Science.gov

Sample records for blended global snow

  1. A Blended Global Snow Product using Visible, Passive Microwave and Scatterometer Satellite Data

    NASA Technical Reports Server (NTRS)

    Foster, James L.; Hall, Dorothy K.; Eylander, John B.; Riggs, George A.; Nghiem, Son V.; Tedesco, Marco; Kim, Edward; Montesano, Paul M.; Kelly, Richard E. J.; Casey, Kimberly A.; Choudhury, Bhaskar

    2009-01-01

    A joint U.S. Air Force/NASA blended, global snow product that utilizes Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and QuikSCAT (Quick Scatterometer) (QSCAT) data has been developed. Existing snow products derived from these sensors have been blended into a single, global, daily, user-friendly product by employing a newly-developed Air Force Weather Agency (AFWA)/National Aeronautics and Space Administration (NASA) Snow Algorithm (ANSA). This initial blended-snow product uses minimal modeling to expeditiously yield improved snow products, which include snow cover extent, fractional snow cover, snow water equivalent (SWE), onset of snowmelt, and identification of actively melting snow cover. The blended snow products are currently 25-km resolution. These products are validated with data from the lower Great Lakes region of the U.S., from Colorado during the Cold Lands Processes Experiment (CLPX), and from Finland. The AMSR-E product is especially useful in detecting snow through clouds; however, passive microwave data miss snow in those regions where the snow cover is thin, along the margins of the continental snowline, and on the lee side of the Rocky Mountains, for instance. In these regions, the MODIS product can map shallow snow cover under cloud-free conditions. The confidence for mapping snow cover extent is greater with the MODIS product than with the microwave product when cloud-free MODIS observations are available. Therefore, the MODIS product is used as the default for detecting snow cover. The passive microwave product is used as the default only in those areas where MODIS data are not applicable due to the presence of clouds and darkness. The AMSR-E snow product is used in association with the difference between ascending and descending satellite passes or Diurnal Amplitude Variations (DAV) to detect the onset of melt, and a QSCAT product will be used to

  2. Monitoring global snow cover

    NASA Technical Reports Server (NTRS)

    Armstrong, Richard; Hardman, Molly

    1991-01-01

    A snow model that supports the daily, operational analysis of global snow depth and age has been developed. It provides improved spatial interpolation of surface reports by incorporating digital elevation data, and by the application of regionalized variables (kriging) through the use of a global snow depth climatology. Where surface observations are inadequate, the model applies satellite remote sensing. Techniques for extrapolation into data-void mountain areas and a procedure to compute snow melt are also contained in the model.

  3. Finland Validation of the New Blended Snow Product

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  4. Preliminary Evaluation of the AFWA-NASA (ANSA) Blended Snow-Cover Product over the Lower Great Lakes Region

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Foster, James L.; Riggs, George A.; Kelly, Richard E. J.; Chien, Janet Y. L.; Montesano, Paul M.

    2009-01-01

    The Air Force Weather Agency (AFWA) - NASA (ANSA) blended-snow product utilizes EOS standard snow products from the Moderate-Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to map daily snow cover and snow-water equivalent (SWE) globally. We have compared ANSA-derived SWE. with SWE values calculated from snow depths reported at approx.1500 National Climatic Data Center (NCDC) coop stations in the Lower Great Lakes basin. Our preliminary results show that conversion of snow depth to SWE is very sensitive to the choice of snow density (we used either 0.2 or 03 as conversion factors). We found overall better agreement between the ANSA-derived SWE and the co-op station data when we use a snow density of 0.3 to convert the snow depths to SWE. In addition, we show that the ANSA underestimates SWE in densely-forested areas, using January and February 2008 ANSA and co-op data. Furthermore, apparent large SWE changes from one day to the next may be caused by thaw-re-freeze events, and do not always represent a real change in SWE. In the near future we will continue the analysis in the 2006-07 and 2007-08 snow seasons.

  5. Blending satellite-based snow depth products with in situ observations for streamflow predictions in the Upper Colorado River Basin

    NASA Astrophysics Data System (ADS)

    Liu, Yuqiong; Peters-Lidard, Christa D.; Kumar, Sujay V.; Arsenault, Kristi R.; Mocko, David M.

    2015-02-01

    In snowmelt-driven river systems, it is critical to enable reliable predictions of the spatiotemporal variability in seasonal snowpack to support local and regional water management. Previous studies have shown that assimilating satellite-station blended snow depth data sets can lead to improved snow predictions, which however do not always translate into improved streamflow predictions, especially in complex mountain regions. In this study, we explore how an existing optimal interpolation-based blending strategy can be enhanced to reduce biases in satellite snow depth products for improving streamflow predictions. Two major new considerations are explored, including: (1) incorporating terrain aspect and (2) incorporating areal snow coverage information. The methodology is applied to the bias reduction of the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) snow depth estimates, which are then assimilated into the Noah land surface model via the ensemble Kalman Filtering (EnKF) for streamflow predictions in the Upper Colorado River Basin. Our results indicate that using only observations from low-elevation stations such as the Global Historical Climatology Network (GHCN) in the bias correction can lead to underestimation in streamflow, while using observations from high-elevation stations (e.g., the Snow Telemetry (SNOTEL) network) along with terrain aspect is critically important for achieving reliable streamflow predictions. Additionally incorporating areal snow coverage information from the Moderate Resolution Imaging Spectroradiometer (MODIS) can slightly improve the streamflow results further.

  6. Improving the Accuracy of the AFWA-NASA (ANSA) Blended Snow-Cover Product over the Lower Great Lakes Region

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Foster, James L.; Kumar, Sujay; Chien, Janety Y. L.; Riggs, George A.

    2012-01-01

    The Air Force Weather Agency (AFWA) -- NASA blended snow-cover product, called ANSA, utilizes Earth Observing System standard snow products from the Moderate- Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to map daily snow cover and snow-water equivalent (SWE) globally. We have compared ANSA-derived SWE with SWE values calculated from snow depths reported at 1500 National Climatic Data Center (NCDC) co-op stations in the Lower Great Lakes Basin. Compared to station data, the ANSA significantly underestimates SWE in densely-forested areas. We use two methods to remove some of the bias observed in forested areas to reduce the root-mean-square error (RMSE) between the ANSA- and station-derived SWE. First, we calculated a 5- year mean ANSA-derived SWE for the winters of 2005-06 through 2009-10, and developed a five-year mean bias-corrected SWE map for each month. For most of the months studied during the five-year period, the 5-year bias correction improved the agreement between the ANSA-derived and station-derived SWE. However, anomalous months such as when there was very little snow on the ground compared to the 5-year mean, or months in which the snow was much greater than the 5-year mean, showed poorer results (as expected). We also used a 7-day running mean (7DRM) bias correction method using days just prior to the day in question to correct the ANSA data. This method was more effective in reducing the RMSE between the ANSA- and co-op-derived SWE values, and in capturing the effects of anomalous snow conditions.

  7. Improving the MODIS Global Snow-Mapping Algorithm

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

    An algorithm (Snowmap) is under development to produce global snow maps at 500 meter resolution on a daily basis using data from the NASA MODIS instrument. MODIS, the Moderate Resolution Imaging Spectroradiometer, will be launched as part of the first Earth Observing System (EOS) platform in 1998. Snowmap is a fully automated, computationally frugal algorithm that will be ready to implement at launch. Forests represent a major limitation to the global mapping of snow cover as a forest canopy both obscures and shadows the snow underneath. Landsat Thematic Mapper (TM) and MODIS Airborne Simulator (MAS) data are used to investigate the changes in reflectance that occur as a forest stand becomes snow covered and to propose changes to the Snowmap algorithm that will improve snow classification accuracy forested areas.

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

    NASA Astrophysics Data System (ADS)

    Jacobi, H.-W.

    2012-03-01

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

  9. The effect of eurasian snow cover on global climate.

    PubMed

    Barnett, T P; Dümenil, L; Schlese, U; Roeckner, E

    1988-01-29

    Numerical simulations with a global atmospheric circulation model suggest that largescale variations in the amount of snowfall over Eurasia in the springtime are linked to the subsequent strength of the Asian summer monsoon. Large-scale changes in Eurasian snow cover are coupled to larger scale changes in the global climate system. There is a large, strong teleconnection to the atmospheric field over North America. The model results also show snow cover effects to subsequently alter other climatic fields known to be intimately associated with the El Niño-Southern Oscillation (ENSO) phenomenon. Thus the model results seem to challenge the current dogma that the ENSO phenomenon is solely the result of close coupling between the atmosphere and ocean by suggesting that processes over continental land masses may also have to be considered. PMID:17838886

  10. A Review of Global Satellite-derived Snow Products

    NASA Technical Reports Server (NTRS)

    Frei, Allan; Tedesco, Marco; Lee, Shihyan; Foster, James; Hall, Dorothy K.; Kelly, Richard; Robinson, David A.

    2012-01-01

    Snow cover over the Northern Hemisphere plays a crucial role in the Earth's hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow.

  11. A Review of Global Satellite-Derived Snow Products

    NASA Technical Reports Server (NTRS)

    Frei, Allan; Tedesco, Marco; Lee, Shihyan; Foster, James; Hall, Dorothy K.; Kelly, Richard; Robinson, David A.

    2011-01-01

    Snow cover over the Northern Hemisphere plays a crucial role in the Earth's hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow.

  12. A Review of Global Satellite-Derived Snow Products

    NASA Technical Reports Server (NTRS)

    Frei, Allan; Tedesco, Marco; Lee, Shihyan; Foster, James; Hall, Dorothy K.; Kelly, Richard; Robinson, David A.

    2011-01-01

    Snow cover over the Northern Hemisphere plays a crucial role in the Earth s hydrology and surface energy balance, and modulates feedbacks that control variations of global climate. While many of these variations are associated with exchanges of energy and mass between the land surface and the atmosphere, other expected changes are likely to propagate downstream and affect oceanic processes in coastal zones. For example, a large component of the freshwater flux into the Arctic Ocean comes from snow melt. The timing and magnitude of this flux affects biological and thermodynamic processes in the Arctic Ocean, and potentially across the globe through their impact on North Atlantic Deep Water formation. Several recent global remotely sensed products provide information at unprecedented temporal, spatial, and spectral resolutions. In this article we review the theoretical underpinnings and characteristics of three key products. We also demonstrate the seasonal and spatial patterns of agreement and disagreement amongst them, and discuss current and future directions in their application and development. Though there is general agreement amongst these products, there can be disagreement over certain geographic regions and under conditions of ephemeral, patchy and melting snow

  13. Use of Sentinels to aid the global monitoring of snow cover

    NASA Astrophysics Data System (ADS)

    Pulliainen, Jouni; Salminen, Miia; Luojus, Kari; Metsämäki, Sari; Lemmetyinen, Juha; Takala, Matias; Cohen, Juval; Böttcher, Kristine

    2014-05-01

    Earth observation instruments onboard Sentinel satellites provide a unique opportunity for the monitoring and investigation of global snow processes. The issue of the possible decay of seasonal snow cover is highly relevant for climate research. In addition to water cycle, the extent and amount of snow affects to surface albedo, and indirectly to carbon cycling. The latter issue includes snow-induced changes in permafrost regions (active layer characteristics), as well as the effect of snow (melt) to vegetation growth and soil respiration. Recent advances in ESA DUE GlobSnow project have shown that by combining data from optical satellite sensors and passive microwave instruments advanced Climate Data Records (CDR) on seasonal snow cover can be produced, extending to time periods of over 30 years. The combined snow cover products provide information both on Snow Extent (SE) and Snow Water Equivalent (SWE) on a daily basis. The applicable instruments providing historical data for CDR generation include such microwave radiometers as SMMR, AMSR and SSMI/I, and such optical sensors as AVHRR, AATSR and VIIRS. Sentinel 3, especially its SLSTR instrument, is a prominent tool for expanding the snow CDR for forthcoming years. The developed global snow cover monitoring methodology, demonstrated and discussed here, derives the SWE information from passive microwave data (accompanied with in situ observations of snow depth at synoptic weather stations). The snow extent and fractional snow cover (FSC) on ground is derived from optical satellite data, in order to accurately map the continental line of seasonal snow cover, and to map regions of ephemeral snow cover. An advanced feature in the developed methodology is the provision of uncertainty information on snow cover characteristics associated with each individual satellite data footprint on ground and moment of time. In addition to assisting the generation and extension of the global snow cover CDR, Sentinel missions provide

  14. An Evaluation of Snow Initializations for NCEP Global and Regional Forecasting Models

    NASA Astrophysics Data System (ADS)

    Dawson, N.; Broxton, P. D.; Zeng, X.; Leuthold, M.; Barlage, M. J.; Holbrook, V. P.

    2015-12-01

    Snow plays a major role in land-atmosphere interactions, affecting the forecasting of weather, climate, and water resources. At the same time, the strong spatial heterogeneity in snow depth and snow water equivalent (SWE) makes it challenging to evaluate gridded snow quantities using in situ point measurements. First, we have developed a new method to upscale point measurements into gridded datasets. This method is found to be superior to three other methods. It is then used to generate daily snow depth and SWE datasets for water years 2012-2014 at eight 2° X 2° areas using in situ measurements from the COOP and SNOTEL networks. These areas encompass a variety of terrain characteristics over North America. These datasets are used to quantify the performance of daily snow depth and SWE initialization in the NCEP global forecasting models (GFS and CFS) and regional models (NAM and RAP). Model initializations which utilize AFWA snow depths (GFS, CFS, and NAM) are found to have a too shallow snow depth compared to our area averaged method. Across all areas and water years, our method averaged 0.58m (0.57m) of snow while the models averaged 0.18m (0.19m) with a mean absolute error of 0.42m (0.47m) for the global (regional) models utilizing AFWA data. These models also ended the snow season much too early on average (by more than a month). The RAP model, which cycles snow instead of initializing with AFWA snow depths, underestimates snow depth to a lesser degree and has a mean absolute error of 0.26m while ending the snow season about two weeks early on average. Compared with snow depth errors, SWE errors from GFS, CFS, and NAM are even larger because of their use of globally constant snow densities. Furthermore, we have evaluated the daily snow depth gridded data produced by the Canadian Meteorological Centre (CMC), which has been utilized as the best available ground truth in multiple studies. It is found that the CMC product underestimates snow depth and has a mean

  15. The Effect of Excess Snow on Sea Ice in a Global Ice-Ocean Prediction System

    NASA Astrophysics Data System (ADS)

    Winter, B.; Bélair, S.; Lemieux, J. F.

    2014-12-01

    Snow cover on sea ice acts as a thermal insulator, greatly reducing the upward heat flux from the ocean through the ice, specifically through thin ice. The treatment of snow in the CICE sea ice model does not include the effects of blowing snow, thereby leading to an unrealistically thick snow layer on the ice. We investigate the consequences of this excess snow for the upward heat fluxes throughout the year, and how this impacts forecast accuracy in a global ice-ocean prediction model (GIOPS). First results will be presented, and computationally efficient solutions will be discussed.

  16. Prey Preferences of the Snow Leopard (Panthera uncia): Regional Diet Specificity Holds Global Significance for Conservation

    PubMed Central

    Lyngdoh, Salvador; Shrotriya, Shivam; Goyal, Surendra P.; Clements, Hayley; Hayward, Matthew W.; Habib, Bilal

    2014-01-01

    The endangered snow leopard is a large felid that is distributed over 1.83 million km2 globally. Throughout its range it relies on a limited number of prey species in some of the most inhospitable landscapes on the planet where high rates of human persecution exist for both predator and prey. We reviewed 14 published and 11 unpublished studies pertaining to snow leopard diet throughout its range. We calculated prey consumption in terms of frequency of occurrence and biomass consumed based on 1696 analysed scats from throughout the snow leopard's range. Prey biomass consumed was calculated based on the Ackerman's linear correction factor. We identified four distinct physiographic and snow leopard prey type zones, using cluster analysis that had unique prey assemblages and had key prey characteristics which supported snow leopard occurrence there. Levin's index showed the snow leopard had a specialized dietary niche breadth. The main prey of the snow leopard were Siberian ibex (Capra sibrica), blue sheep (Pseudois nayaur), Himalayan tahr (Hemitragus jemlahicus), argali (Ovis ammon) and marmots (Marmota spp). The significantly preferred prey species of snow leopard weighed 55±5 kg, while the preferred prey weight range of snow leopard was 36–76 kg with a significant preference for Siberian ibex and blue sheep. Our meta-analysis identified critical dietary resources for snow leopards throughout their distribution and illustrates the importance of understanding regional variation in species ecology; particularly prey species that have global implications for conservation. PMID:24533080

  17. Prey preferences of the snow leopard (Panthera uncia): regional diet specificity holds global significance for conservation.

    PubMed

    Lyngdoh, Salvador; Shrotriya, Shivam; Goyal, Surendra P; Clements, Hayley; Hayward, Matthew W; Habib, Bilal

    2014-01-01

    The endangered snow leopard is a large felid that is distributed over 1.83 million km(2) globally. Throughout its range it relies on a limited number of prey species in some of the most inhospitable landscapes on the planet where high rates of human persecution exist for both predator and prey. We reviewed 14 published and 11 unpublished studies pertaining to snow leopard diet throughout its range. We calculated prey consumption in terms of frequency of occurrence and biomass consumed based on 1696 analysed scats from throughout the snow leopard's range. Prey biomass consumed was calculated based on the Ackerman's linear correction factor. We identified four distinct physiographic and snow leopard prey type zones, using cluster analysis that had unique prey assemblages and had key prey characteristics which supported snow leopard occurrence there. Levin's index showed the snow leopard had a specialized dietary niche breadth. The main prey of the snow leopard were Siberian ibex (Capra sibrica), blue sheep (Pseudois nayaur), Himalayan tahr (Hemitragus jemlahicus), argali (Ovis ammon) and marmots (Marmota spp). The significantly preferred prey species of snow leopard weighed 55±5 kg, while the preferred prey weight range of snow leopard was 36-76 kg with a significant preference for Siberian ibex and blue sheep. Our meta-analysis identified critical dietary resources for snow leopards throughout their distribution and illustrates the importance of understanding regional variation in species ecology; particularly prey species that have global implications for conservation.

  18. Prey preferences of the snow leopard (Panthera uncia): regional diet specificity holds global significance for conservation.

    PubMed

    Lyngdoh, Salvador; Shrotriya, Shivam; Goyal, Surendra P; Clements, Hayley; Hayward, Matthew W; Habib, Bilal

    2014-01-01

    The endangered snow leopard is a large felid that is distributed over 1.83 million km(2) globally. Throughout its range it relies on a limited number of prey species in some of the most inhospitable landscapes on the planet where high rates of human persecution exist for both predator and prey. We reviewed 14 published and 11 unpublished studies pertaining to snow leopard diet throughout its range. We calculated prey consumption in terms of frequency of occurrence and biomass consumed based on 1696 analysed scats from throughout the snow leopard's range. Prey biomass consumed was calculated based on the Ackerman's linear correction factor. We identified four distinct physiographic and snow leopard prey type zones, using cluster analysis that had unique prey assemblages and had key prey characteristics which supported snow leopard occurrence there. Levin's index showed the snow leopard had a specialized dietary niche breadth. The main prey of the snow leopard were Siberian ibex (Capra sibrica), blue sheep (Pseudois nayaur), Himalayan tahr (Hemitragus jemlahicus), argali (Ovis ammon) and marmots (Marmota spp). The significantly preferred prey species of snow leopard weighed 55±5 kg, while the preferred prey weight range of snow leopard was 36-76 kg with a significant preference for Siberian ibex and blue sheep. Our meta-analysis identified critical dietary resources for snow leopards throughout their distribution and illustrates the importance of understanding regional variation in species ecology; particularly prey species that have global implications for conservation. PMID:24533080

  19. Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) Global Snow-Cover Maps

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

    Following the 1999 launch of the Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS), the capability exists to produce global snow-cover maps on a daily basis at 500-m resolution. Eight-day composite snow-cover maps will also be available. MODIS snow-cover products are produced at Goddard Space Flight Center and archived and distributed by the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado. The products are available in both orbital and gridded formats. An online search and order tool and user-services staff will be available at NSIDC to assist users with the snow products. The snow maps are available at a spatial resolution of 500 m, and 1/4 degree x 1/4 degree spatial resolution, and provide information on sub-pixel (fractional) snow cover. Pre-launch validation work has shown that the MODIS snow-mapping algorithms perform best under conditions of continuous snow cover in low vegetation areas, but can also map snow cover in dense forests. Post-launch validation activities will be performed using field and aircraft measurements from a February 2000 validation mission, as well as from existing satellite-derived snow-cover maps from NOAA and Landsat-7 Enhanced Thematic Mapper Plus (ETM+).

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

    PubMed Central

    Diffenbaugh, Noah S.; Scherer, Martin; Ashfaq, Moetasim

    2013-01-01

    Snow accumulation is critical for water availability in the northern hemisphere 1,2, raising concern that global warming could have important impacts on natural and human systems in snow-dependent regions 1,3. Although regional hydrologic changes have been observed (e.g., 1,3–5), the time of emergence of extreme changes in snow accumulation and melt remains a key unknown for assessing climate change impacts 3,6,7. 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-term decades and at 2°C global warming. The occurrence of extremely low snow years becomes widespread by the late-21st century, as do the occurrence 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. PMID:24015153

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

    SciTech Connect

    Diffenbaugh, Noah; Scherer, Martin; Ashfaq, Moetasim

    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.

  2. Global Snow-Cover Evolution from Twenty Years of Satellite Passive Microwave Data

    USGS Publications Warehouse

    Mognard, N.M.; Kouraev, A.V.; Josberger, E.G.

    2003-01-01

    Starting in 1979 with the SMMR (Scanning Multichannel Microwave Radiometer) instrument onboard the satellite NIMBUS-7 and continuing since 1987 with the SSMI (Special Sensor Microwave Imager) instrument on board the DMSP (Defence Meteorological Satellite Program) series, more then twenty years of satellite passive microwave data are now available. This dataset has been processed to analyse the evolution of the global snow cover. This work is part of the AICSEX project from the 5th Framework Programme of the European Community. The spatio-temporal evolution of the satellite-derived yearly snow maximum extent and the timing of the spring snow melt were estimated and analysed over the Northern Hemisphere. Significant differences between the evolution of the yearly maximum snow extent in Eurasia and in North America were found. A positive correlation between the maximum yearly snow cover extent and the ENSO index was obtained. High interannual spatio-temporal variability characterises the timing of snow melt in the spring. Twenty-year trends in the timing of spring snow melt have been computed and compared with spring air temperature trends for the same period and the same area. In most parts of Eurasia and in the central and western parts of North America the tendency has been for earlier snow melt. In northeastern Canada, a large area of positive trends, where snow melt timing starts later than in the early 1980s, corresponds to a region of positive trends of spring air temperature observed over the same period.

  3. Snow cover detection and snow depth algorithms for the Global Change Observation Mission (GCOM) AMSR2 instrument using AMSR-E/AMSR2 measurements

    NASA Astrophysics Data System (ADS)

    Lee, Y. K.; Kongoli, C.; Key, J. R.

    2014-12-01

    Snow is one of the most dynamic hydrological variables on the Earth surface playing a key role in the global energy and water budget. The ability to detect global snow cover and measure snow depth in near all weather conditions has been demonstrated with satellite microwave measurements. The Advanced Microwave Scanning Radiometer 2 (AMSR2), launched on May 18, 2012 onboard SHIZUKU, is included in A-train group of satellites and will replace the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) instrument. The similarity of channels between AMSR-E and AMSR2 makes AMSR2 instrument a successor of AMSR-E instrument. This study will evaluate the suite of AMSR2 algorithms that are being developed for the operational retrieval of snow cover detection and snow depth using AMSR-E and AMSR2 data. AMSR-E data spans 10 years from June 2002 to September 2011; AMSR2 data spans 2 years from August 2012 to May 2014. The snow cover detection algorithm is based on the operational NOAA's heritage microwave algorithm with snow climatology tests and wet snow filtering as new enhancements. The SD algorithm is adopted from the current version of the operational NASA AMSR-E SWE algorithm. The 24- and 4-km IMS snow cover and in-situ SYNOP and COOP snow depth are used as references for the evaluation. More details about the reference data and evaluation results will be discussed.

  4. A GIS Method of Calculating Snow Depth Using IFSAR Data and Differential Global Position System

    NASA Astrophysics Data System (ADS)

    Hinkel, K. M.; Hurd, J. K.

    2005-12-01

    Recent advances in remote sensing platforms, Differential Global Positioning Systems (DGPS) technology, and Geographic Information Systems (GIS) capabilities has led to multiple ways of creating high resolution Digital Elevation Models (DEM). In April 2005 near Barrow, Alaska, a DGPS survey was conducted along a snowdrift formed by a 2.2 km long snow fence. A snow machine was used to pull a sledge equipped with the DGPS, recording geographic location and elevation every 5 seconds. Surveys were conducted along five transects parallel to the snow fence; two along the upwind (eastern) side of the fence and three along the deeper downwind (western) drift. The path of the snow machine was along the drift crest, slope and edge. In addition to the DGPS survey of the snowdrift, Interferometric Synthetic Aperture Radar (IFSAR) data collected in July 2002 by InterMapr was used as a DEM of the ground surface. Within the GIS software package, the DGPS survey points were interpolated using a triangulated irregular network. This surface was rasterized to 5 m2 cells to match the IFSAR DEM. Using a raster calculator, the ground surface DEM was subtracted from the snowdrift DEM to yield a DEM of snow depth. Integrated over the length and width of the affected area, the drift covers an area of 186,900 m2 and contains a volume of 415,858 m3. The mean snow depth is 2.23 m as compared to 0.4 m at a control site located in a nearby region of the tundra unaffected by the snow fence. Empirical measurements were collected with a calibrated metal snow depth probe along transects perpendicular to the snow fence, and were used for an accuracy assessment. The results show agreement to about +/-20 cm. Some Arctic villages rely on snowdrifts as a source of drinking water. Using these techniques, the snow water equivalent can be calculated given a know snow density to estimate fresh water availability.

  5. Future change in seasonal march of snow water equivalent due to global climate change

    NASA Astrophysics Data System (ADS)

    Hara, M.; Kawase, H.; Ma, X.; Wakazuki, Y.; Fujita, M.; Kimura, F.

    2012-04-01

    Western side of Honshu Island in Japan is one of the heaviest snowfall areas in the world, although the location is relatively lower latitude than other heavy snowfall areas. Snowfall is one of major source for agriculture, industrial, and house-use in Japan. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities (ex. Ma et al., 2011). We performed the four numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. NCEP/NCAR reanalysis is used for initial and boundary conditions in present climate simulation and PGW method. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. In much-snow cases, Maximum total snow water equivalent over Japan, which is mostly observed in early February, is 49 G ton in the present simulation, the one decreased 26 G ton in the future simulation. The decreasing rate of snow water equivalent due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is strongly affected by the air temperature rise due to global climate change. The difference in present and future precipitation amount is little.

  6. Global Blended Learning Practices for Teaching and Learning, Leadership and Professional Development

    ERIC Educational Resources Information Center

    Hilliard, Ann Toler

    2015-01-01

    Blended learning is a combination of online and face-to-face activities for classroom instruction or other training modalities to help develop new knowledge and skills that can be transferred to the workplace environment. The use of blended learning is expanding globally (Vaughn, 2007). Blended learning is evident in professional development…

  7. Performance of the Falling Snow Retrieval Algorithms for the Global Precipitation Measurement (GPM) Mission

    NASA Technical Reports Server (NTRS)

    Skofronick-Jackson, Gail; Munchak, Stephen J.; Ringerud, Sarah

    2016-01-01

    Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles, especially during climate change. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges remaining). This work reports on the development and testing of retrieval algorithms for the Global Precipitation Measurement (GPM) mission Core Satellite, launched February 2014.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges and uncertainties remaining. This work reports on the development and post-launch testing of retrieval algorithms for the NASA Global Precipitation Measurement (GPM) mission Core Observatory satellite launched in February 2014. In particular, we will report on GPM Microwave Imager (GMI) radiometer instrument algorithm performance with respect to falling snow detection and estimation. Since GPM's launch, the at-launch GMI precipitation algorithms, based on a Bayesian framework, have been used with the new GPM data. The at-launch database is generated using proxy satellite data merged with surface measurements (instead of models). One year after launch, the Bayesian database will begin to be replaced with the more realistic observational data from the GPM spacecraft radar retrievals and GMI data. It is expected that the observational database will be much more accurate for falling snow retrievals because that database will take full advantage of the 166 and 183 GHz snow-sensitive channels. Furthermore, much retrieval algorithm work has been done to improve GPM retrievals over land. The Bayesian framework for GMI retrievals is dependent on the a priori database used in the algorithm and how profiles are selected from that database. Thus, a land classification sorts land surfaces into ~15 different categories for surface-specific databases (radiometer brightness temperatures are quite dependent on surface characteristics). In addition, our work has shown that knowing if the land surface is snow-covered, or not, can improve the performance of the algorithm. Improvements were made to the algorithm that allow for daily inputs of ancillary snow cover

  9. Global and local-scale variation in bacterial community structure of snow from the Swiss and Australian Alps.

    PubMed

    Wunderlin, Tina; Ferrari, Belinda; Power, Michelle

    2016-09-01

    Seasonally, snow environments cover up to 50% of the land's surface, yet the microbial diversity and ecosystem functioning within snow, particularly from alpine regions are not well described. This study explores the bacterial diversity in snow using next-generation sequencing technology. Our data expand the global inventory of snow microbiomes by focusing on two understudied regions, the Swiss Alps and the Australian Alps. A total biomass similar to cell numbers in polar snow was detected, with 5.2 to 10.5 × 10(3) cells mL(-1) of snow. We found that microbial community structure of surface snow varied by country and site and along the altitudinal range (alpine and sub-alpine). The bacterial communities present were diverse, spanning 25 distinct phyla, but the six phyla Proteobacteria (Alpha- and Betaproteobacteria), Acidobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria and Firmicutes, accounted for 72%-98% of the total relative abundance. Taxa such as Acidobacteriaceae and Methylocystaceae, associated with cold soils, may be part of the atmospherically sourced snow community, while families like Sphingomonadaceae were detected in every snow sample and are likely part of the common snow biome.

  10. Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow

    NASA Technical Reports Server (NTRS)

    Skofronick-Jackson, Gail; Hudak, David; Petersen, Walter; Nesbitt, Stephen W.; Chandrasekar, V.; Durden, Stephen; Gleicher, Kirstin J.; Huang, Gwo-Jong; Joe, Paul; Kollias, Pavlos; Reed, Kimberly A.; Schwaller, Mathew R.; Stewart, Ronald; Tanelli, Simone; Tokay, Ali; Wang, James R.; Wolde, Mengistu

    2014-01-01

    As a component of the Earth's hydrologic cycle, and especially at higher latitudes,falling snow creates snow pack accumulation that in turn provides a large proportion of the fresh water resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) mission Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011-2012 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite,and radiometers on constellation member satellites. Multi-parameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precipitation detection and estimation can be based. The data collection strategy was coordinated, stacked, high-altitude and in-situ cloud aircraft missions with three research aircraft sampling within a broader surface network of five ground sites taking in-situ and volumetric observations. During the field campaign 25 events were identified and classified according to their varied precipitation type, synoptic context, and precipitation amount. Herein, the GCPEx fieldcampaign is described and three illustrative cases detailed.

  11. Global Seasonal Climatologies of Ocean Chlorophyll: Blending In situ and Satellite Data for the CZCS Era

    NASA Technical Reports Server (NTRS)

    Gregg, Watson W.; Conkright, Margarita E.

    1999-01-01

    The historical archives of in situ (National Oceanographic Data Center) and satellite (Coastal Zone Color Scanner) chlorophyll data were combined using the blended analysis method of Reynolds [1988] in an attempt to construct an improved climatological seasonal representation of global chlorophyll distributions. The results of the blended analysis differed dramatically from the CZCS representation: global chlorophyll estimates increased 8-35% in the blended analysis depending upon season. Regional differences were even larger, up to 140% in the equatorial Indian Ocean in summer (during the southwest monsoon). Tropical Pacific chlorophyll values increased 25-41%. The results suggested that the CZCS generally underestimates chlorophyll. Regional and seasonal differences in the blended analysis were sufficiently large as to produce a different representation of global chlorophyll distributions than otherwise inferred from CZCS data alone. Analyses of primary production and biogeochemical cycles may be substantially impacted by these results.

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

    PubMed

    Hofmann, Lorenz; Stemmler, Irene; Lammel, Gerhard

    2012-03-01

    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. PMID:22054697

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

    PubMed

    Hofmann, Lorenz; Stemmler, Irene; Lammel, Gerhard

    2012-03-01

    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.

  14. Pre-Launch Performance Evaluations of Falling Snow using the Global Precipitation Measurement (GPM) Radiometer Retrieval Algorithm

    NASA Astrophysics Data System (ADS)

    Skofronick Jackson, G.; Munchak, S. J.; Johnson, B. T.

    2013-12-01

    Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work reports on the development and pre-launch testing of retrieval algorithms for the Global Precipitation Measurement (GPM) mission Core Observatory satellite, to be launched in early 2014. In particular, we will report on GPM Microwave Imager (GMI) radiometer instrument algorithm performance with respect to falling snow detection and estimation. While satellite-based remote sensing can provide global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges remaining. Estimates of falling snow from ground and space based sensors have been difficult due to the physical characteristics of snowflakes including their complex shapes, sizes, fall patterns, melting fractions, and densities; and their remotely sensed radiative characteristics. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Our earlier work in this field has shown, through both theoretical and observational studies, that falling snow rates of approximately 0.5 mm/hr (melted) can be detected from GMI (Skofronick-Jackson, et al., IEEE Trans. Geoscience and Remote Sensing, 2013, Munchak and Skofronick-Jackson, Atmospheric Research, 2013). Throughout 2013, the at-launch GMI precipitation algorithms (called GPROF2014), based on a Bayesian framework, have been revised and delivered to the GPM data processing center with the final algorithm to be delivered in September 2013. The Bayesian framework for GMI

  15. Distance Education in the Age of Globalization: An Overwhelming Desire towards Blended Learning

    ERIC Educational Resources Information Center

    Sethy, Satya Sundar

    2008-01-01

    The aim of this paper is to discuss the nature and status of distance education in the age of globalization, i.e. how best it fits for the present educational scenario. In this connection, we will discuss how Blended Learning (hence after, BL) is one among the other learning strategies mostly helpful for the learners. Keeping this view in mind,…

  16. ECMWF's Global Snow Analysis: Assessment and Revision Based on Satellite Observations.

    NASA Astrophysics Data System (ADS)

    Drusch, Matthias; Vasiljevic, Drasko; Viterbo, Pedro

    2004-09-01

    Snow water equivalent and snow extent are key parameters for the earth's energy and water budget. In this study, the current operational snow-depth analysis (2D spatial Cressman interpolation) at the European Centre for Medium-Range Weather Forecasts (ECMWF), which relies on real-time observations of snow depth, the short-range forecast, and snow-depth climatic data, is presented. The operational product is compared with satellite-derived snow cover. It is found that the total area of grid boxes affected by snow is approximately 10% larger in the analysis than in the National Oceanic and Atmospheric Administration National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) snow-extent product. The differences are persistent in time and space and cover the entire Northern Hemisphere. They comprise areas with intermittent and/or patchy snow cover, for example, the Tibetan Plateau, the edges of snow fields, and areas with a low density of observations, which are difficult to capture in the current operational analysis. A modified snow analysis is presented, in which the operational NESDIS snow product is incorporated. The current analysis and the revised analysis are compared with high-resolution snow-cover datasets derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) and independent ground-based snow-depth observations from the Meteorological Service of Canada. Using the NOAA/NESDIS snow-extent dataset in the operational analysis leads to a more realistic description of the actual snow extent.


  17. Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework

    NASA Astrophysics Data System (ADS)

    Raleigh, M. S.; Lundquist, J. D.; Clark, M. P.

    2015-07-01

    Physically based models provide insights into key hydrologic processes but are associated with uncertainties due to deficiencies in forcing data, model parameters, and model structure. Forcing uncertainty is enhanced in snow-affected catchments, where weather stations are scarce and prone to measurement errors, and meteorological variables exhibit high variability. Hence, there is limited understanding of how forcing error characteristics affect simulations of cold region hydrology and which error characteristics are most important. Here we employ global sensitivity analysis to explore how (1) different error types (i.e., bias, random errors), (2) different error probability distributions, and (3) different error magnitudes influence physically based simulations of four snow variables (snow water equivalent, ablation rates, snow disappearance, and sublimation). We use the Sobol' global sensitivity analysis, which is typically used for model parameters but adapted here for testing model sensitivity to coexisting errors in all forcings. We quantify the Utah Energy Balance model's sensitivity to forcing errors with 1 840 000 Monte Carlo simulations across four sites and five different scenarios. Model outputs were (1) consistently more sensitive to forcing biases than random errors, (2) generally less sensitive to forcing error distributions, and (3) critically sensitive to different forcings depending on the relative magnitude of errors. For typical error magnitudes found in areas with drifting snow, precipitation bias was the most important factor for snow water equivalent, ablation rates, and snow disappearance timing, but other forcings had a more dominant impact when precipitation uncertainty was due solely to gauge undercatch. Additionally, the relative importance of forcing errors depended on the model output of interest. Sensitivity analysis can reveal which forcing error characteristics matter most for hydrologic modeling.

