High Angular Resolution Measurements of the Anisotropy of Reflectance of Sea Ice and Snow

Science.gov (United States)

Goyens, C.; Marty, S.; Leymarie, E.; Antoine, D.; Babin, M.; Bélanger, S.

2018-01-01

We introduce a new method to determine the anisotropy of reflectance of sea ice and snow at spatial scales from 1 m2 to 80 m2 using a multispectral circular fish-eye radiance camera (CE600). The CE600 allows measuring radiance simultaneously in all directions of a hemisphere at a 1° angular resolution. The spectral characteristics of the reflectance and its dependency on illumination conditions obtained from the camera are compared to those obtained with a hyperspectral field spectroradiometer manufactured by Analytical Spectral Device, Inc. (ASD). Results confirm the potential of the CE600, with the suggested measurement setup and data processing, to measure commensurable sea ice and snow hemispherical-directional reflectance factor, HDRF, values. Compared to the ASD, the reflectance anisotropy measured with the CE600 provides much higher resolution in terms of directional reflectance (N = 16,020). The hyperangular resolution allows detecting features that were overlooked using the ASD due to its limited number of measurement angles (N = 25). This data set of HDRF further documents variations in the anisotropy of the reflectance of snow and ice with the geometry of observation and illumination conditions and its spectral and spatial scale dependency. Finally, in order to reproduce the hyperangular CE600 reflectance measurements over the entire 400-900 nm spectral range, a regression-based method is proposed to combine the ASD and CE600 measurements. Results confirm that both instruments may be used in synergy to construct a hyperangular and hyperspectral snow and ice reflectance anisotropy data set.

Changes in snow cover over China in the 21st century as simulated by a high resolution regional climate model

International Nuclear Information System (INIS)

Shi Ying; Gao Xuejie; Wu Jia; Giorgi, Filippo

2011-01-01

On the basis of the climate change simulations conducted using a high resolution regional climate model, the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model, RegCM3, at 25 km grid spacing, future changes in snow cover over China are analyzed. The simulations are carried out for the period of 1951–2100 following the IPCC SRES A1B emission scenario. The results suggest good performances of the model in simulating the number of snow cover days and the snow cover depth, as well as the starting and ending dates of snow cover to the present day (1981–2000). Their spatial distributions and amounts show fair consistency between the simulation and observation, although with some discrepancies. In general, decreases in the number of snow cover days and the snow cover depth, together with postponed snow starting dates and advanced snow ending dates, are simulated for the future, except in some places where the opposite appears. The most dramatic changes are found over the Tibetan Plateau among the three major snow cover areas of Northeast, Northwest and the Tibetan Plateau in China.

Small scale variability of snow properties on Antarctic sea ice

Science.gov (United States)

Wever, Nander; Leonard, Katherine; Paul, Stephan; Jacobi, Hans-Werner; Proksch, Martin; Lehning, Michael

2016-04-01

Snow on sea ice plays an important role in air-ice-sea interactions, as snow accumulation may for example increase the albedo. Snow is also able to smooth the ice surface, thereby reducing the surface roughness, while at the same time it may generate new roughness elements by interactions with the wind. Snow density is a key property in many processes, for example by influencing the thermal conductivity of the snow layer, radiative transfer inside the snow as well as the effects of aerodynamic forcing on the snowpack. By comparing snow density and grain size from snow pits and snow micro penetrometer (SMP) measurements, highly resolved density and grain size profiles were acquired during two subsequent cruises of the RV Polarstern in the Weddell Sea, Antarctica, between June and October 2013. During the first cruise, SMP measurements were done along two approximately 40 m transects with a horizontal resolution of approximately 30 cm. During the second cruise, one transect was made with approximately 7.5 m resolution over a distance of 500 m. Average snow densities are about 300 kg/m3, but the analysis also reveals a high spatial variability in snow density on sea ice in both horizontal and vertical direction, ranging from roughly 180 to 360 kg/m3. This variability is expressed by coherent snow structures over several meters. On the first cruise, the measurements were accompanied by terrestrial laser scanning (TLS) on an area of 50x50 m2. The comparison with the TLS data indicates that the spatial variability is exhibiting similar spatial patterns as deviations in surface topology. This suggests a strong influence from surface processes, for example wind, on the temporal development of density or grain size profiles. The fundamental relationship between variations in snow properties, surface roughness and changes therein as investigated in this study is interpreted with respect to large-scale ice movement and the mass balance.

Small scale variability of snow density on Antarctic sea ice

Science.gov (United States)

Wever, N.; Leonard, K. C.; Paul, S.; Jacobi, H. W.; Proksch, M.; Lehning, M.

2016-12-01

Snow on sea ice plays an important role in air-ice-sea interactions. For example, snow may smooth the ice surface when snow drift is occurring, while at the same time it may also generate roughness elements by interactions with the wind. Snow density is a key property in many processes, for example by influencing the thermal conductivity of the snow layer, radiative transfer inside the snow as well as the effects of aerodynamic forcing on the snowpack. We present data from an in-situ measurement campaign in the Weddell Sea during two subsequent cruises of RV Polarstern. By comparing snow density from snow pits and snow micro penetrometer (SMP) measurements, augmented by terrestrial laser scanning (TLS) on an area of 50x50 m2, highly resolved density profiles and surface topology were acquired at a horizontal resolution of approximately 30 cm. Average snow densities are about 280 kg/m3, but the analysis also reveals a high spatial variability in snow density on sea ice in both horizontal and vertical direction, ranging from roughly 170 to 360 kg/m3. This variability is expressed by coherent snow structures over several meters, which disappear over larger distances. A comparison with TLS data indicates that the spatial variability is related to deviations in surface topology. This suggests a strong influence from surface processes, for example wind, on the temporal development of density profiles. The fundamental relationship between density variations, surface roughness and changes therein as investigated in this study are interpreted with respect to larger-scale ice-movement and the ice mass balance.

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

Science.gov (United States)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability

The performance of the new enhanced-resolution satellite passive microwave dataset applied for snow water equivalent estimation

Science.gov (United States)

Pan, J.; Durand, M. T.; Jiang, L.; Liu, D.

2017-12-01

The newly-processed NASA MEaSures Calibrated Enhanced-Resolution Brightness Temperature (CETB) reconstructed using antenna measurement response function (MRF) is considered to have significantly improved fine-resolution measurements with better georegistration for time-series observations and equivalent field of view (FOV) for frequencies with the same monomial spatial resolution. We are looking forward to its potential for the global snow observing purposes, and therefore aim to test its performance for characterizing snow properties, especially the snow water equivalent (SWE) in large areas. In this research, two candidate SWE algorithms will be tested in China for the years between 2005 to 2010 using the reprocessed TB from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), with the results to be evaluated using the daily snow depth measurements at over 700 national synoptic stations. One of the algorithms is the SWE retrieval algorithm used for the FengYun (FY) - 3 Microwave Radiation Imager. This algorithm uses the multi-channel TB to calculate SWE for three major snow regions in China, with the coefficients adapted for different land cover types. The second algorithm is the newly-established Bayesian Algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM). This algorithm uses the physically-based snow radiative transfer model to find the histogram of most-likely snow property that matches the multi-frequency TB from 10.65 to 90 GHz. It provides a rough estimation of snow depth and grain size at the same time and showed a 30 mm SWE RMS error using the ground radiometer measurements at Sodankyla. This study will be the first attempt to test it spatially for satellite. The use of this algorithm benefits from the high resolution and the spatial consistency between frequencies embedded in the new dataset. This research will answer three questions. First, to what extent can CETB increase the heterogeneity in the mapped SWE? Second, will

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

Science.gov (United States)

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

2018-04-01

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

Snow driven Radiative Forcing in High Latitude Areas of Disturbance Using Higher Resolution Albedo Products from Landsat and Sentinel-2

Science.gov (United States)

Erb, A.; Li, Z.; Schaaf, C.; Wang, Z.; Rogers, B. M.

2017-12-01

Land surface albedo plays an important role in the surface energy budget and radiative forcing by determining the proportion of absorbed incoming solar radiation available to drive photosynthesis and surface heating. In Arctic regions, albedo is particularly sensitive to land cover and land use change (LCLUC) and modeling efforts have shown it to be the primary driver of effective radiative forcing from the biogeophysical effects of LCLUC. In boreal forests, the effects of these changes are complicated during snow covered periods when newly exposed, highly reflective snow can serve as the primary driver of radiative forcing. In Arctic biomes disturbance scars from fire, pest and harvest can remain in the landscape for long periods of time. As such, understanding the magnitude and persistence of these disturbances, especially in the shoulder seasons, is critical. The Landsat and Sentinel-2 Albedo Products couple 30m and 20m surface reflectances with concurrent 500m BRDF Products from the MODerate resolution Imaging Spectroradiometer (MODIS). The 12 bit radiometric fidelity of Sentinel-2 and Landsat-8 allow for the inclusion of high-quality, unsaturated albedo calculations over snow covered surfaces at scales more compatible with fragmented landscapes. Recent work on the early spring albedo of fire scars has illustrated significant post-fire spatial heterogeneity of burn severity at the landscape scale and highlights the need for a finer spatial resolution albedo record. The increased temporal resolution provided by multiple satellite instruments also allows for a better understanding of albedo dynamics during the dynamic shoulder seasons and in historically difficult high latitude locations where persistent cloud cover limits high quality retrievals. Here we present how changes in the early spring albedo of recent boreal forest disturbance in Alaska and central Canada affects landscape-scale radiative forcing. We take advantage of the long historical Landsat record

A Snow Density Dataset for Improving Surface Boundary Conditions in Greenland Ice Sheet Firn Modeling

Directory of Open Access Journals (Sweden)

Robert S. Fausto

2018-05-01

Full Text Available The surface snow density of glaciers and ice sheets is of fundamental importance in converting volume to mass in both altimetry and surface mass balance studies, yet it is often poorly constrained. Site-specific surface snow densities are typically derived from empirical relations based on temperature and wind speed. These parameterizations commonly calculate the average density of the top meter of snow, thereby systematically overestimating snow density at the actual surface. Therefore, constraining surface snow density to the top 0.1 m can improve boundary conditions in high-resolution firn-evolution modeling. We have compiled an extensive dataset of 200 point measurements of surface snow density from firn cores and snow pits on the Greenland ice sheet. We find that surface snow density within 0.1 m of the surface has an average value of 315 kg m−3 with a standard deviation of 44 kg m−3, and has an insignificant annual air temperature dependency. We demonstrate that two widely-used surface snow density parameterizations dependent on temperature systematically overestimate surface snow density over the Greenland ice sheet by 17–19%, and that using a constant density of 315 kg m−3 may give superior results when applied in surface mass budget modeling.

Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches

Science.gov (United States)

Selkowitz, David J.; Forster, Richard; Caldwell, Megan K.

2014-01-01

Remote sensing of snow-covered area (SCA) can be binary (indicating the presence/absence of snow cover at each pixel) or fractional (indicating the fraction of each pixel covered by snow). Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed) pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days and averaged 37

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.

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

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

Kadlec, J.; Ames, D. P.

2014-12-01

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

Evaluation of an assimilation scheme to estimate snow water equivalent in the High Atlas of Morocco.

Science.gov (United States)

Baba, W. M.; Baldo, E.; Gascoin, S.; Margulis, S. A.; Cortés, G.; Hanich, L.

2017-12-01

The snow melt from the Atlas mountains represents a crucial water resource for crop irrigation in Morocco. Due to the paucity of in situ measurements, and the high spatial variability of the snow cover in this semi-arid region, assimilation of snow cover area (SCA) from high resolution optical remote sensing into a snowpack energy-balance model is considered as a promising method to estimate the snow water equivalent (SWE) and snow melt at catchment scales. Here we present a preliminary evaluation of an uncalibrated particle batch smoother data assimilation scheme (Margulis et al., 2015, J. Hydrometeor., 16, 1752-1772) in the High-Atlas Rheraya pilot catchment (225 km2) over a snow season. This approach does not require in situ data since it is based on MERRA-2 reanalyses data and satellite fractional snow cover area data. We compared the output of this prior/posterior ensemble data assimilation system to output from the distributed snowpack evolution model SnowModel (Liston and Elder, 2006, J. Hydrometeor. 7, 1259-1276). SnowModel was forced with in situ meteorological data from five automatic weather stations (AWS) and some key parameters (precipitation correction factor and rain-snow phase transition parameters) were calibrated using a time series of 8-m resolution SCA maps from Formosat-2. The SnowModel simulation was validated using a continuous snow height record at one high elevation AWS. The results indicate that the open loop simulation was reasonably accurate (compared to SnowModel results) in spite of the coarse resolution of the MERRA-2 forcing. The assimilation of Formosat-2 SCA further improved the simulation in terms of the peak SWE and SWE evolution over the melt season. During the accumulation season, the differences between the modeled and estimated (posterior) SWE were more substantial. The differences appear to be due to some observed precipitation events not being captured in MERRA-2. Further investigation will determine whether additional

An automated approach for mapping persistent ice and snow cover over high latitude regions

Science.gov (United States)

Selkowitz, David J.; Forster, Richard R.

2016-01-01

We developed an automated approach for mapping persistent ice and snow cover (glaciers and perennial snowfields) from Landsat TM and ETM+ data across a variety of topography, glacier types, and climatic conditions at high latitudes (above ~65°N). Our approach exploits all available Landsat scenes acquired during the late summer (1 August–15 September) over a multi-year period and employs an automated cloud masking algorithm optimized for snow and ice covered mountainous environments. Pixels from individual Landsat scenes were classified as snow/ice covered or snow/ice free based on the Normalized Difference Snow Index (NDSI), and pixels consistently identified as snow/ice covered over a five-year period were classified as persistent ice and snow cover. The same NDSI and ratio of snow/ice-covered days to total days thresholds applied consistently across eight study regions resulted in persistent ice and snow cover maps that agreed closely in most areas with glacier area mapped for the Randolph Glacier Inventory (RGI), with a mean accuracy (agreement with the RGI) of 0.96, a mean precision (user’s accuracy of the snow/ice cover class) of 0.92, a mean recall (producer’s accuracy of the snow/ice cover class) of 0.86, and a mean F-score (a measure that considers both precision and recall) of 0.88. We also compared results from our approach to glacier area mapped from high spatial resolution imagery at four study regions and found similar results. Accuracy was lowest in regions with substantial areas of debris-covered glacier ice, suggesting that manual editing would still be required in these regions to achieve reasonable results. The similarity of our results to those from the RGI as well as glacier area mapped from high spatial resolution imagery suggests it should be possible to apply this approach across large regions to produce updated 30-m resolution maps of persistent ice and snow cover. In the short term, automated PISC maps can be used to rapidly

Post-depositional enrichment of black soot in snow-pack and accelerated melting of Tibetan glaciers

International Nuclear Information System (INIS)

Xu Baiqing; Joswiak, Daniel R; Zhao Huabiao; Cao Junji; Liu Xianqin; He Jianqiao

2012-01-01

The post-depositional enrichment of black soot in snow-pack was investigated by measuring the redistribution of black soot along monthly snow-pits on a Tien Shan glacier. The one-year experiment revealed that black soot was greatly enriched, defined as the ratio of concentration to original snow concentration, in the unmelted snow-pack by at least an order of magnitude. Greatest soot enrichment was observed in the surface snow and the lower firn-pack within the melt season percolation zone. Black carbon (BC) concentrations as high as 400 ng g −1 in the summer surface snow indicate that soot can significantly contribute to glacier melt. BC concentrations reaching 3000 ng g −1 in the bottom portion of the firn pit are especially concerning given the expected equilibrium-line altitude (ELA) rise associated with future climatic warming, which would expose the dirty underlying firn and ice. Since most of the accumulation area on Tibetan glaciers is within the percolation zone where snow densification is characterized by melting and refreezing, the enrichment of black soot in the snow-pack is of foremost importance. Results suggest the effect of black soot on glacier melting may currently be underestimated. (letter)

Antarctic snow and global climate

International Nuclear Information System (INIS)

Granberg, H.B.

2001-01-01

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

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

Science.gov (United States)

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

2012-12-01

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

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.

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Science.gov (United States)

Wang, Zhuosen; Erb, Angela M.; Schaaf, Crystal B.; Sun, Qingsong; Liu, Yan; Yang, Yun; Shuai, Yanmin; Casey, Kimberly A.; Roman, Miguel O.

2016-01-01

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (less than 100 m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high-burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500 m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will

High resolution climate scenarios for snowmelt modelling in small alpine catchments

Science.gov (United States)

Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.

2017-12-01

Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire

Measurements of Air and Snow Photochemical Species at WAIS Divide, Antarctica, Version 1

Data.gov (United States)

National Aeronautics and Space Administration — This data set contains atmospheric mixing ratios of nitric oxide, ozone, hydrogen peroxide, methylhydroperoxide, and concentrations in surface snow and in snow pits...

NOAA's National Snow Analyses

Science.gov (United States)

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

2005-12-01

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

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.

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-09-01

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

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Spontaneous Resolution of Long-Standing Macular Detachment due to Optic Disc Pit with Significant Visual Improvement.

Science.gov (United States)

Parikakis, Efstratios A; Chatziralli, Irini P; Peponis, Vasileios G; Karagiannis, Dimitrios; Stratos, Aimilianos; Tsiotra, Vasileia A; Mitropoulos, Panagiotis G

2014-01-01

To report a case of spontaneous resolution of a long-standing serous macular detachment associated with an optic disc pit, leading to significant visual improvement. A 63-year-old female presented with a 6-month history of blurred vision and micropsia in her left eye. Her best-corrected visual acuity was 6/24 in the left eye, and fundoscopy revealed serous macular detachment associated with optic disc pit, which was confirmed by optical coherence tomography (OCT). The patient was offered vitrectomy as a treatment alternative, but she preferred to be reviewed conservatively. Three years after initial presentation, neither macular detachment nor subretinal fluid was evident in OCT, while the inner segment/outer segment (IS/OS) junction line was intact. Her visual acuity was improved from 6/24 to 6/12 in her left eye, remaining stable at the 6-month follow-up after resolution. We present a case of spontaneous resolution of a long-standing macular detachment associated with an optic disc pit with significant visual improvement, postulating that the integrity of the IS/OS junction line may be a prognostic factor for final visual acuity and suggesting OCT as an indicator of visual prognosis and the probable necessity of a surgical management.

Spontaneous Resolution ofLong-Standing Macular Detachment due to Optic Disc Pit with Significant Visual Improvement

Directory of Open Access Journals (Sweden)

Efstratios A. Parikakis

2014-03-01

Full Text Available Purpose: To report a case of spontaneous resolution of a long-standing serous macular detachment associated with an optic disc pit, leading to significant visual improvement. Case Presentation: A 63-year-old female presented with a 6-month history of blurred vision and micropsia in her left eye. Her best-corrected visual acuity was 6/24 in the left eye, and fundoscopy revealed serous macular detachment associated with optic disc pit, which was confirmed by optical coherence tomography (OCT. The patient was offered vitrectomy as a treatment alternative, but she preferred to be reviewed conservatively. Three years after initial presentation, neither macular detachment nor subretinal fluid was evident in OCT, while the inner segment/outer segment (IS/OS junction line was intact. Her visual acuity was improved from 6/24 to 6/12 in her left eye, remaining stable at the 6-month follow-up after resolution. Conclusion: We present a case of spontaneous resolution of a long-standing macular detachment associated with an optic disc pit with significant visual improvement, postulating that the integrity of the IS/OS junction line may be a prognostic factor for final visual acuity and suggesting OCT as an indicator of visual prognosis and the probable necessity of a surgical management.

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

Directory of Open Access Journals (Sweden)

I. I. Lavrentiev

2018-01-01

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

Sentinels for snow science

Science.gov (United States)

Gascoin, S.; Grizonnet, M.; Baba, W. M.; Hagolle, O.; Fayad, A.; Mermoz, S.; Kinnard, C.; Fatima, K.; Jarlan, L.; Hanich, L.

2017-12-01

Current spaceborne sensors do not allow retrieving the snow water equivalent in mountain regions, "the most important unsolved problem in snow hydrology" (Dozier, 2016). While the NASA is operating an airborne mission to survey the SWE in the western USA, elsewhere, however, snow scientists and water managers do not have access to routine SWE measurements at the scale of a mountain range. In this presentation we suggest that the advent of the Copernicus Earth Observation programme opens new perspectives to address this issue in mountain regions worldwide. The Sentinel-2 mission will provide global-scale multispectral observations at 20 m resolution every 5-days (cloud permitting). The Sentinel-1 mission is already imaging the global land surface with a C-band radar at 10 m resolution every 6 days. These observations are unprecedented in terms of spatial and temporal resolution. However, the nature of the observation (radiometry, wavelength) is in the continuity of previous and ongoing missions. As a result, it is relatively straightforward to re-use algorithms that were developed by the remote sensing community over the last decades. For instance, Sentinel-2 data can be used to derive maps of the snow cover extent from the normalized difference snow index, which was initially proposed for Landsat. In addition, the 5-days repeat cycle allows the application of gap-filling algorithms, which were developed for MODIS based on the temporal dimension. The Sentinel-1 data can be used to detect the wet snow cover and track melting areas as proposed for ERS in the early 1990's. Eventually, we show an example where Sentinel-2-like data improved the simulation of the SWE in the data-scarce region of the High Atlas in Morocco through assimilation in a distributed snowpack model. We encourage snow scientists to embrace Sentinel-1 and Sentinel-2 data to enhance our knowledge on the snow cover dynamics in mountain regions.

The Impact Snow Albedo Feedback over Mountain Regions as Examined through High-Resolution Regional Climate Change Experiments over the Rocky Mountains

Science.gov (United States)

Letcher, Theodore

As the climate warms, the snow albedo feedback (SAF) will play a substantial role in shaping the climate response of mid-latitude mountain regions with transient snow cover. One such region is the Rocky Mountains of the western United States where large snow packs accumulate during the winter and persist throughout the spring. In this dissertation, the Weather Research and Forecast model (WRF) configured as a regional climate model is used to investigate the role of the SAF in determining the regional climate response to forced anthropogenic climate change. The regional effects of climate change are investigated by using the pseudo global warming (PGW) framework, which is an experimental configuration in a which a mean climate perturbation is added to the boundary forcing of a regional model, thus preserving the large-scale circulation entering the region through the model boundaries and isolating the mesoscale climate response. Using this framework, the impact of the SAF on the regional energetics and atmospheric dynamics is examined and quantified. Linear feedback analysis is used to quantify the strength of the SAF over the Headwaters region of the Colorado Rockies for a series of high-resolution PGW experiments. This technique is used to test sensitivity of the feedback strength to model resolution and land surface model. Over the Colorado Rockies, and integrated over the entire spring season, the SAF strength is largely insensitive to model resolution, however there are more substantial differences on the sub-seasonal (monthly) timescale. In contrast, the SAF strength over this region is very sensitive to choice of land surface model. These simulations are also used to investigate how spatial and diurnal variability in warming caused by the SAF influences the dynamics of thermally driven mountain-breeze circulations. It is shown that, the SAF causes stronger daytime mountain-breeze circulations by increasing the warming on the mountains slopes thus enhancing

The electrical self-potential method is a non-intrusive snow-hydrological sensor

Science.gov (United States)

Thompson, S. S.; Kulessa, B.; Essery, R. L. H.; Lüthi, M. P.

2015-08-01

Our ability to measure, quantify and assimilate hydrological properties and processes of snow in operational models is disproportionally poor compared to the significance of seasonal snowmelt as a global water resource and major risk factor in flood and avalanche forecasting. Encouraged by recent theoretical, modelling and laboratory work, we show here that the diurnal evolution of aerially-distributed self-potential magnitudes closely track those of bulk meltwater fluxes in melting in-situ snowpacks at Rhone and Jungfraujoch glaciers, Switzerland. Numerical modelling infers temporally-evolving liquid water contents in the snowpacks on successive days in close agreement with snow-pit measurements. Muting previous concerns, the governing physical and chemical properties of snow and meltwater became temporally invariant for modelling purposes. Because measurement procedure is straightforward and readily automated for continuous monitoring over significant spatial scales, we conclude that the self-potential geophysical method is a highly-promising non-intrusive snow-hydrological sensor for measurement practice, modelling and operational snow forecasting.

The AMSR2 Satellite-based Microwave Snow Algorithm (SMSA) to estimate regional to global snow depth and snow water equivalent

Science.gov (United States)

Kelly, R. E. J.; Saberi, N.; Li, Q.

2017-12-01

With moderate to high spatial resolution (observation approaches yet to be fully scoped and developed, the long-term satellite passive microwave record remains an important tool for cryosphere-climate diagnostics. A new satellite microwave remote sensing approach is described for estimating snow depth (SD) and snow water equivalent (SWE). The algorithm, called the Satellite-based Microwave Snow Algorithm (SMSA), uses Advanced Microwave Scanning Radiometer - 2 (AMSR2) observations aboard the Global Change Observation Mission - Water mission launched by the Japan Aerospace Exploration Agency in 2012. The approach is unique since it leverages observed brightness temperatures (Tb) with static ancillary data to parameterize a physically-based retrieval without requiring parameter constraints from in situ snow depth observations or historical snow depth climatology. After screening snow from non-snow surface targets (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]), moderate and shallow snow depths are estimated by minimizing the difference between Dense Media Radiative Transfer model estimates (Tsang et al., 2000; Picard et al., 2011) and AMSR2 Tb observations to retrieve SWE and SD. Parameterization of the model combines a parsimonious snow grain size and density approach originally developed by Kelly et al. (2003). Evaluation of the SMSA performance is achieved using in situ snow depth data from a variety of standard and experiment data sources. Results presented from winter seasons 2012-13 to 2016-17 illustrate the improved performance of the new approach in comparison with the baseline AMSR2 algorithm estimates and approach the performance of the model assimilation-based approach of GlobSnow. Given the variation in estimation power of SWE by different land surface/climate models and selected satellite-derived passive microwave approaches, SMSA provides SWE estimates that are independent of real or near real

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.

MODIS Snow and Sea Ice Products

Science.gov (United States)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.

2004-01-01

In this chapter, we describe the suite of Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow and sea ice products. Global, daily products, developed at Goddard Space Flight Center, are archived and distributed through the National Snow and Ice Data Center at various resolutions and on different grids useful for different communities Snow products include binary snow cover, snow albedo, and in the near future, fraction of snow in a 5OO-m pixel. Sea ice products include ice extent determined with two different algorithms, and sea ice surface temperature. The algorithms used to develop these products are described. Both the snow and sea ice products, available since February 24,2000, are useful for modelers. Validation of the products is also discussed.

Snow cover volumes dynamic monitoring during melting season using high topographic accuracy approach for a Lebanese high plateau witness sinkhole

Science.gov (United States)

Abou Chakra, Charbel; Somma, Janine; Elali, Taha; Drapeau, Laurent

2017-04-01

Climate change and its negative impact on water resource is well described. For countries like Lebanon, undergoing major population's rise and already decreasing precipitations issues, effective water resources management is crucial. Their continuous and systematic monitoring overs long period of time is therefore an important activity to investigate drought risk scenarios for the Lebanese territory. Snow cover on Lebanese mountains is the most important water resources reserve. Consequently, systematic observation of snow cover dynamic plays a major role in order to support hydrologic research with accurate data on snow cover volumes over the melting season. For the last 20 years few studies have been conducted for Lebanese snow cover. They were focusing on estimating the snow cover surface using remote sensing and terrestrial measurement without obtaining accurate maps for the sampled locations. Indeed, estimations of both snow cover area and volumes are difficult due to snow accumulation very high variability and Lebanese mountains chains slopes topographic heterogeneity. Therefore, the snow cover relief measurement in its three-dimensional aspect and its Digital Elevation Model computation is essential to estimate snow cover volume. Despite the need to cover the all lebanese territory, we favored experimental terrestrial topographic site approaches due to high resolution satellite imagery cost, its limited accessibility and its acquisition restrictions. It is also most challenging to modelise snow cover at national scale. We therefore, selected a representative witness sinkhole located at Ouyoun el Siman to undertake systematic and continuous observations based on topographic approach using a total station. After four years of continuous observations, we acknowledged the relation between snow melt rate, date of total melting and neighboring springs discharges. Consequently, we are able to forecast, early in the season, dates of total snowmelt and springs low

NHM-SMAP: spatially and temporally high-resolution nonhydrostatic atmospheric model coupled with detailed snow process model for Greenland Ice Sheet

Science.gov (United States)

Niwano, Masashi; Aoki, Teruo; Hashimoto, Akihiro; Matoba, Sumito; Yamaguchi, Satoru; Tanikawa, Tomonori; Fujita, Koji; Tsushima, Akane; Iizuka, Yoshinori; Shimada, Rigen; Hori, Masahiro

2018-02-01

To improve surface mass balance (SMB) estimates for the Greenland Ice Sheet (GrIS), we developed a 5 km resolution regional climate model combining the Japan Meteorological Agency Non-Hydrostatic atmospheric Model and the Snow Metamorphism and Albedo Process model (NHM-SMAP) with an output interval of 1 h, forced by the Japanese 55-year reanalysis (JRA-55). We used in situ data to evaluate NHM-SMAP in the GrIS during the 2011-2014 mass balance years. We investigated two options for the lower boundary conditions of the atmosphere: an offline configuration using snow, firn, and ice albedo, surface temperature data from JRA-55, and an online configuration using values from SMAP. The online configuration improved model performance in simulating 2 m air temperature, suggesting that the surface analysis provided by JRA-55 is inadequate for the GrIS and that SMAP results can better simulate physical conditions of snow/firn/ice. It also reproduced the measured features of the GrIS climate, diurnal variations, and even a strong mesoscale wind event. In particular, it successfully reproduced the temporal evolution of the GrIS surface melt area extent as well as the record melt event around 12 July 2012, at which time the simulated melt area extent reached 92.4 %. Sensitivity tests showed that the choice of calculation schemes for vertical water movement in snow and firn has an effect as great as 200 Gt year-1 in the GrIS-wide accumulated SMB estimates; a scheme based on the Richards equation provided the best performance.

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

Science.gov (United States)

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

2017-04-01

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

Snowpack spatial and temporal variability assessment using SMP high-resolution penetrometer

Science.gov (United States)

Komarov, Anton; Seliverstov, Yuriy; Sokratov, Sergey; Grebennikov, Pavel

2017-04-01

This research is focused on study of spatial and temporal variability of structure and characteristics of snowpack, quick identification of layers based on hardness and dispersion values received from snow micro penetrometer (SMP). We also discuss the detection of weak layers and definition of their parameters in non-alpine terrain. As long as it is the first SMP tool available in Russia, our intent is to test it in different climate and weather conditions. During two separate snowpack studies in plain and mountain landscapes, we derived density and grain size profiles by comparing snow density and grain size from snowpits and SMP measurements. The first case study was MSU meteorological observatory test site in Moscow. SMP data was obtained by 6 consecutive measurements along 10 m transects with a horizontal resolution of approximately 50 cm. The detailed description of snowpack structure, density, grain size, air and snow temperature was also performed. By comparing this information, the detailed scheme of snowpack evolution was created. The second case study was in Khibiny mountains. One 10-meter-long transect was made. SMP, density, grain size and snow temperature data was obtained with horizontal resolution of approximately 50 cm. The high-definition profile of snowpack density variation was acquired using received data. The analysis of data reveals high spatial and temporal variability in snow density and layer structure in both horizontal and vertical dimensions. It indicates that the spatial variability is exhibiting similar spatial patterns as surface topology. This suggests a strong influence from such factors as wind and liquid water pressure on the temporal and spatial evolution of snow structure. It was also defined, that spatial variation of snowpack characteristics is substantial even within homogeneous plain landscape, while in high-latitude mountain regions it grows significantly.

Atypical pit craters on Mars: new insights from THEMIS, CTX and HiRISE observations

Science.gov (United States)

Cushing, Glen; Okubo, Chris H.; Titus, Timothy N.

2015-01-01

More than 100 pit craters in the Tharsis region of Mars exhibit morphologies, diameters and thermal behaviors that diverge from the much larger bowl-shaped pit craters that occur in most regions across Mars. These Atypical Pit Craters (APCs) generally have sharp and distinct rims, vertical or overhanging walls that extend down to their floors, surface diameters of ~50-350 m, and high depth-to-diameter (d/D) ratios that are usually greater than 0.3 (which is an upper-range value for impacts and bowl-shaped pit craters), and can exceed values of 1.8. Observations by the Mars Odyssey THermal Emission Imaging System (THEMIS) show that APC floor temperatures are warmer at night, and fluctuate with much lower diurnal amplitudes than nearby surfaces or adjacent bowl-shaped pit craters. Kīlauea volcano, Hawai'i, hosts pit craters that formed through subsurface collapse into active volcanic dikes, resulting in pits that can appear morphologically analogous to either APCs or bowl-shaped pit craters. Partially-drained dikes are sometimes exposed within the lower walls and floors of these terrestrial APC analogs and can form extensive cave systems with unique microclimates. Similar caves in martian pit craters are of great interest for astrobiology. This study uses new observations by the Mars Reconnaissance Orbiter (MRO) High Resolution Imaging Science Experiment (HiRISE) and Context Camera (CTX) to refine previous work where seven APCs were described from lower-resolution THEMIS visible-wavelength (VIS) observations. Here, we identify locations of 115 APCs, map their distribution across the Tharsis region, characterize their internal morphologies with high-resolution observations, and discuss possible formation mechanisms.

Impact of high resolution land surface initialization in Indian summer ...

Indian Academy of Sciences (India)

The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years ... surface initialization using a regional climate model. ...... ization of the snow field in a cloud model; J. Clim. Appl.

ANALYSIS OF THE PIT REMOVAL METHODS IN DIGITAL TERRAIN MODELS OF VARIOUS RESOLUTIONS

Directory of Open Access Journals (Sweden)

S. Šamanović

2016-06-01

Full Text Available Digital terrain model (DTM is the base for calculation of the surface runoff under the influence of the gravity (gravity flow in hydrological analysis. It is important to produce hydrologically corrected DTM with the removed natural and artificial depressions to avoid numerical problems in algorithms of the gravity flow. The pit removal procedure changes geomorphometry of the DTM. GIS software packages use pit removal algorithm independently of geomorphmetric features of the analyzed area. In need of minimally modified DTM after the pit removal areas, the carving method (deepen drainage routes and the filling method (fill sink were analyzed on three different geomorphometric areas (bare mountain range, hilly wooded area and the plain area intersected with the network of the drainage canals. The recommendation is given for the choice of geomorphometric least changing DTM algorithm. The input data are raster data of elevation points created by stereoscopic photogrammetry method in 5x5 and 25x25 meter resolution. Differences have been noticed during the process of creating raster data. The recommendation is given for the choice of the most acceptable method for each type of area on the basis of comparison of the original elevation points with the elevation points in created DTM.

Identification of mineral dust layers in high alpine snow packs

Science.gov (United States)

Greilinger, Marion; Kau, Daniela; Schauer, Gerhard; Kasper-Giebl, Anne

2017-04-01

Deserts serve as a major source for aerosols in the atmosphere with mineral dust as a main contributor to primary aerosol mass. Especially the Sahara, the largest desert in the world, contributes roughly half of the primarily emitted aerosol mass found in the atmosphere [1]. The eroded Saharan dust is episodically transported over thousands of kilometers with synoptic wind patterns towards Europe [2] and reaches Austria about 20 to 30 days per year. Once the Saharan dust is removed from the atmosphere via dry or wet deposition processes, the chemical composition of the precipitation or the affected environment is significantly changed. Saharan dust serves on the one hand as high ionic input leading to an increase of ionic species such as calcium, magnesium or sulfate. On the other hand Saharan dust provides a high alkaline input neutralizing acidic components and causing the pH to increase [3]. Based on these changes in the ion composition, the pH and cross plots of the ion and conductivity balance [4] we tried to develop a method to identify Saharan dust layers in high alpine snow packs. We investigated seasonal snow packs of two high alpine sampling sites situated on the surrounding glaciers of the meteorological Sonnblick observatory serving as a global GAW (Global Atmospheric Watch) station located in the National Park Hohe Tauern in the Austrian Alps. Samples with 10 cm resolution representing the whole winter accumulation period were taken just prior to the start of snow melt at the end of April 2016. In both snow packs two layers with clearly different chemical behavior were observed. In comparison with the aerosol data from the Sonnblick observatory, these layers could be clearly identified as Saharan dust layers. Identified Saharan dust layers in the snow pack allow calculations of the ecological impact of deposited ions, with and without Saharan dust, during snow melt. Furthermore the chemical characteristics for the identification of Saharan dust layers

The Electrical Self-Potential Method as a Non-Intrusive Snow-Hydrological Sensor

Science.gov (United States)

Kulessa, B.; Thompson, S. S.; Luethi, M. P.; Essery, R.

2015-12-01

Building on growing momentum in the application of geophysical techniques to snow problems and, specifically, on new theory and an electrical geophysical snow hydrological model published recently; we demonstrate for the first time that the electrical self-potential geophysical technique can sense in-situ bulk meltwater fluxes. This has broad and immediate implications for snow measurement practice, modelling and operational snow forecasting. Our ability to measure, quantify and assimilate hydrological properties and processes of snow in operational models is disproportionally poor compared to the significance of seasonal snowmelt as a global water resource and major risk factor in flood and avalanche forecasting. Encouraged by recent theoretical, modelling and laboratory work, we show here that the diurnal evolution of aerially-distributed self-potential magnitudes closely track those of bulk meltwater fluxes in melting in-situ snowpacks at Rhone and Jungfraujoch glaciers, Switzerland. Numerical modelling infers temporally-evolving liquid water contents in the snowpacks on successive days in close agreement with snow-pit measurements. Muting previous concerns, the governing physical and chemical properties of snow and meltwater became temporally invariant for modelling purposes. Because measurement procedure is straightforward and readily automated for continuous monitoring over significant spatial scales, we conclude that the self-potential geophysical method is a highly-promising non-intrusive snow-hydrological sensor for measurement practice, modelling and operational snow forecasting.

