mediterranean-like mountain regions in the western United States, the central Chilean Andes, and the Mediterranean basin. A large amount of studies in the western United States form a strong scientific basis for other Mediterranean mountain regions. We found that: (1) the persistence of snow cover is highly variable in space and time but mainly controlled by elevation and precipitation; (2) the snowmelt is driven by radiative fluxes, but the contribution of heat fluxes is stronger at the end of the snow season and during heat waves and rain-on-snow events; (3) the snow densification rates are higher in these regions when compared to other climate regions; and (4) the snow sublimation is an important component of snow ablation, especially in high-elevation regions. Among the pressing issues is the lack of continuous ground observation in high-elevation regions. However, a few years of snow depth (HS) and snow water equivalent (SWE) data can provide realistic information on snowpack variability. A better spatial characterization of snow cover can be achieved by combining ground observations with remotely sensed snow data. SWE reconstruction using satellite snow cover area and a melt model provides reasonable information that

  12. 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

  13. 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

  14. MODIS Snow Cover Recovery Using Variational Interpolation

    Science.gov (United States)

    Tran, H.; Nguyen, P.; Hsu, K. L.; Sorooshian, S.

    2017-12-01

    Cloud obscuration is one of the major problems that limit the usages of satellite images in general and in NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) global Snow-Covered Area (SCA) products in particular. Among the approaches to resolve the problem, the Variational Interpolation (VI) algorithm method, proposed by Xia et al., 2012, obtains cloud-free dynamic SCA images from MODIS. This method is automatic and robust. However, computational deficiency is a main drawback that degrades applying the method for larger scales (i.e., spatial and temporal scales). To overcome this difficulty, this study introduces an improved version of the original VI. The modified VI algorithm integrates the MINimum RESidual (MINRES) iteration (Paige and Saunders., 1975) to prevent the system from breaking up when applied to much broader scales. An experiment was done to demonstrate the crash-proof ability of the new algorithm in comparison with the original VI method, an ability that is obtained when maintaining the distribution of the weights set after solving the linear system. After that, the new VI algorithm was applied to the whole Contiguous United States (CONUS) over four winter months of 2016 and 2017, and validated using the snow station network (SNOTEL). The resulting cloud free images have high accuracy in capturing the dynamical changes of snow in contrast with the MODIS snow cover maps. Lastly, the algorithm was applied to create a Cloud free images dataset from March 10, 2000 to February 28, 2017, which is able to provide an overview of snow trends over CONUS for nearly two decades. ACKNOWLEDGMENTSWe would like to acknowledge NASA, NOAA Office of Hydrologic Development (OHD) National Weather Service (NWS), Cooperative Institute for Climate and Satellites (CICS), Army Research Office (ARO), ICIWaRM, and UNESCO for supporting this research.

  15. Modeling Snow Regime in Cores of Small Planetary Bodies

    Science.gov (United States)

    Boukaré, C. E.; Ricard, Y. R.; Parmentier, E.; Parman, S. W.

    2017-12-01

    Observations of present day magnetic field on small planetary bodies such as Ganymede or Mercury challenge our understanding of planetary dynamo. Several mechanisms have been proposed to explain the origin of magnetic fields. Among the proposed scenarios, one family of models relies on snow regime. Snow regime is supported by experimental studies showing that melting curves can first intersect adiabats in regions where the solidifying phase is not gravitationaly stable. First solids should thus remelt during their ascent or descent. The effect of the snow zone on magnetic field generation remains an open question. Could magnetic field be generated in the snow zone? If not, what is the depth extent of the snow zone? How remelting in the snow zone drive compositional convection in the liquid layer? Several authors have tackled this question with 1D-spherical models. Zhang and Schubert, 2012 model sinking of the dense phase as internally heated convection. However, to our knowledge, there is no study on the convection structure associated with sedimentation and phase change at planetary scale. We extend the numerical model developped in [Boukare et al., 2017] to model snow dynamics in 2D Cartesian geometry. We build a general approach for modeling double diffusive convection coupled with solid-liquid phase change and phase separation. We identify several aspects that may govern the convection structure of the solidifying system: viscosity contrast between the snow zone and the liquid layer, crystal size, rate of melting/solidification and partitioning of light components during phase change.

  16. 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" target="_blank">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

  17. Snow and albedo climate change impacts across the United States Northern Great Plains

    Science.gov (United States)

    Fassnacht, S. R.; Cherry, M. L.; Venable, N. B. H.; Saavedra, F.

    2016-02-01

    In areas with a seasonal snowpack, a warmer climate could cause less snowfall, a shallower snowpack, and a change in the timing of snowmelt, all which could reduce the winter albedo and yield an increase in net short-wave radiation. Trends in temperature, precipitation (total and as snow), days with precipitation and snow, and winter albedo were investigated over the 60-year period from 1951 to 2010 for 20 meteorological stations across the Northern Great Plains. This is an area where snow accumulation is shallow but persistent for most of the winter (November to March). The most consistent trends were minimum temperature and days with precipitation, both of which increased at a majority of the stations. Among the stations included, a decrease in the modelled winter albedo was more prevalent than an increase. There was substantial spatial variability in the climate trends. For most variables, the period of record used influenced the magnitude and sign of the significant trends.

  18. PROSNOW - Provision of a prediction system allowing for management and optimization of snow in Alpine ski resorts

    Science.gov (United States)

    Morin, Samuel; Ghislain, Dubois

    2017-04-01

    Snow on the ground is a critical resource for mountain regions to sustain river flow, to provide freshwater input to ecosystems and to support winter tourism, in particular in ski resorts. The level of activity, employment, turnover and profit of hundreds of ski resorts in the European Alps primarily depends on meteorological conditions, in particular natural snowfall but also increasingly conditions favourable for snowmaking (production of machine made snow, also referred to as technical snow). Ski resorts highly depend on appropriate conditions for snowmaking (mainly the availability of cold water, as well as sub-freezing temperature with sufficiently low humidity conditions). However, beyond the time scale of weather forecasts (a few days), managers of ski resorts have to rely on various and scattered sources of information, hampering their ability to cope with highly variable meteorological conditions. Improved anticipation capabilities at all time scales, spanning from "weather forecast" (up to 5 days typically) to "climate prediction" at the seasonal scale (up to several months) holds significant potential to increase the resilience of socio-economic stakeholders and supports their real-time adaptation potential. To address this issue, the recently funded (2017-2020) H2020 PROSNOW project will build a demonstrator of a meteorological and climate prediction and snow management system from one week to several months ahead, specifically tailored to the needs of the ski industry. PROSNOW will apply state-of-the-art knowledge relevant to the predictability of atmospheric and snow conditions, and investigate and document the added value of such services. The project proposes an Alpine-wide system (including ski resorts located in France, Switzerland, Germany, Austria and Italy). It will join and link providers of weather forecasts and climate predictions at the seasonal scale, research institutions specializing in snowpack modelling, a relevant ensemble of at least

  19. Guidelines to Facilitate the Evaluation of Brines for Winter Roadway Maintenance Operations.

    Science.gov (United States)

    2017-09-19

    This document presents guidelines to facilitate the evaluation of brines for winter weather roadway maintenance applications in Texas. Brines are used in anti-icing applications which typically consist of placing liquid snow and ice control chemicals...

  20. Tow plows could help Michigan save time and money on winter maintenance : research spotlight.

    Science.gov (United States)

    2016-11-01

    As winter maintenance costs rise, MDOT is looking into innovative approaches to increase snow removal efficiency. As part of this effort, the department recently estimated the costs and benefits of incorporating tow plows into its equipment fleet. Re...

  1. Tracking Forest and Open Area Effects on Snow Accumulation by Unmanned Aerial Vehicle Photogrammetry

    Science.gov (United States)

    Lendzioch, T.; Langhammer, J.; Jenicek, M.

    2016-06-01

    Airborne digital photogrammetry is undergoing a renaissance. The availability of low-cost Unmanned Aerial Vehicle (UAV) platforms well adopted for digital photography and progress in software development now gives rise to apply this technique to different areas of research. Especially in determining snow depth spatial distributions, where repetitive mapping of cryosphere dynamics is crucial. Here, we introduce UAV-based digital photogrammetry as a rapid and robust approach for evaluating snow accumulation over small local areas (e.g., dead forest, open areas) and to reveal impacts related to changes in forest and snowpack. Due to the advancement of the technique, snow depth of selected study areas such as of healthy forest, disturbed forest, succession, dead forest, and of open areas can be estimated at a 1 cm spatial resolution. The approach is performed in two steps: 1) developing a high resolution Digital Elevation Model during snow-free and 2) during snow-covered conditions. By substracting these two models the snow depth can be accurately retrieved and volumetric changes of snow depth distribution can be achieved. This is a first proof-of-concept study combining snow depth determination and Leaf Area Index (LAI) retrieval to monitor the impact of forest canopy metrics on snow accumulation in coniferous forest within the Šumava National Park, Czech Republic. Both, downward-looking UAV images and upward-looking LAI-2200 canopy analyser measurements were applied to reveal the LAI, controlling interception and transmitting radiation. For the performance of downward-looking images the snow background instead of the sky fraction was used. In contrast to the classical determination of LAI by hemispherical photography or by LAI plant canopy analyser, our approach will also test the accuracy of LAI measurements by UAV that are taken simultaneously during the snow cover mapping campaigns. Since the LAI parameter is important for snowpack modelling, this method presents

  2. Use of Sentinels to aid the global monitoring of snow cover

    Science.gov (United States)

    Pulliainen, Jouni; Salminen, Miia; Luojus, Kari; Metsämäki, Sari; Lemmetyinen, Juha; Takala, Matias; Cohen, Juval; Böttcher, Kristine

    2014-05-01

    Earth observation instruments onboard Sentinel satellites provide a unique opportunity for the monitoring and investigation of global snow processes. The issue of the possible decay of seasonal snow cover is highly relevant for climate research. In addition to water cycle, the extent and amount of snow affects to surface albedo, and indirectly to carbon cycling. The latter issue includes snow-induced changes in permafrost regions (active layer characteristics), as well as the effect of snow (melt) to vegetation growth and soil respiration. Recent advances in ESA DUE GlobSnow project have shown that by combining data from optical satellite sensors and passive microwave instruments advanced Climate Data Records (CDR) on seasonal snow cover can be produced, extending to time periods of over 30 years. The combined snow cover products provide information both on Snow Extent (SE) and Snow Water Equivalent (SWE) on a daily basis. The applicable instruments providing historical data for CDR generation include such microwave radiometers as SMMR, AMSR and SSMI/I, and such optical sensors as AVHRR, AATSR and VIIRS. Sentinel 3, especially its SLSTR instrument, is a prominent tool for expanding the snow CDR for forthcoming years. The developed global snow cover monitoring methodology, demonstrated and discussed here, derives the SWE information from passive microwave data (accompanied with in situ observations of snow depth at synoptic weather stations). The snow extent and fractional snow cover (FSC) on ground is derived from optical satellite data, in order to accurately map the continental line of seasonal snow cover, and to map regions of ephemeral snow cover. An advanced feature in the developed methodology is the provision of uncertainty information on snow cover characteristics associated with each individual satellite data footprint on ground and moment of time. In addition to assisting the generation and extension of the global snow cover CDR, Sentinel missions provide

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. A research on snow distribution in mountainous area using airborne laser scanning

    Science.gov (United States)

    Nishihara, T.; Tanise, A.

    2015-12-01

    In snowy cold regions, the snowmelt water stored in dams in early spring meets the water demand for the summer season. Thus, snowmelt water serves as an important water resource. However, snowmelt water also can cause snowmelt floods. Therefore, it's necessary to estimate snow water equivalent in a dam basin as accurately as possible. For this reason, the dam operation offices in Hokkaido, Japan conduct snow surveys every March to estimate snow water equivalent in the dam basin. In estimating, we generally apply a relationship between elevation and snow water equivalent. But above the forest line, snow surveys are generally conducted along ridges due to the risk of avalanches or other hazards. As a result, snow water equivalent above the forest line is significantly underestimated. In this study, we conducted airborne laser scanning to measure snow depth in the high elevation area including above the forest line twice in the same target area (in 2012 and 2015) and analyzed the relationships of snow depth above the forest line and some indicators of terrain. Our target area was the Chubetsu dam basin. It's located in central Hokkaido, a high elevation area in a mountainous region. Hokkaido is a northernmost island of Japan. Therefore it's a cold and snowy region. The target range for airborne laser scanning was 10km2. About 60% of the target range was above the forest line. First, we analyzed the relationship between elevation and snow depth. Below the forest line, the snow depth increased linearly with elevation increase. On the other hand, above the forest line, the snow depth varied greatly. Second, we analyzed the relationship between overground-openness and snow depth above the forest line. Overground-openness is an indicator quantifying how far a target point is above or below the surrounding surface. As a result, a simple relationship was clarified. Snow depth decreased linearly as overground-openness increases. This means that areas with heavy snow cover are

  8. Recent research in snow hydrology

    Science.gov (United States)

    Dozier, Jeff

    1987-01-01

    Recent work on snow-pack energy exchange has involved detailed investigations on snow albedo and attempts to integrate energy-balance calculations over drainage basins. Along with a better understanding of the EM properties of snow, research in remote sensing has become more focused toward estimation of snow-pack properties. In snow metamorphism, analyses of the physical processes must now be coupled to better descriptions of the geometry of the snow microstructure. The dilution method now appears to be the best direct technique for measuring the liquid water content of snow; work on EM methods continues. Increasing attention to the chemistry of the snow pack has come with the general focus on acid precipitation in hydrology.

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

    Directory of Open Access Journals (Sweden)

    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.