  18. Can snow save us from global warming? (Louis Agassiz Medal Lecture)

    NASA Astrophysics Data System (ADS)

    Dominé, Florent; Picard, Ghislain; Morin, Samuel; Krinner, Gerhard; Gouttevin, Isabelle; Menegoz, Martin; Gallet, Jean-Charles; Arnaud, Laurent; Dumont, Marie; Lafaysse, Matthieu; Brun, Eric

    2013-04-01

    How snow will interact with climate in the current warming context is an open issue. There is of course the well known snow-albedo feedback, whereby the replacement of snow by darker surfaces positively feedbacks on climate. But many other snow-climate feedbacks have been proposed recently, both positive and negative, so that predictions of future polar climate are rather uncertain. Warming will change precipitation and metamorphic conditions in the snowpack, affecting snow physical properties such as grain size, albedo and thermal conductivity. Their consequences are difficult to predict, with threshold effects between different regimes in snow metamorphism. A significant negative feedback between precipitation, snow albedo and climate has been detected in Antarctica, where increased precipitation increase albedo by bringing small grains to the surface, and this is not compensated by the warmer temperatures that accelerate grain growth. On the contrary, similar processes acting in the Arctic have led to a positive feedback. Changes in snow thermal conductivity can have important effects on the growth of sea ice, with spatially variable effects. In the Arctic, the warming-induced growth of higher vegetation such as shrubs can produce additional effects. Shrubs trap snow, increase snow depth and shield snow from wind erosion. Snow physical properties will change, with the likely partial replacement of wind slabs by layers of depth hoar of lower thermal conductivity. This may limit winter ground cooling, with effects on permafrost stability and on the release of greenhouse gases from thawing carbon stocks. Several examples will be detailed to illustrate the complexity of snow-climate interactions and to stress the need for a detailed description of snow physical properties in climate models, before we can conclude as to whether snow will slow down polar warming or on the contrary accelerate it, with possible catastrophic consequences.

  19. An in situ-satellite blended analysis of global sea surface salinity

    NASA Astrophysics Data System (ADS)

    Xie, P.; Boyer, T.; Bayler, E.; Xue, Y.; Byrne, D.; Reagan, J.; Locarnini, R.; Sun, F.; Joyce, R.; Kumar, A.

    2014-09-01

    The blended monthly sea surface salinity (SSS) analysis, called the NOAA "Blended Analysis of Surface Salinity" (BASS), is constructed for the 4 year period from 2010 to 2013. Three data sets are employed as inputs to the blended analysis: in situ SSS measurements aggregated and quality controlled by NOAA/NODC, and passive microwave (PMW) retrievals from both the National Aeronautics and Space Administration's (NASA) Aquarius/SAC-D and the European Space Agency's (ESA) Soil Moisture-Ocean Salinity (SMOS) satellites. The blended analysis comprises two steps. First, the biases in the satellite retrievals are removed through probability distribution function (PDF) matching against temporally spatially colocated in situ measurements. The blended analysis is then achieved through optimal interpolation (OI), where the analysis for the previous time step is used as the first guess while the in situ measurements and bias-corrected satellite retrievals are employed as the observations to update the first guess. Cross validations illustrate improved quality of the blended analysis, with reduction in bias and random errors over most of the global oceans as compared to the individual inputs. Large uncertainty, however, remains in high-latitude oceans and coastal regions where the in situ networks are sparse and current-generation satellite retrievals have limitations. Our blended SSS analysis shows good agreements with the NODC in situ-based analysis over most of the tropical and subtropical oceans, but large differences are observed for high-latitude oceans and along coasts. In the tropical oceans, the BASS is shown to have coherent variability with precipitation and evaporation associated with the evolution of the El Niño-Southern Oscillation (ENSO).

  20. Anthropogenic osmium in rain and snow reveals global-scale atmospheric contamination

    PubMed Central

    Chen, Cynthia; Sedwick, Peter N.; Sharma, Mukul

    2009-01-01

    Osmium is one of the rarer elements in seawater, with typical concentration of ≈10 × 10−15 g g−1 (5.3 × 10−14 mol kg−1). The osmium isotope composition (187Os/188Os ratio) of deep oceans is 1.05, reflecting a balance between inputs from continental crust (≈1.3) and mantle/cosmic dust (≈0.13). Here, we show that the 187Os/188Os ratios measured in rain and snow collected around the world range from 0.16 to 0.48, much lower than expected (>1), but similar to the isotope composition of ores (≈0.2) that are processed to extract platinum and other metals to be used primarily in automobile catalytic converters. Present-day surface seawater has a lower 187Os/188Os ratio (≈0.95) than deep waters, suggesting that human activities have altered the isotope composition of the world's oceans and impacted the global geochemical cycle of osmium. The contamination of the surface ocean is particularly remarkable given that osmium has few industrial uses. The pollution may increase with growing demand for platinum-based catalysts. PMID:19416862

  1. Anthropogenic osmium in rain and snow reveals global-scale atmospheric contamination.

    PubMed

    Chen, Cynthia; Sedwick, Peter N; Sharma, Mukul

    2009-05-12

    Osmium is one of the rarer elements in seawater, with typical concentration of approximately 10 x 10(-15) g g(-1) (5.3 x 10(-14) mol kg(-1)). The osmium isotope composition ((187)Os/(188)Os ratio) of deep oceans is 1.05, reflecting a balance between inputs from continental crust (approximately 1.3) and mantle/cosmic dust (approximately 0.13). Here, we show that the (187)Os/(188)Os ratios measured in rain and snow collected around the world range from 0.16 to 0.48, much lower than expected (>1), but similar to the isotope composition of ores (approximately 0.2) that are processed to extract platinum and other metals to be used primarily in automobile catalytic converters. Present-day surface seawater has a lower (187)Os/(188)Os ratio (approximately 0.95) than deep waters, suggesting that human activities have altered the isotope composition of the world's oceans and impacted the global geochemical cycle of osmium. The contamination of the surface ocean is particularly remarkable given that osmium has few industrial uses. The pollution may increase with growing demand for platinum-based catalysts.

  2. The Cycles of Snow Cover in Pyrenees Mountain and Mont Lebanon Analyzed Using the Global Modeling Technique.

    NASA Astrophysics Data System (ADS)

    Drapeau, L.; Mangiarotti, S.; Le Jean, F.; Gascoin, S.; Jarlan, L.

    2014-12-01

    The global modeling technique provides a way to obtain ordinary differential equations from single time series1. This technique, initiated in the 1990s, could be applied successfully to numerous theoretic and experimental systems. More recently it could be applied to environmental systems2,3. Here this technique is applied to seasonal snow cover area in the Pyrenees mountain (Europe) and Mont Lebanon (Mediterranean region). The snowpack evolution is complex because it results from combination of processes driven by physiography (elevation, slope, land cover...) and meteorological variables (precipitation, temperature, wind speed...), which are highly heterogeneous in such regions. Satellite observations in visible bands offer a powerful tool to monitor snow cover areas at global scale, with large resolutions range. Although this observable does not directly inform about snow water equivalent, its dynamical behavior strongly relies on it. Therefore, snow cover area is likely to be a good proxy of the global dynamics and global modeling technique a well adapted approach. The MOD10A2 product (500m) generated from MODIS by the NASA is used after a pretreatment is applied to minimize clouds effect. The global modeling technique is then applied using two packages4,5. The analysis is performed with two time series for the whole period (2000-2012) and year by year. Low-dimensional chaotic models are obtained in many cases. Such models provide a strong argument for chaos since involving the two necessary conditions in a synthetic way: determinism and strong sensitivity to initial conditions. The models comparison suggests important non-stationnarities at interannual scale which prevent from detecting long term changes. 1: Letellier et al 2009. Frequently asked questions about global modeling, Chaos, 19, 023103. 2: Maquet et al 2007. Global models from the Canadian lynx cycles as a direct evidence for chaos in real ecosystems. J. of Mathematical Biology, 55 (1), 21-39 3

  3. The impact of snow nitrate photolysis on boundary layer chemistry and the recycling and redistribution of reactive nitrogen across Antarctica and Greenland in a global chemical transport model

    NASA Astrophysics Data System (ADS)

    Zatko, Maria; Geng, Lei; Alexander, Becky; Sofen, Eric; Klein, Katarina

    2016-03-01

    The formation and recycling of reactive nitrogen (NO, NO2, HONO) at the air-snow interface has implications for air quality and the oxidation capacity of the atmosphere in snow-covered regions. Nitrate (NO3-) photolysis in snow provides a source of oxidants (e.g., hydroxyl radical) and oxidant precursors (e.g., nitrogen oxides) to the overlying boundary layer, and alters the concentration and isotopic (e.g., δ15N) signature of NO3- preserved in ice cores. We have incorporated an idealized snowpack with a NO3- photolysis parameterization into a global chemical transport model (Goddard Earth Observing System (GEOS) Chemistry model, GEOS-Chem) to examine the implications of snow NO3- photolysis for boundary layer chemistry, the recycling and redistribution of reactive nitrogen, and the preservation of ice-core NO3- in ice cores across Antarctica and Greenland, where observations of these parameters over large spatial scales are difficult to obtain. A major goal of this study is to examine the influence of meteorological parameters and chemical, optical, and physical snow properties on the magnitudes and spatial patterns of snow-sourced NOx fluxes and the recycling and redistribution of reactive nitrogen across Antarctica and Greenland. Snow-sourced NOx fluxes are most influenced by temperature-dependent quantum yields of NO3- photolysis, photolabile NO3- concentrations in snow, and concentrations of light-absorbing impurities (LAIs) in snow. Despite very different assumptions about snowpack properties, the range of model-calculated snow-sourced NOx fluxes are similar in Greenland (0.5-11 × 108 molec cm-2 s-1) and Antarctica (0.01-6.4 × 108 molec cm-2 s-1) due to the opposing effects of higher concentrations of both photolabile NO3- and LAIs in Greenland compared to Antarctica. Despite the similarity in snow-sourced NOx fluxes, these fluxes lead to smaller factor increases in mean austral summer boundary layer mixing ratios of total nitrate (HNO3+ NO3-), NOx, OH

  4. Global transcriptome changes in perennial ryegrass during early infection by pink snow mould.

    PubMed

    Kovi, Mallikarjuna Rao; Abdelhalim, Mohamed; Kunapareddy, Anil; Ergon, Åshild; Tronsmo, Anne Marte; Brurberg, May Bente; Hofgaard, Ingerd Skow; Asp, Torben; Rognli, Odd Arne

    2016-01-01

    Lack of resistance to pink snow mould (Microdochium nivale) is a major constraint for adaptation of perennial ryegrass (Lolium perenne L.) to continental regions with long-lasting snow cover at higher latitudes. Almost all investigations of genetic variation in resistance have been performed using cold acclimated plants. However, there may be variation in resistance mechanisms that are functioning independently of cold acclimation. In this study our aim was to identify candidate genes involved in such resistance mechanisms. We first characterized variation in resistance to M. nivale among non-acclimated genotypes from the Norwegian cultivar 'Fagerlin' based on relative regrowth and fungal quantification by real-time qPCR. One resistant and one susceptible genotype were selected for transcriptome analysis using paired-end sequencing by Illumina Hiseq 2000. Transcriptome profiles, GO enrichment and KEGG pathway analysis indicate that defense response related genes are differentially expressed between the resistant and the susceptible genotype. A significant up-regulation of defense related genes, as well as genes involved in cell wall cellulose metabolic processes and aryl-alcohol dehydrogenase (NADP+) activity, was observed in the resistant genotype. The candidate genes identified in this study might be potential molecular marker resources for breeding perennial ryegrass cultivars with improved resistance to pink snow mould.

  5. Global transcriptome changes in perennial ryegrass during early infection by pink snow mould

    PubMed Central

    Kovi, Mallikarjuna Rao; Abdelhalim, Mohamed; Kunapareddy, Anil; Ergon, Åshild; Tronsmo, Anne Marte; Brurberg, May Bente; Hofgaard, Ingerd Skow; Asp, Torben; Rognli, Odd Arne

    2016-01-01

    Lack of resistance to pink snow mould (Microdochium nivale) is a major constraint for adaptation of perennial ryegrass (Lolium perenne L.) to continental regions with long-lasting snow cover at higher latitudes. Almost all investigations of genetic variation in resistance have been performed using cold acclimated plants. However, there may be variation in resistance mechanisms that are functioning independently of cold acclimation. In this study our aim was to identify candidate genes involved in such resistance mechanisms. We first characterized variation in resistance to M. nivale among non-acclimated genotypes from the Norwegian cultivar ‘Fagerlin’ based on relative regrowth and fungal quantification by real-time qPCR. One resistant and one susceptible genotype were selected for transcriptome analysis using paired-end sequencing by Illumina Hiseq 2000. Transcriptome profiles, GO enrichment and KEGG pathway analysis indicate that defense response related genes are differentially expressed between the resistant and the susceptible genotype. A significant up-regulation of defense related genes, as well as genes involved in cell wall cellulose metabolic processes and aryl-alcohol dehydrogenase (NADP+) activity, was observed in the resistant genotype. The candidate genes identified in this study might be potential molecular marker resources for breeding perennial ryegrass cultivars with improved resistance to pink snow mould. PMID:27346054

  6. Global transcriptome changes in perennial ryegrass during early infection by pink snow mould.

    PubMed

    Kovi, Mallikarjuna Rao; Abdelhalim, Mohamed; Kunapareddy, Anil; Ergon, Åshild; Tronsmo, Anne Marte; Brurberg, May Bente; Hofgaard, Ingerd Skow; Asp, Torben; Rognli, Odd Arne

    2016-01-01

    Lack of resistance to pink snow mould (Microdochium nivale) is a major constraint for adaptation of perennial ryegrass (Lolium perenne L.) to continental regions with long-lasting snow cover at higher latitudes. Almost all investigations of genetic variation in resistance have been performed using cold acclimated plants. However, there may be variation in resistance mechanisms that are functioning independently of cold acclimation. In this study our aim was to identify candidate genes involved in such resistance mechanisms. We first characterized variation in resistance to M. nivale among non-acclimated genotypes from the Norwegian cultivar 'Fagerlin' based on relative regrowth and fungal quantification by real-time qPCR. One resistant and one susceptible genotype were selected for transcriptome analysis using paired-end sequencing by Illumina Hiseq 2000. Transcriptome profiles, GO enrichment and KEGG pathway analysis indicate that defense response related genes are differentially expressed between the resistant and the susceptible genotype. A significant up-regulation of defense related genes, as well as genes involved in cell wall cellulose metabolic processes and aryl-alcohol dehydrogenase (NADP+) activity, was observed in the resistant genotype. The candidate genes identified in this study might be potential molecular marker resources for breeding perennial ryegrass cultivars with improved resistance to pink snow mould. PMID:27346054

  7. Deeper winter snow reduces ecosystem C losses but increases the global warming potential of Arctic tussock tundra over the growing season.

    NASA Astrophysics Data System (ADS)

    Blanc-Betes, E.; Welker, J. M.; Gomez-Casanovas, N.; Gonzalez-Meler, M. A.

    2015-12-01

    Arctic winter precipitation is projected to increase globally over the next decades, spatial variability encompassing areas with increases and decreases in winter snow. Changes in winter precipitation strongly affect C dynamics in Arctic systems and may lead to major positive climate forcing feedbacks. However, impacts of predicted changes in snowfall and accumulation on the rate and form of C fluxes (CO2 and CH4) and associated forcing feedbacks from Arctic tundra remain uncertain. We investigated how changes in winter precipitation affect net ecosystem CO2 and CH4 fluxes and budgets of moist acidic tundra in an 18-yrs snow fence experiment over a complete growing season at Toolik Lake, AK. Arctic tundra under ambient winter precipitation (CTL) was a net source of CO2 and CH4, yielding net C losses over the growing season. Reduced snow (-15-30% snow depth; RS) switched the system to a net CO2 sink mostly by limiting SOC decomposition within colder soils. Snow additions progressively reduced net ecosystem CO2 losses compared to CTL, switching the system into a weaker net CO2 source with medium additions (+20-45% snow depth; MS) and into a small net CO2 sink with high additions (+70-100% snow depth; HS). Increasingly wetter soils with snow additions constrained the temperature sensitivity of aerobic decomposition and favored the anaerobic metabolism, buffering ecosystem CO2 losses despite substantial soil warming. Accordingly, Arctic tundra switched from a sustained CH4 sink at RS site to an increasingly stronger CH4 source with snow additions. Accounting for both CO2 and CH4, the RS site became a net C sink over the growing season, overall reducing the global warming potential (CO2 equiv.; GWP) of the system relative to CTL. Snow additions progressively reduced net C losses at the MS site compared to CTL and the system transitioned into a net C sink at HS plots, partly due to the slower metabolism of anaerobic decomposition. However, given the greater radiative

  8. The impact of snow nitrate photolysis on boundary layer chemistry and the recycling and redistribution of reactive nitrogen across Antarctica in a global chemical transport model

    NASA Astrophysics Data System (ADS)

    Zatko, M. C.; Geng, L.; Alexander, B.; Sofen, E. D.; Klein, K.

    2015-07-01

    The formation and recycling of reactive nitrogen (NO, NO2, HONO) at the air-snow interface has implications for air quality and the oxidation capacity of the atmosphere in snow-covered regions. Nitrate(NO3-) photolysis in snow provides a source of oxidants (e.g., hydroxyl radical, ozone) and oxidant precursors (e.g., nitrogen oxides) to the overlying boundary layer, and disturbs the preservation of NO3- in ice cores. We have incorporated the photolysis of Antarctic snow NO3- into a global chemical transport model (GEOS-Chem) to examine the implications of snow NO3- photolysis for boundary layer chemistry, the recycling and redistribution of reactive nitrogen across the Antarctic continent, and the preservation of ice-core NO3- in Antarctic ice cores. The calculated potential flux of snow-sourced NOx in Antarctica (0.5-7.8 × 108 molec cm-2 s-1) and calculated e-folding depths of UV actinic flux in snowpack (24-69 cm) are comparable to observations. Snow-sourced NOx increases mean austral summer boundary layer mixing ratios of total nitrate (HNO3 + NO3-), NOx, OH, and O3 in Antarctica by a factor of up to 32, 38, 7, and 2, respectively, in the model. Model results also suggest that NO3- can be recycled between the air and snow multiple times and that NO3- can remain in the snow photic zone for at least 7.5 years on the East Antarctic plateau. The fraction of photolysis-driven loss of NO3- from the snow is ∼ 0.99 on the East Antarctic plateau, while areas of wind convergence (e.g., over the Ronne Ice Shelf) have a net gain of NO3- due to redistribution of snow-sourced reactive nitrogen across the Antarctic continent. The modeled enrichment in ice-core δ 15N(NO3-) due to photolysis-driven loss of snow NO3- ranges from 0 to 363 ‰ and the magnitudes of the spatial trends are consistent with δ 15N(NO3-) observations, suggesting that the spatial variability in snow δ 15N(NO3-) across the Antarctic continent is determined mainly by the degree of photolysis

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

    NASA Astrophysics Data System (ADS)

    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

  10. Appalachia Snow

    Atmospheric Science Data Center

    2014-05-15

    ... on December 4 and 5, 2002, also brought the season's first snow to parts of the south and southern Appalachia. The extent of snow cover over central Kentucky, eastern Tennessee, western North Carolina and ...

  11. NOAA's National Snow Analyses

    NASA Astrophysics Data System (ADS)

    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

    . The NOHRSC NSA products are used operationally by NOAA's National Weather Service field offices when issuing hydrologic forecasts and warnings including river and flood forecasts, water supply forecasts, and spring flood outlooks for the nation. Additionally, the NOHRSC NSA products are used by a wide variety of federal, state, local, municipal, private-sector, and general-public end-users with a requirement for real-time snowpack information. The paper discusses, in detail, the techniques and procedures used to create the NOHRSC NSA products and gives a number of examples of the real-time snow products generated and distributed over the NOHRSC web site (www.nohrsc.noaa.gov). Also discussed are major limitations of the approach, the most notable being deficiencies in observation of snow water equivalent. Snow observation networks generally lack the consistency and coverage needed to significantly improve confidence in snow model states through updating. Many regions of the world simply lack snow water equivalent observations altogether, a significant constraint on global application of the NSA approach.

  12. Estimating snow depth from observations of remotely-sensed snow covered area and the terrain's snow holding capacity

    NASA Astrophysics Data System (ADS)

    Schneider, D.; Molotch, N. P.

    2015-12-01

    Snowmelt is the primary water source in the Western United States and mountainous regions globally. Forecasts of streamflow and water supply rely heavily on snow measurements from sparse observation networks that may not provide adequate information during abnormal climatic conditions. Satellite observations of snow covered area are available globally and in near real-time. In this regard, we have developed a method to estimate snow depth from remotely-sensed images of snow covered area by considering the snow holding capacity of the terrain. We show that the relationship between basin-wide average snow depth, as interpolated from snow surveys, and Landsat TM/ETM+-derived basin snow covered area yields an r2 of 0.64 and 0.68 in two alpine basins of different climatologies in California and Colorado, respectively. Regression analyses that use fractional snow covered as the independent variable to estimate snow depth from a high resolution Lidar survey result in relative mean squared errors between 39% and 58% of measured snow depth for different roughness classifications near the date of peak accumulation. Future work will look at the changes in the relationship between snow depth and snow covered area through the ablation season to determine the relationship's utility to water supply forecasting. The importance of this work is illustrated through examples that estimate snow depths for select alpine regions globally.

  13. Remote Sensing of Snow Cover. Section; Snow Extent

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Frei, Allan; Drey, Stephen J.

    2012-01-01

    Snow was easily identified in the first image obtained from the Television Infrared Operational Satellite-1 (TIROS-1) weather satellite in 1960 because the high albedo of snow presents a good contrast with most other natural surfaces. Subsequently, the National Oceanic and Atmospheric Administration (NOAA) began to map snow using satellite-borne instruments in 1966. Snow plays an important role in the Earth s energy balance, causing more solar radiation to be reflected back into space as compared to most snow-free surfaces. Seasonal snow cover also provides a critical water resource through meltwater emanating from rivers that originate from high-mountain areas such as the Tibetan Plateau. Meltwater from mountain snow packs flows to some of the world s most densely-populated areas such as Southeast Asia, benefiting over 1 billion people (Immerzeel et al., 2010). In this section, we provide a brief overview of the remote sensing of snow cover using visible and near-infrared (VNIR) and passive-microwave (PM) data. Snow can be mapped using the microwave part of the electromagnetic spectrum, even in darkness and through cloud cover, but at a coarser spatial resolution than when using VNIR data. Fusing VNIR and PM algorithms to produce a blended product offers synergistic benefits. Snow-water equivalent (SWE), snow extent, and melt onset are important parameters for climate models and for the initialization of atmospheric forecasts at daily and seasonal time scales. Snowmelt data are also needed as input to hydrological models to improve flood control and irrigation management.

  14. MODIS Snow-Cover Products

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Riggs, George A.; Salomonson, Vinvent V.; DiGirolamo, Nicolo; Bayr, Klaus J.; Houser, Paul (Technical Monitor)

    2001-01-01

    On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. These products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to the currently available operation products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set is generated for long-term climates studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the product. The snow product suite starts with a 500-m resolution swath snow-cover map which is gridded to the Integerized Sinusoidal Grid to produce daily and eight-day composite tile products. The sequence then proceeds to a climate-modeling grid product at 5-km spatial resolution, with both daily and eight-day composite products. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.

  15. Snow Art

    ERIC Educational Resources Information Center

    Kraus, Nicole

    2012-01-01

    It was nearing the end of a very long, rough winter with a lot of snow and too little time to play outside. The snow had formed small hills and valleys over the bushes and this was at the perfect height for the students to paint. In this article, the author describes how her transitional first-grade students created snow art paintings. (Contains 1…

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

    through the seasons. A blended snow product, the Air Force Weather Agency and NASA (ANSA) snow algorithm and product has recently been developed. The ANSA algorithm blends the MODIS snow cover and AMSR-E SWE products into a single snow product that has been shown to improve the performance of snow cover mapping. In this study components of the ANSA snow algorithm are used along with additional MODIS data to monitor daily changes in snow cover over the period of 1 February to 30 June 2008.

  17. Black carbon aerosol size in snow.

    PubMed

    Schwarz, J P; Gao, R S; Perring, A E; Spackman, J R; Fahey, D W

    2013-01-01

    The effect of anthropogenic black carbon (BC) aerosol on snow is of enduring interest due to its consequences for climate forcing. Until now, too little attention has been focused on BC's size in snow, an important parameter affecting BC light absorption in snow. Here we present first observations of this parameter, revealing that BC can be shifted to larger sizes in snow than are typically seen in the atmosphere, in part due to the processes associated with BC removal from the atmosphere. Mie theory analysis indicates a corresponding reduction in BC absorption in snow of 40%, making BC size in snow the dominant source of uncertainty in BC's absorption properties for calculations of BC's snow albedo climate forcing. The shift reduces estimated BC global mean snow forcing by 30%, and has scientific implications for our understanding of snow albedo and the processing of atmospheric BC aerosol in snowfall.

  18. MODIS Snow-Cover Products

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; DiGirolamo, Nicole E.; Bayr, Klaus J.; Houser, Paul R. (Technical Monitor)

    2002-01-01

    On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. MODIS snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to or enhancement of the currently-available operational products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The MODIS snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at about 5.6-km spatial resolution, with both daily and 8-day composite products. Each pixel of the CMG contains fraction of snow cover from 40 - 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02 - 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented to show some early validation work.

  19. Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis

    PubMed Central

    Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

    2016-01-01

    In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as “responding biomarkers” by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress. PMID:27171077

  20. Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis.

    PubMed

    Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

    2016-01-01

    In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as "responding biomarkers" by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress. PMID:27171077

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

    NASA Astrophysics Data System (ADS)

    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

  2. The Impact of Detailed Snow Physics on the Simulation of Snow Cover and Subsurface Thermodynamics at Continental Scales

    NASA Technical Reports Server (NTRS)

    Stieglitz, Marc; Ducharne, Agnes; Koster, Randy; Suarez, Max; Busalacchi, Antonio J. (Technical Monitor)

    2000-01-01

    The three-layer snow model is coupled to the global catchment-based Land Surface Model (LSM) of the NASA Seasonal to Interannual Prediction Project (NSIPP) project, and the combined models are used to simulate the growth and ablation of snow cover over the North American continent for the period 1987-1988. The various snow processes included in the three-layer model, such as snow melting and re-freezing, dynamic changes in snow density, and snow insulating properties, are shown (through a comparison with the corresponding simulation using a much simpler snow model) to lead to an improved simulation of ground thermodynamics on the continental scale.

  3. Snow-Cover Variability in North America in the 2000-2001 Winter as Determined from MODIS Snow Products

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Chien, Y. L.; Houser, Paul R. (Technical Monitor)

    2001-01-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover maps have been available since September 13, 2000. These products, at 500-m spatial resolution, are available through the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado. By the 2001-02 winter, 5-km climate-modeling grid (CMG) products will be available for presentation of global views of snow cover and for use in climate models. All MODIS snow-cover products are produced from automated algorithms that map snow in an objective manner. In this paper, we describe the MODIS snow products, and show snow maps from the fall of 2000 in North America.

  4. Snow-Cover Variability in North America in the 2000-2001 Winter as Determined from MODIS Snow Products

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Chien, Janet Y. L.; Houser, Paul R. (Technical Monitor)

    2001-01-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover maps have been available since September 13, 2000. These products, at 500 m spatial resolution, are available through the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado. By the 2001-02 winter, 5 km climate-modeling grid (CMG) products will be available for presentation of global views of snow cover and for use in climate models. All MODIS snow-cover products are produced from automated algorithms that map snow in an objective manner. In this paper, we describe the MODIS snow products, and show snow maps from the fall of 2000 in North America.

  5. Are extreme cold waves characteristics and snow-temperature feedback well represented in regional and global climate models (WRF and CMIP3/CMIP5)?

    NASA Astrophysics Data System (ADS)

    Quesada, Benjamin; Vautard, Robert; Yiou, Pascal

    2013-04-01

    Despite their economical and health impacts, only a few recent studies concern extreme cold events. However, recent decade was punctuated by cold waves in Europe as during winter 2009-2010, December 2010 and February 2012. Extreme cold days will probably narrow globally in frequency in a global warming future (e.g., 2046-2065) albeit still remain present in regions favored by cold waves such as Europe or United States. Thus, the present-day evaluation (i.e. 1961-2000 period) of climate variability modeled by GCM/RCM remains critical in order to model consistently extreme events characteristics in the future. In this study, an array of global (CMIP3/CMIP5) and regional (WRF) climate models run on Europe domains compared with observations (EOBS) and reanalysis data (ERA 40/ERA Interim) is used to analyze different aspects of extreme cold waves. For each model, skewness and several statistical indices of frequency, intensity, temporal and spatial persistence (coherent in terms of health and energy impacts), for cold spells are calculated in order to assess the capacity of climate models to simulate these extreme events. The purpose of this study is also to address the origins of biases obtained among the models. First, the impact of resolution is analyzed by comparing regional and global climate model output and studying a global climate model (IPSLCM5/CMIP5) on different horizontal scales. Second, a modeling study with regional climate model WRF forced by reanalysis is carried out in order to estimate, with sensitivity analyses, snow/temperature relationship in the development of extreme European cold waves cases. Finally, future projections (2045-2065 period; scenario A2 or RCP8.5) are carried out taking into account the above-mentioned capacity of climate models to represent the extreme cold waves characteristics on present-day period.

  6. MODIS Snow and Sea Ice Products

    NASA Technical Reports Server (NTRS)

    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.

  7. The History of Winter and the Global Snowflake Network, Engaging Teachers and Students in Science Field Research in Snow and Ice

    NASA Astrophysics Data System (ADS)

    Bender, K. J.; Wasilewski, P. J.; Gabrys, R. E.

    2006-05-01

    A weeklong Professional development/"Teacher as scientist" Cryosphere science training camp held annually in February in Lake Placid, NY, the History of Winter program (HOW) has been serving teachers in the NASA Goddard Space Flight Center service area since 2000. Currently, HOW participants include university faculty interested in enhancing their pre-service science education programs, in-service teachers and pre-service education students. HOW utilizes a stratified professional development approach to science content mastery and delivery while involving participants in scientific field research. Each year program components and resources are added to HOW to provide continued, sustainable interest in the program and to support participants as they continue their HOW experience. An offshoot of the HOW Program, the Global Snowflake Network (GSN) launched in the winter of 2006 engages an international audience including both formal and informal education groups. The goal is to provide an interactive online data resource in science and education for the characterization of snowfall and related weather systems. The Global Snowflake Network has been accepted as an education outreach proposal for the International Polar Year. Collaborations with other agencies and universities also with IPY-accepted proposals are now underway. HOW and the GSN are endorsed by the NASA Goddard Education Office and many of the Goddard Snow and Ice scientists. Together these programs offer a unique, sustainable, and proven outreach for the Cryosphere research program.

  8. Incorporation of the Mass Concentration and the New Snow Albedo Schemes into the Global Forecasting Model, GEOS-5 and the Impact of the New Schemes over Himalayan Glaciers

    NASA Technical Reports Server (NTRS)

    Yasunari, Teppei

    2012-01-01

    Recently the issue on glacier retreats comes up and many factors should be relevant to the issue. The absorbing aerosols such as dust and black carbon (BC) are considered to be one of the factors. After they deposited onto the snow surface, it will reduce snow albedo (called snow darkening effect) and probably contribute to further melting of glacier. The Goddard Earth Observing System version 5 (GEOS-5) has developed at NASA/GSFC. However, the original snowpack model used in the land surface model in the GEOS-5 did not consider the snow darkening effect. Here we developed the new snow albedo scheme which can consider the snow darkening effect. In addition, another scheme on calculating mass concentrations on the absorbing aerosols in snowpack was also developed, in which the direct aerosol depositions from the chemical transport model in the GEOS-5 were used. The scheme has been validated with the observed data obtained at backyard of the Institute of Low Temperature Science, Hokkaido University, by Dr. Teruo Aoki (Meteorological Research Institute) et aL including me. The observed data was obtained when I was Ph.D. candidate. The original GEOS-5during 2007-2009 over the Himalayas and Tibetan Plateau region showed more reductions of snow than that of the new GEOS-5 because the original one used lower albedo settings. On snow cover fraction, the new GEOS-5 simulated more realistic snow-covered area comparing to the MODIS snow cover fraction. The reductions on snow albedo, snow cover fraction, and snow water equivalent were seen with statistically significance if we consider the snow darkening effect comparing to the results without the snow darkening effect. In the real world, debris cover, inside refreezing process, surface flow of glacier, etc. affect glacier mass balance and the simulated results immediately do not affect whole glacier retreating. However, our results indicate that some surface melting over non debris covered parts of the glacier would be

  9. A Gauge - OLR Blended Analysis of Global Daily Precipitation: A 37-Year Data Record for Hydroclimate Applications

    NASA Astrophysics Data System (ADS)

    Xie, P.; Lee, H. T.; Meng, J.; Mo, K. C.; Ek, M. B.

    2015-12-01

    Many precipitation data sets have been produced in the past two decades based on gauge measurements, satellite observations and their combinations. Their applications in hydroclimate, however, are compromised by a number of shortcomings in long-term homogeneity, quantitative accuracy, and time/space resolution. The objective of this work is to construct a homogenous analysis of daily precipitation on a 0.25olat/lon grid over the global land for a 37-year period from 1979 to the present through combining information from CDR for the satellite observed HIRS OLR, as well as daily and monthly gauge data. First, CPC unified daily gauge analysis is calibrated against the GPCC monthly gauge data set to correct under-estimates in the daily analysis caused by the negatively biased daily station reports. The resulting adjusted daily gauge analysis presents improved quantitative accuracy over regions with reasonable gauge coverage. A technique is then developed to derive precipitation estimates from the OLR data. PDF tables are created for the OLR and matched against those for the collocated CMORPH satellite precipitation estimates using data for 1998 to 2014. An observed HIRS OLR value is converted to precipitation through the matched OLR and precipitation PDF tables. The technique is applied to generate precipitation estimates on a 0.25olat/lon grid over the globe for the entire HIRS OLR data period from 1979. The adjusted daily gauge analysis and the HIRS OLR-based precipitation estimates are then blended through the OI technique. The OLR precipitation estimates are used as the first guess, while the gauge data are utilized as the observation to refine the first guess. A suite of comprehensive procedures are implemented to examine the quantitative accuracy and homogeneity of the 37-year daily precipitation data set. In particular, experiments are conducted to force the Noah land model with our new daily precipitation analysis operating under the NCEP Global Land Data

  10. Linking snowfall and snow accumulation to generate spatial maps of SWE and snow depth

    NASA Astrophysics Data System (ADS)

    Broxton, Patrick D.; Dawson, Nicholas; Zeng, Xubin

    2016-06-01

    It is critically important but challenging to estimate the amount of snow on the ground over large areas due to its strong spatial variability. Point snow data are used to generate or improve (i.e., blend with) gridded estimates of snow water equivalent (SWE) by using various forms of interpolation; however, the interpolation methodologies often overlook the physical mechanisms for the snow being there in the first place. Using data from the Snow Telemetry and Cooperative Observer networks in the western United States, we show that four methods for the spatial interpolation of peak of winter snow water equivalent (SWE) and snow depth based on distance and elevation can result in large errors. These errors are reduced substantially by our new method, i.e., the spatial interpolation of these quantities normalized by accumulated snowfall from the current or previous water years. Our method results in significant improvement in SWE estimates over interpolation techniques that do not consider snowfall, regardless of the number of stations used for the interpolation. Furthermore, it can be used along with gridded precipitation and temperature data to produce daily maps of SWE over the western United States that are comparable to existing estimates (which are based on the assimilation of much more data). Our results also show that not honoring the constraint between SWE and snowfall when blending in situ data with gridded data can lead to the development and propagation of unrealistic errors.

  11. Detecting Falling Snow from Space

    NASA Technical Reports Server (NTRS)

    Jackson, Gail Skofronick; Johnson, Ben; Munchak, Joe

    2012-01-01

    There is an increased interest in detecting and estimating the amount of falling snow reaching the Earth's surface in order to fully capture the atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms includes determining the thresholds of detection for various active and passive sensor channel configurations, snow event cloud structures and microphysics, snowflake particle electromagnetic properties, and surface types. In this work, cloud resolving model simulations of a lake effect and synoptic snow event were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W -band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) Ku and Ka band, and the GPM Microwave Imager (GMI) channels from 10 to 183 plus or minus 7 GHz. Eleven different snowflake shapes were used to compute radar reflectivities and passive brightness temperatures. Notable results include: (1) the W-Band radar has detection thresholds more than an order of magnitude lower than the future GPM sensors, (2) the cloud structure macrophysics influences the thresholds of detection for passive channels, (3) the snowflake microphysics plays a large role in the detection threshold for active and passive instruments, (4) with reasonable assumptions, "the passive 166 GHz channel has detection threshold values comparable to the GPM DPR Ku and Ka band radars with approximately 0.05 g per cubic meter detected at the surface, or an approximately 0.5-1 millimeter per hr. melted snow rate (equivalent to 0.5-2 centimeters per hr. solid fluffy snowflake rate). With detection levels of falling snow known, we can focus current and future retrieval efforts on detectable storms and concentrate advances on achievable results. We will also have an understanding of the light snowfall events missed by the sensors and not captured in the global estimates.