Snow cover dynamics and water balance in complex high alpine terrain

Science.gov (United States)

Warscher, Michael; Kraller, Gabriele; Kunstmann, Harald; Strasser, Ulrich; Franz, Helmut

2010-05-01

The water balance in high alpine regions in its full complexity is so far insufficiently understood. High altitudinal gradients, a strong variability of meteorological variables in time and space, complex hydrogeological situations, unquantified lateral snow transport processes and heterogenous snow cover dynamics result in high uncertainties in the quantification of the water balance. To achieve interpretable modeling results we have complemented the deterministic hydrological model WaSiM-ETH with the high-alpine specific snow model AMUNDSEN. The integration of the new snow module was done to improve the modeling of water fluxes influenced by the dynamics of the snow cover, which greatly affect the water cycle in high alpine regions. To enhance the reproduction of snow deposition and ablation processes, the new approach calculates the energy balance of the snow cover considering the terrain-dependent radiation fluxes, the interaction between tree canopy and snow cover as well as lateral snow transport processes. The test site for our study is the Berchtesgaden National Park which is characterized by an extreme topography with mountain ranges covering an altitude from 607 to 2713 m.a.s.l. About one quarter of the investigated catchment area, which comprises 433 km² in total, is terrain steeper than 35°. Due to water soluble limestone being predominant in the region, a high number of subsurface water pathways (karst) exist. The results of several tracer experiments and extensive data of spring observations provide additional information to meet the challenge of modeling the unknown subsurface pathways and the complex groundwater system of the region. The validation of the new snow module is based on a dense network of meteorological stations which have been adapted to measure physical properties of the snow cover like snow water equivalent and liquid water content. We will present first results which show that the integration of the new snow module generates a

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.

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

An Assessment of Existing Methodologies to Retrieve Snow Cover Fraction from MODIS Data

Directory of Open Access Journals (Sweden)

Théo Masson

2018-04-01

Full Text Available The characterization of snow extent is critical for a wide range of applications. Since 1966, snow maps at different spatial resolutions have been produced using various satellite sensor images. Nowadays, the most widely used products are likely those derived from Moderate-Resolution Imaging Spectroradiometer (MODIS data, which cover the whole Earth at a near-daily frequency. There are a variety of snow mapping methods for MODIS data, based on different methodologies and applied at different spatial resolutions. Up to now, all these products have been tested and evaluated separately. This study aims to compare the methods currently available for retrieving snow from MODIS data. The focus is on fractional snow cover, which represents the snow cover area at the subpixel level. We examine the two main approaches available for generating such products from MODIS data; namely, linear regression of the Normalized Difference Snow Index (NDSI and spectral unmixing (SU. These two approaches have resulted in several methods, such as MOD10A1 (the NSIDC MODIS snow product for NDSI regression, and MODImLAB for SU. The assessment of these approaches was carried out using higher resolution binary snow maps (i.e., showing the presence or absence of snow at spatial resolutions of 10, 20, and 30 m, produced by SPOT 4, SPOT 5, and LANDSAT-8, respectively. Three areas were selected in order to provide landscape diversity: the French Alps (117 dates, the Pyrenees (30 dates, and the Moroccan Atlas (24 dates. This study investigates the impact of reference maps on accuracy assessments, and it is suggested that NDSI-based high spatial resolution reference maps advantage NDSI medium-resolution snow maps. For MODIS snow maps, the results show that applying an NDSI approach to accurate surface reflectance corrected for topographic and atmospheric effects generally outperforms other methods for the global retrieval of snow cover area. The improvements to the newer version

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

Science.gov (United States)

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

2015-04-01

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

Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

Science.gov (United States)

Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

2017-04-01

General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All

Monitoring Snow and Land Ice Using Satellite data in the GMES Project CryoLand

Science.gov (United States)

Bippus, Gabriele; Nagler, Thomas

2013-04-01

The main objectives of the project "CryoLand - GMES Service Snow and Land Ice" are to develop, implement and validate services for snow, glaciers and lake and river ice products as a Downstream Service within the Global Monitoring for Environment and Security (GMES) program of the European Commission. CryoLand exploits Earth Observation data from current optical and microwave sensors and of the upcoming GMES Sentinel satellite family. The project prepares also the basis for the cryospheric component of the GMES Land Monitoring services. The CryoLand project team consists of 10 partner organisations from Austria, Finland, Norway, Sweden, Switzerland and Romania and is funded by the 7th Framework Program of the European Commission. The CryoLand baseline products for snow include fractional snow extent from optical satellite data, the extent of melting snow from SAR data, and coarse resolution snow water equivalent maps from passive microwave data. Experimental products include maps of snow surface wetness and temperature. The products range from large scale coverage at medium resolution to regional products with high resolution, in order to address a wide user community. Medium resolution optical data (e.g. MODIS, in the near future Sentinel-3) and SAR (ENVISAT ASAR, in the near future Sentinel-1) are the main sources of EO data for generating large scale products in near real time. For generation of regional products high resolution satellite data are used. Glacier products are based on high resolution optical (e.g. SPOT-5, in the near future Sentinel-2) and SAR (TerraSAR-X, in the near future Sentinel-1) data and include glacier outlines, mapping of glacier facies, glacier lakes and ice velocity. The glacier products are generated on users demand. Current test areas are located in the Alps, Norway, Greenland and the Himalayan Mountains. The lake and river ice products include ice extent and its temporal changes and snow extent on ice. The algorithms for these

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

Science.gov (United States)

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

2012-04-01

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

Collaborative Project. 3D Radiative Transfer Parameterization Over Mountains/Snow for High-Resolution Climate Models. Fast physics and Applications

Energy Technology Data Exchange (ETDEWEB)

Liou, Kuo-Nan [Univ. of California, Los Angeles, CA (United States)

2016-02-09

Under the support of the aforementioned DOE Grant, we have made two fundamental contributions to atmospheric and climate sciences: (1) Develop an efficient 3-D radiative transfer parameterization for application to intense and intricate inhomogeneous mountain/snow regions. (2) Innovate a stochastic parameterization for light absorption by internally mixed black carbon and dust particles in snow grains for understanding and physical insight into snow albedo reduction in climate models. With reference to item (1), we divided solar fluxes reaching mountain surfaces into five components: direct and diffuse fluxes, direct- and diffuse-reflected fluxes, and coupled mountain-mountain flux. “Exact” 3D Monte Carlo photon tracing computations can then be performed for these solar flux components to compare with those calculated from the conventional plane-parallel (PP) radiative transfer program readily available in climate models. Subsequently, Parameterizations of the deviations of 3D from PP results for five flux components are carried out by means of the multiple linear regression analysis associated with topographic information, including elevation, solar incident angle, sky view factor, and terrain configuration factor. We derived five regression equations with high statistical correlations for flux deviations and successfully incorporated this efficient parameterization into WRF model, which was used as the testbed in connection with the Fu-Liou-Gu PP radiation scheme that has been included in the WRF physics package. Incorporating this 3D parameterization program, we conducted simulations of WRF and CCSM4 to understand and evaluate the mountain/snow effect on snow albedo reduction during seasonal transition and the interannual variability for snowmelt, cloud cover, and precipitation over the Western United States presented in the final report. With reference to item (2), we developed in our previous research a geometric-optics surface-wave approach (GOS) for the

Ross Ice Drainage System (RIDS) Glaciochemical Analysis, Version 1

Data.gov (United States)

National Aeronautics and Space Administration — The Ross Ice Drainage System (RIDS) project provides a high-resolution record of atmospheric chemical deposition taken from several ice cores and snow pits located...

The distribution of snow accumulation across the Austfonna ice cap, Svalbard: direct measurements and modelling

OpenAIRE

Taurisano, Andrea; Schuler, Thomas V.; Hagen, Jon Ove; Eiken, Trond; Loe, Even; Melvold, Kjetil; Kohler, Jack

2007-01-01

We present an analysis of the spatial variability in the snow accumulation on the Austfonna ice cap in Svalbard, Norway, based on the results of field investigations conducted in the spring of 1999, 2004 and 2005. During the campaigns ground penetrating radar measurements at 500 and 800 MHz were collected along profiles, along with additional manual snow sounding and pit stratigraphy work. The analysis of the data reveals a consistent pattern in the spatial distribution of the snow accumulati...

Potential and limitations of webcam images for snow cover monitoring in the Swiss Alps

Science.gov (United States)

Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

2017-04-01

In Switzerland, several thousands of outdoor webcams are currently connected to the Internet. They deliver freely available images that can be used to analyze snow cover variability on a high spatio-temporal resolution. To make use of this big data source, we have implemented a webcam-based snow cover mapping procedure, which allows to almost automatically derive snow cover maps from such webcam images. As there is mostly no information about the webcams and its parameters available, our registration approach automatically resolves these parameters (camera orientation, principal point, field of view) by using an estimate of the webcams position, the mountain silhouette, and a high-resolution digital elevation model (DEM). Combined with an automatic snow classification and an image alignment using SIFT features, our procedure can be applied to arbitrary images to generate snow cover maps with a minimum of effort. Resulting snow cover maps have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or hidden from webcams' positions. Up to now, we processed images of about 290 webcams from our archive, and evaluated images of 20 webcams using manually selected ground control points (GCPs) to evaluate the mapping accuracy of our procedure. We present methodological limitations and ongoing improvements, show some applications of our snow cover maps, and demonstrate that webcams not only offer a great opportunity to complement satellite-derived snow retrieval under cloudy conditions, but also serve as a reference for improved validation of satellite-based approaches.

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.

Improving snow water equivalent simulations in an alpine basin using blended gage precipitation and snow pillow measurements

Science.gov (United States)

Sohrabi, M.; Safeeq, M.; Conklin, M. H.

2017-12-01

Snowpack is a critical freshwater reservoir that sustains ecosystem, natural habitat, hydropower, agriculture, and urban water supply in many areas around the world. Accurate estimation of basin scale snow water equivalent (SWE), through both measurement and modeling, has been significantly recognized to improve regional water resource management. Recent advances in remote data acquisition techniques have improved snow measurements but our ability to model snowpack evolution is largely hampered by poor knowledge of inherently variable high-elevation precipitation patterns. For a variety of reasons, majority of the precipitation gages are located in low and mid-elevation range and function as drivers for basin scale hydrologic modeling. Here, we blend observed gage precipitation from low and mid-elevation with point observations of SWE from high-elevation snow pillow into a physically based snow evolution model (SnowModel) to better represent the basin-scale precipitation field and improve snow simulations. To do this, we constructed two scenarios that differed in only precipitation. In WTH scenario, we forced the SnowModel using spatially distributed gage precipitation data. In WTH+SP scenario, the model was forced with spatially distributed precipitation data derived from gage precipitation along with observed precipitation from snow pillows. Since snow pillows do not directly measure precipitation, we uses positive change in SWE as a proxy for precipitation. The SnowModel was implemented at daily time step and 100 m resolution for the Kings River Basin, USA over 2000-2014. Our results show an improvement in snow simulation under WTH+SP as compared to WTH scenario, which can be attributed to better representation in high-elevation precipitation patterns under WTH+SP. The average Nash Sutcliffe efficiency over all snow pillow and course sites was substantially higher for WTH+SP (0.77) than for WTH scenario (0.47). The maximum difference in observed and simulated

Fractional Snow Cover Mapping by Artificial Neural Networks and Support Vector Machines

Science.gov (United States)

Çiftçi, B. B.; Kuter, S.; Akyürek, Z.; Weber, G.-W.

2017-11-01

Snow is an important land cover whose distribution over space and time plays a significant role in various environmental processes. Hence, snow cover mapping with high accuracy is necessary to have a real understanding for present and future climate, water cycle, and ecological changes. This study aims to investigate and compare the design and use of artificial neural networks (ANNs) and support vector machines (SVMs) algorithms for fractional snow cover (FSC) mapping from satellite data. ANN and SVM models with different model building settings are trained by using Moderate Resolution Imaging Spectroradiometer surface reflectance values of bands 1-7, normalized difference snow index and normalized difference vegetation index as predictor variables. Reference FSC maps are generated from higher spatial resolution Landsat ETM+ binary snow cover maps. Results on the independent test data set indicate that the developed ANN model with hyperbolic tangent transfer function in the output layer and the SVM model with radial basis function kernel produce high FSC mapping accuracies with the corresponding values of R = 0.93 and R = 0.92, respectively.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

Science.gov (United States)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Snow observations in Mount Lebanon (2011-2016)

Science.gov (United States)

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

2017-08-01

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

Using High Resolution Simulations with WRF/SSiB Regional Climate Model Constrained by In Situ Observations to Assess the Impacts of Dust in Snow in the Upper Colorado River Basin

Science.gov (United States)

Oaida, C. M.; Skiles, M.; Painter, T. H.; Xue, Y.

2015-12-01

The mountain snowpack is an essential resource for both the environment as well as society. Observational and energy balance modeling work have shown that dust on snow (DOS) in western U.S. (WUS) is a major contributor to snow processes, including snowmelt timing and runoff amount in regions like the Upper Colorado River Basin (UCRB). In order to accurately estimate the impact of DOS to the hydrologic cycle and water resources, now and under a changing climate, we need to be able to (1) adequately simulate the snowpack (accumulation), and (2) realistically represent DOS processes in models. Energy balance models do not capture the impact on a broader local or regional scale, nor the land-atmosphere feedbacks, while GCM studies cannot resolve orographic-related precipitation processes, and therefore snowpack accumulation, owing to coarse spatial resolution and smoother terrain. All this implies the impacts of dust on snow on the mountain snowpack and other hydrologic processes are likely not well captured in current modeling studies. Recent increase in computing power allows for RCMs to be used at higher spatial resolutions, while recent in situ observations of dust in snow properties can help constrain modeling simulations. Therefore, in the work presented here, we take advantage of these latest resources to address the some of the challenges outlined above. We employ the newly enhanced WRF/SSiB regional climate model at 4 km horizontal resolution. This scale has been shown by others to be adequate in capturing orographic processes over WUS. We also constrain the magnitude of dust deposition provided by a global chemistry and transport model, with in situ measurements taken at sites in the UCRB. Furthermore, we adjust the dust absorptive properties based on observed values at these sites, as opposed to generic global ones. This study aims to improve simulation of the impact of dust in snow on the hydrologic cycle and related water resources.

Impact of model resolution on simulated wind, drifting snow and surface mass balance in Terre Adélie, East Antarctica

NARCIS (Netherlands)

Lenaerts, J.T.M.|info:eu-repo/dai/nl/314850163; van den Broeke, M.R.|info:eu-repo/dai/nl/073765643; Scarchilli, C.; Agosta, C.

2012-01-01

This paper presents the impact of model resolution on the simulated wind speed, drifting snow climate and surface mass balance (SMB) of Terre Ad´elie and its surroundings, East Antarctica. We compare regional climate model simulations at 27 and 5.5 km resolution for the year 2009. The wind speed

A NEW HIGH-RESOLUTION ELEVATION MODEL OF GREENLAND DERIVED FROM TANDEM-X

Directory of Open Access Journals (Sweden)

B. Wessel

2016-06-01

Full Text Available In this paper we present for the first time the new digital elevation model (DEM for Greenland produced by the TanDEM-X (TerraSAR add-on for digital elevation measurement mission. The new, full coverage DEM of Greenland has a resolution of 0.4 arc seconds corresponding to 12 m. It is composed of more than 7.000 interferometric synthetic aperture radar (InSAR DEM scenes. X-Band SAR penetrates the snow and ice pack by several meters depending on the structures within the snow, the acquisition parameters, and the dielectricity constant of the medium. Hence, the resulting SAR measurements do not represent the surface but the elevation of the mean phase center of the backscattered signal. Special adaptations on the nominal TanDEM-X DEM generation are conducted to maintain these characteristics and not to raise or even deform the DEM to surface reference data. For the block adjustment, only on the outer coastal regions ICESat (Ice, Cloud, and land Elevation Satellite elevations as ground control points (GCPs are used where mostly rock and surface scattering predominates. Comparisons with ICESat data and snow facies are performed. In the inner ice and snow pack, the final X-Band InSAR DEM of Greenland lies up to 10 m below the ICESat measurements. At the outer coastal regions it corresponds well with the GCPs. The resulting DEM is outstanding due to its resolution, accuracy and full coverage. It provides a high resolution dataset as basis for research on climate change in the arctic.

Very high-resolution regional climate simulations over Scandinavia-present climate

DEFF Research Database (Denmark)

Christensen, Ole B.; Christensen, Jens H.; Machenhauer, Bennert

1998-01-01

realistically simulated. It is found in particular that in mountainous regions the high-resolution simulation shows improvements in the simulation of hydrologically relevant fields such as runoff and snow cover. Also, the distribution of precipitation on different intensity classes is most realistically...... on a high-density station network for the Scandinavian countries compiled for the present study. The simulated runoff is compared with observed data from Sweden extracted from a Swedish climatological atlas. These runoff data indicate that the precipitation analyses are underestimating the true...... simulated in the high-resolution simulation. It does, however, inherit certain large-scale systematic errors from the driving GCM. In many cases these errors increase with increasing resolution. Model verification of near-surface temperature and precipitation is made using a new gridded climatology based...

Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau

Science.gov (United States)

Wang, Kun; Zhang, Li; Qiu, Yubao; Ji, Lei; Tian, Feng; Wang, Cuizhen; Wang, Zhiyong

2013-01-01

Understanding the relationships between snow and vegetation is important for interpretation of the responses of alpine ecosystems to climate changes. The Qinghai-Tibetan Plateau is regarded as an ideal area due to its undisturbed features with low population and relatively high snow cover. We used 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) datasets during 2001–2010 to examine the snow–vegetation relationships, specifically, (1) the influence of snow melting date on vegetation green-up date and (2) the effects of snow cover duration on vegetation greenness. The results showed that the alpine vegetation responded strongly to snow phenology (i.e., snow melting date and snow cover duration) over large areas of the Qinghai-Tibetan Plateau. Snow melting date and vegetation green-up date were significantly correlated (p growth was influenced by different seasonal snow cover durations (SCDs) in different regions. Generally, the December–February and March–May SCDs played a significantly role in vegetation growth, both positively and negatively, depending on different water source regions. Snow's positive impact on vegetation was larger than the negative impact.

Structure and Evolution of Hawaii's Loihi Seamount from High-resolution Mapping

Science.gov (United States)

Clague, D. A.; Paduan, J. B.; Moyer, C. L.; Glazer, B. T.; Caress, D. W.; Yoerger, D.; Kaiser, C. L.

2016-12-01

Loihi Seamount has been mapped repeatedly using shipboard multibeam sonars with improving resolution over time. Simrad EM302 data with 25m resolution at the 950m summit and 90m at the 5000m base of the volcano were collected from Schmidt Ocean Institute's R/V Falkor in 2014. A contracted multibeam survey in 1997 employing a deep-towed vehicle has 7m resolution for the summit and upper north and south rift zones, but suffered from poor navigation. Woods Hole Oceanographic Institution's AUV Sentry surveyed most of the summit and low-T hydrothermal vents on the base of the south rift in 2013 and 2014. The 2m resolution of most data is more precise than the navigation. The 6 summit surveys were reprocessed using MB-System to remove abundant bad bottom picks and adjust the navigation to produce a spatially accurate map. The 3 summit pits, including Pele's Pit that formed in 1996, are complex collapse structures and nested inside a larger caldera that was modified by large landslides on the east and west summit flanks. The pits cut low shields that once formed a complex of overlapping summit shields, similar to Kilauea before the current caldera formed 1500 to 1790 CE. An 11m section of ash deposits crops out on the east rim of the summit along a caldera-bounding fault and is analogous to Kilauea where the caldera-bounding faults expose ash erupted as the present caldera formed. Most of the Loihi ash section is 3300 to 5880 yr BP, indicating that the larger caldera structure at Loihi is younger than 3300 yr BP. The landslides on the east and west edges of the summit are therefore younger 3300 yr BP. The uppermost south rift has several small pit craters between cones and pillow ridges, also analogous to Kilauea. Two cones near the deep low-T vents are steep pillow mounds with slopes of talus. High-resolution mapping reveals, for the first time, the many similarities between the structure and evolution of submarine Loihi Seamount and subaerial Kilauea Volcano.

Next Generation Snow Cover Mapping: Can Future Hyperspectral Satellite Spectrometer Systems Improve Subpixel Snow-covered Area and Grain Size in the Sierra Nevada?

Science.gov (United States)

Hill, R.; Calvin, W. M.; Harpold, A.

2017-12-01

Mountain snow storage is the dominant source of water for humans and ecosystems in western North America. Consequently, the spatial distribution of snow-covered area is fundamental to both hydrological, ecological, and climate models. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were collected along the entire Sierra Nevada mountain range extending from north of Lake Tahoe to south of Mt. Whitney during the 2015 and 2016 snow-covered season. The AVIRIS dataset used in this experiment consists of 224 contiguous spectral channels with wavelengths ranging 400-2500 nanometers at a 15-meter spatial pixel size. Data from the Sierras were acquired on four days: 2/24/15 during a very low snow year, 3/24/16 near maximum snow accumulation, and 5/12/16 and 5/18/16 during snow ablation and snow loss. Building on previous retrieval of subpixel snow-covered area algorithms that take into account varying grain size we present a model that analyzes multiple endmembers of varying snow grain size, vegetation, rock, and soil in segmented regions along the Sierra Nevada to determine snow-cover spatial extent, snow sub-pixel fraction, and approximate grain size. In addition, varying simulated models of the data will compare and contrast the retrieval of current snow products such as MODIS Snow-Covered Area and Grain Size (MODSCAG) and the Airborne Space Observatory (ASO). Specifically, does lower spatial resolution (MODIS), broader resolution bandwidth (MODIS), and limited spectral resolution (ASO) affect snow-cover area and grain size approximations? The implications of our findings will help refine snow mapping products for planned hyperspectral satellite spectrometer systems such as EnMAP (slated to launch in 2019), HISUI (planned for inclusion on the International Space Station in 2018), and HyspIRI (currently under consideration).

Light-absorption of dust and elemental carbon in snow in the Indian Himalayas and the Finnish Arctic

Science.gov (United States)

Svensson, Jonas; Ström, Johan; Kivekäs, Niku; Dkhar, Nathaniel B.; Tayal, Shresth; Sharma, Ved P.; Jutila, Arttu; Backman, John; Virkkula, Aki; Ruppel, Meri; Hyvärinen, Antti; Kontu, Anna; Hannula, Henna-Reetta; Leppäranta, Matti; Hooda, Rakesh K.; Korhola, Atte; Asmi, Eija; Lihavainen, Heikki

2018-03-01

Light-absorbing impurities (LAIs) deposited in snow have the potential to substantially affect the snow radiation budget, with subsequent implications for snow melt. To more accurately quantify the snow albedo, the contribution from different LAIs needs to be assessed. Here we estimate the main LAI components, elemental carbon (EC) (as a proxy for black carbon) and mineral dust in snow from the Indian Himalayas and paired the results with snow samples from Arctic Finland. The impurities are collected onto quartz filters and are analyzed thermal-optically for EC, as well as with an additional optical measurement to estimate the light-absorption of dust separately on the filters. Laboratory tests were conducted using substrates containing soot and mineral particles, especially prepared to test the experimental setup. Analyzed ambient snow samples show EC concentrations that are in the same range as presented by previous research, for each respective region. In terms of the mass absorption cross section (MAC) our ambient EC surprisingly had about half of the MAC value compared to our laboratory standard EC (chimney soot), suggesting a less light absorptive EC in the snow, which has consequences for the snow albedo reduction caused by EC. In the Himalayan samples, larger contributions by dust (in the range of 50 % or greater for the light absorption caused by the LAI) highlighted the importance of dust acting as a light absorber in the snow. Moreover, EC concentrations in the Indian samples, acquired from a 120 cm deep snow pit (possibly covering the last five years of snow fall), suggest an increase in both EC and dust deposition. This work emphasizes the complexity in determining the snow albedo, showing that LAI concentrations alone might not be sufficient, but additional transient effects on the light-absorbing properties of the EC need to be considered and studied in the snow. Equally as imperative is the confirmation of the spatial and temporal representativeness

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

Directory of Open Access Journals (Sweden)

Leo eSold

2016-02-01

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

Long-range transported dissolved organic matter, ions and black carbon deposited on Central Asian snow covered glaciers

Science.gov (United States)

Schmale, Julia; Kang, Shichang; Peltier, Richard

2014-05-01

Ninety percent of the Central Asian population depend on water precipitated in the mountains stored in glaciers and snow cover. Accelerated melting of the snow and ice can be induced by the deposition of airborne impurities such as mineral dust, black carbon and co-emitted species leading to significant reductions of the surface albedo. However, Central Asia is a relatively understudied region and data on the source regions, chemical and microphysical characteristics as well as modelling studies of long-range transported air pollution and dust to the Tien Shan mountains is very scarce. We studied the atmospheric aerosol deposited most likely between summer 2012 and summer 2013on three different glaciers in the Kyrgyz Republic. Samples were taken from four snow pits on the glaciers Abramov (2 pits, 39.59 °N, 71.56 °E, 4390 m elevation, 240 cm deep, and 39.62°N, 71.52 °E, 4275 m elevation, 125 cm deep), Ak-Shiirak (41.80 °N, 78.18 °E, 4325 m elevation, 75 cm deep) and Suek (41.78 °N, 77.75 °E, 4341 m elevation, 200 cm deep). The latter two glaciers are located roughly within 6 and 38 km of an operating gold mine. The snow was analyzed for black carbon, ions, metals and organic carbon. We here focus on the results of inorganic ion measurements and organic carbon speciation based on analysis with an Aerodyne high-resolution time-of-flight aerosol spectrometer (HR-ToF-AMS) and potential pollution sources that can be deduced from the chemical information as well as back trajectories. Average contributions of snow impurities measured by the HR-ToF-AMS were dominated by organic carbon. Relative concentrations of organic carbon, sulfate, nitrate and ammonium in snow were 86 %, 3 %, 9 % and 2 % respectively for Abramov, 92 %, 1 %, 5 % and 1 % for Suek, and 95 %, 1 %, 3 % and 1 % for Ak-Shiirak. Generally, impurities on Suek and Ak-Shiirak were three and five times higher than on Abramov. Mass concentrations of organic carbon were on average 6 times higher in samples

Spatial-temporal dynamics of chemical composition of surface snow in East Antarctica along the Progress station-Vostok station transect

Science.gov (United States)

Khodzher, T. V.; Golobokova, L. P.; Osipov, E. Yu.; Shibaev, Yu. A.; Lipenkov, V. Ya.; Osipova, O. P.; Petit, J. R.

2014-05-01

In January of 2008, during the 53rd Russian Antarctic Expedition, surface snow samples were taken from 13 shallow (0.7 to 1.5 m depth) snow pits along the first tractor traverse from Progress to Vostok stations, East Antarctica. Sub-surface snow/firn layers are dated from 2.1 to 18 yr. The total length of the coast to inland traverse is more than 1280 km. Here we analysed spatial variability of concentrations of sulphate ions and elements and their fluxes in the snow deposited within the 2006-2008 time interval. Anions were analysed by high-performance liquid chromatography (HPLC), and the determination of selected metals, including Na, K, Mg, Ca and Al, was carried out by mass spectroscopy with atomization by induced coupled plasma (ICP-MS). Surface snow concentration records were examined for trends versus distance inland, elevation, accumulation rate and slope gradient. Na shows a significant positive correlation with accumulation rate, which decreases as distance from the sea and altitude increase. K, Ca and Mg concentrations do not show any significant relationship either with distance inland or with elevation. Maximal concentrations of these elements with a prominent Al peak are revealed in the middle part of the traverse (500-600 km from the coast). Analysis of element correlations and atmospheric circulation patterns allow us to suggest their terrestrial origin (e.g. aluminosilicates carried as a continental dust) from the Antarctic nunatak areas. Sulphate concentrations show no significant relationship with distance inland, elevation, slope gradient and accumulation rate. Non-sea salt secondary sulphate is the most important contribution to the total sulphate budget along the traverse. Sulphate of volcanic origin attributed to the Pinatubo eruption (1991) was revealed in the snow pit at 1276 km (depth 120-130 cm).

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

Science.gov (United States)

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

2013-04-01

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

Deriving Snow-Cover Depletion Curves for Different Spatial Scales from Remote Sensing and Snow Telemetry Data

Science.gov (United States)

Fassnacht, Steven R.; Sexstone, Graham A.; Kashipazha, Amir H.; Lopez-Moreno, Juan Ignacio; Jasinski, Michael F.; Kampf, Stephanie K.; Von Thaden, Benjamin C.

2015-01-01

During the melting of a snowpack, snow water equivalent (SWE) can be correlated to snow-covered area (SCA) once snow-free areas appear, which is when SCA begins to decrease below 100%. This amount of SWE is called the threshold SWE. Daily SWE data from snow telemetry stations were related to SCA derived from moderate-resolution imaging spectro radiometer images to produce snow-cover depletion curves. The snow depletion curves were created for an 80,000 sq km domain across southern Wyoming and northern Colorado encompassing 54 snow telemetry stations. Eight yearly snow depletion curves were compared, and it is shown that the slope of each is a function of the amount of snow received. Snow-cover depletion curves were also derived for all the individual stations, for which the threshold SWE could be estimated from peak SWE and the topography around each station. A stations peak SWE was much more important than the main topographic variables that included location, elevation, slope, and modelled clear sky solar radiation. The threshold SWE mostly illustrated inter-annual consistency.

High-resolution subsurface imaging and neural network recognition: Non-intrusive buried substance location. Final report

Energy Technology Data Exchange (ETDEWEB)

Sternberg, B.K.; Poulton, M.M.

1997-01-26

A high-frequency, high-resolution electromagnetic (EM) imaging system has been developed for environmental geophysics surveys. Some key features of this system include: (1) rapid surveying to allow dense spatial sampling over a large area, (2) high-accuracy measurements which are used to produce a high-resolution image of the subsurface, (3) measurements which have excellent signal-to-noise ratio over a wide bandwidth (31 kHz to 32 MHz), (4) elimination of electric-field interference at high frequencies, (5) large-scale physical modeling to produce accurate theoretical responses over targets of interest in environmental geophysics surveys, (6) rapid neural network interpretation at the field site, and (7) visualization of complex structures during the survey. Four major experiments were conducted with the system: (1) Data were collected for several targets in our physical modeling facility. (2) The authors tested the system over targets buried in soil. (3) The authors conducted an extensive survey at the Idaho National Engineering Laboratory (INEL) Cold Test Pit (CTP). The location of the buried waste, category of waste, and thickness of the clay cap were successfully mapped. (4) The authors ran surveys over the acid pit at INEL. This was an operational survey over a hot site. The interpreted low-resistivity region correlated closely with the known extent of the acid pit.

High-resolution subsurface imaging and neural network recognition: Non-intrusive buried substance location. Final report

International Nuclear Information System (INIS)

Sternberg, B.K.; Poulton, M.M.

1997-01-01

A high-frequency, high-resolution electromagnetic (EM) imaging system has been developed for environmental geophysics surveys. Some key features of this system include: (1) rapid surveying to allow dense spatial sampling over a large area, (2) high-accuracy measurements which are used to produce a high-resolution image of the subsurface, (3) measurements which have excellent signal-to-noise ratio over a wide bandwidth (31 kHz to 32 MHz), (4) elimination of electric-field interference at high frequencies, (5) large-scale physical modeling to produce accurate theoretical responses over targets of interest in environmental geophysics surveys, (6) rapid neural network interpretation at the field site, and (7) visualization of complex structures during the survey. Four major experiments were conducted with the system: (1) Data were collected for several targets in our physical modeling facility. (2) The authors tested the system over targets buried in soil. (3) The authors conducted an extensive survey at the Idaho National Engineering Laboratory (INEL) Cold Test Pit (CTP). The location of the buried waste, category of waste, and thickness of the clay cap were successfully mapped. (4) The authors ran surveys over the acid pit at INEL. This was an operational survey over a hot site. The interpreted low-resistivity region correlated closely with the known extent of the acid pit

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

Directory of Open Access Journals (Sweden)

K. Aalstad

2018-01-01

Full Text Available With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD at the 1 km scale by assimilating fractional snow-covered area (fSCA satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation ensemble smoother with multiple data assimilation (ES-MDA scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e. and 0.13, respectively. The ES-MDA either

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

Science.gov (United States)

Aalstad, Kristoffer; Westermann, Sebastian; Vikhamar Schuler, Thomas; Boike, Julia; Bertino, Laurent

2018-01-01

With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least

High fidelity remote sensing of snow properties from MODIS and the Airborne Snow Observatory: Snowflakes to Terabytes

Science.gov (United States)

Painter, T.; Mattmann, C. A.; Brodzik, M.; Bryant, A. C.; Goodale, C. E.; Hart, A. F.; Ramirez, P.; Rittger, K. E.; Seidel, F. C.; Zimdars, P. A.

2012-12-01

The response of the cryosphere to climate forcings largely determines Earth's climate sensitivity. However, our understanding of the strength of the simulated snow albedo feedback varies by a factor of three in the GCMs used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, mainly caused by uncertainties in snow extent and the albedo of snow-covered areas from imprecise remote sensing retrievals. Additionally, the Western US and other regions of the globe depend predominantly on snowmelt for their water supply to agriculture, industry and cities, hydroelectric power, and recreation, against rising demand from increasing population. In the mountains of the Upper Colorado River Basin, dust radiative forcing in snow shortens snow cover duration by 3-7 weeks. Extended to the entire upper basin, the 5-fold increase in dust load since the late-1800s results in a 3-week earlier peak runoff and a 5% annual loss of total runoff. The remotely sensed dynamics of snow cover duration and melt however have not been factored into hydrological modeling, operational forecasting, and policymaking. To address these deficiencies in our understanding of snow properties, we have developed and validated a suite of MODIS snow products that provide accurate fractional snow covered area and radiative forcing of dust and carbonaceous aerosols in snow. The MODIS Snow Covered Area and Grain size (MODSCAG) and MODIS Dust Radiative Forcing in Snow (MODDRFS) algorithms, developed and transferred from imaging spectroscopy techniques, leverage the complete MODIS surface reflectance spectrum. 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. We have created the Airborne Snow Observatory (ASO), an imaging spectrometer and scanning LiDAR system, to quantify SWE and snow albedo, generate unprecedented knowledge of snow properties, and provide complete

Retention and radiative forcing of black carbon in eastern Sierra Nevada snow

Directory of Open Access Journals (Sweden)

K. M. Sterle

2013-02-01

Full Text Available When contaminated by absorbing particles, such as refractory black carbon (rBC and continental dust, snow's albedo decreases and thus its absorption of solar radiation increases, thereby hastening snowmelt. For this reason, an understanding of rBC's affect on snow albedo, melt processes, and radiation balance is critical for water management, especially in a changing climate. Measurements of rBC in a sequence of snow pits and surface snow samples in the eastern Sierra Nevada of California during the snow accumulation and ablation seasons of 2009 show that concentrations of rBC were enhanced sevenfold in surface snow (~25 ng g^–1 compared to bulk values in the snowpack (~3 ng g^–1. Unlike major ions, which were preferentially released during the initial melt, rBC and continental dust were retained in the snow, enhancing concentrations well into late spring, until a final flush occurred during the ablation period. We estimate a combined rBC and continental dust surface radiative forcing of 20 to 40 W m⁻² during April and May, with dust likely contributing a greater share of the forcing.

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

Science.gov (United States)

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

2017-12-01

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

High-Resolution Discharge Forecasting for Snowmelt and Rainfall Mixed Events

Directory of Open Access Journals (Sweden)

Tomasz Berezowski

2018-01-01

Full Text Available Discharge events induced by mixture of snowmelt and rainfall are strongly nonlinear due to consequences of rain-on-snow phenomena and snowmelt dependence on energy balance. However, they received relatively little attention, especially in high-resolution discharge forecasting. In this study, we use Random Forests models for 24 h discharge forecasting in 1 h resolution in a 105.9 km 2 urbanized catchment in NE Poland: Biala River. The forcing data are delivered by Weather Research and Forecasting (WRF model in 1 h temporal and 4 × 4 km spatial resolutions. The discharge forecasting models are set in two scenarios with snowmelt and rainfall and rainfall only predictors in order to highlight the effect of snowmelt on the results (both scenarios use also pre-forecast discharge based predictors. We show that inclusion of snowmelt decrease the forecast errors for longer forecasts’ lead times. Moreover, importance of discharge based predictors is higher in the rainfall only models then in the snowmelt and rainfall models. We conclude that the role of snowmelt for discharge forecasting in mixed snowmelt and rainfall environments is in accounting for nonlinear physical processes, such as initial wetting and rain on snow, which cannot be properly modelled by rainfall only.

Snow chemistry of high altitude glaciers in the French Alps

OpenAIRE

MAUPETIT, FRANÇOIS; DELMAS, ROBERT J.

2011-01-01

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

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

Can GRACE detect winter snows in Japan?

Science.gov (United States)

Heki, Kosuke

2010-05-01

Current spatial resolution of the GRACE (Gravity Recovery and Climate Experiment) satellites is 300-400 km, and so its hydrological applications have been limited to continents and large islands. The Japanese Islands have width slightly smaller than this spatial resolution, but are known to show large amplitude seasonal changes in surface masses due mainly to winter snow. Such loads are responsible for seasonal crustal deformation observed with GEONET, a dense array of GPS (Global Positioning System) receivers in Japan (Heki, 2001). There is also a dense network of surface meteorological sensors for, e.g. snow depths, atmospheric pressures, etc. Heki (2004) showed that combined effects of surface loads, i.e. snow (predominant), atmosphere, soil moisture, dam impoundment, can explain seasonal crustal deformation observed by GPS to a large extent. The total weight of the winter snow in the Japanese Islands in its peak season may reach ~50 Gt. This is comparable to the annual loss of mountain glaciers in the Asian high mountains (Matsuo & Heki, 2010), and is above the detection level of GRACE. In this study, I use GRACE Level-2 Release-4 data from CSR, Univ. Texas, up to 2009 November, and evaluated seasonal changes in surface loads in and around the Japanese Islands. After applying a 350 km Gaussian filter and a de-striping filter, the peak-to-peak change of the water depth becomes ~4 cm in northern Japan. The maximum value is achieved in February-March. The region of large winter load spans from Hokkaido, Japan, to northeastern Honshu, which roughly coincides with the region of deep snow in Japan. Next I compiled snow depth data from surface meteorological observations, and converted them to loads using time-dependent snow density due to compaction. By applying the same spatial filter as the GRACE data, its spatial pattern becomes similar to the GRACE results. The present study suggests that GRACE is capable of detecting seasonal mass changes in an island arc not

Snow-avalanche impact craters in southern Norway: Their morphology and dynamics compared with small terrestrial meteorite craters

Science.gov (United States)

Matthews, John A.; Owen, Geraint; McEwen, Lindsey J.; Shakesby, Richard A.; Hill, Jennifer L.; Vater, Amber E.; Ratcliffe, Anna C.