  10. An ensemble-based subgrid snow data assimilation framework

    Science.gov (United States)

    Aalstad, K.; Westermann, S.; Bertino, L.

    2016-12-01

    Snow, with high albedo, low thermal conductivity and large water storing capacity strongly modulates the surface energy and water balance. At the same time, the estimation of the seasonal snow cycle at the kilometer scale is a major hydrometeorological challenge and thus represents a significant source of uncertainty in land surface schemes. To constrain this uncertainty we are developing a modular ensemble-based subgrid snow data assimilation framework (ESSDA) for satellite-era snow distribution (SD) reanalyses. ESSDA makes use of an ensemble Kalman smoother (EnKS) approach to assimilate MODIS and LandSat retrievals of snow cover fraction into the subgrid snow distribution submodel (SSNOWD). Our problem is particularly challenging as snow cover is doubly bounded in physical space, which violates the Gaussian error assumption in the EnKS and thus compromises the performance of the reanalysis. In an attempt to alleviate this issue we make use of the technique of analytical Gaussian anamorphosis (GA) and apply the EnKS in a transformed space. The potential of the framework is presented through both synthetic (twin) and real experiments. The latter are carried out for the Bayelva catchment near Ny Ålelsund (79°N, Svalbard, Norway) where independent and accurate ground-based observations of snow cover and snow depth distributions are available. Our ensuing evaluation demonstrates that ESSDA provides robust estimates of the evolution of the SD over almost a decade long validation period. The use of GA, and our emphasis on the subgrid SD, is what sets ESSDA apart from previously proposed snow reanalysis frameworks. ESSDA has been developed to aid in satellite-based permafrost mapping efforts. Nonetheless, being modular and given the improved error treatment through GA, the ESSDA approach may also prove valuable for broader hydrometeorological reanalysis and forecast initialization efforts.

  11. Experimental investigation of ice and snow melting process on pavement utilizing geothermal tail water

    International Nuclear Information System (INIS)

    Wang Huajun; Zhao Jun; Chen Zhihao

    2008-01-01

    Road ice and snow melting based on low temperature geothermal tail water is of significance to realize energy cascading utilization. A small scale ice and snow melting system is built in this work. Experiments of dynamic melting processes of crushed ice, solid ice, artificial snow and natural snow are conducted on concrete pavement. The results show that the melting process of ice and snow includes three phases: a starting period, a linear period and an accelerated period. The critical value of the snow free area ratio between the linear period and the accelerated period is about 0.6. The physical properties of ice and snow, linked with ambient conditions, have an obvious effect on the melting process. The difference of melting velocity and melting time between ice and snow is compared. To reduce energy consumption, the formation of ice on roads should be avoided if possible. The idling process is an effective pathway to improve the performance of melting systems. It is feasible to utilize geothermal tail water of about 40 deg. C for melting ice and snow on winter roads, and it is unnecessary to keep too high fluid temperatures during the practical design and applications. Besides, with the exception of solid ice, the density and porosity of snow and ice tend to be decreasing and increasing, respectively, as the ambient temperature decreases

  12. 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

  13. Snow, ice and solar radiation

    NARCIS (Netherlands)

    Kuipers Munneke, P.

    2009-01-01

    The snow-covered ice sheets of Antarctica and Greenland reflect most of the incoming solar radiation. The reflectivity, commonly called the albedo, of snow on these ice sheets has been observed to vary in space and time. In this thesis, temporal and spatial changes in snow albedo is found to depend

  14. Wind Tunnel Experiments: Influence of Erosion and Deposition on Wind-Packing of New Snow

    Directory of Open Access Journals (Sweden)

    Christian G. Sommer

    2018-01-01

    Full Text Available Wind sometimes creates a hard, wind-packed layer at the surface of a snowpack. The formation of such wind crusts was observed during wind tunnel experiments with combined SnowMicroPen and Microsoft Kinect sensors. The former provides the hardness of new and wind-packed snow and the latter spatial snow depth data in the test section. Previous experiments had shown that saltation is necessary but not sufficient for wind-packing. The combination of hardness and snow depth data now allows to study the case with saltation in more detail. The Kinect data requires complex processing but with the appropriate corrections, snow depth changes can be measured with an accuracy of about 1 mm. The Kinect is therefore well suited to quantify erosion and deposition. We found that no hardening occurred during erosion and that a wind crust may or may not form when snow is deposited. Deposition is more efficient at hardening snow in wind-exposed than in wind-sheltered areas. The snow hardness increased more on the windward side of artificial obstacles placed in the wind tunnel. Similarly, the snow was harder in positions with a low Sx parameter. Sx describes how wind-sheltered (high Sx or wind-exposed (low Sx a position is and was calculated based on the Kinect data. The correlation between Sx and snow hardness was −0.63. We also found a negative correlation of −0.4 between the snow hardness and the deposition rate. Slowly deposited snow is harder than a rapidly growing accumulation. Sx and the deposition rate together explain about half of the observed variability of snow hardness.

  15. Validation of snow characteristics and snow albedo feedback in the Canadian Regional Climate Model simulations over North America

    Science.gov (United States)

    Fang, B.; Sushama, L.; Diro, G. T.

    2015-12-01

    Snow characteristics and snow albedo feedback (SAF) over North America, as simulated by the fifth-generation Canadian Regional Climate Model (CRCM5), when driven by ERA-40/ERA-Interim, CanESM2 and MPI-ESM-LR at the lateral boundaries, are analyzed in this study. Validation of snow characteristics is performed by comparing simulations against available observations from MODIS, ISCCP and CMC. Results show that the model is able to represent the main spatial distribution of snow characteristics with some overestimation in snow mass and snow depth over the Canadian high Arctic. Some overestimation in surface albedo is also noted for the boreal region which is believed to be related to the snow unloading parameterization, as well as the overestimation of snow albedo. SAF is assessed both in seasonal and climate change contexts when possible. The strength of SAF is quantified as the amount of additional net shortwave radiation at the top of the atmosphere as surface albedo decreases in association with a 1°C increase in surface temperature. Following Qu and Hall (2007), this is expressed as the product of the variation in planetary albedo with surface albedo and the change in surface albedo for 1°C change in surface air temperature during the season, which in turn is determined by the strength of the snow cover and snowpack metamorphosis feedback loops. Analysis of the latter term in the seasonal cycle suggests that for CRCM5 simulations, the snow cover feedback loop is more dominant compared to the snowpack metamorphosis feedback loop, whereas for MODIS, the two feedback loops have more or less similar strength. Moreover, the SAF strength in the climate change context appears to be weaker than in the seasonal cycle and is sensitive to the driving GCM and the RCP scenario.

  16. Snow chemistry of high altitude glaciers in the French Alps

    Science.gov (United States)

    Maupetit, François; Delmas, Robert J.

    1994-09-01

    Snow samples were collected as snowcores in the accumulation zone of four high altitude glaciers (2980 3540m.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, in 1990 and 1991. All samples were analysed for major ions (but also for total formate and acetate in fresh-snow samples) using ion chromatography. The acidity-alkalinity was accurately determined with a titration technique. The ion balance of alpine snow has been achieved from those analyses. High alpine snow is slightly acid (H+ 3 20 μeq 11), but is episodically affected by alkaline saharan dust events. The different sources (pollution, seasalt and soil dust) affecting the impurity content of snow were identified using principal component analysis. The measured free acidity, mainly from anthropogenic origin, originates from nitric acid scavenging while sulfuric acidity is partially neutralized by atmospheric ammonia and by alkaline soil dust derived species, the contribution of hydrochloric acid being negligible. All ions exhibit higher concentrations in spring than in winter snow, indicating most likely the influence of increased vertical transport from the lower troposphere at this time. The transport of saharan dust is described through three major events reaching the Alps during March 1990 and 1991. Very high concentrations of Ca2+ and HCO3 were measured in corresponding samples, indicating that the solubilisation of CaCO3 represents the major influence of saharan dust on the impurity content of alpine snow, shifting the pH from acid towards alkaline values. Chemical analysis suggests that during their transport, mineral alkaline particles can react through acid

  17. Simulation of wind-induced snow transport and sublimation in alpine terrain using a fully coupled snowpack/atmosphere model

    Science.gov (United States)

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

    2014-03-01

    In alpine regions, wind-induced snow transport strongly influences the spatio-temporal evolution of the snow cover throughout the winter season. To gain understanding on the complex processes that drive the redistribution of snow, a new numerical model is developed. It directly couples the detailed snowpack model Crocus with the atmospheric model Meso-NH. Meso-NH/Crocus simulates snow transport in saltation and in turbulent suspension and includes the sublimation of suspended snow particles. The coupled model is evaluated against data collected around the experimental site of Col du Lac Blanc (2720 m a.s.l., French Alps). First, 1-D simulations show that a detailed representation of the first metres of the atmosphere is required to reproduce strong gradients of blowing snow concentration and compute mass exchange between the snowpack and the atmosphere. Secondly, 3-D simulations of a blowing snow event without concurrent snowfall have been carried out. Results show that the model captures the main structures of atmospheric flow in alpine terrain. However, at 50 m grid spacing, the model reproduces only the patterns of snow erosion and deposition at the ridge scale and misses smaller scale patterns observed by terrestrial laser scanning. When activated, the sublimation of suspended snow particles causes a reduction of deposited snow mass of 5.3% over the calculation domain. Total sublimation (surface + blowing snow) is three times higher than surface sublimation in a simulation neglecting blowing snow sublimation.

  18. 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.

  19. Simulation of snow accumulation and melt in needleleaf forest environments

    Directory of Open Access Journals (Sweden)

    C. R. Ellis

    2010-06-01

    Full Text Available Drawing upon numerous field studies and modelling exercises of snow processes, the Cold Regions Hydrological Model (CRHM was developed to simulate the four season hydrological cycle in cold regions. CRHM includes modules describing radiative, turbulent and conductive energy exchanges to snow in open and forest environments, as well as account for losses from canopy snow sublimation and rain evaporation. Due to the physical-basis and rigorous testing of each module, there is a minimal need for model calibration. To evaluate CRHM, simulations of snow accumulation and melt were compared to observations collected at paired forest and clearing sites of varying latitude, elevation, forest cover density, and climate. Overall, results show that CRHM is capable of characterising the variation in snow accumulation between forest and clearing sites, achieving a model efficiency of 0.51 for simulations at individual sites. Simulations of canopy sublimation losses slightly overestimated observed losses from a weighed cut tree, having a model efficiency of 0.41 for daily losses. Good model performance was demonstrated in simulating energy fluxes to snow at the clearings, but results were degraded from this under forest cover due to errors in simulating sub-canopy net longwave radiation. However, expressed as cumulative energy to snow over the winter, simulated values were 96% and 98% of that observed at the forest and clearing sites, respectively. Overall, the good representation of the substantial variations in mass and energy between forest and clearing sites suggests that CRHM may be useful as an analytical or predictive tool for snow processes in needleleaf forest environments.

  20. Snow and ice on Bear Lake (Alaska – sensitivity experiments with two lake ice models

    Directory of Open Access Journals (Sweden)

    Tido Semmler

    2012-03-01

    Full Text Available Snow and ice thermodynamics of Bear Lake (Alaska are investigated with a simple freshwater lake model (FLake and a more complex snow and ice thermodynamic model (HIGHTSI. A number of sensitivity experiments have been carried out to investigate the influence of snow and ice parameters and of different complexity on the results. Simulation results are compared with observations from the Alaska Lake Ice and Snow Observatory Network. Adaptations of snow thermal and optical properties in FLake can largely improve accuracy of the results. Snow-to-ice transformation is important for HIGHTSI to calculate the total ice mass balance. The seasonal maximum ice depth is simulated in FLake with a bias of −0.04 m and in HIGHTSI with no bias. Correlation coefficients between ice depth measurements and simulations are high (0.74 for FLake and 0.9 for HIGHTSI. The snow depth simulation can be improved by taking into account a variable snow density. Correlation coefficients for surface temperature are 0.72 for FLake and 0.81 for HIGHTSI. Overall, HIGHTSI gives slightly more accurate surface temperature than FLake probably due to the consideration of multiple snow and ice layers and the expensive iteration calculation procedure.

  1. Using geostatistical methods to estimate snow water equivalence distribution in a mountain watershed

    Science.gov (United States)

    Balk, B.; Elder, K.; Baron, Jill S.

    1998-01-01

    Knowledge of the spatial distribution of snow water equivalence (SWE) is necessary to adequately forecast the volume and timing of snowmelt runoff.  In April 1997, peak accumulation snow depth and density measurements were independently taken in the Loch Vale watershed (6.6 km2), Rocky Mountain National Park, Colorado.  Geostatistics and classical statistics were used to estimate SWE distribution across the watershed.  Snow depths were spatially distributed across the watershed through kriging interpolation methods which provide unbiased estimates that have minimum variances.  Snow densities were spatially modeled through regression analysis.  Combining the modeled depth and density with snow-covered area (SCA produced an estimate of the spatial distribution of SWE.  The kriged estimates of snow depth explained 37-68% of the observed variance in the measured depths.  Steep slopes, variably strong winds, and complex energy balance in the watershed contribute to a large degree of heterogeneity in snow depth.

  2. Erosion dynamics of powder snow avalanches - model of frontal entrainment

    Science.gov (United States)

    Louge, Michel; Sovilla, Betty

    2013-04-01

    We analyze entrainment at the head of powder snow avalanches (PSA) behaving as an eruption current. Instead of invoking an erosion model or other fitted parameters, the analysis assumes that erosion is sustained by a massive blow-out arising as the snow cover is fluidized by the very pore pressure gradients that the avalanche induces within the snow pack. The stability of a mass balance involving snow cover and flow in the PSA's head region then sets frontal speed, height, mixed-mean density, snowpack fluidization depth, frontal impact pressure and static pressure. We show that acceleration of the front is insensitive to local slope, but effectively depends on the rate of change in cloud width. We compare predictions with data collected at the Vallee de la Sionne.

