WorldWideScience

Sample records for hemisphere snow cover

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

    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...

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

    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...

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

    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...

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

    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

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

    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.

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

    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

  7. The value of snow cover

    Sokratov, S. A.

    2009-04-01

    only and not even the main outcome from snow cover use. The value of snow cover for agriculture, water resources, industry and transportation is so naturally inside the activities that is not often quantified. However, any considerations of adaptation strategies for climate change with changing snow conditions need such quantification.

  8. Global warming: Sea ice and snow cover

    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

  9. [Snow cover pollution monitoring in Ufa].

    Daukaev, R A; Suleĭmanov, R A

    2008-01-01

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

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

    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

  11. Observational evidence of changes in global snow and ice cover

    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

  12. The seasonal cycle of snow cover, sea ice and surface albedo

    Robock, A.

    1980-01-01

    The paper examines satellite data used to construct mean snow cover caps for the Northern Hemisphere. The zonally averaged snow cover from these maps is used to calculate the seasonal cycle of zonally averaged surface albedo. The effects of meltwater on the surface, solar zenith angle, and cloudiness are parameterized and included in the calculations of snow and ice albedo. The data allows a calculation of surface albedo for any land or ocean 10 deg latitude band as a function of surface temperature ice and snow cover; the correct determination of the ice boundary is more important than the snow boundary for accurately simulating the ice and snow albedo feedback.

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

    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,.

  14. Central Asian Snow Cover from Hydrometeorological Surveys

    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...

  15. IMS Daily Northern Hemisphere Snow and Ice Analysis at 1 km, 4 km, and 24 km Resolutions

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set provides snow and ice cover maps for the Northern Hemisphere from February 1997 to the present from the National Ice Center's Interactive Multisensor...

  16. Estimating Snow Cover from Publicly Available Images

    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...

  17. Is Eurasian October snow cover extent increasing?

    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)

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

    Yunlong Wang

    2018-01-01

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

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

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

    2003-04-01

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

  20. Correlated declines in Pacific arctic snow and sea ice cover

    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

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

    Riggs, George A.; Hall, Dorothy K.

    2010-01-01

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

  2. MODIS Snow Cover Recovery Using Variational Interpolation

    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.

  3. Deriving Snow Cover Metrics for Alaska from MODIS

    Chuck Lindsay

    2015-09-01

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

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

    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.

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

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

    2017-01-01

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

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

    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.

  7. Monitoring Areal Snow Cover Using NASA Satellite Imagery

    Harshburger, Brian J.; Blandford, Troy; Moore, Brandon

    2011-01-01

    The objective of this project is to develop products and tools to assist in the hydrologic modeling process, including tools to help prepare inputs for hydrologic models and improved methods for the visualization of streamflow forecasts. In addition, this project will facilitate the use of NASA satellite imagery (primarily snow cover imagery) by other federal and state agencies with operational streamflow forecasting responsibilities. A GIS software toolkit for monitoring areal snow cover extent and producing streamflow forecasts is being developed. This toolkit will be packaged as multiple extensions for ArcGIS 9.x and an opensource GIS software package. The toolkit will provide users with a means for ingesting NASA EOS satellite imagery (snow cover analysis), preparing hydrologic model inputs, and visualizing streamflow forecasts. Primary products include a software tool for predicting the presence of snow under clouds in satellite images; a software tool for producing gridded temperature and precipitation forecasts; and a suite of tools for visualizing hydrologic model forecasting results. The toolkit will be an expert system designed for operational users that need to generate accurate streamflow forecasts in a timely manner. The Remote Sensing of Snow Cover Toolbar will ingest snow cover imagery from multiple sources, including the MODIS Operational Snowcover Data and convert them to gridded datasets that can be readily used. Statistical techniques will then be applied to the gridded snow cover data to predict the presence of snow under cloud cover. The toolbar has the ability to ingest both binary and fractional snow cover data. Binary mapping techniques use a set of thresholds to determine whether a pixel contains snow or no snow. Fractional mapping techniques provide information regarding the percentage of each pixel that is covered with snow. After the imagery has been ingested, physiographic data is attached to each cell in the snow cover image. This data

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

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

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

    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...

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

    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.

  11. Snow cover distribution over elevation zones in a mountainous catchment

    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.

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

    E. E. Stigter

    2017-07-01

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

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

    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.

  14. Snow cover and temperature relationships in North America and Eurasia

    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.

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

    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

  16. Brilliant Colours from a White Snow Cover

    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…

  17. Validation of MODIS snow cover images over Austria

    J. Parajka

    2006-01-01

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

  18. On the impact of snow cover on daytime pollution dispersion

    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.

  19. Effect of snow cover on soil frost penetration

    Rožnovský, Jaroslav; Brzezina, Jáchym

    2017-12-01

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

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

    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

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

    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

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

    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.

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

    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.

  4. Dynamics of actual aggregation of petroleum products in snow cover

    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.

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

    R. Mott

    2010-12-01

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

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

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

    2015-05-01

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

  7. UAS applications in high alpine, snow-covered terrain

    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

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

    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,.

  9. Springtime warming and reduced snow cover from carbonaceous particles

    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

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

    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.

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

    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.

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

    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.

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

    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.

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

    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

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

    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 ...

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

    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)

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

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

    2017-12-01

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

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

    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.

  19. Variability in snow cover phenology in China from 1952 to 2010

    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 ...

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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

  6. Western Italian Alps Monthly Snowfall and Snow Cover Duration

    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...

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

    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.

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

    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

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

    Yu Lu

    2010-03-01

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

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

    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.

  11. Variability in snow cover phenology in China from 1952 to 2010

    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....

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

    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...

  13. Multitemporal Snow Cover Mapping in Mountainous Terrain for Landsat Climate Data Record Development

    Crawford, Christopher J.; Manson, Steven M.; Bauer, Marvin E.; Hall, Dorothy K.

    2013-01-01

    A multitemporal method to map snow cover in mountainous terrain is proposed to guide Landsat climate data record (CDR) development. The Landsat image archive including MSS, TM, and ETM+ imagery was used to construct a prototype Landsat snow cover CDR for the interior northwestern United States. Landsat snow cover CDRs are designed to capture snow-covered area (SCA) variability at discrete bi-monthly intervals that correspond to ground-based snow telemetry (SNOTEL) snow-water-equivalent (SWE) measurements. The June 1 bi-monthly interval was selected for initial CDR development, and was based on peak snowmelt timing for this mountainous region. Fifty-four Landsat images from 1975 to 2011 were preprocessed that included image registration, top-of-the-atmosphere (TOA) reflectance conversion, cloud and shadow masking, and topographic normalization. Snow covered pixels were retrieved using the normalized difference snow index (NDSI) and unsupervised classification, and pixels having greater (less) than 50% snow cover were classified presence (absence). A normalized SCA equation was derived to independently estimate SCA given missing image coverage and cloud-shadow contamination. Relative frequency maps of missing pixels were assembled to assess whether systematic biases were embedded within this Landsat CDR. Our results suggest that it is possible to confidently estimate historical bi-monthly SCA from partially cloudy Landsat images. This multitemporal method is intended to guide Landsat CDR development for freshwaterscarce regions of the western US to monitor climate-driven changes in mountain snowpack extent.

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

    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...

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

    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.

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

    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

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

    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

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

    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.

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

    Kyeong-Sang Lee

    2017-01-01

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

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

    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.

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

    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.

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

    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

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

    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.

  4. Analysis of the Lake Superior Watershed Seasonal Snow Cover

    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...

  5. Snow cover dynamics and water balance in complex high alpine terrain

    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

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

    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.

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

    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.

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

    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

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

    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)

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

    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.

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

    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

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

    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

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

    Théo Masson

    2018-04-01

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

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

    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.

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

    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

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

    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

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

    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.

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

    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

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

    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.

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

    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.

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

    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

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

    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...

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

    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

  4. Brief communication "Application of mobile laser scanning in snow cover profiling"

    S. Kaasalainen

    2011-03-01

    Full Text Available We present a snowmobile-based mobile mapping system and its first application to snow cover roughness and change detection measurement. The ROAMER mobile mapping system, constructed at the Finnish Geodetic Institute, consists of the positioning and navigating systems, a terrestrial laser scanner, and the carrying platform (a snowmobile sledge in this application. We demonstrate the applicability of the instrument to snow cover roughness profiling and change detection by presenting preliminary results from a mobile laser scanning (MLS campaign. The results show the potential of MLS for fast and efficient snow profiling from large areas in a millimetre scale.

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

    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.

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

    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...

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

    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.

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

    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.

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

    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.

  10. 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.

    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

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

    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.

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

    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

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

    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.

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

    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.

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

    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

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

    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

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

    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.

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

    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.

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

    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...

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

    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

  1. A Distributed Snow Evolution Modeling System (SnowModel)

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

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

    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.

  8. Combining MOD10A1 and MYD10A1 Images For Snow Cover Area Monitoring

    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.

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

    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

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

    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

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

    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.

  12. Investigation of snow cover dust pollution by contact and satellite observations

    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.

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

    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

  14. Proposed hybrid-classifier ensemble algorithm to map snow cover area

    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.

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

    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

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

    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

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

    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.

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

    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.

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

    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.

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

    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,...

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

    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,

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

    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. 

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

    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.

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

    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...

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

    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...

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

    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.

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

    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.

  8. Variability in snow cover phenology in China from 1952 to 2010

    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.

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

    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.

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

    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.

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

    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.

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

    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

  13. Carbon dioxide evolution from snow-covered agricultural ecosystems in Finland

    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.

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

    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

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

    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

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

    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

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

    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.

  18. Subpixel Snow Cover Mapping from MODIS Data by Nonparametric Regression Splines

    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

  19. Retrieving the characteristics of slab ice covering snow by remote sensing

    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.

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

    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.

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

    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

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

    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

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

    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

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

    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

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

    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.

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

    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.

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

    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.

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

    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

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

    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...

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

    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...

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

    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

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

    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

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

    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)

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

    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

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

    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

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

    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.

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

    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

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

    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.

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

    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.

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

    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.

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

    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.

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

    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

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

    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

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

    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

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

    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.

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

    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

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

    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.

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

    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.

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

    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

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

    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

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

    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)

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

    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.

  13. The impact of the snow cover on sea-ice thickness products retrieved by Ku-band radar altimeters

    Ricker, R.; Hendricks, S.; Helm, V.; Perovich, D. K.

    2015-12-01

    Snow on sea ice is a relevant polar climate parameter related to ocean-atmospheric interactions and surface albedo. It also remains an important factor for sea-ice thickness products retrieved from Ku-band satellite radar altimeters like Envisat or CryoSat-2, which is currently on its mission and the subject of many recent studies. Such satellites sense the height of the sea-ice surface above the sea level, which is called sea-ice freeboard. By assuming hydrostatic equilibrium and that the main scattering horizon is given by the snow-ice interface, the freeboard can be transformed into sea-ice thickness. Therefore, information about the snow load on hemispherical scale is crucial. Due to the lack of sufficient satellite products, only climatological values are used in current studies. Since such values do not represent the high variability of snow distribution in the Arctic, they can be a substantial contributor to the total sea-ice thickness uncertainty budget. Secondly, recent studies suggest that the snow layer cannot be considered as homogenous, but possibly rather featuring a complex stratigraphy due to wind compaction and/or ice lenses. Therefore, the Ku-band radar signal can be scattered at internal layers, causing a shift of the main scattering horizon towards the snow surface. This alters the freeboard and thickness retrieval as the assumption that the main scattering horizon is given by the snow-ice interface is no longer valid and introduces a bias. Here, we present estimates for the impact of snow depth uncertainties and snow properties on CryoSat-2 sea-ice thickness retrievals. We therefore compare CryoSat-2 freeboard measurements with field data from ice mass-balance buoys and aircraft campaigns from the CryoSat Validation Experiment. This unique validation dataset includes airborne laser scanner and radar altimeter measurements in spring coincident to CryoSat-2 overflights, and allows us to evaluate how the main scattering horizon is altered by the

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

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

    2012-10-15

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

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

    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.

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

    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

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

    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)

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

    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.

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

    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.

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

    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.

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

    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

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

    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...

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

    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.

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

    V. S. Sokratov

    2013-01-01

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

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

    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.

  6. Interannual variability of dust-mass loading and composition of dust deposited on snow cover in the San Juan Mountains, CO, USA: Insights into effects on snow melt

    Goldstein, H. L.; Reynolds, R. L.; Derry, J.; Kokaly, R. F.; Moskowitz, B. M.

    2017-12-01

    Dust deposited on snow cover (DOS) in the American West can enhance snow-melt rates and advance the timing of melting, which together can result in earlier-than-normal runoff and overall smaller late-season water supplies. Understanding DOS properties and how they affect the absorption of solar radiation can lead to improved snow-melt models by accounting for important dust components. Here, we report on the interannual variability of DOS-mass loading, particle size, organic matter, and iron mineralogy, and their correspondences to laboratory-measured reflectance of samples from the Swamp Angel Study Plot in the San Juan Mountains, Colorado, USA. Samples were collected near the end of spring in water year 2009 (WY09) and from WY11-WY16, when dust layers deposited throughout the year had merged into one layer at the snow surface. Dust-mass loading on snow ranged 2-64 g/m2, mostly as particles with median sizes of 13-33 micrometers. Average reflectance values of DOS varied little across total (0.4 to 2.50 µm) and visible (0.4 to 0.7 µm) wavelengths at 0.30-0.45 and 0.19-0.27, respectively. Reflectance values lacked correspondence to particle-size. Total reflectance values inversely corresponded to concentrations of (1) organic matter content (4-20 weight %; r2 = 0.71) that included forms of black carbon and locally derived material such as pollen, and (2) magnetite (0.05 to 0.13 weight %; r2 = 0.44). Magnetite may be a surrogate for related dark, light-absorbing minerals. Concentrations of crystalline ferric oxide minerals (hematite+goethite) based on magnetic properties at room-temperature did not show inverse association to visible reflectance values. These ferric oxide measures, however, did not account for the amounts of nano-sized ferric oxides known to exist in these samples. Quantification of such nano-sized particles is required to evaluate their possible effects on visible reflectance. Nonetheless, our results emphasize that reflectance values of year

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

    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.

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

    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.

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

    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.

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

    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)

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

    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...

  12. Monitoring of carbon isotope composition of snow cover for Tomsk region

    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.

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

    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.

  14. 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

    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

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

    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

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

    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%).

  17. 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

    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

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

    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...

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

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

    2015-01-01

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

  20. MEaSUREs Northern Hemisphere State of Cryosphere Daily 25km EASE-Grid 2.0

    National Aeronautics and Space Administration — This data set reports the location of Northern Hemisphere snow cover and sea ice extent, the status of melt onset across Greenland and Artic sea ice, and the level...

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

    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!

  2. On the Linkage between Springtime Eurasian Snow Cover Retreat due to the Global Warming and Changes in Summertime Atmospheric Circulation over Japan and East Asia

    Nozawa, T.; Fujiwara, S.

    2017-12-01

    According to the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5), snow cover extent (SCE) over the northern hemisphere is greatly decreasing in spring. This change is expected to affect atmospheric circulation change via land-atmosphere interactions. In this study, we investigated relationships between spring SCE anomaly over the Eurasia and changes in atmospheric circulations, mainly analyzing the Japanese 55-year Reanalysis (JRA-55). Differences in composites of zonal winds at upper and middle levels between large and small SCE years over Western Siberia in spring show that, around Japan and East Asia, jet stream in small SCE years is shifted southward in April and June. We also analyzed surface temperature and soil moisture and find that, in small SCE years, surface temperature in Western Siberia and Central Asia is increased and soil moisture reduced significantly in June. The air temperature in the middle and low level atmosphere also significantly increased and have wave-like pattern in May. These results suggest that there are some linkages between the springtime Eurasian SCE reduction and changes in summertime jet stream over Japan and East Asia through land-atmosphere interactions.

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

    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.

