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

Energy Technology Data Exchange (ETDEWEB)

Wass, Eva (Geosigma AB (Sweden))

2011-07-15

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

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

International Nuclear Information System (INIS)

Wass, Eva

2011-07-01

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

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

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.

Is Eurasian October snow cover extent increasing?

International Nuclear Information System (INIS)

Brown, R D; Derksen, C

2013-01-01

A number of recent studies present evidence of an increasing trend in Eurasian snow cover extent (SCE) in the October snow onset period based on analysis of the National Oceanic and Atmospheric Administration (NOAA) historical satellite record. These increases are inconsistent with fall season surface temperature warming trends across the region. Using four independent snow cover data sources (surface observations, two reanalyses, satellite passive microwave retrievals) we show that the increasing SCE is attributable to an internal trend in the NOAA CDR dataset to chart relatively more October snow cover extent over the dataset overlap period (1982–2005). Adjusting the series for this shift results in closer agreement with other independent datasets, stronger correlation with continentally-averaged air temperature anomalies, and a decrease in SCE over 1982–2011 consistent with surface air temperature warming trends over the same period. (letter)

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

Science.gov (United States)

Zhang, Yinsheng; Ma, Ning

2018-04-01

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

Estimation of snow cover distribution in Beas basin, Indian Himalaya ...

Indian Academy of Sciences (India)

In the present paper, a methodology has been developed for the mapping of snow cover in Beas ... Different snow cover mapping methods using snow indices are compared to find the suitable ... cover are important factors for human activities,.

Modeling the influence of snow cover temperature and water content on wet-snow avalanche runout

Directory of Open Access Journals (Sweden)

C. Vera Valero

2018-03-01

Full Text Available Snow avalanche motion is strongly dependent on the temperature and water content of the snow cover. In this paper we use a snow cover model, driven by measured meteorological data, to set the initial and boundary conditions for wet-snow avalanche calculations. The snow cover model provides estimates of snow height, density, temperature and liquid water content. This information is used to prescribe fracture heights and erosion heights for an avalanche dynamics model. We compare simulated runout distances with observed avalanche deposition fields using a contingency table analysis. Our analysis of the simulations reveals a large variability in predicted runout for tracks with flat terraces and gradual slope transitions to the runout zone. Reliable estimates of avalanche mass (height and density in the release and erosion zones are identified to be more important than an exact specification of temperature and water content. For wet-snow avalanches, this implies that the layers where meltwater accumulates in the release zone must be identified accurately as this defines the height of the fracture slab and therefore the release mass. Advanced thermomechanical models appear to be better suited to simulate wet-snow avalanche inundation areas than existing guideline procedures if and only if accurate snow cover information is available.

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

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

Science.gov (United States)

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

2018-02-01

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

Characteristics of snow cover duration across the northeast United States of America

Science.gov (United States)

Leathers, Daniel J.; Luff, Barbara L.

1997-11-01

The presence or absence of a snow cover affects a myriad of environmental and societal systems through its modification of the surface radiation balance and its ultimate impact on near-surface air temperatures. Daily snow cover data were collected for a network of 91 stations covering the northeast USA from Maine, south through to West Virginia. The snow cover data along with ancillary temperature, snowfall and precipitation data were used to investigate the characteristics of snow cover duration in this region and the effects of the snow cover on boundary layer climate variables for the snow cover seasons 1948-1949 through to 1987-1988.Results indicate that snow cover duration is variable in both space and time. The duration of a snow cover of 2.5 cm or greater varies from greater than 100 days in northern New England to less than 20 days across areas of Delaware, Maryland and West Virginia. Temporally, snow cover duration for the region as a whole was very short from the late 1940s through to the mid-1950s. From the late 1950s to the end of the period snow cover duration has varied around a consistent mean value. No long-term trends in snow cover duration are apparent in the record for the northeast USA.Principal components analysis and clustering techniques were utilized to isolate spatially coherent regions in which snow cover duration has varied similarly over the period of record. This analysis resulted in the identification of four snow-cover-duration regions across the northeast USA: including (i) the West Virginia area, (ii) the mid-Atlantic from southern New England through to western Pennsylvania, (iii) western and central New York and (iv) northern New England. Snow cover duration is shown to be highly associated with snowfall and temperature but not strongly related to total liquid precipitation. The intra-annual variability of snow cover duration is also investigated for each region.

Snow cover distribution over elevation zones in a mountainous catchment

Science.gov (United States)

Panagoulia, D.; Panagopoulos, Y.

2009-04-01

A good understanding of the elevetional distribution of snow cover is necessary to predict the timing and volume of runoff. In a complex mountainous terrain the snow cover distribution within a watershed is highly variable in time and space and is dependent on elevation, slope, aspect, vegetation type, surface roughness, radiation load, and energy exchange at the snow-air interface. Decreases in snowpack due to climate change could disrupt the downstream urban and agricultural water supplies, while increases could lead to seasonal flooding. Solar and longwave radiation are dominant energy inputs driving the ablation process. Turbulent energy exchange at the snow cover surface is important during the snow season. The evaporation of blowing and drifting snow is strongly dependent upon wind speed. Much of the spatial heterogeneity of snow cover is the result of snow redistribution by wind. Elevation is important in determining temperature and precipitation gradients along hillslopes, while the temperature gradients determine where precipitation falls as rain and snow and contribute to variable melt rates within the hillslope. Under these premises, the snow accumulation and ablation (SAA) model of the US National Weather Service (US NWS) was applied to implement the snow cover extent over elevation zones of a mountainous catchment (the Mesochora catchment in Western-Central Greece), taking also into account the indirectly included processes of sublimation, interception, and snow redistribution. The catchment hydrology is controlled by snowfall and snowmelt and the simulated discharge was computed from the soil moisture accounting (SMA) model of the US NWS and compared to the measured discharge. The elevationally distributed snow cover extent presented different patterns with different time of maximization, extinction and return during the year, producing different timing of discharge that is a crucial factor for the control and management of water resources systems.

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.

On the impact of snow cover on daytime pollution dispersion

Science.gov (United States)

Segal, M.; Garratt, J. R.; Pielke, R. A.; Hildebrand, P.; Rogers, F. A.; Cramer, J.; Schanot, A.

A preliminary evaluation of the impact of snow cover on daytime pollutant dispersion conditions is made by using conceptual, scaling, and observational analyses. For uniform snow cover and synoptically unperturbed sunny conditions, observations indicate a considerate suppression of the surface sensible heat flux, the turbulence, and the development of the daytime atmospheric boundary layer (ABL) when compared to snow-free conditions. However, under conditions of non-uniform snow cover, as in urban areas, or associated with vegetated areas or bare ground patches, a milder effect on pollutant dispersion conditions would be expected. Observed concentrations of atmospheric particles within the ABL, and surface pollutant concentrations in urban areas, reflect the impact of snow cover on the modification of ABL characteristics.

Snow cover and temperature relationships in North America and Eurasia

Science.gov (United States)

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

1983-01-01

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

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

Estimating Snow Cover from Publicly Available Images

OpenAIRE

Fedorov, Roman; Camerada, Alessandro; Fraternali, Piero; Tagliasacchi, Marco

2016-01-01

In this paper we study the problem of estimating snow cover in mountainous regions, that is, the spatial extent of the earth surface covered by snow. We argue that publicly available visual content, in the form of user generated photographs and image feeds from outdoor webcams, can both be leveraged as additional measurement sources, complementing existing ground, satellite and airborne sensor data. To this end, we describe two content acquisition and processing pipelines that are tailored to...

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

Directory of Open Access Journals (Sweden)

Yu Lu

2010-03-01

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

UAS applications in high alpine, snow-covered terrain

Science.gov (United States)

Bühler, Y.; Stoffel, A.; Ginzler, C.

2017-12-01

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

Variability in snow cover phenology in China from 1952 to 2010

OpenAIRE

C. Q. Ke; X. C. Li; H. Xie; X. Liu; C. Kou

2015-01-01

Daily snow observation data from 672 stations, particularly the 352 stations with over ten annual mean snow cover days (SCD), during 1952–2010 in China, are used in this study. We first examine spatiotemporal variations and trends of SCD, snow cover onset date (SCOD), and snow cover end date (SCED). We then investigate SCD relationships with number of days with temperature below 0 °C (TBZD), mean air temperature (MAT), and Arctic Oscillation (AO) index, the ...

Springtime warming and reduced snow cover from carbonaceous particles

Directory of Open Access Journals (Sweden)

M. G. Flanner

2009-04-01

Full Text Available Boreal spring climate is uniquely susceptible to solar warming mechanisms because it has expansive snow cover and receives relatively strong insolation. Carbonaceous particles can influence snow coverage by warming the atmosphere, reducing surface-incident solar energy (dimming, and reducing snow reflectance after deposition (darkening. We apply a range of models and observations to explore impacts of these processes on springtime climate, drawing several conclusions: 1 Nearly all atmospheric particles (those with visible-band single-scatter albedo less than 0.999, including all mixtures of black carbon (BC and organic matter (OM, increase net solar heating of the atmosphere-snow column. 2 Darkening caused by small concentrations of particles within snow exceeds the loss of absorbed energy from concurrent dimming, thus increasing solar heating of snowpack as well (positive net surface forcing. Over global snow, we estimate 6-fold greater surface forcing from darkening than dimming, caused by BC+OM. 3 Equilibrium climate experiments suggest that fossil fuel and biofuel emissions of BC+OM induce 95% as much springtime snow cover loss over Eurasia as anthropogenic carbon dioxide, a consequence of strong snow-albedo feedback and large BC+OM emissions from Asia. 4 Of 22 climate models contributing to the IPCC Fourth Assessment Report, 21 underpredict the rapid warming (0.64°C decade⁻¹ observed over springtime Eurasia since 1979. Darkening from natural and anthropogenic sources of BC and mineral dust exerts 3-fold greater forcing on springtime snow over Eurasia (3.9 W m⁻² than North America (1.2 W m⁻². Inclusion of this forcing significantly improves simulated continental warming trends, but does not reconcile the low bias in rate of Eurasian spring snow cover decline exhibited by all models, likely because BC deposition trends are negative or near-neutral over much of Eurasia. Improved Eurasian

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

Indian Academy of Sciences (India)

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

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 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)

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

Science.gov (United States)

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

2018-03-01

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

Variability in snow cover phenology in China from 1952 to 2010

OpenAIRE

Ke, Chang-Qing; Li, Xiu-Cang; Xie, Hongjie; Ma, Dong-Hui; Liu, Xun; Kou, Cheng

2016-01-01

Daily snow observation data from 672 stations in China, particularly the 296 stations with over 10 mean snow cover days (SCDs) in a year during the period of 1952–2010, are used in this study. We first examine spatiotemporal variations and trends of SCDs, snow cover onset date (SCOD), and snow cover end date (SCED). We then investigate the relationships of SCDs with number of days with temperature below 0 °C (TBZD), mean air temperature (MAT), and Arctic Oscillation (AO) index....

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

Directory of Open Access Journals (Sweden)

David J. Selkowitz

2014-12-01

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

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

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.

Dynamics of actual aggregation of petroleum products in snow cover

Science.gov (United States)

Begunova, L. A.; Kuznetsova, O. V.; Begunov, D. A.; Kuznetsova, A. N.

2017-11-01

The paper presents issues of snow cover pollution by petroleum products. Petroleum products content was determined using the fluorimetric method of analysis. The samples of snow were selected on the territory of Angarsk and Irkutsk cities. According to the obtained data, the content of petroleum products in the analyzed samples exceeds the background value up to 6 times. Analysis of the reference data for similar research confirms need for creation of an environmental monitoring centralized system to monitor atmospheric precipitation and, particularly, snow cover.

Global warming: Sea ice and snow cover

International Nuclear Information System (INIS)

Walsh, J.E.

1993-01-01

In spite of differences among global climate simulations under scenarios where atmospheric CO 2 is doubled, all models indicate at least some amplification of greenouse warming at the polar regions. Several decades of recent data on air temperature, sea ice, and snow cover of the high latitudes of the Northern Hemisphere are summarized to illustrate the general compatibility of recent variations in those parameters. Despite a data void over the Arctic Ocean, some noteworthy patterns emerge. Warming dominates in winter and spring, as projected by global climate models, with the warming strongest over subpolar land areas of Alaska, northwestern Canada, and northern Eurasia. A time-longitude summary of Arctic sea ice variations indicates that timescales of most anomalies range from several months to several years. Wintertime maxima of total sea ice extent contain no apparent secular trends. The statistical significance of trends in recent sea ice variations was evaluated by a Monte Carlo procedure, showing a statistically significant negative trend in the summer. Snow cover data over the 20-y period of record show a noticeable decrease of Arctic snow cover in the late 1980s. This is of potential climatic significance since the accompanying decrease of surface albedo leads to a rapid increase of solar heating. 21 refs., 3 figs., 1 tab

Mechanical construction and installation of the ATLAS tile calorimeter

Energy Technology Data Exchange (ETDEWEB)

Abdallah, J [IFIC, Centro Mixto Universidad de Valencia-CSIC, E46100 Burjassot, Valencia (Spain); Adragna, P; Bosi, F [Pisa University and INFN, Pisa (Italy); Alexa, C; Boldea, V [Institute of Atomic Physics, Bucharest (Romania); Alves, R [LIP and FCTUC University of Coimbra (Portugal); Amaral, P; Andresen, X; Behrens, A; Blocki, J [CERN, Geneva (Switzerland); Ananiev, A [LIP and IDMEC-IST, Lisbon (Portugal); Anderson, K [University of Chicago, Chicago, Illinois (United States); Antonaki, A [University of Athens, Athens (Greece); Batusov, V [JINR, Dubna (Russian Federation); Bednar, P [Comenius University, Bratislava (Slovakia); Bergeaas, E; Bohm, C [Stockholm University, Stockholm (Sweden); Biscarat, C [LPC Clermont-Ferrand, Université Blaise Pascal, Clermont-Ferrand (France); Blanch, O; Blanchot, G [Institut de Fisica d' Altes Energies, Universitat Autònoma de Barcelona, Barcelona (Spain); others, and

2013-11-01

This paper summarises the mechanical construction and installation of the Tile Calorimeter for the ATLAS experiment at the Large Hadron Collider in CERN, Switzerland. The Tile Calorimeter is a sampling calorimeter using scintillator as the sensitive detector and steel as the absorber and covers the central region of the ATLAS experiment up to pseudorapidities ±1.7. The mechanical construction of the Tile Calorimeter occurred over a period of about 10 years beginning in 1995 with the completion of the Technical Design Report and ending in 2006 with the installation of the final module in the ATLAS cavern. During this period approximately 2600 metric tons of steel were transformed into a laminated structure to form the absorber of the sampling calorimeter. Following instrumentation and testing, which is described elsewhere, the modules were installed in the ATLAS cavern with a remarkable accuracy for a structure of this size and weight.

Mechanical construction and installation of the ATLAS tile calorimeter

International Nuclear Information System (INIS)

Abdallah, J; Adragna, P; Bosi, F; Alexa, C; Boldea, V; Alves, R; Amaral, P; Andresen, X; Behrens, A; Blocki, J; Ananiev, A; Anderson, K; Antonaki, A; Batusov, V; Bednar, P; Bergeaas, E; Bohm, C; Biscarat, C; Blanch, O; Blanchot, G

2013-01-01

This paper summarises the mechanical construction and installation of the Tile Calorimeter for the ATLAS experiment at the Large Hadron Collider in CERN, Switzerland. The Tile Calorimeter is a sampling calorimeter using scintillator as the sensitive detector and steel as the absorber and covers the central region of the ATLAS experiment up to pseudorapidities ±1.7. The mechanical construction of the Tile Calorimeter occurred over a period of about 10 years beginning in 1995 with the completion of the Technical Design Report and ending in 2006 with the installation of the final module in the ATLAS cavern. During this period approximately 2600 metric tons of steel were transformed into a laminated structure to form the absorber of the sampling calorimeter. Following instrumentation and testing, which is described elsewhere, the modules were installed in the ATLAS cavern with a remarkable accuracy for a structure of this size and weight

Chemical elements contamination of snow cover in region of coal production 'Karazhyra'

International Nuclear Information System (INIS)

Evlampieva, E.P.; Panin, M.S.

2008-01-01

Peculiarities of space distribution of chemical elements in hardphase and water-soluble falls of snow cover in region of coal deposit 'Karazhyra' are investigated. The maximal, minimal and background areas of elements accumulation in the snow of this region and distribution of their cumulative rates are determined. The main pollutants of snow cover unto background level are revealed.

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

Science.gov (United States)

Kadlec, Jiri

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

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

Snow cover as a source of technogenic pollution of surface water during the snow melting period

OpenAIRE

Labuzova Olga; Noskova Tatyana; Lysenko Maria; Ovcharenko Elena; Papina Tatyana

2016-01-01

The study of pollutants in melt water of snow cover and snow disposal sites in the city of Barnaul showed that during the snow melting period the surface water is not subjected to significant technogenic impact according to a number of studied indices. The oils content is an exception: it can exceed MAC more than 20 times in river- water due to the melting of city disposal sites. Environmental damage due to an oils input into water resources during the snow melting period...

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.

Central Asian Snow Cover from Hydrometeorological Surveys

Data.gov (United States)

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

ATLAS construction status

International Nuclear Information System (INIS)

Jenni, P.

2006-01-01

The ATLAS detector is being constructed at the LHC, in view of a data-taking startup in 2007. This report concentrates on the progress and the technical challenges of the detector construction, and summarizes the status of the work as of August 2004. The project is on track to allow the highly motivated ATLAS Collaboration to enter into a new exploratory domain of high-energy physics in 2007. (author)

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

Directory of Open Access Journals (Sweden)

E. A. Istomina

2014-01-01

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

Reconstructed North American, Eurasian, and Northern Hemisphere Snow Cover Extent, 1915-1997

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains time series of monthly snow cover extent (SCE) for North America, Eurasia, and the Northern Hemisphere from 1915 to 1997, based on snow cover...

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.

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

Science.gov (United States)

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

2012-01-01

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

Remote sensing, hydrological modeling and in situ observations in snow cover research: A review

Science.gov (United States)

Dong, Chunyu

2018-06-01

Snow is an important component of the hydrological cycle. As a major part of the cryosphere, snow cover also represents a valuable terrestrial water resource. In the context of climate change, the dynamics of snow cover play a crucial role in rebalancing the global energy and water budgets. Remote sensing, hydrological modeling and in situ observations are three techniques frequently utilized for snow cover investigations. However, the uncertainties caused by systematic errors, scale gaps, and complicated snow physics, among other factors, limit the usability of these three approaches in snow studies. In this paper, an overview of the advantages, limitations and recent progress of the three methods is presented, and more effective ways to estimate snow cover properties are evaluated. The possibility of improving remotely sensed snow information using ground-based observations is discussed. As a rapidly growing source of volunteered geographic information (VGI), web-based geotagged photos have great potential to provide ground truth data for remotely sensed products and hydrological models and thus contribute to procedures for cloud removal, correction, validation, forcing and assimilation. Finally, this review proposes a synergistic framework for the future of snow cover research. This framework highlights the cross-scale integration of in situ and remotely sensed snow measurements and the assimilation of improved remote sensing data into hydrological models.

[Characteristics of chemical pollution of snow cover in Aktobe areas].

Science.gov (United States)

Iskakov, A Zh

2010-01-01

The paper gives data on the nature of snow cover pollution in the urbanized areas in relation to the remoteness from the basic sources of ambient air pollution. The total snow content of carcinogens has been estimated.

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

Snow cover as a source of technogenic pollution of surface water during the snow melting period

Directory of Open Access Journals (Sweden)

Labuzova Olga

2016-10-01

Full Text Available The study of pollutants in melt water of snow cover and snow disposal sites in the city of Barnaul showed that during the snow melting period the surface water is not subjected to significant technogenic impact according to a number of studied indices. The oils content is an exception: it can exceed MAC more than 20 times in river- water due to the melting of city disposal sites. Environmental damage due to an oils input into water resources during the snow melting period can be more than 300000 thousand rubles.

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.

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.

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

Science.gov (United States)

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

2013-08-01

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

Geochemistry of snow cover in taiga and alpine permafrost landscapes in Yakutia

Directory of Open Access Journals (Sweden)

V. N. Makarov

2014-01-01

Full Text Available The work is devoted to results of study the chemical composition of snow in mountain taiga and permafrost landscapes of Yakutia. We studied snow cover in different mountain-belt types of landscapes. The composition and calculated volumes of chemical elements and compounds are studied in snow. The chemical composition of snow in mountain taiga and permafrost landscape has remained relatively constant (hydrocarbonate chloride-bicarbonate or sodium-calcium, low sulfate content. The dominant influence on the chemical composition of snow at plains and mountain permafrost landscapes has a continental origin, mainly carbon compounds. In mountain desert, where there is predominantly regional transfer, along with the carbon significant role in atmospheric precipitation in cold season belongs to the nitrogen compounds, mainly ammonium. The total density of the entry of soluble and insoluble components in the form of snow decreases regularly with change of altitude. The distribution of trace elements in the snow cover is not a subject to altitudinal zonation. The maximum content of heavy metals (Mn, Cu, Pb, Cd, F, and Sr in the snow cover is observed in the landscapes of mountain woodlands and mountain tundra, where the route crossed research Sette-Daban metallogenic zone of stratiform Cu and Pb-Zn mineralization.

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

International Nuclear Information System (INIS)

Fujimoto, Kenzo; Kobayashi, Sadayoshi

1988-01-01

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

Spatiotemporal 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.

[Evaluation of pollution of an urban area by level of heavy metals in snow cover].

Science.gov (United States)

Stepanova, N V; Khamitova, R Ia; Petrova, R S

2003-01-01

The goal of this study was to systematize various methodological approaches to evaluating the contamination of the snow cover with heavy metals (HM) by using Kazan, an industrial city with diversified industry, as an example. The findings suggest that it is necessary to characterize the contamination of the snow cover by the actual entrance of an element per area unit of the snow cover for a definite period of time rather than by the concentration of TM in the volume unit of snow water (mg/l), which minimizes the uncertainties with spatial and temporary snow cover variations. The index of the maximum allowable entrance, which is of practical value, may be used to objectively calibrate the pollution of the snow cover, by estimating the amount of a coming element and its toxicity.

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.

High-resolution LIDAR and ground observations of snow cover in a complex forested terrain in the Sierra Nevada - implications for optical remote sensing of seasonal snow.

Science.gov (United States)

Kostadinov, T. S.; Harpold, A.; Hill, R.; McGwire, K.

