WorldWideScience

Sample records for ground hardness snow

  1. From the clouds to the ground - snow precipitation patterns vs. snow accumulation patterns

    Science.gov (United States)

    Gerber, Franziska; Besic, Nikola; Mott, Rebecca; Gabella, Marco; Germann, Urs; Bühler, Yves; Marty, Mauro; Berne, Alexis; Lehning, Michael

    2017-04-01

    Knowledge about snow distribution and snow accumulation patterns is important and valuable for different applications such as the prediction of seasonal water resources or avalanche forecasting. Furthermore, accumulated snow on the ground is an important ground truth for validating meteorological and climatological model predictions of precipitation in high mountains and polar regions. Snow accumulation patterns are determined by many different processes from ice crystal nucleation in clouds to snow redistribution by wind and avalanches. In between, snow precipitation undergoes different dynamical and microphysical processes, such as ice crystal growth, aggregation and riming, which determine the growth of individual particles and thereby influence the intensity and structure of the snowfall event. In alpine terrain the interaction of different processes and the topography (e.g. lifting condensation and low level cloud formation, which may result in a seeder-feeder effect) may lead to orographic enhancement of precipitation. Furthermore, the redistribution of snow particles in the air by wind results in preferential deposition of precipitation. Even though orographic enhancement is addressed in numerous studies, the relative importance of micro-physical and dynamically induced mechanisms on local snowfall amounts and especially snow accumulation patterns is hardly known. To better understand the relative importance of different processes on snow precipitation and accumulation we analyze snowfall and snow accumulation between January and March 2016 in Davos (Switzerland). We compare MeteoSwiss operational weather radar measurements on Weissfluhgipfel to a spatially continuous snow accumulation map derived from airborne digital sensing (ADS) snow height for the area of Dischma valley in the vicinity of the weather radar. Additionally, we include snow height measurements from automatic snow stations close to the weather radar. Large-scale radar snow accumulation

  2. STUDIES ON THE HARDNESS OF WET SNOW AND ITS DECREASE DUE TO SOLAR RADIATION

    OpenAIRE

    Izumi, Kaoru

    1987-01-01

    As wet snow plays one of the most important roles in the release of avalanches in temperate snowy districts, observations and experiments were made on the characteristics of hardness of wet snow in the field and laboratory. By measuring Kinosita's hardness of natural wet snow over a wide range of snow density, a relation among hardness, dry density and free water content of wet snow was obtained for each snow type. As hardness of snow decreased with an increase in water content according to t...

  3. Ground-Truthing a Next Generation Snow Radar

    Science.gov (United States)

    Yan, S.; Brozena, J. M.; Gogineni, P. S.; Abelev, A.; Gardner, J. M.; Ball, D.; Liang, R.; Newman, T.

    2016-12-01

    During the early spring of 2016 the Naval Research Laboratory (NRL) performed a test of a next generation airborne snow radar over ground truth data collected on several areas of fast ice near Barrow, AK. The radar was developed by the Center for Remote Sensing of Ice Sheets (CReSIS) at the University of Kansas, and includes several improvements compared to their previous snow radar. The new unit combines the earlier Ku-band and snow radars into a single unit with an operating frequency spanning the entire 2-18 GHz, an enormous bandwidth which provides the possibility of snow depth measurements with 1.5 cm range resolution. Additionally, the radar transmits on dual polarizations (H and V), and receives the signal through two orthogonally polarized Vivaldi arrays, each with 128 phase centers. The 8 sets of along-track phase centers are combined in hardware to improve SNR and narrow the beamwidth in the along-track, resulting in 8 cross-track effective phase centers which are separately digitized to allow for beam sharpening and forming in post-processing. Tilting the receive arrays 30 degrees from the horizontal also allows the formation of SAR images and the potential for estimating snow-water equivalent (SWE). Ground truth data (snow depth, density, salinity and SWE) were collected over several 60 m wide swaths that were subsequently overflown with the snow radar mounted on a Twin Otter. The radar could be operated in nadir (by beam steering the receive antennas to point beneath the aircraft) or side-looking modes. Results from the comparisons will be shown.

  4. Estimation of snow cover distribution in Beas basin, Indian Himalaya using satellite data and ground measurements

    Indian Academy of Sciences (India)

    H S Negi; A V Kulkarni; B S Semwal

    2009-10-01

    In the present paper,a methodology has been developed for the mapping of snow cover in Beas basin,Indian Himalaya using AWiFS (IRS-P6)satellite data.The complexities in the mapping of snow cover in the study area are snow under vegetation,contaminated snow and patchy snow. To overcome these problems,field measurements using spectroradiometer were carried out and reflectance/snow indices trend were studied.By evaluation and validation of different topographic correction models,it was observed that,the normalized difference snow index (NDSI)values remain constant with the variations in slope and aspect and thus NDSI can take care of topography effects.Different snow cover mapping methods using snow indices are compared to find the suitable mapping technique.The proposed methodology for snow cover mapping uses the NDSI (estimated using planetary re flectance),NIR band reflectance and forest/vegetation cover information.The satellite estimated snow or non-snow pixel information using proposed methodology was validated with the snow cover information collected at three observatory locations and it was found that the algorithm classify all the sample points correctly,once that pixel is cloud free.The snow cover distribution was estimated using one year (2004 –05)cloud free satellite data and good correlation was observed between increase/decrease areal extent of seasonal snow cover and ground observed fresh snowfall and standing snow data.

  5. Snow

    Institute of Scientific and Technical Information of China (English)

    小雅

    2011-01-01

    雪花,雪花,白又凉。雪花,雪花,来了又走。啊,雪花!你去哪儿?我不知道,我不知道,飘到哪儿。%Snow, snow, White and cold. Snow, snow, Come and go. Oh, snow! Where do you go? I don't know, I don't know. Where I go.

  6. 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

  7. Snow Mass Quantification and Avalanche Victim Search By Ground Penetrating Radar

    Science.gov (United States)

    Jaedicke, C.

    Ground penetrating radar (GPR) systems can be used in many applications of snow and ice research. The information from the GPR is interpreted to identify layers, ob- ject and different structures in the snow. A commercially available GPR system was further developed to work in the rough environment of snow and ice. The applied GPR is a 900 MHz system that easily reaches snow depths of ten meters. The system is cal- ibrated by several manual snow depth measurements during each survey. The depth resolution is depending on the snow type and ranges around +/- 0.1 m. The GPR sys- tem carried along a line of interest and is triggered by an odometer wheel at regular adjustable steps. All equipment is mounted in a sledge and is moved by a snow mo- bile over the surface. This setup allows the efficient coverage of several kilometers of profiles. The radar profiles give a real time two-dimensional impression of structures and objects and the interface between snow and underlying ground. The actual radar profile is shown on a screen on the sledge allowing the immediate marking of objects and structures. During the past three years the instrument was successfully used for the study of snow distributions, for the detection of glacier crevasses under the snow cover and for the search of avalanche victims in avalanche debris. The results show the capability of the instrument to detect persons and objects in the snow cover. In the future this could be new tool for avalanche rescue operations. Today the size and weight of the system prevents the access to very steep slopes and areas not accessible for snowmobile. Further development will decrease the size of the system and make it a valuable tool to quantify the snow mass in avalanche release zones and run out areas.

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

    Science.gov (United States)

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

    2016-12-01

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

  9. Quantifying snow and vegetation interactions in the high arctic based on ground penetrating radar (GPR)

    DEFF Research Database (Denmark)

    Gacitúa, G.; Bay, C.; Tamstorf, M.

    2013-01-01

    The quantification of the relationship between accumulation of snow and vegetation is crucial for understanding the influence of vegetation dynamics. We here present an analysis of the thickness of the snow and hydrological availability in relation to the seven main vegetation types in the High...... Arctic in Northeast Greenland. We used ground penetrating radar (GPR) for snow thickness measurements across the Zackenberg valley. Measurements were integrated to the physical conditions that support the vegetation distribution. Descriptive statistics and correlations of the distribution of each...

  10. Impact of the variability of the seasonal snow cover on the ground surface regimes in Hurd Peninsula (Livingston Island, Antarctic)

    Science.gov (United States)

    Nieuwendam, Alexandre; Ramos, Miguel; Vieira, Gonçalo

    2014-05-01

    Seasonally snow cover has a great impact on the thermal regime of the active layer and permafrost. Ground temperatures over a year are strongly affected by the timing, duration, thickness, structure and physical and thermal properties of snow cover. The purpose of this communication is to characterize the shallow ground thermal regimes, with special reference to the understanding of the influence snow cover in permafrost spatial distribution, in the ice-free areas of the north western part of Hurd Peninsula in the vicinity of the Spanish Antarctic Station "Juan Carlos I" and Bulgarian Antarctic Station "St. Kliment Ohridski". We have analyzed and ground temperatures as well as snow thickness data in four sites distributed along an altitudinal transect in Hurd Peninsula from 2007 to 2013: Nuevo Incinerador (25 m asl), Collado Ramos (110 m), Ohridski (140 m) and Reina Sofia Peak (275 m). At each study site, data loggers were installed for the monitoring of air temperatures (at 1.5 m high), ground temperatures (5, 20 and 40 cm depth) and for snow depth (2, 5, 10, 20, 40, 80 and 160 cm) at 4-hour intervals. The winter data suggests the existence of three types of seasonal stages regarding the ground surface thermal regime and the thickness of snow cover: (a) shallow snow cover with intense ground temperatures oscillations; (b) thick snow cover and low variations of soil temperatures; and (c) stability of ground temperatures. Ground thermal conditions are also conditioned by a strong variability. Winter data indicates that Nuevo Incinerador site experiences more often thicker snow cover with higher ground temperatures and absence of ground temperatures oscillations. Collado Ramos and Ohridski show frequent variations of snow cover thickness, alternating between shallow snow cover with high ground temperature fluctuation and thick snow cover and low ground temperature fluctuation. Reina Sofia in all the years has thick snow cover with little variations in soil

  11. Inferring snow pack ripening and melt out from distributed ground surface temperature measurements

    Directory of Open Access Journals (Sweden)

    M.-O. Schmid

    2012-02-01

    Full Text Available The seasonal snow cover and its melting are heterogeneous both in space and time. Describing and modelling this variability are important because it affects divers phenomena such as runoff, ground temperatures or slope movements. This study investigates the derivation of melting characteristics based on spatial clusters of temperature measurements. Results are based on data from Switzerland where ground surface temperatures were measured with miniature loggers (iButtons at 40 locations, referred to as footprints. At each footprint, ten iButtons have been distributed randomly few cm below the ground surface over an area of 10 m × 10 m. Footprints span elevations of 2100–3300 m a.s.l. and slope angles of 0–55°, as well as diverse slope expositions and types of surface cover and ground material. Based on two years of temperature data, the basal ripening date and the melt-out date are determined for each iButton, aggregated to the footprint level and further analysed. The date of melt out could be derived for nearly all iButtons, the ripening date could be extracted for only approximately half of them because it requires ground freezing below the snow pack. The variability within a footprint is often considerable and one to three weeks difference between melting or ripening of the points in one footprint is not uncommon. The correlation of mean annual ground surface temperatures, ripening date and melt-out date is moderate, making them useful intuitive complementary measured for model evaluation.

  12. Modelling runoff in the northern boreal forest using SLURP with snow ripening and frozen ground

    Science.gov (United States)

    St. Laurent, M. E.; Valeo, C.

    2003-04-01

    Northern Manitoba is rich in water resources and the management of this water resource is affected by the hydrological processes taking place in the primarily Boreal forested, flat landscape of the region. This work provides insight into large-scale hydrological modelling in this area using the SLURP hydrological model while incorporating the effects of ripening snow and frozen ground. SLURP was applied to two large watersheds in northern Manitoba. The Taylor River watershed (800 square-km) and the Burntwood River watershed (7000 square-km) were used as study boundaries for the calibration and validation of the original SLURP model (version 12.2) and a modified version that incorporated frozen ground and ripening snow. Digital Elevation Models were derived with ARC/INFO's TOPOGRID function, and in conjunction with digital land cover data, ASAs and their associated physiographic data were derived using SLURPView. A thorough literature review of boreal forest hydrology provided initial parameter estimates. Daily data from 1984 to 1998 were used to calibrate and verify the original model under a variety of meteorological conditions. Calibration on the Taylor River watershed produced respectable results, and model verification efficiencies over the 15 year period were quite good. Verification performance of the Taylor parameter set on the Burntwood River watershed was not acceptable, but only modifications to the evapotranspiration parameters were required to bring model performance up to acceptable levels. Comparisons between observed and computed hydrographs identified problems with spring snowmelt timing, peak and volume prediction. This may be attributed to a lack of consideration for frozen ground in the model, and the use of the temperature index method for snowmelt. Simulations that incorporated a widely used frozen ground infiltration model into SLURP did not improve model performance. However, when SLURP's snowmelt routine was modified to consider the effects

  13. The role of snow cover in ground thermal conditions in three sites with contrasted topography in Sierra Nevada (Spain)

    Science.gov (United States)

    Oliva, Marc; Salvador, Ferran; Gómez Ortiz, Antonio; Salvà, Montserrat

    2014-05-01

    Snow cover has a high capacity to insulate the soil from the external thermal influences. In regions of high snowfall, such as the summit areas of the highest Iberian mountain ranges, the presence of a thick snow cover may condition the existence or inexistence of permafrost conditions. In order to analyze the impact of the thickness, duration and interannual variability of snow cover on the ground thermal regime in the massif of Sierra Nevada, we have analyzed soil temperatures at a depth of 2 cm for the period 2006-2012 in three sites of contrasting topography as well as air temperatures for the same period: (a) Corral del Veleta (3100 m) in a rock glacier located in the northern Veleta cirque, with high and persistent snow cover. (b) Collado de los Machos (3300 m), in a summit area with relict stone circles, with little snow accumulation due to wind effect. (c) Río Seco (3000 m), in a solifluction lobe located in this southern glacial cirque with moderate snowfall. Considering the air and 2 cm depth soil temperature records, the freezing degree-days were calculated for each year from November to May in order to characterize the role of snow as a thermal insulator of the ground during the cold season (Frauenfeld et al., 2007). In all cases, the highest values of freezing degree-days correspond to years with little snowfall (2006-2007, 2007-2008, 2011-2012), while in years with a thicker snow cover (2008-2009, 2009-2010, 2010-2011) the total freezing degree-days were significantly lower. The accumulation of freezing degree-days is maximum at the wind-exposed site of Collado de los Machos, where the wind redistributes snow and favours the penetration of cold into the ground. The opposite pattern occurs in the Veleta cirque, where most persistent snow cover conditions determine lower accumulated freezing degree-days than in Collado de los Machos and Rio Seco.

  14. Recovering the Seismic Energy Transmitted to the Ground by Snow Avalanches.

    Science.gov (United States)

    Mangeney, A.; Surinach, E.; Levy, C.; Roig, P.

    2016-12-01

    The energy transmitted into the ground by flowing snow avalanches was estimated by using the seismic signal recorded at two different sites by UB LE-3D/5s seismic sensors. One sensor was located on the avalanche path, so that the avalanche passes over it. The second one was placed at about 400 m from the runout zone. The energy was recovered at each position of the path taking into account the attenuation factors (intrinsic attenuation and geometrical spreading) as in Vilajosana et al. (2008). Seismic characteristics of the ground, Digital Elevation Model of the area were taking into account for this calculation. The coincidence of the recovered energy at each position coming from the two sensors validates the approach. We then simulated the avalanches that occurred in 2004-2008 at the Ryggfonn experimental site (Norway) (Gauer and Kristensen, 2016) using the data obtained in collaboration with the Norwegian Geotechnical Institute. Dense and Mixed (artificially triggered and spontaneous) avalanches of large and medium size were studied. Video images and characteristics of the snow helped in the determination of the characteristics of the avalanches. The approximate length of the path was 2 km and the vertical drop was 900 m. The transmitted energy shows a good correspondence with the outputs of the SHALTOP numerical model that we used to simulate the snow avalanche along the real topography. We also show a correlation between the seismic energy and the fluctuations of the topography along the avalanche path. Moreover, for the two sites and different parts of the avalanche we recovered similar power laws relating the seismic energy and the signal duration than those observed in a very different environment with different gravitational flows (i. e. rockfalls and pyroclastic flows in La Réunion by Hibert et al., 2011 and Montserrat by Levy et al., 2015).

  15. Effects of ground freezing and snow avalanche deposits on debris flows in alpine environments

    Directory of Open Access Journals (Sweden)

    E. Bardou

    2004-01-01

    Full Text Available Debris flows consist of a mixture of water and sediments of various sizes. Apart from few exceptions, the water is usually contributed directly from precipitation. In a high mountain environment like the Alps, it appears necessary to consider infiltration of water into the ground during rainfall events, the runoff characteristics and the potential supply of sediment as a function of a multitude of climatic and hydrogeological factors. This paper outlines several new processes - either linked to ice formation in the ground before an event, or to the presence of snow avalanche deposits - that change the probability of observing an event. These processes were identified during field observations connected with extreme weather events that occurred recently in the Valais Alps (south-western Switzerland: they can be seen as factors either amplifying or reducing the potential of slope instability caused by the precipitation event. An intense freezing of the ground during the week preceding the exceptional rainfall event in mid-October 2000 amplified the probability of triggering debris flows between roughly 1800 and 2300m asl. Both growth of ice needles and superficial ground freezing destroyed soil aggregates (increasing the availability of sediments and/or, a deeper ground freezing resulted in decreased infiltration rate (increased runoff during the first hours of heavy rainfall. The presence of snow avalanche deposits in a gully could be simultaneously an amplifying factor (the snow deposits increase the base flow and create a sliding plane for the sediments, mainly at the time of summer storms or a reducing factor (reduction in the impact energy of the raindrops, mainly at the time of winter storms of the risk of triggering debris flows. If it is not currently possible to establish rainfall threshold values for debris flow triggering, the knowledge and the implementation of these processes in the analysis of the potential triggering (for example by

  16. Evidence of wintertime CO2 emission from snow-covered grounds in high latitudes

    Institute of Scientific and Technical Information of China (English)

    方精云; 唐艳鸿KOIZUMI; Hiroshi(Division; of; Plant; Ecology; National; Institute; of; Agro-Environmental; Sciences; Tsukuba; 305; Japan)BEKKU; Yukiko(National; Polar; Institute; Tokyo; 192; Japan)

    1999-01-01

    In order to measure CO2 flux in wintertime arctic ecosystems, CO2 gas was sampled from various snow-covered grounds by using a closed chamber method during the First China Arctic Scientific Expedition from March to May in 1995. The CO2 gas samples were measured by using an infra-red analyzer (IRGA). The results showed that (ⅰ) CO2 emission was detected from all kinds of the snow-covered grounds, which provides direct evidence that the arctic tundra is functioning as a source of atmospheric CO2; (ⅱ) CO2 release was also detected from the permanent ice profile and icecap, and (ⅲ) CO2 evolution from terrestrial ecosystems in higher latitudes increased with an increase of surface temperature in accordance with the exponential function. This indicates a close coincidence with that under normal temperature conditions, and provides a useful method for predicting change in CO2 flux in the arctic ecosystems with the global climate change.

  17. Assessment of the temperature variability at the snow-ground interface - concept and first results

    Science.gov (United States)

    Hiller, Clemens; Keuschnig, Markus; Hartmeyer, Ingo; Götz, Joachim

    2014-05-01

    Bottom temperatures of the winter snow cover (BTS) represent the thermal conditions at the snow-ground interface and serve as a proxy for local permafrost ocurrence. The BTS method has been used in numerous studies to investigate local permafrost evidence and to validate larger scale permafrost distribution models. However, former studies have shown a relatively strong scattering between single measurements indicating that BTS values are sensitive to further factors. In order to identify the spatial and temporal variability and mentioned sources of irritation and to better understand their influence we applied repeated BTS measurements on a small scale test site situated below the Maurerkogel (2990 m) nearby the Kitzsteinhorn, Hohe Tauern Range, Austria. The site (c. 2000 m2) shows fairly homogenous surface conditions in terms of roughness and morphometry (bedrock with thin layer of fine-grained talus, slightly inclined to N). The measurement setup consists of a BTS grid with a minimum spacing of 5 m. Four campaigns with a total of 94 measurements were carried out from March 2012 to April 2013. Universal Temperature Logger (UTL), snow profiles and meteorological data from automatic weather stations are used to interpret the BTS values. The standard deviations of BTS values for each campaign range between 0.4 and 0.9 °C. The mean BTS value within the overall period is -3.1 °C. The near surface temperature logger shows a mean temperature of -3.7 °C in 10 cm depth covering four campaign days. Both, the correlation between near surface temperatures and BTS values as well as the low standard deviation between the BTS values demonstrate the applicability of the method under appropriate conditions.

  18. Comparison of Snow Albedo from MISR, MODIS and AVHRR with ground-based observations on the Greenland Ice Sheet

    Science.gov (United States)

    Stroeve, J. C.; Nolin, A.

    2001-12-01

    The surface albedo is an important climate parameter, as it controls the amount of solar radiation absorbed by the surface. For snow-covered surfaces, the albedo may be greater than 0.80, thereby allowing very little solar energy to be absorbed by the snowpack. As the snow ages and/or begins to melt, the albedo is reduced considerably, leading to enhanced absorption of solar radiation. Consequently, snow melt, comprises an unstable, positive feedback component of the climate system, which amplifies small pertubations to that system. Satellite remote sensing offers a means for measuring and monitoring the surface albedo of snow-covered areas. This study evaluates snow surface albedo retrievals from MISR, MODIS and AVHRR through comparisons with surface albedo measurements obtained in Greenland. Data from automatic weather stations, in addition to other in situ data collected during 2000 provide the ground-based measurements with which to compare coincident clear-sky satellite albedo retrievals. In general, agreements are good with the satellite data. However, satellite calibration and difficulties accurately representing the angular signature of the snow surface make it difficult to reach an albedo accuracy within 0.05.

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

    Science.gov (United States)

    Mizinski, Bartlomiej; Niedzielski, Tomasz

    2017-04-01

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

  20. Investigation of snow-firn thickness and ground in the East Antarctica by means of geophysical radar

    Directory of Open Access Journals (Sweden)

    S. V. Popov

    2014-01-01

    Full Text Available Results of field investigations of snow-and-firn thickness and ground structures performed with the use of geophysical radar GPR (Ground-Penetrating Radar are discussed in the paper. Industrial radar GSSI SIR10B (Geophysical Survey Systems, Inc., USA with «5106» antenna (pulses frequency of 200 MHz was used. Its mean wavelength is 1.57±0.18 km. The main purpose of this work was to test this new technique for solution of glaciological and geological problems. The works were done during the austral summer season of 2012–2013 (58th Russian Antarctic Expedition in the Eastern Antarctica and mainly concentrated in the vicinity of the Lake Vostok, between the Russian stations Vostok and Progress (the Larsemann Hills. The GPR sounding was carried out together with precise geodetic measurements. The electromagnetic wave propagation in the snow-firn layer was analyzed using the data on density obtained from the 5G borehole at the Vostok Station. Investigations near the Vostok Station focused on a huge snow ridge or so-called “megadune” located eastward from the station at a distance of 30 km. About 80 km of the GPR cross-sections were collected there. Eight internal layers were traced. They demonstrated wavy forms with amplitudes of about 10 m high which corresponded to the megadunes. Main result of GPR investigations in the Larsemann Hills was our understanding of the snow-firn and ground structures in this region. The GPR data collected on structures of crevasses near Progress-1, shallow glacier near the Progress-3, and ground not far from Progress-2 are also discussed. Methodological recommendations on using the GPR under conditions of the Eastern Antarctica were developed.

  1. Study of seasonal snow cover influencing the ground thermal regime on western flank of Da Xing'anling Mountains, northeastern China

    Institute of Scientific and Technical Information of China (English)

    XiaoLi Chang; HuiJun Jin; YanLin Zhang; HaiBin Sun

    2015-01-01

    Although many studies relevant to snow cover and permafrost have focused on alpine, arctic, and subarctic areas, there is still a lack of understanding of the influences of seasonal snow cover on the thermal regime of the soils in permafrost regions in the mid-latitudes and boreal regions, such as that on the western flank of the Da Xing'anling (Hinggan) Mountains, northeastern China. This paper gives a detailed analysis on meteorological data series from 2001 to 2010 provided by the Gen'he Weather Station, which is located in a talik of discontinuous permafrost zone and with sparse meadow on the observation field. It is inferred that snow cover is important for the ground thermal regime in the middle Da Xing'anling Mountains. Snow cover of 10-cm in thickness and five to six months in duration (generally November to next March) can reduce the heat loss from the ground to the atmosphere by 28%, and by 71% if the snow depth increases to 36 cm. Moreover, the occurrence of snow cover resulted in mean annual ground surface temperatures 4.7–8.2°C higher than the mean annual air temperatures recorded at the Gen'he Weather Station. The beginning date for stable snow cover establishment (SE date) and the initial snow depth (SDi) also had a great influences on the ground freezing process. Heavy snowfall before ground surface freeze-up could postpone and retard the freezing process in Gen'he. As a result, the duration of ground freezing was shortened by at least 20 days and the maximum depth of frost penetration was as much as 90 cm shallower.

  2. Effects of spatially variable snow cover on thermal regime and hydrology of an Arctic ice wedge polygon landscape identified using ground penetrating radar and LIDAR datasets

    Science.gov (United States)

    Gusmeroli, A.; Liljedahl, A. K.; Peterson, J. E.; Hubbard, S. S.; Hinzman, L. D.

    2012-12-01

    Ice wedge polygons are common in Arctic terrains underlain by permafrost. Permafrost degradation could transform low- into high centered polygons, causing profound changes in the hydrologic regime of Arctic lands, which in turn, could affect the energy balance and subsurface biodegradation of organic carbon responsible for greenhouse gas production. Understanding the linkages between microtopography, snow cover, thermal properties, and thaw depth is critical for developing a predictive understanding of terrestrial ecosystems and their feedbacks to climate. In this study, we use high frequency (500-1000 MHz) ground penetrating radar (GPR) data acquired in spring 2012 within the Next Generation Ecosystem Experiment (NGEE) study site in Barrow, AK to characterize the spatial variability of snow distribution. We compare it's distribution to microtopography, estimated using LIDAR data, and thaw depth, also estimated using ground penetrating radar collected at different times during the year and simulated over time using mechanistic thermal-hydrologic modeling. The high spatial resolution offered by LIDAR and ground penetrating radar permit detailed investigations of the control of microtopography on snow and thaw layer depth. Results suggest that microtopographical variations are responsible for substantial differences in snow accumulation. In low centered polygons, snow depth can be up to four times greater in the troughs than on the rims. Both modeling and observations suggest that the microtopography-governed snow thickness affects the thermal properties of the subsurface and thus the thaw layer thickness; regions with thicker snowpack generally correspond to regions of greater thaw depth. We conclude that a transition from low- to high centered polygons will not only impact watershed runoff but, since snow accumulation is sensitive to the microtopography, it will also impact snow distribution. In turn, snow distribution affects thaw depth thickness, and the

  3. Estimating spatial distribution of daily snow depth with kriging methods: combination of MODIS snow cover area data and ground-based observations

    Directory of Open Access Journals (Sweden)

    C. L. Huang

    2015-09-01

    Full Text Available Accurately measuring the spatial distribution of the snow depth is difficult because stations are sparse, particularly in western China. In this study, we develop a novel scheme that produces a reasonable spatial distribution of the daily snow depth using kriging interpolation methods. These methods combine the effects of elevation with information from Moderate Resolution Imaging Spectroradiometer (MODIS snow cover area (SCA products. The scheme uses snow-free pixels in MODIS SCA images with clouds removed to identify virtual stations, or areas with zero snow depth, to compensate for the scarcity and uneven distribution of stations. Four types of kriging methods are tested: ordinary kriging (OK, universal kriging (UK, ordinary co-kriging (OCK, and universal co-kriging (UCK. These methods are applied to daily snow depth observations at 50 meteorological stations in northern Xinjiang Province, China. The results show that the spatial distribution of snow depth can be accurately reconstructed using these kriging methods. The added virtual stations improve the distribution of the snow depth and reduce the smoothing effects of the kriging process. The best performance is achieved by the OK method in cases with shallow snow cover and by the UCK method when snow cover is widespread.

  4. Temporal monitoring of the soil freeze-thaw cycles over snow-cover land by using off-ground GPR

    KAUST Repository

    Jadoon, Khan

    2013-07-01

    We performed off-ground ground-penetrating radar (GPR) measurements over a bare agricultural field to monitor the freeze-thaw cycles over snow-cover. The GPR system consisted of a vector network analyzer combined with an off-ground monostatic horn antenna, thereby setting up an ultra-wideband stepped-frequency continuous-wave radar. Measurements were performed during nine days and the surface of the bare soil was exposed to snow fall, evaporation and precipitation as the GPR antenna was mounted 110 cm above the ground. Soil surface dielectric permittivity was retrieved using an inversion of time-domain GPR data focused on the surface reflection. The GPR forward model used combines a full-waveform solution of Maxwell\\'s equations for three-dimensional wave propagation in planar layered media together with global reflection and transmission functions to account for the antenna and its interactions with the medium. Temperature and permittivity sensors were installed at six depths to monitor the soil dynamics in the top 8 cm depth. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and permittivity data and in particular freeze and thaw events were clearly visible. A good agreement of the trend was observed between the temperature, permittivity and GPR time-lapse data with respect to five freeze-thaw cycles. The GPR-derived permittivity was in good agreement with sensor observations. The proposed method appears to be promising for the real-time mapping and monitoring of the frozen layer at the field scale. © 2013 IEEE.

  5. Permafrost, Seasonally Frozen Ground, Snow Cover and Vegetation in the USSR

    Science.gov (United States)

    1984-12-01

    Late Quaternary History and the Formation of Sedi- ments in the Marginal and Inland Seas (Pozdnechetvertichnaia Istorlia i Sedimentogenez...rasprostraneniia snezhnogo pokrova na poverkhnosti sushi zemnogo shara). In Geography of Snow Cover (Geo- grafiya Snezhnogo Prokrova). Moscow: Izdat...Papers, 18(3): 198-202. (36-1668) Vigdorchik, M.E. (1980) Arctic Pleistocene History and the Development of Submarine Permafrost. Boulder

  6. 50 years of snow stratigraphy observations

    Science.gov (United States)

    Johansson, C.; Pohjola, V.; Jonasson, C.; Challagan, T. V.

    2012-04-01

    With start in autumn 1961 the Abisko Scientific Research Station (ASRS) located in the Swedish sub Arctic has performed snow stratigraphy observations, resulting in a unique 50 year long time series of data. The data set contains grain size, snow layer hardness, grain compactness and snow layer dryness, observed every second week during the winter season. In general snow and snow cover are important factors for the global radiation budget, and the earth's climate. On a more local scale the layered snowpack creates a relatively mild microclimate for Arctic plants and animals, and it also determines the water content of the snowpack (snow water equivalent) important for e.g. hydrological applications. Analysis of the snow stratigraphy data, divided into three consecutive time periods, show that there has been a change in the last time period. The variable most affected is the snow layer hardness, which shows an increase in hardness of the snowpack. The number of observations with a very hard snow layer/ice at ground level increased three-fold between the first two time periods and the last time period. The thickness of the bottom layer in the snowpack is also highly affected. There has been a 60% increase in layers thinner than 10 cm in the last time period, resulting in a mean reduction in the thickness of the bottom layer from 14 cm to 11 cm. Hence the living conditions for plants and animals at the ground surface have been highly changed. The changes in the snowpack are correlated to an increased mean winter air temperature. Thus, continued increasing, or temperatures within the same ranges as in the last time period, is likely to create harder snow condition in the future. These changes are likely to affect animals that live under the snow such as lemmings and voles or animals that graze sub-Arctic vegetation in winter (e.g. reindeer that would potentially require increased supplementary feeding that incurs financial costs to Sami reindeer herders). Any decrease

  7. Snow physics as relevant to snow photochemistry

    Directory of Open Access Journals (Sweden)

    F. Domine

    2007-05-01

    Full Text Available Snow on the ground is a complex multiphase photochemical reactor that dramatically modifies the chemical composition of the overlying atmosphere. A quantitative description of the emissions of reactive gases by snow requires the knowledge of snow physical properties. This overview details our current understanding of how those physical properties relevant to snow photochemistry vary during snow metamorphism. Properties discussed are density, specific surface area, optical properties, thermal conductivity, permeability and gas diffusivity. Inasmuch as possible, equations to parameterize these properties as a function of climatic variables are proposed, based on field measurements, laboratory experiments and theory. The potential of remote sensing methods to obtain information on some snow physical variables such as grain size, liquid water content and snow depth are discussed. The possibilities for and difficulties of building a snow photochemistry model by adapting current snow physics models are explored. Elaborate snow physics models already exist, and including variables of particular interest to snow photochemistry such as light fluxes and specific surface area appears possible. On the other hand, understanding the nature and location of reactive molecules in snow seems to be the greatest difficulty modelers will have to face for lack of experimental data, and progress on this aspect will require the detailed study of natural snow samples.

  8. Ground Snow Measurements: Comparisons of the Hotplate, Weighing and Manual Methods

    Science.gov (United States)

    Wettlaufer, A.; Snider, J.; Campbell, L. S.; Steenburgh, W. J.; Burkhart, M.

    2015-12-01

    The Yankee Environmental Systems (YES) Hotplate was developed to avoid some of the problems associated with weighing snowfall sensors. This work compares Hotplate, weighing sensor (ETI NOAH-II) and manual measurements of liquid-equivalent depth. The main field site was at low altitude in western New York; Hotplate and ETI comparisons were also made at two forested subalpine sites in southeastern Wyoming. The manual measurement (only conducted at the New York site) was derived by weighing snow cores sampled from a snow board. The two recording gauges (Hotplate and ETI) were located within 5 m of the snow board. Hotplate-derived accumulations were corrected using a wind-speed dependent catch efficiency and the ETI orifice was heated and alter shielded. Three important findings are evident from the comparisons: 1) The Yes-derived accumulations, recorded in a user-accessible file, were compared to accumulations derived using an in-house calibration and fundamental measurements (plate power, long and shortwave radiances, wind speed, and temperature). These accumulations are highly correlated (N=24; r2=0.99), but the YES-derived values are larger by 20%. 2) The in-house Hotplate accumulations are in good agreement with ETI-based accumulations but with larger variability (N=24; r2=0.88). 3) The comparison of in-house Hotplate accumulation versus manual accumulation, expressed as mm of liquid, exhibits a fitted linear relationship Y (in-house) versus X (manual) given by Y = -0.2 (±1.4) + 0.9 (±0.1) · X (N= 20; r2=0.89). Thus, these two methods agree within statistical uncertainty.

  9. Microwave scattering coefficient of snow in MEMLS and DMRT-ML revisited: the relevance of sticky hard spheres and tomography-based estimates of stickiness

    Science.gov (United States)

    Löwe, H.; Picard, G.

    2015-11-01

    The description of snow microstructure in microwave models is often simplified to facilitate electromagnetic calculations. Within dense media radiative transfer (DMRT), the microstructure is commonly described by sticky hard spheres (SHS). An objective mapping of real snow onto SHS is however missing which prevents measured input parameters from being used for DMRT. In contrast, the microwave emission model of layered snowpacks (MEMLS) employs a conceptually different approach, based on the two-point correlation function which is accessible by tomography. Here we show the equivalence of both electromagnetic approaches by reformulating their microstructural models in a common framework. Using analytical results for the two-point correlation function of hard spheres, we show that the scattering coefficient in both models only differs by a factor which is close to unity, weakly dependent on ice volume fraction and independent of other microstructural details. Additionally, our analysis provides an objective retrieval method for the SHS parameters (diameter and stickiness) from tomography images. For a comprehensive data set we demonstrate the variability of stickiness and compare the SHS diameter to the optical equivalent diameter. Our results confirm the necessity of a large grain-size scaling when relating both diameters in the non-sticky case, as previously suggested by several authors.

  10. Using ground penetrating radar to assess the variability of snow water equivalent and melt in a mixed canopy forest, Northern Colorado

    Science.gov (United States)

    Webb, Ryan W.

    2017-09-01

    Snow is an important environmental variable in headwater systems that controls hydrological processes such as streamflow, groundwater recharge, and evapotranspiration. These processes will be affected by both the amount of snow available for melt and the rate at which it melts. Snow water equivalent (SWE) and snowmelt are known to vary within complex subalpine terrain due to terrain and canopy influences. This study assesses this variability during the melt season using ground penetrating radar to survey multiple plots in northwestern Colorado near a snow telemetry (SNOTEL) station. The plots include south aspect and flat aspect slopes with open, coniferous (subalpine fir, Abies lasiocarpa and engelman spruce, Picea engelmanii), and deciduous (aspen, populous tremuooides) canopy cover. Results show the high variability for both SWE and loss of SWE during spring snowmelt in 2014. The coefficient of variation for SWE tended to increase with time during snowmelt whereas loss of SWE remained similar. Correlation lengths for SWE were between two and five meters with melt having correlation lengths between two and four meters. The SNOTEL station regularly measured higher SWE values relative to the survey plots but was able to reasonably capture the overall mean loss of SWE during melt. Ground Penetrating Radar methods can improve future investigations with the advantage of non-destructive sampling and the ability to estimate depth, density, and SWE.

  11. Ground measurements of the hemispherical-directional reflectance of Arctic snow covered tundra for the validation of satellite remote sensing products

    Science.gov (United States)

    Ball, C. P.; Marks, A. A.; Green, P.; Mac Arthur, A.; Fox, N.; King, M. D.

    2013-12-01

    Surface albedo is the hemispherical and wavelength integrated reflectance over the visible, near infrared and shortwave infrared regions of the solar spectrum. The albedo of Arctic snow can be in excess of 0.8 and it is a critical component in the global radiation budget because it determines the proportion of solar radiation absorbed, and reflected, over a large part of the Earth's surface. We present here our first results of the angularly resolved surface reflectance of Arctic snow at high solar zenith angles (~80°) suitable for the validation of satellite remote sensing products. The hemispherical directional reflectance factor (HDRF) of Arctic snow covered tundra was measured using the GonioRAdiometric Spectrometer System (GRASS) during a three-week field campaign in Ny-Ålesund, Svalbard, in March/April 2013. The measurements provide one of few existing HDRF datasets at high solar zenith angles for wind-blown Arctic snow covered tundra (conditions typical of the Arctic region), and the first ground-based measure of HDRF at Ny-Ålesund. The HDRF was recorded under clear sky conditions with 10° intervals in view zenith, and 30° intervals in view azimuth, for several typical sites over a wavelength range of 400-1500 nm at 1 nm resolution. Satellite sensors such as MODIS, AVHRR and VIIRS offer a method to monitor the surface albedo with high spatial and temporal resolution. However, snow reflectance is anisotropic and is dependent on view and illumination angle and the wavelength of the incident light. Spaceborne sensors subtend a discrete angle to the target surface and measure radiance over a limited number of narrow spectral bands. Therefore, the derivation of the surface albedo requires accurate knowledge of the surfaces bidirectional reflectance as a function of wavelength. The ultimate accuracy to which satellite sensors are able to measure snow surface properties such as albedo is dependant on the accuracy of the BRDF model, which can only be assessed

  12. Wind slab formation in snow: experimental setup and first results

    Science.gov (United States)

    Sommer, Christian; Lehning, Michael; Fierz, Charles

    2016-04-01

    The formation of wind-hardened surface layers, also known as wind slabs or wind crusts, is studied. Better knowledge about which processes and parameters are important will lead to an improved understanding of the mass balances in polar and alpine areas. It will also improve snow-cover models (i.e. SNOWPACK) as well as the forecast of avalanche danger. A ring-shaped wind tunnel has been built and instrumented. The facility is ring-shaped to simulate an infinitely long snow surface (infinite fetch). A SnowMicroPen (SMP) is used to measure the snow hardness. Other sensors measure environmental conditions such as wind velocity, air temperature, air humidity, the temperature of the snow and of the snow surface. A camera is used to detect drifting particles and to measure the Specific Surface Area (SSA) at the snow surface via near-infrared photography. First experiments indicate that mechanical fragmentation followed by sintering is the most efficient process to harden the surface. The hardness increased rapidly during drifting snow events, but only slowly or not at all when the wind speed was kept below the threshold for drifting snow. With drifting, the penetration resistance increased from the original 0.07 N to around 0.3 N in about an hour. Without drifting, a slow, further increase in resistance was observed. In about six hours, the hardness of the top 1-2 cm increased to 0.5 N. During this eight-hour experiment consisting of about two hours with intermittent drifting and six hours without drifting, the density at the surface increased from 66 kg/m3 to around 170 kg/m3. In the unaffected region close to the ground, the density increased from 100 kg/m3 to 110 kg/m3.

  13. SITE-94. Geochemical characterization of Simpevarp ground waters near the Aespoe Hard Rock Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Glynn, P.D.; Voss, C.I. [US Geological Survey, Reston, VA (United States)

    1999-09-01

    The present report analyzes the geochemical data in order to evaluate collection and interpretation techniques that will be used to site the repository and to assess its safety. Ground waters near the Aespoe Hard Rock Laboratory (HRL) may be grouped into five chemically and isotopically distinct water types, on the basis of their deuterium and chloride contents: 1) recent waters, 2) 5 g/L chloride waters, 3) deep waters, 4) seawater imprint waters, and 5) glacial melt waters. The sampled ground waters show a progressive change from a predominantly NaHCO{sub 3} composition at shallow depth to a CaCl{sub 2}-rich composition at depth. Despite the proximity of the Baltic, relatively few of the sampled ground waters contain any evidence of a seawater component. This finding, together with the rather shallow depths at which saline waters were found, indicates that Aespoe island is presently in a regional ground-water discharge area. The chemical and isotopic composition of the sampled waters also indicates that local recharge of dilute recent waters occurs only down to shallow depths (generally less than 100 in). The Aespoe ground waters are sulfidic and do not presently contain any dissolved oxygen. Measured E{sub H} values are generally near -300 mV, and on average are only about 50 mV lower than E{sub H} values calculated from the sulfide/sulfate couple. Maintenance of reducing conditions, such as presently found at the Aespoe HRL, is an important consideration in assessing the performance of nuclear waste disposal sites. Measurements of dissolved radon and of uranium concentrations in fracture-fill materials were used to calculate an average effective flow-wetted surface area of 3.1 m{sup 2} per liter of water for the Aespoe site. Estimation of flow-wetted surface areas is essential in determining the importance of matrix diffusion and surface sorption processes for radionuclide release calculations. The Rn calculation technique shows promise in helping narrow the

  14. Temporal Monitoring of the Soil Freeze-Thaw Cycles over a Snow-Covered Surface by Using Air-Launched Ground-Penetrating Radar

    KAUST Repository

    Jadoon, Khan

    2015-09-18

    We tested an off-ground ground-penetrating radar (GPR) system at a fixed location over a bare agricultural field to monitor the soil freeze-thaw cycles over a snow-covered surface. The GPR system consisted of a monostatic horn antenna combined with a vector network analyzer, providing an ultra-wideband stepped-frequency continuous-wave radar. An antenna calibration experiment was performed to filter antenna and back scattered effects from the raw GPR data. Near the GPR setup, sensors were installed in the soil to monitor the dynamics of soil temperature and dielectric permittivity at different depths. The soil permittivity was retrieved via inversion of time domain GPR data focused on the surface reflection. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and dielectric permittivity measurements. In particular, five freeze and thaw events were clearly detectable, indicating that the GPR signals respond to the contrast between the dielectric permittivity of frozen and thawed soil. The GPR-derived permittivity was in good agreement with sensor observations. Overall, the off-ground nature of the GPR system permits non-invasive time-lapse observation of the soil freeze-thaw dynamics without disturbing the structure of the snow cover. The proposed method shows promise for the real-time mapping and monitoring of the shallow frozen layer at the field scale.

  15. Temporal Monitoring of the Soil Freeze-Thaw Cycles over a Snow-Covered Surface by Using Air-Launched Ground-Penetrating Radar

    Directory of Open Access Journals (Sweden)

    Khan Zaib Jadoon

    2015-09-01

    Full Text Available We tested an off-ground ground-penetrating radar (GPR system at a fixed location over a bare agricultural field to monitor the soil freeze-thaw cycles over a snow-covered surface. The GPR system consisted of a monostatic horn antenna combined with a vector network analyzer, providing an ultra-wideband stepped-frequency continuous-wave radar. An antenna calibration experiment was performed to filter antenna and back scattered effects from the raw GPR data. Near the GPR setup, sensors were installed in the soil to monitor the dynamics of soil temperature and dielectric permittivity at different depths. The soil permittivity was retrieved via inversion of time domain GPR data focused on the surface reflection. Significant effects of soil dynamics were observed in the time-lapse GPR, temperature and dielectric permittivity measurements. In particular, five freeze and thaw events were clearly detectable, indicating that the GPR signals respond to the contrast between the dielectric permittivity of frozen and thawed soil. The GPR-derived permittivity was in good agreement with sensor observations. Overall, the off-ground nature of the GPR system permits non-invasive time-lapse observation of the soil freeze-thaw dynamics without disturbing the structure of the snow cover. The proposed method shows promise for the real-time mapping and monitoring of the shallow frozen layer at the field scale.

  16. Snow monitoring using microwave radars

    OpenAIRE

    Koskinen, Jarkko

    2001-01-01

    Remote sensing has proven its usefulness in various applications. For mapping, land-use classification and forest monitoring optical satellite and airborne images are used operationally. However, this is not the case with snow monitoring. Currently only ground-based in situ and weather measurements are used operationally for snow monitoring in Finland. Ground measurements are conducted once a month on special snow courses. These measurements are used to update the hydrological model that simu...

  17. Characteristics of ground behavior of fully mechanized caving faces in hard thick seams

    Institute of Scientific and Technical Information of China (English)

    SUO Yong-lu(索永录)

    2003-01-01

    It is showed in practice that the support load and its fluctuation is large, the periodic weighting is obvious and can be divided into two kinds, the large and small pressure, sometimes the behavior of the large pressure is very violent in hard thick seam caving faces. These are obviously different from those of the generally soft or medium hard seam caving feces. All above these are summarized, and the causes aroused these are researched. Finally the powered support selection of hard thick seam caving faces is discussed.

  18. Struggling with and for: A Grounded Theory of Parents Managing Life with Hard-to-Treat ADHD Teenagers

    Directory of Open Access Journals (Sweden)

    Berit Støre Brinchmann

    2014-06-01

    Full Text Available The aim of this study was to develop a grounded theory of being a parent of hard-to- treat teenagers with the diagnosis of ADHD. Caretakers of 11 adolescents with ADHD were interviewed and analyzed according to the principles of classic grounded theory. The parents’ main concern was how to handle everyday challenges with the teenagers and how to get the help they needed and required. Struggling with and for is the core category in our findings. In addition, we identified four sub-categories: good “mothering”, advocating, seeking support, and giving up. The meeting with the helping services causes just as many problems as the relationship with the teenagers. Professionals should be able to identify family strengths and capabilities. In that way, professional support can be built upon coping strategies with which a family is already familiar. Keywords: ADHD, coping strategies, grounded theory, parents, professional services, teenagers

  19. Ground-based integrated path coherent differential absorption lidar measurement of CO2: hard target return

    Directory of Open Access Journals (Sweden)

    A. Sato

    2012-11-01

    Full Text Available The National Institute of Information and Communications Technology (NICT have made a great deal of effort to develop a coherent 2-μm differential absorption and wind lidar (Co2DiaWiL for measuring CO2 and wind speed. First, coherent Integrated Path Differential Absorption (IPDA lidar experiments were conducted using the Co2DiaWiL and a hard target (surface return located about 7.12 km south of NICT on 11, 27, and 28 December 2010. The detection sensitivity of a 2-μm IPDA lidar was examined in detail using the CO2 concentration measured by the hard target. The precisions of CO2 measurement for the hard target and 900, 4500 and 27 000 shot pairs were 6.5, 2.8, and 1.2%, respectively. The results indicated that a coherent IPDA lidar with a laser operating at a high pulse repetition frequency of a few tens of KHz is necessary for measuring the CO2 concentration of the hard target with a precision of 1–2 ppm. Statistical comparisons indicated that, although a small amount of in situ data and the fact that they were not co-located with the hard target made comparison difficult, the CO2 volume mixing ratio measured with the Co2DiaWiL was about 5 ppm lower than that measured with the in situ sensor. The statistical results indicated that there were no differences between the hard target and atmospheric return measurements. A precision of 1.5% was achieved from the atmospheric return, which is lower than that obtained from the hard-target returns. Although long-range DIfferential Absorption Lidar (DIAL CO2 measurement with the atmospheric return can result in highly precise measurement, the precision of the atmospheric return measurement was widely distributed comparing to that of the hard target return. Our results indicated that it is important to use a Q-switched laser to measure the range-gated differential absorption optical depth with the atmospheric return and that it is better to simultaneously conduct both hard target and atmospheric return

  20. Bacteriophages reduce experimental contamination of hard surfaces, tomato, spinach, broccoli, and ground beef by Escherichia coli O157:H7.

    Science.gov (United States)

    Abuladze, Tamar; Li, Manrong; Menetrez, Marc Y; Dean, Timothy; Senecal, Andre; Sulakvelidze, Alexander

    2008-10-01

    A bacteriophage cocktail (designated ECP-100) containing three Myoviridae phages lytic for Escherichia coli O157:H7 was examined for its ability to reduce experimental contamination of hard surfaces (glass coverslips and gypsum boards), tomato, spinach, broccoli, and ground beef by three virulent strains of the bacterium. The hard surfaces and foods contaminated by a mixture of three E. coli O157:H7 strains were treated with ECP-100 (test samples) or sterile phosphate-buffered saline buffer (control samples), and the efficacy of phage treatment was evaluated by comparing the number of viable E. coli organisms recovered from the test and control samples. Treatments (5 min) with the ECP-100 preparation containing three different concentrations of phages (10(10), 10(9), and 10(8) PFU/ml) resulted in statistically significant reductions (P = E. coli O157:H7 organisms recovered from the glass coverslips. Similar treatments resulted in reductions of 100%, 95%, and 85%, respectively, in the number of E. coli O157:H7 organisms recovered from the gypsum board surfaces; the reductions caused by the two most concentrated phage preparations were statistically significant. Treatment with the least concentrated preparation that elicited significantly less contamination of the hard surfaces (i.e., 10(9) PFU/ml) also significantly reduced the number of viable E. coli O157:H7 organisms on the four food samples. The observed reductions ranged from 94% (at 120 +/- 4 h posttreatment of tomato samples) to 100% (at 24 +/- 4 h posttreatment of spinach samples). The data suggest that naturally occurring bacteriophages may be useful for reducing contamination of various hard surfaces, fruits, vegetables, and ground beef by E. coli O157:H7.

  1. Energy Spectrum of Ground State and Excitation Spectrum of Quasi-particle for Hard-Core Boson in Optical Lattices

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    We investigate the energy spectrum of ground state and quasi-particle excitation spectrum of hard-core bosons, which behave very much like spinless noninteracting fermions, in optical lattices by means of the perturbation expansion and Bogoliubov approach. The results show that the energy spectrum has a single band structure, and the energy is lower near zero momentum; the excitation spectrum gives corresponding energy gap, and the system is in Mott-insulating state at Tonks limit. The analytic result of energy spectrum is in good agreement with that calculated in terms of Green's function at strong correlation limit.

  2. 基于不同雪深的地面温度、雪(草)面温度与气温的关系%The Relationship Between Air Temperature and Ground, Snow or Grass Temperature under the Conditions of Different Snow Depth

    Institute of Scientific and Technical Information of China (English)

    王秀琴; 马玲霞; 卢新玉; 孙智娟; 王艳

    2012-01-01

    Taking samples of 451 days when snow depth is greater than or equal to 0 cm from November 2006 to March 2010 at the automatic weather stations in Tacheng, ground temperature, snow or grass surface temperature, 0 cm surface temperature, cloudiness, sunshine time and snow depth were analyzed. The results show as follow: the snow or grass surface temperature was consistent with air temperature, and it was influenced obviously by cloudiness and sunshine time, and the average snow surface temperature was lower than the average air temperature in snow season; there are two distinctions when ground temperature varied with snow depth: 20 cm and 50 cm; when snow depth was less than or equal to 20 cm, the ground temperature was greatly influenced by snow depth and air temperature, and its change trend was mainly consistent with air temperature, and the ground temperature was higher than air temperature; when snow was thinner, the ground temperature was influenced obviously by cloudiness and sunshine; when snow depth was more than 20 cm but less than 50 cm, the ground temperature was only influenced by the long time air temperature change, therefore, the ground temperature varying ranges tended to a fixed value, and it was no less than -5 ℃; when the snow depth was more than 50 cm, the ground temperature tended to the fixed value (-1 ℃).%以新疆塔城基准站自动气象站2006年11月-2010年3月积雪深度≥0cm的451d为样本,对0cm地面温度、雪面(草面)温度、气温及云量、日照时数、雪深进行统计分析,找出不同积雪深度下地面温度、雪(草)面温度与气温的关系,结果显示:雪(草)面温度在积雪期,变化趋势与气温一致,受云量及日照时数影响明显,平均雪温低于平均气温;地温随雪深变化有20cm和50cm两个分界点,雪深≤20cm时,地温受雪深、气温影响较大,变化趋势与气温基本一致,地温高于气温,雪层较薄时,受云量和

  3. Automatic monitoring of the effective thermal conductivity of snow in a low Arctic shrub tundra

    Science.gov (United States)

    Domine, F.; Barrere, M.; Sarrazin, D.; Morin, S.

    2015-03-01

    The effective thermal conductivity of snow, keff, is a critical variable which determines the temperature gradient in the snowpack and heat exchanges between the ground and the atmosphere through the snow. Its accurate knowledge is therefore required to simulate snow metamorphism, the ground thermal regime, permafrost stability, nutrient recycling and vegetation growth. Yet, few data are available on the seasonal evolution of snow thermal conductivity in the Arctic. We have deployed heated needle probes on low Arctic shrub tundra near Umiujaq, Quebec, (56°34´ N; 76°29´ W) and monitored automatically the evolution of keff for two consecutive winters, 2012-2013 and 2013-2014, at 4 heights in the snowpack. Shrubs are 20 cm high dwarf birch. Here, we develop an algorithm for the automatic determination of keff from the heating curves and obtain 404 keff values. We evaluate possible errors and biases associated with the use of the heated needles. The time-evolution of keff is very different for both winters. This is explained by comparing the meteorological conditions in both winters, which induced different conditions for snow metamorphism. In particular, important melting events the second year increased snow hardness, impeding subsequent densification and increase in thermal conductivity. Shrubs are observed to have very important impacts on snow physical evolution: (1) shrubs absorb light and facilitate snow melt under intense radiation; (2) the dense twig network of dwarf birch prevents snow compaction and therefore keff increase; (3) the low density depth hoar that forms within shrubs collapsed in late winter, leaving a void that was not filled by snow.

  4. Automatic monitoring of the effective thermal conductivity of snow in a low-Arctic shrub tundra

    Science.gov (United States)

    Domine, F.; Barrere, M.; Sarrazin, D.; Morin, S.; Arnaud, L.

    2015-06-01

    The effective thermal conductivity of snow, keff, is a critical variable which determines the temperature gradient in the snowpack and heat exchanges between the ground and the atmosphere through the snow. Its accurate knowledge is therefore required to simulate snow metamorphism, the ground thermal regime, permafrost stability, nutrient recycling and vegetation growth. Yet, few data are available on the seasonal evolution of snow thermal conductivity in the Arctic. We have deployed heated needle probes on low-Arctic shrub tundra near Umiujaq, Quebec, (N56°34'; W76°29') and monitored automatically the evolution of keff for two consecutive winters, 2012-2013 and 2013-2014, at four heights in the snowpack. Shrubs are 20 cm high dwarf birch. Here, we develop an algorithm for the automatic determination of keff from the heating curves and obtain 404 keff values. We evaluate possible errors and biases associated with the use of the heated needles. The time evolution of keff is very different for both winters. This is explained by comparing the meteorological conditions in both winters, which induced different conditions for snow metamorphism. In particular, important melting events in the second year increased snow hardness, impeding subsequent densification and increase in thermal conductivity. We conclude that shrubs have very important impacts on snow physical evolution: (1) shrubs absorb light and facilitate snow melt under intense radiation; (2) the dense twig network of dwarf birch prevent snow compaction, and therefore keff increase; (3) the low density depth hoar that forms within shrubs collapsed in late winter, leaving a void that was not filled by snow.

  5. Photogrammetric quantitative study of habitat and benthic communities of deep Cantabrian Sea hard grounds

    Science.gov (United States)

    Sánchez, F.; Serrano, A.; Ballesteros, M. Gómez

    2009-05-01

    To study the highly complex deep-sea habitats of the Cantabrian Sea and their macro-epibenthic communities a new towed underwater sled was designed to carry out quantitative visual transects based on photogrammetric analysis. The main objective of the study was undertaken to provide a first approach for gaining a better understanding of the correlation between hard substrates, depth and ecology in this region; thereby enabling researchers to determine the extent to which benthic communities depend on physical factors. The results were compared from two areas with different characteristics and methodological problems: one in the central Cantabrian Sea outer shelf (150 m depth), near the head of the Lastres Canyon, and another at the summit of the Le Danois Bank (555 m depth). Two image databases corresponding to two transects were analysed, with every photo being linked to a faunal list and a set of environmental variables. To assess the amount of variation in faunal densities related to the set of habitat environmental characteristics, a redundancy analysis (RDA) was used. The set of environmental variables comprised depth, temperature, salinity, substrate type and seafloor reflectivity. Using the hierarchical classification proposed by EUNIS, three habitats were identified from a Cantabrian Sea shelf visual transect: A4.12—Sponge communities on circalittoral rock (14.5% coverage), A5.35—Circalittoral sandy mud (56.8%) and A5.44—Circalittoral mixed sediments (28.7%). A typical community appeared on the rocky habitat, made up of yellow coral Dendrophyllia cornigera and the cup sponge Phakellia ventilabrum. On Le Danois Bank, three habitats were identified and the cnidarians ( Caryophyllia smithii and Callogorgia verticillata) and the sponges ( Asconema setubalense, Aplysilla sp., hexactinellids) characterized rocky habitats and patchy rock-sand habitats. This study provided groundtruthing for the existing surficial seafloor features and very valuable

  6. Can a snow structure model estimate snow characteristics relevant to reindeer husbandry?

    Directory of Open Access Journals (Sweden)

    Sirpa Rasmus

    2014-02-01

    Full Text Available Snow affects foraging conditions of reindeer e.g. by increasing the energy expenditures for moving and digging work or, in contrast, by making access of arboreal lichen easier. Still the studies concentrating on the role of the snow pack structure on reindeer population dynamics and reindeer management are few. We aim to find out which of the snow characteristics are relevant for reindeer in the northern boreal zone according to the experiences of reindeer herders and is this relevance seen also in reproduction rate of reindeer in this area. We also aim to validate the ability of the snow model SNOWPACK to reliably estimate the relevant snow structure characteristics. We combined meteorological observations, snow structure simulations by the model SNOWPACK and annual reports by reindeer herders during winters 1972-2010 in the Muonio reindeer herding district, northern Finland. Deep snow cover and late snow melt were the most common unfavorable conditions reported. Problematic conditions related to snow structure were icy snow and ground ice or unfrozen ground below the snow, leading to mold growth on ground vegetation. Calf production percentage was negatively correlated to the measured annual snow depth and length of the snow cover time and to the simulated snow density. Winters with icy snow could be distinguished in three out of four reported cases by SNOWPACK simulations and we could detect reliably winters with conditions favorable for mold growth. Both snow amount and also quality affects the reindeer herding and reindeer reproduction rate in northern Finland. Model SNOWPACK can relatively reliably estimate the relevant structural properties of snow. Use of snow structure models could give valuable information about grazing conditions, especially when estimating the possible effects of warming winters on reindeer populations and reindeer husbandry. Similar effects will be experienced also by other arctic and boreal species.