  4. Validation of Satellite Snow Cover Maps in North America and Norway

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

    2002-01-01

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

  5. A simple model for predicting soil temperature in snow-covered and seasonally frozen soil: model description and testing

    K. Rankinen

    2004-01-01

    Full Text Available Microbial processes in soil are moisture, nutrient and temperature dependent and, consequently, accurate calculation of soil temperature is important for modelling nitrogen processes. Microbial activity in soil occurs even at sub-zero temperatures so that, in northern latitudes, a method to calculate soil temperature under snow cover and in frozen soils is required. This paper describes a new and simple model to calculate daily values for soil temperature at various depths in both frozen and unfrozen soils. The model requires four parameters: average soil thermal conductivity, specific heat capacity of soil, specific heat capacity due to freezing and thawing and an empirical snow parameter. Precipitation, air temperature and snow depth (measured or calculated are needed as input variables. The proposed model was applied to five sites in different parts of Finland representing different climates and soil types. Observed soil temperatures at depths of 20 and 50 cm (September 1981–August 1990 were used for model calibration. The calibrated model was then tested using observed soil temperatures from September 1990 to August 2001. R2-values of the calibration period varied between 0.87 and 0.96 at a depth of 20 cm and between 0.78 and 0.97 at 50 cm. R2-values of the testing period were between 0.87 and 0.94 at a depth of 20cm, and between 0.80 and 0.98 at 50cm. Thus, despite the simplifications made, the model was able to simulate soil temperature at these study sites. This simple model simulates soil temperature well in the uppermost soil layers where most of the nitrogen processes occur. The small number of parameters required means that the model is suitable for addition to catchment scale models. Keywords: soil temperature, snow model

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

    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.

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

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

    2017-01-01

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

  8. The strengthening relationship between Eurasian snow cover and December haze days in central North China after the mid-1990s

    Yin, Zhicong; Wang, Huijun

    2018-04-01

    The haze pollution in December has become increasingly serious over recent decades and imposes damage on society, ecosystems, and human health. In addition to anthropogenic emissions, climate change and variability were conducive to haze in China. In this study, the relationship between the snow cover over eastern Europe and western Siberia (SCES) and the number of haze days in December in central North China was analyzed. This relationship significantly strengthened after the mid-1990s, which is attributed to the effective connections between the SCES and the Eurasian atmospheric circulations. During 1998-2016, the SCES significantly influenced the soil moisture and land surface radiation, and then the combined underlying drivers of enhanced soil moisture and radiative cooling moved the the East Asia jet stream northward and induced anomalous, anti-cyclonic circulation over central North China. Modulated by such atmospheric circulations, the local lower boundary layer, the decreased surface wind, and the more humid air were conducive to the worsening dispersion conditions and frequent haze occurrences. In contrast, from 1979 to 1997, the linkage between the SCES and soil moisture was negligible. Furthermore, the correlated radiative cooling was distributed narrowly and far from the key area of snow cover. The associated atmospheric circulations with the SCES were not significantly linked with the ventilation conditions over central North China. Consequently, the relationship between the SCES and the number of hazy days in central North China was insignificant before the mid-1990s but has strengthened and has become significant since then.

  9. The strengthening relationship between Eurasian snow cover and December haze days in central North China after the mid-1990s

    Z. Yin

    2018-04-01

    Full Text Available The haze pollution in December has become increasingly serious over recent decades and imposes damage on society, ecosystems, and human health. In addition to anthropogenic emissions, climate change and variability were conducive to haze in China. In this study, the relationship between the snow cover over eastern Europe and western Siberia (SCES and the number of haze days in December in central North China was analyzed. This relationship significantly strengthened after the mid-1990s, which is attributed to the effective connections between the SCES and the Eurasian atmospheric circulations. During 1998–2016, the SCES significantly influenced the soil moisture and land surface radiation, and then the combined underlying drivers of enhanced soil moisture and radiative cooling moved the the East Asia jet stream northward and induced anomalous, anti-cyclonic circulation over central North China. Modulated by such atmospheric circulations, the local lower boundary layer, the decreased surface wind, and the more humid air were conducive to the worsening dispersion conditions and frequent haze occurrences. In contrast, from 1979 to 1997, the linkage between the SCES and soil moisture was negligible. Furthermore, the correlated radiative cooling was distributed narrowly and far from the key area of snow cover. The associated atmospheric circulations with the SCES were not significantly linked with the ventilation conditions over central North China. Consequently, the relationship between the SCES and the number of hazy days in central North China was insignificant before the mid-1990s but has strengthened and has become significant since then.

  10. 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

    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

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

    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...

  12. 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

    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

  13. Hydrocarbons (aliphatic and aromatic) in the snow-ice cover in the Arctic

    Nemirovskaya, I.A.; Novigatsky, A.N.; Kluvitkin, A.A.

    2002-01-01

    This paper presented the concentration and composition of aliphatic hydrocarbons and polycyclic aromatic hydrocarbons (PAHs) in snow and ice-infested waters in the France-Victoria trough in the northern Barents Sea and in the Mendeleev ridge in the Amerasian basin of the Arctic Ocean. Extreme conditions such as low temperatures, ice sheets and the polar nights render the arctic environment susceptible to oil spills. Hydrocarbons found in these northern seas experience significant transformations. In order to determine the sources, pathways and transformations of the pollutants, it is necessary to know their origin. Hydrocarbon distributions is determined mostly by natural hydrobiological and geochemical conditions. The regularity of migration is determined by natural factors such as formation and circulation of air and ice drift. There is evidence suggesting that the hydrocarbons come from pyrogenic sources. It was noted that hydrocarbons could be degraded even at low temperatures. 17 refs., 1 tab

  14. 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

    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.

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

    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.

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

    Schmale, Julia; Kang, Shichang; Peltier, Richard

    2014-05-01

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

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

    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.

  18. MODIS land cover and LAI collection 4 product quality across nine states in the western hemisphere.

    Warren B. Cohen; Thomas K. Maiersperger; David P. Turner; William D. Ritts; Dirk Pflugmacher; Robert E. Kennedy; Alan Kirschbaum; Steven W. Running; Marcos Costa; Stith T. Gower

    2006-01-01

    Global maps of land cover and leaf area index (LAI) derived from the Moderate Resolution Imaging Spectrometer (MODIS) reflectance data are an important resource in studies of global change, but errors in these must be characterized and well understood. Product validation requires careful scaling from ground and related measurements to a grain commensurate with MODIS...

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

    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.

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

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

    2006-01-01

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

  1. Hg in snow cover and snowmelt waters in high-sulfide tailing regions (Ursk tailing dump site, Kemerovo region, Russia).

    Gustaytis, M A; Myagkaya, I N; Chumbaev, A S

    2018-07-01

    Gold-bearing polymetallic Cu-Zn deposits of sulphur-pyrite ores were discovered in the Novo-Ursk region in the 1930s. The average content of mercury (Hg) was approximately 120 μg/g at the time. A comprehensive study of Hg distribution in waste of metal ore enrichment industry was carried out in the cold season on the tailing dump site and in adjacent areas. Mercury concentration in among snow particulate, dissolved and colloid fractions was determined. The maximal Hg content in particulate fraction from the waste tailing site ranged 230-573 μg/g. Such indices as the frequency of aerosol dust deposition events per units of time and area, enrichment factor and the total load allowed to establish that the territory of the tailing waste dump site had a snow cover highly contaminated with dust deposited at a rate of 247-480 mg/(m 2 ∙day). Adjacent areas could be considered as area with low Hg contamination rate with average deposition rate of 30 mg/(m 2 ∙day). The elemental composition of the aerosol dust depositions was determined as well, which allowed to reveal the extent of enrichment waste dispersion throughout adjacent areas. The amount of Hg entering environment with snowmelt water discharge was estimated. As a result of snowmelting, in 2014 the nearest to the dump site hydrographic network got Hg as 7.1 g with colloids and as 5880 g as particles. The results obtained allowed to assess the degree of Hg contamination of areas under the impact of metal enrichment industry. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

    Jadoon, Khan

    2013-07-01

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

  3. Evaluation of MODIS albedo product (MCD43A) over grassland, agriculture and forest surface types during dormant and snow-covered periods

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

    2014-01-01

    This study assesses the Moderate-resolution Imaging Spectroradiometer (MODIS) BRDF/albedo 8 day standard product and products from the daily Direct Broadcast BRDF/albedo algorithm, and shows that these products agree well with ground-based albedo measurements during the more difficult periods of vegetation dormancy and snow cover. Cropland, grassland, deciduous and...

  4. 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

    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

  5. Possible association of the western Tibetan Plateau snow cover with the decadal to interdecadal variations of northern China heatwave frequency

    Wu, Zhiwei [Nanjing University of Information Science and Technology, Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing (China); Chinese Academy of Sciences, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Beijing (China); Jiang, Zhihong; Zhong, Shanshan; Wang, Lijuan [Nanjing University of Information Science and Technology, Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing (China); Li, Jianping [Chinese Academy of Sciences, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Beijing (China)

    2012-11-15

    Northern China has been subject to increased heatwave frequency (HWF) in recent decades, which deteriorates the local droughts and desertification. More than half a billion people face drinking water shortages and worsening ecological environment. In this study, the variability in the western Tibetan Plateau snow cover (TPSC) is observed to have an intimate linkage with the first empirical orthogonal function mode of the summer HWF across China. This distinct leading mode is dominated by the decadal to inter-decadal variability and features a mono-sign pattern with the extreme value center prevailing over northern China and high pressure anomalies at mid- and upper troposphere over Mongolia and the adjacent regions. A simplified general circulation model is utilized to examine the possible physical mechanism. A reduced TPSC anomaly can induce a positive geopotential height anomaly at the mid- and upper troposphere and subsequently enhance the climatological high pressure ridge over Mongolia and the adjacent regions. The subsidence associated with the high pressure anomalies tends to suppress the local cloud formation, which increases the net radiation budget, heats the surface, and favors more heatwaves. On the other hand, the surface heating can excite high pressure anomalies at mid- and upper troposphere. The latter further strengthens the upper troposphere high pressure anomalies over Mongolia and the adjacent regions. Through such positive feedback effect, the TPSC is tied to the interdecadal variations of the northern China HWF. (orig.)

  6. Empirical and theoretical evidence concerning the response of the earth's ice and snow cover to a global temperature increase

    Hollin, J T; Barry, R G

    1979-01-01

    As a guide to the possible effects of a CO/sub 2/-induced warming on the cryosphere, we review the effects of three warm periods in the past, and our theoretical understanding of fluctuations in mountain glaciers, the Greenland and Antarctic ice sheets, ground ice, sea ice and seasonal snow cover. Between 1890 and 1940 A.D. the glaciated area in Switzerland was reduced by over 25%. In the Hypsithermal, at about 6000 BP, ground ice in Eurasia retreated northward by several hundred kilometers. In the interglacial Stage 5e, at about 120 000 BP, glocal sea-level rose by over 6 m. Fluctuations of mountain glaciers depend on mesoscale weather and on their mechanical response to it. Any melting of the Greenland ice sheet is likely to be slow in human terms. The West Antarctic ice sheet (its base below sea-level) is susceptible to an ungrounding, and such an event may have been the cause of the sea-level rise above. The East Antarctic ice sheet is susceptible to mechanical surges, which might be triggered by a warming at its margin. Both an ungrounding and a surge might occupy less than 100 yr, and are potentially the most important ice changes in human terms. Modeling studies suggest that a 5/sup 0/C warming would remove the Arctic pack ice in summer. and this may be the most significant effect for further climatic change.

  7. Particle size distribution, chemical composition and meteorological factor analysis: A case study during wintertime snow cover in Zhengzhou, China

    Yu, Fei; Wang, Qun; Yan, Qishe; Jiang, Nan; Wei, Junhua; Wei, Zhiyuan; Yin, Shasha

    2018-04-01

    There was a significant snowfall event in North China from November 23 to 25 in 2015. Considering that most of the bare surface and road dust were covered by snow, the effect of dust and soil could be ignored. Atmospheric particle samples were collected in Zhengzhou, China during a haze event from November 28 to December 4, 2015. To better understand the formation and evolution of this hazy event, the size distribution, particle number, composition of particles and meteorological parameters were measured and analyzed. Results show that the meteorological conditions played an important role in the occurrence and elimination of this event. The hourly fine particle matter (PM2.5) concentration was positively correlated with relative humidity (r = 0.84, p NH4+) on hazy days was higher than that on clean days. The higher NH4+ concentration in this case may be contributed by traffic and coal-power emission. Crustal matter accounted for 2.4% in PM2.5 on hazy days, and it confirmed that the contribution of dust emission source was negligible during this event. The ratios of NO3-/SO42 - ranging from 0.41 to 0.67 indicated the relative importance of stationary combustion. The ratios of OC/EC varied from 2.73 to 3.42 and indicated the presence of secondary organic carbon. Effective haze mitigation should enforce pollutant control measures for primary emission (dust) and secondary aerosol gaseous precursor (NH3, NO2 and SO2).

  8. 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

    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

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

    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

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

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

    2015-11-01

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

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

    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.

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

    A. A. Marks

    2013-07-01

    Full Text Available 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 over the visible wavelengths suggests black carbon is the dominating light-absorbing impurity. The response of first-year and multi-year sea ice albedo to increasing black carbon, from 1 to 1024 ng g−1, in a top 5 cm layer of a 155 cm-thick sea ice was calculated using a radiative-transfer model. The albedo of the first-year sea ice is more sensitive to additional loadings of black carbon than the multi-year sea ice. An addition of 8 ng g−1 of black carbon causes a decrease to 98.7% of the original albedo for first-year sea ice compared to a decrease to 99.7% for the albedo of multi-year sea ice, at a wavelength of 500 nm. The albedo of sea ice is surprisingly unresponsive to additional black carbon up to 100 ng g−1 . Snow layers on sea ice may mitigate the effects of black carbon in sea ice. Wet and dry snow layers of 0.5, 1, 2, 5 and 10 cm depth were added onto the sea ice surface. The albedo of the snow surface was calculated whilst the black carbon in the underlying sea ice was increased. A layer of snow 0.5 cm thick greatly diminishes the effect of black carbon in sea ice on the surface albedo. The albedo of a 2–5 cm snow layer (less than the e-folding depth of snow is still influenced by the underlying sea ice, but the effect of additional black carbon in the sea ice is masked.

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

    A. Stehr

    2017-10-01

    Full Text Available 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

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

    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

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

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

    2013-01-01

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

  16. Sensitivity of Support Vector Machine Predictions of Passive Microwave Brightness Temperature Over Snow-covered Terrain in High Mountain Asia

    Ahmad, J. A.; Forman, B. A.

    2017-12-01

    High Mountain Asia (HMA) serves as a water supply source for over 1.3 billion people, primarily in south-east Asia. Most of this water originates as snow (or ice) that melts during the summer months and contributes to the run-off downstream. In spite of its critical role, there is still considerable uncertainty regarding the total amount of snow in HMA and its spatial and temporal variation. In this study, the NASA Land Information Systems (LIS) is used to model the hydrologic cycle over the Indus basin. In addition, the ability of support vector machines (SVM), a machine learning technique, to predict passive microwave brightness temperatures at a specific frequency and polarization as a function of LIS-derived land surface model output is explored in a sensitivity analysis. Multi-frequency, multi-polarization passive microwave brightness temperatures as measured by the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) over the Indus basin are used as training targets during the SVM training process. Normalized sensitivity coefficients (NSC) are then computed to assess the sensitivity of a well-trained SVM to each LIS-derived state variable. Preliminary results conform with the known first-order physics. For example, input states directly linked to physical temperature like snow temperature, air temperature, and vegetation temperature have positive NSC's whereas input states that increase volume scattering such as snow water equivalent or snow density yield negative NSC's. Air temperature exhibits the largest sensitivity coefficients due to its inherent, high-frequency variability. Adherence of this machine learning algorithm to the first-order physics bodes well for its potential use in LIS as the observation operator within a radiance data assimilation system aimed at improving regional- and continental-scale snow estimates.

  17. Improvement of distributed snowmelt energy balance modeling with MODIS-based NDSI-derived fractional snow-covered area data

    Joel W. Homan; Charles H. Luce; James P. McNamara; Nancy F. Glenn

    2011-01-01

    Describing the spatial variability of heterogeneous snowpacks at a watershed or mountain-front scale is important for improvements in large-scale snowmelt modelling. Snowmelt depletion curves, which relate fractional decreases in snowcovered area (SCA) against normalized decreases in snow water equivalent (SWE), are a common approach to scale-up snowmelt models....

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

    Bokhorst, Stef; Pedersen, Stine Højlund; Brucker, Ludovic

    2016-01-01

    on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict...