2017-12-01

Seasonal snow cover is a key component of the hydrologic regime in many regions of the world, especially those in temperate latitudes with mountainous terrain and dry summers. Such regions support large human populations which depend on the mountain snowpack for their water supplies. It is thus important to quantify snow cover accurately and continuously in these regions. Optical remote-sensing methods are able to detect snow and leverage space-borne spectroradiometers with global coverage such as MODIS to produce global snow cover maps. However, snow is harder to detect accurately in mountainous forested terrain, where topography influences retrieval algorithms, and importantly - forest canopies complicate radiative transfer and obfuscate the snow. Current satellite snow cover algorithms assume that fractional snow-covered area (fSCA) under the canopy is the same as the fSCA in the visible portion of the pixel. In-situ observations and first principles considerations indicate otherwise, therefore there is a need for improvement of the under-canopy correction of snow cover. Here, we leverage multiple LIDAR overflights and in-situ observations with a distributed fiber-optic temperature sensor (DTS) to quantify snow cover under canopy as opposed to gap areas at the Sagehen Experimental Forest in the Northern Sierra Nevada, California, USA. Snow-off LIDAR overflights from 2014 are used to create a baseline high-resolution digital elevation model and classify pixels at 1 m resolution as canopy-covered or gap. Low canopy pixels are excluded from the analysis. Snow-on LIDAR overflights conducted by the Airborne Snow Observatory in 2016 are then used to classify all pixels as snow-covered or not and quantify fSCA under canopies vs. in gap areas over the Sagehen watershed. DTS observations are classified as snow-covered or not based on diel temperature fluctuations and used as validation for the LIDAR observations. LIDAR- and DTS-derived fSCA is also compared with

Proposed hybrid-classifier ensemble algorithm to map snow cover area

Science.gov (United States)

Nijhawan, Rahul; Raman, Balasubramanian; Das, Josodhir

2018-01-01

Metaclassification ensemble approach is known to improve the prediction performance of snow-covered area. The methodology adopted in this case is based on neural network along with four state-of-art machine learning algorithms: support vector machine, artificial neural networks, spectral angle mapper, K-mean clustering, and a snow index: normalized difference snow index. An AdaBoost ensemble algorithm related to decision tree for snow-cover mapping is also proposed. According to available literature, these methods have been rarely used for snow-cover mapping. Employing the above techniques, a study was conducted for Raktavarn and Chaturangi Bamak glaciers, Uttarakhand, Himalaya using multispectral Landsat 7 ETM+ (enhanced thematic mapper) image. The study also compares the results with those obtained from statistical combination methods (majority rule and belief functions) and accuracies of individual classifiers. Accuracy assessment is performed by computing the quantity and allocation disagreement, analyzing statistic measures (accuracy, precision, specificity, AUC, and sensitivity) and receiver operating characteristic curves. A total of 225 combinations of parameters for individual classifiers were trained and tested on the dataset and results were compared with the proposed approach. It was observed that the proposed methodology produced the highest classification accuracy (95.21%), close to (94.01%) that was produced by the proposed AdaBoost ensemble algorithm. From the sets of observations, it was concluded that the ensemble of classifiers produced better results compared to individual classifiers.

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

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.

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

Directory of Open Access Journals (Sweden)

Qiang Fu

2017-05-01

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

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.

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

Science.gov (United States)

Armstrong, Richard L.; Brodzik, Mary Jo

2003-04-01

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

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

Directory of Open Access Journals (Sweden)

E. Martin

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

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

Black carbon and mineral dust in snow cover on the Tibetan Plateau

Science.gov (United States)

Zhang, Yulan; Kang, Shichang; Sprenger, Michael; Cong, Zhiyuan; Gao, Tanguang; Li, Chaoliu; Tao, Shu; Li, Xiaofei; Zhong, Xinyue; Xu, Min; Meng, Wenjun; Neupane, Bigyan; Qin, Xiang; Sillanpää, Mika

2018-02-01

Snow cover plays a key role for sustaining ecology and society in mountainous regions. Light-absorbing particulates (including black carbon, organic carbon, and mineral dust) deposited on snow can reduce surface albedo and contribute to the near-worldwide melting of snow and ice. This study focused on understanding the role of black carbon and other water-insoluble light-absorbing particulates in the snow cover of the Tibetan Plateau (TP). The results found that the black carbon, organic carbon, and dust concentrations in snow cover generally ranged from 202 to 17 468 ng g-1, 491 to 13 880 ng g-1, and 22 to 846 µg g-1, respectively, with higher concentrations in the central to northern areas of the TP. Back trajectory analysis suggested that the northern TP was influenced mainly by air masses from Central Asia with some Eurasian influence, and air masses in the central and Himalayan region originated mainly from Central and South Asia. The relative biomass-burning-sourced black carbon contributions decreased from ˜ 50 % in the southern TP to ˜ 30 % in the northern TP. The relative contribution of black carbon and dust to snow albedo reduction reached approximately 37 and 15 %, respectively. The effect of black carbon and dust reduced the snow cover duration by 3.1 ± 0.1 to 4.4 ± 0.2 days. Meanwhile, the black carbon and dust had important implications for snowmelt water loss over the TP. The findings indicate that the impacts of black carbon and mineral dust need to be properly accounted for in future regional climate projections, particularly in the high-altitude cryosphere.

Organic compounds and suspended matter in the White Sea snow-ice cover

International Nuclear Information System (INIS)

Nemirovskaya, I.; Shevchenko, V.

2008-01-01

The pollution of the White Sea snow-ice cover was estimated by examining the distribution of organic compounds, including oil and pyrogenic hydrocarbons. Ice and snow cores were taken from Chupa Bay and the Kandalaksha Gulf in the Cape Kartesh area in the spring of 2004 and from the mouth of the Severnaya Dvina River in the spring of 2005, 2006, and 2007. This paper presented data on the lipid content, aliphatic hydrocarbons (AHC), polycyclic aromatic hydrocarbons (PAH) and suspended particulate matter in snow, ice and under-ice water. This paper focused on organic compounds and suspended matter (SM) concentrations in the sea snow-ice cover and described the ice forming conditions and interactions of the substances with ice, snow and sub-ice water. The amount of particulate matter and organic compounds in the snow increased sharply near industrial centres. The concentration of compounds decreased further away from these centres, suggesting that most pollutants are deposited locally. The study revealed that organic compounds concentrate in barrier zones, such as snow-ice and water-ice, depending on the source of pollution. There was no obvious evidence of petrogenic sources of PAHs in particulate matter from the White Sea snow-ice cover. The SM and organic compounds accumulated in layers characterized by local depositional processes. The zones remained biogeochemically active even under low temperature conditions, but the accumulation of both SM and organic compounds was at its highest during the initial stage of ice formation. 16 refs., 2 tabs., 4 figs

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

Science.gov (United States)

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

2018-05-15

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

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.

Complex responses of spring alpine vegetation phenology to snow cover dynamics over the Tibetan Plateau, China.

Science.gov (United States)

Wang, Siyuan; Wang, Xiaoyue; Chen, Guangsheng; Yang, Qichun; Wang, Bin; Ma, Yuanxu; Shen, Ming

2017-09-01

Snow cover dynamics are considered to play a key role on spring phenological shifts in the high-latitude, so investigating responses of spring phenology to snow cover dynamics is becoming an increasingly important way to identify and predict global ecosystem dynamics. In this study, we quantified the temporal trends and spatial variations of spring phenology and snow cover across the Tibetan Plateau by calibrating and analyzing time series of the NOAA AVHRR-derived normalized difference vegetation index (NDVI) during 1983-2012. We also examined how snow cover dynamics affect the spatio-temporal pattern of spring alpine vegetation phenology over the plateau. Our results indicated that 52.21% of the plateau experienced a significant advancing trend in the beginning of vegetation growing season (BGS) and 34.30% exhibited a delaying trend. Accordingly, the snow cover duration days (SCD) and snow cover melt date (SCM) showed similar patterns with a decreasing trend in the west and an increasing trend in the southeast, but the start date of snow cover (SCS) showed an opposite pattern. Meanwhile, the spatial patterns of the BGS, SCD, SCS and SCM varied in accordance with the gradients of temperature, precipitation and topography across the plateau. The response relationship of spring phenology to snow cover dynamics varied within different climate, terrain and alpine plant community zones, and the spatio-temporal response patterns were primarily controlled by the long-term local heat-water conditions and topographic conditions. Moreover, temperature and precipitation played a profound impact on diverse responses of spring phenology to snow cover dynamics. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

Kulasova, Alena

2015-04-01

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

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

Directory of Open Access Journals (Sweden)

Alexander Nestler

2014-07-01

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

Subpixel Snow-covered Area Including Differentiated Grain Size from AVIRIS Data Over the Sierra Nevada Mountain Range

Science.gov (United States)

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

2016-12-01

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. Previous retrieval of subpixel snow-covered area in alpine regions used multiple snow endmembers due to the sensitivity of snow spectral reflectance to grain size. We will 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 or melt state. The root mean squared error will provide a spectrum-wide assessment of the mixture model's goodness-of-fit. Analysis will compare snow-covered area and snow-cover depletion in the 2016 year, and annual variation from the 2015 year. Field data were also acquired on three days concurrent with the 2016 flights in the Sagehen Experimental Forest and will support ground validation of the airborne data set.

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

OpenAIRE

A. N. Gelfan; V. M. Moreido

2014-01-01

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

Monitoring and evaluation of seasonal snow cover in Kashmir valley ...

Indian Academy of Sciences (India)

89 to 2007–08) climatic conditions prevailed in both ranges of Kashmir valley. Region-wise ... effective use of snowmelt runoff models (Rango and Martinec ... J. Earth Syst. Sci. 118, No. ... of cloud cover can affect delineation of snow cover,.

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

Water availability forecasting for Naryn River using ground-based and satellite snow cover data

Directory of Open Access Journals (Sweden)

O. Y. Kalashnikova

2017-01-01

Full Text Available The main source of river nourishment in arid regions of Central Asia is the melting of seasonal snow accu‑ mulated in mountains during the cold period. In this study, we analyzed data on seasonal snow cover by ground‑based observations from Kyrgyzhydromet network, as well as from MODIS satellite imagery for the period of 2000–2015. This information was used to compile the forecast methods of water availability of snow‑ice and ice‑snow fed rivers for the vegetation period. The Naryn river basin was chosen as a study area which is the main tributary of Syrdarya River and belongs to the Aral Sea basin. The representative mete‑ orological stations with ground‑based observations of snow cover were identified and regression analysis between mean discharge for the vegetation period and number of snow covered days, maximum snow depth based on in‑situ data as well as snow cover area based on MODIS images was conducted. Based on this infor‑ mation, equations are derived for seasonal water availability forecasting using multiple linear regression anal‑ ysis. Proposed equations have high correlation coefficients (R = 0.89÷0.92 and  and fore‑ casting accuracy. The methodology was implemented in Kyrgyzhydromet and is used for forecasting of water availability in Naryn basin and water inflow into Toktogul Reservoir.

Observational evidence of changes in global snow and ice cover

International Nuclear Information System (INIS)

Barry, R.G.

1990-01-01

Sources of observational data on recent variations in the seasonal extent of snow cover and sea ice, of the terminal position and volume of alpine glaciers, and of ground temperature profiles in areas of permafrost are briefly reviewed. Recent evidence of changes in these variables is then examined. The extent of seasonal snow cover in the Northern hemisphere and of sea ice in both hemispheres has fluctuated irregularly over the last 15-20 years with a range of about 10-15% in each case. There is no clear evidence of any recent trends, despite general global warming. In contrast, most glaciers retreated and thinned from before the turn of the century until the 1960s and alaskan permafrost temperatures have risen 2-4 C per century. Recently, glacier advances have been noted, perhaps in response to increased accumulation. Problems of linking climate forcing and snow/ice responses are discussed

Threshold temperatures mediate the impact of reduced snow cover on overwintering freeze-tolerant caterpillars

Science.gov (United States)

Marshall, Katie E.; Sinclair, Brent J.

2012-01-01

Decreases in snow cover due to climate change could alter the energetics and physiology of ectothermic animals that overwinter beneath snow, yet how snow cover interacts with physiological thresholds is unknown. We applied numerical simulation of overwintering metabolic rates coupled with field validation to determine the importance of snow cover and freezing to the overwintering lipid consumption of the freeze-tolerant Arctiid caterpillar Pyrrharctia isabella. Caterpillars that overwintered above the snow experienced mean temperatures 1.3°C lower than those below snow and consumed 18.36 mg less lipid of a total 68.97-mg reserve. Simulations showed that linear temperature effects on metabolic rate accounted for only 30% of the difference in lipid consumption. When metabolic suppression by freezing was included, 93% of the difference between animals that overwintered above and below snow was explained. Our results were robust to differences in temperature sensitivity of metabolic rate, changes in freezing point, and the magnitude of metabolic suppression by freezing. The majority of the energy savings was caused by the non-continuous reduction in metabolic rate due to freezing, the first example of the importance of temperature thresholds in the lipid use of overwintering insects.

Removal of snow cover inhibits spring growth of Arctic ice algae through physiological and behavioral effects

DEFF Research Database (Denmark)

Lund-Hansen, L.C.; Hawes, Ian; Sorrell, Brian Keith

2014-01-01

The snow cover of Arctic sea ice has recently decreased, and climate models forecast that this will continue and even increase in future. We therefore tested the effect of snow cover on the optical properties of sea ice and the biomass, photobiology, and species composition of sea ice algae at Ka...... of the spring bloom is predominantly due to temperature effects on brine channel volume, and that the algal decline after snow removal was primarily due to emigration rather than photodamage.......The snow cover of Arctic sea ice has recently decreased, and climate models forecast that this will continue and even increase in future. We therefore tested the effect of snow cover on the optical properties of sea ice and the biomass, photobiology, and species composition of sea ice algae...... at Kangerlussuaq, West Greenland, during March 2011, using a snow-clearance experiment. Sea ice algae in areas cleared of snow was compared with control areas, using imaging variable fluorescence of photosystem II in intact, unthawed ice sections. The study coincided with the onset of spring growth of ice algae...

Use of AMSR-E microwave satellite data for land surface characteristics and snow cover variation

Directory of Open Access Journals (Sweden)

Mukesh Singh Boori

2016-12-01

Full Text Available This data article contains data related to the research article entitled “Global land cover classification based on microwave polarization and gradient ratio (MPGR” [1] and “Microwave polarization and gradient ratio (MPGR for global land surface phenology” [2]. This data article presents land surface characteristics and snow cover variation information from sensors like EOS Advanced Microwave Scanning Radiometer (AMSR-E. This data article use the HDF Explorer, Matlab, and ArcGIS software to process the pixel latitude, longitude, snow water equivalent (SWE, digital elevation model (DEM and Brightness Temperature (BT information from AMSR-E satellite data to provide land surface characteristics and snow cover variation data in all-weather condition at any time. This data information is useful to discriminate different land surface cover types and snow cover variation, which is turn, will help to improve monitoring of weather, climate and natural disasters.

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.

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

Directory of Open Access Journals (Sweden)

A. N. Gelfan

2014-01-01

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

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

Snow cover is an important variable for climate and hydrologic models due to its effects on energy and moisture budgets. Over the past several decades both optical and passive microwave satellite data have been utilized for snow mapping at the regional to global scale. For the period 1978 to 2002, we have shown earlier that both passive microwave and visible data sets indicate a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are, depending on season, less than those provided by the visible satellite data and the visible data typically show higher monthly variability. Snow mapping using optical data is based on the magnitude of the surface reflectance while microwave data can be used to identify snow cover because the microwave energy emitted by the underlying soil is scattered by the snow grains resulting in a sharp decrease in brightness temperature and a characteristic negative spectral gradient. Our previous work has defined the respective advantages and disadvantages of these two types of satellite data for snow cover mapping and it is clear that a blended product is optimal. We present a multi-sensor approach to snow mapping based both on historical data as well as data from current NASA EOS sensors. For the period 1978 to 2002 we combine data from the NOAA weekly snow charts with passive microwave data from the SMMR and SSM/I brightness temperature record. For the current and future time period we blend MODIS and AMSR-E data sets. An example of validation at the brightness temperature level is provided through the comparison of AMSR-E with data from the well-calibrated heritage SSM/I sensor over a large homogeneous snow-covered surface (Dome C, Antarctica). Prototype snow cover maps from AMSR-E compare well with maps derived from SSM/I. Our current blended product is being developed in the 25 km EASE-Grid while the MODIS data being used are in the Climate Modelers Grid (CMG) at approximately 5 km

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

Directory of Open Access Journals (Sweden)

Frédérique C. Pivot

2012-07-01

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

Investigation of snow cover dust pollution by contact and satellite observations

Science.gov (United States)

Raputa, Vladimir F.; Yaroslavtseva, Tatyana V.

2015-11-01

The problems of reconstructing the snow cover pollution fields from dusting, point, linear and area sources according to ground and satellite observations are considered. Using reconstruction models, the methods of the combined analysis of the characteristic images of snow cover pollution haloes in the vicinity of sources of dust and contact data observations have been developed. On the basis of the numerical data analysis of ground monitoring and satellite imagery, the stable quantitative regularities between the fields of dust fallouts and the intensity of a change of tones of gray in the radial directions relative to the main sources are identified.

Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

Science.gov (United States)

Zaitchik, Benjamin F.; Rodell, Matthew

2008-01-01

Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

Changing Snow Cover and Stream Discharge in the Western United States - Wind River Range, Wyoming

Science.gov (United States)

Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Barton, Jonathan S.; Riggs, George A.

2011-01-01

Earlier onset of springtime weather has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack has important implications for the management of water resources. We studied ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover products, 40 years of stream discharge and meteorological station data and 30 years of snow-water equivalent (SWE) SNOw Telemetry (SNOTEL) data in the Wind River Range (WRR), Wyoming. Results show increasing air temperatures for.the 40-year study period. Discharge from streams in WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades. Changes in streamflow may be related to increasing air temperatures which are probably contributing to a reduction in snow cover, although no trend of either increasingly lower streamflow or earlier snowmelt was observed within the decade of the 2000s. And SWE on 1 April does not show an expected downward trend from 1980 to 2009. The extent of snow cover derived from the lowest-elevation zone of the WRR study area is strongly correlated (r=0.91) with stream discharge on 1 May during the decade of the 2000s. The strong relationship between snow cover and streamflow indicates that MODIS snow-cover maps can be used to improve management of water resources in the drought-prone western U.S.

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

Snow Cover Mapping at the Continental to Global Scale Using Combined Visible and Passive Microwave Satellite Data

Science.gov (United States)

Armstrong, R. L.; Brodzik, M.; Savoie, M. H.

2007-12-01

Over the past several decades both visible and passive microwave satellite data have been utilized for snow mapping at the continental to global scale. Snow mapping using visible data has been based primarily on the magnitude of the surface reflectance, and in more recent cases on specific spectral signatures, while microwave data can be used to identify snow cover because the microwave energy emitted by the underlying soil is scattered by the snow grains resulting in a sharp decrease in brightness temperature and a characteristic negative spectral gradient. Both passive microwave and visible data sets indicate a similar pattern of inter-annual variability, although the maximum snow extents derived from the microwave data are consistently less than those provided by the visible satellite data and the visible data typically show higher monthly variability. We describe the respective problems as well as the advantages and disadvantages of these two types of satellite data for snow cover mapping and demonstrate how a multi-sensor approach is optimal. For the period 1978 to present we combine data from the NOAA weekly snow charts with snow cover derived from the SMMR and SSM/I brightness temperature data. For the period since 2002 we blend NASA EOS MODIS and AMSR-E data sets. Our current product incorporates MODIS data from the Climate Modelers Grid (CMG) at approximately 5 km (0.05 deg.) with microwave-derived snow water equivalent (SWE) at 25 km, resulting in a blended product that includes percent snow cover in the larger grid cell whenever the microwave SWE signal is absent. Validation of AMSR-E at the brightness temperature level is provided through the comparison with data from the well-calibrated heritage SSM/I sensor over large homogeneous snow-covered surfaces (e.g. Dome C region, Antarctica). We also describe how the application of the higher frequency microwave channels (85 and 89 GHz)enhances accurate mapping of shallow and intermittent snow cover.

Missing (in-situ) snow cover data hampers climate change and runoff studies in the Greater Himalayas

International Nuclear Information System (INIS)

Rohrer, Mario; Salzmann, Nadine; Stoffel, Markus; Kulkarni, Anil V.

2013-01-01

The Himalayas are presently holding the largest ice masses outside the polar regions and thus (temporarily) store important freshwater resources. In contrast to the contemplation of glaciers, the role of runoff from snow cover has received comparably little attention in the past, although (i) its contribution is thought to be at least equally or even more important than that of ice melt in many Himalayan catchments and (ii) climate change is expected to have widespread and significant consequences on snowmelt runoff. Here, we show that change assessment of snowmelt runoff and its timing is not as straightforward as often postulated, mainly as larger partial pressure of H 2 O, CO 2 , CH 4 , and other greenhouse gases might increase net long-wave input for snowmelt quite significantly in a future atmosphere. In addition, changes in the short-wave energy balance – such as the pollution of the snow cover through black carbon – or the sensible or latent heat contribution to snowmelt are likely to alter future snowmelt and runoff characteristics as well. For the assessment of snow cover extent and depletion, but also for its monitoring over the extremely large areas of the Himalayas, remote sensing has been used in the past and is likely to become even more important in the future. However, for the calibration and validation of remotely-sensed data, and even more so in light of possible changes in snow-cover energy balance, we strongly call for more in-situ measurements across the Himalayas, in particular for daily data on new snow and snow cover water equivalent, or the respective energy balance components. Moreover, data should be made accessible to the scientific community, so that the latter can more accurately estimate climate change impacts on Himalayan snow cover and possible consequences thereof on runoff. - Highlights: • Remotely sensed snow-cover data need to be validated by in-situ measurements. • More in-situ snow measurement programs are needed along

Missing (in-situ) snow cover data hampers climate change and runoff studies in the Greater Himalayas

Energy Technology Data Exchange (ETDEWEB)

Rohrer, Mario [Meteodat GmbH, Technoparkstrasse 1, CH-8005 Zurich (Switzerland); Salzmann, Nadine [Department of Geosciences, Geography, University of Fribourg, Chemin du Musée 4, CH-1700 Fribourg (Switzerland); Stoffel, Markus, E-mail: markus.stoffel@unige.ch [Institute for Environmental Sciences, University of Geneva, Chemin de Drize 7, CH-1227 Carouge, Geneva (Switzerland); Dendrolab.ch, Institute of Geological Sciences, University of Bern, Baltzerstrasse 1+3, CH-3012 Bern (Switzerland); Kulkarni, Anil V. [Divecha Center for Climate Change, Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore 560 012 (India)

2013-12-01

The Himalayas are presently holding the largest ice masses outside the polar regions and thus (temporarily) store important freshwater resources. In contrast to the contemplation of glaciers, the role of runoff from snow cover has received comparably little attention in the past, although (i) its contribution is thought to be at least equally or even more important than that of ice melt in many Himalayan catchments and (ii) climate change is expected to have widespread and significant consequences on snowmelt runoff. Here, we show that change assessment of snowmelt runoff and its timing is not as straightforward as often postulated, mainly as larger partial pressure of H{sub 2}O, CO{sub 2}, CH{sub 4}, and other greenhouse gases might increase net long-wave input for snowmelt quite significantly in a future atmosphere. In addition, changes in the short-wave energy balance – such as the pollution of the snow cover through black carbon – or the sensible or latent heat contribution to snowmelt are likely to alter future snowmelt and runoff characteristics as well. For the assessment of snow cover extent and depletion, but also for its monitoring over the extremely large areas of the Himalayas, remote sensing has been used in the past and is likely to become even more important in the future. However, for the calibration and validation of remotely-sensed data, and even more so in light of possible changes in snow-cover energy balance, we strongly call for more in-situ measurements across the Himalayas, in particular for daily data on new snow and snow cover water equivalent, or the respective energy balance components. Moreover, data should be made accessible to the scientific community, so that the latter can more accurately estimate climate change impacts on Himalayan snow cover and possible consequences thereof on runoff. - Highlights: • Remotely sensed snow-cover data need to be validated by in-situ measurements. • More in-situ snow measurement programs are

Snow cover monitoring model and change over both time and space in pastoral area of northern China

Science.gov (United States)

Cui, Yan; Li, Suju; Wang, Ping; Zhang, Wei; Nie, Juan; Wen, Qi

2014-11-01

Snow disaster is a natural phenomenon owning to widespread snowfall for a long time and usually affect people's life, property and economic. During the whole disaster management circle, snow disaster in pastoral area of northern china which including Xinjiang, Inner Mongolia, Qinghai, Tibet has been paid more attention. Thus do a good job in snow cover monitoring then found snow disaster in time can help the people in disaster area to take effective rescue measures, which always been the central and local government great important work. Remote sensing has been used widely in snow cover monitoring for its wide range, high efficiency, less conditions, more methods and large information. NOAA/AVHRR data has been used for wide range, plenty bands information and timely acquired and act as an import data of Snow Cover Monitoring Model (SCMM). SCMM including functions list below: First after NOAA/AVHRR data has been acquired, geometric calibration, radiometric calibration and other pre-processing work has been operated. Second after band operation, four threshold conditions are used to extract snow spectrum information among water, cloud and other features in NOAA/AVHRR image. Third snow cover information has been analyzed one by one and the maximum snow cover from about twenty images in a week has been selected. Then selected image has been mosaic which covered the pastoral area of China. At last both time and space analysis has been carried out through this operational model ,such as analysis on the difference between this week and the same period of last year , this week and last week in three level regional. SCMM have been run successfully for three years, and the results have been take into account as one of the three factors which led to risk warning of snow disaster and analysis results from it always play an important role in disaster reduction and relief.