2017-11-01

This regional inventory and study of a globally uncommon landform type reveals similarities in form and process between craters produced by snow-avalanche and meteorite impacts. Fifty-two snow-avalanche impact craters (mean diameter 85 m, range 10-185 m) were investigated through field research, aerial photographic interpretation and analysis of topographic maps. The craters are sited on valley bottoms or lake margins at the foot of steep avalanche paths (α = 28-59°), generally with an easterly aspect, where the slope of the final 200 m of the avalanche path (β) typically exceeds 15°. Crater diameter correlates with the area of the avalanche start zone, which points to snow-avalanche volume as the main control on crater size. Proximal erosional scars ('blast zones') up to 40 m high indicate up-range ejection of material from the crater, assisted by air-launch of the avalanches and impulse waves generated by their impact into water-filled craters. Formation of distal mounds up to 12 m high of variable shape is favoured by more dispersed down-range deposition of ejecta. Key to the development of snow-avalanche impact craters is the repeated occurrence of topographically-focused snow avalanches that impact with a steep angle on unconsolidated sediment. Secondary craters or pits, a few metres in diameter, are attributed to the impact of individual boulders or smaller bodies of snow ejected from the main avalanche. The process of crater formation by low-density, low-velocity, large-volume snow flows occurring as multiple events is broadly comparable with cratering by single-event, high-density, high-velocity, small-volume projectiles such as small meteorites. Simple comparative modelling of snow-avalanche events associated with a crater of average size (diameter 85 m) indicates that the kinetic energy of a single snow-avalanche impact event is two orders of magnitude less than that of a single meteorite-impact event capable of producing a crater of similar size

Powder-in-Tube (PIT) Nb3Sn conductors for high-field magnets

NARCIS (Netherlands)

Lindenhovius, J.H.; Hornsveld, E.M.; den Ouden, A.; Wessel, Wilhelm A.J.; ten Kate, Herman H.J.

2000-01-01

New Nb3Sn conductors, based on the powder-in-tube (PIT) process, have been developed for application in accelerator magnets and high-field solenoids. For application in accelerator magnets, SMI has developed a binary 504 filament PIT conductor by optimizing the manufacturing process and adjustment

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

Directory of Open Access Journals (Sweden)

Krajčí Pavel

2016-03-01

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

Atmospheric pollution for trace elements in the remote high-altitude atmosphere in central Asia as recorded in snow from Mt. Qomolangma (Everest) of the Himalayas.

Science.gov (United States)

Lee, Khanghyun; Hur, Soon Do; Hou, Shugui; Hong, Sungmin; Qin, Xiang; Ren, Jiawen; Liu, Yapping; Rosman, Kevin J R; Barbante, Carlo; Boutron, Claude F

2008-10-01

A series of 42 snow samples covering over a one-year period from the fall of 2004 to the summer of 2005 were collected from a 2.1-m snow pit at a high-altitude site on the northeastern slope of Mt. Everest. These samples were analyzed for Al, V, Cr, Mn, Co, Ni, Cu, Zn, As, Rb, Sr, Cd, Sb, Pb, and Bi in order to characterize the relative contributions from anthropogenic and natural sources to the fallout of these elements in central Himalayas. Our data were also considered in the context of monsoon versus non-monsoon seasons. The mean concentrations of the majority of the elements were determined to be at the pg g(-1) level with a strong variation in concentration with snow depth. While the mean concentrations of most of the elements were significantly higher during the non-monsoon season than during the monsoon season, considerable variability in the trace element inputs to the snow was observed during both periods. Cu, Zn, As, Cd, Sb, and Bi displayed high crustal enrichment factors (EFc) in most samples, while Cr, Ni, Rb, and Pb show high EFc values in some of the samples. Our data indicate that anthropogenic inputs are potentially important for these elements in the remote high-altitude atmosphere in the central Himalayas. The relationship between the EFc of each element and the Al concentration indicates that a dominant input of anthropogenic trace elements occurs during both the monsoon and non-monsoon seasons, when crustal contribution is relatively minor. Finally, a comparison of the trace element fallout fluxes calculated in our samples with those recently obtained at Mont Blanc, Greenland, and Antarctica provides direct evidence for a geographical gradient of the atmospheric pollution with trace elements on a global scale.

Mesoscale spiral vortex embedded within a Lake Michigan snow squall band - High resolution satellite observations and numerical model simulations

Science.gov (United States)

Lyons, Walter A.; Keen, Cecil S.; Hjelmfelt, Mark; Pease, Steven R.

1988-01-01

It is known that Great Lakes snow squall convection occurs in a variety of different modes depending on various factors such as air-water temperature contrast, boundary-layer wind shear, and geostrophic wind direction. An exceptional and often neglected source of data for mesoscale cloud studies is the ultrahigh resolution multispectral data produced by Landsat satellites. On October 19, 1972, a clearly defined spiral vortex was noted in a Landsat-1 image near the southern end of Lake Michigan during an exceptionally early cold air outbreak over a still very warm lake. In a numerical simulation using a three-dimensional Eulerian hydrostatic primitive equation mesoscale model with an initially uniform wind field, a definite analog to the observed vortex was generated. This suggests that intense surface heating can be a principal cause in the development of a low-level mesoscale vortex.

High-resolution subsurface imaging and neural network recognition: Non-intrusive buried substance location. Final report, January 26, 1997

International Nuclear Information System (INIS)

Sternberg, B.K.; Poulton, M.M.

1998-01-01

A high-frequency, high-resolution electromagnetic (EIVI) imaging system has been developed for environmental geophysics surveys. Some key features of this system include: (1) rapid surveying to allow dense spatial sampling over a large area, (2) high-accuracy measurements which are used to produce a high-resolution image of the subsurface, (3) measurements which have excellent signal-to-noise ratio over a wide bandwidth (31 kHz to 32 MHZ), (4) elimination of electric-field interference at high frequencies, (5) large-scale physical modeling to produce accurate theoretical responses over targets of interest in environmental geophysics surveys, (6) rapid neural network interpretation at the field site, and (7) visualization of complex structures during the survey. Four major experiments were conducted with the system: (1) Data were collected for several targets in our physical modeling facility. (2) We tested the system over targets buried in soil. (3) We conducted an extensive survey at the Idaho National Engineering Laboratory (INEL) Cold Test Pit (CTP). The location of the buried waste, category of waste, and thickness of the clay cap were successfully mapped. (4) We ran surveys over the acid pit at INEL. This was an operational survey over a hot site. The interpreted low-resistivity region correlated closely with the known extent of the acid pit

Efficient coupling of high intensity short laser pulses into snow clusters

Science.gov (United States)

Palchan, T.; Pecker, S.; Henis, Z.; Eisenmann, S.; Zigler, A.

2007-01-01

Measurements of energy absorption of high intensity laser pulses in snow clusters are reported. Targets consisting of sapphire coated with snow nanoparticles were found to absorb more than 95% of the incident light compared to 50% absorption in flat sapphire targets.

A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model

Directory of Open Access Journals (Sweden)

S. Kolberg

2006-01-01

Full Text Available A method for assimilating remotely sensed snow covered area (SCA into the snow subroutine of a grid distributed precipitation-runoff model (PRM is presented. The PRM is assumed to simulate the snow state in each grid cell by a snow depletion curve (SDC, which relates that cell's SCA to its snow cover mass balance. The assimilation is based on Bayes' theorem, which requires a joint prior distribution of the SDC variables in all the grid cells. In this paper we propose a spatial model for this prior distribution, and include similarities and dependencies among the grid cells. Used to represent the PRM simulated snow cover state, our joint prior model regards two elevation gradients and a degree-day factor as global variables, rather than describing their effect separately for each cell. This transformation results in smooth normalised surfaces for the two related mass balance variables, supporting a strong inter-cell dependency in their joint prior model. The global features and spatial interdependency in the prior model cause each SCA observation to provide information for many grid cells. The spatial approach similarly facilitates the utilisation of observed discharge. Assimilation of SCA data using the proposed spatial model is evaluated in a 2400 km2 mountainous region in central Norway (61° N, 9° E, based on two Landsat 7 ETM+ images generalized to 1 km2 resolution. An image acquired on 11 May, a week before the peak flood, removes 78% of the variance in the remaining snow storage. Even an image from 4 May, less than a week after the melt onset, reduces this variance by 53%. These results are largely improved compared to a cell-by-cell independent assimilation routine previously reported. Including observed discharge in the updating information improves the 4 May results, but has weak effect on 11 May. Estimated elevation gradients are shown to be sensitive to informational deficits occurring at high altitude, where snowmelt has not started

California's Snow Gun and its implications for mass balance predictions under greenhouse warming

Science.gov (United States)

Howat, I.; Snyder, M.; Tulaczyk, S.; Sloan, L.

2003-12-01

Precipitation has received limited treatment in glacier and snowpack mass balance models, largely due to the poor resolution and confidence of precipitation predictions relative to temperature predictions derived from atmospheric models. Most snow and glacier mass balance models rely on statistical or lapse rate-based downscaling of general or regional circulation models (GCM's and RCM's), essentially decoupling sub-grid scale, orographically-driven evolution of atmospheric heat and moisture. Such models invariably predict large losses in the snow and ice volume under greenhouse warming. However, positive trends in the mass balance of glaciers in some warming maritime climates, as well as at high elevations of the Greenland Ice Sheet, suggest that increased precipitation may play an important role in snow- and glacier-climate interactions. Here, we present a half century of April snowpack data from the Sierra Nevada and Cascade mountains of California, USA. This high-density network of snow-course data indicates that a gain in winter snow accumulation at higher elevations has compensated loss in snow volume at lower elevations by over 50% and has led to glacier expansion on Mt. Shasta. These trends are concurrent with a region-wide increase in winter temperatures up to 2° C. They result from the orographic lifting and saturation of warmer, more humid air leading to increased precipitation at higher elevations. Previous studies have invoked such a "Snow Gun" effect to explain contemporaneous records of Tertiary ocean warming and rapid glacial expansion. A climatological context of the California's "snow gun" effect is elucidated by correlation between the elevation distribution of April SWE observations and the phase of the Pacific Decadal Oscillation and the El Nino Southern Oscillation, both controlling the heat and moisture delivered to the U.S. Pacific coast. The existence of a significant "Snow Gun" effect presents two challenges to snow and glacier mass

Subpixel Snow Cover Mapping from MODIS Data by Nonparametric Regression Splines

Science.gov (United States)

Akyurek, Z.; Kuter, S.; Weber, G. W.

2016-12-01

Spatial extent of snow cover is often considered as one of the key parameters in climatological, hydrological and ecological modeling due to its energy storage, high reflectance in the visible and NIR regions of the electromagnetic spectrum, significant heat capacity and insulating properties. A significant challenge in snow mapping by remote sensing (RS) is the trade-off between the temporal and spatial resolution of satellite imageries. In order to tackle this issue, machine learning-based subpixel snow mapping methods, like Artificial Neural Networks (ANNs), from low or moderate resolution images have been proposed. Multivariate Adaptive Regression Splines (MARS) is a nonparametric regression tool that can build flexible models for high dimensional and complex nonlinear data. Although MARS is not often employed in RS, it has various successful implementations such as estimation of vertical total electron content in ionosphere, atmospheric correction and classification of satellite images. This study is the first attempt in RS to evaluate the applicability of MARS for subpixel snow cover mapping from MODIS data. Total 16 MODIS-Landsat ETM+ image pairs taken over European Alps between March 2000 and April 2003 were used in the study. MODIS top-of-atmospheric reflectance, NDSI, NDVI and land cover classes were used as predictor variables. Cloud-covered, cloud shadow, water and bad-quality pixels were excluded from further analysis by a spatial mask. MARS models were trained and validated by using reference fractional snow cover (FSC) maps generated from higher spatial resolution Landsat ETM+ binary snow cover maps. A multilayer feed-forward ANN with one hidden layer trained with backpropagation was also developed. The mutual comparison of obtained MARS and ANN models was accomplished on independent test areas. The MARS model performed better than the ANN model with an average RMSE of 0.1288 over the independent test areas; whereas the average RMSE of the ANN model

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

Science.gov (United States)

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

2017-12-01

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

Snow Matters

DEFF Research Database (Denmark)

Gyimóthy, Szilvia; Jensen, Martin Trandberg

2018-01-01

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

A STUDY ON SNOW PROFILES AND SURFACE CHARACTERISTICS ALONG 6000km TRANSANTARCTIC ROUTE (Ⅰ)——THE "1990 INTERNATIONAL TRANS-ANTARCTIC EXPEDITION" GLACIOLOGICAL RESEARCH

Institute of Scientific and Technical Information of China (English)

秦大河; 任贾文

1992-01-01

Along a 5986 km route on Antarctic ice sheet from west to east, 106 snow pits with a depth ranging from 1.0—2.0 m have been dug by the first author of this paper, the Chinese member of the "1990 International Trans-Antarctic Expedition". The basic physical characteristics of the surface layer of the ice sheet on a large scale are obtained through the observations of snow profiles at these snow pits. The sastrugi shapes and major axis azimuths have also been observed or measured on the way. Analysis for these observation data shows that in West Antarctica the meltwater infiltration-congelation is obvious and the annual precipitation is larger than that in East Antarctica, which implies that climate in West Antarctica is warmer, more humid and influenced more greatly by the South Ocean than that in East Antarctica. Radiation ice-glazes frequently found in snow profiles indicate that even in East Antarctica under very low temperatures, surface "melting" occurs in summer due to the long-time solar radiatio

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

Science.gov (United States)

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

2015-01-01

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

Seasonal variations in the sources of natural and anthropogenic lead deposited at the East Rongbuk Glacier in the high-altitude Himalayas.

Science.gov (United States)

Burn-Nunes, Laurie; Vallelonga, Paul; Lee, Khanghyun; Hong, Sungmin; Burton, Graeme; Hou, Shugui; Moy, Andrew; Edwards, Ross; Loss, Robert; Rosman, Kevin

2014-07-15

Lead (Pb) isotopic compositions and concentrations, and barium (Ba) and indium (In) concentrations have been analysed at sub-annual resolution in three sections from a snow pit samples dated to 2004/2005, recovered from the East Rongbuk Glacier in the high-altitude Himalayas. Ice core sections indicate that atmospheric chemistry prior to ~1,953 was controlled by mineral dust inputs, with no discernible volcanic or anthropogenic contributions. Eighteenth century monsoon ice core chemistry is indicative of dominant contributions from local Himalayan sources; non-monsoon ice core chemistry is linked to contributions from local (Himalayan), regional (Indian/Thar Desert) and long-range (North Africa, Central Asia) sources. Twentieth century monsoon and non-monsoon ice core data demonstrate similar seasonal sources of mineral dust, however with a transition to less-radiogenic isotopic signatures that suggests local and regional climate/environmental change. The snow pit record demonstrates natural and anthropogenic contributions during both seasons, with increased anthropogenic influence during non-monsoon times. Monsoon anthropogenic inputs are most likely sourced to South/South-East Asia and/or India, whereas non-monsoon anthropogenic inputs are most likely sourced to India and Central Asia. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Modeling the Observed Microwave Emission from Shallow Multi-Layer Tundra Snow Using DMRT-ML

Directory of Open Access Journals (Sweden)

Nastaran Saberi

2017-12-01

Full Text Available The observed brightness temperatures (Tb at 37 GHz from typical moderate density dry snow in mid-latitudes decreases with increasing snow water equivalent (SWE due to volume scattering of the ground emissions by the overlying snow. At a certain point, however, as SWE increases, the emission from the snowpack offsets the scattering of the sub-nivean emission. In tundra snow, the Tb slope reversal occurs at shallower snow thicknesses. While it has been postulated that the inflection point in the seasonal time series of observed Tb V 37 GHz of tundra snow is controlled by the formation of a thick wind slab layer, the simulation of this effect has yet to be confirmed. Therefore, the Dense Media Radiative Transfer Theory for Multi Layered (DMRT-ML snowpack is used to predict the passive microwave response from airborne observations over shallow, dense, slab-layered tundra snow. Airborne radiometer observations coordinated with ground-based in situ snow measurements were acquired in the Canadian high Arctic near Eureka, NT, in April 2011. The DMRT-ML was parameterized with the in situ snow measurements using a two-layer snowpack and run in two configurations: a depth hoar and a wind slab dominated pack. With these two configurations, the calibrated DMRT-ML successfully predicted the Tb V 37 GHz response (R correlation of 0.83 when compared with the observed airborne Tb footprints containing snow pits measurements. Using this calibrated model, the DMRT-ML was applied to the whole study region. At the satellite observation scale, observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E over the study area reflected seasonal differences between Tb V 37 GHz and Tb V 19 GHz that supports the hypothesis of the development of an early season volume scattering depth hoar layer, followed by the growth of the late season emission-dominated wind slab layer. This research highlights the necessity to consider the two

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

Directory of Open Access Journals (Sweden)

E. E. Stigter

2017-07-01

Full Text Available Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water equivalent (SWE. Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF. Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May and decreases during the late melt season (June to September as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

Imaging of the CO snow line in a solar nebula analog.

Science.gov (United States)

Qi, Chunhua; Öberg, Karin I; Wilner, David J; D'Alessio, Paola; Bergin, Edwin; Andrews, Sean M; Blake, Geoffrey A; Hogerheijde, Michiel R; van Dishoeck, Ewine F

2013-08-09

Planets form in the disks around young stars. Their formation efficiency and composition are intimately linked to the protoplanetary disk locations of "snow lines" of abundant volatiles. We present chemical imaging of the carbon monoxide (CO) snow line in the disk around TW Hya, an analog of the solar nebula, using high spatial and spectral resolution Atacama Large Millimeter/Submillimeter Array observations of diazenylium (N2H(+)), a reactive ion present in large abundance only where CO is frozen out. The N2H(+) emission is distributed in a large ring, with an inner radius that matches CO snow line model predictions. The extracted CO snow line radius of ~30 astronomical units helps to assess models of the formation dynamics of the solar system, when combined with measurements of the bulk composition of planets and comets.

Oxygen isotope variability in snow from western Dronning Maud Land, Antarctica and its relation to temperature

International Nuclear Information System (INIS)

Helsen, M.M.; Wal, R.S.W. van de; Broeke, M.R. van den; As, D. van; Reijmer, C.H.; Meijer, H.A.J.

2005-01-01

This paper presents (delta) 18 O records from snow pits from four locations in Dronning Maud Land, Antarctica that contain at least four annual cycles. The aim of the study was to analyse in detail these records as well as the prevailing temperatures during accumulation in order to infer to what extent isotopic composition in this area can be interpreted as temperature information. The original seasonal amplitudes of the isotope records were reconstructed by use of a simple back-diffusion model. Automatic weather station data were used to describe the accumulation history and the near-surface temperatures; the temperatures at the atmospheric level of snow formation were inferred from a regional climate model. The results show that the strongly intermittent nature of the accumulation in this area can result in the exclusion of entire seasons from the isotope records. The temperature records also reveal that the oxygen isotope records in these snow pits are biased towards higher temperatures, since snowfall conditions are associated with higher temperatures. This effect is greatest at low temperatures. A comparison between the seasonal extreme isotopic and temperature values points out that on timescales of seasons to several years, isotopic variability cannot be interpreted with confidence as temperature changes at the accumulation sites

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

Science.gov (United States)

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

2014-06-01

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

Modelling snow ice and superimposed ice on landfast sea ice in Kongsfjorden, Svalbard

Directory of Open Access Journals (Sweden)

Caixin Wang

2015-08-01

Full Text Available Snow ice and superimposed ice formation on landfast sea ice in a Svalbard fjord, Kongsfjorden, was investigated with a high-resolution thermodynamic snow and sea-ice model, applying meteorological weather station data as external forcing. The model shows that sea-ice formation occurs both at the ice bottom and at the snow/ice interface. Modelling results indicated that the total snow ice and superimposed ice, which formed at the snow/ice interface, was about 14 cm during the simulation period, accounting for about 15% of the total ice mass and 35% of the total ice growth. Introducing a time-dependent snow density improved the modelled results, and a time-dependent oceanic heat flux parameterization yielded reasonable ice growth at the ice bottom. Model results suggest that weather conditions, in particular air temperature and precipitation, as well as snow thermal properties and surface albedo are the most critical factors for the development of snow ice and superimposed ice in Kongsfjorden. While both warming air and higher precipitation led to increased snow ice and superimposed ice forming in Kongsfjorden in the model runs, the processes were more sensitive to precipitation than to air temperature.

An Experimental High-Resolution Forecast System During the Vancouver 2010 Winter Olympic and Paralympic Games

Science.gov (United States)

Mailhot, J.; Milbrandt, J. A.; Giguère, A.; McTaggart-Cowan, R.; Erfani, A.; Denis, B.; Glazer, A.; Vallée, M.

2014-01-01

Environment Canada ran an experimental numerical weather prediction (NWP) system during the Vancouver 2010 Winter Olympic and Paralympic Games, consisting of nested high-resolution (down to 1-km horizontal grid-spacing) configurations of the GEM-LAM model, with improved geophysical fields, cloud microphysics and radiative transfer schemes, and several new diagnostic products such as density of falling snow, visibility, and peak wind gust strength. The performance of this experimental NWP system has been evaluated in these winter conditions over complex terrain using the enhanced mesoscale observing network in place during the Olympics. As compared to the forecasts from the operational regional 15-km GEM model, objective verification generally indicated significant added value of the higher-resolution models for near-surface meteorological variables (wind speed, air temperature, and dewpoint temperature) with the 1-km model providing the best forecast accuracy. Appreciable errors were noted in all models for the forecasts of wind direction and humidity near the surface. Subjective assessment of several cases also indicated that the experimental Olympic system was skillful at forecasting meteorological phenomena at high-resolution, both spatially and temporally, and provided enhanced guidance to the Olympic forecasters in terms of better timing of precipitation phase change, squall line passage, wind flow channeling, and visibility reduction due to fog and snow.

Wet Snow Mapping in Southern Ontario with Sentinel-1A Observations

Science.gov (United States)

Chen, H.; Kelly, R. E. J.

2017-12-01

Wet snow is defined as snow with liquid water present in an ice-water mix. It is can be an indicator for the onset of the snowmelt period. Knowledge about the extent of wet snow area can be of great importance for the monitoring of seasonal snowmelt runoff with climate-induced changes in snowmelt duration having implications for operational hydrological and ecological applications. Spaceborne microwave remote sensing has been used to observe seasonal snow under all-weather conditions. Active microwave observations of snow at C-band are sensitive to wet snow due to the high dielectric contrast with non-wet snow surfaces and synthetic aperture radar (SAR) is now openly available to identify and map the wet snow areas globally at relatively fine spatial resolutions ( 100m). In this study, a semi-automated workflow is developed from the change detection method of Nagler et al. (2016) using multi-temporal Sentinel-1A (S1A) dual-polarization observations of Southern Ontario. Weather station data and visible-infrared satellite observations are used to refine the wet snow area estimates. Wet snow information from National Operational Hydrologic Remote Sensing Center (NOHRSC) is used to compare with the S1A estimates. A time series of wet snow maps shows the variations in backscatter from wet snow on a pixel basis. Different land cover types in Southern Ontario are assessed with respect to their impacts on wet snow estimates. While forests and complex land surfaces can impact the ability to map wet snow, the approach taken is robust and illustrates the strong sensitivity of the approach to wet snow backscattering characteristics. The results indicate the feasibility of the change detection method on non-mountainous large areas and address the usefulness of Sentinel-1A data for wet snow mapping.

Evaluating MODIS snow products for modelling snowmelt runoff: Case study of the Rio Grande headwaters

Science.gov (United States)

Steele, Caitriana; Dialesandro, John; James, Darren; Elias, Emile; Rango, Albert; Bleiweiss, Max

2017-12-01

Snow-covered area (SCA) is a key variable in the Snowmelt-Runoff Model (SRM) and in other models for simulating discharge from snowmelt. Landsat Thematic Mapper (TM), Enhanced Thematic Mapper (ETM +) or Operational Land Imager (OLI) provide remotely sensed data at an appropriate spatial resolution for mapping SCA in small headwater basins, but the temporal resolution of the data is low and may not always provide sufficient cloud-free dates. The coarser spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) offers better temporal resolution and in cloudy years, MODIS data offer the best alternative for mapping snow cover when finer spatial resolution data are unavailable. However, MODIS' coarse spatial resolution (500 m) can obscure fine spatial patterning in snow cover and some MODIS products are not sensitive to end-of-season snow cover. In this study, we aimed to test MODIS snow products for use in simulating snowmelt runoff from smaller headwater basins by a) comparing maps of TM and MODIS-based SCA and b) determining how SRM streamflow simulations are changed by the different estimates of seasonal snow depletion. We compared gridded MODIS snow products (Collection 5 MOD10A1 fractional and binary SCA; SCA derived from Collection 6 MOD10A1 Normalised Difference Snow Index (NDSI) Snow Cover), and the MODIS Snow Covered-Area and Grain size retrieval (MODSCAG) canopy-corrected fractional SCA (SCAMG), with reference SCA maps (SCAREF) generated from binary classification of TM imagery. SCAMG showed strong agreement with SCAREF; excluding true negatives (where both methods agreed no snow was present) the median percent difference between SCAREF and SCAMG ranged between -2.4% and 4.7%. We simulated runoff for each of the four study years using SRM populated with and calibrated for snow depletion curves derived from SCAREF. We then substituted in each of the MODIS-derived depletion curves. With efficiency coefficients ranging between 0.73 and 0.93, SRM

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

Directory of Open Access Journals (Sweden)

Norihiro Watanabe

2017-11-01

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

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

Science.gov (United States)

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

2017-12-01

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

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.

Comparison of snow melt properties across multiple spatial scales and landscape units in interior sub-Arctic boreal Alaskan watersheds

Science.gov (United States)

Bennett, K. E.; Cherry, J. E.; Hiemstra, C. A.; Bolton, W. R.

2013-12-01

Interior sub-Arctic Alaskan snow cover is rapidly changing and requires further study for correct parameterization in physically based models. This project undertook field studies during the 2013 snow melt season to capture snow depth, snow temperature profiles, and snow cover extent to compare with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor at four different sites underlain by discontinuous permafrost. The 2013 melt season, which turned out to be the latest snow melt period on record, was monitored using manual field measurements (SWE, snow depth data collection), iButtons to record temperature of the snow pack, GoPro cameras to capture time lapse of the snow melt, and low level orthoimagery collected at ~1500 m using a Navion L17a plane mounted with a Nikon D3s camera. Sites were selected across a range of landscape conditions, including a north facing black spruce hill slope, a south facing birch forest, an open tundra site, and a high alpine meadow. Initial results from the adjacent north and south facing sites indicate a highly sensitive system where snow cover melts over just a few days, illustrating the importance of high resolution temporal data capture at these locations. Field observations, iButtons and GoPro cameras show that the MODIS data captures the melt conditions at the south and the north site with accuracy (2.5% and 6.5% snow cover fraction present on date of melt, respectively), but MODIS data for the north site is less variable around the melt period, owing to open conditions and sparse tree cover. However, due to the rapid melt rate trajectory, shifting the melt date estimate by a day results in a doubling of the snow cover fraction estimate observed by MODIS. This information can assist in approximating uncertainty associated with remote sensing data that is being used to populate hydrologic and snow models (the Sacramento Soil Moisture Accounting model, coupled with SNOW-17, and the Variable

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).

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

Seasonal variations in the sources of natural and anthropogenic lead deposited at the East Rongbuk Glacier in the high-altitude Himalayas

International Nuclear Information System (INIS)

Burn-Nunes, Laurie; Vallelonga, Paul; Lee, Khanghyun; Hong, Sungmin; Burton, Graeme; Hou, Shugui; Moy, Andrew; Edwards, Ross; Loss, Robert; Rosman, Kevin

2014-01-01

Lead (Pb) isotopic compositions and concentrations, and barium (Ba) and indium (In) concentrations have been analysed at sub-annual resolution in three sections from a < 110 m ice core dated to the 18th and 20th centuries, as well as snow pit samples dated to 2004/2005, recovered from the East Rongbuk Glacier in the high-altitude Himalayas. Ice core sections indicate that atmospheric chemistry prior to ∼ 1953 was controlled by mineral dust inputs, with no discernible volcanic or anthropogenic contributions. Eighteenth century monsoon ice core chemistry is indicative of dominant contributions from local Himalayan sources; non-monsoon ice core chemistry is linked to contributions from local (Himalayan), regional (Indian/Thar Desert) and long-range (North Africa, Central Asia) sources. Twentieth century monsoon and non-monsoon ice core data demonstrate similar seasonal sources of mineral dust, however with a transition to less-radiogenic isotopic signatures that suggests local and regional climate/environmental change. The snow pit record demonstrates natural and anthropogenic contributions during both seasons, with increased anthropogenic influence during non-monsoon times. Monsoon anthropogenic inputs are most likely sourced to South/South-East Asia and/or India, whereas non-monsoon anthropogenic inputs are most likely sourced to India and Central Asia. - Highlights: • Pb isotopes in ice and snow show seasonality in Mt Everest atmospheric chemistry. • Local (Himalayan) mineral dust inputs are present year round. • Regional and long-range mineral dust inputs are evident during non-monsoon times. • Snow samples indicate increased anthropogenic inputs during non-monsoon times. • Anthropogenic inputs are linked with Indian, South Asian and Central Asian sources

Seasonal variations in the sources of natural and anthropogenic lead deposited at the East Rongbuk Glacier in the high-altitude Himalayas

Energy Technology Data Exchange (ETDEWEB)

Burn-Nunes, Laurie, E-mail: L.Nunes@curtin.edu.au [Department of Imaging and Applied Physics, Curtin University, GPO Box U 1987, Perth 6845, Western Australia (Australia); Vallelonga, Paul [Centre for Ice and Climate, Niels Bohr Institute, University of Copenhagen, Juliane Maries Vej 30, DK-2100 Copenhagen Ø (Denmark); Lee, Khanghyun [Environmental Measurement and Analysis Center, National Institute of Environmental Research, Environmental Research Complex, Kyungseo-dong, Seo-gu, Incheon 404-170 (Korea, Republic of); Hong, Sungmin [Department of Ocean Sciences, Inha University, 100 Inha-ro, Nam-gu, Incheon 402-751 (Korea, Republic of); Burton, Graeme [Department of Imaging and Applied Physics, Curtin University, GPO Box U 1987, Perth 6845, Western Australia (Australia); Hou, Shugui [Key Laboratory of Coast and Island development of Ministry of Education, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093 (China); Moy, Andrew [Department of the Environment, Australian Antarctic Division, Channel Highway, Kingston 7050, Tasmania (Australia); Antarctic Climate and Ecosystems Cooperative Research Centre, University of Tasmania, Private Bag 80, Hobart 7001, Tasmania (Australia); Edwards, Ross; Loss, Robert; Rosman, Kevin [Department of Imaging and Applied Physics, Curtin University, GPO Box U 1987, Perth 6845, Western Australia (Australia)

2014-07-01

Lead (Pb) isotopic compositions and concentrations, and barium (Ba) and indium (In) concentrations have been analysed at sub-annual resolution in three sections from a < 110 m ice core dated to the 18th and 20th centuries, as well as snow pit samples dated to 2004/2005, recovered from the East Rongbuk Glacier in the high-altitude Himalayas. Ice core sections indicate that atmospheric chemistry prior to ∼ 1953 was controlled by mineral dust inputs, with no discernible volcanic or anthropogenic contributions. Eighteenth century monsoon ice core chemistry is indicative of dominant contributions from local Himalayan sources; non-monsoon ice core chemistry is linked to contributions from local (Himalayan), regional (Indian/Thar Desert) and long-range (North Africa, Central Asia) sources. Twentieth century monsoon and non-monsoon ice core data demonstrate similar seasonal sources of mineral dust, however with a transition to less-radiogenic isotopic signatures that suggests local and regional climate/environmental change. The snow pit record demonstrates natural and anthropogenic contributions during both seasons, with increased anthropogenic influence during non-monsoon times. Monsoon anthropogenic inputs are most likely sourced to South/South-East Asia and/or India, whereas non-monsoon anthropogenic inputs are most likely sourced to India and Central Asia. - Highlights: • Pb isotopes in ice and snow show seasonality in Mt Everest atmospheric chemistry. • Local (Himalayan) mineral dust inputs are present year round. • Regional and long-range mineral dust inputs are evident during non-monsoon times. • Snow samples indicate increased anthropogenic inputs during non-monsoon times. • Anthropogenic inputs are linked with Indian, South Asian and Central Asian sources.

Tracing the contribution of debris flow-dominated channels to gravel-bed torrential river channel: implementing pit-tags in the upper Guil River (French Alps)

Science.gov (United States)

Arnaud-Fassetta, Gilles; Lissak, Candide; Fort, Monique; Bétard, François; Carlier, Benoit; Cossart, Etienne; Madelin, Malika; Viel, Vincent; Charnay, Bérengère; Bletterie, Xavier

2014-05-01

In the upper, wider reaches of Alpine valleys, shaping of active channels is usually subject to rapid change. It mostly depends upon hydro-climatic variability, runoff concentration and sediment supply, and may result in alternating sequences of fluvial and debris-flow pulses, as recorded in alluvial fans and terraces. Our study, carried in the frame of SAMCO (ANR) project, focuses on the upper Guil River Valley (Queyras, Southern French Alps) cut into the slaty shale "schistes lustrés". Steep, lower order drains carry a contrasted solid discharge, including predominantly sandy-loam particles mixed with gravels and boulders (sandstone schists, ophiolites). Abundant sediment supply by frost shattering, snow avalanche and landslides is then reworked during snowmelt or summer storm runoff events, and may result in catastrophic, very destructive floods along the main channel, as shown by historical records. Following the RI-30 year 2000 flood, our investigations included sediment budgets, i.e. balance of erosion and deposition, and the mapping of the source, transport and storage of various sediments (talus, colluvium, torrential fans, terraces). To better assess sediment fluxes and sediment delivery into the main channel network, we implemented tracers (pit-tags) in selected sub-catchments, significantly contributing to the sediment yield of the valley bottoms during the floods and/or avalanches: Maloqueste, Combe Morel, Bouchouse and Peyronnelle catchments. The first three are direct tributaries of the Guil River whereas the Peyronnelle is a left bank tributary of the Peynin River, which joins the Guil River via an alluvial cone with high human and material stakes. The Maloqueste and the Combe Morel are two tributaries facing each other in the Guil valley, representing a double lateral constraint for the road during flood events of the Guil River. After pit-tag initialisation in laboratory, we set them up along the four tributaries: Maloqueste (20 pit-tags), Combe

Assessing the value of real-time snow and avalanche information

Science.gov (United States)

Zeidler, Antonia; Adams, Marc; Schuster, Martin; Berner, Martin; Nagy, Wilhelm

2017-04-01

This poster presentation shows first results from a pilot study on exploring the possibilities of using existing and new information and communication technologies (ICT) for snow and avalanche assessments. Today, ICT solutions allow the utilisation of information at a high spatiotemporal resolution, due to the widespread availability of internet access, high computing power and affordable mobile devices. Therefore, there is an increasing request for up to date information on snow and avalanche decision-making. However, there are challenges that need to be addressed from different view points. These include topics in the field of technological feasibility of providing a stable network, exchanging trustworthy information and motivation of experts to participate. This contribution discusses the lessons-learnt, from the establishment of a platform to the user-experience.

Validation of AVHRR- and MODIS-derived albedos of snow and ice surfaces by means of helicopter measurements

NARCIS (Netherlands)

Greuell, W.; Oerlemans, J.

2005-01-01

We describe the validation of surface albedos of snow and glacier ice as derived from Advanced Very High Resolution Radiometer (AVHRR) and MOderate Resolution Imaging Spectrometer (MODIS) satellite data. For this purpose we measured surface albedos from a helicopter over Vatnajökull, Iceland, and

Using crowdsourced web content for informing water systems operations in snow-dominated catchments

Science.gov (United States)

Giuliani, Matteo; Castelletti, Andrea; Fedorov, Roman; Fraternali, Piero

2016-12-01

Snow is a key component of the hydrologic cycle in many regions of the world. Despite recent advances in environmental monitoring that are making a wide range of data available, continuous snow monitoring systems that can collect data at high spatial and temporal resolution are not well established yet, especially in inaccessible high-latitude or mountainous regions. The unprecedented availability of user-generated data on the web is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatiotemporally dense. In this paper, we contribute a novel crowdsourcing procedure for extracting snow-related information from public web images, either produced by users or generated by touristic webcams. A fully automated process fetches mountain images from multiple sources, identifies the peaks present therein, and estimates virtual snow indexes representing a proxy of the snow-covered area. Our procedure has the potential for complementing traditional snow-related information, minimizing costs and efforts for obtaining the virtual snow indexes and, at the same time, maximizing the portability of the procedure to several locations where such public images are available. The operational value of the obtained virtual snow indexes is assessed for a real-world water-management problem, the regulation of Lake Como, where we use these indexes for informing the daily operations of the lake. Numerical results show that such information is effective in extending the anticipation capacity of the lake operations, ultimately improving the system performance.

A Distributed Snow Evolution Modeling System (SnowModel)

Science.gov (United States)

Liston, G. E.; Elder, K.

2004-12-01

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

Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals

Science.gov (United States)

Langlois, A.; Royer, A.; Derksen, C.; Montpetit, B.; Dupont, F.; GoïTa, K.

2012-12-01

Satellite-passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resolution introduces uncertainties to SWE retrievals due to the surface heterogeneity within individual pixels. In this article, we investigate the coupling of a thermodynamic multilayered snow model with a passive microwave emission model. Results show that the snow model itself provides poor SWE simulations when compared to field measurements from two major field campaigns. Coupling the snow and microwave emission models with successive iterations to correct the influence of snow grain size and density significantly improves SWE simulations. This method was further validated using an additional independent data set, which also showed significant improvement using the two-step iteration method compared to standalone simulations with the snow model.

New Approach for Snow Cover Detection through Spectral Pattern Recognition with MODIS Data

Directory of Open Access Journals (Sweden)

Kyeong-Sang Lee

2017-01-01

Full Text Available Snow cover plays an important role in climate and hydrology, at both global and regional scales. Most previous studies have used static threshold techniques to detect snow cover, which can lead to errors such as misclassification of snow and clouds, because the reflectance of snow cover exhibits variability and is affected by several factors. Therefore, we present a simple new algorithm for mapping snow cover from Moderate Resolution Imaging Spectroradiometer (MODIS data using dynamic wavelength warping (DWW, which is based on dynamic time warping (DTW. DTW is a pattern recognition technique that is widely used in various fields such as human action recognition, anomaly detection, and clustering. Before performing DWW, we constructed 49 snow reflectance spectral libraries as reference data for various solar zenith angle and digital elevation model conditions using approximately 1.6 million sampled data. To verify the algorithm, we compared our results with the MODIS swath snow cover product (MOD10_L2. Producer’s accuracy, user’s accuracy, and overall accuracy values were 92.92%, 78.41%, and 92.24%, respectively, indicating good overall classification accuracy. The proposed algorithm is more useful for discriminating between snow cover and clouds than threshold techniques in some areas, such as those with a high viewing zenith angle.

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/.