  19. Using Air Temperature to Quantitatively Predict the MODIS Fractional Snow Cover Retrieval Errors over the Continental US (CONUS)

    Dong, Jiarui; Ek, Mike; Hall, Dorothy K.; Peters-Lidard, Christa; Cosgrove, Brian; Miller, Jeff; Riggs, George A.; Xia, Youlong

    2013-01-01

    In the middle to high latitude and alpine regions, the seasonal snow pack can dominate the surface energy and water budgets due to its high albedo, low thermal conductivity, high emissivity, considerable spatial and temporal variability, and ability to store and then later release a winters cumulative snowfall (Cohen, 1994; Hall, 1998). With this in mind, the snow drought across the U.S. has raised questions about impacts on water supply, ski resorts and agriculture. Knowledge of various snow pack properties is crucial for short-term weather forecasts, climate change prediction, and hydrologic forecasting for producing reliable daily to seasonal forecasts. One potential source of this information is the multi-institution North American Land Data Assimilation System (NLDAS) project (Mitchell et al., 2004). Real-time NLDAS products are used for drought monitoring to support the National Integrated Drought Information System (NIDIS) and as initial conditions for a future NCEP drought forecast system. Additionally, efforts are currently underway to assimilate remotely-sensed estimates of land-surface states such as snowpack information into NLDAS. It is believed that this assimilation will not only produce improved snowpack states that better represent snow evolving conditions, but will directly improve the monitoring of drought.

  20. Financial evaluation of the integration of satellite technology for snow cover measurements at a hydroelectric plant. (Utilization of Radarsat I in the La Grande river basin, Quebec)

    Martin, D.; Bernier, M.; Sasseville, J.L.; Charbonneau, R.

    1999-01-01

    The emergence, on the markets, of new technologies evokes, for the potential users, a lot of questions concerning the implementation and operation costs associated with these technologies. Nevertheless, for a lot of users, costs should be considered with the benefits these technologies are able to generate. The benefit-cost analysis is a useful tool for a financial evaluation of the transferability of the technology. This method has been selected to evaluate the eventual implementation of remote sensing technologies for snow cover measurements in the La Grande river basin (Quebec, Canada). Indeed, a better assessment of the snow water equivalent leads to a better forecasting of the water inputs due to the snowmelt. Thus, the improvement of the snow cover monitoring has direct impact on hydroelectric reservoir management. The benefit-cost analysis was used to compare three acquisition modes of the satellite Radarsat 1 (ScanSAR, Wide and Standard). The costs considered for this project are: R and D costs and operations costs (the purchase of images and costs of ground truth measurements). We evaluated the raw benefits on the basis of reducing the standard deviation of predicted inflows. The results show that the ScanSAR mode is the primary remote sensing tool for the monitoring of the snow cover, on an operational basis. With this acquisition mode, the benefit-cost ratios range between 2.3:1 and 3.9:1, using a conservative 4% reduction of the standard deviation. Even if the reduction is only 3%, ScanSAR remains profitable. Due to the large number of images needed to cover all the territory, the Standard and Wide modes are penalized by the purchase and the processing costs of the data and with delays associated to the processing. Nevertheless, with these two modes, it could be possible to work with a partial coverage of the watershed, 75% being covered in 4 days in Wide mod. The estimated B/C ratios (1.5:1 and 2:1) confirm the advantages of this alternative

  1. Quantification of spatial temporal variability of snow cover and hydro-climatic variables based on multi-source remote sensing data in the Swat watershed, Hindukush Mountains, Pakistan

    Anjum, Muhammad Naveed; Ding, Yongjian; Shangguan, Donghui; Liu, Junguo; Ahmad, Ijaz; Ijaz, Muhammad Wajid; Khan, Muhammad Imran

    2018-02-01

    The northern part of Hindukush Mountains has a perplexing environment due to the influence of adjacent mountains of Himalaya, Karakoram, and Tibetan Plateau. Although reliable evidences of climate change are available; however, a clear knowledge of snow cover dynamics in the context of climate change is missing for this region. In this study, we used various remotely sensed (TRMM precipitation product, while MODIS temperature and snow cover products) and gauge-based datasets to quantify the spatiotemporal variability of climatic variables and their turn effects over the snow cover area (SCA) and river discharge in the Swat watershed, northern Hindukush Mountains, Pakistan. The Mann-Kendall method and Sen's slope estimator were used to estimate the trends in SCA and hydro-climatic variables, at 5% significant level (P = 0.05). Results show that the winter and springs temperatures have increased (at the rate of 0.079 and 0.059 °C year-1, respectively), while decreasing in the summer and autumn (at the rate of 0.049 and 0.070 °C year-1, respectively). Basin-wide increasing tendency of precipitation was identified with a highest increasing rate of 3.563 mm year-1 in the spring season. A decreasing trend in the winter SCA (at the rate of -0.275% year-1) and increasing trends in other seasons were identified. An increasing tendency of river discharge on annual and seasonal scales was also witnessed. The seasonal variations in discharge showed significant positive and negative relationships with temperature and SCA, respectively. We conclude that the future variations in the temperature and SCA in the higher altitudes of the Swat watershed could substantially affect the seasonality of the river discharge. Moreover, it implies that the effect of ongoing global warming on the SCA in the snowmelt-dominated river basins needs to be considered for sustainable regional planning and management of water resources, hydropower production, and downstream irrigation scheduling.

  2. A Warming Surface but a Cooling Top of Atmosphere Associated with Warm, Moist Air Mass Advection over the Ice and Snow Covered Arctic

    Sedlar, J.

    2015-12-01

    Atmospheric advection of heat and moisture from lower latitudes to the high-latitude Arctic is a critical component of Earth's energy cycle. Large-scale advective events have been shown to make up a significant portion of the moist static energy budget of the Arctic atmosphere, even though such events are typically infrequent. The transport of heat and moisture over surfaces covered by ice and snow results in dynamic changes to the boundary layer structure, stability and turbulence, as well as to diabatic processes such as cloud distribution, microphysics and subsequent radiative effects. Recent studies have identified advection into the Arctic as a key mechanism for modulating the melt and freeze of snow and sea ice, via modification to all-sky longwave radiation. This paper examines the radiative impact during summer of such Arctic advective events at the top of the atmosphere (TOA), considering also the important role they play for the surface energy budget. Using infrared sounder measurements from the AIRS satellite, the summer frequency of significantly stable and moist advective events from 2003-2014 are characterized; justification of AIRS profiles over the Arctic are made using radiosoundings during a 3-month transect (ACSE) across the Eastern Arctic basin. One such event was observed within the East Siberian Sea in August 2014 during ACSE, providing in situ verification on the robustness and capability of AIRS to monitor advective cases. Results will highlight the important surface warming aspect of stable, moist instrusions. However a paradox emerges as such events also result in a cooling at the TOA evident on monthly mean TOA radiation. Thus such events have a climatic importance over ice and snow covered surfaces across the Arctic. ERA-Interim reanalyses are examined to provide a longer term perspective on the frequency of such events as well as providing capability to estimate meridional fluxes of moist static energy.

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

    Jadoon, Khan

    2015-09-18

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

  4. Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

    Peltoniemi, Mikko; Aurela, Mika; Böttcher, Kristin; Kolari, Pasi; Loehr, John; Karhu, Jouni; Linkosalmi, Maiju; Melih Tanis, Cemal; Tuovinen, Juha-Pekka; Nadir Arslan, Ali

    2018-01-01

    In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1-3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/). Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862). Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

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

    Jadoon, Khan; Weihermller, Lutz; McCabe, Matthew; Moghadas, Davood; Vereecken, Harry; Lambot, Sbastien

    2015-01-01

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

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

    Khan Zaib Jadoon

    2015-09-01

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

  7. Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

    M. Peltoniemi

    2018-01-01

    Full Text Available In recent years, monitoring of the status of ecosystems using low-cost web (IP or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1–3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/. Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862. Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

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

    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

  9. SNOW COVER OF THE CENTRAL ANTARCTICA (VOSTOK STATION AS AN IDEAL NATURAL TABLET FOR COSMIC DUST COLLECTION: PRELIMINARY RESULTS ON THE IDENTIFICATION OF MICROMETEORITES OF CARBONACEOUS CHONDRITE TYPE

    E. S. Bulat

    2012-01-01

    Full Text Available During the 2010/11 season nearby the Vostok station the 56th Russian Antarctic Expedition has collected surface snow in a big amount from a 3 m deep pit using 15 220 L vol. containers (about 70 kg snow each. Snow melting and processing by ultra-centrifugation was performed in a clean (class 10 000 and 100 laboratory. Total dust concentrations were not exceeded 37.4 mkg per liter with particle dispersal mode around 2.5 mkm. To analyze the elemental composition of fine dust particles aimed to reveal Antarctic micrometeorites (AMM two electron microscopy devices equipped with different micro-beams were implemented. As a preliminary result, three particles (of 107 analyzed featured by Mg content clearly dominated over Al along with Si and Fe as major elements (a feature of carbonaceous chondrites were observed. By this the Vostok AMM CS11 collection was established. The occurrence of given particles was averaged 2.8% – the factual value obtained for the first time for chondritic type AMM at Vostok which should be considered as the lowest estimate for all other families of AMM. Given the reference profile of total dust content in East Antarctic snow during Holocene (18 mkg/kg the MM deposition in Antarctica was quantified for the first time – 14 tons per day for carbonaceous chondrites for the Vostok AMM CS11 collection and up to 245 tons per day for all MM types for the Concordia AMM DC02 collection. The results obtained allowed to prove that snow cover (ice sheet in total of Central East Antarctica is the best spot (most clean of other natural locations and always below 0 ºC for collecting native MM deposited on the Earth during the last million years and could be useful in deciphering the origin and evolution of solid matter in our Solar System and its effects on Earth-bound biogeochemical and geophysical processes including the life origin. The farther analyses of the Vostok AMMs are in a progress.

  10. Temporal changes of inorganic ion deposition in the seasonal snow cover for the Austrian Alps (1983-2014)

    Greilinger, Marion; Schöner, Wolfgang; Winiwarter, Wilfried; Kasper-Giebl, Anne

    2016-05-01

    A long-term record of inorganic ion concentrations in wet and dry deposition sampled from snow packs at two high altitude glaciers was used to assess impacts of air pollution on remote sites in central Europe. Sampling points were located at Wurtenkees and Goldbergkees near the Sonnblick Observatory (3106 m above sea level), a background site for measuring the status of the atmosphere in Austria's Eastern Alps. Sampling was carried out every spring at the end of the winter accumulation period in the years 1983-2014. Concentrations of major ions (NH4+, SO42-, NO3-, Ca2+, Mg2+, K+, Na+ and Cl-) were determined using ion chromatography (IC) as well as atomic absorption spectroscopy (AAS) in the earlier years. Concentration of H+ was calculated via the measured pH of the samples. Trends in deposition and concentration were analysed for all major ions within the period from 1983 to 2014 using Kendall's tau rank correlation coefficient. From 1983 to 2014, total ion concentration declined ∼25%, i.e. solutions became ∼25% more dilute, indicating reduced acidic atmospheric deposition, even at high altitude in winter snow. SO42- and NO3- concentrations decreased significantly by 70% and 30%, respectively, accompanied by a 54% decrease of H+ concentrations. Ionic concentrations in snowpack were dominated by H+ and SO42- in the earliest decade measured, whereas they were dominated by Ca2+ by the most recent decade. SO42- and H+ depositions, i.e. concentrations multiplied by volume, also showed a significant decrease of more than 50% at both sites. This reflects the successful emission reductions of the precursor gases SO2 and NOx. Seasonal values with significantly elevated spring concentrations of NH4+, SO42- and H+ compared to fall snow reflects the beginning of vertical mixing during spring. All other ions do not show any seasonality. Source identification of the ions was performed using a principal component analysis (PCA). One anthropogenic cluster (SO42-, NO3- and NH

  11. Snow contribution to springtime atmospheric predictability over the second half of the twentieth century

    Peings, Yannick [CNRM-GAME, Meteo-France et CNRS, Toulouse (France); CNRM/GMGEC/VDR, Toulouse (France); Douville, H.; Alkama, R.; Decharme, B. [CNRM-GAME, Meteo-France et CNRS, Toulouse (France)

    2011-09-15

    A set of global atmospheric simulations has been performed with the ARPEGE-Climat model in order to quantify the contribution of realistic snow conditions to seasonal atmospheric predictability in addition to that of a perfect sea surface temperature (SST) forcing. The focus is on the springtime boreal hemisphere where the combination of a significant snow cover variability and an increasing solar radiation favour the potential snow influence on the surface energy budget. The study covers the whole 1950-2000 period through the use of an original snow mass reanalysis based on an off-line land surface model and possibly constrained by satellite snow cover observations. Two ensembles of 10-member AMIP-type experiments have been first performed with relaxed versus free snow boundary conditions. The nudging towards the monthly snow mass reanalysis significantly improves both potential and actual predictability of springtime surface air temperature over Central Europe and North America. Yet, the impact is confined to the lower troposphere and there is no clear improvement in the predictability of the large-scale atmospheric circulation. Further constraining the prescribed snow boundary conditions with satellite observations does not change much the results. Finally, using the snow reanalysis only for initializing the model on March 1st also leads to a positive impact on predicted low-level temperatures but with a weaker amplitude and persistence. A conditional skill approach as well as some selected case studies provide some guidelines for interpreting these results and suggest that an underestimated snow cover variability and a misrepresentation of ENSO teleconnections may hamper the benefit of an improved snow initialization in the ARPEGE-Climat model. (orig.)

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

    Wyard, Coraline; Fettweis, Xavier

    2016-04-01

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

  13. Towards Year-round Estimation of Terrestrial Water Storage over Snow-Covered Terrain via Multi-sensor Assimilation of GRACE/GRACE-FO and AMSR-E/AMSR-2.

    Wang, J.; Xue, Y.; Forman, B. A.; Girotto, M.; Reichle, R. H.

    2017-12-01

    The Gravity and Recovery Climate Experiment (GRACE) has revolutionized large-scale remote sensing of the Earth's terrestrial hydrologic cycle and has provided an unprecedented observational constraint for global land surface models. However, the coarse-scale (in space and time), vertically-integrated measure of terrestrial water storage (TWS) limits GRACE's applicability to smaller scale hydrologic applications. In order to enhance model-based estimates of TWS while effectively adding resolution (in space and time) to the coarse-scale TWS retrievals, a multi-variate, multi-sensor data assimilation framework is presented here that simultaneously assimilates gravimetric retrievals of TWS in conjunction with passive microwave (PMW) brightness temperature (Tb) observations over snow-covered terrain. The framework uses the NASA Catchment Land Surface Model (Catchment) and an ensemble Kalman filter (EnKF). A synthetic assimilation experiment is presented for the Volga river basin in Russia. The skill of the output from the assimilation of synthetic observations is compared with that of model estimates generated without the benefit of assimilating the synthetic observations. It is shown that the EnKF framework improves modeled estimates of TWS, snow depth, and snow mass (a.k.a. snow water equivalent). The data assimilation routine produces a conditioned (updated) estimate that is more accurate and contains less uncertainty during both the snow accumulation phase of the snow season as well as during the snow ablation season.