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.

The role of surface energy fluxes in pan-Arctic snow cover changes

International Nuclear Information System (INIS)

Shi Xiaogang; Lettenmaier, Dennis P; Groisman, Pavel Ya; Dery, Stephen J

2011-01-01

We analyze snow cover extent (SCE) trends in the National Oceanic and Atmospheric Administration's (NOAA) northern hemisphere weekly satellite SCE data using the Mann-Kendall trend test and find that North American and Eurasian snow cover in the pan-Arctic have declined significantly in spring and summer over the period of satellite record beginning in the early 1970s. These trends are reproduced, both in trend direction and statistical significance, in reconstructions using the variable infiltration capacity (VIC) hydrological model. We find that spring and summer surface radiative and turbulent fluxes generated in VIC have strong correlations with satellite observations of SCE. We identify the role of surface energy fluxes and determine which is most responsible for the observed spring and summer SCE recession. We find that positive trends in surface net radiation (SNR) accompany most of the SCE trends, whereas modeled latent heat (LH) and sensible heat (SH) trends associated with warming on SCE mostly cancel each other, except for North America in spring, and to a lesser extent for Eurasia in summer. In spring over North America and summer in Eurasia, the SH contribution to the observed snow cover trends is substantial. The results indicate that ΔSNR is the primary energy source and ΔSH plays a secondary role in changes of SCE. Compared with ΔSNR and ΔSH, ΔLH has a minor influence on pan-Arctic snow cover changes.

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...

Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts

NARCIS (Netherlands)

Bokhorst, Stef; Pedersen, Stine Højlund; Brucker, Ludovic; Anisimov, Oleg; Bjerke, Jarle W.; Brown, Ross D.; Ehrich, Dorothee; Essery, Richard L. H.; Heilig, Achim; Ingvander, Susanne; Johansson, Cecilia; Johansson, Margareta; Jónsdóttir, Ingibjörg Svala; Inga, Niila; Luojus, Kari; Macelloni, Giovanni; Mariash, Heather|info:eu-repo/dai/nl/41327697X; Mclennan, Donald; Rosqvist, Gunhild Ninis; Sato, Atsushi; Savela, Hannele; Schneebeli, Martin; Sokolov, Aleksandr; Sokratov, Sergey A.; Terzago, Silvia; Vikhamar-schuler, Dagrun; Williamson, Scott; Qiu, Yubao; Callaghan, Terry V.

2016-01-01

Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for

Scaling and Numerical Model Evaluation of Snow-Cover Effects on the Generation and Modification of Daytime Mesoscale Circulations.

Science.gov (United States)

Segal, M.; Garratt, J. R.; Pielke, R. A.; Ye, Z.

1991-04-01

Consideration of the sensible heat flux characteristics over a snow surface suggests a significant diminution in the magnitude of the flux, compared to that over a snow-free surface under the same environmental conditions. Consequently, the existence of snow-covered mesoscale areas adjacent to snow-free areas produces horizontal thermal gradients in the lower atmosphere during the daytime, possibly resulting in a `snow breeze.' In addition, suppression of the daytime thermally induced upslope flow over snow-covered slopes is likely to occur. The present paper provides scaling and modeling evaluations of these situations, with quantification of the generated and modified circulations. These evaluations suggest that under ideal situations involved with uniform snow cover over large areas, particularly in late winter and early spring, a noticeable `snow breeze' is likely to develop. Additionally: suppression of the daytime thermally induced upslope flow is significant and may even result in a daytime drainage flow. The effects of bare ground patchiness in the snow cover on these circulations are also explored, both for flat terrain and slope-flow situations. A patchiness fraction greater than 0.5 is found to result in a noticeably reduced snow-breeze circulation, while a patchiness fraction of only 0.1 caused the simulated daytime drainage flow over slopes to he reversed.

[Monitoring of the chemical composition of snow cover pollution in the Moscow region].

Science.gov (United States)

Ermakov, A A; Karpova, E A; Malysheva, A G; Mikhaylova, R I; Ryzhova, I N

2014-01-01

Monitoring of snow cover pollution as an indicator of ambient air pollution in 20 districts in the Moscow region during 2009-2013 was performed. The identification with a quantitative assessment of a wide array of organic compounds and the control of the main physical and chemical and inorganic indices of snow water pollution were carried out. More than 60 organic substances for most of which there are no the hygienic standards were established. The assessment of pollution levels of basic inorganic indices was given by means of the comparing them with the average values in the snow cover in the European territory of Russia and natural content in areas not been exposed to human impact.

A new strategy for snow-cover mapping using remote sensing data and ensemble based systems techniques

Science.gov (United States)

Roberge, S.; Chokmani, K.; De Sève, D.

2012-04-01

The snow cover plays an important role in the hydrological cycle of Quebec (Eastern Canada). Consequently, evaluating its spatial extent interests the authorities responsible for the management of water resources, especially hydropower companies. The main objective of this study is the development of a snow-cover mapping strategy using remote sensing data and ensemble based systems techniques. Planned to be tested in a near real-time operational mode, this snow-cover mapping strategy has the advantage to provide the probability of a pixel to be snow covered and its uncertainty. Ensemble systems are made of two key components. First, a method is needed to build an ensemble of classifiers that is diverse as much as possible. Second, an approach is required to combine the outputs of individual classifiers that make up the ensemble in such a way that correct decisions are amplified, and incorrect ones are cancelled out. In this study, we demonstrate the potential of ensemble systems to snow-cover mapping using remote sensing data. The chosen classifier is a sequential thresholds algorithm using NOAA-AVHRR data adapted to conditions over Eastern Canada. Its special feature is the use of a combination of six sequential thresholds varying according to the day in the winter season. Two versions of the snow-cover mapping algorithm have been developed: one is specific for autumn (from October 1st to December 31st) and the other for spring (from March 16th to May 31st). In order to build the ensemble based system, different versions of the algorithm are created by varying randomly its parameters. One hundred of the versions are included in the ensemble. The probability of a pixel to be snow, no-snow or cloud covered corresponds to the amount of votes the pixel has been classified as such by all classifiers. The overall performance of ensemble based mapping is compared to the overall performance of the chosen classifier, and also with ground observations at meteorological

Influence of ice and snow covers on the UV exposure of terrestrial microbial communities: dosimetric studies.

Science.gov (United States)

Cockell, Charles S; Rettberg, Petra; Horneck, Gerda; Wynn-Williams, David D; Scherer, Kerstin; Gugg-Helminger, Anton

2002-08-01

Bacillus subtilis spore biological dosimeters and electronic dosimeters were used to investigate the exposure of terrestrial microbial communities in micro-habitats covered by snow and ice in Antarctica. The melting of snow covers of between 5- and 15-cm thickness, depending on age and heterogeneity, could increase B. subtilis spore inactivation by up to an order of magnitude, a relative increase twice that caused by a 50% ozone depletion. Within the snow-pack at depths of less than approximately 3 cm snow algae could receive two to three times the DNA-weighted irradiance they would receive on bare ground. At the edge of the snow-pack, warming of low albedo soils resulted in the formation of overhangs that provided transient UV protection to thawed and growing microbial communities on the soils underneath. In shallow aquatic habitats, thin layers of heterogeneous ice of a few millimetres thickness were found to reduce DNA-weighted irradiances by up to 55% compared to full-sky values with equivalent DNA-weighted diffuse attenuation coefficients (K(DNA)) of >200 m(-1). A 2-mm snow-encrusted ice cover on a pond was equivalent to 10 cm of ice on a perennially ice covered lake. Ice covers also had the effect of stabilizing the UV exposure, which was often subject to rapid variations of up to 33% of the mean value caused by wind-rippling of the water surface. These data show that changing ice and snow covers cause relative changes in microbial UV exposure at least as great as those caused by changing ozone column abundance. Copyright 2002 Elsevier Science B.V.

Correlated declines in Pacific arctic snow and sea ice cover

Science.gov (United States)

Stone, Robert P.; Douglas, David C.; Belchansky, Gennady I.; Drobot, Sheldon

2005-01-01

Simulations of future climate suggest that global warming will reduce Arctic snow and ice cover, resulting in decreased surface albedo (reflectivity). Lowering of the surface albedo leads to further warming by increasing solar absorption at the surface. This phenomenon is referred to as “temperature–albedo feedback.” Anticipation of such a feedback is one reason why scientists look to the Arctic for early indications of global warming. Much of the Arctic has warmed significantly. Northern Hemisphere snow cover has decreased, and sea ice has diminished in area and thickness. As reported in the Arctic Climate Impact Assessment in 2004, the trends are considered to be outside the range of natural variability, implicating global warming as an underlying cause. Changing climatic conditions in the high northern latitudes have influenced biogeochemical cycles on a broad scale. Warming has already affected the sea ice, the tundra, the plants, the animals, and the indigenous populations that depend on them. Changing annual cycles of snow and sea ice also affect sources and sinks of important greenhouse gases (such as carbon dioxide and methane), further complicating feedbacks involving the global budgets of these important constituents. For instance, thawing permafrost increases the extent of tundra wetlands and lakes, releasing greater amounts of methane into the atmosphere. Variable sea ice cover may affect the hemispheric carbon budget by altering the ocean–atmosphere exchange of carbon dioxide. There is growing concern that amplification of global warming in the Arctic will have far-reaching effects on lower latitude climate through these feedback mechanisms. Despite the diverse and convincing observational evidence that the Arctic environment is changing, it remains unclear whether these changes are anthropogenically forced or result from natural variations of the climate system. A better understanding of what controls the seasonal distributions of snow and ice

Snow Cover, Snowmelt Timing and Stream Power in the Wind River Range, Wyoming

Science.gov (United States)

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

2011-01-01

Earlier onset of springtime weather, including earlier snowmelt, has been documented in the western United States over at least the last 50 years. Because the majority (is greater than 70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for the management of streamflow. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work, such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud-gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from streams in WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period as a whole. The extent of snow-cover (percent of basin covered) derived from the lowest elevation zone (2500-3000 m) of the WRR, using MODIS CGF snow-cover maps, is strongly correlated with maximum monthly discharge on 30 April, where Spearman's Rank correlation, rs,=0.89 for the decade of the 2000s. We also investigated stream power for Bull Lake Creek above Bull Lake; and found a trend (significant at the 90% confidence level) toward reduced stream power from 1970 to 2009. Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature

Seasonal snow cover regime and historical change in Central Asia from 1986 to 2008

Science.gov (United States)

Zhou, Hang; Aizen, Elena; Aizen, Vladimir

2017-01-01

A series of statistics describing seasonal Snow Cover Extent and timing in Central Asia (CA) have been derived from AVHRR satellite images for the time period from 1986 to 2008. Analysis of long term mean snow cover statistics shows that the area weighted mean of long term Snow Covering Days (SCD) for the whole CA is 95.2 ± 65.7 days. High elevation mountainous areas above 3000 m in Altai, Tien Shan and Pamir, which account for about 2.8% of total area in CA, have SCD > 240 days. Deserts (Karakorum Desert, Taklamakan Desert, Kumtag Desert) and rain shadow areas of major mountains, accounting for 27.0% of total area in CA, have SCD in the range of 0-30 days. Factors affecting snow cover distribution have been analyzed using simple linear regression and segmented regression. For plain regions and windward regions, the SCD rate is + 5.9 days/100 m, while for leeward regions, the rate jumps from + 0.7 days/100 m to + 10.0 days/100 m at about 2335 m. Latitude affects the SCD, especially in plain regions with insignificant change of elevation, with rates of 9-10 days/degree from south to north. The Mann-Kendal test and the Theil-Sen regression methods have been applied to analyze the spatial heterogeneous trends of change of SCD, Snow Cover Onset Date (SCOD), and Snow Cover Melt Date (SCMD). Area weighed mean SCD in the whole CA does not exhibit significant trend of change from 1986 to 2008. Increase of SCD was observed in the northeastern Kazakh Steppe. Low elevation areas below 2000 m in Central Tien Shan and Eastern Tien Shan, as well as mid-elevation areas from 1000 m to 3000 m in Western Tien Shan, Pamiro-Alai and Western Pamir, also experienced increase of SCD, associated with both earlier SCOD and later SCMD. Decrease of SCD was observed in mountainous areas of Altai, Tien Shan and Pamir, and vast areas in plains surrounding the Aral Sea.

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

Science.gov (United States)

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

2012-04-01

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

Variability in snow cover phenology in China from 1952 to 2010

Science.gov (United States)

Ke, Chang-Qing; Li, Xiu-Cang; Xie, Hongjie; Ma, Dong-Hui; Liu, Xun; Kou, Cheng

2016-02-01

Daily snow observation data from 672 stations in China, particularly the 296 stations with over 10 mean snow cover days (SCDs) in a year during the period of 1952-2010, are used in this study. We first examine spatiotemporal variations and trends of SCDs, snow cover onset date (SCOD), and snow cover end date (SCED). We then investigate the relationships of SCDs with number of days with temperature below 0 °C (TBZD), mean air temperature (MAT), and Arctic Oscillation (AO) index. The results indicate that years with a positive anomaly of SCDs for the entire country include 1955, 1957, 1964, and 2010, and years with a negative anomaly of SCDs include 1953, 1965, 1999, 2002, and 2009. The reduced TBZD and increased MAT are the main reasons for the overall late SCOD and early SCED since 1952. This explains why only 12 % of the stations show significant shortening of SCDs, while 75 % of the stations show no significant change in the SCDs trends. Our analyses indicate that the distribution pattern and trends of SCDs in China are very complex and are not controlled by any single climate variable examined (i.e. TBZD, MAT, or AO), but a combination of multiple variables. It is found that the AO has the maximum impact on the shortening trends of SCDs in the Shandong peninsula, Changbai Mountains, Xiaoxingganling, and north Xinjiang, while the combined TBZD and MAT have the maximum impact on the shortening trends of SCDs in the Loess Plateau, Tibetan Plateau, and Northeast Plain.

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

Combining MOD10A1 and MYD10A1 Images For Snow Cover Area Monitoring

Science.gov (United States)

Tekeli, A. E.

2008-12-01

MOD10A1 and MYD10A1 daily snow cover maps at 500 m resolution are available from MODIS sensors on Terra and Aqua satellites. Aqua obtains the image of same region approximately three hours after Terra over Turkey region. MODIS is an optic sensor and cloud cover degrades the usability of derived snow cover maps. Moreover, spectral similarity between clouds and snow complicates their separability in visible imagery. Fortunately, dynamic behavior of clouds enables their discrimination from snow stationary on the surface. Combined use of MOD10A1 and MYD10A1 images mostly reduces the cloud cover present in one image alone and provides better representation of surface snow cover. Comparison of merged images with in situ data indicated higher hit ratios. The individual comparison of MOD10A1 and MYD10A1 images with ground data each yielded 31% hit ratio whereas, the merged images provided 38%. One-day shifts in comparisons increased hit ratios to 52 % and 46% whereas and two-day shifts gave 77 % and 79 % for MOD10A1 and MYD10A1 respectively. Merged maps yielded 54% and 83% for one and two day shifts. The improvement provided by the merging technique is found to be 7% for the present day, 7 % for one- day and 5% for two-day shifts for the whole season. Monthly decomposition resulted 25% improvement as the maximum. The snow cover product obtained by merging Terra and Aqua satellites provided higher hit ratios, as expected.

Missing (in-situ) snow cover data hampers climate change and runoff studies in the Greater Himalayas.

Science.gov (United States)

Rohrer, Mario; Salzmann, Nadine; Stoffel, Markus; Kulkarni, Anil V

2013-12-01

The Himalayas are presently holding the largest ice masses outside the polar regions and thus (temporarily) store important freshwater resources. In contrast to the contemplation of glaciers, the role of runoff from snow cover has received comparably little attention in the past, although (i) its contribution is thought to be at least equally or even more important than that of ice melt in many Himalayan catchments and (ii) climate change is expected to have widespread and significant consequences on snowmelt runoff. Here, we show that change assessment of snowmelt runoff and its timing is not as straightforward as often postulated, mainly as larger partial pressure of H2O, CO2, CH4, and other greenhouse gases might increase net long-wave input for snowmelt quite significantly in a future atmosphere. In addition, changes in the short-wave energy balance - such as the pollution of the snow cover through black carbon - or the sensible or latent heat contribution to snowmelt are likely to alter future snowmelt and runoff characteristics as well. For the assessment of snow cover extent and depletion, but also for its monitoring over the extremely large areas of the Himalayas, remote sensing has been used in the past and is likely to become even more important in the future. However, for the calibration and validation of remotely-sensed data, and even more so in light of possible changes in snow-cover energy balance, we strongly call for more in-situ measurements across the Himalayas, in particular for daily data on new snow and snow cover water equivalent, or the respective energy balance components. Moreover, data should be made accessible to the scientific community, so that the latter can more accurately estimate climate change impacts on Himalayan snow cover and possible consequences thereof on runoff. © 2013 Elsevier B.V. All rights reserved.

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

Radiation balances of melting snow covers at an open site in the Central Sierra Nevada, California

International Nuclear Information System (INIS)

Aguado, E.

1985-01-01

The radiation balances of melting snow packs for three seasons at an open site at the Central Sierra Snow Laboratory near Soda Springs, California were examined. The snow covers were examples of below-normal, near-normal and much-above-normal water equivalents. Two of the snow covers melted under generally clear skies in late spring while the other melted under cloudier conditions and at a time when less extraterrestrial radiation was available. Moreover, the snow covers were of very different densities, thereby allowing examination of a possible relationship between that characteristic and albedo. No such relationship was observed. Despite the dissimilarities in the conditions under which melt occurred, the disposition of solar radiation was similar for the three melt seasons. Albedos and their rates of decline through the melt season were similar for the three seasons. Absorbed solar radiation and a cloudiness index were useful predictors for daily net radiation, accounting for 71% of the total variance. (author)

Aerotechnogenic Monitoring of Urban Environment on Snow Cover Pollution (on the Example of Voronezh City

Directory of Open Access Journals (Sweden)

Prozhorina Tatyana Ivanovna

2014-09-01

Full Text Available Snow cover is characterized by high sorption ability and represents an informative object in the process of identifying the technogenic pollution of urban environment. The article contains the results of the research on the chemical composition of the snow which fell in Voronezh in the winter period of 2013–2014. The coefficients of chemical elements concentration were calculated to provide objective characteristics of snow cover pollution. The authors analyze the connection between the presence of pollutants in snow and the level of technogenic impact. The obtained ranges of anomaly coefficients among anions reflect the composition of technogenic emissions. The mineralization of snow water reliably characterizes the intensity of anthropogenic impact on the urban environment, and the value of mineralization snow samples ranges from 62,6 (background to 183,9 mg/l. Maximum values of mineralization (more than 150 mg/l are typical for samples taken in transport area. High values of salinity (more than 120 mg/l are observed in snow samples taken in the industrial area, which confirms the high “technogenic pressure” on the urban environment in zones of industrial and transport potential of the city. The investigated functional areas can be arranged in the following series by descending level of contamination: transport area > industrial zone > residential and recreational areas > background territory. The study of the chemical composition of snow cover in the various functional areas of Voronezh allows to conclude that the pH level, mineralization and the content of suspended solids in snow waters characterize the intensity of anthropogenic pressure on the urban environment, and the composition of melt waters indicates the nature of its pollution.

Timing and Statistics of Autumn and Spring Annual Snow Cover for the Northern Hemisphere, 1972 to 2000

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The National Snow and Ice Data Center hosts a time-series data set comprising annual snow cover data for the Northern Hemisphere (covering land primarily over 45...

A Prognostic Methodology for Precipitation Phase Detection using GPM Microwave Observations —With Focus on Snow Cover

Science.gov (United States)

Takbiri, Z.; Ebtehaj, A.; Foufoula-Georgiou, E.; Kirstetter, P.

2017-12-01

Improving satellite retrieval of precipitation requires increased understanding of its passive microwave signature over different land surfaces. Passive microwave signals over snow-covered surfaces are notoriously difficult to interpret because they record both emission from the land below and absorption/scattering from the liquid/ice crystals. Using data from the Global Precipitation Measurement (GPM) core satellite, we demonstrate that the microwave brightness temperatures of rain and snowfall shifts from a scattering to an emission regime from summer to winter, due to expansion of the less emissive snow cover underneath. We present evidence that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The study also examines a prognostic nearest neighbor matching method for the detection of precipitation and its phase from passive microwave observations using GPM data. The nearest neighbor uses the weighted Euclidean distance metric to search through an a priori database that is populated with coincident GPM radiometer and radar data as well as ancillary snow cover fraction. The results demonstrate prognostic capabilities of the proposed method in detection of terrestrial snowfall. At the global scale, the average probability of hit and false alarm reaches to 0.80 and remains below 0.10, respectively. Surprisingly, the results show that the snow cover may help to better detect precipitation as the detection rate of terrestrial precipitation is increased from 0.75 (no snow cover) to 0.84 (snow-covered surfaces). For solid precipitation, this increased rate of detection is larger than its liquid counterpart by almost 8%. The main reasons are found to be related to the multi-frequency capabilities of the nearest neighbor matching that can properly isolate the atmospheric signal from the background emission and the fact that the precipitation can exhibit an emission-like (warmer

Retrieving the characteristics of slab ice covering snow by remote sensing

Directory of Open Access Journals (Sweden)

F. Andrieu

2016-09-01

Full Text Available We present an effort to validate a previously developed radiative transfer model, and an innovative Bayesian inversion method designed to retrieve the properties of slab-ice-covered surfaces. This retrieval method is adapted to satellite data, and is able to provide uncertainties on the results of the inversions. We focused on surfaces composed of a pure slab of water ice covering an optically thick layer of snow in this study. We sought to retrieve the roughness of the ice–air interface, the thickness of the slab layer and the mean grain diameter of the underlying snow. Numerical validations have been conducted on the method, and showed that if the thickness of the slab layer is above 5 mm and the noise on the signal is above 3 %, then it is not possible to invert the grain diameter of the snow. In contrast, the roughness and the thickness of the slab can be determined, even with high levels of noise up to 20 %. Experimental validations have been conducted on spectra collected from laboratory samples of water ice on snow using a spectro-radiogoniometer. The results are in agreement with the numerical validations, and show that a grain diameter can be correctly retrieved for low slab thicknesses, but not for bigger ones, and that the roughness and thickness are correctly inverted in every case.

Assessment of the economic risk for the ski resorts of changes in snow cover duration

Directory of Open Access Journals (Sweden)

S. A. Sokratov

2014-01-01

Full Text Available Winter tourism that is intensively developed in the Russian Federation in recent years strongly depends on the snow availability and properties in the region. Climate changes exert significant influence on the functioning of mountain ski resorts, especially if they are located in areas with relatively high air temperatures in winter season. At the present time, a snowy cluster of mountain ski resorts is intensively progressing in vicinity of Krasnaya Polyana. This region in the West Caucasus (Russia is characterized by relatively warm climate conditions. The snow cover thickness (of 1% insurance in area of the Aibga mountain range may reach 8.1 m. But the snow cover thickness is not the only characteristic of the mountain skiing attractiveness. According to the Swiss standards a mountain ski resort can be considered reliable if during seven seasons of ten ones the snow cover with minimal thickness of 30–50 cm exists for a time not shorter than 100 days during a period from 1st December till 15th April.According to the forecast, during future decades the calculated amount of solid precipitation should reduce by 25–30% in mountain regions on the south macro-slope of the Great Caucasus. As the calculations show, by 2041–2050 the maximal decade thickness of snow cover will decrease by 29–35% while a number of days with snow – by 35–40%. If this is the case, artificial snow will be needed in addition to the natural one. But, under warm climate conditions using of plants for artificial snow production will require a certain perfecting of the nowadays technologies, and very likely, with use of chemicals. That is why a shadowing of existing mountain ski routes by means of the tree planting along them could be ecologically more promising. As for the mountain ski resorts of the West Caucasus, we should mention a possible weakening of the avalanche activity as a potential positive effect of the climate warming predicted by models.

