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Search Results: 1 - 10 of 398 matches for " snow "
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Relationship between the Concentration of Impurity and Albedo in Snow Surface  [PDF]
Yuki Komuro, Toshitaka Suzuki
Atmospheric and Climate Sciences (ACS) , 2015, DOI: 10.4236/acs.2015.54034
Abstract: Recent decline of cryosphere typified by retreat of glaciers is often explained by temperature rise due to global warming. However, the existence of glaciers shrinking since before 1950s warming accelerated suggested that decline of cryosphere may be due to not only temperature rise, but also another possibility. As a possible cause of snow and ice melting, it has been pointed out that the surface albedo reduction due to increase of snow impurity, aeolian dust and anthropogenic pollutant, for example. To clarify the quantitative relationship between albedo and impurity in snow surface, we investigated the correlativity of turbidity and metal concentration in snow to the snow surface albedo from the simultaneous observations on the snow-covered area in Yamagata, Japan. The observed albedo shows a tendency of decrease with the turbidity increase in snow surface, we could find strong correlation between the albedo and the turbidity in 76% of contribution factor using logarithmic regression analysis. The relationship of albedo to total concentration of Fe and Al in snow surface shows the similar tendency to turbidity, we could model the relationship using logarithmic equation with high value of contribution ratio, 74% and 66%, respectively. The concentration ratio of Fe/Al is nearly constant with about 0.75, which is close to mean crustal ratio of both elements, therefore, it can be said there is a strong correlation between the albedo and the concentration of mineral particle in snow surface. We cannot find a significant correlation between the albedo and total concentration of Na in snow surface. It can be considered that Na existed as dissolved ion has not significant effect to the albedo in snow surface. These results indicate that the snow albedo correlates strongly with the particulate matter in snow surface, which is typified by mineral particle.
Snow Cover Area Estimation Using Radar and Optical Satellite Information  [PDF]
Ana Paula Salcedo, Marisa G. Cogliati
Atmospheric and Climate Sciences (ACS) , 2014, DOI: 10.4236/acs.2014.44047
Abstract: Obtaining the seasonal variation of snow cover in areas of the Argentinian Andes is important for hydrological studies and can facilitate proper planning of water resources, with regard to irrigation, supply, flood attenuation and hydroelectricity. Remote sensors that work in the visible and infrared wavelength range are operational tools for monitoring the snow in clear skies. However, microwave satellites are able to obtain data regardless of atmospheric conditions. The advantage of using radar images is that they are very useful to obtain highly accurate parameters such as snow moisture depth, density and water equivalent resulting in improved forecasting models. In this paper, we analyze an ERS-2 image of the Andes mountain range in the northern region of the Neuquén province, Patagonia, Argentina. The objective was to obtain the spatial distribution of wet and dry snow and to compare these results with data from optical sensors (LANDSAT) in order to understand the topographic variables that influence the spatial distribution of wet snow. Optical information from sensors like LANDSAT TM 5 was analyzed to obtain fractional and binary snow indexes during a passage simultaneously with radar data. Surface temperature is used to study the association between the different types of snow altitudinal ranges and surface temperature. In this paper, we selected a scene on October 8th 2005. The entire methodology was systematized in a code implemented in IDL language.
Estimation of Melt Contribution to Total Streamflow in River Bhagirathi and River DhauliGanga at Loharinag Pala and Tapovan Vishnugad Project Sites  [PDF]
Manohar Arora, D S Rathore, R D Singh, Rakesh Kumar, Amit Kumar
Journal of Water Resource and Protection (JWARP) , 2010, DOI: 10.4236/jwarp.2010.27073
Abstract: Many of the major rivers in India originate from the Himalayas. These rivers have significant contribution from snow and ice which makes these rivers perennial. Due to steep slopes, all such streams have potential sites for hydropower generation. There is a requirement of estimation of the contribution from snow and glacier melt, rainfall contribution and sub surface contribution in the total runoff for sustainable supply of water to the hydropower plants. Considering this aspects, in this study a snowmelt runoff simulation model SNOWMOD suitable for Himalayan basins developed earlier has been modified and applied for simulation of flows. Input to the model such as glacier cover, permanent snow cover, seasonal snow cover generated through remote sensing techniques were used in conjunction with daily maximum and minimum temperature, rainfall and discharge. Two hydropower dam sites on major tributaries (Bhagirathi and DhauliGanga) of River Ganga have been selected for determination of different runoff components. However, though the data available was for a very limited period but the results indicate that these tributaries have significant contribution from snow and ice for long term sustainability of flows to these schemes.