  14. Use of time series of optical and SAR images in the estimation of snow cover for the optimization of water use in the Andes of Argentina and Chile

    Salinas de Salmuni, Graciela; Cabezas Cartes, Ricardo; Menicocci, Felix

    2014-05-01

    This paper describes the progress in the bilateral cooperation project between academic and water resources management institutions from the Andes region of Argentina and Chile. The study zone is located in fragile ecosystems and mountain areas of the Andes (limit zone between the Province of San Juan, Argentina, and the IV Region of Coquimbo, Chile), with arid climate, where snow precipitates in the headwaters of watershed feed the rivers of the region by melting, which are the only source of water for human use, productive and energetic activities, as well as the native flora and fauna. CONAE, the Argentine Space Agency, participates in the Project through the provision of satellite data to the users and by this it contributes to ensuring the continuity of the results of the project. Also, it provides training in digital image processing. The project also includes the participation of water resource management institutions like Secretaria de Recursos Hidricos of Argentina and the Centro de Información de Recursos Naturales de Chile (CIREN), and of academic institution like the University of San Juan (Argentina) and University of La Serena (Chile). These institutions benefit from the incorporation of new methodologies advanced digital image processing and training of staff (researcher, lecturers, PhD Students and technical). Objectives: 1-Improve water distribution incorporating space technology for application in the prediction models of the stream flow. 2- Conduct an inventory of glaciers as well as studies in selected watersheds in the Andean region, aiming to know the water resource, its availability and potential risks to communities in the region. 3. Contribute to vulnerability studies in biodiversity Andean watersheds. Results: For estimation Snow cover Area, the MODIS images are appropriate due their high temporal resolution and allows for monitoring large areas (greater than 10 km) The proposed methodology (Use of snow index, NSDI) is appropriate for

  15. Frozen soil and snow cover with respect to the hydrological land-surface behaviour; Gefrorener Boden und Schneebedeckung unter besonderer Beruecksichtigung des hydrologischen Verhaltens der Landoberflaeche

    Warrach, K. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Atmosphaerenphysik

    2000-07-01

    Investigations of the water and energy cycle in the climate system using atmospheric circulation models require a proper representation of the land surface. The land-surface model SEWAB calculates the vertical exchange of water and energy between the atmosphere and the land-surface. This includes the calculation of runoff from the land-surface into the rivers and of the vertical heat and water fluxes within the soil. The inclusion of soil freezing and thawing and the accumulation and ablation of a snow cover in SEWAB is introduced. Additionally changes in the runoff calculation such as the inclusion of the TOPMODEL-approach to consider orographic effects are made. Applications carried out for various regions of North America show good agreement between model results and measurements. (orig.)

  16. Snow, ice and solar radiation

    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

  17. Atmospheric transport of persistent organic pollutants - development of a 3-d dynamical transport model covering the northern hemisphere

    Hansen, K. M.; Christensen, J. H.; Geels, C.; Frohn, L. M.; Brandt, J.

    2003-04-01

    The Danish Eulerian Hemispheric Model (DEHM) is a 3-D dynamical atmospheric transport model originally developed to describe the atmospheric transport of sulphur, lead, and mercury to the Arctic. The model has been validated carefully for these compounds. A new version of DEHM is currently being developed to describe the atmospheric transport of persistent organic pollutants (POPs) which are toxic, lipophilic and bio-accumulating compounds showing great persistence in the environment. The model has a horizontal resolution of 150 km x 150 km and 18 vertical layers, and it is driven by meteorological data from the numerical weather prediction model MM5V2. During environmental cycling POPs can be deposited and re-emitted several times before reaching a final destination. A description of the exchange processes between the land/ocean surfaces and the atmosphere is included in the model to account for this multi-hop transport. The present model version describes the atmospheric transport of the pesticide alpha-hexachlorocyclohexane (alpha-HCH). Other POPs may be included when proper data on emissions and physical-chemical parameters becomes available. The model-processes and the first model results are presented. The atmospheric transport of alpha-HCH for the 1990s is well described by the model.

  18. Vertical distribution and diel vertical migration of krill beneath snow-covered ice and in ice-free waters

    Vestheim, Hege; Rø stad, Anders; Klevjer, Thor A.; Solberg, Ingrid; Kaartvedt, Stein

    2013-01-01

    A bottom mounted upward looking Simrad EK60 120-kHz echo sounder was used to study scattering layers (SLs) and individuals of the krill Meganyctiphanes norvegica. The mooring was situated at 150-m depth in the Oslofjord, connected with an onshore cable for power and transmission of digitized data. Records spanned 5 months from late autumn to spring. A current meter and CTD was associated with the acoustic mooring and a shore-based webcam monitored ice conditions in the fjord. The continuous measurements were supplemented with intermittent krill sampling campaigns and their physical and biological environment.The krill carried out diel vertical migration (DVM) throughout the winter, regardless of the distribution of potential prey. The fjord froze over in mid-winter and the daytime distribution of a mid-water SL of krill immediately became shallower associated with snow fall after freezing, likely related to reduction of light intensities. Still, a fraction of the population always descended all the way to the bottom, so that the krill population by day seemed to inhabit waters with light levels spanning up to six orders of magnitude. Deep-living krill ascended in synchrony with the rest of the population in the afternoon, but individuals consistently reappeared in near-bottom waters already? 1 h after the ascent. Thereafter, the krill appeared to undertake asynchronous migrations, with some krill always being present in near-bottom waters even though the entire population appeared to undertake DVM. The Author 2013. Published by Oxford University Press. All rights reserved.

  19. Vertical distribution and diel vertical migration of krill beneath snow-covered ice and in ice-free waters

    Vestheim, Hege

    2013-11-11

    A bottom mounted upward looking Simrad EK60 120-kHz echo sounder was used to study scattering layers (SLs) and individuals of the krill Meganyctiphanes norvegica. The mooring was situated at 150-m depth in the Oslofjord, connected with an onshore cable for power and transmission of digitized data. Records spanned 5 months from late autumn to spring. A current meter and CTD was associated with the acoustic mooring and a shore-based webcam monitored ice conditions in the fjord. The continuous measurements were supplemented with intermittent krill sampling campaigns and their physical and biological environment.The krill carried out diel vertical migration (DVM) throughout the winter, regardless of the distribution of potential prey. The fjord froze over in mid-winter and the daytime distribution of a mid-water SL of krill immediately became shallower associated with snow fall after freezing, likely related to reduction of light intensities. Still, a fraction of the population always descended all the way to the bottom, so that the krill population by day seemed to inhabit waters with light levels spanning up to six orders of magnitude. Deep-living krill ascended in synchrony with the rest of the population in the afternoon, but individuals consistently reappeared in near-bottom waters already? 1 h after the ascent. Thereafter, the krill appeared to undertake asynchronous migrations, with some krill always being present in near-bottom waters even though the entire population appeared to undertake DVM. The Author 2013. Published by Oxford University Press. All rights reserved.

  20. Operational satellites and the global monitoring of snow and ice

    Walsh, John E.

    1991-01-01

    The altitudinal dependence of the global warming projected by global climate models is at least partially attributable to the albedo-temperature feedback involving snow and ice, which must be regarded as key variables in the monitoring for global change. Statistical analyses of data from IR and microwave sensors monitoring the areal coverage and extent of sea ice have led to mixed conclusions about recent trends of hemisphere sea ice coverage. Seasonal snow cover has been mapped for over 20 years by NOAA/NESDIS on the basis of imagery from a variety of satellite sensors. Multichannel passive microwave data show some promise for the routine monitoring of snow depth over unforested land areas.

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

    T. Maki

    2018-06-01

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

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

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

    2018-06-01

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

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

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

    2018-01-01

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

  4. NOAA's National Snow Analyses

    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

  5. Antarctic snow and global climate

    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

  6. Sentinels for snow science

    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.

  7. Impact of northern Eurasian snow cover in autumn on the warm Arctic-cold Eurasia pattern during the following January and its linkage to stationary planetary waves

    Xu, Xinping; He, Shengping; Li, Fei; Wang, Huijun

    2018-03-01

    The connection between Eurasian snow cover (SC) in autumn and Eurasian winter mean surface air temperature (SAT) has been identified by many studies. However, some recent observations indicate that early and late winter climate sometimes shows an out-of-phase relationship, suggesting that the winter mean situation might obscure the important relationships that are relevant for scientific research and applications. This study investigates the relationship between October northern Eurasian SC (NESC; 58°-68°N, 30°-90°E) and Eurasian SAT during the winter months and finds a significant relationship only exists in January. Generally, following reduced October NESC, the East Asian trough and Ural high are intensified in January, and anomalous northeasterly winds prevail in mid-latitudes, causing cold anomalies over Eurasia. Meanwhile, anomalous southwesterly winds along the northern fringe of the Ural high favor warm anomalies in the Arctic. The dynamical mechanism for the connection between NESC in October and the warm Arctic-cold Eurasia (WACE) anomaly in January is further investigated from the perspective of quasi-stationary planetary wave activity. It is found that planetary waves with zonal wavenumber-1 (ZWN1) play a dominant role in this process. Specifically, the ZWN1 pattern of planetary-scale waves concurrent with October NESC anomaly extends from the surface to the upper-stratosphere. It persists in the stratosphere through November-December and propagates downward to the surface by the following January, making the connection between October NESC and January climate possible. Additionally, the influence of October NESC on the January WACE pattern has intensified since the early-2000s.

  8. Snow Matters

    Gyimóthy, Szilvia; Jensen, Martin Trandberg

    2018-01-01

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

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

    Tao Wang

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

  10. Seasonal and inter-annual variability of aerosol optical properties during 2005-2010 over Red Mountain Pass and Impact on the Snow Cover of the San Juan Mountains

    Singh, R. P.; Gautam, R.; Painter, T. H.

    2011-12-01

    Growing body of evidence suggests the significant role of aerosol solar absorption in accelerated seasonal snowmelt in the cryosphere and elevated mountain regions via snow contamination and radiative warming processes. Characterization of aerosol optical properties over seasonal snow cover and snowpacks is therefore important towards the better understanding of aerosol radiative effects and associated impact on snow albedo. In this study, we present seasonal variations in column-integrated aerosol optical properties retrieved from AERONET sunphotometer measurements (2005-2010) at Red Mountain Pass (37.90° N, 107.72° W, 3368 msl) in the San Juan Mountains, in the vicinity of the North American Great Basin and Colorado Plateau deserts. The aerosol optical depth (AOD) measured at 500nm is generally low (pollutant transport. In addition, the possibility of the observed increased coarse-mode influence associated with mineral dust influx cannot be ruled out, due to westerly-airmass driven transport from arid/desert regions as suggested by backward trajectory simulations. A meteorological coupling is also found in the summer season between AOD and column water vapor retrieved from AERONET with co-occurring enhanced water vapor and AOD. Based on column measurements, it is difficult to ascertain the aerosol composition, however, the summer-time enhanced aerosol loading as presented here is consistent with the increased dust deposition in the San Juan mountain snow cover as reported in recent studies. In summary, this study is expected to better understand the seasonal and inter-annual aerosol column variations and is an attempt to provide an insight into the effects of aerosol solar absorption on accelerated seasonal snowmelt in the San Juan mountains.

  11. Quantifying the potential for low-level transport of black carbon emissions from cropland burning in Russia to the snow-covered Arctic.

    Hall, Joanne V.; Loboda, Tatiana V.

    2017-12-01

    Short-lived aerosols and pollutants transported from northern mid-latitudes have amplified the short term warming in the Arctic region. Among those black carbon is recognized as the second most important human emission in regards to climate forcing, behind carbon dioxide, with a total climate forcing of +1.1Wm-2. Studies have suggested that cropland burning may be a large contributor to the black carbon emissions which are directly deposited on the snow in the Arctic. However, commonly applied atmospheric transport models rely on estimates of black carbon emissions from cropland burning which are known to be highly inaccurate in both the amount and the timing of release. Instead, this study quantifies the potential for the deposition of hypothetical black carbon emissions from known cropland burning in Russia, identified by the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire detections, through low-level transport to the snow in the Arctic using wind vectors from the European Centre for Medium-Range Weather Forecasts’ ERA-Interim Reanalysis product. Our results confirm that Russian cropland burning is a potentially significant source of black carbon deposition on the Arctic snow in the spring despite the low injection heights associated with cropland burning. Approximately 10% of the observed spring (March - May) cropland active fires (7% annual) likely contribute to black carbon deposition on the Arctic snow from as far south as at least 40°N. Furthermore, our results show that potential spring black carbon emissions from cropland burning in Russia can be deposited beyond 80°N, however, the majority ( 90% - depending on injection height) of all potential spring deposition occurs below 75°N.

  12. Quantifying the Potential for Low-Level Transport of Black Carbon Emissions from Cropland Burning in Russia to the Snow-Covered Arctic

    Joanne V. Hall

    2017-12-01

    Full Text Available Short lived aerosols and pollutants transported from northern mid-latitudes have amplified the short term warming in the Arctic region. Among those black carbon is recognized as the second most important human emission in regards to climate forcing, behind carbon dioxide, with a total climate forcing of +1.1 Wm−2. Studies have suggested that cropland burning may be a large contributor to the black carbon emissions which are directly deposited on the snow in the Arctic. However, commonly applied atmospheric transport models rely on estimates of black carbon emissions from cropland burning which are known to be highly inaccurate in both the amount and the timing of release. Instead, this study quantifies the potential for the deposition of hypothetical black carbon emissions from known cropland burning in Russia, identified by the Moderate Resolution Imaging Spectroradiometer (MODIS active fire detections, through low-level transport to the snow in the Arctic using wind vectors from the European Centre for Medium-Range Weather Forecasts' ERA-Interim Reanalysis product. Our results confirm that Russian cropland burning is a potentially significant source of black carbon deposition on the Arctic snow in the spring despite the low injection heights associated with cropland burning. Approximately 10% of the observed spring (March–May cropland active fires (7% annual likely contribute to black carbon deposition on the Arctic snow from as far south as at least 40°N. Furthermore, our results show that potential spring black carbon emissions from cropland burning in Russia can be deposited beyond 80°N, however, the majority (~90%-depending on injection height of all potential spring deposition occurs below 75°N.

  13. Snow Leopard

    adult females (dimorphic); a male on average weighing between. 45–55 kg, while a .... performance of wild prey, eventually leading to a decline in their population. Research .... working towards enhancing knowledge on snow leopard ecology.

  14. Snow farming: conserving snow over the summer season

    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

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

    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.

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

    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

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

    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.

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

    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.

  19. Snow clearance

    Mauro Nonis

    2005-01-01

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

  20. Estonian Mean Snow Depth and Duration (1891-1994)

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

  1. MODIS Snow and Sea Ice Products

    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.

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

    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...

  3. Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

    Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

    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. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their

  4. Modelling stable atmospheric boundary layers over snow

    Sterk, H.A.M.

    2015-01-01

    Thesis entitled:

    Modelling Stable Atmospheric Boundary Layers over Snow

    H.A.M. Sterk

    Wageningen, 29th of April, 2015

    Summary

    The emphasis of this thesis is on the understanding and forecasting of the Stable Boundary Layer (SBL) over snow-covered surfaces. SBLs

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

    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.

  6. Snow darkening caused by black carbon emitted from fires

    Engels, Jessica; Kloster, Silvia; Bourgeois, Quentin

    2014-05-01

    We implemented the effect of snow darkening caused by black carbon (BC) emitted from forest fires into the Max Planck Institute for Meteorology Earth System Model (MPI-M ESM) to estimate its potential climate impact of present day fire occurrence. Considerable amounts of black carbon emitted from fires are transported into snow covered regions. Already very small quantities of black carbon reduce the snow reflectance, with consequences for snow melting and snow spatial coverage. Therefore, the SNICAR (SNow And Ice Radiation) model (Flanner and Zender (2005)) is implemented in the land surface component (JSBACH) of the atmospheric general circulation model ECHAM6, developed at the MPI-M. The SNICAR model includes amongst other processes a complex calculation of the snow albedo depending on black carbon in snow and snow grain growth depending on water vapor fluxes for a five layer snow scheme. For the implementation of the SNICAR model into the one layer scheme of ECHAM6-JSBACH, we used the SNICAR-online version (http://snow.engin.umich.edu). This single-layer simulator provides the albedo of snow for selectable combinations of impurity content (e.g. black carbon), snow grain size, and incident solar flux characteristics. From this scheme we derived snow albedo values for black carbon in snow concentrations ranging between 0 and 1500 ng(BC)/g(snow) and 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 required snow age is taken from the BATS (Biosphere Atmosphere Transfer Scheme, Dickinson et al. (1986)) snow albedo implementation in ECHAM6-JSBACH. Here, we will present an extended evaluation of the model including a comparison of modeled black carbon in snow concentrations to observed

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

    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.

  8. Introduction to snow rheology

    Montmollin, Vincent de

    1978-01-01

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

  9. Sublimation From Snow in Northern Environments

    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.

  10. Water and life from snow: A trillion dollar science question

    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.

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

    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.

  12. 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

    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

  13. Snow and Water: Imaging Spectroscopy for coasts and snow cover

    National Aeronautics and Space Administration — This proposal addresses the NASA Earth Science focus areas of Carbon Cycle & Ecosystems, and Water & Energy Cycle. We will develop and demonstrate a scalable...