  12. Snow Avalanches

    NASA Astrophysics Data System (ADS)

    Ancey, C.

    Over the last century, mountain ranges in Europe and North America have seen substantial development due to the increase in recreational activities, transportation, construction in high altitude areas, etc. In these mountain ranges, avalanches often threaten man's activities and life. Typical examples include recent disasters, such as the avalanche at Val d'Isère in 1970 (39 people were killed in a hostel) or the series of catastrophic avalanches throughout the Northern Alps in February 1999 (62 residents killed). The rising demand for higher safety measures has given new impetus to the development of mitigation technology and has given rise to a new scientific area entirely devoted to snow and avalanches. This paper summarises the paramount features of avalanches (formation and motion) and outlines the main approaches used for describing their movement. We do not tackle specific problems related to snow mechanics and avalanche forecasting. For more information on the subject, the reader is referred to the main textbooks published in Alpine countries [1-8].

  13. Snow Radiance Assimilation Studies

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  14. Yeah!!! A Snow Day!

    ERIC Educational Resources Information Center

    Cone, Theresa Purcell; Cone, Stephen L.

    2006-01-01

    As children see the first snowflake fall from the sky, they are filled with anticipation of playing in the snow. The snowy environment presents a wonderful opportunity for presenting interdisciplinary activities that connect snow play, snow formation, and snow stories with manipulative activities, gymnastic balances, and dance sequences. In this…

  15. New nitrogen uptake strategy: specialized snow roots.

    PubMed

    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.

  16. A Comparison of Satellite-Derived Snow Maps with a Focus on Ephemeral Snow in North Carolina

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Fuhrmann, Christopher M.; Perry, L. Baker; Riggs, George A.; Robinson, David A.; Foster, James L.

    2010-01-01

    In this paper, we focus on the attributes and limitations of four commonly-used daily snowcover products with respect to their ability to map ephemeral snow in central and eastern North Carolina. We show that the Moderate-Resolution Imaging Spectroradiometer (MODIS) fractional snow-cover maps can delineate the snow-covered area very well through the use of a fully-automated algorithm, but suffer from the limitation that cloud cover precludes mapping some ephemeral snow. The semi-automated Interactive Multi-sensor Snow and ice mapping system (IMS) and Rutgers Global Snow Lab (GSL) snow maps are often able to capture ephemeral snow cover because ground-station data are employed to develop the snow maps, The Rutgers GSL maps are based on the IMS maps. Finally, the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) provides some good detail of snow-water equivalent especially in deeper snow, but may miss ephemeral snow cover because it is often very thin or wet; the AMSR-E maps also suffer from coarse spatial resolution. We conclude that the southeastern United States represents a good test region for validating the ability of satellite snow-cover maps to capture ephemeral snow cover,

  17. Snow Bedforms Create the Surface Roughness of Polar Snow

    NASA Astrophysics Data System (ADS)

    Filhol, S.; Sturm, M.

    2015-12-01

    Polar snow surfaces are rough. The wind moves, piles up, and scours snow grains from the snow surface, and recombines them into various shapes also called bedforms. Individual bedforms may have shapes that can be readily described and perhaps understood, but one storm event after another generate a complex compound surface whose roughness is the sum of both deposition and erosion. Characterizing and understanding the origin of this bedform roughness is one key toward a better estimation of precipitation at a global scale from microwave remote sensing, and also a better understanding of two critical sea ice processes; the transfer of momentum from the atmosphere to ice floes, and the spatial distribution of melt ponds in springtime. During this presentation, we will describe the dynamics of snow bedform formation and we will explore how the basic palette of bedforms combined with a unique weather history can reveal the genesis of a rough snow surface. Detailed laser scanner maps of bedforms measured in Arctic Alaska will be used to illustrate these processes and forms.

  18. Snow particle speeds in drifting snow

    NASA Astrophysics Data System (ADS)

    Nishimura, Kouichi; Yokoyama, Chika; Ito, Yoichi; Nemoto, Masaki; Naaim-Bouvet, Florence; Bellot, Hervé; Fujita, Koji

    2014-08-01

    Knowledge of snow particle speeds is necessary for deepening our understanding of the internal structures of drifting snow. In this study, we utilized a snow particle counter (SPC) developed to observe snow particle size distributions and snow mass flux. Using high-frequency signals from the SPC transducer, we obtained the sizes of individual particles and their durations in the sampling area. Measurements were first conducted in the field, with more precise measurements being obtained in a boundary layer established in a cold wind tunnel. The obtained results were compared with the results of a numerical analysis. Data on snow particle speeds, vertical velocity profiles, and their dependence on wind speed obtained in the field and in the wind tunnel experiments were in good agreement: both snow particle speed and wind speed increased with height, and the former was always 1 to 2 m s-1 less than the latter below a height of 1 m. Thus, we succeeded in obtaining snow particle speeds in drifting snow, as well as revealing the dependence of particle speed on both grain size and wind speed. The results were verified by similar trends observed using random flight simulations. However, the difference between the particle speed and the wind speed in the simulations was much greater than that observed under real conditions. Snow transport by wind is an aeolian process. Thus, the findings presented here should be also applicable to other geophysical processes relating to the aeolian transport of particles, such as blown sand and soil.

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

    NASA Astrophysics Data System (ADS)

    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

  20. Satellite Snow-Cover Mapping: A Brief Review

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.

    1995-01-01

    Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow

  1. Snow depth on Arctic and Antarctic sea ice derived from autonomous (Snow Buoy) measurements

    NASA Astrophysics Data System (ADS)

    Nicolaus, Marcel; Arndt, Stefanie; Hendricks, Stefan; Heygster, Georg; Huntemann, Marcus; Katlein, Christian; Langevin, Danielle; Rossmann, Leonard; Schwegmann, Sandra

    2016-04-01

    The snow cover on sea ice received more and more attention in recent sea ice studies and model simulations, because its physical properties dominate many sea ice and upper ocean processes. In particular; the temporal and spatial distribution of snow depth is of crucial importance for the energy and mass budgets of sea ice, as well as for the interaction with the atmosphere and the oceanic freshwater budget. Snow depth is also a crucial parameter for sea ice thickness retrieval algorithms from satellite altimetry data. Recent time series of Arctic sea ice volume only use monthly snow depth climatology, which cannot take into account annual changes of the snow depth and its properties. For Antarctic sea ice, no such climatology is available. With a few exceptions, snow depth on sea ice is determined from manual in-situ measurements with very limited coverage of space and time. Hence the need for more consistent observational data sets of snow depth on sea ice is frequently highlighted. Here, we present time series measurements of snow depths on Antarctic and Arctic sea ice, recorded by an innovative and affordable platform. This Snow Buoy is optimized to autonomously monitor the evolution of snow depth on sea ice and will allow new insights into its seasonality. In addition, the instruments report air temperature and atmospheric pressure directly into different international networks, e.g. the Global Telecommunication System (GTS) and the International Arctic Buoy Programme (IABP). We introduce the Snow Buoy concept together with technical specifications and results on data quality, reliability, and performance of the units. We highlight the findings from four buoys, which simultaneously drifted through the Weddell Sea for more than 1.5 years, revealing unique information on characteristic regional and seasonal differences. Finally, results from seven snow buoys co-deployed on Arctic sea ice throughout the winter season 2015/16 suggest the great importance of local

  2. Camping in the Snow.

    ERIC Educational Resources Information Center

    Brown, Constance

    1979-01-01

    Describes the experience of winter snow camping. Provides suggestions for shelter, snow kitchens, fires and stoves, cooking, latrines, sleeping warm, dehydration prevention, and clothing. Illustrated with full color photographs. (MA)

  3. Remote sensing of global snowpack energy and mass balance: In-situ measurements on the snow of interior and Arctic Alaska

    NASA Technical Reports Server (NTRS)

    Benson, Carl S.

    1989-01-01

    Observations led to a study of the physical properties of snow and the processes which operate on it. These observations included microwave brightness temperatures in interior Alaska which revealed: (1) up to three times more variability from one cell (1/2 degree latitude x 1/2 degree longitude) to the next in winter than in summer (5 to 15 K in winter and about 5 K in summer); (2) the overall range of temperature from week to week is about seven times greater in winter than in summer; (3) the microwave brightness temperature is about 25 K less than air temperature during summer but 35 to 60 K less during winter; and (4) the presence of snow cover appears to contribute to increasing the difference between air temperature and brightness temperature. The role of irregular substrate under the snow in enhancing convection has been studied with particular attention to variations in snow cover on water surfaces and in forested regions. LANDSAT imagery has been obtained to prepare a classification of ground surface types of the area. The extreme conditions of the 1988 to 1989 winter are discussed with respect to comparing the microwave data sets from 1985, and before, up to the present. The use of the Mt. Wrangell area as aerial photogrammetric controls for glacier measurements is given attention.

  4. Remote sensing of global snowpack energy and mass balance: In-situ measurements on the snow of interior and Arctic Alaska

    NASA Technical Reports Server (NTRS)

    Benson, Carl S.

    1994-01-01

    This project is continuing along the lines of the semiannual report dated January 1993. Four major tasks have been addressed: analysis of variability in the seasonal snow of interior and arctic Alaska, the interpretation of microwave brightness temperature across Alaska on transects from south to north, study of nonclimatic controls which affect glaciers, and the location of glacier facies boundaries.

  5. Snow Bank Detectives

    ERIC Educational Resources Information Center

    Olson, Eric A.; Rule, Audrey C.; Dehm, Janet

    2005-01-01

    In the city where the authors live, located on the shore of Lake Ontario, children have ample opportunity to interact with snow. Water vapor rising from the relatively warm lake surface produces tremendous "lake effect" snowfalls when frigid winter winds blow. Snow piles along roadways after each passing storm, creating impressive snow banks. When…

  6. Blended Learning

    ERIC Educational Resources Information Center

    Tucker, Catlin; Umphrey, Jan

    2013-01-01

    Catlin Tucker, author of "Blended Learning in Grades 4-12," is an English language arts teacher at Windsor High School in Sonoma County, CA. In this conversation with "Principal Leadership," she defines blended learning as a formal education program in which a student is engaged in active learning in part online where they…

  7. Blended Learning

    ERIC Educational Resources Information Center

    Imbriale, Ryan

    2013-01-01

    Teachers always have been and always will be the essential element in the classroom. They can create magic inside four walls, but they have never been able to create learning environments outside the classroom like they can today, thanks to blended learning. Blended learning allows students and teachers to break free of the isolation of the…

  8. Sensitivity of Passive Microwave Snow Depth Retrievals to Weather Effects and Snow Evolution

    NASA Technical Reports Server (NTRS)

    Markus, Thorsten; Powell, Dylan C.; Wang, James R.

    2006-01-01

    Snow fall and snow accumulation are key climate parameters due to the snow's high albedo, its thermal insulation, and its importance to the global water cycle. Satellite passive microwave radiometers currently provide the only means for the retrieval of snow depth and/or snow water equivalent (SWE) over land as well as over sea ice from space. All algorithms make use of the frequency-dependent amount of scattering of snow over a high-emissivity surface. Specifically, the difference between 37- and 19-GHz brightness temperatures is used to determine the depth of the snow or the SWE. With the availability of the Advanced Microwave Scanning Radiometer (AMSR-E) on the National Aeronautics and Space Administration's Earth Observing System Aqua satellite (launched in May 2002), a wider range of frequencies can be utilized. In this study we investigate, using model simulations, how snow depth retrievals are affected by the evolution of the physical properties of the snow (mainly grain size growth and densification), how they are affected by variations in atmospheric conditions and, finally, how the additional channels may help to reduce errors in passive microwave snow retrievals. The sensitivity of snow depth retrievals to atmospheric water vapor is confirmed through the comparison with precipitable water retrievals from the National Oceanic and Atmospheric Administration's Advanced Microwave Sounding Unit (AMSU-B). The results suggest that a combination of the 10-, 19-, 37-, and 89-GHz channels may significantly improve retrieval accuracy. Additionally, the development of a multisensor algorithm utilizing AMSR-E and AMSU-B data may help to obtain weather-corrected snow retrievals.

  9. The Role of Snow and Ice in the Climate System

    SciTech Connect

    Barry, Roger G.

    2007-12-19

    Global snow and ice cover (the 'cryosphere') plays a major role in global climate and hydrology through a range of complex interactions and feedbacks, the best known of which is the ice - albedo feedback. Snow and ice cover undergo marked seasonal and long term changes in extent and thickness. The perennial elements - the major ice sheets and permafrost - play a role in present-day regional and local climate and hydrology, but the large seasonal variations in snow cover and sea ice are of importance on continental to hemispheric scales. The characteristics of these variations, especially in the Northern Hemisphere, and evidence for recent trends in snow and ice extent are discussed.

  10. The Role of Snow and Ice in the Climate System

    ScienceCinema

    Barry, Roger G.

    2016-07-12

    Global snow and ice cover (the 'cryosphere') plays a major role in global climate and hydrology through a range of complex interactions and feedbacks, the best known of which is the ice - albedo feedback. Snow and ice cover undergo marked seasonal and long term changes in extent and thickness. The perennial elements - the major ice sheets and permafrost - play a role in present-day regional and local climate and hydrology, but the large seasonal variations in snow cover and sea ice are of importance on continental to hemispheric scales. The characteristics of these variations, especially in the Northern Hemisphere, and evidence for recent trends in snow and ice extent are discussed.

  11. Evaluating the Consistency of Remote Sensing Based Snow Depth Products in Arid Zone of Western China

    NASA Astrophysics Data System (ADS)

    Zhou, Q.; Sun, B.

    2012-08-01

    Snow cover is a sensitive indicator of global climate change. Among various snow cover parameters, snow depth which can indicate snow accumulation is essential for retrieving snow water equivalent. In arid zone of western China, based on different inversion models, snow depth products retrieved from passive microwave remote sensing sensors have been issued. However, none of them can promise a high accuracy due to the spatial heterogeneity of snow cover especially in mountain areas with complex terrain. This study aims to analyse the reliability of existing long-term snow depth products in arid zone of western China. Two datasets are compared including GlobSnow snow water equivalent (SWE) product and snow depth dataset provided by Environmental and Ecological Science Data Center for West China. Statistical techniques like regression and intra-class correlation coefficient (ICC) models are employed to examine the consistency of these two remote sensing based snow depth products in a selected sampling site. More than 260 samples during three years are tested covering from snow falling to snow melting periods. Result shows that there is a discrepancy between the two datasets. Accordingly, remote sensing based snow depth measurement is not reliable in mountain areas in arid zone of western China. This study gives an awareness of the stabilities of current snow depth detection models. A further study is expected to calibrate snow depth products based on in-situ observation and measurements from ground monitoring stations.

  12. Enhancement of the MODIS Daily Snow Albedo Product

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Schaaf, Crystal B.; Wang, Zhuosen; Riggs, George A.

    2009-01-01

    The MODIS daily snow albedo product is a data layer in the MOD10A1 snow-cover product that includes snow-covered area and fractional snow cover as well as quality information and other metadata. It was developed to augment the MODIS BRDF/Albedo algorithm (MCD43) that provides 16-day maps of albedo globally at 500-m resolution. But many modelers require daily snow albedo, especially during the snowmelt season when the snow albedo is changing rapidly. Many models have an unrealistic snow albedo feedback in both estimated albedo and change in albedo over the seasonal cycle context, Rapid changes in snow cover extent or brightness challenge the MCD43 algorithm; over a 16-day period, MCD43 determines whether the majority of clear observations was snow-covered or snow-free then only calculates albedo for the majority condition. Thus changes in snow albedo and snow cover are not portrayed accurately during times of rapid change, therefore the current MCD43 product is not ideal for snow work. The MODIS daily snow albedo from the MOD10 product provides more frequent, though less robust maps for pixels defined as "snow" by the MODIS snow-cover algorithm. Though useful, the daily snow albedo product can be improved using a daily version of the MCD43 product as described in this paper. There are important limitations to the MOD10A1 daily snow albedo product, some of which can be mitigated. Utilizing the appropriate per-pixel Bidirectional Reflectance Distribution Functions (BRDFs) can be problematic, and correction for anisotropic scattering must be included. The BRDF describes how the reflectance varies with view and illumination geometry. Also, narrow-to-broadband conversion specific for snow on different surfaces must be calculated and this can be difficult. In consideration of these limitations of MOD10A1, we are planning to improve the daily snow albedo algorithm by coupling the periodic per-pixel snow albedo from MCD43, with daily surface ref|outanoom, In this paper, we

  13. A real-time snow water equivalent interpolation system using wireless sensor networks and historical remotely sensed data

    NASA Astrophysics Data System (ADS)

    Zheng, Z.; Zhang, Z.; Molotch, N. P.; Glaser, S.; Bales, R. C.; Conklin, M. H.

    2015-12-01

    Over 100 wireless sensors for monitoring real-time snow conditions were deployed in ten clusters distributed across the headwaters of the American River Basin. The sensors are strategically placed to measure snow depth across elevation gradients and local differences in slope, aspect and canopy coverage. The sensors provided near-real-time snow-depth readings during the 2014 and 2015 snow seasons. Also, time series of snow water equivalent (SWE) maps were reconstructed for 2012-2014 using energy-balance modeling with modeled energy forcings (NLDAS), terrain corrections for solar radiation (TOPORAD), and fractional snow cover data (MODIS). We blended the real-time snow-depth readings with the historical SWE reconstructions to interpolate real-time SWE conditions across the basin. Snow-depth readings from all sensors for selected dates in 2014 were converted into SWE estimates using density values from snow-pillow sites in the basin. SWE values for pixels where sensors were located were extracted from the reconstructed 2012-2013 data to develop a time-series array. Using a Nearest-Neighbor algorithm we searched the array for the closest conditions that matched the sensor data, interpolated the residuals between reconstructed versus measured SWE across the basin, and added the interpolated values to the reconstructed SWE. We also blended the sensor measurements with the 2014 reconstruction results that were from the same dates. We evaluated both the historical SWE blending results and the concurrent SWE blending results with the operational networks measurements, finding that the concurrent SWE blending has a slightly lower RMSE compared to that of historical SWE blending. Since the reconstruction results could only be estimated after the end of the season, concurrent SWE blending is not applicable to the real time SWE interpolation even though it has a more accurate estimation. However, the small difference of RMSE between the two approaches informs us that the

  14. Normalized-Difference Snow Index (NDSI)

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Riggs, George A.

    2010-01-01

    The Normalized-Difference Snow Index (NDSI) has a long history. 'The use of ratioing visible (VIS) and near-infrared (NIR) or short-wave infrared (SWIR) channels to separate snow and clouds was documented in the literature beginning in the mid-1970s. A considerable amount of work on this subject was conducted at, and published by, the Air Force Geophysics Laboratory (AFGL). The objective of the AFGL work was to discriminate snow cover from cloud cover using an automated algorithm to improve global cloud analyses. Later, automated methods that relied on the VIS/NIR ratio were refined substantially using satellite data In this section we provide a brief history of the use of the NDSI for mapping snow cover.

  15. A study of stable isotopic variations of Antarctic snow by albedo differences

    NASA Astrophysics Data System (ADS)

    Lee, Jeonghoon; Han, Yeongcheol; Ham, Ji-Young; Kim, Young-Hee; Kim, Songyi; Kim, Hyerin; Na, Un-Sung

    2015-04-01

    Snow's albedo can be decreased if there are any impurities on the snow surface other than snow itself. Due to the decrease of albedo of snow, melting rates of surface snow can be enhanced, which is very crucial in climate change and hydrogeology in many parts of the world. Anthropogenic black carbons caused by the incomplete combustion of fossil fuel affect on snow and tephra particles generated by geologic volcanic activities reduce snow albedo. In this study, we investigated isotopic compositions between snow covered by tephra particles and clean snow. Isotopic compositions of snow with tephra statistically shows more enriched than those of clean snow (p<0.02). This can be explained by the fact that snow becomes enriched in 18O or D relative to meltwater as melting rates are increased. In addition, the slopes of the linear regression between oxygen and hydrogen for snow with tephra and clean snow are 6.7 and 8, respectively, and the latter is similar to that of the global meteoric water line of 8. Therefore, we can conclude that snow impurities control the isotopic compositions of snow, which is very crucial in the study of climate change and hydrogeology. To quantitatively explain these observations, melting experiments and numerical approaches are required.

  16. Assessment of Northern Hemisphere Snow Water Equivalent Datasets in ESA SnowPEx project

    NASA Astrophysics Data System (ADS)

    Luojus, Kari; Pulliainen, Jouni; Cohen, Juval; Ikonen, Jaakko; Derksen, Chris; Mudryk, Lawrence; Nagler, Thomas; Bojkov, Bojan

    2016-04-01

    Reliable information on snow cover across the Northern Hemisphere and Arctic and sub-Arctic regions is needed for climate monitoring, for understanding the Arctic climate system, and for the evaluation of the role of snow cover and its feedback in climate models. In addition to being of significant interest for climatological investigations, reliable information on snow cover is of high value for the purpose of hydrological forecasting and numerical weather prediction. Terrestrial snow covers up to 50 million km² of the Northern Hemisphere in winter and is characterized by high spatial and temporal variability. Therefore satellite observations provide the best means for timely and complete observations of the global snow cover. There are a number of independent SWE products available that describe the snow conditions on multi-decadal and global scales. Some products are derived using satellite-based information while others rely on meteorological observations and modelling. What is common to practically all the existing hemispheric SWE products, is that their retrieval performance on hemispherical and multi-decadal scales are not accurately known. The purpose of the ESA funded SnowPEx project is to obtain a quantitative understanding of the uncertainty in satellite- as well as model-based SWE products through an internationally coordinated and consistent evaluation exercise. The currently available Northern Hemisphere wide satellite-based SWE datasets which were assessed include 1) the GlobSnow SWE, 2) the NASA Standard SWE, 3) NASA prototype and 4) NSIDC-SSM/I SWE products. The model-based datasets include: 5) the Global Land Data Assimilation System Version 2 (GLDAS-2) product 6) the European Centre for Medium-Range Forecasts Interim Land Reanalysis (ERA-I-Land) which uses a simple snow scheme 7) the Modern Era Retrospective Analysis for Research and Applications (MERRA) which uses an intermediate complexity snow scheme; and 8) SWE from the Crocus snow scheme, a

  17. Microwave emissions from snow

    NASA Technical Reports Server (NTRS)

    Chang, A. T. C.

    1984-01-01

    The radiation emitted from dry and wet snowpack in the microwave region (1 to 100 GHz) is discussed and related to ground observations. Results from theoretical model calculations match the brightness temperatures obtained by truck mounted, airborne and spaceborne microwave sensor systems. Snow wetness and internal layer structure complicate the snow parameter retrieval algorithm. Further understanding of electromagnetic interaction with snowpack may eventually provide a technique to probe the internal snow properties

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

    PubMed

    Matsumoto, Naoyuki

    2009-01-01

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

  19. Role of Tibetan Buddhist monasteries in snow leopard conservation.

    PubMed

    Li, Juan; Wang, Dajun; Yin, Hang; Zhaxi, Duojie; Jiagong, Zhala; Schaller, George B; Mishra, Charudutt; McCarthy, Thomas M; Wang, Hao; Wu, Lan; Xiao, Lingyun; Basang, Lamao; Zhang, Yuguang; Zhou, Yunyun; Lu, Zhi

    2014-02-01

    The snow leopard (Panthera uncia) inhabits the rugged mountains in 12 countries of Central Asia, including the Tibetan Plateau. Due to poaching, decreased abundance of prey, and habitat degradation, it was listed as endangered by the International Union for Conservation of Nature in 1972. Current conservation strategies, including nature reserves and incentive programs, have limited capacities to protect snow leopards. We investigated the role of Tibetan Buddhist monasteries in snow leopard conservation in the Sanjiangyuan region in China's Qinghai Province on the Tibetan Plateau. From 2009 to 2011, we systematically surveyed snow leopards in the Sanjiangyuan region. We used the MaxEnt model to determine the relation of their presence to environmental variables (e.g., elevation, ruggedness) and to predict snow leopard distribution. Model results showed 89,602 km(2) of snow leopard habitat in the Sanjiangyuan region, of which 7674 km(2) lay within Sanjiangyuan Nature Reserve's core zones. We analyzed the spatial relation between snow leopard habitat and Buddhist monasteries and found that 46% of monasteries were located in snow leopard habitat and 90% were within 5 km of snow leopard habitat. The 336 monasteries in the Sanjiangyuan region could protect more snow leopard habitat (8342 km(2) ) through social norms and active patrols than the nature reserve's core zones. We conducted 144 household interviews to identify local herders' attitudes and behavior toward snow leopards and other wildlife. Most local herders claimed that they did not kill wildlife, and 42% said they did not kill wildlife because it was a sin in Buddhism. Our results indicate monasteries play an important role in snow leopard conservation. Monastery-based snow leopard conservation could be extended to other Tibetan Buddhist regions that in total would encompass about 80% of the global range of snow leopards.

  20. Role of Tibetan Buddhist monasteries in snow leopard conservation.

    PubMed

    Li, Juan; Wang, Dajun; Yin, Hang; Zhaxi, Duojie; Jiagong, Zhala; Schaller, George B; Mishra, Charudutt; McCarthy, Thomas M; Wang, Hao; Wu, Lan; Xiao, Lingyun; Basang, Lamao; Zhang, Yuguang; Zhou, Yunyun; Lu, Zhi

    2014-02-01

    The snow leopard (Panthera uncia) inhabits the rugged mountains in 12 countries of Central Asia, including the Tibetan Plateau. Due to poaching, decreased abundance of prey, and habitat degradation, it was listed as endangered by the International Union for Conservation of Nature in 1972. Current conservation strategies, including nature reserves and incentive programs, have limited capacities to protect snow leopards. We investigated the role of Tibetan Buddhist monasteries in snow leopard conservation in the Sanjiangyuan region in China's Qinghai Province on the Tibetan Plateau. From 2009 to 2011, we systematically surveyed snow leopards in the Sanjiangyuan region. We used the MaxEnt model to determine the relation of their presence to environmental variables (e.g., elevation, ruggedness) and to predict snow leopard distribution. Model results showed 89,602 km(2) of snow leopard habitat in the Sanjiangyuan region, of which 7674 km(2) lay within Sanjiangyuan Nature Reserve's core zones. We analyzed the spatial relation between snow leopard habitat and Buddhist monasteries and found that 46% of monasteries were located in snow leopard habitat and 90% were within 5 km of snow leopard habitat. The 336 monasteries in the Sanjiangyuan region could protect more snow leopard habitat (8342 km(2) ) through social norms and active patrols than the nature reserve's core zones. We conducted 144 household interviews to identify local herders' attitudes and behavior toward snow leopards and other wildlife. Most local herders claimed that they did not kill wildlife, and 42% said they did not kill wildlife because it was a sin in Buddhism. Our results indicate monasteries play an important role in snow leopard conservation. Monastery-based snow leopard conservation could be extended to other Tibetan Buddhist regions that in total would encompass about 80% of the global range of snow leopards. PMID:23992599

  1. "Let It Snow, Let It Snow, Let It Snow!"

    ERIC Educational Resources Information Center

    Pangbourne, Laura

    2010-01-01

    Winter in the UK has, in recent years, brought a significant amount of snow and cold weather. This was the case while the author was a trainee teacher on placement at a rural primary school in Dartmoor early in 2010. The day started promisingly with the class looking at the weather forecast on the interactive whiteboard and having a short…

  2. Loropetalum chinense 'Snow Panda'

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  3. Let It Snow!

    NASA Astrophysics Data System (ADS)

    Williams, Kathryn R.

    2000-02-01

    The February 1930 issue of JCE contains an article, "Calcium Chloride for Snow Removal", by Lionel Richardson. The author presents a photograph and personal observations of an experimental truck/trailer combination for spreading CaCl2 on Brooklyn's streets after a heavy snowstorm. The From Past Issues story summarizes the 1930 paper and directs readers to additional library resources on snow removal.

  4. Snow and Ice.

    ERIC Educational Resources Information Center

    Minneapolis Independent School District 275, Minn.

    This experimental edition provides a number of activities useful for investigating snow and ice with elementary school children. Commencing with games with ice cubes, the activities lead through studies of snowflakes, snowdrifts, effects of wind and obstacles on the shape and formation of drifts, to a study of animals living under snow. The…

  5. Snow and Glacier Hydrology

    NASA Astrophysics Data System (ADS)

    Brubaker, Kaye

    The study of snow and ice is rich in both fundamental science and practical applications. Snow and Glacier Hydrology offers something for everyone, from resource practitioners in regions where water supply depends on seasonal snow pack or glaciers, to research scientists seeking to understand the role of the solid phase in the water cycle and climate. The book is aimed at the advanced undergraduate or graduate-level student. A perusal of online documentation for snow hydrology classes suggests that there is currently no single text or reference book on this topic in general use. Instructors rely on chapters from general hydrology texts or operational manuals, collections of journal papers, or their own notes. This variety reflects the fact that snow and ice regions differ in climate, topography, language, water law, hazards, and resource use (hydropower, irrigation, recreation). Given this diversity, producing a universally applicable book is a challenge.

  6. 50 years of snow stratigraphy observations

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  7. Snow and ice ecosystems: not so extreme.

    PubMed

    Maccario, Lorrie; Sanguino, Laura; Vogel, Timothy M; Larose, Catherine

    2015-12-01

    Snow and ice environments cover up to 21% of the Earth's surface. They have been regarded as extreme environments because of their low temperatures, high UV irradiation, low nutrients and low water availability, and thus, their microbial activity has not been considered relevant from a global microbial ecology viewpoint. In this review, we focus on why snow and ice habitats might not be extreme from a microbiological perspective. Microorganisms interact closely with the abiotic conditions imposed by snow and ice habitats by having diverse adaptations, that include genetic resistance mechanisms, to different types of stresses in addition to inhabiting various niches where these potential stresses might be reduced. The microbial communities inhabiting snow and ice are not only abundant and taxonomically diverse, but complex in terms of their interactions. Altogether, snow and ice seem to be true ecosystems with a role in global biogeochemical cycles that has likely been underestimated. Future work should expand past resistance studies to understanding the function of these ecosystems.

  8. GPM Sees Nor'easter Dump Snow on New England

    NASA Video Gallery

    At 5:05 p.m. EST Monday, Jan. 26, 2015, the Global Precipitation Measurement mission's Core Observatory flew over the Nor'easter that dumped snow on New England. This satellite image shows the rate...

  9. Improved Snow Mapping Accuracy with Revised MODIS Snow Algorithm

    NASA Technical Reports Server (NTRS)

    Riggs, George; Hall, Dorothy K.

    2012-01-01

    The MODIS snow cover products have been used in over 225 published studies. From those reports, and our ongoing analysis, we have learned about the accuracy and errors in the snow products. Revisions have been made in the algorithms to improve the accuracy of snow cover detection in Collection 6 (C6), the next processing/reprocessing of the MODIS data archive planned to start in September 2012. Our objective in the C6 revision of the MODIS snow-cover algorithms and products is to maximize the capability to detect snow cover while minimizing snow detection errors of commission and omission. While the basic snow detection algorithm will not change, new screens will be applied to alleviate snow detection commission and omission errors, and only the fractional snow cover (FSC) will be output (the binary snow cover area (SCA) map will no longer be included).

  10. Make Your Own Snow Day!

    ERIC Educational Resources Information Center

    Robeck, Edward

    2011-01-01

    Children love snow days, even when they come during the warmest weather. In this lesson the snow isn't falling outside, it's in the classroom--thanks to "Snowflake Bentley" (Briggs Martin 1998) and several models of snowflakes. A lesson on snow demonstrates several principles of practice for using models in elementary science. Focusing on snow was…

  11. High resolution Arctic snow observations: SnowNet (Invited)

    NASA Astrophysics Data System (ADS)

    Hiemstra, C. A.; Sturm, M.; Gelvin, A. B.; Berezovskaya, S.; Saari, S. P.; Finnegan, D. C.; Liston, G. E.

    2009-12-01

    Snow’s importance has become especially prominent in the terrestrial Arctic, where snow dominates the landscape most of the year and changes in snow arrival, depth, and melt have substantial energy budget and biotic consequences. Yet, the Arctic presents formidable challenges to accurate snow measurements because snow depths can vary greatly over relatively short distances (< 10 m). Snow distribution patterns in windy environments, such as the Arctic, arise from interactions among wind, snow, vegetation, and topography. In this environment, snow is transported easily and is retained in topographic depressions, near taller vegetation, and deposited on the lee sides of hills. Reliable observations of where snow exists in the Arctic landscape can be difficult to obtain, and estimates vary depending on where snow is sampled. Measurements tend to be widely distributed and sparse. In addition, observed changes in Arctic vegetation (e.g., increasing shrubs) and land surfaces (e.g., thermokarst) complicate matters further. In response to this critical shortcoming in Arctic snow measurements, we have developed a prototype observational network (SnowNet) that employs standard meteorological observations and high resolution topographic and vegetation data in concert with a comprehensive spatially-intensive snow measurement program. Our sites at Barrow (started 2007) and Imnavait Creek (started 2008), Alaska, feature frequent site visits and intensive spatial sampling of snow depths and densities and snow-surface topography. Both sites have high resolution (~20 cm) topographic and vegetation data layers generated from remote sensing and ground surveys. Further, we have been incorporating extremely high-resolution (< 10 cm) ground-based LiDAR snow and vegetation datasets that allow us to identify relationships among topography, vegetation, and snow in Arctic environments. In addition, we have collected tens of thousands of manual snow depths across our research sites. This

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

    At high latitudes, the climate has warmed at twice the rate of the global average with most changes observed in autumn, winter and spring. Increasing winter temperatures and wide temperature fluctuations are leading to more frequent rain-on-snow events and freeze-thaw cycles causing snow compaction and formation of ice layers in the snowpack, thus creating ice encasement (IE). By decreasing the snowpack insulation capacity and restricting soil-atmosphere gas exchange, modification of the snow properties may lead to colder soil but also to hypoxia and accumulation of trace gases in the subnivean environment. To test the effects of these overwintering conditions changes on plant winter survival and growth, we established a snow manipulation experiment in a coniferous forest in Northern Finland with Norway spruce and Scots pine seedlings. In addition to ambient conditions and prevention of IE, we applied three snow manipulation levels: IE created by artificial rain-on-snow events, snow compaction and complete snow removal. Snow removal led to deeper soil frost during winter, but no clear effect of IE or snow compaction done in early winter was observed on soil temperature. Hypoxia and accumulation of CO2 were highest in the IE plots but, more importantly, the duration of CO2 concentration above 5% was 17 days in IE plots compared to 0 days in ambient plots. IE was the most damaging winter condition for both species, decreasing the proportion of healthy seedlings by 47% for spruce and 76% for pine compared to ambient conditions. Seedlings in all three treatments tended to grow less than seedlings in ambient conditions but only IE had a significant effect on spruce growth. Our results demonstrate a negative impact of winter climate change on boreal forest regeneration and productivity. Changing snow conditions may thus partially mitigate the positive effect of increasing growing season temperatures on boreal forest productivity. PMID:27254100

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

    PubMed Central

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

    2016-01-01

    At high latitudes, the climate has warmed at twice the rate of the global average with most changes observed in autumn, winter and spring. Increasing winter temperatures and wide temperature fluctuations are leading to more frequent rain-on-snow events and freeze-thaw cycles causing snow compaction and formation of ice layers in the snowpack, thus creating ice encasement (IE). By decreasing the snowpack insulation capacity and restricting soil-atmosphere gas exchange, modification of the snow properties may lead to colder soil but also to hypoxia and accumulation of trace gases in the subnivean environment. To test the effects of these overwintering conditions changes on plant winter survival and growth, we established a snow manipulation experiment in a coniferous forest in Northern Finland with Norway spruce and Scots pine seedlings. In addition to ambient conditions and prevention of IE, we applied three snow manipulation levels: IE created by artificial rain-on-snow events, snow compaction and complete snow removal. Snow removal led to deeper soil frost during winter, but no clear effect of IE or snow compaction done in early winter was observed on soil temperature. Hypoxia and accumulation of CO2 were highest in the IE plots but, more importantly, the duration of CO2 concentration above 5% was 17 days in IE plots compared to 0 days in ambient plots. IE was the most damaging winter condition for both species, decreasing the proportion of healthy seedlings by 47% for spruce and 76% for pine compared to ambient conditions. Seedlings in all three treatments tended to grow less than seedlings in ambient conditions but only IE had a significant effect on spruce growth. Our results demonstrate a negative impact of winter climate change on boreal forest regeneration and productivity. Changing snow conditions may thus partially mitigate the positive effect of increasing growing season temperatures on boreal forest productivity. PMID:27254100

  15. Simulating Snow Over Sea Ice In Climate Models

    NASA Technical Reports Server (NTRS)

    Arnold, James E. (Technical Monitor); Marshall, Susan; Oglesby, Robert J.; Drobot, Sheldon; Anderson, Mark

    2002-01-01

    We have evaluated two methods of simulating the seasonal cycle of snow over sea ice in and around the Arctic: The NCAR global climate model CCM3, with its standard snow hydrology, and the snow pack model SNTHERM, forced with hourly atmospheric output from CCM3. A new dataset providing dates for the onset of snow melt over Arctic sea ice provides a means for assessing basin-wide how well the models simulate melt onset, but contains no information on how long it then takes for all the snow to melt. Use of data from the SHEBA site provides very detailed information on the behavior of the snow before and during the melt season, but only for a very limited area. Russian drift data provide climatological data on the seasonal cycle of snow water equivalent and snow density, over multi-year sea ice in the central Arctic basin. These datasets are used to compare the two modeling methods, and to see if use of the more physically-realistic SNTHERM provides any significant improvements. Conclusions obtained so far include: 1. Both CCM3 and CCM3/SNTHERM do a good job overall of matching the onset of snow melt dataset; although CCM3/SNTHERM consistently trends to underestimate the date and CCM3 to overestimate it. 2. SHEBA and ice drift data for the Arctic show that CCM3/ SNTHERM does a better job than CCM3 at simulating the total melt period. 3. Ice drift snow density and accumulation data suggest that while providing superior results, CCM3/SNTHERM may still suffer from overly vigorous melting. 4. Both the large-scale atmospheric forcing and snow pack physical processes are important in proper simulation of the snow seasonal cycle. Ongoing work includes further diagnosis of CCM3/SNTHERM, use of more observational datasets, especially from marginal seas in the pan-Arctic, and full coupling of SNTHERM into CCM3 (work to date has all been off-line simulations).