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

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

Science.gov (United States)

Schindlbacher, Andreas; Jandl, Robert; Schindlbacher, Sabine

2014-02-01

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

Dust pollution of snow cover in the industrial areas of Tomsk city (Western Siberia, Russia)

Science.gov (United States)

Talovskaya, A. V.; Filimonenko, E. A.; Osipova, N. A.; Yazikov, E. G.; Nadeina, L. V.

2016-03-01

This article describes the results of long-term monitoring (2007-2014) of snow cover pollution in the territory of Tomsk city. Snow samples were collected in the territory of Tomsk. Determination of dust load level was carried out by comparing with the background and reference values. It has been determined that the north-east and central parts of Tomsk are the most contaminated areas, where brickworks, coal and gas-fired thermal power plant are located. The analysis of long-term dynamics showed a dust load decrease in the vicinity of coal and gas-fired thermal power plant due to upgrading of the existing dust collecting systems. During the monitoring period the high dust load in the vicinity of brickworks did not change. The lowest value of the dust load on snow cover was detected in the vicinity of the petrochemical plant and concrete product plants. The near and far zones of dust load on snow cover were determined with the reference to the location of the studied plants.

Automated mapping of persistent ice and snow cover across the western U.S. with Landsat

Science.gov (United States)

Selkowitz, David J.; Forster, Richard R.

2016-01-01

We implemented an automated approach for mapping persistent ice and snow cover (PISC) across the conterminous western U.S. using all available Landsat TM and ETM+ scenes acquired during the late summer/early fall period between 2010 and 2014. Two separate validation approaches indicate this dataset provides a more accurate representation of glacial ice and perennial snow cover for the region than either the U.S. glacier database derived from US Geological Survey (USGS) Digital Raster Graphics (DRG) maps (based on aerial photography primarily from the 1960s–1980s) or the National Land Cover Database 2011 perennial ice and snow cover class. Our 2010–2014 Landsat-derived dataset indicates 28% less glacier and perennial snow cover than the USGS DRG dataset. There are larger differences between the datasets in some regions, such as the Rocky Mountains of Northwest Wyoming and Southwest Montana, where the Landsat dataset indicates 54% less PISC area. Analysis of Landsat scenes from 1987–1988 and 2008–2010 for three regions using a more conventional, semi-automated approach indicates substantial decreases in glaciers and perennial snow cover that correlate with differences between PISC mapped by the USGS DRG dataset and the automated Landsat-derived dataset. This suggests that most of the differences in PISC between the USGS DRG and the Landsat-derived dataset can be attributed to decreases in PISC, as opposed to differences between mapping techniques. While the dataset produced by the automated Landsat mapping approach is not designed to serve as a conventional glacier inventory that provides glacier outlines and attribute information, it allows for an updated estimate of PISC for the conterminous U.S. as well as for smaller regions. Additionally, the new dataset highlights areas where decreases in PISC have been most significant over the past 25–50 years.

MODIS snow cover mapping accuracy in a small mountain catchment – comparison between open and forest sites

Directory of Open Access Journals (Sweden)

G. Blöschl

2012-07-01

Full Text Available Numerous global and regional validation studies have examined MODIS snow mapping accuracy by using measurements at climate stations, which are mainly at open sites. MODIS accuracy in alpine and forested regions is, however, still not well understood. The main objective of this study is to evaluate MODIS (MOD10A1 and MYD10A1 snow cover products in a small experimental catchment by using extensive snow course measurements at open and forest sites. The MODIS accuracy is tested in the Jalovecky creek catchment (northern Slovakia in the period 2000–2011. The results show that the combined Terra and Aqua images enable snow mapping at an overall accuracy of 91.5%. The accuracies at forested, open and mixed land uses at the Červenec sites are 92.7%, 98.3% and 81.8%, respectively. The use of a 2-day temporal filter enables a significant reduction in the number of days with cloud coverage and an increase in overall snow mapping accuracy. In total, the 2-day temporal filter decreases the number of cloudy days from 61% to 26% and increases the snow mapping accuracy to 94%. The results indicate three possible factors leading to misclassification of snow as land: patchy snow cover, limited MODIS geolocation accuracy and mapping algorithm errors. Out of a total of 27 misclassification cases, patchy snow cover, geolocation issues and mapping errors occur in 12, 12 and 3 cases, respectively.

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

Directory of Open Access Journals (Sweden)

V. V. Popova

2014-01-01

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

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

The impact of organochlorines cycling in the cryosphere on global distributions and fate – 2. Land ice and temporary snow cover

International Nuclear Information System (INIS)

Hofmann, Lorenz; Stemmler, Irene; Lammel, Gerhard

2012-01-01

Global fate and transport of γ-HCH and DDT was studied using a global multicompartment chemistry-transport model, MPI-MCTM, with and without inclusion of land ice (in Antarctica and Greenland) or snow cover (dynamic). MPI-MCTM is based on coupled ocean and atmosphere general circulation models. After a decade of simulation 4.2% γ-HCH and 2.3% DDT are stored in land ice and snow. Neglection of land ice and snow in modelling would underestimate the total environmental residence time, τ ov , of γ-HCH and overestimate τ ov for DDT, both on the order of 1% and depending on actual compartmental distribution. Volatilisation of DDT from boreal, seasonally snow covered land is enhanced throughout the year, while volatilisation of γ-HCH is only enhanced during the snow-free season. Including land ice and snow cover in modelling matters in particular for the Arctic, where higher burdens are predicted to be stored. - Highlights: ► Land ice and snow hosts 2–4% of the global environmental burden of γ-HCH and DDT. ► Inclusion of land ice and snow cover matters for global environmental residence time. ► Including of land ice and snow cover matters in particular for the Arctic. - The inclusion of cycling in temporary snow cover and land ice in the model is found relevant for predicted POPs multicompartmental distribution and fate in the Arctic and on the global scale.

Carbon dioxide evolution from snow-covered agricultural ecosystems in Finland

Directory of Open Access Journals (Sweden)

Hiroshi Koizumi

1996-07-01

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

Distribution and variability of total mercury in snow cover-a case study from a semi-urban site in Poznań, Poland.

Science.gov (United States)

Siudek, Patrycja

2016-12-01

In the present paper, the inter-seasonal Hg variability in snow cover was examined based on multivariate statistical analysis of chemical and meteorological data. Samples of freshly fallen snow cover were collected at the semi-urban site in Poznań (central Poland), during 3-month field measurements in winter 2013. It was showed that concentrations of atmospherically deposited Hg were highly variable in snow cover, from 0.43 to 12.5 ng L -1 , with a mean value of 4.62 ng L -1 . The highest Hg concentration in snow cover coincided with local intensification of fossil fuel burning, indicating large contribution from various anthropogenic sources such as commercial and domestic heating, power generation plants, and traffic-related pollution. Moreover, the variability of Hg in collected snow samples was associated with long-range transport of pollutants, nocturnal inversion layer, low boundary layer height, and relatively low air temperature. For three snow episodes, Hg concentration in snow cover was attributed to southerly advection, suggesting significant contribution from the highly polluted region of Poland (Upper Silesia) and major European industrial hotspots. However, the peak Hg concentration was measured in samples collected during predominant N to NE advection of polluted air masses and after a relatively longer period without precipitation. Such significant contribution to the higher Hg accumulation in snow cover was associated with intensive emission from anthropogenic sources (coal combustion) and atmospheric conditions in this area. These results suggest that further measurements are needed to determine how the Hg transformation paths in snow cover change in response to longer/shorter duration of snow cover occurrence and to determine the interactions between mercury and absorbing carbonaceous aerosols in the light of climate change.

Cadmium content in snow cover on the Pavlodar territory of the Republic of Kazakhstan

International Nuclear Information System (INIS)

Azhaev, G.S.; Panin, M.S.

2008-01-01

In the present report results of Cadmium concentration determination in aqueous and solid phases of snow cover on the Pavlodar territory of the Republic of Kazakhstan are presented. Cadmium content was tested with atomic absorption method on spectrophotometer of Perkin Elmer Company, model 403 with thermal-electric analyser HGA-74 and deuterium background corrector. Average concentration of cadmium in solid phase of snow goes up to 3.2 mg/kg, in aqueous phase - 2.1 mkg/dm 3 . That is respectively 22.9 and 13.1 times higher than background level. The cadmium concentration level in aqueous and solid phases of snow cover on the different areas of Pavlodar city is unequal. That indicates the specific character of different manufacturing enterprises, their anthropogenic impact on the environment and purification efficiency of emissions

ATLAS construction: A status report

CERN Document Server

Sfyrla, Anna

2006-01-01

ATLAS is a general purpose p-p collider detector being constructed for the CERN Large Hadron Collider (LHC). It is located in one of the two high luminosity bunch crossing points (peak luminosity of 1 0 3 4 c m - 2 s _ 1 ) of the LHC. It consists of 3 main sections. Located close to the beam axis, the tracking system employs pixel detectors, silicon microstrip modules and transition radiation straws, all within a 2 Tesla superconducting solenoid. The tracker is surrounded by the electromagnetic and hadronic calorimeters. In the outer part of the detector, 8 superconducting coils define an open toroidal magnetic field for muon detection. The construction status of the ATLAS detector towards being ready for the first collisions in 2007 will be presented, with particular emphasis on the construction and projected performance of the tracking system.

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

Science.gov (United States)

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

2016-04-01

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

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

Data.gov (United States)

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

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

Snowmelt and sublimation: field experiments and modelling in the High Atlas Mountains of Morocco

Directory of Open Access Journals (Sweden)

O. Schulz

2004-01-01

Full Text Available Snow in the High Atlas Mountains is a major source for freshwater renewal and for water availability in the semi-arid lowlands of south-eastern Morocco. Snowfall- and snow-ablation monitoring and modelling is important for estimating potential water delivery from the mountain water towers to the forelands. This study is part of GLOWA-IMPETUS, an integrated management project dealing with scarce water resources in West Africa. The Ameskar study area is located to the south of the High Atlas Mountains, in their rain shadow. As a part of the M’Goun river basin within the upper Drâa valley, the study area is characterised by high radiation inputs, low atmospheric humidity and long periods with sub-zero temperatures. Its altitude ranges between 2000 m and 4000 m, with dominant north- and south-facing slopes. Snowfall occurs mainly from November to April but even summit regions can become repeatedly devoid of snow cover. Snow cover maps for the M’Goun basin (1240 km2 are derived from calculations of NDSI (Normalized Difference Snow Index from MODIS satellite images and snow depth is monitored at four automatic weather stations between 2000–4000 m. Snowfall events are infrequent at lower altitudes. The presence of snow penitentes at altitudes above 3000 m indicates that snow sublimation is an important component of snow ablation. Snow ablation was modelled with the UEB Utah Energy Balance Model (Tarboton and Luce, 1996. This single layer, physically-based, point energy and mass balance model is driven by meteorological variables recorded at the automatic weather stations at Tounza (2960 m and Tichki (3260 m. Data from snow pillows at Tounza and Tichki are used to validate the model’s physical performance in terms of energy and water balances for a sequence of two snowfall events in the winter of 2003/4. First UEB modelling results show good overall performance and timing of snowmelt and sublimation compared to field investigations. Up to 44

Global warming in the context of 2000 years of Australian alpine temperature and snow cover.

Science.gov (United States)

McGowan, Hamish; Callow, John Nikolaus; Soderholm, Joshua; McGrath, Gavan; Campbell, Micheline; Zhao, Jian-Xin

2018-03-13

Annual resolution reconstructions of alpine temperatures are rare, particularly for the Southern Hemisphere, while no snow cover reconstructions exist. These records are essential to place in context the impact of anthropogenic global warming against historical major natural climate events such as the Roman Warm Period (RWP), Medieval Climate Anomaly (MCA) and Little Ice Age (LIA). Here we show for a marginal alpine region of Australia using a carbon isotope speleothem reconstruction, warming over the past five decades has experienced equivalent magnitude of temperature change and snow cover decline to the RWP and MCA. The current rate of warming is unmatched for the past 2000 years and seasonal snow cover is at a minimum. On scales of several decades, mean maximum temperatures have undergone considerable change ≈ ± 0.8 °C highlighting local scale susceptibility to rapid temperature change, evidence of which is often masked in regional to hemisphere scale temperature reconstructions.

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

Science.gov (United States)

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

2001-01-01

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

Methane fluxes during the cold season: distribution and mass transfer in the snow cover of bogs

Science.gov (United States)

Smagin, A. V.; Shnyrev, N. A.

2015-08-01

Fluxes and profile distribution of methane in the snow cover and different landscape elements of an oligotrophic West-Siberian bog (Mukhrino Research Station, Khanty-Mansiisk autonomous district) have been studied during a cold season. Simple models have been proposed for the description of methane distribution in the inert snow layer, which combine the transport of the gas and a source of constant intensity on the soil surface. The formation rates of stationary methane profiles in the snow cover have been estimated (characteristic time of 24 h). Theoretical equations have been derived for the calculation of small emission fluxes from bogs to the atmosphere on the basis of the stationary profile distribution parameters, the snow porosity, and the effective methane diffusion coefficient in the snow layer. The calculated values of methane emission significantly (by 2-3 to several tens of times) have exceeded the values measured under field conditions by the closed chamber method (0.008-0.25 mg C/(m2 h)), which indicates the possibility of underestimating the contribution of the cold period to the annual emission cycle of bog methane.

Using NASA Earth Observations to Assist the National Park Service in Assessing Snow Cover Distribution and Persistence Changes in the Sky Islands

Science.gov (United States)

Bayat, F.; Barrow, C., III; Gonsoroski, E.; Dutta, S.; Lynn, T.; Harville, K.; Spruce, J.

2017-12-01

Saguaro National Park in southeastern Arizona occupies one of several unique mountain ranges known collectively as the Sky Islands or the Madrean Archipelago. The Sky Islands are biodiversity hotspots and host different ecosystems, ranging from arid deserts to temperate forests. Snowmelt provides a source of water during the dry season for various flora and fauna inhabiting the region. Climate change and its effect on snow cover is of growing concern by resource managers in this location. Currently, the National Park Service (NPS) monitors water presence via stream gauges, but a synoptic record of snow presence does not exist due to the remote and rugged topography of the region. As a result, it is difficult to study how climate change has affected water resources in the Sky Islands and what effect this has on wildlife and vegetation. This project used NASA Earth observations (e.g., Landsat data) and GIS technology to help the NPS in understanding the role of snow cover in the Sky Islands. Historical snow cover maps were compiled using a combination of snow detection indices to provide spatio-temporal information on snow presence and phenology. With a more complete understanding of snow cover trends in the park, the NPS can further analyze snow cover impacts to improve future land management decisions.

An airborne gamma ray snow survey of a forest covered area with a deep snowpack

International Nuclear Information System (INIS)

Glynn, J.E.; Carroll, T.R.; Holman, P.B.; Grasty, R.L.

1988-01-01

Problems arising from the airborne gamma ray measurement of snow water equivalent over a forest covered deep snowpack are examined. The principal sources of error are believed to be due to the radioactivity in the biomass and to variability in the snow cover. A theoretical model is developed to correct the airborne measurements for these sources of error. The application of the theory to data collected over the St. John River Basin, located in the eastern part of Canada and the United States, is found to significantly improve the airborne results

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

Brightness temperature simulation of snow cover based on snow grain size evolution using in situ data

Science.gov (United States)

Wu, Lili; Li, Xiaofeng; Zhao, Kai; Zheng, Xingming; Jiang, Tao

2016-07-01

Snow depth parameter inversion from passive microwave remote sensing is of great significance to hydrological process and climate systems. The Helsinki University of Technology (HUT) model is a commonly used snow emission model. Snow grain size (SGS) is one of the important input parameters, but SGS is difficult to obtain in broad areas. The time series of SGS are first evolved by an SGS evolution model (Jordan 91) using in situ data. A good linear relationship between the effective SGS in HUT and the evolution SGS was found. Then brightness temperature simulations are performed based on the effective SGS and evolution SGS. The results showed that the biases of the simulated brightness temperatures based on the effective SGS and evolution SGS were -6.5 and -3.6 K, respectively, for 18.7 GHz and -4.2 and -4.0 K for 36.5 GHz. Furthermore, the model is performed in six pixels with different land use/cover type in other areas. The results showed that the simulated brightness temperatures based on the evolution SGS were consistent with those from the satellite. Consequently, evolution SGS appears to be a simple method to obtain an appropriate SGS for the HUT model.

Distribution and variability of total mercury in snow cover?a case study from a semi-urban site in Pozna?, Poland

OpenAIRE

Siudek, Patrycja

2016-01-01

In the present paper, the inter-seasonal Hg variability in snow cover was examined based on multivariate statistical analysis of chemical and meteorological data. Samples of freshly fallen snow cover were collected at the semi-urban site in Pozna? (central Poland), during 3-month field measurements in winter 2013. It was showed that concentrations of atmospherically deposited Hg were highly variable in snow cover, from 0.43 to 12.5?ng?L?1, with a mean value of 4.62?ng?L?1. The highest Hg conc...

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

Directory of Open Access Journals (Sweden)

Ermanno Zanini

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

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

International Nuclear Information System (INIS)

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

1990-12-01

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

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.

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

Science.gov (United States)

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

2016-12-01

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

Intensity and sulci landmark combined brain atlas construction for Chinese pediatric population.

Science.gov (United States)

Luo, Yishan; Shi, Lin; Weng, Jian; He, Hongjian; Chu, Winnie C W; Chen, Feiyan; Wang, Defeng

2014-08-01

Constructing an atlas from a population of brain images is of vital importance to medical image analysis. Especially in neuroscience study, creating a brain atlas is useful for intra- and inter-population comparison. Research on brain atlas construction has attracted great attention in recent years, but the research on pediatric population is still limited, mainly due to the limited availability and the relatively low quality of pediatric magnetic resonance brain images. This article is targeted at creating a high quality representative brain atlas for Chinese pediatric population. To achieve this goal, we have designed a set of preprocessing procedures to improve the image quality and developed an intensity and sulci landmark combined groupwise registration method to align the population of images for atlas construction. As demonstrated in experiments, the newly constructed atlas can better represent the size and shape of brains of Chinese pediatric population, and show better performance in Chinese pediatric brain image analysis compared with other standard atlases. Copyright © 2014 Wiley Periodicals, Inc.

EnviroAtlas - Austin, TX - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. Vegetated cover is defined as Trees & Forest and Grass & Herbaceous. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Percent Stream Buffer Zone As Natural Land Cover for the Conterminous United States

Science.gov (United States)

This EnviroAtlas dataset shows the percentage of land area within a 30 meter buffer zone along the National Hydrography Dataset (NHD) high resolution stream network, and along water bodies such as lakes and ponds that are connected via flow to the streams, that is classified as forest land cover, modified forest land cover, and natural land cover using the 2006 National Land Cover Dataset (NLCD) for each Watershed Boundary Dataset (WBD) 12-digit hydrological unit (HUC) in the conterminous United States. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

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

Science.gov (United States)

McCabe, Gregory J.; Wolock, David M.

2010-01-01

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

EnviroAtlas - Cleveland, OH - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Austin, TX - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Portland, ME - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Woodbine, IA - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Milwaukee, WI - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Tampa, FL - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Pittsburgh, PA - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Phoenix, AZ - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Durham, NC - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Portland, OR - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Paterson, NJ - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Memphis, TN - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Fresno, CA - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas Estimated Percent Tree Cover Along Walkable Roads Web Service

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

Using multi-source satellite data to assess snow-cover change in Qinghai-Tibetan Plateau in last decade

Science.gov (United States)

Jiang, Y.; Chen, F.; Gao, Y.; Barlage, M. J.

2017-12-01

Snow cover in Qinghai-Tibetan Plateau (QTP) is a critical component of water cycle and affects regional climate of East Asia. Satellite data from three different sources (i.e., FY3A/B/C, MODIS and IMS) were used to analyze the QTP fractional-snow-cover (FSC) change and associated uncertainties in the last decade. To reduce the high percentage of cloud in FY3A/B/C and MODIS, a four-step cloud removal procedure was applied and effectively reduced the cloud percentage from 40.8-56.1% to 2.2­-­3.3%. The averaged error introduced by the cloud removal procedure was about 2% estimated by a random sampling method. Results show that the snow cover in QTP significantly decreased in recent 5 years. Three data sets (FY3B, MODIS and IMS) showed significant decreased annual FSC at all elevation bands from 2012-2016, and a significant shorter snow season with delayed snow onset and earlier melting. Both IMS and MODIS had a slightly decline annual FSC from 2000 to 3000 m, while MODIS FSC slightly decreased in 2002-2016 and IMS FSC slightly increased from 2006-2016 in the region with elevation higher than 3000 m. Results also show significant uncertainties among the five data sets (FY3A/B/C, MODIS, IMS), although they showed similar fluctuations of daily FSC. IMS had largest snow-cover extent and highest daily FSC due to its multi data sources. FY3A/C and MODIS (observed in the morning) had around 5% higher mean FSC than FY3B (observed in the afternoon) due to the 3 hours detection time gap. The relative error of daily FSC (taking MODIS as `truth') between FY3A/B/C, IMS and MODIS is 23%, -35%, 8% and 63%, respectively, averaged in five elevation bands in 2015-2017.

Consequences of changes in vegetation and snow cover for climate feedbacks in Alaska and northwest Canada

Science.gov (United States)

Euskirchen, Eugénie S.; Bennett, A. P.; Breen, Amy L.; Genet, Helene; Lindgren, Michael A.; Kurkowski, Tom; McGuire, A. David; Rupp, T. Scott

2016-01-01

Changes in vegetation and snow cover may lead to feedbacks to climate through changes in surface albedo and energy fluxes between the land and atmosphere. In addition to these biogeophysical feedbacks, biogeochemical feedbacks associated with changes in carbon (C) storage in the vegetation and soils may also influence climate. Here, using a transient biogeographic model (ALFRESCO) and an ecosystem model (DOS-TEM), we quantified the biogeophysical feedbacks due to changes in vegetation and snow cover across continuous permafrost to non-permafrost ecosystems in Alaska and northwest Canada. We also computed the changes in carbon storage in this region to provide a general assessment of the direction of the biogeochemical feedback. We considered four ecoregions, or Landscape Conservations Cooperatives (LCCs; including the Arctic, North Pacific, Western Alaska, and Northwest Boreal). We examined the 90 year period from 2010 to 2099 using one future emission scenario (A1B), under outputs from two general circulation models (MPI-ECHAM5 and CCCMA-CGCM3.1). We found that changes in snow cover duration, including both the timing of snowmelt in the spring and snow return in the fall, provided the dominant positive biogeophysical feedback to climate across all LCCs, and was greater for the ECHAM (+3.1 W m−2 decade−1regionally) compared to the CCCMA (+1.3 W m−2 decade−1 regionally) scenario due to an increase in loss of snow cover in the ECHAM scenario. The greatest overall negative feedback to climate from changes in vegetation cover was due to fire in spruce forests in the Northwest Boreal LCC and fire in shrub tundra in the Western LCC (−0.2 to −0.3 W m−2 decade−1). With the larger positive feedbacks associated with reductions in snow cover compared to the smaller negative feedbacks associated with shifts in vegetation, the feedback to climate warming was positive (total feedback of +2.7 W m−2decade regionally in the ECHAM scenario compared to +0.76 W

Insects, Fires, and Climate Change: Implications for Snow Cover, Water Resources and Ecosystem Recovery in Western North America

Science.gov (United States)

Brooks, P. D.; Harpold, A. A.; Biederman, J. A.; Litvak, M. E.; Broxton, P. D.; Gochis, D.; Molotch, N. P.; Troch, P. A.; Ewers, B. E.