  14. New nitrogen uptake strategy: specialized snow roots.

    Onipchenko, Vladimir G; Makarov, Mikhail I; van Logtestijn, Richard S P; Ivanov, Viktor B; Akhmetzhanova, Assem A; Tekeev, Dzhamal K; Ermak, Anton A; Salpagarova, Fatima S; Kozhevnikova, Anna D; Cornelissen, Johannes H C

    2009-08-01

    The evolution of plants has yielded a wealth of adaptations for the acquisition of key mineral nutrients. These include the structure, physiology and positioning of root systems. We report the discovery of specialized snow roots as a plant strategy to cope with the very short season for nutrient uptake and growth in alpine snow-beds, i.e. patches in the landscape that remain snow-covered well into the summer. We provide anatomical, chemical and experimental (15)N isotope tracking evidence that the Caucasian snow-bed plant Corydalis conorhiza forms extensive networks of specialized above-ground roots, which grow against gravity to acquire nitrogen directly from within snow packs. Snow roots capture nitrogen that would otherwise partly run off down-slope over a frozen surface, thereby helping to nourish these alpine ecosystems. Climate warming is changing and will change mountain snow regimes, while large-scale anthropogenic N deposition has increased snow N contents. These global changes are likely to impact on the distribution, abundance and functional significance of snow roots.

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

    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

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

    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.

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

    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.

  18. Northern Hemisphere forcing of Southern Hemisphere climate during the last deglaciation.

    He, Feng; Shakun, Jeremy D; Clark, Peter U; Carlson, Anders E; Liu, Zhengyu; Otto-Bliesner, Bette L; Kutzbach, John E

    2013-02-07

    According to the Milankovitch theory, changes in summer insolation in the high-latitude Northern Hemisphere caused glacial cycles through their impact on ice-sheet mass balance. Statistical analyses of long climate records supported this theory, but they also posed a substantial challenge by showing that changes in Southern Hemisphere climate were in phase with or led those in the north. Although an orbitally forced Northern Hemisphere signal may have been transmitted to the Southern Hemisphere, insolation forcing can also directly influence local Southern Hemisphere climate, potentially intensified by sea-ice feedback, suggesting that the hemispheres may have responded independently to different aspects of orbital forcing. Signal processing of climate records cannot distinguish between these conditions, however, because the proposed insolation forcings share essentially identical variability. Here we use transient simulations with a coupled atmosphere-ocean general circulation model to identify the impacts of forcing from changes in orbits, atmospheric CO(2) concentration, ice sheets and the Atlantic meridional overturning circulation (AMOC) on hemispheric temperatures during the first half of the last deglaciation (22-14.3 kyr BP). Although based on a single model, our transient simulation with only orbital changes supports the Milankovitch theory in showing that the last deglaciation was initiated by rising insolation during spring and summer in the mid-latitude to high-latitude Northern Hemisphere and by terrestrial snow-albedo feedback. The simulation with all forcings best reproduces the timing and magnitude of surface temperature evolution in the Southern Hemisphere in deglacial proxy records. AMOC changes associated with an orbitally induced retreat of Northern Hemisphere ice sheets is the most plausible explanation for the early Southern Hemisphere deglacial warming and its lead over Northern Hemisphere temperature; the ensuing rise in atmospheric CO(2

  19. ESA GlobSnow Snow Water Equivalent (SWE)

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

  20. Snow observations in Mount Lebanon (2011-2016)

    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

  1. Mac OS X Snow Leopard pocket guide

    Seiblod, Chris

    2009-01-01

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

  2. A distributed snow-evolution modeling system (SnowModel)

    Glen E. Liston; Kelly. Elder

    2006-01-01

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

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

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

  4. Snowscape Ecology: Linking Snow Properties to Wildlife Movements and Demography

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

    2017-12-01

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

  5. Snow snake performance monitoring.

    2008-12-01

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

  6. Modelling of snow exceedances

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

    2017-07-01

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

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

    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...

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

    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

  9. Use of machine learning techniques for modeling of snow depth

    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.

  10. Ensemble mean climatology of snow darkening effect due to deposition of dust, black carbon, and organic carbon as simulated with the NASA GEOS-5 Earth System Model

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

    2013-12-01

    The importance of the snow darkening effect (SDE) caused by solar absorbing aerosols such as dust and black carbon (BC) on climate has been discussed in previous studies. We have developed a snow darkening package for the catchment land surface model coupled to the NASA Goddard Earth Observing System, version 5 (GEOS-5), Earth System Model. Our snow darkening package includes the schemes for snow albedo and mass concentration calculations in polluted snow by dust, BC, and organic carbon (OC) depositions. The snow darkening package is currently available for seasonal snowpack over the model-defined land areas, excluding sea ice and inland of the ice sheets. The depositions of the solar absorbing aerosols are obtained from the GOCART aerosol module in the GEOS-5. Here we show the preliminary results of ensemble mean climatology (EMC) of the full SDE (i.e., dust+BC+OC). Ensemble simulations covering 10-year of 2002-2011 were carried out with the GEOS-5 including and excluding the full SDE for which each has 10 ensemble members. Shortwave radiative forcing (RF) at the top of atmosphere under all-sky condition for the 10-member EMC of the full SDE was relatively larger over Europe, Central Asia (CA), the Himalayas, the Tibetan Plateau (TP), East Asia (EA), Eastern Siberia (ES), the US, and Canadian Arctic. The RF was the strongest over the Himalayas and the TP in the northern hemisphere. The increases of surface air temperature also well correspond to the RF pattern. Larger reductions of snow water equivalent in seasonal snowpack were seen over the Himalayas, the TP, Alaska, Western Canada, and Arctic regions. We will discuss more on the day of the presentation.

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

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

    2017-03-01

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

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

    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.

  13. A comparison of Normalised Difference Snow Index (NDSI) and ...

    As an alternative, thematic cover–types based on remotely sensed data-sets are becoming popular. In this study we hypothesise that the reduced dimensionality using Principal Components Analysis (PCA) in concert Normalized Difference Snow Index (NDSI) is valuable for improving the accuracy of snow cover maps.

  14. Impact of climate change in Switzerland on socioeconomic snow indices

    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.

  15. Snow hydrology in Mediterranean mountain regions: A review

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

    2017-08-01

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

  16. Response of snow-dependent hydrologic extremes to continued global warming

    Diffenbaugh, Noah [Stanford University; Scherer, Martin [Stanford University; Ashfaq, Moetasim [ORNL

    2012-01-01

    Snow accumulation is critical for water availability in the Northern Hemisphere1,2, raising concern that global warming could have important impacts on natural and human systems in snow-dependent regions1,3. Although regional hydrologic changes have been observed (for example, refs 1,3 5), the time of emergence of extreme changes in snow accumulation and melt remains a key unknown for assessing climate- change impacts3,6,7. We find that the CMIP5 global climate model ensemble exhibits an imminent shift towards low snow years in the Northern Hemisphere, with areas of western North America, northeastern Europe and the Greater Himalaya showing the strongest emergence during the near- termdecadesandat2 Cglobalwarming.Theoccurrenceof extremely low snow years becomes widespread by the late twenty-first century, as do the occurrences of extremely high early-season snowmelt and runoff (implying increasing flood risk), and extremely low late-season snowmelt and runoff (implying increasing water stress). Our results suggest that many snow-dependent regions of the Northern Hemisphere are likely to experience increasing stress from low snow years within the next three decades, and from extreme changes in snow-dominated water resources if global warming exceeds 2 C above the pre-industrial baseline.

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

    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.

  18. Snow model design for operational purposes

    Kolberg, Sjur

    2017-04-01

    A parsimonious distributed energy balance snow model intended for operational use is evaluated using discharge, snow covered area and grain size; the latter two as observed from the MODIS sensor. The snow model is an improvement of the existing GamSnow model, which is a part of the Enki modelling framework. Core requirements for the new version have been: 1. Reduction of calibration freedom, motivated by previous experience of non-identifiable parameters in the existing version 2. Improvement of process representation based on recent advances in physically based snow modelling 3. Limiting the sensitivity to forcing data which are poorly known over the spatial domain of interest (often in mountainous areas) 4. Preference for observable states, and the ability to improve from updates. The albedo calculation is completely revised, now based on grain size through an emulation of the SNICAR model (Flanner and Zender, 2006; Gardener and Sharp, 2010). The number of calibration parameters in the albedo model is reduced from 6 to 2. The wind function governing turbulent energy fluxes has been reduced from 2 to 1 parameter. Following Raleigh et al (2011), snow surface radiant temperature is split from the top layer thermodynamic temperature, using bias-corrected wet-bulb temperature to model the former. Analyses are ongoing, and the poster will bring evaluation results from 16 years of MODIS observations and more than 25 catchments in southern Norway.

  19. Loropetalum chinense 'Snow Panda'

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

  20. SnowEx17 Cloud Absorption Radiometer BRDF V001

    National Aeronautics and Space Administration — This data set contains measurements of the bidirectional reflectance distribution function (BRDF) for two locations in Colorado, USA: Grand Mesa, a snow-covered,...

  1. Variability in snow depth time series in the Adige catchment

    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.

  2. The chemical composition of the snow in urban environment in the Far North

    Saltan N.V.; Shlapak E.P.; Zhirov V.K.; Gontar O.B.; Svyatkovskaya E.A.

    2015-01-01

    The paper presents experimental data of the chemical composition of snow cover of squares and streets in the polar cities. It has been revealed that the natural ratio of cations and anions is modified in the snow. Comparative assessment of the levels of concentration of metals in the snow showed higher values in squares than on the streets. It has been shown that the main share in the pollution of snow by heavy metals belongs to the dust of anthropogenic origin

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

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

    2009-04-01

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

  4. Natural radioactivity balance in the atmosphere of the southern hemisphere

    Lambert, G.; Ardouin, B.; Polian, G.; Sanak, J.

    1972-01-01

    It is well known that radon-222 is a radioactive rare gas, continuously produced in the soil by the disintegration of radium-226. Radon can diffuse in the soil and is outgassed into the atmosphere from the surface of the continents at the rate of about 0.7 atoms/ (cm 2 -second). Whenever the soil is covered by snow or even an iceshelf, the flux of radon becomes negligible. Surficial sea water also contains radium-226 and the oceans could release into the atmosphere a part of the produced radon. Therefore a small flux of 10 -2 atoms/(cm 2 -second) can be expected from the surface of the oceans. The radon-222 half-life of 3.8 days is long enough so that the measured radon is usually of continental origin even in the middle of any main ocean. However, below 50 0 South, it is difficult to attribute the radon to either a continental or oceanic origin. Data are presented on seasonal and altitudinal variations in radon-220, lead-210, polonium-210, and radon-222 concentrations in air samples from various locations in the Southern Hemisphere. The relation of air mass circulation in the Antartic to radioactivity in air is discussed. (U.S.)

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

    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.

  6. Snow loads in a changing climate: new risks?

    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.

  7. Ultratrace analysis for organolead compounds in Greenland snow

    Lobinski, R.; Szpunar-Lobinska, J.; Adams, F.C.

    1994-01-01

    The degradation products of tetraalkyllead compounds used as antiknock additives are unique indicators of automotive environmental pollution by lead. Recent dramatic improvements in species-specific ultrasensitive analytical procedures enabled the identification and quantification of organolead compounds in ancient Greenland snow which is considered as the archives of northern hemispheric pollution records. Organolead species determined in fresh and ancient polar snow demonstrate unambiguously the global range of petrol-related pollution not only with ionic Pb 2+ but also with more toxic metalloorganic compounds. (authors). 9 refs., 5 figs

  8. Snow model analysis.

    2014-01-01

    This study developed a new snow model and a database which warehouses geometric, weather and traffic : data on New Jersey highways. The complexity of the model development lies in considering variable road : width, different spreading/plowing pattern...

  9. Anoxia in the snow

    Bristow, Laura A.

    2018-04-01

    Substantial amounts of denitrification and other anaerobic metabolisms can occur in anoxic microenvironments within marine snow particles, according to model simulations. This microbial activity may have a global impact on nitrogen cycling.

  10. Learn Mac OS X Snow Leopard

    Meyers, Scott

    2009-01-01

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

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

    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

  12. Early results from NASA's SnowEx campaign

    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

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

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

    2017-12-01

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

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

    H.-Y. Li

    2011-07-01

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

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

    Simonetta Paloscia

    2017-01-01

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

  16. The importance of snow albedo for ice sheet evolution over the last glacial cycle

    M. Willeit

    2018-05-01

    Full Text Available The surface energy and mass balance of ice sheets strongly depends on the amount of solar radiation absorbed at the surface, which is mainly controlled by the albedo of snow and ice. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the representation of snow albedo in the model. It is well known that the albedo of snow depends strongly on snow grain size and the content of light-absorbing impurities. Excluding either the snow aging effect or the dust darkening effect on snow albedo leads to an excessive ice build-up during glacial times and consequently to a failure in simulating deglaciation. While the effect of snow grain growth on snow albedo is well constrained, the albedo reduction due to the presence of dust in snow is much more uncertain because the light-absorbing properties of dust vary widely as a function of dust mineral composition. We also show that assuming slightly different optical properties of dust leads to very different ice sheet and climate evolutions in the model. Conversely, ice sheet evolution is less sensitive to the choice of ice albedo in the model. We conclude that a proper representation of snow albedo is a fundamental prerequisite for a successful simulation of glacial cycles.

  17. Modeling the isotopic composition of Antarctic snow using backward trajectories: simulation of snow pit records

    Helsen, M.M.; van de Wal, R.S.W.; van den Broeke, M.R.; Masson-Delmotte, V.; Meijer, H.A.J.; Scheele, M.P.; Werner, M.

    2006-01-01

    The quantitative interpretation of isotope records (d18O, dD, and d excess) in ice cores can benefit from a comparison of observed meteorology with associated isotope variability. For this reason we studied four isotope records from snow pits in western Dronning Maud Land (DML), Antarctica, covering

  18. SWANN: The Snow Water Artificial Neural Network Modelling System

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

    2017-12-01

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

  19. SWEAT: Snow Water Equivalent with AlTimetry

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

    2017-04-01

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

  20. Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau

    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.

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

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

    2017-04-01

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

  2. Airborne Surveys of Snow Depth over Arctic Sea Ice

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

    2011-01-01

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

  3. A Particle Batch Smoother Approach to Snow Water Equivalent Estimation

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

    2015-01-01

    This paper presents a newly proposed data assimilation method for historical snow water equivalent SWE estimation using remotely sensed fractional snow-covered area fSCA. The newly proposed approach consists of a particle batch smoother (PBS), which is compared to a previously applied Kalman-based ensemble batch smoother (EnBS) approach. The methods were applied over the 27-yr Landsat 5 record at snow pillow and snow course in situ verification sites in the American River basin in the Sierra Nevada (United States). This basin is more densely vegetated and thus more challenging for SWE estimation than the previous applications of the EnBS. Both data assimilation methods provided significant improvement over the prior (modeling only) estimates, with both able to significantly reduce prior SWE biases. The prior RMSE values at the snow pillow and snow course sites were reduced by 68%-82% and 60%-68%, respectively, when applying the data assimilation methods. This result is encouraging for a basin like the American where the moderate to high forest cover will necessarily obscure more of the snow-covered ground surface than in previously examined, less-vegetated basins. The PBS generally outperformed the EnBS: for snow pillows the PBSRMSE was approx.54%of that seen in the EnBS, while for snow courses the PBSRMSE was approx.79%of the EnBS. Sensitivity tests show relative insensitivity for both the PBS and EnBS results to ensemble size and fSCA measurement error, but a higher sensitivity for the EnBS to the mean prior precipitation input, especially in the case where significant prior biases exist.

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

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

    2018-01-01

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

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

    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

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

    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.

  7. Pavement Snow Melting

    Lund, John W.

    2005-01-01

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

  8. Fukushima Nuclear Accident Recorded in Tibetan Plateau Snow Pits

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

    2015-01-01

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

  9. Iodine-129 in Snow and Seawater in the Antarctic: Level and Source

    Xing, Shan; Hou, Xiaolin; Aldahan, Ala

    2015-01-01

    Anthropogenic 129I has been released to the environment in different ways and chemical species by human nuclear activities since the 1940s. These sources provide ideal tools to trace the dispersion of volatile pollutants in the atmosphere. Snow and seawater samples collected in Bellingshausen...... sites in the Southern Hemisphere. This feature indicates that 129I in Antarctic snow mainly originates from atmospheric nuclear weapons testing from 1945 to 1980; resuspension and re-emission of the fallout 129I in the Southern Hemisphere maintains the 129I level in the Antarctic atmosphere. 129I...