  7. Snow White Trenches

    Science.gov (United States)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Surface Stereo Imager on the 25th Martian day of the mission, or Sol 24 (June 19, 2008), after the May 25, 2008, landing. This image shows the trenches informally called 'Snow White 1' (left) and 'Snow White 2' (right). The trench is about 5 centimeters (2 inches) deep and 30 centimeters (12 inches) long. 'Snow White' is located in a patch of Martian soil near the center of a polygonal surface feature, nicknamed 'Cheshire Cat.' The 'dump pile' is located at the top of the trench, the side farthest away from the lander, and has been dubbed 'Croquet Ground.' The digging site has been named 'Wonderland.' This image has been enhanced to brighten shaded areas. 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.

  8. Nordic Snow Radar Experiment

    Science.gov (United States)

    Lemmetyinen, Juha; Kontu, Anna; Pulliainen, Jouni; Vehviläinen, Juho; Rautiainen, Kimmo; Wiesmann, Andreas; Mätzler, Christian; Werner, Charles; Rott, Helmut; Nagler, Thomas; Schneebeli, Martin; Proksch, Martin; Schüttemeyer, Dirk; Kern, Michael; Davidson, Malcolm W. J.

    2016-09-01

    The objective of the Nordic Snow Radar Experiment (NoSREx) campaign was to provide a continuous time series of active and passive microwave observations of snow cover at a representative location of the Arctic boreal forest area, covering a whole winter season. The activity was a part of Phase A studies for the ESA Earth Explorer 7 candidate mission CoReH2O (Cold Regions Hydrology High-resolution Observatory). The NoSREx campaign, conducted at the Finnish Meteorological Institute Arctic Research Centre (FMI-ARC) in Sodankylä, Finland, hosted a frequency scanning scatterometer operating at frequencies from X- to Ku-band. The radar observations were complemented by a microwave dual-polarization radiometer system operating from X- to W-bands. In situ measurements consisted of manual snow pit measurements at the main test site as well as extensive automated measurements on snow, ground and meteorological parameters. This study provides a summary of the obtained data, detailing measurement protocols for each microwave instrument and in situ reference data. A first analysis of the microwave signatures against snow parameters is given, also comparing observed radar backscattering and microwave emission to predictions of an active/passive forward model. All data, including the raw data observations, are available for research purposes through the European Space Agency and the Finnish Meteorological Institute. A consolidated dataset of observations, comprising the key microwave and in situ observations, is provided through the ESA campaign data portal to enable easy access to the data.

  9. Using environmental niche modeling to find suitable habitats for the Hard-ground Barasingha in Madhya Pradesh, India

    Directory of Open Access Journals (Sweden)

    C. P. Singh

    2015-09-01

    Full Text Available The subspecies of Swamp Deer, the Hard-ground Barasingha (Rucervus duvaucelii branderi Pocock, is presently found only in Kanha Tiger Reserve (KTR in Madhya Pradesh, India. This subspecies is highly vulnerable to extinction, and reintroduction in suitable sites is the need of the hour.  Environmental niche models (GARP, SVM, ED, CSM aimed at providing a detailed prediction of species distribution by relating presence of species to 19 bioclimatic indices were developed, using swamp deer occurrence records in KTR. The predictions were appropriately weighted with the prevailing LU/LC classes to identify suitable habitats in Madhya Pradesh, India. The result shows that the southern region of Madhya Pradesh is suitable for the sustenance of Barasingha with varying degrees of habitability. Vicarious validation shows that most of these forest areas were the same as that of historical records dating back to 50 years. However, land use maps can help identify areas where this subspecies can be reintroduced. 

  10. 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

  11. 积雪混合像元光谱特征观测及解混方法比较%Observations of Snow Mixed Pixel Spectral Characteristics Using a Ground-Based Spectral Radiometer and Comparing with Unmixing Algorithms

    Institute of Scientific and Technical Information of China (English)

    郝晓华; 王杰; 王建; 黄晓东; 李弘毅; 刘艳

    2012-01-01

    The unmixing algorithms of mixed snow pixels and the fractional snow cover products are an important research direc-tion for snow remote sensing. In the present study, we first designed the mixed snow pixels of different snow fraction/proportion in Northern Xinjiang, China as ground truth. Then, a SVC HR-1024 ground-based spectral radiometer was used for measuring the spectral property of this designed pixel for different snow fractions and different underlying surfaces. Finally, using the measured spectral data, the four mixed-pixel decomposition models were validated and evaluated for their performance in terms of accuracy and computational efficiency. The results showed that the reflectivity does not decline linearly with the reduction of snow ratio in the pixel, and that the unmixing accuracy inversely depends on the scales of the observation. Further, the comparison of the above mentioned unmixing algotihms showed that the linear regression method has the worst accuracy, especially when the snow proportion is less than 50%; the accuracy of sparse regression algorithm and non-negative matrix factorization were slightly higher than the full constrained linear mixed-pixel decomposition; however, full constrained linear mixed-pixel decomposition method had higher computational efficiency than the other two methods; the sparse regression algorithm has lowest computational efficiency. With unmixing remote sensing images, due to the large data volumes, we must consider the algorithms' computational efficiency. This study would promote quantitative researches on snow mixed pixel decomposition, and provide a theoretical basis for accurately extracting the snow coverage of interest area using remote sensing images.%积雪混合像元分解方法研究及积雪比例产品的发展是积雪遥感的重要研究方向.在我国北疆地区利用SVC HR-1024野外便携式光谱仪观测了已知积雪比例的混合像元光谱特征并进行系统分析,同时,采用四

  12. 'Snow Queen' Animation

    Science.gov (United States)

    2008-01-01

    This animation consists of two close-up images of 'Snow Queen,' taken several days apart, by the Robotic Arm Camera (RAC) aboard NASA's Phoenix Mars Lander. Snow Queen is the informal name for a patch of bright-toned material underneath the lander. Thruster exhaust blew away surface soil covering Snow Queen when Phoenix landed on May 25, 2008, exposing this hard layer comprising several smooth rounded cavities beneath the lander. The RAC images show how Snow Queen visibly changed between June 15, 2008, the 21st Martian day, or sol, of the mission and July 9, 2008, the 44th sol. Cracks as long as 10 centimeters (about four inches) appeared. One such crack is visible at the left third and the upper third of the Sol 44 image. A seven millimeter (one-third inch) pebble or clod appears just above and slightly to the right of the crack in the Sol 44 image. Cracks also appear in the lower part of the left third of the image. Other pieces noticeably shift, and some smooth texture has subtly roughened. The Phoenix team carefully positioned and focused RAC the same way in both images. Each image is about 60 centimeters, or about two feet, wide. The object protruding in from the top on the right half of the images is Phoenix's thermal and electrical conductivity probe. Snow Queen and other ice exposed by Phoenix landing and trenching operations on northern polar Mars is the first time scientists have been able to monitor Martian ice at a place where temperatures are cold enough that the ice doesn't immediately sublimate, or vaporize, away. 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.

  13. Snow micro-structure at Kongsvegen glacier, Svalbard

    Science.gov (United States)

    Bilgeri, F.; Karner, F.; Steinkogler, W.; Fromm, R.; Obleitner, F.; Kohler, J.

    2012-04-01

    Measurements of physical snow properties have been performed at several sites at Kongsvegen glacier, which is a key Arctic glacier in western Spitzbergen (79N, 13E). The data were collected at six locations along the flow line of the glacier at different elevations (161 to 741m asl.) and describe snow that was deposited during winter 2010/11. We basically consider the vertical profiles of snow temperature, density, hardness, grain size and crystal shapes derived from standard stratigraphic methods (snow pits)and measurements using advanced instruments like Snow Micropen® and NIR imagery. Some parameters were measured repeatedly and with different instruments which proves a high quality as well as long-term and spatial representativeness of the data. The general snow conditions at the end of winter are characterized by a linear increase of snow depth and water equivalent with elevation. Snow hardness also increases with elevation while density remains remarkably constant. At most sites the snow temperature, density, hardness and grain size increase from the surface towards the snow-ice interface. The surface and the bottom layers stand out by specific changes in snow signature (crystal types) and delineate the bulk of the snow pack which itself features a rather complex layering. Comparison of the high-resolution profiles measured at different elevations at the glacier suggests some principal correlations of the signatures of hardness, grain size and crystal type. Thus, some major features (e.g. particularly hard layers) can be traced along the glacier, but the high-resolution layering can not straightforwardly be related from one site to the other. This basically reflects a locally different history of the snow pack in terms of precipitation events and post-depositional snow metamorphism. The issue is investigated more quantitatively by enhanced statistical processing of the observed signatures and simulation of the history of individual layers. These studies are

  14. Understanding and modeling the physical processes that govern the melting of snow cover in a tropical mountain environment in Ecuador

    Science.gov (United States)

    Wagnon, P.; Lafaysse, M.; Lejeune, Y.; Maisincho, L.; Rojas, M.; Chazarin, J. P.

    2009-10-01

    The ISBA/CROCUS coupled ground-snow model developed for the Alps and subsequently adapted to the outer tropical conditions of Bolivia has been applied to a full set of meteorological data recorded at 4860 m above sea level on a moraine area in Ecuador (Antizana 15 glacier, 0°28'S; 78°09'W) between 16 June 2005 and 30 June 2006 to determine the physical processes involved in the melting and disappearance of transient snow cover in nonglaciated areas of the inner tropics. Although less accurate than in Bolivia, the model is still able to simulate snow behavior over nonglaciated natural surfaces, as long as the modeled turbulent fluxes over bare ground are reduced and a suitable function is included to represent the partitioning of the surface between bare soil and snow cover. The main difference between the two tropical sites is the wind velocity, which is more than 3 times higher at the Antizana site than at the Bolivian site, leading to a nonuniform spatial distribution of snow over nonglaciated areas that is hard to describe with a simple snow partitioning function. Net solar radiation dominates the surface energy balance and is responsible for the energy stored in snow-free areas (albedo = 0.05) and transferred horizontally to adjacent snow patches by conduction within the upper soil layers and by turbulent advection. These processes can prevent the snow cover from lasting more than a few hours or a few days. Sporadically, and at any time of the year, this inner tropical site, much wetter than the outer tropics, experiences heavy snowfalls, covering all the moraine area, and thus limiting horizontal transfers and inducing a significant time lag between precipitation events and runoff.

  15. SNOW CLEARING

    CERN Multimedia

    Groupe de Transport/Transport Group

    1999-01-01

    In order to facilitate snow-clearing operations, which commence at 4.30 every morning, drivers of CERN vehicles are kindly requested to group their cars together in the car parks. This will greatly help us in our work. Thank you for your co-operation.Transport Group / ST-HMTel. 72202

  16. 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...

  17. Snow hydrology in a general circulation model

    Science.gov (United States)

    Marshall, Susan; Roads, John O.; Glatzmaier, Gary

    1994-01-01

    A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.

  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. Brilliant Colours from a White Snow Cover

    Science.gov (United States)

    Vollmer, Michael; Shaw, Joseph A

    2013-01-01

    Surprisingly colourful views are possible from sparkling white snow. It is well known that similarly colourful features can exist in the sky whenever appropriate ice crystals are around. However, the transition of light reflection and refraction from ice crystals in the air to reflection and refraction from those in snow on the ground is not…

  20. 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

  1. Snow Radiance Assimilation Studies

    Science.gov (United States)

    Kim, E. J.; Durand, M. T.; Toure, A.; Margulis, S. A.; Goita, K.; Royer, A.; Lu, H.

    2009-12-01

    Passive microwave-based retrievals of terrestrial snow parameters from satellite observations form a 30-year global record which will continue for the forseeable future. So far, these snow retrievals have been generated primarily by regression-based empirical “inversion” methods based on snapshots in time, and are limited to footprints around 25 km in diameter. Assimilation of microwave radiances into physical land surface models may be used to create a retrieval framework that is inherently self-consistent with respect to model physics as well as a more physically-based approach vs. legacy retrieval/inversion methods. This radiance assimilation approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success, and represents one motivation for our work. A radiance assimilation scheme for snow requires a snowpack land surface model (LSM) coupled to a radiative transfer model (RTM). In previous local-scale studies, Durand, Kim, & Margulis (2008) explored the requirements on LSM model fidelity (i.e., snowpack state information) required in order for the RTM to produce brightness temperatures suitable for radiance assimilation purposes at a local scale, using the well-known Microwave Emission Model for Layered Snowpacks (MEMLS) as the RTM and a combination of Simple SIB (SSiB) and Snow Atmosphere (SAST) as the LSM. They also demonstrated improvement of simulated snow depth through the use of an ensemble Kalman filter scheme at this local scale (2009). This modeling framework reflects another motivation—namely, possibilities for downscaling. Our focus at this stage has been at the local scale where high-quality ground truth data is available in order to evaluate radiance assimilation under a “best case scenario.” The quantitative results then form a benchmark for future assessment of effects such as sparse forcing data, upscaling/downscaling, forest attenuation, and model details. Field data from

  2. MELIFT - A new device for accurate measurements in a snow rich environment

    Science.gov (United States)

    Dorninger, M.

    2012-04-01

    A deep snow pack, remote locations, no external power supply and very low temperatures are often the main ingredients when it comes to the deployment of meteorological stations in mountainous terrain. The accurate position of the sensor related to the snow surface is normally not known. A new device called METLIFT overcomes the problems. WMO recommends a height between 1.2 m and 2 m above ground level for the measurement of air temperature and humidity. The height above ground level is specified to take care of the possible strong vertical temperature and humidity gradients at the lowest layers in the atmosphere. Especially in snow rich and remote locations it may be hardly possible to follow this advice. Therefore most of the meteorological stations in mountainous terrain are situated at mountain tops where strong winds will blow off the snow or in valleys where a daily inspection of the sensors is possible. In other unpopulated mountainous areas, e.g. basins, plateaus, the distance of the sensor to the snow surface is not known or the sensor will be snow-covered. A new device was developed to guarantee the sensor height above surface within the WMO limits in harsh and remote environments. An ultrasonic snow height sensor measures the distance to the snow surface. If it exceeds certain limits due to snow accumulation or snow melt the lift adapts its height accordingly. The prototype of METLIFT has been installed in Lower Austria at an altitude of 1000m. The lift is 6 m high and can pull out for another 4 m. Sensor arms are mounted every meter to allow the connection of additional sensors or to measure a profile of a certain parameter of the lowest 5 m above surface. Sensors can be added easily since cable wiring is provided to each sensor arm. Horizontal winds are measured at 7 m height above surface. METLIFT is independent of external power supply. Three lead gel accumulators recharged by three solar panels provide the energy necessary for the sensors, the data

  3. Snow water equivalent mapping in Norway

    Science.gov (United States)

    Tveito, O. E.; Udnæs, H.-C.; Engeset, R.; Førland, E. J.; Isaksen, K.; Mengistu, Z.

    2003-04-01

    In high latitude area snow covers the ground large parts of the year. Information about the water volume as snow is of major importance in many respects. Flood forecasters at NVE need it in order to assess possible flood risks. Hydropower producers need it to plan the most efficient production of the water in their reservoirs, traders to estimate the potential energy available for the market. Meteorologists on their side use the information as boundary conditions in weather forecasting models. The Norwegian meteorological institute has provided snow accumulation maps for Norway for more than 50 years. These maps are now produced twice a month in the winter season. They show the accumulated precipitation in the winter season from the day the permanent snow cover is established. They do however not take melting into account, and do therefore not give a good description of the actual snow amounts during and after periods with snowmelt. Due to an increased need for a direct measure of water volumes as snow cover, met.no and NVE initialized a joint project in order to establish maps of the actual snow cover expressed in water equivalents. The project utilizes recent developments in the use of GIS in spatial modeling. Daily precipitation and temperature are distributed in space by using objective spatial interpolation methods. The interpolation considers topographical and other geographical parameters as well as weather type information. A degree-day model is used at each modeling point to calculate snow-accumulation and snowmelt. The maps represent a spatial scale of 1x1 km2. The modeled snow reservoir is validated by snow pillow values as well traditional snow depth observations. Preliminary results show that the new snow modeling approach reproduces the snow water equivalent well. The spatial approach also opens for a wide use in the terms of areal analysis.

  4. Seeing the Snow through the Trees: Towards a Validated Canopy Adjustment for Fractional Snow Covered Area

    Science.gov (United States)

    Coons, L.; Nolin, A. W.; Painter, T.

    2012-12-01

    Satellite remote sensing is an important tool for monitoring the spatial distribution of snow cover, which acts as a vital reservoir of water for human and ecosystem needs. Current methods exist mapping the fraction of snow in each image pixel from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper (TM). Although these methods can effectively detect this fractional snow-covered area (fSCA) in open areas, snow cover is underestimated in forested areas where canopy cover obscures the snow. Accounting for obscured snow cover will significantly improve estimates of fSCA for hydrologic forecasting and monitoring. This study will address how individual trees and the overall forest canopy affect snow distributions on the ground with the goal of determining metrics that can parameterize the spatial patterns of sub-canopy snow cover. Snow cover measurements were made during winter 2011-2012 at multiple sites representing a range of canopy densities. In the snow-free season, we used terrestrial laser scanning (TLS) and manual field methods to fully characterize the forest canopy height, canopy gap fraction, crown width, tree diameter at breast height (DBH), and stand density. We also use multi-angle satellite imagery from MISR and airborne photos to map canopy characteristics over larger areas. Certain canopy structure characteristics can be represented with remote sensing data. These data serve as a key first step in developing canopy adjustment factors for fSCA from MODIS, TM, and other snow mapping sensors.

  5. Soot on snow experiment: bidirectional reflectance factor measurements of contaminated snow

    Directory of Open Access Journals (Sweden)

    J. I. Peltoniemi

    2015-06-01

    Full Text Available In order to quantify the effects of absorbing contaminants on snow, a series of spectral reflectance measurements were conducted. Chimney soot, volcanic sand, and glaciogenic silt were deposited on a natural snow surface in a controlled way as a part of the Soot on Snow (SoS campaign. The bidirectional reflectance factors of these soiled surfaces and untouched snow were measured using the Finnish Geodetic Institute's Field Goniospectropolariradiometer, FIGIFIGO. A remarkable feature is the fact that the absorbing contaminants on snow enhanced in our experiments the metamorphosis of snow under strong sunlight. Immediately after deposition, the contaminated snow surface appeared darker than the pure snow in all viewing directions, but the absorbing particles sank deep into the snow in minutes. The nadir measurement remained the darkest, but at larger zenith angles the surface of the contaminated snow changed back to almost as white as clean snow. Thus, for a ground observer the darkening caused by impurities can be completely invisible, overestimating the albedo, but a nadir observing satellite sees the darkest points, now underestimating the albedo. By a reciprocity argument, we predict, that at noon the albedo should be lower than in the morning or afternoon. When sunlight stimulates sinking more than melting, the albedo should be higher in the afternoon than in the morning, and vice versa when melting dominates. However, differences in the hydrophobic properties, porosity, clumping, or size of the impurities may cause different results than observed in these measurements.

  6. Soot on Snow experiment: bidirectional reflectance factor measurements of contaminated snow

    Science.gov (United States)

    Peltoniemi, J. I.; Gritsevich, M.; Hakala, T.; Dagsson-Waldhauserová, P.; Arnalds, Ó.; Anttila, K.; Hannula, H.-R.; Kivekäs, N.; Lihavainen, H.; Meinander, O.; Svensson, J.; Virkkula, A.; de Leeuw, G.

    2015-12-01

    In order to quantify the effects of absorbing contaminants on snow, a series of spectral reflectance measurements were conducted. Chimney soot, volcanic sand, and glaciogenic silt were deposited on a natural snow surface in a controlled way as a part of the Soot on Snow (SoS) campaign. The bidirectional reflectance factors of these soiled surfaces and untouched snow were measured using the Finnish Geodetic Institute's Field Goniospectropolariradiometer, FIGIFIGO. A remarkable feature is the fact that the absorbing contaminants on snow enhanced the metamorphism of snow under strong sunlight in our experiments. Immediately after deposition, the contaminated snow surface appeared darker than the natural snow in all viewing directions, but the absorbing particles sank deep into the snow in minutes. The nadir measurement remained the darkest, but at larger zenith angles, the surface of the contaminated snow changed back to almost as white as clean snow. Thus, for a ground observer the darkening caused by impurities can be completely invisible, overestimating the albedo, but a nadir-observing satellite sees the darkest points, underestimating the albedo. Through a reciprocity argument, we predict that at noon, the albedo perturbation should be lower than in the morning or afternoon. When sunlight stimulates sinking more than melting, the albedo should be higher in the afternoon than in the morning, and vice versa when melting dominates. However, differences in the hydrophobic properties, porosity, clumping, or size of the impurities may cause different results than observed in these measurements.

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

    Science.gov (United States)

    Meng, Chunlei

    2016-10-01

    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.

  8. Variation of snow water resources in northwestern China,1951—1997

    Institute of Scientific and Technical Information of China (English)

    李培基

    1999-01-01

    An observation study is carried out on snow mass amount estimate in northwestern China by using microwave derived snow depth charts employing data from SMMR in conjunction with daily snow depth, density and snow cover duration records for 46 ground climate stations. Spatial patterns, seasonal cycle, and interannual variation of snow cover are discussed. Results show that snow cover is the second largest water supply over the arid northwestern China,and unlike most other areas in the world, northwestern China did not experience any decrease in snow cover since 1987.Secular trends reveal systematic increase in snow mass and durations. Analysis of snow cover-climate relationship indicates that gradual increase in snow cover is primarily in response to increase in snow season precipitation.

  9. Integrating geospatial and ground geophysical information as guidelines for groundwater potential zones in hard rock terrains of south India.

    Science.gov (United States)

    Rashid, Mehnaz; Lone, Mahjoor Ahmad; Ahmed, Shakeel

    2012-08-01

    The increasing demand of water has brought tremendous pressure on groundwater resources in the regions were groundwater is prime source of water. The objective of this study was to explore groundwater potential zones in Maheshwaram watershed of Andhra Pradesh, India with semi-arid climatic condition and hard rock granitic terrain. GIS-based modelling was used to integrate remote sensing and geophysical data to delineate groundwater potential zones. In the present study, Indian Remote Sensing RESOURCESAT-1, Linear Imaging Self-Scanner (LISS-4) digital data, ASTER digital elevation model and vertical electrical sounding data along with other data sets were analysed to generate various thematic maps, viz., geomorphology, land use/land cover, geology, lineament density, soil, drainage density, slope, aquifer resistivity and aquifer thickness. Based on this integrated approach, the groundwater availability in the watershed was classified into four categories, viz. very good, good, moderate and poor. The results reveal that the modelling assessment method proposed in this study is an effective tool for deciphering groundwater potential zones for proper planning and management of groundwater resources in diverse hydrogeological terrains.

  10. 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...

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

    Science.gov (United States)

    Dai, Liyun; Che, Tao; Ding, Yongjian; Hao, Xiaohua

    2017-08-01

    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 depth across the QTP, new algorithms

  12. 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

  13. Polarized hard X-ray photoemission system with micro-positioning technique for probing ground-state symmetry of strongly correlated materials.

    Science.gov (United States)

    Fujiwara, Hidenori; Naimen, Sho; Higashiya, Atsushi; Kanai, Yuina; Yomosa, Hiroshi; Yamagami, Kohei; Kiss, Takayuki; Kadono, Toshiharu; Imada, Shin; Yamasaki, Atsushi; Takase, Kouichi; Otsuka, Shintaro; Shimizu, Tomohiro; Shingubara, Shoso; Suga, Shigemasa; Yabashi, Makina; Tamasaku, Kenji; Ishikawa, Tetsuya; Sekiyama, Akira

    2016-05-01

    An angle-resolved linearly polarized hard X-ray photoemission spectroscopy (HAXPES) system has been developed to study the ground-state symmetry of strongly correlated materials. The linear polarization of the incoming X-ray beam is switched by a transmission-type phase retarder composed of two diamond (100) crystals. The best value of the degree of linear polarization was found to be -0.96, containing a vertical polarization component of 98%. A newly developed low-temperature two-axis manipulator enables easy polar and azimuthal rotations to select the detection direction of photoelectrons. The lowest temperature achieved was 9 K, offering the chance to access the ground state even for strongly correlated electron systems in cubic symmetry. A co-axial sample monitoring system with long-working-distance microscope enables the same region on the sample surface to be measured before and after rotation. Combining this sample monitoring system with a micro-focused X-ray beam by means of an ellipsoidal Kirkpatrick-Baez mirror (25 µm × 25 µm FWHM), polarized valence-band HAXPES has been performed on NiO for voltage application as resistive random access memory to demonstrate the micro-positioning technique and polarization switching.

  14. 2D ground motion at a soft viscoelastic layer/hard substratum site in response to SH cylindrical seismic waves radiated by deep and shallow line sources

    CERN Document Server

    Wirgin, A; Wirgin, Armand

    2004-01-01

    We show, essentially by theoretical means, that for a site with the chosen simple geometry and mechanical properties (horizontal, homogeneous, soft viscoelastic layer of infinite lateral extent overlying, and in welded contact with, a homogeneous, hard elastic substratum of half-infinite radial extent, shear-horizontal motion): 1) coupling to Love modes is all the weaker the farther the seismic source (modeled as a line, assumed to lie in the substratum) is from the lower boundary of the soft layer, 2) for a line source close to the lower boundary of the soft layer, the ground response is characterized by possible beating phenomena, and is of significantly-longer duration than for excitation by cylindrical waves radiated by deep sources. Numerical applications of the theory show, for instance, that a line source, located 40m below the lower boundary of a 60m thick soft layer in a hypothetical Mexico City-like site, radiating a SH pulse of 4s duration, produces substantial ground motion during 200s, with marke...

  15. Assimilation of AMSR-E snow water equivalent data in a spatially-lumped snow model

    Science.gov (United States)

    Dziubanski, David J.; Franz, Kristie J.

    2016-09-01

    Accurately initializing snow model states in hydrologic prediction models is important for estimating future snowmelt, water supplies, and flooding potential. While ground-based snow observations give the most reliable information about snowpack conditions, they are spatially limited. In the north-central USA, there are no continual observations of hydrologically critical snow variables. Satellites offer the most likely source of spatial snow data, such as the snow water equivalent (SWE), for this region. In this study, we test the impact of assimilating SWE data from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument into the US National Weather Service (NWS) SNOW17 model for seven watersheds in the Upper Mississippi River basin. The SNOW17 is coupled with the NWS Sacramento Soil Moisture Accounting (SACSMA) model, and both simulated SWE and discharge are evaluated. The ensemble Kalman filter (EnKF) assimilation framework is applied and updating occurs on a daily cycle for water years 2006-2011. Prior to assimilation, AMSR-E data is bias corrected using data from the National Operational Hydrologic Remote Sensing Center (NOHRSC) airborne snow survey program. An average AMSR-E SWE bias of -17.91 mm was found for the study basins. SNOW17 and SAC-SMA model parameters from the North Central River Forecast Center (NCRFC) are used. Compared to a baseline run without assimilation, the SWE assimilation improved discharge for five of the seven study sites, in particular for high discharge magnitudes associated with snow melt runoff. SWE and discharge simulations suggest that the SNOW17 is underestimating SWE and snowmelt rates in the study basins. Deep snow conditions and periods of snowmelt may have introduced error into the assimilation due to difficulty obtaining accurate brightness temperatures under these conditions. Overall results indicate that the AMSR-E data and EnKF are viable and effective solutions for improving simulations

  16. 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.

  17. Hard probes 2006 Asilomar

    CERN Multimedia

    2006-01-01

    "The second international conference on hard and electromagnetic probes of high-energy nuclear collisions was held June 9 to 16, 2006 at the Asilomar Conference grounds in Pacific Grove, California" (photo and 1/2 page)

  18. Georadar Measurements for the Snow Cover Density

    Directory of Open Access Journals (Sweden)

    A. Godio

    2009-01-01

    Full Text Available Ground Probing Radar (GPR devices is adopted for the analysis of thickness and the mechanical properties (density of the snow cover in some test site in Alps, in Northern Italy. The performances of standard radar systems for the snow cover characterisation are analysed, the main aim is to assess the reliability of the method to estimate the snow density, the snowpack thickness and the depth resolution in terms of capability to detect thin layers. The main relationships between the electrical permittivity and the density of the dry-snow are applied to estimate the density vertical profiles inferred by the GPR investigation. The data were calibrated and compared with the results coming from direct measurements of the density and thickness.

  19. Finland Validation of the New Blended Snow Product

    Science.gov (United States)

    Kim, E. J.; Casey, K. A.; Hallikainen, M. T.; Foster, J. L.; Hall, D. K.; Riggs, G. A.

    2008-01-01

    As part of an ongoing effort to validate satellite remote sensing snow products for the recentlydeveloped U.S. Air Force Weather Agency (AFWA) - NASA blended snow product, Satellite and in-situ data for snow extent and snow water equivalent (SWE) are evaluated in Finland for the 2006-2007 snow season Finnish Meteorological Institute (FMI) daily weather station data and Finnish Environment Institute (SYKE) bi-monthly snow course data are used as ground truth. Initial comparison results display positive agreement between the AFWA NASA Snow Algorithm (ANSA) snow extent and SWE maps and in situ data, with discrepancies in accordance with known AMSR-E and MODIS snow mapping limitations. Future ANSA product improvement plans include additional validation and inclusion of fractional snow cover in the ANSA data product. Furthermore, the AMSR-E 19 GHz (horizontal channel) with the difference between ascending and descending satellite passes (Diurnal Amplitude Variations, DAV) will be used to detect the onset of melt, and QuikSCAT scatterometer data (14 GHz) will be used to map areas of actively melting snow.

  20. 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.

  1. 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.

  2. Quantification of uncertainties in snow accumulation, snowmelt, and snow disappearance dates

    Science.gov (United States)

    Raleigh, Mark S.

    Seasonal mountain snowpack holds hydrologic and ecologic significance worldwide. However, observation networks in complex terrain are typically sparse and provide minimal information about prevailing conditions. Snow patterns and processes in this data sparse environment can be characterized with numerical models and satellite-based remote sensing, and thus it is essential to understand their reliability. This research quantifies model and remote sensing uncertainties in snow accumulation, snowmelt, and snow disappearance as revealed through comparisons with unique ground-based measurements. The relationship between snow accumulation uncertainty and model configuration is assessed through a controlled experiment at 154 snow pillow sites in the western United States. To simulate snow water equivalent (SWE), the National Weather Service SNOW-17 model is tested as (1) a traditional "forward" model based primarily on precipitation, (2) a reconstruction model based on total snowmelt before the snow disappearance date, and (3) a combination of (1) and (2). For peak SWE estimation, the reliability of the parent models was indistinguishable, while the combined model was most reliable. A sensitivity analysis demonstrated that the parent models had opposite sensitivities to temperature that tended to cancel in the combined model. Uncertainty in model forcing and parameters significantly controlled model accuracy. Uncertainty in remotely sensed snow cover and snow disappearance in forested areas is enhanced by canopy obstruction but has been ill-quantified due to the lack of sub-canopy observations. To better quantify this uncertainty, dense networks of near-surface temperature sensors were installed at four study areas (≤ 1 km2) with varying forest cover in the Sierra Nevada, California. Snow presence at each sensor was detected during periods when temperature was damped, which resulted from snow cover insulation. This methodology was verified using time-lapse analysis and

  3. Hard electronics; Hard electronics

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    Hard material technologies were surveyed to establish the hard electronic technology which offers superior characteristics under hard operational or environmental conditions as compared with conventional Si devices. The following technologies were separately surveyed: (1) The device and integration technologies of wide gap hard semiconductors such as SiC, diamond and nitride, (2) The technology of hard semiconductor devices for vacuum micro- electronics technology, and (3) The technology of hard new material devices for oxides. The formation technology of oxide thin films made remarkable progress after discovery of oxide superconductor materials, resulting in development of an atomic layer growth method and mist deposition method. This leading research is expected to solve such issues difficult to be easily realized by current Si technology as high-power, high-frequency and low-loss devices in power electronics, high temperature-proof and radiation-proof devices in ultimate electronics, and high-speed and dense- integrated devices in information electronics. 432 refs., 136 figs., 15 tabs.

  4. Experiment Research on Freeze-thaw Splitting of Asphalt Concrete of Deicing and Snow Melting Based on Ground-Source Heat Pump%地源热泵融雪化冰沥青混凝土冻融劈裂实验研究

    Institute of Scientific and Technical Information of China (English)

    杨豪; 屠艳平; 朱志刚

    2016-01-01

    The technology of deicing and snow melting based on ground-source heat pump has many advantages, but some scholars pointed out that water damage was intensified because of deicing and snow melting. An experimental program was designed to estimate the degree of water damage of deicing and snow melting based on ground-source heat pump. The tensile splitting strength based on ground-source heat pump is 0.72MPa,but the tensile splitting strength of based on test procedures is 0.68MPa. The results showed that deicing and snow melting technology based on ground-source heat pump not only will increase the water damage of asphalt pavement, but also will improve the capability of resistance to water.%地源热泵融雪化冰技术具有许多优越性,有的学者指出道路融雪化冰会导致沥青路面水损害加剧。通过设计一套试验方案来评价利用地热源泵融雪化冰后路面的水损坏程度。地源热泵加热融化的试件的劈裂抗拉强度为0.72MPa,而根据试验规程测得的劈裂抗拉强度为0.68M孕a,结果表明地源热泵融雪化冰技术不仅不会增加沥青路面的水损害,还会提高路面抗水损害性能。

  5. 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

    detailed physical snowpack model driven by meteorology from ERA-Interim. The model-based SWE datasets were available for the years 1980-2010. The GlobSnow SWE data are available for 1979-2014 and the NASA SWE for 2002-2011. The intercomparison presented here was carried out by using ground-based snow course observations from the former Soviet Union and Russia and Finland as ground truth reference. For the first time an independent assessment has been carried out for the existing satellite- and model-based datasets in a coordinated fashion. The detailed results will be presented at the conference.

  6. Snow Roads and Runways

    Science.gov (United States)

    1990-11-01

    CONSTRUCT ROADS FOR MARCHING COLUMNS ALL ARMS (1) Pass over the trace twice with (1) Two passes with the harrow the harrow. and roller. (2) After harrowing...should be accomplished by successive passes with beams or slabs to the towing bars. A method forballasting D-7 orD-8 tractortracks. Normally twoto five... waffle -type snow surface (Fig. 85)and is notas suitable for snow pavement surface has been previously compacted snow compaction as other types of rollers

  7. Phase-field modeling of dry snow metamorphism.

    Science.gov (United States)

    Kaempfer, Thomas U; Plapp, Mathis

    2009-03-01

    Snow on the ground is a complex three-dimensional porous medium consisting of an ice matrix formed by sintered snow crystals and a pore space filled with air and water vapor. If a temperature gradient is imposed on the snow, a water vapor gradient in the pore space is induced and the snow microstructure changes due to diffusion, sublimation, and resublimation: the snow metamorphoses. The snow microstructure, in turn, determines macroscopic snow properties such as the thermal conductivity of a snowpack. We develop a phase-field model for snow metamorphism that operates on natural snow microstructures as observed by computed x-ray microtomography. The model takes into account heat and mass diffusion within the ice matrix and pore space, as well as phase changes at the ice-air interfaces. Its construction is inspired by phase-field models for alloy solidification, which allows us to relate the phase-field to a sharp-interface formulation of the problem without performing formal matched asymptotics. To overcome the computational difficulties created by the large difference between diffusional and interface-migration time scales, we introduce a method for accelerating the numerical simulations that formally amounts to reducing the heat- and mass-diffusion coefficients while maintaining the correct interface velocities. The model is validated by simulations for simple one- and two-dimensional test cases. Furthermore, we perform qualitative metamorphism simulations on natural snow structures to demonstrate the potential of the approach.

  8. Snow molds: A group of fungi that prevail under snow.

    Science.gov (United States)

    Matsumoto, Naoyuki

    2009-01-01

    Snow molds are a group of fungi that attack dormant plants under snow. In this paper, their survival strategies are illustrated with regard to adaptation to the unique environment under snow. Snow molds consist of diverse taxonomic groups and are divided into obligate and facultative fungi. Obligate snow molds exclusively prevail during winter with or without snow, whereas facultative snow molds can thrive even in the growing season of plants. Snow molds grow at low temperatures in habitats where antagonists are practically absent, and host plants deteriorate due to inhibited photosynthesis under snow. These features characterize snow molds as opportunistic parasites. The environment under snow represents a habitat where resources available are limited. There are two contrasting strategies for resource utilization, i.e., individualisms and collectivism. Freeze tolerance is also critical for them to survive freezing temperatures, and several mechanisms are illustrated. Finally, strategies to cope with annual fluctuations in snow cover are discussed in terms of predictability of the habitat.

  9. A snow cover climatology for the Pyrenees from MODIS snow products

    Science.gov (United States)

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

    2015-05-01

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

  10. Evaluation of North Eurasian snow-off dates in the ECHAM5.4 atmospheric GCM

    Directory of Open Access Journals (Sweden)

    P. Räisänen

    2014-06-01

    Ts from rising above 0 °C before all snow has vanished. Consequently, too much (too little of the surface net radiation is consumed in melting snow (heating the air. On the other hand, ECHAM5 does not include a canopy layer. Thus, while the albedo reduction due to canopy is accounted for, the shielding of snow on ground by the overlying canopy is not considered, which leaves too much solar radiation available for melting snow.

  11. Digging of 'Snow White' Begins

    Science.gov (United States)

    2008-01-01

    NASA's Phoenix Mars Lander began excavating a new trench, dubbed 'Snow White,' in a patch of Martian soil located near the center of a polygonal surface feature, nicknamed 'Cheshire Cat.' The trench is about 2 centimeters (.8 inches) deep and 30 centimeters (about 12 inches) long. The 'dump pile' is located at the top of the trench, the side farthest away from the lander, and has been dubbed 'Croquet Ground.' The digging site has been named 'Wonderland.' At this early stage of digging, the Phoenix team did not expect to find any of the white material seen in the first trench, now called 'Dodo-Goldilocks.' That trench showed white material at a depth of about 5 centimeters (2 inches). More digging of Snow White is planned for coming sols, or Martian days. The dark portion of this image is the shadow of the lander's solar panel; the bright areas within this region are not in shadow. Snow White was dug on Sol 22 (June 17, 2008) with Phoenix's Robotic Arm. This picture was acquired on the same day by the lander's Surface Stereo Imager. This image has been enhanced to brighten shaded areas. 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.

  12. Hard electronics; Hard electronics

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    In the fields of power conversion devices and broadcasting/communication amplifiers, high power, high frequency and low losses are desirable. Further, for electronic elements in aerospace/aeronautical/geothermal surveys, etc., heat resistance to 500degC is required. Devices which respond to such hard specifications are called hard electronic devices. However, with Si which is at the core of the present electronics, the specifications cannot fully be fulfilled because of the restrictions arising from physical values. Accordingly, taking up new device materials/structures necessary to construct hard electronics, technologies to develop these to a level of IC were examined and studied. They are a technology to make devices/IC of new semiconductors such as SiC, diamond, etc. which can handle higher temperature, higher power and higher frequency than Si and also is possible of reducing losses, a technology to make devices of hard semiconducter materials such as a vacuum microelectronics technology using ultra-micro/high-luminance electronic emitter using negative electron affinity which diamond, etc. have, a technology to make devices of oxides which have various electric properties, etc. 321 refs., 194 figs., 8 tabs.

  13. 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.

  14. 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...

  15. 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

  16. Overview of SnowEx Year 1 Activities

    Science.gov (United States)

    Kim, Edward; Gatebe, Charles; Hall, Dorothy; Newlin, Jerry; Misakonis, Amy; Elder, Kelly; Marshall, Hans Peter; Heimstra, Chris; Brucker, Ludovic; De Marco, Eugenia; hide

    2017-01-01

    SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earths terrestrial snow-covered regions? Year 1 (2016-17) focused on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site was Grand Mesa and the secondary site was the Senator Beck Basin, both in western, Colorado, USA. Nine sensors on five aircraft made observations using a broad range of sensing techniques, active and passive microwave, and active and passive optical infrared to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also included an extensive range of ground truth measurements in-situ manual samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some preliminary results will be presented.

  17. Snow Depth Retrieval with UAS Using Photogrammetric Techniques

    Directory of Open Access Journals (Sweden)

    Benjamin Vander Jagt

    2015-07-01

    Full Text Available Alpine areas pose challenges for many existing remote sensing methods for snow depth retrieval, thus leading to uncertainty in water forecasting and budgeting. Herein, we present the results of a field campaign conducted in Tasmania, Australia in 2013 from which estimates of snow depth were derived using a low-cost photogrammetric approach on-board a micro unmanned aircraft system (UAS. Using commercial off-the-shelf (COTS sensors mounted on a multi-rotor UAS and photogrammetric image processing techniques, the results demonstrate that snow depth can be accurately retrieved by differencing two surface models corresponding to the snow-free and snow-covered scenes, respectively. In addition to accurate snow depth retrieval, we show that high-resolution (50 cm spatially continuous snow depth maps can be created using this methodology. Two types of photogrammetric bundle adjustment (BA routines are implemented in this study to determine the optimal estimates of sensor position and orientation, in addition to 3D scene information; conventional BA (which relies on measured ground control points and direct BA (which does not require ground control points. Error sources that affect the accuracy of the BA and subsequent snow depth reconstruction are discussed. The results indicate the UAS is capable of providing high-resolution and high-accuracy (<10 cm estimates of snow depth over a small alpine area (~0.7 ha with significant snow accumulation (depths greater than one meter at a fraction of the cost of full-size aerial survey approaches. The RMSE of estimated snow depths using the conventional BA approach is 9.6 cm, whereas the direct BA is characterized by larger error, with an RMSE of 18.4 cm. If a simple affine transformation is applied to the point cloud derived from the direct BA, the overall RMSE is reduced to 8.8 cm RMSE.

  18. Learn Mac OS X Snow Leopard

    CERN Document Server

    Meyers, Scott

    2009-01-01

    You're smart and savvy, but also busy. This comprehensive guide to Apple's Mac OS X 10.6, Snow Leopard, gives you everything you need to know to live a happy, productive Mac life. Learn Mac OS X Snow Leopard will have you up and connected lickity split. With a minimum of overhead and a maximum of useful information, you'll cover a lot of ground in the time it takes other books to get you plugged in. If this isn't your first experience with Mac OS X, skip right to the "What's New in Snow Leopard" sections. You may also find yourself using this book as a quick refresher course or a way

  19. 'Snow White' Trench After Scraping

    Science.gov (United States)

    2008-01-01

    This view from the Surface Stereo Imager on NASA's Phoenix Mars Lander shows the trench informally named 'Snow White.' This image was taken after a series of scrapings by the lander's Robotic Arm on the 58th Martian day, or sol, of the mission (July 23, 2008). The scrapings were done in preparation for collecting a sample for analysis from a hard subsurface layer where soil may contain frozen water. The trench is 4 to 5 centimeters (about 2 inches) deep, about 23 centimeters (9 inches) wide and about 60 centimeters (24 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.

  20. Snow water content estimation from measured snow temperature

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The vertical temperature profiles of snow and sea ice have been measured in the Arctic during the 2nd Chinese National Arctic Research Expedition in 2003 (CHINARE2003). The high-resolution temperature profile in snow is solved by one-dimensional heat transfer equation. The effective heat diffusivity, internal heat sources are identified. The internal heat source refers to the penetrated solar radiation which usually warms the lower part of the snow layer in summer. By temperature gradient analysis, the zero level can be clarified quantitatively as the boundary of the dry and wet snow. According to the in situ time series of vertical temperature profile, the time series of water content in snow is obtained based on an evaluation method of snow water content associated with the snow and ice physical parameters. The relationship of snow water content and snow temperature and temporal-spatial distribution of snow water content are presented

  1. Responses of Snow Depth and Seasonal Frozen Ground Temperature to Enhanced Air Temperature in Kunges Valley, Tianshan Mountains%天山巩乃斯河谷积雪深度及季节冻土温度对气温变化的响应

    Institute of Scientific and Technical Information of China (English)

    郭玲鹏; 李兰海; 徐俊荣; 包安明

    2012-01-01

    Climate change is influencing the temporal and spatial variation of snow cover and the hydro-thermal variation of seasonal frozen ground. And both seasonal snow cover and frozen ground significantly affect the streamflow in spring and its annual distribution. In order to analyze the effects of snow cover and air temperature on the thermal regime of seasonal frozen ground, an air temperature enhancement experiment was performed at the Tianshan Station for Snow-cover and Avalanche Research with a temperature enhancement system based on the principle of Temperature Free-Air Controlled Enhancement(TFACE). The field experiment was conducted under three treatments: natural condition, temperature-enhanced treatment I (enhanced by approximately 2 ℃ ) and temperature-enhanced treatment II (enhanced by approximately 4 ℃ ). It began on March 13 and ended on April 15. The results indicate that the air temperature enhancement has greater impact on snow cover than on the seasonal frozen ground. With an initial snow depth of 128cm, snow-melting under the temperature-enhanced treatment I and treatment II are 19 days and 25 days respectively earlier than that under natural condition. Air temperature, maximum snow depth and its date are the key factors that influence the seasonal frozen ground temperature during the snow-melting season. Soil thaws from the bottom to the top soil layer under the condition of snow covering. Because of the disappearance of snow cover, the soil receives solar radiation directly and its temperature rises rapidly, which results in the advanced thaw of frozen soil under temperature-enhanced treatment I and treatment II. Besides, it thaws from surface to the bottom. When the snow depth is more than 100cm, the heat exchange on snow-earth interface is more or less balanced and the loss of soil heat flux is minimum. Snowmelt has cooling effect on soil temperature, especially the deep unfrozen soil layer. As the air temperature enhancement

  2. Retrieving dry snow density with SIR-C polarimetric SAR data

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    For a given incidence angle at the snow surface, a greater snow density causes a greater change in the inci- dence angle at the snow-ground interface; for a given snow density, however, a larger incidence angle at the snow surface results in a greater change in the refractive angle in the snow layer, by comparing the difference of incidence angle at the snow-ground interface and the air-snow interface with dif- ferent snow density. Algorithm for estimating dry snow den- sity used backscattering measurements with polarimetric SAR at L-band frequency is developed based on simulation of the surface backscattering components s ghh and s gvv using the IEM model and regression analysis. The comparison of the estimated snow density from SAR L-band images with that from field measurements during the SIR-C/X-SAR overpass shows root means square error of 0.050 g/cm3. It shows that this algorithm can be accurately used to estimate dry snow density distribution.

  3. Spatial Patterns of Snow Cover in North Carolina: Surface and Satellite Perspectives

    Science.gov (United States)

    Fuhrmann, Christopher M.; Hall, Dorothy K.; Perry, L. Baker; Riggs, George A.

    2010-01-01

    Snow mapping is a common practice in regions that receive large amounts of snowfall annually, have seasonally-continuous snow cover, and where snowmelt contributes significantly to the hydrologic cycle. Although higher elevations in the southern Appalachian Mountains average upwards of 100 inches of snow annually, much of the remainder of the Southeast U.S. receives comparatively little snowfall (snow cover and the physical processes that act to limit or improve its detection across the Southeast. In the present work, both in situ and remote sensing data are utilized to assess the spatial distribution of snow cover for a sample of recent snowfall events in North Carolina. Specifically, this work seeks to determine how well ground measurements characterize the fine-grained patterns of snow cover in relation to Moderate- Resolution Imaging Spectroradiometer (MODIS) snow cover products (in this case, the MODIS Fractional Snow Cover product).

  4. 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

  5. Hardness and excitation energy

    Indian Academy of Sciences (India)

    Á Nagy

    2005-09-01

    The concept of the ensemble Kohn-Sham hardness is introduced. It is shown that the first excitation energy can be given by the Kohn-Sham hardness (i.e. the energy difference of the ground-state lowest unoccupied and highest occupied levels) plus an extra term coming from the partial derivative of the ensemble exchange-correlation energy with respect to the weighting factor in the limit → 0. It is proposed that the first excitation energy can be used as a reactivity index instead of the hardness.

  6. 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

  7. A snow cover climatology for the Pyrenees from MODIS snow products

    Directory of Open Access Journals (Sweden)

    S. Gascoin

    2015-05-01

    a MODIS pixel. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85 for MOD10A1 and 96% (κ = 0.81 for MYD10A1, which indicates a good agreement between both data sets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decrease over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67. We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gap-filling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band and aspect classes. There is snow on the ground at least 50% of the time above 1600 m between December and April. We finally analyze the snow patterns for the atypical winter 2011–2012. Snow cover duration anomalies reveal a deficient snowpack on the Spanish side of the Pyrenees, which seems to have caused a drop in the national hydropower production.

  8. 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.

  9. 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.

  10. 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.

  11. John Snow and research.

    Science.gov (United States)

    Shephard, D A

    1989-03-01

    John Snow's leadership in epidemiology as well as anaesthesia resulted from his research as much as his clinical practice. In anaesthesia, Snow's research concerned the regulation of concentrations of volatile agents and the development of efficient inhalers; the uptake and elimination of volatile agents; stages of anaesthesia; carbon dioxide metabolism and rebreathing; and metabolism in anaesthesia and the theory of anaesthesia. In epidemiology, Snow investigated the relationship of water supplies to mortality in cholera during the London epidemic in 1854, which led him to formulate an original and valid theory of the transmission of cholera. Snow's research, which has received less attention than anecdotes concerning his career (e.g., his anaesthetizing Queen Victoria and urging removal of the handle of a contaminated water pump), was always directed towards solving specific problems. The significance of his research is evident in its leading not only to improvements in health care but also to the evolution of anaesthesia and epidemiology as professional disciplines.

  12. Dry Snow Metamorphism

    Science.gov (United States)

    2012-09-19

    S. Chen and I. Baker, 12th International Conference on the Physics and Chemistry of Ice, Sapporo , Japan, September 5-10th, 2010. “Advanced...Microstructural Characterization of Snow and Ice”, I. Baker, 12th International Conference on the Physics and Chemistry of Ice, Sapporo , Japan, September 5...on the Physics and Chemistry of Ice, Sapporo , Japan, September 5-10th, 2010. 10 “Advanced Microstructural Characterization of Snow and Ice”, I

  13. Cloudiness and snow cover in Alpine areas from MODIS products

    Science.gov (United States)

    Da Ronco, P.; De Michele, C.

    2014-04-01

    Snow cover maps provide an information of great practical interest for hydrologic purposes: when combined with point values of snow water equivalent (SWE), they allow to estimate the regional snow resource. Earth observation satellites are an interesting tool for evaluating large scale snow distribution and extension. In this context, MODIS (MODerate resolution Imaging Spectroradiometeron on board Terra and Aqua satellites) daily Snow Covered Area product has been widely tested and proved to be appropriate for hydrologic applications. However, within a daily map the presence of cloudiness can hide the ground, thus preventing snow detection. Here, we considered MODIS binary products for daily snow mapping over Po river basin. Modeling the variability of snow cover duration, distribution and snow water equivalent is a first important step in investigating climate change impacts on the regime of the major Italian river. Ten years (2003-2012) of MOD10A1 and MYD10A1 snow maps have been analyzed and processed with the support of 500 m-resolution Digital Elevation Model (DEM). We firstly investigated the issue of cloudiness, highlighting its dependence on altitude and season. Snow maps seem to suffer the influence of overcast conditions mainly in mountain and during the melting season. Such a result is certainly related to satellite crossing times, since cloud coverage over mountains usually increases in the afternoon: however, in Aqua and Terra snow products it highly influences those areas where snow detection is regarded with more interest. In spring, the average percentages of area lying beneath clouds are in the order of 70%, for altitudes over 1000 m a.s.l. Then, on the basis of previous studies, we proposed a cloud removal procedure and its application to a wide area, characterized by high topographic and geomorphological heterogeneities such as northern Italy. While conceiving the new method, our first target was to preserve the daily temporal resolution of the

  14. Is snow sublimation important in the alpine water balance?

    Directory of Open Access Journals (Sweden)

    U. Strasser

    2007-09-01

    Full Text Available In alpine terrain, snow sublimation as a component of the winter moisture budget represents a proportion of precipitation which does not contribute to melt. To quantify its amount we analyze the spatial pattern of snow sublimation at the ground, from a canopy and from turbulent suspension during wind-induced snow transport for a high alpine area in the Berchtesgaden National Park (Germany, and we discuss the efficiency of these processes with respect to seasonal snowfall. Therefore, we utilized hourly meteorological recordings from a network of automatic stations, and a distributed simulation framework comprising validated, physically based models. Meteorological data records were spatially distributed over the simulation domain by means of a quasi-physically based interpolation scheme that accounts for topographic influences on the distributed fields. The applied simulation tools were: a detailed model for shortwave and longwave radiative fluxes, a mass and energy balance model for the ground snow cover, a model for the microclimatic conditions within a forest canopy and related snow-vegetation interactions including snow sublimation from the surface of the trees, and a model for the simulation of wind-induced snow transport and related sublimation from suspended snow particles. For each of the sublimation processes, mass rates were quantified and aggregated over an entire winter season. Sublimation from the ground and from most canopy types are spatially relatively homogeneous and sum up to about 100 mm of snow water equivalent (SWE over the winter period. Accumulated seasonal sublimation due to turbulent suspension is small in the valley areas, but can locally, at very wind-exposed mountain ridges, add up to more than 1000 mm of SWE. The fraction of these sublimation losses of winter snowfall is between 10 and 90%.

  15. Weather effects on aerial snow measurement

    Energy Technology Data Exchange (ETDEWEB)

    Tollan, O.

    1979-01-01

    When aerial snow measurements are carried out, various weather phenomena have influence on the survey operations and the registered gamma radiation values. Among these phenomena are low visibility and wind causing problems to aircraft operations, and temperature inversions which may trap radioactive gases and particles in the air layer near the ground. The pressure and temperature of the air and its humidity influence the gamma radiation field above the ground, and this should be taken into consideration. As some types of weather may cause delays and errors in the snow measurement, it is important for the operators to have a reliable account of the weather situation prior to and during the survey flights. This will reduce the cost of the measurement operation and improve the quality of the collected data.

  16. Lemming winter habitat choice: a snow-fencing experiment.

    Science.gov (United States)

    Reid, Donald G; Bilodeau, Frédéric; Krebs, Charles J; Gauthier, Gilles; Kenney, Alice J; Gilbert, B Scott; Leung, Maria C-Y; Duchesne, David; Hofer, Elizabeth

    2012-04-01

    The insulative value of early and deep winter snow is thought to enhance winter reproduction and survival by arctic lemmings (Lemmus and Dicrostonyx spp). This leads to the general hypothesis that landscapes with persistently low lemming population densities, or low amplitude population fluctuations, have a low proportion of the land base with deep snow. We experimentally tested a component of this hypothesis, that snow depth influences habitat choice, at three Canadian Arctic sites: Bylot Island, Nunavut; Herschel Island, Yukon; Komakuk Beach, Yukon. We used snow fencing to enhance snow depth on 9-ha tundra habitats, and measured the intensity of winter use of these and control areas by counting rodent winter nests in spring. At all three sites, the density of winter nests increased in treated areas compared to control areas after the treatment, and remained higher on treated areas during the treatment. The treatment was relaxed at one site, and winter nest density returned to pre-treatment levels. The rodents' proportional use of treated areas compared to adjacent control areas increased and remained higher during the treatment. At two of three sites, lemmings and voles showed significant attraction to the areas of deepest snow accumulation closest to the fences. The strength of the treatment effect appeared to depend on how quickly the ground level temperature regime became stable in autumn, coincident with snow depths near the hiemal threshold. Our results provide strong support for the hypothesis that snow depth is a primary determinant of winter habitat choice by tundra lemmings and voles.

  17. Early results from NASA's SnowEx campaign

    Science.gov (United States)

    Kim, Edward; Gatebe, Charles; Hall, Dorothy; Misakonis, Amy; Elder, Kelly; Marshall, Hans Peter; Hiemstra, Chris; Brucker, Ludovic; Crawford, Chris; Kang, Do Hyuk; De Marco, Eugenia; Beckley, Matt; Entin, Jared

    2017-04-01

    SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earth's terrestrial snow-covered regions? Year 1 (2016-17) focuses on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site is Grand Mesa and the secondary site is the Senator Beck Basin, both in western, Colorado, USA. Ten core sensors on four core aircraft will make observations using a broad suite of airborne sensors including active and passive microwave, and active and passive optical/infrared sensing techniques to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also includes an extensive range of ground truth measurements—in-situ samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some early results will be presented. Seasonal snow cover is the largest single component of the cryosphere in areal extent (covering an average of 46M km2 of Earth's surface (31 % of land areas) each year). This seasonal snow has major societal impacts in the areas of water resources, natural hazards (floods and droughts), water security, and weather and climate. The only practical way to estimate the quantity of snow on a consistent global basis is through satellites. Yet, current space-based techniques underestimate storage of snow water equivalent (SWE) by as much as 50%, and model-based estimates can differ greatly vs. estimates based on remotely-sensed observations. At peak coverage, as much as half of snow-covered terrestrial areas involve forested areas, so quantifying the challenge represented by forests is important to plan any future snow mission. Single-sensor approaches may work for certain snow types and certain conditions, but not for others

  18. [The measurement and retrieval of the spectral reflectance of different snow grain size on Northern Xinjiang, China].