  16. Integration of snow management practices into a detailed snow pack model

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    The management of snow on ski slopes is a key socio-economic and environmental issue in mountain regions. Indeed the winter sports industry has become a very competitive global market although this economy remains particularly sensitive to weather and snow conditions. The understanding and implementation of snow management in detailed snowpack models is a major step towards a more realistic assessment of the evolution of snow conditions in ski resorts concerning past, present and future climate conditions. Here we describe in a detailed manner the integration of snow management processes (grooming, snowmaking) into the snowpack model Crocus (Spandre et al., Cold Reg. Sci. Technol., in press). The effect of the tiller is explicitly taken into account and its effects on snow properties (density, snow microstructure) are simulated in addition to the compaction induced by the weight of the grooming machine. The production of snow in Crocus is carried out with respect to specific rules and current meteorological conditions. Model configurations and results are described in detail through sensitivity tests of the model of all parameters related to snow management processes. In-situ observations were carried out in four resorts in the French Alps during the 2014-2015 winter season considering for each resort natural, groomed only and groomed plus snowmaking conditions. The model provides realistic simulations of the snowpack properties with respect to these observations. The main uncertainty pertains to the efficiency of the snowmaking process. The observed ratio between the mass of machine-made snow on ski slopes and the water mass used for production was found to be lower than was expected from the literature, in every resort. The model now referred to as "Crocus-Resort" has been proven to provide realistic simulations of snow conditions on ski slopes and may be used for further investigations. Spandre, P., S. Morin, M. Lafaysse, Y. Lejeune, H. François and E. George

  17. Future Change of Snow Water Equivalent over Japan

    NASA Astrophysics Data System (ADS)

    Hara, M.; Kawase, H.; Kimura, F.; Fujita, M.; Ma, X.

    2012-12-01

    Western side of Honshu Island and Hokkaido Island in Japan are ones of the heaviest snowfall areas in the world. Although a heavy snowfall often brings disaster, snow is one of the major sources for agriculture, industrial, and house-use in Japan. Even during the winter, the monthly mean of the surface air temperature often exceeds 0 C in large parts of the heavy snow areas along the Sea of Japan. Thus, snow cover may be seriously reduced in these areas as a result of the global warming, which is caused by an increase in greenhouse gases. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities. We performed a series of numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. The precipitation, snow depth, and surface air temperature of the hindcast simulations show good agreement with the AMeDAS station data. In much-snow cases, The decreasing rate of maximum total snow water equivalent over Japan due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is the air temperature rise due to global climate change. The difference in the precipitation amount between the present and the future simulations is small.

  18. BOREAS HYD-3 Snow Measurements

    NASA Technical Reports Server (NTRS)

    Hardy, Janet P.; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Davis, Robert E.; Smith, David E. (Technical Monitor)

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-3 team collected several data sets related to the hydrology of forested areas. This data set contains measurements of snow depth, snow density in three cm intervals, an integrated snow pack density and snow water equivalent (SWE), and snow pack physical properties from snow pit evaluation taken in 1994 and 1996. The data were collected from several sites in both the southern study area (SSA) and the northern study area (NSA). A variety of standard tools were used to measure the snow pack properties, including a meter stick (snow depth), a 100 cc snow density cutter, a dial stem thermometer, and the Canadian snow sampler as used by HYD-4 to obtain a snow pack-integrated measure of SWE. This study was undertaken to predict spatial distributions of snow properties important to the hydrology, remote sensing signatures, and the transmissivity of gases through the snow. The data are available in tabular ASCII files. The snow measurement data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

  19. Evaporation characteristics of ETBE-blended gasoline.

    PubMed

    Okamoto, Katsuhiro; Hiramatsu, Muneyuki; Hino, Tomonori; Otake, Takuma; Okamoto, Takashi; Miyamoto, Hiroki; Honma, Masakatsu; Watanabe, Norimichi

    2015-04-28

    To reduce greenhouse gas emissions, which contribute to global warming, production of gasoline blended with ethyl tert-buthyl ether (ETBE) is increasing annually. The flash point of ETBE is higher than that of gasoline, and blending ETBE into gasoline will change the flash point and the vapor pressure. Therefore, it is expected that the fire hazard caused by ETBE-blended gasoline would differ from that caused by normal gasoline. The aim of this study was to acquire the knowledge required for estimating the fire hazard of ETBE-blended gasoline. Supposing that ETBE-blended gasoline was a two-component mixture of gasoline and ETBE, we developed a prediction model that describes the vapor pressure and flash point of ETBE-blended gasoline in an arbitrary ETBE blending ratio. We chose 8-component hydrocarbon mixture as a model gasoline, and defined the relation between molar mass of gasoline and mass loss fraction. We measured the changes in the vapor pressure and flash point of gasoline by blending ETBE and evaporation, and compared the predicted values with the measured values in order to verify the prediction model. The calculated values of vapor pressures and flash points corresponded well to the measured values. Thus, we confirmed that the change in the evaporation characteristics of ETBE-blended gasoline by evaporation could be predicted by the proposed model. Furthermore, the vapor pressure constants of ETBE-blended gasoline were obtained by the model, and then the distillation curves were developed.

  20. 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

    USGS Publications Warehouse

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

  1. Politics of Snow

    NASA Astrophysics Data System (ADS)

    Burko, D.

    2012-12-01

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

  2. Nordic Snow Radar Experiment

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  3. A spotlight on snow leopard conservation in China.

    PubMed

    Alexander, Justine S; Zhang, Chengcheng; Shi, Kun; Riordan, Philip

    2016-07-01

    China holds the greatest proportion of the snow leopard's (Panthera uncia) global range and is central to their conservation. The country is also undergoing unprecedented economic growth, which increases both the threats to the snow leopard and the opportunities for its conservation. In this paper we aim to review published literature (from 1950 to 2014) in English and Mandarin on snow leopard ecology and conservation in China in order to identify thematic and geographic research gaps and propose research priorities. We first retrieved all published items that considered snow leopards in China (n = 106). We extracted from these papers 274 reports of snow leopard presence in China. We then reviewed a subset of papers (n = 33) of this literature, which specifically focused on snow leopard ecology and conservation within China. We introduced a thematic framework that allows a structured and comprehensive assessment of findings. This framework recognizes 4 critical and interrelated topics underpinning snow leopard ecology and conservation: habitat (distribution and protected area coverage); prey (distribution and abundance, predator-prey relationships); human interactions (hunting and trade, livestock interactions and conflicts); and the underlying policy context. Significant gains in knowledge as well as research gaps and priorities are discussed with reference to our framework. The modest quantity and limited scope of published research on the snow leopard in China calls for a continued and intensified effort to inform and support national conservation policies.

  4. A spotlight on snow leopard conservation in China.

    PubMed

    Alexander, Justine S; Zhang, Chengcheng; Shi, Kun; Riordan, Philip

    2016-07-01

    China holds the greatest proportion of the snow leopard's (Panthera uncia) global range and is central to their conservation. The country is also undergoing unprecedented economic growth, which increases both the threats to the snow leopard and the opportunities for its conservation. In this paper we aim to review published literature (from 1950 to 2014) in English and Mandarin on snow leopard ecology and conservation in China in order to identify thematic and geographic research gaps and propose research priorities. We first retrieved all published items that considered snow leopards in China (n = 106). We extracted from these papers 274 reports of snow leopard presence in China. We then reviewed a subset of papers (n = 33) of this literature, which specifically focused on snow leopard ecology and conservation within China. We introduced a thematic framework that allows a structured and comprehensive assessment of findings. This framework recognizes 4 critical and interrelated topics underpinning snow leopard ecology and conservation: habitat (distribution and protected area coverage); prey (distribution and abundance, predator-prey relationships); human interactions (hunting and trade, livestock interactions and conflicts); and the underlying policy context. Significant gains in knowledge as well as research gaps and priorities are discussed with reference to our framework. The modest quantity and limited scope of published research on the snow leopard in China calls for a continued and intensified effort to inform and support national conservation policies. PMID:27135283

  5. Distribution and characteristic of PAHs in snow of Fildes Peninsula.

    PubMed

    Na, Guangshui; Liu, Chunyang; Wang, Zhen; Ge, Linke; Ma, Xindong; Yao, Ziwei

    2011-01-01

    Polycyclic aromatic hydrocarbons (PAHs) investigation in different matrices has been reported largely, whereas reports on snow samples were limited. Snow, as the main matrix in the polar region, has an important study meaning. PAHs in snow samples were analyzed to investigate the distribution and contamination status of them in the Antarctic, as well as to provide some references for global migration of PAHs. Snow samples collected in Fildes Peninsula were enriched and separated by solid-phase membrane disks and eluted by methylene dichloride, then quantified by gas chromatography/mass spectrometry. All types of PAHs were detected except for Benzo(a)pyrene. Principal component analysis method was applied to characterize them. Three factors (Naphthalene, Fluorene and Phenanthrene) accounted for 60.57%, 21.61% and 9.80%, respectively. The results showed that the major PAHs sources maybe the atmospheric transportation, and the combustion of fuel in Fildes Peninsula. The comparison of concentration and types of PAHs between accumulated snow and fresh snow showed that the main compound concentrations in accumulated snow samples were higher than those in fresh ones. The risk assessment indicated that the amount of PAHs in the snow samples would not lead to ecological risk.

  6. Recent research in snow hydrology

    NASA Technical Reports Server (NTRS)

    Dozier, Jeff

    1987-01-01

    Recent work on snow-pack energy exchange has involved detailed investigations on snow albedo and attempts to integrate energy-balance calculations over drainage basins. Along with a better understanding of the EM properties of snow, research in remote sensing has become more focused toward estimation of snow-pack properties. In snow metamorphism, analyses of the physical processes must now be coupled to better descriptions of the geometry of the snow microstructure. The dilution method now appears to be the best direct technique for measuring the liquid water content of snow; work on EM methods continues. Increasing attention to the chemistry of the snow pack has come with the general focus on acid precipitation in hydrology.

  7. Secrets of Snow Liveshot Recap

    NASA Video Gallery

    Research Physical Scientist and Deputy Project Scientist for GPM Gail Skofronick-Jackson answers questions about the importance of studying snow from space, the impact of not enough snow, and the f...

  8. Bacterial diversity in snow on North Pole ice floes.

    PubMed

    Hauptmann, Aviaja L; Stibal, Marek; Bælum, Jacob; Sicheritz-Pontén, Thomas; Brunak, Søren; Bowman, Jeff S; Hansen, Lars H; Jacobsen, Carsten S; Blom, Nikolaj

    2014-11-01

    The microbial abundance and diversity in snow on ice floes at three sites near the North Pole was assessed using quantitative PCR and 454 pyrosequencing. Abundance of 16S rRNA genes in the samples ranged between 43 and 248 gene copies per millilitre of melted snow. A total of 291,331 sequences were obtained through 454 pyrosequencing of 16S rRNA genes, resulting in 984 OTUs at 97 % identity. Two sites were dominated by Cyanobacteria (72 and 61 %, respectively), including chloroplasts. The third site differed by consisting of 95 % Proteobacteria. Principal component analysis showed that the three sites clustered together when compared to the underlying environments of sea ice and ocean water. The Shannon indices ranged from 2.226 to 3.758, and the Chao1 indices showed species richness between 293 and 353 for the three samples. The relatively low abundances and diversity found in the samples indicate a lower rate of microbial input to this snow habitat compared to snow in the proximity of terrestrial and anthropogenic sources of microorganisms. The differences in species composition and diversity between the sites show that apparently similar snow habitats contain a large variation in biodiversity, although the differences were smaller than the differences to the underlying environment. The results support the idea that a globally distributed community exists in snow and that the global snow community can in part be attributed to microbial input from the atmosphere.

  9. Crystal growth of artificial snow

    NASA Technical Reports Server (NTRS)

    Kimura, S.; Oka, A.; Taki, M.; Kuwano, R.; Ono, H.; Nagura, R.; Narimatsu, Y.; Tanii, J.; Kamimiytat, Y.

    1984-01-01

    Snow crystals were grown onboard the space shuttle during STS-7 and STS-8 to facilitate the investigation of crystal growth under conditions of weightlessness. The experimental design and hardware are described. Space-grown snow crystals were polyhedrons looking like spheres, which were unlike snow crystals produced in experiments on Earth.

  10. Authentication and encryption in the Snow disease surveillance network.

    PubMed

    Bellika, Johan Gustav; Ilebrekke, Lars; Bakkevoll, Per Atle; Johansen, Håvard; Scholl, Jeremiah; Johansen, Monika Alise

    2009-01-01

    The paper presents how authentication and encryption is implemented in the Snow disease surveillance network. Requirements for the authentication mechanism were collected from General Practitioners (GPs). The identity of each Snow user is preserved across health institutions allowing GPs to move freely between health institutions and use the system independent of location. This ability is combined with close to zero user account administration within the participating institutions. The system provides global user certificate revocation and end-to-end encryption.

  11. Snow White II.

    ERIC Educational Resources Information Center

    Gundy, Jan

    1978-01-01

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

  12. Snow White 5 Trench

    NASA Technical Reports Server (NTRS)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Robotic Arm Camera on the 35th Martian day of the mission, or Sol 34 (June 29, 2008), after the May 25, 2008, landing. This image shows the trench informally called 'Snow White 5.' The trench is 4-to-5 centimeters (about 1.5-to-1.9 inches) deep, 24 centimeters (about 9 inches) wide and 33 centimeters (13 inches) long.

    Snow White 5 is Phoenix's current active digging area after additional trenching, grooming, and scraping by Phoenix's Robotic Arm in the last few sols to trenches informally called Snow White 1, 2, 3, and 4. Near the top center of the image is the Robotic Arm's Thermal and Electrical Conductivity Probe.

    Snow White 5 is located in a patch of Martian soil near the center of a polygonal surface feature, nicknamed 'Cheshire Cat.' The digging site has been named 'Wonderland.'

    This image has been enhanced to brighten shaded areas.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  13. Can GRACE detect winter snows in Japan?

    NASA Astrophysics Data System (ADS)

    Heki, Kosuke

    2010-05-01

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

  14. 'Snow Queen' Animation

    NASA Technical Reports Server (NTRS)

    2008-01-01

    This animation consists of two close-up images of 'Snow Queen,' taken several days apart, by the Robotic Arm Camera (RAC) aboard NASA's Phoenix Mars Lander.

    Snow Queen is the informal name for a patch of bright-toned material underneath the lander.

    Thruster exhaust blew away surface soil covering Snow Queen when Phoenix landed on May 25, 2008, exposing this hard layer comprising several smooth rounded cavities beneath the lander. The RAC images show how Snow Queen visibly changed between June 15, 2008, the 21st Martian day, or sol, of the mission and July 9, 2008, the 44th sol.

    Cracks as long as 10 centimeters (about four inches) appeared. One such crack is visible at the left third and the upper third of the Sol 44 image. A seven millimeter (one-third inch) pebble or clod appears just above and slightly to the right of the crack in the Sol 44 image. Cracks also appear in the lower part of the left third of the image. Other pieces noticeably shift, and some smooth texture has subtly roughened.

    The Phoenix team carefully positioned and focused RAC the same way in both images. Each image is about 60 centimeters, or about two feet, wide. The object protruding in from the top on the right half of the images is Phoenix's thermal and electrical conductivity probe.

    Snow Queen and other ice exposed by Phoenix landing and trenching operations on northern polar Mars is the first time scientists have been able to monitor Martian ice at a place where temperatures are cold enough that the ice doesn't immediately sublimate, or vaporize, away.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  15. Spectral Profiler Probe for In Situ Snow Grain Size and Composition Stratigraphy

    NASA Technical Reports Server (NTRS)

    Berisford, Daniel F.; Molotch, Noah P.; Painter, Thomas

    2012-01-01

    An ultimate goal of the climate change, snow science, and hydrology communities is to measure snow water equivalent (SWE) from satellite measurements. Seasonal SWE is highly sensitive to climate change and provides fresh water for much of the world population. Snowmelt from mountainous regions represents the dominant water source for 60 million people in the United States and over one billion people globally. Determination of snow grain sizes comprising mountain snowpack is critical for predicting snow meltwater runoff, understanding physical properties and radiation balance, and providing necessary input for interpreting satellite measurements. Both microwave emission and radar backscatter from the snow are dominated by the snow grain size stratigraphy. As a result, retrieval algorithms for measuring snow water equivalents from orbiting satellites is largely hindered by inadequate knowledge of grain size.

  16. Measurements of thermal infrared spectral reflectance of frost, snow, and ice

    NASA Technical Reports Server (NTRS)

    Salisbury, John W.; D'Aria, Dana M.; Wald, Andrew

    1994-01-01

    Because much of Earth's surface is covered by frost, snow, and ice, the spectral emissivities of these materials are a significant input to radiation balance calculations in global atmospheric circulation and climate change models. Until now, however, spectral emissivities of frost and snow have been calculated from the optical constants of ice. We have measured directional hemispherical reflectance spectra of frost, snow, and ice from which emissivities can be predicted using Kirchhoff's law (e = 1-R). These measured spectra show that contrary to conclusions about the emissivity of snow drawn from previously calculated spectra, snow emissivity departs significantly from blackbody behavior in the 8-14 micrometer region of the spectrum; snow emissivity decreases with both increasing particle size and increasing density due to packing or grain welding; while snow emissivity increases due to the presence of meltwater.

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

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

    NASA Astrophysics Data System (ADS)

    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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    The two most critical properties for understanding snowmelt runoff and timing are the spatial and temporal distributions of snow water equivalent (SWE) and snow albedo. Despite their importance in controlling volume and timing of runoff, snowpack albedo and SWE are still largely unquantified in the US and not at all in most of the globe, leaving runoff models poorly constrained. NASA Jet Propulsion Laboratory, in partnership with the California Department of Water Resources, has developed the Airborne Snow Observatory (ASO), an imaging spectrometer and scanning LiDAR system, to quantify SWE and snow albedo, generate unprecedented knowledge of snow properties for cutting edge cryospheric science, and provide complete, robust inputs to water management models and systems of the future. This poster will describe the NASA Airborne Snow Observatory, its outputs and their uses and applications, along with recent advancements to the system and plans for the project's future. Specifically, we will look at how ASO uses its imaging spectrometer to quantify spectral albedo, broadband albedo, and radiative forcing by dust and black carbon in snow. Additionally, we'll see how the scanning LiDAR is used to determine snow depth against snow-free acquisitions and to quantify snow water equivalent when combined with in-situ constrained modeling of snow density.

  20. Modeling and measuring snow for assessing climate change impacts in Glacier National Park, Montana

    USGS Publications Warehouse

    Fagre, Daniel B.; Selkowitz, David J.; Reardon, Blase; Holzer, Karen; Mckeon, Lisa L.

    2002-01-01

    A 12-year program of global change research at Glacier National Park by the U.S. Geological Survey and numerous collaborators has made progress in quantifying the role of snow as a driver of mountain ecosystem processes. Spatially extensive snow surveys during the annual accumulation/ablation cycle covered two mountain watersheds and approximately 1,000 km2 . Over 7,000 snow depth and snow water equivalent (SWE) measurements have been made through spring 2002. These augment two SNOTEL sites, 9 NRCS snow courses, and approximately 150 snow pit analyses. Snow data were used to establish spatially-explicit interannual variability in snowpack SWE. East of the Continental Divide, snowpack SWE was lower but also less variable than west of the Divide. Analysis of snowpacks suggest downward trends in SWE, a reduction in snow cover duration, and earlier melt-out dates during the past 52 years. Concurrently, high elevation forests and treelines have responded with increased growth. However, the 80 year record of snow from 3 NRCS snow courses reflects a strong influence from the Pacific Decadal Oscillation, resulting in 20-30 year phases of greater or lesser mean SWE. Coupled with the fine-resolution spatial snow data from the two watersheds, the ecological consequences of changes in snowpack can be empirically assessed at a habitat patch scale. This will be required because snow distribution models have had varied success in simulating snowpack accumulation/ablation dynamics in these mountain watersheds, ranging from R2=0.38 for individual south-facing forested snow survey routes to R2=0.95 when aggregated to the watershed scale. Key ecological responses to snowpack changes occur below the watershed scale, such as snow-mediated expansion of forest into subalpine meadows, making continued spatially-explicit snow surveys a necessity. 

  1. Nye Lecture: Snow Crystals, Shrubs, and the Changing Climate of the Arctic

    NASA Astrophysics Data System (ADS)

    Sturm, M.

    2005-12-01

    At the peak of winter, snow covers more than 45 million km2 of the northern hemisphere. More than 90 percent of this snow will melt before the end of the following summer. In the southern part of this snow-covered area, the seasonal pack is ephemeral, lasting but a few short weeks, but with increasing latitude (or altitude), it lasts much longer. In arctic and alpine locations it can persist for 9 months of the year. In these more extreme locations, the snow is an essential element of the ecosystem, both acting upon, and being acted on, by the biota. For historical reasons, our understanding of snow cover and its interactions has come from two disparate scientific sources: geophysicists working on glaciers and avalanches who were trying to understand snow properties and to develop a physical basis for snow science, and ecologists who were trying to understand the impact of snow on plants, animals, and humans. With the recognition now that snow is both a passive and active agent, we are seeing an increasing number of studies wherein both of these traditional approaches are combined. Geophysicists are learning the Latin names of shrubs while botanist can now identify wind slab. A personal example that illustrates the necessity of this melding process has been our effort to understand the climatic implications of Arctic snow-shrub interactions. We have had to combine traditional snow geophysical studies (i.e., crystal growth, thermal processes, light reflection) with traditional ecological studies (i.e., competition, carbon and nitrogen cycling). Through this process we have discovered that snow-shrub interactions, or more broadly, snow-vegetation interactions, are helping to push the Arctic down a warming trajectory that has global implications. Soil microbes and snow crystals, wind-blown snow and shrubs, are all leading actors in a climate change drama whose outcome is of concern to us all.

  2. 'Snow White' Trench

    NASA Technical Reports Server (NTRS)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Surface Stereo Imager on Sol 43, the 43rd Martian day after landing (July 8, 2008). This image shows the trench informally called 'Snow White.'

    Two samples were delivered to the Wet Chemistry Laboratory, which is part of Phoenix's Microscopy, Electrochemistry, and Conductivity Analyzer (MECA). The first sample was taken from the surface area just left of the trench and informally named 'Rosy Red.' It was delivered to the Wet Chemistry Laboratory on Sol 30 (June 25, 2008). The second sample, informally named 'Sorceress,' was taken from the center of the 'Snow White' trench and delivered to the Wet Chemistry Laboratory on Sol 41 (July 6, 2008).

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  3. Development of an Automatic Blowing Snow station

    NASA Astrophysics Data System (ADS)

    Nishimura, K.

    2010-12-01

    On the Antarctic ice sheet, strong katabatic winds blow throughout the year and a large but unknown fraction of the snow which falls on it is removed continuously. This constitutes a significant factor in mass and energy balance and is all the more important when predicting the likely effects of global climate change. Further, recent experimental work has indicated that the snowdrift sublimation can lead to significant mass losses during strong winds and can be also an important factor in the surface mass balance of the Antarctic ice sheets. Nishimura and Nemoto (2005) carried out the blowing snow observations at Mizuho station, Antarctica in 2000 with the snow particle counters (SPC) that can sense not only the number of snow particles but also their diameters. SPC worked properly and the data obtained revealed profiles of mass flux and particle size distributions as a function of the friction velocity. However, the SPC requires rather high power supply and the data is stored in PC; it is not always suitable for the unmanned observations under the severe Antarctic conditions. Thus, we have developed a simpler device by measuring the attenuation of the light intensity, which strongly depends on the blowing snow flux. A small wind turbine and a cold-proof buttery were utilized as a power source. Firstly, its performance was tested with comparing the SPC in a cold wind tunnel system and it proved adequately fit for practical use by combining the output of the anemometer. In 2009/2010 winter, three systems have been set at Ishikari, Col du Lac blanc in France, and S17 near Syowa station in Antarctica, and the tests are still continuing.

  4. Snow White Trenches

    NASA Technical Reports Server (NTRS)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Surface Stereo Imager on the 25th Martian day of the mission, or Sol 24 (June 19, 2008), after the May 25, 2008, landing. This image shows the trenches informally called 'Snow White 1' (left) and 'Snow White 2' (right). The trench is about 5 centimeters (2 inches) deep and 30 centimeters (12 inches) long.

    'Snow White' is located in a patch of Martian soil near the center of a polygonal surface feature, nicknamed 'Cheshire Cat.' The 'dump pile' is located at the top of the trench, the side farthest away from the lander, and has been dubbed 'Croquet Ground.' The digging site has been named 'Wonderland.'

    This image has been enhanced to brighten shaded areas.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  5. Impurities in Snow: Effects on Spectral Albedo of Prairie Snowpacks

    NASA Astrophysics Data System (ADS)

    Morris, J. N.; Klein, A. G.

    2007-12-01

    While extensive research on soot in snow has been done in the Polar Regions, there remains a lack of observations addressing the effect of soot on snow albedo in North American prairie snowpacks which causes uncertainty to the overall global effect that soot in snow has on climate. Measurements of snow impurities in freshly fallen prairie snowpacks in northwestern Iowa and central Texas collected from February 28 - March 5, 2007 and April 6, 2007, respectively. Two significant snowfall events occurred in northwestern Iowa during the study; the second snowfall event produced the most severe blizzard conditions in northwestern Iowa in the last thirty years. An unusual snowfall event in central Texas offered a unique sampling opportunity Several types of sites were sampled during the field campaign; this includes: frozen lakes with minimal human impact, agricultural fields impacted by agricultural dust, and human impacted sample sites. At twelve sites in northwestern Iowa samples were collected on multiple days and for both snow events to examine changes in snow impurities over time. At all site locations snow samples, temperature, density, and grain size were recorded. Snow reflectance and snow radiance was collected at a subset of the sites with an ASD VNIR Spectroradiometer (350 - 1500 nm). Snow impurities of light-absorbing particulate matter were measured by filtering the meltwater through a nuclepore 0.4 micrometer filter. Impurity concentration was determined by comparing the filters against a set of standards. A photometer will provide a more exact determination of snow impurities in the near future. Preliminary soot observations indicate prairie snow pack concentrations ranging from 1 ngC/g to 236 ngC/g with an average of 61.4 ngC/g. These measurements are within range of previously published values in the Arctic and can lower snow albedo. Differences in soot concentrations were observed between the two Iowa snowfall events. Impurity concentrations measured

  6. Dynamic Equilibrium Inter-annual Snow Modeling for Wyoming using Reconstructed Regional Atmospheric Conditions

    NASA Astrophysics Data System (ADS)

    Ohara, N.; Johnson, R. J.

    2015-12-01

    The inland glacier retreat has often been considered as one of clearest evidences of the global warming last several decades. However, when we try to model the evolution of the inland inter-annual snow storage including glaciers using a standard energy and mass balance snow model, it is impossible to keep the snow storage constant under a constant climate condition. This study treats the inland glaciers as a dynamic equilibrium system that remains constant under static climate condition. We introduced a sub-grid scale parameterization that moves snow/ice from high elevation areas to valleys as the equilibrating factor of the system. This movement of snow/ice occurs by means of wind re-distribution, avalanches, and glaciation. The physically-based model of a dynamic equilibrium snow system at a regional scale was applied to the entire state of Wyoming for long-term simulation. The developed snow model, named RegSnow model, was coupled with the Weather Research and Forecasting (WRF) model to estimate the snow surface energy fluxes during the 33-year-long historical period for transient model calibration. The RegSnow model predicted that 82.2% of interannual snow and ice storage in Wyoming may disappear by 2100 under the RCP4.5 emission scenario based on the climate projection by CMIP5 GCMs.

  7. Continuity of MODIS and VIIRS Snow-Cover Maps during Snowmelt in the Catskill Mountains in New York

    NASA Astrophysics Data System (ADS)

    Hall, D. K.; Riggs, G. A., Jr.; Roman, M. O.; DiGirolamo, N. E.

    2015-12-01

    We investigate the local and regional differences and possible biases between the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible-Infrared Imager Radiometer Suite (VIIRS) snow-cover maps in the winter of 2012 during snowmelt conditions in the Catskill Mountains in New York using a time series of cloud-gap filled daily snow-cover maps. The MODIS Terra instrument has been providing daily global snow-cover maps since February 2000 (Riggs and Hall, 2015). Using the VIIRS instrument, launched in 2011, NASA snow products are being developed based on the heritage MODIS snow-mapping algorithms, and will soon be available to the science community. Continuity of the standard NASA MODIS and VIIRS snow-cover maps is essential to enable environmental-data records (EDR) to be developed for analysis of snow-cover trends using a consistent data record. For this work, we compare daily MODIS and VIIRS snow-cover maps of the Catskill Mountains from 29 February through 14 March 2012. The entire region was snow covered on 29 February and by 14 March the snow had melted; we therefore have a daily time series available to compare normalized difference snow index (NDSI), as an indicator of snow-cover fraction. The MODIS and VIIRS snow-cover maps have different spatial resolutions (500 m for MODIS and 375 m for VIIRS) and different nominal overpass times (10:30 AM for MODIS Terra and 2:30 PM for VIIRS) as well as different cloud masks. The results of this work will provide a quantitative assessment of the continuity of the snow-cover data records for use in development of an EDR of snow cover.http://modis-snow-ice.gsfc.nasa.gov/Riggs, G.A. and D.K. Hall, 2015: MODIS Snow Products User Guide to Collection 6, http://modis-snow-ice.gsfc.nasa.gov/?c=userguides

  8. Influence of wet conditions on snow temperature diurnal variations: An East Antarctic sea-ice case study

    NASA Astrophysics Data System (ADS)

    Lecomte, O.; Toyota, T.

    2016-09-01

    A one-dimensional snow-sea-ice model is used to simulate the evolution of temperature profiles in dry and wet snow over a diurnal cycle, at locations where associated observations collected during the Sea Ice Physics and Ecosystem eXperiment (SIPEX-II) are available. The model is used at two sites, corresponding to two of the field campaign's sea-ice stations (2 and 6), and under two configurations: dry and wet snow conditions. In the wet snow model setups, liquid water may refreeze internally into the snow. At station 6, this releases latent heat to the snow and results in temperature changes at the base of the snow pack of a magnitude comparing to the model-observation difference (1 - 2 ° C). As the temperature gradient across the snow is in turn weakened, the associated conductive heat flux through snow decreases. At station 2, internal refreezing also occurs but colder air temperatures and the competing process of strengthened heat conduction in snow concurrent to snow densification maintain a steady temperature profile. However, both situations share a common feature and show that the conductive heat flux through the snow may significantly be affected (by 10-20% in our simulations) as a result of the liquid water refreezing in snow, either through thermal conductivity enhancement or direct temperature gradient alteration. This ultimately gives motivation for further investigating the impacts of these processes on the sea-ice mass balance in the framework of global scale model simulations.

  9. Snow White Trench (Animation)

    NASA Technical Reports Server (NTRS)

    2008-01-01

    [figure removed for brevity, see original site] Click on image for animation

    This animation shows the evolution of the trench called 'Snow White' that NASA's Phoenix Mars Lander began digging on the 22nd Martian day of the mission after the May 25, 2008, landing.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  10. 'Snow White' in Color

    NASA Technical Reports Server (NTRS)

    2008-01-01

    This color image taken by the Surface Stereo Imager on NASA's Phoenix Mars Lander shows the trench dubbed 'Snow White,' after further digging on the 25th Martian day, or sol, of the mission (June 19, 2008). The lander's solar panel is casting a shadow over a portion of the trench.

    The trench is about 5 centimeters (2 inches) deep and 30 centimeters (12 inches) long.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  11. Phoenix's Snow White Trench

    NASA Technical Reports Server (NTRS)

    2008-01-01

    A soil sample taken from the informally named 'Snow White' trench at NASA's Phoenix Mars Lander work site produced minerals that indicate evidence of past interaction between the minerals and liquid water.

    This image was taken by the Surface Stereo Imager on Sol 103, the 103rd day since landing (Sept. 8, 2008).

    The trench is approximately 23 centimeters (9 inches) long.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by JPL, Pasadena, Calif. Spacecraft development was by Lockheed Martin Space Systems, Denver.

  12. Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

    NASA Technical Reports Server (NTRS)

    Skofronick-Jackson, Gail; Johnson, Benjamin T.; Munchak, S. Joseph

    2012-01-01

    Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The challenges of estimating falling snow from space still exist though progress is being made. These challenges include weak falling snow signatures with respect to background (surface, water vapor) signatures for passive sensors over land surfaces, unknowns about the spherical and non-spherical shapes of the snowflakes, their particle size distributions (PSDs) and how the assumptions about the unknowns impact observed brightness temperatures or radar reflectivities, differences in near surface snowfall and total column snow amounts, and limited ground truth to validate against. While these challenges remain, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (approx 2.5 km) cloud tops having an ice water content (IWC) at the

  13. Spatiotemporal variations of snow cover in northeast China based on flexible multiday combinations of moderate resolution imaging spectroradiometer snow cover products

    NASA Astrophysics Data System (ADS)

    Chen, Shengbo; Yang, Qian; Xie, Hongjie; Zhang, Haijun; Lu, Peng; Zhou, Chao

    2014-01-01

    Daily moderate resolution imaging spectroradiometer (MODIS) (Terra and Aqua) snow cover products are used to produce flexible multiday combinations for each hydrological year between October 2003 and September 2013 in northeast China. Compared with in situ observations, the daily and flexible multiday combinations achieve overall accuracy of 47.51 and 76.52%, respectively, which is >34.45% of MODIS Terra and 30.57% of MODIS Aqua under all-sky conditions. Snow cover fraction, snow cover day map (SCD), snow cover onset date map (SCOD), snow cover end date map (SCED), and snow cover index (SCI) are then generated. The highest SCD, earliest SCOD, and latest SCED are always located in the southern edge of Da Hinggan Mountain and Changbai Mountain, followed by Xiao Hinggan Mountain. SCI negatively correlated with air temperature, with a correlation coefficient of -0.73 (p<0.05) in snowfall season; SCI positively correlated with precipitation, but is insignificant at the 95% level. This suggests that snow cover is more sensitive to air temperature than precipitation. In other words, continuous increase in air temperature due to global warming in the long term will result in continuous reducing of snow cover, a gracious water resource for northeast China, although a relative decrease in air temperature in the recent 10 years has resulted in snow cover increase.

  14. Tyzzer's disease in snow leopards.

    PubMed

    Schmidt, R E; Eisenbrandt, D L; Hubbard, G B

    1984-01-01

    Tyzzer's disease was diagnosed histologically in 2 litters of newborn snow leopard kittens. The gross and histological lesions were similar to those reported in domestic cats and other animals. No signs of illness was noted in either of the snow leopard dams.

  15. Tyzzer's disease in snow leopards.

    PubMed

    Schmidt, R E; Eisenbrandt, D L; Hubbard, G B

    1984-01-01

    Tyzzer's disease was diagnosed histologically in 2 litters of newborn snow leopard kittens. The gross and histological lesions were similar to those reported in domestic cats and other animals. No signs of illness was noted in either of the snow leopard dams. PMID:6699226

  16. The value of snow cover

    NASA Astrophysics Data System (ADS)

    Sokratov, S. A.

    2009-04-01

    Snow is the natural resource, like soil and water. It has specific properties which allow its use not just for skiing but also for houses cooling in summer (Swedish experience), for air fields construction (Arctic and Antarctic), for dams (north of Russia), for buildings (not only snow-houses of some Polar peoples but artistic hotel attracting tourists in Sweden), and as art material (Sapporo snow festival, Finnish events), etc. "Adjustment" of snow distribution and amount is not only rather common practice (avalanche-protection constructions keeping snow on slopes) but also the practice with long history. So-called "snow irrigation" was used in Russia since XIX century to protect winter crop. What is now named "artificial snow production", is part of much larger pattern. What makes it special—it is unavoidable in present climate and economy situation. 5% of national income in Austria is winter tourism. 50% of the economy in Savoy relay on winter tourism. In terms of money this can be less, but in terms of jobs and income involved this would be even more considerable in Switzerland. As an example—the population of Davos is 14000 in Summer and 50000 in Winter. Skiing is growing business. In present time you can find ski slopes in Turkey and Lebanon. To keep a cite suitable for attracting tourists you need certain amount of sunny days and certain amount of snow. The snow cannons are often the only way to keep a place running. On the other hand, more artificial snow does not necessary attract more tourists, while heavy natural snowfall does attract them. Artificial snow making is costly and requires infrastructure (ponds and electric lines) with very narrow range of weather conditions. Related companies are searching for alternatives and one of them can be "weather regulation" by distribution of some chemical components in clouds. It did not happen yet, but can happen soon. The consequences of such interference in Nature is hardly known. The ski tourism is not the

  17. [Psycrophilic organisms in snow and ice].