  3. Temperate forest impacts on maritime snowpacks across an elevation gradient: An assessment of the snow surface energy balance and airborne lidar derived forest structure

    Science.gov (United States)

    Roth, T. R.; Nolin, A. W.

    2016-12-01

    Temperate forests modify snow evolution patterns both spatially and temporally relative to open areas. Dense, warm forests both impede snow accumulation through increased canopy snow interception and increase sub-canopy longwave energy inputs onto the snow surface. These process modifications vary in magnitude and duration depending on climatic, topographic and forest characteristics. Here we present results from a four year study of paired forested and open sites at three elevations, Low - 1150 m, Mid - 1325 m and High - 1465 m. Snowpacks are deeper and last up to 3-4 weeks longer at the Low and Mid elevation Open sites relative to the adjacent Forest sites. Conversely, at the High Forest site, snow is retained 2-4 weeks longer than the Open site. This change in snowpack depth and persistence is attributed to deposition patterns at higher elevations and forest structure differences that alter the canopy interception efficiency and the sub-canopy energy balance. Canopy interception efficiency (CIE) in the Low and Mid Forest sites, over the duration of the study were 79% and 76% of the total event snowfall, whereas CIE was 31% at the High Forest site. Longwave radiation in forested environments is the primary energy component across each elevation band due to the warm winter environment and forest presence, accounting for 82%, 88%, and 59% of the energy balance at the Low, Mid, and High Forest sites, respectively. High wind speeds in the High elevation Open site significantly increases the turbulent energy and creates preferential snowfall deposition in the nearby Forest site. These results show the importance of understanding the effects of forest cover on sub-canopy snowpack evolution and highlight the need for improved forest cover model representation to accurately predict water resources in maritime forests.

  4. Multiple Scattering of Terrestrial Snow in X-band and Ku band Radar Remote Sensing

    Science.gov (United States)

    Xu, X.; Tsang, L.; Wenmo, C.; Yueh, S. H.

    2012-12-01

    Terrestrial snow as an important storage of the fresh water plays a key role in the global water cycle. Regional and global snow water equivalence (SWE) distribution has impact on various hydrological, meteorological applications. Using the SAR image at X band and Ku band for remote sensing of SWE is drawing more attention as it can obtain the complete spatial and temporal coverage of snow distribution under nearly all weather conditions. The satellite mission Cold Regions Hydrology High-resolution Observatory, (CoReH2O), is being evaluated by ESA and the Snow and Cold Land process (SCLP) Satellite Mission was recommended for NASA implementation in the Decadal Survey report. The electromagnetic signatures of different snow structures and snow ground interfaces are studied in both X and Ku band. To characterize the electromagnetic properties of snow, we need to establish the detailed snow structure. Recently, we developed a computer generated bi-continuous media to describe the snow structure. The Maxwell equations are directly applied and solved numerically. Then the results are combined with the dense media radiative equations so that full multiple scattering was considered. To systematically study the snow structure influence to the backscattering signal, we generate a look up table for a few typical types of snow status, such as fresh snow, depth hoar etc. The snow-ground interface is considered as rough surface. The backscattering from the surfaces is calculated through the look up table, which is generated by solving full wave simulations of Numerical Maxwell Model in 3 Dimensional (NMM3D) rough surfaces. Both co-polarization and cross-polarization are computed. The combined model is validated through comparison with recent CLPX, SnowSCAT and SnowSAR field measurements.

  5. Projections for Changes in Natural and Technical Snow Reliability of a Major Turkish Ski Resort by Using RegCM4.3.5

    Science.gov (United States)

    Ozturk, Tugba; Cenk Demiroglu, O.; Tufan Turp, M.; Türkeş, Murat; Kurnaz, M. Levent

    2014-05-01

    Climate change has been and increasingly will be a major threat to the ski tourism industry whose survival is highly dependent on existence of snow cover of sufficient depth and duration. The common knowledge requires that in order for a ski resort to be viable, it has to perform operations for at least 100 days in seven out of ten winters. For this matter, it is now even more usual for the ski resorts to adapt to this issue by technical snowmaking. In this study, projected future changes for the period of 2010-2040, 2040-2070, and 2070-2100 in air temperature, relative humidity, and snow depth climatology and variability with respect to the control period of 1970-2000 were assessed for the domain of a major ski resort in Turkey. Regional Climate Model (RegCM4.3.5) of ICTP (International Centre for Theoretical Physics) was used for projections of future and present climate conditions. HadGEM2 global climate model of the Met Office Hadley Centre, MPI-ESM-MR of the Max Planck Institute for Meteorology, GFDL-ESM2M of the National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory were downscaled to 10 km for the resort and its surrounding region. Both the projections and the downscaling were realized according to the RCP4.5 and the RCP8.5 emission scenarios of the IPCC. The outputs on snow depth were used for a count of the changes on snow cover duration sufficient for skiing actitivies, signaling natural snow-reliability, whereas the outputs on air temperature and relative humidity were utilized for determination of wet-bulb temperatures. The latter measure was used to interpret the changes in the snowmaking capacity, in other words; technical snow-reliability, of the resort. This work was supported by the BU Reasearch Fund under the project number 7362. One of the authors (MLK) was partially supported by Mercator-IPC Fellowship Program.

  6. The Kühtai data set: 25 years of lysimetric, snow pillow, and meteorological measurements

    Science.gov (United States)

    Kirnbauer, R.; Parajka, J.; Schöber, J.; Blöschl, G.

    2017-01-01

    Abstract Snow measurements at the Kühtai station in Tirol, Austria, (1920 m.a.s.l.) are described. The data set includes snow water equivalent from a 10 m2 snow pillow, snow melt outflow from a 10 m2 snow lysimeter placed at the same location as the pillow, meteorological data (precipitation, incoming shortwave radiation, reflected shortwave radiation, air temperature, relative air humidity, and wind speed), and other data (snow depths, snow temperatures at seven heights) from the period October 1990 to May 2015. All data have been quality checked, and gaps in the meteorological data have been filled in. The data set is unique in that all data are available at a temporal resolution of 15 min over a period of 25 years with minimal changes in the experimental setup. The data set can therefore be used to analyze snow pack processes over a long‐time period, including their extremes and long‐term changes, in an Alpine climate. Analyses may benefit from the combined measurement of snow water equivalent, lysimeter outflow, and precipitation at a wind‐sheltered alpine site. An example use of data shows the temporal variability of daily and 1 April snow water equivalent observed at the Kühtai site. The results indicate that the snow water equivalent maximum varies between 200 and more than 500 mm w.e., but there is no statistically significant temporal trend in the period 1990–2015. PMID:28931957

  7. Development of a land surface model with coupled snow and frozen soil physics

    Science.gov (United States)

    Wang, Lei; Zhou, Jing; Qi, Jia; Sun, Litao; Yang, Kun; Tian, Lide; Lin, Yanluan; Liu, Wenbin; Shrestha, Maheswor; Xue, Yongkang; Koike, Toshio; Ma, Yaoming; Li, Xiuping; Chen, Yingying; Chen, Deliang; Piao, Shilong; Lu, Hui

    2017-06-01

    Snow and frozen soil are important factors that influence terrestrial water and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new land surface model (LSM) with coupled snow and frozen soil physics was developed based on a hydrologically improved LSM (HydroSiB2). First, an energy-balance-based three-layer snow model was incorporated into HydroSiB2 (hereafter HydroSiB2-S) to provide an improved description of the internal processes of the snow pack. Second, a universal and simplified soil model was coupled with HydroSiB2-S to depict soil water freezing and thawing (hereafter HydroSiB2-SF). In order to avoid the instability caused by the uncertainty in estimating water phase changes, enthalpy was adopted as a prognostic variable instead of snow/soil temperature in the energy balance equation of the snow/frozen soil module. The newly developed models were then carefully evaluated at two typical sites of the Tibetan Plateau (TP) (one snow covered and the other snow free, both with underlying frozen soil). At the snow-covered site in northeastern TP (DY), HydroSiB2-SF demonstrated significant improvements over HydroSiB2-F (same as HydroSiB2-SF but using the original single-layer snow module of HydroSiB2), showing the importance of snow internal processes in three-layer snow parameterization. At the snow-free site in southwestern TP (Ngari), HydroSiB2-SF reasonably simulated soil water phase changes while HydroSiB2-S did not, indicating the crucial role of frozen soil parameterization in depicting the soil thermal and water dynamics. Finally, HydroSiB2-SF proved to be capable of simulating upward moisture fluxes toward the freezing front from the underlying soil layers in winter.

  8. Distribution and habitat use of the Bluenose caribou herd in mid-winter

    Directory of Open Access Journals (Sweden)

    D. R. Carruthers

    1986-06-01

    Full Text Available The mid-winter distribution and densities of the Bluenose caribou herd were compared with previous surveys over six years and were similar in all years except 1981 when exceptionally mild weather prevailed. Differences in group size, distribution and habitat use between sexes were noted in 1983. Caribou were distributed disproportionately to availability of vegetation types and used lakes significantly more than expected based on their occurrence. Male groups used conifer cover more than did female-calf groups which used open areas (lakes, fens, bogs more than males. Cow-calf groups chose areas with a higher small lake density compared to lake density generally available. Generally caribou preferred habitat between 200 and 300 m in elevation with high densities of lakes less than 1 km2 in size. Snow depths and hardness were greater in most unoccupied habitats than in occupied habitats. Wolves were associated with high densities of cow/calf groups.

  9. WINTER SAECULUM

    Directory of Open Access Journals (Sweden)

    Emil Mihalina

    2017-03-01

    Full Text Available Accumulated imbalances in the economy and on the markets cause specific financial market dynamics that have formed characteristic patterns kept throughout long financial history. In 2008 Authors presented their expectations of key macroeconomic and selected asset class markets developments for period ahead based on Saeculum theory. Use of term Secular describes a specific valuation environment during prolonged period. If valuations as well as selected macro variables are considered as a tool for understanding business cycles then market cycles become much more obvious and easily understandable. Therefore over the long run, certain asset classes do better in terms of risk reward profile than others. Further on, there is no need for frequent portfolio rebalancing and timing of specific investment positions within a particular asset class market. Current stage in cycle development suggests a need for reassessment of trends and prevailing phenomena due to cyclical nture of long lasting Saeculums. Paper reviews developments in recognizable patterns of selected metrics in current Winter Saeculum dominated with prevailing forces of delivering, deflation and decrease in velocity of money.

  10. Snow route optimization.

    Science.gov (United States)

    2016-01-01

    Route optimization is a method of creating a set of winter highway treatment routes to meet a range of targets, including : service level improvements, resource reallocation and changes to overriding constraints. These routes will allow the : operato...

  11. 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

  12. Run-off of strontium with melting snow in spring

    International Nuclear Information System (INIS)

    Quenild, C.; Tveten, U.

    1986-09-01

    When assessing the consequences of atmospheric releases caused by a large reactor accident, one usually finds that the major contributions to the dose are via nutrition and from exposure to radiation from radioactive materials deposited on ground. The experiment described is concerned with run-off from agricultural surface which has been contaminated with strontiom while covered with snow. Migration experiments show a significant difference between summer and winter conditions. Roughly 54% of the strontium with which the experimental area was contaminated, ran off with the melt-water. Under winter conditions, portions of the contaminant will flow with the melt-water without coming in contact with the soil

  13. Increasing the efficiency of the process of snow mass utilization from the urban infrastructure and reducing the negative impact on the environment through the introduction of an installation for the utilization of snow mass

    Science.gov (United States)

    Dovbysh, V. O.; Burakova, L. N.; Burakova, A. D.

    2018-01-01

    The article raises the problem of the maintenance of the urban area in winter, namely, the problem of disposal of snow masses from the urban area. The article describes the main disadvantages of the existing snow-melting systems for the utilization of city snow mass and are encouraged to develop an installation for melting of snow, functioning at the expense of power consumption. The developed installation allows to reduce the noise level during its operation, to exclude the influence of exhaust gases on the environment, therefore, to improve the environmental safety of the urban infrastructure.

  14. The performance of a simple degree-day estimate of snow accumulation to an alpine watershed

    Science.gov (United States)

    R. A. Sommerfeld; R. C. Musselman; G. L. Wooldridge; M. A. Conrad

    1991-01-01

    We estimated the yearly snow accumulation to the Glacier Lakes Ecosystems Experiments Site (GLEES) for the winters of 1987-88, 1988-89, and 1989-90, using a simple degree-day model developed by J. Martinec and A. Rango. Comparisons with other data indicate that the estimates are accurate. In particular, a calibration with an intensive snow core-probe survey in 1989-90...

  15. 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...