    Science.gov (United States)

    Hao, Xiao-Hua; Wang, Jie; Wang, Jian; Zhang, Pu; Huang, Chun-Lin

    2013-01-01

    The retrieval of snow grain size is one of the important research directions for cryosphere snow remote sensing. In the present study, we designed the measurement plan of different snow grain size by different snow layer. A SVC HR-1024 ground-based spectral radiometer was used for measuring the spectral property of different snow grain size in northern Xinjiang, China. At the same time, the snow grain size and shape were measured by a hand-loupe with scale. Then the DSPP method was used to calculate the equivalent snow grain size. Finally, the asymptotic radiative transfer (ART) theory was applied to retrieve the snow grain size from measured snow spectral reflectance of different snow layer by optimizing the inversion band and the snow grain size factor "b". The retrieved snow grain size was validated by the measured snow grain size from DSPP method. The results showed that the DSPP method is an effective means of measuring the equivalent snow grain size. However, there is a large deviation of the snow grain size sample in the same snow layer. It is necessary to improve the measurement method of the single snow grain size sample; The study showed that the near-infrared bands are the most effective selection for retrieval of snow grain size. The retrieval algorithm from ART is feasible. When the snow is dry, the authors optimize the inversion band and the snow grain size factor b in the Northern Xinjiang, China. The optimal band wavelength is 1.20 microm and b is 3.62.

  19. Assimilation of satellite information in a snowpack model to improve characterization of snow cover for runoff simulation and forecasting

    OpenAIRE

    2009-01-01

    A new technique for constructing spatial fields of snow characteristics for runoff simulation and forecasting is presented. The technique incorporates satellite land surface monitoring data and available ground-based hydrometeorological measurements in a physical based snowpack model. The snowpack model provides simulation of temporal changes of the snow depth, density and water equivalent (SWE), accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with...

  20. Evaluation of the Impact of Lake Ice on Passive Microwave Snow Retrieval Algorithms Using Ground-based Observation%利用地面观测实验评价湖冰对被动微波反演积雪算法的影响

    Institute of Scientific and Technical Information of China (English)

    王培; 蒋玲梅; 张立新

    2011-01-01

    通过对东北积雪实验观测数据和HUT(the Helsinki University of Technology)积雪-冰-水层模型模拟数据的比较分析,描述了积雪-冰-水系统的发射率特征.并于2010年1月21日~22日在吉林省松原市的松花江进行了积雪辐射计观测试验,通过对湖冰上的积雪的亮温观测和HUT模型模拟的亮温比较结果来看,HUT模型在各个角度下模拟亮温与实测亮温均较吻合,其中模拟的水平极化亮温的拟合结果要好于垂直极化的结果.HUT模拟和地面测量结果的水平极化的拟合度——R2为0.9316,垂直极化的R2为0.9194.通过地面观测数据,本文分析了湖冰对现有被动微波反演积雪算法的影响,利用HUT模型进行了雪层厚度和冰层厚度对当前雪水当量反演所用的亮温差的敏感性分析,发现当前的雪水当量反演算法对冰层厚度非常敏感,尤其在冰层比较薄的情况下,要精确获得富湖泊区的雪水当量,还需要更进一步的研究.%In this work,we chose the Helsinki University of Technology (HUT) snow emission model to characterize the emission behavior of snowpack-ice-water system with the ground microwave radiometer observation. The snow and lake ice surveys were conducted in Songhua river,Songyuan city,Jilin Province,on Jan. 21 - 22,2010. Compared to the ground measurements over shallow snow-covered lake surface, the simulated brightness temperature at horizontal polarization was better than that at vertical polarizations. The R2 of the HUT simulation and measured value was 0. 9316 at H-pol. And 0. 9194 at V-pol. Respectively. Further, we investigated the impact of lake on snow retrieval using a passive microwave remote sensing and these ground-based observations. Finally,we took a sensitivity analysis of ice thickness and snow depth using HUT model on the show and found that the current brightness temperature difference snow retrieval algorithm was very sensitive to the ice thickness,especially in

  1. Monitoring and modelling snow avalanches in Svalbard

    Science.gov (United States)

    Humlum, O.; Christiansen, H.; Neumann, U.; Eckerstorfer, M.; Sjöblom, A.; Stalsberg, K.; Rubensdotter, L.

    2009-04-01

    Monitoring and modelling snow avalanches in Svalbard Ole Humlum 1,3, Hanne H. Christiansen 1, Ulrich Neumann 1, Markus Eckerstorfer 1, Anna Sjöblom 1, Knut Stalsberg 2 and Lena Rubensdotter 2. 1: The University Centre in Svalbard (UNIS). 2: Geological Survey of Norway (NGU) 3: University of Oslo Ground based transportation in Svalbard landscape all takes place across mountainous terrain affected by different geomorphological slope processes. Traffic in and around the Svalbard settlements is increasing, and at the same time global climate models project substantial increases in temperature and precipitation in northern high latitudes for coming century. Therefore improved knowledge on the effect of climatic changes on slope processes in such high arctic landscapes is becoming increasingly important. Motivated by this, the CRYOSLOPE Svalbard research project since 2007 has carried out field observations on snow avalanche frequency and associated meteorological conditions. Snow avalanches are important geomorphic agents of erosion and deposition, and have long been a source of natural disasters in many mid-latitude mountain areas. Avalanches as a natural hazard has thereby been familiar to inhabitants of the Alps and Scandinavia for centuries, while it is a more recent experience in high arctic Svalbard. In addition, overall climate, topography and especially high winter wind speeds makes it difficult to apply snow avalanche models (numerical or empirical) developed for use at lower latitudes, e.g. in central Europe. In the presentation we examplify results from the ongoing (since winter 2006-07) monitoring of snow avalanches in Svalbard along a 70 km long observational route in the mountains. In addition, we present observations on the geomorphological impact of avalanches, with special reference to the formation of rock glaciers. Finally, we also present some initial results from numerical attempts of snow avalanche risk modelling within the study area.

  2. 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

  3. Field Observations of the Effects of Explosives on Snow Properties

    Science.gov (United States)

    Wooldridge, R.; Hendrikx, J.; Miller, D. A.; Birkeland, K.

    2012-12-01

    Explosives are a critically important component of avalanche control programs. They are used to both initiate avalanches and to test snowpack instability by ski areas, highway departments and other avalanche programs around the world. Current understanding of the effects of explosives on snow is mainly limited to shock wave behavior demonstrated through stress wave velocities, pressures and attenuation. This study seeks to enhance current knowledge of how explosives physically alter snow by providing practical, field-based observations and analyses that quantify the effect of explosives on snow density, snow hardness and snow stability test results. Density, hardness and stability test results were evaluated both before and after the application of 0.9 kg cast pentolite boosters as air blasts. Changes in these properties were evaluated at specified distances up to 4 meters (m) from the blast center using a density gauge, hand hardness, Compression Tests (CTs), and Extended Column Tests (ECTs). Statistically significant density increases occurred out to a distance of 1.5 m from the blast center and down to a depth of 60 centimeters (cm). Statistically significant density increases were also observed at the surface (down to 20 cm) out to a distance of 4 m. Hardness increased slightly at the surface and at the bottom of the snowpack (depths of 80-100 cm), while decreasing slightly in the middle of the snowpack (depths of 30-60 cm). Results from CTs showed a decrease in the number of taps needed for column failure in the post explosive tests, while a smaller data set of ECT results showed no overall change in ECT score. The findings of this study provide a better understanding of the physical changes in snow following explosives, which may lead to more effective and efficient avalanche risk mitigation.

  4. Assessing the application of a laser rangefinder for determining snow depth in inaccessible alpine terrain

    Directory of Open Access Journals (Sweden)

    J. L. Hood

    2010-01-01

    Full Text Available Snow is a major contributor to stream flow in alpine watersheds and quantifying snow depth and distribution is important for hydrological research. However, direct measurement of snow in rugged alpine terrain is often impossible due to avalanche and rock fall hazard. A laser rangefinder was used to determine the depth of snow in inaccessible areas. Laser rangefinders use ground based light detection and ranging technology but are more cost effective than airborne surveys or terrestrial laser scanning systems and are highly portable. Data was collected within the Opabin watershed in the Canadian Rockies. Surveys were conducted on one accessible slope for validation purposes and two inaccessible talus slopes. Laser distance data was used to generate surface models of slopes when snow covered and snow-free and snow depth distribution was quantified by differencing the two surfaces. The results were compared with manually probed snow depths on the accessible slope. The accuracy of the laser rangefinder method as compared to probed depths was 0.21 m or 12% of average snow depth. Results from the two inaccessible talus slopes showed regions near the top of the slopes with 6–9 m of snow accumulation. These deep snow accumulation zones result from re-distribution of snow by avalanches and are hydrologically significant as they persist until late summer.

  5. Assessing the application of a laser rangefinder for determining snow depth in inaccessible alpine terrain

    Directory of Open Access Journals (Sweden)

    J. L. Hood

    2010-06-01

    Full Text Available Snow is a major contributor to stream flow in alpine watersheds and quantifying snow depth and distribution is important for hydrological research. However, direct measurement of snow in rugged alpine terrain is often impossible due to avalanche and rock fall hazard. A laser rangefinder was used to determine the depth of snow in inaccessible areas. Laser rangefinders use ground based light detection and ranging technology but are more cost effective than airborne surveys or terrestrial laser scanning systems and are highly portable. Data were collected within the Opabin watershed in the Canadian Rockies. Surveys were conducted on one accessible slope for validation purposes and two inaccessible talus slopes. Laser distance data was used to generate surface models of slopes when snow covered and snow-free and snow depth distribution was quantified by differencing the two surfaces. The results were compared with manually probed snow depths on the accessible slope. The accuracy of the laser rangefinder method as compared to probed depths was 0.21 m or 12% of average snow depth. Results from the two inaccessible talus slopes showed regions near the top of the slopes with 6–9 m of snow accumulation. These deep snow accumulation zones result from re-distribution of snow by avalanches and are hydrologically significant as they persist until late summer.

  6. Producing Snow Extent and Snow Water Equivalent Information for Climate Research Purposes - ESA DUE Globsnow Effort

    Science.gov (United States)

    Luojus, Kari; Pulliainen, Jouni; Rott, Helmut; Nagler, Thomas; Solberg, Rune; Wiesmann, Andreas; Derksen, Chris; Metsämäki, Sari; Malnes, Eirik; Bojkov, Bojan

    2010-05-01

    The European Space Agency (ESA) Data User Element (DUE) funded GlobSnow project aims at creating a global database of snow parameters for climate research purposes. The main objective is to create a long term dataset on two essential snow parameters. The project will provide information concerning the areal extent of snow (SE) on a global scale and snow water equivalent (SWE) for the Northern Hemisphere. Both products will include the end product derived from the satellite data along with accuracy information for each snow parameter. The temporal span of the SE product will be 15 years and the span for the SWE product will be 30 years. A key improvement of the snow products, when compared with the currently available data sets, will be the inclusion of a statistically derived accuracy estimate accompanying each SE or SWE estimate (on a pixel level). In addition to the SE and SWE time-series, an operational near-real time (NRT) snow information service will be implemented. The service will provide daily snow maps for hydrological, meteorological, and climate research purposes. The snow products will be based on data acquired from optical and passive microwave-based spaceborne sensors combined with ground-based weather station observations. The work was initiated in November 2008, and is being coordinated by the Finnish Meteorological Institute (FMI). Other project partners involved are NR (Norwegian Computing Centre), ENVEO IT GmbH, GAMMA Remote Sensing AG, Finnish Environment Institute (SYKE), Environment Canada (EC) and Northern Research Institute (Norut). Extensive algorithm evaluation efforts were carried out for the candidate SWE and SE algorithms during 2009 using ground truth data gathered from Canada, Scandinavia, Russia and the Alps. The acquired evaluation results have enabled the selection of the algorithms to be utilized for the GlobSnow SE and SWE products. The SWE product is derived using the FMI Algorithm and the SE product is a combination of NR and

  7. Microwave snow emission modeling uncertainties in boreal and subarctic environments

    Directory of Open Access Journals (Sweden)

    A. Roy

    2015-10-01

    Full Text Available This study aims to better understand and quantify the uncertainties in microwave snow emission models using the Dense Media Radiative Theory-Multilayer model (DMRT-ML with in situ measurements of snow properties. We use surface-based radiometric measurements at 10.67, 19 and 37 GHz in boreal forest and subarctic environments and a new in situ dataset of measurements of snow properties (profiles of density, snow grain size and temperature, soil characterization and ice lens detection acquired in the James Bay and Umijuaq regions of Northern Québec, Canada. A snow excavation experiment – where snow was removed from the ground to measure the microwave emission of bare frozen ground – shows that small-scale spatial variability in the emission of frozen soil is small. Hence, variability in the emission of frozen soil has a small effect on snow-covered brightness temperature (TB. Grain size and density measurement errors can explain the errors at 37 GHz, while the sensitivity of TB at 19 GHz to snow increases during the winter because of the snow grain growth that leads to scattering. Furthermore, the inclusion of observed ice lenses in DMRT-ML leads to significant improvements in the simulations at horizontal polarization (H-pol for the three frequencies (up to 20 K of root mean square error. However, the representation of the spatial variability of TB remains poor at 10.67 and 19 GHz at H-pol given the spatial variability of ice lens characteristics and the difficulty in simulating snowpack stratigraphy related to the snow crust. The results also show that for ground-based radiometric measurements, forest emission reflected by the surface leads to TB underestimation of up to 40 K if neglected. We perform a comprehensive analysis of the components that contribute to the snow-covered microwave signal, which will help to develop DMRT-ML and to improve the required field measurements. The analysis shows that a better consideration of ice lenses and

  8. Numerical Simulation of Sensitivities of Snow Melting to Spectral Composition of the Incoming Solar Radiation

    Institute of Scientific and Technical Information of China (English)

    LI Weiping; SUN Shufen; WANG Siao; LIU Xin

    2009-01-01

    Snow albedo is an important factor influencing the snow surface energy budget and snow melting,yet uncertainties remain in the calculation of spectrally resolved snow surface albedo because the spectral composition (visible versus near infrared) of the incident solar radiation is seldom available. The influence of the spectral composition of the incoming solar radiation on the snow surface albedo, snow surface energy budget, and final snow ablation is investigated through sensitivity experiments of four snow seasons at two open sites in the Alps by using a multi-layer Snow-Atmosphere-Soil-Transfer scheme (SAST). Since the snow albedo in the near infrared (NIR) spectral band is significantly lower than that in the visible (VIS) band, and almost the entire NIR part of the solar radiation is absorbed in the top layer of the snow pack, given a fixed amount of incoming solar radiation, a lower VIS/NIR ratio implies that more NIR radiation is reaching the ground surface and more is absorbed by the top layer of the snow pack, therefore, speeding up the snow melting and increasing the surface runoff, although a lesser part of the solar radiation in the visible band is transmitted into and trapped by the sub-layer of the snow pack. The above VIS/NIR ratio effect of the incoming solar radiation can result in a couple of days difference in the timing of snow ablation and it becomes more significant in late spring when the total solar radiation is intensified with seasonal evolution. Snow aging also slightly intensifies this VIS/NIR ratio effect.

  9. 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

  10. Estimation of global snow cover using passive microwave data

    Science.gov (United States)

    Chang, Alfred T. C.; Kelly, Richard E.; Foster, James L.; Hall, Dorothy K.

    2003-04-01

    This paper describes an approach to estimate global snow cover using satellite passive microwave data. Snow cover is detected using the high frequency scattering signal from natural microwave radiation, which is observed by passive microwave instruments. Developed for the retrieval of global snow depth and snow water equivalent using Advanced Microwave Scanning Radiometer EOS (AMSR-E), the algorithm uses passive microwave radiation along with a microwave emission model and a snow grain growth model to estimate snow depth. The microwave emission model is based on the Dense Media Radiative Transfer (DMRT) model that uses the quasi-crystalline approach and sticky particle theory to predict the brightness temperature from a single layered snowpack. The grain growth model is a generic single layer model based on an empirical approach to predict snow grain size evolution with time. Gridding to the 25 km EASE-grid projection, a daily record of Special Sensor Microwave Imager (SSM/I) snow depth estimates was generated for December 2000 to March 2001. The estimates are tested using ground measurements from two continental-scale river catchments (Nelson River and the Ob River in Russia). This regional-scale testing of the algorithm shows that for passive microwave estimates, the average daily snow depth retrieval standard error between estimated and measured snow depths ranges from 0 cm to 40 cm of point observations. Bias characteristics are different for each basin. A fraction of the error is related to uncertainties about the grain growth initialization states and uncertainties about grain size changes through the winter season that directly affect the parameterization of the snow depth estimation in the DMRT model. Also, the algorithm does not include a correction for forest cover and this effect is clearly observed in the retrieval. Finally, error is also related to scale differences between in situ ground measurements and area-integrated satellite estimates. With AMSR

  11. Pavement Snow Melting

    Energy Technology Data Exchange (ETDEWEB)

    Lund, John W.

    2005-01-01

    The design of pavement snow melting systems is presented based on criteria established by ASHRAE. The heating requirements depends on rate of snow fall, air temperature, relative humidity and wind velocity. Piping materials are either metal or plastic, however, due to corrosion problems, cross-linked polyethylene pipe is now generally used instead of iron. Geothermal energy is supplied to systems through the use of heat pipes, directly from circulating pipes, through a heat exchanger or by allowing water to flow directly over the pavement, by using solar thermal storage. Examples of systems in New Jersey, Wyoming, Virginia, Japan, Argentina, Switzerland and Oregon are presented. Key words: pavement snow melting, geothermal heating, heat pipes, solar storage, Wyoming, Virginia, Japan, Argentina, Klamath Falls.

  12. Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation

    Science.gov (United States)

    Forman, Bart; Reichle, Rofl; Rodell, Matt

    2011-01-01

    Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean.

  13. Design of an optimal snow observation network to estimate snowpack

    Science.gov (United States)

    Juan Collados Lara, Antonio; Pardo-Iguzquiza, Eulogio; Pulido-Velazquez, David

    2016-04-01

    Snow is an important water resource in many river basins that must be taken into account in hydrological modeling. Although the snow cover area may be nowadays estimated from satellite data, the snow pack thickness must be estimated from experimental data by using some interpolation procedure or hydrological models that approximates snow accumulation and fusion processes. The experimental data consist of hand probes and snow samples collected in a given number of locations that constitute the monitoring network. Assuming that there is an existing monitoring network, its optimization may imply the selection of an optimal network as a subset of the existing network (decrease of the existing network in the case that there are no funds for maintaining the full existing network) or to increase the existing network by one or more stations (optimal augmentation problem). In this work we propose a multicriterion approach for the optimal design of a snow network. These criteria include the estimation variance from a regression kriging approach for estimating thickness of the snowpack (using ground and satellite data), to minimize the total snow volume and accessibility criteria. We have also proposed a procedure to analyze the sensitivity of the results to the non-snow data deduced from the satellite information. We intent to minimize the uncertities in snowpack estimation. The methodology has been applied to estimation of the snow cover area and the design of the optimal snow observation network in Sierra Nevada mountain range in the Southern of Spain. Acknowledgments: This research has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank ERHIN program and NASA DAAC for the data provided for this study.

  14. Calibration of a distributed snow model using MODIS snow covered area data

    Science.gov (United States)

    Franz, Kristie J.; Karsten, Logan R.

    2013-06-01

    Spatial ground-based observations of snow are often limited at the watershed-scale, therefore the snow modeling component of a hydrologic modeling system is often calibrated along with the rainfall-runoff model using watershed discharge observations. This practice works relatively well for lumped modeling applications when the accuracy of sub-watershed processes is generally not of concern. However, with the increasing use of distributed models, realistic representation of processes, such as snow areal depletion, become more important. In this study, we test the use of snow covered area (SCA) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite for calibration of four key parameters in the distributed US National Weather Service (NWS) SNOW17 model in the North Fork of the American River basin in California, USA. Three tests are conducted; two rely solely on MODIS SCA data and one includes discharge in the calibration procedure. The three calibrations are compared to the use of parameters obtained from the NWS California Nevada River Forecast Center (CNRFC). The calibration approach that utilizes both MODIS SCA and discharge data produces the most accurate spatial (gridded) SCA and basin discharge simulations but not the best SCA summary statistics. In general it was found that improvement in simulated SCA when averaged and evaluated by elevation zone using standard summary statistics, does not necessarily coincide with more accurate discharge simulations.

  15. ASAR analysis of the snow cover in Livingston and Deception Islands.

    Science.gov (United States)

    Mora, C.; Vieira, G.; Ramos, M.

    2009-04-01

    ASAR images from Envisat are analyzed to study the snow cover regime of Deception and Livingston Islands (South Sthetlands, Antarctic Peninsula). Data is provided by the European Space Agency in the framework of the Proposal Category-1: Snow cover characteristics and regime in the South Shetlands (Maritime Antarctic) - SnowAntar. Medium resolution images (WSW, APM and IMM) are analyzed since December 2008, and are prepared using the processing chains from BEST (Basic Envisat SAR Toolbox). The process includes the transformation of DN into power values, geometric and radiometric correction, image filtering and computation of the backscattering coefficient for each pixel. Thereafter, the imagery is analyzed in image analysis software for the classification of backscattering. A multitemporal imagery analysis is conducted in order to set a threshold on the differential backscatter between scenes under wet snow and snow free-conditions. These algorithms allow for the study of snow surface wetness and snow water equivalent. The study of snow cover regime is linked to the permafrost monitoring and modeling effort conducted in the region in the framework of the PERMANTAR-PERMAMODEL projects. The proprieties of snow are of major significance for the ground energy balance and therefore to the ground thermal regime, since thick snow provides excellent insulation. Permafrost is therefore influenced by snow cover properties, spatial distribution and regime. Snow cover maps will be produced for integration in permafrost modeling and also for comparison with re-analysis data from ERA-Interim. The poster presents the first results of the imagery analysis of the snow cover regime since December 2008. The satellite data is validated in the field with several areas of interest (AOI) with snow thickness monitoring devices based on thermal regimes at different heights.

  16. Quantification of basal friction for technical and silvicultural glide-snow avalanche mitigation measures

    OpenAIRE

    2014-01-01

    A long-standing problem in avalanche engineering is to design defense structures and manage forest stands such that they can withstand the forces of the natural snow cover. In this way, glide-snow avalanches can be prevented. Ground friction plays a crucial role in this process. To verify existing guidelines, we collected data on the vegetation cover and terrain characteristics of 101 glide-snow release areas in Davos, Switzerland. We quantified the Coulomb friction paramete...

  17. 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

  18. 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

  19. snowBOTS: a mobile robot on snow covered ice

    OpenAIRE

    2007-01-01

    We introduce snowBOTs as a generic name for robots working in snow. This paper is a study on using scan ning range measuring lasers towards an autonomous snow cleaning robot, working in an environment consisting al most entirely of snow and ice. The problem addressed here is using lasers for detecting the edges generated by "the snow meeting the road". First the laser data were filtered using his togram/median to discriminate against falling snowflakes and small objects. Then the road surface w...

  20. Combining low-cost GPS receivers with upGPR to derive continuously liquid water content, snow height and snow water equivalent in Alpine snow covers

    Science.gov (United States)

    Koch, Franziska; Schmid, Lino; Prasch, Monika; Heilig, Achim; Eisen, Olaf; Schweizer, Jürg; Mauser, Wolfram

    2015-04-01

    The temporal evolution of Alpine snowpacks is important for assessing water supply, hydropower generation, flood predictions and avalanche forecasts. Especially in high mountain regions with an extremely varying topography, it is until now often difficult to derive continuous and non-destructive information on snow parameters. Since autumn 2012, we are running a new low-cost GPS (Global Positioning System) snow measurement experiment at the high alpine study site Weissfluhjoch (2450 m a.s.l.) in Switzerland. The globally and freely broadcasted GPS L1-band (1.57542 GHz) was continuously recorded with GPS antennas, which are installed at the ground surface underneath the snowpack. GPS raw data, containing carrier-to-noise power density ratio (C/N0) as well as elevation and azimuth angle information for each time step of 1 s, was stored and analyzed for all 32 GPS satellites. Since the dielectric permittivity of an overlying wet snowpack influences microwave radiation, the bulk volumetric liquid water content as well as daily melt-freeze cycles can be derived non-destructively from GPS signal strength losses and external snow height information. This liquid water content information is qualitatively in good accordance with meteorological and snow-hydrological data and quantitatively highly agrees with continuous data derived from an upward-looking ground-penetrating radar (upGPR) working in a similar frequency range. As a promising novelty, we combined the GPS signal strength data with upGPR travel-time information of active impulse radar rays to the snow surface and back from underneath the snow cover. This combination allows determining liquid water content, snow height and snow water equivalent from beneath the snow cover without using any other external information. The snow parameters derived by combining upGPR and GPS data are in good agreement with conventional sensors as e.g. laser distance gauges or snow pillows. As the GPS sensors are cheap, they can easily

  1. Estimation of snow water equivalent using a radiance assimilation scheme with a multi-layered snow physical model

    Science.gov (United States)

    Mounirou Toure, Ally

    The feasibility of a radiance assimilation using a multi-layered snow physical model to estimate snow physical parameters is studied. The work is divided in five parts. The first two chapters are dedicated to the literature review. In the third chapter, experimental work was conducted in the alpine snow to estimate snow correlation (for microwave emission modelling) using near-infrared digital photography. We made microwave radiometric and near-infrared reflectance measurements of snow slabs under different experimental conditions. We used an empirical relation to link near-infrared reflectance of snow to the specific surface area (SSA), and converted the SSA into the correlation length. From the measurements of snow radiances at 21 and 35 GHz, we derived the microwave scattering coefficient by inverting two coupled radiative transfer models (RTM) (the sandwich and six-flux model). The correlation lengths found are in the same range as those determined in the literature using cold laboratory work. The technique shows great potential in the determination of the snow correlation length under field conditions. In the fourth chapter, the performance of the ensemble Kalman filter (EnKF) for snow water equivalent (SWE) estimation is assessed by assimilating synthetic microwave observations at Ground Based Microwave Radiometer (GBMR-7) frequencies (18.7, 23.8, 36.5, 89 vertical and horizontal polarization) into a snow physics model, CROCUS. CROCUS has a realistic stratigraphic and ice layer modelling scheme. This work builds on previous methods that used snow physics model with limited number of layers. Data assimilation methods require accurate predictions of the brightness temperature (Tb) emitted by the snowpack. It has been shown that the accuracy of RTMs is sensitive to the stratigraphic representation of the snowpack. However, as the stratigraphic fidelity increases, the number of layers increases, as does the number of state variables estimated in the assimilation

  2. Annual Snow Assessments Using Multi-spectral and Passive Microwave Remote Sensing

    Science.gov (United States)

    Daly, S. F.; Vuyovich, C. M.; Deeb, E. J.; Newman, S. D.; Baldwin, T. B.

    2010-12-01

    Since the winter season of 2004-2005, annual snow assessments have been conducted for regions across the Middle East (including Eastern Turkey, Afghanistan, and Pakistan) using multispectral (AVHRR and MODIS) and passive microwave (SSM/I and AMSR-E) remote sensing technologies. Due to limited ground-based observations of precipitation and snow pack conditions, remote sensing provides a unique opportunity to assess these conditions at different scales and offer an appraisal of the current conditions in an historical context. During each winter season, bi-weekly snow products and assessments are produced including: current Snow Covered Area (SCA) at regional and watershed scales; estimation of SCA by elevation band; current snowpack total Snow Water Equivalent (SWE) for each watershed with an historical perspective (1987-present); snow condition outlook by watershed; general summary of snow conditions based on remote sensing products and limited ground-based observations; and if warranted, a snow melt flooding advisory. Most recently, the winter 2009-2010 season provided interesting aspects that are further investigated: comparison of reported drought conditions, SCA extents, and passive microwave SWE estimates in Afghanistan; flooding event in Northeastern Afghanistan perhaps due to late season snow fall and subsequent snow melt; lower SCA in Eastern Turkey throughout winter despite heavy precipitation perhaps explained by warmer regional temperatures.

  3. Snow White II.

    Science.gov (United States)

    Gundy, Jan

    1978-01-01

    Presented as a fairy tale with the characters of Snow White and the seven dwarves, this paper points out some of the professional, emotional, and health characteristics and problems of individual teachers, and ways an administrator might deal with them. (SJL)

  4. Snow White 5 Trench

    Science.gov (United States)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Robotic Arm Camera on the 35th Martian day of the mission, or Sol 34 (June 29, 2008), after the May 25, 2008, landing. This image shows the trench informally called 'Snow White 5.' The trench is 4-to-5 centimeters (about 1.5-to-1.9 inches) deep, 24 centimeters (about 9 inches) wide and 33 centimeters (13 inches) long. Snow White 5 is Phoenix's current active digging area after additional trenching, grooming, and scraping by Phoenix's Robotic Arm in the last few sols to trenches informally called Snow White 1, 2, 3, and 4. Near the top center of the image is the Robotic Arm's Thermal and Electrical Conductivity Probe. Snow White 5 is located in a patch of Martian soil near the center of a polygonal surface feature, nicknamed 'Cheshire Cat.' The digging site has been named 'Wonderland.' This image has been enhanced to brighten shaded areas. 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.

  5. Snow-clearing operations

    CERN Multimedia

    EN Department

    2010-01-01

    To facilitate snow clearing operations, which commence at 4.30 in the morning, all drivers of CERN cars are kindly requested to park them together in groups. This will help us greatly assist us in our work. Thank-you for your help. Transport Group / EN-HE Tel. 72202

  6. Principles of snow hydrology

    National Research Council Canada - National Science Library

    DeWalle, David R; Rango, Albert

    2008-01-01

    ... Hydrology describes the factors that control the accumulation, melting, and runoff of water from seasonal snowpacks over the surface of the earth. The book addresses not only the basic principles governing snow in the hydrologic cycle, but also the latest applications of remote sensing, and principles applicable to modelling streamflow from snowmelt across lar...

  7. Backpack Snow Shovel/Snow Kit and Ahkio Snow Shovel/Snow Saw Kit

    Science.gov (United States)

    for backpacking by the individual soldier. A larger, more durable shovel is for use in conjunction with the man-hauled sled (Ahkio). A snow saw in a...scabbard is provided which can be attached either to the handle of the Ahkio shovel, to the disassembled backpack shovel in the carrying case, to the rucksack or to the belt.

  8. Snow-white teeth

    National Research Council Canada - National Science Library

    Sarll, D

    2006-01-01

    ... well have pointed out, but unavailingly, that snow-white teeth adorn only the grins of infants.There is, however, another ploy that colleagues might try in their quest to enlighten patients, particularly those of a literary disposition: adduce the attributes of 'youthful beauty' given to us by Virginia Woolf (1882 - 1941). From her novel, Orla...

  9. 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.

  10. Distributed snow and rock temperature modelling in steep rock walls using Alpine3D

    Science.gov (United States)

    Haberkorn, Anna; Wever, Nander; Hoelzle, Martin; Phillips, Marcia; Kenner, Robert; Bavay, Mathias; Lehning, Michael

    2017-02-01

    In this study we modelled the influence of the spatially and temporally heterogeneous snow cover on the surface energy balance and thus on rock temperatures in two rugged, steep rock walls on the Gemsstock ridge in the central Swiss Alps. The heterogeneous snow depth distribution in the rock walls was introduced to the distributed, process-based energy balance model Alpine3D with a precipitation scaling method based on snow depth data measured by terrestrial laser scanning. The influence of the snow cover on rock temperatures was investigated by comparing a snow-covered model scenario (precipitation input provided by precipitation scaling) with a snow-free (zero precipitation input) one. Model uncertainties are discussed and evaluated at both the point and spatial scales against 22 near-surface rock temperature measurements and high-resolution snow depth data from winter terrestrial laser scans.In the rough rock walls, the heterogeneously distributed snow cover was moderately well reproduced by Alpine3D with mean absolute errors ranging between 0.31 and 0.81 m. However, snow cover duration was reproduced well and, consequently, near-surface rock temperatures were modelled convincingly. Uncertainties in rock temperature modelling were found to be around 1.6 °C. Errors in snow cover modelling and hence in rock temperature simulations are explained by inadequate snow settlement due to linear precipitation scaling, missing lateral heat fluxes in the rock, and by errors caused by interpolation of shortwave radiation, wind and air temperature into the rock walls.Mean annual near-surface rock temperature increases were both measured and modelled in the steep rock walls as a consequence of a thick, long-lasting snow cover. Rock temperatures were 1.3-2.5 °C higher in the shaded and sunny rock walls, while comparing snow-covered to snow-free simulations. This helps to assess the potential error made in ground temperature modelling when neglecting snow in steep bedrock.

  11. Snow on Antarctic sea ice

    Science.gov (United States)

    Massom, Robert A.; Eicken, Hajo; Hass, Christian; Jeffries, Martin O.; Drinkwater, Mark R.; Sturm, Matthew; Worby, Anthony P.; Wu, Xingren; Lytle, Victoria I.; Ushio, Shuki; Morris, Kim; Reid, Phillip A.; Warren, Stephen G.; Allison, Ian

    2001-08-01

    Snow on Antarctic sea ice plays a complex and highly variable role in air-sea-ice interaction processes and the Earth's climate system. Using data collected mostly during the past 10 years, this paper reviews the following topics: snow thickness and snow type and their geographical and seasonal variations; snow grain size, density, and salinity; frequency of occurrence of slush; thermal conductivity, snow surface temperature, and temperature gradients within snow; and the effect of snow thickness on albedo. Major findings include large regional and seasonal differences in snow properties and thicknesses; the consequences of thicker snow and thinner ice in the Antarctic relative to the Arctic (e.g., the importance of flooding and snow-ice formation); the potential impact of increasing snowfall resulting from global climate change; lower observed values of snow thermal conductivity than those typically used in models; periodic large-scale melt in winter; and the contrast in summer melt processes between the Arctic and the Antarctic. Both climate modeling and remote sensing would benefit by taking account of the differences between the two polar regions.

  12. Monitoring Snow Using Geostationary Satellite Retrievals During the SAAWSO Project

    Science.gov (United States)

    Rabin, Robert M.; Gultepe, Ismail; Kuligowski, Robert J.; Heidinger, Andrew K.

    2016-09-01

    The SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) field programs were conducted by Environment Canada near St. Johns, NL and Goose Bay, NL in the winters of 2012-13 and 2013-14, respectively. The goals of these programs were to validate satellite-based nowcasting products, including snow amount, wind intensity, and cloud physical parameters (e.g., cloud cover), over northern latitudes with potential applications to Search And Rescue (SAR) operations. Ground-based in situ sensors and remote sensing platforms were used to measure microphysical properties of precipitation, clouds and fog, radiation, temperature, moisture and wind profiles. Multi-spectral infrared observations obtained from Geostationary Operational Environmental Satellite (GOES)-13 provided estimates of cloud top temperature and height, phase (water, ice), hydrometer size, extinction, optical depth, and horizontal wind patterns at 15 min intervals. In this work, a technique developed for identifying clouds capable of producing high snowfall rates and incorporating wind information from the satellite observations is described. The cloud top physical properties retrieved from operational satellite observations are validated using measurements obtained from the ground-based in situ and remote sensing platforms collected during two precipitation events: a blizzard heavy snow storm case and a moderate snow event. The retrieved snow precipitation rates are found to be comparable to those of ground-based platform measurements in the heavy snow event.

  13. Multidecadal climate and seasonal snow conditions in Svalbard

    Science.gov (United States)

    Pelt, W. J. J.; Kohler, J.; Liston, G. E.; Hagen, J. O.; Luks, B.; Reijmer, C. H.; Pohjola, V. A.

    2016-11-01

    Svalbard climate is undergoing amplified change with respect to the global mean. Changing climate conditions directly affect the evolution of the seasonal snowpack, through its impact on accumulation, melt, and moisture exchange. We analyze long-term trends and spatial patterns of seasonal snow conditions in Svalbard between 1961 and 2012. Downscaled regional climate model output is used to drive a snow modeling system (SnowModel), with coupled modules simulating the surface energy balance and snowpack evolution. The precipitation forcing is calibrated and validated against snow depth data on a set of glaciers around Svalbard. Climate trends reveal seasonally inhomogeneous warming and a weakly positive precipitation trend, with strongest changes in the north. In response to autumn warming the date of snow onset increased (2 days decade-1), whereas in spring/summer opposing effects cause a nonsignificant trend in the snow disappearance date. Maximum snow water equivalent (SWE) in winter/spring shows a modest increase (+0.01 meters water equivalent (mwe) decade-1), while the end-of-summer minimum snow area fraction declined strongly (from 48% to 36%). The equilibrium line altitude is highest in relatively dry inland regions, and time series show a clear positive trend (25 m decade-1) as a result of summer warming. Finally, rain-on-snow in the core winter season, affecting ground ice formation and limiting access of grazing animals to food supplies, peaks during specific years (1994, 1996, 2000, and 2012) and is found to be concentrated in the lower lying coastal regions in southwestern Svalbard.

  14. Validating reconstruction of snow water equivalent in California's Sierra Nevada using measurements from the NASA Airborne Snow Observatory

    Science.gov (United States)

    Bair, Edward H.; Rittger, Karl; Davis, Robert E.; Painter, Thomas H.; Dozier, Jeff

    2016-11-01

    Accurately estimating basin-wide snow water equivalent (SWE) is the most important unsolved problem in mountain hydrology. Models that rely on remotely sensed inputs are especially needed in ranges with few surface measurements. The NASA Airborne Snow Observatory (ASO) provides estimates of SWE at 50 m spatial resolution in several basins across the Western U.S. during the melt season. Primarily, water managers use this information to forecast snowmelt runoff into reservoirs; another impactful use of ASO measurements lies in validating and improving satellite-based snow estimates or models that can scale to whole mountain ranges, even those without ground-based measurements. We compare ASO measurements from 2013 to 2015 to four methods that estimate spatially distributed SWE: two versions of a SWE reconstruction method, spatial interpolation from snow pillows and courses, and NOAA's Snow Data Assimilation System (SNODAS). SWE reconstruction downscales energy forcings to compute potential melt, then multiplies those values by satellite-derived estimates of fractional snow-covered area to calculate snowmelt. The snowpack is then built in reverse from the date the snow is observed to disappear. The two SWE reconstruction models tested include one that employs an energy balance calculation of snowmelt, and one that combines net radiation and degree-day approaches to estimate melt. Our full energy balance model, without ground observations, performed slightly better than spatial interpolation from snow pillows, having no systematic bias and 26% mean absolute error when compared to SWE from ASO. Both reconstruction models and interpolation were more accurate than SNODAS.

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

    Science.gov (United States)

    Joyce, M.; Painter, T. H.; Mattmann, C. A.; Ramirez, P.; Laidlaw, R.; Bormann, K. J.; Skiles, M.; Richardson, M.; Berisford, D. F.

    2015-12-01

    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.

  16. 'Snow White' Trench

    Science.gov (United States)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Surface Stereo Imager on Sol 43, the 43rd Martian day after landing (July 8, 2008). This image shows the trench informally called 'Snow White.' Two samples were delivered to the Wet Chemistry Laboratory, which is part of Phoenix's Microscopy, Electrochemistry, and Conductivity Analyzer (MECA). The first sample was taken from the surface area just left of the trench and informally named 'Rosy Red.' It was delivered to the Wet Chemistry Laboratory on Sol 30 (June 25, 2008). The second sample, informally named 'Sorceress,' was taken from the center of the 'Snow White' trench and delivered to the Wet Chemistry Laboratory on Sol 41 (July 6, 2008). 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.

  17. Dependence of snow melting and surface-atmosphere interactions on the forest structure

    Science.gov (United States)

    Otterman, J.; Staenz, K.; Itten, K. I.; Kukla, G.

    1988-01-01

    The surface albedo and the surface roughness for forested areas with snow on the ground are expressed in terms of the tree silhouette parameter, s, the projection on the vertical plane of trees per unit area. The absorption of insolation (direct solar beam) is quantitatively described for a horizontal snow surface with vertical tree trunks, stressing the role of the bark at snow level as triggering the snow melt. Measurement of s by field sampling in two forested sites in central Switzerland yielded values ranging from 1.8 to 2.1.

  18. 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

  19. Snow White Trench (Animation)

    Science.gov (United States)

    2008-01-01

    [figure removed for brevity, see original site] Click on image for animation This animation shows the evolution of the trench called 'Snow White' that NASA's Phoenix Mars Lander began digging on the 22nd Martian day of the mission after the May 25, 2008, landing. 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.

  20. Snow accretion on overhead wires

    Energy Technology Data Exchange (ETDEWEB)

    Sakamoto, Y. [Meteorological Research Inst. for Technology Co. Ltd., Tokyo (Japan); Tachizaki, S.; Sudo, N. [Tohoku Electric Power Co. Ltd., Miyagi (Japan)

    2005-07-01

    Wet snow accretion can cause extensive damage to transmission systems. This paper reviewed some of the difficulties faced by researchers in the study of wet snow accretion on overhead lines in Japan. The study of snow accretion phenomena is complicated by the range of phase changes in water. Snowflakes produced in an upper atmospheric layer with a temperature below freezing do not melt when they go through a lower atmospheric layer with a temperature above freezing, but are in a mixed state of solid and liquid due to the latent heat of melting. The complicated properties of water make studies of snow accretion difficult, as well as the fact that snow changes its physical properties rapidly, due to the effects of ambient temperature, rainfall, and solar radiation. The adhesive forces that cause snow accretion include freezing; bonding through freezing; sintering; condensation and freezing of vapor in the air; mechanical intertwining of snowflakes; capillary action due to liquids; coherent forces between ice particles and water formed through the metamorphosis of snowflakes. In addition to these complexities, differences in laboratory room environments and natural snow environments can also pose difficulties for researchers. Equations describing the relationship between the density of accreted snow and the meteorological parameters involved were presented, as well as empirical equations which suggested that snow accretion efficiency has a dependency on air temperature. An empirical model for estimating snow loads in Japan was outlined, as well as various experiments observing show shedding. Correlations for wet snow accretion included precipitation intensity; duration of precipitation; air temperature; wind speed and wind direction in relation to the overhead line. Issues concerning topography and wet snow accretion were reviewed. It was concluded that studies of snow accretion will benefit by the collection of data in each matrix of the relevant parameters. 12 refs

  1. Influence of snow cover changes on surface radiation and heat balance based on the WRF model

    Science.gov (United States)

    Yu, Lingxue; Liu, Tingxiang; Bu, Kun; Yang, Jiuchun; Chang, Liping; Zhang, Shuwen

    2016-07-01

    The snow cover extent in mid-high latitude areas of the Northern Hemisphere has significantly declined corresponding to the global warming, especially since the 1970s. Snow-climate feedbacks play a critical role in regulating the global radiation balance and influencing surface heat flux exchange. However, the degree to which snow cover changes affect the radiation budget and energy balance on a regional scale and the difference between snow-climate and land use/cover change (LUCC)-climate feedbacks have been rarely studied. In this paper, we selected Heilongjiang Basin, where the snow cover has changed obviously, as our study area and used the WRF model to simulate the influences of snow cover changes on the surface radiation budget and heat balance. In the scenario simulation, the localized surface parameter data improved the accuracy by 10 % compared with the control group. The spatial and temporal analysis of the surface variables showed that the net surface radiation, sensible heat flux, Bowen ratio, temperature and percentage of snow cover were negatively correlated and that the ground heat flux and latent heat flux were positively correlated with the percentage of snow cover. The spatial analysis also showed that a significant relationship existed between the surface variables and land cover types, which was not obviously as that for snow cover changes. Finally, six typical study areas were selected to quantitatively analyse the influence of land cover types beneath the snow cover on heat absorption and transfer, which showed that when the land was snow covered, the conversion of forest to farmland can dramatically influence the net radiation and other surface variables, whereas the snow-free land showed significantly reduced influence. Furthermore, compared with typical land cover changes, e.g., the conversion of forest into farmland, the influence of snow cover changes on net radiation and sensible heat flux were 60 % higher than that of land cover changes

  2. Between a rock and a hard place: habitat selection in female-calf humpback whale (Megaptera novaeangliae) Pairs on the Hawaiian breeding grounds.

    Science.gov (United States)

    Cartwright, Rachel; Gillespie, Blake; Labonte, Kristen; Mangold, Terence; Venema, Amy; Eden, Kevin; Sullivan, Matthew

    2012-01-01

    The Au'au Channel between the islands of Maui and Lanai, Hawaii comprises critical breeding habitat for humpback whales (Megaptera novaeangliae) of the Central North Pacific stock. However, like many regions where marine mega-fauna gather, these waters are also the focus of a flourishing local eco-tourism and whale watching industry. Our aim was to establish current trends in habitat preference in female-calf humpback whale pairs within this region, focusing specifically on the busy, eastern portions of the channel. We used an equally-spaced zigzag transect survey design, compiled our results in a GIS model to identify spatial trends and calculated Neu's Indices to quantify levels of habitat use. Our study revealed that while mysticete female-calf pairs on breeding grounds typically favor shallow, inshore waters, female-calf pairs in the Au'au Channel avoided shallow waters (whale breeding grounds, there was only minimal evidence of typical patterns of stratification or segregation according to group composition. A review of habitat use by maternal females across Hawaiian waters indicates that maternal habitat choice varies between localities within the Hawaiian Islands, suggesting that maternal females alter their use of habitat according to locally varying pressures. This ability to respond to varying environments may be the key that allows wildlife species to persist in regions where human activity and critical habitat overlap.

  3. Molecular hardness and softness, local hardness and softness, hardness and softness kernels, and relations among these quantities

    Science.gov (United States)

    Berkowitz, Max; Parr, Robert G.

    1988-02-01

    Hardness and softness kernels η(r,r') and s(r,r') are defined for the ground state of an atomic or molecular electronic system, and the previously defined local hardness and softness η(r) and s(r) and global hardness and softness η and S are obtained from them. The physical meaning of s(r), as a charge capacitance, is discussed (following Huheey and Politzer), and two alternative ``hardness'' indices are identified and briefly discussed.

  4. 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.

  5. Anisotropy of seasonal snow measured by polarimetric phase differences in radar time series

    Science.gov (United States)

    Leinss, Silvan; Löwe, Henning; Proksch, Martin; Lemmetyinen, Juha; Wiesmann, Andreas; Hajnsek, Irena

    2016-08-01

    The snow microstructure, i.e., the spatial distribution of ice and pores, generally shows an anisotropy which is driven by gravity and temperature gradients and commonly determined from stereology or computer tomography. This structural anisotropy induces anisotropic mechanical, thermal, and dielectric properties. We present a method based on radio-wave birefringence to determine the depth-averaged, dielectric anisotropy of seasonal snow with radar instruments from space, air, or ground. For known snow depth and density, the birefringence allows determination of the dielectric anisotropy by measuring the copolar phase difference (CPD) between linearly polarized microwaves propagating obliquely through the snowpack. The dielectric and structural anisotropy are linked by Maxwell-Garnett-type mixing formulas. The anisotropy evolution of a natural snowpack in Northern Finland was observed over four winters (2009-2013) with the ground-based radar instrument "SnowScat". The radar measurements indicate horizontal structures for fresh snow and vertical structures in old snow which is confirmed by computer tomographic in situ measurements. The temporal evolution of the CPD agreed in ground-based data compared to space-borne measurements from the satellite TerraSAR-X. The presented dataset provides a valuable basis for the development of new snow metamorphism models which include the anisotropy of the snow microstructure.

  6. Between a rock and a hard place: habitat selection in female-calf humpback whale (Megaptera novaeangliae Pairs on the Hawaiian breeding grounds.

    Directory of Open Access Journals (Sweden)

    Rachel Cartwright

    Full Text Available The Au'au Channel between the islands of Maui and Lanai, Hawaii comprises critical breeding habitat for humpback whales (Megaptera novaeangliae of the Central North Pacific stock. However, like many regions where marine mega-fauna gather, these waters are also the focus of a flourishing local eco-tourism and whale watching industry. Our aim was to establish current trends in habitat preference in female-calf humpback whale pairs within this region, focusing specifically on the busy, eastern portions of the channel. We used an equally-spaced zigzag transect survey design, compiled our results in a GIS model to identify spatial trends and calculated Neu's Indices to quantify levels of habitat use. Our study revealed that while mysticete female-calf pairs on breeding grounds typically favor shallow, inshore waters, female-calf pairs in the Au'au Channel avoided shallow waters (<20 m and regions within 2 km of the shoreline. Preferred regions for female-calf pairs comprised water depths between 40-60 m, regions of rugged bottom topography and regions that lay between 4 and 6 km from a small boat harbor (Lahaina Harbor that fell within the study area. In contrast to other humpback whale breeding grounds, there was only minimal evidence of typical patterns of stratification or segregation according to group composition. A review of habitat use by maternal females across Hawaiian waters indicates that maternal habitat choice varies between localities within the Hawaiian Islands, suggesting that maternal females alter their use of habitat according to locally varying pressures. This ability to respond to varying environments may be the key that allows wildlife species to persist in regions where human activity and critical habitat overlap.

  7. Modelling the snowmelt and the snow water equivalent by creating a simplified energy balance conceptual snow model

    Science.gov (United States)

    Riboust, Philippe; Thirel, Guillaume; Le Moine, Nicolas; Ribstein, Pierre

    2016-04-01

    A better knowledge of the accumulated snow on the watersheds will help flood forecasting centres and hydro-power companies to predict the amount of water released during spring snowmelt. Since precipitations gauges are sparse at high elevations and integrative measurements of the snow accumulated on watershed surface are hard to obtain, using snow models is an adequate way to estimate snow water equivalent (SWE) on watersheds. In addition to short term prediction, simulating accurately SWE with snow models should have many advantages. Validating the snow module on both SWE and snowmelt should give a more reliable model for climate change studies or regionalization for ungauged watersheds. The aim of this study is to create a new snow module, which has a structure that allows the use of measured snow data for calibration or assimilation. Energy balance modelling seems to be the logical choice for designing a model in which internal variables, such as SWE, could be compared to observations. Physical models are complex, needing high computational resources and many different types of inputs that are not widely measured at meteorological stations. At the opposite, simple conceptual degree-day models offer to simulate snowmelt using only temperature and precipitation as inputs with fast computing. Its major drawback is to be empirical, i.e. not taking into account all of the processes of the energy balance, which makes this kind of model more difficult to use when willing to compare SWE to observed measurements. In order to reach our objectives, we created a snow model structured by a simplified energy balance where each of the processes is empirically parameterized in order to be calculated using only temperature, precipitation and cloud cover variables. This model's structure is similar to the one created by M.T. Walter (2005), where parameterizations from the literature were used to compute all of the processes of the energy balance. The conductive fluxes into the

  8. Snow cover detection algorithm using dynamic time warping method and reflectances of MODIS solar spectrum channels

    Science.gov (United States)

    Lee, Kyeong-sang; Choi, Sungwon; Seo, Minji; Lee, Chang suk; Seong, Noh-hun; Han, Kyung-Soo

    2016-10-01

    Snow cover is biggest single component of cryosphere. The Snow is covering the ground in the Northern Hemisphere approximately 50% in winter season and is one of climate factors that affects Earth's energy budget because it has higher reflectance than other land types. Also, snow cover has an important role about hydrological modeling and water resource management. For this reason, accurate detection of snow cover acts as an essential element for regional water resource management. Snow cover detection using satellite-based data have some advantages such as obtaining wide spatial range data and time-series observations periodically. In the case of snow cover detection using satellite data, the discrimination of snow and cloud is very important. Typically, Misclassified cloud and snow pixel can lead directly to error factor for retrieval of satellite-based surface products. However, classification of snow and cloud is difficult because cloud and snow have similar optical characteristics and are composed of water or ice. But cloud and snow has different reflectance in 1.5 1.7 μm wavelength because cloud has lower grain size and moisture content than snow. So, cloud and snow shows difference reflectance patterns change according to wavelength. Therefore, in this study, we perform algorithm for classifying snow cover and cloud with satellite-based data using Dynamic Time Warping (DTW) method which is one of commonly used pattern analysis such as speech and fingerprint recognitions and reflectance spectral library of snow and cloud. Reflectance spectral library is constructed in advance using MOD21km (MODIS Level1 swath 1km) data that their reflectance is six channels including 3 (0.466μm), 4 (0.554μm), 1 (0.647μm), 2 (0.857μm), 26 (1.382μm) and 6 (1.629μm). We validate our result using MODIS RGB image and MOD10 L2 swath (MODIS swath snow cover product). And we use PA (Producer's Accuracy), UA (User's Accuracy) and CI (Comparison Index) as validation criteria

  9. Toward mountains without permanent snow and ice

    Science.gov (United States)

    Huss, M.; Bookhagen, B.; Huggel, C.; Jacobsen, D.; Bradley, R. S.; Clague, J. J.; Vuille, M.; Buytaert, W.; Cayan, D. R.; Greenwood, G.; Mark, B. G.; Milner, A. M.; Weingartner, R.; Winder, M.

    2017-05-01

    The cryosphere in mountain regions is rapidly declining, a trend that is expected to accelerate over the next several decades due to anthropogenic climate change. A cascade of effects will result, extending from mountains to lowlands with associated impacts on human livelihood, economy, and ecosystems. With rising air temperatures and increased radiative forcing, glaciers will become smaller and, in some cases, disappear, the area of frozen ground will diminish, the ratio of snow to rainfall will decrease, and the timing and magnitude of both maximum and minimum streamflow will change. These changes will affect erosion rates, sediment, and nutrient flux, and the biogeochemistry of rivers and proglacial lakes, all of which influence water quality, aquatic habitat, and biotic communities. Changes in the length of the growing season will allow low-elevation plants and animals to expand their ranges upward. Slope failures due to thawing alpine permafrost, and outburst floods from glacier- and moraine-dammed lakes will threaten downstream populations. Societies even well beyond the mountains depend on meltwater from glaciers and snow for drinking water supplies, irrigation, mining, hydropower, agriculture, and recreation. Here, we review and, where possible, quantify the impacts of anticipated climate change on the alpine cryosphere, hydrosphere, and biosphere, and consider the implications for adaptation to a future of mountains without permanent snow and ice.

  10. Spatial estimates of snow water equivalent from reconstruction

    Science.gov (United States)

    Rittger, Karl; Bair, Edward H.; Kahl, Annelen; Dozier, Jeff

    2016-08-01

    Operational ground-based measurements of snow water equivalent (SWE) do not adequately explain spatial variability in mountainous terrain. To address this problem, we combine satellite-based retrievals of fractional snow cover for the period 2000 to 2011 with spatially distributed energy balance calculations to reconstruct SWE values throughout each melt season in the Sierra Nevada of California. Modeled solar radiation, longwave radiation, and air temperature from NLDAS drive the snowmelt model. The modeled solar radiation compares well to ground observations, but modeled longwave radiation is slightly lower than observations. Validation of reconstructed SWE with snow courses and our own snow surveys shows that the model can accurately estimate SWE at the sampled locations in a variety of topographic settings for a range of wet to dry years. The relationships of SWE with elevation and latitude are significantly different for wet, mean and dry years as well as between drainages. In all the basins studied, the relationship between remaining SWE and snow-covered area (SCA) becomes increasingly correlated from March to July as expected because SCA is an important model input. Though the SWE is calculated retrospectively SCA observations are available in near-real time and combined with historical reconstructions may be sufficient for estimating SWE with more confidence as the melt season progresses.

  11. The assessment of EUMETSAT HSAF Snow Products for mountainuos areas in the eastern part of Turkey

    Science.gov (United States)

    Akyurek, Z.; Surer, S.; Beser, O.; Bolat, K.; Erturk, A. G.

    2012-04-01

    Monitoring the snow parameters (e.g. snow cover area, snow water equivalent) is a challenging work. Because of its natural physical properties, snow highly affects the evolution of weather from daily basis to climate on a longer time scale. The derivation of snow products over mountainous regions has been considered very challenging. This can be done by periodic and precise mapping of the snow cover. However inaccessibility and scarcity of the ground observations limit the snow cover mapping in the mountainous areas. Today, it is carried out operationally by means of optical satellite imagery and microwave radiometry. In retrieving the snow cover area from satellite images bring the problem of topographical variations within the footprint of satellite sensors and spatial and temporal variation of snow characteristics in the mountainous areas. Most of the global and regional operational snow products use generic algorithms for flat and mountainous areas. However the non-uniformity of the snow characteristics can only be modeled with different algorithms for mountain and flat areas. In this study the early findings of Satellite Application Facilities on Hydrology (H-SAF) project, which is financially supported by EUMETSAT, will be presented. Turkey is a part of the H-SAF project, both in product generation (eg. snow recognition, fractional snow cover and snow water equivalent) for mountainous regions for whole Europe, cal/val of satellite-derived snow products with ground observations and cal/val studies with hydrological modeling in the mountainous terrain of Europe. All the snow products are operational on a daily basis. For the snow recognition product (H10) for mountainous areas, spectral thresholding methods were applied on sub pixel scale of MSG-SEVIRI images. The different spectral characteristics of cloud, snow and land determined the structure of the algorithm and these characteristics were obtained from subjective classification of known snow cover features

  12. Tool and Method for Testing the Resistance of the Snow Road Cover to Destruction

    Science.gov (United States)

    Zhelykevich, R.; Lysyannikov, A.; Kaiser, Yu; Serebrenikova, Yu; Lysyannikova, N.; Shram, V.; Kravtsova, Ye; Plakhotnikova, M.

    2016-06-01

    The paper presents the design of the tool for efficient determination of the hardness of the snow road coating. The tool increases vertical positioning of the rod with the tip through replacement of the rod slide friction of the ball element by roll friction of its outer bearing race in order to enhance the accuracy of determining the hardness of the snow-ice road covering. A special feature of the tool consists in possibility of creating different impact energy by the change of the lifting height of the rod with the tip (indenter) and the exchangeable load mass. This allows the study of the influence of the tip shape and the impact energy on the snow strength parameters in a wide range, extends the scope of application of the durometer and makes possible to determine the strength of snow-ice formations by indenters with various geometrical parameters depending on climatic conditions.

  13. Local and regional variability in snow conditions in northern Finland: A reindeer herding perspective.

    Science.gov (United States)

    Rasmus, Sirpa; Kivinen, Sonja; Bavay, Mathias; Heiskanen, Janne

    2016-05-01

    Weather station measurements were used to force the SNOWPACK snow model and combined with reindeer herders' experiences to study the local and regional variations in snow conditions in a Finnish reindeer herding area for the 1981-2010 period. Winter conditions varied significantly between the four selected herding districts and between open and forest environments within the districts. The highest snow depths and densities, the thicknesses of ground ice, and the lengths of snow cover period were generally found in the northernmost districts. The snow depths showed the strongest regional coherence, whereas the thicknesses of ground ice were weakly correlated among the districts. The local variation in snow depths was higher than the regional variation and limits for rare or exceptional events varied notably between different districts and environments. The results highlight that forests diversify snow and foraging conditions, e.g., ground ice rarely forms simultaneously in different environments. Sufficient and diverse forest pastures are important during the critical winter season if reindeer herding is pursued on natural grazing grounds also in the future.