2012-12-01

Unprecedented levels of insect induced tree mortality and massive wildfires both have spread through the forests of Western North America over the last decade. Warming temperatures and increased drought stress have been implicated as major factors in the increasing spatial extent and frequency of these forest disturbances, but it is unclear how simultaneous changes in forest structure and climate will interact to affect either downstream water resources or the regeneration and recovery of forested ecosystems. Because both streamflow and ecosystem productivity depend on seasonal snowmelt, a critical knowledge gap exists in how these disturbances will interact with a changing climate to control to the amount, timing, and the partitioning of seasonal snow cover This presentation will address this knowledge gap by synthesizing recent work on snowpack dynamics and ecosystem productivity from seasonally snow-covered forests along a gradient of snow depth and duration from Arizona to Montana. These include undisturbed sites, recently burned forests, and areas of extensive insect-induced forest mortality. Both before-after and control-impacted studies of forest disturbance on snow accumulation and ablation suggest that the spatial scale of snow distribution increases following disturbance, but net snow water input likely will not increase under a warming climate. While forest disturbance changes spatial scale of snowpack partitioning, the amount and especially the timing of snow cover accumulation and ablation are strongly related to interannual variability in ecosystem productivity with both earlier snowmelt and later snow accumulation associated with decreased carbon uptake. These observations suggest that the ecosystem services of water provision and carbon storage may be very different in the forests that regenerate after disturbance.

On a snow cover composition in the vicinity of the Verkhnekamsky Salt Deposit

Directory of Open Access Journals (Sweden)

S. M. Blinov

2015-01-01

Full Text Available The snow cover chemical composition was investigated on the territory of the Verkhnekamskiy potash-magnesium salt deposit in the zone of influence of atmospheric emissions of Berezniki Potash Mining Complex (Perm Region. The object of researches was the snow in this area. Features of specific pollutants contained in the emissions of these mine groups and their relationship with the air intake and following atmospheric deposition were examined. With regard for specific character of pollutants in the emissions, studies of melt water included determination of the following chemical components – SO42-, Cl-, NO3-, NO2-, НCO3-, Ca2+, Mg2+, Na+, K+, of the pH value as well as suspended solid substances, and total mineralization. An analysis of snow composition was performed on two sites from which one was the surrounding background territory, while another area was the urban territory of city Berezniki, i.e. area of operating mine group. To assess the results the indicator of specific stock macro component was used. Increased specific stock relative to the background snowpack is clearly indicative of components directly related to the extraction and processing of salts Cl-, Na+, K+. The revealed anomalies have a local character and, as a rule, do not extend beyond boundaries of sanitary protection zones of the enterprises. Maps of distribution of values of the specific reserves for the analyzed list of components in the melt water were constructed. Our results obtained for the Verkhnekamskiy Deposit area were compared with similar published data on the territories of cities in the zone influenced by motor roads, reserves, and coastal zones of the Russian Arctic seas.

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing in the Wind River Range, Wyoming

Science.gov (United States)

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

2010-01-01

MODIS-derived snow cover measured on 30 April in any given year explains approximately 89 % of the variance in stream discharge for maximum monthly streamflow in that year. Observed changes in streamflow appear to be related to increasing maximum air temperatures over the last four decades causing lower spring snow-cover extent. The majority (>70%) of the water supply in the western United States comes from snowmelt, thus analysis of the declining spring snowpack (and resulting declining stream discharge) has important implications for streamflow management in the drought-prone western U.S.

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

Science.gov (United States)

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

2017-04-01

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

Impacts of changing climate and snow cover on the flow regime of Jhelum River, Western Himalayas

KAUST Repository

Azmat, Muhammad

2016-11-17

This study examines the change in climate variables and snow cover dynamics and their impact on the hydrological regime of the Jhelum River basin in Western Himalayas. This study utilized daily streamflow records from Mangla dam, spanning a time period of 19 years (1995–2013), along with precipitation and temperature data over 52 years (1961–2013) from 12 different climate stations in the catchment. Additionally, moderate-resolution imaging spectroradiometer (MODIS) remote sensing product MOD10A2 was utilized to analyze the change in snow cover dynamics during 2000–2013. The Pearson and Kendall rank correlation tests were used to scrutinize snow cover trends and correlation between temperature, precipitation, snow cover area (SCA) and streamflows records. Basin-wide trend analysis showed a slightly increasing tendency in temperature (τ = 0.098) and precipitation (τ = 0.094), during the years 1961–2013. The changes in streamflow indicated a positive (r > 0.12) relationship with respect to temperature but variable trends (r = −0.45–0.41) with respect to precipitation during both the winter and monsoon seasons. This indicates that temperature has a significant impact on the hydrological regime of the basin. MODIS data-based investigations suggested an expansion in SCA during 2000–2013. The changes in SCA of high-altitude zones (>2000 m a.s.l.) depicted a stronger positive correlation with climate variables and streamflow compared with those obtained for low-altitude regions (<2000 m a.s.l.). Overall, these results signify that high-altitude areas contribute to the streamflow largely in the form of snow- and glacier-melt during the early summer season. The streamflow is then further augmented by monsoon rainfall in the low-elevation regions during late summer.

Airborne gamma-radiation snow water-equivalent and soil-moisture measurements and satellite areal extent of snow-cover measurements. A user's guide. Version 3.0

International Nuclear Information System (INIS)

Carroll, T.; Allen, M.

1988-01-01

The National Remote Sensing Hydrology Program is managed by the Office of Hydrology and consists of the Airborne Snow Survey Section and the Satellite Hydrology Section. The Airborne Snow Survey Section makes airborne snow water-equivalent and soil-moisture measurements over large areas of the country subject to a severe and chronic snowmelt flooding threat. The User's Guide is intended primarily to provide field hydrologists with some background on the technical and administrative aspects of the National Remote Sensing Hydrology Program. The guide summarizes the techniques and procedures used to make and distribute real-time, operational airborne snow water-equivalent measurements and satellite areal extent of snow-cover measurements made over large areas of the country. The current airborne and satellite databases are summarized, and procedures to access the real-time observations through both AFOS and through a commercial, electronic bulletin board system are given in the appendices

EnviroAtlas - Cleveland, OH - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. In this community, vegetated cover is defined as Trees & Forest, Grass & Herbaceous, Woody Wetlands, and Emergent Wetlands. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas ) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

EnviroAtlas - Memphis, TN - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. Vegetated cover is defined as Trees & Forest, Grass & Herbaceous, Woody Wetlands, and Emergent Wetlands. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

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.

EnviroAtlas - Des Moines, IA - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. Vegetated cover is defined as Trees & Forest and Grass & Herbaceous. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://enviroatlas.epa.gov/EnviroAtlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

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

Science.gov (United States)

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

2016-12-01

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

Commodifying snow, taming the waters. Socio-ecological niche construction in an Alpine village.

Science.gov (United States)

Gross, Robert; Winiwarter, Verena

White belts of snow clad mountains all over the world each winter. Even if there is no snow, the tourism industry is able to produce the white finery at the push of the button, thereby consuming large amounts of water. Studying Damüls, a well-known ski resort in Austria's westernmost province Vorarlberg, we can show that the development of a service sector within agro-pastoral landscapes was connected with novel water uses and massive interventions into Alpine landscapes. Human niche construction theory offers a unique avenue for studying the development of Alpine communities, but also highlights side effects accompanying the change from agrarian to tourism livelihoods. One aim of this paper is to broaden the scope of human niche construction theory. Inceptive, counteractive and relocational niche construction activities were coupled to the differentiation of actor groups. To incorporate social dynamics, indispensable for studies in environmental history, we propose the concept of socio-ecological niche construction. The paper investigates how villagers balanced resource limitations typical for an agrarian society with the differentiation of sub-niches, mediating selective forces on the population. When the valleys were industrialized, Damüls was almost given up as a permanent settlement. Then, tourists entered the stage, by and by turning the wheel of local development into a different direction. A tourism niche based on natural snow evolved from the 1930s onwards. While the socio-ecological niches of agriculture and tourism coexisted in the interwar years, this changed when ski lifts were built, embedded into a debt-based economy that made the tourism niche vulnerable to snow availability. Snow-dependency became a powerful selective force. It was mediated by the ski lift companies through a range of niche construction activities that turned water into an important resource of snowmaking systems.

Environmental Controls on Snow Cover Thickness and Water Equivalent in Two Sub-Arctic Mountain Catchments

OpenAIRE

Cosgrove, Christopher

2015-01-01

The spatial variability of snow cover characteristics (depth, density, and snow water equivalent [SWE]) has paramount importance for the management of water resources in mountain environments. Passive microwave (PM) inference of SWE from space-borne instrumentation is increasingly used but the reliability of this technique remains limited in mountainous areas. Complex topography and the transition between forest and alpine tundra vegetation zones create large spatial heterogeneities in the sn...

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

Directory of Open Access Journals (Sweden)

Xinyue Zhang

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

EnviroAtlas - Paterson, NJ - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The Paterson, New Jersey EnviroAtlas Meter-Scale Urban Land Cover (MULC) data comprises approximately 66 km2 around the city of Paterson. The land cover data were...

EVALUATION OF THE URBAN DEVELOPMENT INFLUENCE ON POLLUTION OF SNOW COVER USING GEOINFORMATION AND STATISTICAL ANALYSIS

Directory of Open Access Journals (Sweden)

I. D. Korlyakov

2017-01-01

Full Text Available The influence of urban development parameters on the pollution of snow with heavy metals and metalloids (HMM has been assessed.The aim of the work is to assess the barrier functions of urban development by means of a joint analysis of data on the content of HMM in the snow cover and the parameters of the artificial relief. The residential area of the Ulan-Ude city was chosen as an object of the study, where 27 snow samples were selected. According to the data of the snow survey in 2014, the total content of HMM in the snow suspension was determined, the priority pollutants of the snow were received and the total indicator of immission at the sampling points was calculated. Data processing in the OpenStreetMap, 2GIS, ArcGis 10.0 and Statistica 7.0 software packages made it possible to determine the main parameters of the buildings near the sampling points. Correlation analysis has shown a significant influence of building parameters on the HMM immission in the snow cover. With an increase in the total and average building area, proximity of buildings to the sampling point, an increase in the immission of most or all HMMs has been observed. The height of houses is a secondary factor which positively affects the immission of Cu and Bi. The maximum correlation links are established in radii of 50, 100 and 150 m. The parameters of development affect the total precipitation of pollutants both in all cardinal directions, and in the south-western, northeast, southeast directions, which can be explained by the wind regime features during the winter season. 

EnviroAtlas - Des Moines, IA - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Green Bay, WI - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - New York, NY - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - New Bedford, MA - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Cleveland, OH - 51m Riparian Buffer Vegetated Cover

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. In this community, vegetated cover is defined as Trees & Forest,...

Features of Duration and Borders of the Bedding of Snow Cover in the Conditions of Climatic Changes in the Territory of Northern Kazakhstan According to Land and Space Monitoring

Science.gov (United States)

Salnikov, Vitaliy; Turulina, Galina; Polyakova, Svetlana; Muratova, Nadiya; Kauazov, Azamat; Abugalieva, Aigul; Tazhibayeva, Tamara

2014-05-01

Precipitation and air temperature datasets from 34 meteorological stations were analyzed to reveal the regional climate changes at the territory in North Kazakhstan over the last 58 years (i.e., 1950-2008). Peculiarities and conditions of snow cover formation and melting have been analyzed at territory of Northern Kazakhstan using surface and space monitoring data. Methods of both the geo-informational processing of remote probing data and statistical processing of databases on snow cover, air temperature and precipitations have been used. Analysis of snow cover observations data for territory of Northern Kazakhstan has shown that the stable snow cover might be observed since the middle of November till the beginning of April. In a few last decades the tendency is observed for longevity decrease of snow cover bedding that appears to be on the background air temperature increase and insignificant increase of cold period precipitations due to the later bedding of the snow cover and its earlier destruction. Peculiarities of atmospheric circulation in Atlantic-Eurasian sector of Northern Semi sphere and their influence of formation of snow cover at territory of Northern Kazakhstan. The higher longevity of the snow cover bedding is defined by the predominance of E form circulation and lower longevity - by the predominance of W+C circulation form. Analysis conducted of the highest height of snow cover bedding has shown that for period of 1936-2012 in the most cases the statistically reliable decreasing trends are observed with the linear trend coefficients of 0,50 - 0,60 cm/year. The method is offered for determination of probable characteristics of the snow cover decade height. Using data of space monitoring are allocated the frontiers of snow cover bedding for the period of snow melting 1982-2008 and the snow cover melting maps are developed. The results further confirm the proposition that snow cover availability is an important and limiting factor in the generation

Snow cover and End of Summer Snowline statistics from a simple stochastic model

Science.gov (United States)

Petrelli, A.; Crouzy, B.; Perona, P.

2012-04-01

One essential parameter characterizing snow cover statistics is the End Of Summer Snowline (EOSS), which is also a good indicator of actual climatic trends in mountain regions. EOSS is usually modelled by means of spatially distributed physically based models, and typically require heavy parameterization. In this paper we validate the simple stochastic model proposed by Perona et al. (2007), by showing that the snow cover statistics and the position of EOSS can in principle be explained by only four essential (meteorological) parameters. Perona et al. (2007) proposed a model accounting for stochastic snow accumulation in the cold period, and deterministic melting dynamics in the warm period, and studied the statistical distribution of the snowdepth on the long term. By reworking the ensemble average of the steady state evolution equation we single out a relationship between the snowdepth statistics (including the position of EOSS) and the involved parameters. The validation of the established relationship is done using 50 years of field data from 73 Swiss stations located above 2000 m a.s.l. First an estimation of the meteorological parameters is made. Snow height data are used as a precipitation proxy, using temperature data to estimate SWE during the precipitation event. Thresholds are used both to separate accumulation from actual precipitation and wind transport phenomena, and to better assess summer melting rate, considered to be constant over the melting period according to the simplified model. First results show that data for most of the weather stations actually scales with the proposed relationship. This indicates that, on the long term, the effect of spatial and temporal noise masks most of the process detail so that minimalist models suffice to obtain reliable statistics. Future works will test the validity of this approach at different spatial scales, e.g., regional, continental and planetary. Reference: P. Perona, A. Porporato, and L. Ridolfi, "A

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.

EnviroAtlas - New York, NY - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. In this community, vegetated cover is defined as Trees & Forest and Grass & Herbaceous. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

Dust pollution of snow cover in the industrial areas of Tomsk city (Western Siberia, Russia)

OpenAIRE

Talovskaya, Anna Valerievna; Filimonenko, Ekaterina Anatolievna; Osipova, Nina Aleksandrovna; Yazikov, Yegor (Egor) Grigoryevich; Nadeina, Louise Vasilievna

2016-01-01

This article describes the results of long-term monitoring (2007-2014) of snow cover pollution in the territory of Tomsk city. Snow samples were collected in the territory of Tomsk. Determination of dust load level was carried out by comparing with the background and reference values. It has been determined that the north-east and central parts of Tomsk are the most contaminated areas, where brickworks, coal and gas-fired thermal power plant are located. The analysis of long-term dynamics sho...

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.

EnviroAtlas - Des Moines, IA - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The Des Moines, IA EnviroAtlas Meter-Scale Urban Land Cover (MULC) Data were generated from the High Resolution Land Cover (HRLC) product created by the Iowa...

Technique for radionuclide composition analysis of snow cover in the Chernobyl' NPP 30-km zone using fiber sorbents

International Nuclear Information System (INIS)

Kham'yanov, L.P.; Rau, D.F.; Amosov, M.M.; Strel'nikova, A.E.; Tereshchenko, V.I.; Veber, T.S.

1989-01-01

The high-sensitivity, simple and fast technique for analysis of large-dispersive and ionic components of snow cover radioactivity is suggested. It is based on separation of a sample by fractions, concentration of the dispersive fraction on mechanical filters and the dissolved one on ion-exchange sorbents and separated fraction spectrometry. The minimum measured contamination level is 3.7 Bq/dm 3 for each radionuclide analyzed. The conclusion is made that the technique suggested is the reliable method for radionuclide content analysis is snow cover samples of the Chernobyl' NPP zone. 1 tab

EnviroAtlas - Tampa, FL - Tree Cover Configuration and Connectivity, Water Background

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, forest is trees & forest...

EnviroAtlas - Woodbine, IA - Tree Cover Configuration and Connectivity, Water Background

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, forest is only trees &...

EnviroAtlas - Durham, NC - Tree Cover Configuration and Connectivity, Water Background

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, forest is only trees &...

EnviroAtlas - Fresno, CA - Tree Cover Configuration and Connectivity, Water Background

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, forest is only trees &...

EnviroAtlas - Portland, OR - Tree Cover Configuration and Connectivity, Water Background

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, forest is trees & forest...

EnviroAtlas - Minneapolis/St. Paul, MN - Estimated Percent Tree Cover Along Walkable Roads

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset estimates tree cover along walkable roads. The road width is estimated for each road and percent tree cover is calculated in a 8.5 meter...

EnviroAtlas - Minneapolis/St. Paul, MN - Tree Cover Configuration and Connectivity

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, forest is defined as Trees...

EnviroAtlas - Memphis, TN - Tree Cover Configuration and Connectivity, Water Background

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). Forest is defined as Trees & Forest and Woody...

EnviroAtlas - Austin, TX - Tree Cover Configuration and Connectivity, Water Background

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, Forest is defined as Trees...

Brilliant Colours from a White Snow Cover

Science.gov (United States)

Vollmer, Michael; Shaw, Joseph A

2013-01-01

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

NOAA Climate Data Record (CDR) of Northern Hemisphere (NH) Snow Cover Extent (SCE), Version 1

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This NOAA Climate Data Record (CDR) is a record for the Northern Hemisphere (NH) Snow Cover Extent (SCE) spanning from October 4, 1966 to present, updated monthly...

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.

State of the Earth’s cryosphere at the beginning of the 21st century : glaciers, global snow cover, floating ice, and permafrost and periglacial environments: Chapter A in Satellite image atlas of glaciers of the world

Science.gov (United States)

Williams, Richard S.; Ferrigno, Jane G.; Williams, Richard S.; Ferrigno, Jane G.

2012-01-01

This chapter is the tenth in a series of 11 book-length chapters, collectively referred to as “this volume,” in the series U.S. Geological Survey Professional Paper 1386, Satellite Image Atlas of Glaciers of the World. In the other 10 chapters, each of which concerns a specific glacierized region of Earth, the authors used remotely sensed images, primarily from the Landsat 1, 2, and 3 series of spacecraft, in order to analyze that glacierized region and to monitor changes in its glaciers. Landsat images, acquired primarily during the period 1972 through 1981, were used by an international team of glaciologists and other scientists to study the various glacierized regions and (or) to discuss related glaciological topics. In each glacierized region, the present distribution of glaciers within its geographic area is compared, wherever possible, with historical information about their past areal extent. The atlas provides an accurate regional inventory of the areal extent of glacier ice on our planet during the 1970s as part of an expanding international scientific effort to measure global environmental change on the Earth’s surface. However, this chapter differs from the other 10 in its discussion of observed changes in all four elements of the Earth’s cryosphere (glaciers, snow cover, floating ice, and permafrost) in the context of documented changes in all components of the Earth System. Human impact on the planet at the beginning of the 21st century is pervasive. The focus of Chapter A is on changes in the cryosphere and the importance of long-term monitoring by a variety of sensors carried on Earth-orbiting satellites or by a ground-based network of observatories in the case of permafrost. The chapter consists of five parts. The first part provides an introduction to the Earth System, including the interrelationships of the geosphere (cryosphere, hydrosphere, lithosphere, and atmosphere), the biosphere, climate processes, biogeochemical cycles, and the

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.

The ATLAS Liquid Argon Calorimeter: Construction, Integration, Commissioning

International Nuclear Information System (INIS)

Aleksa, Martin

2006-01-01

The ATLAS liquid argon (LAr) calorimeter system consists of an electromagnetic barrel calorimeter and two end caps with electromagnetic, hadronic and forward calorimeters. The liquid argon sampling technique, with an accordion geometry was chosen for the barrel electromagnetic calorimeter (EMB) and adapted to the end cap (EMEC). The hadronic end cap calorimeter (HEC) uses a copper-liquid argon sampling technique with flat plate geometry and is subdivided in depth in two wheels per end-cap. Finally, the forward calorimeter (FCAL) is composed of three modules employing cylindrical electrodes with thin liquid argon gaps.The construction of the full calorimeter system is complete since mid-2004. Production modules constructed in the home institutes were integrated into wheels at CERN in 2003-2004, and inserted into the three cryostats. They passed their first complete cold test before the lowering into the ATLAS cavern. Results of quality checks (e.g. electrical, mechanical, ...) performed on all the 190304 read-out channels after cool down will be reported. End 2004 the ATLAS barrel electromagnetic (EM) calorimeter was installed in the ATLAS cavern and since summer 2005 the front-end electronics are being connected and tested. Results of this first commissioning phase will be shown to demonstrate the high standards of quality control for our detectors

Snow loads in a changing climate: new risks?

Directory of Open Access Journals (Sweden)

U. Strasser

2008-01-01

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

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

Influence of cloud fraction and snow cover to the variation of surface UV radiation at King Sejong station, Antarctica

Science.gov (United States)

Lee, Yun Gon; Koo, Ja-Ho; Kim, Jhoon

2015-10-01

This study investigated how cloud fraction and snow cover affect the variation of surface ultraviolet (UV) radiation by using surface Erythemal UV (EUV) and Near UV (NUV) observed at the King Sejong Station, Antarctica. First the Radiative Amplification Factor (RAF), the relative change of surface EUV according to the total-column ozone amount, is compared for different cloud fractions and solar zenith angles (SZAs). Generally, all cloudy conditions show that the increase of RAF as SZA becomes larger, showing the larger effects of vertical columnar ozone. For given SZA cases, the EUV transmission through mean cloud layer gradually decreases as cloud fraction increases, but sometimes the maximum of surface EUV appears under partly cloudy conditions. The high surface EUV transmittance under broken cloud conditions seems due to the re-radiation of scattered EUV by cloud particles. NUV transmission through mean cloud layer also decreases as cloud amount increases but the sensitivity to the cloud fraction is larger than EUV. Both EUV and NUV radiations at the surface are also enhanced by the snow cover, and their enhancement becomes higher as SZA increases implying the diurnal variation of surface albedo. This effect of snow cover seems large under the overcast sky because of the stronger interaction between snow surface and cloudy sky.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Snow Cover Environmental Data Record (EDR) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of snow cover from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument...

The effects of additional black carbon on Arctic sea ice surface albedo: variation with sea ice type and snow cover

OpenAIRE

A. A. Marks; M. D. King

2013-01-01

Black carbon in sea ice will decrease sea ice surface albedo through increased absorption of incident solar radiation, exacerbating sea ice melting. Previous literature has reported different albedo responses to additions of black carbon in sea ice and has not considered how a snow cover may mitigate the effect of black carbon in sea ice. Sea ice is predominately snow covered. Visible light absorption and light scattering coefficients are calculated for a typical first year and multi-y...

EnviroAtlas - Minneapolis/St. Paul, MN - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. In this community, vegetated cover is defined as Trees and Forest, Grass and Herbaceous, Woody Wetlands, and Emergent Wetlands. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Snow as building material for construction of technological along-the-route roads of main pipelines

Science.gov (United States)

Merdanov, S. M.; Egorov, A. L.; Kostyrchenko, V. A.; Madyarov, T. M.