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

    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.

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

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

    2017-12-01

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

  12. [Characteristics of mercury exchange flux between soil and atmosphere under the snow retention and snow melting control].

    Zhang, Gang; Wang, Ning; Ai, Jian-Chao; Zhang, Lei; Yang, Jing; Liu, Zi-Qi

    2013-02-01

    Jiapigou gold mine, located in the upper Songhua River, was once the largest mine in China due to gold output, where gold extraction with algamation was widely applied to extract gold resulting in severe mercury pollution to ambient environmental medium. In order to study the characteristics of mercury exchange flux between soil (snow) and atmosphere under the snow retention and snow melting control, sampling sites were selected in equal distances along the slope which is situated in the typical hill-valley terrain unit. Mercury exchange flux between soil (snow) and atmosphere was determined with the method of dynamic flux chamber and in all sampling sites the atmosphere concentration from 0 to 150 cm near to the earth in the vertical direction was measured. Furthermore, the impact factors including synchronous meteorology, the surface characteristics under the snow retention and snow melting control and the mercury concentration in vertical direction were also investigated. The results are as follows: During the period of snow retention and melting the air mercury tends to gather towards valley bottom along the slope and an obvious deposit tendency process was found from air to the earth's surface under the control of thermal inversion due to the underlying surface of cold source (snow surface). However, during the period of snow melting, mercury exchange flux between the soil and atmosphere on the surface of the earth with the snow being melted demonstrates alternative deposit and release processes. As for the earth with snow covered, the deposit level of mercury exchange flux between soil and atmosphere is lower than that during the period of snow retention. The relationship between mercury exchange flux and impact factors shows that in snow retention there is a remarkable negative linear correlation between mercury exchange flux and air mercury concentration as well as between the former and the air temperature. In addition, in snow melting mercury exchange

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

    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.

  14. Is Snow Gliding a Major Soil Erosion Agent in Steep Alpine Areas?

    Meusburger, K.; Walter, A.; Alewell, C.; Leitinger, G.; Mabit, L.; Mueller, M.H.

    2015-01-01

    Snow cover is a key hydrological characteristic of mountain areas. Nevertheless, a majority of studies focused on quantifying rates of soil erosion and sediment transport in steep mountain areas has largely neglected the role of snow cover on soil erosion rates (Stanchi et al., 2014). Soil erosion studies have focused almost exclusively on the snow-free periods even though it is well known that wet avalanches can yield enormous erosive forces (Freppaz et al., 2010; Korup and Rixen, 2014). This raises the question whether annual snow cover and particularly the slow movement of snow packages over the soil surface, termed ‘‘snow gliding’’, contribute significantly to the total soil loss in these areas. Three different approaches to estimate soil erosion rates were used to address this question. These include (1) the anthropogenic soil tracer 137 Cs, (2) the Revised Universal Soil Loss Equation (RUSLE), and (3) direct sediment yield measurements of snow glide deposits. The fallout radionuclide 137 Cs integrates total soil loss due to all erosion agents involved, the RUSLE model is suitable to estimate soil loss by water erosion and the sediment yield measurements yield represents a direct estimate of soil removal by snow gliding. Moreover, cumulative snow glide distance was measured for 14 sites and modelled for the surrounding area with the Spatial Snow Glide Model (Leitinger et al., 2008)

  15. Snow measurement by cosmic radiation; Mesure de la neige par rayonnement cosmique

    NONE

    2004-02-01

    The knowledge of the water content equivalence of the snow cover is an important element for the improvement of the water resource management. It allows in particular to evaluate and foresee the filling up supplies of big seasonal reservoirs. Electricite de France (EdF), in collaboration with the national center of scientific research (CNRS) and Meteo France, has developed a new generation of sensors, the cosmic radiation snow gauge, allowing the automatic monitoring of the status of snow stocks by the measurement of the water value of the snow cover. (J.S.)

  16. Snow-clearing operations

    EN Department

    2010-01-01

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

  17. Unilateral Hemispheric Encephalitis

    Mohan Leslie Noone

    2014-10-01

    Full Text Available A 10 year old boy presented with history of mild fever and upper respiratory symptoms followed by recurrent seizures and loss of consciousness on the next day. Normal blood counts and abnormal hepatic transaminases were noted. MRI of the brain, done on the fourth day of illness, showed extensive involvement of the cortex in the right hemisphere. Lumbar CSF was normal. The EEG showed bilateral slowing with frontal sharp wave discharges and marked attenuation over the entire right hemisphere. The patient succumbed to the illness on the ninth day. A similar pattern of acute unilateral hemispheric cortical involvement is described in the hemiconvulsion-hemiplegia-epilepsy (HHE syndrome, which is typically described to occur in children below 4 years of age. This case of fulminant acute unilateral encaphilitic illness could represent the acute phase of HHE syndrome.

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

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

    2015-12-01

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

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

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

    2017-12-01

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

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

    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

  1. Resilience to Changing Snow Depth in a Shrubland Ecosystem.

    Loik, M. E.

    2008-12-01

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

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

    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

  3. Endolithic Microbial Life in Extreme Cold Climate: Snow Is Required, but Perhaps Less Is More

    Henry J. Sun

    2013-04-01

    Full Text Available Cyanobacteria and lichens living under sandstone surfaces in the McMurdo Dry Valleys require snow for moisture. Snow accumulated beyond a thin layer, however, is counterproductive, interfering with rock insolation, snow melting, and photosynthetic access to light. With this in mind, the facts that rock slope and direction control colonization, and that climate change results in regional extinctions, can be explained. Vertical cliffs, which lack snow cover and are perpetually dry, are devoid of organisms. Boulder tops and edges can trap snow, but gravity and wind prevent excessive buildup. There, the organisms flourish. In places where snow-thinning cannot occur and snow drifts collect, rocks may contain living or dead communities. In light of these observations, the possibility of finding extraterrestrial endolithic communities on Mars cannot be eliminated.

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

    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.

  5. Snow accretion on overhead wires

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

    2005-07-01

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

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

    Vershinina, L K

    1979-01-01

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

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

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

    1979-01-01

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

  8. Temporal Changes in the Observed Relationship between Cloud Cover and Surface Air Temperature.

    Sun, Bomin; Groisman, Pavel Ya.; Bradley, Raymond S.; Keimig, Frank T.

    2000-12-01

    The relationship between cloud cover and near-surface air temperature and its decadal changes are examined using the hourly synoptic data for the past four to six decades from five regions of the Northern Hemisphere: Canada, the United States, the former Soviet Union, China, and tropical islands of the western Pacific. The authors define the normalized cloud cover-surface air temperature relationship, NOCET or dT/dCL, as a temperature anomaly with a unit (one-tenth) deviation of total cloud cover from its average value. Then mean monthly NOCET time series (night- and daytime, separately) are area-averaged and parameterized as functions of surface air humidity and snow cover. The day- and nighttime NOCET variations are strongly anticorrelated with changes in surface humidity. Furthermore, the daytime NOCET changes are positively correlated to changes in snow cover extent. The regionally averaged nighttime NOCET varies from 0.05 K tenth1 in the wet Tropics to 1.0 K tenth1 at midlatitudes in winter. The daytime regional NOCET ranges from 0.4 K tenth1 in the Tropics to 0.7 K tenth1 at midlatitudes in winter.The authors found a general strengthening of a daytime surface cooling during the post-World War II period associated with cloud cover over the United States and China, but a minor reduction of this cooling in higher latitudes. Furthermore, since the 1970s, a prominent increase in atmospheric humidity has significantly weakened the effectiveness of the surface warming (best seen at nighttime) associated with cloud cover.The authors apportion the spatiotemporal field of interactions between total cloud cover and surface air temperature into a bivariate relationship (described by two equations, one for daytime and one for nighttime) with surface air humidity and snow cover and two constant factors. These factors are invariant in space and time domains. It is speculated that they may represent empirical estimates of the overall cloud cover effect on the surface air

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

    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

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

    Andrew Gorman-Murray

    2010-03-01

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

  11. Forest influences on snow accumulation and snowmelt at the Hubbard Brook Experimental Forest, New Hampshire, USA

    Colin A. Penn; Beverley C. Wemple; John L. Campbell

    2012-01-01

    Many factors influence snow depth, water content and duration in forest ecosystems. The effects of forest cover and canopy gap geometry on snow accumulation has been well documented in coniferous forests of western North America and other regions; however, few studies have evaluated these effects on snowpack dynamics in mixed deciduous forests of the northeastern USA....

  12. Forest canopy effects on snow accumulation and ablation: an integrative review of empirical results

    Andres Varhola; Nicholas C. Coops; Markus Weiler; R. Dan Moore

    2010-01-01

    The past century has seen significant research comparing snow accumulation and ablation in forested and open sites. In this review we compile and standardize the results of previous empirical studies to generate statistical relations between changes in forest cover and the associated changes in snow accumulation and ablation rate. The analysis drew upon 33 articles...

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

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

    2016-04-01

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

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

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

    2010-09-01

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

  15. Snow and SMOW

    1967-01-01

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

  16. Field observations of the electrostatic charges of blowing snow in Hokkaido, Japan

    Omiya, S.; Sato, A.

    2011-12-01

    An electrostatic charge of blowing snow may be a contributing factor in the formation of a snow drift and a snow cornice, and changing of the trajectory of own motion. However, detailed electrification characteristics of blowing snow are not known as there are few reports of charge measurements. We carried out field observations of the electrostatic charges of blowing snow in Tobetsu, Hokkaido, Japan in the mid winter of 2011. An anemovane and a thermohygrometer were used for the meteorological observation. Charge-to-mass ratios of blowing snow were obtained by a Faraday-cage, an electrometer and an electric balance. In this observation period, the air temperature during the blowing snow event was -6.5 to -0.5 degree Celsius. The measured charges in this observation were consistent with the previous studies in sign, which is negative, but they were smaller than the previous one. In most cases, the measured values increased with the temperature decrease, which corresponds with previous studies. However, some results contradicted the tendency, and the maximum value was obtained on the day of the highest air temperature of -0.5 degree Celsius. This discrepancy may be explained from the difference of the snow surface condition on observation day. The day when the maximum value was obtained, the snow surface was covered with old snow, and hard. On the other hand, in many other cases, the snow surface was covered with the fresh snow, and soft. Blowing snow particles on the hard surface can travel longer distance than on the soft one. Therefore, it can be surmised that the hard surface makes the blowing snow particles accumulate a lot of negative charges due to a large number of collisions to the surface. This can be supported by the results of the wind tunnel experiments by Omiya and Sato (2011). By this field observation, it was newly suggested that the electrostatic charge of blowing snow are influenced greatly by the difference of the snow surface condition. REFERENCE

  17. The chemical composition of the snow in urban environment in the Far North

    Saltan N.V.

    2015-06-01

    Full Text Available The paper presents experimental data of the chemical composition of snow cover of squares and streets in the polar cities. It has been revealed that the natural ratio of cations and anions is modified in the snow. Comparative assessment of the levels of concentration of metals in the snow showed higher values in squares than on the streets. It has been shown that the main share in the pollution of snow by heavy metals belongs to the dust of anthropogenic origin

  18. Cold, Ice, and Snow Safety (For Parents)

    ... to mention a few. Plus, someone has to shovel the snow, right? Once outdoors, however, take precautions ... re going to get the family outside to shovel the snow? Fine, but take care. Snow shoveling ...

  19. Drones application on snow and ice surveys in alpine areas

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

    2015-04-01

    First results from Climate change are now clear in Europe, and in Italy in particular, with the natural disasters that damaged irreparably the territory and the habitat due to extreme meteorological events. The Directive 2007/60/EC highlight that an "effective natural hazards prevention and mitigation that requires coordination between Member States above all on natural hazards prevention" is necessary. A climate change adaptation strategy is identified on the basis of the guidelines of the European Community program 2007-2013. Following the directives provided in the financial instrument for civil protection "Union Civil Protection Mechanism" under Decision No. 1313/2013 / EU of the European Parliament and Council, a cross-cutting approach that takes into account a large number of implementation tools of EU policies is proposed as climate change adaptation strategy. In last 7 years a network of trans-Alpine area's authorities was created between Italy and Switzerland to define an adaptive strategy on climate change effects on natural enviroment based on non structural remedies. The Interreg IT - CH STRADA Project (STRategie di ADAttamento al cambiamento climatico) was born to join all the non structural remedies to climate change effects caused by snow and avalanches, on mountain sources, extreme hydrological events and to manage all transnational hydrological resources, involving all stakeholders from Italy and Switzerland. The STRADA project involved all civil protection authorities and all research centers in charge of snow, hydrology end civil protection. The Snow - meteorological center of the Regional Agency for Environment Protection (CNM of ARPA Lombardia) and the Civil Protection of Lombardy Region created a research team to develop tools for avalanche prediction and to observe and predict snow cover on Alpine area. With this aim a lot of aerial photo using Drone as been performed in unusual landscape. Results of all surveys were really interesting on a

  20. Enhancement of the MODIS Snow and Ice Product Suite Utilizing Image Segmentation

    Tilton, James C.; Hall, Dorothy K.; Riggs, George A.

    2006-01-01

    A problem has been noticed with the current NODIS Snow and Ice Product in that fringes of certain snow fields are labeled as "cloud" whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. This occurs because the current MODIS Snow and Ice Product generation algorithm relies solely on the MODIS Cloud Mask Product for the labeling of image pixels as cloud. It is proposed here that information obtained from image segmentation can be used to determine when it is appropriate to override the cloud indication from the cloud mask product. Initial tests show that this approach can significantly reduce the cloud "fringing" in modified snow cover labeling. More comprehensive testing is required to determine whether or not this approach consistently improves the accuracy of the snow and ice product.

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

    Kim, Edward

    2015-01-01

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

  2. Features of change of permanent snow patches in the Mongun-Taiga Massif, 1966–2011

    D. A. Ganyushkin

    2013-01-01

    Full Text Available The article is dedicated to perennial snow patches of Mongun-Taiga mountain massif (south-western Tuva, their morphology, present state and dynamics over the last 45 years. We created a scheme of snow patch classification with regard to genesis of relief and position on the slopes. Dynamics of snow patches is analyzed for periods between several time points – 1966 (on basis of aerial photos, 2000, 2007–2008 and 2011 (on basis of field measurements and observations. From 1966 to 2008 the number of snow patches decreased by 4 times, the total area – by 15 times, the altitudinal zone of snow patches moved 250–300 m up. In 2008–2011 the altitudinal zone of snow patches partly recovered, its lower limit moved 250 m down, periglacial snow patches recovered, a new type – snow patches of buried ice and debris-covered glaciers appeared. It could be the first face of the process of small glaciers recovery in the massif. Using the changes of the altitudinal position of snow patches in comparison with data of the closest meteorological station we estimated the amount of annual precipitation, critical for the existence of local snow patches.

  3. Inorganic carbon addition stimulates snow algae primary productivity

    Hamilton, T. L.; Havig, J. R.

    2017-12-01

    Earth has experienced glacial/interglacial oscillations throughout its history. Today over 15 million square kilometers (5.8 million square miles) of Earth's land surface is covered in ice including glaciers, ice caps, and the ice sheets of Greenland and Antarctica, most of which are retreating as a consequence of increased atmospheric CO2. Glaciers are teeming with life and supraglacial snow and ice surfaces are often red due to blooms of photoautotrophic algae. Recent evidence suggests the red pigmentation, secondary carotenoids produced in part to thrive under high irradiation, lowers albedo and accelerates melt. However, there are relatively few studies that report the productivity of snow algae communities and the parameters that constrain their growth on snow and ice surfaces. Here, we demonstrate that snow algae primary productivity can be stimulated by the addition of inorganic carbon. We found an increase in light-dependent carbon assimilation in snow algae microcosms amended with increasing amounts of inorganic carbon. Our snow algae communities were dominated by typical cosmopolitan snow algae species recovered from Alpine and Arctic environments. The climate feedbacks necessary to enter and exit glacial/interglacial oscillations are poorly understood. Evidence and models agree that global Snowball events are accompanied by changes in atmospheric CO2 with increasing CO2 necessary for entering periods of interglacial time. Our results demonstrate a positive feedback between increased CO2 and snow algal productivity and presumably growth. With the recent call for bio-albedo effects to be considered in climate models, our results underscore the need for robust climate models to include feedbacks between supraglacial primary productivity, albedo, and atmospheric CO2.