Why do Pit-Hours outlive the Pit?

NARCIS (Netherlands)

S.R. Ozturk (Sait); M. van der Wel (Michel); D.J.C. van Dijk (Dick)

2015-01-01

markdownabstract__Abstract__ We study why a majority of trades still happen during the pit hours, i.e. when the trading pit is open, even after the pit ceased to be a liquid and informative venue. We investigate the case of 30-year U.S. Treasury futures using a ten-years-long intraday data set

Changes in Andes snow cover from MODIS data, 2000-2016

Science.gov (United States)

Saavedra, Freddy A.; Kampf, Stephanie K.; Fassnacht, Steven R.; Sibold, Jason S.

2018-03-01

The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent). This analysis is conducted between 8 and 36° S due to high frequency of cloud (> 30 % of the time) south and north of this range. We ran Mann-Kendall and Theil-Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP = 20 %). We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) and University of Delaware datasets and climate indices as El Niño-Southern Oscillation (ENSO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO). Areas north of 29° S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2) with persistent snow cover between 29 and 36° S experienced a significant loss of snow cover (2-5 fewer days of snow year-1). Snow loss was more pronounced (62 % of the area with significant trends) on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10-30 m year-1 south of 29-30° S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31° S, whereas the SAM better predicted SP south of 31° S.

Improving snow fraction spatio-temporal continuity using a combination of MODIS and Fengyun-2 satellites over China

Science.gov (United States)

Jiang, L.; Wang, G.

2017-12-01

Snow cover is one of key elements in the investigations of weather, climatic change, water resource, and snow hazard. Satellites observations from on-board optical sensors provides the ability to snow cover mapping through the discrimination of snow from other surface features and cloud. MODIS provides maximum of snow cover data using 8-day composition data in order to reduce the cloud obscuration impacts. However, snow cover mapping is often required to obtain at the temporal scale of less than one day, especially in the case of disasters. Geostationary satellites provide much higher temporal resolution measurements (typically at 15 min or half or one hour), which has a great potential to reduce cloud cover problem and observe ground surface for identifying snow. The proposed method in this work is that how to take the advantages of polar-orbiting and geostationary optical sensors to accurately map snow cover without data gaps due to cloud. FY-2 geostationary satellites have high temporal resolution observations, however, they are lacking enough spectral bands essential for snow cover monitoring, such as the 1.6 μm band. Based on our recent work (Wang et al., 2017), we improved FY-2/VISSR fractional snow cover estimation with a linear spectral unmixing analysis method. The linear approach is applied then using the reflectance observed at the certain hourly image of FY-2 to calculate pixel-wise snow cover fraction. The composition of daily factional snow cover employs the sun zenith angle, where the snow fraction under lowest sun zenith angle is considered as the most confident result. FY-2/VISSR fractional snow cover map has less cloud due to the composition of multi-temporal snow maps in a single day. In order to get an accurate and cloud-reduced fractional snow cover map, both of MODIS and FY-2/VISSR daily snow fraction maps are blended together. With the combination of FY-2E/VISSR and MODIS, there are still some cloud existing in the daily snow fraction map

Powder-in-tube (PIT) Nb$_{3}$Sn conductors for high-field magnets

CERN Document Server

Lindenhovius, J L H; den Ouden, A; Wessel, W A J; ten Kate, H H J

2000-01-01

New Nb/sub 3/Sn conductors, based on the powder-in-tube (PIT) process, have been developed for application in accelerator magnets and high-field solenoids. For application in accelerator magnets, SMI has developed a binary 504 filament PIT conductor by optimizing the manufacturing process and adjustment of the conductor lay-out. It uniquely combines a non-copper current density of 2680 A/mm/sup 2/@10 T with an effective filament diameter of about 20 mu m. This binary conductor may be used in a 10 T, wide bore model separator dipole magnet for the LHC, which is being developed by a collaboration of the University of Twente and CERN. A ternary (Nb/7.5wt%Ta)/sub 3/Sn conductor containing 37 filaments is particularly suited for application in extremely high-field superconducting solenoids. This wire features a copper content of 43%, a non-copper current density of 217 A/mm/sup 2/@20 T and a B/sub c2/ of 25.6 T. The main issues and the experimental results of the development program of PIT Nb/sub 3/Sn conductors a...

Oxygen pitting failure of a bagasse boiler tube

CSIR Research Space (South Africa)

Heyes, AM

2001-04-01

Full Text Available Examination of a failed roof tube from a bagasse boiler showed transverse through-cracks and extensive pitting. The pitting was typically oxygen induced pitting and numerous fatigue cracks had started within these pits. It is highly probable...

Optic Nerve Pit

Science.gov (United States)

... Conditions Frequently Asked Questions Español Condiciones Chinese Conditions Optic Nerve Pit What is optic nerve pit? An optic nerve pit is a ... may be seen in both eyes. How is optic pit diagnosed? If the pit is not affecting ...

Breeding snow: an instrumented sample holder for simultaneous tomographic and thermal studies

International Nuclear Information System (INIS)

Pinzer, B; Schneebeli, M

2009-01-01

To study the recrystallization processes during temperature gradient metamorphism of snow, we developed a sample holder that allows applying well-defined and stable thermal gradients to a snow sample while it is scanned in an x-ray micro-tomograph. To this end, both the thermal insulation of the sample as well as image contrast and resolution of the tomography had to be optimized. We solved this conflict by using thin aluminum cylinders in combination with highly insulating foam. This design is light, does not corrupt image quality and provides very good thermal decoupling from the environment. The sample holder was instrumented to measure the effective conductivity of the snow sample and calibrated using five materials of known conductivity. Finite element simulations were consistent with the calibration measurements and gave insight into the internal temperature and heat flux fields. With this setup, geometric and thermal evolution of snow under realistic thermal boundary conditions like alternating temperature gradients can be measured

Experimental and model based investigation of the links between snow bidirectional reflectance and snow microstructure

Science.gov (United States)

Dumont, M.; Flin, F.; Malinka, A.; Brissaud, O.; Hagenmuller, P.; Dufour, A.; Lapalus, P.; Lesaffre, B.; Calonne, N.; Rolland du Roscoat, S.; Ando, E.

2017-12-01

Snow optical properties are unique among Earth surface and crucial for a wide range of applications. The bi-directional reflectance, hereafter BRDF, of snow is sensible to snow microstructure. However the complex interplays between different parameters of snow microstructure namely size parameters and shape parameters on reflectance are challenging to disentangle both theoretically and experimentally. An accurate understanding and modelling of snow BRDF is required to correctly process satellite data. BRDF measurements might also provide means of characterizing snow morphology. This study presents one of the very few dataset that combined bi-directional reflectance measurements over 500-2500 nm and X-ray tomography of the snow microstructure for three different snow samples and two snow types. The dataset is used to evaluate the approach from Malinka, 2014 that relates snow optical properties to the chord length distribution in the snow microstructure. For low and medium absorption, the model accurately reproduces the measurements but tends to slightly overestimate the anisotropy of the reflectance. The model indicates that the deviation of the ice chord length distribution from an exponential distribution, that can be understood as a characterization of snow types, does not impact the reflectance for such absorptions. The simulations are also impacted by the uncertainties in the ice refractive index values. At high absorption and high viewing/incident zenith angle, the simulations and the measurements disagree indicating that some of the assumptions made in the model are not met anymore. The study also indicates that crystal habits might play a significant role for the reflectance under such geometries and wavelengths. However quantitative relationship between crystal habits and reflectance alongside with potential optical methodologies to classify snow morphology would require an extended dataset over more snow types. This extended dataset can likely be obtained

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

Science.gov (United States)

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

2014-05-01

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

Interacting Effects Induced by Two Neighboring Pits Considering Relative Position Parameters and Pit Depth

Directory of Open Access Journals (Sweden)

Yongfang Huang

2017-04-01

Full Text Available For pre-corroded aluminum alloy 7075-T6, the interacting effects of two neighboring pits on the stress concentration are comprehensively analyzed by considering various relative position parameters (inclination angle θ and dimensionless spacing parameter λ and pit depth (d with the finite element method. According to the severity of the stress concentration, the critical corrosion regions, bearing high susceptibility to fatigue damage, are determined for intersecting and adjacent pits, respectively. A straightforward approach is accordingly proposed to conservatively estimate the combined stress concentration factor induced by two neighboring pits, and a concrete application example is presented. It is found that for intersecting pits, the normalized stress concentration factor Ktnor increases with the increase of θ and λ and always reaches its maximum at θ = 90°, yet for adjacent pits, Ktnor decreases with the increase of λ and the maximum value appears at a slight asymmetric location. The simulations reveal that Ktnor follows a linear and an exponential relationship with the dimensionless depth parameter Rd for intersecting and adjacent cases, respectively.

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...

Microstructure and pitting corrosion of shielded metal arc welded high nitrogen stainless steel

Directory of Open Access Journals (Sweden)

Raffi Mohammed

2015-09-01

Full Text Available The present work is aimed at studying the microstructure and pitting corrosion behaviour of shielded metal arc welded high nitrogen steel made of Cromang-N electrode. Basis for selecting this electrode is to increase the solubility of nitrogen in weld metal due to high chromium and manganese content. Microscopic studies were carried out using optical microscopy (OM and field emission scanning electron microscopy (FESEM. Energy back scattered diffraction (EBSD method was used to determine the phase analysis, grain size and orientation image mapping. Potentio-dynamic polarization testing was carried out to study the pitting corrosion resistance in aerated 3.5% NaCl environment using a GillAC electrochemical system. The investigation results showed that the selected Cr–Mn–N type electrode resulted in a maximum reduction in delta-ferrite and improvement in pitting corrosion resistance of the weld zone was attributed to the coarse austenite grains owing to the reduction in active sites of the austenite/delta ferrite interface and the decrease in galvanic interaction between austenite and delta-ferrite.

Improving snow cover mapping in forests through the use of a canopy reflectance model

International Nuclear Information System (INIS)

Klein, A.G.; Hall, D.K.; Riggs, G.A.

1998-01-01

MODIS, the moderate resolution imaging spectro radiometer, will be launched in 1998 as part of the first earth observing system (EOS) platform. Global maps of land surface properties, including snow cover, will be created from MODIS imagery. The MODIS snow-cover mapping algorithm that will be used to produce daily maps of global snow cover extent at 500 m resolution is currently under development. With the exception of cloud cover, the largest limitation to producing a global daily snow cover product using MODIS is the presence of a forest canopy. A Landsat Thematic Mapper (TM) time-series of the southern Boreal Ecosystem–Atmosphere Study (BOREAS) study area in Prince Albert National Park, Saskatchewan, was used to evaluate the performance of the current MODIS snow-cover mapping algorithm in varying forest types. A snow reflectance model was used in conjunction with a canopy reflectance model (GeoSAIL) to model the reflectance of a snow-covered forest stand. Using these coupled models, the effects of varying forest type, canopy density, snow grain size and solar illumination geometry on the performance of the MODIS snow-cover mapping algorithm were investigated. Using both the TM images and the reflectance models, two changes to the current MODIS snow-cover mapping algorithm are proposed that will improve the algorithm's classification accuracy in forested areas. The improvements include using the normalized difference snow index and normalized difference vegetation index in combination to discriminate better between snow-covered and snow-free forests. A minimum albedo threshold of 10% in the visible wavelengths is also proposed. This will prevent dense forests with very low visible albedos from being classified incorrectly as snow. These two changes increase the amount of snow mapped in forests on snow-covered TM scenes, and decrease the area incorrectly identified as snow on non-snow-covered TM scenes. (author)

The effects of snow and salt on ice table stability in University Valley, Antarctica

Science.gov (United States)

Williams, Kaj; Heldmann, Jennifer L.; McKay, Christopher P.; Mellon, Michael T.

2018-01-01

The Antarctic Dry Valleys represent a unique environment where it is possible to study dry permafrost overlaying an ice-rich permafrost. In this paper, two opposing mechanisms for ice table stability in University Valley are addressed: i) diffusive recharge via thin seasonal snow deposits and ii) desiccation via salt deposits in the upper soil column. A high-resolution time-marching soil and snow model was constructed and applied to University Valley, driven by meteorological station atmospheric measurements. It was found that periodic thin surficial snow deposits (observed in University Valley) are capable of drastically slowing (if not completely eliminating) the underlying ice table ablation. The effects of NaCl, CaCl2 and perchlorate deposits were then modelled. Unlike the snow cover, however, the presence of salt in the soil surface (but no periodic snow) results in a slight increase in the ice table recession rate, due to the hygroscopic effects of salt sequestering vapour from the ice table below. Near-surface pore ice frequently forms when large amounts of salt are present in the soil due to the suppression of the saturation vapour pressure. Implications for Mars high latitudes are discussed.

Characterization of etch pits found on a large-grain bulk niobium superconducting radio-frequency resonant cavity

Science.gov (United States)

Zhao, Xin; Ciovati, G.; Bieler, T. R.

2010-12-01

The performance of superconducting radio-frequency (SRF) resonant cavities made of bulk niobium is limited by nonlinear localized effects. Surface analysis of regions of higher power dissipation is thus of intense interest. Such areas (referred to as “hotspots”) were identified in a large-grain single-cell cavity that had been buffered-chemical polished and dissected for examination by high resolution electron microscopy, electron backscattered diffraction microscopy (EBSD), and optical microscopy. Pits with clearly discernible crystal facets were observed in both “hotspot” and “coldspot” specimens. The pits were found in-grain, at bicrystal boundaries, and on tricrystal junctions. They are interpreted as etch pits induced by crystal defects (e.g. dislocations). All coldspots examined had a qualitatively lower density of etch pits or relatively smooth tricrystal boundary junctions. EBSD mapping revealed the crystal orientation surrounding the pits. Locations with high pit density are correlated with higher mean values of the local average misorientation angle distributions, indicating a higher geometrically necessary dislocation content. In addition, a survey of the samples by energy dispersive x-ray analysis did not show any significant contamination of the samples’ surface. The local magnetic field enhancement produced by the sharp-edge features observed on the samples is not sufficient to explain the observed degradation of the cavity quality factor, which starts at peak surface magnetic field as low as 20 mT.

A distributed snow-evolution modeling system (SnowModel)

Science.gov (United States)

Glen E. Liston; Kelly. Elder

2006-01-01

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

High-resolution surface analysis for extended-range downscaling with limited-area atmospheric models

Science.gov (United States)

Separovic, Leo; Husain, Syed Zahid; Yu, Wei; Fernig, David

2014-12-01

High-resolution limited-area model (LAM) simulations are frequently employed to downscale coarse-resolution objective analyses over a specified area of the globe using high-resolution computational grids. When LAMs are integrated over extended time frames, from months to years, they are prone to deviations in land surface variables that can be harmful to the quality of the simulated near-surface fields. Nudging of the prognostic surface fields toward a reference-gridded data set is therefore devised in order to prevent the atmospheric model from diverging from the expected values. This paper presents a method to generate high-resolution analyses of land-surface variables, such as surface canopy temperature, soil moisture, and snow conditions, to be used for the relaxation of lower boundary conditions in extended-range LAM simulations. The proposed method is based on performing offline simulations with an external surface model, forced with the near-surface meteorological fields derived from short-range forecast, operational analyses, and observed temperatures and humidity. Results show that the outputs of the surface model obtained in the present study have potential to improve the near-surface atmospheric fields in extended-range LAM integrations.

Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

Directory of Open Access Journals (Sweden)

S. Naha

2016-06-01

Full Text Available The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006. Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I and Ensemble Kalman Filter (EnKF that uses observations of snow covered area (SCA to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU, rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated

Ice Shell Thickness and Endogenic Processes on Europa from Mapping and Topographic Analyses of Pits, Uplifts and Small Chaos Features (Invited)

Science.gov (United States)

Singer, K. N.; McKinnon, W. B.; Schenk, P.

2013-12-01

Constraining the thickness of the ice shell on Europa and the geological processes occurring in it are keys to understanding this icy world and its potential habitability. We focus on circular-to-subcircular features generally agreed to have been created by endogenic processes in Europa's ice shell or ocean: pits, uplifts, and subcircular chaos. Pits and uplifts are defined by their negative or positive topographic expression, respectively. Pits and uplifts generally retain pre-existing surface structures such as ridges, while chaos specifically refers to areas where the surface is broken up, in some cases to the point of destroying all original surface topography. We have mapped all features plausibly created by upwellings or other endogenic processes in the size range of 1 to 50 km in diameter, and incorporated previously unavailable topographic data as an aid to mapping and characterization of features. Topography was derived from albedo-controlled photoclinometry and crosschecked with stereo data where possible. Mapping was carried out over the medium-resolution Galileo regional maps (RegMaps) covering approximately 9% of Europa's surface, as well as over available high-resolution regions. While limited in extent, the latter are extremely valuable for detecting smaller features and for overall geomorphological analysis. Results of this new mapping show decreasing numbers of small features, and a peak in the size distribution for all features at approximately 5-6 km in diameter. No pits smaller than 3.3 km in diameter were found in high resolution imagery. Topography was used to find the depths and heights of pits and uplifts in the mapped regions. A general trend of increasing pit depth with increasing pit size was found, a correlation more easily understood in the context of a diapiric hypothesis for feature formation (as opposed to purely non-diapiric, melt-through models). Based on isostasy, maximum pit depths of ~0.3-to-0.48 km imply a minimum shell

Pyramidal pits created by single highly charged ions in BaF2 single crystals

International Nuclear Information System (INIS)

El-Said, A. S.; Heller, R.; Facsko, S.; Aumayr, F.

2010-01-01

In various insulators, the impact of individual slow highly charged ions (eV-keV) creates surface nanostructures, whose size depends on the deposited potential energy. Here we report on the damage created on a cleaved BaF 2 (111) surface by irradiation with 4.5xq keV highly charged xenon ions from a room-temperature electron-beam ion trap. Up to charge states q=36, no surface topographic changes on the BaF 2 surface are observed by scanning force microscopy. The hidden stored damage, however, can be made visible using the technique of selective chemical etching. Each individual ion impact develops into a pyramidal etch pits, as can be concluded from a comparison of the areal density of observed etch pits with the applied ion fluence (typically 10 8 ions/cm 2 ). The dimensional analysis of the measured pits reveals the significance of the deposited potential energy in the creation of lattice distortions/defects in BaF 2 .

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

Science.gov (United States)

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

2018-02-01

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

Retinitis pigmentosa inversa with unilateral high myopia with fellow eye optic disc pitting.

Science.gov (United States)

Sheth, Saumil; Rush, Ryan; Narayanan, Raja

2011-01-01

To report a possible rare association of bilateral retinitis pigmentosa inversa (RPI) with unilateral high myopia with fellow eye optic disc pitting. A 55-year-old man with a history of reduced vision in the right eye since childhood presented with gradually decreasing vision in the left eye. On examination, a -23.00 diopter refractive error and diffuse chorioretinal atrophy consistent with pathologic myopia was found in the right eye. An optic disc pit with posterior pole pigmentary alterations thought to be consequent to a previous neurosensory detachment was found in the left eye. Though the retinal arteriolar attenuation seen in both eyes with an inconsistent history of night blindness since childhood pointed towards the possibility of a concurrently existing rod or rod-cone dystrophy, the posterior pole pigmentary alterations characteristic of RPI were clearly masked by the above pathologies. Optical coherence tomography demonstrated prominent foveal atrophy and an optic disc pit in the left eye. Electroretinography (ERG) demonstrated moderately attenuated amplitudes with prolonged implicit times of rod and cone responses bilaterally. The patient was diagnosed with bilateral RPI and anisometropic amblyopia in the right eye. This report documents a unique constellation of findings which include bilateral RPI and unilateral high myopia with an optic disc pit in the fellow eye. An ERG confirmation of a dystrophic etiology should be sought in suspicious cases, especially when findings are masked by the concurrent presence of other pathologies.

Long-range-transported bioaerosols captured in snow cover on Mount Tateyama, Japan: impacts of Asian-dust events on airborne bacterial dynamics relating to ice-nucleation activities

Directory of Open Access Journals (Sweden)

T. Maki

2018-06-01

Full Text Available The westerly wind travelling at high altitudes over eastern Asia transports aerosols from the Asian deserts and urban areas to downwind areas such as Japan. These long-range-transported aerosols include not only mineral particles but also microbial particles (bioaerosols, that impact the ice-cloud formation processes as ice nuclei. However, the detailed relations of airborne bacterial dynamics to ice nucleation in high-elevation aerosols have not been investigated. Here, we used the aerosol particles captured in the snow cover at altitudes of 2450 m on Mt Tateyama to investigate sequential changes in the ice-nucleation activities and bacterial communities in aerosols and elucidate the relationships between the two processes. After stratification of the snow layers formed on the walls of a snow pit on Mt Tateyama, snow samples, including aerosol particles, were collected from 70 layers at the lower (winter accumulation and upper (spring accumulation parts of the snow wall. The aerosols recorded in the lower parts mainly came from Siberia (Russia, northern Asia and the Sea of Japan, whereas those in the upper parts showed an increase in Asian dust particles originating from the desert regions and industrial coasts of Asia. The snow samples exhibited high levels of ice nucleation corresponding to the increase in Asian dust particles. Amplicon sequencing analysis using 16S rRNA genes revealed that the bacterial communities in the snow samples predominately included plant associated and marine bacteria (phyla Proteobacteria during winter, whereas during spring, when dust events arrived frequently, the majority were terrestrial bacteria of phyla Actinobacteria and Firmicutes. The relative abundances of Firmicutes (Bacilli showed a significant positive relationship with the ice nucleation in snow samples. Presumably, Asian dust events change the airborne bacterial communities over Mt Tateyama and carry terrestrial bacterial populations, which

Long-range-transported bioaerosols captured in snow cover on Mount Tateyama, Japan: impacts of Asian-dust events on airborne bacterial dynamics relating to ice-nucleation activities

Science.gov (United States)

Maki, Teruya; Furumoto, Shogo; Asahi, Yuya; Lee, Kevin C.; Watanabe, Koichi; Aoki, Kazuma; Murakami, Masataka; Tajiri, Takuya; Hasegawa, Hiroshi; Mashio, Asami; Iwasaka, Yasunobu

2018-06-01

The westerly wind travelling at high altitudes over eastern Asia transports aerosols from the Asian deserts and urban areas to downwind areas such as Japan. These long-range-transported aerosols include not only mineral particles but also microbial particles (bioaerosols), that impact the ice-cloud formation processes as ice nuclei. However, the detailed relations of airborne bacterial dynamics to ice nucleation in high-elevation aerosols have not been investigated. Here, we used the aerosol particles captured in the snow cover at altitudes of 2450 m on Mt Tateyama to investigate sequential changes in the ice-nucleation activities and bacterial communities in aerosols and elucidate the relationships between the two processes. After stratification of the snow layers formed on the walls of a snow pit on Mt Tateyama, snow samples, including aerosol particles, were collected from 70 layers at the lower (winter accumulation) and upper (spring accumulation) parts of the snow wall. The aerosols recorded in the lower parts mainly came from Siberia (Russia), northern Asia and the Sea of Japan, whereas those in the upper parts showed an increase in Asian dust particles originating from the desert regions and industrial coasts of Asia. The snow samples exhibited high levels of ice nucleation corresponding to the increase in Asian dust particles. Amplicon sequencing analysis using 16S rRNA genes revealed that the bacterial communities in the snow samples predominately included plant associated and marine bacteria (phyla Proteobacteria) during winter, whereas during spring, when dust events arrived frequently, the majority were terrestrial bacteria of phyla Actinobacteria and Firmicutes. The relative abundances of Firmicutes (Bacilli) showed a significant positive relationship with the ice nucleation in snow samples. Presumably, Asian dust events change the airborne bacterial communities over Mt Tateyama and carry terrestrial bacterial populations, which possibly induce ice

Flyover Modeling of Planetary Pits - Undergraduate Student Instrument Project

Science.gov (United States)

Bhasin, N.; Whittaker, W.

2015-12-01

On the surface of the moon and Mars there are hundreds of skylights, which are collapsed holes that are believed to lead to underground caves. This research uses Vision, Inertial, and LIDAR sensors to build a high resolution model of a skylight as a landing vehicle flies overhead. We design and fabricate a pit modeling instrument to accomplish this task, implement software, and demonstrate sensing and modeling capability on a suborbital reusable launch vehicle flying over a simulated pit. Future missions on other planets and moons will explore pits and caves, led by the technology developed by this research. Sensor software utilizes modern graph-based optimization techniques to build 3D models using camera, LIDAR, and inertial data. The modeling performance was validated with a test flyover of a planetary skylight analog structure on the Masten Xombie sRLV. The trajectory profile closely follows that of autonomous planetary powered descent, including translational and rotational dynamics as well as shock and vibration. A hexagonal structure made of shipping containers provides a terrain feature that serves as an appropriate analog for the rim and upper walls of a cylindrical planetary skylight. The skylight analog floor, walls, and rim are modeled in elevation with a 96% coverage rate at 0.25m2 resolution. The inner skylight walls have 5.9cm2 color image resolution and the rims are 6.7cm2 with measurement precision superior to 1m. The multidisciplinary student team included students of all experience levels, with backgrounds in robotics, physics, computer science, systems, mechanical and electrical engineering. The team was commited to authentic scientific experimentation, and defined specific instrument requirements and measurable experiment objectives to verify successful completion.This work was made possible by the NASA Undergraduate Student Instrument Project Educational Flight Opportunity 2013 program. Additional support was provided by the sponsorship of an

Everywhere and nowhere: snow and its linkages

Science.gov (United States)

Hiemstra, C. A.

2017-12-01

Interest has grown in quantifying higher latitude precipitation change and snow-related ecosystem and economic impacts. There is a high demand for creating and using snow-related datasets, yet available datasets contain limitations, aren't scale appropriate, or lack thorough validation. Much of the uncertainty in snow estimates relates to ongoing snow measurement problems that are chronic and pervasive in windy, Arctic environments. This, coupled with diminishing support for long-term snow field observations, creates formidable hydrologic gaps in snow dominated landscapes. Snow touches most aspects of high latitude landscapes and spans albedo, ecosystems, soils, permafrost, and sea ice. In turn, snow can be impacted by disturbances, landscape change, ecosystem, structure, and later arrival of sea or lake ice. Snow, and its changes touch infrastructure, housing, and transportation. Advances in snow measurements, modeling, and data assimilation are under way, but more attention and a concerted effort is needed in a time of dwindling resources to make required advances during a time of rapid change.

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

A Comprehensive Pitting Study of High Velocity Oxygen Fuel Inconel 625 Coating by Using Electrochemical Testing Techniques

Science.gov (United States)

Niaz, Akbar; Khan, Sajid Ullah

2016-01-01

In the present work, Inconel 625 was coated on a mild steel substrate using a high velocity oxygen fuel coating process. The pitting propensity of the coating was tested by using open circuit potential versus time, potentiodynamic polarization, electrochemical potentiokinetic reactivation, and scanning electrochemical microscopy. The pitting propensity of the coating was compared with bulk Inconel 625 alloy. The results confirmed that there were regions of different electrochemical activities on the coating which have caused pitting corrosion.

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

Science.gov (United States)

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

2017-12-01

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

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

Science.gov (United States)

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

2018-05-01

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

Snowmelt runoff in the Green River basin derived from MODIS snow extent

Science.gov (United States)

Barton, J. S.; Hall, D. K.

2011-12-01

The Green River represents a vital water supply for southwestern Wyoming, northern Colorado, eastern Utah, and the Lower Colorado River Compact states (Arizona, Nevada, and California). Rapid development in the southwestern United States combined with the recent drought has greatly stressed the water supply of the Colorado River system, and concurrently increased the interest in long-term variations in stream flow. Modeling of snowmelt runoff represents a means to predict flows and reservoir storage, which is useful for water resource planning. An investigation is made into the accuracy of the Snowmelt Runoff Model of Martinec and Rango, driven by Moderate Resolution Imaging Spectroradiometer (MODIS) snow maps for predicting stream flow within the Green River basin. While the moderate resolution of the MODIS snow maps limits the spatial detail that can be captured, the daily coverage is an important advantage of the MODIS imagery. The daily MODIS snow extent is measured using the most recent clear observation for each 500-meter pixel. Auxiliary data used include temperature and precipitation time series from the Snow Telemetry (SNOTEL) and Remote Automated Weather Station (RAWS) networks as well as from National Weather Service records. Also from the SNOTEL network, snow-water equivalence data are obtained to calibrate the conversion between snow extent and runoff potential.

Co-production of Snow Projections for a Study of Snow Persistence Projections for the American Wolverine Gulo gulo

Science.gov (United States)

Ray, A. J.; Barsugli, J. J.; Guinotte, J. M.; Livneh, B.; Dewes, C.; Rangwala, I.; Heldmyer, A.; Torbit, S.

2017-12-01

This presentation will describe the efforts of climate scientists to work with the US Fish and Wildlife Service (FWS) to provide analysis of future snow persistence to support a Species Status Assessment (SSA) for the American wolverine (Gulo gulo), under the Endangered Species Act (ESA). The project has been a research to application (R2A) study, aimed directly at the FWS needs, and in regular collaboration with FWS Region 6 personnel to discuss and agree on the choice downscaled projections to represent a range of plausible futures, and other methodological choices including use of high resolution (250m) physical hydrology modeling. FWS sought improved information on which to base a court-ordered re-evaluation of the conclusions of a previous SSA, due in 12 months, necessitating a quick turn-around for the snow research. The goal was to improve upon the the previous evaluation of snow persistence, both in understanding of the range of uncertainty and by using new snow modeling at spatial scales intended to be more relevant to both physical snowpack processes and to making inferences about potential wolverine denning opportunity. This project was embedded both in a specific legal/regulatory process and also in a broader FWS interest in building body of science for snow-dependent species that might support other ESA processes. Results of the co-production included new scientific questions and analytic approaches that arose from the interaction between climate scientists and ecologists. The fine spatial scales of the analysis compared to previous work allowed new hypotheses to be articulated, but also led to significant issues in the interpretation of the snow model output. This presentation will discuss key issues that arose in the collaboration between scientists and the managers developing the SSA, including the managing the independence of the science while remaining in a co-production mode, the challenges of the rapid time frame, and the challenges

Validation of MODIS snow cover images over Austria

Directory of Open Access Journals (Sweden)

J. Parajka

2006-01-01

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

Geochemical evidence on the source regions of Tibetan Plateau dusts during non-monsoon period in 2008/09

Science.gov (United States)

Li, C.; Kang, S.; Zhang, Q.; Gao, S.

2012-12-01

Geochemical characteristics, source regions and related transport patterns of dust over the Tibetan Plateau (TP) are still unclear. To address these issues, major (Na, Mg, Al, K and Ca), trace (e.g. Li, Cr, Ni, As, Cd, Cs, Pb and U) and rare earth elements of dust samples from five snow-pits over the TP and its fringe areas during the non-monsoon period in 2008/2009 were analyzed. The results indicate that rare earth element compositions of snow-pit dust are similar to those of the upper continental crust. Enrichment factors of all the elements of snow-pit dust are identical to those of the pollution elements (e.g. Cu and Ni) and elements like Li, As and Cs that are concentrated in surface soils. In contrast, concentrations of some typical pollution elements (e.g. Cr and Cd) of snow pit dust are lower than those of dusts derived from the Sahara Desert and the Thar Desert surrounding the TP. Additionally, the compositions of rare earth elements and high field strength elements (Hf, Zr and Nb) of snow-pit dust are also similar to those of surface soils and different from dusts of these two deserts. The combined evidence, including dust transport patterns around the TP, supports the conclusion that the TP itself is the main source region of snow-pit dusts of the inner TP. It is unlikely that those particle-bound pollutants are transported into the TP from outside sources during the non-monsoon period. Ratios of Ce/Sm against Eu/Sm for the snow-pit dust, fine dust from the Sahara desert (A), and ratios of Ce/Er against Eu/Er for the snow-pit dust, fine dust from the Thar Desert (B). Dust from Sahasa cannot penetrate into the TP and transport only along the Himalayas at south and the Tianshan at north due to their high elevation

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

Science.gov (United States)

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

2016-10-01

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

Characterization of etch pits found on a large-grain bulk niobium superconducting radio-frequency resonant cavity

Directory of Open Access Journals (Sweden)

Xin Zhao

2010-12-01

Full Text Available The performance of superconducting radio-frequency (SRF resonant cavities made of bulk niobium is limited by nonlinear localized effects. Surface analysis of regions of higher power dissipation is thus of intense interest. Such areas (referred to as “hotspots” were identified in a large-grain single-cell cavity that had been buffered-chemical polished and dissected for examination by high resolution electron microscopy, electron backscattered diffraction microscopy (EBSD, and optical microscopy. Pits with clearly discernible crystal facets were observed in both “hotspot” and “coldspot” specimens. The pits were found in-grain, at bicrystal boundaries, and on tricrystal junctions. They are interpreted as etch pits induced by crystal defects (e.g. dislocations. All coldspots examined had a qualitatively lower density of etch pits or relatively smooth tricrystal boundary junctions. EBSD mapping revealed the crystal orientation surrounding the pits. Locations with high pit density are correlated with higher mean values of the local average misorientation angle distributions, indicating a higher geometrically necessary dislocation content. In addition, a survey of the samples by energy dispersive x-ray analysis did not show any significant contamination of the samples’ surface. The local magnetic field enhancement produced by the sharp-edge features observed on the samples is not sufficient to explain the observed degradation of the cavity quality factor, which starts at peak surface magnetic field as low as 20 mT.

Utilizing LiDAR Datasets From Experimental Watersheds to Advance Ecohydrological Understanding in Seasonally Snow-Covered Forests

Science.gov (United States)

Harpold, A. A.; Broxton, P. D.; Guo, Q.; Barlage, M. J.; Gochis, D. J.

2014-12-01

The Western U.S. is strongly reliant on snowmelt from forested areas for ecosystem services and downstream populations. The ability to manage water resources from snow-covered forests faces major challenges from drought, disturbance, and regional changes in climate. An exciting avenue for improving ecohydrological process understanding is Light Detection and Ranging (LiDAR) because the technology simultaneously observes topography, forest properties, and snow/ice at high-resolution (100 km2). The availability and quality of LiDAR datasets is increasing rapidly, however they remain under-utilized for process-based ecohydrology investigations. This presentation will illustrate how LiDAR datasets from the Critical Zone Observatory (CZO) network have been applied to advance ecohydrological understanding through direct empirical analysis, as well as model parameterization and verification. Direct analysis of the datasets has proved fruitful for pre- and post-disturbance snow distribution estimates and interpreting in-situ snow depth measurements across sites. In addition, we illustrate the potential value of LiDAR to parameterize and verify of physical models with two examples. First, we use LiDAR to parameterize a land surface model, Noah multi-parameterization (Noah-MP), to investigate the sensitivity of modeled water and energy fluxes to high-resolution forest information. Second, we present a Snow Physics and Laser Mapping (SnowPALM) model that is parameterized with LiDAR information at its native 1-m scale. Both modeling studies demonstrate the value of LiDAR for representing processes with greater fidelity. More importantly, the increased model fidelity led to different estimates of water and energy fluxes at larger, watershed scales. Creating a network of experimental watersheds with LiDAR datasets offers the potential to test theories and models in previously unexplored ways.

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

Quantifying the changes in the High Mountain Asia snow hydrology

Science.gov (United States)

Yoon, Y.; Kumar, S.; Mocko, D. M.; Rosenberg, R. I.; Kwon, Y.; Forman, B. A.; Zaitchik, B. F.

2017-12-01

The melting of snow and glaciers in the High Mountain Asia (HMA) provides the water needs of approximately 1.3 billion people in the region. Increasing temperatures have large effects on the hydrologic cycle, influencing snowmelt, snowpack, stream flow, and water runoff, which can impact all aspects of water security, such as water allocation, conservation, efficiency and land-use planning. Most mountain regions, however, remain ungauged without in-situ measurement of precipitation or snowpack due to the complex terrain, and thus it is difficult to understand the regional water balance and assess how it might change in the future. In this study, we focus on characterizing the spatiotemporal patterns of snowpack states and fluxes over the last 30+ years (1980 - present) and assessing the relationship between snowmelt and runoff. The Noah land surface model with multi-parameterization options, version 3.6 (Noah-MP.3.6) in the NASA Land Information System (LIS) is used to establish a high resolution (1 km) modeling environment over the HMA. Combining information from satellite observations and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is used to provide an effective way to develop spatially and temporally continuous estimates of changes. To improve the spatial representativeness of the precipitation field for modeling at 1km resolution, the input field is downscaled using a stochastic downscaling method with the monthly WorldClim data. The other meteorological inputs (e.g., air temperature, humidity, pressure, wind, and downward shortwave and longwave) are corrected for elevation through lapse-rate and slope-aspect methods. Evaluation of the model estimates is presented using satellite-derived data (e.g., MODIS and GRACE) and reanalysis products (e.g., CMC and ERA-interim).

Airborne Surveys of Snow Depth over Arctic Sea Ice

Science.gov (United States)

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

2011-01-01

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

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

Directory of Open Access Journals (Sweden)

Christian Vögeli

2016-12-01

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

MODIS Snow Cover Recovery Using Variational Interpolation

Science.gov (United States)

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

2017-12-01

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

Sublimation From Snow in Northern Environments

Science.gov (United States)

Pomeroy, J. W.

2002-12-01

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

Near-Surface Refractory Black Carbon Observations in the Atmosphere and Snow in the McMurdo Dry Valleys, Antarctica, and Potential Impacts of Foehn Winds

Science.gov (United States)

Khan, Alia L.; McMeeking, Gavin R.; Schwarz, Joshua P.; Xian, Peng; Welch, Kathleen A.; Berry Lyons, W.; McKnight, Diane M.

2018-03-01

Measurements of light-absorbing particles in the boundary layer of the high southern latitudes are scarce, particularly in the McMurdo Dry Valleys (MDV), Antarctica. During the 2013-2014 austral summer near-surface boundary layer refractory black carbon (rBC) aerosols were measured in air by a single-particle soot photometer (SP2) at multiple locations in the MDV. Near-continuous rBC atmospheric measurements were collected at Lake Hoare Camp (LH) over 2 months and for several hours at more remote locations away from established field camps. We investigated periods dominated by both upvalley and downvalley winds to explore the causes of differences in rBC concentrations and size distributions. Snow samples were also collected in a 1 m pit on a glacier near the camp. The range of concentrations rBC in snow was 0.3-1.2 ± 0.3 μg-rBC/L-H2O, and total organic carbon was 0.3-1.4 ± 0.3 mg/L. The rBC concentrations measured in this snow pit are not sufficient to reduce surface albedo; however, there is potential for accumulation of rBC on snow and ice surfaces at low elevation throughout the MDV, which were not measured as part of this study. At LH, the average background rBC mass aerosol concentrations were 1.3 ng/m3. rBC aerosol mass concentrations were slightly lower, 0.09-1.3 ng/m3, at the most remote sites in the MDV. Concentration spikes as high as 200 ng/m3 were observed at LH, associated with local activities. During a foehn wind event, the average rBC mass concentration increased to 30-50 ng/m3. Here we show that the rBC increase could be due to resuspension of locally produced BC from generators, rocket toilets, and helicopters, which may remain on the soil surface until redistributed during high wind events. Quantification of local production and long-range atmospheric transport of rBC to the MDV is necessary for understanding the impacts of this species on regional climate.