    PubMed

    Kohshima, S

    2000-12-01

    Psychrophilic and psycrotrophic organisms are important in global ecology as a large proportion of our planet is cold. Two-third of sea-water covering more than 70% of Earth is cold deep sea water with temperature around 2 degrees C, and more than 90% of freshwater is in polar ice-sheets and mountain glaciers. Though biological activity in snow and ice had been believed to be extremely limited, various specialized biotic communities were recently discovered at glaciers of various part of the world. The glacier is relatively simple and closed ecosystem with special biotic community containing various psychrophilic and psycrotrophic organisms. Since psychrophilic organisms was discovered in the deep ice-core recovered from the antarctic ice-sheet and a lake beneath it, snow and ice environments in Mars and Europa are attracting a great deal of scientific attention as possible extraterrestrial habitats of life. This paper briefly reviews the results of the studies on ecology of psychrophilic organisms living in snow and ice environments and their physiological and biochemical adaptation to low temperature.

  18. Snow reflectance from thematic mapper

    NASA Technical Reports Server (NTRS)

    Dozier, J.

    1983-01-01

    Calculations of snow reflectance in all 6 TM reflective bands (i.e., 1,2,3,4,5, and 7) using a delta Eddington model show that snow reflectance in bands 4,5, and 7 is sensitive to grain size. Efforts to interpret the surface optical grain size for the spectral extension of albedo are described. Results show the TM data include spectral channels suitable for snow/cloud discrimination and for snow albedo measurements that can be extended throughout the solar spectrum. Except for band 1, the dynamic range is large enough that saturation occurs only occasionally. The finer resolution gives much better detail on the snowcovered area and might make it possible to use textural information instead of the snowline as an index to the amount of snow melt runoff.

  19. ESA SnowLab project

    NASA Astrophysics Data System (ADS)

    Wiesmann, Andreas; Caduff, Rafael; Frey, Othmar; Werner, Charles

    2016-04-01

    Retrieval of the snow water equivalaent (SWE) from passive microwave observations dates back over three decades to initial studies made using the first operational radiometers in space. However, coarse spatial resolution (25 km) is an acknowledged limitation for the application of passive microwave measurements. The natural variability of snow cover itself is also notable; properties such as stratigraphy and snow microstructure change both spatially and over time, affecting the microwave signature. To overcome this deficit, the satellite mission COld REgions Hydrology High-resolution Observatory (CoReH2O) was proposed to the European Space Agency (ESA) in 2005 in response to the call for Earth Explorer 7 candidate missions. CoReH2O was a dual frequency (X- and Ku-band) SAR mission aimed to provide maps of SWE over land and snow accumulation on glaciers at a spatial resolution of 200 to 500 meters with an unprecedented accuracy. Within the frame of preparatory studies for CoReH2O Phase A, ESA undertook several research initiatives from 2009 to 2013 to study the mission concept and capabilities of the proposed sensor. These studies provided a wealth of information on emission and backscattering signatures of natural snow cover, which can be exploited to study new potential mission concepts for retrieval of snow cover properties and other elements of the cryosphere. Currently data related to multi-frequency, multi-polarisation, multitemporal of active and passive microwave measurements are still not available. In addition, new methods related to e.g. tomography are currently under development and need to be tested with real data. Also, the potential of interferometric and polarimetric measurements of the snow cover and its possible impact for novel mission/retrieval concepts must be assessed. . The objective of the SnowLab activity is to fill this gap and complement these datasets from earlier campaigns by acquiring a comprehensive multi-frequency, multi

  20. Mixing of anthropogenic dust and carbonaceous aerosols in seasonal snow on snow albedo reduction in 2014 China survey

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Huang, Jianping; Pu, Wei

    2016-04-01

    Anthropogenic dusts produced from the affected by human activities derived from the industrial areas and carbonaceous aerosols (black carbon and organic carbon) deposited into snow or ice core via wet and dry deposition play key roles to the regional and global climate. Recently, a China survey was performed to measure the concentrations of insoluble light-absorbing particles (ILAP) in seasonal snow across northern China in January and February of 2014. The results indicate that the higher concentration of NO3- and SO42- and heavy metals of Zn, Pb, Cd, Ni, and Cu are likely to be attributed to enhanced local industrial emissions due to human activities. The emissions from fossil fuel combustion and biomass burning are likely to be important for the chemical elements in the seasonal snow with long-range transport, while medium enrichment factors of Mg, Ca, and Al were predominantly associated with soil dust, which is the most important natural source. There are large ranges of the BC and AD in seasonal snow over northeast China because of the anthropogenic emissions, which are caused by human activities. In addition, although the values of the snow albedo by model simulations are little higher in the visible to near-infrared wavelength than that during the China survey, the surface snow albedo by field campaign measurements have good agreement with the model simulations in the visible wavelength.

  1. Climate Records of Snow, Glaciers and Sea Ice

    NASA Astrophysics Data System (ADS)

    Ballagh, L.; Dye, D.; Howard, A.; Fetterer, F.

    2005-12-01

    Cryospheric data can be used to study global climate change. For example, various environmental factors contribute to changes in annual and interannual snow cover, glacier terminus movement and anomalies of sea ice extent. Archiving and making the data easily accessible is important. At the National Snow and Ice Data Center (NSIDC), three data sets in particular exhibit characteristics that allow for understanding global climate change. Users can analyze glacier retreat from historical glacier photographs, study changes in sea ice by reviewing historical ice charts, and review changes in the annual autumn snow cover onset and last day of snow cover in the Northern Hemisphere. By including a temporal component, the Timing and Statistics of Autumn and Spring Annual Snow Cover for the Northern Hemisphere data set is useful for analyzing statistics of snow cover timing and their relation to other environmental phenomena, for example, vegetation growth dynamics. The Online Glacier Photograph Database, which contains approximately 3,000 images, provides online search and order options for photographs that were previously in risk of deterioration. The Arctic Sea Ice Charts, 1953-1986: W. Dehn Collection data set includes ice charts of the Canadian and Alaskan Arctic Ocean that can be browsed by region and date range. Previously, these ice charts were archived in analog format and in need of long-term preservation. The NOAA Climate Database Modernization Program (CDMP) supported the digitization of both the historical photographs and the sea ice charts. By evaluating these data sets, users will have the opportunity to better interpret climatic change related to snow cover, sea ice and glacier retreat.

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

    NASA Astrophysics Data System (ADS)

    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. "Journey to the Stars": Presenting What Stars Are to Global Planetarium Audiences by Blending Astrophysical Visualizations Into a Single Immersive Production at the American Museum of Natural History

    NASA Astrophysics Data System (ADS)

    Emmart, Carter; Mac Low, M.; Oppenheimer, B. R.; Kinzler, R.; Paglione, T. A. D.; Abbott, B. P.

    2010-01-01

    "Journey to the Stars" is the latest and fourth space show based on storytelling from data visualization at the Rose Center for Earth and Space at the American Museum of Natural History. This twenty five minute, full dome movie production presents to planetarium audiences what the stars are, where they come from, how they vary in type and over time, and why they are important to life of Earth. Over forty scientists from around the world contributed their research to what is visualized into roughly fifteen major scenes. How this production is directed into a consolidated immersive informal science experience with learning goals is an integrative process with many inputs and concerns for scientific accuracy. The goal is a seamless merger of visualizations at varying spatial and temporal scales with acuity toward depth perception, revealing unseen phenomena, and the layering of concepts together to build an understanding of stars; to blend our common experience of them in the sky with the uncommon meaning we have come to know through science. Scripted by Louise Gikow who has worked for Children's Television Workshop, narrated by Whoopie Goldberg, and musically scored by Robert Miller, this production strives to guide audiences through challenging scientific concepts by complimenting the natural beauty the subject matter presents with understandable prose and musical grandeur. "Journey to the Stars" was produced in cooperation with NASA's Science Mission Directorate, Heliophysics Division and is in release at major planetariums, worldwide.

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

    PubMed

    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.

  5. An Evaluation of High-Resolution Regional Climate Model Simulated Snow Cover Using Satellite Data (With Implications for the Simulated Snow-Albedo Feedback)

    NASA Astrophysics Data System (ADS)

    Minder, J. R.; Letcher, T.

    2015-12-01

    warmed climate using the pseudo global warming framework. These simulations show markedly different spatial and seasonal patterns of warming that are linked to differences in snow-albedo feedback strength and the treatment of fractional snow cover.

  6. The Role of Terrestrial Snow Cover in the Climate System

    NASA Astrophysics Data System (ADS)

    Vavrus, S. J.

    2005-12-01

    Snow cover is known to exert a strong influence on the overlying atmosphere and underlying soil, but quantifying this impact is difficult. Besides its well-accepted ability to cool locally, snow cover can also force climate remotely in complex ways by inducing changes in the atmospheric circulation. Most research on the impact of snow cover has focused on the regional rather than global scale. By contrast, this study investigates the global impact of terrestrial snow cover in the present climate by comparing a pair of Community Climate System Model (CCSM3) simulations run with prognostic snow cover (control case) and with all snow cover on land eliminated (NOSNOWCOVER). In this experiment all snowfall over land was converted into liquid water-equivalent upon reaching the surface. Compared with the control run, NOSNOWCOVER produces mean-annual surface air temperatures up to 5 K higher over northern North America and Eurasia and 8 to 9 K greater in these regions during winter. The global-mean warming of 0.8 K in NOSNOWCOVER is nearly 1/3 as large as the simulated 2 x CO2 response. This pronounced surface heating dramatically increases geopotential heights throughout the troposphere: annual increases of up to 50 m occur at the 250 hPa level, along with even larger inflations during winter. Despite the large surface warming, the absence of an insulating snow pack causes soil temperatures in NOSNOWCOVER to fall throughout northern Asia and Canada, including extreme wintertime cooling of more than 20 K in Siberia and a 5 to 10o equatorward expansion of simulated permafrost. The absence of local melt-water percolation causes significantly drier soils over northern boreal regions and a consequent decrease in cloudiness. The removal of snow cover also drastically affects extreme weather in middle latitudes. Extreme cold-air outbreaks (CAOs), defined relative to the control simulation, essentially disappear in NOSNOWCOVER. The loss of CAOs appears to stem from both the local

  7. Snow metamorphism: A fractal approach.

    PubMed

    Carbone, Anna; Chiaia, Bernardino M; Frigo, Barbara; Türk, Christian

    2010-09-01

    Snow is a porous disordered medium consisting of air and three water phases: ice, vapor, and liquid. The ice phase consists of an assemblage of grains, ice matrix, initially arranged over a random load bearing skeleton. The quantitative relationship between density and morphological characteristics of different snow microstructures is still an open issue. In this work, a three-dimensional fractal description of density corresponding to different snow microstructure is put forward. First, snow density is simulated in terms of a generalized Menger sponge model. Then, a fully three-dimensional compact stochastic fractal model is adopted. The latter approach yields a quantitative map of the randomness of the snow texture, which is described as a three-dimensional fractional Brownian field with the Hurst exponent H varying as continuous parameters. The Hurst exponent is found to be strongly dependent on snow morphology and density. The approach might be applied to all those cases where the morphological evolution of snow cover or ice sheets should be conveniently described at a quantitative level.

  8. Snow metamorphism: A fractal approach.

    PubMed

    Carbone, Anna; Chiaia, Bernardino M; Frigo, Barbara; Türk, Christian

    2010-09-01

    Snow is a porous disordered medium consisting of air and three water phases: ice, vapor, and liquid. The ice phase consists of an assemblage of grains, ice matrix, initially arranged over a random load bearing skeleton. The quantitative relationship between density and morphological characteristics of different snow microstructures is still an open issue. In this work, a three-dimensional fractal description of density corresponding to different snow microstructure is put forward. First, snow density is simulated in terms of a generalized Menger sponge model. Then, a fully three-dimensional compact stochastic fractal model is adopted. The latter approach yields a quantitative map of the randomness of the snow texture, which is described as a three-dimensional fractional Brownian field with the Hurst exponent H varying as continuous parameters. The Hurst exponent is found to be strongly dependent on snow morphology and density. The approach might be applied to all those cases where the morphological evolution of snow cover or ice sheets should be conveniently described at a quantitative level. PMID:21230135

  9. NASA’s Sense of Snow: the Airborne Snow Observatory

    NASA Video Gallery

    Water is a critical resource in the western U.S. NASA’s Airborne Snow Observatory is giving California water agencies the first complete measurements of the water available in the Sierra snowpack ...

  10. Microwave Radar Retrieval of Snow Water Equivalent

    NASA Astrophysics Data System (ADS)

    Yueh, S. H.; Rott, H.; Nagler, T. F.; Cline, D. W.; Duguay, C. R.; Essery, R.; Etchevers, P.; Hajnsek, I.; Kern, M.; Macelloni, G.; Malnes, E.; Pulliainen, J. T.; Tsang, L.; Xu, X.; Marshall, H.; Elder, K.

    2010-12-01

    Fresh water stored in snow on land is an important component of the global water cycle. In many regions of the world it is vital to health and commerce. To make global observations of snow water equivalent (SWE), the Cold Regions Hydrology High Resolution Observatory (CoReH2O) candidate mission based on X- and Ku-band synthetic aperture radar (SAR) technologies is currently going through the Phase-A study, sponsored by the European Space Agency. In addition, the Snow and Cold Land Processes (SCLP) mission, also based on the dual-frequency SAR concept, was one of the satellite missions recommended for future NASA implementation. The frequency range for the CoReH2O and SCLP microwave radar, chosen to optimize the sensitivity to volumetric snowpack properties, is 8-18 GHz (X- and Ku-bands). The overall radar SWE measurement principle has been demonstrated by measurements in 1980s-1990s and more recently the NASA Cold Land Processes Experiments in Colorado and Alaska, 2006-2008, the SARALPS-2007 and Helisnow-2008 campaigns in Europe. Ku-band has the capability to estimate SWE in shallow snowpacks, while X-band provides greater penetration for deeper snow. A dual-polarization (VV and VH) SAR will enable discrimination of the radar backscatter into volume and background vegetation/surface components, while the dual frequency design offers the capability of resolving a wide range of snow depths and snow grains. The baseline CoReH2O algorithm statistically minimizes the differences between radar measurements and radiative transfer model for snowpack. The performance of the retrieval algorithm has been studied with Ku- and X-band backscatter data measured by ground-based scatterometers at test sites in the Austrian Alps. The algorithm has also been applied to the airborne POLSCAT and satellite TerraSAR-X data acquired for the CLPX-II Kuparuk River Study Site in the tundra region of northern Alaska. The comparison with the field measurements reveals a RMSE of 0.7 cm for SWE

  11. Passive Microwave Remote Sensing of Falling Snow and Associated GPM Field Campaigns

    NASA Technical Reports Server (NTRS)

    Skofronick-Jackson, Gail

    2011-01-01

    Retrievals of falling snow from space represent one of the next important challenges for the atmospheric, hydrological, and energy budget scientific communities. Historically, retrievals of falling snow have been difficult due to the relative insensitivity of satellite rain-based channels as used in the past. We emphasize the use of high frequency passive microwave channels (85-200 GHz) since these are more sensitive to the ice in clouds and have been used to estimate falling snow from space. While satellite-based remote sensing provides global coverage of falling snow events and the science is relatively new, retrievals are still undergoing development with challenges remaining. There are several current satellite sensors, though not specifically designed for estimating falling snow, are capable of measuring snow from space. These include NOAA's AMSU-B, the MHS sensors, and CloudSat radar. They use high frequency (greater than 85 GHz) passive and active microwave and millimeter-wave channels that are sensitive to the scattering from ice and snow particles in the atmosphere. Sensors with water vapor channels near 183 GHz center line provide opaqueness to the Earth's surface features that can contaminate the falling snow signatures, especially over snow covered surface. In addition, the Global Precipitation Measurement (GPM) mission scheduled for launch in 2013 is specifically designed to measure both liquid rain and frozen snow precipitation. Since falling snow from space is the next precipitation measurement challenge from space, information must be determined in order to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, snow event system characteristics, and surface types. For example, can a lake effect snow system with low cloud tops having an ice water content (IWC) at the surface of 1.0 gram per cubic meter be detected? If this information is

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

    NASA Astrophysics Data System (ADS)

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

    2003-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  14. Better interpretation of snow remote sensing data with physics-based models

    NASA Astrophysics Data System (ADS)

    Sandells, M.; Davenport, I. J.; Quaife, T. L.; Flerchinger, G. N.; Marks, D. G.; Gurney, R. J.

    2012-12-01

    assimilation techniques. For the physically-based model, the computationally efficient two-layer snow model, Snobal, has been coupled with the bare soil component of the multi-layer soil model, SHAW, which simulates freeze-thaw processes well. This will be coupled with the multi-layer HUT microwave emission model. The physics and assumptions behind these models, and their accuracy, will be discussed, along with the other components of the data assimilation system. We will also discuss the challenges and the theoretical advancements that will need to be made for the next generation of snow mass and soil moisture retrieval systems. This should pave the way for more accurate global estimates of important components of the water cycle.

  15. Using Snow to Teach Geology.

    ERIC Educational Resources Information Center

    Roth, Charles

    1991-01-01

    A lesson plan, directed at middle school students and older, describes using snow to study the geological processes of solidification of molten material, sedimentation, and metamorphosis. Provides background information on these geological processes. (MCO)

  16. Factors Controlling Black Carbon Deposition in Snow in the Arctic

    NASA Astrophysics Data System (ADS)

    Qi, L.; Li, Q.; He, C.; Li, Y.

    2015-12-01

    This study evaluates the sensitivity of black carbon (BC) concentration in snow in the Arctic to BC emissions, dry deposition and wet scavenging efficiency using a 3D global chemical transport model GEOS-Chem driven by meteorological field GEOS-5. With all improvements, simulated median BC concentration in snow agrees with observation (19.2 ng g-1) within 10%, down from -40% in the default GEOS-Chem. When the previously missed gas flaring emissions (mainly located in Russia) are included, the total BC emission in the Arctic increases by 70%. The simulated BC in snow increases by 1-7 ng g-1, with the largest improvement in Russia. The discrepancy of median BC in snow in the whole Arctic reduces from -40% to -20%. In addition, recent measurements of BC dry deposition velocity suggest that the constant deposition velocity of 0.03 cm s-1 over snow and ice used in the GEOS-Chem is too low. So we apply resistance-in-series method to calculate the dry deposition velocity over snow and ice and the resulted dry deposition velocity ranges from 0.03 to 0.24 cm s-1. However, the simulated total BC deposition flux in the Arctic and BC in snow does not change, because the increased dry deposition flux has been compensated by decreased wet deposition flux. However, the fraction of dry deposition to total deposition increases from 16% to 25%. This may affect the mixing of BC and snow particles and further affect the radative forcing of BC deposited in snow. Finally, we reduced the scavenging efficiency of BC in mixed-phase clouds to account for the effect of Wegener-Bergeron-Findeisen (WBF) process based on recent observations. The simulated BC concentration in snow increases by 10-100%, with the largest increase in Greenland (100%), Tromsø (50%), Alaska (40%), and Canadian Arctic (30%). Annual BC loading in the Arctic increases from 0.25 to 0.43 mg m-2 and the lifetime of BC increases from 9.2 to 16.3 days. This indicates that BC simulation in the Arctic is really sensitive to

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

    NASA Technical Reports Server (NTRS)

    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. Influence of temperature and precipitation variability on near-term snow trends

    NASA Astrophysics Data System (ADS)

    Mankin, Justin S.; Diffenbaugh, Noah S.

    2015-08-01

    Snow is a vital resource for a host of natural and human systems. Global warming is projected to drive widespread decreases in snow accumulation by the end of the century, potentially affecting water, food, and energy supplies, seasonal heat extremes, and wildfire risk. However, over the next few decades, when the planning and implementation of current adaptation responses are most relevant, the snow response is more uncertain, largely because of uncertainty in regional and local precipitation trends. We use a large (40-member) single-model ensemble climate model experiment to examine the influence of precipitation variability on the direction and magnitude of near-term Northern Hemisphere snow trends. We find that near-term uncertainty in the sign of regional precipitation change does not cascade into uncertainty in the sign of regional snow accumulation change. Rather, temperature increases drive statistically robust consistency in the sign of future near-term snow accumulation trends, with all regions exhibiting reductions in the fraction of precipitation falling as snow, along with mean decreases in late-season snow accumulation. However, internal variability does create uncertainty in the magnitude of hemispheric and regional snow changes, including uncertainty as large as 33 % of the baseline mean. In addition, within the 40-member ensemble, many mid-latitude grid points exhibit at least one realization with a statistically significant positive trend in net snow accumulation, and at least one realization with a statistically significant negative trend. These results suggest that the direction of near-term snow accumulation change is robust at the regional scale, but that internal variability can influence the magnitude and direction of snow accumulation changes at the local scale, even in areas that exhibit a high signal-to-noise ratio.

  19. Skill of remote sensing snow products for distributed runoff prediction

    NASA Astrophysics Data System (ADS)

    Berezowski, Tomasz; Chormański, Jarosław; Batelaan, Okke

    2015-05-01

    With increasing availability of remote sensing snow cover products we aim to evaluate the skill of these datasets with regard to hydrological discharge simulation. In this paper ten model variants using different snow cover data (MOD10A1, IMS, AMSR-E SWE, GLOBSNOW SWE and observed in situ snow depth) and two different model structures for snow accumulation and snowmelt switching (based on snow cover data time series or temperature time series) are calibrated with a global optimisation algorithm. The simulated discharge is subjected to five criteria for validation, while the GLUE methodology is used for uncertainty analysis of the ten model variants. The skill of the datasets is tested for the Biebrza River catchment, which has a hydrological regime dominated by snowmelt. The discharge simulations are conducted with the distributed rainfall-runoff model WetSpa. MOD10A1 was the only data source which improved the validation Nash-Sutcliffe (NS) scores in reference to a standard model. However, other evaluation measures indicate that the following data sources performed better than the standard model: MOD10A1, observed snow depth and GLOBSNOW for Kling-Gupta efficiency and for high flows; IMS and MOD10A1 for bias; GLOBSNOW and MOD10A1 for coefficient of determination. MOD10A1 has the highest spatial resolution of all analysed data sources which might contribute to the high skill of this data. The use of the data-based switching model structure generally narrowed the behavioural parameter sets during the uncertainty analysis when compared to the temperature-based switching. However, no clear relation was observed between the prediction confidence interval and the two model structures. It is concluded that the skill of the remote sensing snow cover data for the model is positive, although, strongly varying with the data source used.

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

    NASA Technical Reports Server (NTRS)

    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.

  1. Establishing Transferable Sub-Pixel Relationships for Estimating Snow Depth from Remotely-Sensed Snow Covered Area and Terrain Variability

    NASA Astrophysics Data System (ADS)

    Schneider, D.; Molotch, N. P.

    2014-12-01

    Snowmelt is the primary water source in the Western United States and mountainous regions globally. Forecasts of streamflow and water supply rely heavily on snow measurements from sparse observation networks that may not provide adequate information during abnormal climatic conditions. In this regard, remote sensing can be used to monitor snow covered area (SCA), which we hypothesize can be used in conjunction with terrain information to estimate spatially explicit snow depth (SD). Small-scale terrain variability can be considered a proxy for the snow holding capacity of the ground. SCA should be more sensitive to changes in snow depth for smooth, or low variable terrain, and less sensitive to rougher terrain. To this end, we have developed a method that is not expected to depend on repeated climatic conditions because it accounts for the static accumulation capacity rather than dynamic processes. In preliminary investigations, a LiDaR dataset from 2010 from Green Lakes Valley, Colorado, USA (Harpold et al. 2014) was used to relate snow depth with fSCA and the sub-pixel terrain variability. Snow depth (dependent variable) and fSCA (independent variable) were aggregated from 1 meter to 30 meters from the LiDaR snow depth product while terrain variability metrics such as the coefficient of variation of elevation were calculated using the 900 1-meter elevation pixels inside each 30 meter pixel. Single linear regression of SD fit with fSCA explains 38% of the variability with a mean absolute error (MAE) of 0.36 m, but the goodness of fit increases to an average of 53% with MAE of 0.25 m as the data is binned by elev-cv; this may indicate that SD-SCA relationships vary by terrain type (slope, aspect, etc.). Further analysis of the scales at which these relationships are applicable and the viability with off-the-shelf DEM and fSCA products is needed. The utility of these relationships is such that snow depth could be estimated above treeline for any set of climatic

  2. A Better Blend

    ERIC Educational Resources Information Center

    Demski, Jennifer

    2010-01-01

    In May 2009, the US Department of Education released a meta-analysis of effectiveness studies of online, face-to-face, and blended learning models. The analysis found that online learning produced better student outcomes than face-to-face classes, and that blended learning offered an even "larger advantage" over face-to-face. The hybrid approach…

  3. Tuning the Blend

    ERIC Educational Resources Information Center

    Schaffhauser, Dian

    2012-01-01

    "Tuning the blend" is a phrase that educators hear a lot these days. It refers to finding the correct balance of online activities and face-to-face instruction in hybrid--or blended--courses. Finding a mix that meets the needs of both faculty and students requires experimentation, experience, and constant tweaking. And, as with coffee, the same…

  4. A Blended Learning Experience

    ERIC Educational Resources Information Center

    Gecer, Aynur; Dag, Funda

    2012-01-01

    Blended (hybrid) learning is one of the approaches that is utilized to help students for meaningful learning via information and communication technologies in educational settings. In this study, Computer II Course which is taught in faculties of education was planned and implemented in the form of a blended learning environment. The data were…

  5. Effectiveness of Blended Learning

    ERIC Educational Resources Information Center

    Rao, A. V. Nageswararao

    2006-01-01

    The introduction of blended learning added new dimension to training, and the possibilities for delivering knowledge and information to learners at an accelerated pace and opened new vistas for knowledge management. Industry pioneers and academicians agree that blended learning will continue to become a driving force in business and in education.…

  6. Retrievals of Falling Snow from Satellite-borne Active and Passive Sensors

    NASA Astrophysics Data System (ADS)

    Jackson, Gail; Munchak, S. Joseph; Johnson, Benjamin

    2014-05-01

    Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The Global Precipitation Measurement (GPM) mission's Core satellite, scheduled for launch in February 2014, is well designed to detect and estimate falling snow. The GPM core carries a passive radiometer with frequencies (10-183 GHz) and an active radar with Ku- and Ka-band frequencies. Combined with the 65o inclination of the GPM Core satellite, these instruments allow for the GPM Core to sense and retrieve information about falling snow and light rain in regions of the earth where snow is common. The GPM Core's comprehensive active and passive channel set will also allow it to serve as a unifying reference for GPM constellation radiometer satellites. Since falling snow from space is the next precipitation measurement challenge from space, information is needed to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, sensitivity to macroscale snow event system characteristics, and sensitivity to microscale snowflake particle characteristics. While the work in this area will continue for many years to come, our group has made substantial progress in this area by identifying minimum detectable melted rates of ~0.5 mm hr-1. Results

  7. Wind tunnel observations of drifting snow

    NASA Astrophysics Data System (ADS)

    Paterna, Enrico; Crivelli, Philip; Lehning, Michael

    2016-04-01

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

  8. Sodankylä manual snow survey program

    NASA Astrophysics Data System (ADS)

    Leppänen, L.; Kontu, A.; Hannula, H.-R.; Sjöblom, H.; Pulliainen, J.

    2015-12-01

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

  9. Coupling of a Simple 3-Layer Snow Model to GISS GCM

    NASA Astrophysics Data System (ADS)

    Aleinov, I.

    2001-12-01

    Appropriate simulation of the snow cover dynamics is an important issue for the General Circulation Models (GCMs). The presence of snow has a significant impact on ground albedo and on heat and moisture balance. A 3-layer snow model similar to the one proposed by Lynch-Stieglitz was developed with the purpose of using it inside the GCM developed in the NASA Goddard Institute for Space Studies (GISS). The water transport between the layers is modeled explicitly while the heat balance is computed implicitly between the snow layers and semi-implicitly on the surface. The processes of melting and refreezing and compactification of layers under the gravitational force are modeled appropriately. It was noticed that implicit computation of the heat transport can cause a significant under- or over-estimation of the incoming heat flux when the temperature of the upper snow layer is equal to 0 C. This may lead in particular to delayed snow melting in spring. To remedy this problem a special flux-control algorithm was added to the model, which checks computed flux for possible errors and if such are detected the heat transport is recomputed again with the appropriate corrections. The model was tested off-line with Sleepers River forcing data and exhibited a good agreement between simulated and observed quantities for snow depth, snow density and snow temperature. The model was then incorporated into the GISS GCM. Inside the GCM the model is driven completely by the data simulated by other parts of the GCM. The screening effect of the vegetation is introduced by means of masking depth. For a thin snowpack a fractional cover is implemented so that the total thickness of the the snow is never less then 10 cm (rather, the areal fraction of the snow cover decreases when it melts). The model was tested with 6 year long GCM speed-up runs. It proved to be stable and produced reasonable results for the global snow cover. In comparison to the old GISS GCM snow model (which was

  10. An Analysis of the NOAA Satellite-Derived Snow-Cover Record, 1972 - Present

    NASA Technical Reports Server (NTRS)

    Robinson, David A.; Frei, Allan

    1995-01-01

    The large-scale distribution of snow cover over northern hemisphere lands has been a topic of increasing attention in recent years. This interest has been spurred, at least in part, by concerns associated with potential changes in the global climate system associated with anthropogenic and natural causes. Satellite observations using visible satellite imagery permit a hemispheric analysis of snow extent. For almost three decades the National Oceanic and Atmospheric Administration (NOAA) has been using visible imagery to produce weekly charts depicting the extent of snow cover over northern hemisphere lands. These charts constitute the longest satellite-derived environmental dataset available on a continuous basis and produced in a consistent manner. We will briefly describe the NOAA charts and then provide an update on the variability of snow extent over the hemisphere from January 1972 through August 1995. Concentration will be on snow kinematics.

  11. Snow Micro-Structure Model

    2014-06-25

    PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implementedmore » using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations: the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.« less

  12. Snow Micro-Structure Model

    SciTech Connect

    Micah Johnson, Andrew Slaughter

    2014-06-25

    PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations: the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.

  13. Modeling chemistry in and above snow at Summit, Greenland - Part 1: Model description and results

    NASA Astrophysics Data System (ADS)

    Thomas, J. L.; Stutz, J.; Lefer, B.; Huey, L. G.; Toyota, K.; Dibb, J. E.; von Glasow, R.

    2011-05-01

    Sun-lit snow is increasingly recognized as a chemical reactor that plays an active role in uptake, transformation, and release of atmospheric trace gases. Snow is known to influence boundary layer air on a local scale, and given the large global surface coverage of snow may also be significant on regional and global scales. We present a new detailed one-dimensional snow chemistry module that has been coupled to the 1-D atmospheric boundary layer model MISTRA. The new 1-D snow module, which is dynamically coupled to the overlaying atmospheric model, includes heat transport in the snowpack, molecular diffusion, and wind pumping of gases in the interstitial air. The model includes gas phase chemical reactions both in the interstitial air and the atmosphere. Heterogeneous and multiphase chemistry on atmospheric aerosol is considered explicitly. The chemical interaction of interstitial air with snow grains is simulated assuming chemistry in a liquid-like layer (LLL) on the grain surface. The coupled model, referred to as MISTRA-SNOW, was used to investigate snow as the source of nitrogen oxides (NOx) and gas phase reactive bromine in the atmospheric boundary layer in the remote snow covered Arctic (over the Greenland ice sheet) as well as to investigate the link between halogen cycling and ozone depletion that has been observed in interstitial air. The model is validated using data taken 10 June-13 June, 2008 as part of the Greenland Summit Halogen-HOx experiment (GSHOX). The model predicts that reactions involving bromide and nitrate impurities in the surface snow can sustain atmospheric NO and BrO mixing ratios measured at Summit, Greenland during this period.

  14. Scavenging insoluble light-absorbing particulates (ILAP) in seasonal snow over northern China

    NASA Astrophysics Data System (ADS)

    Wang, X.; Huang, J.

    2013-12-01

    It has been long believed that Black Carbon (BC) from biomass burning, fossil fuel and biofuel plays an important role in the earth's system through its climate effect. Compared with other insoluble light-absorbing particulates (ILAP), BC is a main component of the most effective light-absorbing particulates, which can dominates the absorption of solar radiation at the visible wavelengths. Furthermore, once deposits on snow, it could significant reduces the snow reflectance and accelerate the snow melting, therefore, it is considered as the second most important component as the CO2 to affect the globe warming. Although several experiments have already been performed for collecting and measuring the scavenging BC in snow on a global scale. Little attention has been given to the quantitative measurements of ILAP deposit on the snowpack at mid-latitude regions in Asia, especially over Northern China. Recently, there are two field campaigns were conducted in January and February 2010 and 2012 to measuring the ILAP in snow across northern China. About 700 snow samples were collected at 84 sites in seven provinces. The BC mass fractions in seasonal snow across northern Xinjiang have a median value of 70 ng g-1, and the concentrations of BC were in the remote northeast on the border of Siberia, with a median concentration in surface snow of 120 ng g-1. South of this, in the industrial northeast, the median snow BC concentration was 1200 ng g-1. In the northeast, snow particulate light absorption was dominated by BC. Across the grassland of Inner Mongolia, OC, likely mostly from local soil, dominates light absorption, with median BC concentrations of 340 ng g-1 responsible for only about one third of total particulate light absorption. In the Qilian Mountains, at the northern boundary of the Tibetan Plateau, snow particulate light absorption is dominated by local soil and desert dust.

  15. Effects of seasonal snow on the growing season of temperate vegetation in China.

    PubMed

    Yu, Zhen; Liu, Shirong; Wang, Jingxin; Sun, Pengsen; Liu, Weiguo; Hartley, Damon S

    2013-07-01

    Variations in seasonal snowfall regulate regional and global climatic systems and vegetation growth by changing energy budgets of the lower atmosphere and land surface. We investigated the effects of snow on the start of growing season (SGS) of temperate vegetation in China. Across the entire temperate region in China, the winter snow depth increased at a rate of 0.15 cm yr(-1) (P = 0.07) during the period 1982-1998, and decreased at a rate of 0.36 cm yr(-1) (P = 0.09) during the period 1998-2005. Correspondingly, the SGS advanced at a rate of 0.68 day yr(-1) (P < 0.01) during 1982-1998, and delayed at a rate of 2.13 day yr(-1) (P = 0.07) during 1998-2005, against a warming trend throughout the entire study period of 1982-2005. Spring air temperature strongly regulated the SGS of both deciduous broad-leaf and coniferous forests, whereas the winter snow had a greater impact on the SGS of grassland and shrubs. Snow depth variation combined with air temperature contributed to the variability in the SGS of grassland and shrubs, as snow acted as an insulator and modulated the underground thermal conditions. In addition, differences were seen between the impacts of winter snow depth and spring snow depth on the SGS; as snow depths increased, the effect associated went from delaying SGS to advancing SGS. The observed thresholds for these effects were snow depths of 6.8 cm (winter) and 4.0 cm (spring). The results of this study suggest that the response of the vegetation's SGS to seasonal snow change may be attributed to the coupling effects of air temperature and snow depth associated with the underground thermal conditions.

  16. Effects of seasonal snow on the growing season of temperate vegetation in China.

    PubMed

    Yu, Zhen; Liu, Shirong; Wang, Jingxin; Sun, Pengsen; Liu, Weiguo; Hartley, Damon S

    2013-07-01

    Variations in seasonal snowfall regulate regional and global climatic systems and vegetation growth by changing energy budgets of the lower atmosphere and land surface. We investigated the effects of snow on the start of growing season (SGS) of temperate vegetation in China. Across the entire temperate region in China, the winter snow depth increased at a rate of 0.15 cm yr(-1) (P = 0.07) during the period 1982-1998, and decreased at a rate of 0.36 cm yr(-1) (P = 0.09) during the period 1998-2005. Correspondingly, the SGS advanced at a rate of 0.68 day yr(-1) (P < 0.01) during 1982-1998, and delayed at a rate of 2.13 day yr(-1) (P = 0.07) during 1998-2005, against a warming trend throughout the entire study period of 1982-2005. Spring air temperature strongly regulated the SGS of both deciduous broad-leaf and coniferous forests, whereas the winter snow had a greater impact on the SGS of grassland and shrubs. Snow depth variation combined with air temperature contributed to the variability in the SGS of grassland and shrubs, as snow acted as an insulator and modulated the underground thermal conditions. In addition, differences were seen between the impacts of winter snow depth and spring snow depth on the SGS; as snow depths increased, the effect associated went from delaying SGS to advancing SGS. The observed thresholds for these effects were snow depths of 6.8 cm (winter) and 4.0 cm (spring). The results of this study suggest that the response of the vegetation's SGS to seasonal snow change may be attributed to the coupling effects of air temperature and snow depth associated with the underground thermal conditions. PMID:23532953

  17. Sodankylä manual snow survey program

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  18. Lake Effect Snow Covers Buffalo

    NASA Technical Reports Server (NTRS)

    2002-01-01

    An average of one foot of snow per day has fallen on Buffalo, New York, since Christmas Eve, resulting in a total of up to 5 feet from December 24-28. The snow fell very heavily, with accumulations of up to 3 inches per hour. Cold winds blowing along the surface of Lake Erie pick up warmth and moisture, which falls as snow as the warm air rises. This image was acquired by the Geostationary Operational Environmental Satellite (GOES), operated by NOAA, on December 27, 2001, at 12:32 p.m. EST. The scene shows thick bands of clouds extending from the eastern tip of Lake Erie and over Buffalo. The arrows show the wind direction, which is blowing down the length of the lake. Image and animation by Robert Simmon, based on data from the NASA GOES Project Science Office.