  16. The influence of snow cover on alpine floods reconstructed from the analysis of satellite images. The case of the Hasli-Aare river basin, Berner Oberland (1987-2012)

    Science.gov (United States)

    Cabrera-Medina, Paula; Schulte, Lothar; Carvalho, Filipe; Peña, Juan Carlos; García, Carles

    2016-04-01

    Regarding the hydrological hazards in the Hasli-Aare river over the last century, instrumental and documentary data show that flood frequency and magnitude increased since 1977. One of the main water inputs contributing to peak discharges is given by the thaw of the stored snow. Therefore, the knowledge of the evolution of snow cover is considered essential for the assessment of alpine floods. Snow cover studies can be made by different approaches such as the analysis of data provided by field work or by nivometeorological stations. However, these methods are usually expensive and do not present adequate spatial or temporal coverage data. For this reason, satellite images with different spatial and temporal resolution are an interesting complementary source for the understanding of the snow cover dynamics. The aim of the paper is to study the influence of snow cover variations during years of severe floods that occurred in the upper Aare basin from 1987 to 2012. Three satellite images have been selected for each of the 9 studied events: 1) maximum snow cover during winter, 2) the last image before the event and 3) the first image after the flood. Each image has been processed with the ArcGIS software applying a statistical method of supervised classification. This image processing allows the spatial quantification of the variation of the snow cover in the Aare headwater catchment. Because the melting of snow cover is related to the changes of weather situations before and during the flood episode, it is important to analyse also the nivometeorological data of stations located in the catchment (snow depth, temperature and precipitation). From these data we determined 4 types of flood, which can be classified according to their nivometeorological variables and synoptic situation (500 hPa geopotential and Sea Level Pressure) into two patterns. The first group of events can be associated to an Atlantic pattern recording decreasing temperatures, moderate to high

  17. Winter Weather: Frostbite

    Science.gov (United States)

    ... Safety During Fire Cleanup Wildfires PSAs Related Links Winter Weather About Winter Weather Before a Storm Prepare Your Home Prepare Your Car Winter Weather Checklists During a Storm Indoor Safety During ...

  18. Weak layer fracture: facets and depth hoar

    Directory of Open Access Journals (Sweden)

    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.

  19. 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...

  20. Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data

    Science.gov (United States)

    Zheng, Z.; Kirchner, P. B.; Bales, R. C.

    2016-01-01

    Airborne light detection and ranging (lidar) measurements carried out in the southern Sierra Nevada in 2010 in the snow-free and peak-snow-accumulation periods were analyzed for topographic and vegetation effects on snow accumulation. Point-cloud data were processed from four primarily mixed-conifer forest sites covering the main snow-accumulation zone, with a total surveyed area of over 106 km2. The percentage of pixels with at least one snow-depth measurement was observed to increase from 65-90 to 99 % as the sampling resolution of the lidar point cloud was increased from 1 to 5 m. However, a coarser resolution risks undersampling the under-canopy snow relative to snow in open areas and was estimated to result in at least a 10 cm overestimate of snow depth over the main snow-accumulation region between 2000 and 3000 m, where 28 % of the area had no measurements. Analysis of the 1 m gridded data showed consistent patterns across the four sites, dominated by orographic effects on precipitation. Elevation explained 43 % of snow-depth variability, with slope, aspect and canopy penetration fraction explaining another 14 % over the elevation range of 1500-3300 m. The relative importance of the four variables varied with elevation and canopy cover, but all were statistically significant over the area studied. The difference between mean snow depth in open versus under-canopy areas increased with elevation in the rain-snow transition zone (1500-1800 m) and was about 35 ± 10 cm above 1800 m. Lidar has the potential to transform estimation of snow depth across mountain basins, and including local canopy effects is both feasible and important for accurate assessments.

  1. Introduction to snow rheology

    International Nuclear Information System (INIS)

    Montmollin, Vincent de

    1978-01-01

    The tests described in the thesis are rotating shearing tests, with rotational constant speed ranging between 0.00075 rpm and 0.75 rpm. The results obtained are similar to those observed with compression tests at constant speed, except that shearing tests are carried out with densities nearly constant. So, we show three different domains when the rotation speed increases: 1) viscous (without failure) 2) brittle of first type (cycles of brittle failures) and 3) brittle of second type (only one brittle failure and solid friction). These results show clearly that the fundamental mechanism that rules the mechanisms of snow, is fast metamorphosis of bonds, binding ice grains: this metamorphosis is important when solicitation speeds are low (permanent rate of shearing in viscous domain, regeneration of the failure surfaces in the brittle domain of the first type) and this metamorphosis does not exist when speed increases (only one failure and solid friction in the brittle domain of second type). It is also included an important bibliographic analysis of the snow mechanics, and an experimental and theoretical study about shock wave propagation in natural snow covers. (author) [fr

  2. Application of snow models to snow removal operations on the Going-to-the-Sun Road, Glacier National Park

    Science.gov (United States)

    Fagre, Daniel B.; Klasner, Frederick L.

    2000-01-01

    Snow removal, and the attendant avalanche risk for road crews, is a major issue on mountain highways worldwide. The Going-to-the-Sun Road is the only road that crosses Glacier National Park, Montana. This 80-km highway ascends over 1200m along the wall of a glaciated basin and crosses the continental divide. The annual opening of the road is critical to the regional economy and there is public pressure to open the road as early as possible. Despite the 67-year history of snow removal activities, few stat on snow conditions at upper elevations were available to guide annual planning for the raod opening. We examined statistical relationships between the opening date and nearby SNOTEL data on snow water equivalence (WE) for 30 years. Early spring SWE (first Monday in April) accounted for only 33% of the variance in road opening dates. Because avalanche spotters, used to warn heavy equipment operators of danger, are ineffective during spring storms or low-visibility conditions, we incorporated the percentage of days with precipitation during plowing as a proxy for visibility. This improved the model's predictive power to 69%/ A mountain snow simulator (MTSNOW) was used to calculate the depth and density of snow at various points along the road and field data were collected for comparison. MTSNOW underestimated the observed snow conditions, in part because it does not yet account for wind redistribution of snow. The severe topography of the upper reaches of the road are subjected to extensive wind redistribution of snow as evidence by the formation of "The Big Drift" on the lee side of Logan Pass.

  3. Surviving winter: Food, but not habitat structure, prevents crashes in cyclic vole populations

    OpenAIRE

    Johnsen, Kaja; Boonstra, Rudy; Boutin, Stan; Devineau, Olivier; Krebs, Charles J.; Andreassen, Harry Peter

    2016-01-01

    Vole population cycles are a major force driving boreal ecosystem dynamics in north - western Eurasia. However, our understanding of the impact of winter on these cycles is increasingly uncertain, especially because climate change is affecting snow predict - ability, quality, and abundance. We examined the role of winter weathe...

  4. 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.

  5. 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.

  6. Validating the EUMETSAT HSAF Snow Recognition Product over Mountainous Areas of Turkey

    Science.gov (United States)

    Surer, S.; Akyurek, Z.; Sorman, A. U.

    2009-12-01

    An algorithm has been running in order to produce real-time snow cover maps from MSG-SEVIRI sensor imagery, covering whole Europe, for more than two years under the framework of EUMETSAT Hydrology-SAF (HSAF) Project. Hydrological processes and climate in the mountainous areas are highly affected by the seasonal snow cover. Due to lack of enough field observations because of the inaccessibility of high mountains, it is convenient to monitor the amount of snow with remote sensing satellite data besides setting up and managing ground weather stations. Developed algorithm is based on a multi-spectral thresholding method which uses visible, shortwave-infrared and near-infrared channels of MSG-SEVIRI. For a single day, 32 successive satellite images which have 15 minutes time interval between each of them are interpreted in order to produce a daily snow cover map. The algorithm uses Nowcasting-SAF (SAFNWC) cloud products in classifying the clouds. In this study 2007-2008 and 2008-2009 snow melting seasons are considered for the validation and evaluation purposes of the HSAF snow recognition product. The validation is performed for the mountainous region in the eastern part of Turkey on a daily basis by using the ground observations from 30 climate stations operated by Turkish State Meteorological Service (TSMS). The snow depth was recorded to the nearest 1 cm and reported in integer form. Besides the validation of snow product with ground data, the utility of the snow product in deriving the snow depletion curves (SDC) is evaluated. Other satellite snow products namely, MODIS 8-day snow cover data (MOD10C2) are also used in deriving the snow depletion curves. Results show high agreement between ground snow measurements and HSAF snow recognition product. The overall accuracies for 2008 and 2009 are calculated as 90.96 % and 80.59 % respectively. The commission error for 2008 is 8.12 % whereas for 2009 it is calculated as 17.03 %. The high cloud coverage percentage

  7. Verifying Snow Photochemistry Models by Combining Actinometry and UV Radiometry

    Science.gov (United States)

    Phillips, G. J.; Simpson, W. R.

    2003-12-01

    In the past few years, experiments and modeling studies have shown that chemical processes in the snow pack may have significant impacts on the chemistry of the atmosphere. A number of these studies have suggested that solar UV radiation penetrating the snow pack is the driving force for some of these chemical processes. Owing to the need to quantify the extent of the photochemical processing in the snow pack, radiative transfer models have been developed for use in the snow pack. The goal of this study is the development and performance testing of radiative transfer models constrained with photometric measurements of UV irradiance. To test these models, we compare the modeled photolysis rates to photolysis rates measured by chemical actinometry within an artificial snow-like scattering medium. This snow analog was made by flash freezing small droplets of a dilute actinometer solution in liquid nitrogen. Radiative transfer models based on both the delta-Eddington and the DISORT methods were used. The DISORT model was TUV, developed by Lee-Taylor and Madronich. To use these models, measurements of the snow analog's optical properties are needed. The light attenuation and intensity were measured in the scattering medium using a cosine- response sensor coupled to a spectrometer by fiber optic. With these optical properties constraining the model, we can then predict photolysis rates as a function of depth within the snow analog. The veracity of the radiative transfer models in the absence of light scattering was tested using 2-nitrobenzaldehyde (NBA) as an actinometer in liquid solution. The model results were found to have good agreement with the actinometer in this control experiment. The photolysis rate of NBA with respect to depth was measured from the conversion of the NBA to 2-nitrosobenzoic acid. The snow analog was irradiated with a UV light source. After exposure, samples of the snow analog were collected with respect to depth and the conversion of the

  8. 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...

  9. Simulation of wind-induced snow transport in alpine terrain using a fully coupled snowpack/atmosphere model

    Science.gov (United States)

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

    2013-06-01

    In alpine regions, wind-induced snow transport strongly influences the spatio-temporal evolution of the snow cover throughout the winter season. To gain understanding on the complex processes that drive the redistribution of snow, a new numerical model is developed. It couples directly the detailed snowpack model Crocus with the atmospheric model Meso-NH. Meso-NH/Crocus simulates snow transport in saltation and in turbulent suspension and includes the sublimation of suspended snow particles. A detailed representation of the first meters of the atmosphere allows a fine reproduction of the erosion and deposition process. The coupled model is evaluated against data collected around the experimental site of Col du Lac Blanc (2720 m a.s.l., French Alps). For this purpose, a blowing snow event without concurrent snowfall has been selected and simulated. Results show that the model captures the main structures of atmospheric flow in alpine terrain, the vertical profile of wind speed and the snow particles fluxes near the surface. However, the horizontal resolution of 50 m is found to be insufficient to simulate the location of areas of snow erosion and deposition observed by terrestrial laser scanning. When activated, the sublimation of suspended snow particles causes a reduction in deposition of 5.3%. Total sublimation (surface + blowing snow) is three times higher than surface sublimation in a simulation neglecting blowing snow sublimation.

  10. Food, energy, and water in an era of disappearing snow

    Science.gov (United States)

    Mote, P.; Lettenmaier, D. P.; Li, S.; Xiao, M.

    2017-12-01

    Mountain snowpack stores a significant quantity of water in the western US, accumulating during the wet season and melting during the dry summers and supplying more than 65% of the water used for irrigated agriculture, energy production (both hydropower and thermal), and municipal and industrial uses. The importance of snow to western agriculture is demonstrated by the fact that most snow monitoring is performed by the US Department of Agriculture. In a paper published in 2005, we showed that roughly 70% of monitoring sites showed decreasing trends through 2002. Now, with 14 additional years of data, over 90% of snow monitoring sites with long records across the western US show declines through 2016, of which 33% are significant (vs 5% expected by chance) and 2% are significant and positive (vs 5% expected by chance). Declining trends are observed across all months, states, and climates, but are largest in spring, in the Pacific states, and in locations with mild winter climate. We corroborate and extend these observations using a gridded hydrology model, which also allows a robust estimate of total western snowpack and its decline. Averaged across the western US, the decline in total April 1 snow water equivalent since mid-century is roughly 15-30% or 25-50 km3, comparable in volume to the West's largest man-made reservoir, Lake Mead. In the absence of rapid reductions in emissions of greenhouse gases, these losses will accelerate; snow losses on this scale demonstrate the necessity of rethinking water storage, policy, and usage.

  11. 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.

  12. Experimental study of snow friction

    Science.gov (United States)

    Cohen, Caroline; Canale, Luca; Siria, Alessandro; Quere, David; Bocquet, Lyderic; Clanet, Christophe

    2017-11-01

    Snow friction results from the interplay of different physical processes: solid friction of granular material, phase change and lubrication, heat transport, capillarity, elasticity and plasticity. The multiple conditions of temperature, humidity and density of the snow result in different regimes of friction. In particular, there is an optimal amount of melted water to lubricate the contact between the ski sole and the snow grains. The thickness of the water layer depends on temperature, speed... A huge variety of waxes have been empirically developed to adapt the amount of water to the conditions of skiing, but remain mysterious. In these study, we investigate experimentally the mechanisms of snow friction at different scales: first, the friction of a ski on snow is measured on a test bench, depending on the snow characteristics and for different waxes. Then microscopic experiments are led in order to understand the friction at the ice crystals scale.

  13. 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.