2018-05-01

The article deals with the process of compacting snow in a closed volume with the use of vacuum processing for the construction of technological along-the-route roads of main pipelines. The relevance of the chosen study is substantiated; methods and designs for snow compaction are considered. The publication activity and defenses of doctoral and candidate dissertations on the research subject are analyzed. Patent analysis of existing methods and equipment for snow compaction with indication of their disadvantages is carried out. A design calculation was carried out using computer programs in which a strength calculation was performed to identify the most stressed places in the construction of a vibrating hydraulic tyre-type roller. A 3D model of the experimental setup was developed.

Ligninolytic Activity at 0 °C of Fungi on Oak Leaves Under Snow Cover in a Mixed Forest in Japan.

Science.gov (United States)

Miyamoto, Toshizumi; Koda, Keiichi; Kawaguchi, Arata; Uraki, Yasumitsu

2017-08-01

Despite the importance of litter decomposition under snow cover in boreal forests and tundra, very little is known regarding the characteristics and functions of litter-decomposing fungi adapted to the cold climate. We investigated the decomposition of oak leaves in a heavy snowfall forest region of Japan. The rate of litter weight loss reached 26.5% during the snow cover period for 7 months and accounted for 64.6% of the annual loss (41.1%). Although no statistically significant lignin loss was detected, decolourization portions of oak leaf litter, which was attributable to the activities of ligninolytic fungi, were observed during snow cover period. This suggests that fungi involved in litter decomposition can produce extracellular enzymes to degrade lignin that remain active at 0 °C. Fungi were isolated from oak leaves collected from the forest floor under the snow layer. One hundred and sixty-six strains were isolated and classified into 33 operational taxonomic units (OTUs) based on culture characteristics and nuclear rDNA internal transcribed spacer (ITS) region sequences. To test the ability to degrade lignin, the production of extracellular phenoloxidases by isolates was quantified at 0 °C. Ten OTUs (9 Ascomycota and 1 Basidiomycota) of fungi exhibited mycelial growth and ligninolytic activity. These results suggested that some litter-decomposing fungi that had the potential to degrade lignin at 0 °C significantly contribute to litter decomposition under snow cover.

The construction of the ATLAS semi-conductor tracker

International Nuclear Information System (INIS)

Jones, Tim

2006-01-01

The ATLAS (A Toroidal LHC ApparatuS) experiment at the Large Hadron Collider (LHC) at CERN has been designed to explore physics at the TeV energy scale and will be commissioned in 2007. In the innermost region of the experiment is a charged particle tracker, the Inner Detector of which the Semiconductor Tracker (SCT) is a major component. The SCT comprises a central barrel section enclosed by two endcaps (A and C). The construction of the major components of the ATLAS Semi-conductor tracker (SCT) is now nearing completion. Following a brief description of the design of the SCT, the logistics and organisation of the construction phase of the project are discussed. Central to the delivery of a high quality detector is the testing of large numbers of modules both during assembly and after they are mounted on their final support structures. The results of these tests for endcap C are presented showing that the electrical performance of the 988 modules to be installed in ATLAS is compatible with the specifications required

EnviroAtlas - Pittsburgh, PA - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The EnviroAtlas Pittsburgh, PA Meter-Scale Urban Land Cover (MULC) data was generated from United States Department of Agriculture (USDA) National Agricultural...

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

Performances of an expanding insect under elevated CO{sub 2} and snow cover in the Alps

Energy Technology Data Exchange (ETDEWEB)

Battisti, B.; Petrucco-Toffolo, E. [University of Padova, Legnaro (Italy). Dept. of Environmental Agronomy

2008-09-30

Variations of phenology and distribution have been recently highlighted in numerous insect species and attributed to climate change, particularly the increase of temperature and atmospheric carbon dioxide (CO{sub 2}). Both have been shown to have direct and indirect effects on insect species of various ecosystems, though the responses are often species-specific. The pine processionary moth, Thaumetopoea pityocampa (Lepidoptera, Notodontidae) is an important pest of conifers in the Mediterranean region, and has been recently shown to expand its altitudinal range in the Alps, including the mountain pine Pinus mugo as a novel host. We had the opportunity to transplant colonies of the pine processionary moth to a high elevation site well outside of the current range of the insect (Stillberg, Davos, Switzerland, 2180 m), where trees of the mountain pine have been grown for five years under ambient and elevated CO{sub 2} concentrations (ca. 570 ppm). The aim of the study was to evaluate the response of first instar larvae to extreme conditions of temperature and to an altered performance induced by the change of host metabolism under elevated CO{sub 2}. Larval mortality and relative growth rate did not differ between host trees grown in ambient or elevated CO{sub 2}. As extended snow cover may be an important mortality factor of larval colonies on the dwarf trees of mountain pine, we tested the survival of colonies transplanted at two extreme sites of Eastern Alps. The snow cover extended over more than one month proved to be an important mortality factor of larval colonies on mountain pine. We concluded that the first instar larvae of the pine processionary moth are not concerned by unusually low temperature and CO{sub 2} increase whereas they can be later strongly affected by snow accumulation. The decrease of snow cover observed in the last decades, however, may reduce such a risk.

EnviroAtlas - Austin, TX - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The Austin, TX EnviroAtlas One Meter-scale Urban Land Cover (MULC) Data were generated from United States Department of Agriculture (USDA) National Agricultural...

EnviroAtlas - Green Bay, WI - Tree Cover Configuration and Connectivity, Water Background

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, forest is trees & forest...

EnviroAtlas - Des Moines, IA - Tree Cover Configuration and Connectivity, Water Background

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset categorizes forest land cover into structural elements (e.g. core, edge, connector, etc.). In this community, Forest is defined as Trees...

EnviroAtlas - Green Bay, WI - Riparian Buffer Land Cover by Block Group

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset describes the percentage of different land cover types within 15- and 50-meters of hydrologically connected streams, rivers, and other water...

EnviroAtlas - New Bedford, MA - Riparian Buffer Land Cover by Block Group

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset describes the percentage of different land cover types within 15- and 50-meters of hydrologically connected streams, rivers, and other water...

EnviroAtlas - Portland, ME - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The EnviroAtlas Portland, ME Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green,...

Southern Hemisphere origins for interannual variations of Tibetan Plateau snow cover in boreal summer

Science.gov (United States)

Wu, Z.

2017-12-01

The climate response to the Tibetan Plateau (TP) snow cover (TPSC) has been receiving extensive concern. However, relatively few studies have devoted to revealing the potential factors that can contribute to the TPSC variability on the interannual time scale. Especially during the boreal summer, snow cover can persist over the TP at high elevations, which exerts profound influences on the local and remote climate change. The present study finds that May Southern Hemisphere (SH) annular mode (SAM), the dominating mode of atmospheric circulation variability in the SH extratropics, exhibits a significant positive relationship with the boreal summer TPSC interannual variability. Observational analysis and numerical experiments manifest that the signal of May SAM can be "prolonged" by a meridional Indian Ocean tripole (IOT) sea surface temperature anomaly (SSTA) via atmosphere-ocean interaction. The IOT SSTA pattern persists into the following summer and excites anomalous local-scale zonal vertical circulation. Subsequently, a positive (or negative) tropical dipole rainfall (TDR) mode is induced with deficient (or sufficient) precipitation in tropical western Indian Ocean and sufficient (or deficient) precipitation in eastern Indian Ocean-Maritime continent. Rossby wave source diagnosis reveals that the wave energies, generated by the latent heat release of the TDR mode, propagate northward into western TP. As a response, abnormal cyclonic circulation and upward movement are triggered and prevail over western TP, providing favorable dynamical conditions for more TPSC, and vice versa. Hence, the IOT SSTA plays an "ocean bridge" role and the TDR mode acts as an "atmosphere bridge" role in the process of May SAM impacting the following summer TPSC variability. The results of our work may provide new insight about the cross-equatorial propagation of the SAM influence. Keywords Southern Hemisphere annular mode; Tibetan Plateau snow cover; Rossby wave source

EnviroAtlas - Fresno, CA - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The Fresno, CA EnviroAtlas Meter-Scale Urban Land Cover (MULC) Data were generated via supervised classification of combined aerial photography and LiDAR data. The...

EnviroAtlas - Tampa, FL - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The EnviroAtlas Tampa, FL Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue...

EnviroAtlas - Portland, OR - Meter-Scale Urban Land Cover (MULC) Data (2012)

Data.gov (United States)

U.S. Environmental Protection Agency — The EnviroAtlas Portland, OR Meter-Scale Urban Land Cover (MULC) dataset includes data for the Portland metropolitan area plus the city of Vancouver, Washington and...

EnviroAtlas - Woodbine, IA - Meter-Scale Urban Land Cover (MULC) Data (2011)

Data.gov (United States)

U.S. Environmental Protection Agency — The EnviroAtlas Woodbine, IA Meter-Scale Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red,...

EnviroAtlas - Phoenix, AZ - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The EnviroAtlas Phoenix, AZ Meter-Scale Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red,...

EnviroAtlas - Durham, NC - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The EnviroAtlas Durham, NC Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue...

Snow cover variability in a forest ecotone of the Oregon Cascades via MODIS Terra products

Science.gov (United States)

Tihomir Sabinov Kostadinov; Todd R. Lookingbill

2015-01-01

Snowcover pattern and persistence have important implications for planetary energy balance, climate sensitivity to forcings, and vegetation structure, function, and composition. Variability in snow cover within mountainous regions of the Pacific Northwest, USA is attributable to a combination of anthropogenic climate change and climate oscillations. However,...

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

Science.gov (United States)

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

2016-01-01

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

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.

Impacts of changing climate and snow cover on the flow regime of Jhelum River, Western Himalayas

KAUST Repository

Azmat, Muhammad; Liaqat, Umar Waqas; Qamar, Muhammad Uzair; Awan, Usman Khalid

2016-01-01

This study examines the change in climate variables and snow cover dynamics and their impact on the hydrological regime of the Jhelum River basin in Western Himalayas. This study utilized daily streamflow records from Mangla dam, spanning a time

EnviroAtlas - Memphis, TN - Meter-Scale Urban Land Cover (MULC) Data (2012)

Data.gov (United States)

U.S. Environmental Protection Agency — The Memphis, TN EnviroAtlas One Meter-scale Urban Land Cover (MULC) dataset comprises 2,733 km2 around the city of Memphis, surrounding towns, and rural areas. These...

Modeling the influence of snow cover on low Arctic net ecosystem exchange

International Nuclear Information System (INIS)

Luus, K A; Kelly, R E J; Lin, J C; Humphreys, E R; Lafleur, P M; Oechel, W C

2013-01-01

The Arctic net ecosystem exchange (NEE) of CO 2 between the land surface and the atmosphere is influenced by the timing of snow onset and melt. The objective of this study was to examine whether uncertainty in model estimates of NEE could be reduced by representing the influence of snow on NEE using remote sensing observations of snow cover area (SCA). Observations of NEE and time-lapse images of SCA were collected over four locations at a low Arctic site (Daring Lake, NWT) in May–June 2010. Analysis of these observations indicated that SCA influences NEE, and that good agreement exists between SCA derived from time-lapse images, Landsat and MODIS. MODIS SCA was therefore incorporated into the vegetation photosynthesis respiration model (VPRM). VPRM was calibrated using observations collected in 2005 at Daring Lake. Estimates of NEE were then generated over Daring Lake and Ivotuk, Alaska (2004–2007) using VPRM formulations with and without explicit representations of the influence of SCA on respiration and/or photosynthesis. Model performance was assessed by comparing VPRM output against unfilled eddy covariance observations from Daring Lake and Ivotuk (2004–2007). The uncertainty in VPRM estimates of NEE was reduced when respiration was estimated as a function of air temperature when SCA ≤ 50% and as a function of soil temperature when SCA > 50%. (letter)

Western Italian Alps Monthly Snowfall and Snow Cover Duration

Data.gov (United States)

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

Investigating Snow Cover and Hydrometeorological Trends in Contrasting Hydrological Regimes of the Upper Indus Basin

Directory of Open Access Journals (Sweden)

Iqra Atif

2018-04-01

Full Text Available The Upper Indus basin (UIB is characterized by contrasting hydrometeorological behaviors; therefore, it has become pertinent to understand hydrometeorological trends at the sub-watershed level. Many studies have investigated the snow cover and hydrometeorological modeling at basin level but none have reported the spatial variability of trends and their magnitude at a sub-basin level. This study was conducted to analyze the trends in the contrasting hydrological regimes of the snow and glacier-fed river catchments of the Hunza and Astore sub-basins of the UIB. Mann-Kendall and Sen’s slope methods were used to study the main trends and their magnitude using MODIS snow cover information (2001–2015 and hydrometeorological data. The results showed that in the Hunza basin, the river discharge and temperature were significantly (p ≤ 0.05 decreased with a Sen’s slope value of −2.541 m3·s−1·year−1 and −0.034 °C·year−1, respectively, while precipitation data showed a non-significant (p ≥ 0.05 increasing trend with a Sen’s slope value of 0.023 mm·year−1. In the Astore basin, the river discharge and precipitation are increasing significantly (p ≤ 0.05 with a Sen’s slope value of 1.039 m3·s−1·year−1 and 0.192 mm·year−1, respectively. The snow cover analysis results suggest that the Western Himalayas (the Astore basin had a stable trend with a Sen’s slope of 0.07% year−1 and the Central Karakoram region (the Hunza River basin shows a slightly increasing trend with a Sen’s slope of 0.394% year−1. Based on the results of this study it can be concluded that since both sub-basins are influenced by different climatological systems (monsoon and westerly, the results of those studies that treat the Upper Indus basin as one unit in hydrometeorological modeling should be used with caution. Furthermore, it is suggested that similar studies at the sub-basin level of the UIB will help in a better understanding of the

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

EnviroAtlas - Milwaukee, WI - Meter-Scale Urban Land Cover Data (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The EnviroAtlas Milwaukee, WI Meter Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green,...

EnviroAtlas - New York, NY - Meter-Scale Urban Land Cover (MULC) Data (2008)

Data.gov (United States)

U.S. Environmental Protection Agency — The New York, NY EnviroAtlas Meter-scale Urban Land Cover (MULC) Data were generated by the University of Vermont Spatial Analysis Laboratory (SAL) under the...

Enhancement of snow cover change detection with sparse representation and dictionary learning

Science.gov (United States)

Varade, D.; Dikshit, O.

2014-11-01

Sparse representation and decoding is often used for denoising images and compression of images with respect to inherent features. In this paper, we adopt a methodology incorporating sparse representation of a snow cover change map using the K-SVD trained dictionary and sparse decoding to enhance the change map. The pixels often falsely characterized as "changes" are eliminated using this approach. The preliminary change map was generated using differenced NDSI or S3 maps in case of Resourcesat-2 and Landsat 8 OLI imagery respectively. These maps are extracted into patches for compressed sensing using Discrete Cosine Transform (DCT) to generate an initial dictionary which is trained by the K-SVD approach. The trained dictionary is used for sparse coding of the change map using the Orthogonal Matching Pursuit (OMP) algorithm. The reconstructed change map incorporates a greater degree of smoothing and represents the features (snow cover changes) with better accuracy. The enhanced change map is segmented using kmeans to discriminate between the changed and non-changed pixels. The segmented enhanced change map is compared, firstly with the difference of Support Vector Machine (SVM) classified NDSI maps and secondly with a reference data generated as a mask by visual interpretation of the two input images. The methodology is evaluated using multi-spectral datasets from Resourcesat-2 and Landsat-8. The k-hat statistic is computed to determine the accuracy of the proposed approach.

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.

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

KAUST Repository

Jadoon, Khan; Lambot, Sé bastien; Dimitrov, Marin; Weihermü ller, Lutz

2013-01-01

We performed off-ground ground-penetrating radar (GPR) measurements over a bare agricultural field to monitor the freeze-thaw cycles over snow-cover. The GPR system consisted of a vector network analyzer combined with an off-ground monostatic horn

Performance of complex snow cover descriptions in a distributed hydrological model system: A case study for the high Alpine terrain of the Berchtesgaden Alps.

Science.gov (United States)

Warscher, M; Strasser, U; Kraller, G; Marke, T; Franz, H; Kunstmann, H

2013-05-01

[1] Runoff generation in Alpine regions is typically affected by snow processes. Snow accumulation, storage, redistribution, and ablation control the availability of water. In this study, several robust parameterizations describing snow processes in Alpine environments were implemented in a fully distributed, physically based hydrological model. Snow cover development is simulated using different methods from a simple temperature index approach, followed by an energy balance scheme, to additionally accounting for gravitational and wind-driven lateral snow redistribution. Test site for the study is the Berchtesgaden National Park (Bavarian Alps, Germany) which is characterized by extreme topography and climate conditions. The performance of the model system in reproducing snow cover dynamics and resulting discharge generation is analyzed and validated via measurements of snow water equivalent and snow depth, satellite-based remote sensing data, and runoff gauge data. Model efficiency (the Nash-Sutcliffe coefficient) for simulated runoff increases from 0.57 to 0.68 in a high Alpine headwater catchment and from 0.62 to 0.64 in total with increasing snow model complexity. In particular, the results show that the introduction of the energy balance scheme reproduces daily fluctuations in the snowmelt rates that trace down to the channel stream. These daily cycles measured in snowmelt and resulting runoff rates could not be reproduced by using the temperature index approach. In addition, accounting for lateral snow transport changes the seasonal distribution of modeled snowmelt amounts, which leads to a higher accuracy in modeling runoff characteristics.

Polycyclic Aromatic Hydrocarbons In Aerosol and Snow Cover of Siberian Towns (east Siberia)

Science.gov (United States)

Gorshkov, A.; Marinayte, I.

Contamination of the atmosphere above Siberian towns has a few peculiarities: (i) level of pollution is presumably determined by discharges of large enterprises sur- rounded by company towns; (ii) long (up to 150 days) winter is characterized by the highest concentrations of pollutants within the near-ground atmospheric layer due to pronounced anti-cyclonic circulation of the atmosphere; (iii) polycyclic aromatic hydrocarbons (PAH) are specific minor components of the aerosols. Relatively high PAH concentrations in aerosol of Siberian towns are caused by the presence of ad- ditional intensive sources of PAH (besides those traditional: gas discharges of met- allurgy, heat-and-power engineering enterprises, and motor transport). These are the discharges of low power (produc- ing plant (50000 residents) - are presented in the report. Daily and seasonal dynamics of aerosol pollution and level of PAH accumulation in snow covers during 1996 U 2001 are estimated. The highest PAH concentrations (total concentrations of identi- fied compounds) are up to 300 ng/m3 in aerosol and up to 16 mg/m2 in snow cover. At day and night temperatures lowering up to -30 oe -40 01057;, the maximum of PAH concentration is observed in the daytime due to displacement of the tempera-ture in- version. When temperature increases, two SclassicalT maximums are observed during & cedil;the morning and the evening hours. It was shown that the effect of Scity air circula- & cedil;tionT caused by air masses transportation above a city from its center to out-skirts (within the near-ground air layer U to its center) does not contribute to efficient level- ing of PAH concentrations. The level of PAH accumulation in snow cover in different citySs sites and within one citySs region is ranging up to 10 times during a season. Calculated benz[a]pyren fluxes allow us to conclude that contamination of the atmo- sphere above Irkutsk (2.5 mkg/m2 per week) is comparable with that above large cities of Western

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.

On the need for a time- and location-dependent estimation of the NDSI threshold value for reducing existing uncertainties in snow cover maps at different scales

Science.gov (United States)

Härer, Stefan; Bernhardt, Matthias; Siebers, Matthias; Schulz, Karsten

2018-05-01

Knowledge of current snow cover extent is essential for characterizing energy and moisture fluxes at the Earth's surface. The snow-covered area (SCA) is often estimated by using optical satellite information in combination with the normalized-difference snow index (NDSI). The NDSI thereby uses a threshold for the definition if a satellite pixel is assumed to be snow covered or snow free. The spatiotemporal representativeness of the standard threshold of 0.4 is however questionable at the local scale. Here, we use local snow cover maps derived from ground-based photography to continuously calibrate the NDSI threshold values (NDSIthr) of Landsat satellite images at two European mountain sites of the period from 2010 to 2015. The Research Catchment Zugspitzplatt (RCZ, Germany) and Vernagtferner area (VF, Austria) are both located within a single Landsat scene. Nevertheless, the long-term analysis of the NDSIthr demonstrated that the NDSIthr at these sites are not correlated (r = 0.17) and different than the standard threshold of 0.4. For further comparison, a dynamic and locally optimized NDSI threshold was used as well as another locally optimized literature threshold value (0.7). It was shown that large uncertainties in the prediction of the SCA of up to 24.1 % exist in satellite snow cover maps in cases where the standard threshold of 0.4 is used, but a newly developed calibrated quadratic polynomial model which accounts for seasonal threshold dynamics can reduce this error. The model minimizes the SCA uncertainties at the calibration site VF by 50 % in the evaluation period and was also able to improve the results at RCZ in a significant way. Additionally, a scaling experiment shows that the positive effect of a locally adapted threshold diminishes using a pixel size of 500 m or larger, underlining the general applicability of the standard threshold at larger scales.

The effects of additional black carbon on the albedo of Arctic sea ice: variation with sea ice type and snow cover

OpenAIRE

A. A. Marks; M. D. King

2013-01-01

The response of the albedo of bare sea ice and snow-covered sea ice to the addition of black carbon is calculated. Visible light absorption and light-scattering cross-sections are derived for a typical first-year and multi-year sea ice with both "dry" and "wet" snow types. The cross-sections are derived using data from a 1970s field study that recorded both reflectivity and light penetration in Arctic sea ice and snow overlying sea ice. The variation of absorption cross-section ov...

[MONITORING OF THE CONTENT OF HEAVY METALS AND ELEMENTS IN THE SNOW COVER IN AGRICULTURAL SOILS AT THE TERRITORY OF THE MOSCOW REGION].

Science.gov (United States)

Ermakov, A A; Karpova, E A; Malysheva, A G; Mikhaylova, R I; Ryzhova, I N

2015-01-01

The monitoring of snow cover pollution by heavy metals and elements (zinc, copper, lead, cadmium, arsenic, nickel, chromium, strontium, manganese, fluorine, lithium) was performed in 20 districts of the Moscow region in 2009, 2012 and 2013. The assessment of the levels of contamination by heavy metals and elements was given by means of comparison of them with the average values in the snow cover near Moscow in the end of the last century and in some areas of the world, that no exposed to technological environmental impact. 7 districts of Moscow region were characterized by a high content of lead and cadmium in the snow water. It requires the control of water, soil and agricultural products pollution.

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

River flow regime and snow cover of the Pamir Alay (Central Asia) in a changing climate

NARCIS (Netherlands)

Chevallier, P.; Pouyaud, B.; Mojaisky, M.; Bolgov, M.; Olsson, O.; Bauer, M.; Froebrich, J.

2014-01-01

The Vakhsh and Pyandj rivers, main tributaries of the Amu Darya River in the mountainous region of the Pamir Alay, play an important role in the water resources of the Aral Sea basin (Central Asia). In this region, the glaciers and snow cover significantly influence the water cycle and flow regime,

Toxic elements (As, Se, Cd, Hg, Pb) and their mineral and technogenic formations in the snow cover in the vicinity of the industrial enterprises of Tomsk

International Nuclear Information System (INIS)

Talovskaya, A V; Filimonenko, E A; Osipova, N A; Lyapina, E E; Azikov, E G Y

2014-01-01

Snow samples were collected in four industrial areas of Tomsk where brickworks, factories for the production of reinforced concrete structures, machine repair industries and local boilers, petrochemical plant and thermal power station are located. Study of insoluble fraction of aerosols in snow and melted snow water was performed to determine the contents of the emissions from these facilities. The insoluble fraction of aerosols in snow is aerosol particles deposited on snow cover. As, Se, Cd, Hg, Pb concentration was analyzed by inductively coupled plasma mass spectrometry (ICP-MS). Mineral modes of the elements were determined by scanning electron microscope. It was found the snow cover is mainly polluted by As, Se, Cd, Hg, Pb in the thermal power station impact area, by As – in the brickworks impact area, by Se – in the impact area of densely located factories for the production of reinforced concrete structures, machine repair industries and local boilers. The research results show that the mineral modes of As are associated with arsenopyrite, of Pb – with galena in the insoluble fraction of aerosols in snow

Radiative forcing over the conterminous United States due to contemporary land cover land use change and sensitivity to snow and interannual albedo variability

Science.gov (United States)

Barnes, Christopher A.; Roy, David P.