Impacts of Early Summer Eurasian Snow Cover Change on Atmospheric Circulation in Northern Mid-Latitudes

Science.gov (United States)

Nozawa, T.

2016-12-01

Recently, Japan Aerospace Exploration Agency (JAXA) has developed a new long-term snow cover extent (SCE) product using Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data spanning from 1980's to date. This new product (JAXA/SCE) has higher spatial resolution and smaller commission error compared with traditional SCE dataset of National Oceanic and Atmospheric Administration (NOAA/SCE). Continuity of the algorithm is another strong point in JAXA/SCE. According to the new JAXA/SCE dataset, the Eurasian SCE has been significantly retreating since 1980's, especially in late spring and early summer. Here, we investigate impacts of early summer Eurasian snow cover change on atmospheric circulation in Northern mid-latitudes, especially over the East Asia, using the new JAXA/SCE dataset and a few reanalysis data. We will present analyzed results on relationships between early summer SCE anomaly over the Eurasia and changes in atmospheric circulations such as upper level zonal jets (changes in strength, positions, etc.) over the East Asia.

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

Science.gov (United States)

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

2010-12-01

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

Does seasonal snowpacks enhance or decrease mercury contamination of high elevation ecosystems?

Science.gov (United States)

Pierce, A.; Fain, X.; Obrist, D.; Helmig, D.; Barth, C.; Jacques, H.; Chowanski, K.; Boyle, D.; William, M.

2009-12-01

Mercury (Hg) is an extremely toxic pollutant globally dispersed in the environment. Natural and anthropogenic sources emit Hg to the atmosphere, either as gaseous elemental mercury (GEM; Hg0) or as divalent mercury species. Due to the long lifetime of GEM mercury contamination is not limited to industrialized sites, but also a concern in remote areas such as high elevation mountain environments. During winter and spring 2009, we investigated the fate of atmospheric mercury deposited to mountain ecosystems in the Sierra Nevada (Sagehen station, California, USA) and the Rocky Mountains (Niwot Ridge station, Colorado, USA). At Sagehen, we monitored mercury in snow (surface snow sampling and snow pits), wet deposition, and stream water during the snow-dominated season. Comparison of Hg stream discharge to snow Hg wet deposition showed that only a small fraction of Hg wet deposition reached stream in the melt water. Furthermore, Hg concentration in soil transects (25 different locations) showed no correlations to wet deposition Hg loads due to pronounced altitudinal precipitation gradient suggesting that Hg deposited to the snowpack was not transferred to ecosystems. At Niwot Ridge, further characterization of the chemical transformation involving mercury species within snowpacks was achieved by 3-months of continuous monitoring of GEM and ozone concentrations in the snow air at eight depths from the soil-snow interface to the top of the up to 2 meter deep snowpack. Divalent mercury concentrations were monitored as well (surface snow sampling and snow pits). GEM levels in snow air exhibited strong diurnal pattern indicative of both oxidation and reduction processes. Low levels of divalent mercury concentrations in snow pack suggest that large fractions of Hg originally deposited as wet deposition was reemitted back to the atmosphere after reduction. Hence, these results suggest that the presence of a seasonal snowpack may decrease effective wet deposition of mercury and

Validation of Satellite Snow Cover Maps in North America and Norway

Science.gov (United States)

Hall, Dorothy K.; Solberg, Rune; Riggs, George A.

2002-01-01

Satellite-derived snow maps from NASA's Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) have been produced since February of 2000. The global maps are available daily at 500-m resolution, and at a climate-modeling grid (CMG) resolution of 1/20 deg (approximately 5.6 km). We compared the 8-day composite CMG MODIS-derived global maps from November 1,2001, through March 21,2002, and daily CMG maps from February 26 - March 5,2002, with National Oceanic and Atmospheric Administration (NOAA) Interactive Multisensor Snow and Ice Mapping System (IMS) 25-km resolution maps for North America. For the Norwegian study area, national snow maps, based on synoptic measurements as well as visual interpretation of AVHRR images, published by the Det Norske Meteorologiske Institutt (Norwegian Meteorological Institute) (MI) maps, as well as Landsat ETM+ images were compared with the MODIS maps. The MODIS-derived maps agreed over most areas with the IMS or MI maps, however, there are important areas of disagreement between the maps, especially when the 8-day composite maps were used. It is concluded that MODIS daily CMG maps should be studied for validation purposes rather than the 8-day composite maps, despite the limitations imposed by cloud obscuration when using the daily maps.

Inhibition of Copper Pitting Corrosion in Aggressive Potable Waters

Directory of Open Access Journals (Sweden)

Emily Sarver

2012-01-01

Full Text Available Copper pitting corrosion can lead to premature plumbing failures, and can be caused by aggressive potable waters characterized by high pH, free chlorine residual and low alkalinity. In such waters and under continuous flow, certain inhibitors including phosphate, silica or natural organic matter may greatly reduce pitting occurrence. In the current work, 1 mg/L phosphate (as P completely prevented initiation of pits, and 5 mg/L silica (as Si significantly decelerated pitting. However, much lower doses of these inhibitors had little benefit and actually accelerated the rate of attack in some cases. Effects of organic matter were dependent on both the type (e.g., natural versus ozonated humic substances and dosage. Dose-response effects of free chlorine and alkalinity were also investigated. Based on electrochemical data, pits initiated more rapidly with increased free chlorine, but even moderate levels of chlorine (~0.4 mg/L eventually caused severe pitting. High alkalinity decreased pit propagation rates but did not prevent pit formation.

Interaction and Cooperative Nucleation of InAsSbP Quantum Dots and Pits on InAs(100 Substrate

Directory of Open Access Journals (Sweden)

Gambaryan Karen

2009-01-01

Full Text Available Abstract An example of InAsSbP quaternary quantum dots (QDs, pits and dots–pits cooperative structures’ growth on InAs(100 substrates by liquid phase epitaxy (LPE is reported. The interaction and surface morphology of the dots–pits combinations are investigated by the high-resolution scanning electron microscope. Bimodal growth mechanism for the both QDs and pits nucleation is observed. Cooperative structures consist of the QDs banded by pits, as well as the “large” pits banded by the quantum wires are detected. The composition of the islands and the pits edges is found to be quaternary, enriched by antimony and phosphorus, respectively. This repartition is caused by dissociation of the wetting layer, followed by migration (surface diffusion of the Sb and P atoms in opposite directions. The “small” QDs average density ranges from 0.8 to 2 × 109 cm−2, with heights and widths dimensions from 2 to 20 nm and 5 to 45 nm, respectively. The average density of the “small” pits is equal to (6–10 × 109 cm−2 with dimensions of 5–40 nm in width and depth. Lifshits–Slezov-like distribution for the amount and surface density of both “small” QDs and pits versus their average diameter is experimentally detected. A displacement of the absorption edge toward the long wavelength region and enlargement toward the short wavelength region is detected by the Fourier transform infrared spectrometry.

Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations

Science.gov (United States)

Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.

2012-12-01

Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea ice. Together these instruments provide data from which a wide range of sea ice properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent

Feedback mechanisms between snow and atmospheric mercury: Results and observations from field campaigns on the Antarctic plateau.

Science.gov (United States)

Spolaor, Andrea; Angot, Hélène; Roman, Marco; Dommergue, Aurélien; Scarchilli, Claudio; Vardè, Massimiliano; Del Guasta, Massimo; Pedeli, Xanthi; Varin, Cristiano; Sprovieri, Francesca; Magand, Olivier; Legrand, Michel; Barbante, Carlo; Cairns, Warren R L

2018-04-01

The Antarctic Plateau snowpack is an important environment for the mercury geochemical cycle. We have extensively characterized and compared the changes in surface snow and atmospheric mercury concentrations that occur at Dome C. Three summer sampling campaigns were conducted between 2013 and 2016. The three campaigns had different meteorological conditions that significantly affected mercury deposition processes and its abundance in surface snow. In the absence of snow deposition events, the surface mercury concentration remained stable with narrow oscillations, while an increase in precipitation results in a higher mercury variability. The Hg concentrations detected confirm that snowfall can act as a mercury atmospheric scavenger. A high temporal resolution sampling experiment showed that surface concentration changes are connected with the diurnal solar radiation cycle. Mercury in surface snow is highly dynamic and it could decrease by up to 90% within 4/6 h. A negative relationship between surface snow mercury and atmospheric concentrations has been detected suggesting a mutual dynamic exchange between these two environments. Mercury concentrations were also compared with the Br concentrations in surface and deeper snow, results suggest that Br could have an active role in Hg deposition, particularly when air masses are from coastal areas. This research presents new information on the presence of Hg in surface and deeper snow layers, improving our understanding of atmospheric Hg deposition to the snow surface and the possible role of re-emission on the atmospheric Hg concentration. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

Directory of Open Access Journals (Sweden)

X. Huang

2016-10-01

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

Flying Fast and High: Operational Flight Planning for Maximum Data Return for Airborne Snow Observatory Mountain Surveys

Science.gov (United States)

Berisford, D. F.; Painter, T. H.; Richardson, M.; Wallach, A.; Deems, J. S.; Bormann, K. J.

2017-12-01

The Airborne Snow Observatory (ASO - http://aso.jpl.nasa.gov) uses an airborne laser scanner to map snow depth, and imaging spectroscopy to map snow albedo in order to estimate snow water equivalent and melt rate over mountainous, hydrologic basin-scale areas. Optimization of planned flight lines requires the balancing of many competing factors, including flying altitude and speed, bank angle limitation, laser pulse rate and power level, flightline orientation relative to terrain, surface optical properties, and data output requirements. These variables generally distill down to cost vs. higher resolution data. The large terrain elevation variation encountered in mountainous terrain introduces the challenge of narrow swath widths over the ridgetops, which drive tight flightline spacing and possible dropouts over the valleys due to maximum laser range. Many of the basins flown by ASO exceed 3,000m of elevation relief, exacerbating this problem. Additionally, sun angle may drive flightline orientations for higher-quality spectrometer data, which may change depending on time of day. Here we present data from several ASO missions, both operational and experimental, showing the lidar performance and accuracy limitations for a variety of operating parameters. We also discuss flightline planning strategies to maximize data density return per dollar, and a brief analysis on the effect of short turn times/steep bank angles on GPS position accuracy.

Estimation of snow pollution in the region of non-ferrous metallurgy enterprises by the neutron activation method

International Nuclear Information System (INIS)

Khatamov, Sh.; Khamidova, R.; Kist, A.A.

1980-01-01

Possibility of determination of more than 25 chemical elements in snow water selected in the region of non-ferrous metallurgy enterprises has been shown using the methods of neutron activation and γ-spectrometry of high resolution. Elements were determined from one sample by three-fold irradiation in the nuclear reactor depending on the half-life period and other nuclear activation parameters of the formed radioisotopes. The analysis of snow cover has revealed the character of pollution of surrounding medium and air basin by toxical elements

High-Elevation Sierra Nevada Conifers Reveal Increasing Reliance on Snow Water with Changing Climate

Science.gov (United States)

Lepley, K. S.; Meko, D. M.; Touchan, R.; Shamir, E.; Graham, R.

2017-12-01

Snowpack in the Sierra Nevada Mountains accounts for around one third of California's water supply. Melting snow can provide water into dry summer months characteristic of the region's Mediterranean climate. As climate changes, understanding patterns of snowpack, snowmelt, and biological response are critical in this region of agricultural, recreational, and ecological value. Tree rings can act as proxy records to inform scientists and resource managers of past climate variability where instrumental data is unavailable. Here we investigate relationships between tree rings of high-elevation, snow-adapted conifer trees (Tsuga mertensiana, Abies magnifica) and April 1st snow-water equivalent (SWE) in the northern Sierra Nevada Mountains. The 1st principal component of 29 highly correlated regional SWE time series was modeled using multiple linear regression of four tree-ring chronologies including two lagged chronologies. Split-period verification analysis of this model revealed poor predictive skill in the early half (1929 - 1966) of the calibration period (1929 - 2003). Further analysis revealed a significant (p time. Snow water is becoming a more limiting resource to tree growth as average temperatures rise and the hydrologic regime shifts. These results highlight the need for resource managers and policy makers to consider that biological response to climate is not static.

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

Science.gov (United States)

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

2017-12-01

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

Inter-annual Variations in Snow/Firn Density over the Greenland Ice Sheet by Combining GRACE gravimetry and Envisat Altimetry

Science.gov (United States)

Su, X.; Shum, C. K.; Guo, J.; Howat, I.; Jezek, K. C.; Luo, Z.; Zhou, Z.

2017-12-01

Satellite altimetry has been used to monitor elevation and volume change of polar ice sheets since the 1990s. In order to derive mass change from the measured volume change, different density assumptions are commonly used in the research community, which may cause discrepancies on accurately estimating ice sheets mass balance. In this study, we investigate the inter-annual anomalies of mass change from GRACE gravimetry and elevation change from Envisat altimetry during years 2003-2009, with the objective of determining inter-annual variations of snow/firn density over the Greenland ice sheet (GrIS). High positive correlations (0.6 or higher) between these two inter-annual anomalies at are found over 93% of the GrIS, which suggests that both techniques detect the same geophysical process at the inter-annual timescale. Interpreting the two anomalies in terms of near surface density variations, over 80% of the GrIS, the inter-annual variation in average density is between the densities of snow and pure ice. In particular, at the Summit of Central Greenland, we validate the satellite data estimated density with the in situ data available from 75 snow pits and 9 ice cores. This study provides constraints on the currently applied density assumptions for the GrIS.

Assimilation and High Resolution Forecasts of Surface and Near Surface Conditions for the 2010 Vancouver Winter Olympic and Paralympic Games

Science.gov (United States)

Bernier, Natacha B.; Bélair, Stéphane; Bilodeau, Bernard; Tong, Linying

2014-01-01

A dynamical model was experimentally implemented to provide high resolution forecasts at points of interests in the 2010 Vancouver Olympics and Paralympics Region. In a first experiment, GEM-Surf, the near surface and land surface modeling system, is driven by operational atmospheric forecasts and used to refine the surface forecasts according to local surface conditions such as elevation and vegetation type. In this simple form, temperature and snow depth forecasts are improved mainly as a result of the better representation of real elevation. In a second experiment, screen level observations and operational atmospheric forecasts are blended to drive a continuous cycle of near surface and land surface hindcasts. Hindcasts of the previous day conditions are then regarded as today's optimized initial conditions. Hence, in this experiment, given observations are available, observation driven hindcasts continuously ensure that daily forecasts are issued from improved initial conditions. GEM-Surf forecasts obtained from improved short-range hindcasts produced using these better conditions result in improved snow depth forecasts. In a third experiment, assimilation of snow depth data is applied to further optimize GEM-Surf's initial conditions, in addition to the use of blended observations and forecasts for forcing. Results show that snow depth and summer temperature forecasts are further improved by the addition of snow depth data assimilation.

Snow farming: conserving snow over the summer season

Science.gov (United States)

Grünewald, Thomas; Wolfsperger, Fabian; Lehning, Michael

2018-01-01

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

A Decade of High-Resolution Arctic Sea Ice Measurements from Airborne Altimetry

Science.gov (United States)

Duncan, K.; Farrell, S. L.; Connor, L. N.; Jackson, C.; Richter-Menge, J.

2017-12-01

Satellite altimeters carried on board ERS-1,-2, EnviSat, ICESat, CryoSat-2, AltiKa and Sentinel-3 have transformed our ability to map the thickness and volume of the polar sea ice cover, on seasonal and decadal time-scales. The era of polar satellite altimetry has coincided with a rapid decline of the Arctic ice cover, which has thinned, and transitioned from a predominantly multi-year to first-year ice cover. In conjunction with basin-scale satellite altimeter observations, airborne surveys of the Arctic Ocean at the end of winter are now routine. These surveys have been targeted to monitor regions of rapid change, and are designed to obtain the full snow and ice thickness distribution, across a range of ice types. Sensors routinely deployed as part of NASA's Operation IceBridge (OIB) campaigns include the Airborne Topographic Mapper (ATM) laser altimeter, the frequency-modulated continuous-wave snow radar, and the Digital Mapping System (DMS). Airborne measurements yield high-resolution data products and thus present a unique opportunity to assess the quality and characteristics of the satellite observations. We present a suite of sea ice data products that describe the snow depth and thickness of the Arctic ice cover during the last decade. Fields were derived from OIB measurements collected between 2009-2017, and from reprocessed data collected during ad-hoc sea ice campaigns prior to OIB. Our bespoke algorithms are designed to accommodate the heterogeneous sea ice surface topography, that varies at short spatial scales. We assess regional and inter-annual variability in the sea ice thickness distribution. Results are compared to satellite-derived ice thickness fields to highlight the sensitivities of satellite footprints to the tails of the thickness distribution. We also show changes in the dynamic forcing shaping the ice pack over the last eight years through an analysis of pressure-ridge sail-height distributions and surface roughness conditions

PIT 9 Project: A private sector initiative

International Nuclear Information System (INIS)

Macdonald, D.W.; Hughes, F.P.; Burton, B.N.

1993-01-01

The Pit 9 Comprehensive Demonstration is intended to demonstrate a cost-effective approach to remediate an Idaho National Engineering Lab. (INEL) waste disposal pit through a Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Interim Action. The remediation will include additional requirements, if needed, to provide high confidence that only minor additional work would be necessary to accomplish the final closure as part of the overall final closure strategy for the INEL's Subsurface Disposal Area (SDA). Pit 9 is an inactive waste disposal pit located in the northeastern corner of the SDA at the INEL's Radioactive Waste Management Complex (RWMC). It covers approximately 1 acre. The waste within Pit 9 is primarily transuranic waste generated at the Rocky Flats Plant and additional wastes, both hazardous and low-level radioactive, from generators at the INEL

Pitting corrosion as a mixed system: coupled deterministic-probabilistic simulation of pit growth

Science.gov (United States)

Ibrahim, Israr B. M.; Fonna, S.; Pidaparti, R.

2018-05-01

Stochastic behavior of pitting corrosion poses a unique challenge in its computational analysis. However, it also stems from electrochemical activity causing general corrosion. In this paper, a framework for corrosion pit growth simulation based on the coupling of the Cellular Automaton (CA) and Boundary Element Methods (BEM) is presented. The framework assumes that pitting corrosion is controlled by electrochemical activity inside the pit cavity. The BEM provides the prediction of electrochemical activity given the geometrical data and polarization curves, while the CA is used to simulate the evolution of pit shapes based on electrochemical activity provided by BEM. To demonstrate the methodology, a sample case of local corrosion cells formed in pitting corrosion with varied dimensions and polarization functions is considered. Results show certain shapes tend to grow in certain types of environments. Some pit shapes appear to pose a higher risk by being potentially significant stress raisers or potentially increasing the rate of corrosion under the surface. Furthermore, these pits are comparable to commonly observed pit shapes in general corrosion environments.

Bacterial community structure in High-Arctic snow and freshwater as revealed by pyrosequencing of 16S rRNA genes and cultivation

Directory of Open Access Journals (Sweden)

Annette K. Møller

2013-04-01

Full Text Available The bacterial community structures in High-Arctic snow over sea ice and an ice-covered freshwater lake were examined by pyrosequencing of 16S rRNA genes and 16S rRNA gene sequencing of cultivated isolates. Both the pyrosequence and cultivation data indicated that the phylogenetic composition of the microbial assemblages was different within the snow layers and between snow and freshwater. The highest diversity was seen in snow. In the middle and top snow layers, Proteobacteria, Bacteroidetes and Cyanobacteria dominated, although Actinobacteria and Firmicutes were relatively abundant also. High numbers of chloroplasts were also observed. In the deepest snow layer, large percentages of Firmicutes and Fusobacteria were seen. In freshwater, Bacteroidetes, Actinobacteria and Verrucomicrobia were the most abundant phyla while relatively few Proteobacteria and Cyanobacteria were present. Possibly, light intensity controlled the distribution of the Cyanobacteria and algae in the snow while carbon and nitrogen fixed by these autotrophs in turn fed the heterotrophic bacteria. In the lake, a probable lower light input relative to snow resulted in low numbers of Cyanobacteria and chloroplasts and, hence, limited input of organic carbon and nitrogen to the heterotrophic bacteria. Thus, differences in the physicochemical conditions may play an important role in the processes leading to distinctive bacterial community structures in High-Arctic snow and freshwater.

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

Science.gov (United States)

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

2008-05-01

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

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

Science.gov (United States)

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

2017-12-01

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

Is Playing in the Pit Really the Pits?: Pain, Strength, Music Performance Anxiety, and Workplace Satisfaction in Professional Musicians in Stage, Pit, and Combined Stage/Pit Orchestras.

Science.gov (United States)

Kenny, Dianna T; Driscoll, Tim; Ackermann, Bronwen J

2016-03-01

Typically, Australian orchestral musicians perform on stage, in an orchestra pit, or in a combination of both workplaces. This study explored a range of physical and mental health indicators in musicians who played in these different orchestra types to ascertain whether orchestra environment was a risk factor affecting musician wellbeing. Participants comprised 380 full-time orchestral musicians from the eight major state orchestras in Australia comprised of two dedicated pit orchestras, three stage-only symphonic orchestras, and three mixed stage/pit orchestras. Participants completed a physical assessment and a range of self-report measures assessing performance-related musculoskeletal disorders (PRMD), physical characteristics including strength and perceived exertion, and psychological health, including music performance anxiety (MPA), workplace satisfaction, and bullying. Physical characteristics and performance-related musculoskeletal profiles were similar for most factors on the detailed survey completed by orchestra members. The exceptions were that pit musicians demonstrated greater shoulder and elbow strength, while mixed-workload orchestra musicians had greater flexibility Significantly more exertion was reported by pit musicians when rehearsing and performing. Stage/pit musicians reported less physical exertion when performing in the pit compared with performing on stage. Severity of MPA was significantly greater in pit musicians than mixed orchestra musicians. Pit musicians also reported more frequent bullying and lower job satisfaction compared with stage musicians. There were few differences in the objective physical measures between musicians in the different orchestra types. However, pit musicians appear more psychologically vulnerable and less satisfied with their work than musicians from the other two orchestra types. The physical and psychological characteristics of musicians who perform in different orchestra types have not been adequately

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

NARCIS (Netherlands)

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

2017-01-01

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

The Influence of Radiation on Pit Solution Chemistry as it Pertains to the Transition from Metastable to Stable Pitting in Steels

International Nuclear Information System (INIS)

Galuszka-Muga, Barbara; Muga, Luis M.

2006-01-01

Previous work relevant to current efforts is summarized. A description of an improved version of a new electrochemical probe, the ArtPit, is given. The distinct feature of the probe for investigating metastable pitting of carbon steels is specified and compared to other approaches. The electrochemical response of the ArtPit under the gamma irradiation and elevated temperature conditions that occur at high level waste (HLW) storage tanks is presented. In particular, the Tafel slope determinations and chemical analyses of the ArtPit confined volume electrolyte are described. Based on results a possible approach for reducing the corrosion rate of HLW tank walls is suggested. Additional statistical analysis of the occurrence of short duration (passivated pits) and long term (stable pitting) electrochemical pulses (current surges) during exposure confirm that radiation enhances the occurrence of both more and smaller sized pits due to increased likelihood of repassivation

Changes in Andes snow cover from MODIS data, 2000–2016

Directory of Open Access Journals (Sweden)

F. A. Saavedra

2018-03-01

Full Text Available The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS satellite sensors (500 m, 8-day maximum snow cover extent. This analysis is conducted between 8 and 36° S due to high frequency of cloud (>  30 % of the time south and north of this range. We ran Mann–Kendall and Theil–Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP  =  20 %. We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2 and University of Delaware datasets and climate indices as El Niño–Southern Oscillation (ENSO, Southern Annular Mode (SAM, and Pacific Decadal Oscillation (PDO. Areas north of 29° S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2 with persistent snow cover between 29 and 36° S experienced a significant loss of snow cover (2–5 fewer days of snow year−1. Snow loss was more pronounced (62 % of the area with significant trends on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10–30 m year−1 south of 29–30° S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31° S, whereas the SAM better predicted SP south of 31° S.

Quantifying forest mortality with the remote sensing of snow

Science.gov (United States)

Baker, Emily Hewitt

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

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

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

Science.gov (United States)

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

2017-12-01

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

Radiative effects of light-absorbing particles deposited in snow over Himalayas using WRF-Chem simulations

Science.gov (United States)

Sarangi, C.; Qian, Y.; Painter, T. H.; Liu, Y.; Lin, G.; Wang, H.

2017-12-01

Radiative forcing induced by light-absorbing particles (LAP) deposited on snow is an important surface forcing. It has been debated that an aerosol-induced increase in atmospheric and surface warming over Tibetan Plateau (TP) prior to the South Asian summer monsoon can have a significant effect on the regional thermodynamics and South Asian monsoon circulation. However, knowledge about the radiative effects due to deposition of LAP in snow over TP is limited. In this study we have used a high-resolution WRF-Chem (coupled with online chemistry and snow-LAP-radiation model) simulations during 2013-2014 to estimate the spatio-temporal variation in LAP deposition on snow, specifically black carbon (BC) and dust particles, in Himalayas. Simulated distributions in meteorology, aerosol concentrations, snow albedo, snow grain size and snow depth are evaluated against satellite and in-situ measurements. The spatio-temporal change in snow albedo and snow grain size with variation in LAP deposition is investigated and the resulting shortwave LAP radiative forcing at surface is calculated. The LAP-radiative forcing due to aerosol deposition, both BC and dust, is higher in magnitude over Himalayan slopes (terrain height below 4 km) compared to that over TP (terrain height above 4 km). We found that the shortwave aerosol radiative forcing efficiency at surface due to increase in deposited mass of BC particles in snow layer ( 25 (W/m2)/ (mg/m2)) is manifold higher than the efficiency of dust particles ( 0.1 (W/m2)/ (mg/m2)) over TP. However, the radiative forcing of dust deposited in snow is similar in magnitude (maximum 20-30 W/m2) to that of BC deposited in snow over TP. This is mainly because the amount of dust deposited in snow over TP can be about 100 times greater than the amount of BC deposited in snow during polluted conditions. The impact of LAP on surface energy balance, snow melting and atmospheric thermodynamics is also examined.

Simulation of snow distribution and melt under cloudy conditions in an Alpine watershed

Directory of Open Access Journals (Sweden)

H.-Y. Li

2011-07-01

Full Text Available An energy balance method and remote-sensing data were used to simulate snow distribution and melt in an alpine watershed in northwestern China within a complete snow accumulation-melt period. The spatial energy budgets were simulated using meteorological observations and a digital elevation model of the watershed. A linear interpolation method was used to estimate the daily snow cover area under cloudy conditions, using Moderate Resolution Imaging Spectroradiometer (MODIS data. Hourly snow distribution and melt, snow cover extent and daily discharge were included in the simulated results. The root mean square error between the measured snow-water equivalent samplings and the simulated results is 3.2 cm. The Nash and Sutcliffe efficiency statistic (NSE between the measured and simulated discharges is 0.673, and the volume difference (Dv is 3.9 %. Using the method introduced in this article, modelling spatial snow distribution and melt runoff will become relatively convenient.

Performance evaluation of snow and ice plows.

Science.gov (United States)

2015-11-01

Removal of ice and snow from road surfaces is a critical task in the northern tier of the United States, : including Illinois. Highways with high levels of traffic are expected to be cleared of snow and ice quickly : after each snow storm. This is ne...

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

Science.gov (United States)

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

2013-10-01

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

Factors influencing spring and summer areal snow ablation and snowcover depletion in alpine terrain: detailed measurements from the Canadian Rockies

OpenAIRE

Schirmer, Michael; Pomeroy, John W.

2018-01-01

The spatial distribution of snow water equivalent (SWE) and melt are important to estimating areal melt rates and snowcover depletion dynamics but are rarely measured in detail during the late ablation period. This study contributes the result of high resolution observations made using large numbers of sequential aerial photographs taken from an Unmanned Aerial Vehicle on an alpine ridge in the Fortress Mountain Snow Laboratory in the Canadian Rocky Mountains from May to July. With Structure-...

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

Science.gov (United States)

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

2013-12-01

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

Spatial considerations of snow chemistry as a non-point contamination source in Alpine watersheds

International Nuclear Information System (INIS)

Elder, K.; Williams, M.; Dozier, J.

1991-01-01

Alpine watersheds act as a temporary storage basin for large volumes of precipitation as snow. Monitoring these basins for the presence and effects of acid precipitation is important because these areas are often weakly buffered and sensitive to acidification. Study of these sensitive areas may provide early detection of trends resulting form anthropogenic atmospheric inputs. In an intensive study of an alpine watershed in the Sierra Nevada in 1987 and 1988, the authors carefully monitored snow distribution and chemistry through space and time. They found that the volume-weighted mean ionic concentrations within the snowpack did not vary greatly over the basin at peak accumulation. However, the distribution of total snow water equivalence (SWE) was highly variable spatially. Coefficients of variation (CV) for SWE lead to a corresponding high spatial variance in the chemical loading of their study basin. Their results show that to obtain accurate estimates of chemical loading they must measure the chemical and physical snow parameters at a resolution proportional to their individual variances. It is therefore necessary to combine many SWE measurements with fewer carefully obtained chemistry measurements. They used a classification method based on physical parameters to partition the basin into similar zones for estimation of SWE distribution. This technique can also be used for sample design

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

Science.gov (United States)

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

2017-12-01

high temporal resolution to investigate how hydrologic responses evolve in both space and time, data not available from operational networks.

Regional pattern of snow characteristics around Antarctic Lake Vostok

Science.gov (United States)

Vladimirova, Diana; Ekaykin, Alexey; Popov, Sergey; Shibaev, Yuriy; Kozachek, Anna; Lipenkov, Vladimir

2015-04-01

Since 1998 Russian Antarctic Expedition has organized several scientific traverses in the region of subglacial Lake Vostok mainly devoted to the radar echo and seismic sounding of the glacier and water (the results have been published elsewhere). Along with the geophysical studies, a number of glaciological investigations have been carried out: snow pit digging, installation of accumulation stakes, snow sampling to study the stable water isotope content. Here we for the first time present a synthesis of these works and demonstrate a series of maps that characterize the snow density, isotope content and accumulation rate the studied region. A general tendency of the snow accumulation rate and isotope content is a significant increase from south (south-west) to north (north-east) from 35 to 23 mm w.e. per year and from -53,3 ‰ to -57,3 ‰ for delta oxygen-18 respectively, which likely reflects the continental-scale pattern, i.e., increase from inland to the coast. Deuterium excess varies from 11,7 ‰ to 16,3 ‰ is negatively correlated with the isotope content, which is typical for central Antarctica. The snow density demonstrate different pattern: higher values offshore the lake (up to 0,356 g/cm^3), and lower values within the lake's shoreline (lower limit is 0,328 g/cm^3). We suggest that this is related to the katabatic wind activity: very flat nearly horizontal surface of the glacier above the lake is not favorable for the strong winds, which leads to lower surface snow density. Superimposed on the main trend is the regional pattern, namely, curved contour lines in the middle part of the lake. We suggest that it may be related to the local anomalies of the snow drift by wind. Indeed, on the satellite images of the lake one can easily see a snowdrift stretching from the lake's western shore downwind in the middle part of the lake. The isolines of delta oxygen-18 and deuterium excess become perpendicular to each other in the north part of the lake which also

Sustainable Environmental Protection Using Modified Pit-Latrines

NARCIS (Netherlands)

Chaggu, E.J.

2004-01-01

Pit-latrines are on-site excreta disposal facilities widely used as anaerobic accumulation system for stabilizing human wastes like excreta, both in rural and urban settlements of developing countries. Flooding of pit-latrines is often a common phenomenon, especially in situations of high water

Operational warnings issued by the SMC in the 8th March snow event in Catalonia

Science.gov (United States)

Vilaclara, E.; Segalà, S.; Andrés, A.; Aran, M.

2010-09-01

The snowfall event of 8th March 2010 was one of the most important of the last years in Catalonia, with high societal impact in the communication and in the power distribution. Since 2002, after an agreement between Meteorological Service of Catalonia (SMC) and Civil Protection authority, the SMC is the agency responsible to carry out meteorological warnings in Catalonia. These warnings are issued depending on the thresholds which are expected to be exceeded (three different probability degrees are defined), and are characterized by a high spatial and temporal resolution. In the snow event of 8th March, forecasting team of the SMC did the first meteorological warning three days before, on 5th March. During the two following days broadcasted four different warnings, taking into account the high probability of exceeding 2 cm of snow above 200 meters, 15 above 400 m and 30 above 800 m. Furthermore, the SMC disseminated also two special press releases with the aim to extend the forecast to the public. In the afternoon of Sunday, 7th March, the snow precipitation started in some areas of Catalonia. From this moment, the SMC followed the surveillance of situation with the remote sensing tools and the Meteorological Observers Network data. This network is formed by a hundred of spotters with mobile phones able to transmit observations in real time to our web site. This surveillance and the conceptual model of snow events in Catalonia allowed the forecasters to improve the estimation of the snow level forecasted by mesoscale meteorological models. In this event, the snow level obtained from these models was higher than the real one. In spite of the accuracy of the forecast, the impact was very important in Catalonia. On one hand, it was due to the exceptionality of the event, with 3 cm of snow in Barcelona in the afternoon of a working day. On the other hand, the large amount of wet snow precipitation (until 100 mm), and the wind, contributed to an important snow

CHerenkov detectors In mine PitS (CHIPS) Letter of Intent to FNAL

Energy Technology Data Exchange (ETDEWEB)

Adamson, P. [Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Austin, J. [Univ. of Minnesota, Duluth, MN (United States); Cao, S. V. [Univ. of Texas, Austin, TX (United States); Coelho, J. A. B. [Tufts Univ., Medford, MA (United States); Davies, G. S. [Iowa State Univ., Ames, IA (United States); Evans, J. J. [Univ. of Manchester (United Kingdom); Guzowski, P. [Univ. of Manchester (United Kingdom); Habig, A. [Univ. of Minnesota, Duluth, MN (United States); Holin, A. [Univ. College London, London (United Kingdom); Huang, J. [Univ. of Texas, Austin, TX (United States); Johnson, R. [Univ. of Cincinnati, OH (United States); St. John, J. [Univ. of Cincinnati, OH (United States); Kreymer, A. [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Kordosky, M. [College of William and Mary, Williamsburg, VA (United States); Lang, K. [Univ. of Texas, Austin, TX (United States); Marshak, M. L. [Univ. of Minnesota, Minneapolis, MN (United States); Mehdiyev, R. [Univ. of Texas, Austin, TX (United States); Meier, J. [Univ. of Minnesota, Minneapolis, MN (United States); Miller, W. [Univ. of Minnesota, Minneapolis, MN (United States); Naples, D. [Univ. of Pittsburgh, PA (United States); Nelson, J. K. [College of William and Mary, Williamsburg, VA (United States); Nichol, R. J. [Univ. College London, London (United Kingdom); Patterson, R. B. [California Inst. of Technology (CalTech), Pasadena, CA (United States); Paolone, V. [Univ. of Pittsburgh, PA (United States); Pawloski, G. [Univ. of Minnesota, Minneapolis, MN (United States); Perch, A. [Univ. College London, London (United Kingdom); Pfutzner, M. [Univ. College London, London (United Kingdom); Proga, M. [Univ. of Texas, Austin, TX (United States); Qian, X. [Brookhaven National Lab. (BNL), Upton, NY (United States); Radovic, A. [Univ. College London, London (United Kingdom); Sanchez, M. C. [Iowa State Univ., Ames, IA (United States); Schreiner, S. [Univ. of Minnesota, Minneapolis, MN (United States); Soldner-Rembold, S. [Univ. of Manchester (United Kingdom); Sousa, A. [Univ. of Cincinnati, OH (United States); Thomas, J. [Univ. College London, London (United Kingdom); Vahle, P. [College of William and Mary, Williamsburg, VA (United States); Wendt, C. [Univ. of Wisconsin, Madison, WI (United States); Whitehead, L. H. [Univ. College London, London (United Kingdom); Wojcicki, S. [Stanford Univ., CA (United States)

2013-12-30

This Letter of Intent outlines a proposal to build a large, yet cost-effective, 100 kton fiducial mass water Cherenkov detector that will initially run in the NuMI beam line. The CHIPS detector (CHerenkov detector In Mine PitS) will be deployed in a flooded mine pit, removing the necessity and expense of a substantial external structure capable of supporting a large detector mass. There are a number of mine pits in northern Minnesota along the NuMI beam that could be used to deploy such a detector. In particular, the Wentworth Pit 2W is at the ideal off-axis angle to contribute to the measurement of the CP violating phase. The detector is designed so that it can be moved to a mine pit in the LBNE beam line once that becomes operational.

Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models

Science.gov (United States)

Terzago, Silvia; von Hardenberg, Jost; Palazzi, Elisa; Provenzale, Antonello

2017-07-01

The estimate of the current and future conditions of snow resources in mountain areas would require reliable, kilometre-resolution, regional-observation-based gridded data sets and climate models capable of properly representing snow processes and snow-climate interactions. At the moment, the development of such tools is hampered by the sparseness of station-based reference observations. In past decades passive microwave remote sensing and reanalysis products have mainly been used to infer information on the snow water equivalent distribution. However, the investigation has usually been limited to flat terrains as the reliability of these products in mountain areas is poorly characterized.This work considers the available snow water equivalent data sets from remote sensing and from reanalyses for the greater Alpine region (GAR), and explores their ability to provide a coherent view of the snow water equivalent distribution and climatology in this area. Further we analyse the simulations from the latest-generation regional and global climate models (RCMs, GCMs), participating in the Coordinated Regional Climate Downscaling Experiment over the European domain (EURO-CORDEX) and in the Fifth Coupled Model Intercomparison Project (CMIP5) respectively. We evaluate their reliability in reproducing the main drivers of snow processes - near-surface air temperature and precipitation - against the observational data set EOBS, and compare the snow water equivalent climatology with the remote sensing and reanalysis data sets previously considered. We critically discuss the model limitations in the historical period and we explore their potential in providing reliable future projections.The results of the analysis show that the time-averaged spatial distribution of snow water equivalent and the amplitude of its annual cycle are reproduced quite differently by the different remote sensing and reanalysis data sets, which in fact exhibit a large spread around the ensemble mean. We

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.