Snow Cover Detection Based on Visible Red and Blue Channel from MODIS Imagery Data  [PDF]
Paipai Pan, Guoyue Chen, Kazuki Saruta, Yuki Terata
International Journal of Geosciences (IJG) , 2015, DOI: 10.4236/ijg.2015.61004
Abstract: In the present work, a new snow cover detection method based on visible red and blue bands from MODIS imagery data is proposed for Akita prefecture under the sunny cloud-free conditions. Before the snow cover detection, the MODIS imagery of the study area is pre-processed by geographic correction, clipping, atmospheric correction and topographic correction. Snow cover detection is carried out by applying the reflectance similarities of snow and other substances in the visible red band 1 and blue band 3. Then, the threshold values are confirmed to distinguish snow pixels from other substances by analyzing the composited true color images and 2-dimensional scatter plots. The MOD10_L2 products andin-situsnow depth data from 31 observation stations across the whole study area are chosen to compare and validate the effectivity of proposed method for snow cover detection. We calculate the overall accuracy, over-estimation error and under-estimation error of snow cover detection during the snowy season from May 2012 to April 2014, and the results are compared by classifying all of the observation stations into forest areas, basin areas and plain areas. It proves that the snow cover can be detected effectively in Akita prefecture by the proposed method. And the average overall accuracy of proposed method is higher than MOD10_L2 product, improved by 26.27%. The proposed method is expected to improve the environment management and agricultural development for local residents.
Fractional Snow/Non-Snow Cover Mapping through Incorporation of Thermal Band in Snow Index Design  [PDF]
B. C. Yadav, Kamal Jain
International Journal of Geosciences (IJG) , 2017, DOI: 10.4236/ijg.2017.811082
Substantial development has been achieved in snow cover delineations through binary mapping techniques. Continuous efforts for development and institution of methodologies in fractional snow cover mapping are steadily conducted by the research communities. In this work, the attempts are driven towards the attainment of the same. MODIS (Moderate Resolution Imaging Spectroradiometer) images are worked upon Landsat 8 images under multivariate polynomial regression schemes utilizing corresponding count of pixels in a test region of Himachal Pradesh. 11.00 μm centered waveband is employed to develop a scheme for snow mapping followed by a qualitative and quantitative comparison with NDSI and S3 snow index where the values of correlation coefficient between fractional snow cover and index values have been obtained as 77.04%, 78.82% and 85.15% for NDSI, S3 and our scheme respectively. Exponential empirical relationships have been tried to be employed to attain improvements in prediction of snow cover followed by a test of correlation between true and theoretical fractional snow cover values. An improvement in degree of correlation is obtained over the conventional methodologies which serves for the verification of scheme employed and empirical relationship defined, collectively. The results provide a scope for improvements and investigations in the subject of fractional snow cover mapping.
Snow Cover Maps from MODIS Images at 250 m Resolution, Part 2: Validation
Claudia Notarnicola,Martial Duguay,Nico Moelg,Thomas Schellenberger,Anke Tetzlaff,Roberto Monsorno,Armin Costa,Christian Steurer,Marc Zebisch
Remote Sensing , 2013, DOI: 10.3390/rs5041568
Abstract: 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.
Remote Sensing, Model-Derived and Ground Measurements of Snow Water Equivalent and Snow Density in Alaska  [PDF]
Reginald R. Muskett
International Journal of Geosciences (IJG) , 2012, DOI: 10.4236/ijg.2012.35114
Abstract: Snow water equivalent (SWE) is important for investigations of annual to decadal-scale changes in Arctic environment and energy-water cycles. Passive microwave satellite-based retrieval algorithm estimates of SWE now span more than three decades. SWE retrievals by the Advanced Microwave Scanning Radiometer for the Earth Observation System (AMSR-E) onboard the NASA-Aqua satellite ended at October 2011. A critical parameter in the AMSR-E retrieval algorithm is snow density assumed from surveys in Canada and Russia from 1940s-1990s. We compare ground SWE measurements in Alaska to those of AMSR-E, European Space Agency GlobSnow, and GIPL model. AMSR-E SWE underperforms (is less than on average) ground SWE measurements in Alaska through 2011. Snow density measurements along the Alaska permafrost transect in April 2009 and 2010 show a significant latitude-gradient in snow density increasing to the Arctic coast at Prudhoe Bay. Large differences are apparent in comparisons of our measured mean snow densities on a same snow cover class basis March-April 2009-2011 Alaska to those measured in Alaska winter 1989-1992 and Canadian March-April 1961-1990. Snow density like other properties of snow is an indicator of climate and a non-stationary variable of SWE.