  14. 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....

  15. '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.

  16. Phoenix's Snow White Trench

    Science.gov (United States)

    2008-01-01

    A soil sample taken from the informally named 'Snow White' trench at NASA's Phoenix Mars Lander work site produced minerals that indicate evidence of past interaction between the minerals and liquid water. This image was taken by the Surface Stereo Imager on Sol 103, the 103rd day since landing (Sept. 8, 2008). The trench is approximately 23 centimeters (9 inches) long. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by JPL, Pasadena, Calif. Spacecraft development was by Lockheed Martin Space Systems, Denver.

  17. Between a Rock and a Hard Place: Habitat Selection in Female-Calf Humpback Whale (Megaptera novaeangliae) Pairs on the Hawaiian Breeding Grounds

    Science.gov (United States)

    Cartwright, Rachel; Gillespie, Blake; LaBonte, Kristen; Mangold, Terence; Venema, Amy; Eden, Kevin; Sullivan, Matthew

    2012-01-01

    The Au'au Channel between the islands of Maui and Lanai, Hawaii comprises critical breeding habitat for humpback whales (Megaptera novaeangliae) of the Central North Pacific stock. However, like many regions where marine mega-fauna gather, these waters are also the focus of a flourishing local eco-tourism and whale watching industry. Our aim was to establish current trends in habitat preference in female-calf humpback whale pairs within this region, focusing specifically on the busy, eastern portions of the channel. We used an equally-spaced zigzag transect survey design, compiled our results in a GIS model to identify spatial trends and calculated Neu's Indices to quantify levels of habitat use. Our study revealed that while mysticete female-calf pairs on breeding grounds typically favor shallow, inshore waters, female-calf pairs in the Au'au Channel avoided shallow waters (Hawaiian waters indicates that maternal habitat choice varies between localities within the Hawaiian Islands, suggesting that maternal females alter their use of habitat according to locally varying pressures. This ability to respond to varying environments may be the key that allows wildlife species to persist in regions where human activity and critical habitat overlap. PMID:22666432

  18. Photographic Snow-cover Monitoring on St Sorlin Glacier, France.

    Science.gov (United States)

    Gerbaux, M.; Genthon, C.; Dedieu, J.; Balestrieri, J.

    2004-12-01

    Like most other glaciers in the Alps, the St Sorlin glacier (french Alps, 45.16°N, 6.16°E, 2900 m asl mean elevation and 3km2 of surface area) has been retreating fast in the last 20 years. To understand the meteorological factors responsible for this retreat, and to tentatively predict glaciers evolution in a changing (warming) climate, we use a distributed snow/ice mass and energy balance model derived from the CROCUS snow model (Météo-France). There is no direct meteorological observation on or near St Sorlin glacier yet, and hourly meteorology to force the snow/ice model is obtained from disaggregated meteorological analyses. The model is found to reproduce the St Sorlin mass balance of the last 20 years as obtained from field glaciological measurements and stereophotographic reconstructions. The model is also found to reproduce the interannual variations of the equilibrium line as determined from optical satellite imagery. Because of the albedo feedback involved, it is also important to verify that the summer snow/ice transition on the glacier is correctly simulated. Thus, an automated photographic system was set up facing St Sorlin glacier to monitor the evolution of the snow cover. The system was installed on the 13th of July 2004 and is still in operation at time of abstract writing. Digital photographies are taken every 4 hours, permitting so far at least one non-obstructed (rain, fog) picture per day. The first pictures in the series show an almost fully snow-covered glacier while the latest ones show bare ice up to the highest parts of the glacier. Snow is occasionally deposited during precipitation events but hardly last more than 3 days. Snow line position is deduced from pictures using a DEM with georeferenced points visible on pictures. It should then be compared with the modelled one. The automated photographic system provides not only snow cover to check snow/ice model results at seasonal time-scales, but also qualitative meteorological

  19. Using Commercial Digital Cameras and Structure-for-Motion Software to Map Snow Cover Depth from Small Aircraft

    Science.gov (United States)

    Sturm, M.; Nolan, M.; Larsen, C. F.

    2014-12-01

    A long-standing goal in snow hydrology has been to map snow cover in detail, either mapping snow depth or snow water equivalent (SWE) with sub-meter resolution. Airborne LiDAR and air photogrammetry have been used successfully for this purpose, but both require significant investments in equipment and substantial processing effort. Here we detail a relatively inexpensive and simple airborne photogrammetric technique that can be used to measure snow depth. The main airborne hardware consists of a consumer-grade digital camera attached to a survey-quality, dual-frequency GPS. Photogrammetric processing is done using commercially available Structure from Motion (SfM) software that does not require ground control points. Digital elevation models (DEMs) are made from snow-free acquisitions in the summer and snow-covered acquisitions in winter, and the maps are then differenced to arrive at snow thickness. We tested the accuracy and precision of snow depths measured using this system through 1) a comparison with airborne scanning LiDAR, 2) a comparison of results from two independent and slightly different photogrameteric systems, and 3) comparison to extensive on-the-ground measured snow depths. Vertical accuracy and precision are on the order of +/-30 cm and +/- 8 cm, respectively. The accuracy can be made to approach that of the precision if suitable snow-free ground control points exists and are used to co-register summer to winter DEM maps. Final snow depth accuracy from our series of tests was on the order of ±15 cm. This photogrammetric method substantially lowers the economic and expertise barriers to entry for mapping snow.

  20. Changes in Snow Cover Characteristics over Northern Eurasia since 1966

    Science.gov (United States)

    Bulygina, Olga; Groisman, Pavel; Razuvaev, Vyacheslav; Korshunova, Natalia

    2010-05-01

    metamorphosis on its surface changing snow albedo and generating snow crust as well as on its bottom generating ice crust. Once formed, the crusts will not disappear until complete snowmelt. These crusts have numerous modes of impact on the wild birds and animals in the Arctic environment as well as on domesticated reindeers. In extreme cases, the crusts may kill some wild species and prevent reindeers' migration and feeding. In the temperate zone, the ice crust can affect the winter crop yield. The warming and earlier snowmelt worldwide signal that the 'shoulder' spring period when ice crust remains on the ground may shorten. However, earlier and more frequent thaw occurrence may cause an opposite tendency and lengthen the period with the ice crust. Our study reveals substantial changes in the snow and ice crust characteristics that have practical importance for wildlife and human activity in the Arctic as well as in the major agricultural regions of Russia. Among the two competing factors that can cause a systematic change in the ice crust characteristics over the humid half of Northern Eurasia, i.e., the increase in thaws due to strong regional warming and a potential shortening of the period of snowmelt, the second factor appeared to be more significant during the past 43 years. In particular, the entire process of the spring snowmelt has become shorter in duration and (taking into account a parallel rise in the snow depth across most of Russia) more intense. This might contribute to increasing frequencies and severity of spring floods, and require further studies.

  1. The use of remotely-sensed canopy variables and ultrasonic snow depth sensors to improve the understanding of forest - snow interactions (Invited)

    Science.gov (United States)

    Varhola, A.; Coops, N.; Teti, P.; Weiler, M.

    2013-12-01

    Current methods to estimate snow accumulation and ablation at the plot and watershed levels can be improved as new technologies offer alternative approaches to more accurately monitor snow dynamics and their drivers. Here we conduct a meta-analysis of snow and vegetation data collected in British Columbia to explore the relationships between a wide range of forest structure variables --obtained from Light Detection and Ranging (LiDAR), hemispherical photography (HP) and Landsat Thematic Mapper-- and several indicators of snow accumulation and ablation estimated from manual snow surveys and ultrasonic range sensors. By merging and standardizing all the ground plot information available in the study area, we demonstrate how LiDAR-derived forest cover above 0.5 m was the variable explaining the highest percentage of absolute peak snow water equivalent (SWE) (33%), while HP-derived leaf area index and gap fraction (45° angle of view) were the best potential predictors of snow ablation rate (SAR) (explaining 57% of variance). This study reveals how continuous SWE data from ultrasonic sensors are fundamental to obtain statistically-significant relationships between snow indicators and structural metrics by increasing mean coefficient of determination by 20% when compared to manual surveys. The relationships between vegetation and some spectral indices from Landsat and snow indicators, not explored before, were almost as high as those shown by LiDAR or HP and thus point towards a new line of research with important practical implications. While the use of different data sources from two snow seasons prevented us from developing models with predictive capacity, a large sample size allowed us to identify outliers that weakened the relationships and suggest improvements for future research. A concise overview of the limitations of this and previous studies is provided along with propositions to consistently improve experimental designs to take advantage of remote sensing

  2. Snow multivariable data assimilation for hydrological predictions in mountain areas

    Science.gov (United States)

    Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

    2016-04-01

    The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, 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 observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. 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, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground

  3. Impact Analysis of Climate Change on Snow over a Complex Mountainous Region Using Weather Research and Forecast Model (WRF Simulation and Moderate Resolution Imaging Spectroradiometer Data (MODIS-Terra Fractional Snow Cover Products

    Directory of Open Access Journals (Sweden)

    Xiaoduo Pan

    2017-07-01

    Full Text Available Climate change has a complex effect on snow at the regional scale. The change in snow patterns under climate change remains unknown for certain regions. Here, we used high spatiotemporal resolution snow-related variables simulated by a weather research and forecast model (WRF including snowfall, snow water equivalent and snow depth along with fractional snow cover (FSC data extracted from Moderate Resolution Imaging Spectroradiometer Data (MODIS-Terra to evaluate the effects of climate change on snow over the Heihe River Basin (HRB, a typical inland river basin in arid northwestern China from 2000 to 2013. We utilized Empirical Orthogonal Function (EOF analysis and Mann-Kendall/Theil-Sen trend analysis to evaluate the results. The results are as follows: (1 FSC, snow water equivalent, and snow depth across the entire HRB region decreased, especially at elevations over 4500 m; however, snowfall increased at mid-altitude ranges in the upstream area of the HRB. (2 Total snowfall also increased in the upstream area of the HRB; however, the number of snowfall days decreased. Therefore, the number of extreme snow events in the upstream area of the HRB may have increased. (3 Snowfall over the downstream area of the HRB decreased. Thus, ground stations, WRF simulations and remote sensing products can be used to effectively explore the effect of climate change on snow at the watershed scale.

  4. Estimating snow depth in real time using unmanned aerial vehicles

    Science.gov (United States)

    Niedzielski, Tomasz; Mizinski, Bartlomiej; Witek, Matylda; Spallek, Waldemar; Szymanowski, Mariusz

    2016-04-01

    In frame of the project no. LIDER/012/223/L-5/13/NCBR/2014, financed by the National Centre for Research and Development of Poland, we elaborated a fully automated approach for estimating snow depth in real time in the field. The procedure uses oblique aerial photographs taken by the unmanned aerial vehicle (UAV). The geotagged images of snow-covered terrain are processed by the Structure-from-Motion (SfM) method which is used to produce a non-georeferenced dense point cloud. The workflow includes the enhanced RunSFM procedure (keypoint detection using the scale-invariant feature transform known as SIFT, image matching, bundling using the Bundler, executing the multi-view stereo PMVS and CMVS2 software) which is preceded by multicore image resizing. The dense point cloud is subsequently automatically georeferenced using the GRASS software, and the ground control points are borrowed from positions of image centres acquired from the UAV-mounted GPS receiver. Finally, the digital surface model (DSM) is produced which - to improve the accuracy of georeferencing - is shifted using a vector obtained through precise geodetic GPS observation of a single ground control point (GCP) placed on the Laboratory for Unmanned Observations of Earth (mobile lab established at the University of Wroclaw, Poland). The DSM includes snow cover and its difference with the corresponding snow-free DSM or digital terrain model (DTM), following the concept of the digital elevation model of differences (DOD), produces a map of snow depth. Since the final result depends on the snow-free model, two experiments are carried out. Firstly, we show the performance of the entire procedure when the snow-free model reveals a very high resolution (3 cm/px) and is produced using the UAV-taken photographs and the precise GCPs measured by the geodetic GPS receiver. Secondly, we perform a similar exercise but the 1-metre resolution light detection and ranging (LIDAR) DSM or DTM serves as the snow-free model

  5. C-Band SAR Imagery for Snow-Cover Monitoring at Treeline, Churchill, Manitoba, Canada

    Directory of Open Access Journals (Sweden)

    Frédérique C. Pivot

    2012-07-01

    Full Text Available RADARSAT and ERS-2 data collected at multiple incidence angles are used to characterize the seasonal variations in the backscatter of snow-covered landscapes in the northern Hudson Bay Lowlands during the winters of 1997/98 and 1998/99. The study evaluates the usefulness of C-band SAR systems for retrieving the snow water equivalent under dry snow conditions in the forest–tundra ecotone. The backscatter values are compared against ground measurements at six sampling sites, which are taken to be representative of the land-cover types found in the region. The contribution of dry snow to the radar return is evident when frost penetrates the first 20 cm of soil. Only then does the backscatter respond positively to changes in snow water equivalent, at least in the open and forested areas near the coast, where 1-dB increases in backscatter for each approximate 5–10 mm of accumulated water equivalent are observed at 20–31° incidence angles. Further inland, the backscatter shows either no change or a negative change with snow accumulation, which suggests that the radar signal there is dominated by ground surface scattering (e.g., fen when not attenuated by vegetation (e.g., forested and transition. With high-frequency ground-penetrating radar, we demonstrate the presence of a 10–20-cm layer of black ice underneath the snow cover, which causes the reduced radar returns (−15 dB and less observed in the inland fen. A correlation between the backscattering and the snow water equivalent cannot be determined due to insufficient observations at similar incidence angles. To establish a relationship between the snow water equivalent and the backscatter, only images acquired with similar incidence angles should be used, and they must be corrected for both vegetation and ground effects.

  6. HONO emissions from snow surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Beine, Harry; Colussi, AgustIn J; Hoffmann, Michael R [California Institute of Technology, Environmental Science and Engineering, Pasadena, CA (United States); Amoroso, Antonio; Esposito, Giulio; Montagnoli, Mauro [Consiglio Nazionale delle Ricerche-Istituto Inquinamento Atmosferico (CNR-IIA), Roma (Italy)], E-mail: hbeine@ucdavis.edu

    2008-10-15

    Photochemical production of NO{sub x} and HONO from surface snow can significantly impact the NO{sub x}, OH, and O{sub 3} budgets in the overlying atmosphere. NO{sub x} production is driven by the solar photolysis of NO{sub 3}{sup -} within or at the surface of snowpacks. HONO, however, is a secondary species that involves H-atom transfer between natural donors and photogenerated NO{sub 2}. Here we investigate the mechanism of HONO generation in snowpacks by exploring how its emissions respond to on-and-off illumination and temperature cycles, and to the addition of various snow dopants. The presence of humic substances within or at the surface of the snowpack significantly enhances, and may be an essential requisite for HONO production. Emission fluxes of NO, NO{sub 2}, and HONO from snow surfaces were measured under controlled temperature, ozone mixing ratio and actinic flux conditions. We used natural mid-latitude surface snow as the snow substrate. Their combined peak emission fluxes reached up to {approx}3 x 10{sup 10} molecules cm{sup -2} s{sup -1}, {approx}10{sup 3} times larger than typical emissions from polar snowpacks. Less than 1% of available N was released in these experiments. We report significant post-irradiation HONO emissions from the snow. Present results indicate a strong, direct correlation between HONO emissions and the HULIS (humic-like substances) content of the snow surface.

  7. 'Snow White' Trench After Scraping (Stereo View)

    Science.gov (United States)

    2008-01-01

    This 3D view from the Surface Stereo Imager on NASA's Phoenix Mars Lander shows the trench informally named 'Snow White.' This anaglyph was taken after a series of scrapings by the lander's Robotic Arm on the 58th Martian day, or sol, of the mission (July 23, 2008). The scrapings were done in preparation for collecting a sample for analysis from a hard subsurface layer where soil may contain frozen water. The trench is 4 to 5 centimeters (about 2 inches) deep, about 23 centimeters (9 inches) wide and about 60 centimeters (24 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.

  8. Standard hardness conversion tables for metals relationship among brinell hardness, vickers hardness, rockwell hardness, superficial hardness, knoop hardness, and scleroscope hardness

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    2007-01-01

    1.1 Conversion Table 1 presents data in the Rockwell C hardness range on the relationship among Brinell hardness, Vickers hardness, Rockwell hardness, Rockwell superficial hardness, Knoop hardness, and Scleroscope hardness of non-austenitic steels including carbon, alloy, and tool steels in the as-forged, annealed, normalized, and quenched and tempered conditions provided that they are homogeneous. 1.2 Conversion Table 2 presents data in the Rockwell B hardness range on the relationship among Brinell hardness, Vickers hardness, Rockwell hardness, Rockwell superficial hardness, Knoop hardness, and Scleroscope hardness of non-austenitic steels including carbon, alloy, and tool steels in the as-forged, annealed, normalized, and quenched and tempered conditions provided that they are homogeneous. 1.3 Conversion Table 3 presents data on the relationship among Brinell hardness, Vickers hardness, Rockwell hardness, Rockwell superficial hardness, and Knoop hardness of nickel and high-nickel alloys (nickel content o...

  9. Snow optical properties at Dome C (Concordia, Antarctica; implications for snow emissions and snow chemistry of reactive nitrogen

    Directory of Open Access Journals (Sweden)

    J. L. France

    2011-09-01

    Full Text Available Measurements of e-folding depth, nadir reflectivity and stratigraphy of the snowpack around Concordia station (Dome C, 75.10° S, 123.31° E were undertaken to determine wavelength dependent coefficients (350 nm to 550 nm for light scattering and absorption and to calculate potential fluxes (depth-integrated production rates of nitrogen dioxide (NO2 from the snowpack due to nitrate photolysis within the snowpack. The stratigraphy of the top 80 cm of Dome C snowpack generally consists of three main layers:- a surface of soft windpack (not ubiquitous, a hard windpack, and a hoar-like layer beneath the windpack(s. The e-folding depths are ~10 cm for the two windpack layers and ~20 cm for the hoar-like layer for solar radiation at a wavelength of 400 nm; about a factor 2–4 larger than previous model estimates for South Pole. The absorption cross-section due to impurities in each snowpack layer are consistent with a combination of absorption due to black carbon and HULIS (HUmic LIke Substances, with amounts of 1–2 ng g−1 of black carbon for the surface snow layers. Depth-integrated photochemical production rates of NO2 in the Dome C snowpack were calculated as 5.3 × 1012 molecules m−2 s−1, 2.3 × 1012 molecules m−2 s−1 and 8 × 1011 molecules m−2 s−1 for clear skies and solar zenith angles of 60°, 70° and 80° respectively using the TUV-snow radiative-transfer model. Depending upon the snowpack stratigraphy, a minimum of 85% of the NO2 may originate from the top 20 cm of the Dome C snowpack. It is found that on a multi-annual time-scale photolysis can remove up to 80% of nitrate from surface snow, confirming independent isotopic evidence that photolysis is an important driver of nitrate loss occurring in the EAIS (East Antarctic Ice Sheet snowpack. However, the model cannot

  10. Snow cover and permafrost evolution in Siberia as simulated by the MGO regional climate model in the 20th and 21st centuries

    Science.gov (United States)

    Shkolnik, I. M.; Nadyozhina, E. D.; Pavlova, T. V.; Molkentin, E. K.; Semioshina, A. A.

    2010-01-01

    An approach to ground thermodynamics description using a coupled system of atmospheric regional climate and ground heat transfer models is improved by accounting for the time varying snow density. The simulations are compared to available observational analyses, and the sensitivity of the ground thermal regime to variable snow density is analysed. Projected changes of the ground thermal regime in the 21st century relative to the late 20th century are shown and compared to earlier estimates.

  11. Hartree–Fock variational bounds for ground state energy of chargeless fermions with finite magnetic moment in the presence of a hard core potential: A stable ferromagnetic state

    Indian Academy of Sciences (India)

    Sudhanshu S Jha; S D Mahanti

    2007-05-01

    We use different determinantal Hartree–Fock (HF) wave functions to calculate true variational upper bounds for the ground state energy of spin-half fermions in volume 0, with mass , electric charge zero, and magnetic moment , interacting through magnetic dipole–dipole interaction. We find that at high densities when the average interparticle distance 0 becomes small compared to the magnetic length m ≡ 22/ħ2, a ferromagnetic state with spheroidal occupation function ↑ $(\\vec{k})$, involving quadrupolar deformation, gives a lower upper bound compared to the variational energy for the uniform paramagnetic state or for the state with dipolar deformation. This system is unstable towards infinite density collapse, but we show explicitly that a suitable short-range repulsive (hard core) interaction of strength 0 and range a can stop this collapse. The existence of a stable equilibrium high density ferromagnetic state with spheroidal occupation function is possible as long as the ratio of coupling constants cm ≡ (03/2) is not very smallcompared to 1.

  12. Snow economics and the NOHRSC Snow Information System (SNOW-INFO) for the United States

    Science.gov (United States)

    Carroll, T.; Cline, D.; Berkowitz, E.; Savage, D.

    2003-04-01

    The National Operational Hydrologic Remote Sensing Center (NOHRSC) in the National Weather Service (NWS), National Oceanic and Atmospheric Administration (NOAA), provides remotely sensed and modeled snow cover products and data sets to support river and flood forecasting in the United States and also to enhance the national economy. Nationwide, on average, about 16% of the total annual precipitation occurs as snowfall. Many sectors of the U.S. economy rely on surface water from snowfall for production, including manufacturing, mining, thermoelectric power, agriculture, and others. Snow contributes 1.7 trillion annually (16%) to the Nation's gross domestic product (GDP) of 10.5 trillion. Manufacturing is by far the largest contributor to the Nation's GDP and is also the Nation's largest surface-water user. The contribution of snow to manufacturing revenue totals 1.6 trillion annually for the Nation and ranges from just a few billion dollars in the southeastern U.S. to over 200 billion each in Michigan and New York. Hydropower supplies about 10% of the electricity used in the United States, enough to serve the needs of 28 million people. Annual hydroelectric power production exceeds 250 billion kilowatt-hours with the contribution from snow exceeding 6 billion in energy revenue each year (i.e., 30% of the Nation's annual hydroelectric production of 20 billion). Seasonal snowpacks are an essential component of agricultural water supplies throughout most of the U.S. and provide much of the surface water used to irrigate over 55 million acres of U.S. farmland each year. Agriculture net revenue supported by snowmelt exceeds 33 billion annually. Surface water supplies are essential for thermoelectric power generation by coal-fired, oil-fired, and nuclear power plants. Providing about 90% of the Nation's electricity supply, thermoelectric power revenues exceed 215 billion each year while water from snow contributes about 25 billion to this revenue annually. With 1

  13. Soil moisture ground truth: Steamboat Springs, Colorado, site and Walden, Colorado, site

    Science.gov (United States)

    Jones, E. B.

    1976-01-01

    Ground-truth data taken at Steamboat Springs and Walden, Colorado in support of the NASA missions in these areas during the period March 8, 1976 through March 11, 1976 was presented. This includes the following information: snow course data for Steamboat Springs and Walden, snow pit and snow quality data for Steamboat Springs, and soil moisture report.

  14. 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.

  15. Measurement of snow depth distribution in the upper basin in the Japanese Alps using an airborne laser scanning

    Science.gov (United States)

    Suzuki, Keisuke; Sasaki, Akihiko

    2016-04-01

    In the Japanese Alps region, large amounts of precipitation in the form of snow constitute a more important water resource than rain. During the winter, precipitation that is deposited as snowfall accumulates in the river basins, and it forms natural dams known as "white dams." A quantitative understanding of snow depth distribution in these mountainous areas is important not only for evaluating water resource volume, but also for understanding the effects of snow in terms of its impact on landforms and its effect on the distribution of vegetation. However, it is not easy to perform a quantitative evaluation of snow depth distribution in mountainous areas. Several methods have been proposed for clarifying snow depth distribution. The most widely used of these is a method of inserting a sounding rod into the snow to measure its depth at each geographic position. Another method is to dig a trench in the snow and then perform an observational measurement of the side of the trench. These methods enable accurate measurement of the snow depth; however, when the snow is several meters deep, the methods may be limited by the measuring capacity of the equipment, or by the time restrictions of the survey. For these reasons, wide area measurement of the spatial distribution of snow is very difficult, and it is not suitable for investigating snow depth distribution in river basins. In recent years, a measurement technology has been developed that uses laser scanners mounted on aircraft. This method enables researchers to obtain ground surface coordinate data with high precision over a wide area from the air. Using such a scanner to measure the ground surface during snow coverage and during no snow coverage, and then finding the differences between the surface elevations, has made it possible to ascertain snow depth with high precision. Airborne laser measurement enables high-precision measurements over a wide area and in a short amount of time, and measurements can be made

  16. MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.

    2010-01-01

    Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

  17. Application of Snpp/viirs Data in Near Real-Time Supra-Snow Flood Detection

    Science.gov (United States)

    Li, S.; Sun, D.; Goldberg, M.; Sjoberg, B.; Plumb, E. W.; Holloway, E.; Lindsey, S.; Kreller, M.

    2015-12-01

    Supra-snow/ice flood is very common in high latitude areas from winter to spring break-up seasons along rivers flowing to even higher latitude areas, but this flood type doesn't draw much attention due to poor ground conditions for river watch and ground observations. Satellite data from SNPP/VIIRS (Suomi-National Polar-orbit Partnership/Visible/Infrared Imager Radiometer Suite) instead have shown great advantages in supra-snow/ice flood detection due to its large swath coverage, multiple daily observations in high latitude areas and moderate spatial resolution. Thus, methods for supra-snow/ice water detection were developed to detect near real-time supra-snow/ice floods automatically using SNPP/VIIRS imagery. The methods were mainly based on spectral features of supra-snow/ice floodwater, assisting by geometry-based algorithm and object-based algorithm to remove cloud shadows and terrain shadows over snow/ice surface. The detected supra-snow/ice floodwater was further applied in water fraction retrieval for better representation of flood extent using a modified histogram method based on linear combination model. The developed methods were successfully applied in dynamic monitoring of 2015's supra-snow/ice flood along Sag River in Alaska, which was claimed as a state disaster by Alaska state government, and further tested with more than 1000 VIIRS granules year around. Analyses through visual inspection with VIIRS false-color composite images and quantitative comparison with Landsat-8 OLI images show promising and robust performance in detection of supra-snow/ice floodwater, indicating a high feasibility for the method to be applied in operations for near real-time supra-snow/ice flood detection.

  18. Additional Contributions to the Development of the New Snow-Physics Scheme for SSiB

    Science.gov (United States)

    Mocko, David M.; Sud, Y. C.

    1999-01-01

    The Simplified Simple Biosphere Model (SSiB) had a well-documented problem with snowmelt timing and infiltration. A new snow-physics scheme was developed for use in SSIB. In this, the snow layer is separated from the soil, with its own energy budget and temperature. Solar energy reaching the top of the snowpack is divided into three parts: one, reflected by the snow; two, absorbed by the snow; and three, transmitted to the ground following a simple extinction relation. Heat is exchanged between the ground and snow by conduction and by radiation through an arbitrary air-gap between them. In the GSWP exercise using the GEWEX ISLSCP Initiative I forcing data (hereafter "offline"), it was found that the new snow scheme ameliorated a significant fraction of snowmelt time-delay as compared to observations from satellite. It also produced warmer ground temperatures under the snowpack, which allowed realistic meltwater infiltration, resulting in better simulated spring soil moisture recharge and peak runoff amount as compared to observations. An ensemble of six June-July-August (JJA) simulations for 1987 and 1988 were performed with the NASA Goddard GEOS II GCM coupled with the new snow-physics SSIB using new initial soil moisture (ISM) from the offline simulations. The GCM produced more realistic precipitation in northern regions that had large snowmelt and wetter ISM in response to better snow-physics, as compared to simulations with ISM without the new snow scheme. The new SSiB-GCM also increased the interannual precipitation signal in the Indian monsoon region, resulting from changes in ISM in the Himalayas and central Asia.

  19. Relating weak layer and slab properties to snow slope stability

    Directory of Open Access Journals (Sweden)

    J. Schweizer

    2014-07-01

    Full Text Available Snow slope stability evaluation requires considering weak layer as well as slab properties – and in particular their interaction. We developed a stability index from snow micro-penetrometer measurements and compared it to 129 concurrent point observations with the compression test (CT. The index considers the SMP-derived micro-structural strength and the additional load which depends on the hardness of the surface layers. The new quantitative measure of stability discriminated well between point observations rated as either "poor" or "fair" (CT < 19 and those rated as "good" (CT ≥ 19. However, discrimination power within the intermediate range was low. We then applied the index to gridded snow micro-penetrometer measurements from 11 snow slopes to explore the spatial structure and possibly relate it to slope stability. Stability distributions on the 11 slopes reflected various possible strength and load (stress distributions that naturally can occur. Their relation to slope stability was poor possibly because the index does not consider crack propagation. Hence, the relation between spatial patterns of point stability and slope stability remains elusive. Whereas this is the first attempt of a truly quantitative measure of stability, future developments should consider a better reference of stability and incorporate a measure of crack propagation.

  20. Importance of temporal resolution of meteorological forcings for physics-based snow modeling

    Science.gov (United States)

    Sohrabi, M.; Benjankar, R. M.; Kumar, M.; Marks, D. G.; Kormos, P.; Tonina, D.

    2015-12-01

    In alpine regions, snow delays hydrological responses to precipitation and controls initiation and length of the growing season. Therefore, precise simulations of snow accumulation and melt are crucial for understanding hydrological dynamics and predicting hydrologic response from watersheds. These predictions are important for water resource management and for ecological studies of vegetation distribution, growth and for wildlife habitat. Snow models require fine temporal resolution of meteorological inputs to capture diurnal changes. However, lack of meteorological data at fine-temporal resolution may force the use of coarser than hourly data. The objective of this work is to understand what sort of information can be lost over the watershed depending on the temporal resolution of meteorological inputs, for a range of hydroclimatic and topographic conditions. To address this goal, a spatially distributed and physics-based snow model (iSnobal) was run using 1-, 3- and 6-hourly meteorological inputs for a wet, average and a dry year over Boise River Basin (BRB), Idaho, USA. Simulated snow variables such as Snow Water Equivalent (SWE) and Surface Water Input (SWI - melt draining from the snowcover plus rain on bare ground) were averaged over 3 elevation bands including rain dominated (≤1400m), rain-snow transition (>1400 and ≤1900m) and snow dominated (>1900m). Except at the rain dominated band, using 6-hr inputs causes considerable overestimation of SWE and SWI, particularly in the wet year. The results show that at the rain-snow transition and snow dominated bands at least 3-hr meteorological data are necessary for snow modeling, due to strong diurnal changes in meteorological variables at these elevations. However, using course temporal resolution data for the rain dominated band made only a small difference in results.

  1. 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).

  2. Small-scale variation of snow in a regional permafrost model

    Directory of Open Access Journals (Sweden)

    K. Gisnås

    2016-06-01

    estimated fractions of sub-zero mean annual ground surface temperatures within ±10 %. We also find that snow distributions within areas of 1 km2 in Norwegian mountain environments are closer to a gamma than to a lognormal theoretical distribution. The modelled permafrost distribution seems to be more sensitive to the choice of distribution function than to the fine-tuning of the coefficient of variation. When incorporating the small-scale variation of snow, the modelled total permafrost area of mainland Norway is nearly twice as large compared to the area obtained with grid-cell average snow depths without a sub-grid approach.

  3. Detection of Oil in Ice and Snow

    Directory of Open Access Journals (Sweden)

    Merv Fingas

    2013-11-01

    Full Text Available The response to a major oil spill can be challenging in temperate climates and with good weather conditions. By contrast, a major spill in or under ice and snow, presents a whole new series of challenges. This paper reviews detection technologies for these challenging situations. A number of acoustic techniques have been tried in test tank situations and it was found that acoustic detection of oil was possible because oil behaves as a solid in acoustic terms and transmits shear waves. Laboratory tests have been carried out and a prototype was built and tested in the field. Radio frequency methods, such as ground penetrating radar (GPR, have been tested for both oil-under-ice and oil-under-snow. The GPR method does not provide sufficient discrimination for positive oil detection in actual spills. Preliminary tests on the use of Nuclear Magnetic Resonance for detecting oil, in and under ice, shows promise and further work on this is being done at this time. A number of other oil-in-ice detection technologies have been tried and evaluated, including standard acoustic thickness probes, fluorosensor techniques, and augmented infrared detection. Each of these showed potential in theory during tank tests. Further testing on these proposed methods is required.

  4. Wind tunnel observations of drifting snow

    Science.gov (United States)

    Paterna, Enrico; Crivelli, Philip; Lehning, Michael

    2016-04-01

    Drifting snow has a significant impact on snow redistribution in mountains, prairies as well as on glaciers, ice shelves, and sea ice. In all these environments, the local mass balance is highly influenced by drifting snow. Understanding the dynamic of snow saltation is crucial to the accurate description of the process. We applied digital shadowgraphy in a cold wind tunnel to measure drifting snow over natural snow covers. The acquisition and evaluation of time-resolved shadowgraphy images allowed us to resolve a large part of the saltation layer. The technique has been successfully compared to the measurements obtained from a Snow Particle Counter, considered the most robust technique for snow mass-flux measurements so far. The streamwise snow transport is dominated by large-scale events. The vertical snow transport has a more equal distribution of energy across the scales, similarly to what is observed for the flow turbulence velocities. It is hypothesized that the vertical snow transport is a quantity that reflects the local entrainment of the snow crystals into the saltation layer while the streamwise snow transport results from the streamwise development of the trajectories of the snow particles once entrained, and therefore is rather a non-local quantity.

  5. Densification and grain coarsening of melting snow

    Institute of Scientific and Technical Information of China (English)

    周石硚; 中尾正义; 桥本重将; 坂井亚规子; 成田英器; 石川信敬

    2003-01-01

    A field work was conducted at Moshiri in Japan.The work included intensive snow pit work, taking snow grain photos, recording snow and air temperatures, as well as measuring snow water content.By treating the snow as a viscous fluid, it is found that the snow compactive viscosity decreases as the density increases, which is opposite to the relation for dry snow.Based on the measurements of snow grain size, it is shown that, similar to the water-saturated snow, the frequency distributions of grain size at different times almost have the same shape.This reveals that the water-unsaturated melting snow holds the same grain-coarsening behavior as the water-saturated snow does.It is also shown that the water-unsaturated melting snow coarsens much more slowly than the water-saturated snow.The C value, which is the viscosity when the snow density is zero, is related to the mean grain size and found to decrease with increasing grain size.The decreasing rate of C value increases with decreasing grain-coarsening rate.

  6. Sodankylä manual snow survey program

    Directory of Open Access Journals (Sweden)

    L. Leppänen

    2015-12-01

    Full Text Available The manual snow survey program of the Arctic Research Centre of Finnish Meteorological Institute (FMI-ARC consists of numerous observations of natural seasonal taiga snowpack in Sodankylä, northern Finland. The easily accessible measurement areas represent the typical forest and soil types in the boreal forest zone. Systematic snow measurements began in 1909 with snow depth (SD and snow water equivalent (SWE; however some older records of the snow and ice cover exists. In 2006 the manual snow survey program expanded to cover snow macro- and microstructure from regular snow pits at several sites using both traditional and novel measurement techniques. Present-day measurements include observations of SD, SWE, temperature, density, horizontal layers of snow, grain size, specific surface area (SSA, and liquid water content (LWC. Regular snow pit measurements are performed weekly during the snow season. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack. This snow survey program is an excellent base for the future research of snow properties.

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

    Science.gov (United States)

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

    2017-07-01

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

  8. Politics of Snow

    Science.gov (United States)

    Burko, D.

    2012-12-01

    In a 2010 catalog introduction for my exhibition titled: POLITICS OF SNOW, Eileen Claussen, President of the Pew Center on Global Climate Change wrote the following: "Climate change has been taken over by politics…We are awash in talking points, briefing papers, scientific studies, and communiqués from national governments… Diane Burko's paintings remind us that all these words can often obscure or even obstruct our view of what is truly happening …..There is only so much you can do with words. People need to see that the world is changing before our eyes. When we look at Diane's images of the effects of climate change, we connect to something much deeper and more profound (and more moving) than the latest political pitch from one side or another in this debate…These paintings also connect us to something else. Even as Diane documents how things are changing, she also reminds us of the stunning beauty of nature - and, in turn, the urgency of doing everything in our power to protect it." The creation of this body of work was made possible because of the collaboration of many glacial geologists and scientists who continually share their visual data with me. Since 2006 I've been gathering repeats from people like Bruce Molnia (USGS) and Tad Pfeffer of Alaskan glaciers, from Daniel Fagre (USGS) of Glacier National Park and Lonnie Thompson and Jason Box (Ohio University's Byrd Polar Center) about Kilimanjaro, Qori Kalis and Petermann glaciers as well as from photographer David Breashears on the disappearing Himalayan glaciers. In my practice, I acknowledge the photographers, or archive agencies, such as USGS, NASA or Snow and Ice Center, in the title and all printed material. As a landscape painter and photographer my intent is to not reproduce those images but rather use them as inspiration. At first I used the documentary evidence in sets of diptychs or triptychs. Since 2010 I have incorporated geological charts of recessional lines, graphs, symbols and

  9. Defining snow drought and why it matters

    Science.gov (United States)

    Harpold, Adrian; Dettinger, Michael; Rajagopal, Seshadri

    2017-01-01

    On 12 February, water resource managers at the Oroville Dam issued an evacuation warning that forced some 180,000 Californians to relocate to higher ground. The story of how conditions got to this point involves several factors, but two clearly stand out: the need to prevent water shortages during a record drought, followed by one of the wettest October–February periods in California history.The situation at Oroville Dam highlights difficulties that many reservoir managers face in managing flood risks while simultaneously storing water to mitigate severe droughts and smaller snowpacks. Central to this difficulty is the idea of “snow drought,” a term that’s gaining traction in both scientific and lay literature.

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

    Science.gov (United States)

    Zatko, Maria; Erbland, Joseph; Savarino, Joel; Geng, Lei; Easley, Lauren; Schauer, Andrew; Bates, Timothy; Quinn, Patricia K.; Light, Bonnie; Morison, David; Osthoff, Hans D.; Lyman, Seth; Neff, William; Yuan, Bin; Alexander, Becky

    2016-11-01

    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 the estimated snow NOx emissions presented in this study. Our results suggest

  11. Role of blowing snow in snow processes in Qilian Mountainous region

    Institute of Scientific and Technical Information of China (English)

    HongYi Li; Jian Wang; XiaoHua Hao

    2014-01-01

    Blowing snow is an important part of snow hydrologic processes in mountainous region, however the related researches were rare for the Qilian mountainous region where blowing snow is frequent. Using the observation dataset in 2008 snow season in Binggou wa-tershed in Qilian mountainous region, we systematically studied the energy and mass processes of blowing snow by field observation and model simulation. The results include the analysis of snow observation, the occurrence probability of blowing snow, blowing snow transport and blowing snow sublimation. It was found that blowing snow was obvious in high altitude region (4,146 m), the snow redistribution phenomena was remarkable. In Yakou station in the study region, blowing snow was easily occurred in midwinter and early spring when no snowmelt, the blowing snow transport was dominated in this period;when snowmelt beginning, the occur-rence probability of blowing snow decreased heavily because of the increasing air temperature, melt, and refrozen phenomena. The blowing snow sublimation accounted for 41.5%of total snow sublimation at Yakou station in 2008 snow season.

  12. Advances in RUC LSM snow component to address cold biases in snow-covered regions in RAP and HRRR

    Science.gov (United States)

    Smirnova, T. G.; Benjamin, S.; Brown, J. M.

    2016-12-01

    RUC Land-Surface Model (LSM), a Weather Research and Forecast (WRF) LSM option, is used as a land surface component in the operational Rapid Refresh (RAP) over North America domain and in the High-Resolution Rapid Refresh (HRRR) over CONUS domain. It was also added to the land-surface model suite available in NASA Land Information System (LIS), and work has been started to implement it in the Next Generation Global Prediction System (NGGPS) as part of the RAP/HRRR physics suite. The RUC LSM performance has been evaluated for almost two decades within the real-time operational weather prediction systems focused on storm-scale predictions for severe weather and safer aviation. And in the recent couple of years it has been more and more extensively utilized by the WRF community in different parts of the world, including Arctic regions, and for different applications. Valuable feedback from the National Weather Prediction forecast offices and the WRF community has motivated further advances towards better representation of processes in snow-covered regions. The new treatment has been implemented for grid cells partially covered with snow. It considers snow-covered and non-snow-covered portions of a grid cell independently, and independently determined surface fluxes are aggregated to feed back into the surface-layer scheme at the end of each time step. This new "mosaic" approach removes the constraint of keeping skin temperature of partially covered with snow grid cells at or below the freezing point, and helps to reduce cold biases in these regions. Comparison results from experiments with the new and old approaches will be presented at the meeting. Also, techniques impemented in RAP/HRRR for optimal initialization of snow cover on the ground will be presented.

  13. Snow optical properties at Dome C, Antarctica – implications for snow emissions and snow chemistry of reactive nitrogen

    Directory of Open Access Journals (Sweden)

    J. L. France

    2011-04-01

    Full Text Available Measurements of $e$-folding depth, nadir reflectivity and stratigraphy of the snowpack around Concordia station (Dome C, 75.10° S, 123.31° E were undertaken and used to determine wavelength dependent coefficients (350 nm to 550 nm for light scattering and absorption and to calculate potential fluxes of nitrogen dioxide (NO2 from the snowpack due to nitrate photolysis within the snowpack. The stratigraphy of the top 80 cm of Dome C snowpack generally consists of three main layers: a surface of soft windpack (not ubiquitous, a hard windpack and a hoar-like layer beneath the windpack(s. The $e$-folding depths are ~10 cm for the two windpack layers and ~20 cm for the hoar-like layer for solar radiation at a wavelength of 400 nm, about a factor 2–4 larger than previous model estimates for South Pole. Depth integrated photochemical reaction rates of nitrate photolysis in the Dome C snowpack were calculated to give molecular fluxes of NO2 of 5.3×1012 molecules m−2 s−1, 2.3×1012 molecules m−2 s−1 and 8×1011 molecules m−2 s−1 for solar zenith angles of 60°, 70° and 80° respectively for clear sky conditions using the TUV-snow radiative-transfer model. Depending upon the snowpack stratigraphy, a minimum of 85% of the NO2 originates from within the top 20 cm of the Dome C snowpack. It is found that on a multi-annual scale, nitrate photolysis can remove up to 80% of nitrate from surface snow, confirming independent isotopic evidence that photolysis is an important driver of nitrate loss occurring in the EAIS snowpack. However, the model cannot account for the total observed nitrate loss of 90–95% or the shape of the observed nitrate depth profile. A more complete model will need to include also physical processes such as evaporation, re-deposition or diffusion between the quasi-liquid layer on snow grains

  14. Sodankylä manual snow survey program

    Science.gov (United States)

    Leppänen, Leena; Kontu, Anna; Hannula, Henna-Reetta; Sjöblom, Heidi; Pulliainen, Jouni

    2016-05-01

    The manual snow survey program of the Arctic Research Centre of the Finnish Meteorological Institute (FMI-ARC) consists of numerous observations of natural seasonal taiga snowpack in Sodankylä, northern Finland. The easily accessible measurement areas represent the typical forest and soil types in the boreal forest zone. Systematic snow measurements began in 1909 with snow depth (HS) and snow water equivalent (SWE). In 2006 the manual snow survey program expanded to cover snow macro- and microstructure from regular snow pits at several sites using both traditional and novel measurement techniques. Present-day snow pit measurements include observations of HS, SWE, temperature, density, stratigraphy, grain size, specific surface area (SSA) and liquid water content (LWC). Regular snow pit measurements are performed weekly during the snow season. Extensive time series of manual snow measurements are important for the monitoring of temporal and spatial changes in seasonal snowpack. This snow survey program is an excellent base for the future research of snow properties.

  15. Siberia snow depth climatology derived from SSM/I data using a combined dynamic and static algorithm

    Science.gov (United States)

    Grippa, M.; Mognard, N.; Le, Toan T.; Josberger, E.G.

    2004-01-01

    One of the major challenges in determining snow depth (SD) from passive microwave measurements is to take into account the spatiotemporal variations of the snow grain size. Static algorithms based on a constant snow grain size cannot provide accurate estimates of snow pack thickness, particularly over large regions where the snow pack is subjected to big spatial temperature variations. A recent dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from the Special Sensor Microwave/Imager (SSM/I) over the Northern Great Plains (NGP) in the US. In this paper, we develop a combined dynamic and static algorithm to estimate snow depth from 13 years of SSM/I observations over Central Siberia. This region is characterised by extremely cold surface air temperatures and by the presence of permafrost that significantly affects the ground temperature. The dynamic algorithm is implemented to take into account these effects and it yields accurate snow depths early in the winter, when thin snowpacks combine with cold air temperatures to generate rapid crystal growth. However, it is not applicable later in the winter when the grain size growth slows. Combining the dynamic algorithm to a static algorithm, with a temporally constant but spatially varying coefficient, we obtain reasonable snow depth estimates throughout the entire snow season. Validation is carried out by comparing the satellite snow depth monthly averages to monthly climatological data. We show that the location of the snow depth maxima and minima is improved when applying the combined algorithm, since its dynamic portion explicitly incorporate the thermal gradient through the snowpack. The results obtained are presented and evaluated for five different vegetation zones of Central Siberia. Comparison with in situ measurements is also shown and discussed. ?? 2004 Elsevier Inc. All rights reserved.

  16. Snow Roads at McMurdo Station, Antarctica

    Science.gov (United States)

    2010-05-01

    We found that the disaggregation was not uniform and it left the snow in larger clumps rather than fine particles . These data indicate that snow...33 Snow moisture ............................................................................................................................ 33...52 Snow moisture

  17. Snow HDRF Measurements on Various Snow Surfaces with the new IAC-Gonio-Spectrometer

    Science.gov (United States)

    Bourgeois, C. S.; Schroff, K.; Frei, H.

    2004-12-01

    This work presents a field Gonio-Spectrometer developed at the Institute for Atmospheric and Climate Science, Swiss Federal Institute of Technology, Zurich (IAC-ETH). The main motivation to built this Gonio-Spectrometer was the study of the Hemispherical Distribution Reflectance Factor (HDRF) of dry snow on the Ice Sheet of Greenland and to examine the influence of the HDRF on the surface energy balance. The surface Albedo is of great importance for both, large scale and small scale climate modelling and energy balance studies. Especially for remote regions, satellites provide an extraordinary means to measure reflected sunlight. However, raw satellite data have to undergo several corrections depending on the viewing angles of the sensors relative to the targets and the irradiance source (sun). The function that describes the distribution of reflected radiance with angle is called Bidirectional Reflectance Distribution Function (BRDF). The HDRF is the commonly used dimensionless form of the angular distribution of reflectance. BRDF and HDRF are a functions of four angles: incoming (solar) zenith angle and azimuth, and outgoing (reflected) zenith angle and azimuth. In situ measurements of HDRF data, a combination of multidirectional and hyperspectral data, require complex and demanding experiments. Therefore, existing data sets a rare. However, the advent of new satellite systems that offer hyperspectral resolution and off-nadir tilting capability ask for ground truth data sets. The IAC-Gonio-Spectrometer measures the HDRF with a distance of 1 meter between sensor and target. The sensor, an optic cable, can be placed on an arbitrary place on the hemisphere and always points towards the same surface area. Depending on the viewing geometry, the diameter of the footprint area varies from 5~cm (at nadir) to 20~cm (at 75 degree zenith angle). The pointing accuracy, analyzed in a laboratory experiment with a laser beam, was measured at ± 2.5~cm. In the summer field

  18. Changes of snow cover in Poland

    Science.gov (United States)

    Szwed, Małgorzata; Pińskwar, Iwona; Kundzewicz, Zbigniew W.; Graczyk, Dariusz; Mezghani, Abdelkader

    2017-02-01

    The present paper examines variability of characteristics of snow cover (snow cover depth, number of days with snow cover and dates of beginning and end of snow cover) in Poland. The study makes use of a set of 43 long time series of observation records from the stations in Poland, from 1952 to 2013. To describe temporal changes in snow cover characteristics, the intervals of 1952-1990 and of 1991-2013 are compared and trends in analysed data are sought (e.g., using the Mann-Kendall test). Observed behaviour of time series of snow-related variables is complex and not easy to interpret, for instance because of the location of the research area in the zone of transitional moderate climate, where strong variability of climate events is one of the main attributes. A statistical link between the North Atlantic Oscillation (NAO) index and the snow cover depth, as well as the number of snow cover days is found.

  19. Reconstruction of a 50-Year Record of Seasonal Snow Cover in Central Asia

    Science.gov (United States)

    Kuzmichenok, V.; Khalsa, S.; Surazakov, A. B.; Aizen, V. B.; Aizen, E.

    2006-12-01

    Water resources in the mountains of interior Eurasia are highly vulnerable to climate change because the closed drainage basins are very sensitive to the changes in energy and mass fluxes at the land surface and, as a result, the near-surface physical conditions such as snow cover which affect river. Current and further expected declines in the water resources of the central Asian mountains are related to factors such as degradation of glaciers and seasonal snow cover extent, the changes in precipitation partitioning among land surface stores, and evaporation fluxes. To study snow cover impact on river runoff formation in the Tien Shan mountains of central Asia for the last half a century, we have applied to a combination of remote sensing, in situ snow course, and meteorological data. Here we present preliminary results of comparing AVHRR-derived Snow Covered Area (SCA) with the ground data over selected Tien Shan representative basins for the period of overlap between in situ and remote observations from 1979 to 1991. For the runoff modeling purposes maximum SCA was determined for each year at the dates of maximum snow accumulation determined by snow surveys data in the studied basins. From 1991 to present the maximum SCAs were determined independently from AVHRR and MODIS data and validated with Landsat data. The MODIS fractional snow cover product for the 5 seasons (2000/01 through 02005/06) characterized the spatial and temporal patterns of snow cover in each studied basin which we relate to the surface observational data (air temperature, and larger scale synoptic patterns revealed in the Numerical Weather Prediction (NWP) products. This SCA pattern analysis is applied to in situ snow course, and meteorological data for the period 1950 to 1979 to estimate maximum SCA for runoff modeling.

  20. MONITORING OF SNOW COVER VARIATION USING MODIS SNOW PRODUCT

    Directory of Open Access Journals (Sweden)

    N. Fayaz

    2013-09-01

    Full Text Available Snow is one of the integral components of hydrological and climatic systems. Needless to say, snow cover areas (SCA are considered as indispensable input of hydrological and general circulation models. Studying the spatial and temporal variability of SCA is of the paramount importance for tremendous variety of research such as climate change, water supply and properly managing water resources. In this study by means of Moderate Resolution Imaging Spectroradiometer (MODIS snow cover product, the variation of snow cover extent (SCE in Karoun basin located in western part of Iran is evaluated for twelve years' duration; since 2000 to 2012. The results show that the paramount occurrence of SCE is observed during February months of 2003, 2010 and 2011 as well as during December months of 2006 and 2009.The utmost occurrence of SCE is considered during January months of the other remaining years. Annual average shows that SCE varies from 11% in 2011 to 22% in 2006. According to Mann-Kendal trend test, throughout twelve years; 2000 to 2012, a majority of the pixels in the study area have no considerable trend although there is a decreasing trend on a small portion of the pixels located in the eastern part the study domain.

  1. [Snow cover pollution monitoring in Ufa].

    Science.gov (United States)

    Daukaev, R A; Suleĭmanov, R A

    2008-01-01

    The paper presents the results of examining the snow cover polluted with heavy metals in the large industrial town of Ufa. The level of man-caused burden on the snow cover of the conventional parts of the town was estimated and compared upon exposure to a wide range of snow cover pollutants. The priority snow cover pollutants were identified among the test heavy metals.

  2. How do patchy snow covers affect turbulent sensible heat fluxes? - Numerical analysis and experimental findings

    Science.gov (United States)

    Schlögl, Sebastian; Mott, Rebecca; Lehning, Michael

    2017-04-01

    turbulence as a function of the measurement height, atmospheric stability and wind speed. For patchy snow covers with flux footprints larger than the fetch distance, the observed turbulence is typically recorded as a combination of the turbulence over snow and the turbulence over the adjacent bare ground. These conditions were observed in the upper Dischma valley at the end of the melting period for a small snow cover fraction (calculated in the physics-based one-dimensional snow model SNOWPACK. We show that at least two eddy-covariance measurements in different vertical heights and a snow cover mask to detect the fetch distance are required to clearly separate the turbulence over snow and the turbulence over the adjacent bare ground. Using the footprint technique turbulent sensible heat fluxes towards the snow patch significantly increase by this separation. This approach will allow an improved parametrization of turbulent heat fluxes over patchy snow-covers in larger-scale energy balance models.

  3. A 7-year dataset for driving and evaluating snow models at an Arctic site (Sodankylä, Finland)

    Science.gov (United States)

    Essery, Richard; Kontu, Anna; Lemmetyinen, Juha; Dumont, Marie; Ménard, Cécile B.

    2016-06-01

    Datasets derived from measurements at Sodankylä, Finland, for driving and evaluating snow models are presented. This is the first time that such complete datasets have been made available for a site in the Arctic. The continuous October 2007-September 2014 driving data comprise all of the meteorological variables required as inputs for physically based snow models at hourly intervals: incoming solar and longwave radiation, snowfall and rainfall rates, air temperature, humidity, wind speed and atmospheric pressure. Two versions of the driving data are provided: one using radiation and wind speed measurements made above the height of the trees around the clearing where the evaluation data were measured and one with adjustments for the influence of the trees on conditions close to the ground. The available evaluation data include automatic and manual measurements of bulk snow depth and snow water equivalent, and profiles of snow temperature, snow density and soil temperature. A physically based snow model is driven and evaluated with the datasets to illustrate their utility. Shading by trees is found to extend the duration of both modelled and observed snow cover on the ground by several days a year.

  4. Snow Water Equivalent Retrieval Using Multitemporal COSMO Skymed X-Band SAR Images To Inform Water Systems Operation

    Science.gov (United States)

    Denaro, S.; Del Gobbo, U.; Castelletti, A.; Tebaldini, S.; Monti Guarnieri, A.

    2015-12-01

    In this work, we explore the use of exogenous snow-related information for enhancing the operation of water facilities in snow dominated watersheds. Traditionally, such information is assimilated into short-to-medium term streamflow forecasts, which are then used to inform water systems operation. Here, we adopt an alternative model-free approach, where the policy is directly conditioned upon a small set of selected observational data able to surrogate the snow-pack dynamics. In snow-fed water systems, the Snow Water Equivalent (SWE) stored in the basin often represents the largest contribution to the future season streamflow. The SWE estimation process is challenged by the high temporal and spatial variability of snow-pack and snow properties. Traditional retrieval methods, based on few ground sensors and optical satellites, often fail at representing the spatial diversity of snow conditions over large basins and at producing continuous (gap-free) data at the high sample frequency (e.g. daily) required to optimally control water systems. Against this background, SWE estimates from remote sensed radar products stand out, being able to acquire spatial information with no dependence on cloud coverage. In this work, we propose a technique for retrieving SWE estimates from Synthetic Aperture Radar (SAR) Cosmo SkyMed X-band images: a regression model, calibrated on ground SWE measurements, is implemented on dry snow maps obtained through a multi-temporal approach. The unprecedented spatial scale of this application is novel w.r.t. state of the art radar analysis conducted on limited spatial domains. The operational value of the SAR retrieved SWE estimates is evaluated based on ISA, a recently developed information selection and assessment framework. The method is demonstrated on a snow-rain fed river basin in the Italian Alps. Preliminary results show SAR images have a good potential for monitoring snow conditions and for improving water management operations.

  5. Changes in Snow Albedo Resulting from Snow Darkening Caused by Black Carbon

    Science.gov (United States)

    Engels, J.; Kloster, S.; Bourgeois, Q.

    2014-12-01

    We investigate the potential impact of snow darkening caused by pre-industrial and present-day black carbon (BC) emissions on snow albedo and subsequently climate. To assess this impact, we implemented the effect of snow darkening caused by BC emitted from natural as well as anthropogenic sources into the Max Planck Institute for Meteorology Earth System Model (MPI-M ESM). Considerable amounts of BC are emitted e.g. from fires and are transported through the atmosphere for several days before being removed by rain or snow precipitation in snow covered regions. Already very small quantities of BC reduce the snow reflectance significantly, with consequences for snow melting and snow spatial coverage. We implemented the snow albedo reduction caused by BC contamination and snow aging in the one layer land surface component (JSBACH) of the atmospheric general circulation model ECHAM6, developed at MPI-M. For this we used the single-layer simulator of the SNow, Ice, and Aerosol Radiation (SNICAR-Online (Flanner et al., 2007); http://snow.engin.umich.edu) model to derive snow albedo values for BC in snow concentrations ranging between 0 and 1500 ng(BC)/g(snow) for different snow grain sizes for the visible (0.3 - 0.7 μm) and near infrared range (0.7 - 1.5 μm). As snow grains grow over time, we assign different snow ages to different snow grain sizes (50, 150, 500, and 1000 μm). Here, a radius of 50 μm corresponds to new snow, whereas a radius of 1000 μm corresponds to old snow. The deposition rates of BC on snow are prescribed from previous ECHAM6-HAM simulations for two time periods, pre-industrial (1880-1889) and present-day (2000-2009), respectively. We perform a sensitivity study regarding the scavenging of BC by snow melt. To evaluate the newly implemented albedo scheme we will compare the modeled black carbon in snow concentrations to observed ones. Moreover, we will show the impact of the BC contamination and snow aging on the simulated snow albedo. The

  6. 'Snow White' and Language Awareness.

    Science.gov (United States)

    Larson, Deborah Aldrich

    1987-01-01

    Noting that knowledge of grammar rules does not ensure correct usage in one's own writing, describes an approach used in a summer workshop to promote awareness of appropriate idiom where 35 highly motivated black students produced 'Snow White' using their own script, half in standard dialect and half in black dialect. (JG)

  7. Application of asymptotic radiative transfer theory for the retrievals of snow parameters using reflection and transmission observations

    Directory of Open Access Journals (Sweden)

    H. S. Negi

    2011-04-01

    Full Text Available An asymptotic analytical radiative transfer (AART theory was used to retrieve snow optical parameters such as extinction coefficient, diffuse exponent, asymptotic flux extinction coefficient (AFEC, snow optical thickness and probability of photon absorption (PPA. This theory was applied to the reflection and transmission data for a temperate snow cover from 400–1000 nm wavelength region, to retrieve AFEC for different types of snow cover (thick, thin, dry, wet, new and old snow. The AFEC values were found at 450 nm wavelength region in the range from 0.06 to 0.22 cm−1, where high values were observed for increased wetness and impurity in snow. A good agreement between AART retrieved and other radiative transfer model retrieved parameter shows that AART theory can work well for different types of snow. The extinction coefficients for temperate snow ranged from 0.5 to 1.0 mm−1 and the e-folding depths ranged from 5 to 25 cm. The snow physical characteristics such as grain size and density were also retrieved using derived optical parameters and found in agreement with ground measurements. The main advantages of the proposed AART method are the simple analytical equations that provide a valuable alternative from complex numerical radiative transfer solutions.