  14. Canadian snow and sea ice: historical trends and projections

    Science.gov (United States)

    Mudryk, Lawrence R.; Derksen, Chris; Howell, Stephen; Laliberté, Fred; Thackeray, Chad; Sospedra-Alfonso, Reinel; Vionnet, Vincent; Kushner, Paul J.; Brown, Ross

    2018-04-01

    The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state of the art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. Here, we present an assessment from the CanSISE Network on trends in the historical record of snow cover (fraction, water equivalent) and sea ice (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea ice likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and ice is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer sea ice cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year ice loss in the Beaufort Sea and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020-2050 period shows reductions in fall and spring snow cover fraction and sea ice concentration of 5-10 % per decade (or 15-30 % in total), with similar reductions in winter sea ice concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10 % per decade (30 % in total) are projected across southern Canada.

  15. MODIS Snow-Cover Products

    Science.gov (United States)

    Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; DiGirolamo, Nicole E.; Bayr, Klaus J.; Houser, Paul R. (Technical Monitor)

    2002-01-01

    On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. MODIS snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to or enhancement of the currently-available operational products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The MODIS snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at about 5.6-km spatial resolution, with both daily and 8-day composite products. Each pixel of the CMG contains fraction of snow cover from 40 - 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02 - 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented to show some early validation work.

  16. Boreal Ecosystem-Atmosphere Study/FFC-Winter (BOREAS) Campaign MODIS Airborne Simulator (MAS) Level-1B Data Products

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of the Boreal Ecosystem-Atmosphere Study/FFC-Winter (BOREAS) campaign was to study Snow and Ice Detection over Glacier National Park in Montana and...

  17. A Vision for an International Multi-Sensor Snow Observing Mission

    Science.gov (United States)

    Kim, Edward

    2015-01-01

    Discussions within the international snow remote sensing community over the past two years have led to encouraging consensus regarding the broad outlines of a dedicated snow observing mission. The primary consensus - that since no single sensor type is satisfactory across all snow types and across all confounding factors, a multi-sensor approach is required - naturally leads to questions about the exact mix of sensors, required accuracies, and so on. In short, the natural next step is to collect such multi-sensor snow observations (with detailed ground truth) to enable trade studies of various possible mission concepts. Such trade studies must assess the strengths and limitations of heritage as well as newer measurement techniques with an eye toward natural sensitivity to desired parameters such as snow depth and/or snow water equivalent (SWE) in spite of confounding factors like clouds, lack of solar illumination, forest cover, and topography, measurement accuracy, temporal and spatial coverage, technological maturity, and cost.

  18. Sensitivity of the French Alps snow cover to the variation of climatic variables

    Directory of Open Access Journals (Sweden)

    E. Martin

    Full Text Available In order to study the sensitivity of snow cover to changes in meteorological variables at a regional scale, a numerical snow model and an analysis system of the meteorological conditions adapted to relief were used. This approach has been successfully tested by comparing simulated and measured snow depth at 37 sites in the French Alps during a ten year data period. Then, the sensitivity of the snow cover to a variation in climatic conditions was tested by two different methods, which led to very similar results. To assess the impact of a particular "doubled CO2" scenario, coherent perturbations were introduced in the input data of the snow model. It was found that although the impact would be very pronounced, it would also be extremely differentiated, dependent on the internal state of the snow cover. The most sensitive areas are the elevations below 2400 m, especially in the southern part of the French Alps.

  19. Vertical profiles of specific surface area, thermal conductivity and density of mid-latitude, Arctic and Antarctic snow: relationships between snow physics and climat

    Science.gov (United States)

    Domine, F.; Arnaud, L.; Bock, J.; Carmagnola, C.; Champollion, N.; Gallet, J.; Lesaffre, B.; Morin, S.; Picard, G.

    2011-12-01

    We have measured vertical profiles of specific surface area (SSA), thermal conductivity (TC) and density in snow from 12 different climatic regions featuring seasonal snowpacks of maritime, Alpine, taiga and tundra types, on Arctic sea ice, and from ice caps in Greenland and Antarctica. We attempt to relate snow physical properties to climatic variables including precipitation, temperature and its yearly variation, wind speed and its short scale temporal variations. As expected, temperature is a key variable that determines snow properties, mostly by determining the metamorphic regime (temperature gradient or equi-temperature) in conjunction with precipitation. However, wind speed and wind speed distribution also seem to have an at least as important role. For example high wind speeds determine the formation of windpacks of high SSA and high TC instead of depth hoar with lower values of these variables. The distribution of wind speed also strongly affects properties, as for example frequent moderate winds result in frequent snow remobilization, producing snow with higher SSA and lower TC than regions with the same average wind speeds, but with less frequent and more intense wind episodes. These strong effects of climate on snow properties imply that climate change will greatly modify snow properties, which in turn will affect climate, as for example changes in snow SSA modify albedo and changes in TC affect permafrost and the release of greenhouse gases from thawing permafrost. Some of these climate-snow feedbacks will be discussed.

  20. Antarctic snow and global climate

    International Nuclear Information System (INIS)

    Granberg, H.B.

    2001-01-01

    Global circulation models (GCM) indicate that global warming will be most pronounced at polar regions and high latitudes, causing concern about the stability of the Antarctic ice cap. A project entitled the Seasonal Snow in Antarctica examined the properties of the near surface snow to determine the current conditions that influence snow cover development. The goal was to assess the response of the snow cover in Queen Maud Land (QML) to an increased atmospheric carbon dioxide content. The Antarctic snow cover in QML was examined as part of the FINNARP expeditions in 1999 and 2000 which examined the processes that influence the snow cover. Its energy and mass balance were also assessed by examining the near surface snow strata in shallow (1-2 m) pits and by taking measurements of environmental variables. This made it possible to determine if the glacier is in danger of melting at this northerly location in the Antarctic. The study also made it possible to determine which variables need to change and by how much, for significant melting to occur. It was shown that the Antarctic anticyclone creates particular conditions that protect the snow cover from melting. The anticyclone brings dry air from the stratosphere during most of the year and is exempt from the water vapour feedback. It was concluded that even a doubling of atmospheric carbon dioxide will not produce major snow melt runoff. 8 refs

  1. 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.

  2. Snow cover monitoring in the Kyrgyz Republic through MODIS time series (2000-2010)

    Science.gov (United States)

    Dedieu, J.-P.; Doutreleau, V.; Lessard-Fontaine, A.; Shalpykova, G.

    2012-04-01

    The Kyrgyz Republic is located at the convergence of two mountain systems (Tien Shan and Pamirs) in Central Asia. The region is of great interest all of Central Asia because of its consequent capital in water resources. Theses resources are of importance for electricity production (~15 TWH/year) and irrigation of agricultural land. Over 50% of the 52 km3 of Kyrgyz runoff water irrigates the Syr Darya River which flows over 2200 km from the confluence of Naryn and Kara Darya rivers to the Aral Sea. Around 40% of the Kyrgyz territory lies above 3000m; part of the water resource is cumulated as snow during large periods of the year. Snow cover is thus an important part of the Kyrgyz hydrological cycle. In this already water-stressed region, both climate change and irrigation expansion could trigger a greater scarcity of the resource in the future. One of the major impact could be a modification of the melting season period and the snow melt behavior. The use of passive optical remote sensing data could provide helpful complementary information for hydrological modeling of these effects, but currently, very few scientific publications concerning the Syr Darya headwaters in Kyrgyztan exist. Integrated in the EU-FP7 ACQWA Project (www.acqwa.ch), this study proposes 11 years of snow cover analysis using MODIS snow cover product data. The following parameters are retrieved from MODIS data: Snow Cover Area (SCA), Snow Fraction (FRA), snow cover duration and depletion maps. A Digital Elevation Model (DEM) from the NASA-SRTM database is used to better understand the topographic influence on snow melt behavior and a Land Use database (GlobCover 2009) for the environmental context of snow cover evolution. A statistical analysis of snow cover dynamics is performed on a 2000-2010 8-days temporal resolution dataset. Yearly mean snow cover is 40 ± 5 % and melting runs with 5%.8j-1 average velocity. We observe a greater variation of the inter-annual snow cover extent in winter

  3. Method to determine snow albedo values in the ultraviolet for radiative transfer modeling.

    Science.gov (United States)

    Schwander, H; Mayer, B; Ruggaber, A; Albold, A; Seckmeyer, G; Koepke, P

    1999-06-20

    For many cases modeled and measured UV global irradiances agree to within +/-5% for cloudless conditions, provided that all relevant parameters for describing the atmosphere and the surface are well known. However, for conditions with snow-covered surfaces this agreement is usually not achievable, because on the one hand the regional albedo, which has to be used in a model, is only rarely available and on the other hand UV irradiance alters with different snow cover of the surface by as much as 50%. Therefore a method is given to determine the regional albedo values for conditions with snow cover by use of a parameterization on the basis of snow depth and snow age, routinely monitored by the weather services. An algorithm is evolved by multiple linear regression between the snow data and snow-albedo values in the UV, which are determined from a best fit of modeled and measured UV irradiances for an alpine site in Europe. The resulting regional albedo values in the case of snow are in the 0.18-0.5 range. Since the constants of the regression depend on the area conditions, they have to be adapted if the method is applied for other sites. Using the algorithm for actual cases with different snow conditions improves the accuracy of modeled UV irradiances considerably. Compared with the use of an average, constant snow albedo, the use of actual albedo values, provided by the algorithm, halves the average deviations between measured and modeled UV global irradiances.

  4. Snow and SMOW

    International Nuclear Information System (INIS)

    1967-01-01

    In the midst of Vienna's hottest weather spell this year, members of the Agency's headquarters laboratory staff found themselves unpacking a consignment of fresh snow from the Antarctic. It had been sent by air through Los Angeles, not for cooling purposes, but to assist in making more accurate measurements as part of the study of the world's water distribution and movement. The same research also involves SMOW (Standard Mean Ocean Water) and samples of water from the mid-Pacific will also soon arrive for scientific examination

  5. 'Snow White' in Color

    Science.gov (United States)

    2008-01-01

    This color image taken by the Surface Stereo Imager on NASA's Phoenix Mars Lander shows the trench dubbed 'Snow White,' after further digging on the 25th Martian day, or sol, of the mission (June 19, 2008). The lander's solar panel is casting a shadow over a portion of the trench. The trench is about 5 centimeters (2 inches) deep and 30 centimeters (12 inches) long. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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

  8. A novel multi-temporal approach to wet snow retrieval with Sentinel-1 images (Conference Presentation)

    Science.gov (United States)

    Marin, Carlo; Callegari, Mattia; Notarnicola, Claudia

    2016-10-01

    Snow is one of the most relevant natural water resources present in nature. It stores water in winter and releases it in spring during the melting season. Monitoring snow cover and its variability is thus of great importance for a proactive management of water-resources. Of particular interest is the identification of snowmelt processes, which could significantly support water administration, flood prediction and prevention. In the past years, remote sensing has demonstrated to be an essential tool for providing accurate inputs to hydrological models concerning the spatial and temporal variability of snow. Even though the analysis of snow pack can be conducted in the visible, near-infrared and short-wave infrared spectrum, the presence of clouds during the melting season, which may be pervasive in some parts of the World (e.g., polar regions), renders impossible the regular acquisition of information needed for the operational purposes. Therefore, the use of the microwave sensors, which signal can penetrate the clouds, can be an asset for the detection of snow proprieties. In particular, the SAR images have demonstrated to be effective and robust measurements to identify the wet snow. Among the several methods presented in the literature, the best results in wet snow mapping have been achieved by the bi-temporal change detection approach proposed by Nagler and Rott [1], or its slight improvements presented afterwards (e.g., [2]). Nonetheless, with the introduction of the Sentinel-1 by ESA, which provides free-of-charge SAR images every 6 days over the same geographical area with a resolution of 20m, the scientists have the opportunity to better investigate and improve the state-of-the-art methods for wet snow detection. In this work, we propose a novel method based on a supervised learning approach able to exploit both the experience of the state-of-the-art algorithms and the high multi-temporal information provided by the Sentinel-1 data. In detail, this is done

  9. Sampling in the Snow

    Science.gov (United States)

    Hanson, Eric; Burakowski, Elizabeth

    2015-01-01

    For much of the northern United States, the months surrounding the winter solstice are a time of increased darkness, low temperatures, and frozen landscapes. Each year, the ubiquitous white ice crystals that blanket regions of the north go uninvestigated. Instead of hunkering down indoors with their classes, however, teachers can take advantage of…

  10. Aerial view of CERN under the snow

    CERN Multimedia

    CERN PhotoLab

    1963-01-01

    In this photograph taken in the winter of 1963, CERN still looks quite bare under its mantle of snow. The Proton Synchrotron (PS), resembling a bicycle wheel in shape, had been in operation since the summer of 1959. A proposal had just been made for the site of CERN's second large project, the Intersecting Storage Rings (ISR): France was to house the world's first proton-proton collider. In September 1965, the French authorities signed an agreement making more than 40 hectares of land available for the extension of the CERN site established in Switzerland into French territory. The ISR project received final approval from the CERN Council in December 1965. The civil engineering work on the French part began in November 196

  11. Snow Plow Activity (2015-2016)

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — Snow Plow data from the the City of Pittsburgh's Snow Plow Tracker. These data are collected from the Snow Plow Tracker's Fusion Table and converted to geoJSON....

  12. 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)

  13. Snow sublimation on a high-altitude Himalayan glacier

    Science.gov (United States)

    Stigter, E.; Litt, M.; Steiner, J. F.; Bonekamp, P. N. J.; Bierkens, M. F.; Shea, J.; Immerzeel, W. W.