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

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

    2017-04-01

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

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

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

    2016-12-01

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

  6. Quantifying forest mortality with the remote sensing of snow

    Baker, Emily Hewitt

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

  7. Automated Snow Extent Mapping Based on Orthophoto Images from Unmanned Aerial Vehicles

    Niedzielski, Tomasz; Spallek, Waldemar; Witek-Kasprzak, Matylda

    2018-04-01

    The paper presents the application of the k-means clustering in the process of automated snow extent mapping using orthophoto images generated using the Structure-from-Motion (SfM) algorithm from oblique aerial photographs taken by unmanned aerial vehicle (UAV). A simple classification approach has been implemented to discriminate between snow-free and snow-covered terrain. The procedure uses the k-means clustering and classifies orthophoto images based on the three-dimensional space of red-green-blue (RGB) or near-infrared-red-green (NIRRG) or near-infrared-green-blue (NIRGB) bands. To test the method, several field experiments have been carried out, both in situations when snow cover was continuous and when it was patchy. The experiments have been conducted using three fixed-wing UAVs (swinglet CAM by senseFly, eBee by senseFly, and Birdie by FlyTech UAV) on 10/04/2015, 23/03/2016, and 16/03/2017 within three test sites in the Izerskie Mountains in southwestern Poland. The resulting snow extent maps, produced automatically using the classification method, have been validated against real snow extents delineated through a visual analysis and interpretation offered by human analysts. For the simplest classification setup, which assumes two classes in the k-means clustering, the extent of snow patches was estimated accurately, with areal underestimation of 4.6% (RGB) and overestimation of 5.5% (NIRGB). For continuous snow cover with sparse discontinuities at places where trees or bushes protruded from snow, the agreement between automatically produced snow extent maps and observations was better, i.e. 1.5% (underestimation with RGB) and 0.7-0.9% (overestimation, either with RGB or with NIRRG). Shadows on snow were found to be mainly responsible for the misclassification.

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

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

    2017-12-01

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

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

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

    2014-03-01

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

  10. In Situ Observations of Snow Metamorphosis Acceleration Induced by Dust and Black Carbon

    Schneider, A. M.; Flanner, M.

    2017-12-01

    Previous studies demonstrate the dependence of shortwave infrared (SWIR) reflectance on snow specific surface area (SSA) and others examine the direct darkening effect dust and black carbon (BC) deposition has on snow and ice-covered surfaces. The extent to which these light absorbing aerosols (LAAs) accelerate snow metamorphosis, however, is challenging to assess in situ as measurement techniques easily disturb snowpack. Here, we use two Near-Infrared Emitting Reflectance Domes (NERDs) to measure 1300 and 1550nm bidirectional reflectance factors (BRFs) of natural snow and experimental plots with added dust and BC. We obtain NERD measurements and subsequently collect and transport snow samples to the nearby U.S. Army Corps of Engineers' Cold Regions Research and Engineering Lab for micro computed tomography (micro-CT) analysis. Snow 1300 (1550) nm BRFs evolve from 0.6 (0.15) in fresh snow to 0.2 (0.03) after metamorphosis. Hourly-scale time evolving snow surface BRFs and SSA estimates from micro-CT reveal more rapid SWIR darkening and snow metamorphosis in contaminated versus natural plots. Cloudiness and high wind speeds can completely obscure these results if LAAs mobilize before absorbing enough radiant energy. These findings verify experimentally that dust and BC deposition can accelerate snow metamorphosis and enhance snow albedo feedback in sunny, calm weather conditions. Although quantifying the enhancement of snow albedo feedback induced by LAAs requires further surface temperature, solar irradiance, and impurity concentration measurements, this study provides experimental verification of positive feedback occurring where dust and BC accelerate snow metamorphosis.

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

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

    2016-10-01

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

  12. Desarrollo de metgis, un sistema combinado de información geográfica, meteorológica y de cobertura de nieve de alta resolución, para la región andina Development of metgis, a combined high-resolution system of geographic, meteorological and snow cover information for the andes region

    Gerald Spreitzhofer

    2006-12-01

    Shuttle Radar Topographic Mission (SRTM and representations of roads, railway lines, rivers, frontiers and cities. On top of various modes of terrain (elevation, slope, aspect, meteorological and snow information can be visualized in a variety of styles. The combined display of observations from various networks, of forecasts from numerical models like MM5 and of forecast errors will be possible. For a variety of parameters, meteorological input data may be subject to downscaling procedures using the VERA system (Vienna Enhanced Resolution Analysis. Regarding features of the system specifically related to mountain areas, the SRTM data combined with VERA allows a good estimation of areas with temperatures below zero and snow accumulation. For the future the inclusion of the Swiss model SNOWPACK is planned which provides simulations of the snow cover.

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

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

    2016-04-01

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

  14. Spectral composition of shortwave radiation reflected and deep penetrating into snow near the Barentsburg settlement (Svalbard

    P. N. Svyashchennikov

    2015-01-01

    Full Text Available Data on spectral composition of shortwave radiation that is reflected from snow and penetrates deep into the snow cover obtained near the Barentsburg settlement (Svalbard are discussed in the paper. Measurements were made by the use of the spectral radiometer TriOS Ramses within the wavelength range of 280–950 nm. The results will allow more proper taking account of the anthropogenic pollution effects on the radiative properties of snow cover under conditions of industrial activity related to the coal extraction and burning in Barentsburg.

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

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

    2007-12-01

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

  16. Relating black carbon content to reduction of snow albedo

    Brandt, R. E.; Warren, S. G.; Clarke, A. D.

    2011-12-01

    In remote snow of the Northern Hemisphere, the levels of soot pollution are in the parts-per-billion (ppb) range, where the effect on albedo is at the level of a few percent. A reduction of albedo by 1-2% is significant for climate but is difficult to detect experimentally, because snow albedo depends on several other variables. In our work to quantify the climatic effect of black carbon (BC) in snow, we therefore do not directly measure the albedo reduction. Instead, we use a two-step procedure: (1) We collect snow samples, melt and filter them, and analyze the filters spectrophotometrically for BC concentration. (2) We use the BC amount from the filter measurement, together with snow grain size, in a radiative transfer model to compute the albedo reduction. Our radiative transfer model uses the discrete ordinates algorithm DISORT 2.0. We have chosen a representative BC size distribution and optical constants, and have incorporated those of mineral dust as well. While a given mass of BC causes over an order of magnitude more snow albedo reduction compared to dust, a snowpack containing dust mutes the albedo-reducing effect of BC. Because the computed reduction of snow albedo is model-based, it requires experimental verification. We doubt that direct measurement of albedo-reduction will be feasible in nature, because of the vertical variation of both snow grain size and soot content, and because the natural soot content is small. We conclude that what is needed is an artificial snowpack, with uniform grain size and large uniform soot content (ppm not ppb), to produce a large signal on albedo. We have chosen to pursue this experiment outdoors rather than in the laboratory, for the following reasons: (1) The snowpack in the field of view is uniformly illuminated if the source of radiation is the Sun. (2) Visible radiation penetrates into the snow, so photons emerge horizontally distant from where they entered. In the limited width of a laboratory snowpack, radiation

  17. Annually resolved southern hemisphere volcanic history from two Antarctic ice cores

    Cole-Dai, Jihong; Mosley-Thompson, Ellen; Thompson, Lonnie G.

    1997-07-01

    The continuous sulfate analysis of two Antarctic ice cores, one from the Antarctic Peninsula region and one from West Antarctica, provides an annually resolved proxy history of southern semisphere volcanism since early in the 15th century. The dating is accurate within ±3 years due to the high rate of snow accumulation at both core sites and the small sample sizes used for analysis. The two sulfate records are consistent with each other. A systematic and objective method of separating outstanding sulfate events from the background sulfate flux is proposed and used to identify all volcanic signals. The resulting volcanic chronology covering 1417-1989 A.D. resolves temporal ambiguities about several recently discovered events. A number of previously unknown, moderate eruptions during late 1600s are uncovered in this chronology. The eruption of Tambora (1815) and the recently discovered eruption of Kuwae (1453) in the tropical South Pacific injected the greatest amount of sulfur dioxide into the southern hemisphere stratosphere during the last half millennium. A technique for comparing the magnitude of volcanic events preserved within different ice cores is developed using normalized sulfate flux. For the same eruptions the variability of the volcanic sulfate flux between the cores is within ±20% of the sulfate flux from the Tambora eruption.

  18. Unexpected Patterns in Snow and Dirt

    Ackerson, Bruce J.

    2018-01-01

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

  19. The Snow Data System at NASA JPL

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

    2014-12-01

    NASA JPL's Snow Data System has a data-processing pipeline powered by Apache OODT, an open source software tool. The pipeline has been running for several years and has successfully generated a significant amount of cryosphere data, including MODIS-based products such as MODSCAG, MODDRFS and MODICE, with historical and near-real time windows and covering regions such as the Artic, Western US, Alaska, Central Europe, Asia, South America, Australia and New Zealand. The team continues to improve the pipeline, using monitoring tools such as Ganglia to give an overview of operations, and improving fault-tolerance with automated recovery scripts. Several alternative adaptations of the Snow Covered Area and Grain size (SCAG) algorithm are being investigated. These include using VIIRS and Landsat TM/ETM+ satellite data as inputs. Parallel computing techniques are being considered for core SCAG processing, such as using the PyCUDA Python API to utilize multi-core GPU architectures. An experimental version of MODSCAG is also being developed for the Google Earth Engine platform, a cloud-based service.

  20. Snow and Ice Crust Changes over Northern Eurasia since 1966

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

    2009-12-01

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

  1. Realism versus simplicity in the snow routine of the HBV model

    Girons Lopez, Marc; Vis, Marc; Seibert, Jan

    2017-04-01

    The HBV model still enjoys great popularity, in part because of its simplicity. Depicting the hydrological processes in a catchment in a simple way reduces data requirements and minimises parameter uncertainty. However, the representation of some processes might benefit from an increased model complexity. This is, for instance, the case of snow routine in the HBV-light version of the HBV model. HBV-light uses a degree-day method with a single threshold parameter to distinguish between rain and snow and simulate snow melt. Recent research has shown that hydrological models with a more realistic representation of snow processes might be more successful in estimating runoff. In this study we explore and test different improvements to the HBV-light snow routine design by considering different threshold temperature values for rain and snow distinction as well as for the beginning of snow melt, and introducing gradual transitions instead of the current sharp threshold. The use of radiation data, which recently became available as gridded data product in Switzerland, is an additional possibility. These modifications would allow for a more realistic depiction of important hydrological processes in alpine and other snow-covered areas while preserving the characteristic simplicity of HBV. Furthermore, in this contribution we evaluate the balance between introducing more realism into the snow routine of the HBV model and keeping the number of parameters as low as possible.

  2. Putting humans in the loop: Using crowdsourced snow information to inform water management

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

    2016-04-01

    The unprecedented availability of user generated data on the Web due to the advent of online services, social networks, and crowdsourcing, is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatio-temporally dense, possibly contributing to our ability of making better decisions. In this work, we contribute a novel crowdsourcing procedure for computing virtual snow indexes from public web images, either produced by users or generated by touristic webcams, which is based on a complex architecture designed for automatically crawling content from multiple web data sources. The procedure retains only geo-tagged images containing a mountain skyline, identifies the visible peaks in each image using a public online digital terrain model, and classifies the mountain image pixels as snow or no-snow. This operation yields a snow mask per image, from which it is possible to extract time series of virtual snow indexes representing a proxy of the snow covered area. The value of the obtained virtual snow indexes is estimated in a real world water management problem. We consider the snow-dominated catchment of Lake Como, a regulated lake in Northern Italy, where snowmelt represents the most important contribution to seasonal lake storage, and we used the virtual snow indexes for informing the daily operation of the lake's dam. Numerical results show that such information is effective in extending the anticipation capacity of the lake operations, ultimately improving the system performance.

  3. Role of nitrite in the photochemical formation of radicals in the snow.

    Jacobi, Hans-Werner; Kleffmann, Jörg; Villena, Guillermo; Wiesen, Peter; King, Martin; France, James; Anastasio, Cort; Staebler, Ralf

    2014-01-01

    Photochemical reactions in snow can have an important impact on the composition of the atmosphere over snow-covered areas as well as on the composition of the snow itself. One of the major photochemical processes is the photolysis of nitrate leading to the formation of volatile nitrogen compounds. We report nitrite concentrations determined together with nitrate and hydrogen peroxide in surface snow collected at the coastal site of Barrow, Alaska. The results demonstrate that nitrite likely plays a significant role as a precursor for reactive hydroxyl radicals as well as volatile nitrogen oxides in the snow. Pollution events leading to high concentrations of nitrous acid in the atmosphere contributed to an observed increase in nitrite in the surface snow layer during nighttime. Observed daytime nitrite concentrations are much higher than values predicted from steady-state concentrations based on photolysis of nitrate and nitrite indicating that we do not fully understand the production of nitrite and nitrous acid in snow. The discrepancy between observed and expected nitrite concentrations is probably due to a combination of factors, including an incomplete understanding of the reactive environment and chemical processes in snow, and a lack of consideration of the vertical structure of snow.

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

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

    2017-12-01

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

  5. LGM permafrost thickness and extent in the Northern Hemisphere derived from the earth system model iLOVECLIM

    Kitover, D.C.; van Balen, R.T.; Vandenberghe, J.F.; Roche, D.M.V.A.P.; Renssen, H.

    2016-01-01

    An estimate of permafrost extent and thickness in the northern hemisphere during the Last Glacial Maximum (LGM, ~ 21 ka) has been produced using the VU University Amsterdam Permafrost Snow (VAMPERS) model, forced by iLOVECLIM, an Earth System Model of Intermediate Complexity. We present model

  6. Assessment of Snow Status Changes Using L-HH Temporal-Coherence Components at Mt. Dagu, China

    Yong Wang

    2015-09-01

    Full Text Available Multitemporal Phased Array type L-band Synthetic Aperture Radar (PALSAR horizontally transmitted and horizontally received (HH coherence data was decomposed into temporal-coherence, spatial-coherence, and thermal noise components. The multitemporal data spanned between February and May of 2008, and consisted of two pairs of interferometric SAR (InSAR images formed by consecutive repeat passes. With the analysis of ancillary data, a snow increase process and a snow decrease process were determined. Then, the multiple temporal-coherence components were used to study the variation of thawing and freezing statuses of snow because the components can mostly reflect the temporal change of the snow that occurred between two data acquisitions. Compared with snow mapping results derived from optical images, the outcomes from the snow increase process and the snow decrease process reached an overall accuracy of 71.3% and 79.5%, respectively. Being capable of delineating not only the areas with or without snow cover but also status changes among no-snow, wet snow, and dry snow, we have developed a critical means to assess the water resource in alpine areas.

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

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

    2013-06-01

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

  8. Detonation in TATB Hemispheres

    Druce, B; Souers, P C; Chow, C; Roeske, F; Vitello, P; Hrousis, C

    2004-03-17

    Streak camera breakout and Fabry-Perot interferometer data have been taken on the outer surface of 1.80 g/cm{sup 3} TATB hemispherical boosters initiated by slapper detonators at three temperatures. The slapper causes breakout to occur at 54{sup o} at ambient temperatures and 42{sup o} at -54 C, where the axis of rotation is 0{sup o}. The Fabry velocities may be associated with pressures, and these decrease for large timing delays in breakout seen at the colder temperatures. At room temperature, the Fabry pressures appear constant at all angles. Both fresh and decade-old explosive are tested and no difference is seen. The problem has been modeled with reactive flow. Adjustment of the JWL for temperature makes little difference, but cooling to -54 C decreases the rate constant by 1/6th. The problem was run both at constant density and with density differences using two different codes. The ambient code results show that a density difference is probably there but it cannot be quantified.