2010-01-01

Satellite-derived land cover land use (LCLU), snow and albedo data, and incoming surface solar radiation reanalysis data were used to study the impact of LCLU change from 1973 to 2000 on surface albedo and radiative forcing for 58 ecoregions covering 69% of the conterminous United States. A net positive surface radiative forcing (i.e., warming) of 0.029 Wm−2 due to LCLU albedo change from 1973 to 2000 was estimated. The forcings for individual ecoregions were similar in magnitude to current global forcing estimates, with the most negative forcing (as low as −0.367 Wm−2) due to the transition to forest and the most positive forcing (up to 0.337 Wm−2) due to the conversion to grass/shrub. Snow exacerbated both negative and positive forcing for LCLU transitions between snow-hiding and snow-revealing LCLU classes. The surface radiative forcing estimates were highly sensitive to snow-free interannual albedo variability that had a percent average monthly variation from 1.6% to 4.3% across the ecoregions. The results described in this paper enhance our understanding of contemporary LCLU change on surface radiative forcing and suggest that future forcing estimates should model snow and interannual albedo variation.

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

Science.gov (United States)

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

2017-12-01

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

The ATLAS Insertable B-Layer: from construction to operation

CERN Document Server

La Rosa, Alessandro; The ATLAS collaboration

2016-01-01

The ATLAS Insertable B-Layer (IBL) is a fourth layer of pixel detectors, and has been installed in May 2014 at a radius of 3.3 cm between the existing Pixel Detector and a new smaller radius beam-pipe. The new detector, built to cope with high radiation and occupancy, is the first large scale application of 3D detectors and CMOS 130nm technology. The IBL detector construction was achieved within about two years starting from mid-2012 to the May 2014 installation in ATLAS, a very tight schedule to meet the ATLAS installation and detector closure before starting the Run2 in Spring 2015. The key features and challenges met during the IBL project will be presented, as well as its commissioning and operational experience in LHC.

EnviroAtlas - 2011 Land Cover by 12-digit HUC for the Conterminous United States

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset represents the percentage of land area that is classified as natural, forest, wetland, agricultural, natural, and developed land cover using...

Predicting average wintertime wind and wave conditions in the North Atlantic sector from Eurasian snow cover in October

International Nuclear Information System (INIS)

Brands, Swen

2014-01-01

The present study assesses the lead–lag teleconnection between Eurasian snow cover in October and the December-to-February mean boreal winter climate with respect to the predictability of 10 m wind speed and significant wave heights in the North Atlantic and adjacent seas. Lead–lag correlations exceeding a magnitude of 0.8 are found for the short time period of 1997/98–2012/13 (n = 16) for which daily satellite-sensed snow cover data is available to date. The respective cross-validated hindcast skill obtained from using linear regression as a statistical forecasting technique is similarly large in magnitude. When using a longer but degraded time series of weekly snow cover data for calculating the predictor variable (1979/80–2011/12, n = 34), hindcast skill decreases but yet remains significant over a large fraction of the study area. In addition, Monte-Carlo field significance tests reveal that the patterns of skill are globally significant. The proposed method might be used to make forecast decisions for wind and wave energy generation, seafaring, fishery and offshore drilling. To exemplify its potential suitability for the latter sector, it is additionally applied to DJF frequencies of significant wave heights exceeding 2 m, a threshold value above which mooring conditions at oil platforms are no longer optimal. (paper)

Construction and test of sMDT chambers for the ATLAS muon spectrometer

Energy Technology Data Exchange (ETDEWEB)

Takasugi, Eric; Schmidt-Sommerfeld, Korbinian; Kortner, Oliver; Kroha, Hubert [Max-Planck-Institut fuer Physik, Muenchen (Germany)

2016-07-01

In the ATLAS muon spectrometer, Monitored Drift Tube chambers (MDTs) are used for precise tracking measurements. In order to increase the geometric acceptance and rate capability, new chambers have been designed and are under construction to be installed in ATLAS during the winter shutdown of 2016/17 of the LHC. The new chambers have a drift tube diameter of 15 mm (compared to 30 mm of the other MDTs) and are therefore called sMDT chambers. This presentation reports on the progress of chamber construction and on the results of quality assurance tests.

EnviroAtlas - Minneapolis/St. Paul, MN - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

U.S. Environmental Protection Agency — The Minneapolis-St. Paul, MN EnviroAtlas Meter-scale Urban Land Cover (MULC) data were generated from four-band (red, green, blue, and near infrared) aerial...

EnviroAtlas - 2011 Agricultural Land Cover on Steep Slopes for the Conterminous United States

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas dataset represents the percentage land area that is classified as agricultural land cover that occurs on slopes above a given threshold for each...

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.

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

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

Effects of soil water and heat relationship under various snow cover during freezing-thawing periods in Songnen Plain, China.

Science.gov (United States)

Fu, Qiang; Hou, Renjie; Li, Tianxiao; Jiang, Ruiqi; Yan, Peiru; Ma, Ziao; Zhou, Zhaoqiang

2018-01-22

In this study, the spatial variations of soil water and heat under bare land (BL), natural snow (NS), compacted snow (CS) and thick snow (TS) treatments were analyzed. The relationship curve between soil temperature and water content conforms to the exponential filtering model, by means of the functional form of the model, it was defined as soil water and heat relation function model. On this basis, soil water and heat function models of 10, 20, 40, 60, 100, and 140 cm were established. Finally, a spatial variation law of the relationship effect was described based on analysising of the differences between the predicted and measured results. During freezing period, the effects of external factors on soil were hindered by snow cover. As the snow increased, the accuracy of the function model gradually improved. During melting period, infiltration by snowmelt affected the relationship between the soil temperature and moisture. With the increasing of snow, the accuracy of the function models gradually decreased. The relationship effects of soil water and heat increased with increasing depth within the frozen zone. In contrast, below the frozen layer, the relationship of soil water and heat was weaker, and the function models were less accurate.

EnviroAtlas - Cleveland, OH - Meter-Scale Urban Land Cover (MULC) Data (2011 and 2013)

Data.gov (United States)

U.S. Environmental Protection Agency — The Cleveland, OH EnviroAtlas Meter-scale Urban Land Cover (MULC) dataset comprises 2,737 km2 around the city of Cleveland and portions of surrounding counties. The...

Snow, ice and solar radiation

NARCIS (Netherlands)

Kuipers Munneke, P.

2009-01-01

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

A GIS Software Toolkit for Monitoring Areal Snow Cover and Producing Daily Hydrologic Forecasts using NASA Satellite Imagery, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Aniuk Consulting, LLC, proposes to create a GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts. This toolkit will be...

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.

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

The bright side of snow cover effects on PV production - How to lower the seasonal mismatch between electricity supply and demand in a fully renewable Switzerland

Science.gov (United States)

Kahl, Annelen; Dujardin, Jérôme; Dupuis, Sonia; Lehning, Michael

2017-04-01

One of the major problems with solar PV in the context of a fully renewable electricity production at mid-latitudes is the trend of higher production in summer and lower production in winter. This trend is most often exactly opposite to demand patterns, causing a seasonal mismatch that requires extensive balancing power from other production sources or large storage capacities. Which possibilities do we have to bring PV production into closer correlation with demand? This question motivated our research and in response we investigated the effects of placing PV panels at different tilt angles in regions with extensive snow cover to increase winter production from ground reflected short wave radiation. The aim of this project is therefore to quantify the effect of varying snow cover duration (SCD) and of panel tilt angle on the annual total production and on production during winter months when electricity is most needed. We chose Switzerland as ideal test site, because it has a wide range of snow cover conditions and a high potential for renewable electricity production. But methods can be applied to other regions of comparable conditions for snow cover and irradiance. Our analysis can be separated into two steps: 1. A systematic, GIS and satellite-based analysis for all of Switzerland: We use time series of satellite-derived irradiance, and snow cover characteristics together with land surface cover types and elevation information to quantify the environmental conditions and to estimate potential production and ideal tilt angles. 2. A scenario-based analysis that contrasts the production patterns of different placement scenarios for PV panels in urban, rural and mountainous areas. We invoke a model of a fully renewable electricity system (including Switzerland's large hydropower system) at national level to compute the electricity import and storage capacity that will be required to balance the remaining mismatch between production and demand to further illuminate

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

Data.gov (United States)

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

The ATLAS hadronic tile calorimeter from construction toward physics

CERN Document Server

Adragna, P; Anderson, K; Antonaki, A; Batusov, V; Bednar, P; Binet, S; Biscarat, C; Blanchot, G; Bogush, A A; Bohm, C; Boldea, V; Bosman, M; Bromberg, C; Budagov, Yu A; Caloba, L; Calvet, D; Carvalho, J; Castelo, J; Castillo, M V; Sforza, M C; Cavasinni, V; Cerqueira, A S; Chadelas, R; Costanzo, D; Cogswell, F; Constantinescu, S; Crouau, M; Cuenca, C; Damazio, D O; Daudon, F; David, M; Davidek, T; De, K; Del Prete, T; Di Girolamo, B; Dita, S; Dolejsi, J; Dolezal, Z; Dotti, A; Downing, R; Efthymiopoulos, I; Errede, D; Errede, S; Farbin, A; Fassouliotis, D; Fedorko, I; Fenyuk, A; Ferdi, C; Ferrer, A; Flaminio, V; Fullana, E; Garde, V; Giakoumopoulou, V; Gildemeister, O; Gilewsky, V; Giangiobbe, V; Giokaris, N; Gomes, A; González, V; Grabskii, V; Grenier, P; Gris, P; Guarino, V; Guicheney, C; Sen-Gupta, A; Hakobyan, H; Haney, M; Henriques, A; Higón, E; Holmgren, S O; Hurwitz, M; Huston, J; Iglesias, C; And, K J; Junk, T; Karyukhin, A N; Khubua, J; Klereborn, J; Korolkov, I Ya; Krivkova, P; Kulchitskii, Yu A; Kurochkin, Yu; Kuzhir, P; Lambert, D; Le Compte, T; Lefèvre, R; Leitner, R; Lembesi, M; Li, J; Liablin, M; Lokajícek, M; Lomakin, Y; Amengual, J M L; Lupi, A; Maidantchik, C; Maio, A; Maliukov, S; Manousakis, A; Marques, C; Marroquim, F; Martin, F; Mazzoni, E; Montarou, G; Merritt, F S; Myagkov, A; Miller, R; Minashvili, I A; Miralles, L; Némécek, S; Nessi, M; Nodulman, L; Norniella, O; Onofre, A; Oreglia, M J; Pantea, D; Pallin, D; Pilcher, J E; Pina, J; Pinhão, J; Podlyski, F; Portell, X; Poveda, J; Price, L E; Pribyl, L; Proudfoot, J; Ramstedt, M; Reinmuth, G; Richards, R; Roda, C; Romanov, V; Rosnet, P; Roy, P; Rumiantsau, V; Russakovich, N; Salto, O; Salvachúa, B; Sanchis, E; Sanders, H; Santoni, C; Santos, J; Saraiva, J G; Sarri, F; Satsunkevich, I S; Says, L P; Schlager, G; Schlereth, J L; Seixas, J M; Selldén, B; Shevtsov, P; Shochet, M; Da Silva, P; Silva, J; Simaitis, V; Sissakian, A N; Solodkov, A; Solovyanov, O; Sosebee, M; Spanó, F; Stanek, R; Starchenko, E A; Starovoitov, P; Suk, M; Sykora, I; Tang, F; Tas, P; Teuscher, R; Tokar, S; Topilin, N; Torres, J; Tsulaia, V; Underwood, D; Usai, G; Valkár, S; Valls, J A; Vartapetian, A H; Vazeille, F; Vichou, I; Vinogradov, V; Vivarelli, I; Volpi, M; White, A; Zaitsev, A; Zenine, A; Zenis, T

2006-01-01

The Tile Calorimeter, which constitutes the central section of the ATLAS hadronic calorimeter, is a non-compensating sampling device made of iron and scintillating tiles. The construction phase of the calorimeter is nearly complete, and most of the effort now is directed toward the final assembly and commissioning in the underground experimental hall. The layout of the calorimeter and the tasks carried out during construction are described, first with a brief reminder of the requirements that drove the calorimeter design. During the last few years a comprehensive test-beam program has been followed in order to establish the calorimeter electromagnetic energy scale, to study its uniformity, and to compare real data to Monte Carlo simulation. The test-beam setup and first results from the data are described. During the test-beam period in 2004, lasting several months, data have been acquired with a complete slice of the central ATLAS calorimeter. The data collected in the test-beam are crucial in order to study...

Some Characteristics of Dust Particles in Atmosphere of Kemerovo City According to Pollution Data of Snow Cover

Science.gov (United States)

Golokhvast, K. S.; Manakov, Yu A.; Bykov, A. A.; Chayka, V. V.; Nikiforov, P. A.; Rogulin, R. S.; Romanova, T. Yu; Karabtsov, A. A.; Semenikhin, V. A.

2017-10-01

The given paper presents the study results of solid particles contained in snow samples, taken on 10 sites in Kemerovo city in spring 2013. The sites were chosen in such a way as to prevent particles flow into the snow cover in other ways, except with atmospheric precipitation. Kuzbass Botanical Garden was chosen as the check point. In 7 out of 10 sampling sites on the territory of Kemerovo city the presence of particles that are particularly dangerous for human health was found. In one of the areas the particles of 200-400 nm size and with a specific surface area of 14,813.34 cm2/cm3 were detected in ecologically significant quantity (8%).

Use of machine learning techniques for modeling of snow depth

Directory of Open Access Journals (Sweden)

G. V. Ayzel

2017-01-01

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

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 ATLAS Liquid Argon Electromagnetic Calorimeter Construction, commissioning and elected test beam results

CERN Document Server

Hervás, L

2004-01-01

The construction of the ATLAS Liquid Argon Electromagnetic Calorimeter has been completed and commissioning is in progress to prepare the cryostats for lowering into the ATLAS pit. After a brief description of the detector, its construction and readout electronics, this paper summarizes results of quality checks (electrical, connectivity) carried out during the integration of the calorimeter wheels into the cryostats. We present also selected results of its performance, such as linearity, energy resolution, timing resolution, uniformity of the energy response, obtained in beam tests with several series modules. 16 Refs.

Hydrologic response to and recovery from differing silvicultural systems in a deciduous forest landscape with seasonal snow cover

Science.gov (United States)

Buttle, J. M.; Beall, F. D.; Webster, K. L.; Hazlett, P. W.; Creed, I. F.; Semkin, R. G.; Jeffries, D. S.

2018-02-01

Hydrological consequences of alternative harvesting strategies in deciduous forest landscapes with seasonal snow cover have received relatively little attention. Most forest harvesting experiments in landscapes with seasonal snow cover have focused on clearcutting in coniferous forests. Few have examined alternative strategies such as selection or shelterwood cutting in deciduous stands whose hydrologic responses to harvesting may differ from those of conifers. This study presents results from a 31-year examination of hydrological response to and recovery from alternative harvesting strategies in a deciduous forest landscape with seasonal snow cover in central Ontario, Canada. A quantitative means of assessing hydrologic recovery to harvesting is also developed. Clearcutting resulted in increased water year (WY) runoff. This was accompanied by increased runoff in all seasons, with greatest relative increases in Summer. Direct runoff and baseflow from treatment catchments generally increased following harvesting, although annual peak streamflow did not. Largest increases in WY runoff and seasonal runoff as well as direct runoff and baseflow generally occurred in the selection harvest catchment, likely as a result of interception of hillslope runoff by a forest access road and redirection to the stream channel. Hydrologic recovery appeared to begin towards the end of the experimental period for several streamflow metrics but was incomplete for all harvesting strategies 15 years after harvesting. Geochemical tracing indicated that harvesting enhanced the relative importance of surface and near-surface water pathways on catchment slopes for all treatments, with the clearcut catchment showing the most pronounced and prolonged response. Such insights into water partitioning between flow pathways may assist assessments of the ecological and biogeochemical consequences of forest disturbance.

Influence of snowpack and melt energy heterogeneity on snow cover depletion and snowmelt runoff simulation in a cold mountain environment

Science.gov (United States)

DeBeer, Chris M.; Pomeroy, John W.

2017-10-01

The spatial heterogeneity of mountain snow cover and ablation is important in controlling patterns of snow cover depletion (SCD), meltwater production, and runoff, yet is not well-represented in most large-scale hydrological models and land surface schemes. Analyses were conducted in this study to examine the influence of various representations of snow cover and melt energy heterogeneity on both simulated SCD and stream discharge from a small alpine basin in the Canadian Rocky Mountains. Simulations were performed using the Cold Regions Hydrological Model (CRHM), where point-scale snowmelt computations were made using a snowpack energy balance formulation and applied to spatial frequency distributions of snow water equivalent (SWE) on individual slope-, aspect-, and landcover-based hydrological response units (HRUs) in the basin. Hydrological routines were added to represent the vertical and lateral transfers of water through the basin and channel system. From previous studies it is understood that the heterogeneity of late winter SWE is a primary control on patterns of SCD. The analyses here showed that spatial variation in applied melt energy, mainly due to differences in net radiation, has an important influence on SCD at multiple scales and basin discharge, and cannot be neglected without serious error in the prediction of these variables. A single basin SWE distribution using the basin-wide mean SWE (SWE ‾) and coefficient of variation (CV; standard deviation/mean) was found to represent the fine-scale spatial heterogeneity of SWE sufficiently well. Simulations that accounted for differences in (SWE ‾) among HRUs but neglected the sub-HRU heterogeneity of SWE were found to yield similar discharge results as simulations that included this heterogeneity, while SCD was poorly represented, even at the basin level. Finally, applying point-scale snowmelt computations based on a single SWE depth for each HRU (thereby neglecting spatial differences in internal

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

Data.gov (United States)

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

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.

Advances in snow cover distributed modelling via ensemble simulations and assimilation of satellite data

Science.gov (United States)

Revuelto, J.; Dumont, M.; Tuzet, F.; Vionnet, V.; Lafaysse, M.; Lecourt, G.; Vernay, M.; Morin, S.; Cosme, E.; Six, D.; Rabatel, A.

2017-12-01

Nowadays snowpack models show a good capability in simulating the evolution of snow in mountain areas. However singular deviations of meteorological forcing and shortcomings in the modelling of snow physical processes, when accumulated on time along a snow season, could produce large deviations from real snowpack state. The evaluation of these deviations is usually assessed with on-site observations from automatic weather stations. Nevertheless the location of these stations could strongly influence the results of these evaluations since local topography may have a marked influence on snowpack evolution. Despite the evaluation of snowpack models with automatic weather stations usually reveal good results, there exist a lack of large scale evaluations of simulations results on heterogeneous alpine terrain subjected to local topographic effects.This work firstly presents a complete evaluation of the detailed snowpack model Crocus over an extended mountain area, the Arve upper catchment (western European Alps). This catchment has a wide elevation range with a large area above 2000m a.s.l. and/or glaciated. The evaluation compares results obtained with distributed and semi-distributed simulations (the latter nowadays used on the operational forecasting). Daily observations of the snow covered area from MODIS satellite sensor, seasonal glacier surface mass balance evolution measured in more than 65 locations and the galciers annual equilibrium line altitude from Landsat/Spot/Aster satellites, have been used for model evaluation. Additionally the latest advances in producing ensemble snowpack simulations for assimilating satellite reflectance data over extended areas will be presented. These advances comprises the generation of an ensemble of downscaled high-resolution meteorological forcing from meso-scale meteorological models and the application of a particle filter scheme for assimilating satellite observations. Despite the results are prefatory, they show a good

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

Directory of Open Access Journals (Sweden)

N. S. Malygina

2017-01-01

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

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

The Airborne Snow Observatory: fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo

Science.gov (United States)

Snow cover and its melt dominate regional climate and water resources in many of the world’s mountainous regions. Snowmelt timing and magnitude in mountains tend to be controlled by absorption of solar radiation and snow water equivalent, respectively, and yet both of these are very poorly known ev...

Boreal and temperate snow cover variations induced by black carbon emissions in the middle of the 21st century

Directory of Open Access Journals (Sweden)

M. Ménégoz

2013-03-01

Full Text Available We used a coupled climate-chemistry model to quantify the impacts of aerosols on snow cover north of 30° N both for the present-day and for the middle of the 21st century. Black carbon (BC deposition over continents induces a reduction in the mean number of days with snow at the surface (MNDWS that ranges from 0 to 10 days over large areas of Eurasia and Northern America for the present-day relative to the pre-industrial period. This is mainly due to BC deposition during the spring, a period of the year when the remaining of snow accumulated during the winter is exposed to both strong solar radiation and a large amount of aerosol deposition induced themselves by a high level of transport of particles from polluted areas. North of 30° N, this deposition flux represents 222 Gg BC month−1 on average from April to June in our simulation. A large reduction in BC emissions is expected in the future in all of the Representative Concentration Pathway (RCP scenarios. In particular, considering the RCP8.5 in our simulation leads to a decrease in the spring BC deposition down to 110 Gg month−1 in the 2050s. However, despite the reduction of the aerosol impact on snow, the MNDWS is strongly reduced by 2050, with a decrease ranging from 10 to 100 days from present-day values over large parts of the Northern Hemisphere. This reduction is essentially due to temperature increase, which is quite strong in the RCP8.5 scenario in the absence of climate mitigation policies. Moreover, the projected sea-ice retreat in the next decades will open new routes for shipping in the Arctic. However, a large increase in shipping emissions in the Arctic by the mid-21st century does not lead to significant changes of BC deposition over snow-covered areas in our simulation. Therefore, the MNDWS is clearly not affected through snow darkening effects associated with these Arctic ship emissions. In an experiment without nudging toward atmospheric reanalyses, we simulated

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

Science.gov (United States)

Stehr, Alejandra; Aguayo, Mauricio

2017-10-01

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

Trace element distribution in the snow cover from an urban area in central Poland.

Science.gov (United States)

Siudek, Patrycja; Frankowski, Marcin; Siepak, Jerzy

2015-05-01

This work presents the first results from winter field campaigns focusing on trace metals and metalloid chemistry in the snow cover from an urbanized region in central Poland. Samples were collected between January and March 2013 and trace element concentrations were determined using GF-AAS. A large inter-seasonal variability depending on anthropogenic emission, depositional processes, and meteorological conditions was observed. The highest concentration (in μg L(-1)) was reported for Pb (34.90), followed by Ni (31.37), Zn (31.00), Cu (13.71), Cr (2.36), As (1.58), and Cd (0.25). In addition, several major anthropogenic sources were identified based on principal component analysis (PCA), among which the most significant was the activity of industry and coal combustion for residential heating. It was stated that elevated concentrations of some trace metals in snow samples were associated with frequent occurrence of south and southeast advection of highly polluted air masses toward the sampling site, suggesting a large impact of regional urban/industrial pollution plumes.

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

SWANN: The Snow Water Artificial Neural Network Modelling System

Science.gov (United States)

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

2017-12-01

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

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

Canadian snow and sea ice: historical trends and projections

Science.gov (United States)

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

2018-04-01

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

Winter survival of Scots pine seedlings under different snow conditions.