    2017-12-01

    Snow sublimation is a loss of water from a snowpack to the atmosphere due to direct phase transition of snow to water vapour. Conditions at high elevations in the Himalaya favour sublimation, i.e. low atmospheric pressure, high wind speed, dry air and high incoming solar radiation. Snow sublimation is a potential important component of the high-altitude water and glacier mass balance, but measurements are non-existent in the Himalaya and models generally ignore this process. Hence, we measured surface latent heat fluxes with an eddy covariance system on Yala Glacier (5350 m a.s.l) in the Nepalese Himalaya to quantify the role snow sublimation plays in the water budget. A one-month data set from October to November 2016 reveals that cumulative sublimation is substantial relative to the dry season precipitation (31 mm for a 32-day period). Sublimation parameterizations of different complexity were subsequently tested against our field measurements to quantify sublimation patterns in space and over longer periods based on nominal meteorological measurements. Results show that a multiple linear regression on wind speed and humidity performed best and this is used to simulate snow sublimation spatially distributed on Yala Glacier for the winter season 2016-2017. Averaged over an entire winter and over the entire glacier surface, sublimation plays a crucial role in the high altitude water balance and in the mass balance of glaciers. Future research should focus on quantifying the role of sublimation at the catchment scale, the development of larger scale parametrizations and efficient measurement strategies to validate the results.

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

    Science.gov (United States)

    Seong, D. K.; Seok, S. W.; Eun, S. H.; Kim, B. G.; Reum, K. A.; Lee, K. M.; Jeon, H. R.; Byoung Choel, C.; Park, Y. S.

    2015-12-01

    Characteristics of heavy snowfall and snow crystal habits have been investigated in the campaign of Experiment on Snow Storms At Yeongdong (ESSAY) using radiosonde soundings, Global Navigation Satellite System (GNSS), and a digital camera with a magnifier for taking a photograph of snowfall crystals. The analysis period is mainly both winters of 2014 and 2015. The synoptic situations are similar to those of the previous studies such as the Low pressure system passing by the far South of the Korean peninsula along with the Siberian High extending to northern Japan, which eventually results in the northeasterly or easterly flows and the long-lasting snowfall episodes in the Yeongdong region. The snow crystal habits observed in the ESSAY campaign were mainly dendrite, consisting of 70% of the entire habits. The rimed habits were frequently captured when two-layered clouds were observed, probably through the process of freezing of super-cooled droplets on the ice particles. The homogeneous habit such as dendrite was shown in case of shallow clouds with its thickness of below 500 m whereas various habits were captured such as graupel, dendrites, rimed dendrites, aggregates of dendrites, plates, rimed plates, etc in the thick cloud with its thickness greater than 1.5 km. The dendrites appeared to be dominant in the condition of cloud top temperature specifically ranging -12~-16℃. Interestingly temporal evolutions of snow crystal habits were consistently shown for several snowfall events such as changes from rimed particles to dendrites(or aggregated dendrites). The association of snow crystal habits with temperature and super-saturation in the cloud will be in detail examined. However, better understandings of characteristics of snow crystal habits would contribute to preventing breakdown accidents such as a greenhouse destruction and collapse of a temporary building due to heavy snowfall, and traffic accidents due to snow-slippery road condition, providing a higher

  15. Rainwater propagation through snowpack during rain-on-snow sprinkling experiments under different snow conditions

    Directory of Open Access Journals (Sweden)

    R. Juras

    2017-09-01

    Full Text Available The mechanisms of rainwater propagation and runoff generation during rain-on-snow (ROS events are still insufficiently known. Understanding storage and transport of liquid water in natural snowpacks is crucial, especially for forecasting of natural hazards such as floods and wet snow avalanches. In this study, propagation of rainwater through snow was investigated by sprinkling experiments with deuterium-enriched water and applying an alternative hydrograph separation technique on samples collected from the snowpack runoff. This allowed us to quantify the contribution of rainwater, snowmelt and initial liquid water released from the snowpack. Four field experiments were carried out during winter 2015 in the vicinity of Davos, Switzerland. Blocks of natural snow were isolated from the surrounding snowpack to inhibit lateral exchange of water and were exposed to artificial rainfall using deuterium-enriched water. The experiments were composed of four 30 min periods of sprinkling, separated by three 30 min breaks. The snowpack runoff was continuously gauged and sampled periodically for the deuterium signature. At the onset of each experiment antecedent liquid water was first pushed out by the sprinkling water. Hydrographs showed four pronounced peaks corresponding to the four sprinkling bursts. The contribution of rainwater to snowpack runoff consistently increased over the course of the experiment but never exceeded 86 %. An experiment conducted on a non-ripe snowpack suggested the development of preferential flow paths that allowed rainwater to efficiently propagate through the snowpack limiting the time for mass exchange processes to take effect. In contrast, experiments conducted on ripe isothermal snowpack showed a slower response behaviour and resulted in a total runoff volume which consisted of less than 50 % of the rain input.

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

    Science.gov (United States)

    Palm, S. P.; Yang, Y.; Kayetha, V.; Pauly, R.

    2017-12-01

    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.

  17. 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.

  18. Persistent reduction of segment growth and photosynthesis in a widespread and important sub-Arctic moss species after cessation of three years of experimental winter warming

    NARCIS (Netherlands)

    Bjerke, J.W.; Bokhorst, S.F.; Callaghan, T.V.; Phoenix, G.K.

    2017-01-01

    Winter is a period of dormancy for plants of cold environments. However, winter climate is changing, leading to an increasing frequency of stochastic warm periods (winter warming events) and concomitant reductions in snow cover. These conditions can break dormancy for some plants and expose them to

  19. Assessment of winter fluxes of CO2 and CH4 in boreal forest soils of central Alaska estimated by the profile method and the chamber method: a diagnosis of methane emission and implications for the regional carbon budget

    International Nuclear Information System (INIS)

    Kim, Yongwon; Ueyama, Masahito; Harazono, Yoshinobu; Tanaka, Noriyuki; Nakagawa, Fumiko; Tsunogai, Urumu

    2007-01-01

    This research was carried out to estimate the winter fluxes of CO 2 and CH 4 using the concentration profile method and the chamber method in black spruce forest soils in central Alaska during the winter of 2004/5. The average winter fluxes of CO 2 and CH 4 by chamber and profile methods were 0.24 ± 0.06 (SE; standard error) and 0.21 ± 0.06 gCO 2 -C/m2/d, and 21.4 ± 5.6 and 21.4 ± 14 μgCH 4 -C/m2/hr. This suggests that the fluxes estimated by the two methods are not significantly different based on a one-way ANOVA with a 95% confidence level. The hypothesis on the processes of CH 4 transport/production/emission in underlying snow-covered boreal forest soils is proven by the pressure differences between air and in soil at 30 cm depth. The winter CO 2 emission corresponds to 23% of the annual CO 2 emitted from Alaska black spruce forest soils, which resulted in the sum of mainly root respiration and microbial respiration during the winter based on the (delta) 13 CO 2 of -2.25%. The average wintertime emissions of CO 2 and CH 4 were 49 ± 13 gCO 2 -C/m 2 /season and 0.11 ± 0.07 gCH 4 -C/m 2 /season, respectively. This implies that winter emissions of CO 2 and CH 4 are an important part of the annual carbon budget in seasonally snow-covered terrain of typical boreal forest soils

  20. Spatial and temporal variations of total mercury in Antarctic snow along the transect from Zhongshan Station to Dome A

    Directory of Open Access Journals (Sweden)

    Chuanjin Li

    2014-12-01

    Full Text Available In this study, the concentrations of total mercury (THg and ions deposited in the surface snow and snow pits in the eastern Antarctic along the 29th inland route of the Chinese National Antarctic Research Expedition were analysed. The THg concentrations in the surface snow ranged from 0.22 to 8.29 ng/L and elevated concentrations were detected in the inland regions of higher altitudes (3000–4000 m. The spatial distribution of the THg in the snow pits showed greater inland concentrations with mean concentrations of <0.2–1.33 ng/L. The THg concentrations in the coastal snow pit (29-A showed higher concentrations in the summer snow layers than in the winter snow layers. The THg records from the two inland snow pits (29-K and 29-L spanned decades and indicated elevated THg concentrations between the late 1970s and early 1980s and during the mid-1990s. The temporal variations of THg in the Antarctic snow layers were consistent with anthropogenic emissions around the world. In addition, the Pinatubo volcanic eruption was the primary contributor to the 1992 THg peak that was observed in the inland snow pits.

  1. Half a Century of Schladming Winter Schools

    International Nuclear Information System (INIS)

    Pietschmann, H.

    2012-01-01

    The Schladming Winter Schools have started as early as in 1962. Over the times the yearly Schools have closely followed the actual developments in nuclear, particle, or more generally, in theoretical physics. Several new achievements have first been dealt with in length in the lectures at the Schladming Winter School. It has seen very prominent lecturers, among them a series of Nobel laureates (some of them reporting on their works even before they got their Nobel prizes). I will try to highlight the role of the Schladming Winter Schools in pro- mulgating new developments of theoretical physics in depth at the lectures given over the past 50 years. (author)

  2. Evolution of snow and ice temperature, thickness and energy balance in Lake Orajärvi, northern Finland

    Directory of Open Access Journals (Sweden)

    Bin Cheng

    2014-05-01

    Full Text Available The seasonal evolution of snow and ice on Lake Orajärvi, northern Finland, was investigated for three consecutive winter seasons. Material consisting of numerical weather prediction model (HIRLAM output, weather station observations, manual snow and ice observations, high spatial resolution snow and ice temperatures from ice mass balance buoys (SIMB, and Moderate Resolution Imaging Spectroradiometer (MODIS lake ice surface temperature observations was gathered. A snow/ice model (HIGHTSI was applied to simulate the evolution of the snow and ice surface energy balance, temperature profiles and thickness. The weather conditions in early winter were found critical in determining the seasonal evolution of the thickness of lake ice and snow. During the winter season (Nov.–Apr., precipitation, longwave radiative flux and air temperature showed large inter-annual variations. The uncertainty in snow/ice model simulations originating from precipitation was investigated. The contribution of snow to ice transformation was vital for the total lake ice thickness. At the seasonal time scale, the ice bottom growth was 50–70% of the total ice growth. The SIMB is suitable for monitoring snow and ice temperatures and thicknesses. The Mean Bias Error (MBE between the SIMB and borehole measurements was −0.7 cm for snow thicknesses and 1.7 cm for ice thickness. The temporal evolution of MODIS surface temperature (three seasons agrees well with SIMB and HIGHTSI results (correlation coefficient, R=0.81. The HIGHTSI surface temperatures were, however, higher (2.8°C≤MBE≤3.9°C than the MODIS observations. The development of HIRLAM by increasing its horizontal and vertical resolution and including a lake parameterisation scheme improved the atmospheric forcing for HIGHTSI, especially the relative humidity and solar radiation. Challenges remain in accurate simulation of snowfall events and total precipitation.

  3. "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.

  4. A comparison study of two snow models using data from different Alpine sites

    Science.gov (United States)

    Piazzi, Gaia; Riboust, Philippe; Campo, Lorenzo; Cremonese, Edoardo; Gabellani, Simone; Le Moine, Nicolas; Morra di Cella, Umberto; Ribstein, Pierre; Thirel, Guillaume

    2017-04-01

    The hydrological balance of an Alpine catchment is strongly affected by snowpack dynamics. Melt-water supplies a significant component of the annual water budget, both in terms of soil moisture and runoff, which play a critical role in floods generation and impact water resource management in snow-dominated basins. Several snow models have been developed with variable degrees of complexity, mainly depending on their target application and the availability of computational resources and data. According to the level of detail, snow models range from statistical snowmelt-runoff and degree-day methods using composite snow-soil or explicit snow layer(s), to physically-based and energy balance snow models, consisting of detailed internal snow-process schemes. Intermediate-complexity approaches have been widely developed resulting in simplified versions of the physical parameterization schemes with a reduced snowpack layering. Nevertheless, an increasing model complexity does not necessarily entail improved model simulations. This study presents a comparison analysis between two snow models designed for hydrological purposes. The snow module developed at UPMC and IRSTEA is a mono-layer energy balance model analytically resolving heat and phase change equations into the snowpack. Vertical mass exchange into the snowpack is also analytically resolved. The model is intended to be used for hydrological studies but also to give a realistic estimation of the snowpack state at watershed scale (SWE and snow depth). The structure of the model allows it to be easily calibrated using snow observation. This model is further presented in EGU2017-7492. The snow module of SMASH (Snow Multidata Assimilation System for Hydrology) consists in a multi-layer snow dynamic scheme. It is physically based on mass and energy balances and it reproduces the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass

  5. 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

  6. Snow farming: conserving snow over the summer season

    Science.gov (United States)

    Grünewald, Thomas; Wolfsperger, Fabian; Lehning, Michael

    2018-01-01

    Summer storage of snow for tourism has seen an increasing interest in the last years. Covering large snow piles with materials such as sawdust enables more than two-thirds of the initial snow volume to be conserved. We present detailed mass balance measurements of two sawdust-covered snow piles obtained by terrestrial laser scanning during summer 2015. Results indicate that 74 and 63 % of the snow volume remained over the summer for piles in Davos, Switzerland and Martell, Italy. If snow mass is considered instead of volume, the values increase to 83 and 72 %. The difference is attributed to settling and densification of the snow. Additionally, we adapted the one-dimensional, physically based snow cover model SNOWPACK to perform simulations of the sawdust-covered snow piles. Model results and measurements agreed extremely well at the point scale. Moreover, we analysed the contribution of the different terms of the surface energy balance to snow ablation for a pile covered with a 40 cm thick sawdust layer and a pile without insulation. Short-wave radiation was the dominant source of energy for both scenarios, but the moist sawdust caused strong cooling by long-wave emission and negative sensible and latent heat fluxes. This cooling effect reduces the energy available for melt by up to a factor of 12. As a result only 9 % of the net short-wave energy remained available for melt. Finally, sensitivity studies of the parameters thickness of the sawdust layer, air temperature, precipitation and wind speed were performed. We show that sawdust thickness has a tremendous effect on snow loss. Higher air temperatures and wind speeds increase snow ablation but less significantly. No significant effect of additional precipitation could be found as the sawdust remained wet during the entire summer with the measured quantity of rain. Setting precipitation amounts to zero, however, strongly increased melt. Overall, the 40 cm sawdust provides sufficient protection for mid