  8. Retrieval of snow albedo and grain size using reflectance measurements in Himalayan basin

    Directory of Open Access Journals (Sweden)

    H. S. Negi

    2011-03-01

    Full Text Available In the present paper, spectral reflectance measurements of Himalayan seasonal snow were carried out and analysed to retrieve the snow albedo and effective grain size. The asymptotic radiative transfer (ART theory was applied to retrieve the plane and spherical albedo. The retrieved plane albedo was compared with the measured spectral albedo and a good agreement was observed with ±10% differences. Retrieved integrated albedo was found within ±6% difference with ground observed broadband albedo. The retrieved snow grain sizes using different models based on the ART theory were compared for various snow types and it was observed that the grain size model using two channel method (one in visible and another in NIR region can work well for the Himalayan seasonal snow and it was found consistent with temporal changes in grain size. This method can work very well for clean, dry snow as in the upper Himalaya, but sometimes, due to the low reflectances (<20% using wavelength 1.24 μm, the ART theory cannot be applied, which is common in lower and middle Himalayan old snow. This study is important for monitoring the Himalayan cryosphere using air-borne or space-borne sensors.

  9. Retrieval of snow albedo and grain size using reflectance measurements in Himalayan basin

    Directory of Open Access Journals (Sweden)

    H. S. Negi

    2010-11-01

    Full Text Available In the present paper spectral reflectance measurements of Himalayan seasonal snow were carried out and analysed to retrieve the snow albedo and effective grain size. The asymptotic radiative transfer (ART theory was applied to retrieve the plane and spherical albedo. The retrieved plane albedo was compared with the measured spectral albedo and a good agreement was observed with ±10% measured error accuracy. Retrieved integrated albedo was found within ±6% difference with ground observed broadband albedo. The snow grain sizes retrieved using different models based on ART theory are compared for different snow types and it was observed that presently grain size model using two channel method (one in visible and another in NIR region can work well for Himalayan seasonal snow and it was found consistence with temporal increased grain size. This method can work very well for clean dry snow like in upper Himalaya but sometime due to low reflectances (<0.2 using wavelength 1.24 μm ART theory can not be applied, which is common in lower and middle Himalayan old snow. This study is of importance for monitoring the Himalayan cryosphere using air-borne or space-borne sensors.

  10. Spatially continuous mapping of snow depth in high alpine catchments using digital photogrammetry

    Directory of Open Access Journals (Sweden)

    Y. Bühler

    2014-06-01

    Full Text Available Information on snow depth and its spatial distribution is crucial for many applications in snow and avalanche research as well as in hydrology and ecology. Today snow depth distributions are usually estimated using point measurements performed by automated weather stations and observers in the field combined with interpolation algorithms. However, these methodologies are not able to capture the high spatial variability of the snow depth distribution present in alpine terrain. Continuous and accurate snow depth mapping has been done using laser scanning but this method can only cover limited areas and is expensive. We use the airborne ADS80 opto-electronic scanner with 0.25 m spatial resolution to derive digital surface models (DSMs of winter and summer terrains in the neighborhood of Davos, Switzerland. The DSMs are generated using photogrammetric image correlation techniques based on the multispectral nadir and backward looking sensor data. We compare these products with the following independent datasets acquired simultaneously: (a manually measured snow depth plots (b differential Global Navigation Satellite System (dGNSS points (c Terrestrial Laser Scanning (TLS and (d Ground Penetrating Radar (GPR datasets, to assess the accuracy of the photogrammetric products. The results of this investigation demonstrate the potential of optical scanners for wide-area, continuous and high spatial resolution snow-depth mapping over alpine catchments above tree line.

  11. Spatiotemporal Variations in Snow and Soil Frost—A Review of Measurement Techniques

    Directory of Open Access Journals (Sweden)

    Angela Lundberg

    2016-07-01

    Full Text Available Large parts of the northern hemisphere are covered by snow and seasonal frost. Climate warming is affecting spatiotemporal variations of snow and frost, hence influencing snowmelt infiltration, aquifer recharge and river runoff patterns. Measurement difficulties have hampered progress in properly assessing how variations in snow and frost impact snowmelt infiltration. This has led to contradicting findings. Some studies indicate that groundwater recharge response is scale dependent. It is thus important to measure snow and soil frost properties with temporal and spatial scales appropriate to improve infiltration process knowledge. The main aim with this paper is therefore to review ground based methods to measure snow properties (depth, density, water equivalent, wetness, and layering and soil frost properties (depth, water and ice content, permeability, and distance to groundwater and to make recommendations for process studies aiming to improve knowledge regarding infiltration in regions with seasonal frost. Ground-based radar (GBR comes in many different combinations and can, depending on design, be used to assess both spatial and temporal variations in snow and frost so combinations of GBR and tracer techniques can be recommended and new promising methods (auocostics and self potential are evolving, but the study design must be adapted to the scales, the aims and the resources of the study.

  12. Downscaling Snow Cover Fraction Data in Mountainous Regions Based on Simulated Inhomogeneous Snow Ablation

    Directory of Open Access Journals (Sweden)

    Hong Yi Li

    2015-07-01

    Full Text Available High-resolution snow distributions are essential for studying cold regions. However, the temporal and spatial resolutions of current remote sensing snow maps remain limited. Remotely sensed snow cover fraction (SCF data only provide quantitative descriptions of snow area proportions and do not provide information on subgrid-scale snow locations. We present a downscaling method based on simulated inhomogeneous snow ablation capacities that are driven by air temperature and solar radiation data. This method employs a single parameter to adjust potential snow ablation capacities. Using this method, SCF data with a resolution of 500 m are downscaled to a resolution of 30 m. Then, 18 remotely sensed TM, CHRIS and EO-1 snow maps are used to verify the downscaled results. The mean overall accuracy is 0.69, the average root-mean-square error (RMSE of snow-covered slopes between the downscaled snow map and the real snow map is 3.9°, and the average RMSE of the sine of the snow covered aspects between the downscaled snow map and the real snow map is 0.34, which is equivalent to 19.9°. This method can be applied to high-resolution snow mapping in similar mountainous regions.

  13. Evaluation of the SMAP model-simulated snow internal physical properties at Sapporo, Japan from 2005 to 2015

    Science.gov (United States)

    Niwano, Masashi; Aoki, Teruo; Kuchiki, Katsuyuki; Matoba, Sumito; Kodama, Yuji; Tanikawa, Tomonori

    2016-04-01

    Temporal evolution of snow internal physical properties such as grain size, density, temperature, and water content are controlled by changes in meteorological conditions. On the other hand, in a snow covered area, surface atmospheric conditions are modulated in response to variations of snow albedo, which is affected by (optically equivalent) snow grain size as well as mass concentration of snow impurities such as black carbon and dust. Therefore, it is necessary for snowpack models incorporated in climate models to simulate realistic snow internal physical properties to perform accurate future climate prediction especially in the cryosphere. In this study, we evaluated snow internal physical properties at Sapporo (43° 05'N, 141° 21'E, 15 m a.s.l.), Japan from 2005 to 2015 simulated with a 1-D multilayered physical snowpack model SMAP (Snow Metamorphism and Albedo Process). The model was driven by quality controlled 30-min averaged data for air temperature, relative humidity, wind speed, surface pressure, snow depth, downward and upward shortwave radiant flux, downward longwave radiant flux, and ground surface soil heat flux. Simulation results were compared against the data obtained from snow pit works performed twice a week at Sapporo. First of all, the model-simulated column integrated SWE (snow water equivalent) were compared against in-situ measurements (273 data were available during the 10 winters). The results show that the model tends to underestimate SWE (mean error; ME was -19 mm); however, root mean square error (RMSE) was 34 mm, and these scores are better than those for simulations driven by not snow depth but precipitation (ME was less than -25 mm and RMSE was more than 40 mm). It suggests that the correction technique for precipitation measurements considering catch efficiency of a rain gauge is still insufficient. Next, the model-simulated profiles for snow density and snow temperature were compared against in-situ measurements. For this purpose

  14. 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.

  15. Investigating the role of topography on snow cover duration and distribution in the Italian Apennines by means of MODIS data

    Science.gov (United States)

    Da Ronco, Pierfrancesco; Piperno, Peter; Avanzi, Francesco; De Michele, Carlo

    2016-04-01

    Snow cover plays an important role in the water cycle influencing water resource availability. As the seasonal cycle of snowpack is highly sensitive to variations of precipitation and temperature, the expected future changes in the atmospheric forcings may impact on the timing of snow accumulation and melt. In this work we investigated the effects of the complex topography of a mountain range on snow dynamics by means of MODIS data of snow cover (2003 - 2014) and a 500 m-resolution Digital Elevation Model. The study area is the central Apennines, having peaks in elevation over 2800 m asl in the Majella and Gran Sasso massifs. Firstly, we carried out a validation of MOD10A1/MYD10A1 SCA products comparing ground data of snow depth measured by seven monitoring stations with the remote sensing time series of snow covered area. The comparison confirms the accuracy of MODIS products in snow cover mapping in mountain areas, in agreement with what found in other regions around the world. Then, we subjected Aqua and Terra snow cover maps to a cloud removal procedure ensuring a pixel-scale estimate of snow cover presence at daily temporal resolution. The new cloud-free dataset was used for deriving trends of snow cover duration and snow cover distribution for different classes of aspect, slope and concavity within the mountain part of the domain. The analysis has allowed us to quantify the impacts of these topographic features on the accumulation and melting processes. In particular, the north-facing slopes show a lower snowline altitude in all seasons and a longer snow duration in spring.

  16. A Comparison of Snow Depth from GPS-Interferometry vs. AMSR-E/AMSR-2

    Science.gov (United States)

    Kim, E. J.; Patel, H.; Wu, A.; Braun, J.; Small, E. E.; Larson, K. M.

    2013-12-01

    The validation of snow data products from satellite sensors has perennially faced the challenge of finding station data that is both widely distributed and possessing sufficient spatial density to provide accurate validation statistics. Point data from ground truth stations have been widely used despite the orders-of-magnitude scale mismatch as well as the insufficient spatial density; this has persisted mainly due to the lack of better alternatives. We evaluate a novel source of validation data that uses ground-based GPS networks, by comparison against snow data products from the AMSR-E sensor aboard the Aqua satellite and now the AMSR2 sensor aboard the GCOM-W1satellite. There are three advantageous features of this approach. First, the GPS networks already exist. Second, the thousands of sites are widely distributed spatially and have a higher spatial density than other stations currently used for snow validation. And third, the observed area of the GPS technique approaches 10,000 m2--much larger than point-scale station observations (1 to 10 m2). Evaluating the new GPS approach along with the more well-known AMSR-E/AMSR-2 snow depth product will provide a baseline for exploiting this potentially large new validation data source in a variety of remote sensing science studies. This work is based on recent advances in GPS techniques by Larson et al that have allowed geodetic quality GPS instrumentation to be used to measure changes in soil moisture and snow depth in the region surrounding GPS antennas. These retrievals relate observed changes in ground reflected GPS signals to changes in either the soil conditions around the antenna or the depth of snow at the site. In this paper, we will focus solely on snow depth. Observations from several GPS stations from the Plate Boundary Observatory (PBO), operating in varied locations in the western United States have been compared with AMSR-E and/or AMSR-2 snow retrievals. These sites span a range of climates (especially

  17. Uncertainty analysis of the optical satellite data-derived snow products

    Science.gov (United States)

    Salminen, Miia; Pulliainen, Jouni; Metsämäki, Sari; Luojus, Kari; Böttcher, Kristin; Hannula, Henna-Reetta

    2014-05-01

    -observations in various measurement conditions. These important error contributors in FSC retrieval with SCAmod are the variabilities in snow reflectance, forest transmissivity, forest reflectance (of an opaque canopy) and snow-free ground reflectance for different land cover classes. Based on the obtained results, it is possible to calculate the statistical error layers for different global FSC products and analyze the performance of the snow monitoring technique in various circumstances. This is highly relevant for the utilization of the CDRs for climate research purposes. We present the results and demonstrate the possibilities in global snow monitoring. Further work will clarify the behavior of the systematic errors by exploiting different ground truth reference datasets available. Optical satellite data-derived information on FSC can be also used in combination with SWE estimates from passive microwave sensors, in order to provide combined information on global snow extent and snow mass with confidence limits. This is furthermore demonstrated here. The presented results are obtained within the ESA DUE GlobSnow project.

  18. Vertical profiles of the specific surface area of the snow at Dome C, Antarctica

    Directory of Open Access Journals (Sweden)

    J.-C. Gallet

    2010-09-01

    Full Text Available The specific surface area (SSA of snow determines in Part the albedo of snow surfaces and the capacity of the snow to adsorb chemical species and catalyze reactions. Despite these crucial roles, almost no value of snow SSA are available for the largest permanent snow expanse on Earth, the Antarctic. We have measured the first vertical profiles of snow SSA near Dome C (DC: 75°06´ S, 123°20´ E, 3233 m a.s.l. on the Antarctic plateau, and at seven sites during the logistical traverse between Dome C and the French coastal base Dumont D'Urville (DDU: 66°40´ S, 140°01´ E during the Austral summer 2008–2009. We used the DUFISSS system, which measures the IR reflectance of snow at 1310 nm with an integrating sphere. At DC, the mean SSA of the snow in the top 1 cm is 38 m2 kg−1, decreasing monotonically to 14 m2 kg−1 at a depth of 15 cm. Along the traverse, the snow SSA profile is similar to that at DC in the first 600 km from DC. Closer to DDU, the SSA of the top 5 cm is 23 m2 kg−1, decreasing to 19 m2 kg−1 at 50 cm depth. This is attributed to wind, which causes a rapid decrease of surface snow SSA, but forms hard windpacks whose SSA decrease more slowly with time. Since light-absorbing impurities are not concentrated enough to affect albedo, the vertical profiles of SSA and density were used to calculate the spectral albedo of the snow for several realistic illumination conditions, using the DISORT radiative transfer model. A preliminary comparison with MODIS data is presented for use in energy balance calculations and for comparison with other satellite retrievals. These calculated albedos are compared to the few existing measurements on the Antarctic plateau. The interest of postulating a submillimetric, high-SSA layer at the snow surface to explain measured albedos is discussed.

  19. Snow Melting and Freezing on Older Townhouses

    DEFF Research Database (Denmark)

    Nielsen, Anker; Claesson, Johan

    2011-01-01

    The snowy winter of 2009/2010 in Scandinavia prompted many newspaper articles on icicles falling from buildings and the risk this presented for people walking below. The problem starts with snow melting on the roof due to heat loss from the building. Melt water runs down the roof and some...... of it will freeze on the overhang. The rest of the water will either run off or freeze in gutters and downpipes or turn into icicles. This paper describes use of a model for the melting and freezing of snow on roofs. Important parameters are roof length, overhang length, heat resistance of roof and overhang......, outdoor and indoor temperature, snow thickness and thermal conductivity. If the snow thickness is above a specific limit value – the snow melting limit- some of the snow will melt. Another interesting limit value is the dripping limit. All the melt water will freeze on the overhang, if the snow thickness...

  20. Simulations of a Canadian snowpack brightness temperatures using SURFEX-Crocus for Snow Water Equivalent (SWE) retrievals

    Science.gov (United States)

    Larue, Fanny; Royer, Alain; De Sève, Danielle; Langlois, Alexandre; Roy, Alexandre; Saint-Jean-Rondeau, Olivier

    2016-04-01

    In Quebec, the water associated to snowmelt represents 30% of the annual electricity production so that the snow cover evaluation in real time is of primary interest. The key variable is snow water equivalent (SWE) which describes the evolution of a global seasonal snow cover. However, the sparse distribution of meteorological stations in northern Québec generates great uncertainty in the extrapolation of SWE. On the contrary, the spatial and temporal coverage of satellite data offer a source of information with a high potential when considered as an alternative to the poor spatial distribution of in-situ information. Thus, this project aims to improve the prediction of SWE by assimilation of satellite passive microwave brightness temperatures (Tb) observations, independently of any ground observations. The snowpack evolution is simulated by the French snow model SURFEX-Crocus, driven by the Canadian atmospheric model GEM with a spatial resolution of 10 km. The bias of the atmospheric model and the impact of initialization errors on the simulated SWE were quantified from our ground measurements. To assimilate satellite observations, the multi-layered snow model is first coupled with a radiative transfer model using the Dense Media Radiative transfer theory (the DMRT-ML model) to estimate the microwave snow emission of the simulated snowpack. In order to retrieve simulated Tb in frequencies of interest (i.e. sensitive to snow dielectric properties), the snow microstructure needs to be well parameterized. It was shown in previous studies that the specific surface area (SSA) of snow grains is a well-defined parameter to describe the size and the shape of snow grains and which allows reproducible field measurements. SURFEX-Crocus estimates a SSA for each simulated snow layer, however, the snow microstructure in DMRT-ML is defined per layer by monodisperse optical radius of grain (~ 1/SSA) and by the stickiness which is not known. It thus becomes necessary to introduce

  1. Cloud obstruction and snow cover in Alpine areas from MODIS products

    Science.gov (United States)

    Da Ronco, P.; De Michele, C.

    2014-11-01

    Snow cover maps provide information of great practical interest for hydrologic purposes: when combined with point values of snow water equivalent (SWE), they enable estimation of the regional snow resource. In this context, Earth observation satellites are an interesting tool for evaluating large scale snow distribution and extension. MODIS (MODerate resolution Imaging Spectroradiometer on board Terra and Aqua satellites) daily Snow Covered Area product has been widely tested and proved to be appropriate for hydrologic applications. However, within a daily map the presence of cloud cover can hide the ground, thus obstructing snow detection. Here, we consider MODIS binary products for daily snow mapping over the Po River basin. Ten years (2003-2012) of MOD10A1 and MYD10A1 snow maps have been analysed and processed with the support of a 500 m resolution Digital Elevation Model (DEM). We first investigate the issue of cloud obstruction, highlighting its dependence on altitude and season. Snow maps seem to suffer the influence of overcast conditions mainly in mountain and during the melting period. Thus, cloud cover highly influences those areas where snow detection is regarded with more interest. In spring, the average percentages of area lying beneath clouds are in the order of 70%, for altitudes over 1000 m a.s.l. Then, starting from previous studies, we propose a cloud removal procedure and we apply it to a wide area, characterized by high geomorphological heterogeneity such as the Po River basin. In conceiving the new procedure, our first target was to preserve the daily temporal resolution of the product. Regional snow and land lines were estimated for detecting snow cover dependence on elevation. In cases when there was not enough information on the same day within the cloud-free areas, we used temporal filters with the aim of reproducing the micro-cycles which characterize the transition altitudes, where snow does not stand continually over the entire winter

  2. Analysis and improvement of estimated snow water equivalent (SWE) using Artificial Neural Networks

    Science.gov (United States)

    E Azar, A.; Ghedira, H.; Khanbilvardi, R.

    2005-12-01

    The goal of this study is to improve the retrieval of SWE/Snow depth in Great lakes area, United States using passive microwave images along with Normalized Difference Vegetation Index NDVI and Artificial Neural Networks (ANNs). Passive microwave images have been successfully used to estimate snow characteristics such as Snow Water Equivalent (SWE) and snow depth. Despite considerable progress, challenges still exist with respect to accuracy and reliability. In this study, Special Sensor Microwave Imager (SSM/I) channels which are available in Equal-Area Scalable Earth Grid (EASE-GRID) format are used. The study area is covered by a 28 by 35 grid of EASE-Grid pixels, 25km by 25km each. To have a comprehensive data set of brightness temperatures (Tb) of SSM/I channels, an assortment of pixels were selected based on latitude and land cover. A time series analysis was conducted for three winter seasons to assess the SSM/I capability to estimates snow depth and SWE for various land covers. Ground truth data' were obtained from the National Climate Data Center (NCDC) and the National Operational Hydrological Remote Sensing Center (NOHRSC). The NCDC provided daily snow depth measurements reported from various stations located in the study area. Measurements were recorded and projected to match EASE-GRID formatting. The NOHRSC produces SNODAS dataset using airborne Gamma radiation and gauge measurements combined with a physical model. The data set consisted of different snow characteristics such as SWE and snow depth. Landcover characteristics are introduced by using Normalized Difference Vegetation Index (NDVI). An Artificial Neural Network (ANN) algorithm has been employed to evaluate the effect of landcover in estimating snow depth and Snow Water Equivalent (SWE). The model is trained using SSM/I channels (19v, 19h, 37v, 37h, 22v, 85v, 85h) and the mean and standard deviation of NDVI for the each pixel. The preliminary time series results showed various degrees of

  3. From Snow White to Tangled: Gender and Genre Fiction in Disney's "Princess" Animations

    OpenAIRE

    Íris Alda Ísleifsdóttir 1988

    2013-01-01

    It is hard to ignore the popularity of the Disney Princess franchise these days. Beginning with Snow White and the Seven Dwarfs in 1937, it now includes Snow White, Cinderella, Aurora, Ariel, Belle, Jasmine, Pocahontas, Mulan, Tiana and Rapunzel. This essay attempts to show how gender identity in the Disney princess animations still conforms to outmoded patriarchal values. To critique the franchise and its ideology, this essay employs Hélène Cixous’s concept of ‘patriarchal binary’ to reveal ...

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

    Directory of Open Access Journals (Sweden)

    Marc Zebisch

    2013-03-01

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

  5. A dense medium electromagnetic scattering model for the InSAR correlation of snow

    Science.gov (United States)

    Lei, Yang; Siqueira, Paul; Treuhaft, Robert

    2016-05-01

    Snow characteristics, such as snow water equivalent (SWE) and snow grain size, are important characteristics for the monitoring of the global hydrological cycle and as indicators of climate change. This paper derives an interferometric synthetic aperture radar (InSAR) scattering model for dense media, such as snow, which takes into account multiple scattering effects through the Quasi-Crystalline Approximation. The result of this derivation is a simplified version of the InSAR correlation model derived for relating the InSAR correlation measurements to the snowpack characteristics of grain size, volume fraction, and layer depth as well as those aspects of the volume-ground interaction that affects the interferometric observation (i.e., the surface topography and the ratio of ground-to-volume scattering). Based on the model, the sensitivity of the InSAR correlation measurements to the snow characteristics is explored by simulation. Through this process, it is shown that Ka-band InSAR phase has a good sensitivity to snow grain size and volume fraction, while for lower frequency signals (Ku-band to L-band), the InSAR correlation magnitude and phase have a sensitivity to snow depth. Since the formulation depends, in part, on the pair distribution function, three functional forms of the pair distribution function are implemented and their effects on InSAR phase measurements compared. The InSAR scattering model described in this paper is intended to be an observational prototype for future Ka-band and L-band InSAR missions, such as NASA's Surface Water and Ocean Topography and NASA-ISRO Synthetic Aperture Radar missions, planned for launch in the 2020-2021 time frame. This formulation also enables further investigation of the InSAR-based snow retrieval approaches.

  6. Upward-looking L-band FMCW radar for snow cover monitoring.

    Science.gov (United States)

    Okorn, Robert; Brunnhofer, Georg; Platzer, Thomas; Heilig, Achim; Schmid, Lino; Mitterer, Christoph; Schweizer, Jürg; Eisen, Olaf

    2014-07-01

    Forecasting snow avalanche danger in mountainous regions is of major importance for the protection of infrastructure in avalanche run-out zones. Inexpensive measurement devices capable of measuring snow height and layer properties in avalanche starting zones may help to improve the quality of risk assessment. We present a low-cost L-band frequency modulated continuous wave radar system (FMCW) in upward-looking configuration. To monitor the snowpack evolution, the radar system was deployed in fall and subsequently was covered by snowfalls. During two winter seasons we recorded reflections from the overlying snowpack. The influence of reflection magnitude and phase to the measured frequency spectra, as well as the influence of signal processing were investigated. We present a method to extract the phase of the reflection coefficients from the phase response of the frequency spectra and their integration into the presentation of the measurement data. The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection. We developed an automated and a semi-automated snow surface tracking algorithm. Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR). The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor. The percolation of water was observable in the radargrams. Results suggest that the upward-looking FMCW system may be a valuable alternative to conventional snow-depth sensors for locations, where fixed installations above ground are not feasible.

  7. Snow depth mapping in high-alpine catchments using digital photogrammetry

    Science.gov (United States)

    Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C.

    2015-02-01

    Information on snow depth and its spatial distribution is crucial for numerous applications in snow and avalanche research as well as in hydrology and ecology. Today, snow depth distributions are usually estimated using point measurements performed by automated weather stations and observers in the field combined with interpolation algorithms. However, these methodologies are not able to capture the high spatial variability of the snow depth distribution present in alpine terrain. Continuous and accurate snow depth mapping has been successfully performed using laser scanning but this method can only cover limited areas and is expensive. We use the airborne ADS80 optoelectronic scanner, acquiring stereo imagery with 0.25 m spatial resolution to derive digital surface models (DSMs) of winter and summer terrains in the neighborhood of Davos, Switzerland. The DSMs are generated using photogrammetric image correlation techniques based on the multispectral nadir and backward-looking sensor data. In order to assess the accuracy of the photogrammetric products, we compare these products with the following independent data sets acquired simultaneously: (a) manually measured snow depth plots; (b) differential Global Navigation Satellite System (dGNSS) points; (c) terrestrial laser scanning (TLS); and (d) ground-penetrating radar (GPR) data sets. We demonstrate that the method presented can be used to map snow depth at 2 m resolution with a vertical depth accuracy of ±30 cm (root mean square error) in the complex topography of the Alps. The snow depth maps presented have an average accuracy that is better than 15 % compared to the average snow depth of 2.2 m over the entire test site.

  8. Absence of snow cover reduces understory plant cover and alters plant community composition in boreal forests.

    Science.gov (United States)

    Kreyling, Juergen; Haei, Mahsa; Laudon, Hjalmar

    2012-02-01

    Snow regimes affect biogeochemistry of boreal ecosystems and are altered by climate change. The effects on plant communities, however, are largely unexplored despite their influence on relevant processes. Here, the impact of snow cover on understory community composition and below-ground production in a boreal Picea abies forest was investigated using a long-term (8-year) snow cover manipulation experiment consisting of the treatments: snow removal, increased insulation (styrofoam pellets), and control. The snow removal treatment caused longer (118 vs. 57 days) and deeper soil frost (mean minimum temperature -5.5 vs. -2.2°C) at 10 cm soil depth in comparison to control. Understory species composition was strongly altered by the snow cover manipulations; vegetation cover declined by more than 50% in the snow removal treatment. In particular, the dominant dwarf shrub Vaccinium myrtillus (-82%) and the most abundant mosses Pleurozium schreberi (-74%) and Dicranum scoparium (-60%) declined strongly. The C:N ratio in V. myrtillus leaves and plant available N in the soil indicated no altered nitrogen nutrition. Fine-root biomass in summer, however, was negatively affected by the reduced snow cover (-50%). Observed effects are attributed to direct frost damage of roots and/ or shoots. Besides the obvious relevance of winter processes on plant ecology and distribution, we propose that shifts in the vegetation caused by frost damage may be an important driver of the reported alterations in biogeochemistry in response to altered snow cover. Understory plant performance clearly needs to be considered in the biogeochemistry of boreal systems in the face of climate change.

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

    Science.gov (United States)

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

    2014-12-01

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

  10. Preparatory Groundwork in 'Snow White' Trench

    Science.gov (United States)

    2008-01-01

    NASA's Phoenix Mars Lander is enlarging a trench informally named 'Snow White' to prepare a cleaned-off area at the top of a subsurface layer of hard material, possibly ice-rich soil. This image taken by Phoenix's Surface Stereo Imager camera on July 13th, the 48th Martian day, or sol, since landing, shows the trench after the previous sol's work by the lander's Robotic Arm. The size of the trench in the image is about 30 centimeters (12 inches) by 20 centimeters (8 inches). A shadow of Phoenix's helical antenna falls across the scene, which is on the northeast side of the lander. The image was taken at 3:32 p.m. local solar time at the Phoenix landing site. The Phoenix team plans to use the arm to extend the trench about 15 centimeters (6 inches) further, working toward the lander, in order to have enough surface area both for testing use of the powered rasp on the back of the scoop and also to use a combination of rasping and scooping to gather a sample of ice-rich material for delivering to the Thermal and Evolved-Gas Analyzer. 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.

  11. Estimating Snow Budget of Karaj Dam Reservoir

    Directory of Open Access Journals (Sweden)

    Manijeh G. Tali

    2009-01-01

    Full Text Available Problem statement: Most of the cold period precipitation of Karaj Basin falls in the form of snow. This snow and its run off are important to the dam and the local needs such as agriculture and the drinking water of Tehran. But due to the scarcity and in some elevations the lack of weather stations, measuring this snow cover and its run off is difficult. We have decided to estimate the amount of this snow cover by using surrogate methods such as satellite images of MODIS and temperature thresholds. Approach: To estimate the snow water budget of the Karaj Dam Reservoir Basin, first a temperature threshold of 3° Celsius was defined according to the analysis of daily temperature and precipitation values of Nesa station during 1960-2000. The elevation of this temperature was as low as 1590 m in February and 5734 m in August. During each month the melting snow was computed over the area between 3 and zero degrees Celsius and precipitation below zero degrees was considered as permanent snow cover. The precipitation of areas above 3° was computed as rain. Using this temperature threshold and the DEM map of the basin we estimated the snow cover and snow melt water of the basin. The snow cover area on the MODIS images was estimated and compared with that computed from temperature threshold. Both methods gave relatively similar results. At the end the snow melt water of the whole cold period was calculated and added up to estimate the total snow water budget. Results: The results showed that during the study months most (67.7% of the precipitation comes in the form of snow. And most of this snow (97.5% melts during months March and onward. Its monthly distributions are 3.8% in March, 22.7% in April and 71% in May. The total snow water entering the dam was about 181.73 million cubic meters. Conclusion: The comparison of the results from temperature thresholds with the MODIS images snow cover showed very little and negligible discrepancy. Therefore, this

  12. Snow and ice: Chapter 3

    Science.gov (United States)

    Littell, Jeremy; McAfee, Stephanie A.; O'Neel, Shad; Sass, Louis; Burgess, Evan; Colt, Steve; Clark, Paul; Hayward, Gregory D.; Colt, Steve; McTeague, Monica L.; Hollingsworth, Teresa N.

    2017-01-01

    Temperature and precipitation are key determinants of snowpack levels. Therefore, climate change is likely to affect the role of snow and ice in the landscapes and hydrology of the Chugach National Forest region.Downscaled climate projections developed by Scenarios Network for Alaska and Arctic Planning (SNAP) are useful for examining projected changes in snow at relatively fine resolution using a variable called “snowday fraction (SDF),” the percentage of days with precipitation falling as snow.We summarized SNAP monthly SDF from five different global climate models for the Chugach region by 500 m elevation bands, and compared historical (1971–2000) and future (2030–2059) SDF. We found that:Snow-day fraction and snow-water equivalent (SWE) are projected to decline most in late autumn (October to November) and at lower elevations.Snow-day fraction is projected to decrease 23 percent (averaged across five climate models) from October to March, between sea level and 500 m. Between sea level and 1000 m, SDF is projected to decrease by 17 percent between October and March.Snow-water equivalent is projected to decrease most in autumn (October and November) and at lower elevations (below 1500 m), an average of -26 percent for the 2030–2059 period compared to 1971– 2000. Averaged across the cool season and the entire domain, SWE is projected to decrease at elevations below 1000 m because of increased temperature, but increase at higher elevations because of increased precipitation.Compared to 1971–2000, the percentage of the landscape that is snowdominant in 2030–2059 is projected to decrease, and the percentage in which rain and snow are co-dominant (transient hydrology) is projected to increase from 27 to 37 percent. Most of this change is at lower elevations.Glaciers on the Chugach National Forest are currently losing about 6 km3 of ice per year; half of this loss comes from Columbia Glacier (Berthier et al. 2010).Over the past decade, almost all

  13. Field Investigations on Snow Leopards

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    @@ The snow leopard (Uncia uncia) is a rare and endangered species of large feline animals. Although sharing its name with the common leopard, it is not believed to be closely related to the leopard or the other members of the Pantherine group and is classified as the sole member of its genus. Its total number in the world is generally estimated at somewhere between 3,500 to 7,000, and experts say the figure is far more outdated. Although it is believed that China is home to more snow leopards than any of the other 11 countries in which they occur, such as Afghanistan, India, Pakistan,Tajikistan, Kazakstan, Kyrgyzstan and Mongolia, no one knows exactly how many of them are there in this country.

  14. Evaluation of North Eurasian snow-off dates in the ECHAM5.4 atmospheric general circulation model

    Directory of Open Access Journals (Sweden)

    P. Räisänen

    2014-12-01

    Full Text Available The timing of springtime end of snowmelt (snow-off date in northern Eurasia in version 5.4 of the ECHAM5 atmospheric general circulation model (GCM is evaluated through comparison with a snow-off date data set based on space-borne microwave radiometer measurements and with Russian snow course data. ECHAM5 reproduces well the observed gross geographical pattern of snow-off dates, with earliest snow-off (in March in the Baltic region and latest snow-off (in June in the Taymyr Peninsula and in northeastern parts of the Russian Far East. The primary biases are (1 a delayed snow-off in southeastern Siberia (associated with too low springtime temperature and too high surface albedo, in part due to insufficient shielding by canopy; and (2 an early bias in the western and northern parts of northern Eurasia. Several sensitivity experiments were conducted, where biases in simulated atmospheric circulation were corrected through nudging and/or the treatment of surface albedo was modified. While this alleviated some of the model biases in snow-off dates, 2 m temperature and surface albedo, especially the early bias in snow-off in the western parts of northern Eurasia proved very robust and was actually larger in the nudged runs. A key issue underlying the snow-off biases in ECHAM5 is that snowmelt occurs at too low temperatures. Very likely, this is related to the treatment of the surface energy budget. On one hand, the surface temperature Ts is not computed separately for the snow-covered and snow-free parts of the grid cells, which prevents Ts from rising above 0 °C before all snow has vanished. Consequently, too much of the surface net radiation is consumed in melting snow and too little in heating the air. On the other hand, ECHAM5 does not include a canopy layer. Thus, while the albedo reduction due to canopy is accounted for, the shielding of snow on ground by the overlying canopy is not considered, which leaves too much solar radiation available for

  15. Light Attenuation in Falling Snow

    Science.gov (United States)

    1978-08-01

    Mexico 38002 DA Task No. 1L161102-B3A I I -CNTROLLING OFFICE NAME AkD ADDRESS 12 REPORT DATE US Army Electronics Resedrch 3 August 1978 and Development...Range 1.5 km 0- I ’ ’ I S1 1 VINO \\ t 01 111 -- I 0- l L _ l-..-1. . . i . . . 4 0 DiAMETER (CM) Figure 7. Snow particle size distribution functions

  16. Spatiotemporal analysis of snow trends in Austria

    Science.gov (United States)

    Koch, Roland; Schöner, Wolfgang

    2015-04-01

    This study presents the spatiotemporal analysis of Austrian snow observations. A set of consistent and reliable long-term time series of snow depth on a daily scale from selected meteorological sites across Austria is used. The time series were collected by the Central Institute for Meteorology and Geodynamics (ZAMG) and the Hydrographical Central Bureau of Austria (HZB). The data cover a time period from the late nineteenth century until today. In the first part of the study spatiotemporal characteristics of seasonal snow depth observations were investigated by the method of principal component analysis (PCA). Furthermore, the spatial patterns of variability have been used for a regionalisation, identifying regions with similar conditions during the base period 1961 to 2010. The results show a clear separation of four major regions including various sub-regions. However, the regionalisation was limited due to sparse data coverage. The non-parametric Mann-Kendall statistical test had been used to assess the significance of trends in snow indices, e.g. snow depth, maximum snow depth, snow cover duration, at monthly and seasonal time scales. In order to remove the influence of the lag-1 serial correlation from the snow data, the trend-free pre-whitening approach was applied. In the monthly and seasonal time series during the period 1961-2010, negative trends in snow indices were significant at the 95% confidence level primarily at stations in the Western and Southern part of Austria. In addition, the correlation between snow observations and gridded HISTALP winter temperature and precipitation fields was investigated. The analysis has shown an increased temperature and decreased precipitation during the 1990s, yielding a pronounced reduction in snow depth and duration. As a matter of fact, the results indicate major shifts of the snow depth and snow cover duration around the 1970s and especially the 1990s, which are predominantly responsible for trends.

  17. Snow specific surface area simulation using the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS)

    OpenAIRE

    2013-01-01

    Snow grain size is a key parameter for modeling microwave snow emission properties and the surface energy balance because of its influence on the snow albedo, thermal conductivity and diffusivity. A model of the specific surface area (SSA) of snow was implemented in the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS) version 3.4. This offline multilayer model (CLASS-SSA) simulates the decrease of SSA based on snow age, snow temperature and t...

  18. Assimilation of satellite information in a snowpack model to improve characterization of snow cover for runoff simulation and forecasting

    Directory of Open Access Journals (Sweden)

    L. S. Kuchment

    2009-08-01

    Full Text Available A new technique for constructing spatial fields of snow characteristics for runoff simulation and forecasting is presented. The technique incorporates satellite land surface monitoring data and available ground-based hydrometeorological measurements in a physical based snowpack model. The snowpack model provides simulation of temporal changes of the snow depth, density and water equivalent (SWE, accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The model was first calibrated against available ground-based snow measurements and then was applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The remote sensing data used in the model consist of products derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites. They include daily maps of snow cover, snow water equivalent (SWE, land surface temperature, and weekly maps of surface albedo. Maps of land cover classes and tree cover fraction derived from NOAA AVHRR were used to characterize the vegetation cover. The developed technique was tested over a study area of approximately 200 000 km2 located in the European part of Russia (56° N to 60° N, and 48° E to 54° E. The study area comprises the Vyatka River basin with the catchment area of 124 000 km2. The spatial distributions of SWE, obtained with the coupled model, as well as solely from satellite data were used as the inputs in a physically-based model of runoff generation to simulate runoff hydrographs on the Vyatka river for spring seasons of 2003, 2005. The comparison of simulated hydrographs with the observed ones has shown that suggested procedure gives a higher accuracy of snow cover spatial distribution representation and hydrograph simulations than the direct use of satellite SWE data.

  19. Assimilation of satellite information in a snowpack model to improve characterization of snow cover for runoff simulation and forecasting

    Science.gov (United States)

    Kuchment, L. S.; Romanov, P.; Gelfan, A. N.; Demidov, V. N.

    2009-08-01

    A new technique for constructing spatial fields of snow characteristics for runoff simulation and forecasting is presented. The technique incorporates satellite land surface monitoring data and available ground-based hydrometeorological measurements in a physical based snowpack model. The snowpack model provides simulation of temporal changes of the snow depth, density and water equivalent (SWE), accounting for snow melt, sublimation, refreezing melt water and snow metamorphism processes with a special focus on forest cover effects. The model was first calibrated against available ground-based snow measurements and then was applied to calculate the spatial distribution of snow characteristics using satellite data and interpolated ground-based meteorological data. The remote sensing data used in the model consist of products derived from observations of MODIS and AMSR-E instruments onboard Terra and Aqua satellites. They include daily maps of snow cover, snow water equivalent (SWE), land surface temperature, and weekly maps of surface albedo. Maps of land cover classes and tree cover fraction derived from NOAA AVHRR were used to characterize the vegetation cover. The developed technique was tested over a study area of approximately 200 000 km2 located in the European part of Russia (56° N to 60° N, and 48° E to 54° E). The study area comprises the Vyatka River basin with the catchment area of 124 000 km2. The spatial distributions of SWE, obtained with the coupled model, as well as solely from satellite data were used as the inputs in a physically-based model of runoff generation to simulate runoff hydrographs on the Vyatka river for spring seasons of 2003, 2005. The comparison of simulated hydrographs with the observed ones has shown that suggested procedure gives a higher accuracy of snow cover spatial distribution representation and hydrograph simulations than the direct use of satellite SWE data.

  20. Global Precipitation Measurement (GPM) Microwave Imager Falling Snow Retrieval Algorithm Performance

    Science.gov (United States)

    Skofronick Jackson, Gail; Munchak, Stephen J.; Johnson, Benjamin T.

    2015-04-01

    values and also updated Bayesian channel weights for various surface types. We will evaluate the algorithm that was released to the public in July 2014 and has already shown that it can detect and estimate falling snow. Performance factors to be investigated include the ability to detect falling snow at various rates, causes of errors, and performance for various surface types. A major source of ground validation data is ground-based radar composites. We will also provide qualitative information on known uncertainties and errors associated with both the satellite retrievals and the ground validation measurements. We will report on the analysis of our falling snow validation completed by the time of the EGU conference including the first complete northern hemisphere winter season. If available, results from improvements in the Bayesian database will be reported.

  1. [The research of the relationship between snow properties and the bidirectional polarized reflectance from snow surface].

    Science.gov (United States)

    Sun, Zhong-Qiu; Wu, Zheng-Fang; Zhao, Yun-Sheng

    2014-10-01

    In the context of remote sensing, the reflectance of snow is a key factor for accurate inversion for snow properties, such as snow grain size, albedo, because of it is influenced by the change of snow properties. The polarized reflectance is a general phenomenon during the reflected progress in natural incident light In this paper, based on the correct measurements for the multiple-angle reflected property of snow field in visible and near infrared wavelength (from 350 to 2,500 nm), the influence of snow grain size and wet snow on the bidirectional polarized property of snow was measured and analyzed. Combining the results measured in the field and previous conclusions confirms that the relation between polarization and snow grain size is obvious in infrared wavelength (at about 1,500 nm), which means the degree of polarization increasing with an increase of snow grain size in the forward scattering direction, it is because the strong absorption of ice near 1,500 nm leads to the single scattering light contributes to the reflection information obtained by the sensor; in other word, the larger grain size, the more absorption accompanying the larger polarization in forward scattering direction; we can illustrate that the change from dry snow to wet snow also influences the polarization property of snow, because of the water on the surface of snow particle adheres the adjacent particles, that means the wet snow grain size is larger than the dry snow grain size. Therefore, combining the multiple-angle polarization with reflectance will provide solid method and theoretical basis for inversion of snow properties.

  2. Mechanics of Ship Grounding

    DEFF Research Database (Denmark)

    Pedersen, Preben Terndrup

    1996-01-01

    In these notes first a simplified mathematical model is presented for analysis of ship hull loading due to grounding on relatively hard and plane sand, clay or rock sea bottoms. In a second section a more rational calculation model is described for the sea bed soil reaction forces on the sea bottom...

  3. Snow depth and snow persistence patterns in the Arctic from analysis of the entire Landsat archive

    Science.gov (United States)

    Macander, M. J.; Swingley, C. S.; Parr, C.; Sturm, M.; Selkowitz, D.; Larsen, C.

    2016-12-01

    The entire archive of Landsat 5 TM, Landat 7 ETM+, and Landsat 8 OLI imagery collected between March 1 and August 31, 1999-2016 was analyzed to map the presence or absence of snow, with consideration given to clouds, cloud shadows, terrain shadows, and canopy cover. Google Earth Engine was utilized to rapidly classify and summarize the entire time-series. The time-series of observations were then pooled across all the years and a binary classification tree determined the day of year that based split the observations into a snow-covered and a snow-free season. The analysis was completed for arctic Alaska and covers approximately one million square kilometers. The snow persistence product was validated using SNOTEL sites and MODIS time series metrics. The snow persistence patterns are highly correlated with end of winter snow depth patterns. We compared the Landsat snow persistence to the normal snow depth from repeat LIDAR surveys and field snow depth measurements and applied the results to estimate snow distribution over much larger regions. A nonlinear relationship between normal snow-free day of year and mean end of winter snow depth was observed. A polynomial model (r-squared = 0.95) was developed and was extrapolated to the surrounding area to produce a regional map of modeled mean end of winter snow depth.

  4. Snow cover regime in Livingston and Deception Islands (Maritime Antarctic) using multitemporal analysis of ASAR imagery from 2009.

    Science.gov (United States)

    Mora, Carla; Vieira, Gonçalo; Ramos, Miguel

    2010-05-01

    ASAR images from Envisat (WSW and IMM) are analyzed to study the snow cover regime of Deception and Livingston Islands (South Shetlands, Antarctic Peninsula) during 2009. The study is part of the project PERMANTAR focusing on monitoring and modeling the thermal regime of permafrost. For a GIS-based spatial modelling of snow cover distribution, spatially distributed data is required and the exploration of microwave remote sensing is the most suitable technique for mapping the snow cover characteristics and regime. This becomes especially true due to the long winter night and unstable weather conditions of the northern Antarctic Peninsula region. For this purpose a multitemporal ASAR imagery analysis was conducted in order to distinguish wet snow cover from snow free terrain using the absorption dependency of the radar signal on the liquid water content of the snow to set a threshold on the differential backscatter between scenes. The imagery was analyzed using the processing chains from NEST (ESA SAR Toolbox). Preliminary results of the analysis of the time-series show strong seasonal changes in the backscattering due to the variations of liquid water content in snow. Validation of the results obtained from the microwave imagery is done using the ground truth data. In January and February 2009 we have installed in Livingston and Deception islands time-lapse camera in key-areas, ultra-sonic sensors of the snow thickness and probes with snow temperature mini-loggers. This data will be collected from field sites n January 2010 and used for the calibration of the results. Satellite immagery is provided by the European Space Agency in the framework of the Proposal Category-1: Snow cover characteristics and regime in the South Shetlands (Maritime Antarctic) - SnowAntar.

  5. Application of the Markov Chain Monte Carlo method for snow water equivalent retrieval based on passive microwave measurements

    Science.gov (United States)

    Pan, J.; Durand, M. T.; Vanderjagt, B. J.

    2015-12-01

    Markov Chain Monte Carlo (MCMC) method is a retrieval algorithm based on Bayes' rule, which starts from an initial state of snow/soil parameters, and updates it to a series of new states by comparing the posterior probability of simulated snow microwave signals before and after each time of random walk. It is a realization of the Bayes' rule, which gives an approximation to the probability of the snow/soil parameters in condition of the measured microwave TB signals at different bands. Although this method could solve all snow parameters including depth, density, snow grain size and temperature at the same time, it still needs prior information of these parameters for posterior probability calculation. How the priors will influence the SWE retrieval is a big concern. Therefore, in this paper at first, a sensitivity test will be carried out to study how accurate the snow emission models and how explicit the snow priors need to be to maintain the SWE error within certain amount. The synthetic TB simulated from the measured snow properties plus a 2-K observation error will be used for this purpose. It aims to provide a guidance on the MCMC application under different circumstances. Later, the method will be used for the snowpits at different sites, including Sodankyla, Finland, Churchill, Canada and Colorado, USA, using the measured TB from ground-based radiometers at different bands. Based on the previous work, the error in these practical cases will be studied, and the error sources will be separated and quantified.

  6. Some fundamentals of handheld snow surface thermography

    Directory of Open Access Journals (Sweden)

    C. Shea

    2011-02-01

    Full Text Available This paper presents the concepts needed to perform snow surface thermography with a modern thermal imager. Snow-specific issues in the 7.5 to 13 μm spectrum such as ice emissivity, photographic angle, operator heating, and others receive detailed review and discussion. To illustrate the usefulness of this measurement technique, various applications are presented. These include detecting spatial temperature variation on snow pit walls and measuring the dependence of heat conduction on grain type.

  7. Some fundamentals of handheld snow surface thermography

    Directory of Open Access Journals (Sweden)

    C. Shea

    2010-08-01

    Full Text Available This paper presents the concepts needed to perform snow surface thermography with a modern thermal imager. Snow-specific issues in the 7.5 to 13 μm spectrum such as ice emissivity, photographic angle, operator heating, and others receive detailed review and discussion. To illustrate the usefulness of this measurement technique, various applications are presented. These include detecting spatial temperature variation on snow pit walls and measuring the dependence of heat conduction on grain type.

  8. Observed Differences between North American Snow Extent and Snow Depth Variability

    Science.gov (United States)

    Ge, Y.; Gong, G.

    2006-12-01

    Snow extent and snow depth are two related characteristics of a snowpack, but they need not be mutually consistent. Differences between these two variables at local scales are readily apparent. However at larger scales which interact with atmospheric circulation and climate, snow extent is typically the variable used, while snow depth is often assumed to be minor and/or mutually consistent compared to snow extent, though this is rarely verified. In this study, a new regional/continental-scale gridded dataset derived from field observations is utilized to quantitatively evaluate the relationship between snow extent and snow depth over North America. Various statistical methods are applied to assess the mutual consistency of monthly snow depth vs. snow extent, including correlations, composites and principal components. Results indicate that snow depth variations are significant in their own rights, and that depth and extent anomalies are largely unrelated, especially over broad high latitude regions north of the snowline. In the vicinity of the snowline, where precipitation and ablation can affect both snow extent and snow depth, the two variables vary concurrently, especially in autumn and spring. It is also found that deeper winter snow translates into larger snow-covered area in the subsequent spring/summer season, which suggests a possible influence of winter snow depth on summer climate. The observed lack of mutual consistency at continental/regional scales suggests that snowpack depth variations may be of sufficiently large magnitude, spatial scope and temporal duration to influence regional-hemispheric climate, in a manner unrelated to the more extensively studied snow extent variations.

  9. Remote Sensing of Snow in the Solar Spectrum: Experiments in the French Alps.

    Directory of Open Access Journals (Sweden)

    M. Fily

    2000-04-01

    Full Text Available Two experiments were perfonned irliApril and December 1992 in the French Alps using simultaneous relnote sensing and ground truth data. Snow grain site and soot content of samples collected in thefield were measured. The Landsat thematic mapper (TM sensor was used because it has a good spatial resolution, a middle infrared channel which is sensitive to grain size and a thermal infraredchannel. Firstj the reflectance data were compared with the theoretical results obtained from a bidirectional reflectance model. Then, some remote sehstng-derived snow parameters wbre comparediWith the outpllt ofa snow metamorphism model (CROCUS,viz., lower elevation of the snowcover, lhe surface grl1in size and the surface temperature. A digital elevation model was used to obtain thelocal incidenc:f angles and the elevation of each snow pixel. The pixels were then grouped according to CROCUS classification (range, elevation, slope, and orientation and the mean snow chart;cheracteristicsfor each class were .compared with the tROCUS results. The lower limit of snow and the surface grain size derived from TM data were compared favourably with the model results. Larger differences werefound for the temperature, because it varies rapidly and is very sensitive to shadowing by the snrrounding mountains and also because its remote measurement is dependent on atmospheric conditions.

  10. Design, Development and Testing of Web Services for Multi-Sensor Snow Cover Mapping

    Science.gov (United States)

    Kadlec, Jiri

    This dissertation presents the design, development and validation of new data integration methods for mapping the extent of snow cover based on open access ground station measurements, remote sensing images, volunteer observer snow reports, and cross country ski track recordings from location-enabled mobile devices. The first step of the data integration procedure includes data discovery, data retrieval, and data quality control of snow observations at ground stations. The WaterML R package developed in this work enables hydrologists to retrieve and analyze data from multiple organizations that are listed in the Consortium of Universities for the Advancement of Hydrologic Sciences Inc (CUAHSI) Water Data Center catalog directly within the R statistical software environment. Using the WaterML R package is demonstrated by running an energy balance snowpack model in R with data inputs from CUAHSI, and by automating uploads of real time sensor observations to CUAHSI HydroServer. The second step of the procedure requires efficient access to multi-temporal remote sensing snow images. The Snow Inspector web application developed in this research enables the users to retrieve a time series of fractional snow cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) for any point on Earth. The time series retrieval method is based on automated data extraction from tile images provided by a Web Map Tile Service (WMTS). The average required time for retrieving 100 days of data using this technique is 5.4 seconds, which is significantly faster than other methods that require the download of large satellite image files. The presented data extraction technique and space-time visualization user interface can be used as a model for working with other multi-temporal hydrologic or climate data WMTS services. The third, final step of the data integration procedure is generating continuous daily snow cover maps. A custom inverse distance weighting method has been developed

  11. The reflectance characteristics of snow covered surfaces

    Science.gov (United States)

    Batten, E. S.

    1979-01-01

    Data analysis techniques were developed to most efficiently use available satellite measurements to determine and understand components of the surface energy budget for ice and snow-covered areas. The emphasis is placed on identifying the important components of the heat budget related to snow surfaces, specifically the albedo and the energy consumed in the melting process. Ice and snow charts are prepared by NOAA from satellite observations which map areas into three relative reflectivity zones. Field measurements are analyzed of the reflectivity of an open snow field to assist in the interpretation of the NOAA reflectivity zones.

  12. Remotely Measuring Snow Depth in Inaccessible Terrain

    Science.gov (United States)

    Dixon, D.; Boon, S.

    2010-12-01

    In watershed-scale studies of snow accumulation, high alpine areas are typically important accumulation areas. While snow depth measurements may not be collected in these regions due to avalanche danger, failing to include them in basin-wide estimates of snow accumulation may lead to large underestimates of basin-scale water yield. We present a new method to measure spatially distributed point snow depths remotely. Previously described methods using terrestrial laser scanning (TLS) systems, airborne light detection and ranging (LiDAR) systems, and hand-held laser distance meters have several limitations related to cost, data processing, and accuracy, thus reducing their applicability. The use of a modern robotic total station attempts to resolve these limitations. Total stations have much greater measurement accuracy than laser distance meters, and are significantly less expensive then TLS and LiDAR systems. Data can be output in common data formats, simplifying data processing and management. Measurement points can also be resampled repeatedly throughout the season with high accuracy and precision. Simple trigonometry is used to convert total station measurements into estimates of snow depth perpendicular to the slope. We present results of remote snow depth measurements using a Leica Geosystems TCRP 1201+ robotic total station. Snow depth estimates from the station are validated against measured depths in a field trial. The method is then applied in a basin-scale study to collect and calculate high elevation snow depth, in combination with traditional snow surveys at lower elevations.

  13. Microwave emission from dry and wet snow

    Science.gov (United States)

    Chang, T. C.; Gloersen, P.

    1975-01-01

    A microscopic model was developed to study the microwave emission from snow. In this model, the individual snow particles are considered to be the scattering centers. Mie scattering theory for spherical particles is then used to compute the volume scattering and extinction coefficients of the closely packed scattering spheres, which are assumed not to interact coherently. The results of the computations show significant volume scattering effects in the microwave region which result in low observed emissivities from cold, dry snow. In the case of wet snow, the microwave emissivities are increased considerably, in agreement with earlier experimental observations in which the brightness temperatures have increased significantly at the onset of melting.

  14. Snow Conditions Near Barrow in Spring 2012

    Science.gov (United States)

    Webster, M.; Rigor, I.; Nghiem, S. V.; Sturm, M.; Kurtz, N. T.; Farrell, S. L.; Gleason, E.; Lieb-Lappen, R.; Saiet, E.

    2012-12-01

    Snow has a dual role in the growth and decay of Arctic sea ice. It provides insulation from colder air temperatures during the winter, which hinders sea ice formation. Snow is highly reflective and, as a result, it delays the surface ice melt during the spring. Summer snow melt influences the formation and location of melt ponds on sea ice, which further modifies heat transport into sea ice and the underlying ocean. Identifying snow thickness and extent is of key importance in understanding the surface heat budget, particularly during the early spring when the maximum snowfall has surpassed, and surface melt has not yet occurred. Regarding Arctic atmospheric chemical processes, snow may sustain or terminate halogen chemical recycling and distribution, depending on the state of the snow cover. Therefore, an accurate assessment of the snow cover state in the changing Arctic is important to identify subsequent impacts of snow change on both physical and chemical processes in the Arctic environment. In this study, we assess the springtime snow conditions near Barrow, Alaska using coordinated airborne and in situ measurements taken during the NASA Operation IceBridge and BRomine, Ozone, and Mercury EXperiment (BROMEX) field campaigns in March 2012, and compare these to climatological records. Operation IceBridge was conceived to bridge the gap between satellite retrievals ice thickness by ICESat which ceased operating in 2009 and ICESat-2 which is planned for launch in 2016. As part of the IceBridge mission, snow depth may be estimated by taking the difference between the snow/air surface and the snow/ice interface measured by University of Kansas's snow radar installed on a P-3 Orion and the measurements have an approximate spatial resolution of 40 m along-track and 16 m across-track. The in situ snow depth measurements were measured by an Automatic Snow Depth Probe (Magnaprobe), which has an accuracy of 0.5 cm. Samples were taken every one-to-two meters at two sites

  15. Infrasound monitoring of snow avalanches in the Italian Alps

    Science.gov (United States)

    Ripepe, Maurizio; Ulivieri, Giacomo; Marchetti, Emanuele; Chiambretti, Igor; Segor, Valerio; Pitet, Luca

    2010-05-01

    Risk assessment of snow avalanches is mostly related to weather conditions and snow cover. However a robust risk validation requires to identify all avalanches occurring, in order to compare predictions to real effects. For this purpose on December 2009 we installed a temporary 4-element, small aperture (100 m), infrasound array in the Alps. The array has been deployed south of Mt. Rosa, at an elevation of 2000 m a.s.l. in the valley of Gressoney, where natural avalanches are expected and triggered ones are regularly programmed. The array consists into 4 absolute pressure transducers with a sensitivity of 0.01 Pa in the 0.1-50 Hz frequency band and a 7 channel Guralp CMG-DM24 A/D converter, sampling at 100 Hz. Timing is achieved with a GPS receiver. The array is completely buried in snow. Gel cell batteries and 200 W solar panels provide the array power requirements (~3 W) and should allow a continuous operation during the winter season. A multi-channel semblance is carried out on the continuous data set as a function of slowness, back-azimuth and frequency of recorded infrasound in order to detect all avalanches occurring from the back-ground signal, strongly affected by microbarom and mountain induced gravity waves. This pilot experiment in Italy will allow to verify the efficiency of the system, and might represent an important validation to modeled avalanches activity during this winter season.

  16. Operational snow mapping with simplified data assimilation using the seNorge snow model

    Science.gov (United States)

    Saloranta, Tuomo M.