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

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

Directory of Open Access Journals (Sweden)

C. Mitterer

2013-02-01

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

Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

International Nuclear Information System (INIS)

Valor, A.; Caleyo, F.; Alfonso, L.; Rivas, D.; Hallen, J.M.

2007-01-01

In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion

Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

Energy Technology Data Exchange (ETDEWEB)

Valor, A. [Facultad de Fisica, Universidad de La Habana, San Lazaro y L, Vedado, 10400 Havana (Cuba); Caleyo, F. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico)]. E-mail: fcaleyo@gmail.com; Alfonso, L. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico); Rivas, D. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico); Hallen, J.M. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico)

2007-02-15

In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion.

Tracking Snow Variations in the Northern Hemisphere Using Multi-Source Remote Sensing Data (2000–2015

Directory of Open Access Journals (Sweden)

Yunlong Wang

2018-01-01

Full Text Available Multi-source remote sensing data were used to generate 500-m resolution cloud-free daily snow cover images for the Northern Hemisphere. Simultaneously, the spatial and temporal dynamic variations of snow in the Northern Hemisphere were evaluated from 2000 to 2015. The results indicated that (1 the maximum, minimum, and annual average snow-covered area (SCA in the Northern Hemisphere exhibited a fluctuating downward trend; the variation of snow cover in the Northern Hemisphere had well-defined inter-annual and regional differences; (2 the average SCA in the Northern Hemisphere was the largest in January and the smallest in August; the SCA exhibited a downward trend for the monthly variations from February to April; and the seasonal variation in the SCA exhibited a downward trend in the spring, summer, and fall in the Northern Hemisphere (no pronounced variation trend in the winter was observed during the 2000–2015 period; (3 the spatial distribution of the annual average snow-covered day (SCD was related to the latitudinal zonality, and the areas exhibiting an upward trend were mainly at the mid to low latitudes with unstable SCA variations; and (4 the snow reduction was significant in the perennial SCA in the Northern Hemisphere, including high-latitude and high-elevation mountainous regions (between 35° and 50°N, such as the Tibetan Plateau, the Tianshan Mountains, the Pamir Plateau in Asia, the Alps in Europe, the Caucasus Mountains, and the Cordillera Mountains in North America.

Effect of pH and chloride on the micro-mechanism of pitting corrosion for high strength pipeline steel in aerated NaCl solutions

International Nuclear Information System (INIS)

Wang, Yafei; Cheng, Guangxu; Wu, Wei; Qiao, Qiao; Li, Yun; Li, Xiufeng

2015-01-01

Highlights: • Pitting behavior of X80 steel in aerated NaCl solutions is studied systematically. • Unique large pit morphology is observed in neutral/acidic NaCl solutions. • In low pH solutions, pit will propagate in the horizontal direction, leading to the shallow shape of pitting morphology; in high pH solutions, the pit sizes are much smaller. • Film growth, which is dependent on the pH and chloride concentration, has great influence on the cathodic reaction by affecting oxygen diffusion process. - Abstract: The pitting corrosion mechanism of high strength pipeline steel in aerated NaCl solutions with different pH and chloride content was investigated, using potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) and scanning electron microscope (SEM). The pitting behavior in alkaline solutions was found to be significantly different from that in neutral and acidic solutions. Electrochemical results and SEM images indicate that the product film formed on the steel surface results in different corrosion behavior in an alkaline solution. SEM images show that pH and chloride concentration in the bulk solution have a great influence on the pitting morphology. Unique large pit morphology due to corrosion in neutral/acidic solutions with 0.05 mol/L NaCl was observed. The relationship between solution pH and the effect of chloride concentration is also discussed

Corrosion Resistance and Pitting Behaviour of Low-Carbon High-Mn Steels in Chloride Solution

Directory of Open Access Journals (Sweden)

Grajcar A.

2016-06-01

Full Text Available Corrosion resistance of the X4MnSiAlNbTi27-4-2 and X6MnSiAlNbTi26-3-3 type austenitic steels, after hot deformation as well as after cold rolling, were evaluated in 3.5% NaCl solution using potentiodynamic polarization tests. A type of nonmetallic inclusions and their pitting corrosion behaviour were investigated. Additionally, the effect of cold deformation on the corrosion resistance of high-Mn steels was studied. The SEM micrographs revealed that corrosion damage formed in both investigated steels is characterized by various shapes and an irregular distribution at the metallic matrix, independently on the steel state (thermomechanically treated or cold worked. Corrosion pits are generated both in grain interiors, grain boundaries and along the deformation bands. Moreover, corrosion damage is stronger in cold deformed steels in comparison to the thermomechanically treated specimens. EDS analysis revealed that corrosion pits preferentially nucleated on MnS and AlN inclusions or complex oxysulphides. The morphology of corrosion damage in 3.5% NaCl supports the data registered in potentiodynamic tests.

High-resolution dynamic downscaling of CMIP5 output over the Tropical Andes

Science.gov (United States)

Reichler, Thomas; Andrade, Marcos; Ohara, Noriaki

2015-04-01

Our project is targeted towards making robust predictions of future changes in climate over the tropical part of the South American Andes. This goal is challenging, since tropical lowlands, steep mountains, and snow covered subarctic surfaces meet over relatively short distances, leading to distinct climate regimes within the same domain and pronounced spatial gradients in virtually every climate quantity. We use an innovative approach to solve this problem, including several quadruple nested versions of WRF, a systematic validation strategy to find the version of WRF that best fits our study region, spatial resolutions at the kilometer scale, 20-year-long simulation periods, and bias-corrected output from various CMIP5 simulations that also include the multi-model mean of all CMIP5 models. We show that the simulated changes in climate are consistent with the results from the global climate models and also consistent with two different versions of WRF. We also discuss the expected changes in snow and ice, derived from off-line coupling the regional simulations to a carefully calibrated snow and ice model.

Diversity and characterization of mercury-resistant bacteria in snow, freshwater and sea-ice brine from the High Arctic

DEFF Research Database (Denmark)

Møller, Annette; Barkay, Tamar; Abu Al-Soud, Waleed

2011-01-01

It is well-established that atmospheric deposition transports mercury from lower latitudes to the Arctic. The role of bacteria in the dynamics of the deposited mercury, however, is unknown. We characterized mercury-resistant bacteria from High Arctic snow, freshwater and sea-ice brine. Bacterial...... densities were 9.4 × 10(5), 5 × 10(5) and 0.9-3.1 × 10(3) cells mL(-1) in freshwater, brine and snow, respectively. Highest cultivability was observed in snow (11.9%), followed by freshwater (0.3%) and brine (0.03%). In snow, the mercury-resistant bacteria accounted for up to 31% of the culturable bacteria, but...

Bacterial community structure in High-Arctic snow and freshwater as revealed by pyrosequencing of 16S rRNA genes and cultivation

DEFF Research Database (Denmark)

Møller, Annette K.; Søborg, Ditte A.; Abu Al-Soud, Waleed

2013-01-01

of the microbial assemblages was different within the snow layers and between snow and freshwater. The highest diversity was seen in snow. In the middle and top snow layers, Proteobacteria, Bacteroidetes and Cyanobacteria dominated, although Actinobacteria and Firmicutes were relatively abundant also. High numbers...... of chloroplasts were also observed. In the deepest snow layer, large percentages of Firmicutes and Fusobacteria were seen. In freshwater, Bacteroidetes, Actinobacteria and Verrucomicrobia were the most abundant phyla while relatively few Proteobacteria and Cyanobacteria were present. Possibly, light intensity...

Spatial and temporal variability in seasonal snow density

KAUST Repository

Bormann, Kathryn J.

2013-03-01

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

Spatial and temporal variability in seasonal snow density

KAUST Repository

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

2013-01-01

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

Variability of {sup 10}Be and {delta}{sup 18}O in snow pits from Greenland and a surface traverse from Antarctica

Energy Technology Data Exchange (ETDEWEB)

Berggren, A.-M. [Dept. of Earth Sciences, Uppsala University, Villav. 16, 752 36 Uppsala (Sweden); Aldahan, A., E-mail: ala.aldahan@geo.uu.se [Dept. of Earth Sciences, Uppsala University, Villav. 16, 752 36 Uppsala (Sweden); Dept. of Geology, United Arab Emirates University, P.O. Box 17551 Al Ain (United Arab Emirates); Possnert, G. [Tandem Laboratory, Uppsala University, P.O. Box 529, 751 20 Uppsala (Sweden); Hansson, M. [Dept. of Physical Geography and Quaternary Geology, Stockholm University, 106 91 Stockholm (Sweden); Steen-Larsen, H.C. [Centre for Ice and Climate, Niels Bohr Institute, University of Copenhagen, Juliane Maries Vej, 30,2100 Copenhagen (Denmark); Sturevik Storm, A. [Dept. of Earth Sciences, Uppsala University, Villav. 16, 752 36 Uppsala (Sweden); Moerth, C.-M. [Dept. of Geology and Geochemistry, Stockholm University, 106 91 Stockholm (Sweden); Murad, A. [Dept. of Geology, United Arab Emirates University, P.O. Box 17551 Al Ain (United Arab Emirates)

2013-01-15

To examine temporal variability of {sup 10}Be in glacial ice, we sampled snow to a depth of 160 cm at the NEEM (North Greenland Eemian Ice Drilling) drilling site in Greenland. The samples span three years between the summers of 2006 and 2009. At the same time, spatial variability of {sup 10}Be in glacial ice was explored through collection of the upper {approx}5 cm of surface snow in Antarctica during part of the Swedish-Japanese traverse from Svea to Syowa station during the austral summer in 2007-2008. The results of the Greenlandic {sup 10}Be snow suggested variable concentrations that apparently do not clearly reflect the seasonal change as indicated by the {delta}{sup 18}O data. The {sup 10}Be concentration variability most likely reflects also effects of aerosol loading and deposition pathways, possibly in combination with post-depositional processes. The Antarctic traverse data expose a negative correlation between {sup 10}Be and {delta}{sup 18}O, while there are weaker but still significant correlations to altitude and distance to the coast (approximated by the distance to the 70th latitude). These relationships indicate that geographical factors, mainly the proximity to the coast, may strongly affect {sup 10}Be concentrations in snow in Queen Maud Land, Antarctica.

Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models

Directory of Open Access Journals (Sweden)

S. Terzago

2017-07-01

Full Text Available The estimate of the current and future conditions of snow resources in mountain areas would require reliable, kilometre-resolution, regional-observation-based gridded data sets and climate models capable of properly representing snow processes and snow–climate interactions. At the moment, the development of such tools is hampered by the sparseness of station-based reference observations. In past decades passive microwave remote sensing and reanalysis products have mainly been used to infer information on the snow water equivalent distribution. However, the investigation has usually been limited to flat terrains as the reliability of these products in mountain areas is poorly characterized.This work considers the available snow water equivalent data sets from remote sensing and from reanalyses for the greater Alpine region (GAR, and explores their ability to provide a coherent view of the snow water equivalent distribution and climatology in this area. Further we analyse the simulations from the latest-generation regional and global climate models (RCMs, GCMs, participating in the Coordinated Regional Climate Downscaling Experiment over the European domain (EURO-CORDEX and in the Fifth Coupled Model Intercomparison Project (CMIP5 respectively. We evaluate their reliability in reproducing the main drivers of snow processes – near-surface air temperature and precipitation – against the observational data set EOBS, and compare the snow water equivalent climatology with the remote sensing and reanalysis data sets previously considered. We critically discuss the model limitations in the historical period and we explore their potential in providing reliable future projections.The results of the analysis show that the time-averaged spatial distribution of snow water equivalent and the amplitude of its annual cycle are reproduced quite differently by the different remote sensing and reanalysis data sets, which in fact exhibit a large spread around

Comparison of high-resolution magnification narrow-band imaging and white-light endoscopy in the prediction of histology in Barrett's oesophagus.

Science.gov (United States)

Singh, Rajvinder; Karageorgiou, Haris; Owen, Victoria; Garsed, Klara; Fortun, Paul J; Fogden, Edward; Subramaniam, Venkataraman; Shonde, Anthony; Kaye, Philip; Hawkey, Christopher J; Ragunath, Krish

2009-01-01

To evaluate whether there is any appreciable difference in imaging characteristics between high-resolution magnification white-light endoscopy (WLE-Z) and narrow-band imaging (NBI-Z) in Barrett's oesophagus (BE) and if this translates into superior prediction of histology. This was a prospective single-centre study involving 21 patients (75 areas, corresponding NBI-Z and WLE-Z images) with BE. Mucosal patterns (pit pattern and microvascular morphology) were evaluated for their image quality on a visual analogue scale (VAS) of 1-10 by five expert endoscopists. The endoscopists then predicted mucosal morphology based on four subtypes which can be visualized in BE. Type A: round pits, regular microvasculature; type B: villous/ridge pits, regular microvasculature; type C: absent pits, regular microvasculature; type D: distorted pits, irregular microvasculature. The sensitivity (Sn), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV) and accuracy (Acc) were then compared with the final histopathological analysis and the interobserver variability calculated. The overall pit and microvasculature quality was significantly higher for NBI-Z, pit: NBI-Z=6, WLE-Z=4.5, p < 0.001; microvasculature: NBI-Z=7.3, WLE-Z=4.9, p < 0.001. This translated into a superior prediction of histology (Sn: NBI-Z: 88.9, WLE-Z: 71.9, p < 0.001). For the prediction of dysplasia, NBI-Z was superior to WLE-Z (chi(2)=10.3, p < 0.05). The overall kappa agreement among the five endoscopists for NBI-Z and WLE-Z, respectively, was 0.59 and 0.31 (p < 0.001). NBI-Z is superior to WLE-Z in the prediction of histology in BE, with good reproducibility. This novel imaging modality could be an important tool for surveillance of patients with BE.

Can High-resolution WRF Simulations Be Used for Short-term Forecasting of Lightning?

Science.gov (United States)

Goodman, S. J.; Lapenta, W.; McCaul, E. W., Jr.; LaCasse, K.; Petersen, W.

2006-01-01

A number of research teams have begun to make quasi-operational forecast simulations at high resolution with models such as the Weather Research and Forecast (WRF) model. These model runs have used horizontal meshes of 2-4 km grid spacing, and thus resolved convective storms explicitly. In the light of recent global satellite-based observational studies that reveal robust relationships between total lightning flash rates and integrated amounts of precipitation-size ice hydrometeors in storms, it is natural to inquire about the capabilities of these convection-resolving models in representing the ice hydrometeor fields faithfully. If they do, this might make operational short-term forecasts of lightning activity feasible. We examine high-resolution WRF simulations from several Southeastern cases for which either NLDN or LMA lightning data were available. All the WRF runs use a standard microphysics package that depicts only three ice species, cloud ice, snow and graupel. The realism of the WRF simulations is examined by comparisons with both lightning and radar observations and with additional even higher-resolution cloud-resolving model runs. Preliminary findings are encouraging in that they suggest that WRF often makes convective storms of the proper size in approximately the right location, but they also indicate that higher resolution and better hydrometeor microphysics would be helpful in improving the realism of the updraft strengths, reflectivity and ice hydrometeor fields.

A Method for Snow Reanalysis: The Sierra Nevada (USA) Example

Science.gov (United States)

Girotto, Manuela; Margulis, Steven; Cortes, Gonzalo; Durand, Michael

2017-01-01

This work presents a state-of-the art methodology for constructing snow water equivalent (SWE) reanalysis. The method is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series. This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data from the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlation greater than 0.95 compared with in situ SWE observations. The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (31 years), and accuracy provide a unique dataset for investigating snow processes. This presentation illustrates how the reanalysis dataset was used to provide a basic accounting of the stored snowpack water in the Sierra Nevada over the last 31 years and ultimately improve real-time streamflow predictions.

Snow fraction products evaluation with Landsat-8/OLI data and its spatial scale effects over the Tibetan Plateau

Science.gov (United States)

Jiang, L.

2016-12-01

Snow cover is one of important elements in the water supply of large populations, especially in those downstream from mountainous watershed. The cryosphere process in the Tibetan Plateau is paid much attention due to rapid change of snow amount and cover extent. Snow mapping from MODIS has been increased attention in the study of climate change and hydrology. But the lack of intensive validation of different snow mapping methods especially at Tibetan Plateau hinders its application. In this work, we examined three MODIS snow products, including standard MODIS fractional snow product (MOD10A1) (Kaufman et al., 2002; Salomonson & Appel, 2004, 2006), two other fractional snow product, MODSCAG (Painter et al., 2009) and MOD_MESMA (Shi, 2012). Both these two methods are based on spectral mixture analysis. The difference between MODISCAG and MOD_MESMA was the endmember selection. For MODSCAG product, snow spectral endmembers of varying grain size was obtained both from a radiative transfer model and spectra of vegetation, rock and soil collected in the field and laboratory. MOD_MESMA was obtained from automated endmember extraction method using linear spectral mixture analysis. Its endmembers are selected in each image to enhance the computational efficiency of MESMA (Multiple Endmember Spectral Analysis). Landsat-8 Operatinal Land Imager (OLI) data from 2013-2015 was used to evaluate the performance of these three snow fraction products in Tibetan Plateau. The effect of land cover types including forest, grass and bare soil was analyzed to evaluate three products. In addition, the effects of relatively flat surface in internal plateau and high mountain areas of Himalaya were also evaluated on the impact of these snow fraction products. From our comparison, MODSCAG and MOD10A1 overestimated snow cover, while MOD_MESMA underestimated snow cover. And RMSE of MOD_MESMA at each land cover type including forest, grass and mountain area decreased with the spatial resolution

Inducing Water Productivity from Snow Cover for Sustainable Water Management in Ibrahim River Basin, Lebanon

OpenAIRE

Darwish , Talal; SHABAN , Amin; Portoghese , Ivan; Vurro , Michele; Khadra , Roula; Saqallah , Sagedah; Drapeau , Laurent; Gascoin , Simon; Amacha , Nabil

2015-01-01

International audience; The aim of this paper is to explore the effects and linkages between snow cover areas, distribution, probability and measured water discharge along east Mediterranean coastal watershed using moderate-resolution satellite images (MODIS-Terra). The Nahr Ibrahim River is a typical Lebanese watershed with an area of 326 km2 stretching between the sea and mountainous terrain to the east. The largest snow cover often exists in January-February with snow-free conditions betwe...

Modeling pitting corrosion damage of high-level radioactive-waste containers, with emphasis on the stochastic approach

Energy Technology Data Exchange (ETDEWEB)

Henshall, G.A.; Halsey, W.G.; Clarke, W.L.; McCright, R.D.

1993-01-01

Recent efforts to identify methods of modeling pitting corrosion damage of high-level radioactive-waste containers are described. The need to develop models that can provide information useful to higher level system performance assessment models is emphasized, and examples of how this could be accomplished are described. Work to date has focused upon physically-based phenomenological stochastic models of pit initiation and growth. These models may provide a way to distill information from mechanistic theories in a way that provides the necessary information to the less detailed performance assessment models. Monte Carlo implementations of the stochastic theory have resulted in simulations that are, at least qualitatively, consistent with a wide variety of experimental data. The effects of environment on pitting corrosion have been included in the model using a set of simple phenomenological equations relating the parameters of the stochastic model to key environmental variables. The results suggest that stochastic models might be useful for extrapolating accelerated test data and for predicting the effects of changes in the environment on pit initiation and growth. Preliminary ideas for integrating pitting models with performance assessment models are discussed. These ideas include improving the concept of container ``failure``, and the use of ``rules-of-thumb`` to take information from the detailed process models and provide it to the higher level system and subsystem models. Finally, directions for future work are described, with emphasis on additional experimental work since it is an integral part of the modeling process.

Modeling pitting corrosion damage of high-level radioactive-waste containers, with emphasis on the stochastic approach

International Nuclear Information System (INIS)

Henshall, G.A.; Halsey, W.G.; Clarke, W.L.; McCright, R.D.

1993-01-01

Recent efforts to identify methods of modeling pitting corrosion damage of high-level radioactive-waste containers are described. The need to develop models that can provide information useful to higher level system performance assessment models is emphasized, and examples of how this could be accomplished are described. Work to date has focused upon physically-based phenomenological stochastic models of pit initiation and growth. These models may provide a way to distill information from mechanistic theories in a way that provides the necessary information to the less detailed performance assessment models. Monte Carlo implementations of the stochastic theory have resulted in simulations that are, at least qualitatively, consistent with a wide variety of experimental data. The effects of environment on pitting corrosion have been included in the model using a set of simple phenomenological equations relating the parameters of the stochastic model to key environmental variables. The results suggest that stochastic models might be useful for extrapolating accelerated test data and for predicting the effects of changes in the environment on pit initiation and growth. Preliminary ideas for integrating pitting models with performance assessment models are discussed. These ideas include improving the concept of container ''failure'', and the use of ''rules-of-thumb'' to take information from the detailed process models and provide it to the higher level system and subsystem models. Finally, directions for future work are described, with emphasis on additional experimental work since it is an integral part of the modeling process

Evaluating the performance of coupled snow-soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site

Science.gov (United States)

Barrere, Mathieu; Domine, Florent; Decharme, Bertrand; Morin, Samuel; Vionnet, Vincent; Lafaysse, Matthieu

2017-09-01

Climate change projections still suffer from a limited representation of the permafrost-carbon feedback. Predicting the response of permafrost temperature to climate change requires accurate simulations of Arctic snow and soil properties. This study assesses the capacity of the coupled land surface and snow models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-Interim reanalyses were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal insulance are examined to determine the critical variables involved in the soil and snow thermal regime. Simulated soil properties are compared to measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are unrealistic, which is most likely caused by the lack of representation in snow models of the upward water vapor fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by adequately representing surface organic layers, i.e., mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces an excessively rapid heat transfer between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate change.

Spatial distributions of soluble salts in surface snow of East Antarctica

Directory of Open Access Journals (Sweden)

Yoshinori Iizuka

2016-07-01

Full Text Available To better understand how sea salt reacts in surface snow of Antarctica, we collected and identified non-volatile particles in surface snow along a traverse in East Antarctica. Samples were obtained during summer 2012/2013 from coastal to inland regions within 69°S to 80°S and 39°E to 45°E, a total distance exceeding 800 km. The spatial resolution of samples is about one sample per latitude between 1500 and 3800 m altitude. Here, we obtain the atomic ratios of Na, S and Cl, and calculate the masses of sodium sulphate and sodium chloride. The results show that, even in the coast snow sample (69°S, sea salt is highly modified by acid (HNO3 or H2SO4. The fraction of sea salt that reacts with acid increases in the region from 70°S to 74°S below 3000 m a.s.l., where some NaCl remains. At the higher altitudes (above 3300 m a.s.l. in the inland region (74°S to 80°S, the reaction uses almost all of the available NaCl.

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

OpenAIRE

Prozhorina Tatyana Ivanovna; Bespalova Elena Vladimirovna; Yakunina Nadezhda

2014-01-01

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

A probability distribution model of tooth pits for evaluating time-varying mesh stiffness of pitting gears

Science.gov (United States)

Lei, Yaguo; Liu, Zongyao; Wang, Delong; Yang, Xiao; Liu, Huan; Lin, Jing

2018-06-01

Tooth damage often causes a reduction in gear mesh stiffness. Thus time-varying mesh stiffness (TVMS) can be treated as an indication of gear health conditions. This study is devoted to investigating the mesh stiffness variations of a pair of external spur gears with tooth pitting, and proposes a new model for describing tooth pitting based on probability distribution. In the model, considering the appearance and development process of tooth pitting, we model the pitting on the surface of spur gear teeth as a series of pits with a uniform distribution in the direction of tooth width and a normal distribution in the direction of tooth height, respectively. In addition, four pitting degrees, from no pitting to severe pitting, are modeled. Finally, influences of tooth pitting on TVMS are analyzed in details and the proposed model is validated by comparing with a finite element model. The comparison results show that the proposed model is effective for the TVMS evaluations of pitting gears.

Analysis of snow bidirectional reflectance from ARCTAS Spring-2008 Campaign

Directory of Open Access Journals (Sweden)

A. Lyapustin

2010-05-01

Full Text Available The spring 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS experiment was one of major intensive field campaigns of the International Polar Year aimed at detailed characterization of atmospheric physical and chemical processes in the Arctic region. A part of this campaign was a unique snow bidirectional reflectance experiment on the NASA P-3B aircraft conducted on 7 and 15 April by the Cloud Absorption Radiometer (CAR jointly with airborne Ames Airborne Tracking Sunphotometer (AATS and ground-based Aerosol Robotic Network (AERONET sunphotometers. The CAR data were atmospherically corrected to derive snow bidirectional reflectance at high 1° angular resolution in view zenith and azimuthal angles along with surface albedo. The derived albedo was generally in good agreement with ground albedo measurements collected on 15 April. The CAR snow bidirectional reflectance factor (BRF was used to study the accuracy of analytical Ross-Thick Li-Sparse (RTLS, Modified Rahman-Pinty-Verstraete (MRPV and Asymptotic Analytical Radiative Transfer (AART BRF models. Except for the glint region (azimuthal angles φ<40°, the best fit MRPV and RTLS models fit snow BRF to within ±0.05. The plane-parallel radiative transfer (PPRT solution was also analyzed with the models of spheres, spheroids, randomly oriented fractal crystals, and with a synthetic phase function. The latter merged the model of spheroids for the forward scattering angles with the fractal model in the backscattering direction. The PPRT solution with synthetic phase function provided the best fit to measured BRF in the full range of angles. Regardless of the snow grain shape, the PPRT model significantly over-/underestimated snow BRF in the glint/backscattering regions, respectively, which agrees with other studies. To improve agreement with experiment, we introduced a model of macroscopic snow surface roughness by averaging the PPRT solution over the

Analysis of Snow Bidirectional Reflectance from ARCTAS Spring-2008 Campaign

Science.gov (United States)

Lyapustin, A.; Gatebe, C. K.; Redemann, J.; Kahn, R.; Brandt, R.; Russell, P.; King, M. D.; Pedersen, C. A.; Gerland, S.; Poudyal, R.;

Review of ice and snow runway pavements

Directory of Open Access Journals (Sweden)

Greg White

2018-05-01

Full Text Available Antarctica is the highest, driest, coldest, windiest, most remote and most pristine place on Earth. Polar operations depend heavily on air transportation and support for personnel and equipment. It follows that improvement in snow and ice runway design, construction and maintenance will directly benefit polar exploration and research. Current technologies and design methods for snow and ice runways remain largely reliant on work performed in the 1950s and 1960s. This paper reviews the design and construction of polar runways using snow and ice as geomaterials. The inability to change existing snow and ice thickness or temperature creates a challenge for polar runway design and construction, as does the highly complex mechanical behaviour of snow, including the phenomena known as sintering. It is recommended that a modern approach be developed for ice and snow runway design, based on conventional rigid and flexible pavement design principles. This requires the development on an analytical model for the prediction of snow strength, based on snow age, temperature history and density. It is also recommended that the feasibility of constructing a snow runway at the South Pole be revisited, in light of contemporary snow sintering methods. Such a runway would represent a revolutionary advance for the logistical support of Antarctic research efforts. Keywords: Runway, Pavement, Snow, Ice, Antarctic

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

Science.gov (United States)

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

2017-04-01

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

SWEAT: Snow Water Equivalent with AlTimetry

Science.gov (United States)

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

2017-04-01

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

Response of alpine vegetation growth dynamics to snow cover phenology on the Tibetan Plateau

Science.gov (United States)

Wang, X.; Wu, C.

2017-12-01

Alpine vegetation plays a crucial role in global energy cycles with snow cover, an essential component of alpine land cover showing high sensitivity to climate change. The Tibetan Plateau (TP) has a typical alpine vegetation ecosystem and is rich of snow resources. With global warming, the snow of the TP has undergone significant changes that will inevitably affect the growth of alpine vegetation, but observed evidence of such interaction is limited. In particular, a comprehensive understanding of the responses of alpine vegetation growth to snow cover variability is still not well characterized on TP region. To investigate this, we calculated three indicators, the start (SOS) and length (LOS) of growing season, and the maximum of normalized difference vegetation index (NDVImax) as proxies of vegetation growth dynamics from the Moderate Resolution Imaging Spectroradiometer (MODIS) data for 2000-2015. Snow cover duration (SCD) and melt (SCM) dates were also extracted during the same time frame from the combination of MODIS and the Interactive Multi-sensor Snow and Ice Mapping System (IMS) data. We found that the snow cover phenology had a strong control on alpine vegetation growth dynamics. Furthermore, the responses of SOS, LOS and NDVImax to snow cover phenology varied among plant functional types, eco-geographical zones, and temperature and precipitation gradients. The alpine steppes showed a much stronger negative correlation between SOS and SCD, and also a more evidently positive relationship between LOS and SCD than other types, indicating a longer SCD would lead to an earlier SOS and longer LOS. Most areas showed positive correlation between SOS and SCM, while a contrary response was also found in the warm but drier areas. Both SCD and SCM showed positive correlations with NDVImax, but the relationship became weaker with the increase of precipitation. Our findings provided strong evidences between vegetation growth and snow cover phenology, and changes in

Tank Riser Pit Decontamination System (Pit Viper) Return on Investment and Break-Even Analysis

International Nuclear Information System (INIS)

Young, Joan K.; Weimar, Mark R.; Balducci, Patrick J.; Fassbender, Linda L.; Hernandez, Melissa

2003-01-01

This study assessed the cost benefit of Pit Viper deployment for 80 tank farm pits between October 1, 2003 and September 30, 2012 under the technical baseline for applicable double-shell tank (DST) and single-shell tank (SST) projects. After this assessment had been completed, the U.S. Department of Energy (DOE) Richland Operations Office (RL) and Office of River Protection (ORP) published the Hanford Performance Management Plan (August 2003), which accelerated the schedule for SST retrieval. Then, DOE/CH2M HILL contract modification M064 (October 2002) and The Integrated Mission Acceleration Plan (March 2003) further accelerated SST retrieval and closure schedules. Twenty-six to 40 tanks must be retrieved by 2006. Thus the schedule for SST pit entries is accelerated and the number of SST pit entries is increased. This study estimates the return on investment (ROI) and the number of pits where Pit Viper deployment would break even or save money over current manual practices. The results of the analysis indicate a positive return on the federal investment for deployment of the Pit Viper provided it is used on a sufficient number of pits

W-12 valve pit decontamination demonstration

International Nuclear Information System (INIS)

Benson, C.E.; Parfitt, J.E.; Patton, B.D.

1995-12-01

Waste tank W-12 is a tank in the ORNL Low-Level Liquid Waste (LLLW) system that collected waste from Building 3525. Because of a leaking flange in the discharge line from W-12 to the evaporator service tank (W-22) and continual inleakage into the tank from an unknown source, W-12 was removed from service to comply with the Federal Facilities Agreement requirement. The initial response was to decontaminate the valve pit between tank W-12 and the evaporator service tank (W-22) to determine if personnel could enter the pit to attempt repair of the leaking flange. Preventing the spread of radioactive contamination from the pit to the environment and to other waste systems was of concern during the decontamination. The drain in the pit goes to the process waste system; therefore, if high-level liquid waste were generated during decontamination activities, it would have to be removed from the pit by means other than the available liquid waste connection. Remote decontamination of W-12 was conducted using the General Mills manipulator bridge and telescoping trolley and REMOTEC RM-10 manipulator. The initial objective of repairing the leaking flange was not conducted because of the repair uncertainty and the unknown tank inleakage. Rather, new piping was installed to empty the W-12 tank that would bypass the valve pit and eliminate the need to repair the flange. The radiological surveys indicated that a substantial decontamination factor was achieved

Pit Water Storage Ottrupgaard

DEFF Research Database (Denmark)

Heller, Alfred

2000-01-01

The pit water storage, a seasonal thermal storage, was built in 1993 with floating lid and hybrid clay-polymer for pit lining. The storage was leaking severe and solutions were to be found. In the paper solutions for pit lining and floating lids are discussed, cost estimations given and coming...

Parameterizations for narrowband and broadband albedo of pure snow and snow containing mineral dust and black carbon

Science.gov (United States)

Dang, Cheng; Brandt, Richard E.; Warren, Stephen G.

2015-06-01

The reduction of snow spectral albedo by black carbon (BC) and mineral dust, both alone and in combination, is computed using radiative transfer modeling. Broadband albedo is shown for mass fractions covering the full range from pure snow to pure BC and pure dust, and for snow grain radii from 5 µm to 2500 µm, to cover the range of possible grain sizes on planetary surfaces. Parameterizations are developed for opaque homogeneous snowpacks for three broad bands used in general circulation models and several narrower bands. They are functions of snow grain radius and the mass fraction of BC and/or dust and are valid up to BC content of 10 ppm, needed for highly polluted snow. A change of solar zenith angle can be mimicked by changing grain radius. A given mass fraction of BC causes greater albedo reduction in coarse-grained snow; BC and grain radius can be combined into a single variable to compute the reduction of albedo relative to pure snow. The albedo reduction by BC is less if the snow contains dust, a common situation on mountain glaciers and in agricultural and grazing lands. Measured absorption spectra of mineral dust are critically reviewed as a basis for specifying dust properties for modeling. The effect of dust on snow albedo at visible wavelengths can be represented by an "equivalent BC" amount, scaled down by a factor of about 200. Dust has little effect on the near-IR albedo because the near-IR albedo of pure dust is similar to that of pure snow.

How Can Polarization States of Reflected Light from Snow Surfaces Inform Us on Surface Normals and Ultimately Snow Grain Size Measurements?

Science.gov (United States)

Schneider, A. M.; Flanner, M.; Yang, P.; Yi, B.; Huang, X.; Feldman, D.

2016-12-01

The Snow Grain Size and Pollution (SGSP) algorithm is a method applied to Moderate Resolution Imaging Spectroradiometer data to estimate snow grain size from space-borne measurements. Previous studies validate and quantify potential sources of error in this method, but because it assumes flat snow surfaces, however, large scale variations in surface normals can cause biases in its estimates due to its dependence on solar and observation zenith angles. To address these variations, we apply the Monte Carlo method for photon transport using data containing the single scattering properties of different ice crystals to calculate polarization states of reflected monochromatic light at 1500nm from modeled snow surfaces. We evaluate the dependence of these polarization states on solar and observation geometry at 1500nm because multiple scattering is generally a mechanism for depolarization and the ice crystals are relatively absorptive at this wavelength. Using 1500nm thus results in a higher number of reflected photons undergoing fewer scattering events, increasing the likelihood of reflected light having higher degrees of polarization. In evaluating the validity of the model, we find agreement with previous studies pertaining to near-infrared spectral directional hemispherical reflectance (i.e. black-sky albedo) and similarities in measured bidirectional reflectance factors, but few studies exist modeling polarization states of reflected light from snow surfaces. Here, we present novel results pertaining to calculated polarization states and compare dependences on solar and observation geometry for different idealized snow surfaces. If these dependencies are consistent across different ice particle shapes and sizes, then these findings could inform the SGSP algorithm by providing useful relationships between measurable physical quantities and solar and observation geometry to better understand variations in snow surface normals from remote sensing observations.

Evolution of mud-capped dredge pits following excavation: sediment trapping and slope instability

Science.gov (United States)

Obelcz, J.; Xu, K.; Bentley, S. J.; Li, C.; Miner, M. D.; O'Connor, M. C.; Wang, J.

2016-02-01

Many fluvial channels incised the Northern Gulf of Mexico inner continental shelf during the late Quaternary. Mud-capped dredge pits (MCDPs), which are generally elongate and deep (8-10 m) excavations, target sandy fluvial channel deposits for coastal restoration projects. The morphological evolution of dredge excavations in noncohesive sandy substrate is well studied, but MCDPs have up to a several-meter-thick veneer of Holocene shelf mud overlying sandy channel deposits. This stratigraphy is hypothesized to result in more complex post-dredge morphology than pit walls simply slumping to the angle of repose shortly after excavation. Numerical modeling of MCDP post-dredge response conducted prior to excavation indicates pit walls may retrogressively fail, which is accounted for in pit design by assigning no-dredge setback buffers from pipelines or cultural and environmental resources. To validate model results and test effectiveness of setback buffers, a geophysical survey of the Sandy Point MCDP (20 km west of the Mississippi River Delta in 10m deep water), where 1.7 million m3 of sandy sediment was excavated in 2012, was conducted May 2015. A total of 84 line-km of high-resolution chirp subbottom and a 27 km2 grid of swath bathymetry and sidescan sonar were collected. The data indicate the dredge pit walls are differentially slumping, with the western pit wall in a more active state of failure than the eastern wall. The western failures morphologically resemble features observed along the muddy Mississippi River Delta Front at water depths of 20-100 m, including bowl-shaped collapse failures and retrogressive stair-stepped slumps; these failures may play a key role in evaluating the distance of setback buffer zone to pipelines. These features indicate the cohesive mud overlying the sandy infill has a prominent role in pit wall stability. A 0.5-1 m thick acoustically transparent package overlies the entire pit floor (interpreted as a possible fluid mud layer

Studies in pitting corrosion on archaeological bronzes. Copper

International Nuclear Information System (INIS)

Bresle, Aa.; Saers, J.; Arrhenius, B.

1983-01-01

Copper has been proposed as a canister material for use in the long-term storage of radioactive waste from nuclear power reactors. The storage period has been set to at least 100 000 years, during which time the copper cylinders must remain intact so that the contained waste has no possibility of leaking out. In this work, the pitting factor in archaelogical copper objects have been determined. The absolute values of the pitting factor obtained are generally very low. In the case of the most thoroughly studied material the pitting factor is only slightly more than three units. Nor does the native copper, with a presumed burial period of about 8000 years, exhibit particularly high values. In summary, it can therefore be concluded that the present study does not provide support for the assumption of extremely high pitting factors in copper-base material that has been buried for periods of several millenia. (G.B.)

Searching for manganese pollution from MMT anti-knock gasoline additives in snow from central Greenland

International Nuclear Information System (INIS)

Veysseyre, A.; Velde, K. van de; Ferrari, C.; Boutron, C.

1998-01-01

Mn has been measured in snow core samples dated from 1967 to 1989 collected in central Greenland. Observed concentrations range from 16 to 236 pg g -1 . A large fraction of Mn in Greenland snow is found to originate from rock and soil dust. The different possible natural sources for 'excess' Mn above that contributed from rock and soil dust include volcanoes, natural vegetation fires and continental biogenic emissions. They could explain part of the observed excess. At least part of it is, however, probably related to anthropogenic inputs, especially from North America. Aside from industrial sources, MMT (methyl-cyclopentadienyl manganese tricarbonyl) anti-knock gasoline additives are good candidates, but our data do not allow to clearly identify their influence. Unambiguous identification will require the direct determination of organo-Mn compounds in comprehensive series of Greenland snow samples with sub-seasonal resolution using highly sensitive speciation techniques. (Copyright (c) 1998 Elsevier Science B.V., Amsterdam. All rights reserved.)