  9. Detonation in TATB hemispheres

    Druce, Robert L.; Souers, P. Clark; Chow, Charles; Roeske, Franklin; Vitello, Peter; Hrousis, Constantine [Lawrence Livermore National Laboratory, Livermore, CA, 94550 (United States)

    2005-04-01

    Streak camera breakout and Fabry-Perot interferometer data have been taken on the outer surface of 1.80 g/cm{sup 3} TATB (triamino-trinitrobenzene) hemispherical boosters initiated by slapper detonators at three temperatures. The slapper causes breakout to occur at 54 at ambient temperatures and 42 at -54 C, where the axis of rotation is 0 . The Fabry velocities may be associated with pressures, and these decrease for large timing delays in breakout seen at the colder temperatures. At room temperature, the Fabry pressures appear constant at all angles. Both fresh and decade-old explosive are tested and no difference is seen. The problem has been modeled with reactive flow. Adjustment of the JWL for temperature makes little difference, but cooling to -54 C decreases the rate constant by 1/6th. The problem was run both at constant density and with density differences using two different codes. The ambient code results show that a density difference is probably present, but it cannot be quantified. (Abstract Copyright [2005], Wiley Periodicals, Inc.)

  10. Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer

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

    2003-01-01

    Snow and sea ice products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, flown on the Terra and Aqua satellites, are or will be available through the National Snow and Ice Data Center Distributed Active Archive Center (DAAC). The algorithms that produce the products are automated, thus providing a consistent global data set that is suitable for climate studies. The suite of MODIS snow products begins with a 500-m resolution, 2330-km swath snow-cover map that is then projected onto a sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to daily and 8-day composite climate-modeling grid (CMG) products at 0.05 resolution. A daily snow albedo product will be available in early 2003 as a beta test product. The sequence of sea ice products begins with a swath product at 1-km resolution that provides sea ice extent and ice-surface temperature (IST). The sea ice swath products are then mapped onto the Lambert azimuthal equal area or EASE-Grid projection to create a daily and 8-day composite sea ice tile product, also at 1 -km resolution. Climate-Modeling Grid (CMG) sea ice products in the EASE-Grid projection at 4-km resolution are planned for early 2003.

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

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

    2013-12-01

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

  12. The Evolution of Northern Hemisphere Glaciation

    Wright, J. D.

    2001-05-01

    For much of the last 50 million years, high-latitude regions remained too warm to allow snow to accumulate and form ice sheets. Shackleton et al. (1984) published a landmark paper correlating the first occurrence of ice-rafted detritus (IRD) observed at Rockall Plateau with a prominent increase in benthic foraminiferal d18O values during the late Pliocene. These late Pliocene to Pleistocene ice sheets were modulated on an orbital frequency and have characterized the global climate over the past 2.6 myr (Shackleton and Opdyke, 1973; Shackleton et al., 1984; Ruddiman, et al., 1986). During the early Pliocene, northern hemisphere glaciation (NHG) variations were less significant (Jansen et al., 1993). Our understanding of the Plio-Pleistocene ice sheet cycles can be viewed from two different perspectives. When viewed from the late Pleistocene, the fundamental question is what changed near the early/late Pliocene boundary to produce the large-scale, glacial-interglacial cycles of the past 2.6 Ma. In contrast, the view from the middle to late Miocene is quite different. Since the pioneering work of Shackleton et al. (1984), the record of NHG has been extended further back in time with drilling in the Norwegian Sea (ODP Leg 104). At Sites 642 and 644, IRD was found throughout the late Miocene and back to ~12 Ma. More recent drilling in the high northern latitudes occurred on ODP Leg 151. Site 909 recovered a middle Miocene section from the Fram Straits with rounded quartz grains that were interpreted as IRD (Wolf-Welling et al., 1996). Age estimates for those sediments place the first northern hemisphere ice sheets at least as old as 14 Ma. The occurrence of sand-sized particles (>1000 μm) and coal below this level indicates the possibility of glacial activity in the Northern Hemisphere as early as 16 Ma. Thus, the late Pliocene to Pleistocene cycles appear to be the resumption of the glacial-interglacial pattern that began during the Miocene. While the Miocene ice

  13. Estimation of snow albedo reduction by light absorbing impurities using Monte Carlo radiative transfer model

    Sengupta, D.; Gao, L.; Wilcox, E. M.; Beres, N. D.; Moosmüller, H.; Khlystov, A.

    2017-12-01

    Radiative forcing and climate change greatly depends on earth's surface albedo and its temporal and spatial variation. The surface albedo varies greatly depending on the surface characteristics ranging from 5-10% for calm ocean waters to 80% for some snow-covered areas. Clean and fresh snow surfaces have the highest albedo and are most sensitive to contamination with light absorbing impurities that can greatly reduce surface albedo and change overall radiative forcing estimates. Accurate estimation of snow albedo as well as understanding of feedbacks on climate from changes in snow-covered areas is important for radiative forcing, snow energy balance, predicting seasonal snowmelt, and run off rates. Such information is essential to inform timely decision making of stakeholders and policy makers. Light absorbing particles deposited onto the snow surface can greatly alter snow albedo and have been identified as a major contributor to regional climate forcing if seasonal snow cover is involved. However, uncertainty associated with quantification of albedo reduction by these light absorbing particles is high. Here, we use Mie theory (under the assumption of spherical snow grains) to reconstruct the single scattering parameters of snow (i.e., single scattering albedo ῶ and asymmetry parameter g) from observation-based size distribution information and retrieved refractive index values. The single scattering parameters of impurities are extracted with the same approach from datasets obtained during laboratory combustion of biomass samples. Instead of using plane-parallel approximation methods to account for multiple scattering, we have used the simple "Monte Carlo ray/photon tracing approach" to calculate the snow albedo. This simple approach considers multiple scattering to be the "collection" of single scattering events. Using this approach, we vary the effective snow grain size and impurity concentrations to explore the evolution of snow albedo over a wide

  14. Ku-Band radar penetration into Snow over Arctic Sea Ice

    Hendricks, Stefan; Stenseng, Lars; Helm, Veit

    is the snow/air interface, whereas radar waves interact with the variable physical properties of the snow cover on the Arctic sea ice. In addition, radar elevation measurements may vary for different retracker algorithms, which determine the track point of the scattered echo power distribution. Since accurate...... knowledge of the reflection horizon is critical for sea ice thickness retrieval, validation data is necessary to investigate the penetration of radar waves into the snow for the upcoming CryoSat-2 mission. Furthermore, the combination of both optical and RF wavelengths might be used to derive snow thickness......, if radar altimeters are capable of measuring the distance to the snow-ice interface reliably. We present the results of aircraft campaigns in the Arctic with a scanning laser altimeter and the Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) of the European Space Agency. The elevation...

  15. The Potential for Snow to Supply Human Water Demand in the Present and Future

    Mankin, Justin S.; Viviroli, Daniel; Singh, Deepti; Hoekstra, Arjen Y.; Diffenbaugh, Noah S.

    2015-01-01

    Runoff from snowmelt is regarded as a vital water source for people and ecosystems throughout the Northern Hemisphere (NH). Numerous studies point to the threat global warming poses to the timing and magnitude of snow accumulation and melt. But analyses focused on snow supply do not show where changes to snowmelt runoff are likely to present the most pressing adaptation challenges, given sub-annual patterns of human water consumption and water availability from rainfall. We identify the NH basins where present spring and summer snowmelt has the greatest potential to supply the human water demand that would otherwise be unmet by instantaneous rainfall runoff. Using a multi-model ensemble of climate change projections, we find that these basins - which together have a present population of approx. 2 billion people - are exposed to a 67% risk of decreased snow supply this coming century. Further, in the multi-model mean, 68 basins (with a present population of more than 300 million people) transition from having sufficient rainfall runoff to meet all present human water demand to having insufficient rainfall runoff. However, internal climate variability creates irreducible uncertainty in the projected future trends in snow resource potential, with about 90% of snow-sensitive basins showing potential for either increases or decreases over the near-term decades. Our results emphasize the importance of snow for fulfilling human water demand in many NH basins, and highlight the need to account for the full range of internal climate variability in developing robust climate risk management decisions.

  16. Data Fusion of Gridded Snow Products Enhanced with Terrain Covariates and a Simple Snow Model

    Snauffer, A. M.; Hsieh, W. W.; Cannon, A. J.

    2017-12-01

    Hydrologic planning requires accurate estimates of regional snow water equivalent (SWE), particularly areas with hydrologic regimes dominated by spring melt. While numerous gridded data products provide such estimates, accurate representations are particularly challenging under conditions of mountainous terrain, heavy forest cover and large snow accumulations, contexts which in many ways define the province of British Columbia (BC), Canada. One promising avenue of improving SWE estimates is a data fusion approach which combines field observations with gridded SWE products and relevant covariates. A base artificial neural network (ANN) was constructed using three of the best performing gridded SWE products over BC (ERA-Interim/Land, MERRA and GLDAS-2) and simple location and time covariates. This base ANN was then enhanced to include terrain covariates (slope, aspect and Terrain Roughness Index, TRI) as well as a simple 1-layer energy balance snow model driven by gridded bias-corrected ANUSPLIN temperature and precipitation values. The ANN enhanced with all aforementioned covariates performed better than the base ANN, but most of the skill improvement was attributable to the snow model with very little contribution from the terrain covariates. The enhanced ANN improved station mean absolute error (MAE) by an average of 53% relative to the composing gridded products over the province. Interannual peak SWE correlation coefficient was found to be 0.78, an improvement of 0.05 to 0.18 over the composing products. This nonlinear approach outperformed a comparable multiple linear regression (MLR) model by 22% in MAE and 0.04 in interannual correlation. The enhanced ANN has also been shown to estimate better than the Variable Infiltration Capacity (VIC) hydrologic model calibrated and run for four BC watersheds, improving MAE by 22% and correlation by 0.05. The performance improvements of the enhanced ANN are statistically significant at the 5% level across the province and

  17. A webgis supported snow information system with long time satellite data for Turkey

    Surer, S.; Bolat, K.; Akyurek, Z.

    2012-04-01

    KARBILSIS is an online platform which is developed in order to provide end-users with daily remote sensing snow products for Turkey (www.karbilsis.com). The project has been started as a research activity after an award by Ministry of Science and Technology has been granted to our company. At the first stage of our project MODIS atmospherically corrected reflectance data has been downloaded covering the period of 2000-2011 which makes more than ten years of satellite imagery for Turkey. The archived MODIS data that have been obtained from National Snow and Ice Data Center (NSIDC) is mainly MOD09GA product that includes seven spectral bands. Only the tiles which are covering Turkey have been archived namely 19&20 horizontal and 4&5 vertical ones. In order to provide scientists with a website giving the availability of analysis of snow covered area for long terms based on their area of interests, a fractional snow extent (FSE) product has been generated. For FSE product a normalized difference snow index (NDSI) based algorithm has been developed using daily land surface reflectance values (MOD09GA). In addition to MODIS data, four different Landsat images belonging to different days of snowy period (January, March, and May) have been used during algorithm development taking into account a better representation of different reflectance values of snow which highly varies depending on the accumulation and melting periods. Landsat images were used as reference images. First the Landsat images were orthorectified and mapped to a cartographic projection. Then image segmentation was applied to obtain homogeneous tiles, where the homogeneity is defined as similarity in pixel values. The mean-shift segmentation approach, where each pixel was associated with a significant mode of the joint domain density located in its neighborhood, was applied. After segmentation, the image was classified into snow and no-snow classes with Maximum Likelihood Classification Method. FSE

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

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

    2013-12-01

    The climate and hydroclimate of the Western US and Alaska are tightly coupled to their snow and ice cover. The Western US depends on mountain snowmelt for the majority of its water supply to agriculture, industrial and urban use, hydroelectric generation, and recreation, all driven by increasing population and demand. Alaskan snow and glacier cover modulate regional climate and, as with the Western US, dominate water supply and hydroelectric generation in much of the state. Projections of climate change in the Western US and Alaska suggest that the most pronounced impacts will include reductions of mountain snow and ice cover, earlier runoff, and a greater fraction of rain instead of snow. We establish a snow and ice climatology of the Western US and Alaska using physically based MODIS Snow Covered Area and Grain size model (MODSCAG) for fractional snow cover, the MODIS Dust Radiative Forcing in Snow model (MODDRFS) for radiative forcing by light absorbing impurities in snow, and the MODIS Permanent Ice model (MODICE) for annual minimum exposed snow. MODSCAG and MODDRFS use EOS MOD09GA historical reflectance data (2000-2012) to provide daily and 8-day composites and near real time products since the beginning of 2013, themselves ultimately composited to 8-day products. The compositing method considers sensor-viewing geometry, solar illumination, clouds, cloud shadows, aerosols and noisy detectors in order to select the best pixel for an 8-day period. The MODICE annual minimum exposed snow and ice product uses the daily time series of fractional snow and ice from MODSCAG to generate annual maps. With this project we have established an ongoing, national-scale, consistent and replicable approach to assessing current and projected climate impacts and climate-related risk in the context of other stressors. We analyze the products in the Northwest, Southwest, and Alaska/Arctic regions of the National Climate Assessment for the last decade, the nation's hottest on record

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

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

    2015-12-01

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

  20. Land Cover

    Kansas Data Access and Support Center — The Land Cover database depicts 10 general land cover classes for the State of Kansas. The database was compiled from a digital classification of Landsat Thematic...

  1. PHASE RELATIONSHIPS OF SOLAR HEMISPHERIC TOROIDAL AND POLOIDAL CYCLES

    Muraközy, J., E-mail: murakozy.judit@csfk.mta.hu [Debrecen Heliophysical Observatory (DHO), Konkoly Observatory, Research Centre for Astronomy and Earth Sciences H-4010 Debrecen P.O.B. 30, H-4010 (Hungary)

    2016-08-01

    The solar northern and southern hemispheres exhibit differences in their intensities and time profiles of the activity cycles. The time variation of these properties was studied in a previous article covering the data from Cycles 12–23. The hemispheric phase lags exhibited a characteristic variation: the leading role was exchanged between hemispheres every four cycles. The present work extends the investigation of this variation using the data of Staudacher and Schwabe in Cycles 1–4 and 7–10 as well as Spörer’s data in Cycle 11. The previously observed variation cannot be clearly recognized using the data of Staudacher, Schwabe, and Spörer. However, it is more interesting that the phase lags of the reversals of the magnetic fields at the poles follow the same variations as those of the hemispheric cycles in Cycles 12–23, i.e., one of the hemispheres leads in four cyles and the leading role jumps to the opposite hemisphere in the next four cycles. This means that this variation is a long-term property of the entire solar dynamo mechanism, for both the toroidal and poloidal fields, which hints at an unidentified component of the process responsible for the long-term memory.

  2. Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

    Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; Berg, Larry K.; Fast, Jerome D.; Easter, Richard C.; Shrivastava, Manish; Thomas, Jennie L.

    2017-10-01

    In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain-Fritsch + Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.

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

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

    2016-12-01

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

  4. Metagenomic and satellite analyses of red snow in the Russian Arctic

    Nao Hisakawa

    2015-12-01

    Full Text Available Cryophilic algae thrive in liquid water within snow and ice in alpine and polar regions worldwide. Blooms of these algae lower albedo (reflection of sunlight, thereby altering melting patterns (Kohshima, Seko & Yoshimura, 1993; Lutz et al., 2014; Thomas & Duval, 1995. Here metagenomic DNA analysis and satellite imaging were used to investigate red snow in Franz Josef Land in the Russian Arctic. Franz Josef Land red snow metagenomes confirmed that the communities are composed of the autotroph Chlamydomonas nivalis that is supporting a complex viral and heterotrophic bacterial community. Comparisons with white snow communities from other sites suggest that white snow and ice are initially colonized by fungal-dominated communities and then succeeded by the more complex C. nivalis-heterotroph red snow. Satellite image analysis showed that red snow covers up to 80% of the surface of snow and ice fields in Franz Josef Land and globally. Together these results show that C. nivalis supports a local food web that is on the rise as temperatures warm, with potential widespread impacts on alpine and polar environments worldwide.

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

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

    2017-12-01

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

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

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

    2016-12-01

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

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

    L. P. Golobokova

    2012-01-01

    Full Text Available The paper presents data on chemical composition of snow in theAntarcticasampled along the first tractor traverse during the 53th Russian Antarctic Expedition from Station Progress (the sea coast to Station Vostok (1,276 kmfrom Progress. Specific features of horizontal and depth distribution of chemical components in snow revealed differ