    2016-07-01

    Frequently updated maps of snow conditions are useful for many applications, e.g., for avalanche and flood forecasting services, hydropower energy situation analysis, as well as for the general public. Numerical snow models are often applied in snow map production for operational hydrological services. However, inaccuracies in the simulated snow maps due to model uncertainties and the lack of suitable data assimilation techniques to correct them in near-real time may often reduce the usefulness of the snow maps in operational use. In this paper the revised seNorge snow model (v.1.1.1) for snow mapping is described, and a simplified data assimilation procedure is introduced to correct detected snow model biases in near real-time. The data assimilation procedure is theoretically based on the Bayesian updating paradigm and is meant to be pragmatic with modest computational and input data requirements. Moreover, it is flexible and can utilize both point-based snow depth and satellite-based areal snow-covered area observations, which are generally the most common data-sources of snow observations. The model and analysis codes as well as the "R" statistical software are freely available. All these features should help to lower the challenges and hurdles hampering the application of data-assimilation techniques in operational hydrological modeling. The steps of the data assimilation procedure (evaluation, sensitivity analysis, optimization) and their contribution to significantly increased accuracy of the snow maps are demonstrated with a case from eastern Norway in winter 2013/2014.

  17. Avoiding errors attributable to topography in GPS-IR snow depth retrievals

    Science.gov (United States)

    Zhang, Shuangcheng; Wang, Xiaolei; Zhang, Qin

    2017-03-01

    Global Positioning System (GPS) interferometric reflectometry represents a potential source of new snow data for climate scientists and water managers with spatial and temporal sensitivity. Generally, the snow layer fluctuation is considered to be correlated with the ground surface fluctuation. The reflector heights in terms of the signal-to-noise ratio (SNR) are quite close to the vertical distance between the antenna and the ground or snow level at the corresponding Fresnel zone. The reflector heights at different zones were represented by a grid model in this work, which can reflect and overcome some of the problems caused by the topography. The proposed method for snow depth retrievals looks for good quality reflector height values of the horizontal reflecting zone in the grid model, and with this method improvements in snow depth retrieval accuracy were achieved (RMSE: 7.40 cm, Corr.: 0.99) compared to the PBO H2O group calculation results (RMSE: 16.58 cm, Corr.: 0.99).

  18. 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.

  19. Investigations on snow parameters by radiometry in the 3- to 60-mm wavelength region

    Science.gov (United States)

    Hofer, R.; MäTzler, C.

    1980-01-01

    We report on a 2-year period of monitoring parameters of a natural snowpack by ground-based microwave radiometry on a high-altitude Alpine test site. The microwave brightness temperatures are compared to a large set of ground-truth data. Three stages in the seasonal development of the snow cover are easily distinguishable which allow the prediction of the beginning of the snow melting. The moisture content of the melting surface layer is estimated by the aid of the typical daily variations of microwave brightness temperatures in spring. The test site was composed of two snow fields. The first one was lying on slightly reflecting soil, and the second one was lying on a completely reflecting metal foil. By measuring on both fields some microwave snow parameters can be determined. The damping coefficients for microwaves between 5 and 100 GHz were estimated by comparing the results of two extreme theories. Both theories gave results from less than 1 dB/m to more than 30 dB/m depending on the snow state, especially its liquid water content.

  20. Modeling visible and near-infrared snow surface reflectance-simulation and validation

    Institute of Scientific and Technical Information of China (English)

    Hongyi Wu; Ling Tong

    2011-01-01

    Retrieving snow surface reflectance is difficult in optical remote sensing.Hence,this letter evaluates five surface reflectance models,including the Ross-Li,Roujean,Walthall,modified Rahman and Staylor models,in terms of their capacities to capture snow reflectance signatures using ground measurements in Antarctica.The biases of all the models are less than 0.0003 in both visible and near-infrared regions.Moreover,with the exception of the Staylor model,all models have root-mean-square errors of around 0.02,indicating that they can simulate the reflectance magnitude well.The R2 performances of the Ross-Li and Roujean models are higher than those of the others,indicating that these two models can capture the angle distribution of snow surface reflectance better.The bidirectional reflectance distribution flmction (BRDF) characterizes the angular distribution of surface reflection[1,2].It plays an important role in performing atmospheric correction,detecting land cover types,and calculating other biophysical parameters[3].Howcver,the retrieval of snow BRDF/albedo is always a difficult issue in the application of remotely sensed information.%Retrieving snow surface reflectance is difficult in optical remote sensing. Hence, this letter evaluates five surface reflectance models, including the Ross-Li, Roujean, Walthall, modified Rahman and Staylor models, in terms of their capacities to capture snow reflectance signatures using ground measurements in Antarctica. The biases of all the models are less than 0.0003 in both visible and near-infrared regions. Moreover, with the exception of the Staylor model, all models have root-mean-square errors of around 0.02, indicating that they can simulate the reflectance magnitude well. The R2 performances of the Ross-Li and Roujean models are higher than those of the others, indicating that these two models can capture the angle distribution of snow surface reflectance better.

  1. The "Teflon basin" myth: Snow-soil interactions in mountain catchments in the western US

    Science.gov (United States)

    Williams, M. W.; Cowie, R. M.

    2015-12-01

    In much of western North America, snow and snowmelt provide the primary means for storage of winter precipitation, effectively transferring water from the relatively wet winter season to the typically dry summers. A common assumption is that high-elevation catchments in the western United States behave like "Teflon basins" and that water released from seasonal storage in snow packs flows directly into streams with little or no interaction with underlying soils. Here I present information from a variety of catchments in the Colorado Front Range on snowmelt/soil interactions using isotopic, geochemical, nutrient and hydrometric data in 2- and 3- component hydrograph separations, along with end-member mixing analysis (EMMA). For most catchments we measured these parameters in weekly precipitation, the seasonal snowpack, snowmelt before contact with the ground, discharge, springs, soil solution, and groundwater. We ran EMMA at the catchment scale for catchments that represent the rain-snow transition zone in the montane forest, the seasonally snow covered sub-alpine to alpine transition zone, and a high-elevation alpine zone near the continental divide. In all catchments three end-members were the source waters for about 95% of discharge. Two end-members were the same in all catchments, snow and groundwater. For the alpine catchment talus springs was the third water source, while rain was the third water source in the two lower-elevation catchments. For all three catchments, soil solution plotted with stream waters along or near a line connecting the snow and groundwater end-members. Thus, for seasonally snow-covered catchments from montane to alpine ecosystems, snowmelt infiltrates underlying soils before snowmelt recharges groundwater reservoirs and contributes to surface flows. Seasonally snow-covered catchments are not Teflon basins. Rather, snowmelt infiltrates soils where solute concentrations are changed by biological and geochemical processes.

  2. Dynamics of snow cover characteristics exerting influence on stability of the Svalbard permafrost

    Directory of Open Access Journals (Sweden)

    N. I. Osokin

    2016-01-01

    Full Text Available Climate variations result in changes of the snow cover characteristics which have a certain influence upon thermal state and stability of permafrost. Analysis of data of meteorological station Barentsburg (Svalbard and our own observations has revealed small change in the snow cover thickness for the period 1984–2015. At the same time, duration of the snow cover presence has shortened by 8%. In recent years, more than 60% of the snow cover thickness was formed during the early third of the cold season which adversely affects a rate of the ground freezing. Durations of thaws increased from 12 to 22 days, and the rainfall amount decreased during the cold period from 60 to 120 mm. The largest increase in the thaw duration (by a factor of 7 and decrease of the rainfall amount (by a factor of 8 fall on January and February. Summing up of the thaw duration and the rainfall amount for the 5‑year periods demonstrated significant growth of both. It should be noted also that, according to data of the Barentsburg station and our ones, in a few last years, these parameters reached anomalously high values. Appearance of anomalous values of the snow cover thickness as well as of the dates of its onset became more frequent. For the last decade, recurrence of anomalous values of the snow cover thickness increased: one event for 2.4 years before 2000, and one occurrence of anomalous thickness for 1.4 years since 2001. The later onset of snow cover resulted in shortening of duration of its presence. Occurrence of anomalous duration of the snow cover presence was observed once for 4.3 years before 2001, and once for 3.3 years after 2000.

  3. A Full Snow Season in Yellowstone: A Database of Restored Aqua Band 6

    Science.gov (United States)

    Gladkova, Irina; Grossberg, Michael; Bonev, George; Romanov, Peter; Riggs, George; Hall, Dorothy

    2013-01-01

    The algorithms for estimating snow extent for the Moderate Resolution Imaging Spectroradiometer (MODIS) optimally use the 1.6- m channel which is unavailable for MODIS on Aqua due to detector damage. As a test bed to demonstrate that Aqua band 6 can be restored, we chose the area surrounding Yellowstone and Grand Teton national parks. In such rugged and difficult-to-access terrain, satellite images are particularly important for providing an estimation of snow-cover extent. For the full 2010-2011 snow season covering the Yellowstone region, we have used quantitative image restoration to create a database of restored Aqua band 6. The database includes restored radiances, normalized vegetation index, normalized snow index, thermal data, and band-6-based snow-map products. The restored Aqua-band-6 data have also been regridded and combined with Terra data to produce a snow-cover map that utilizes both Terra and Aqua snow maps. Using this database, we show that the restored Aqua-band-6-based snow-cover extent has a comparable performance with respect to ground stations to the one based on Terra. The result of a restored band 6 from Aqua is that we have an additional band-6 image of the Yellowstone region each day. This image can be used to mitigate cloud occlusion, using the same algorithms used for band 6 on Terra. We show an application of this database of restored band-6 images to illustrate the value of creating a cloud gap filling using the National Aeronautics and Space Administration s operational cloud masks and data from both Aqua and Terra.

  4. Black carbon in snow in the upper Himalayan Khumbu Valley, Nepal: observations and modeling of the impact on snow albedo, melting, and radiative forcing

    Directory of Open Access Journals (Sweden)

    H.-W. Jacobi

    2014-10-01

    Full Text Available Black carbon (BC in the snow in the Himalayas has recently attracted considerable interest due to its impact on snow albedo, snow and glacier melting, regional climate and water resources. A single particle soot photometer (SP2 instrument was used to measure refractory BC (rBC in a series of surface snow samples collected in the upper Khumbu Valley in Nepal between November 2009 and February 2012. The obtained time series indicates annual cycles with maximum concentration before the onset of the monsoon season and fast decreases in rBC during the monsoon period. Measured concentrations ranged from a few ppb up to 70 ppb rBC. However, due to the handling of the samples the measured concentrations possess rather large uncertainties. Detailed modeling of the snowpack including the measured range and an estimated upper limit of rBC concentrations was performed to study the role of BC in the seasonal snowpack. Simulations were performed for three winter seasons with the snowpack model Crocus including a detailed description of the radiative transfer inside the snowpack. While the standard Crocus model strongly overestimates the height and the duration of the seasonal snowpack, a better calculation of the snow albedo with the new radiative transfer scheme enhanced the representation of the snow. However, the period with snow on the ground neglecting BC in the snow was still over-estimated between 37 and 66 days, which was further diminished by 8 to 15% and more than 40% in the presence of 100 or 300 ppb of BC. Compared to snow without BC the albedo is on average reduced by 0.027 and 0.060 in the presence of 100 and 300 ppb BC. While the impact of increasing BC in the snow on the albedo was largest for clean snow, the impact on the local radiative forcing is the opposite. Here, increasing BC caused an even larger impact at higher BC concentrations. This effect is related to an accelerated melting of the snowpack caused by a more efficient metamorphism

  5. Thermodynamic hardness and the maximum hardness principle

    Science.gov (United States)

    Franco-Pérez, Marco; Gázquez, José L.; Ayers, Paul W.; Vela, Alberto

    2017-08-01

    An alternative definition of hardness (called the thermodynamic hardness) within the grand canonical ensemble formalism is proposed in terms of the partial derivative of the electronic chemical potential with respect to the thermodynamic chemical potential of the reservoir, keeping the temperature and the external potential constant. This temperature dependent definition may be interpreted as a measure of the propensity of a system to go through a charge transfer process when it interacts with other species, and thus it keeps the philosophy of the original definition. When the derivative is expressed in terms of the three-state ensemble model, in the regime of low temperatures and up to temperatures of chemical interest, one finds that for zero fractional charge, the thermodynamic hardness is proportional to T-1(I -A ) , where I is the first ionization potential, A is the electron affinity, and T is the temperature. However, the thermodynamic hardness is nearly zero when the fractional charge is different from zero. Thus, through the present definition, one avoids the presence of the Dirac delta function. We show that the chemical hardness defined in this way provides meaningful and discernible information about the hardness properties of a chemical species exhibiting integer or a fractional average number of electrons, and this analysis allowed us to establish a link between the maximum possible value of the hardness here defined, with the minimum softness principle, showing that both principles are related to minimum fractional charge and maximum stability conditions.

  6. Weekly LiDAR snow depth mapping for operational snow hydrology - the NASA JPL Airborne Snow Observatory (Invited)

    Science.gov (United States)

    Deems, J. S.; Painter, T. H.; McGurk, B. J.

    2013-12-01

    Operational hydrologic simulation and forecasting in snowmelt-dominated watersheds currently relies on indices of snow accumulation and melt from measurements at a small number of point locations or geographically-limited manual surveys. These data sources cannot adequately characterize the spatial distribution of snow depth/water equivalent, which is the primary determinant of snowpack volume and runoff rates. The NASA JPL Airborne Snow Observatory's airborne laser scanning system maps snow depth at high spatial and temporal resolutions, providing an unprecedented snowpack monitoring capability and enabling a new operational paradigm. In the Spring of 2013, the ASO mapped snow depth in the Tuolumne River Basin in California's Yosemite National Park on a nominally weekly basis, and provided fast-turnaround spatial snow depth and water equivalent maps to the operators of Hetch Hetchy Reservoir, the water supply for 2.5 million people on the San Francisco peninsula. These products enabled more accurate runoff simulation and optimal reservoir management in a year of very low snow accumulation. We present the initial results from this new application of multi-temporal LiDAR mapping in operational snow hydrology.

  7. Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations

    Science.gov (United States)

    Bühler, Yves; Adams, Marc S.; Bösch, Ruedi; Stoffel, Andreas

    2016-05-01

    Detailed information on the spatiotemporal snow depth distribution is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Today, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network like the one in Switzerland, with more than one measurement station per 10 km2 on average, is not able to capture the large spatial variability of snow depth present in alpine terrain.Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, in most countries such data acquisition is costly if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UASs), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Compared to manual measurements, such systems are relatively cost-effective and can be applied very flexibly to cover terrain not accessible from the ground. In this study, we map snow depth at two different locations: (a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and (b) an exposed location on a peak (2500 m a.s.l.) in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) of less than 0.07 to 0.15 m on meadows and rocks and a RMSE of less than 0.30 m on sections covered by bushes or tall grass, compared to manual probe measurements

  8. Some considerations about snow crystallogenesis

    CERN Document Server

    Falcon, Federico

    2010-01-01

    We investigate about the possibility of knowing the thermal history of each snow crystal through the analysis of its individual habitus. Supposition, based on experimental observations, that prevailing growth mechanisms of basal and prismatic surfaces are helicoidal and 2D nucleation-spread, respectively, make possible to establish the relation temperature-habitus for all the different kinds of crystals, with the exception of plates in the interval -3^\\circ C < T < 0^\\circ C, where probably the surface melting plays an important role on the habitus development.

  9. Digging in 'Snow White' Trench

    Science.gov (United States)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Surface Stereo Imager on the 44th Martian day of the mission, or Sol 43 (July 7, 2008), after the May 25, 2008, landing, showing the current sample scraping area in the trench informally called 'Snow White.' The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is led by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  10. Wear of hard materials by hard particles

    Energy Technology Data Exchange (ETDEWEB)

    Hawk, Jeffrey A.

    2003-10-01

    Hard materials, such as WC-Co, boron carbide, titanium diboride and composite carbide made up of Mo2C and WC, have been tested in abrasion and erosion conditions. These hard materials showed negligible wear in abrasion against SiC particles and erosion using Al2O3 particles. The WC-Co materials have the highest wear rate of these hard materials and a very different material removal mechanism. Wear mechanisms for these materials were different for each material with the overall wear rate controlled by binder composition and content and material grain size.

  11. Acetaldehyde in the Alaskan subarctic snow pack

    Directory of Open Access Journals (Sweden)

    F. Domine

    2009-09-01

    Full Text Available Acetaldehyde is a reactive intermediate in hydrocarbon oxidation. It is both emitted and taken up by snowpacks and photochemical and physical processes are probably involved. Understanding the reactivity of acetaldehyde in snow and its processes of physical and chemical exchanges requires the knowledge of its incorporation mechanism in snow crystals. We have performed a season-long study of the evolution of acetaldehyde concentrations in the subarctic snowpack near Fairbanks (65° N, central Alaska, which is subjected to a vigorous metamorphism due to persistent elevated temperature gradients in the snowpack, between 20 and 200°C m−1. The snowpack therefore almost entirely transforms into depth hoar. We have also analyzed acetaldehyde in a manipulated snowpack where temperature gradients were suppressed. Snow crystals there transformed much more slowly and their original shapes remained recognizable for months. The specific surface area of snow layers in both types of snowpacks was also measured. We deduce that acetaldehyde is not adsorbed onto the surface of snow crystals and that most of the acetaldehyde is probably not dissolved in the ice lattice of the snow crystals. We propose that most of the acetaldehyde measured is either trapped or dissolved within organic aerosol particles trapped in snow, or that acetaldehyde is formed by the hydrolysis of organic precursors contained in organic aerosols trapped in the snow, when the snow is melted for analysis. These precursors are probably aldehyde polymers formed within the aerosol particles by acid catalysis, but might also be biological molecules. In a laboratory experiment, acetaldehyde-di-n-hexyl acetal, representing a potential acetaldehyde precursor, was subjected to our analytical procedure and reacted to form acetaldehyde. This confirms our suggestion that acetaldehyde in snow could be produced during the melting of snow for analysis.

  12. Use of satellite images in snow water equivalent (SWE) estimation in the Upper Vistula drainage basin in southern Poland

    Science.gov (United States)

    Kasina, M.; Chamerlinska, A.; Lasek, J.; Przeniczny, P.

    2013-12-01

    Snow-water equivalent (SWE) and snow depth are the two most important parameters used in hydrological forecasting offices to estimate the amount of water stored in the form of snow. These two parameters are essential during snowmelt periods when rapid snowmelt (often combined with rainfall) causes slow-onset floods. In this case, the water equivalent can be used as an indicator of the amount of water expected in runoff. So far the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB) produces this estimate based only on SWE and snow depth data obtained from meteorological stations at five day intervals. The two measurements are performed at shorter intervals either when heavy snowfall occurs or when the mean daily air temperature exceeds 0οC. The main aim of this project is to improve the existing method of snow water equivalent estimation by using satellite-derived data. Snow-water equivalent data and the extent of snow cover were derived from satellite products prepared within the H-SAF Project, which is the EUMETSAT Network of Satellite Application Facility dedicated to support Operational Hydrology and Water Management. Both H10 - Snow mask by VIS/IR radiometry and H11 - Snow water equivalent by MW radiometry products are derived in a daily time step. It then becomes possible to compare and further assimilate ground-truth data. Other analyses included Bayesian Kriging spatial interpolation, which is suitable for non-stationary data. The method described in this paper - same as other methods based on satellite derived data - is weather dependent and it is limited to cloud-free periods. A comparison of results obtained using this method and results obtained using ground-based data calculations proved its applicability in lowland areas. In mountainous regions, where differences in SWE values strongly depend on elevation, the obtained SWE values were underestimated.

  13. Vegetation and Variable Snow Cover: Spatial Patterns of Shrubland, and Grassland Snow

    Science.gov (United States)

    Liston, G. E.; Hiemstra, C. A.; Strack, J. E.

    2003-12-01

    Regions that experience long winters with snowfall and high winds frequently exhibit heterogeneous snow distribution patterns that arise from interactions among snow, wind, topography, and vegetation. Variable snow cover and resultant heterogeneities in albedo and growing season length can affect local weather patterns and energy budgets, and produce spatially co-variable ecosystem properties. While snow influences local atmospheric processes and ecosystems, an important and underappreciated feedback exists between vegetation and snow cover. Plant size, canopy density, and rigidity determine how much snow accumulates on the lee side of individual plants (e.g., shrubland vs. grassland). In addition, the canopy can also influence how much energy reaches the snowpack, thereby hindering or accelerating snowmelt. An overhanging canopy reduces incoming solar radiation while providing a source of turbulent sensible and longwave radiative energy. Historically, most snow vegetation interaction studies have been limited to areas that experience an abundance of snow (e.g., mountainous areas) where trees have a large influence on seasonal snow-cover. In contrast, snow cover patterns associated with shrublands and grasslands have received little attention, despite covering vast expanses (53%) of the seasonally snow-covered globe. In this study, snow depths were measured every two weeks from December through March in a small, 0.25 km2 study area located in North Park, Colorado. The study area possesses little topographic relief and consists of shrub patches, dominated by greasewood (Sarcobatus vermiculatus) and sagebrush (Artemisia tridentata), embedded in a matrix of graminoids (sedges, rushes, and grasses). Snow cover patterns and spatial statistics were dramatically different in graminoid-dominated cover compared with shrub cover. The graminoid snow cover was thinner, less variable, and more ephemeral than the shrub snow pack. Snow was readily eroded by wind from graminoid

  14. Vehicle Impact Testing of Snow Roads at McMurdo Station, Antarctica

    Science.gov (United States)

    2014-06-01

    including the im- portance of the tire and suspension components, on preserving satisfacto- ry snow-road surfaces through the melt season. DISCLAIMER: The...in kilo- grams force, kgf). The hardness reading is calculated from the number of hammer blows (drops) required to penetrate a measured distance...Clegg Impact Value (CIV). Although the fourth drop CIV reading is usually used for soil-strength calculations , we used an average of the third

  15. The effect of vegetation cover on the formation of glide-snow avalanches

    Science.gov (United States)

    Feistl, Thomas; Bebi, Peter; Bartelt, Perry

    2014-05-01

    Glide snow avalanches release on steep, smooth slopes and can be prevented either by protection forests or by artificial defense structures. To minimize the risk for people and infrastructure, guidelines have been formulated concerning structure, height and distance between avalanche prevention bridges. These guidelines assure the major functions of the defense structures: first to prevent the release of avalanches and second to withstand the static and dynamic forces of the moving snow cover. The major functions of protection forests are generally similar and therefore guidelines on the maximum tolerable size of forest gaps exist in Switzerland. These guidelines are based on a static relationship between the pressure of the snow cover and the resistance of the defense structure and on empirical observations (forest). Whereas ground friction is only qualitatively taken into account, we assume it to play a crucial role in glide snow avalanche formation. To prove this assumption we collected data on the predominant vegetation cover of 67 release areas in the region of Davos, Switzerland. Our observations reveal a strong relationship between vegetation cover type, slope angle and slab length. We were able to quantify the Coulomb friction parameter μ by applying a physical model that accounts for the dynamic forces of the moving snow on the stauchwall, the fixed snow cover below the release area. The stauchwall resists the dynamic forces of the snow cover, until a critical strain rate is reached and then fails in brittle compression. This failure strongly depends on the friction between snow cover and soil. A typical value of μ for grassy slopes is 0.2. Snow characteristics like density are implemented in the model as constants. We compared the model results with the guidelines for defense structures and forest gap sizes and found accordance for certain friction parameter values. Forest gaps of 40 meter length and a 35° slope angle require friction values of 0

  16. An Inexpensive, Implantable Electronic Sensor for Autonomous Measurement of Snow Pack Parameters

    Science.gov (United States)

    De Roo, R. D.; Haengel, E.; Rogacki, S.

    2015-12-01

    Snow accumulations on the ground are an important source of water in many parts of the world. Mapping the accumulation, usually represented as the snow water equivalent (SWE), is valuable for water resource management. The longest record of regional and global maps of SWE are from orbiting microwave radiometers, which do not directly measure SWE but rather measure the scatter darkening from the snow pack. Robustly linking the scatter darkening to SWE eludes us to this day, in part because the snow pack is highly variable in both time and space. The data needed is currently collected by hand in "snow pits," and the labor-intensive process limits the size of the data sets that can be obtained. In particular, time series measurements are only a one or two samples per day at best, and come at the expense of spatial sampling. We report on the development of a low-power wireless device that can be embedded within a snow pack to report on some of the critical parameters needed to understand scatter darkening. The device autonomously logs temperature, the microwave dielectric constant and infrared backscatter local to the device. The microwave dielectric constant reveals the snow density and the presence of liquid water, while the infrared backscatter measurement, together with the density measurement, reveals a characteristic grain size of the snow pack. The devices are made to be inexpensive (less than $200 in parts each) and easily replicated, so that many can be deployed to monitor variations vertically and horizontally in the snow pack. The low-power operation is important both for longevity of observations as well as insuring minimal anomalous metamorphism of the snow pack. The hardware required for the microwave measurement is intended for wireless communications, and this feature will soon be implemented for near real-time monitoring of snow conditions. We will report on the design, construction and initial deployment of about 30 of these devices in northern lower

  17. Modeling the spatial variability of snow instability with the snow cover model SNOWPACK

    Science.gov (United States)

    Richter, Bettina; Reuter, Benjamin; Gaume, Johan; Fierz, Charles; Bavay, Mathias; van Herwijnen, Alec; Schweizer, Jürg

    2016-04-01

    Snow stratigraphy - key information for avalanche forecasting - can be obtained using numerical snow cover models driven by meteorological data. Simulations are typically performed for the locations of automatic weather station or for virtual slopes of varying aspect. However, it is unclear to which extent these simulations can represent the snowpack properties in the surrounding terrain, in particular snow instability, which is known to vary in space. To address this issue, we implemented two newly developed snow instability criteria in SNOWPACK relating to failure initiation and crack propagation, two fundamental processes for dry-snow slab avalanche release. Snow cover simulations were performed for the Steintälli field site above Davos (Eastern Swiss Alps), where snowpack data from several field campaigns are available. In each campaign, about 150 vertical snow penetration resistance profiles were sampled with the snow micro-penetrometer (SMP). For each profile, SMP and SNOWPACK- based instability criteria were compared. In addition, we carried out SNOWPACK simulations for multiple aspects and slope angles, allowing to obtain statistical distributions of the snow instability at the basin scale. Comparing the modeled to the observed distributions of snow instability suggests that it is feasible to obtain an adequate spatial representation of snow instability without high resolution distributed modeling. Hence, for the purpose of regional avalanche forecasting, simulations for a selection of virtual slopes seems sufficient to assess the influence of basic terrain features such as aspect and elevation.

  18. Snow and rain chemistry around the “Severonikel” industrial complex, NW Russia: Current status and retrospective analysis

    Science.gov (United States)

    Kashulina, Galina; de Caritat, Patrice; Reimann, Clemens

    2014-06-01

    The current (2005-2011) status of the chemical composition of snow cover and rain collected at a height of 1.5 m above ground was studied within 11 km around the Severonikel industrial complex, one of the largest SO2 and metal contamination sources in N Europe. In spite of a significant decrease in emissions during the past 20 years, Ni and Cu concentrations in snow remain extremely high near the source (2500 and 1500 times background values, respectively). Although showing a five- to six-fold decrease in Ni and Cu concentrations since 1994, rain water currently still has concentrations 150 and 80 times background, respectively. Differences in the chemical composition of snow pack and rain collected at a height of 1.5 m above ground in this case are not caused by seasonal effects, but rather by the height of precipitation sampling relative to the ground.

  19. A drought index accounting for snow

    Science.gov (United States)

    Staudinger, Maria; Stahl, Kerstin; Seibert, Jan

    2015-04-01

    The Standardized Precipitation Index (SPI) is the most widely used index to characterize and monitor droughts that are related to precipitation deficiencies. However, the SPI does not always deliver the relevant information for hydrological drought management when precipitation deficiencies are not the only reason for droughts as it is the case for example in snow influenced catchments. If precipitation is temporarily stored as snow, then there is a significant difference between meteorological and hydrological drought because the delayed release of melt water from the snow accumulation to the stream. In this study we introduce an extension to the SPI, the Standardized Snow Melt and Rain Index (SMRI), that captures both rain and snow melt deficits, which in effect modify streamflow. The SMRI does not require any snow data instead observations of temperature and precipitation are used to model snow. The SMRI is evaluated for seven Swiss catchments with varying degrees of snow influence. In particular for catchments with a larger component of snowmelt in runoff generation, we found the SMRI to be a good complementary index to the SPI to describe streamflow droughts. In a further step, the SPI and the SMRI were compared for the summer drought of 2003 and the spring drought of 2011 for Switzerland, using gridded products of precipitation and temperature including the entire country.

  20. Characteristics, dynamics and significance of marine snow

    Science.gov (United States)

    Alldredge, Alice L.; Silver, Mary W.

    Macroscopic aggregates of detritus, living organisms and inorganic matter known as marine snow, have significance in the ocean both as unique, partially isolated microenvironments and as transport agents: much of surface-derived matter in the ocean fluxes to the ocean interior and the sea floor as marine snow. As microhabitats, marine snow aggregates contain enriched microbial communities and chemical gradients within which processes of photosynthesis, decomposition, and nutrient regeneration occur at highly elevated levels. Microbial communities associated with marine snow undergo complex successional changes on time scales of hours to days which significantly alter the chemical and biological properties of the particles. Marine snow can be produced either de novo by living plants and animals especially as mucus feeding webs of zooplankton, or by the biologically-enhanced physical aggregation of smaller particles. By the latter pathway, microaggregates, phytoplankton, fecal pellets, organic debris and clay-mineral particles collide by differential settlement or physical shear and adhere by the action of various, biologically-generated, organic compounds. Diatom flocculation is a poorly understood source of marine snow of potential global significance. Rates of snow production and breakdown are not known but are critical to predicting flux and to understanding biological community structure and transformations of matter and energy in the water column. The greatest challenge to the study of marine snow at present is the development of appropriate technology to measure abundances and characteristics of aggregates in situ.

  1. Modelling stable atmospheric boundary layers over snow

    NARCIS (Netherlands)

    Sterk, H.A.M.

    2015-01-01

    Thesis entitled: Modelling Stable Atmospheric Boundary Layers over Snow H.A.M. Sterk Wageningen, 29th of April, 2015 Summary The emphasis of this thesis is on the understanding and forecasting of the Stable Boundary Layer (SBL) over snow-covered surfaces. SBLs typically form at night and in polar re

  2. Prevent Snow from Blocking your Tailpipe

    Centers for Disease Control (CDC) Podcasts

    2014-12-11

    If it's snowing, make sure your vehicle’s tailpipe is clear of snow before starting the engine to prevent carbon monoxide poisoning.  Created: 12/11/2014 by National Center for Environmental Health (NCEH).   Date Released: 12/11/2014.

  3. Modelling stable atmospheric boundary layers over snow

    NARCIS (Netherlands)

    Sterk, H.A.M.

    2015-01-01

    Thesis entitled: Modelling Stable Atmospheric Boundary Layers over Snow H.A.M. Sterk Wageningen, 29th of April, 2015 Summary The emphasis of this thesis is on the understanding and forecasting of the Stable Boundary Layer (SBL) over snow-covered surfaces. SBLs typically form at night and in polar re

  4. Livestock Husbandry and Snow Leopard Conservation

    NARCIS (Netherlands)

    Mohammad, Ghulam; Mostafawi, Sayed Naqibullah; Dadul, Jigmet; Rosen, Tatjana; Mishra, Charudutt; Bhatnagar, Yash Veer; Trivedi, Pranav; Timbadia, Radhika; Bijoor, Ajay; Murali, Ranjini; Sonam, Karma; Thinley, Tanzin; Namgail, Tsewang; Prins, Herbert H.T.; Nawaz, Muhammad Ali; Ud Din, Jaffar; Buzdar, Hafeez

    2016-01-01

    Livestock depredation is a key source of snow leopard mortality across much of the species' range. Snow leopards break into livestock corrals, killing many domestic animals and thereby inflicting substantial economic damage. Locals may retaliate by killing the cat and selling its parts.

  5. User requirements for satellite snow data service

    Energy Technology Data Exchange (ETDEWEB)

    Kolberg, S.; Standley, A.; Hiltbrunner, D.; Hallikainen, M.

    1997-12-31

    This report discusses the answers given by ten users or potential users of remotely sensed snow data when asked about their data needs and present measurements, their requirements for remote sensing data and potential of using such, and the models or other analysis tools in which the information is used. The answers show both consensus and differences among the respondents` use of snow data and requirements for remote sensing snow products. For water resources planning and management, the most important variable is snow water equivalent, with acceptable errors around 10%. Acceptable spatial error is typically in the range of 200 m to 1 km. For flood forecasting and short-term runoff simulation, snow covered area is more important, with a classification of 5 to 8 steps being generally sufficient. Meteorologists tend to focus on albedo and snow coverage data, with 5% steps desired for albedo. Geometric resolution and accuracy is less important, temporal resolution and delivery time is more important than in water resource management. For avalanche use, most snow variables except water equivalent are important, several in depth profiles. Spatial and temporal requirements are high. In all user groups there is a desire for models which can use measured values quantitatively. Today, measured snow information is largely interpreted manually and subjectively and lead to actions based on experience and judgement. The organizing of measurements, simulations and calibrated sub-models with varying uncertainty levels is partly a conceptual problem, partly a software problem. 1 ref.

  6. Comments on Nancy Snow, "Generativity and Flourishing"

    Science.gov (United States)

    Kamtekar, Rachana

    2015-01-01

    In her rich and wide-ranging paper, Nancy Snow argues that there is a virtue of generativity--an other-regarding desire to invest one's substance in forms of life and work that will outlive the self (p. 10). By "virtue" Snow means not just a desirable or praiseworthy quality of a person, but more precisely, as Aristotle defined it, a…

  7. Livestock Husbandry and Snow Leopard Conservation

    NARCIS (Netherlands)

    Mohammad, Ghulam; Mostafawi, Sayed Naqibullah; Dadul, Jigmet; Rosen, Tatjana; Mishra, Charudutt; Bhatnagar, Yash Veer; Trivedi, Pranav; Timbadia, Radhika; Bijoor, Ajay; Murali, Ranjini; Sonam, Karma; Thinley, Tanzin; Namgail, Tsewang; Prins, Herbert H.T.; Nawaz, Muhammad Ali; Ud Din, Jaffar; Buzdar, Hafeez

    2016-01-01

    Livestock depredation is a key source of snow leopard mortality across much of the species' range. Snow leopards break into livestock corrals, killing many domestic animals and thereby inflicting substantial economic damage. Locals may retaliate by killing the cat and selling its parts. Predator-

  8. Livestock Husbandry and Snow Leopard Conservation

    NARCIS (Netherlands)

    Mohammad, Ghulam; Mostafawi, Sayed Naqibullah; Dadul, Jigmet; Rosen, Tatjana; Mishra, Charudutt; Bhatnagar, Yash Veer; Trivedi, Pranav; Timbadia, Radhika; Bijoor, Ajay; Murali, Ranjini; Sonam, Karma; Thinley, Tanzin; Namgail, Tsewang; Prins, Herbert H.T.; Nawaz, Muhammad Ali; Ud Din, Jaffar; Buzdar, Hafeez

    2016-01-01

    Livestock depredation is a key source of snow leopard mortality across much of the species' range. Snow leopards break into livestock corrals, killing many domestic animals and thereby inflicting substantial economic damage. Locals may retaliate by killing the cat and selling its parts. Predator-

  9. Modelling stable atmospheric boundary layers over snow

    NARCIS (Netherlands)

    Sterk, H.A.M.

    2015-01-01

    Thesis entitled: Modelling Stable Atmospheric Boundary Layers over Snow H.A.M. Sterk Wageningen, 29th of April, 2015 Summary The emphasis of this thesis is on the understanding and forecasting of the Stable Boundary Layer (SBL) over snow-covered surfaces. SBLs typically form at night and in polar

  10. Another Story of Snow white

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    "白兰氏"杯 2006 广东省中学生英语作文比赛决赛题(初中组)命题作文:你的读者是国际幼儿园的 3- 6 岁的小朋友。实际上, 你的作文是要读给他们听的。内容是鼓励孩子们回家后做一件促进文明保护环境的具体的事。可以包括爱护环境、讲究卫生、节约不浪费资源、爱护小动物、语言和行为文明。文体不限 ( 可以包括倡议书、阐述文、议论文、散文、诗歌、童话等)。自定题目。 My dear children,have you ever heard of the story of Snow White?You are very clever children,I know you must remember the happy ending in the story. The beautiful girl who named Snow White went to live in the palace with her lover. Do you want to know what happend next?listen carefully and I'll tell you the story . It is said ...

  11. Observing snow cover using unmanned aerial vehicle

    Science.gov (United States)

    Spallek, Waldemar; Witek, Matylda; Niedzielski, Tomasz

    2016-04-01

    Snow cover is a key environmental variable that influences high flow events driven by snow-melt episodes. Estimates of snow extent (SE), snow depth (SD) and snow water equivalent (SWE) allow to approximate runoff caused by snow-melt episodes. These variables are purely spatial characteristics, and hence their pointwise measurements using terrestrial monitoring systems do not offer the comprehensive and fully-spatial information on water storage in snow. Existing satellite observations of snow reveal moderate spatial resolution which, not uncommonly, is not fine enough to estimate the above-mentioned snow-related variables for small catchments. High-resolution aerial photographs and the resulting orthophotomaps and digital surface models (DSMs), obtained using unmanned aerial vehicles (UAVs), may offer spatial resolution of 3 cm/px. The UAV-based observation of snow cover may be done using the near-infrared (NIR) cameras and visible-light cameras. Since the beginning of 2015, in frame of the research project no. LIDER/012/223/L-5/13/NCBR/2014 financed by the National Centre for Research and Development of Poland, we have performed a series of the UAV flights targeted at four sites in the Kwisa catchment in the Izerskie Mts. (part of the Sudetes, SW Poland). Observations are carried out with the ultralight UAV swinglet CAM (produced by senseFly, lightweight 0.5 kg, wingspan 80 cm) which enables on-demand sampling at low costs. The aim of the field work is to acquire aerial photographs taken using the visible-light and NIR cameras for a purpose of producing time series of DSMs and orthophotomaps with snow cover for all sites. The DSMs are used to calculate SD as difference between observational (with snow) and reference (without snow) models. In order to verify such an approach to compute SD we apply several procedures, one of which is the estimation of SE using the corresponding orthophotomaps generated on a basis of visual-light and NIR images. The objective of this

  12. A conceptual, distributed snow redistribution model

    Science.gov (United States)

    Frey, S.; Holzmann, H.

    2015-11-01

    When applying conceptual hydrological models using a temperature index approach for snowmelt to high alpine areas often accumulation of snow during several years can be observed. Some of the reasons why these "snow towers" do not exist in nature are vertical and lateral transport processes. While snow transport models have been developed using grid cell sizes of tens to hundreds of square metres and have been applied in several catchments, no model exists using coarser cell sizes of 1 km2, which is a common resolution for meso- and large-scale hydrologic modelling (hundreds to thousands of square kilometres). In this paper we present an approach that uses only gravity and snow density as a proxy for the age of the snow cover and land-use information to redistribute snow in alpine basins. The results are based on the hydrological modelling of the Austrian Inn Basin in Tyrol, Austria, more specifically the Ötztaler Ache catchment, but the findings hold for other tributaries of the river Inn. This transport model is implemented in the distributed rainfall-runoff model COSERO (Continuous Semi-distributed Runoff). The results of both model concepts with and without consideration of lateral snow redistribution are compared against observed discharge and snow-covered areas derived from MODIS satellite images. By means of the snow redistribution concept, snow accumulation over several years can be prevented and the snow depletion curve compared with MODIS (Moderate Resolution Imaging Spectroradiometer) data could be improved, too. In a 7-year period the standard model would lead to snow accumulation of approximately 2900 mm SWE (snow water equivalent) in high elevated regions whereas the updated version of the model does not show accumulation and does also predict discharge with more accuracy leading to a Kling-Gupta efficiency of 0.93 instead of 0.9. A further improvement can be shown in the comparison of MODIS snow cover data and the calculated depletion curve, where

  13. Surface decontamination using dry ice snow

    Energy Technology Data Exchange (ETDEWEB)

    Ryu, Jungdong; Park, Kwangheon [College of Mechnical and Industrial System Engineering, Kyunghee University, Yongin (Korea, Republic of); Lee, Bumsik; Kim Yangeun [Wolsung Nuclear Power Plants, KEPCO (Korea, Republic of)

    1999-07-01

    An adjustable nozzle for controlling the size of dry ice snow was developed. The converging/diverging nozzle can control the size of snows from sub-microns to 10 micron size. Using the nozzle, a surface decontamination device was made. The removal mechanisms of surface contaminants are mechanical impact, partial dissolving and evaporation process, and viscous flow. A heat supply system is added for the prevention of surface ice layer formation. The cleaning power is slightly dependent on the size of snow. Small snows are the better in viscous flow cleaning, while large snows are slightly better in dissolving and sublimation process. Human oils like fingerprints on glass were easy to remove. Decontamination ability was tested using a contaminated pump-housing surface. About 40 to 80% of radioactivity was removed. This device is effective in surface-decontamination of any electrical devices like detector, controllers which cannot be cleaned in aqueous solution. (author)

  14. Constraining snow model choices in a transitional snow environment with intensive observations

    Science.gov (United States)

    Wayand, N. E.; Massmann, A.; Clark, M. P.; Lundquist, J. D.

    2014-12-01

    The performance of existing energy balance snow models exhibits a large spread in the simulated snow water equivalent, snow depth, albedo, and surface temperature. Indentifying poor model representations of physical processes within intercomparison studies is difficult due to multiple differences between models as well as non-orthogonal metrics used. Efforts to overcome these obstacles for model development have focused on a modeling framework that allows multiple representations of each physical process within one structure. However, there still exists a need for snow study sites within complex terrain that observe enough model states and fluxes to constrain model choices. In this study we focus on an intensive snow observational site located in the maritime-transitional snow climate of Snoqualmie Pass WA (Figure 1). The transitional zone has been previously identified as a difficult climate to simulate snow processes; therefore, it represents an ideal model-vetting site. From two water years of intensive observational data, we have learned that a more honest comparison with observations requires that the modeled states or fluxes be as similar to the spatial and temporal domain of the instrument, even if it means changing the model to match what is being observed. For example, 24-hour snow board observations do not capture compaction of the underlying snow; therefore, a modeled "snow board" was created that only includes new snow accumulation and new snow compaction. We extend this method of selective model validation to all available Snoqualmie observations to constrain model choices within the Structure for Understanding Multiple Modeling Alternatives (SUMMA) framework. Our end goal is to provide a more rigorous and systematic method for diagnosing problems within snow models at a site given numerous snow observations.

  15. Evaluation of snow dynamics modelling on a pixel scale using terrestrial photography and Ensemble Transform Kalman Filtering

    Science.gov (United States)

    Pimentel, Rafael; José Pérez-Palazón, María; Herrero, Javier; José Polo, María

    2016-04-01

    Snow plays a crucial role in the hydrological regime in mountainous catchments, which increases in semiarid regions, where the recurrence of drought period makes it necessary to accurate the determination of the water availability from the snowpack. Physically based approaches constitute one of the best ways to reproduce the snow dynamics over these highly variable conditions. Moreover, they allow further understanding the processes involved, the snowpack behaviour and evolution. However, in some cases the complexity of the modelled process and the non-availability of all the required data for such models, avoid a correct representation of certain aspects. In these cases, data assimilation techniques can help to improve model performance and may also act as an indirect tool to understand the represented processes. This work assesses snow dynamics on a pixel scale (30x30m) in a Mediterranean site (Sierra Nevada Mountain, southern Spain) combining physical snow modelling (WiMMed, a physically based hydrological model developed for Mediterranean environments), ground sensing information (terrestrial photography) and data assimilation techniques (Ensemble Transform Kalman Filter), throughout a study period of two hydrological years: 2009-2010 and 2010-2011. Snow cover fraction and averaged snow depth were obtained from the terrestrial photography images and used as observations in the assimilation scheme. The model performance was evaluated using different combinations of the variables assimilated: 1) only snow cover fraction, 2) only snow depth, 3) and both variables. The results show how the assimilation enhances the model performance. This improvement is higher if the variable assimilated is snow depth, with RMSE= 0.14 m2m-2and RMSE=12.16 mm for snow cover and snow depth respectively. However, this enhancement varies throughout the study period. During short snowmelt cycles, for example, the assimilation of the snow cover fraction is the most efficient. Nevertheless

  16. On the Importance of High-Resolution Time Series of Optical Imagery for Quantifying the Effects of Snow Cover Duration on Alpine Plant Habitat

    Directory of Open Access Journals (Sweden)

    Jean-Pierre Dedieu

    2016-06-01

    Full Text Available We investigated snow cover dynamics using time series of moderate (MODIS to high (SPOT-4/5, Landsat-8 spatial resolution satellite imagery in a 3700 km2 region of the southwestern French Alps. Our study was carried out in the context of the SPOT (Take 5 Experiment initiated by the Centre National d’Etudes Spatiales (CNES, with the aim of exploring the utility of high spatial and temporal resolution multispectral satellite imagery for snow cover mapping and applications in alpine ecology. Our three objectives were: (i to validate remote sensing observations of first snow free day derived from the Normalized Difference Snow Index (NDSI relative to ground-based measurements; (ii to generate regional-scale maps of first snow free day and peak standing biomass derived from the Normalized Difference Vegetation Index (NDVI; and (iii to examine the usefulness of these maps for habitat mapping of herbaceous vegetation communities above the tree line. Imagery showed strong agreement with ground-based measurements of snow melt-out date, although R2 was higher for SPOT and Landsat time series (0.92 than for MODIS (0.79. Uncertainty surrounding estimates of first snow free day was lower in the case of MODIS, however (±3 days as compared to ±9 days for SPOT and Landsat, emphasizing the importance of high temporal as well as high spatial resolution for capturing local differences in snow cover duration. The main floristic differences between plant communities were clearly visible in a two-dimensional habitat template defined by the first snow free day and NDVI at peak standing biomass, and these differences were accentuated when axes were derived from high spatial resolution imagery. Our work demonstrates the enhanced potential of high spatial and temporal resolution multispectral imagery for quantifying snow cover duration and plant phenology in temperate mountain regions, and opens new avenues to examine to what extent plant community diversity and

  17. 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

  18. 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

  19. 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.

  20. Quantification of basal friction for glide-snow avalanche mitigation measures in forested and non-forested terrain

    Directory of Open Access Journals (Sweden)

    T. Feistl

    2014-04-01

    Full Text Available A long-standing problem in avalanche engineering is to design defense structures and manage forest stands such that they can withstand the forces of the natural snow cover. In this way glide-snow avalanches can be prevented. Ground friction plays a crucial role in this process. To verify existing guidelines, we collected data on the vegetation cover and terrain characteristics of 101 glide-snow release areas in Davos, Switzerland. We quantified the Coulomb friction parameter μ by applying a physical model that accounts for the dynamic forces of the moving snow on the stauchzone. We investigated the role of glide length, slope steepness and friction on avalanche release. Our calculations revealed that the slope angle and slab length for smooth slopes corresponds to the technical guidelines for defense structure distances in Switzerland. Artificial defense structures, built in accordance with guidelines, prevent glide-snow avalanche releases, even when the terrain is smooth. Slopes over 40 m length and 45° steepness require a ground friction of μ = 0.7 corresponding to stumps or tree regeneration to assure protection. Forest management guidelines which define maximum forest gap sizes to prevent glide-snow avalanche release neglect the role of surface roughness and therefore underestimate the danger on smooth slopes.

  1. Snow modeling using SURFEX with the CROCUS snow scheme for Norway

    Science.gov (United States)

    Vikhamar-Schuler, D.; Müller, K.

    2012-04-01

    In 2010 a research project was initiated with the aim to investigate methods to establish a regional snow avalanche forecasting system for Norway. A part of this project concerns snow models that simulate snow stratigraphy and physical parameters in the snow pack. For this purpose we have used the CROCUS snow scheme within the land surface model SURFEX for the location of 18 weather stations in Norway. We have carried out a sensitivity study of available meteorological data. Few weather stations have measurements of all the parameters used by the model on an hourly basis. Therefore it is interesting to investigate if certain parameters can be replaced by short-term prognoses from the operational weather prediction models (Unified Model-4 km, HARMONIE-4 km and postprocessed prognoses of temperature and precipitation). This study indicates that short-term prognoses of radiation, air humidity, wind and air pressure may replace observations without loosing the quality of the snow simulations. For all stations the modeled snow depth is validated with the observed snow depth for the last 2-3 winter seasons. Our results show that the modeled snow depth is most sensitive to precipitation and air temperature. Overall, very good estimates of the snow depth are obtained using the CROCUS snow scheme, except for very wind exposed stations. Temperatures within the snowpack were compared with observations of snow temperature at the Filefjell station, showing promising results. A cold bias was observed, but daily variations were reasonably modeled. During the winter 2011/2012 a series of snow stratigraphy observations from the Filefjell station is carried out for validation purposes of other intra-snowpack physical properties (density, liquid water content, temperature, grain type).

  2. Coping with difficult weather and snow conditions: Reindeer herders’ views on climate change impacts and coping strategies

    Directory of Open Access Journals (Sweden)

    Minna T. Turunen

    2016-01-01

    Full Text Available Winter is a critical season for reindeer herding, with the amount and quality of snow being among the most important factors determining the condition of reindeer and the annual success of the livelihood. Our first aim was to model the future (2035–2064 snow conditions in northern Finland, especially the quantities related to ground ice and/or ice layers within the snow pack, exceptionally deep snow and late snow melt. Secondly, we studied the strategies by which herders cope with the impacts of difficult weather and snow conditions on herding by interviewing 21 herders. SNOWPACK simulations indicate that snow cover formation will be delayed by an average of 19 days and snow will melt 16 days earlier during the period 2035–2064 when compared to 1980–2009. There will be more frequent occurrence of ground ice that persists through the winter and the ice layers in open environments will be thicker in the future. The snow cover will be 26–40% thinner and snow in open environments will be denser. Variability between winters will grow. In interviews, herders indicated that a longer snowless season and thin snow cover would be advantageous for herding due to increased availability of forage, but more frequent icing conditions would cause problems. The most immediate reaction of reindeer to the decreased availability of forage caused by difficult snow conditions is to disperse. This effect is intensified when the lichen biomass on the pastures is low. To cope with the impacts of adverse climatic conditions, herders increase control over their herds, intensify the use of pasture diversity, take reindeer into enclosures and/or start or intensify supplementary feeding. The research also reveals that predators, competing land uses and the high prices of supplementary feed and fuel were the major threats to the herders’ coping capacity. Coping capacity was facilitated by, among other factors, the herders’ experience-based traditional knowledge

  3. [Was Snow White a transsexual?].

    Science.gov (United States)

    Michel, A; Mormont, C

    2002-01-01

    modalities in the transsexual dynamics. Nevertheless, one can ask oneself about the possibility of a request based on a desire rather than on a defense, or even on the existence of a defensive process diametrically opposed to the counter-phobic attitude and which, instead of actively provoking the dreaded reality, would privilege its avoidance and the search of passivity. This latter hypothesis has the advantage of being rather easy to explore with the Rorschach because, according to Exner, the predominance of passive compared to active human movement responses (which he terms the Snow White Syndrome) indicates the propensity to escape into passive fantasies and the tendency to avoid the initiative for behaviour or decision-making, if other people can do it in the subject's place (12). Our results largely confirmed the hypothesis of the existence of an opposite mechanism, as a third of subjects (n = 26) presented Snow White Syndrome. According to Exner, these transsexuals are typically characterized by hiding into a world of make believe, avoiding all responsibility, as well as any decision-making. This passivity in our Snow White Syndrome group was all the more remarkable in that, on the whole, it infiltrated into all the movement responses and seemed to define a rigid style of thinking and mental elaboration, in addition to a suggestive content of passivity. However, this condition cannot be associated with a general lack of dynamism or energy. In fact, the treatment of information, which provides data concerning the motivation to treat a stimulus field of the stimulus--whether this concerns the capture (L) of the stimulus or the elaboration (DQ+) of the response--displayed a sufficient amount of motivation. Furthermore, internal resources (EA) were considerable and were brought into play whenever it was necessary to adopt a behaviour or make a decision. Furthermore, based on these Rorschach findings, we note that in transsexuals with Snow White Syndrome, there is a

  4. The Snow Data System at NASA JPL

    Science.gov (United States)

    Laidlaw, R.; Painter, T. H.; Mattmann, C. A.; Ramirez, P.; Brodzik, M. J.; Rittger, K.; Bormann, K. J.; Burgess, A. B.; Zimdars, P.; McGibbney, L. J.; Goodale, C. E.; Joyce, M.

    2015-12-01

    The Snow Data System at NASA JPL includes a data processing pipeline built with open source software, Apache 'Object Oriented Data Technology' (OODT). It produces a variety of data products using inputs from satellites such as MODIS, VIIRS and Landsat. Processing is carried out in parallel across a high-powered computing cluster. Algorithms such as 'Snow Covered Area and Grain-size' (SCAG) and 'Dust Radiative Forcing in Snow' (DRFS) are applied to satellite inputs to produce output images that are used by many scientists and institutions around the world. This poster will describe the Snow Data System, its outputs and their uses and applications, along with recent advancements to the system and plans for the future. Advancements for 2015 include automated daily processing of historic MODIS data for SCAG (MODSCAG) and DRFS (MODDRFS), automation of SCAG processing for VIIRS satellite inputs (VIIRSCAG) and an updated version of SCAG for Landsat Thematic Mapper inputs (TMSCAG) that takes advantage of Graphics Processing Units (GPUs) for faster processing speeds. The pipeline has been upgraded to use the latest version of OODT and its workflows have been streamlined to enable computer operators to process data on demand. Additional products have been added, such as rolling 8-day composites of MODSCAG data, a new version of the MODSCAG 'annual minimum ice and snow extent' (MODICE) product, and recoded MODSCAG data for the 'Satellite Snow Product Intercomparison and Evaluation Experiment' (SnowPEx) project.

  5. Application and improvement of a georadar system to assess areal snow distribution for advances in hydrological modeling

    Energy Technology Data Exchange (ETDEWEB)

    Marchand, Wolf-Dietrich

    2003-10-01

    A good understanding of the snow processes in the hydrological cycle is crucial in the design of hydrological models in cold regions. Problems are often connected to the missing information on snowcover in remote areas (where the largest amount of snow usually allocates) as well as the lack of ability to simulate or even predict the complex processes of the interaction between the snow and its environment. The objective of this study is to contribute to a further clarification of both of these obstacles. The most effective way of gathering snowcover information is the accomplishment of snow measurements. In recent years, a lot of emphasis has been put on satellite techniques. However, concerning the measurement of snowcover properties, which is more than snow covered area only, satellite techniques are still in the beginning stages and ground-truth data are needed. In many places, conventional ground-based measurements are still common practice. These measurements are warrantable, but traditional manual measurements cannot supply sufficient amounts of data for modern, computer based Geographic Information System (GIS) analyses and distributed hydrological modeling. Thus, it is well worth improving the ground based measuring methods. One goal of the presented research was the improvement of an existing radar system for snow depth measurements. An interface module was used to connect the radar to a Global Positioning System (GPS) receiver. One major advantage of the entire system was the ease of further use of snow data in the GIS. Every snow depth sample had a GPS position and a sufficient amount of data was warranted by the effectiveness of the radar. A study area was determined and snow data were collected for three consecutive winter seasons. clue purpose benefit A comparison study on ground-based and airborne snowradar was made. The results showed good congruence between both data sets, even if the performance of both techniques was different. The second aim of

  6. Assimilation of Airborne Snow Observatory Snow Water Equivalent to Improve Runoff Forecasting Model Performance and Reservoir Management During Warm and Dry Winters

    Science.gov (United States)

    McGurk, B. J.; Painter, T. H.

    2015-12-01

    The Airborne Snow Observatory (ASO) NASA-JPL demonstration mission has collected detailed snow information for portions of the Tuolumne Basin in California for three years, 2013 - 2015. Both 2014 and 2015 were low snow years, and 2015 was exceptionally warm and analogous to future years after climate change. The ASO uses an imaging spectrometer and LiDAR sensors mounted in an aircraft to collect snow depth and extent data, and snow albedo. By combining ground and modeled density fields, the ~weekly flights over the Tuolumne produced both basin-wide and detailed sub-basin snow water equivalent (SWE) estimates that were provided to Hetch Hetchy Reservoir operators. The data were also assimilated into an hydrologic simulation model in an attempt to improve the accuracy and timing of a runoff forecasting tool that can be used to improve the management of Hetch Hetchy Reservoir, the source of 85% of the water supply for 2.6 million people on the San Francisco Peninsula. The USGS Precipitation Runoff Modeling System was calibrated to the 1181 square kilometer basin and simulation results compared to observed runoff with and without assimilation of ASO data. Simulated and observed were also compared with observed with both single updates associated with each flight, and with sequential updates from each flight. Sequential updating was found to improve correlation between observed and simulated reservoir inflows, and there by improve the ability of reservoir operators to more efficiently allocate the last half of the recession limb of snowmelt inflow and be assured of filling the reservoir and minimizing ecologically-damaging late season spills.

  7. Potential for Monitoring Snow Cover in Boreal Forests by Combining MODIS Snow Cover and AMSR-E SWE Maps

    Science.gov (United States)

    Riggs, George A.; Hall, Dorothy K.; Foster, James L.

    2009-01-01

    Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed

  8. Mapping snow depth in open alpine terrain from stereo satellite imagery

    Science.gov (United States)

    Marti, R.; Gascoin, S.; Berthier, E.; de Pinel, M.; Houet, T.; Laffly, D.

    2016-07-01

    To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. Here, we examine the potential of very-high-resolution (VHR) optical stereo satellites to this purpose. Two triplets of 0.70 m resolution images were acquired by the Pléiades satellite over an open alpine catchment (14.5 km2) under snow-free and snow-covered conditions. The open-source software Ame's Stereo Pipeline (ASP) was used to match the stereo pairs without ground control points to generate raw photogrammetric clouds and to convert them into high-resolution digital elevation models (DEMs) at 1, 2, and 4 m resolutions. The DEM differences (dDEMs) were computed after 3-D coregistration, including a correction of a -0.48 m vertical bias. The bias-corrected dDEM maps were compared to 451 snow-probe measurements. The results show a decimetric accuracy and precision in the Pléiades-derived snow depths. The median of the residuals is -0.16 m, with a standard deviation (SD) of 0.58 m at a pixel size of 2 m. We compared the 2 m Pléiades dDEM to a 2 m dDEM that was based on a winged unmanned aircraft vehicle (UAV) photogrammetric survey that was performed on the same winter date over a portion of the catchment (3.1 km2). The UAV-derived snow depth map exhibits the same patterns as the Pléiades-derived snow map, with a median of -0.11 m and a SD of 0.62 m when compared to the snow-probe measurements. The Pléiades images benefit from a very broad radiometric range (12 bits), allowing a high correlation success rate over the snow-covered areas. This study demonstrates the value of VHR stereo satellite imagery to map snow depth in remote mountainous areas even when no field data are available.