Fast Track Characterization of Highly Radioactive Waste Pits Combining Off-the-Shelf Robotics with Innovative Investigation Protocols

International Nuclear Information System (INIS)

Chabeuf, Jean-Michel; Boya, Didier

2008-01-01

The investigation and characterization of radioactive waste pits and effluent storage tanks represents a substantial and challenging step in the overall decommissioning programme launched by AREVA NC in 1998 on the site of Marcoule on behalf of the French Atomic Energy commission. Physical ,radiological and regulatory constraints, combined with a tight schedule, have lead our teams to use proven conventional instrumentation and robotics in innovative configurations . One such investigation, conducted on a particularly challenging radioactive effluent storage pit, is described below. The 'H' pit is a stainless steel clad concrete cavity, located in the second basement of the de-cladding building of Marcoule site. It was used for forty years as buffer storage for high activity effluents and has a length of 5 meters, a width of 3 meters , a height of 2.5 meters, and is topped by lead plates over 5 cm thick and The bottom of the cavity is covered with a layer of mud containing mainly graphite, diatoms and resins. The mud level ranges from about 20 centimeters to over 50 centimeters. The overall mud volume is around 2.4 cubic meters. Ambient dose rates above the lead plates exceed 10 mSv/h. The main purpose of our investigation was to characterize the muds for future recovery and conditioning prior to decontaminating the pit. The history of the pit together with the varying mud altimetry lead us to believe that sedimentation had probably occurred throughout the years. We thus decided to combine dose rate measurements using IF104 probes, gamma spectroscopy with CdTe probes and sample collections at different depths to ensure the representativeness and full characterization of the muds. Poor access, ambient dose rates have lead us to conceive a robotic arm, mounted on an shaft which can be modified to fit a wide range of pits and tanks. Custom built robotic tools with maximum manoeuvrability generally involve costs and delays far exceeding our purposes. SIT, a French

Land Surface Model Biases and their Impacts on the Assimilation of Snow-related Observations

Science.gov (United States)

Arsenault, K. R.; Kumar, S.; Hunter, S. M.; Aman, R.; Houser, P. R.; Toll, D.; Engman, T.; Nigro, J.

2007-12-01

Some recent snow modeling studies have employed a wide range of assimilation methods to incorporate snow cover or other snow-related observations into different hydrological or land surface models. These methods often include taking both model and observation biases into account throughout the model integration. This study focuses more on diagnosing the model biases and presenting their subsequent impacts on assimilating snow observations and modeled snowmelt processes. In this study, the land surface model, the Community Land Model (CLM), is used within the Land Information System (LIS) modeling framework to show how such biases impact the assimilation of MODIS snow cover observations. Alternative in-situ and satellite-based observations are used to help guide the CLM LSM in better predicting snowpack conditions and more realistic timing of snowmelt for a western US mountainous region. Also, MODIS snow cover observation biases will be discussed, and validation results will be provided. The issues faced with inserting or assimilating MODIS snow cover at moderate spatial resolutions (like 1km or less) will be addressed, and the impacts on CLM will be presented.

Observation of Eye Pattern on Super-Resolution Near-Field Structure Disk with Write-Strategy Technique

Science.gov (United States)

Fuji, Hiroshi; Kikukawa, Takashi; Tominaga, Junji

2004-07-01

Pit-edge recording at a density of 150 nm pits and spaces is carried out on a super-resolution near-field structure (super-RENS) disk with a platinum oxide layer. Pits are recorded and read using a 635-nm-wavelength laser and an objective lens with a 0.6 numerical aperture. We arrange laser pulses to correctly record the pits on the disk by a write-strategy technique. The laser-pulse figure includes a unit time of 0.25 T and intensities of Pw1, Pw2 and Pw3. After recording pits of various lengths, the observation of an eye pattern is achieved despite a pit smaller than the resolution limit. Furthermore, the eye pattern maintains its shape even though other pits fill the adjacent tracks at a track density of 600 nm. The disk can be used as a pit-edge recording system through a write-strategy technique.

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

Science.gov (United States)

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

2017-12-01

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

Extended-range high-resolution dynamical downscaling over a continental-scale spatial domain with atmospheric and surface nudging

Science.gov (United States)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

Extended-range high-resolution mesoscale simulations with limited-area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather-dependent renewable energy industry. Long-term simulations over a continental-scale spatial domain, however, require mechanisms to control the large-scale deviations in the high-resolution simulated fields from the coarse-resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high-resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time-varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high-resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high-resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended-range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal

Open Pit Water Control Safety A Case Of Nchanga Open Pit Mine Zambia

Directory of Open Access Journals (Sweden)

Silwamba C

2015-08-01

Full Text Available Abstract Mining in Chingola Zambia started underground in 1931 and was catastrophically flooded and closed. The present Nchanga Underground Mine NUG started in 1937. The Nchanga Open Pit NOP mine started in 1955 situated to the west of NUG and partially overlying it. Open pit water control safety operations in the Nchanga-Chingola area have successfully enabled the safe extraction of millions of tonnes of copper ore annually over the past 60 years from NUG mining as well as the NOP. At the start Nchanga mining license surface already had NUG and many watershed divides with the Nchanga and Chingola streams being the main streams feeding into Zambias second largest river Kafue river and 42 of the year was characterised by heavy rains ranging between 800mm to 1300mm per annum. In this paper the presence of very significant amounts of seasonal rain and subsurface water in the mining area was identified as both a curse and a blessing. An excess in seasonal rain and subsurface water would disrupt both open pit and underground mining operations. In order for NOP to be operated successfully stable and free from flooding coping water management tactics were adopted from 1955 to 2015 including 1. Underground mine pump chamber pumping system 2. Piezometer instrumented boreholes 3. Underground mine 1500-ft sub-haulage east borehole dewatering beneath the open pit 4. Nchanga and Chingola stream diversionary tunnel and open drains 5. Nchanga stream causeway and embankment dam in the Matero School Golf Club area 6. Pit perimeter borehole pumping 7. Outer and inner pit perimeter drains and bund walls 8. In-pit ramp side drains 9. In-pit sub-horizontal borehole geo-drains and water and 10. Pit bottom sump pumps. Application of grout curtains along the Vistula River Poland was noted as a possibility in the right circumstances although it had never been used at Nchanga Open Pit. An additional conclusion was that forward health safety and environmental end

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

Science.gov (United States)

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

2017-11-01

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

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

Science.gov (United States)

Deeb, Elias J.

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

Snow and Ice Climatology of the Western United States and Alaska from MODIS

Science.gov (United States)

Rittger, K. E.; Painter, T. H.; Mattmann, C. A.; Seidel, F. C.; Burgess, A.; Brodzik, M.

2013-12-01

. In the Northwest we use the observations to investigate earlier snowmelt, in the Southwest drought, and in Alaska to measure the change in glacier area. We compare the MODIS retrievals to a time series of AVIRIS retrievals at higher spatial resolution spanning 289km2 and 61km2 in the California's Sierra Nevada and Colorado's Senator Beck Basin. We continue to nest specific investigations of regions and topics that have high priority due to existing or anticipated climate stresses, generally in the context of a variety of other concerns.

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

Science.gov (United States)

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

2016-01-01

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

Use of PIT tag and underwater video recording in assessing estuarine fish movement in a high intertidal mangrove and salt marsh creek

Science.gov (United States)

Meynecke, Jan-Olaf; Poole, Geoffrey C.; Werry, Jonathan; Lee, Shing Yip

2008-08-01

We assessed movement patterns in relation to habitat availability (reflected by the extent of tidal flooding) for several commercially and recreationally important species in and out of a small mangrove creek within the subtropical Burrum River estuary (25°10'S 152°37'E) in Queensland, Australia. Movement patterns of Acanthopagrus australis, Pomadasys kaakan, Lutjanus russelli and Mugil cephalus were examined between December 2006 and April 2007 using a stationary passive integrated transponder (PIT) system adapted for saline environments (30-38 ppt) and underwater digital video cameras (DVCs). This is the second known application of a stationary PIT tag system to studying fish movement in estuarine environments. The transponder system was set in place for 104 days and recorded >5000 detections. Overall 'recapture' rate of tagged fish by the transponder system was >40%. We used PIT tags implanted in a total of 75 fish from a tidal creek connected to the main channel of the estuary. We also developed a high-resolution digital elevation (2.5 m cell size) model of the estuary derived from airborne light detection and ranging (LIDAR) and aerial imagery to estimate inundation dynamics within the tidal creek, and related the timing of inundation in various habitats to the timing of fish immigration to and emigration from the creek. Over 50% of all tagged fish were moving in and out of the creek at a threshold level when 50% of the mangrove forest became flooded. Individuals of all four species moved into and out of the tidal creek repeatedly at different times depending on species and size, indicating strong residential behaviour within the estuary. The main activity of fishes was at night time. Manual interpretation of video from >700 fish sightings at three different mangrove sites confirmed the findings of the stationary PIT system, that the function of shelter vs food in mangrove habitat may be size dependent. Our established techniques assess the spatial ecology

Signals of pollution revealed by trace elements in recent snow from mountain glaciers at the Qinghai-Tibetan plateau.

Science.gov (United States)

Li, Yuefang; Li, Zhen; Cozzi, Giulio; Turetta, Clara; Barbante, Carlo; Huang, Ju; Xiong, Longfei

2018-06-01

In order to extract pollution signal of trace elements (TEs) in glacier snow at the Qinghai-Tibetan plateau of China by human activities, concentrations of 18 TEs (Al, Ti, Fe, Rb, Sr, Ba, V, Cr, Mn, Li, Cu, Co, Mo, Cs, Sb, Pb, Tl, and U), 14 rare earth elements (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu), Y and Th in digested snow samples from five glaciers in April-May 2013 before monsoon season were measured. Results shown that higher TEs concentrations were found in glaciers at the northern plateau while lower concentrations in glaciers at the central and southern plateau. Discussion revealed that EF values calculated from elements with mass fraction TEs such as Sb, Sr, As, Cu and Pb etc. Analysis indicated that most TEs mainly originated from dust sources, whereas Pb, Cu, Mo and Sb showed occasionally significant contributions from polluted sources in three snow pits and the GRHK surface snow samples. The pollution probably originated from mining and smelting, road transport emissions on the plateau and some regions outside of the plateau. Dust provenance tracing results based on REEs indicated that Taklimakan Desert, Qaidam Basin, and Tibetan surface soil were the potential dust sources for the studied glaciers, while the Indian Thar Desert was an occasional dust sources for YZF,XDKMD and GRHK snow samples. Copyright © 2018 Elsevier Ltd. All rights reserved.

Resilience to Changing Snow Depth in a Shrubland Ecosystem.

Science.gov (United States)

Loik, M. E.

2008-12-01

Snowfall is the dominant hydrologic input for high elevations and latitudes of the arid- and semi-arid western United States. Sierra Nevada snowpack provides numerous important services for California, but is vulnerable to anthropogenic forcing of the coupled ocean-atmosphere system. GCM and RCM scenarios envision reduced snowpack and earlier melt under a warmer climate, but how will these changes affect soil and plant water relations and ecosystem processes? And, how resilient will this ecosystem be to short- and long-term forcing of snow depth and melt timing? To address these questions, our experiments utilize large- scale, long-term roadside snow fences to manipulate snow depth and melt timing in eastern California, USA. Interannual snow depth averages 1344 mm with a CV of 48% (April 1, 1928-2008). Snow fences altered snow melt timing by up to 18 days in high-snowfall years, and affected short-term soil moisture pulses less in low- than medium- or high-snowfall years. Sublimation in this arid location accounted for about 2 mol m- 2 of water loss from the snowpack in 2005. Plant water potential increased after the ENSO winter of 2005 and stayed relatively constant for the following three years, even after the low snowfall of winter 2007. Over the long-term, changes in snow depth and melt timing have impacted cover or biomass of Achnatherum thurberianum, Elymus elemoides, and Purshia tridentata. Growth of adult conifers (Pinus jeffreyi and Pi. contorta) was not equally sensitive to snow depth. Thus, complex interactions between snow depth, soil water inputs, physiological processes, and population patterns help drive the resilience of this ecosystem to changes in snow depth and melt timing.

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

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

Geochemical evolution of a high arsenic, alkaline pit-lake in the Mother Lode Gold District, California

Science.gov (United States)

Savage, Kaye S.; Ashley, Roger P.; Bird, Dennis K.

2009-01-01

The Harvard orebody at the Jamestown gold mine, located along the Melones fault zone in the southern Mother Lode gold district, California, was mined in an open-pit operation from 1987 to 1994. Dewatering during mining produced a hydrologic cone of depression; recovery toward the premining ground-water configuration produced a monomictic pit lake with alkaline Ca-Mg-HCO3-SO4–type pit water, concentrations of As up to 1,200 μg/L, and total dissolved solids (TDS) up to 2,000 mg/L. In this study, pit-wall rocks were mapped and chemically analyzed to provide a context for evaluating observed variability in the composition of the pit-lake waters in relationship to seasonal weather patterns. An integrated hydrogeochemical model of pit-lake evolution based on observations of pit-lake volume, water composition (samples collected between 1998–2000, 2004), and processes occurring on pit walls was developed in three stages using the computer code PHREEQC. Stage 1 takes account of seasonally variable water fluxes from precipitation, evaporation, springs, and ground water, as well as lake stratification and mixing processes. Stage 2 adds CO2fluxes and wall-rock interactions, and stage 3 assesses the predictive capability of the model.Two major geologic units in fault contact comprise the pit walls. The hanging wall is composed of interlayered slate, metavolcanic and metavolcaniclastic rocks, and schists; the footwall rocks are chlorite-actinolite and talc-tremolite schists generated by metasomatism of greenschist-facies mafic and ultramafic igneous rocks. Alteration in the ore zone provides evidence for mineralizing fluids that introduced CO2, S, and K2O, and redistributed SiO2. Arsenian pyrite associated with the alteration weathers to produce goethite and jarosite on pit walls and in joints, as well as copiapite and hexahydrite efflorescences that accumulate on wall-rock faces during dry California summers. All of these pyrite weathering products incorporate arsenic at

Optical coherence tomography findings and retinal changes after vitrectomy for optic disc pit maculopathy

Directory of Open Access Journals (Sweden)

Gaurav Sanghi

2014-01-01

Full Text Available Purpose : To study the optical coherence tomography (OCT patterns in optic disc pit maculopathy and retinal changes after vitreous surgery. Materials and Methods : Retrospective review of consecutive cases with optic disc pit maculopathy seen at two tertiary eye institutes from January 2005 to June 2009. Results : Twenty-four eyes of 23 patients are included. The presenting visual acuity ranged from 20/400 to 20/20 (median:20/80. The median age at presentation was 24 years (range, 6-57 years. Optical coherence tomography demonstrated a combination of retinoschisis and outer layer detachment (OLD in 19 (79.17% eyes, OLD only in 3 (12.5% eyes and retinoschisis only in 2 (8.33% eyes. An obvious communication (outer layer hole between the schisis and OLD was seen in 14 (73.68% of the 19 eyes with both features. Of the 21 eyes with retinoschisis, schisis was present in multiple layers in 15 (71.43% and single layer in 6 (28.57% eyes. Eleven eyes underwent pars plana vitrectomy including creation of posterior vitreous detachment (PVD, fluid-air exchange, low intensity laser photocoagulation at the temporal edge of the optic disc pit and non-expansile perfluoropropane gas (14% injection. Five (45.45% of 11 eyes undergoing vitrectomy had complete resolution and 4 (36.36% eyes had partial resolution of maculopathy. Visual acuity improved in 8 (72.72% of 11 eyes. Conclusion : Optical coherence tomography demonstrates multiple layer schisis and outer layer detachment as main features of optic disc pit maculopathy. Vitrectomy with PVD induction, laser photocoagulation and gas tamponade results in anatomical and visual improvement in most cases with optic disc pit maculopathy.

High-resolution measurement of the {sup 16}O({gamma},pn) reaction

Energy Technology Data Exchange (ETDEWEB)

Isaksson, L.

1996-10-01

The {sup 16}O({gamma},pn) reaction has been measured with a resolution high enough to resolve individual low-lying states in the residual {sup 14}N nucleus. Partial cross-sections, available to the acceptance of the detector system, have been extracted for the individual states, and compared to a recent calculation based on absorption on one-pion exchange currents and the {Delta} resonance current. The experiment was performed at the Maxlab accelerator laboratory in Lund, Sweden, using tagged photons at an energy of 67 - 76 MeV. The proton detector angular range was 60 - 100 deg and the corresponding for the neutron detector 81 - 103 deg. A missing energy resolution of 1.5 MeV was obtained. The relative population of the states in the residual {sup 14}N nucleus indicates that the reaction takes place predominantly on proton-neutron pairs coupled to (J{sup {pi}},T) = (1{sup +},0). The cross-section for absorption on (0{sup +},1) pairs is strongly suppressed. Furthermore, the relative population of the states indicates that both L=0 and L=2 pairs participate in the reaction. 45 refs.

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

Extended-Range High-Resolution Dynamical Downscaling over a Continental-Scale Domain

Science.gov (United States)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

High-resolution mesoscale simulations, when applied for downscaling meteorological fields over large spatial domains and for extended time periods, can provide valuable information for many practical application scenarios including the weather-dependent renewable energy industry. In the present study, a strategy has been proposed to dynamically downscale coarse-resolution meteorological fields from Environment Canada's regional analyses for a period of multiple years over the entire Canadian territory. The study demonstrates that a continuous mesoscale simulation over the entire domain is the most suitable approach in this regard. Large-scale deviations in the different meteorological fields pose the biggest challenge for extended-range simulations over continental scale domains, and the enforcement of the lateral boundary conditions is not sufficient to restrict such deviations. A scheme has therefore been developed to spectrally nudge the simulated high-resolution meteorological fields at the different model vertical levels towards those embedded in the coarse-resolution driving fields derived from the regional analyses. A series of experiments were carried out to determine the optimal nudging strategy including the appropriate nudging length scales, nudging vertical profile and temporal relaxation. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil-moisture, and snow conditions, towards their expected values obtained from a high-resolution offline surface scheme was also devised to limit any considerable deviation in the evolving surface fields due to extended-range temporal integrations. The study shows that ensuring large-scale atmospheric similarities helps to deliver near-surface statistical scores for temperature, dew point temperature and horizontal wind speed that are better or comparable to the operational regional forecasts issued by Environment Canada. Furthermore, the meteorological fields

Performance tests of snow-related variables over the Tibetan Plateau and Himalayas using a new version of NASA GEOS-5 land surface model that includes the snow darkening effect

Science.gov (United States)

Yasunari, T. J.; Lau, W. K.; Koster, R. D.; Suarez, M.; Mahanama, S. P.; da Silva, A.; Colarco, P. R.

2011-12-01

The snow darkening effect, i.e. the reduction of snow albedo, is caused by absorption of solar radiation by absorbing aerosols (dust, black carbon, and organic carbon) deposited on the snow surface. This process is probably important over Himalayan and Tibetan glaciers due to the transport of highly polluted Atmospheric Brown Cloud (ABC) from the Indo-Gangetic Plain (IGP). This effect has been incorporated into the NASA Goddard Earth Observing System model, version 5 (GEOS-5) atmospheric transport model. The Catchment land surface model (LSM) used in GEOS-5 considers 3 snow layers. Code was developed to track the mass concentration of aerosols in the three layers, taking into account such processes as the flushing of the compounds as liquid water percolates through the snowpack. In GEOS-5, aerosol emissions, transports, and depositions are well simulated in the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module; we recently made the connection between GOCART and the GEOS-5 system fitted with the revised LSM. Preliminary simulations were performed with this new system in "replay" mode (i.e., with atmospheric dynamics guided by reanalysis) at 2x2.5 degree horizontal resolution, covering the period 1 November 2005 - 31 December 2009; we consider the final three years of simulation here. The three simulations used the following variants of the LSM: (1) the original Catchment LSM with a fixed fresh snowfall density of 150 kg m-3; (2) the LSM fitted with the new snow albedo code, used here without aerosol deposition but with changes in density formulation and melting water effect on snow specific surface area, (3) the LSM fitted with the new snow albedo code as same as (2) but with fixed aerosol deposition rates (computed from GOCART values averaged over the Tibetan Plateau domain [lon.: 60-120E; lat.: 20-50N] during March-May 2008) applied to all grid points at every time step. For (2) and (3), the same setting on the fresh snowfall density as in (1) was

Pitting of malaria parasites and spherocyte formation

Directory of Open Access Journals (Sweden)

Gichuki Charity W

2006-07-01

Full Text Available Abstract Background A high prevalence of spherocytes was detected in blood smears of children enrolled in a case control study conducted in the malaria holoendemic Lake Victoria basin. It was speculated that the spherocytes reflect intraerythrocytic removal of malarial parasites with a concurrent removal of RBC membrane through a process analogous to pitting of intraerythrocytic inclusion bodies. Pitting and re-circulation of RBCs devoid of malaria parasites could be a host mechanism for parasite clearance while minimizing the anaemia that would occur were the entire parasitized RBC removed. The prior demonstration of RBCs containing ring-infected erythrocyte surface antigen (pf 155 or RESA but no intracellular parasites, support the idea of pitting. Methods An in vitro model was developed to examine the phenomenon of pitting and spherocyte formation in Plasmodium falciparum infected RBCs (iRBC co-incubated with human macrophages. In vivo application of this model was evaluated using blood specimens from patients attending Kisumu Ditrict Hospital. RBCs were probed with anti-RESA monoclonal antibody and a DNA stain (propidium iodide. Flow cytometry and fluorescent microscopy was used to compare RBCs containing both the antigen and the parasites to those that were only RESA positive. Results Co-incubation of iRBC and tumor necrosis factor-alpha activated macrophages led to pitting (14% ± 1.31% macrophages with engulfed trophozoites as opposed to erythrophagocytosis (5.33% ± 0.95% (P Conclusion It is proposed that in malaria holoendemic areas where prevalence of asexual stage parasites approaches 100% in children, RBCs with pitted parasites are re-circulated and pitting may produce spherocytes.

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

Science.gov (United States)

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

2014-12-01

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

Retrieval of Effective Correlation Length and Snow Water Equivalent from Radar and Passive Microwave Measurements

Directory of Open Access Journals (Sweden)

Juha Lemmetyinen

2018-01-01

Full Text Available Current methods for retrieving SWE (snow water equivalent from space rely on passive microwave sensors. Observations are limited by poor spatial resolution, ambiguities related to separation of snow microstructural properties from the total snow mass, and signal saturation when snow is deep (~>80 cm. The use of SAR (Synthetic Aperture Radar at suitable frequencies has been suggested as a potential observation method to overcome the coarse resolution of passive microwave sensors. Nevertheless, suitable sensors operating from space are, up to now, unavailable. Active microwave retrievals suffer, however, from the same difficulties as the passive case in separating impacts of scattering efficiency from those of snow mass. In this study, we explore the potential of applying active (radar and passive (radiometer microwave observations in tandem, by using a dataset of co-incident tower-based active and passive microwave observations and detailed in situ data from a test site in Northern Finland. The dataset spans four winter seasons with daily coverage. In order to quantify the temporal variability of snow microstructure, we derive an effective correlation length for the snowpack (treated as a single layer, which matches the simulated microwave response of a semi-empirical radiative transfer model to observations. This effective parameter is derived from radiometer and radar observations at different frequencies and frequency combinations (10.2, 13.3 and 16.7 GHz for radar; 10.65, 18.7 and 37 GHz for radiometer. Under dry snow conditions, correlations are found between the effective correlation length retrieved from active and passive measurements. Consequently, the derived effective correlation length from passive microwave observations is applied to parameterize the retrieval of SWE using radar, improving retrieval skill compared to a case with no prior knowledge of snow-scattering efficiency. The same concept can be applied to future radar

High Resolution Digital Elevation Models of Pristine Explosion Craters

Science.gov (United States)

Farr, T. G.; Krabill, W.; Garvin, J. B.

2004-01-01

In order to effectively capture a realistic terrain applicable to studies of cratering processes and landing hazards on Mars, we have obtained high resolution digital elevation models of several pristine explosion craters at the Nevada Test Site. We used the Airborne Terrain Mapper (ATM), operated by NASA's Wallops Flight Facility to obtain DEMs with 1 m spacing and 10 cm vertical errors of 4 main craters and many other craters and collapse pits. The main craters that were mapped are Sedan, Scooter, Schooner, and Danny Boy. The 370 m diameter Sedan crater, located on Yucca Flat, is the largest and freshest explosion crater on Earth that was formed under conditions similar to hypervelocity impact cratering. As such, it is effectively pristine, having been formed in 1962 as a result of a controlled detonation of a 100 kiloton thermonuclear device, buried at the appropriate equivalent depth of burst required to make a simple crater. Sedan was formed in alluvium of mixed lithology and subsequently studied using a variety of field-based methods. Nearby secondary craters were also formed at the time and were also mapped by ATM. Adjacent to Sedan and also in alluvium is Scooter, about 90 m in diameter and formed by a high-explosive event. Schooner (240 m) and Danny Boy (80 m) craters were also important targets for ATM as they were excavated in hard basalt and therefore have much rougher ejecta. This will allow study of ejecta patterns in hard rock as well as engineering tests of crater and rock avoidance and rover trafficability. In addition to the high resolution DEMs, crater geometric characteristics, RMS roughness maps, and other higher-order derived data products will be generated using these data. These will provide constraints for models of landing hazards on Mars and for rover trafficability. Other planned studies will include ejecta size-frequency distribution at the resolution of the DEM and at finer resolution through air photography and field measurements

Performance Tests of Snow-Related Variables Over the Tibetan Plateau and Himalayas Using a New Version of NASA GEOS-5 Land Surface Model that Includes the Snow Darkening Effect

Science.gov (United States)

Yasunari, Tppei J.; Lau, K.-U.; Koster, Randal D.; Suarez, Max; Mahanama, Sarith; Dasilva, Arlindo M.; Colarco, Peter R.

2011-01-01

The snow darkening effect, i.e. the reduction of snow albedo, is caused by absorption of solar radiation by absorbing aerosols (dust, black carbon, and organic carbon) deposited on the snow surface. This process is probably important over Himalayan and Tibetan glaciers due to the transport of highly polluted Atmospheric Brown Cloud (ABC) from the Indo-Gangetic Plain (IGP). This effect has been incorporated into the NASA Goddard Earth Observing System model, version 5 (GEOS-5) atmospheric transport model. The Catchment land surface model (LSM) used in GEOS-5 considers 3 snow layers. Code was developed to track the mass concentration of aerosols in the three layers, taking into account such processes as the flushing of the compounds as liquid water percolates through the snowpack. In GEOS-5, aerosol emissions, transports, and depositions are well simulated in the Goddard Chemistry Aerosol Radiation and Transport (GO CART) module; we recently made the connection between GOCART and the GEOS-5 system fitted with the revised LSM. Preliminary simulations were performed with this new system in "replay" mode (i.e., with atmospheric dynamics guided by reanalysis) at 2x2.5 degree horizontal resolution, covering the period 1 November 2005 - 31 December 2009; we consider the final three years of simulation here. The three simulations used the following variants of the LSM: (1) the original Catchment LSM with a fixed fresh snowfall density of 150 kg m-3 ; (2) the LSM fitted with the new snow albedo code, used here without aerosol deposition but with changes in density formulation and melting water effect on snow specific surface area, (3) the LSM fitted with the new snow albedo code as same as (2) but with fixed aerosol deposition rates (computed from GOCART values averaged over the Tibetan Plateau domain [Ion.: 60-120E; lat.: 20-50N] during March-May 2008) applied to all grid points at every time step. For (2) and (3), the same setting on the fresh snowfall density as in (1

High-resolution DEMs for High-mountain Asia: A systematic, region-wide assessment of geodetic glacier mass balance and dynamics

Science.gov (United States)

Shean, D. E.; Arendt, A. A.; Osmanoglu, B.; Montesano, P.

2017-12-01

High Mountain Asia (HMA) constitutes the largest glacierized region outside of the Earth's polar regions. Although available observations are limited, long-term records indicate sustained regional glacier mass loss since 1850, with increased loss in recent decades. Recent satellite data (e.g., GRACE, ICESat-1) show spatially variable glacier mass balance, with significant mass loss in the Himalaya and Hindu Kush and slight mass gain in the Karakoram. We generated 4000 high-resolution digital elevation models (DEMs) from sub-meter commercial stereo imagery (DigitalGlobe WorldView/GeoEye) acquired over glaciers in High-mountain Asia from 2002-present (mostly 2013-present). We produced a regional 8-m DEM mosaic for 2015 and estimated 15-year geodetic mass balance for 40000 glaciers larger than 0.1 km2. We are combining with other regional DEM sources to systematically document the spatiotemporal evolution of glacier mass balance for the entire HMA region. We also generated monthly to interannual DEM and velocity time series for high-priority sites distributed across the region, with >15-20 DEMs available for some locations from 2010-present. These records document glacier dynamics, seasonal snow accumulation/redistribution, and processes that affect glacier mass balance (e.g., ice-cliff retreat, debris cover evolution). These efforts will provide basin-scale assessments of snow/ice melt runoff contributions for model cal/val and downstream water resources applications. We will continue processing all archived and newly available commercial stereo imagery for HMA, and will release all DEMs through the HiMAT DAAC.

A novel linear physical model for remote sensing of snow wetness and snow density using the visible and infrared bands

Science.gov (United States)

Varade, D. M.; Dikshit, O.

2017-12-01

Modeling and forecasting of snowmelt runoff are significant for understanding the hydrological processes in the cryosphere which requires timely information regarding snow physical properties such as liquid water content and density of snow in the topmost layer of the snowpack. Both the seasonal runoffs and avalanche forecasting are vastly dependent on the inherent physical characteristics of the snowpack which are conventionally measured by field surveys in difficult terrains at larger impending costs and manpower. With advances in remote sensing technology and the increase in the availability of satellite data, the frequency and extent of these surveys could see a declining trend in future. In this study, we present a novel approach for estimating snow wetness and snow density using visible and infrared bands that are available with most multi-spectral sensors. We define a trapezoidal feature space based on the spectral reflectance in the near infrared band and the Normalized Differenced Snow Index (NDSI), referred to as NIR-NDSI space, where dry snow and wet snow are observed in the left diagonal upper and lower right corners, respectively. The corresponding pixels are extracted by approximating the dry and wet edges which are used to develop a linear physical model to estimate snow wetness. Snow density is then estimated using the modeled snow wetness. Although the proposed approach has used Sentinel-2 data, it can be extended to incorporate data from other multi-spectral sensors. The estimated values for snow wetness and snow density show a high correlation with respect to in-situ measurements. The proposed model opens a new avenue for remote sensing of snow physical properties using multi-spectral data, which were limited in the literature.

High-resolution X-ray television and high-resolution video recorders

International Nuclear Information System (INIS)

Haendle, J.; Horbaschek, H.; Alexandrescu, M.

1977-01-01

The improved transmission properties of the high-resolution X-ray television chain described here make it possible to transmit more information per television image. The resolution in the fluoroscopic image, which is visually determined, depends on the dose rate and the inertia of the television pick-up tube. This connection is discussed. In the last few years, video recorders have been increasingly used in X-ray diagnostics. The video recorder is a further quality-limiting element in X-ray television. The development of function patterns of high-resolution magnetic video recorders shows that this quality drop may be largely overcome. The influence of electrical band width and number of lines on the resolution in the X-ray television image stored is explained in more detail. (orig.) [de

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

NELL-1 increases pre-osteoblast mineralization using both phosphate transporter Pit1 and Pit2

Energy Technology Data Exchange (ETDEWEB)

Cowan, Catherine M. [Department of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza,7523 Boelter Hall, Los Angeles, CA 90095 (United States); Dental and Craniofacial Research Institute and Section of Orthodontics, School of Dentistry, University of California, Los Angeles, 40833 Le Conte Ave, Los Angeles, CA 90095 (United States); Zhang, Xinli; James, Aaron W.; Mari Kim, T.; Sun, Nichole [Dental and Craniofacial Research Institute and Section of Orthodontics, School of Dentistry, University of California, Los Angeles, 40833 Le Conte Ave, Los Angeles, CA 90095 (United States); Wu, Benjamin [Department of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza,7523 Boelter Hall, Los Angeles, CA 90095 (United States); Dental and Craniofacial Research Institute and Section of Orthodontics, School of Dentistry, University of California, Los Angeles, 40833 Le Conte Ave, Los Angeles, CA 90095 (United States); Ting, Kang [Dental and Craniofacial Research Institute and Section of Orthodontics, School of Dentistry, University of California, Los Angeles, 40833 Le Conte Ave, Los Angeles, CA 90095 (United States); Soo, Chia, E-mail: bsoo@ucla.edu [UCLA and Orthopaedic Hospital Department of Orthopaedic Surgery and the Orthopaedic, Hospital Research Center, University of California, Los Angeles, 2641 Charles E. Young Dr. South, Los Angeles, CA 90095 (United States)

2012-06-08

Highlights: Black-Right-Pointing-Pointer NELL-1 accelerates extracellular matrix mineralization in MC3T3-E1 pre-osteoblasts. Black-Right-Pointing-Pointer NELL-1 significantly increases intracellular inorganic phosphate levels. Black-Right-Pointing-Pointer NELL-1 positively regulates osteogenesis but not proliferation in MC3T3-E1 cells. Black-Right-Pointing-Pointer NELL-1 regulates inorganic phosphate transporter activity. -- Abstract: NELL-1 is a potent osteoinductive molecule that enhances bone formation in multiple animal models through currently unidentified pathways. In the present manuscript, we hypothesized that NELL-1 may regulate osteogenic differentiation accompanied by alteration of inorganic phosphate (Pi) entry into the osteoblast via sodium dependent phosphate (NaPi) transporters. To determine this, MC3T3-E1 pre-osteoblasts were cultured in the presence of recombinant human (rh)NELL-1 or rhBMP-2. Analysis was performed for intracellular Pi levels through malachite green staining, Pit-1 and Pit-2 expression, and forced upregulation of Pit-1 and Pit-2. Results showed rhNELL-1 to increase MC3T3-E1 matrix mineralization and Pi influx associated with activation of both Pit-1 and Pit-2 channels, with significantly increased Pit-2 production. In contrast, Pi transport elicited by rhBMP-2 showed to be associated with increased Pit-1 production only. Next, neutralizing antibodies against Pit-1 and Pit-2 completely abrogated the Pi influx effect of rhNELL-1, suggesting rhNELL-1 is dependent on both transporters. These results identify one potential mechanism of action for rhNELL-1 induced osteogenesis and highlight a fundamental difference between NELL-1 and BMP-2 signaling.

NELL-1 increases pre-osteoblast mineralization using both phosphate transporter Pit1 and Pit2

International Nuclear Information System (INIS)

Cowan, Catherine M.; Zhang, Xinli; James, Aaron W.; Mari Kim, T.; Sun, Nichole; Wu, Benjamin; Ting, Kang; Soo, Chia

2012-01-01

Highlights: ► NELL-1 accelerates extracellular matrix mineralization in MC3T3-E1 pre-osteoblasts. ► NELL-1 significantly increases intracellular inorganic phosphate levels. ► NELL-1 positively regulates osteogenesis but not proliferation in MC3T3-E1 cells. ► NELL-1 regulates inorganic phosphate transporter activity. -- Abstract: NELL-1 is a potent osteoinductive molecule that enhances bone formation in multiple animal models through currently unidentified pathways. In the present manuscript, we hypothesized that NELL-1 may regulate osteogenic differentiation accompanied by alteration of inorganic phosphate (Pi) entry into the osteoblast via sodium dependent phosphate (NaPi) transporters. To determine this, MC3T3-E1 pre-osteoblasts were cultured in the presence of recombinant human (rh)NELL-1 or rhBMP-2. Analysis was performed for intracellular Pi levels through malachite green staining, Pit-1 and Pit-2 expression, and forced upregulation of Pit-1 and Pit-2. Results showed rhNELL-1 to increase MC3T3-E1 matrix mineralization and Pi influx associated with activation of both Pit-1 and Pit-2 channels, with significantly increased Pit-2 production. In contrast, Pi transport elicited by rhBMP-2 showed to be associated with increased Pit-1 production only. Next, neutralizing antibodies against Pit-1 and Pit-2 completely abrogated the Pi influx effect of rhNELL-1, suggesting rhNELL-1 is dependent on both transporters. These results identify one potential mechanism of action for rhNELL-1 induced osteogenesis and highlight a fundamental difference between NELL-1 and BMP-2 signaling.

High-accuracy measurements of snow Bidirectional Reflectance Distribution Function at visible and NIR wavelengths – comparison with modelling results

Directory of Open Access Journals (Sweden)

M. Dumont

2010-03-01

Full Text Available High-accuracy measurements of snow Bidirectional Reflectance Distribution Function (BRDF were performed for four natural snow samples with a spectrogonio-radiometer in the 500–2600 nm wavelength range. These measurements are one of the first sets of direct snow BRDF values over a wide range of lighting and viewing geometry. They were compared to BRDF calculated with two optical models. Variations of the snow anisotropy factor with lighting geometry, wavelength and snow physical properties were investigated. Results show that at wavelengths with small penetration depth, scattering mainly occurs in the very top layers and the anisotropy factor is controlled by the phase function. In this condition, forward scattering peak or double scattering peak is observed. In contrast at shorter wavelengths, the penetration of the radiation is much deeper and the number of scattering events increases. The anisotropy factor is thus nearly constant and decreases at grazing observation angles. The whole dataset is available on demand from the corresponding author.