  19. Snow occurrence changes over the central and eastern United States under future warming scenarios

    NASA Astrophysics Data System (ADS)

    Ning, Liang; Bradley, Raymond S.

    2015-11-01

    Changes of snow occurrence across the central and eastern United States under future warming for the late 21st century are investigated by applying an empirical hyperbolic tangent function to both observed and downscaled high spatial resolution (~12.5 km) daily temperature and precipitation, to compare the historical (1981-2000) and future (2081-2100) snow occurrence. The observed distributions of snow frequency show that snow-rain transition zones are mainly zonally distributed, since they are largely determined by temperature, with slight shifts to the south over the Appalachian Mountains. The snow-rain transition zone is located around 38-46°N for November and March, and 32-42°N for winter months (DJF). These observed patterns are reproduced well for the historical period by an ensemble average of multiple general circulation models (GCMs). The probabilistic projections show that the snow-rain transition zone will shift to the north under the background of global warming at magnitudes of 2-6 °C, indicating that large areas will experience a partial, or even a very large, loss of snow occurrence in the future. The northward shifts are about 2° latitude under the representative concentration pathways 4.5 (RCP4.5) scenario and 4° latitude under the RCP8.5 scenario. The percentages of the area losing snow occurrence are also assessed.

  20. Snow occurrence changes over the central and eastern United States under future warming scenarios.

    PubMed

    Ning, Liang; Bradley, Raymond S

    2015-01-01

    Changes of snow occurrence across the central and eastern United States under future warming for the late 21(st) century are investigated by applying an empirical hyperbolic tangent function to both observed and downscaled high spatial resolution (~12.5 km) daily temperature and precipitation, to compare the historical (1981-2000) and future (2081-2100) snow occurrence. The observed distributions of snow frequency show that snow-rain transition zones are mainly zonally distributed, since they are largely determined by temperature, with slight shifts to the south over the Appalachian Mountains. The snow-rain transition zone is located around 38-46°N for November and March, and 32-42°N for winter months (DJF). These observed patterns are reproduced well for the historical period by an ensemble average of multiple general circulation models (GCMs). The probabilistic projections show that the snow-rain transition zone will shift to the north under the background of global warming at magnitudes of 2-6 °C, indicating that large areas will experience a partial, or even a very large, loss of snow occurrence in the future. The northward shifts are about 2° latitude under the representative concentration pathways 4.5 (RCP4.5) scenario and 4° latitude under the RCP8.5 scenario. The percentages of the area losing snow occurrence are also assessed. PMID:26584522

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

    PubMed

    Hisakawa, Nao; Quistad, Steven D; Hester, Eric R; Martynova, Daria; Maughan, Heather; Sala, Enric; Gavrilo, Maria V; Rohwer, Forest

    2015-01-01

    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. PMID:26713242

  2. Snow occurrence changes over the central and eastern United States under future warming scenarios

    PubMed Central

    Ning, Liang; Bradley, Raymond S.

    2015-01-01

    Changes of snow occurrence across the central and eastern United States under future warming for the late 21st century are investigated by applying an empirical hyperbolic tangent function to both observed and downscaled high spatial resolution (~12.5 km) daily temperature and precipitation, to compare the historical (1981–2000) and future (2081–2100) snow occurrence. The observed distributions of snow frequency show that snow-rain transition zones are mainly zonally distributed, since they are largely determined by temperature, with slight shifts to the south over the Appalachian Mountains. The snow-rain transition zone is located around 38–46°N for November and March, and 32–42°N for winter months (DJF). These observed patterns are reproduced well for the historical period by an ensemble average of multiple general circulation models (GCMs). The probabilistic projections show that the snow-rain transition zone will shift to the north under the background of global warming at magnitudes of 2–6 °C, indicating that large areas will experience a partial, or even a very large, loss of snow occurrence in the future. The northward shifts are about 2° latitude under the representative concentration pathways 4.5 (RCP4.5) scenario and 4° latitude under the RCP8.5 scenario. The percentages of the area losing snow occurrence are also assessed. PMID:26584522

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

    PubMed

    Hisakawa, Nao; Quistad, Steven D; Hester, Eric R; Martynova, Daria; Maughan, Heather; Sala, Enric; Gavrilo, Maria V; Rohwer, Forest

    2015-01-01

    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.

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

    PubMed Central

    Hisakawa, Nao; Quistad, Steven D.; Hester, Eric R.; Martynova, Daria; Sala, Enric; Gavrilo, Maria V.

    2015-01-01

    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. PMID:26713242

  5. Large scale snow water equivalent status monitoring: comparison of different snow water products in the upper Colorado Basin

    NASA Astrophysics Data System (ADS)

    Artan, G. A.; Verdin, J. P.; Lietzow, R.

    2013-12-01

    We illustrate the ability to monitor the status of snow water content over large areas by using a spatially distributed snow accumulation and ablation model that uses data from a weather forecast model in the upper Colorado Basin. The model was forced with precipitation fields from the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) and the Tropical Rainfall Measuring Mission (TRMM) data-sets; remaining meteorological model input data were from NOAA's Global Forecast System (GFS) model output fields. The simulated snow water equivalent (SWE) was compared to SWEs from the Snow Data Assimilation System (SNODAS) and SNOwpack TELemetry system (SNOTEL) over a region of the western US that covers parts of the upper Colorado Basin. We also compared the SWE product estimated from the special sensor microwave imager (SSM/I) and scanning multichannel microwave radiometer (SMMR) to the SNODAS and SNOTEL SWE data-sets. Agreement between the spatial distributions of the simulated SWE with MPE data was high with both SNODAS and SNOTEL. Model-simulated SWE with TRMM precipitation and SWE estimated from the passive microwave imagery were not significantly correlated spatially with either SNODAS or the SNOTEL SWE. Average basin-wide SWE simulated with the MPE and the TRMM data were highly correlated with both SNODAS (r = 0.94 and r = 0.64; d.f. = 14 - d.f. = degrees of freedom) and SNOTEL (r = 0.93 and r = 0.68; d.f. = 14). The SWE estimated from the passive microwave imagery was significantly correlated with the SNODAS SWE (r = 0.55, d.f. = 9, p = 0.05) but was not significantly correlated with the SNOTEL-reported SWE values (r = 0.45, d.f. = 9, p = 0.05).The results indicate the applicability of the snow energy balance model for monitoring snow water content at regional scales when coupled with meteorological data of acceptable quality. The two snow water contents from the microwave imagery (SMMR and SSM/I) and the Utah Energy Balance forced with the

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

    USGS Publications Warehouse

    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

  7. Retrievals of Falling Snow from Satellite-borne Active and Passive Sensors

    NASA Astrophysics Data System (ADS)

    Skofronick-Jackson, Gail; Munchak, S. Joseph; Johnson, Benjamin

    2013-04-01

    Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. Precipitation impacts latent heating profiles locally while global circulation patterns distribute precipitation and energy from the equator to the poles. For the hydrological cycle, falling snow is a primary contributor in northern latitudes during the winter seasons. Falling snow is the source of snow pack accumulations that provide fresh water resources for many communities in the world. Furthermore, falling snow impacts society by causing transportation disruptions during severe snow events. In order to collect information on the complete global precipitation cycle, both liquid and frozen precipitation must be collected. The Global Precipitation Measurement (GPM) mission's Core satellite, scheduled for launch in 2014, is well designed to detect and estimate falling snow. The GPM core carries a passive radiometer with frequencies (10-183 GHz) and an active radar with Ku- and Ka-band frequencies. Combined with the 65 degree inclination of the GPM Core satellite, these instruments allow for the GPM Core to sense and retrieve information about falling snow and light rain in regions of the earth where snow is common. The GPM Core's comprehensive active and passive channel set will also allow it to serve as a unifying reference for GPM constellation radiometer satellites. Since falling snow from space is the next precipitation measurement challenge from space, information is needed to guide retrieval algorithm development for these current and future missions. This information includes thresholds of detection for various sensor channel configurations, sensitivity to macroscale snow event system characteristics, and sensitivity to microscale snowflake particle characteristics. While the work in this area will continue for many years to come, our group has made substantial progress in this area by identifying minimum detectable melted rates of ~0.5 mm/hr. Results will

  8. Periodontal status in snow leopards.

    PubMed

    Cook, R A; Stoller, N H

    1986-11-01

    Periodontal examinations were performed on ten 1- to 22-year-old snow leopards (6 males and 4 females), using dentistry methods for determining the plaque and gingival indices. All tooth surfaces were probed, and alveolar bone attachment loss was determined. After subgingival plaque removal, plaque specimens were examined for differential bacterial morphotypes. The small number of leopards evaluated precluded definitive statistical analysis. However, the progression from gingival health to gingivitis to periodontitis was similar to that seen in man. Therefore, the use of plaque index, gingival index, alveolar bone attachment loss, and differential bacterial morphotypes can be used to determine the dental health of snow leopards. PMID:3505932

  9. New Energy-efficient Snow production

    NASA Astrophysics Data System (ADS)

    Rhyner, H.

    2009-04-01

    Artificial snow making is widely used in the Alps, mainly to compensate for missing snow cover. Since snow production requires both water and energy, it is necessary to develop new technologies in this field that optimise the production process. In particular in terms of energy consumption, new technologies are developed to minimize the use of energy and costs. The aims of this paper are to model the process of artificial snow making in the Swiss Alps. Several field and laboratory campaigns will be presented. The actual process of snow produciton, as it exits the snow canons and snow hoses and acummulates on the ground is modelled and validated with field and laboratory experiments. Amongst other techniques, infra-red meausurements show detailed temperature distributions. Techniques are demonstrated on how snow-making can be optimised.

  10. Snow wetness measurements for melt forecasting

    NASA Technical Reports Server (NTRS)

    Linlor, W. I.; Clapp, F. D.; Meier, M. F.; Smith, J. L.

    1975-01-01

    A microwave technique for directly measuring snow pack wetness in remote installations is described. The technique, which uses satellite telemetry for data gathering, is based on the attenuation of a microwave beam in transmission through snow.

  11. Microwave scattering properties of snow fields

    NASA Technical Reports Server (NTRS)

    Angelakos, D. J.

    1977-01-01

    Experimental results were presented showing backscatter dependence on frequency, angle of incidence, snow wetness, and frequency modulation. Theoretical studies were made of the inverse scattering problem yielding some preliminary results concerning the determination of the dielectric constant of the snow layer. The experimental results lead to the following conclusions: (1) snow layering affects backscatter; (2) layer response was significant up to 45 degrees of incidence; (3) wetness modifies snow layer effects; and (4) frequency modulation masks the layer response.

  12. Utilizing Multiple Datasets for Snow Cover Mapping

    NASA Technical Reports Server (NTRS)

    Tait, Andrew B.; Hall, Dorothy K.; Foster, James L.; Armstrong, Richard L.

    1999-01-01

    Snow-cover maps generated from surface data are based on direct measurements, however they are prone to interpolation errors where climate stations are sparsely distributed. Snow cover is clearly discernable using satellite-attained optical data because of the high albedo of snow, yet the surface is often obscured by cloud cover. Passive microwave (PM) data is unaffected by clouds, however, the snow-cover signature is significantly affected by melting snow and the microwaves may be transparent to thin snow (less than 3cm). Both optical and microwave sensors have problems discerning snow beneath forest canopies. This paper describes a method that combines ground and satellite data to produce a Multiple-Dataset Snow-Cover Product (MDSCP). Comparisons with current snow-cover products show that the MDSCP draws together the advantages of each of its component products while minimizing their potential errors. Improved estimates of the snow-covered area are derived through the addition of two snow-cover classes ("thin or patchy" and "high elevation" snow cover) and from the analysis of the climate station data within each class. The compatibility of this method for use with Moderate Resolution Imaging Spectroradiometer (MODIS) data, which will be available in 2000, is also discussed. With the assimilation of these data, the resolution of the MDSCP would be improved both spatially and temporally and the analysis would become completely automated.

  13. Progress in AMSR Snow Algorithm Development

    NASA Technical Reports Server (NTRS)

    Chang, Alfred; Koike, Toshio

    1998-01-01

    Advanced Microwave Scanning Radiometer (AMSR) will be flown on-board of the Japanese Advanced Earth Observing Satellite-II (ADEOS-II) and United States Earth Observation System (EOS) PM-1 satellite. AMSR is a passive microwave radiometer with frequency ranges from 6.9 GHz to 89 GHz. It scans conically with a constant incidence angle of 55 deg at the Earth's surface. The swath width is about 1600 km. With a large antenna, AMSR will provide the best spatial resolution of multi-frequency radiometer from space. This provides us an opportunity to improve the snow parameter retrieval. Accurate determination of snow parameters from space is a challenging effort. Over the years, many different techniques have been used to account for the complicated snow parameters such as the density, stratigraphy, snow grain size, temperature variation of the snow-pack. Forest type, fractional forest cover and land use type also need to be considered in developing an improved retrieval algorithm. However, snow is such a dynamic variable, snow-pack parameter keeps changing once the snow is deposited on the earth surface. Currently, NASDA and NASA are developing AMSR snow retrieval algorithms. These algorithms are now being carefully tested and evaluated using the SSM/I data. Due to limited snow-pack data available for comparison, this activity is progressing slowly. However, it is clear that in order to improve the snow retrieval algorithm, it is necessary to model the metamorphism history of the snow-pack.

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

    MedlinePlus

    ... to Know About Zika & Pregnancy Cold, Ice, and Snow Safety KidsHealth > For Parents > Cold, Ice, and Snow Safety Print A A A Text Size What's ... a few. Plus, someone has to shovel the snow, right? Once outdoors, however, take precautions to keep ...

  15. 44 CFR 206.227 - Snow assistance.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    .... Federal assistance will be provided for all costs eligible under 44 CFR 206.225 for a specified period of... 44 Emergency Management and Assistance 1 2014-10-01 2014-10-01 false Snow assistance. 206.227... Snow assistance. Emergency or major disaster declarations based on snow or blizzard conditions will...

  16. 44 CFR 206.227 - Snow assistance.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    .... Federal assistance will be provided for all costs eligible under 44 CFR 206.225 for a specified period of... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false Snow assistance. 206.227... Snow assistance. Emergency or major disaster declarations based on snow or blizzard conditions will...

  17. 44 CFR 206.227 - Snow assistance.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    .... Federal assistance will be provided for all costs eligible under 44 CFR 206.225 for a specified period of... 44 Emergency Management and Assistance 1 2013-10-01 2013-10-01 false Snow assistance. 206.227... Snow assistance. Emergency or major disaster declarations based on snow or blizzard conditions will...

  18. 44 CFR 206.227 - Snow assistance.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    .... Federal assistance will be provided for all costs eligible under 44 CFR 206.225 for a specified period of... 44 Emergency Management and Assistance 1 2012-10-01 2011-10-01 true Snow assistance. 206.227... Snow assistance. Emergency or major disaster declarations based on snow or blizzard conditions will...

  19. 44 CFR 206.227 - Snow assistance.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    .... Federal assistance will be provided for all costs eligible under 44 CFR 206.225 for a specified period of... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Snow assistance. 206.227... Snow assistance. Emergency or major disaster declarations based on snow or blizzard conditions will...

  20. Seasonal variations of snow depth on Mars.

    PubMed

    Smith, D E; Zuber, M T; Neumann, G A

    2001-12-01

    Using topography collected over one martian year from the Mars Orbiter Laser Altimeter on the Mars Global Surveyor (MGS) spacecraft, we have measured temporal changes in the elevation of the martian surface that correlate with the seasonal cycle of carbon dioxide exchange between the surface and atmosphere. The greatest elevation change (1.5 to 2 meters) occurs at high latitudes ( above 80 degrees ), whereas the bulk of the mass exchange occurs at lower latitudes (below 75 degrees N and below 73 degrees S). An unexpected period of sublimation was observed during northern hemisphere autumn, coincident with dust storms in the southern hemisphere. Analysis of MGS Doppler tracking residuals revealed temporal variations in the flattening of Mars that correlate with elevation changes. The combined changes in gravity and elevation constrain the average density of seasonally deposited carbon dioxide to be 910 +/- 230 kilograms per cubic meter, which is considerably denser than terrestrial snow.

  1. Snow Physics and Meltwater Hydrology of the SSiB Model Employed for Climate Simulation Studies with GEOS 2 GCM

    NASA Technical Reports Server (NTRS)

    Mocko, David M.; Sud, Y. C.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    Present-day climate models produce large climate drifts that interfere with the climate signals simulated in modelling studies. The simplifying assumptions of the physical parameterization of snow and ice processes lead to large biases in the annual cycles of surface temperature, evapotranspiration, and the water budget, which in turn causes erroneous land-atmosphere interactions. Since land processes are vital for climate prediction, and snow and snowmelt processes have been shown to affect Indian monsoons and North American rainfall and hydrology, special attention is now being given to cold land processes and their influence on the simulated annual cycle in GCMs. The snow model of the SSiB land-surface model being used at Goddard has evolved from a unified single snow-soil layer interacting with a deep soil layer through a force-restore procedure to a two-layer snow model atop a ground layer separated by a snow-ground interface. When the snow cover is deep, force-restore occurs within the snow layers. However, several other simplifying assumptions such as homogeneous snow cover, an empirical depth related surface albedo, snowmelt and melt-freeze in the diurnal cycles, and neglect of latent heat of soil freezing and thawing still remain as nagging problems. Several important influences of these assumptions will be discussed with the goal of improving them to better simulate the snowmelt and meltwater hydrology. Nevertheless, the current snow model (Mocko and Sud, 2000, submitted) better simulates cold land processes as compared to the original SSiB. This was confirmed against observations of soil moisture, runoff, and snow cover in global GSWP (Sud and Mocko, 1999) and point-scale Valdai simulations over seasonal snow regions. New results from the current snow model SSiB from the 10-year PILPS 2e intercomparison in northern Scandinavia will be presented.

  2. Seasonal snow cover and glacier change impact on water and energy cycle of Central Asia Endorheic Basin

    NASA Astrophysics Data System (ADS)

    Eisen, Vladimir; Eisen, Elena

    2010-05-01

    High mountains of Central Asia Endorheic Basin (CAEB) hold one of the greatest in the World concentration of snow and glacier ice water resources at mid- latitudes thousands of miles from the oceans providing up to 80% of total river runoff. The total external atmospheric moisture flow over the CAEB comprises approximately 200 billion cubic meters per year. The glaciers of CAEB receive and retain annually up to 10% of moisture transferred over the mountains. However, the area of seasonal snow and glaciers has declining rapidly as result of recent climatic change causes by increase in air temperature and precipitation partitioning between snow and rain, and evaporation fluxes. Based on remote sensing data CAEB glaciers shrunk by 5% between the middle of 1940th and 1970th and 10% during the next 30 years. Evaluation of seasonal snow cover for the same period revealed 20% seasonal snow covered area reduction. During the last thirty years, the duration of snow melt reduced by 30 days from the date of maximum snow cover to the date of its disappearance. Further decrease in seasonal snow cover will be accelerated due to increase of rainfall instead of snowfall in early spring months at high elevations, and consequently a lesser heat expenditure for snowmelt. At high mountains, about 40% of snow ablated during the penultimate 10 days of snow cover. During ablation season, the amount of energy used to melt snow and glacier ice is in the same order as the combination of other components of the heat budget (e.g., heat associated with atmospheric advection, radiation balance and turbulent heat exchange). Heating of the air would have been 3 times higher if snow and glacier ice melt had not occurred. Analysis of shallow ice-cores from high elevation snow/ice fields of CAEB has helped determining the climatic processes controlling hydrological regimes via the changes in global and regional atmospheric circulation patterns and simulates impact of these changes on water and

  3. Photopolarimetric Retrievals of Snow Properties

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

  4. 'Snow White' and Language Awareness.

    ERIC Educational Resources Information Center

    Larson, Deborah Aldrich

    1987-01-01

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

  5. Quantifying forest mortality with the remote sensing of snow

    NASA Astrophysics Data System (ADS)

    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

  6. Snow hydrology in a general circulation model

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  7. Heavy snow loads in Finnish forests respond regionally asymmetrically to projected climate change

    NASA Astrophysics Data System (ADS)

    Lehtonen, Ilari; Kämäräinen, Matti; Gregow, Hilppa; Venäläinen, Ari; Peltola, Heli

    2016-10-01

    This study examined the impacts of projected climate change on heavy snow loads on Finnish forests, where snow-induced forest damage occurs frequently. For snow-load calculations, we used daily data from five global climate models under representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, statistically downscaled onto a high-resolution grid using a quantile-mapping method. Our results suggest that projected climate warming results in regionally asymmetric response on heavy snow loads in Finnish forests. In eastern and northern Finland, the annual maximum snow loads on tree crowns were projected to increase during the present century, as opposed to southern and western parts of the country. The change was rather similar both for heavy rime loads and wet snow loads, as well as for frozen snow loads. Only the heaviest dry snow loads were projected to decrease over almost the whole of Finland. Our results are aligned with previous snowfall projections, typically indicating increasing heavy snowfalls over the areas with mean temperature below -8 °C. In spite of some uncertainties related to our results, we conclude that the risk for snow-induced forest damage is likely to increase in the future in the eastern and northern parts of Finland, i.e. in the areas experiencing the coldest winters in the country. The increase is partly due to the increase in wet snow hazards but also due to more favourable conditions for rime accumulation in a future climate that is more humid but still cold enough.

  8. An automatic snow station experiment in Western Dronning Maud Land, Antarctica

    NASA Astrophysics Data System (ADS)

    Järvinen, O.; Leppäranta, M.

    2012-04-01

    Snow and ice cover 98% of all surfaces in Antarctica and it is one of the principal components of our global climate system. Snow properties easily respond to changes in environmental conditions and therefore studying the spatio-temporal variations in the physical properties of Antarctic snow cover is crucial. We present here results from a snow station experiment recording the temperature evolution of the snow surface layer over one year in two stations. The snow stations were installed in December 2009 to measure the snow temperature at 15 different depths for one year, the deepest sensor being at 4 m at the moment of installation. The stations were recovered in January 2011 and both were still fully operational. It was the first time when this kind of experiment was successful in the western Dronning Maud Land. The stations were located 50 km (station 1) and 10 km (station 2) from the Finnish research station Aboa (73o 02.5'S, 013o24.4'W), 80 and 130 km south of the ice shelf edge. The temperature data are analyzed for the annual temperature cycle of surface layer temperature, surface heat budget, and net snow accumulation. The power spectra of temperature at the depth of 54 cm were calculated for the whole measurement interval, and separately for the polar night and polar day seasons. The daily cycle was strong during the polar day but disappeared when the polar night started. The daily cycle is also seen when looking over the whole measurement interval. Also physical characterization of the snow stratigraphy was made at the installation sites at the start and end of the recordings, including thickness, density, hardness (hand test), and grain size and shape (photographs from crystals). Also the dielectric constant was measured using the Snow Fork (designed and manufactured by Toikka Oy) to estimate the liquid water content (wetness).

  9. Heat generation during metamorphic processes in snow

    NASA Astrophysics Data System (ADS)

    Tyagunin, A. V.; Koposov, G. D.

    2016-09-01

    The research analyzes known metamorphic processes in the snow from the point of view of energy approach. A list of these processes is complemented with the processes associated with runoff of a quasi-liquid layer from snow granules. The experimental results of studying the heat generation from the snow cover and the temperature gradient at the depth of the snow cover are presented. It is emphasized that snow cover is not merely a passive conductor of heat but also it is a heat generating medium.

  10. Population genetic analysis and origin discrimination of snow crab (Chionoecetes opilio) using microsatellite markers.

    PubMed

    Kang, Jung-Ha; Park, Jung-Youn; Kim, Eun-Mi; Ko, Hyun-Sook

    2013-10-01

    Major habitats for the snow crab Chionoecetes opilio are mostly found within the northwest Atlantic and North Pacific Oceans. However, the East Sea populations of C. opilio, along with its relative the red snow crab (C. japonicas), are two of the most important commercial crustacean species for fisheries on the east coast of the Korean Peninsula. The East Sea populations of C. opilio are facing declining resources due to overfishing and global climate change. Thus, an analysis of population structure is necessary for future management. Five Korean and one Russian group of C. opilio were analyzed using nine microsatellite markers that were recently developed using next-generation sequencing. No linkage disequilibrium was found between any pair of loci, indicating that the markers were independent. The number of alleles per locus varied from 4 to 18 with a mean of 12, and allelic richness per locus ranged from 4.0 to 17.1 across all populations with a mean of 9.7. The Hardy-Weinberg equilibrium test revealed significant deviation in three out of nine loci in some populations after sequential Bonferroni correction and all of them had higher expected heterozygosity than observed heterozygosity. Null alleles were presumed in four loci, which explained the homozygosity in three loci. The pairwise fixation index (F ST ) values among the five Korean snow crab populations did not differ significantly, but all of the pairwise F ST values between each of the Korean snow crab populations and the Russian snow crab population differed significantly. An UPGMA dendrogram revealed clear separation of the Russian snow crab population from the Korean snow crab populations. Assignment tests based on the allele distribution discriminated between Korean and Russian origins with 93 % accuracy. Therefore, the snow crab populations around the Korean Peninsula need to be managed separately from the populations in Bering Sea in global scale resource management. Also, this information can be

  11. Population genetic analysis and origin discrimination of snow crab (Chionoecetes opilio) using microsatellite markers.

    PubMed

    Kang, Jung-Ha; Park, Jung-Youn; Kim, Eun-Mi; Ko, Hyun-Sook

    2013-10-01

    Major habitats for the snow crab Chionoecetes opilio are mostly found within the northwest Atlantic and North Pacific Oceans. However, the East Sea populations of C. opilio, along with its relative the red snow crab (C. japonicas), are two of the most important commercial crustacean species for fisheries on the east coast of the Korean Peninsula. The East Sea populations of C. opilio are facing declining resources due to overfishing and global climate change. Thus, an analysis of population structure is necessary for future management. Five Korean and one Russian group of C. opilio were analyzed using nine microsatellite markers that were recently developed using next-generation sequencing. No linkage disequilibrium was found between any pair of loci, indicating that the markers were independent. The number of alleles per locus varied from 4 to 18 with a mean of 12, and allelic richness per locus ranged from 4.0 to 17.1 across all populations with a mean of 9.7. The Hardy-Weinberg equilibrium test revealed significant deviation in three out of nine loci in some populations after sequential Bonferroni correction and all of them had higher expected heterozygosity than observed heterozygosity. Null alleles were presumed in four loci, which explained the homozygosity in three loci. The pairwise fixation index (F ST ) values among the five Korean snow crab populations did not differ significantly, but all of the pairwise F ST values between each of the Korean snow crab populations and the Russian snow crab population differed significantly. An UPGMA dendrogram revealed clear separation of the Russian snow crab population from the Korean snow crab populations. Assignment tests based on the allele distribution discriminated between Korean and Russian origins with 93 % accuracy. Therefore, the snow crab populations around the Korean Peninsula need to be managed separately from the populations in Bering Sea in global scale resource management. Also, this information can be

  12. Validation of Airborne FMCW Radar Measurements of Snow Thickness Over Sea Ice in Antarctica

    NASA Technical Reports Server (NTRS)

    Galin, Natalia; Worby, Anthony; Markus, Thorsten; Leuschen, Carl; Gogineni, Prasad

    2012-01-01

    Antarctic sea ice and its snow cover are integral components of the global climate system, yet many aspects of their vertical dimensions are poorly understood, making their representation in global climate models poor. Remote sensing is the key to monitoring the dynamic nature of sea ice and its snow cover. Reliable and accurate snow thickness data are currently a highly sought after data product. Remotely sensed snow thickness measurements can provide an indication of precipitation levels, predicted to increase with effects of climate change in the polar regions. Airborne techniques provide a means for regional-scale estimation of snow depth and distribution. Accurate regional-scale snow thickness data will also facilitate an increase in the accuracy of sea ice thickness retrieval from satellite altimeter freeboard estimates. The airborne data sets are easier to validate with in situ measurements and are better suited to validating satellite algorithms when compared with in situ techniques. This is primarily due to two factors: better chance of getting coincident in situ and airborne data sets and the tractability of comparison between an in situ data set and the airborne data set averaged over the footprint of the antennas. A 28-GHz frequency modulated continuous wave (FMCW) radar loaned by the Center for Remote Sensing of Ice Sheets to the Australian Antarctic Division is used to measure snow thickness over sea ice in East Antarctica. Provided with the radar design parameters, the expected performance parameters of the radar are summarized. The necessary conditions for unambiguous identification of the airsnow and snowice layers for the radar are presented. Roughnesses of the snow and ice surfaces are found to be dominant determinants in the effectiveness of layer identification for this radar. Finally, this paper presents the first in situ validated snow thickness estimates over sea ice in Antarctica derived from an FMCW radar on a helicopterborne platform.

  13. Comparison of the Snow Simulations in Community Land Model Using Two Snow Cover Fraction Parameterizations

    NASA Astrophysics Data System (ADS)

    Xie, Zhipeng; Hu, Zeyong

    2016-04-01

    Snow cover is an important component of local- and regional-scale energy and water budgets, especially in mountainous areas. This paper evaluates the snow simulations by using two snow cover fraction schemes in CLM4.5 (NY07 is the original snow-covered area parameterization used in CLM4, and SL12 is the default scheme in CLM4.5). Off-line simulations are carried out forced by the China Meteorological forcing dataset from January 1, 2001 to December 31, 2010 over the Tibetan Plateau. Simulated snow cover fraction (SCF), snow depth, and snow water equivalent (SWE) were compared against a set of observations including the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover product, the daily snow depth dataset of China, and China Meteorological Administration (CMA) in-situ snow depth and SWE observations. The comparison results indicate significant differences existing between those two SCF parameterizations simulations. Overall, the SL12 formulation shows a certain improvement compared to the NY07 scheme used in CLM4, with the percentage of correctly modeled snow/no snow being 75.8% and 81.8% when compared with the IMS snow product, respectively. Yet, this improvement varies both temporally and spatially. Both these two snow cover schemes overestimated the snow depth, in comparison with the daily snow depth dataset of China, the average biases of simulated snow depth are 7.38cm (8.77cm), 6.97cm (8.2cm) and 5.49cm (5.76cm) NY07 (and SL12) in the snow accumulation period (September through next February), snowmelt period (March through May) and snow-free period (June through August), respectively. When compared with the CMA in-situ snow depth observations, averaged biases are 3.18cm (4.38cm), 2.85cm (4.34cm) and 0.34cm (0.34cm) for NY07 (SL12), respectively. Though SL12 does worse snow depth simulation than NY07, the simulated SWE by SL12 is better than that by NY07, with average biases being 2.64mm, 6.22mm, 1.33mm for NY07, and 1.47mm, 2.63mm, 0.31mm

  14. [Effects of snow pack removal on soil microbial biomass carbon and nitrogen and the number of soil culturable microorganisms during wintertime in alpine Abies faxoniana forest of western Sichuan, Southwest China].

    PubMed

    Yang, Yu-Lian; Wu, Fu-Zhong; He, Zhen-Hua; Xu, Zhen-Feng; Liu, Yang; Yang, Wan-Qin; Tan, Bo

    2012-07-01

    To understand the effects of the lack of snow pack under global warming on the characteristics of soil microorganisms during wintertime, a snow-shading experiment was conducted in a primary fir (Abies faxoniana) forest after snow pack removal, with the soil microbial biomass carbon (MBC) and nitrogen (MBN) and soil culturable microorganisms (bacteria and fungi) at the stages of snow forming, snow covering, and snow melting investigated. Snow pack removal had significant effects on the soil MBC and MBN and the number of soil culturable bacteria and fungi, but the responses of the culturable microorganisms differed with the stages of snow-shading. Under the condition of snow pack removal, the MBC and MBN in soil organic layer decreased significantly at the early stages of snow forming and snow melting but increased significantly at snow covering stage and at the later stage of snow melting, and the number of culturable bacteria decreased significantly from the early stage of snow forming to the stage of snow covering while that of culturable fungi had a significant increase from the early stage of snow forming to the stage of snow melting. After snow melting, the MBC and the number of culturable fungi in soil organic layer had a significant decrease, the number of cultural bacteria was in adverse, but the MBN had less change. The MBC and MBN and the number of culturable microorganisms in soil mineral layer had the similar variation trends as those in soil organic layer, but the fluctuations were smaller. It was suggested that snow pack removal changed the ratio of culturable bacteria to culturable fungi, showing positive effects on the number of soil culturable fungi during wintertime in alpine Abies faxoniana forest of western Sichuan.

  15. Characteristics of Heavy Snowfall and Snow Crystal Habits in the ESSAY (Experiment on Snow Storms At Yeongdong) Campaign in Korea

    NASA Astrophysics Data System (ADS)

    Seong, D. K.; Seok, S. W.; Eun, S. H.; Kim, B. G.; Reum, K. A.; Lee, K. M.; Jeon, H. R.; Byoung Choel, C.; Park, Y. S.

    2015-12-01

    Characteristics of heavy snowfall and snow crystal habits have been investigated in the campaign of Experiment on Snow Storms At Yeongdong (ESSAY) using radiosonde soundings, Global Navigation Satellite System (GNSS), and a digital camera with a magnifier for taking a photograph of snowfall crystals. The analysis period is mainly both winters of 2014 and 2015. The synoptic situations are similar to those of the previous studies such as the Low pressure system passing by the far South of the Korean peninsula along with the Siberian High extending to northern Japan, which eventually results in the northeasterly or easterly flows and the long-lasting snowfall episodes in the Yeongdong region. The snow crystal habits observed in the ESSAY campaign were mainly dendrite, consisting of 70% of the entire habits. The rimed habits were frequently captured when two-layered clouds were observed, probably through the process of freezing of super-cooled droplets on the ice particles. The homogeneous habit such as dendrite was shown in case of shallow clouds with its thickness of below 500 m whereas various habits were captured such as graupel, dendrites, rimed dendrites, aggregates of dendrites, plates, rimed plates, etc in the thick cloud with its thickness greater than 1.5 km. The dendrites appeared to be dominant in the condition of cloud top temperature specifically ranging -12~-16℃. Interestingly temporal evolutions of snow crystal habits were consistently shown for several snowfall events such as changes from rimed particles to dendrites(or aggregated dendrites). The association of snow crystal habits with temperature and super-saturation in the cloud will be in detail examined. However, better understandings of characteristics of snow crystal habits would contribute to preventing breakdown accidents such as a greenhouse destruction and collapse of a temporary building due to heavy snowfall, and traffic accidents due to snow-slippery road condition, providing a higher

  16. A stable snow-atmosphere coupled mode

    NASA Astrophysics Data System (ADS)

    Zhao, Liang; Zhu, Yuxiang; Liu, Haiwen; Liu, Zhongfang; Liu, Yanju; Li, Xiuping; Chen, Zhou

    2016-10-01

    Snow is both an important lower boundary forcing of the atmosphere and a response to atmospheric forcing in the extratropics. It is still unclear whether a stable snow-atmosphere coupled mode exists in the extratropics, like the ENSO in the tropics. Using Sliding Correlation analysis over Any Window, the present study quantitatively evaluates the stability of coupling relationships between the major modes of winter snow over the Northern Hemisphere and the winter atmospheric Arctic Oscillation (AO), the Antarctic Oscillation (AAO) and the Siberian High over the period 1872-2010, and discusses their possible relationships for different seasons. Results show that the first mode of the winter snow cover fraction and the winter AO together constitute a stable snow-atmosphere coupled mode, the SNAO. The coupled mode is stronger during recent decades than before. The snow anomaly over Europe is one key factor of the SNAO mode due to the high stability there, and the polar vortex anomaly in the atmosphere is its other key factor. The continuity of signals in the SNAO between autumn and winter is weaker than that between winter and spring. The second winter snow mode is generally stably correlated with the winter AAO and was more stable before the 1970s. The AAO signal with boreal snow has a strong continuity in seasonal transition. Generally, through these coupled modes, snow and atmosphere can interact in the same season or between different seasons: autumn snow can influence the winter atmosphere; the winter atmosphere can influence spring snow.

  17. A blended land emissivity product from the Inter-Comparison of different Land Surface Emissivity Estimates

    NASA Astrophysics Data System (ADS)

    Norouzi, H.; Temimi, M.; Khanbilvardi, R.