Science.gov (United States)

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

2018-04-01

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

Design and Construction of Large Size Micromegas Chambers for the Upgrade of the ATLAS Muon Spectrometer

CERN Document Server

Lösel, Philipp; Müller, Ralph

2015-01-01

Large area Micromegas detectors will be employed for the first time in high-energy physics experiments. A total surface of about $\\mathbf{150~m^2}$ of the forward regions of the Muon Spectrometer of the ATLAS detector at LHC will be equipped with 8-layer Micromegas modules. Each layer covers more than $\\mathbf{2~m^2}$ for a total active area of $\\mathbf{1200~m^2}$. Together with the small strip Thin Gap Chambers they will compose the two New Small Wheels, which will replace the innermost stations of the ATLAS endcap muon tracking system in the 2018/19 shutdown. In order to achieve a 15$\\mathbf{\\%}$ transverse momentum resolution for $\\mathbf{1~TeV}$ muons, in addition to an excellent intrinsic resolution, the mechanical precision of each plane of the assembled module must be as good as $\\mathbf{30~\\mu m}$ along the precision coordinate and $\\mathbf{80~\\mu m}$ perpendicular to the chamber. The design and construction procedure of the Micromegas modules will be presented, as well as the design for the assembly ...

Impact of climate change in Switzerland on socioeconomic snow indices

Science.gov (United States)

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

2017-02-01

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

Using hacked point and shoot cameras for time-lapse snow cover monitoring in an Alpine valley

Science.gov (United States)

Weijs, S. V.; Diebold, M.; Mutzner, R.; Golay, J. R.; Parlange, M. B.

2012-04-01

In Alpine environments, monitoring snow cover is essential get insight in the hydrological processes and water balance. Although measurement techniques based on LIDAR are available, their cost is often a restricting factor. In this research, an experiment was done using a distributed array of cheap consumer cameras to get insight in the spatio-temporal evolution of snowpack. Two experiments are planned. The first involves the measurement of eolic snow transport around a hill, to validate a snow saltation model. The second monitors the snowmelt during the melting season, which can then be combined with data from a wireless network of meteorological stations and discharge measurements at the outlet of the catchment. The poster describes the hardware and software setup, based on an external timer circuit and CHDK, the Canon Hack Development Kit. This latter is a flexible and developing software package, released under a GPL license. It was developed by hackers that reverse engineered the firmware of the camera and added extra functionality such as raw image output, more full control of the camera, external trigger and motion detection, and scripting. These features make it a great tool for geosciences. Possible other applications involve aerial stereo photography, monitoring vegetation response. We are interested in sharing experiences and brainstorming about new applications. Bring your camera!

Snow deposition and melt under different vegetative covers in central New York

Science.gov (United States)

A. R. Eschner; D. R. Satterlund

1963-01-01

Two-thirds of the annual runoff from watersheds in the Allegheny Plateau of central New York comes from the snow-or snow and rain that falls in December through April. Although the amounts of precipitation in this period are fairly uniform from year to year, the proportion that falls as snow varies; so does the amount that accumulates on the ground, and its duration...

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.

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

High Resolution Urban Land Cover Mapping Using NAIP Aerial Photography and Image Processing for the USEPA National Atlas of Sustainability and Ecosystem Services

Science.gov (United States)

Pilant, A. N.; Baynes, J.; Dannenberg, M.

2012-12-01

The US EPA National Atlas for Sustainability is a web-based, easy-to-use, mapping application that allows users to view and analyze multiple ecosystem services in a specific region. The Atlas provides users with a visual method for interpreting ecosystem services and understanding how they can be conserved and enhanced for a sustainable future. The Urban Atlas component of the National Atlas will provide fine-scale information linking human health and well-being to environmental conditions such as urban heat islands, near-road pollution, resource use, access to recreation, drinking water quality and other quality of life indicators. The National Land Cover Data (NLCD) derived from 30 m scale 2006 Landsat imagery provides the land cover base for the Atlas. However, urban features and phenomena occur at finer spatial scales, so higher spatial resolution and more current LC maps are required. We used 4 band USDA NAIP imagery (1 m pixel size) and various classification approaches to produce urban land cover maps with these classes: impervious surface, grass and herbaceous, trees and forest, soil and barren, and water. Here we present the remote sensing methods used and results from four pilot cities in this effort, highlighting the pros and cons of the approach, and the benefits to sustainability and ecosystem services analysis. Example of high resolution land cover map derived from USDA NAIP aerial photo. Compare 30 m and 1 m resolution land cover maps of downtown Durham, NC.

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

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

[Litter decomposition and soil faunal diversity of two understory plant debris in the alpine timberline ecotone of western Sichuan in a snow cover season].

Science.gov (United States)

He, Run-lian; Chen, Ya-mei; Deng, Chang-chun; Yan, Wan-qin; Zhang, Jian; Liu, Yang

2015-03-01

In order to understand the relationship between litter decomposition and soil fauna diversity during snow cover season, litterbags with plant debris of Actinothuidium hookeri, Cystopteris montana, two representative understory plants in the alpine timberline ecotone, and their mixed litter were incubated in the dark coniferous forest, timberline and alpine meadow, respectively. After a snow cover season, the mass loss and soil fauna in litterbags were investigated. After decomposition with a snow cover season, alpine meadow showed the highest mass loss of plant debris in comparison with coniferous forest and timberline, and the mass loss of A. hookeri was more significant. The mixture of two plants debris accelerated the mass loss, especially in the timberline. A total of 968 soil invertebrates, which belonged to 5 classes, 10 orders and 35 families, were captured in litterbags. Acarina and Collembola were the dominant groups in plant debris. The numbers of individuals and groups of soil faunal communities in litter of timberline were higher than those of alpine meadow and dark coniferous forest. Canonical correspondence analysis (CCA) indicated that the groups of soil animals were related closely with the average temperature, and endemic species such as Isoptera and Geophilomorpha were observed only in coniferous forest, while Hemiptera and Psocoptera only in.the alpine meadow. The diversity of soil faunal community was more affected by plant debris varieties in the timberline than in the coniferous forest and alpine meadow. Multiple regression analysis indicated that the average temperature and snow depth explained 30.8% of the variation of litter mass loss rate, soil animals explained 8.3%, and altogether explained 34.1%. Snow was one of the most critical factors impacting the decomposition of A. hookeri and C. montana debris in the alpine timberline ecotone.

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.

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.

Distributed snow modeling suitable for use with operational data for the American River watershed.

Science.gov (United States)

Shamir, E.; Georgakakos, K. P.

2004-12-01

The mountainous terrain of the American River watershed (~4300 km2) at the Western slope of the Northern Sierra Nevada is subject to significant variability in the atmospheric forcing that controls the snow accumulation and ablations processes (i.e., precipitation, surface temperature, and radiation). For a hydrologic model that attempts to predict both short- and long-term streamflow discharges, a plausible description of the seasonal and intermittent winter snow pack accumulation and ablation is crucial. At present the NWS-CNRFC operational snow model is implemented in a semi distributed manner (modeling unit of about 100-1000 km2) and therefore lump distinct spatial variability of snow processes. In this study we attempt to account for the precipitation, temperature, and radiation spatial variability by constructing a distributed snow accumulation and melting model suitable for use with commonly available sparse data. An adaptation of the NWS-Snow17 energy and mass balance that is used operationally at the NWS River Forecast Centers is implemented at 1 km2 grid cells with distributed input and model parameters. The input to the model (i.e., precipitation and surface temperature) is interpolated from observed point data. The surface temperature was interpolated over the basin based on adiabatic lapse rates using topographic information whereas the precipitation was interpolated based on maps of climatic mean annual rainfall distribution acquired from PRISM. The model parameters that control the melting rate due to radiation were interpolated based on aspect. The study was conducted for the entire American basin for the snow seasons of 1999-2000. Validation of the Snow Water Equivalent (SWE) prediction is done by comparing to observation from 12 snow Sensors. The Snow Cover Area (SCA) prediction was evaluated by comparing to remotely sensed 500m daily snow cover derived from MODIS. The results that the distribution of snow over the area is well captured and the

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

Science.gov (United States)

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

2010-01-01

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS-derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant end toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The

Modeling of surface dust concentration in snow cover at industrial area using neural networks and kriging

Science.gov (United States)

Sergeev, A. P.; Tarasov, D. A.; Buevich, A. G.; Shichkin, A. V.; Tyagunov, A. G.; Medvedev, A. N.

2017-06-01

Modeling of spatial distribution of pollutants in the urbanized territories is difficult, especially if there are multiple emission sources. When monitoring such territories, it is often impossible to arrange the necessary detailed sampling. Because of this, the usual methods of analysis and forecasting based on geostatistics are often less effective. Approaches based on artificial neural networks (ANNs) demonstrate the best results under these circumstances. This study compares two models based on ANNs, which are multilayer perceptron (MLP) and generalized regression neural networks (GRNNs) with the base geostatistical method - kriging. Models of the spatial dust distribution in the snow cover around the existing copper quarry and in the area of emissions of a nickel factory were created. To assess the effectiveness of the models three indices were used: the mean absolute error (MAE), the root-mean-square error (RMSE), and the relative root-mean-square error (RRMSE). Taking into account all indices the model of GRNN proved to be the most accurate which included coordinates of the sampling points and the distance to the likely emission source as input parameters for the modeling. Maps of spatial dust distribution in the snow cover were created in the study area. It has been shown that the models based on ANNs were more accurate than the kriging, particularly in the context of a limited data set.

Non-linear Feedbacks Between Forest Mortality and Climate Change: Implications for Snow Cover, Water Resources, and Ecosystem Recovery in Western North America (Invited)

Science.gov (United States)

Brooks, P. D.; Harpold, A. A.; Biederman, J. A.; Gochis, D. J.; Litvak, M. E.; Ewers, B. E.; Broxton, P. D.; Reed, D. E.

2013-12-01

Unprecedented levels of tree mortality from insect infestation and wildfire are dramatically altering forest structure and composition in Western North America. Warming temperatures and increased drought stress have been implicated as major factors in the increasing spatial extent and frequency of these forest disturbances, but it is unclear how these changes in forest structure will interact with ongoing climate change to affect snowmelt water resources either for society or for ecosystem recovery following mortality. Because surface discharge, groundwater recharge, and ecosystem productivity all depend on seasonal snowmelt, a critical knowledge gap exists not only in predicting discharge, but in quantifying spatial and temporal variability in the partitioning of snowfall into abiotic vapor loss, plant available water, recharge, and streamflow within the complex mosaic of forest disturbance and topography that characterizes western mountain catchments. This presentation will address this knowledge gap by synthesizing recent work on snowpack dynamics and ecosystem productivity from seasonally snow-covered forests along a climate gradient from Arizona to Wyoming; including undisturbed sites, recently burned forests, and areas of extensive insect-induced forest mortality. Both before-after and control-impacted studies of forest disturbance on snow accumulation and ablation suggest that the spatial scale of snow distribution increases following disturbance, but net snow water input in a warming climate will increase only in topographically sheltered areas. While forest disturbance changes spatial scale of snowpack partitioning, the amount and especially the timing of snow cover accumulation and ablation are strongly related to interannual variability in ecosystem productivity with both earlier snowmelt and later snow accumulation associated with decreased carbon uptake. Empirical analyses and modeling are being developed to identify landscapes most sensitive to

Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression.

Science.gov (United States)

Serag, Ahmed; Aljabar, Paul; Ball, Gareth; Counsell, Serena J; Boardman, James P; Rutherford, Mary A; Edwards, A David; Hajnal, Joseph V; Rueckert, Daniel

2012-02-01

Medical imaging has shown that, during early development, the brain undergoes more changes in size, shape and appearance than at any other time in life. A better understanding of brain development requires a spatio-temporal atlas that characterizes the dynamic changes during this period. In this paper we present an approach for constructing a 4D atlas of the developing brain, between 28 and 44 weeks post-menstrual age at time of scan, using T1 and T2 weighted MR images from 204 premature neonates. The method used for the creation of the average 4D atlas utilizes non-rigid registration between all pairs of images to eliminate bias in the atlas toward any of the original images. In addition, kernel regression is used to produce age-dependent anatomical templates. A novelty in our approach is the use of a time-varying kernel width, to overcome the variations in the distribution of subjects at different ages. This leads to an atlas that retains a consistent level of detail at every time-point. Comparisons between the resulting atlas and atlases constructed using affine and non-rigid registration are presented. The resulting 4D atlas has greater anatomic definition than currently available 4D atlases created using various affine and non-rigid registration approaches, an important factor in improving registrations between the atlas and individual subjects. Also, the resulting 4D atlas can serve as a good representative of the population of interest as it reflects both global and local changes. The atlas is publicly available at www.brain-development.org. Copyright © 2011 Elsevier Inc. All rights reserved.

Meter-scale Urban Land Cover Mapping for EPA EnviroAtlas Using Machine Learning and OBIA Remote Sensing Techniques

Science.gov (United States)

Pilant, A. N.; Baynes, J.; Dannenberg, M.; Riegel, J.; Rudder, C.; Endres, K.

2013-12-01

US EPA EnviroAtlas is an online collection of tools and resources that provides geospatial data, maps, research, and analysis on the relationships between nature, people, health, and the economy (http://www.epa.gov/research/enviroatlas/index.htm). Using EnviroAtlas, you can see and explore information related to the benefits (e.g., ecosystem services) that humans receive from nature, including clean air, clean and plentiful water, natural hazard mitigation, biodiversity conservation, food, fuel, and materials, recreational opportunities, and cultural and aesthetic value. EPA developed several urban land cover maps at very high spatial resolution (one-meter pixel size) for a portion of EnviroAtlas devoted to urban studies. This urban mapping effort supported analysis of relations among land cover, human health and demographics at the US Census Block Group level. Supervised classification of 2010 USDA NAIP (National Agricultural Imagery Program) digital aerial photos produced eight-class land cover maps for several cities, including Durham, NC, Portland, ME, Tampa, FL, New Bedford, MA, Pittsburgh, PA, Portland, OR, and Milwaukee, WI. Semi-automated feature extraction methods were used to classify the NAIP imagery: genetic algorithms/machine learning, random forest, and object-based image analysis (OBIA). In this presentation we describe the image processing and fuzzy accuracy assessment methods used, and report on some sustainability and ecosystem service metrics computed using this land cover as input (e.g., carbon sequestration from USFS iTREE model; health and demographics in relation to road buffer forest width). We also discuss the land cover classification schema (a modified Anderson Level 1 after the National Land Cover Data (NLCD)), and offer some observations on lessons learned. Meter-scale urban land cover in Portland, OR overlaid on NAIP aerial photo. Streets, buildings and individual trees are identifiable.

Monitoring of carbon isotope composition of snow cover for Tomsk region

Science.gov (United States)

Akulov, P. A.; Volkov, Y. V.; Kalashnikova, D. A.; Markelova, A. N.; Melkov, V. N.; Simonova, G. V.; Tartakovskiy, V. A.

2016-11-01

This article shows the potential of using δ13C values of pollutants in snow pack to study the human impact on the environment of Tomsk and its surroundings. We believe that it is possible to use a relation between the isotope compositions of a fuel and black carbon for establishing the origin of the latter. The main object of our investigation was dust accumulated by the snow pack in the winter of 2015-2016. The study of dust samples included the following steps: determination of the total carbon content in snow pack samples of Tomsk and its surroundings, extraction of black carbon from the dust, as well as the determination of δ13C values of the total and black carbon accumulated in the snow pack. A snow survey was carried out on the 26th of January and on the 18th of March. The relative carbon content in the dust samples was determined by using an EA Flash 2000 element analyzer. It varied from 3 to 24%. The maximum carbon content was in the dust samples from areas of cottage building with individual heating systems. The δ13C values of the total and black carbon were determined by using a DELTA V Advantage isotope mass spectrometer (TomTsKP SB RAS). The isotope composition of black carbon corresponded to that of the original fuel. This fact allowed identifying the origin of black carbon in some areas of Tomsk.

Water and life from snow: A trillion dollar science question

Science.gov (United States)

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

2017-05-01

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

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

Science.gov (United States)

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

2017-12-01

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

ATLAS pixel IBL modules construction experience and developments for future upgrade

Energy Technology Data Exchange (ETDEWEB)

Gaudiello, A.

2015-10-01

The first upgrade of the ATLAS Pixel Detector is the Insertable B-Layer (IBL), installed in May 2014 in the core of ATLAS. Two different silicon sensor technologies, planar n-in-n and 3D, are used. Sensors are connected with the new generation 130 nm IBM CMOS FE-I4 read-out chip via solder bump-bonds. Production quality control tests were set up to verify and rate the performance of the modules before integration into staves. An overview of module design and construction, the quality control results and production yield will be discussed, as well as future developments foreseen for future detector upgrades.

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

Directory of Open Access Journals (Sweden)

M. Darvishi

2013-09-01

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

ATLAS endcap liquid argon calorimeters. Description and construction of the cryostats

Energy Technology Data Exchange (ETDEWEB)

Mace, Guy; Prat, Serge; Veillet, Jean-Jacques [Laboratoire de l' Accelerateur Lineaire IN2P3-CNRS et Universite de Paris-Sud 11, BP 34, F-91898 Orsay Cedex (France)

2006-05-15

All forward calorimeters of the ATLAS detector use the same detection technique, energy loss in passive plates, followed by ionisation and charge detection in liquid argon. They are therefore all grouped in the same vessel which must basically support and keep in place the heavy plates and the detection electrodes and maintain liquid argon at cold and stable temperature. Taking into account all the constraints as detailed below, and the overall detector size, 5 meter diameter by 3 meter length this was quite a challenge. The design, construction and tests of these two cryostats, up to their delivery at CERN, are described in this document. These two cryostats are a joint 'in kind' contribution to the Atlas experiment of LAL (Orsay), Max Planck Institute (Muenchen) and Wuppertal University (Wuppertal) and have been designed and built under the responsibility of LAL (Orsay) with contributions of the technical groups of the above institutions and of ATLAS-CERN. (authors)

ATLAS endcap liquid argon calorimeters. Description and construction of the cryostats

International Nuclear Information System (INIS)

Mace, Guy; Prat, Serge; Veillet, Jean-Jacques

2006-05-01

All forward calorimeters of the ATLAS detector use the same detection technique, energy loss in passive plates, followed by ionisation and charge detection in liquid argon. They are therefore all grouped in the same vessel which must basically support and keep in place the heavy plates and the detection electrodes and maintain liquid argon at cold and stable temperature. Taking into account all the constraints as detailed below, and the overall detector size, 5 meter diameter by 3 meter length this was quite a challenge. The design, construction and tests of these two cryostats, up to their delivery at CERN, are described in this document. These two cryostats are a joint 'in kind' contribution to the Atlas experiment of LAL (Orsay), Max Planck Institute (Muenchen) and Wuppertal University (Wuppertal) and have been designed and built under the responsibility of LAL (Orsay) with contributions of the technical groups of the above institutions and of ATLAS-CERN. (authors)

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.

Variability in snow depth time series in the Adige catchment

Directory of Open Access Journals (Sweden)

Giorgia Marcolini

2017-10-01

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

Facilitating the exploitation of ERTS-1 imagery utilizing snow enhancement techniques

Science.gov (United States)

Wobber, F. J. (Principal Investigator); Martin, K. R.; Amato, R. V.

1973-01-01

The author has identified the following significant results. Snow cover in combination with low angle solar illumination has been found to provide increased tonal contrast of surface feature and is useful in the detection of bedrock fractures. Identical fracture systems were not as readily detectable in the fall due to the lack of a contrasting surface medium (snow) and a relatively high sun angle. Low angle solar illumination emphasizes topographic expressions not as apparent on imagery acquired with a higher sun angle. A strong correlation exists between the major fracture-lineament directions interpreted from multi-sensor imagery (including snow-free and snow cover ERTS) and the strike of bedrock joints recorded in the field indicating the structural origin of interpreted fracture-lineaments. A fracture-annotated ERTS-1 photo base map (1:250,000 scale) is being prepared for western Massachusetts. The map will document the utilization of ERTS-1 imagery for geological analysis in comparative snow-free and snow-covered terrain.

Construction of the new silicon microstrips tracker for the Phase-II ATLAS detector

CERN Document Server

Liang, Zhijun; The ATLAS collaboration

2018-01-01

The inner detector of the present ATLAS detector has been designed and developed to function in the environment of the present Large Hadron Collider (LHC). At the next-generation tracking detector proposed for the High Luminosity LHC (HL-LHC), the so-called ATLAS Phase-II Upgrade, the particle densities and radiation levels will be higher by as much as a factor of ten. The new detectors must be faster, they need to be more highly segmented, and covering more area. They also need to be more resistant to radiation, and they require much greater power delivery to the front-end systems. For those reasons, the inner tracker of the ATLAS detector must be redesigned and rebuilt completely. The design of the ATLAS Upgrade inner tracker (ITk) has already been defined. It consists of several layers of silicon particle detectors. The innermost layers will be composed of silicon pixel sensors, and the outer layers will consist of silicon microstrip sensors. This paper will focus on the latest research and development act...

Moving sidewalk for snow board gelande; Snow board gerendemuke ugoku hodo

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-04-20

This is a moving sidewalk installed on the indoor type artificial snow board gelande at Shigenobu-cho, Ehime prefecture, constructed for the first time in Shikoku. It carries snow boarders in gelande. The main specifications are as follows. Type: 800 type. Sidewalk width: 600mm. Length: 76.0m. Speed: 30m/min. Inclination angle: 13 degrees (inclination type). The features are as follows. (1) The tread is rubber-belt made and skid-resistant if it gets wet. (2) It is equipped with the each-part antifreezer, considering the snow quality and the environment where it is used at low temperature. (translated by NEDO)

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

International Nuclear Information System (INIS)

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

2013-01-01

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

29 CFR 776.27 - Construction which is related to covered production.

Science.gov (United States)

2010-07-01

... Construction Industry Individual Employee Coverage in the Construction Industry § 776.27 Construction which is... Construction work performed upon the plant and facilities of such a utility is covered as in the case of any... 29 Labor 3 2010-07-01 2010-07-01 false Construction which is related to covered production. 776.27...

EnviroAtlas - Paterson, NJ - 51m Riparian Buffer Forest Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is forested. There is a potential for decreased water quality in areas where the riparian buffer is less forested. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. EnviroAtlas defines tree buffer for this community as only trees and forest. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Analysis of the Lake Superior Watershed Seasonal Snow Cover

National Research Council Canada - National Science Library

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

2007-01-01

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

ATLAS Forward Proton (AFP) time-of-flight (ToF) detector: construction & existing experiences

CERN Document Server

Sykora, Tomas; The ATLAS collaboration

2018-01-01

In 2017 the ATLAS collaboration successfully completed the installation of the ATLAS Forward Proton (AFP) detector to measure diffractive protons leaving under very small angles (hundreds of micro radians) the ATLAS proton-proton interaction point. The AFP tags and measures forward protons scattered in single diffraction or hard central diffraction, where two protons are emitted and a central system is created. In addition, the AFP has a potential to measure two-photon exchange processes, and to be sensitive to eventual anomalous quartic couplings of Vector Bosons: γγW+W−, γγZZ, and γγγγ. Such measurements at high luminosities will be possible only due the combination of high resolution tracking (semi-edgeless 3D Silicon pixel) detectors and ultra-high precision ToF (Quartz-Cherenkov) detectors at both sides of the ATLAS detector. The ToF detector construction and experiences with its operation represent the subject of the talk.

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

Science.gov (United States)

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

2012-04-01

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

EnviroAtlas 15m Riparian Buffer Forest Cover Web Service

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). This EnviroAtlas dataset...

EnviroAtlas 51m Riparian Buffer Vegetated Cover Web Service

Data.gov (United States)

U.S. Environmental Protection Agency — This EnviroAtlas web service supports research and online mapping activities related to EnviroAtlas (https://www.epa.gov/enviroatlas). This EnviroAtlas dataset...

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

Directory of Open Access Journals (Sweden)

L. M. Kitaev

2013-01-01

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

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