Significant Variations of Surface Albedo during a Snowy Period at Xianghe Observatory, China

YU Yu,CHEN Hongbin,XIA Xiangao,XUAN Yuejian,YU Ke,

大气科学进展 , 2010,
Abstract: Surface albedo over typical types of surfaces in the North China Plain was observed using a Multi-field Albedo Observation System before and after several snowfalls from 13 to 27 February 2005.Dramatic variations of the surface albedos of bare land,a frozen pond,and withered grassland during that period were analyzed.Under cloudy sky,the mean surface albedo of bare land was about 0.23,but it immediately rose to 0.85 when the surface was covered by fresh snow.The albedo decreased gradually to normal levels a...
Snow Cover Maps from MODIS Images at 250 m Resolution, Part 1: Algorithm Description
Claudia Notarnicola,Martial Duguay,Nico Moelg,Thomas Schellenberger,Anke Tetzlaff,Roberto Monsorno,Armin Costa,Christian Steurer,Marc Zebisch
Remote Sensing , 2013, DOI: 10.3390/rs5010110
Abstract: A new algorithm for snow cover monitoring at 250 m resolution based on Moderate Resolution Imaging Spectroradiometer (MODIS) images is presented. In contrast to the 500 m resolution MODIS snow products of NASA (MOD10 and MYD10), the main goal was to maintain the resolution as high as possible to allow for a more accurate detection of snow covered area (SCA). This is especially important in mountainous regions characterized by extreme landscape heterogeneity, where maps at a resolution of 500 m could not provide the desired amount of spatial details. Therefore, the algorithm exploits only the 250 m resolution bands of MODIS in the red?(B1) and infrared (B2) spectrum, as well as the Normalized Difference Vegetation Index?(NDVI) for snow detection, while clouds are classified using also bands at 500 m and 1 km resolution. The algorithm is tailored to process MODIS data received in real-time through the EURAC receiving station close to Bolzano, Italy, but also standard MODIS products are supported. It is divided into three steps: first the data is preprocessed, including reprojection, calculation of physical reflectance values and masking of water bodies. In a second step, the actual classification of snow, snow in forested areas, and clouds takes place based on MODIS images both from Terra and Aqua satellites. In the third step, snow cover maps derived from images of both sensors of the same day are combined to reduce cloud coverage in the final SCA product. Four different quality indices are calculated to verify the reliability of input data, snow classification, cloud detection and viewing geometry. Using the data received through their own station, EURAC can provide SCA maps of central Europe to end users in near real-time. Validation of the algorithm is outlined in a companion paper and indicates good performance with accuracies ranging from 94% to around 82% compared to in situ snow depth measurements, and around 93% compared to SCA derived from Landsat ETM+ images.
Osmanl Devleti’nde Saray htiya lar n n Kar lanmas : “Kar ve Buz Temini”
Mustafa Nuri Türkmen
Journal of Gazi Academic View , 2011,
Abstract: How did the needs such as ice and snow and cooling food and water supply in the Ottoman Empire? What kind of standards were formed for the snow pits and how were these snow pits run? Who were the officiers that dealt with this job at Topkapi Palace? How were ice and snow distributed and to whom were they disributed at the palace? Since ice and snow were used to cool food and water, some standardizations were formed to provide necessary hygiene. Becasue this job was a sector, it was done for a living by a lot of people. In this paper, with the help of archive sources, we will both handle subjects of spaces, supply, transport,prize and regulation of the functioning of snow and ice and try to find out their prevalence in terms of tradesmen and consumption.
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