    2012-12-01

    Passive microwave observations are routinely used to estimate rain rate, cloud liquid water, and total precipitable water. In order to have accurate estimations from microwave, the contribution of the surface should be accounted for. Over land, due to the complex interaction between the microwave signal and the soil surface, retrieval of land surface emissivity and other surface and subsurface parameters is not straightforward. Several microwave emissivity products from various microwave sensors have been proposed. However, lack of ground truth measurements makes the validation of these products difficult. This study aims to inter-compare several available emissivity products over land and ultimately proposes a unique blended product that overcomes the flaws of each individual product. The selected products are based on observations from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), the Special Sensor Microwave Imager (SSM/I), the Advanced Microwave Sounding unit (AMSU), and the Special Sensor Microwave Imager/Sounder (SSMIS). In retrieval of emissivities from these sensors different methods and ancillary data have been used. Some inherent discrepancies between the selected products can be introduced by as the difference in geometry in terms of incident angle, spectral response, and the foot print size which can affect the estimations. Moreover, ancillary data especially skin temperature and cloud mask cover can cause significant discrepancies between various estimations. The time series and correlation between emissivity maps are explored to assess the consistency of emissivity variations with geophysical variable such as snow, precipitation and drought. Preliminary results reveal that inconsistency between products varies based on land cover type due to penetration depth effect and ancillary data. Six years of estimations are employed in this research study, and a global blended emissivity estimations based on all product with minimal discrepancies

  18. Arctic moisture source for Eurasian snow cover variations in autumn

    NASA Astrophysics Data System (ADS)

    Wegmann, Martin; Orsolini, Yvan; Vázquez Dominguez, Marta; Gimeno Presa, Luis; Nieto, Raquel; Buligyna, Olga; Jaiser, Ralf; Handorf, Dörthe; Rinke, Anette; Dethloff, Klaus; Sterin, Alexander; Brönnimann, Stefan

    2015-04-01

    Global warming is enhanced at high northern latitudes where the Arctic surface air temperature has risen at twice the rate of the global average in recent decades - a feature called Arctic amplification. This recent Arctic warming signal likely results from several factors such as the albedo feedback due to a diminishing cryosphere, enhanced poleward atmospheric and oceanic transport, and change in humidity. The reduction in Arctic sea ice is without doubt substantial and a key factor. Arctic summer sea-ice extent has declined by more than 10% per decade since the start of the satellite era (e.g. Stroeve et al., 2012), culminating in a new record low in September 2012, with the long-term trend largely attributed to anthropogenic global warming. Eurasian snow cover changes have been suggested as a driver for changes in the Arctic Oscillation and might provide a link between sea ice decline in the Arctic during summer and atmospheric circulation in the following winter. However, the mechanism connecting snow cover in Eurasia to sea ice decline in autumn is still under debate. Our analysis focuses at sea ice decline in the Barents-Kara Sea region, which allows us to specify regions of interest for FLEXPART forward and backwards moisture trajectories. Based on Eularian and Lagrangian diagnostics from ERA-INTERIM, we can address the origin and cause of late autumn snow depth variations in a dense (snow observations from 820 land stations), unutilized observational datasets over the Commonwealth of Independent States. Open waters in the Barents and Kara Sea have been shown to increase the diabatic heating of the atmosphere, which amplifies baroclinic cyclones and might induce a remote atmospheric response by triggering stationary Rossby waves (Honda et al. 2009). In agreement with these studies, our results show enhanced storm activity originating at the Barents and Kara with disturbances entering the continent through a small sector from the Barents and Kara Seas

  19. Experimental manipulations of snow-depth: Effects on nutrient content of caribou forage

    USGS Publications Warehouse

    Walsh, N.E.; McCabe, T.R.; Welker, J.M.; Parsons, A.N.

    1997-01-01

    We investigated the potential effects of global climate change on arctic tundra vegetation used as caribou forage. A total of 96 experimental plots was established at six sites on the coastal plain of the Arctic National Wildlife Refuge, Alaska, in 1993 and 1994. We erected snow-fences to increase the amount of snow deposition, and therefore delay the date of the snowmelt on 48 plots (referred to as increased snow/late melting plots). We used black mesh netting on the surface of the snow to increase the rate of melting on 24 plots; the remaining 24 plots served as controls. In July 1994, we collected green leaves from Eriophorum vaginatum, Salix planifolia, and Betula nana and analysed these samples for total carbon and total nitrogen content. Ratios of carbon to nitrogen differed among treatments for all three species. Generally, C:N ratios for B. nana and E. vaginatum on increased snow/late melting plots were lower than on control plots. C:N ratios for S. planifolia on increased snow/late melting plots did not differ from controls, but were lower than on plots which started to melt early. These results may be due to the timing of nitrogen translocation from leaf and stem tissue into storage organs, or due to an increase in available nitrogen input to the system. Further sampling is needed to adequately determine the mechanism responsible for increased nitrogen content of caribou forage in areas with increased amount of snow and delayed snowmelt. ?? 1997 Blackwell Science Ltd.

  20. Snow cover dynamics and hydrological regime of the Hunza River basin, Karakoram Range, Northern Pakistan

    NASA Astrophysics Data System (ADS)

    Tahir, A. A.; Chevallier, P.; Arnaud, Y.; Ahmad, B.

    2011-03-01

    A major proportion of flow in the Indus River is contributed by its snow- and glacier-fed river catchments situated in the Himalaya, Karakoram and Hindukush ranges. It is therefore essential to understand the cryosphere dynamics in this area for water resource management. The MODIS MOD10A2 remote-sensing database of snow cover products from March 2000 to December 2009 was selected to analyse the snow cover changes in the Hunza River basin (the snow- and glacier-fed sub-catchment of the Indus River). A database of daily flows for the Hunza River at Dainyor Bridge over a period of 40 years and climate data (precipitation and temperature) for 10 years from three meteorological stations within the catchment was made available to investigate the hydrological regime in the area. Analysis of remotely sensed cryosphere (snow and ice cover) data showed a slight expansion of snow cover in the area in contrast to most of the regions in the world where glaciers are melting rapidly. This increase in snow cover may be the result of an increase in winter precipitation caused by westerly circulation. The impact of global warming is not effective because a large part of the basin area lies under high altitudes where the temperature remains negative throughout most of the year.

  1. Feasibility of Estimating Snow Depth in Complex Terrain Using Satellite Lidar Altimetry

    NASA Technical Reports Server (NTRS)

    Jasinski, Michael F.; Stoll, Jeremy

    2012-01-01

    Satellite retrievals of snow depth and water equivalent (SWE) are critical for monitoring watershed scale processes around the world. However, the problem is especially challenging in mountainous regions where complex heterogeneities limit the utility of low resolution satellite sensors. The Geoscience Laser Altimeter Sensor (GLAS) aboard the Ice, Cloud, and land Elevation Satellite (ICESat) collected surface elevation data along near-repeat reference transects over land areas from 2003-2009. Although intended for monitoring ice caps and sea ice, the seven year global GLAS data base has provided unprecedented opportunity to test the capability of satellite lidar technology for estimating snow depth over land. GLAS single track and low repeat frequency does not provide data sufficient for operational estimates. However, its comparatively small footprint size of -65 m and its database of seasonal repeat observations during both snow and no-snow conditions have been sufficient to evaluate the potential of spacebased lidar altimetry for estimating snow depth. Recent analysis of ICESat elevations in the Uinta Mountains in NE Utah provide encouraging results for watershed scale estimates of snow depth. Research reported here focuses on the sensitivity of several versions of an ICESat snow depth algorithm to a range of landscape types defined by vegetation cover, slope and roughness. Results are compared to available SNOTEL data.

  2. Reconstructing solid precipitation from snow depth measurements and a land surface model

    NASA Astrophysics Data System (ADS)

    Cherry, Jessie Ellen; Tremblay, L. Bruno; DéRy, Stephen J.; Stieglitz, Marc

    2005-09-01

    The amount and distribution of snowfall in the Arctic has significant effects on global climate. However, measurements of snowfall from gauges are strongly biased. A new method is described for reconstructing snowfall from observed snow depth records, meteorological observations, and running the NASA Seasonal-to-Interannual Prediction Project Catchment Land Surface Model (NSIPP CLSM) in an inverse mode. This method is developed and tested with observations from Reynolds Creek Experimental Watershed. Results show snowfall can be accurately reconstructed on the basis of how much snow must have fallen to produce the observed snow depth. The mean cumulative error (bias) of the reconstructed precipitation for 11 snow seasons is 29 mm snow water equivalent (SWE) for the corrected gauge measurement compared to ‒77 mm SWE for the precipitation from the corrected snow gauges. This means the root-mean-square error of reconstructed solid precipitation is 30% less than that of gauge corrections. The intended application of this method is the pan-Arctic landmass, where estimates of snowfall are highly uncertain but where more than 60 years of historical snow depth and air temperature records exist.

  3. Reconstructing solid precipitation from snow depth measurements and a land surface model

    NASA Astrophysics Data System (ADS)

    Cherry, Jessie Ellen; Tremblay, L. Bruno; Déry, Stephen J.; Stieglitz, Marc

    2005-09-01

    The amount and distribution of snowfall in the Arctic has significant effects on global climate. However, measurements of snowfall from gauges are strongly biased. A new method is described for reconstructing snowfall from observed snow depth records, meteorological observations, and running the NASA Seasonal-to-Interannual Prediction Project Catchment Land Surface Model (NSIPP CLSM) in an inverse mode. This method is developed and tested with observations from Reynolds Creek Experimental Watershed. Results show snowfall can be accurately reconstructed on the basis of how much snow must have fallen to produce the observed snow depth. The mean cumulative error (bias) of the reconstructed precipitation for 11 snow seasons is 29 mm snow water equivalent (SWE) for the corrected gauge measurement compared to -77 mm SWE for the precipitation from the corrected snow gauges. This means the root-mean-square error of reconstructed solid precipitation is 30% less than that of gauge corrections. The intended application of this method is the pan-Arctic landmass, where estimates of snowfall are highly uncertain but where more than 60 years of historical snow depth and air temperature records exist.

  4. Estimation of Sea Ice Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data

    NASA Technical Reports Server (NTRS)

    Kurtz, Nathan T.; Markus, Thorsten; Cavalieri, Donald J.; Sparling, Lynn C.; Krabill, William B.; Gasiewski, Albin J.; Sonntag, John G.

    2009-01-01

    Combinations of sea ice freeboard and snow depth measurements from satellite data have the potential to provide a means to derive global sea ice thickness values. However, large differences in spatial coverage and resolution between the measurements lead to uncertainties when combining the data. High resolution airborne laser altimeter retrievals of snow-ice freeboard and passive microwave retrievals of snow depth taken in March 2006 provide insight into the spatial variability of these quantities as well as optimal methods for combining high resolution satellite altimeter measurements with low resolution snow depth data. The aircraft measurements show a relationship between freeboard and snow depth for thin ice allowing the development of a method for estimating sea ice thickness from satellite laser altimetry data at their full spatial resolution. This method is used to estimate snow and ice thicknesses for the Arctic basin through the combination of freeboard data from ICESat, snow depth data over first-year ice from AMSR-E, and snow depth over multiyear ice from climatological data. Due to the non-linear dependence of heat flux on ice thickness, the impact on heat flux calculations when maintaining the full resolution of the ICESat data for ice thickness estimates is explored for typical winter conditions. Calculations of the basin-wide mean heat flux and ice growth rate using snow and ice thickness values at the 70 m spatial resolution of ICESat are found to be approximately one-third higher than those calculated from 25 km mean ice thickness values.

  5. Effects of increased snow cover on the rates and sources of ecosystem respiration from high arctic tundra

    NASA Astrophysics Data System (ADS)

    Lupascu, M.; Welker, J. M.; Cooper, E.; Xu, X.; Czimczik, C. I.

    2013-12-01

    A key driver of carbon (C) cycling in arctic ecosystems is the amount, onset and duration of snow cover. Arctic tundra is covered in snow for 8-10 months of the year, although spatial and internannual variability of snow cover is high. Anticipated changes in the amount and timing of snow cover as a consequence of climate warming and their implications for regional C budget and biogeochemistry are highly uncertain. Here, we investigated the effects of increased winter snow depth on the rates and sources of ecosystem respiration (Reco) of a polar semi-desert and mesic meadow at two long-term snowpack manipulation experiments in NW Greenland and Svalbard, Norway. We monitored Reco, the concentrations of CO2 in the soil pore space and their radiocarbon (14C) contents (as an age proxy) over the course of three summers in Greenland and one winter in Svalbard. Preliminary results show that wintertime Reco fluxes were 45% higher in areas of deep as compared to ambient snow. Summertime Reco fluxes were positively correlated to total water-year precipitation (summer rain plus winter snow). However, due to the shorter, snow-free vegetation period, cumulative summertime Reco fluxes under increased snow cover were reduced by up to -34.1×5.4% compared to the control. The mean age of soil CO2 was always older during both the winter- and summertime under increased snow cover. Similarly, the mean age of Reco was older under increased snowpack during the wintertime. However, summertime Reco was dominated by decomposition of younger C and plant respiration, and we found no effect of snow cover. Our results demonstrate the vulnerability of permafrost C to increasing snow cover and the strong potential to serve as a positive feedback to global climate change.

  6. The Inverted Snow Globe Shadow

    NASA Astrophysics Data System (ADS)

    Ribeiro, Jair Lúcio Prados

    2015-01-01

    Our high school optics course finishes with an assignment that students usually appreciate. They must take pictures of everyday situations representing optical phenomena such as reflection, refraction, or dispersion, and post them on Instagram.1 When the photos were presented to the class, one student revealed an intriguing photo, similar to Fig. 1, showing a snow globe exposed to sunlight and its inverted shadow. This paper offers an explanation of the problem, which occurs due to light refraction from the globe.

  7. Dirty snow after nuclear war

    NASA Technical Reports Server (NTRS)

    Warren, S. G.; Wiscombe, W. J.

    1985-01-01

    It is shown that smoke from fires started by nuclear explosions could continue to cause significant disruption even after it has fallen from the atmosphere, by lowering the reflectivity of snow and sea ice surfaces, with possible effects on climate in northern latitudes caused by enhanced absorption of sunlight. The reduced reflectivity could persist for several years on Arctic sea ice and on the ablation area of the Greenland ice sheet.

  8. Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

    NASA Technical Reports Server (NTRS)

    Jackson, Gail

    2012-01-01

    Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. In order to collect information on the complete global precipitation cycle and to understand the energy budget in terms of precipitation, uniform global estimates of both liquid and frozen precipitation must be collected. Active observations of falling snow are somewhat easier to estimate since the radar will detect the precipitation particles and one only needs to know surface temperature to determine if it is liquid rain or snow. The challenges of estimating falling snow from passive spaceborne observations still exist though progress is being made. While these challenges are still being addressed, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Important information to assess falling snow retrievals includes knowing thresholds of detection for active and passive sensors, various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (2.5 km) cloud tops having an ice water content (Iwe) at the surface of 0.25 g m-3 and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The analysis relies on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Results are presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz (Skofronick-Jackson, et al. submitted to IEEE TGRS, April 2012). The notable results show: (1) the W-Band radar has detection thresholds more

  9. On charging of snow particles in blizzard

    NASA Technical Reports Server (NTRS)

    Shio, Hisashi

    1991-01-01

    The causes of the charge polarity on the blizzard, which consisted of fractured snow crystals and ice particles, were investigated. As a result, the charging phenomena showed that the characteristics of the blizzard are as follows: (1) In the case of the blizzard with snowfall, the fractured snow particles drifting near the surface of snow field (lower area: height 0.3 m) had positive charge, while those drifting at higher area (height 2 m) from the surface of snow field had negative charge. However, during the series of blizzards two kinds of particles positively and negatively charged were collected in equal amounts in a Faraday Cage. It may be considered that snow crystals with electrically neutral properties were separated into two kinds of snow flakes (charged positively and negatively) by destruction of the snow crystals. (2) In the case of the blizzard which consisted of irregularly formed ice drops (generated by peeling off the hardened snow field), the charge polarity of these ice drops salting over the snow field was particularly controlled by the crystallographic characteristics of the surface of the snow field hardened by the powerful wind pressure.

  10. Impacts of Snow Darkening by Absorbing Aerosols on Eurasian Climate

    NASA Technical Reports Server (NTRS)

    Kim, Kyu-Myong; Lau, William K M.; Yasunari, Teppei J.; Kim, Maeng-Ki; Koster, Randal D.

    2016-01-01

    The deposition of absorbing aerosols on snow surfaces reduces snow-albedo and allows snowpack to absorb more sunlight. This so-called snow darkening effect (SDE) accelerates snow melting and leads to surface warming in spring. To examine the impact of SDE on weather and climate during late spring and early summer, two sets of NASA GEOS-5 model simulations with and without SDE are conducted. Results show that SDE-induced surface heating is particularly pronounced in Eurasian regions where significant depositions of dust transported from the North African deserts, and black carbon from biomass burning from Asia and Europe occur. In these regions, the surface heating due to SDE increases surface skin temperature by 3-6 degrees Kelvin near the snowline in spring. Surface energy budget analysis indicates that SDE-induced excess heating is associated with a large increase in surface evaporation, subsequently leading to a significant reduction in soil moisture, and increased risks of drought and heat waves in late spring to early summer. Overall, we find that rainfall deficit combined with SDE-induced dry soil in spring provide favorable condition for summertime heat waves over large regions of Eurasia. Increased frequency of summer heat waves with SDE and the region of maximum increase in heat-wave frequency are found along the snow line, providing evidence that early snowmelt by SDE may increase the risks of extreme summer heat wave. Our results suggest that climate models that do not include SDE may significantly underestimate the effect of global warming over extra-tropical continental regions.

  11. Physical vulnerability of reinforced concrete buildings impacted by snow avalanches

    NASA Astrophysics Data System (ADS)

    Bertrand, D.; Naaim, M.; Brun, M.

    2010-07-01

    This paper deals with the assessment of physical vulnerability of civil engineering structures to snow avalanche loadings. In this case, the vulnerability of the element at risk is defined by its damage level expressed on a scale from 0 (no damage) to 1 (total destruction). The vulnerability of a building depends on its structure and flow features (geometry, mechanical properties, type of avalanche, topography, etc.). This makes it difficult to obtain vulnerability relations. Most existing vulnerability relations have been built from field observations. This approach suffers from the scarcity of well documented events. Moreover, the back analysis is based on both rough descriptions of the avalanche and the structure. To overcome this problem, numerical simulations of reinforced concrete structures loaded by snow avalanches are carried out. Numerical simulations allow to study, in controlled conditions, the structure behavior under snow avalanche loading. The structure is modeled in 3-D by the finite element method (FEM). The elasto-plasticity framework is used to represent the mechanical behavior of both materials (concrete and steel bars) and the transient feature of the avalanche loading is taken into account in the simulation. Considering a reference structure, several simulation campaigns are conducted in order to assess its snow avalanches vulnerability. Thus, a damage index is defined and is based on global and local parameters of the structure. The influence of the geometrical features of the structure, the compressive strength of the concrete, the density of steel inside the composite material and the maximum impact pressure on the damage index are studied and analyzed. These simulations allow establishing the vulnerability as a function of the impact pressure and the structure features. The derived vulnerability functions could be used for risk analysis in a snow avalanche context.

  12. Digging of 'Snow White' Begins

    NASA Technical Reports Server (NTRS)

    2008-01-01

    NASA's Phoenix Mars Lander began excavating a new trench, dubbed 'Snow White,' in a patch of Martian soil located near the center of a polygonal surface feature, nicknamed 'Cheshire Cat.' The trench is about 2 centimeters (.8 inches) deep and 30 centimeters (about 12 inches) long. The 'dump pile' is located at the top of the trench, the side farthest away from the lander, and has been dubbed 'Croquet Ground.' The digging site has been named 'Wonderland.'

    At this early stage of digging, the Phoenix team did not expect to find any of the white material seen in the first trench, now called 'Dodo-Goldilocks.' That trench showed white material at a depth of about 5 centimeters (2 inches). More digging of Snow White is planned for coming sols, or Martian days.

    The dark portion of this image is the shadow of the lander's solar panel; the bright areas within this region are not in shadow.

    Snow White was dug on Sol 22 (June 17, 2008) with Phoenix's Robotic Arm. This picture was acquired on the same day by the lander's Surface Stereo Imager. This image has been enhanced to brighten shaded areas.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  13. Measuring snow liquid water content with low-cost GPS receivers.

    PubMed

    Koch, Franziska; Prasch, Monika; Schmid, Lino; Schweizer, Jürg; Mauser, Wolfram

    2014-01-01

    The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC) in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS). For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N0) and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements. PMID:25384007

  14. Measuring Snow Liquid Water Content with Low-Cost GPS Receivers

    PubMed Central

    Koch, Franziska; Prasch, Monika; Schmid, Lino; Schweizer, Jürg; Mauser, Wolfram

    2014-01-01

    The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC) in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS). For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N0) and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements. PMID:25384007

  15. Enhanced solar energy absorption by internally-mixed black carbon in snow grains

    NASA Astrophysics Data System (ADS)

    Flanner, M. G.; Liu, X.; Zhou, C.; Penner, J. E.; Jiao, C.

    2012-05-01

    Here we explore light absorption by snowpack containing black carbon (BC) particles residing within ice grains. Basic considerations of particle volumes and BC/snow mass concentrations show that there are generally 0.05-109 BC particles for each ice grain. This suggests that internal BC is likely distributed as multiple inclusions within ice grains, and thus the dynamic effective medium approximation (DEMA) (Chýlek and Srivastava, 1983) is a more appropriate optical representation for BC/ice composites than coated-sphere or standard mixing approximations. DEMA calculations show that the 460 nm absorption cross-section of BC/ice composites, normalized to the mass of BC, is typically enhanced by factors of 1.8-2.1 relative to interstitial BC. BC effective radius is the dominant cause of variation in this enhancement, compared with ice grain size and BC volume fraction. We apply two atmospheric aerosol models that simulate interstitial and within-hydrometeor BC lifecycles. Although only ~2% of the atmospheric BC burden is cloud-borne, 71-83% of the BC deposited to global snow and sea-ice surfaces occurs within hydrometeors. Key processes responsible for within-snow BC deposition are development of hydrophilic coatings on BC, activation of liquid droplets, and subsequent snow formation through riming or ice nucleation by other species and aggregation/accretion of ice particles. Applying deposition fields from these aerosol models in offline snow and sea-ice simulations, we calculate that 32-73% of BC in global surface snow resides within ice grains. This fraction is smaller than the within-hydrometeor deposition fraction because meltwater flux preferentially removes internal BC, while sublimation and freezing within snowpack expose internal BC. Incorporating the DEMA into a global climate model, we simulate increases in BC/snow radiative forcing of 43-86%, relative to scenarios that apply external optical properties to all BC. We show that snow metamorphism driven by

  16. Enhanced Solar Energy Absorption by Internally-mixed Black Carbon in Snow Grains

    SciTech Connect

    Flanner, M. G.; Liu, Xiaohong; Zhou, Cheng; Penner, Joyce E.; Jiao, C.

    2012-05-30

    Here we explore light absorption by snowpack containing black carbon (BC) particles residing within ice grains. Basic considerations of particle volumes and BC/snow mass concentrations show that there are generally 0:05-109 BC particles for each ice grain. This suggests that internal BC is likely distributed as multiple inclusions within ice grains, and thus the dynamic effective medium approximation (DEMA) (Chylek and Srivastava, 1983) is a more appropriate optical representation for BC/ice composites than coated-sphere or standard mixing approximations. DEMA calculations show that the 460 nm absorption cross-section of BC/ice composites, normalized to the mass of BC, is typically enhanced by factors of 1.8-2.1 relative to interstitial BC. BC effective radius is the dominant cause of variation in this enhancement, compared with ice grain size and BC volume fraction. We apply two atmospheric aerosol models that simulate interstitial and within-hydrometeor BC lifecycles. Although only {approx}2% of the atmospheric BC burden is cloud-borne, 71-83% of the BC deposited to global snow and sea-ice surfaces occurs within hydrometeors. Key processes responsible for within-snow BC deposition are development of hydrophilic coatings on BC, activation of liquid droplets, and subsequent snow formation through riming or ice nucleation by other species and aggregation/accretion of ice particles. Applying deposition fields from these aerosol models in offline snow and sea-ice simulations, we calculate that 32-73% of BC in global surface snow resides within ice grains. This fraction is smaller than the within-hydrometeor deposition fraction because meltwater flux preferentially removes internal BC, while sublimation and freezing within snowpack expose internal BC. Incorporating the DEMA into a global climate model, we simulate increases in BC/snow radiative forcing of 43-86%, relative to scenarios that apply external optical properties to all BC. We show that snow metamorphism

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

    PubMed

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

    2014-10-01

    In the context of remote sensing, the reflectance of snow is a key factor for accurate inversion for snow properties, such as snow grain size, albedo, because of it is influenced by the change of snow properties. The polarized reflectance is a general phenomenon during the reflected progress in natural incident light In this paper, based on the correct measurements for the multiple-angle reflected property of snow field in visible and near infrared wavelength (from 350 to 2,500 nm), the influence of snow grain size and wet snow on the bidirectional polarized property of snow was measured and analyzed. Combining the results measured in the field and previous conclusions confirms that the relation between polarization and snow grain size is obvious in infrared wavelength (at about 1,500 nm), which means the degree of polarization increasing with an increase of snow grain size in the forward scattering direction, it is because the strong absorption of ice near 1,500 nm leads to the single scattering light contributes to the reflection information obtained by the sensor; in other word, the larger grain size, the more absorption accompanying the larger polarization in forward scattering direction; we can illustrate that the change from dry snow to wet snow also influences the polarization property of snow, because of the water on the surface of snow particle adheres the adjacent particles, that means the wet snow grain size is larger than the dry snow grain size. Therefore, combining the multiple-angle polarization with reflectance will provide solid method and theoretical basis for inversion of snow properties. PMID:25739241

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

    NASA Astrophysics Data System (ADS)

    Grünewald, Thomas; Wolfsperger, Fabian

    2016-04-01

    Snow farming is the conservation of snow during the warm half-year. This means that large piles of snow are formed in spring in order to be conserved over the summer season. Well-insulating materials such as chipped wood are added as surface cover to reduce melting. The aim of snow farming is to provide a "snow guaranty" for autumn or early winter - this means that a specific amount of snow will definitively be available, independent of the weather conditions. The conserved snow can then be used as basis for the preparation of winter sports grounds such as cross-country tracks or ski runs. This helps in the organization of early winter season sport events such as World Cup races or to provide appropriate training conditions for athletes. We present a study on two snow farming projects, one in Davos (Switzerland) and one in the Martell valley of South Tyrol. At both places snow farming has been used for several years. For the summer season 2015, we monitored both snow piles in order to assess the amount of snow conserved. High resolution terrestrial laser scanning was performed to measure snow volumes of the piles at the beginning and at the end of the summer period. Results showed that only 20% to 30 % of the snow mass was lost due to ablation. This mass loss was surprisingly low considering the extremely warm and dry summer. In order to identify the most relevant drivers of snow melt we also present simulations with the sophisticated snow cover models SNOWPACK and Alpine3D. The simulations are driven by meteorological input data recorded in the vicinity of the piles and enable a detailed analysis of the relevant processes controlling the energy balance. The models can be applied to optimize settings for snow farming and to examine the suitability of new locations, configurations or cover material for future snow farming projects.

  19. Soot climate forcing via snow and ice albedos.

    PubMed

    Hansen, James; Nazarenko, Larissa

    2004-01-13

    Plausible estimates for the effect of soot on snow and ice albedos (1.5% in the Arctic and 3% in Northern Hemisphere land areas) yield a climate forcing of +0.3 W/m(2) in the Northern Hemisphere. The "efficacy" of this forcing is approximately 2, i.e., for a given forcing it is twice as effective as CO(2) in altering global surface air temperature. This indirect soot forcing may have contributed to global warming of the past century, including the trend toward early springs in the Northern Hemisphere, thinning Arctic sea ice, and melting land ice and permafrost. If, as we suggest, melting ice and sea level rise define the level of dangerous anthropogenic interference with the climate system, then reducing soot emissions, thus restoring snow albedos to pristine high values, would have the double benefit of reducing global warming and raising the global temperature level at which dangerous anthropogenic interference occurs. However, soot contributions to climate change do not alter the conclusion that anthropogenic greenhouse gases have been the main cause of recent global warming and will be the predominant climate forcing in the future.

  20. Soot climate forcing via snow and ice albedos

    PubMed Central

    Hansen, James; Nazarenko, Larissa

    2004-01-01

    Plausible estimates for the effect of soot on snow and ice albedos (1.5% in the Arctic and 3% in Northern Hemisphere land areas) yield a climate forcing of +0.3 W/m2 in the Northern Hemisphere. The “efficacy” of this forcing is ∼2, i.e., for a given forcing it is twice as effective as CO2 in altering global surface air temperature. This indirect soot forcing may have contributed to global warming of the past century, including the trend toward early springs in the Northern Hemisphere, thinning Arctic sea ice, and melting land ice and permafrost. If, as we suggest, melting ice and sea level rise define the level of dangerous anthropogenic interference with the climate system, then reducing soot emissions, thus restoring snow albedos to pristine high values, would have the double benefit of reducing global warming and raising the global temperature level at which dangerous anthropogenic interference occurs. However, soot contributions to climate change do not alter the conclusion that anthropogenic greenhouse gases have been the main cause of recent global warming and will be the predominant climate forcing in the future. PMID:14699053

  1. Soot climate forcing via snow and ice albedos

    NASA Astrophysics Data System (ADS)

    Hansen, James; Nazarenko, Larissa

    2004-01-01

    Plausible estimates for the effect of soot on snow and ice albedos (1.5% in the Arctic and 3% in Northern Hemisphere land areas) yield a climate forcing of +0.3 W/m2 in the Northern Hemisphere. The "efficacy" of this forcing is 2, i.e., for a given forcing it is twice as effective as CO2 in altering global surface air temperature. This indirect soot forcing may have contributed to global warming of the past century, including the trend toward early springs in the Northern Hemisphere, thinning Arctic sea ice, and melting land ice and permafrost. If, as we suggest, melting ice and sea level rise define the level of dangerous anthropogenic interference with the climate system, then reducing soot emissions, thus restoring snow albedos to pristine high values, would have the double benefit of reducing global warming and raising the global temperature level at which dangerous anthropogenic interference occurs. However, soot contributions to climate change do not alter the conclusion that anthropogenic greenhouse gases have been the main cause of recent global warming and will be the predominant climate forcing in the future. aerosols | air pollution | climate change | sea level

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  3. Arctic Moisture Source for Eurasian Snow Cover Variations in Autumn

    NASA Astrophysics Data System (ADS)

    Wegmann, M.

    2015-12-01

    Global warming is enhanced at high northern latitudes where the Arctic surface airtemperature has risen at twice the rate of the global average in recent decades - afeature called Arctic amplification. This recent Arctic warming signal likely resultsfrom several factors such as the albedo feedback due to a diminishing cryosphere,enhanced poleward atmospheric and oceanic transport, and change in humidity. Moreover, Arcticsummer sea-ice extent has declined by more than 10% per decade since the start ofthe satellite era (e.g. Stroeve et al., 2012), culminating in a new record low inSeptember 2012.Eurasian snow cover changes have been suggested as a driver for changes in theArctic Oscillation and might provide a link between sea ice decline in the Arcticduring summer and atmospheric circulation in the following winter. However, themechanism connecting snow cover in Eurasia to sea ice decline in autumn is stillunder debate. Our analysis focuses on sea ice decline in the Barents-Kara Sea region, which allowsus to specify regions of interest for FLEXPART forward and backwards moisturetrajectories. Based on Eularian and Lagrangian diagnostics from ERA-INTERIM, wecan address the origin and cause of late autumn snow depth variations in a dense(snow observations from 820 land stations), unutilized observational datasets over theCommonwealth of Independent States.Open waters in the Barents and Kara Sea have been shown to increase the diabaticheating of the atmosphere, which amplifies baroclinic cyclones and might induce aremote atmospheric response by triggering stationary Rossby waves (Honda et al.2009).In agreement with these studies, our results show enhanced storm activity originatingat the Barents and Kara with disturbances entering the continent through a smallsector from the Barents and Kara Seas. Maxima in storm activity trigger increasing uplift, oftenaccompanied by positive snowfall and snow depth anomalies.We show that declining sea ice in the Barents and Kara Seas

  4. [Effects of snow pack removal on the dynamics of winter-time soil temperature, carbon, nitrogen, and phosphorus in alpine forests of west Sichuan].

    PubMed

    Tan, Bo; Wu, Fu-zhong; Yang, Wan-qin; Yang, Yu-lian; Wang, Ao; Kang, Li-na

    2011-10-01

    The dynamic changes of snow pack as affected by global warming might have strong effects on the ecological processes in alpine forests. To understand the responses of soil ecological processes in the alpine forests of west Sichuan to the decreasing snow pack under global warming, a snow-shading experiment was conducted in a primary fir forest from October 19, 2009 to May 18, 2010, with the effects of snow pack removal on the dynamics of soil temperature, carbon, nitrogen, and phosphorus investigated. The results showed that snow pack removal increased the diurnal variation amplitude of soil temperature and the frequency of freeze-thaw cycle, and advanced the time of soil frozen and melt as well as the peak time of soil dissolved carbon and nitrogen, available P, NH4(+)-N, and NO3(-)-N. Snow pack removal increased the concentrations of soil dissolved carbon and nitrogen and NO3(-)-N but decreased the concentrations of soil available P and NH4(+)-N, and changed the ratios of soil dissolved carbon and nitrogen, available P, NH4(+)-N, and NO3(-)-N in the period of snow cover and snow melt. The decreased snow pack in winter time in the alpine forests of west Sichuan as affected by global warming could alter the soil exterior environment, and further, affect the processes of soil carbon, nitrogen and phosphorus.

  5. Apparatus for blending small particles

    DOEpatents

    Bradley, R.A.; Reese, C.R.; Sease, J.D.

    1975-08-26

    An apparatus is described for blending small particles and uniformly loading the blended particles in a receptacle. Measured volumes of various particles are simultaneously fed into a funnel to accomplish radial blending and then directed onto the apex of a conical splitter which collects the blended particles in a multiplicity of equal subvolumes. Thereafter the apparatus sequentially discharges the subvolumes for loading in a receptacle. A system for blending nuclear fuel particles and loading them into fuel rod molds is described in a preferred embodiment. (auth)

  6. Wideband Instrument for Snow Measurements (WISM)

    NASA Technical Reports Server (NTRS)

    Miranda, Felix A.

    2015-01-01

    This presentation provides a brief summary of the utility of a wideband active and passive (radar and radiometer, respectively) instrument (8-40 GHz) to support the snow science community. The effort seeks to improve snow measurements through advanced calibration and expanded frequency of active and passive sensors and to demonstrate their science utility through airborne retrievals of snow water equivalent (SWE). In addition the effort seeks to advance the technology readiness of broadband current sheet array (CSA) antenna technology for spaceflight applications.

  7. Mobility of lightweight robots over snow

    NASA Astrophysics Data System (ADS)

    Lever, James H.; Shoop, Sally A.

    2006-05-01

    Snowfields are challenging terrain for lightweight (<50 kg) unmanned ground vehicles. Deep sinkage, high snowcompaction resistance, traction loss while turning and ingestion of snow into the drive train can cause immobility within a few meters of travel. However, for suitably designed vehicles, deep snow offers a smooth, uniform surface that can obliterate obstacles. Key requirements for good over-snow mobility are low ground pressure, large clearance relative to vehicle size and a drive system that tolerates cohesive snow. A small robot will invariably encounter deep snow relative to its ground clearance. Because a single snowstorm can easily deposit 30 cm of fresh snow, robots with ground clearance less than about 10 cm must travel over the snow rather than gain support from the underlying ground. This can be accomplished using low-pressure tracks (< 1.5 kPa). Even still, snow-compaction resistance can exceed 20% of vehicle weight. Also, despite relatively high traction coefficients for low track pressures, differential or skid steering is difficult because the outboard track can easily break traction as the vehicle attempts to turn against the snow. Short track lengths (relative to track separation) or coupled articulated robots offer steering solutions for deep snow. This paper presents preliminary guidance to design lightweight robots for good mobility over snow based on mobility theory and tests of PackBot, Talon and SnoBot, a custom-designed research robot. Because many other considerations constrain robot designs, this guidance can help with development of winterization kits to improve the over-snow performance of existing robots.

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

    NASA Astrophysics Data System (ADS)

    Ge, Y.; Gong, G.

    2006-12-01

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

  9. Remotely Measuring Snow Depth in Inaccessible Terrain

    NASA Astrophysics Data System (ADS)

    Dixon, D.; Boon, S.

    2010-12-01

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

  10. Wideband Instrument for Snow Measurements (WISM)

    NASA Technical Reports Server (NTRS)

    Miranda, Felix A.; Lambert, Kevin M.; Romanofsky, Robert R.; Durham, Tim; Speed, Kerry; Lange, Robert; Olsen, Art; Smith, Brett; Taylor, Robert; Schmidt, Mark; Racette, Paul; Bonds, Quenton; Brucker, Ludovic; Koenig, Lora; Marshall, Hans-Peter; Vanhille, Ken; Borissenko, Anatoly; Tsang, Leung; Tan, Shurun

    2016-01-01

    This presentation discusses current efforts to develop a Wideband Instrument for Snow Measurements (WISM). The objective of the effort are as follows: to advance the utility of a wideband active and passive instrument (8-40 gigahertz) to support the snow science community; improve snow measurements through advanced calibration and expanded frequency of active and passive sensors; demonstrate science utility through airborne retrievals of snow water equivalent (SWE); and advance the technology readiness of broadband current sheet array (CSA) antenna technology for spaceflight applications.