  9. Mac OS X Snow Leopard pocket guide

    CERN Document Server

    Seiblod, Chris

    2009-01-01

    Whether you're new to the Mac or a longtime user, this handy book is the quickest way to get up to speed on Snow Leopard. Packed with concise information in an easy-to-read format, Mac OS X Snow Leopard Pocket Guide covers what you need to know and is an ideal resource for problem-solving on the fly. This book goes right to the heart of Snow Leopard, with details on system preferences, built-in applications, and utilities. You'll also find configuration tips, keyboard shortcuts, guides for troubleshooting, lots of step-by-step instructions, and more. Learn about new features and changes s

  10. Tensile Strength of Snow using Centrifugal Technique

    Directory of Open Access Journals (Sweden)

    Agraj Upadhyay

    2007-11-01

    Full Text Available Tensile strength of snow was determined using indigenously developed automated centrifugalmachine. Processed snow (sintered at 20 °C for 4 days samples of dia: 65 mm andheight:130 mm were tested using this machine.The experiments were conducted on sieved snowat four temperature levels of 0 °C, 3 °C,6 °C and 9 °C at density ranging from 200-460 kg/m3.Results of these experiments have been compared with the earlier  suggested models. Probabilitydistribution of snow strength on the basis of current experimental data has also been presented.

  11. Resume of Interview with Professor Charles Snow

    Directory of Open Access Journals (Sweden)

    Dorthe Døjbak Håkonsson

    2015-04-01

    Full Text Available This interview is with Professor Charles Snow. Snow is Professor Emeritus of Strategy and Organization at Penn State University. He was a professor at Penn State from 1974 to 2012. The interview was conducted in 2013 while he was visiting professor at ICOA (Interdisciplinary Center for Organizational Architecture at Aarhus University. Professor Snow is a founding member of the Organizational Design Community and co-editor of the Journal of Organization Design. He is a Fellow of the Academy of Management and is listed in Who’s Who in the Management Sciences and Great Writers on Organizations.

  12. SNOWMIP2: An evaluation of forest snow process simulations

    Science.gov (United States)

    Richard Essery; Nick Rutter; John Pomeroy; Robert Baxter; Manfred Stahli; David Gustafsson; Alan Barr; Paul Bartlett; Kelly Elder

    2009-01-01

    Models of terrestrial snow cover, or snow modules within land surface models, are used in many meteorological, hydrological, and ecological applications. Such models were developed first, and have achieved their greatest sophistication, for snow in open areas; however, huge tracts of the Northern Hemisphere both have seasonal snow cover and are forested (Fig. 1)....

  13. A snow forecasting decision tree for significant snowfall over the interior of South Africa

    Directory of Open Access Journals (Sweden)

    Jan Hendrik Stander

    2016-09-01

    Full Text Available Snowfall occurs every winter over the mountains of South Africa but is rare over the highly populated metropolises over the interior of South Africa. When snowfall does occur over highly populated areas, it causes widespread disruption to infrastructure and even loss of life. Because of the rarity of snow over the interior of South Africa, inexperienced weather forecasters often miss these events. We propose a five-step snow forecasting decision tree in which all five criteria must be met to forecast snowfall. The decision tree comprises physical attributes that are necessary for snowfall to occur. The first step recognises the synoptic circulation patterns associated with snow and the second step detects whether precipitation is likely in an area. The remaining steps all deal with identifying the presence of a snowflake in a cloud and determining that the snowflake will not melt on the way to the ground. The decision tree is especially useful to forecast the very rare snow events that develop from relatively dry and warmer surface conditions. We propose operational implementation of the decision tree in the weather forecasting offices of South Africa, as it is foreseen that this approach could significantly contribute to accurately forecasting snow over the interior of South Africa.

  14. Multi Population Genetic Algorithm to estimate snow properties from GPR data

    Science.gov (United States)

    Godio, A.

    2016-08-01

    Multi-population genetic algorithms (DGA or MGA) are based on the partition of the population into several semi-isolated subpopulations (demes). Each sub-population is associated to an independent GA and explores different promising regions of the search space. We evaluate the sensitivity of some parameters to solve a non-linear problem in georadar data analysis. Particularly, we adapt the DGAs to optimize the model parameters of a data set of variable-offset data, collected in variable offset modality with Ground Penetrating Radar, to estimate porosity, saturation and density of snowpack in a glacial environment. The data set comes from investigation on glaciers to estimate the thickness and density of the seasonal snow. The main strategies to select the best parameters of the optimization process are outlined. We analyze the sensitivity on the solution of the optimization problems of some parameters of DGA; we deal with the effects of population and sub-population, and mutation properties. We consider the reflection traveltimes in a layered medium including a relationship between the traveltimes, porosity and saturation of the snow. We solve the problem for the layer thickness and the porosity, saturation and structural exponent of the snow. Reliable results are obtained in the snow density estimating, while the evaluation of free water content into the snow still remains challenging.

  15. Distribution of Snow and Maximum Snow Water Equivalent Obtained by LANDSAT Data and Degree Day Method

    Science.gov (United States)

    Takeda, K.; Ochiai, H.; Takeuchi, S.

    1985-01-01

    Maximum snow water equivalence and snowcover distribution are estimated using several LANDSAT data taken in snowmelting season over a four year period. The test site is Okutadami-gawa Basin located in the central position of Tohoku-Kanto-Chubu District. The year to year normalization for snowmelt volume computation on the snow line is conducted by year to year correction of degree days using the snowcover percentage within the test basin obtained from LANDSAT data. The maximum snow water equivalent map in the test basin is generated based on the normalized snowmelt volume on the snow line extracted from four LANDSAT data taken in a different year. The snowcover distribution on an arbitrary day in snowmelting of 1982 is estimated from the maximum snow water equivalent map. The estimated snowcover is compared with the snowcover area extracted from NOAA-AVHRR data taken on the same day. The applicability of the snow estimation using LANDSAT data is discussed.

  16. Estimation of Snow Thickness on Sea Ice and Lake Ice Using Airborne SnowSAR Data

    Science.gov (United States)

    Veijola, Katriina; Makynen, Marko; Lemmetyinen, Juha; Praks, Jaan

    2016-08-01

    Currently, snow thickness on sea ice is operationally estimated using microwave radiometer data. However, the estimates are hampered by the inherent coarse spatial resolution of passive microwave sensors. Successful application of SAR imagery for snow thickness estimation has the potential of providing estimates of snow thickness with much finer spatial resolution.In this study, we concentrate on assessing the capability of X- and Ku-band SAR backscattering to estimate snow thickness on sea and lake ice. Co- and cross -polarized X- and Ku-band SAR backscattering data, acquired with the ESA airborne SnowSAR sensor, are applied. The SAR data acquisition and co-incident in-situ measurements were conducted in Finland in the winter of 2012 over sea ice and lake ice test sites.Our analysis shows which frequency and polarization combinations have best sensitivity to snow thickness on sea and lake ice and in deep discussion provides plausible ways to improve the results.

  17. Mechanics of Ship Grounding

    DEFF Research Database (Denmark)

    Pedersen, Preben Terndrup

    1996-01-01

    In these notes first a simplified mathematical model is presented for analysis of ship hull loading due to grounding on relatively hard and plane sand, clay or rock sea bottoms. In a second section a more rational calculation model is described for the sea bed soil reaction forces on the sea bottom....... Finally, overall hull failure is considered first applying a quasistatic analysis model and thereafter a full dynamic model....

  18. Research on the seasonal snow of the Arctic Slope

    Energy Technology Data Exchange (ETDEWEB)

    Benson, C.S.

    1986-01-01

    This project deals with the seasonal snow on Alaska's Arctic Slope. It is concentrated on snow of the R{sub 4}D project area. However, an important aspect of this study is to relate the snow cover of this area with the rest of the Arctic Slope. The goals include determination of the amount of precipitation which comes as snow, the wind transport of this snow and its depositional pattern as influenced by drifting, the physical properties of the snow, the physical processes which operate in it, the proportions of it which go into evaporation, infiltration and runoff, and the biological role of the snow cover.

  19. Research on the seasonal snow of the Arctic Slope

    Energy Technology Data Exchange (ETDEWEB)

    Benson, C.S.

    1991-01-01

    This project deals with the seasonal snow on Alaska's Arctic Slope. Although it is concentrated on snow of the R{sub 4}D project area, it is important to relate the snow cover of this area with the rest of the Arctic Slope. The goals include determination of the amount of precipitation which comes as snow, the wind transport of this snow and its depositional pattern as influenced by drifting, the physical properties of the snow, the physical processes which operate in it, the proportions of it which go into evaporation, infiltration and runoff, and the biological role of the snow cover.

  20. Research on the seasonal snow of the Arctic Slope

    Energy Technology Data Exchange (ETDEWEB)

    Benson, C.S.

    1989-01-01

    This project deals with the seasonal snow on Alaska's Arctic Slope. Although it is concentrated on snow of the R40 project area, it is important to relate the snow cover of this area with the rest of the Arctic Slope. The goals include determination Of the amount of precipitation which comes as snow, the wind transport of this snow and its depositional pattern as influenced by drifting, the physical properties of the snow, the physical processes which operate in it, the proportions of it which go into evaporation, infiltration and runoff, and the biological role of the snow cover.

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

    Directory of Open Access Journals (Sweden)

    Michele Freppaz

    2011-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Ermanno Zanini

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

  3. 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.

  4. Snow water equivalent interpolation for the Colorado River Basin from snow telemetry (SNOTEL) data

    OpenAIRE

    Fassnacht, SR; Dressler, KA; Bales, RC

    2003-01-01

    Inverse weighted distance and regression nonexact techniques were evaluated for interpolating methods snow water equivalent (SWE) across the entire Colorado River Basin of the western United States. A 1-km spacing was used for the gridding of snow telemetry (SNOTEL) measurements for the years 1993, 1998, and 1999, which on average, represented higher than average, average, and lower than average snow years. Because of the terrain effects, the regression techniques (hypsometric elevation and m...

  5. Application of MODIS snow cover products: wildfire impacts on snow and melt in the Sierra Nevada

    Directory of Open Access Journals (Sweden)

    P. D. Micheletty

    2014-07-01

    Full Text Available The current work evaluates the spatial and temporal variability in snow after a large forest fire in northern California with Moderate Resolution Imaging Spectroradiometer (MODIS snow covered area and grain size (MODSCAG algorithm. MODIS MOD10A1 fractional snow covered area and MODSCAG fractional snow cover products are utilized to detect spatial and temporal changes in snowpack after the 2007 Moonlight Fire and an unburned basin, Grizzly Ridge, for water years (WY 2002–2012. Estimates of canopy adjusted and non-adjusted MODSCAG fractional snow covered area (fSCA are smoothed and interpolated to provide a continuous timeseries of daily basin average snow extent over the two basins. The removal of overstory canopy by wildfire exposes more snow cover; however, elemental pixel comparisons and statistical analysis show that the MOD10A1 product has a tendency to overestimate snow coverage pre-fire, muting the effects of wildfire. The MODSCAG algorithm better distinguishes sub-pixel snow coverage in forested areas and is highly correlated to soil burn severity after the fire. Annual MODSCAG fSCA estimates show statistically significant increased fSCA in the Moonlight Fire study area after the fire (WY 2008–2011; P < 0.01 compared to pre-fire averages and the control basin. After the fire, the number of days exceeding a pre-fire high snow cover threshold increased by 81%. Canopy reduction increases exposed viewable snow area and the amount of solar radiation that reaches the snowpack leading to earlier basin average melt-out dates compared to the nearby unburned basin. There is also a significant increase in MODSCAG fSCA post-fire regardless of slope or burn severity. Alteration of regional snow cover has significant implications for both short and long-term water supplies for downstream communities and resource managers.

  6. Arctic Snow Microstructure Experiment for the development of snow emission modelling

    OpenAIRE

    Maslanka, William; Leppänen, Leena; Kontu, Anna; Sandells, Mel; Lemmetyinen, Juha; Schneebeli, Martin; Proksch, Martin; Matzl, Margret; Hannula, Henna-Reetta; Gurney, Robert

    2016-01-01

    The Arctic Snow Microstructure Experiment (ASMEx) took place in Sodankylä, Finland in the winters of 2013–2014 and 2014–2015. Radiometric, macro-, and microstructure measurements were made under different experimental conditions of homogenous snow slabs, extracted from the natural seasonal taiga snowpack. Traditional and modern measurement techniques were used for snow macro- and microstructure observations. Radiometric measurements of the microwave emission of s...

  7. Outdoor ground impedance models.

    Science.gov (United States)

    Attenborough, Keith; Bashir, Imran; Taherzadeh, Shahram

    2011-05-01

    Many models for the acoustical properties of rigid-porous media require knowledge of parameter values that are not available for outdoor ground surfaces. The relationship used between tortuosity and porosity for stacked spheres results in five characteristic impedance models that require not more than two adjustable parameters. These models and hard-backed-layer versions are considered further through numerical fitting of 42 short range level difference spectra measured over various ground surfaces. For all but eight sites, slit-pore, phenomenological and variable porosity models yield lower fitting errors than those given by the widely used one-parameter semi-empirical model. Data for 12 of 26 grassland sites and for three beech wood sites are fitted better by hard-backed-layer models. Parameter values obtained by fitting slit-pore and phenomenological models to data for relatively low flow resistivity grounds, such as forest floors, porous asphalt, and gravel, are consistent with values that have been obtained non-acoustically. Three impedance models yield reasonable fits to a narrow band excess attenuation spectrum measured at short range over railway ballast but, if extended reaction is taken into account, the hard-backed-layer version of the slit-pore model gives the most reasonable parameter values.

  8. The growth of shrubs on high Arctic tundra at Bylot Island: impact on snow physical properties and permafrost thermal regime

    Science.gov (United States)

    Domine, Florent; Barrere, Mathieu; Morin, Samuel

    2016-12-01

    With climate warming, shrubs have been observed to grow on Arctic tundra. Their presence is known to increase snow height and is expected to increase the thermal insulating effect of the snowpack. An important consequence would be the warming of the ground, which will accelerate permafrost thaw, providing an important positive feedback to warming. At Bylot Island (73° N, 80° W) in the Canadian high Arctic where bushes of willows (Salix richardsonii Hook) are growing, we have observed the snow stratigraphy and measured the vertical profiles of snow density, thermal conductivity and specific surface area (SSA) in over 20 sites of high Arctic tundra and in willow bushes 20 to 40 cm high. We find that shrubs increase snow height, but only up to their own height. In shrubs, snow density, thermal conductivity and SSA are all significantly lower than on herb tundra. In shrubs, depth hoar which has a low thermal conductivity was observed to grow up to shrub height, while on herb tundra, depth hoar only developed to 5 to 10 cm high. The thermal resistance of the snowpack was in general higher in shrubs than on herb tundra. More signs of melting were observed in shrubs, presumably because stems absorb radiation and provide hotspots that initiate melting. When melting was extensive, thermal conductivity was increased and thermal resistance was reduced, counteracting the observed effect of shrubs in the absence of melting. Simulations of the effect of shrubs on snow properties and on the ground thermal regime were made with the Crocus snow physics model and the ISBA (Interactions between Soil-Biosphere-Atmosphere) land surface scheme, driven by in situ and reanalysis meteorological data. These simulations did not take into account the summer impact of shrubs. They predict that the ground at 5 cm depth at Bylot Island during the 2014-2015 winter would be up to 13 °C warmer in the presence of shrubs. Such warming may however be mitigated by summer effects.

  9. Snow: a reliable indicator for global warming in the future?

    Science.gov (United States)

    Jacobi, H.-W.

    2012-03-01

    The cryosphere consists of water in the solid form at the Earth's surface and includes, among others, snow, sea ice, glaciers and ice sheets. Since the 1990s the cryosphere and its components have often been considered as indicators of global warming because rising temperatures can enhance the melting of solid water (e.g. Barry et al 1993, Goodison and Walker 1993, Armstrong and Brun 2008). Changes in the cryosphere are often easier to recognize than a global temperature rise of a couple of degrees: many locals and tourists have hands-on experience in changes in the extent of glaciers or the duration of winter snow cover on the Eurasian and North American continents. On a more scientific basis, the last IPCC report left no doubt: the amount of snow and ice on Earth is decreasing (Lemke et al 2007). Available data showed clearly decreasing trends in the sea ice and frozen ground extent of the Northern Hemisphere (NH) and the global glacier mass balance. However, the trend in the snow cover extent (SCE) of the NH was much more ambiguous; a result that has since been confirmed by the online available up-to-date analysis of the SCE performed by the Rutgers University Global Snow Lab (climate.rutgers.edu/snowcover/). The behavior of snow is not the result of a simple cause-and-effect relationship between air temperature and snow. It is instead related to a rather complex interplay between external meteorological parameters and internal processes in the snowpack. While air temperature is of course a crucial parameter for snow and its melting, precipitation and radiation are also important. Further physical properties like snow grain size and the amount of absorbing impurities in the snow determine the fraction of absorbed radiation. While all these parameters affect the energy budget of the snowpack, each of these variables can dominate depending on the season or, more generally, on environmental conditions. As a result, the reduction in SCE in spring and summer in the

  10. Spectral Reflectance Characteristics of Different Snow and Snow-Covered Land Surface Objects and Mixed Spectrum Fitting

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jia-hua; ZHOU Zheng-ming; WANG Pei-juan; YAO Feng-mei; Liming Yang

    2011-01-01

    The field spectroradiometer was used to measure spectra of different snow and snow-covered land surface objects in Beijing area.The result showed that for a pure snow spectrum,the snow reflectance peaks appeared from visible to 800 nm band locations; there was an obvious absorption valley of snow spectrum near 1 030 nm wavelength.Compared with fresh snow,the reflection peaks of the old snow and melting snow showed different degrees of decline in the ranges of 300~1 300,1 700~1 800 and 2 200~2 300 nm,the lowest was from the compacted snow and frozen ice.For the vegetation and snow mixed spectral characteristics,it was indicated that the spectral reflectance increased for the snow-covered land types (including pine leaf with snow and pine leaf on snow background),due to the influence of snow background in the range of 350~1 300 nm.However,the spectrum reflectance of mixed pixel remained a vegetation spectral characteristic.In the end,based on the spectrum analysis of snow,vegetation,and mixed snow/vegetation pixels,the mixed spectral fitting equations were established,and the results showed that there was good correlation between spectral curves by simulation fitting and observed ones (correlation coefficient R2 =0.950 9).

  11. Spectral reflectance characteristics of different snow and snow-covered land surface objects and mixed spectrum fitting.

    Science.gov (United States)

    Zhang, Jia-Hua; Zhou, Zheng-Ming; Wang, Pei-Juan; Yao, Feng-Mei; Liming, Yang

    2011-09-01

    The field spectroradiometer was used to measure spectra of different snow and snow-covered land surface objects in Beijing area. The result showed that for a pure snow spectrum, the snow reflectance peaks appeared from visible to 800 nm band locations; there was an obvious absorption valley of snow spectrum near 1 030 nm wavelength. Compared with fresh snow, the reflection peaks of the old snow and melting snow showed different degrees of decline in the ranges of 300-1 300, 1 700-1 800 and 2 200-2 300 nm, the lowest was from the compacted snow and frozen ice. For the vegetation and snow mixed spectral characteristics, it was indicated that the spectral reflectance increased for the snow-covered land types (including pine leaf with snow and pine leaf on snow background), due to the influence of snow background in the range of 350-1 300 nm. However, the spectrum reflectance of mixed pixel remained a vegetation spectral characteristic. In the end, based on the spectrum analysis of snow, vegetation, and mixed snow/vegetation pixels, the mixed spectral fitting equations were established, and the results showed that there was good correlation between spectral curves by simulation fitting and observed ones (correlation coefficient R2 = 0.950 9).

  12. Measured black carbon deposition on the Sierra Nevada snow pack and implication for snow pack retreat

    Directory of Open Access Journals (Sweden)

    O. L. Hadley

    2010-04-01

    Full Text Available Modeling studies show that the darkening of snow and ice by black carbon (BC deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition on the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain at a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.

  13. Measured black carbon deposition on the Sierra Nevada snow pack and implication for snow pack retreat

    Directory of Open Access Journals (Sweden)

    O. L. Hadley

    2010-08-01

    Full Text Available Modeling studies show that the darkening of snow and ice by black carbon deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition to the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain at a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.

  14. Modelling high-resolution snow cover precipitation supply for German river catchments with SNOW 4

    Science.gov (United States)

    Böhm, Uwe; Reich, Thomas; Schneider, Gerold; Fiedler, Anett

    2013-04-01

    Formation of snow cover causes a delayed response of surface to precipitation. Both melting of snow and release of liquid water retained within the snow cover form precipitation supply which contributes to runoff and infiltration. The model SNOW 4 is developed to simulate snow cover accumulation and depletion and the resulting precipitation supply on a regular grid. The core of the model is formed by a set of equations which describe the snow cover energy and mass balance. The snow surface energy balance is calculated as a result of the radiation balance and the heat fluxes between atmosphere, soil and snow cover. The available melting heat enters the mass balance computation part of the model and melting of snow or freezing of liquid water within the snow layer takes place depending on its sign. Retention, aging and snow cover regeneration are taken into consideration. The model runs operationally 4 times a day and provides both a snow cover and precipitation supply analysis for the last 30 hours and a forecast for up to 72 hours. For the 30-hour analysis, regionalised observations are used both to define the initial state and force the model. Hourly measurements of air temperature, water vapour pressure, wind speed, global radiation or sunshine duration and precipitation are interpolated to the model grid. For the forecast period, SNOW 4 obtains the required input data from the operational products of the COSMO-EU weather forecast model. The size of a grid box is 1km2. The model area covers a region of 1100x1000km2 and includes the catchments of the German rivers completely. The internal time step is set to 1 hour. Once a day, the compliance between model and regionalized snow cover data is assessed. If discrepancies exceed certain thresholds, the model must be adjusted by a weighted approach towards the observations. The model simulations are updated every six hours based on the most recent observations and weather forecasts. The model works operationally since

  15. Measured Black Carbon Deposition on the Sierra Nevada Snow Pack and Implication for Snow Pack Retreat

    Energy Technology Data Exchange (ETDEWEB)

    Hadley, O.L.; Corrigan, C.E.; Kirchstetter, T.W.; Cliff, S.S.; Ramanathan, V.

    2010-01-12

    Modeling studies show that the darkening of snow and ice by black carbon deposition is a major factor for the rapid disappearance of arctic sea ice, mountain glaciers and snow packs. This study provides one of the first direct measurements for the efficient removal of black carbon from the atmosphere by snow and its subsequent deposition to the snow packs of California. The early melting of the snow packs in the Sierras is one of the contributing factors to the severe water problems in California. BC concentrations in falling snow were measured at two mountain locations and in rain at a coastal site. All three stations reveal large BC concentrations in precipitation, ranging from 1.7 ng/g to 12.9 ng/g. The BC concentrations in the air after the snow fall were negligible suggesting an extremely efficient removal of BC by snow. The data suggest that below cloud scavenging, rather than ice nuclei, was the dominant source of BC in the snow. A five-year comparison of BC, dust, and total fine aerosol mass concentrations at multiple sites reveals that the measurements made at the sampling sites were representative of large scale deposition in the Sierra Nevada. The relative concentration of iron and calcium in the mountain aerosol indicates that one-quarter to one-third of the BC may have been transported from Asia.

  16. Multi-GNSS and Multi-frequency SNR Multipath Reflectometry of Snow Depth

    Science.gov (United States)

    Tabibi, S.; Geremia-Nievinski, F.; van Dam, T. M.

    2015-12-01

    Global Navigation Satellite System multipath reflectometry (GNSS-MR) uses ground-based signals of opportunity to retrieve snow depth at an intermediate space scale. This technique is based on the signal-to-noise ratio (SNR) of the simultaneously received direct (line-of-sight) and coherently ground reflected signals. In this contribution, forward and inverse modeling of SNR observations is presented for GLONASS-MR, extending GPS-MR to multiple GNSS. The coupling of the surface and antenna responses from short-delay near-grazing incidence multipath from CDMA and FDMA satellite navigation systems are simulated using an electromagnetic forward model. The inverse model is used to estimate parameter corrections responsible for observation residuals to estimate snow depth. The correlation between snow depth retrievals using GPS L2C signal and GLONASS R2-C/A signal is excellent, with r2 value of 0.990. In a related approach, dual-frequency SNR-based GNSS-MR, which is based on linear combination of SNR observables, is used to estimate snow depth. This ionospheric delay free method synthesizes longer carrier wavelengths ("widelaning" or delta-k) to isolate the direct power contribution in environmental retrievals.

  17. Central Asian Snow Cover from Hydrometeorological Surveys

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Central Asian Snow Cover from Hydrometeorological Surveys data are based on observations made by personnel for three river basins: Amu Darya, Sir Darya, and...

  18. 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.

  19. Light-absorbing impurities in Arctic snow

    Directory of Open Access Journals (Sweden)

    S. J. Doherty

    2010-08-01

    Full Text Available Absorption of radiation by ice is extremely weak at visible and near-ultraviolet wavelengths, so small amounts of light-absorbing impurities in snow can dominate the absorption of solar radiation at these wavelengths, reducing the albedo relative to that of pure snow, contributing to the surface energy budget and leading to earlier snowmelt. In this study Arctic snow is surveyed for its content of light-absorbing impurities, expanding and updating the 1983–1984 survey of Clarke and Noone. Samples were collected in Alaska, Canada, Greenland, Svalbard, Norway, Russia, and the Arctic Ocean during 2005–2009, on tundra, glaciers, ice caps, sea ice, frozen lakes, and in boreal forests. Snow was collected mostly in spring, when the entire winter snowpack is accessible for sampling. Sampling was carried out in summer on the Greenland ice sheet and on the Arctic Ocean, of melting glacier snow and sea ice as well as cold snow. About 1200 snow samples have been analyzed for this study.

    The snow is melted and filtered; the filters are analyzed in a specially designed spectrophotometer system to infer the concentration of black carbon (BC, the fraction of absorption due to non-BC light-absorbing constituents and the absorption Ångstrom exponent of all particles. The reduction of snow albedo is primarily due to BC, but other impurities, principally brown (organic carbon, are typically responsible for ~40% of the visible and ultraviolet absorption. The meltwater from selected snow samples was saved for chemical analysis to identify sources of the impurities. Median BC amounts in surface snow are as follows (nanograms of carbon per gram of snow: Greenland 3, Arctic Ocean snow 7, melting sea ice 8, Arctic Canada 8, Subarctic Canada 14, Svalbard 13, Northern Norway 21, Western Arctic Russia 26, Northeastern Siberia 17. Concentrations are more variable in the European Arctic than in Arctic Canada or the Arctic Ocean, probably because of the proximity

  20. Who made John Snow a hero?

    Science.gov (United States)

    Vandenbroucke, J P; Eelkman Rooda, H M; Beukers, H

    1991-05-15

    This paper describes how and why John Snow's investigation of the transmission of cholera grew into an epidemiologic classic. The evolution of the interpretation of the work of John Snow was first studied in depth in the Dutch medical literature, and thereafter traced more superficially in the bacteriologic, hygienic, and epidemiologic literature of Germany, the United Kingdom, and the United States. From the oral tradition of teaching, as well as from the written sources, it is concluded that US epidemiologist W. H. Frost was responsible for the revival of the work of John Snow in the 1930s. Besides the obvious and enjoyable clarity of thinking and reasoning, epidemiologically and medically, of the writings of John Snow, his example well suited epidemiology of the 1930s since his convictions came very close to the bacteriologic paradigm of the day.

  1. 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)...

  2. Modeling of AC arc inside wet snow

    Energy Technology Data Exchange (ETDEWEB)

    Hemmatjou, H.

    2006-07-01

    Overhead transmission lines cover long distances over a broad range of topographic relief, climates, and environments. As such, the high voltage equipment is subject to pollution, wet snow and atmospheric icing. Each of these factors have been the source of power outages recorded on power transmission lines. Electric arcs can develop on outdoor insulators until they cause a total flashover. This study involved the modeling of flashover in snow-covered insulators to better understand how electric discharges initiate inside snow and how they develop into flashover. The main objective of this thesis was to develop a mathematical model to predict the flashover voltage of snow-covered insulator surfaces and to ultimately design adequate insulators for cold regions. The results obtained through mathematical modeling were in good agreement with those obtained in experiments.

  3. Hardness Tester for Polyur

    Science.gov (United States)

    Hauser, D. L.; Buras, D. F.; Corbin, J. M.

    1987-01-01

    Rubber-hardness tester modified for use on rigid polyurethane foam. Provides objective basis for evaluation of improvements in foam manufacturing and inspection. Typical acceptance criterion requires minimum hardness reading of 80 on modified tester. With adequate correlation tests, modified tester used to measure indirectly tensile and compressive strengths of foam.

  4. 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.

  5. A Creep Model for High Density Snow

    Science.gov (United States)

    2017-04-01

    Director of ERDC-CRREL was Dr. Lance Hansen, and the Director was Dr. Robert E. Davis. COL Bryan S. Green was Commander of ERDC, and Dr. David W...Station, Green - land, and that will be founded on a compacted snow surface. The defor- mation of snow under a constant load (creep deformation, or...developed in this study are enough similar to the generalized creep model used in the ABAQUS finite element software that the ABAQUS creep model was used

  6. Snow Drift Management: Summit Station Greenland

    Science.gov (United States)

    2016-05-01

    ER D C/ CR RE L TR -1 6- 6 Engineering for Polar Operations, Logistics, and Research (EPOLAR) Snow Drift Management Summit Station...Drift Management Summit Station Greenland Robert B. Haehnel and Matthew F. Bigl U.S. Army Engineer Research and Development Center (ERDC) Cold...Engineering for Polar Operations, Logistics, and Research (EPOLAR) EP-ARC-15-33, “Monitoring and Managing Snow Drifting at Summit Station, Greenland” ERDC

  7. UV albedo of arctic snow in spring

    Directory of Open Access Journals (Sweden)

    O. Meinander

    2008-02-01

    Full Text Available The relevance of snow for climate studies is based on its physical properties, such as high surface reflectivity. Surface ultraviolet (UV albedo is an essential parameter for various applications based on radiative transfer modeling. Here, new continuous measurements of the local UV albedo of natural Arctic snow were made at Sodankylä (67.37° N, 26.63° E, 179 m a.s.l. during the spring of 2007. The data were logged at 1-min intervals. The accumulation of snow was up to 68 cm. The surface layer thickness varied from 0.5 to 35 cm with the snow grain size between 0.2 and 2.5 mm. The midday erythemally weighted UV albedo ranged from 0.6 to 0.8 in the accumulation period and 0.5–0.7 during melting. During the snow melt period, under cases of an almost clear sky and variable cloudiness, an unexpected diurnal decrease of 0.05 in albedo soon after midday, and recovery thereafter, was detected. This diurnal decrease in albedo was found to be asymmetric with respect to solar midday, thus indicating a change in the properties of the snow. Independent UV albedo results with two different types of instruments confirm these findings. The measured temperature of the snow surface was below 0°C on the following mornings. Hence, the reversible diurnal change, evident for ~1–2 h, could be explained by the daily metamorphosis of the surface of the snowpack, in which the temperature of the surface increases, melting some of the snow to liquid water, after which the surface freezes again.

  8. Comprehensive hard materials

    CERN Document Server

    2014-01-01

    Comprehensive Hard Materials deals with the production, uses and properties of the carbides, nitrides and borides of these metals and those of titanium, as well as tools of ceramics, the superhard boron nitrides and diamond and related compounds. Articles include the technologies of powder production (including their precursor materials), milling, granulation, cold and hot compaction, sintering, hot isostatic pressing, hot-pressing, injection moulding, as well as on the coating technologies for refractory metals, hard metals and hard materials. The characterization, testing, quality assurance and applications are also covered. Comprehensive Hard Materials provides meaningful insights on materials at the leading edge of technology. It aids continued research and development of these materials and as such it is a critical information resource to academics and industry professionals facing the technological challenges of the future. Hard materials operate at the leading edge of technology, and continued res...

  9. Snow mapping from MODIS products: the application of an improved cloud removal methodology to the Po river basin

    Science.gov (United States)

    Da Ronco, Pierfrancesco; De Michele, Carlo

    2014-05-01

    Digital snow maps are a powerful tool for reproducing large-scale snow distribution and extension. The use of such information for hydrological purposes is now considered an outlet of great practical interest: when combined with local assessments or measurements of the snow water equivalent (SWE), it allows to estimate the regional snow resource. In this context, MODIS (MODerate resolution Imaging Spectroradiometer on board Terra and Aqua satellites) daily Snow Covered Area product has been widely tested and proved to be appropriate for hydrologic applications. However, within a daily map the presence of cloudiness can hide the ground, thus preventing any snow detection. On the basis of previous studies, we recently developed a new methodology for cloud removal able to deal with the problem in wide areas, characterized by an high topographical and geomorphological heterogeneity such as northern Italy. Given the Aqua/Terra daily snow map of the basin, the standard condition shows a cloud-free part and a cloud-covered part. The latter is the assessment area, where a stepped procedure for cloud reduction combines temporal and spatial information obtained from neighboring areas to estimate whether there is snow. While conceiving the new method, our first target was to preserve the daily temporal resolution of the product as far as possible. In cases when there were not enough information on the same day within the cloud-free part, or in the nearest days, we adopted an improved method which ensures an acceptable reproduction of the micro-cycles which characterize the transition altitudes (where snow does not stand continually over the entire winter). Daily binary (snow/not snow) maps of ten years (2003-2012) have been analyzed and processed with the support of a Digital Elevation Model (DEM) of the basin with 500 m spatial resolution. We deeply investigated the issue of cloudiness over the study period, highlighting its dependence on altitude and season. Snow maps seem

  10. The structure of powder snow avalanches

    Science.gov (United States)

    Sovilla, Betty; McElwaine, Jim N.; Louge, Michel Y.

    2015-01-01

    Powder snow avalanches (PSAs) can be hundreds of metres high and descend at astonishing speeds. This review paints a composite picture of PSAs from data acquired at the Vallée de la Sionne test site in Switzerland, including time-histories of snow cover thickness from buried RADAR and, at several elevations on a pylon, impact pressures from load cells, air pressure, particle velocity from optical sensors, and cloud density and particle cluster size from capacitance probes. PSAs feature distinct flow regions with stratification in mean density. At the head, highly fluctuating impact pressures weaken with elevation, while vertical velocity profiles evolve rapidly along the flow, suggesting that surface snow layers of light, cold, cohesionless snow erupt into a turbulent, inhomogeneous, recirculating frontal cloud region. For hundreds of metres behind the head, cloud stratification sharpens with the deposition of suspended cloud particles, while a denser basal flow of increasing thickness forms as deeper, warmer and heavier parts of the weakened snow cover are entrained. Toward the tail, vertical velocity profiles are more uniform, impact pressures become lower and steadier as the flow becomes thinner, and snow pack entrainment is negligible.

  11. Snow as a habitat for microorganisms

    Science.gov (United States)

    Hoham, Ronald W.

    1989-01-01

    There are three major habitats involving ice and snow, and the microorganisms studied from these habitats are most eukaryotic. Sea ice is inhabited by algae called diatoms, glacial ice has sparse populations of green algai cal desmids, and the temporary and permanent snows in mountainous regions and high latitudes are inhabited mostly by green algal flagellates. The life cycle of green algal flagellates is summarized by discussing the effects of light, temperature, nutrients, and snow melts. Specific examples of optimal conditions and environmental effects for various snow algae are given. It is not likely that the eukaryotic snow algae presented are candidated for life on the planet Mars. Evolutionally, eukaryotic cells as know on Earth may not have had the opportunity to develop on Mars (if life evolved at all on Mars) since eukaryotes did not appear on Earth until almost two billion years after the first prokaryotic organisms. However, the snow/ice ecosystems on Earth present themselves as extreme habitats were there is evidence of prokaryotic life (eubacteria and cyanbacteria) of which literally nothing is known. Any future surveillances of extant and/or extinct life on Mars should include probes (if not landing sites) to investigate sites of concentrations of ice water. The possibility of signs of life in Martian polar regions should not be overlooked.

  12. Spatial and Temporal Variation of Bulk Snow Properties in North Boreal and Tundra Environments Based on Extensive Field Measurements

    Science.gov (United States)

    Hannula, H. R.; Lemmetyinen, J.; Pulliainen, J.; Kontu, A.; Derksen, C.

    2015-12-01

    A large collection of in situ snow data was collected in a support of ESA SnowSAR airborne acquisitions in Northern Finland (Lemmetyinen et al., 2014). The purpose was to demonstrate the mission concept of the proposed ESA CoReH2O (Cold Regions Hydrology High-resolution Observatory, Rott et al., 2010) mission, a candidate in the ESA Earth Explorer series of Earth observing satellites. Around 21400 snow depth measurements, 600 SWE measurements and a number of distributed snow pit measurements were collected during 19 days between December 2011 and March 2012. In this study, these field measurements will be used to analyse the snow property variation within and between different land-cover types in North boreal and tundra environments. The wide heterogeneity of snow properties forms a challenge for remote snow information retrieval as even in flat areas the amount and type of heterogeneity vary in a number of different scales. Especially, information of hemispheric scale SWE variation is suffering from large uncertainties, although, assimilation of ground-based and space-borne information and algorithms specific for a land-cover type have lowered these remaining uncertainties (Takala et al., 2011). This study aims to contribute to this future work for more reliable SWE retrievals by statistically describing the snow parameter variation in these northern environments. Lemmetyinen, J., J. Pulliainen, A. Kontu, A. Wiesmann, C. Mätzler, H. Rott, K. Voglmeier, T. Nagler, A. Meta, A. Coccia, M. Schneebeli, M. Proksch, M. Davidson, D. Schüttemeyer, Chung-Chi Lin, and M. Kern, 2014. Observations of seasonal snow cover at X- and Ku bands during the NoSREx campaign. Proc. EUSAR 2014, 3-5 June 2014, Berlin. Rott, H., S.H. Yueh, D.W. Cline, C. Duguay, R. Essery et al., 2010. Cold Regions Hydrology High-resolution Observatory for Snow and Cold Land Processes. Proc. IEEE, 98(5), 752-765. Takala, M., K. Luojus, J. Pulliainen, C. Derksen, J. Lemmetyinen, J-P. Kärnä, J. Koskinen

  13. The contact density to characterize the mechanics of cohesive granular materials: application to snow microstructure modeling.

    Science.gov (United States)

    Gaume, Johan; Löwe, Henning

    2016-04-01

    Microstructural properties are essential to characterize the mechanics of loose and cohesive granular materials such as snow. In particular, mechanical properties and physical processes of porous media are often related to the volume fraction ν. Low-density microstructures typically allow for considerable structural diversity at a given volume fraction, leading to uncertainties in modeling approaches using ν-based parametrizations only. We have conducted discrete element simulations of cohesive granular materials with initial configurations which are drawn from Baxter's sticky hard sphere (SHS) model. This method allows to control independently the initial volume fraction ν and the average coordination number Z. We show that variations in elasticity and strength of the samples can be fully explained by the initial contact density C = νZ over a wide range of volume fractions and coordination numbers. Hence, accounting for the contact density C allows to resolve the discrepancies in particle based modeling between samples with similar volume fractions but different microstructures. As an application, we applied our method to the microstructure of real snow samples which have been imaged by micro-computed tomography and reconstructed using the SHS model. Our new approach opens a promising route to evaluate snow physical and mechanical properties from field measurements, for instance using the Snow Micro Penetrometer (SMP), by linking the penetration resistance to the contact density.

  14. Understanding snow-transport processes shaping the mountain snow-cover

    Directory of Open Access Journals (Sweden)

    R. Mott

    2010-12-01

    Full Text Available Mountain snow-cover is normally heterogeneously distributed due to wind and precipitation interacting with the snow cover on various scales. The aim of this study was to investigate snow deposition and wind-induced snow-transport processes on different scales and to analyze some major drift events caused by north-west storms during two consecutive accumulation periods. In particular, we distinguish between the individual processes that cause specific drifts using a physically based model approach. Very high resolution wind fields (5 m were computed with the atmospheric model Advanced Regional Prediction System (ARPS and used as input for a model of snow-surface processes (Alpine3D to calculate saltation, suspension and preferential deposition of precipitation. Several flow features during north-west storms were identified with input from a high-density network of permanent and mobile weather stations and indirect estimations of wind directions from snow-surface structures, such as snow dunes and sastrugis. We also used Terrestrial and Airborne Laser Scanning measurements to investigate snow-deposition patterns and to validate the model. The model results suggest that the in-slope deposition patterns, particularly two huge cross-slope cornice-like drifts, developed only when the prevailing wind direction was northwesterly and were formed mainly due to snow redistribution processes (saltation-driven. In contrast, more homogeneous deposition patterns on a ridge scale were formed during the same periods mainly due to preferential deposition of precipitation. The numerical analysis showed that snow-transport processes were sensitive to the changing topography due to the smoothing effect of the snow cover.

  15. Satellite Based Probabilistic Snow Cover Extent Mapping (SCE) at Hydro-Québec

    Science.gov (United States)

    Teasdale, Mylène; De Sève, Danielle; Angers, Jean-François; Perreault, Luc

    2016-04-01

    Over 40% of Canada's water resources are in Quebec and Hydro-Quebec has developed potential to become one of the largest producers of hydroelectricity in the world, with a total installed capacity of 36,643 MW. The Hydro-Québec fleet park includes 27 large reservoirs with a combined storage capacity of 176 TWh, and 668 dams and 98 controls. Thus, over 98% of all electricity used to supply the domestic market comes from water resources and the excess output is sold on the wholesale markets. In this perspective the efficient management of water resources is needed and it is based primarily on a good river flow estimation including appropriate hydrological data. Snow on ground is one of the significant variables representing 30% to 40% of its annual energy reserve. More specifically, information on snow cover extent (SCE) and snow water equivalent (SWE) is crucial for hydrological forecasting, particularly in northern regions since the snowmelt provides the water that fills the reservoirs and is subsequently used for hydropower generation. For several years Hydro Quebec's research institute ( IREQ) developed several algorithms to map SCE and SWE. So far all the methods were deterministic. However, given the need to maximize the efficient use of all resources while ensuring reliability, the electrical systems must now be managed taking into account all risks. Since snow cover estimation is based on limited spatial information, it is important to quantify and handle its uncertainty in the hydrological forecasting system. This paper presents the first results of a probabilistic algorithm for mapping SCE by combining Bayesian mixture of probability distributions and multiple logistic regression models applied to passive microwave data. This approach allows assigning for each grid point, probabilities to the set of the mutually exclusive discrete outcomes: "snow" and "no snow". Its performance was evaluated using the Brier score since it is particularly appropriate to

  16. SNOW COVER MONITORING BY REMOTE SENSING AND SNOWMELT RUNOFF CALCULATION IN THE UPPER HUANGHE RIVER BASIN

    Institute of Scientific and Technical Information of China (English)

    LANYong-chao; MAQua-jie; 等

    2002-01-01

    The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai-Xizang(Tibet)Plateau of China.The melt-water from the snow-cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring .So snowmelt runoff forecast has importance for hydropower,flood prevention and water resources utilize-tion.The application of remote sensing and Geographic Information System(GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper.The key parame-ter-snow cover area can be computed by satellite images from multi-platform,multi-templral and multi-spectral.A clus-ter of snow-cover data can be yielded by means of the classification filter method.Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning .According to the typical samples extracting snow covered moun-tained in detail also.The runoff snowmelt models based on the snow-cover data from NOAA images and observation data of runoff,precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reser-voir,which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June.The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin.With the develop-ment of remote sensing technique and the progress of the interpretation method,the forecast accuracy of snowmelt runoff will be improved in the near future .Large scale extent and few stations are two objective reality situations in Chian,so they should be considered in simulation and forecast.Apart from dividing ,the derivation of

  17. SNOW COVER MONITORING BY REMOTE SENSING AND SNOWMELT RUNOFF CALCULATION IN THE UPPER HUANGHE RIVER BASIN

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai-Xizang(Tibet)Plateau of China. The melt-water from the snow-cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring. So snowmelt runoff forecast has importance for hydropower, flood prevention and water resources utilization. The application of remote sensing and Geographic Information System (GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper. The key parameter- snow cover area can be computed by satellite images from multi-platform, multi-temporal and multi-spectral. A cluster of snow-cover data can be yielded by means of the classification filter method. Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning. According to the typical samples extracting snow covered mountainous region, the snowmelt runoff calculation models in the upper Huanghe River basin are presented and they are mentioned in detail also. The runoff snowmelt models based on the snow-cover data from NOAA images and observation data of runoff, precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reservoir , which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June. The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin. With the development of remote sensing technique and the progress of the interpretation method, the forecast accuracy of snowmelt runoff will be improved in the near future. Large scale extent and few stations are two

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

    Science.gov (United States)

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

    2017-04-01

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

  19. Crossing physical simulations of snow conditions and a geographic model of ski area to assess ski resorts vulnerability

    Science.gov (United States)

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

    2016-04-01

    In order to face climate change, meteorological variability and the recurrent lack of natural snow on the ground, ski resorts adaptation often rely on technical responses. Indeed, since the occurrence of episodes with insufficient snowfalls in the early 1990's, snowmaking has become an ordinary practice of snow management, comparable to grooming, and contributes to optimise the operation of ski resorts. It also participates to the growth of investments and is associated with significant operating costs, and thus represents a new source of vulnerability. The assessment of the actual effects of snowmaking and of snow management practices in general is a real concern for the future of the ski industry. The principal model use to simulate snow conditions in resorts, Ski Sim, has also been moving this way. Its developers introduced an artificial input of snow on ski area to complete natural snowfalls and considered different organisations of ski lifts (lower and upper zones). However the use of a degree-day model prevents them to consider the specific properties of artificial snow and the impact of grooming on the snowpack. A first proof of concept in the French Alps has shown the feasibility and the interest to cross the geographic model of ski areas and the output of the physically-based reanalysis of snow conditions SAFRAN - Crocus (François et al., CRST 2014). Since these initial developments, several ways have been explored to refine our model. A new model of ski areas has been developed. Our representation is now based on gravity derived from a DEM and ski lift localisation. A survey about snow management practices also allowed us to define criteria in order to model snowmaking areas given ski areas properties and tourism infrastructures localisation. We also suggest to revisit the assessment of ski resort viability based on the "one hundred days rule" based on natural snow depth only. Indeed, the impact of snow management must be considered so as to propose

  20. Dynamic hardness of metals

    Science.gov (United States)

    Liang, Xuecheng

    Dynamic hardness (Pd) of 22 different pure metals and alloys having a wide range of elastic modulus, static hardness, and crystal structure were measured in a gas pulse system. The indentation contact diameter with an indenting sphere and the radius (r2) of curvature of the indentation were determined by the curve fitting of the indentation profile data. r 2 measured by the profilometer was compared with that calculated from Hertz equation in both dynamic and static conditions. The results indicated that the curvature change due to elastic recovery after unloading is approximately proportional to the parameters predicted by Hertz equation. However, r 2 is less than the radius of indenting sphere in many cases which is contradictory to Hertz analysis. This discrepancy is believed due to the difference between Hertzian and actual stress distributions underneath the indentation. Factors which influence indentation elastic recovery were also discussed. It was found that Tabor dynamic hardness formula always gives a lower value than that directly from dynamic hardness definition DeltaE/V because of errors mainly from Tabor's rebound equation and the assumption that dynamic hardness at the beginning of rebound process (Pr) is equal to kinetic energy change of an impact sphere over the formed crater volume (Pd) in the derivation process for Tabor's dynamic hardness formula. Experimental results also suggested that dynamic to static hardness ratio of a material is primarily determined by its crystal structure and static hardness. The effects of strain rate and temperature rise on this ratio were discussed. A vacuum rotating arm apparatus was built to measure Pd at 70, 127, and 381 mum sphere sizes, these results exhibited that Pd is highly depended on the sphere size due to the strain rate effects. P d was also used to substitute for static hardness to correlate with abrasion and erosion resistance of metals and alloys. The particle size effects observed in erosion were

  1. Snow Monitoring Using Remote Sensing Data: Modification of Normalized Difference Snow Index

    Science.gov (United States)

    Kaplan, G.; Avdan, U.

    2016-12-01

    Snow cover is an important part of the Earth`s climate system so its continuous monitoring is necessary to map snow cover in high resolution. Satellite remote sensing can successfully fetch land cover and land cover changes. Although normalized difference snow index NDSI has quite good accuracy, topography shadow, water bodies and clouds can be easily misplaced as snow. Using Landsat TM, +ETM and TIRS/OLI satellite images, the NDSI was modified for more accurate snow mapping. In this paper, elimination of the misplaced water bodies was made using the high reflectance of the snow in the blue band. Afterwards, the modified NDSI (MNDSI) was used for estimating snow cover through the years on the highest mountains in Republic of Macedonia. The results from this study show that the MNDSI accuracy is bigger than the NDSI`s, totally eliminating the misplaced water bodies, and partly the one caused from topography and clouds. Also, it was noticed that the snow cover in the study area has been lowered through the years. For future studies, the MNDSI should be validated on different study areas with different characteristics.

  2. A blending snow cover data base on MODIS and AMSR-E snow cover in Qinghai-Tibet Plateau

    Science.gov (United States)

    Xiaohua, H.; Wang, J.; Che, T.; Dai, L. Y.

    2012-04-01

    The algorithms of MODIS Terra and MODIS Aqua versions of the snow products have been developed by the NASA National Snow and Ice Data Center (NSIDC). The MODIS global snow-cover products have been available through the NSIDC Distributed Active Archive Center (DAAC) since February 24, 2000 to Terra and July 4, 2002 to Aqua. The MODIS snow-cover maps represent a potential improvement relative to hemispheric-scale snow maps that are available today mainly because of the improved spatial resolution and snow/cloud discrimination capabilities of MODIS, and the frequent global coverage. In China, the snow distribution is different to other regions. Their accuracy on Qinghai-Tibet Plateau (QTP), however, has not yet been established. There are some drawbacks about NSIDC global snow cover products on QTP: 1. The characteristics of snow depth distribution on QTP: Thin, discontinuous. Our research indicated the MODIS snow-cover products underestimated the snow cover area in QTP. 2. The daily snow cover product from MODIS-Terra and Aqua can include the data gaps. 3. The snow products can separate snow from most obscuring clouds. However, there are still many cloud pixels in daily snow cover products. The study developed a new blending daily snow cover algorithm through improving the NSIDC snow algorithms and combining MODIS and AMSR-E data in QTP. The new snow cover products will provide daily snow cover at 500-m resolution in QTP. The new snow cover algorithm employs a grouped-criteria technique using the Normalized Difference Snow Index (NDSI) and other spectral threshold tests and image fusion technology to identify and classify snow on a pixel-by-pixel basis. The usefulness of the NDSI is based on the fact that snow and ice are considerably more reflective in the visible than in the shortwave IR part of the spectrum, and the reflectance of most clouds remains high in the short-wave IR, while the reflectance of snow is low. We propose a set of three steps, based on a

  3. The Importance of Snow Distribution on Sea Ice

    Science.gov (United States)

    Butler, B.; Polashenski, C.; Divine, D.; King, J.; Liston, G. E.; Nicolaus, M.; Rösel, A.

    2015-12-01

    Snow's insulating and reflective properties substantially influence Arctic sea ice growth and decay. A particularly important, but under-appreciated, aspect of snow on sea ice is its fine-scale spatial distribution. Snow redistribution into dunes and drifts controls the effective thermal conductivity of a snowpack and dictates the locations of melt pond formation, exerting considerable control over ice mass balance. The effective thermal conductivity of snow distributions created on sea ice, for example, is often considerably greater than a uniform snowpack of equivalent mean thickness. During the N-ICE 2015 campaign north of Svalbard, we studied snow distributions across multiple ice types and the impacts these have on thermal fluxes and ice mass balance. We used terrestrial LiDAR to observe the snow surface topography over km2 areas, conducted many thousands of manual snow depth measurements, and collected hundreds of observations of the snow physical properties in snow pits. We find that the wind driven redistribution of snow can alter the net effect of a constant snow cover volume on ice mass balance as strongly as inter-annual variability in the amount and timing of snowfall. Further comparison with snow depth distributions from field campaigns in other parts of the Arctic highlights regional and inter-annual differences in snow distribution. We quantify the impact of this variability on ice mass balance and demonstrate the need for considering snow distributions and redistribution processes in sea ice models.

  4. Uncertainty in alpine snow mass balance simulations due to snow model parameterisation and windflow representation

    Science.gov (United States)

    Musselman, K. N.; Pomeroy, J. W.; Essery, R.; Leroux, N.

    2013-12-01

    Despite advances in alpine snow modelling there remain two fundamental areas of divergent scientific thought in estimating alpine snow mass balances: i) blowing snow sublimation losses, and ii) wind flow representation. Sublimation calculations have poorly understood humidity feedbacks that vary considerably and mathematical representations of alpine windflow vary in complexity - these differences introduce uncertainty. To better estimate and restrain this uncertainty, a variety of physically based, spatially distributed snowmelt models that consider the physics of wind redistribution and sublimation of blowing snow were evaluated for their ability to simulate seasonal snow distribution and melt patterns in a windy alpine environment in the Canadian Rockies. The primary difference in the snow models was their calculation of blowing snow sublimation losses which ranged from large to small estimates. To examine the uncertainty introduced by windflow calculations on the snow model simulations, each model was forced with output from windflow models of varying computational complexity and physical realism from a terrain-based empirical interpolation of station observations to a simple turbulence model to a computational fluid dynamics model that solves for the Navier-Stokes equations. The high-resolution snow simulations were run over a 1 km2 spatial extent centred on a ridgetop meteorological station within the Marmot Creek Research basin, Alberta, Canada. The three windflow simulations all produced reasonable results compared to wind speeds measured on two opposing slopes (bias better than ×0.3 m s-1; RMSE errors were greatest when forced with output from the empirical wind model and smallest using output from either of the two turbulence models. Simulations with higher blowing snow sublimation rates tended to better match measured SWE at multiple scales, confirming that alpine blowing snow sublimation is an important component of the snow mass balance in this region

  5. Processing and analysis of Global snow cover time series for climate change assessment

    OpenAIRE

    2014-01-01

    Remote sensing data offer the opportunity to detect terrestrial snow cover in high temporal and spatial resolution. Such information is essential for various applications – ranging from small scale predictions of runoff or floods, ground water recharge and hydro power generation to large scale planetary processes connected to climate change. The processing of globally available time series of remote sensing data constitutes a challenging task due to the huge data volume and computational dema...

  6. Data sets for snow cover monitoring and modelling from the National Snow and Ice Data Center

    Science.gov (United States)

    Holm, M.; Daniels, K.; Scott, D.; McLean, B.; Weaver, R.

    2003-04-01

    A wide range of snow cover monitoring and modelling data sets are pending or are currently available from the National Snow and Ice Data Center (NSIDC). In-situ observations support validation experiments that enhance the accuracy of remote sensing data. In addition, remote sensing data are available in near-real time, providing coarse-resolution snow monitoring capability. Time series data beginning in 1966 are valuable for modelling efforts. NSIDC holdings include SMMR and SSM/I snow cover data, MODIS snow cover extent products, in-situ and satellite data collected for NASA's recent Cold Land Processes Experiment, and soon-to-be-released ASMR-E passive microwave products. The AMSR-E and MODIS sensors are part of NASA's Earth Observing System flying on the Terra and Aqua satellites Characteristics of these NSIDC-held data sets, appropriateness of products for specific applications, and data set access and availability will be presented.

  7. Estimating maritime snow density from seasonal climate variables

    Science.gov (United States)

    Bormann, K. J.; Evans, J. P.; Westra, S.; McCabe, M. F.; Painter, T. H.

    2013-12-01

    Snow density is a complex parameter that influences thermal, optical and mechanical snow properties and processes. Depth-integrated properties of snowpacks, including snow density, remain very difficult to obtain remotely. Observations of snow density are therefore limited to in-situ point locations. In maritime snowfields such as those in Australia and in parts of the western US, snow densification rates are enhanced and inter-annual variability is high compared to continental snow regions. In-situ snow observation networks in maritime climates often cannot characterise the variability in snowpack properties at spatial and temporal resolutions required for many modelling and observations-based applications. Regionalised density-time curves are commonly used to approximate snow densities over broad areas. However, these relationships have limited spatial applicability and do not allow for interannual variability in densification rates, which are important in maritime environments. Physically-based density models are relatively complex and rely on empirical algorithms derived from limited observations, which may not represent the variability observed in maritime snow. In this study, seasonal climate factors were used to estimate late season snow densities using multiple linear regressions. Daily snow density estimates were then obtained by projecting linearly to fresh snow densities at the start of the season. When applied spatially, the daily snow density fields compare well to in-situ observations across multiple sites in Australia, and provide a new method for extrapolating existing snow density datasets in maritime snow environments. While the relatively simple algorithm for estimating snow densities has been used in this study to constrain snowmelt rates in a temperature-index model, the estimates may also be used to incorporate variability in snow depth to snow water equivalent conversion.

  8. Integrated snow and avalanche monitoring syatem for Indian Himalaya using multi-temporal satellite imagery and ancillary data

    Science.gov (United States)

    Sharma, S. S.; Mani, Sneh; Mathur, P.

    . Different methods have been used for the analysis of the temporal changes in satellite images. Multi-sensor data fusion techniques have been applied to increase the accuracy of classification, and also for extraction of necessary information about characteristics of snow and avalanches and the ground conditions. The results of the analysis of time series of last two winters are reported. The study confirms that significant changes in snow characteristics and wetness are mainly due to large variations in temperature at these altitudes, which contribute towards avalanche activities in early winter. A definite relationship has been observed between snow wetness, altitude and period of the year with respect to the probability of an avalanche occurrence. Snow wetness is found to be inversely proportional to the altitude, whereas probability of an avalanche is directly proportional to the wetness of snow, lying either over thin grass or boulder-covered ground. The results were verified through extensive field measurements. The emphasis has been laid on establishment of a dense network of Automatic Weather Stations (AWS), Upper Air Stations (UAS) and observatories in entire Himalaya; development of GIS based data bases using satellite imageries and other ancillary data for weather, snow and land cover monitoring. Records of past years will provide base information for realistic estimation of the impact of climatic changes and confidence to predict the weather and avalanches in various regions of Himalaya. Key Words: Integrated Monitoring System, Time series multi-sensor/multi-temporal Satellite Imageries, Multi-sensor Data Fusion, Change Detection, Snow characteristics

  9. Integrated snow and avalanche monitoring system for Indian Himalaya using multi-temporal satellite imagery and ancillary data

    Science.gov (United States)

    Sharma, S. S.; Mani, Sneh; Mathur, P.