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

Indian Academy of Sciences (India)

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

Arrested Development: High-Resolution Imaging of Foveal Morphology in Albinism

Science.gov (United States)

McAllister, John T.; Dubis, Adam M.; Tait, Diane M.; Ostler, Shawn; Rha, Jungtae; Stepien, Kimberly E.; Summers, C. Gail; Carroll, Joseph

2010-01-01

Albinism, an inherited disorder of melanin biosynthesis, disrupts normal retinal development, with foveal hypoplasia as one of the more commonly associated ocular phenotypes. However the cellular integrity of the fovea in albinism is not well understood – there likely exist important anatomical differences that underlie phenotypic variability within the disease and that also may affect responsiveness to therapeutic intervention. Here, using spectral domain optical coherence tomography (SD-OCT) and adaptive optics (AO) retinal imaging, we obtained high-resolution images of the foveal region in six individuals with albinism. We provide a quantitative analysis of cone density and outer segment elongation demonstrating that foveal cone specialization is variable in albinism. In addition, our data reveal a continuum of foveal pit morphology, roughly aligning with schematics of normal foveal development based on post-mortem analyses. Different albinism subtypes, genetic mutations, and constitutional pigment background likely play a role in determining the degree of foveal maturation. PMID:20149815

Single pit propagation on austenitic stainless steel

International Nuclear Information System (INIS)

Heurtault, Stephane

2016-01-01

The electrochemical characterization of metastable events such as pitting corrosion of stainless steel in chloride electrolyte remains complex because many individual processes may occur simultaneously on the alloy surface. To overcome these difficulties, an experimental setup, the flow micro-device, has been developed to achieve the initiation of a single pit and to propagate the single pit in three dimensions. In this work, we take advantage of such a device in order to revisit the pitting process on a 316L stainless steel in a chloride - sulphate bulk. In a first step, the time evolution of the pit geometry (depth, radius) and the chemical evolution of the pit solution investigated using in situ Raman spectroscopy have shown that the pit depth propagation depends on the formation of a metal chloride and sulphate gel in the pit solution, and is controlled by the metallic cations diffusion from the pit bottom to the pit mouth. The pit radius growth is defined by the initial surface de-passivation, by the presence of a pit cover and by the gel development in the solution. all of these phenomena are function of applied potential and chemical composition of the solution. In a last step, it was demonstrated that a critical chloride concentration is needed in order to maintain the pit propagation. This critical concentration slightly increases with the pit depth. From statistical analysis performed on identical experiments, a zone diagram showing the pit stability as a function of the chloride concentration and the pit dimensions was built. (author) [fr

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

Science.gov (United States)

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

2017-12-01

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

Stochastic models for predicting pitting corrosion damage of HLRW containers

International Nuclear Information System (INIS)

Henshall, G.A.

1991-10-01

Stochastic models for predicting aqueous pitting corrosion damage of high-level radioactive-waste containers are described. These models could be used to predict the time required for the first pit to penetrate a container and the increase in the number of breaches at later times, both of which would be useful in the repository system performance analysis. Monte Carlo implementations of the stochastic models are described, and predictions of induction time, survival probability and pit depth distributions are presented. These results suggest that the pit nucleation probability decreases with exposure time and that pit growth may be a stochastic process. The advantages and disadvantages of the stochastic approach, methods for modeling the effects of environment, and plans for future work are discussed

The role of hardness and microstructure in high temperature pitting in the impact wear of 9Cr boiler material. Part 1

International Nuclear Information System (INIS)

Morri, J.

1987-11-01

This report describes impact wear experiments on 9Cr1Mo finned boiler tube specimens in 3 different heat treated forms. The objective of the tests was to establish whether a high temperature, high wear rate, pitting form of wear was dependent upon the residual microstructure and hardness. Although a x2 reduction in specific wear rate was achieved for the martensitic structure, the pitting characteristic remained. It is concluded that modifying the as-received 9Cr microstructure has not suppressed the high temperature severe form of wear. (author)

Sublimation pit distribution indicates convection cell surface velocities of ∼10 cm per year in Sputnik Planitia, Pluto

Science.gov (United States)

Buhler, Peter B.; Ingersoll, Andrew P.

2018-01-01

The ∼106 km2 Sputnik Planitia, Pluto is the upper surface of a vast basin of nitrogen ice. Cellular landforms in Sputnik Planitia with areas in the range of a few × 102-103 km2 are likely the surface manifestation of convective overturn in the nitrogen ice. The cells have sublimation pits on them, with smaller pits near their centers and larger pits near their edges. We map pits on seven cells and find that the pit radii increase by between 2.1 ± 0.4 × 10-3 and 5.9 ± 0.8 × 10-3 m m-1 away from the cell center, depending on the cell. This is a lower bound on the size increase because of the finite resolution of the data. Accounting for resolution yields upper bounds on the size vs. distance distribution of between 4.2 ± 0.2 × 10-3 and 23.4 ± 1.5 × 10-3 m m-1. We then use an analytic model to calculate that pit radii grow via sublimation at a rate of 3.6-0.6+2.1 ×10-4 m yr-1, which allows us to convert the pit size vs. distance distribution into a pit age vs. distance distribution. This yields surface velocities between 1.5-0.2+1.0 and 6.2-1.4+3.4 cm yr-1 for the slowest cell and surface velocities between 8.1-1.0+5.5 and 17.9-5.1+8.9 cm yr-1 for the fastest cell. These convection rates imply that the surface ages at the edge of cells reach ∼4.2-8.9 × 105 yr. The rates are comparable to rates of ∼6 cm yr-1 that were previously obtained from modeling of the convective overturn in Sputnik Planitia (McKinnon et al., 2016). Finally, we investigate the surface rheology of the convection cells and estimate that the minimum ice viscosity necessary to support the geometry of the observed pits is of order 1016-1017 Pa s, based on the argument that pits would relax away before growing to their observed radii of several hundred meters if the viscosity were lower than this value.

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

Science.gov (United States)

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

2017-12-01

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

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Science.gov (United States)

Riggs, George A.; Hall, Dorothy K.; Román, Miguel O.

2017-10-01

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6; https://nsidc.org/data/modis/data_summaries) and VIIRS Collection 1 (C1; https://doi.org/10.5067/VIIRS/VNP10.001) represent the state-of-the-art global snow-cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow-cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map. The increased data content allows flexibility in using the datasets for specific regions and end-user applications. Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Science.gov (United States)

Riggs, George A.; Hall, Dorothy K.; Roman, Miguel O.

2017-01-01

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data

J-SEx : The Jollie Snow Experiment, New Zealand

Science.gov (United States)

Kerr, T.; Singh, S.; Kees, L.; Webster, C.; Clark, M.; Hendrikx, J.; Woods, R.

2012-04-01

out being gullies and cliff bases. This distribution is explained well by accumulation processes but poorly by melt processes. In an effort to model the observed snow variability, an assessment of including a sub-grid snow variability probability distribution parameterisation in the TopNet hydrological model has been made. Tests have shown that objective calibration of this parameterisation leads to a distribution that matches the observed and an improved hydrograph, giving weight to the value of its inclusion in the model. From a methods point-of-view, air-borne ground penetrating radar (GPR) has proven to be an efficient method of obtaining snow storage information that is equivalent in quality to manual snow probing, but is less limited in terms of terrain coverage and has a spatial resolution that is better matched to model input requirements. Air-borne GPR has been proven as the method of choice for obtaining catchment-wide snow storage estimates. The J-SEx campaign has provided much needed guidance in understanding snow variability processes in steep mountain catchments, direction for and validation of methods to encapsulate this variability in hydrological models, and confirmation of the value of air-borne radar techniques for efficient snow-storage estimation. The data collected as part of the J-SEx campaign is available to the public from Tim Kerr t.kerr@niwa.co.nz.

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

Directory of Open Access Journals (Sweden)

J. Revuelto

2017-12-01

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

Snow noise disturbance in Antarctic radio communications and development of mobile antenna for snow vehicle in Antarctica

Directory of Open Access Journals (Sweden)

Isao Fukushima

1997-07-01

Full Text Available Radio operators of the Japanese Antarctic Research Expedition (JARE have encountered critical radio noise disturbances caused by blizzards during oversnow travel. This noise appears to be caused by corona discharge at the edges of the vertical whip antenna. This paper describes several examples of snow noise experienced in Antarctica by JARE, the mechanism of generation of the noise, and a method of reducing the intensity of the noise. It also describes a High Effeciency Transmission Line Antenna which is small enough to mount on a snow vehicle and reduces the intensity of the snow noise.

Pitting corrosion of copper. An equilibrium - mass transport study

International Nuclear Information System (INIS)

Taxen, C.

2002-08-01

A mathematical model for the propagation of corrosion pits is described and used to calculate the potentials below which copper is immune to pitting. The model uses equilibrium data and diffusion coefficients and calculates the stationary concentration profiles of 26 aqueous species from the bulk water outside a corrosion pit to the site of the metal dissolution. Precipitation of oxides and salts of copper is considered. Studied conditions include water compositions from tap waters to seawater at the temperatures 25 deg C and 75 deg C. Carbonate and sulphate are aggressive towards copper because of complex formation with divalent copper. Carbonate is less aggressive in a corrosion pit than outside at the pH of the bulk. Carbonate carries acidity out from the pit, favours oxide formation and may prevent the initiation of acidic corrosion pits. The concentration profiles are used to estimate the maximum propagation rates for a corrosion pit. A high potential is found to be the most important factor for the rate of propagation. The levels of potential copper can sustain, as corrosion potentials are discussed in terms of the stability of cuprous oxide as a cathode material for oxygen reduction relative to non-conducting cupric phases

Pitting corrosion of copper. An equilibrium - mass transport study

Energy Technology Data Exchange (ETDEWEB)

Taxen, C. [Swedish Corrosion Inst., Stockholm (Sweden)

2002-08-01

A mathematical model for the propagation of corrosion pits is described and used to calculate the potentials below which copper is immune to pitting. The model uses equilibrium data and diffusion coefficients and calculates the stationary concentration profiles of 26 aqueous species from the bulk water outside a corrosion pit to the site of the metal dissolution. Precipitation of oxides and salts of copper is considered. Studied conditions include water compositions from tap waters to seawater at the temperatures 25 deg C and 75 deg C. Carbonate and sulphate are aggressive towards copper because of complex formation with divalent copper. Carbonate is less aggressive in a corrosion pit than outside at the pH of the bulk. Carbonate carries acidity out from the pit, favours oxide formation and may prevent the initiation of acidic corrosion pits. The concentration profiles are used to estimate the maximum propagation rates for a corrosion pit. A high potential is found to be the most important factor for the rate of propagation. The levels of potential copper can sustain, as corrosion potentials are discussed in terms of the stability of cuprous oxide as a cathode material for oxygen reduction relative to non-conducting cupric phases.

Pitting type of pretibial edema in a patient with silent thyroiditis successfully treated by angiotensin ii receptor blockade.

Science.gov (United States)

Kazama, Itsuro; Mori, Yoko; Baba, Asuka; Nakajima, Toshiyuki

2014-01-01

Female, 56 FINAL DIAGNOSIS: Thyroiditis - silent Symptoms: Palpitations • pretibial pitting edema • short of breath • sweating - Clinical Procedure: - Specialty: Endocrinology and Metabolic. Unknown etiology. Hyper- or hypothyroidism sometimes causes pretibial myxedema characterized by non-pitting infiltration of a proteinaceous ground substance. However, in those patients, the "pitting" type of pretibial edema as a result of increased sodium and fluid retention or vascular hyper-permeability rarely occurs, except in cases complicated by heart failures due to severe cardiomyopathy or pulmonary hypertension. A 56-year-old woman developed bilateral pretibial pitting edema, followed by occasional sweating, palpitations, and shortness of breath, which persisted for more than 2 months. The diagnosis of hyperthyroidism due to silent thyroiditis was supported by elevated levels of free thyroxine (T4) and triiodothyronine (T3), with a marked decrease in thyroid-stimulating hormone (TSH), and the negative results for TSH receptor antibodies with typical findings of destructive thyrotoxicosis. Despite her "pitting" type of pretibial edema, a chest radio-graph demonstrated the absence of cardiomyopathy or congestive heart failure. Oral administration of angiotensin II receptor blocker (ARB) was initiated for her systolic hypertension, with a relatively higher elevation of plasma renin activity compared to that of the aldosterone level. Although the symptoms characteristic to hyperthyroidism, such as increased sweating, palpitations and shortness of breath, slowly improved with a spontaneous resolution of the disease, ARB quickly resolved the pretibial pitting edema shortly after the administration.. In this case, increased activity of the renin-angiotensin-aldosterone system stimulated by thyroid hormone was likely responsible for the patient's pitting type of edema. The pharmacological blockade of the renin-angiotensin-aldosterone system was thought to be effective for

Diversity and characterization of mercury-resistant bacteria in snow, freshwater and sea-ice brine from the High Arctic.

Science.gov (United States)

Møller, Annette K; Barkay, Tamar; Abu Al-Soud, Waleed; Sørensen, Søren J; Skov, Henrik; Kroer, Niels

2011-03-01

It is well-established that atmospheric deposition transports mercury from lower latitudes to the Arctic. The role of bacteria in the dynamics of the deposited mercury, however, is unknown. We characterized mercury-resistant bacteria from High Arctic snow, freshwater and sea-ice brine. Bacterial densities were 9.4 × 10(5), 5 × 10(5) and 0.9-3.1 × 10(3) cells mL(-1) in freshwater, brine and snow, respectively. Highest cultivability was observed in snow (11.9%), followed by freshwater (0.3%) and brine (0.03%). In snow, the mercury-resistant bacteria accounted for up to 31% of the culturable bacteria, but levels of most isolates were not temperature dependent. Of the resistant isolates, 25% reduced Hg(II) to Hg(0). No relation between resistance level, ability to reduce Hg(II) and phylogenetic group was observed. An estimation of the potential bacterial reduction of Hg(II) in snow suggested that it was important in the deeper snow layers where light attenuation inhibited photoreduction. Thus, by reducing Hg(II) to Hg(0), mercury-resistant bacteria may limit the supply of substrate for methylation processes and, hence, contribute to lowering the risk that methylmercury is being incorporated into the Arctic food chains. © 2010 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

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

Science.gov (United States)

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

2013-06-01

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

SNOW LINES AS PROBES OF TURBULENT DIFFUSION IN PROTOPLANETARY DISKS

International Nuclear Information System (INIS)

Owen, James E.

2014-01-01

Sharp chemical discontinuities can occur in protoplanetary disks, particularly at ''snow lines'' where a gas-phase species freezes out to form ice grains. Such sharp discontinuities will diffuse out due to the turbulence suspected to drive angular momentum transport in accretion disks. We demonstrate that the concentration gradient—in the vicinity of the snow line—of a species present outside a snow line but destroyed inside is strongly sensitive to the level of turbulent diffusion (provided the chemical and transport timescales are decoupled) and provides a direct measurement of the radial ''Schmidt number'' (the ratio of the angular momentum transport to radial turbulent diffusion). Taking as an example the tracer species N 2 H + , which is expected to be destroyed inside the CO snow line (as recently observed in TW Hya) we show that ALMA observations possess significant angular resolution to constrain the Schmidt number. Since different turbulent driving mechanisms predict different Schmidt numbers, a direct measurement of the Schmidt number in accretion disks would allow inferences to be made about the nature of the turbulence

Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

Science.gov (United States)

Steffen, K.; Bindschadler, R.; Casassa, G.; Comiso, J.; Eppler, D.; Fetterer, F.; Hawkins, J.; Key, J.; Rothrock, D.; Thomas, R.;

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

Science.gov (United States)

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

1995-04-01

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

Tale of two pit lakes: initial results of a three-year study of the Main Zone and Waterline pit lakes near Houston, British Columbia, Canada

Science.gov (United States)

Crusius, John; Pieters, R.; Leung, A.; Whittle, P.; Pedersen, T.; Lawrence, G.; McNee, J.J.

2003-01-01

Pit lakes are becoming increasingly common in North America as well as in the rest of the world. They are created as openpit mines fill passively with ground water and surface inflows on cessation of mining activity. In many instances, the water quality in these pit lakes does not meet regulatory requirements due to a number of influences. The most important are the oxidation of sulfide minerals and the associated release of acid and metals and the flushing of soluble metals during pit filling. Examples of pit lakes with severe water-quality problems include the Berkeley Pit lake (Butte, MT) and the Liberty Pit lake (Nevada), whose waters are characterized by a pH near 3 and Cu concentrations as high as ~150 mg/L (Miller et al., 1996; Davis and Eary, 1997). The importance of the problem can be seen in the fact that some of these sites in the United States are Superfund sites.

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

Science.gov (United States)

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

2018-03-01

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

Photopolarimetric Retrievals of Snow Properties

Science.gov (United States)

Ottaviani, M.; van Diedenhoven, B.; Cairns, B.

2015-01-01

Polarimetric observations of snow surfaces, obtained in the 410-2264 nm range with the Research Scanning Polarimeter onboard the NASA ER-2 high-altitude aircraft, are analyzed and presented. These novel measurements are of interest to the remote sensing community because the overwhelming brightness of snow plagues aerosol and cloud retrievals based on airborne and spaceborne total reflection measurements. The spectral signatures of the polarized reflectance of snow are therefore worthwhile investigating in order to provide guidance for the adaptation of algorithms currently employed for the retrieval of aerosol properties over soil and vegetated surfaces. At the same time, the increased information content of polarimetric measurements allows for a meaningful characterization of the snow medium. In our case, the grains are modeled as hexagonal prisms of variable aspect ratios and microscale roughness, yielding retrievals of the grains' scattering asymmetry parameter, shape and size. The results agree with our previous findings based on a more limited data set, with the majority of retrievals leading to moderately rough crystals of extreme aspect ratios, for each scene corresponding to a single value of the asymmetry parameter.

An Ultra-Wideband, Microwave Radar for Measuring Snow Thickness on Sea Ice and Mapping Near-Surface Internal Layers in Polar Firn

Science.gov (United States)

Panzer, Ben; Gomez-Garcia, Daniel; Leuschen, Carl; Paden, John; Rodriguez-Morales, Fernando; Patel, Azsa; Markus, Thorsten; Holt, Benjamin; Gogineni, Prasad

2013-01-01

Sea ice is generally covered with snow, which can vary in thickness from a few centimeters to >1 m. Snow cover acts as a thermal insulator modulating the heat exchange between the ocean and the atmosphere, and it impacts sea-ice growth rates and overall thickness, a key indicator of climate change in polar regions. Snow depth is required to estimate sea-ice thickness using freeboard measurements made with satellite altimeters. The snow cover also acts as a mechanical load that depresses ice freeboard (snow and ice above sea level). Freeboard depression can result in flooding of the snow/ice interface and the formation of a thick slush layer, particularly in the Antarctic sea-ice cover. The Center for Remote Sensing of Ice Sheets (CReSIS) has developed an ultra-wideband, microwave radar capable of operation on long-endurance aircraft to characterize the thickness of snow over sea ice. The low-power, 100mW signal is swept from 2 to 8GHz allowing the air/snow and snow/ ice interfaces to be mapped with 5 c range resolution in snow; this is an improvement over the original system that worked from 2 to 6.5 GHz. From 2009 to 2012, CReSIS successfully operated the radar on the NASA P-3B and DC-8 aircraft to collect data on snow-covered sea ice in the Arctic and Antarctic for NASA Operation IceBridge. The radar was found capable of snow depth retrievals ranging from 10cm to >1 m. We also demonstrated that this radar can be used to map near-surface internal layers in polar firn with fine range resolution. Here we describe the instrument design, characteristics and performance of the radar.

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

Regime shift of snow days in Switzerland

Science.gov (United States)

Marty, Christoph

2008-06-01

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

PITTING CORROSION OF STAINLESS STEEL AT THE VARIOUS SURFACE TREATMENT

Directory of Open Access Journals (Sweden)

Viera Zatkalíková

2011-09-01

Full Text Available The stainless steel surface treatment is very important with regard to its pitting corrosion susceptibility. An effect of various types surfacing on pitting corrosion resistance of AISI 304stainless steel is investigated in this work. The samples of the tested material are turned, blasted, peened, grinded and a half of them are pickled to achieve higher purity of surfaces and better quality of passive film. Eight types of different finished surfaces are tested by electrochemical and immersion tests to determine corrosion behaviour in conditions where pitting is evoked by controlled potential and second by solution with high redox potential. By this way the effect of mechanical and chemical surface treatment on the resistance to pitting corrosion, character, size and shape of pits are compared in the conditions of different mechanisms of corrosion process.

Insights on nitrate sources at Dome C (East Antarctic Plateau from multi-year aerosol and snow records

Directory of Open Access Journals (Sweden)

Rita Traversi

2014-06-01

Full Text Available Here we present the first multi-year record of nitrate in the atmospheric aerosol (2005–2008 and surface snow (2006–08 from central Antarctica. PM10 and size-segregated aerosol, together with superficial snow, have been collected all year-round at high resolution (daily for all the snow samples and for most of aerosol samples at Dome C since the 2004/05 field season and analysed for main and trace ionic markers. The suitability of the sampling location in terms of possible contamination from the base is shown in detail. In spite of the relevance of nitrate in Antarctic atmosphere, both for better understanding the chemistry of N cycle in the plateau boundary layer and for improving the interpretation of long-term nitrate records from deep ice core records, nitrate sources in Antarctica are not well constrained yet, neither in extent nor in timing. A recurring seasonal pattern was pointed out in both aerosol and snow records, showing summer maxima and winter minima, although aerosol maxima lead the snow ones of 1–2 months, possibly due to a higher acidity in the atmosphere in mid-summer, favouring the repartition of nitrate as nitric acid and thus its uptake by the surface snow layers. On the basis of a meteorological analysis of one major nitrate event, of data related to PSC I extent and of irradiance values, we propose that the high nitrate summer levels in aerosol and snow are likely due to a synergy of enhanced source of nitrate and/or its precursors (such as the stratospheric inputs, higher solar irradiance and higher oxidation rates in this season. Moreover, we show here a further evidence of the substantial contribution of HNO3/NOx re-emission from the snowpack, already shown in previous works, and which can explain a significant fraction of atmospheric nitrate, maintaining the same seasonal pattern in the snow. As concerning snow specifically, the presented data suggest that nitrate is likely to be controlled mainly by atmospheric

Fusion of NASA Airborne Snow Observatory (ASO Lidar Time Series over Mountain Forest Landscapes

Directory of Open Access Journals (Sweden)

António Ferraz

2018-01-01

Full Text Available Mountain ecosystems are among the most fragile environments on Earth. The availability of timely updated information on forest 3D structure would improve our understanding of the dynamic and impact of recent disturbance and regeneration events including fire, insect damage, and drought. Airborne lidar is a critical tool for monitoring forest change at high resolution but it has been little used for this purpose due to the scarcity of long-term time-series of measurements over a common region. Here, we investigate the reliability of on-going, multi-year lidar observations from the NASA-JPL Airborne Snow Observatory (ASO to characterize forest 3D structure at a fine spatial scale. In this study, weekly ASO measurements collected at ~1 pt/m2, primarily acquired to quantify snow volume and dynamics, are coherently merged to produce high-resolution point clouds ( ~ 12 pt/m2 that better describe forest structure. The merging methodology addresses the spatial bias in multi-temporal data due to uncertainties in platform trajectory and motion by collecting tie objects from isolated tree crown apexes in the lidar data. The tie objects locations are assigned to the centroid of multi-temporal lidar points to fuse and optimize the location of multiple measurements without the need for ancillary data or GPS control points. We apply the methodology to ASO lidar acquisitions over the Tuolumne River Basin in the Sierra Nevada, California, during the 2014 snow monitoring campaign and provide assessment of the fidelity of the fused point clouds for forest mountain ecosystem studies. The availability of ASO measurements that currently span 2013–2017 enable annual forest monitoring of important vegetated ecosystems that currently face ecological threads of great significance such as the Sierra Nevada (California and Olympic National Forest (Washington.

Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

Science.gov (United States)

Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick

2015-01-01

Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

Temporally delineated sources of major chemical species in high Arctic snow

Directory of Open Access Journals (Sweden)

K. M. Macdonald

2018-03-01

Full Text Available Long-range transport of aerosol from lower latitudes to the high Arctic may be a significant contributor to climate forcing in the Arctic. To identify the sources of key contaminants entering the Canadian High Arctic an intensive campaign of snow sampling was completed at Alert, Nunavut, from September 2014 to June 2015. Fresh snow samples collected every few days were analyzed for black carbon, major ions, and metals, and this rich data set provided an opportunity for a temporally refined source apportionment of snow composition via positive matrix factorization (PMF in conjunction with FLEXPART (FLEXible PARTicle dispersion model potential emission sensitivity analysis. Seven source factors were identified: sea salt, crustal metals, black carbon, carboxylic acids, nitrate, non-crustal metals, and sulfate. The sea salt and crustal factors showed good agreement with expected composition and primarily northern sources. High loadings of V and Se onto Factor 2, crustal metals, was consistent with expected elemental ratios, implying these metals were not primarily anthropogenic in origin. Factor 3, black carbon, was an acidic factor dominated by black carbon but with some sulfate contribution over the winter-haze season. The lack of K+ associated with this factor, a Eurasian source, and limited known forest fire events coincident with this factor's peak suggested a predominantly anthropogenic combustion source. Factor 4, carboxylic acids, was dominated by formate and acetate with a moderate correlation to available sunlight and an oceanic and North American source. A robust identification of this factor was not possible; however, atmospheric photochemical reactions, ocean microlayer reaction, and biomass burning were explored as potential contributors. Factor 5, nitrate, was an acidic factor dominated by NO3−, with a likely Eurasian source and mid-winter peak. The isolation of NO3− on a separate factor may reflect its complex atmospheric

Modelling assessment of End Pit Lakes meromictic potential

International Nuclear Information System (INIS)

2006-11-01

The use of End Pit Lakes have been proposed as a remediation solution for oil sands reclamation and operational waters. This report modelled the main factors controlling the occurrence of stratification in Pit Lakes in order to establish design and management guidelines for the Cumulative Environmental Management Association's End Pit Lake Sub-group. The study focused on End Pit Lake size, depth, starting lake salinity concentrations, inflow rates and inflow salinity flux, and investigated their influence on density gradients. One-dimensional modelling and limited 2-D modelling simulations were conducted to examine meromictic potential for a large range of End Pit Lake configurations and conditions. Modelling results showed that fall is the governing season for determining meromixis. The expelling of salt from saline water upon ice formation and its effect on stratification potential and the effect of fresh water loading on stratification potential during spring melt events were not observed to be dominant factors governing meromictic potential for the scenarios examined in the study. Results suggested that shallow End Pit Lakes showed a high turn-over rate with seasonal heating and cooling cycles. Moderately deep End Pit Lakes demonstrated a meromictic potential that was inversely proportional to lake size and require higher starting salinities. With a 2 or 10 million m 3 /yr inflow rate and a 5 parts per thousand starting salinity, a 50 m deep End Pit Lake achieved meromixis at all 3 size ranges considered in the study. Results also showed that the rate of influent salinity decrease was the least important of the parameters influencing meromixis. It was observed that meromixis was a temporary condition in all of the End Pit Lake scenarios envisioned due to the lack of a constant, positive salt replenishment over the long term. It was concluded that further 3-D modelling is required to represent littoral areas as well as to account for extreme winter conditions. A

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

Science.gov (United States)

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

1995-11-01

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

Pit 9 project: A private sector initiative

International Nuclear Information System (INIS)

Macdonald, D.W.; Hughes, F.P.; Burton, B.N.

1993-01-01

This report discusses the Pit 9 Comprehensive Demonstration which is intended to demonstrate a cost-effective approach to remediate an Idaho National Engineering Laboratory (INEL) waste disposal pit through a Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Interim Action. The remediation will include additional requirements, if needed, to provide high confidence that only minor additional work would be necessary to accomplish the final closure as part of the overall final closure strategy for the INEL's Subsurface Disposal Area (SDA)

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.

New high-resolution record of Holocene climate change in the Weddell Sea from combined biomarker analysis of the Patriot Hills blue ice area

Science.gov (United States)

Fogwill, Christopher; Turney, Chris; Baker, Andy; Ellis, Bethany; Cooper, Alan; Etheridge, David; Rubino, Mauro; Thornton, David; Fernando, Francisco; Bird, Michale; Munksgaard, Niels

2017-04-01

We report preliminary analysis of biomarkers (including dissolved organic matter (DOM) and DNA) from the Patriot Hills blue ice area (BIA), from the Ellsworth Mountains in the Weddell Sea Embayment. Preliminary isotopic and multiple gas analysis (CO2, CH4, N2O and CO) demonstrate that the Holocene comprises more than 50% of the 800m long BIA record, and in combination isotopic and biomarker analysis reveals a remarkable record of centennial variability through the Holocene in this sector of the Weddell Sea. Analysis using a Horiba Aqualog - which measures the fluorescence of DOM by producing a map of the fluorescence through an excitation-emission matrix (EEM) - identifies the presence of two marine protein-like components in both modern snow pit samples and within the Holocene part of Patriot Hills BIA transect. Intriguingly, the modern seasonal trends in DOM, recorded in contemporary snow pits, have relatively low signals compared to those recorded in the mid-Holocene record, suggesting a reduction in DOM signal in contemporary times. Given that the δD excess data suggests the source of precipitation has remained constant through the Holocene, the biomarker signal must relate to multi-year marine productivity signals from the Weddell Sea. The marked variability in DOM between the mid-Holocene and contemporary times can only relate to periods of sustained, enhanced biological productivity in the Weddell Sea associated with shifts in Southern Annular Mode, sea ice variability, changes in ventilation or polynya activity. Here we discuss the possible drivers of these changes and describe how this approach at this BIA could benefit conventional ice core records regionally.

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

International Nuclear Information System (INIS)

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

2008-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-11-01

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

Snow Extent Variability in Lesotho Derived from MODIS Data (2000–2014

Directory of Open Access Journals (Sweden)

Stefan Wunderle

2016-05-01

Full Text Available In Lesotho, snow cover is not only highly relevant to the climate system, but also affects socio-economic factors such as water storage for irrigation or hydro-electricity. However, while sound knowledge of annual and inter-annual snow dynamics is strongly required by local stakeholders, in-situ snow information remains limited. In this study, satellite data are used to generate a time series of snow cover and to provide the missing information on a national scale. A snow retrieval method, which is based on MODIS data and considers the concept of a normalized difference snow index (NDSI, has been implemented. Monitoring gaps due to cloud cover are filled by temporal and spatial post-processing. The comparison is based on the use of clear sky reference images from Landsat-TM and ENVISAT-MERIS. While the snow product is considered to be of good quality (mean accuracy: 68%, a slight bias towards snow underestimation is observed. Based on the daily product, a consistent time series of snow cover for Lesotho from 2000–2014 was generated for the first time. Analysis of the time series showed that the high annual variability of snow coverage and the short duration of single snow events require daily monitoring with a gap-filling procedure.

The Use of Pit and Fissure Sealants—A Literature Review

Directory of Open Access Journals (Sweden)

Reem Naaman

2017-12-01

Full Text Available This paper reviews the literature and discusses the latest updates on the use of pit and fissure sealants. It demonstrates the effectiveness of pit and fissure sealants in preventing caries and the management of early carious lesions. It compares the use of different sealant materials and their indications. It describes the application technique for sealants. It also reviews the cost-effectiveness of sealants as a preventive strategy. From this review and after the discussion of recently published studies on pit and fissure sealants, it is evident that sealants are effective in caries prevention and in preventing the progression of incipient lesions. It is therefore recommended that pit and fissure sealant be applied to high-caries-risk children for optimum cost-effectiveness. It is a highly sensitive technique that needs optimum isolation, cleaning of the tooth surface, etching, and the application of a thin bonding layer for maximum benefit. Recall and repair, when needed, are important to maximize the effectiveness of such sealant use.

The Use of Pit and Fissure Sealants—A Literature Review

Science.gov (United States)

Naaman, Reem; El-Housseiny, Azza A.; Alamoudi, Najlaa

2017-01-01

This paper reviews the literature and discusses the latest updates on the use of pit and fissure sealants. It demonstrates the effectiveness of pit and fissure sealants in preventing caries and the management of early carious lesions. It compares the use of different sealant materials and their indications. It describes the application technique for sealants. It also reviews the cost-effectiveness of sealants as a preventive strategy. From this review and after the discussion of recently published studies on pit and fissure sealants, it is evident that sealants are effective in caries prevention and in preventing the progression of incipient lesions. It is therefore recommended that pit and fissure sealant be applied to high-caries-risk children for optimum cost-effectiveness. It is a highly sensitive technique that needs optimum isolation, cleaning of the tooth surface, etching, and the application of a thin bonding layer for maximum benefit. Recall and repair, when needed, are important to maximize the effectiveness of such sealant use. PMID:29563440

Snow snake performance monitoring.

Science.gov (United States)

2008-12-01

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

Composição mineral e severidade de "bitter pit" em maçãs 'Catarina' Mineral composition and bitter pit severity in 'Catarina' apples

Directory of Open Access Journals (Sweden)

Cassandro Vidal Talamini do Amarante

2006-04-01

Full Text Available Maçãs 'Catarina', colhidas na maturação comercial em pomar no município de São Joaquim-SC, foram separadas em quatro lotes de 14 frutos, de acordo com a severidade de incidência de "bitter pit": nula (nenhuma lesão/fruto, baixa (1-2 lesões/fruto, moderada (3-5 lesões/fruto e alta (6-18 lesões/fruto. Foram determinadas as concentrações de Ca, Mg, K e N na casca e na polpa de cada fruto. Foram verificadas relação linear (P 'Catarina' apples were harvested at the commercial maturity in an orchard in São Joaquim-SC and segregated in four lots of 14 fruits with different levels of bitter pit severity: null (none pit/fruit, low (1-2 pits/fruit, moderate (3-5 pits/fruit, and high (6-18 pits/fruit. Nutritional analysis (Ca, Mg, K, and N in the skin and flesh tissues were performed on individual fruits of each severity level. The average number of pits/fruit (calculated for each lot of bitter pit severity showed a negative linear relationship (P < 0.05 with the skin Ca content, and a negative linear relationship (P < 0.05 with the ratios of Mg/Ca, (K+Mg/Ca, and (K+Mg+N/Ca in the skin. For the flesh, the increasing of bitter pit severity was accompanied by significant reduction of Ca and Mg contents. The multivariate analysis (canonical discriminant analysis showed that the Mg/Ca ratio in the skin provided the best discrimination between the lots of fruit with different levels of bitter pit severity. Therefore, for 'Catarina' apples, increasing values of the Mg/Ca ratio in the skin are indicative of fruits with increasing bitter pit susceptibility.

ANL high resolution injector

International Nuclear Information System (INIS)

Minehara, E.; Kutschera, W.; Hartog, P.D.; Billquist, P.

1985-01-01

The ANL (Argonne National Laboratory) high-resolution injector has been installed to obtain higher mass resolution and higher preacceleration, and to utilize effectively the full mass range of ATLAS (Argonne Tandem Linac Accelerator System). Preliminary results of the first beam test are reported briefly. The design and performance, in particular a high-mass-resolution magnet with aberration compensation, are discussed. 7 refs., 5 figs., 2 tabs

Baseline Risk Assessment for the F-Area Burning/Rubble Pits and Rubble Pit

Energy Technology Data Exchange (ETDEWEB)

Palmer, E. [Westinghouse Savannah River Company, AIKEN, SC (United States)

1996-03-01

This document provides an overview of the Savannah River Site (SRS) and a description of the F-Area Burning/Rubble Pits (BRPs) and Rubble Pit (RP) unit. It also describes the objectives and scope of the baseline risk assessment (BRA).

Multi-Sensor Approach to Mapping Snow Cover Using Data From NASA's EOS Aqua and Terra Spacecraft

Science.gov (United States)

Armstrong, R. L.; Brodzik, M. J.

2003-12-01

(0.05 deg.) allowing the blended product to indicate percent snow cover over the larger grid cell. Relationships between the percent area covered by snow as indicated by the MODIS data and the threshold for the appearance of snow as indicated by the passive microwave data are presented. Both MODIS and AMSR-E data have enhanced spatial resolution compared to the earlier data sources and examples of how this increased spatial resolution results in more accurate snow cover maps are presented. A wide range of validation data sets are being employed in this study including the NASA Cold Lands Processes Field Experiment undertaken in Colorado during 2002 and 2003.

Effects of selected water chemistry variables on copper pitting propagation in potable water

International Nuclear Information System (INIS)

Ha Hung; Taxen, Claes; Williams, Keith; Scully, John

2011-01-01

Highlights: → The effects of water composition on pit propagation kinetics on Cu were separated from pit initiation and stabilization using the artificial pit method in a range of dilute HCO 3 - , SO 4 2- and Cl - -containing waters. → The effective polarization and Ohmic resistance of pits were lower in SO4 2- -containing solutions and greater in Cl - -containing solutions. → Relationship between the solution composition and the corrosion product identity and morphology were found. → These, in turn controlled the corrosion product Ohmic resistance and subsequently the pit growth rate. - Abstract: The pit propagation behavior of copper (UNS C11000) was investigated from an electrochemical perspective using the artificial pit method. Pit growth was studied systematically in a range of HCO 3 - , SO 4 2- and Cl - containing-waters at various concentrations. Pit propagation was mediated by the nature of the corrosion products formed both inside and over the pit mouth (i.e., cap). Certain water chemistry concentrations such as those high in sulfate were found to promote fast pitting that could be sustained over long times at a fixed applied potential but gradually stifled in all but the lowest concentration solutions. In contrast, Cl - containing waters without sulfate ions resulted in slower pit growth and eventual repassivation. These observations were interpreted through understanding of the identity, amount and porosity of corrosion products formed inside and over pits. These factors controlled their resistive nature as characterized using electrochemical impedance spectroscopy. A finite element model (FEM) was developed which included copper oxidation kinetics, transport by migration and diffusion, Cu(I) and Cu(II) solid corrosion product formation and porosity governed by equilibrium thermodynamics and a saturation index, as well as pit current and depth of penetration. The findings of the modeling were in good agreement with artificial pit experiments

Intercomparison and validation of snow albedo parameterization schemes in climate models

Energy Technology Data Exchange (ETDEWEB)

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

2005-09-01

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

Assessing the Climate Change Impact on Snow-Glacier Melting Dominated Basins in the Greater Himalaya Region Using a Distributed Glacio-Hydrologic Model

Science.gov (United States)

Wi, S.; Yang, Y. C. E.; Khalil, A.

2014-12-01

Glacier and snow melting is main source of water supply making a large contribution to streamflow of major river basins in the Greater Himalaya region including the Syr Darya, the Amu Darya, the Indus, the Ganges and the Brahmaputra basins. Due to the critical role of glacier and snow melting as water supply for both food production and hydropower generation in the region (especially during the low flow season), it is important to evaluate the vulnerability of snow and glacier melting streamflow to different climate conditions. In this study, a distributed glacio-hydrologic model with high resolution climate input is developed and calibrated that explicitly simulates all major hydrological processes and the glacier and snow dynamics for area further discretized by elevation bands. The distributed modeling structure and the glacier and snow modules provide a better understanding about how temperature and precipitation alterations are likely to affect current glacier ice reserves. Climate stress test is used to explore changes in the total streamflow change, snow/glacier melting contribution and glacier accumulation and ablation under a variety of different temperature and precipitation conditions. The latest future climate projections provided from the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) is used to inform the possibility of different climate conditions.