  7. Snow farming: conserving snow over the summer season

    Directory of Open Access Journals (Sweden)

    T. Grünewald

    2018-01-01

    Full Text Available Summer storage of snow for tourism has seen an increasing interest in the last years. Covering large snow piles with materials such as sawdust enables more than two-thirds of the initial snow volume to be conserved. We present detailed mass balance measurements of two sawdust-covered snow piles obtained by terrestrial laser scanning during summer 2015. Results indicate that 74 and 63 % of the snow volume remained over the summer for piles in Davos, Switzerland and Martell, Italy. If snow mass is considered instead of volume, the values increase to 83 and 72 %. The difference is attributed to settling and densification of the snow. Additionally, we adapted the one-dimensional, physically based snow cover model SNOWPACK to perform simulations of the sawdust-covered snow piles. Model results and measurements agreed extremely well at the point scale. Moreover, we analysed the contribution of the different terms of the surface energy balance to snow ablation for a pile covered with a 40 cm thick sawdust layer and a pile without insulation. Short-wave radiation was the dominant source of energy for both scenarios, but the moist sawdust caused strong cooling by long-wave emission and negative sensible and latent heat fluxes. This cooling effect reduces the energy available for melt by up to a factor of 12. As a result only 9 % of the net short-wave energy remained available for melt. Finally, sensitivity studies of the parameters thickness of the sawdust layer, air temperature, precipitation and wind speed were performed. We show that sawdust thickness has a tremendous effect on snow loss. Higher air temperatures and wind speeds increase snow ablation but less significantly. No significant effect of additional precipitation could be found as the sawdust remained wet during the entire summer with the measured quantity of rain. Setting precipitation amounts to zero, however, strongly increased melt. Overall, the 40 cm sawdust provides

  8. 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

  9. Experimental High-Resolution Land Surface Prediction System for the Vancouver 2010 Winter Olympic Games

    Science.gov (United States)

    Belair, S.; Bernier, N.; Tong, L.; Mailhot, J.

    2008-05-01

    The 2010 Winter Olympic and Paralympic Games will take place in Vancouver, Canada, from 12 to 28 February 2010 and from 12 to 21 March 2010, respectively. In order to provide the best possible guidance achievable with current state-of-the-art science and technology, Environment Canada is currently setting up an experimental numerical prediction system for these special events. This system consists of a 1-km limited-area atmospheric model that will be integrated for 16h, twice a day, with improved microphysics compared with the system currently operational at the Canadian Meteorological Centre. In addition, several new and original tools will be used to adapt and refine predictions near and at the surface. Very high-resolution two-dimensional surface systems, with 100-m and 20-m grid size, will cover the Vancouver Olympic area. Using adaptation methods to improve the forcing from the lower-resolution atmospheric models, these 2D surface models better represent surface processes, and thus lead to better predictions of snow conditions and near-surface air temperature. Based on a similar strategy, a single-point model will be implemented to better predict surface characteristics at each station of an observing network especially installed for the 2010 events. The main advantage of this single-point system is that surface observations are used as forcing for the land surface models, and can even be assimilated (although this is not expected in the first version of this new tool) to improve initial conditions of surface variables such as snow depth and surface temperatures. Another adaptation tool, based on 2D stationnary solutions of a simple dynamical system, will be used to produce near-surface winds on the 100-m grid, coherent with the high- resolution orography. The configuration of the experimental numerical prediction system will be presented at the conference, together with preliminary results for winter 2007-2008.

  10. Rain or snow?

    Science.gov (United States)

    Richman, Barbara T.

    It's easy to look out the window and decide whether it's raining, snowing, or hailing, right? Well, not always—especially when the region of interest isn't directly outside your window. To help discern the difference, the National Oceanic and Atmospheric Administration (NOAA) has developed a laser beam device that differentiates between the precipitation types.The laser weather identifier produces different signals when raindrops, snowflakes, or hailstones pass through the laser's beam, according to Ting-i Wang—until recently a scientist at NOAA's Environmental Research Laboratories in Boulder, Colo. These signature signals can be read by computer and integrated into present weather networks. ‘It can eliminate human error or negligence, and can be cost effective by constantly observing and monitoring the weather,’ Wang noted. Wang and his colleagues are developing several of the laser instruments for evaluation by NOAA's National Weather Service. The first of these is scheduled to be installed in 1984.

  11. Wet meadow ecosystems contribute the majority of overwinter soil respiration from snow-scoured alpine tundra

    Science.gov (United States)

    Knowles, John F.; Blanken, Peter D.; Williams, Mark W.

    2016-04-01

    We measured soil respiration across a soil moisture gradient ranging from dry to wet snow-scoured alpine tundra soils throughout three winters and two summers. In the absence of snow accumulation, soil moisture variability was principally determined by the combination of mesotopographical hydrological focusing and shallow subsurface permeability, which resulted in a patchwork of comingled ecosystem types along a single alpine ridge. To constrain the subsequent carbon cycling variability, we compared three measures of effective diffusivity and three methods to calculate gradient method soil respiration from four typical vegetation communities. Overwinter soil respiration was primarily restricted to wet meadow locations, and a conservative estimate of the rate of overwinter soil respiration from snow-scoured wet meadow tundra was 69-90% of the maximum carbon dioxide (CO2) respired by seasonally snow-covered soils within this same catchment. This was attributed to higher overwinter soil temperatures at wet meadow locations relative to fellfield, dry meadow, and moist meadow communities, which supported liquid water and heterotrophic respiration throughout the winter. These results were corroborated by eddy covariance-based measurements that demonstrated an average of 272 g C m-2 overwinter carbon loss during the study period. As a result, we updated a conceptual model of soil respiration versus snow cover to express the potential for soil respiration variability from snow-scoured alpine tundra.

  12. Spatial and temporal variation in weather events critical for boreal agriculture: III Frost and winter time fluctuation

    Directory of Open Access Journals (Sweden)

    Pirjo Peltonen-Sainio

    2016-03-01

    Full Text Available In the boreal zone of Europe, differences between the four seasons are considerable. Also, the within-season variation in climatic conditions is substantial. This has many impacts on agriculture that are exceptional when compared to any other environmental zone in Europe. All the meteorological data were based on weather observations made by the Finnish Meteorological Institute. Likelihood (% for soil frost (≤ 0 °C at 20 cm soil depth at nine weather stations, and late snow cover (> 1 cm (10 km × 10 km grid were estimated for late spring. Probabilities (% of night frost at the ground surface (March-September were calculated at nine weather stations by frequencies of the lowest observed night-time temperature: a between –2 and –5 °C (mild, b ≤ –5 °C (moderate and c ≤ –9 °C (severe. Also, the probabilities (% of night frost in mid-summer were estimated (≤ –1 °C for at least five hours. Furthermore, a significant shift from mild to below-freezing conditions was measured in winter as a period of at least ten days with daily maximum temperatures above 0°C followed by at least a 10-day period with daily mean temperatures below –5°C in order to characterize high fluctuating winter conditions. All these except late snow cover constitute high risks to crop production. Deep soil frost may postpone sowings, while in advanced springs, night frost may cause damage. For winter crops and perennials, shifts from mild to cold spells outside the growing season are particularly detrimental. Again the data may have many other applications beyond the assessments highlighted in this paper.

  13. Fukushima Nuclear Accident Recorded in Tibetan Plateau Snow Pits

    Science.gov (United States)

    Wang, Ninglian; Wu, Xiaobo; Kehrwald, Natalie; Li, Zhen; Li, Quanlian; Jiang, Xi; Pu, Jianchen

    2015-01-01

    The β radioactivity of snow-pit samples collected in the spring of 2011 on four Tibetan Plateau glaciers demonstrate a remarkable peak in each snow pit profile, with peaks about ten to tens of times higher than background levels. The timing of these peaks suggests that the high radioactivity resulted from the Fukushima nuclear accident that occurred on March 11, 2011 in eastern Japan. Fallout monitoring studies demonstrate that this radioactive material was transported by the westerlies across the middle latitudes of the Northern Hemisphere. The depth of the peak β radioactivity in each snow pit compared with observational precipitation records, suggests that the radioactive fallout reached the Tibetan Plateau and was deposited on glacier surfaces in late March 2011, or approximately 20 days after the nuclear accident. The radioactive fallout existed in the atmosphere over the Tibetan Plateau for about one month. PMID:25658094

  14. Fukushima nuclear accident recorded in Tibetan Plateau snow pits.

    Directory of Open Access Journals (Sweden)

    Ninglian Wang

    Full Text Available The β radioactivity of snow-pit samples collected in the spring of 2011 on four Tibetan Plateau glaciers demonstrate a remarkable peak in each snow pit profile, with peaks about ten to tens of times higher than background levels. The timing of these peaks suggests that the high radioactivity resulted from the Fukushima nuclear accident that occurred on March 11, 2011 in eastern Japan. Fallout monitoring studies demonstrate that this radioactive material was transported by the westerlies across the middle latitudes of the Northern Hemisphere. The depth of the peak β radioactivity in each snow pit compared with observational precipitation records, suggests that the radioactive fallout reached the Tibetan Plateau and was deposited on glacier surfaces in late March 2011, or approximately 20 days after the nuclear accident. The radioactive fallout existed in the atmosphere over the Tibetan Plateau for about one month.

  15. Snow cover, freeze-thaw, and the retention of nutrients in an oceanic mountain ecosystem

    NARCIS (Netherlands)

    Wipf, Sonja; Sommerkorn, Martin; Stutter, Marc I.; Wubs, E. R. Jasper; van der Wal, René

    2015-01-01

    As the climate warms, winters with less snow and therefore more soil freeze-thaw cycles are likely to become more frequent in oceanic mountain areas. It is a concern that this might impair the soil's ability to store carbon and nutrients, and lead to increased leaching losses of dissolved C and

  16. Winter Weather Emergencies

    Science.gov (United States)

    Severe winter weather can lead to health and safety challenges. You may have to cope with Cold related health ... Although there are no guarantees of safety during winter weather emergencies, you can take actions to protect ...

  17. Winter maintenance performance measure.

    Science.gov (United States)

    2016-01-01

    The Winter Performance Index is a method of quantifying winter storm events and the DOTs response to them. : It is a valuable tool for evaluating the States maintenance practices, performing post-storm analysis, training : maintenance personnel...

  18. Winter weather demand considerations.

    Science.gov (United States)

    2015-04-01

    Winter weather has varied effects on travel behavior. Using 418 survey responses from the Northern Virginia : commuting area of Washington, D.C. and binary logit models, this study examines travel related changes under : different types of winter wea...

  19. Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

    Science.gov (United States)

    Wang, Tao; Peng, Shushi; Krinner, Gerhard; Ryder, James; Li, Yue; Dantec-Nédélec, Sarah; Ottlé, Catherine

    2015-01-01

    Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation) into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique) improve the simulation accuracy of mean seasonal (October throughout May) snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the magnitude of

  20. Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

    Directory of Open Access Journals (Sweden)

    Tao Wang

    Full Text Available Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique improve the simulation accuracy of mean seasonal (October throughout May snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the

  1. Assessment of dynamic probabilistic methods for mapping snow cover in Québec Canada

    Science.gov (United States)

    De Seve, D.; Perreault, L.; Vachon, F.; Guay, F.; choquette, Y.

    2012-04-01

    Hydro-Quebec is the leader in electricity production in North America and uses hydraulic resources to generate 97% of its overall production where snow represents 30% of its annual energy reserve. Information on snow cover extent (SC) and snow water equivalent (SWE) is crucial for hydrological forecasting, particularly in Nordic regions where a majority of total precipitations falls as snow. Accurate estimation of the spatial distribution of snow cover variables is required to measure the extent of this resource but snow surveys are expensive due to inaccessibility factors and to the large extent nature of the Quebec geography. Consequently, the follow-up of snowmelt is particularly challenging for operational forecasting resulting in the need to develop a new approach to assist forecasters. For improved understanding of the dynamics of snow melting over watersheds and to generate optimized power production, Hydro-Québec's Research Institute (IREQ) has developed expertise in in-situ, remote sensing monitoring and statistical treatment of such data. The main goal of this Hydro-Quebec project is to develop an automatic and dynamic snow mapping system providing a daily snow map by merging remote sensing (AVHRR and SSMI) and in situ data. This paper focuses on the work accomplished on passive microwave SSM/I data to follow up snow cover. In our problematic, it is highly useful to classify snow, more specifically during the snowmelt period. The challenge is to be able to discriminate ground from wet snow as it will react as a black body, therefore, adding noise to global brightness temperature. Two dynamic snow classifiers were developed and tested. For this purpose, channels at 19 and 37 GHz in vertical polarization have been used to feed each model. SWE values from gamma ray in situ stations (GMON) and data snow depth from ultrasonic sensor (SR50) were used to validate the output models. The first algorithm is based on a standard K-mean clustering approach, combined

  2. An Australian Feeling for Snow: Towards Understanding Cultural and Emotional Dimensions of Climate Change

    Directory of Open Access Journals (Sweden)

    Andrew Gorman-Murray

    2010-03-01

    Full Text Available In Australia, snow is associated with alpine and subalpine regions in rural areas; snow is a component of ‘natural’ rather than urban environments. But the range, depth and duration of Australia’s regional snow cover is imperilled by climate change. While researchers have considered the impacts of snow retreat on the natural environment and responses from the mainland ski industry, this paper explores associated cultural and emotional dimensions of climate change. This responds to calls to account for local meanings of climate, and thus localised perceptions of and responses to climate change. Accordingly, this paper presents a case study of reactions to the affect of climate change on Tasmania’s snow country. Data is drawn from a nationwide survey of responses to the impact of climate change on Australia’s snow country, and a Tasmanian focus group. Survey respondents suggested the uneven distribution of Australia’s snow country means snow cover loss may matter more in certain areas: Tasmania was a key example cited by residents of both that state and others. Focus group respondents affirmed a connection between snow and Tasmanian cultural identity, displaying sensitivity to recent changing snow patterns. Moreover, they expressed concerns about the changes using emotive descriptions of local examples: the loss of snow cover mattered culturally and emotionally, compromising local cultural activities and meanings, and invoking affective responses. Simultaneously, respondents were ‘realistic’ about how important snow loss was, especially juxtaposed with sea level rise. Nevertheless, the impact of climate change on cultural and emotional attachments can contribute to urgent ethical, practical and political arguments about arresting global warming.