    . Different methods have been used for the analysis of the temporal changes in satellite images. Multi-sensor data fusion techniques have been applied to increase the accuracy of classification, and also for extraction of necessary information about characteristics of snow and avalanches and the ground conditions. The results of the analysis of time series of last two winters are reported. The study confirms that significant changes in snow characteristics and wetness are mainly due to large variations in temperature at these altitudes, which contribute towards avalanche activities in early winter. A definite relationship has been observed between snow wetness, altitude and period of the year with respect to the probability of an avalanche occurrence. Snow wetness is found to be inversely proportional to the altitude, whereas probability of an avalanche is directly proportional to the wetness of snow, lying either over thin grass or boulder-covered ground. The results were verified through extensive field measurements. The emphasis has been laid on establishment of a dense network of Automatic Weather Stations (AWS), Upper Air Stations (UAS) and observatories in entire Himalaya; development of GIS based data bases using satellite imageries and other ancillary data for weather, snow and land cover monitoring. Records of past years will provide base information for realistic estimation of the impact of climatic changes and confidence to predict the weather and avalanches in various regions of Himalaya. Key Words: Integrated Monitoring System, Time series multi-sensor/multi-temporal Satellite Imageries, Multi-sensor Data Fusion, Change Detection, Snow characteristics

  10. Evaluation of MODIS Albedo Product (MCD43A) over Grassland, Agriculture and Forest Surface Types During Dormant and Snow-Covered Periods

    Science.gov (United States)

    Wang, Zhousen; Schaaf, Crystal B.; Strahler, Alan H.; Chopping, Mark J.; Roman, Miguel O.; Shuai, Yanmin; Woodcock, Curtis E.; Hollinger, David Y.; Fitzjarrald, David R.

    2013-01-01

    This study assesses the Moderate-resolution Imaging Spectroradiometer (MODIS) BRDF/albedo 8 day standard product and products from the daily Direct Broadcast BRDF/albedo algorithm, and shows that these products agree well with ground-based albedo measurements during the more difficult periods of vegetation dormancy and snow cover. Cropland, grassland, deciduous and coniferous forests are considered. Using an integrated validation strategy, analyses of the representativeness of the surface heterogeneity under both dormant and snow-covered situations are performed to decide whether direct comparisons between ground measurements and 500-m satellite observations can be made or whether finer spatial resolution airborne or spaceborne data are required to scale the results at each location. Landsat Enhanced Thematic Mapper Plus (ETM +) data are used to generate finer scale representations of albedo at each location to fully link ground data with satellite data. In general, results indicate the root mean square errors (RMSEs) are less than 0.030 over spatially representative sites of agriculture/grassland during the dormant periods and less than 0.050 during the snow-covered periods for MCD43A albedo products. For forest, the RMSEs are less than 0.020 during the dormant period and 0.025 during the snow-covered periods. However, a daily retrieval strategy is necessary to capture ephemeral snow events or rapidly changing situations such as the spring snow melt.

  11. Spatial Scaling of Snow Observations and Microwave Emission Modeling During CLPX and Appropriate Satellite Sensor Resolution

    Science.gov (United States)

    Kim, Edward J.; Tedesco, Marco

    2005-01-01

    Accurate estimates of snow water equivalent and other properties play an important role in weather, natural hazard, and hydrological forecasting and climate modeling over a range of scales in space and time. Remote sensing-derived estimates have traditionally been of the "snapshot" type, but techniques involving models with assimilation are also being explored. In both cases, forward emission models are useful to understand the observed passive microwave signatures and developing retrieval algorithms. However, mismatches between passive microwave sensor resolutions and the scales of processes controlling subpixel heterogeneity can affect the accuracy of the estimates. Improving the spatial resolution of new passive microwave satellite sensors is a major desire in order to (literally) resolve such subpixel heterogeneity, but limited spacecraft and mission resources impose severe constraints and tradeoffs. In order to maximize science return while mitigating risk for a satellite concept, it is essential to understand the scaling behavior of snow in terms of what the sensor sees (brightness temperature) as well as in terms of the actual variability of snow. NASA's Cold Land Processes Experiment-1 (CLPX-1: Colorado, 2002 and 2003) was designed to provide data to measure these scaling behaviors for varying snow conditions in areas with forested, alpine, and meadow/pasture land cover. We will use observations from CLPX-1 ground, airborne, and satellite passive microwave sensors to examine and evaluate the scaling behavior of observed and modeled brightness temperatures and observed and retrieved snow parameters across scales from meters to 10's of kilometers. The conclusions will provide direct examples of the appropriate spatial sampling scales of new sensors for snow remote sensing. The analyses will also illustrate the effects and spatial scales of the underlying phenomena (e.g., land cover) that control subpixel heterogeneity.

  12. Evaluation of the snow-covered area data product from MODIS

    Science.gov (United States)

    Maurer, Edwin P.; Rhoads, Joshua D.; Dubayah, Ralph O.; Lettenmaier, Dennis P.

    2003-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS), flown on board the Terra Earth Observing System (EOS) platform launched in December 1999, produces a snow-covered area (SCA) product. This product is expected to be of better quality than SCA products based on operational satellites (notably GOES and AVHRR), due both to improved spectral resolution and higher spatial resolution of the MODIS instrument. The gridded MODIS SCA product was compared with the SCA product produced and distributed by the National Weather Service National Operational Hydrologic Remote Sensing Center (NOHRSC) for 46 selected days over the Columbia River basin and 32 days over the Missouri River basin during winter and spring of 2000-01. Snow presence or absence was inferred from ground observations of snow depth at 1330 stations in the Missouri River basin and 762 stations in the Columbia River basin, and was compared with the presence/absence classification for the corresponding pixels in the MODIS and NOHRSC SCA products. On average, the MODIS SCA images classified fewer pixels as cloud than NOHRSC, the effect of which was that 15% more of the Columbia basin area could be classified as to presence-absence of snow, while overall there was a statistically insignificant difference over the Missouri basin. Of the pixels classified as cloud free, MODIS misclassified 4% and 5% fewer overall (for the Columbia and Missouri basins respectively) than did the NOHRSC product. When segregated by vegetation cover, forested areas had the greatest differences in fraction of cloud cover reported by the two SCA products, with MODIS classifying 13% and 17% less of the images as cloud for the Missouri and Columbia basins respectively. These differences are particularly important in the Columbia River basin, 39% of which is forested. The ability of MODIS to classify significantly greater amounts of snow in the presence of cloud in more topographically complex, forested, and snow-dominated areas of

  13. Spring Snow Depth on Arctic Sea Ice using the IceBridge Snow Depth Product (Invited)

    Science.gov (United States)

    Webster, M.; Rigor, I. G.; Nghiem, S. V.; Kurtz, N. T.; Farrell, S. L.

    2013-12-01

    Snow has dual roles in the growth and decay of Arctic sea ice. In winter, it insulates sea ice from colder air temperatures, slowing its growth. From spring into summer, the albedo of snow determines how much insolation is transmitted through the sea ice and into the underlying ocean, ultimately impacting the progression of the summer ice melt. Knowing the snow thickness and distribution are essential for understanding and modeling sea ice thermodynamics and the surface heat budget. Therefore, an accurate assessment of the snow cover is necessary for identifying its impacts in the changing Arctic. This study assesses springtime snow conditions on Arctic sea ice using airborne snow thickness measurements from Operation IceBridge (2009-2012). The 2012 data were validated with coordinated in situ measurements taken in March 2012 during the BRomine, Ozone, and Mercury EXperiment field campaign. We find a statistically significant correlation coefficient of 0.59 and RMS error of 5.8 cm. The comparison between the IceBridge snow thickness product and the 1937, 1954-1991 Soviet drifting ice station data suggests that the snow cover has thinned by 33% in the western Arctic and 44% in the Beaufort and Chukchi Seas. A rudimentary estimation shows that a thinner snow cover in the Beaufort and Chukchi Seas translates to a mid-December surface heat flux as high as 81 W/m2 compared to 32 W/m2. The relationship between the 2009-2012 thinner snow depth distribution and later sea ice freeze-up is statistically significant, with a correlation coefficient of 0.59. These results may help us better understand the surface energy budget in the changing Arctic, and may improve our ability to predict the future state of the sea ice cover.

  14. Hard and Soft

    OpenAIRE

    Claes H. de Vreese; Boomgaarden, Hajo G.; Semetko, Holli A.

    2008-01-01

    Abstract Support for European integration is a function no longer only of `hard' economic and utilitarian predictors but also of `soft' predictors such as feelings of identity and attitudes towards immigrants. Focusing on the issue of the potential membership of Turkey in the European Union (EU), this study demonstrates that the importance of `soft' predictors outweighs the role of `hard' predictors in understanding public opinion about Turkish membership. The study draws on survey...

  15. Modeling the snow cover in climate studies: 2. The sensitivity to internal snow parameters and interface processes

    Science.gov (United States)

    Loth, Bettina; Graf, Hans-F.

    1998-05-01

    In order to find an optimal complexity for snow-cover models in climate studies, the influence of single snow processes on both the snow mass balance and the energy fluxes between snow surface and atmosphere has been investigated. Using a sophisticated model, experiments were performed under several different atmospheric and regional conditions (Arctic, midlatitudes, alpine regions). A high simulation quality can be achieved with a multilayered snow-cover model resolving the internal snow processes (cf. part 1,[Loth and Graf, this issue]). Otherwise, large errors can occur, mostly in zones which are of paramount importance for the entire climate dynamics. Owing to simplifications of such a model, the mean energy balance of the snow cover, the turbulent heat fluxes, and the long-wave radiation at the snow surface may alter by between 1 W/m2 and 8 W/m2. The snow-surface temperatures can be systematically changed by about 10 K.

  16. Remember Hard but Think Softly: Metaphorical Effects of Hardness/Softness on Cognitive Functions

    Directory of Open Access Journals (Sweden)

    Jiushu Xie

    2016-09-01

    Full Text Available Previous studies have found that bodily stimulation, such as hardness, biases social judgment and evaluation via metaphorical association; however, it remains unclear whether bodily stimulation also affects cognitive functions, such as memory and creativity. The current study used metaphorical associations between hard and rigid and between soft and flexible in Chinese, to investigate whether the experience of hardness affected cognitive functions requiring either rigidity (memory or flexibility (creativity. In Experiment 1, we found that Chinese-speaking participants performed better at recalling previously memorized words while sitting on a hard-surface stool (the hard condition than a cushioned one (the soft condition. In Experiment 2, participants sitting on a cushioned stool outperformed those sitting on a hard-surface stool on a Chinese riddle task, which required creative/flexible thinking, but not on an analogical reasoning task, which required both rigid and flexible thinking. The results suggest the hardness experience affects cognitive functions that are metaphorically associated with rigidity and flexibility. They support the embodiment proposition that cognitive functions and representations could be grounded via metaphorical association in bodily states.

  17. Snow cover and soil moisture in mountains

    Science.gov (United States)

    Wever, N.; Lehning, M.

    2012-04-01

    Soil moisture is an important parameter of the climate system. It constrains evapotranspiration of plants and it functions as a storage of water, giving it an economic value, e.g. for agriculture. Furthermore, soil moisture is an important factor for predicting flood risk. In mountainous areas with a seasonal snow cover, the spatial distribution of snow depth is strongly influencing the spatial variation of soil moisture. To assess potential flooding situations during snow melt and rain on snow events in particular but for any heavy precipitation event in the mountains, it is important to understand the influence of the snow cover on soil status with respect to liquid and solid water. Only if this is known, the reaction of the soil i.e. amount of runoff, storage or melt, on additional water input can be assessed. For an operational assessment of the soil moisture state in the Swiss Alps at 140 measurement sites for snow and avalanche forecasting (IMIS network), the SNOWPACK model has been extended with a soil module, solving the Richards equation for the matrix flow. The modelling is validated with vertical profile measurements of soil moisture at meteorological stations in an Alpine catchment near Davos, Switzerland. It was found that the combination of a physical based snowpack model with a Richards equation solver seems to provide an adequate description of soil moisture fluctuations, especially in near surface layers. Soil moisture fluctuations, both measured and modelled, are strongly reduced when a snow cover is present. The measurements also revealed a strong increase in soil moisture, accompanied by a daily cycle in soil moisture during snow melt, extending down to 120cm depth. When soil properties from literature were assumed for the soil type in the vertical profile, the daily cycle in the model during snow melt was restricted mainly to the top layers, while observations show also a reaction in deeper layers. These observations are consistent with the

  18. Hardness amplification in nondeterministic logspace

    OpenAIRE

    Gupta, Sushmita

    2007-01-01

    A hard problem is one which cannot be easily computed by efficient algorithms. Hardness amplification is a procedure which takes as input a problem of mild hardness and returns a problem of higher hardness. This is closely related to the task of decoding certain error-correcting codes. We show amplification from mild average case hardness to higher average case hardness for nondeterministic logspace and worst-to-average amplification for nondeterministic linspace. Finally we explore possible ...

  19. Satellite discrimination of snow/cloud surfaces

    Science.gov (United States)

    Crane, R. G.; Anderson, M. R.

    1984-01-01

    Differentiation between cloud cover and snow surfaces using remotely sensed data is complicated by the similarity of their radiative temperatures, and also by their similar reflectances at visible wavelengths. A method of cloud analysis over snow-covered regions is presented, using 1.51-1.63 micron data from an experimental sensor on board a U.S. Air Force Defense Meteorological Satellite Program platform. At these wavelengths, snow appears relatively 'black' while clouds are highly reflective. The spatial structure of the 1.51-1.63 micron reflectivity fields over a continuous snow surface are examined. Plots of mean reflectance against coefficients of variation for 4 x 4 pixel areas reveals a cluster of points have low reflectivity and low variability, corresponding to snow-covered (cloud free) areas, and a similar cluster with high reflectances corresponding to 100 per cent cloud cover. For the case of a single layered cloud, the radiances associated with partially filled fields of view are also inferred.

  20. John Snow: the first hired gun?

    Science.gov (United States)

    Lilienfeld, D E

    2000-07-01

    The 1854 English cholera outbreak led to reform of Victorian public health legislation, including the Nuisances Removal and Diseases Prevention Act. The reforms threatened the closure of many factories whose fumes were considered hazardous to the public's health. The second witness to appear before the Parliamentary committee considering the reforms was Dr. John Snow. Snow testified on behalf of the manufacturers threatened by the reforms. He stated that the fumes from such establishments were not hazardous. He contended that the workers in these factories did not become ill as a result of their exposures, and therefore these fumes could not be a hazard to the general public's health. Snow also presented data from the 1854 cholera outbreak as the basis for his belief that epidemic diseases were transmitted by water, not air. Although the data concerned cholera, Snow extended the inference to all epidemic diseases. When the committee's report was published, The Lancet chastised Snow in a stinging editorial. Parliament subsequently revised the bill in favor of the manufacturers and passed it into law. The implications of this particular episode in the history of epidemiology are discussed.

  1. Invited commentary: the testimony of Dr. Snow.

    Science.gov (United States)

    Vandenbroucke, J P

    2000-07-01

    This paper presents a commentary on the testimony delivered by Dr. John Snow before the British Parliamentary Committee in 1855. It is noted that in Snow's testimony was highlighted his extremely strong belief in germ theory and contagion and his consequent contempt for anything close to the rivaling theory that miasmatic emanations cause disease. Snow's unreasonableness may have been because he already held his germ theory and drinking water convictions before he made his observations. In addition, based on his published books it has become apparent that even his data analysis was guided by such preconceptions. Although Snow's opinion on germ theory created contemporaries, it is noted however, that Snow did not truly sway contemporary opinion, and his theories were not agreed as a complete breakthrough in the way that they are often presented as being in epidemiological textbooks. Overall, the fundamental problem with the miasma and contagion theories at the time was that both failed to answer certain questions, including transmission of diseases, development of diseases, and the issue of temporary carriers of causative germs.

  2. Extreme heterogeneity of land surface in spring inducing highly complex micrometeorological flow features and heat exchange processes over partly snow covered areas

    Science.gov (United States)

    Mott, Rebecca; Schlögl, Sebastian; Dirks, Lisa; Lehning, Michael

    2017-04-01

    The melting mountain snow cover in spring typically changes from a continuous snow cover to a mosaic of patches of snow and bare ground inducing an extreme heterogeneity of the land surface. Energy balance models typically assume a continuous snow cover, neglecting the complex interaction between the atmospheric boundary layer and the strongly variable surface. We experimentally investigated the small-scale boundary layer dynamics over snow patches and their effect on the energy balance at the snow surface. A comprehensive measurement campaign, the Dischma Experiment, was conducted during three entire ablation periods in spring 2014, 2015 and 2016. The aim of this project is to investigate the boundary layer development and the energy exchange over a melting snow cover with a gradually decreasing snow cover fraction. For this purpose, two measurement towers equipped with five to six ultrasonic anemometers were installed over a long-lasting snow patch. Furthermore, temporally and spatially high resolution ablation rates and snow surface temperatures were determined with a terrestrial laser scanner and an Infrared camera. This data set allows us to relate the spatial patterns of ablation rates and snow surface temperatures to boundary layer dynamics and the changing snow cover fraction. Experimental data reveal that wind conditions, snow cover distribution, local wind fetch distance and topographical curvature control the near-surface boundary layer characteristics and heat exchange processes over snow. The strong heterogeneity of land surface induced by the patchy snow cover caused a high spatial and temporal variability of snow surface temperature and snow melt patterns. Small scale flow features, such as katabatic flows or wind sheltering can be shown to strongly affect the temporal evolution of snow surface patterns. Furthermore, turbulence data reveal a strong correlation of turbulent heat exchange over melting snow with the occurrence of internal thermal

  3. PERSPECTIVE: Snow matters in the polar regions

    Science.gov (United States)

    Sodeau, John

    2010-03-01

    to 30 times greater than those found in ice-free areas. The main question to ask is: how might the bromine have become released to the atmosphere? Many ideas have, in fact, been put forward over the last few years as to how such polar ocean-troposphere exchanges can take place. Much of the interest was driven by the so-called 'sudden' ozone depletion episodes first detected in Arctic air during the 1990s alongside simultaneous bromine 'explosions' which were monitored by ground-based instrumentation and satellite (as the radical BrO) over sea-ice covered by snowpack (Hausmann and Platt 1994, Schonhardt et al 2008). The likely precursors suggested, to date, have been sea-salt, frost-flowers and anthropogenic contents rather than organo- bromine matter (Simpson et al 2007). Associated processing routes including the formation of HOBr, the need for acidity, the involvement of trihalide ions and the potential role of freezing processes and the quasi-liquid layer have all been discussed in this context (Abbatt 1994, Neshyba et al 2009, O'Driscoll et al 2006). Computational work has also led to suggestions that preferential surface dispersion of the more highly polarizable halides (iodide and bromide ions) may lead to their direct interfacial reaction with atmospheric ozone leading to BrO or IO formation (Jungwirth and Winter 2008). The involvement of snow micro-algae in the production of halo-compounds such as CHBr3 and CH2Br2 in Antarctica cannot, of course, be ignored following the measurement of these compounds by Sturges and co-workers over 15 years ago (Sturges et al 1993). And the measurement of high levels of nutrient discussed in the recent work by Antony et al (2010) in the ice-cap areas do provide a basis for understanding why micro- algae growth in snow might be promoted. However the question still comes back to: how are these halo-compounds processed to produce 'active' species like BrO radicals, HOBr, Br atoms, Br2 gas or interhalogens such as BrCl? The

  4. Simulation of Snow Processes Beneath a Boreal Scots Pine Canopy

    Institute of Scientific and Technical Information of China (English)

    LI Weiping; LUO Yong; XIA Kun; LIU Xin

    2008-01-01

    A physically-based multi-layer snow model Snow-Atmosphere-Soil-Transfer scheme (SAST) and a land surface model Biosphere-Atmosphere Transfer Scheme (BATS) were employed to investigate how boreal forests influence snow accumulation and ablation under the canopy. Mass balance and energetics of snow beneath a Scots pine canopy in Finland at different stages of the 2003-2004 and 2004-2005 snow seasons are analyzed. For the fairly dense Scots pine forest, drop-off of the canopy-intercepted snow contributes, in some cases, twice as much to the underlying snowpack as the direct throughfall of snow. During early winter snow melting, downward turbulent sensible and condensation heat fluxes play a dominant role together with downward net longwave radiation. In the final stage of snow ablation in middle spring, downward net all-wave radiation dominates the snow melting. Although the downward sensible heat flux is comparable to the net solar radiation during this period, evaporative cooling of the melting snow surface makes the turbulent heat flux weaker than net radiation. Sensitivities of snow processes to leaf area index (LAI) indicate that a denser canopy speeds up early winter snowmelt, but also suppresses melting later in the snow season. Higher LAI increases the interception of snowfall, therefore reduces snow accumulation under the canopy during the snow season; this effect and the enhancement of downward longwave radiation by denser foliage outweighs the increased attenuation of solar radiation, resulting in earlier snow ablation under a denser canopy. The difference in sensitivities to LAI in two snow seasons implies that the impact of canopy density on the underlying snowpack is modulated by interannual variations of climate regimes.

  5. Micrometeorological processes driving snow ablation in an Alpine catchment

    Directory of Open Access Journals (Sweden)

    R. Mott

    2011-08-01

    Full Text Available Mountain snow covers typically become patchy over the course of a melting season. The snow pattern during melt is mainly governed by the end of winter snow depth distribution and the local energy balance. The objective of this study is to investigate micrometeorological processes driving snow ablation in an Alpine catchment. For this purpose we combine a meteorological model (ARPS with a fully distributed energy balance model (Alpine3D. Turbulent fluxes above melting snow are further investigated by using data from eddy-correlation systems. We compare modelled snow ablation to measured ablation rates as obtained from a series of Terrestrial Laser Scanning campaigns covering a complete ablation season. The measured ablation rates indicate that the advection of sensible heat causes locally increased ablation rates at the upwind edges of the snow patches. The effect, however, appears to be active over rather short distances except for very strong wind conditions. Neglecting this effect, the model is able to capture the mean ablation rates for early ablation periods but strongly overestimates snow ablation once the fraction of snow coverage is below a critical value. While radiation dominates snow ablation early in the season, the turbulent flux contribution becomes important late in the season. Simulation results indicate that the air temperatures appear to overestimate the local air temperature above snow patches once the snow coverage is below a critical value. Measured turbulent fluxes support these findings by suggesting a stable internal boundary layer close to the snow surface causing a strong decrease of the sensible heat flux towards the snow cover. Thus, the existence of a stable internal boundary layer above a patchy snow cover exerts a dominant control on the timing and magnitude of snow ablation for patchy snow covers.

  6. 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

  7. Deriving Snow Cover Metrics for Alaska from MODIS

    Directory of Open Access Journals (Sweden)

    Chuck Lindsay

    2015-09-01

    Full Text Available Moderate Resolution Imaging Spectroradiometer (MODIS daily snow cover products provide an opportunity for determining snow onset and melt dates across broad geographic regions; however, cloud cover and polar darkness are limiting factors at higher latitudes. This study presents snow onset and melt dates for Alaska, portions of western Canada and the Russian Far East derived from Terra MODIS snow cover daily 500 m grid data (MOD10A1 and evaluates our method for filling data gaps caused by clouds or polar darkness. Pixels classified as cloud or no data were reclassified by: spatial filtering using neighboring pixel values; temporal filtering using pixel values for days before/after cloud cover; and snow-cycle filtering based on a time series assessment of a pixel’s position within snow accumulation, cover or melt periods. During the 2012 snow year, these gap-filling methods reduced cloud pixels from 27.7% to 3.1%. A total of 12 metrics (e.g., date of first and last snow, date of persistent snow cover and periods of intermittence for each pixel were calculated by snow year. A comparison of MODIS-derived snow onset and melt dates with in situ observations from 244 weather stations generally showed an early bias in MODIS-derived dates and an effect of increasing cloudiness exacerbating bias. Our results show that mean regional duration of seasonal snow cover is 179–311 days/year and that snow cover is often intermittent, with 41% of the area experiencing ≥2 snow-covered periods during a snow season. Other regional-scale patterns in the timing of snow onset and melt are evident in the yearly 500 m gridded products publically available at http://static.gina.alaska.edu/NPS_products/MODIS_snow/.

  8. 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.

  9. Remote sensing of aerosols over snow using infrared AATSR observations

    Science.gov (United States)

    Istomina, L. G.; von Hoyningen-Huene, W.; Kokhanovsky, A. A.; Schultz, E.; Burrows, J. P.

    2011-06-01

    Infrared (IR) retrievals of aerosol optical thickness (AOT) are challenging because of the low reflectance of aerosol layer at longer wavelengths. In this paper we present a closer analysis of this problem, performed with radiative transfer (RT) simulations for coarse and accumulation mode of four main aerosol components. It shows the strong angular dependence of aerosol IR reflectance at low solar elevations resulting from the significant asymmetry of aerosol phase function at these wavelengths. This results in detectable values of aerosol IR reflectance at certain non-nadir observation angles providing the advantage of multiangle remote sensing instruments for a retrieval of AOT at longer wavelengths. Such retrievals can be of importance e.g. in case of a very strong effect of the surface on the top of atmosphere (TOA) reflectance in the visible spectral range. In the current work, a new method to retrieve AOT of the coarse and accumulation mode particles over snow has been developed using the measurements of Advanced Along Track Scanning Radiometer (AATSR) on board the ENVISAT satellite. The algorithm uses AATSR channel at 3.7 μm and utilizes its dual-viewing observation technique, implying the forward view with an observation zenith angle of around 55 degrees and the nadir view. It includes cloud/snow discrimination, extraction of the atmospheric reflectance out of measured brightness temperature (BT) at 3.7 μm, and interpolation of look-up tables (LUTs) for a given aerosol reflectance. The algorithm uses LUTs, separately simulated with RT forward calculations. The resulting AOT at 500 nm is estimated from the value at 3.7 μm using a fixed Angström parameter. The presented method has been validated against ground-based Aerosol Robotic Network (AERONET) data for 4 high Arctic stations and shows good agreement. A case study has been performed at W-Greenland on 5 July 2008. The day before was characterized by a noticeable dust event. The retrieved AOT maps of

  10. Remote sensing of aerosols over snow using infrared AATSR observations

    Directory of Open Access Journals (Sweden)

    L. G. Istomina

    2011-01-01

    Full Text Available Infrared (IR retrievals of aerosol optical thickness (AOT are challenging because of the low reflectance of aerosol layer at longer wavelengths. In this paper we present a closer analysis of this problem, performed with radiative transfer (RT simulations for coarse and accumulation mode of four main aerosol components. It shows the strong angular dependence of aerosol IR reflectance at low solar elevations resulting from significant asymmetry of aerosol phase function at these wavelengths. This results in detectable values of aerosol IR reflectance at certain non-nadir observation angles providing the advantage of multiangle remote sensing instruments for a retrieval of AOT at longer wavelengths. Such retrievals can be of importance e.g. in case of a very strong effect of the surface on the top of atmosphere (TOA reflectance in the visible range of spectrum. In current work, a new method to retrieve AOT over snow has been developed using the measurements of Advanced Along Track Scanning Radiometer (AATSR on board the ENVISAT satellite. The algorithm uses AATSR channel at 3.7 μm and utilizes its dual-viewing observation technique implying the forward view with an observation zenith angle around 55 degrees and the nadir view. It includes cloud/snow discrimination, extraction of the atmospheric reflectance out of measured brightness temperature (BT at 3.7 μm, interpolation of look-up tables (LUTs for a given aerosol reflectance. The algorithm uses LUTs, separately simulated with RT forward calculations. The resulting AOT at 500 nm is estimated from the value at 3.7 μm using a fixed Angström parameter.

    The presented method has been validated against ground-based Aerosol Robotic Network (AERONET data for 4 high Arctic stations and shows good agreement.

    A case study has been performed at W-Greenland on 5 July 2008. The day before was characterized by a noticeable dust event. The retrieved AOT maps of the region show a clear

  11. Remote sensing of aerosols over snow using infrared AATSR observations

    Directory of Open Access Journals (Sweden)

    L. G. Istomina

    2011-06-01

    Full Text Available Infrared (IR retrievals of aerosol optical thickness (AOT are challenging because of the low reflectance of aerosol layer at longer wavelengths. In this paper we present a closer analysis of this problem, performed with radiative transfer (RT simulations for coarse and accumulation mode of four main aerosol components. It shows the strong angular dependence of aerosol IR reflectance at low solar elevations resulting from the significant asymmetry of aerosol phase function at these wavelengths. This results in detectable values of aerosol IR reflectance at certain non-nadir observation angles providing the advantage of multiangle remote sensing instruments for a retrieval of AOT at longer wavelengths. Such retrievals can be of importance e.g. in case of a very strong effect of the surface on the top of atmosphere (TOA reflectance in the visible spectral range. In the current work, a new method to retrieve AOT of the coarse and accumulation mode particles over snow has been developed using the measurements of Advanced Along Track Scanning Radiometer (AATSR on board the ENVISAT satellite. The algorithm uses AATSR channel at 3.7 μm and utilizes its dual-viewing observation technique, implying the forward view with an observation zenith angle of around 55 degrees and the nadir view. It includes cloud/snow discrimination, extraction of the atmospheric reflectance out of measured brightness temperature (BT at 3.7 μm, and interpolation of look-up tables (LUTs for a given aerosol reflectance. The algorithm uses LUTs, separately simulated with RT forward calculations. The resulting AOT at 500 nm is estimated from the value at 3.7 μm using a fixed Angström parameter.

    The presented method has been validated against ground-based Aerosol Robotic Network (AERONET data for 4 high Arctic stations and shows good agreement.

    A case study has been performed at W-Greenland on 5 July 2008. The day before was characterized by a noticeable dust

  12. Mac OS X Snow Leopard for dummies

    CERN Document Server

    LeVitus, Bob

    2010-01-01

    Get to know Snow Leopard and make the most of your Mac Snow Leopard has a few new tricks up its sleeve, so whether you're new to Mac or a longtime Mac-thusiast, Mac expert Bob LeVitus has tips you'll appreciate. Learn how to start up your Mac, get to know the Dock and Finder, work your way through windows and dialogs, and organize and manage files and folders. Open the book and find: How to navigate around the Finder, Dock, and desktop Tips for opening, closing, resizing, and moving windows Steps for keeping Snow Leopard organized How to back up your system with Time Machine® Troubleshooting a

  13. NORMALIZED DIFFERENCE SNOW INDEX SIMULATION FOR SNOW-COVER MAPPING IN FOREST BY GEOSAIL MODEL

    Institute of Scientific and Technical Information of China (English)

    CAO Yun-gang; LIU Chuang

    2006-01-01

    The snow-cover mapping in forest area is always one of the difficult points for optical satellite remote sensing. To investigate reflectance variability and to improve the mapping of snow in forest area, GeoSail model was used to simulate the reflectance of a snow-covered forest. Using this model, the effects of varying canopy density, solar illumination and view geometry on the performance of the MODIS (Moderate-resolution Imaging Spectroradiometer)snow-cover mapping algorithm were investigated. The relationship between NDSI (Normalized Difference Snow Index), NDVI (Normalized Difference Vegetation Index) and snow fraction was discussed in detail. Results indicated that the weak performance would be achieved if fixed criteria were used for different regions especially in the complicated land cover components. Finally, some suggestions to MODIS SNOWMAP algorithm were put forward to improve snow mapping precision in forest area based on the simulation, for example, new criteria should be used in coniferous forest, that is, NDSI greater than 0.3 and NDVI greater than zero. Otherwise, a threshold on view zenith angle may be used in the criteria such as 45°.

  14. Arctic Snow Microstructure Experiment for the development of snow emission modelling

    Science.gov (United States)

    Maslanka, William; Leppänen, Leena; Kontu, Anna; Sandells, Mel; Lemmetyinen, Juha; Schneebeli, Martin; Proksch, Martin; Matzl, Margret; Hannula, Henna-Reetta; Gurney, Robert

    2016-04-01

    The Arctic Snow Microstructure Experiment (ASMEx) took place in Sodankylä, Finland in the winters of 2013-2014 and 2014-2015. Radiometric, macro-, and microstructure measurements were made under different experimental conditions of homogenous snow slabs, extracted from the natural seasonal taiga snowpack. Traditional and modern measurement techniques were used for snow macro- and microstructure observations. Radiometric measurements of the microwave emission of snow on reflector and absorber bases were made at frequencies 18.7, 21.0, 36.5, 89.0, and 150.0 GHz, for both horizontal and vertical polarizations. Two measurement configurations were used for radiometric measurements: a reflecting surface and an absorbing base beneath the snow slabs. Simulations of brightness temperatures using two microwave emission models, the Helsinki University of Technology (HUT) snow emission model and Microwave Emission Model of Layered Snowpacks (MEMLS), were compared to observed brightness temperatures. RMSE and bias were calculated; with the RMSE and bias values being smallest upon an absorbing base at vertical polarization. Simulations overestimated the brightness temperatures on absorbing base cases at horizontal polarization. With the other experimental conditions, the biases were small, with the exception of the HUT model 36.5 GHz simulation, which produced an underestimation for the reflector base cases. This experiment provides a solid framework for future research on the extinction of microwave radiation inside snow.

  15. Effects of snow accumulation on soil temperature and change of salinity in frozen soil from laboratory experiments

    Science.gov (United States)

    Harada, K.; Sato, E.; Ishii, M.; Nemoto, M.; Mochizuki, S.

    2008-12-01

    In order to clarify the effect of snow depth on the ground temperature, snowfalls were occurred on soil samples using an artificial snowfall machine in the laboratory and variations of soil temperatures up to 30cm were measured during snowfall. The snow types used here were dendrites (type A) and sphere (type B). The snow depths on the soil surface were 10cm and 30cm for each snow type, so four deferent experimental results were obtained. At each experiment, two samples with deferent initial volumetric water content were prepared, about 10% and 20%. The initial soil temperature was set to 5°C and temperature in the laboratory was kept at -10°C. Soil temperatures were measured at the depths of 0cm, 10cm, 20cm and 30cm during the snowfall, and continuous measurements were conducted for ten hours after the stop of snowfall. From the experiments, it is confirmed that the soil temperature strongly depended on the depths of snow on the surface, density and water content. The soil sample using the type A with the depth of 30cm snow accumulation had the highest temperature at the surface, followed by the type A with 10cm snow, type B with 30cm snow and type B with 10cm snow. It was also pointed that temperature of the high water content samples showed the high temperature decrease compared with the low water one due to the high heat capacity except for the sample using type A with 10cm snow. Numerical calculation will be needed to explain these results. In addition, another experiment will be carried out to clarify the change of salinity during soil freezing with snow accumulation. The method to measure the salinity of soil is to measure the electrical conductivity of soil and volumetric water content at the same depth. The temperature condition in the cooling bath is ranged between -10 and 5°C and changed in 24 hours. Firstly, the temperature profiles will be measured to detect the frozen front, then measurements will start and discuss the results.

  16. Thermal energy in dry snow avalanches

    Science.gov (United States)

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

    2015-09-01

    Avalanches can exhibit many different flow regimes from powder clouds to slush flows. Flow regimes are largely controlled by the properties of the snow released and entrained along the path. Recent investigations showed the temperature of the moving snow to be one of the most important factors controlling the mobility of the flow. The temperature of an avalanche is determined by the temperature of the released and entrained snow but also increases by frictional processes with time. For three artificially released avalanches, we conducted snow profiles along the avalanche track and in the deposition area, which allowed quantifying the temperature of the eroded snow layers. This data set allowed to calculate the thermal balance, from release to deposition, and to discuss the magnitudes of different sources of thermal energy of the avalanches. For the investigated dry avalanches, the thermal energy increase due to friction was mainly depending on the effective elevation drop of the mass of the avalanche with a warming of approximately 0.3 °C per 100 vertical metres. Contrarily, the temperature change due to entrainment varied for the individual avalanches, from -0.08 to 0.3 °C, and depended on the temperature of the snow along the path and the erosion depth. Infrared radiation thermography (IRT) was used to assess the surface temperature before, during and just after the avalanche with high spatial resolution. This data set allowed to identify the warmest temperatures to be located in the deposits of the dense core. Future research directions, especially for the application of IRT, in the field of thermal investigations in avalanche dynamics are discussed.

  17. Snow and ice blocking of tunnels

    Energy Technology Data Exchange (ETDEWEB)

    Lia, Leif

    1998-12-31

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

  18. Thermal energy in dry snow avalanches

    Directory of Open Access Journals (Sweden)

    W. Steinkogler

    2014-11-01

    Full Text Available Avalanches can exhibit many different flow regimes from powder clouds to slush flows. Flow regimes are largely controlled by the properties of the snow released and entrained along the path. Recent investigations showed the temperature of the moving snow to be one of the most important factors controlling the mobility of the flow. The temperature of an avalanche is determined by the temperature of the released and entrained snow but also increases by frictional and collisional processes with time. For three artificially released avalanches, we conducted snow profiles along the avalanche track and in the deposition area, which allowed quantifying the temperature of the eroded snow layers. Infrared radiation thermography (IRT was used to assess the surface temperature before, during and just after the avalanche with high spatial resolution. This data set allowed to calculate the thermal balance, from release to deposition, and to discuss the magnitudes of different sources of thermal energy of the avalanches. We could confirm that, for the investigated dry avalanches, the thermal energy increase due to friction was mainly depending on the elevation drop of the avalanche with a warming of approximately 0.5 °C per 100 height meters. Contrary, warming due to entrainment was very specific to the individual avalanche and depended on the temperature of the snow along the path and the erosion depth ranging from nearly no warming to a maximum observed warming of 1 °C. Furthermore, we could observe the warmest temperatures are located in the deposits of the dense core. Future research directions, especially for the application of IRT, in the field of thermal investigations in avalanche dynamics are discussed.

  19. Monitoring the spatio-temporal evolution of the snow cover in the eastern Alps from MODIS data

    Science.gov (United States)

    Cianfarra, P.; Salvini, F.; Valt, M.

    2009-04-01

    Estimating the snow cover extent in mountain ranges is important for a wide variety purposes including of scientific studies, environmental and meteo-climatic applications, as well as predicting water availability for energy resource and agriculture. Moreover, the monitoring of the spatio-temporal variation of the snow cover thickness, coupled with ground data from weather stations, allows to identify avalanche risk areas after heavy snowfall. The aim of this study is to test an automatic procedure to identify and map the snow coverage for different altitude interval in the eastern part of the Alpine range. There has been much progress since 1966 when the first operational snow mapping was done by NOAA with spaceborne sensors that provide daily, global observations to monitor the variability in space and time in the extent of snow cover. MODIS sensors offer increased improvements relative to the AVHRR that has been operational for many years on the NOAA Polar Operational Environmental Satellite System. In this context the MODIS provides observations at a nominal spatial resolution of 500 m versus the 1.1 km spatial resolution of the AVHRR and continuously available (spatially and temporally), spectral band observation that span the visible and short-wave infrared wavelengths, including those useful for recognize snow cover. The other advantage of using MODIS data is its availability and cost by the NASA's server. In this work we used MOD02 (L1B) data providing calibrated radiance values at the sensor (without atmospheric correction). Snow cover map production included the following steps: selection of the images with clear sky conditions, geometric correction and georeferencing to UTM zone 32 ,WSG 84 ellipsoid, to eliminate the distortion of and the typical bow-tie effect that produces the observed not alignment of the scan lines in the row image; spatial sub setting to produce an image covering an area of about 200 x 120 km; identification of the snow cover was

  20. Potential feedbacks between snow cover, soil moisture and surface energy fluxes in Southern Norway

    Science.gov (United States)

    Brox Nilsen, Irene; Tallaksen, Lena M.; Stordal, Frode

    2017-04-01

    At high latitudes, the snow season has become shorter during the past decades because snowmelt is highly sensitive to a warmer climate. Snowmelt influences the energy balance by changing the albedo and the partitioning between latent and sensible heat fluxes. It further influences the water balance by changing the runoff and soil moisture. In a previous study, we identified southern Norway as a region where significant temperature changes in summer could potentially be explained by land-atmosphere interactions. In this study we hypothesise that changes in snow cover would influence the summer surface fluxes in the succeeding weeks or months. The exceptionally warm summer of 2014 was chosen as a test bed. In Norway, evapotranspiration is not soil moisture limited, but energy limited, under normal conditions. During warm summers, however, such as in 2014, evapotranspiration can be restricted by the available soil moisture. Using the Weather Research and Forecasting (WRF) model we replace the initial ground conditions for 2014 with conditions representative of a snow-poor spring and a snow-rich spring. WRF was coupled to Noah-MP at 3 km horizontal resolution in the inner domain, and the simulations covered mid-May through September 2014. Boundary conditions used to force WRF were taken from the Era-Interim reanalysis. Snow, runoff, soil moisture and soil temperature observational data were provided by the Norwegian Water Resources and Energy Directorate for validation. The validation shows generally good agreement with observations. Preliminary results show that the reduced snowpack, hereafter "sim1" increased the air temperature by up to 5 K and the surface temperature by up to 10 K in areas affected by snow changes. The increased snowpack, hereafter "sim2", decreased the air and surface temperature by the same amount. These are weekly mean values for the first eight simulation weeks from mid May. Because of the higher net energy available ( 100 Wm-2) in sim 1, both

  1. Our sense of Snow: the myth of John Snow in medical geography.

    Science.gov (United States)

    McLeod, K S

    2000-04-01

    In 1854, Dr. John Snow identified the Broad Street pump as the source of an intense cholera outbreak by plotting the location of cholera deaths on a dot-map. He had the pump handle removed and the outbreak ended...or so one version of the story goes. In medical geography, the story of Snow and the Broad Street cholera outbreak is a common example of the discipline in action. While authors in other health-related disciplines focus on Snow's "shoe-leather epidemiology", his development of a water-borne theory of cholera transmission, and/or his pioneering role in anaesthesia, it is the dot-map that makes him a hero in medical geography. The story forms part of our disciplinary identity. Geographers have helped to shape the Snow narrative: the map has become part of the myth. Many of the published accounts of Snow are accompanied by versions of the map, but which map did Snow use? What happens to the meaning of our story when the determinative use of the map is challenged? In his book On the Mode of Communication of Cholera (2nd ed., John Churchill, London, 1855), Snow did not write that he used a map to identify the source of the outbreak. The map that accompanies his text shows cholera deaths in Golden Square (the subdistrict of London's Soho district where the outbreak occurred) from August 19 to September 30, a period much longer than the intense outbreak. What happens to the meaning of the myth when the causal connection between the pump's disengagement and the end of the outbreak is examined? Snow's data and text do not support this link but show that the number of cholera deaths was abating before the handle was removed. With the drama of the pump handle being questioned and the map, our artifact, occupying a more illustrative than central role, what is our sense of Snow?

  2. Grounded theory.

    Science.gov (United States)

    Harris, Tina

    2015-04-29

    Grounded theory is a popular research approach in health care and the social sciences. This article provides a description of grounded theory methodology and its key components, using examples from published studies to demonstrate practical application. It aims to demystify grounded theory for novice nurse researchers, by explaining what it is, when to use it, why they would want to use it and how to use it. It should enable nurse researchers to decide if grounded theory is an appropriate approach for their research, and to determine the quality of any grounded theory research they read.

  3. Western Italian Alps Monthly Snowfall and Snow Cover Duration

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of snow observations for 18 stations in the western Italian Alps. Two types of data are included: monthly snowfall amounts and monthly snow...

  4. 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....

  5. 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...

  6. Snow covers detection using terrestrial photography. Application to a mountain catchment in Alps region (France).

    Science.gov (United States)

    Barth, Thierry; Saulnier, Georges-Marie; Malet, Emmanuel

    2010-05-01

    In August 2005, a significant mudflow leaded to major impacts damages at the Sainte-Agnes village located downstream the Vorz torrent (35 km2, elevations ranging from 1248m and 2977m, Alps region, France). To meet the demand of populations and civil authorities a research program was launched to both monitor and model these regions to help to quantify water resources and vulnerability to such hazardous events, including their probable evolutions do to climatic changes. This communication focuses on one of the several forcing variables of the water cycle in mountainous regions: the snow covering. Indeed, its controls a significant part of the future available water resources and may strongly interact with liquid precipitations during snow melting season. Usual sensors such as remote sensing cannot easily quantify accurately the snow covering for small mountainous catchment at hydrological models spatial and temporal resolutions (typically Dx fog, clouds, etc.) taking into account for the very various luminosity and cloud covers conditions. To make the 2D to 3D conversion, the camera referential needs to be replaced in the catchment referential by geometrical transformations. This operation is automatically realized by automatic recognition of geo referenced ground points (particular DTM points) within the camera pictures and resolution of a matrix system. Solving this inverse matrix problem raises numerous mathematical difficulties that will be discussed in the presentation. When successfully solved, every picture pixel can then be dropped on the DTM taking into account classical problems such as hidden faces. The automatically detection of the snow pixels in each picture is then achieved. The recurrent problem is the changing of luminosity and cloud cover of the catchment. It is often very difficult to distinguish between white clouds and snow within the picture by automatic algorithm. Difficulties also arise when shading effects fade colours of the compressed

  7. Using multi-year data to evaluate performance of one-layer and multi-layer models in snow hydrology: an example from Col De Porte

    Science.gov (United States)

    Avanzi, Francesco; De Michele, Carlo; Morin, Samuel; Carmagnola, Carlo Maria; Ghezzi, Antonio; Lejeune, Yves

    2016-04-01

    Snow mass dynamics prediction represents an important task for snow hydrologists, since snow on the ground influences local/global water availability and streamflow timing and amount. Different modeling tools have been formulated for decades to predict snowmelt runoff dynamics and therefore to integrate snow mass dynamics in watershed hydrology modeling. Typical variables of interest include snow depth, snow bulk density, snow water equivalent (SWE) and snowmelt runoff. All these variables have been monitored at several locations worldwide for several decades in order to evaluate model performance. As a result, several multi-year datasets are now available to perform extensive evaluation tests. In this presentation, we report an example of these evaluations by discussing the performance of two models of different complexity in reproducing observed data of snow dynamics at a site in French Alps (Col De Porte, 1325 m AMSL), where 18 continuous-time years of observations are available. We consider Crocus as an example of multi-layer physically-based complex models and HyS (De Michele et al. 2013) as an example of a one-layer temperature-index models. Using multi-year data allows us to compare models performance over long periods of time, thus considering different climatic and snow conditions. Moreover, the use of continuous-time data allows to evaluate models performance at different temporal resolutions. De Michele, C., Avanzi, F., Ghezzi, A., and Jommi, C.: Investigating the dynamics of bulk snow density in dry and wet conditions using a one-dimensional model, The Cryosphere, 7, 433-444, doi:10.5194/tc-7-433-2013, 2013.

  8. Mapping snow depth from manned aircraft on landscape scales at centimeter resolution using structure-from-motion photogrammetry

    Science.gov (United States)

    Nolan, M.; Larsen, C.; Sturm, M.

    2015-08-01

    Airborne photogrammetry is undergoing a renaissance: lower-cost equipment, more powerful software, and simplified methods have significantly lowered the barriers to entry and now allow repeat mapping of cryospheric dynamics at spatial resolutions and temporal frequencies that were previously too expensive to consider. Here we apply these advancements to the measurement of snow depth from manned aircraft. Our main airborne hardware consists of a consumer-grade digital camera directly coupled to a dual-frequency GPS; no inertial motion unit (IMU) or on-board computer is required, such that system hardware and software costs less than USD 30 000, exclusive of aircraft. The photogrammetric processing is done using a commercially available implementation of the structure from motion (SfM) algorithm. The system is simple enough that it can be operated by the pilot without additional assistance and the technique creates directly georeferenced maps without ground control, further reducing overall costs. To map snow depth, we made digital elevation models (DEMs) during snow-free and snow-covered conditions, then subtracted these to create difference DEMs (dDEMs). We assessed the accuracy (real-world geolocation) and precision (repeatability) of our DEMs through comparisons to ground control points and to time series of our own DEMs. We validated these assessments through comparisons to DEMs made by airborne lidar and by a similar photogrammetric system. We empirically determined that our DEMs have a geolocation accuracy of ±30 cm and a repeatability of ±8 cm (both 95 % confidence). We then validated our dDEMs against more than 6000 hand-probed snow depth measurements at 3 separate test areas in Alaska covering a wide-variety of terrain and snow types. These areas ranged from 5 to 40 km2 and had ground sample distances of 6 to 20 cm. We found that depths produced from the dDEMs matched probe depths with a 10 cm standard deviation, and were statistically identical at 95

  9. Mapping snow-depth from manned-aircraft on landscape scales at centimeter resolution using Structure-from-Motion photogrammetry

    Science.gov (United States)

    Nolan, M.; Larsen, C. F.; Sturm, M.

    2015-01-01

    Airborne photogrammetry is undergoing a renaissance: lower-cost equipment, more powerful software, and simplified methods have significantly lowered the barriers-to-entry and now allow repeat-mapping of cryospheric dynamics at spatial resolutions and temporal frequencies that were previously too expensive to consider. Here we apply these techniques to the measurement of snow depth from manned aircraft. The main airborne hardware consists of a consumer-grade digital camera coupled to a dual-frequency GPS. The photogrammetric processing is done using a commercially-available implementation of the Structure from Motion (SfM) algorithm. The system hardware and software, exclusive of aircraft, costs less than USD 30 000. The technique creates directly-georeferenced maps without ground control, further reducing costs. To map snow depth, we made digital elevation models (DEMs) during snow-free and snow-covered conditions, then subtracted these to create difference DEMs (dDEMs). We assessed the accuracy (geolocation) and precision (repeatability) of our DEMs through comparisons to ground control points and to time-series of our own DEMs. We validated these assessments through comparisons to DEMs made by airborne lidar and by another photogrammetric system. We empirically determined an accuracy of ± 30 cm and a precision of ± 8 cm (both 95% confidence) for our methods. We then validated our dDEMs against more than 6000 hand-probed snow depth measurements at 3 test areas in Alaska covering a wide-variety of terrain and snow types. These areas ranged from 5 to 40 km2 and had ground sample distances of 6 to 20 cm. We found that depths produced from the dDEMs matched probe depths with a 10 cm standard deviation, and these depth distributions were statistically identical at 95% confidence. Due to the precision of this technique, other real changes on the ground such as frost heave, vegetative compaction by snow, and even footprints become sources of error in the measurement of

  10. Mapping snow-depth from manned-aircraft on landscape scales at centimeter resolution using Structure-from-Motion photogrammetry

    Directory of Open Access Journals (Sweden)

    M. Nolan

    2015-01-01

    Full Text Available Airborne photogrammetry is undergoing a renaissance: lower-cost equipment, more powerful software, and simplified methods have significantly lowered the barriers-to-entry and now allow repeat-mapping of cryospheric dynamics at spatial resolutions and temporal frequencies that were previously too expensive to consider. Here we apply these techniques to the measurement of snow depth from manned aircraft. The main airborne hardware consists of a consumer-grade digital camera coupled to a dual-frequency GPS. The photogrammetric processing is done using a commercially-available implementation of the Structure from Motion (SfM algorithm. The system hardware and software, exclusive of aircraft, costs less than USD 30 000. The technique creates directly-georeferenced maps without ground control, further reducing costs. To map snow depth, we made digital elevation models (DEMs during snow-free and snow-covered conditions, then subtracted these to create difference DEMs (dDEMs. We assessed the accuracy (geolocation and precision (repeatability of our DEMs through comparisons to ground control points and to time-series of our own DEMs. We validated these assessments through comparisons to DEMs made by airborne lidar and by another photogrammetric system. We empirically determined an accuracy of ± 30 cm and a precision of ± 8 cm (both 95% confidence for our methods. We then validated our dDEMs against more than 6000 hand-probed snow depth measurements at 3 test areas in Alaska covering a wide-variety of terrain and snow types. These areas ranged from 5 to 40 km2 and had ground sample distances of 6 to 20 cm. We found that depths produced from the dDEMs matched probe depths with a 10 cm standard deviation, and these depth distributions were statistically identical at 95% confidence. Due to the precision of this technique, other real changes on the ground such as frost heave, vegetative compaction by snow, and even footprints become sources of error in the

  11. Snow in Time for the Solstice

    Science.gov (United States)

    2004-01-01

    In mid-December, the weather in eastern North America cooperated with the calendar, and a wintry blast from the Arctic delivered freezing cold air, blustery winds, and snow just in time for the Winter Solstice on December 21' the Northern Hemisphere's longest night of the year and the official start of winter. This image was captured by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on December 20, 2004, the day after an Arctic storm dove down into the United States, bringing snow to New England (upper right of top image); the coastal mid-Atlantic, including Washington, D.C.; and the southern Appalachian Mountains in Tennessee and North Carolina. Over the Atlantic Ocean (image right), the fierce Arctic winds were raking the clouds into rows, like a gardener getting ready to plant the seeds of winter. The detailed close-up at the bottom of this image pair shows the cloud and snow patterns around Lake Ontario, illustrating the occurrence of 'lake-effect snow.' Areas in western upstate New York often get as much as fifteen feet or more of snow each year as cold air from Canada and the Arctic sweeps down over the relatively warm waters of Lakes Ontario and Erie. Cold air plus moisture from the lakes equals heavy snow. Since the wind generally blows from west to east, it is the 'downwind' cities like Buffalo and Rochester that receive the heaping helpings of snowfall, while cities on the upwind side of the lake, such as Toronto, receive much less. Unlike storms that begin with specific low-pressure systems in the Pacific Ocean and march eastward across the Pacific Northwest, the Rockies, the Great Plains, and sometimes the East, the lake-effect snows aren't tied to a specific atmospheric disturbance. They are more a function of geography, which means that the lakes can keep fueling snow storms for as long as they remain ice-free in early winter, as well as when they begin to thaw in late winter and early spring. Image courtesy the SeaWiFS Project, NASA

  12. Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow

    Science.gov (United States)

    Skofronick-Jackson, Gail; Hudak, David; Petersen, Walter; Nesbitt, Stephen W.; Chandrasekar, V.; Durden, Stephen; Gleicher, Kirstin J.; Huang, Gwo-Jong; Joe, Paul; Kollias, Pavlos; Reed, Kimberly A.; Schwaller, Mathew R.; Stewart, Ronald; Tanelli, Simone; Tokay, Ali; Wang, James R.; Wolde, Mengistu

    2014-01-01

    As a component of the Earth's hydrologic cycle, and especially at higher latitudes,falling snow creates snow pack accumulation that in turn provides a large proportion of the fresh water resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) mission Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011-2012 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite,and radiometers on constellation member satellites. Multi-parameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precipitation detection and estimation can be based. The data collection strategy was coordinated, stacked, high-altitude and in-situ cloud aircraft missions with three research aircraft sampling within a broader surface network of five ground sites taking in-situ and volumetric observations. During the field campaign 25 events were identified and classified according to their varied precipitation type, synoptic context, and precipitation amount. Herein, the GCPEx fieldcampaign is described and three illustrative cases detailed.

  13. 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

  14. Subgrid snow depth coefficient of variation within complex mountainous terrain

    OpenAIRE

    Sexstone, Graham A.; Fassnacht, Steven R.; López-Moreno, Juan Ignacio; Christopher A. Hiemstra

    2016-01-01

    Given the substantial variability of snow in complex mountainous terrain, a considerable challenge of coarse scale modeling applications is accurately representing the subgrid variability of snowpack properties. The snow depth coefficient of variation (CVds) is a useful metric for characterizing subgrid snow distributions but has not been well defined by a parameterization for mountainous environments. This study utilizes lidar-derived snow depth datasets from mountainous terrain in Colorado,...

  15. Hard and superhard nanocomposite coatings

    Energy Technology Data Exchange (ETDEWEB)

    Musil, J. [Univ. of West Bohemia, Plzen (Czech Republic). Dept. of Phys.

    2000-03-01

    This article reviews the development of hard coatings from a titanium nitride film through superlattice coatings to nanocomposite coatings. Significant attention is devoted to hard and superhard single layer nanocomposite coatings. A strong correlation between the hardness and structure of nanocomposite coatings is discussed in detail. Trends in development of hard nanocomposite coatings are also outlined. (orig.)

  16. Drifting snow climate of the Antarctic and Greenland ice sheets

    NARCIS (Netherlands)

    Lenaerts, J.T.M.

    2013-01-01

    This study presents the drifting snow climate of the Earth's ice sheets, Antarctica and Greenland. For that purpose we use a regional atmospheric climate model, RACMO2. We included a routine that is able to calculate the drifting snow fluxes and accounts for the interaction between drifting snow on

  17. 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.

  18. Numerical simulation of drifting snow sublimation in the saltation layer.

    Science.gov (United States)

    Dai, Xiaoqing; Huang, Ning

    2014-10-14

    Snow sublimation is an important hydrological process and one of the main causes of the temporal and spatial variation of snow distribution. Compared with surface sublimation, drifting snow sublimation is more effective due to the greater surface exposure area of snow particles in the air. Previous studies of drifting snow sublimation have focused on suspended snow, and few have considered saltating snow, which is the main form of drifting snow. In this study, a numerical model is established to simulate the process of drifting snow sublimation in the saltation layer. The simulated results show 1) the average sublimation rate of drifting snow particles increases linearly with the friction velocity; 2) the sublimation rate gradient with the friction velocity increases with increases in the environmental temperature and the undersaturation of air; 3) when the friction velocity is less than 0.525 m/s, the snowdrift sublimation of saltating particles is greater than that of suspended particles; and 4) the snowdrift sublimation in the saltation layer is less than that of the suspended particles only when the friction velocity is greater than 0.625 m/s. Therefore, the drifting snow sublimation in the saltation layer constitutes a significant portion of the total snow sublimation.

  19. Drifting snow climate of the Antarctic and Greenland ice sheets

    NARCIS (Netherlands)

    Lenaerts, J.T.M.|info:eu-repo/dai/nl/314850163

    2013-01-01

    This study presents the drifting snow climate of the Earth's ice sheets, Antarctica and Greenland. For that purpose we use a regional atmospheric climate model, RACMO2. We included a routine that is able to calculate the drifting snow fluxes and accounts for the interaction between drifting snow on

  20. Changing images of John Snow in the history of epidemiology.

    Science.gov (United States)

    Vandenbroucke, J P

    2001-01-01

    Ever since the end of the 19th century, the story of John Snow and his investigations into the contagiousness of cholera has fascinated epidemiologists. Several different lessons have been extracted from the interpretation and reinterpretation of Snow's work--according to prevailing insights. The story of John Snow continues to evolve, even into the 21st century.