  3. An Australian feeling for snow : towards understanding cultural and emotional dimensions of climate change

    Directory of Open Access Journals (Sweden)

    Gorman-Murray, Andrew

    2010-01-01

    Full Text Available In Australia, snow is associated with alpine and subalpine regions in rural areas; snow is a component of ‘natural’ rather than urban environments. But the range, depth and duration of Australia’s regional snow cover is imperilled by climate change. While researchers have considered the impacts of snow retreat on the natural environment and responses from the mainland ski industry, this paper explores associated cultural and emotional dimensions of climate change. This responds to calls to account for local meanings of climate, and thus localised perceptions of and responses to climate change. Accordingly, this paper presents a case study of reactions to the affect of climate change on Tasmania’s snow country. Data is drawn from a nationwide survey of responses to the impact of climate change on Australia’s snow country, and a Tasmanian focus group. Survey respondents suggested the uneven distribution of Australia’s snow country means snow cover loss may matter more in certain areas: Tasmania was a key example cited by residents of both that state and others. Focus group respondents affirmed a connection between snow and Tasmanian cultural identity, displaying sensitivity to recent changing snow patterns. Moreover, they expressed concerns about the changes using emotive descriptions of local examples: the loss of snow cover mattered culturally and emotionally, compromising local cultural activities and meanings, and invoking affective responses. Simultaneously, respondents were ‘realistic’ about how important snow loss was, especially juxtaposed with sea level rise. Nevertheless, the impact of climate change on cultural and emotional attachments can contribute to urgent ethical, practical and political arguments about arresting global warming.

  4. 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.

  5. Modeling winter ozone episodes near oil and natural gas fields in Wyoming

    Science.gov (United States)

    Wu, Yuling; Rappenglück, Bernhard; Pour-Biazar, Arastoo; Field, Robert A.; Soltis, Jeff

    2017-04-01

    Wintertime ozone episodes have been reported in the oil and natural gas (O&NG) producing fields in Uintah Basin, Utah and the Upper Green River Basin (UGRB) in Wyoming in recent years. High concentrations of ozone precursors facilitated by favorable meteorological conditions, including low wind and shallow boundary layer (BL), were found in these episodes, although the exact roles of these precursor species in different O&NG fields are to be determined. Meanwhile, snow cover is also found to play an important role in these winter ozone episodes as the cold snow covered surface enhances the inversion, further limits the BL and the high snow albedo greatly boosts photolysis reactions that are closely related to ozone chemistry. In this study, we utilize model simulation to explore the role of chemical compositions, in terms of different VOC groups and NOx, and that of the enhanced photolysis due to snow cover in the UGRB ozone episodes in the late winter of 2011.

  6. Evaluation of snow and frozen soil parameterization in a cryosphere land surface modeling framework in the Tibetan Plateau

    Science.gov (United States)

    Zhou, J.

    2017-12-01

    Snow and frozen soil are important components in the Tibetan Plateau, and influence the water cycle and energy balances through snowpack accumulation and melt and soil freeze-thaw. In this study, a new cryosphere land surface model (LSM) with coupled snow and frozen soil parameterization was developed based on a hydrologically improved LSM (HydroSiB2). First, an energy-balance-based three-layer snow model was incorporated into HydroSiB2 (hereafter HydroSiB2-S) to provide an improved description of the internal processes of the snow pack. Second, a universal and simplified soil model was coupled with HydroSiB2-S to depict soil water freezing and thawing (hereafter HydroSiB2-SF). In order to avoid the instability caused by the uncertainty in estimating water phase changes, enthalpy was adopted as a prognostic variable instead of snow/soil temperature in the energy balance equation of the snow/frozen soil module. The newly developed models were then carefully evaluated at two typical sites of the Tibetan Plateau (TP) (one snow covered and the other snow free, both with underlying frozen soil). At the snow-covered site in northeastern TP (DY), HydroSiB2-SF demonstrated significant improvements over HydroSiB2-F (same as HydroSiB2-SF but using the original single-layer snow module of HydroSiB2), showing the importance of snow internal processes in three-layer snow parameterization. At the snow-free site in southwestern TP (Ngari), HydroSiB2-SF reasonably simulated soil water phase changes while HydroSiB2-S did not, indicating the crucial role of frozen soil parameterization in depicting the soil thermal and water dynamics. Finally, HydroSiB2-SF proved to be capable of simulating upward moisture fluxes toward the freezing front from the underlying soil layers in winter.

  7. The stepwise discriminant algorithm for snow cover mapping based on FY-3/MERSI data

    Science.gov (United States)

    Han, Tao; Wang, Dawei; Jiang, Youyan; Wang, Xiaowei

    2013-10-01

    Medium Resolution Spectral Imager (MERSI) on board China's new generation polar orbit meteorological satellite FY- 3A provides a new data source for snow monitoring in large area. As a case study, the typical snow cover of Qilian Mountains in northwest China was selected in this paper to develop the algorithm to map snow cover using FY- 3A/MERSI. By analyzing the spectral response characteristics of snow and other surface elements, as well as each channel image quality on FY-3A/MERSI, the widely used Normalized Difference Snow Index (NDSI) was defined to be computed from channel 2 and channel 7 for this satellite data. Basing on NDSI, a tree-structure prototype version of snow identification model was proposed, including five newly-built multi-spectral indexes to remove those pixels such as forest, cloud shadow, water, lake ice, sand (salty land), or cloud that are usually confused with snow step by step, especially, a snow/cloud discrimination index was proposed to eliminate cloud, apart from use of cloud mask product in advance. Furthermore, land cover land use (LULC) image has been adopted as auxiliary dataset to adjust the corresponding LULC NDSI threshold constraints for snow final determination and optimization. This model is composed as the core of FY-3A/MERSI snow cover mapping flowchart, to produce daily snow map at 250m spatial resolution, and statistics can be generated on the extent and persistence of snow cover in each pixel for time series maps. Preliminary validation activities of our snow identification model have been undertaken. Comparisons of the 104 FY- 3A/MERSI snow cover maps in 2010-2011 snow season with snow depth records from 16 meteorological stations in Qilian Mountains region, the sunny snow cover had an absolute accuracy of 92.8%. Results of the comparison with the snow cover identified from 6 Terra/MODIS scenes showed that they had consistent pixels about 85%. When the two satellite resultant snow cover maps compared with the 6

  8. Impact of warm winters on microbial growth

    Science.gov (United States)

    Birgander, Johanna; Rousk, Johannes; Axel Olsson, Pål

    2014-05-01

    temperature relationships of the bacterial community from winter-warmed plots and plots with ambient soil temperatures were compared. No change in optimum temperature for growth could be detected, indicating that the microbial community has not been warm-adapted. This fits with what was seen also in the laboratory experiment where no changes in temperature response occurred when exposing bacteria to temperatures below 10 °C within two months. The increase in activity measured during winter should thereby be due to changes in environmental factors, which will be further investigated. One big difference between heated and control plots was that heated plots were snow free during the entire winter, while control plots were covered by a 10 cm snow cover. The plant community composition and flowering time also differed in the warmed and ambient plot.

  9. Heavy snow loads in Finnish forests respond regionally asymmetrically to projected climate change

    Directory of Open Access Journals (Sweden)

    I. Lehtonen

    2016-10-01

    Full Text Available This study examined the impacts of projected climate change on heavy snow loads on Finnish forests, where snow-induced forest damage occurs frequently. For snow-load calculations, we used daily data from five global climate models under representative concentration pathway (RCP scenarios RCP4.5 and RCP8.5, statistically downscaled onto a high-resolution grid using a quantile-mapping method. Our results suggest that projected climate warming results in regionally asymmetric response on heavy snow loads in Finnish forests. In eastern and northern Finland, the annual maximum snow loads on tree crowns were projected to increase during the present century, as opposed to southern and western parts of the country. The change was rather similar both for heavy rime loads and wet snow loads, as well as for frozen snow loads. Only the heaviest dry snow loads were projected to decrease over almost the whole of Finland. Our results are aligned with previous snowfall projections, typically indicating increasing heavy snowfalls over the areas with mean temperature below −8 °C. In spite of some uncertainties related to our results, we conclude that the risk for snow-induced forest damage is likely to increase in the future in the eastern and northern parts of Finland, i.e. in the areas experiencing the coldest winters in the country. The increase is partly due to the increase in wet snow hazards but also due to more favourable conditions for rime accumulation in a future climate that is more humid but still cold enough.

  10. TRACKING FOREST AND OPEN AREA EFFECTS ON SNOW ACCUMULATION BY UNMANNED AERIAL VEHICLE PHOTOGRAMMETRY

    Directory of Open Access Journals (Sweden)

    T. Lendzioch

    2016-06-01

    Full Text Available Airborne digital photogrammetry is undergoing a renaissance. The availability of low-cost Unmanned Aerial Vehicle (UAV platforms well adopted for digital photography and progress in software development now gives rise to apply this technique to different areas of research. Especially in determining snow depth spatial distributions, where repetitive mapping of cryosphere dynamics is crucial. Here, we introduce UAV-based digital photogrammetry as a rapid and robust approach for evaluating snow accumulation over small local areas (e.g., dead forest, open areas and to reveal impacts related to changes in forest and snowpack. Due to the advancement of the technique, snow depth of selected study areas such as of healthy forest, disturbed forest, succession, dead forest, and of open areas can be estimated at a 1 cm spatial resolution. The approach is performed in two steps: 1 developing a high resolution Digital Elevation Model during snow-free and 2 during snow-covered conditions. By substracting these two models the snow depth can be accurately retrieved and volumetric changes of snow depth distribution can be achieved. This is a first proof-of-concept study combining snow depth determination and Leaf Area Index (LAI retrieval to monitor the impact of forest canopy metrics on snow accumulation in coniferous forest within the Šumava National Park, Czech Republic. Both, downward-looking UAV images and upward-looking LAI-2200 canopy analyser measurements were applied to reveal the LAI, controlling interception and transmitting radiation. For the performance of downward-looking images the snow background instead of the sky fraction was used. In contrast to the classical determination of LAI by hemispherical photography or by LAI plant canopy analyser, our approach will also test the accuracy of LAI measurements by UAV that are taken simultaneously during the snow cover mapping campaigns. Since the LAI parameter is important for snowpack modelling, this

  11. Modeling Road Vulnerability to Snow Using Mixed Integer Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez, Tony K [ORNL; Omitaomu, Olufemi A [ORNL; Ostrowski, James A [ORNL; Bhaduri, Budhendra L [ORNL

    2017-01-01

    As the number and severity of snowfall events continue to grow, the need to intelligently direct road maintenance during these snowfall events will also grow. In several locations, local governments lack the resources to completely treat all roadways during snow events. Furthermore, some governments utilize only traffic data to determine which roads should be treated. As a result, many schools, businesses, and government offices must be unnecessarily closed, which directly impacts the social, educational, and economic well-being of citizens and institutions. In this work, we propose a mixed integer programming formulation to optimally allocate resources to manage snowfall on roads using meteorological, geographical, and environmental parameters. Additionally, we evaluate the impacts of an increase in budget for winter road maintenance on snow control resources.

  12. Winter-to-winter variations in indoor radon

    International Nuclear Information System (INIS)

    Mose, D.G.; Mushrush, G.W.; Kline, S.W.

    1989-01-01

    Indoor radon concentrations in northern Virginia and central Maryland show a strong dependence on weather. Winter tends to be associated with higher than average indoor radon, and summer with lower than average. However, compared to the winter of 1986-1987, the winter of 1987-1988 was warmer and drier. Consequently, winter-to-winter indoor radon decreased by about 25%. This winter-to-winter decrease is unexpectedly large, and simulates winter-to-summer variations that have been reported

  13. Optimum soil frost depth to alleviate climate change effects in cold region agriculture

    Science.gov (United States)

    Yanai, Yosuke; Iwata, Yukiyoshi; Hirota, Tomoyoshi

    2017-03-01

    On-farm soil frost control has been used for the management of volunteer potatoes (Solanum tuberosum L.), a serious weed problem caused by climate change, in northern Japan. Deep soil frost penetration is necessary for the effective eradication of unharvested small potato tubers; however, this process can delay soil thaw and increase soil wetting in spring, thereby delaying agricultural activity initiation and increasing nitrous oxide emissions from soil. Conversely, shallow soil frost development helps over-wintering of unharvested potato tubers and nitrate leaching from surface soil owing to the