  11. Snow Conditions Near Barrow in Spring 2012

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Saloranta, Tuomo M.

    2016-07-01

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

  13. Subpixel Snow-Covered-Area and Snow Grain Size From Mixture Analysis with AVIRIS Data

    NASA Technical Reports Server (NTRS)

    Green Robert O.; Painter, Thomas H.; Roberts, Dar A.; Dozier, Jeff

    1996-01-01

    Snow-covered-area (SCA) and snow grain size are crucial inputs to hydrologic and climatologic modeling of alpine and other seasonally snow-covered regions. SCA is necessary to parameterize energy budget calculations in climate models, to determine in which regions point snowmelt models are to be run for distributed snowmelt modeling efforts and to provide a basis from which estimates of snow water equivalent (SWE) may be made. Snow grain size, SWE and snow impurities determine the spectral albedo of snow, which controls the net solar flux at the snowpack surface. Snow albedo is of the utmost importance in snowmelt modeling, yet the difficulty with which grain size, SWE, and impurities are mapped has left the spatial distribution of snow albedo in alpine catchments poorly understood. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has been used to estimate sub-pixel snow-covered-area and snow grain size independently. In this paper we present a technique which improves estimates of both snow parameters by treating their mapping simultaneously.

  14. The Morphology of Polar Snow Surfaces: A Race Between Time and Snow Grain Properties

    NASA Astrophysics Data System (ADS)

    Filhol, S. V. P.; Sturm, M.

    2014-12-01

    Polar snow surfaces are rough, composed of multiple forms shaped by the interaction of snow grains and the wind. Based on the literature and new three-dimensional laser scanning data acquired in the Alaskan Arctic, we revisited the existing classifications of snow forms, and suggest a new genetic classification. Next we compared the morphology of aeolian snow features to analogous sand features, and then investigated the processes responsible for the differences. Although previous studies have suggested close similitudes between sand and snow features (barchan dunes, transverse dunes, etc.), we find significant differences, including: 1) snow features are smaller by a factor of a 100, 2) snow dunes are flatter, 3) snow dunes move four orders of magnitude faster than sand dunes, and 4) sand dunes last millennia, while snow dunes are by and large ephemeral. Coupling equations for dune age, propagation speed, snow flux, and wind speed, we find that the lower density of snow grains vs. sand (which should produce a higher flux) is balanced by sintering, which serves as a countdown timer, eventually bonding grains together, reducing material fluxes, and thereby limiting the growth and age of snow dunes.

  15. Arrest of Avalanche Propagation by Discontinuities on Snow Cover

    NASA Astrophysics Data System (ADS)

    Frigo, B.; Chiaia, B.

    2009-04-01

    results are supported also by other investigations, which suggested that increased spatial variability in the snow cover leads to a lower release probability of snow avalanches. The above studies are based on very different approaches, such as cellular automata (Kronholm and Birkeland, 2005) and statistical renormalization (Chiaia and Frigo, 2009) models, but come to the same conclusion, i.e. that the presence of randomly distributed weak zones increase the global robustness and toughness of the snow slope. From a practical engineering viewpoint, results could be used towards a new idea of active avalanche protection, based on the presence of natural (e.g., trees) or artificial objects throughout the slope, able to create low deposition zones as discontinuities in the snow cover. Key words: snow avalanche, fracture mechanics, crack arrester. References Chiaia, B., Cornetti, P., Frigo, B., 2008. Triggering of dry snow slab avalanches: Stress versus fracture mechanical approach Cold Reg. Sci. Technol. 53 170-178. Chiaia, B., Frigo, B., 2009, A scale-invariant model for snow slab-avalanches, J. Stat. Phys., submitted Föhn, P.M.B., Camponovo, C., Krüsi, G., 1998. Mechanical and structural properties of weak snow layers measured in situ. Annals of Glaciology 26, 1-6. Jamieson, J.B., Johnston, C.D., 1992. A fracture-arrest model for unconfined dry slab avalanches. Canadian Geotechnical Journal, 29, 61-66. Jamieson, B., Johnston, C.D., 2001. Evaluation of shear frame test for weak snowpack layers. Annals of Glaciology 32, 59-69. Kirchner, H.O.K., Michot, G., Schweizer, J., 2002. Fracture toughness of snow in shear and tension. Scripta Materialia 46, 425-429. Kronholm, K., Birkeland, K. W., 2005. Integrating spatial patterns into a snow avalanche cellular automata model, Geophysical Research Letters 32, L19504. McClung, D. M. 1979. Shear fracture precipitated by strain softening as a mechanism of dry slab avalanche release, J. Geophys. Res. 84(B7) 3519-3526. Schweizer, J., 1999

  16. Simulations of Snow Redistribution in Marmot Creek with a Coupled Multiscale Atmospheric-Land Surface-Blowing Snow Model

    NASA Astrophysics Data System (ADS)

    Guzman, E. H.; Pomeroy, J. W.; Pietroniro, A.

    2009-12-01

    The hydrology of mountainous cold regions is significantly influenced by the development of the seasonal snowcover. However snow is often transported, sublimated and redistributed by wind before it can form a snowpack. Physical based hydrological models are well accepted methods to simulate snow processes. But even these sophisticated tools have a limited application with the lack of high (spatial and temporal) resolution forcing data. Economic and practical limitations normally make it impossible to have a sufficient spatial density of hydrometeorological observation stations to run snow redistribution models at high elevations. Therefore, a different method must be adopted in order to provide the forcing wind speeds, wind direction precipitation, temperature and humidity fields required. The objective of this study is to develop a multiscale modeling system capable of dynamically downscaling boundary layer atmospheric processes from the global model (~15 km) to the hydrological model spatial scale (~500 m). The methodology consists of coupling the atmospheric models: Global Environmental Multiscale Limited Area Model (GEM-LAM), the Mesoscale Compressible Community (MC2) model and the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface scheme with the hydrological model: Cold Regions Hydrological Model (CRHM). Each model is run at the scale for which it is most appropriate; GEM-LAM and ISBA at large scales (15 km), MC2 and CRHM at smaller scales (500 m). The atmospheric models are used on a non-interactive nesting configuration, where the variables chosen to validate the simulations correspond to the forcing data of CRHM set up for blowing snow simulations. Temperature, precipitation, relative humidity and the wind direction and speed were modelled and measured from eight hydrometeorological stations located in open environments from valley bottom to mountain ridgetop in Marmot Creek Research Basin (50° 57’ N, 115° 10’ W) in the Rocky

  17. Digging in 'Snow White' Trench

    NASA Technical Reports Server (NTRS)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Surface Stereo Imager on the 44th Martian day of the mission, or Sol 43 (July 7, 2008), after the May 25, 2008, landing, showing the current sample scraping area in the trench informally called 'Snow White.'

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is led by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  18. Temperature Control Method in the Snow Road Construction

    NASA Astrophysics Data System (ADS)

    Serebrenikova, Yu; Lysyannikov, A.; Kaizer, Yu; Zhelykevich, R.; Plakhotnikova, M.; Lysyannikova, N.; Merko, M.; Merko, I.

    2016-06-01

    The paper substantiates the process of heat treatment before the snow compaction in snow road construction. The methods to measure the temperature of snow as a moving dispersed material have been considered in the paper.

  19. Multi-model blending

    DOEpatents

    Hamann, Hendrik F.; Hwang, Youngdeok; van Kessel, Theodore G.; Khabibrakhmanov, Ildar K.; Muralidhar, Ramachandran

    2016-10-18

    A method and a system to perform multi-model blending are described. The method includes obtaining one or more sets of predictions of historical conditions, the historical conditions corresponding with a time T that is historical in reference to current time, and the one or more sets of predictions of the historical conditions being output by one or more models. The method also includes obtaining actual historical conditions, the actual historical conditions being measured conditions at the time T, assembling a training data set including designating the two or more set of predictions of historical conditions as predictor variables and the actual historical conditions as response variables, and training a machine learning algorithm based on the training data set. The method further includes obtaining a blended model based on the machine learning algorithm.

  20. Miscibility of Polyolefin Blends

    NASA Astrophysics Data System (ADS)

    Luettmer-Strathmann, Jutta; Lipson, Jane E. G.

    1998-10-01

    Phase separation in polymers is important for many technical applications but difficult to predict theoretically. Recently, extensive experimental studies on the miscibility of polyolefins revealed that these systems display a wider variety of mixing behavior than their chemical similarity suggests. In order to predict phase diagrams of polyolefin blends from pure component properties, we have developed a method in which small scale simulations of local interactions are combined with an analytical model for the thermodynamics, the Born-Green-Yvon lattice model. A comparison with experimental data shows that the new approach yields qualitatively correct predictions for phase separation in LCST as well as UCST blends, including the effects of pressure and molar mass of the components on the phase transition temperatures.

  1. Potential of a low-cost sensor network to understand the spatial and temporal dynamics of a mountain snow cover

    NASA Astrophysics Data System (ADS)

    Pohl, Stefan; Garvelmann, Jakob; Wawerla, Jens; Weiler, Markus

    2014-03-01

    The spatial and temporal dynamics of seasonal snow covers play a critical role for many hydrological, ecological, and climatic processes. This paper presents a new, innovative approach to continuously monitor these dynamics using numerous low-cost, standalone snow monitoring stations (SnoMoS). These stations provide snow and related meteorological data with a high temporal and spatial resolution. Data collected by SnoMoS include: snow depth, surface temperature, air temperature and humidity, total precipitation, global radiation, wind speed, and barometric pressure. A total of 99 sensors were placed over the winters 2010/2011 and 2011/2012 at multiple locations within three 40-180 km2 basins in the Black Forest region of Southern Germany. The locations were chosen to cover a wide range of slopes, elevations, and expositions in a stratified sampling design. Furthermore, "paired stations" located in close proximity to each other, one in the open and one underneath various forest canopies, were set up to investigate the influence of vegetation on snow dynamics. The results showed that considerable differences in snow depth and, therefore, snow water equivalent (SWE) are present within the study area despite its moderate temperatures and medium elevation range (400-1500 m). The relative impact of topographical factors like elevation, aspect, and of different types of forest vegetation were quantified continuously and were found to change considerably over the winter period. The recorded differences in SWE and snow cover duration were large enough that they should be considered in hydrologic and climate models.

  2. Lasting effects of snow accumulation on summer performance of large herbivores in alpine ecosystems may not last.

    PubMed

    Mysterud, Atle; Austrheim, Gunnar

    2014-05-01

    One of the clearest predictions from the IPCC is that we can expect much less snow cover due to global warming in the 21st century, especially in the lower alpine areas. In alpine ecosystems, snow accumulation in depressions gives rise to distinct snow-bed vegetation types, assumed to play a key role in ecosystem function. A delayed plant phenology yields high-quality forage in late summer for wild and domestic herbivores. Yet, the mechanistic pathways for how declining snow may affect future performance of large herbivores beyond the effect of phenology remain poorly documented. Here, we link unique individual-based data on diet choice, habitat selection and performance of domestic sheep over a 10-year period to manually GPS-recorded spatial positions of snow cover in early summer (0.57% to 43.3% in snow beds on 1st of July) in an alpine ecosystem. Snowy winters gave a higher proportion of easily digestible herbs in the diet and a more variable use of snow-bed and meadow vegetation types resulting in faster growing lambs. These patterns were consistent between two density treatment levels although slightly more marked for diet at low density, suggesting that effects of simple mitigation efforts such as managing population numbers will be meagre. Our study thus yields novel insight into the strong impact of melting snow on ecosystem function in alpine habitats, which are likely to affect productivity of both domestic and wild ungulate populations.

  3. Synthesizing optimal waste blends

    SciTech Connect

    Narayan, V.; Diwekar, W.M.; Hoza, M.

    1996-10-01

    Vitrification of tank wastes to form glass is a technique that will be used for the disposal of high-level waste at Hanford. Process and storage economics show that minimizing the total number of glass logs produced is the key to keeping cost as low as possible. The amount of glass produced can be reduced by blending of the wastes. The optimal way to combine the tanks to minimize the vole of glass can be determined from a discrete blend calculation. However, this problem results in a combinatorial explosion as the number of tanks increases. Moreover, the property constraints make this problem highly nonconvex where many algorithms get trapped in local minima. In this paper the authors examine the use of different combinatorial optimization approaches to solve this problem. A two-stage approach using a combination of simulated annealing and nonlinear programming (NLP) is developed. The results of different methods such as the heuristics approach based on human knowledge and judgment, the mixed integer nonlinear programming (MINLP) approach with GAMS, and branch and bound with lower bound derived from the structure of the given blending problem are compared with this coupled simulated annealing and NLP approach.

  4. A satellite snow depth multi-year average derived from SSM/I for the high latitude regions

    USGS Publications Warehouse

    Biancamaria, S.; Mognard, N.M.; Boone, A.; Grippa, M.; Josberger, E.G.

    2008-01-01

    The hydrological cycle for high latitude regions is inherently linked with the seasonal snowpack. Thus, accurately monitoring the snow depth and the associated aerial coverage are critical issues for monitoring the global climate system. Passive microwave satellite measurements provide an optimal means to monitor the snowpack over the arctic region. While the temporal evolution of snow extent can be observed globally from microwave radiometers, the determination of the corresponding snow depth is more difficult. A dynamic algorithm that accounts for the dependence of the microwave scattering on the snow grain size has been developed to estimate snow depth from Special Sensor Microwave/Imager (SSM/I) brightness temperatures and was validated over the U.S. Great Plains and Western Siberia. The purpose of this study is to assess the dynamic algorithm performance over the entire high latitude (land) region by computing a snow depth multi-year field for the time period 1987-1995. This multi-year average is compared to the Global Soil Wetness Project-Phase2 (GSWP2) snow depth computed from several state-of-the-art land surface schemes and averaged over the same time period. The multi-year average obtained by the dynamic algorithm is in good agreement with the GSWP2 snow depth field (the correlation coefficient for January is 0.55). The static algorithm, which assumes a constant snow grain size in space and time does not correlate with the GSWP2 snow depth field (the correlation coefficient with GSWP2 data for January is - 0.03), but exhibits a very high anti-correlation with the NCEP average January air temperature field (correlation coefficient - 0.77), the deepest satellite snow pack being located in the coldest regions, where the snow grain size may be significantly larger than the average value used in the static algorithm. The dynamic algorithm performs better over Eurasia (with a correlation coefficient with GSWP2 snow depth equal to 0.65) than over North America

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  7. Assimilation of AMSR-E snow products with optimized snow parameters in mountainous basins

    NASA Astrophysics Data System (ADS)

    Lin, C.; Li, X.; Tsang, L.; Josberger, E. G.; Lettenmaier, D. P.

    2012-12-01

    Of the factors that affect microwave emissions of snowpacks, and in turn recoveries of snow radiative temperature, the snow pack grain size is among the most important. In an attempt to improve the ability to retrieve snow water equivalent from satellite passive microwave observations, we attempt first to improve estimates of the radiative temperature of the snow pack, and then use data assimilation techniques in a forward model. First, we partition the snow accumulation season based on the snow accumulation rate. For each period we calculate the brightness temperature (TB) of bare snow from AMSR-E observations, corrected for the forest cover fraction of each AMSR-E footprint. Given the observed snow depth (SD) and snow water equivalent (SWE), we then calculate the snow density and absorption coefficient (κa) of the snow. The optimal scattering coefficient (κs) is determined using Dense Media Radiative Transfer (DMRT) model of QCA and also of the bicontinuous medium. Finally, the optimal grain size is determined with respect to the optimal scattering coefficient. We verify the approach using field measurements from the Stanley Basin, Idaho. Finally, we assimilate the AMSR-E satellite observations of brightness temperature into the Variable Infiltration Capacity (VIC) hydrologic model. Combination of the VIC SWE simulation with the DMRT output using optimal physical parameters is expected to improve satellite-based SWE estimates in the mountainous region.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  10. Snow, Wind, Sun, and Time - How snow-driven processes control the Arctic sea ice

    NASA Astrophysics Data System (ADS)

    Polashenski, C.; Druckenmiller, M. L.; Perovich, D. K.

    2012-12-01

    Snowfall on Arctic sea ice is important for a number of reasons. The snowpack insulates sea ice from the cold winter atmosphere, redistribution of snow alters the surface roughness of the ice, light scattering in the snow increases ice albedo and reduces light transmission, and the weight of early season snow can result in ice surface flooding. An integrated set of field observations were collected to better understand how snowfall and, particularly, snow redistribution processes impact Arctic ice mass balance. Coincident measurements of snow depth and ice thickness on un-deformed first year ice indicate that snow dunes 'lock' in place early in the winter growth season, resulting in thinner ice beneath the dunes due to lower rates of energy loss. Coincident ground-based LiDAR measurements of surface topography and snow depth show that snow dune formation is largely responsible for the topographic relief of otherwise flat first year ice. Past work has shown that pond formation during the early melt season is strongly guided by the snow-controlled relative surface heights at a given site. Here multiple study sites are examined in an effort to better understand how differing patterns of snow redistribution can impact the overall extent of melt ponds, and therefore ice albedo. The results enhance basic knowledge of how snow processes control sea ice mass balance, and evoke several questions which must be answered in order to understand how changing precipitation regimes may affect sea ice in the Arctic.

  11. LANDSAT-D investigations in snow hydrology

    NASA Technical Reports Server (NTRS)

    Dozier, J. (Principal Investigator)

    1984-01-01

    Thematic mapper radiometric characteristics, snow/cloud reflectance, and atmospheric correction are discussed with application to determining the spectral albedo of snow. The geometric characterics of TM and digital elevation data are examined. The geometric transformations and resampling required to coregister these data are discussed.

  12. A drought index accounting for snow

    NASA Astrophysics Data System (ADS)

    Staudinger, Maria; Stahl, Kerstin; Seibert, Jan

    2015-04-01

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

  13. Brilliant Colours from a White Snow Cover

    ERIC Educational Resources Information Center

    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…

  14. Blast noise propagation above a snow cover.

    PubMed

    Albert, D G; Hole, L R

    2001-06-01

    A porous medium model of a snow cover, rather than a viscoelastic treatment, has been used to simulate measured, horizontally traveling acoustic waveform propagation above a dry snow cover 11-20 cm thick. The waveforms were produced by explosions of 1-kg charges at propagation distances of 100 to 1400 m. These waveforms, with a peak frequency around 30 Hz, show pulse broadening effects similar to those previously seen for higher-frequency waves over shorter propagation distances. A rigid-ice-frame porous medium ("rigid-porous") impedance model, which includes the effect of the pores within the snow but ignores any induced motion of the ice particles, is shown to produce much better agreement with the measured waveforms compared with a viscoelastic solid treatment of the snow cover. From the acoustic waveform modeling, the predicted average snow cover depth of 18 cm and effective flow resistivities of 16-31 kPa s m(-2) agree with snow pit observations and with previous acoustic measurements over snow. For propagation in the upwind direction, the pulse broadening caused by the snow cover interaction is lessened, but the overall amplitude decay is greater because of refraction of the blast waves. PMID:11425110

  15. Kindergarten Explorations with Snow, Ice, and Water

    ERIC Educational Resources Information Center

    Carroll, Martha A.

    1978-01-01

    Using winter snow, kindergarten students can explore the properties of water. Students demonstrate melting, freezing, expansion, and evaporation through a number of activities involving a paper cup and a scoop of snow. Procedures and student reactions are described in detail by the teacher-author. (MA)

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

    ERIC Educational Resources Information Center

    Kamtekar, Rachana

    2015-01-01

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

  17. Red and near-infrared spectral reflectance of snow

    NASA Technical Reports Server (NTRS)

    Obrien, H. W.; Munis, R. H.

    1975-01-01

    The spectral reflectance of snow in the range of 0.60 to 2.50 microns wavelengths was studied in a cold laboratory using natural snow and simulated preparations of snow. A white barium sulfate powder was used as the standard for comparison. The high reflectance (usually nearly 100%) of fresh natural snow in visible wavelengths declines rapidly at wavelengths longer than the visible, as the spectral absorption coefficients of ice increase. Aging snow becomes only somewhat less reflective than fresh snow in the visible region and usually retains a reflectance greater than 80%. In the near infrared, aging snow tends to become considerably less reflective than fresh snow.

  18. Microbes in High Arctic Snow and Implications for the Cold Biosphere ▿ †

    PubMed Central

    Harding, Tommy; Jungblut, Anne D.; Lovejoy, Connie; Vincent, Warwick F.

    2011-01-01

    We applied molecular, microscopic, and culture techniques to characterize the microbial communities in snow and air at remote sites in the Canadian High Arctic (Ward Hunt Island, Ellesmere Island, and Cornwallis Island, latitudes 74 to 83oN). Members of the Bacteria and Eukarya were prevalent in the snow, and their small subunit (SSU) rRNA gene signatures indicated strong local aerial transport within the region over the preceding 8 months of winter snowpack accumulation. Many of the operational taxonomic units (OTUs) were similar to previously reported SSU rRNA gene sequences from the Arctic Ocean, suggesting the importance of local aerial transport processes for marine microbiota. More than 47% of the cyanobacterial OTUs in the snow have been previously found in microbial mats in the region, indicating that this group was also substantially derived from local sources. Viable cyanobacteria isolated from the snow indicated free exchange between the snow and adjacent mat communities. Other sequences were most similar to those found outside the Canadian Arctic but were from snow, lake and sea ice, glaciers and permafrost, alpine regions, Antarctica, and other regions of the Arctic, supporting the concept of global distribution of microbial ecotypes throughout the cold biosphere. PMID:21460114

  19. Snow cover dynamics and hydrological regime of the Hunza River basin, Karakoram Range, Northern Pakistan

    NASA Astrophysics Data System (ADS)

    Tahir, A. A.; Chevallier, P.; Arnaud, Y.; Ahmad, B.

    2011-07-01

    A major proportion of flow in the Indus River is contributed by its snow- and glacier-fed river catchments situated in the Himalaya, Karakoram and Hindukush ranges. It is therefore essential to understand the cryosphere dynamics in this area for water resource management. The MODIS MOD10A2 remote-sensing database of snow cover products from March 2000 to December 2009 was selected to analyse the snow cover changes in the Hunza River basin (the snow- and glacier-fed sub-catchment of the Indus River). A database of daily flows for the Hunza River at Dainyor Bridge over a period of 40 yr and climate data (precipitation and temperature) for 10 yr from three meteorological stations within the catchment was made available to investigate the hydrological regime in the area. Analysis of remotely sensed cryosphere (snow and ice cover) data during the last decade (2000-2009) suggest a rather slight expansion of cryosphere in the area in contrast to most of the regions in the world where glaciers are melting rapidly. This increase in snow cover may be the result of an increase in winter precipitation caused by westerly circulation. The impact of global warming is not effective because a large part of the basin area lies under high altitudes where the temperature remains negative throughout most of the year.

  20. Combining Passive Microwave and Optical Data to Estimate Snow Water Equivalent in Afghanistan's Hindu Kush

    NASA Astrophysics Data System (ADS)

    Dozier, J.; Bair, N.; Calfa, A. A.; Skalka, C.; Tolle, K.; Bongard, J.

    2015-12-01

    The task is to estimate spatiotemporally distributed estimates of snow water equivalent (SWE) in snow-dominated mountain environments, including those that lack on-the-ground measurements such as the Hindu Kush range in Afghanistan. During the snow season, we can use two measurements: (1) passive microwave estimates of SWE, which generally underestimate in the mountains; (2) fractional snow-covered area from MODIS. Once the snow has melted, we can reconstruct the accumulated SWE back to the last significant snowfall by calculating the energy used in melt. The reconstructed SWE values provide a training set for predictions from the passive microwave SWE and snow-covered area. We examine several machine learning methods—regression-boosted decision trees, bagged trees, neural networks, and genetic programming—to estimate SWE. All methods work reasonably well, with R2 values greater than 0.8. Predictors built with multiple years of data reduce the bias that usually appears if we predict one year from just one other year's training set. Genetic programming tends to produce results that additionally provide physical insight. Adding precipitation estimates from the Global Precipitation Measurements mission is in progress.

  1. Microbes in high arctic snow and implications for the cold biosphere.

    PubMed

    Harding, Tommy; Jungblut, Anne D; Lovejoy, Connie; Vincent, Warwick F

    2011-05-01

    We applied molecular, microscopic, and culture techniques to characterize the microbial communities in snow and air at remote sites in the Canadian High Arctic (Ward Hunt Island, Ellesmere Island, and Cornwallis Island, latitudes 74 to 83(o)N). Members of the Bacteria and Eukarya were prevalent in the snow, and their small subunit (SSU) rRNA gene signatures indicated strong local aerial transport within the region over the preceding 8 months of winter snowpack accumulation. Many of the operational taxonomic units (OTUs) were similar to previously reported SSU rRNA gene sequences from the Arctic Ocean, suggesting the importance of local aerial transport processes for marine microbiota. More than 47% of the cyanobacterial OTUs in the snow have been previously found in microbial mats in the region, indicating that this group was also substantially derived from local sources. Viable cyanobacteria isolated from the snow indicated free exchange between the snow and adjacent mat communities. Other sequences were most similar to those found outside the Canadian Arctic but were from snow, lake and sea ice, glaciers and permafrost, alpine regions, Antarctica, and other regions of the Arctic, supporting the concept of global distribution of microbial ecotypes throughout the cold biosphere.

  2. The potential for snow to supply human water demand in the present and future

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

    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 ∼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 >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.

  3. Combination of MODIS Snow, Cloud and Land Spatial Coverage Data with SNOTEL to Generate Inter-Annual and Within-Season Snow Depletion Curves and Maps

    NASA Astrophysics Data System (ADS)

    Qualls, R. J.; Arogundade, A. B.

    2015-12-01

    Quantification of spatial coverage of snow and its temporal decline throughout the snowmelt season is an important input for snowmelt runoff models in the prediction of runoff and simulation of streamflow. Several remote sensing methods of snow cover mapping exist today with differing spatial and temporal resolutions that can be used in determining the progressive reduction of snow cover during snowmelt. The Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite sensor has provided global coverage with daily temporal resolution and a spatial resolution on the order of 1 km2 since the year 2000. Several challenges hinder the development and routine use of MODIS snow covered area products, which include cloud and forest obscuration of snow-covered surfaces. Furthermore, the relatively recent launch of the MODIS sensor prevents its direct use in historical or future (e.g., climate change scenario) studies. Based on numerous observations in the literature that snowmelt occurs in a repeating spatial pattern, albeit shifted and/or accelerated or decelerated in time, from one year to the next, a method is presented that makes use of remotely sensed MODIS snow, land and cloud data and concurrent ground-based Snow Telemetry (SNOTEL) data to construct a single, inter-annually applicable and temporally dimensionless snow depletion curve and a corresponding snow depletion map. MODIS Cloud data and ground-based SNOTEL snowfall data during the snowmelt season are used together with the inter-annual snowmelt curve/map to generate within-year snowmelt curves that account for the impact of additional melt-season snowfall. The method is successfully applied to the 9000 km2 Upper Snake River Basin in Wyoming, USA as a test case. The method may be used with historical SNOTEL data to reconstruct snow depletion curves or maps for base periods preceding the availability of current satellite remote sensing, and with synthesized weather datasets for future periods associated with

  4. Observing snow cover using unmanned aerial vehicle

    NASA Astrophysics Data System (ADS)

    Spallek, Waldemar; Witek, Matylda; Niedzielski, Tomasz

    2016-04-01

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

  5. A conceptual, distributed snow redistribution model

    NASA Astrophysics Data System (ADS)

    Frey, S.; Holzmann, H.

    2015-11-01

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

  6. Simulated Albedo in Needleleaf Forests is Highly Sensitive to the Treatment of Intercepted Snow: An Examination of Canopy Snow Parameterizations in the Canadian Land Surface Scheme

    NASA Astrophysics Data System (ADS)

    Bartlett, P. A.; Verseghy, D. L.

    2015-12-01

    The winter albedo of boreal evergreen needleleaf forest (ENF) has been poorly simulated in climate models, with a reported range among CMIP5 models exceeding 0.25 in April, and a strong positive bias in areas with high canopy cover. Such errors have been attributed to unrealistic representation of leaf area index, snow interception and unloading, and are associated with biases in the simulated snow albedo feedback. The Canadian Atmospheric Global Climate Model has been shown to underestimate the winter albedo in boreal ENF. We present changes to the parameterization of the albedo of ENF with intercepted snow; a new relationship between interception and the fractional coverage of the canopy by snow (fsnow); and unloading based on weather conditions. The new algorithms are employed in version 3.6 of the Canadian Land Surface Scheme (CLASS) in off-line mode and the simulated daily albedo compared with observations at four ENF sites.Default values for the visible and near-infrared albedo of snow-covered canopy were increased from 0.17 and 0.23, respectively, to 0.27 and 0.38. fsnow increased too slowly with interception, producing a damped albedo response. A new model for fsnow is based on zI* = 3 cm, the effective depth of newly intercepted snow required to raise the canopy albedo to its maximum (corresponding to fsnow = 1). Snow unloading rates were derived from visual assessments of photographs and modeled based on relationships with meteorological variables. A model based on wind speed at the canopy top produced the best result, replacing the time-based method employed in CLASS. Model configurations were assessed based on the index of agreement, d, and the root mean squared error (RMSE). The mean d and RMSE over four sites were 0.58 and 0.058 for the default configuration of CLASS 3.6, and 0.86 and 0.038 for the best model configuration.

  7. Remote sensing of snow and ice

    NASA Technical Reports Server (NTRS)

    Rango, A.

    1979-01-01

    This paper reviews remote sensing of snow and ice, techniques for improved monitoring, and incorporation of the new data into forecasting and management systems. The snowcover interpretation of visible and infrared data from satellites, automated digital methods, radiative transfer modeling to calculate the solar reflectance of snow, and models using snowcover input data and elevation zones for calculating snowmelt are discussed. The use of visible and near infrared techniques for inferring snow properties, microwave monitoring of snowpack characteristics, use of Landsat images for collecting glacier data, monitoring of river ice with visible imagery from NOAA satellites, use of sequential imagery for tracking ice flow movement, and microwave studies of sea ice are described. Applications of snow and ice research to commercial use are examined, and it is concluded that a major problem to be solved is characterization of snow and ice in nature, since assigning of the correct properties to a real system to be modeled has been difficult.

  8. Modelling snow properties in Kautokeino, Northern Norway

    NASA Astrophysics Data System (ADS)

    Vikhamar-Schuler, D.; Dish Mathiesen, S.; Hanssen-Bauer, I.

    2010-09-01

    Hard snow layers deteriorate the grazing situation for reindeers during winter. By modelling the snowpack evolution in Kautokeino over the period 1966-2009, we analyse the weather situations that favor the formation of high-density snow. This work is part of the IPY project EALAT (http://icr.arcticportal.org/en/ealat). We used daily meteorological observations to drive the Swiss multi-layer model SNOWPACK to simulate the evolution of snow cover stratigraphy in terms of density, temperature and grain size. Results are evaluated using direct snow pack observations made during the winter seasons 2007-2010. Furthermore, we compare the modelled snowpack 1966-2010 with historical records of difficult grazing conditions reported by reindeer herders. In particular, the considerable losses of animal lives during the winter 1967/68 was caused by the occurrence of ground ice in conjunction to the long snow cover duration. This unfavorable coincidence is well reproduced by our model results.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Despite advances in alpine snow modelling there remain two fundamental areas of divergent scientific thought in estimating alpine snow mass balances: i) blowing snow sublimation losses, and ii) wind flow representation. Sublimation calculations have poorly understood humidity feedbacks that vary considerably and mathematical representations of alpine windflow vary in complexity - these differences introduce uncertainty. To better estimate and restrain this uncertainty, a variety of physically based, spatially distributed snowmelt models that consider the physics of wind redistribution and sublimation of blowing snow were evaluated for their ability to simulate seasonal snow distribution and melt patterns in a windy alpine environment in the Canadian Rockies. The primary difference in the snow models was their calculation of blowing snow sublimation losses which ranged from large to small estimates. To examine the uncertainty introduced by windflow calculations on the snow model simulations, each model was forced with output from windflow models of varying computational complexity and physical realism from a terrain-based empirical interpolation of station observations to a simple turbulence model to a computational fluid dynamics model that solves for the Navier-Stokes equations. The high-resolution snow simulations were run over a 1 km2 spatial extent centred on a ridgetop meteorological station within the Marmot Creek Research basin, Alberta, Canada. The three windflow simulations all produced reasonable results compared to wind speeds measured on two opposing slopes (bias better than ×0.3 m s-1; RMSE < 1.1 m s-1), however there was great sensitivity in SWE simulated by the snow models to the driving windflow simulation used. Specifically, there were distinct differences in the magnitude and location of snow drifts from all snow models that depended on the windflow scheme. When compared to measurements from airborne LiDAR, snow surveys, and automated snow depth

  11. Comparing snow models under current and future climates: Uncertainties and implications for hydrological impact studies

    NASA Astrophysics Data System (ADS)

    Troin, Magali; Poulin, Annie; Baraer, Michel; Brissette, François

    2016-09-01

    Projected climate change effects on snow hydrology are investigated for the 2041-2060 horizon following the SRES A2 emissions scenario over three snowmelt-dominated catchments in Quebec, Canada. A 16-member ensemble of eight snow models (SM) simulations, based on the high-resolution Canadian Regional Climate Model (CRCM-15 km) simulations driven by two realizations of the Canadian Global Climate Model (CGCM3), is established per catchment. This study aims to compare a range of SMs in their ability at simulating snow processes under current climate, and to evaluate how they affect the assessment of the climate change-induced snow impacts at the catchment scale. The variability of snowpack response caused by the use of different models within two different SM approaches (degree-day (DD) versus mixed degree-day/energy balance (DD/EB)) is also evaluated, as well as the uncertainty of natural climate variability. The simulations cover 1961-1990 in the present period and 2041-2060 in the future period. There is a general convergence in the ensemble spread of the climate change signals on snow water equivalent at the catchment scale, with an earlier peak and a decreased magnitude in all basins. The results of four snow indicators show that most of the uncertainty arises from natural climate variability (inter-member variability of the CRCM) followed by the snow model. Both the DD and DD/EB models provide comparable assessments of the impacts of climate change on snow hydrology at the catchment scale.

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

    NASA Astrophysics Data System (ADS)

    Lei, Yang; Siqueira, Paul; Treuhaft, Robert

    2016-05-01

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

  13. Spatial and temporal variability of snow accumulation in East Antarctica from traverse data

    NASA Astrophysics Data System (ADS)

    Frezzotti, Massimo; Pourchet, Michel; Flora, Onelio; Gandolfi, Stefano; Gay, Michel; Urbini, Stefano; Vincent, Christian; Becagli, Silvia; Gragnani, Roberto; Proposito, Marco; Severi, Mirko; Traversi, Rita; Udisti, Roberto; Fily, Michel

    Recent snow accumulation rate is a key quantity for ice-core and mass-balance studies. Several accumulation measurement methods (stake farm, fin core, snow-radar profiling, surface morphology, remote sensing) were used, compared and integrated at eight sites along a transect from Terra Nova Bay to Dome C, East Antarctica, to provide information about the spatial and temporal variability of snow accumulation. Thirty-nine cores were dated by identifying tritium/β marker levels (1965-66) and non-sea-salt (nss) SO42- spikes of the Tambora (Indonesia) volcanic event (1816) in order to provide information on temporal variability. Cores were linked by snow radar and global positioning system surveys to provide detailed information on spatial variability in snow accumulation. Stake-farm and ice-core accumulation rates are observed to differ significantly, but isochrones (snow radar) correlate well with ice-core derived accumulation. The accumulation/ablation pattern from stake measurements suggests that the annual local noise (metre scale) in snow accumulation can approach 2 years of ablation and more than four times the average annual accumulation, with no accumulation or ablation for a 5 year period in up to 40% of cases. The spatial variability of snow accumulation at the kilometre scale is one order of magnitude higher than temporal variability at the multi-decadal/secular scale. Stake measurements and firn cores at Dome C confirm an approximate 30% increase in accumulation over the last two centuries, with respect to the average over the last 5000 years.

  14. Arctic Light Snow Observations: Missing Precipitation

    NASA Astrophysics Data System (ADS)

    Gultepe, Ismail; Rabin, Robert; Pavolonis, Michael; Heymsfield, Andrew; Girard, Eric; Burrows, William

    2015-04-01

    The objective of this work is to describe measurement conditions for light snow that is important for meteorological and hydrometeorological applications. Snow microphysical properties play a crucial role for developing better nowcasting/forecasting techniques, and to validate numerical weather prediction (NWP) simulations and assess climate change. Observations collected during the Fog Remote Sensing and Modeling (FRAM) and Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations (SAAWSO) projects that took place over the cold climatic regions of Canada, including Yellowknife, St. John's, and Goose Bay, respectively, were studied to assess missing snow effect on weather and climate change simulations. The Ground Cloud Imaging Probe (GCIP) together with other microphysical precipitation sensors (e.g. fog device, distrometer) can be used to better understand fog deposition, freezing drizzle, light rain, and light snow spectral characteristics and shape. Light snow particle size range based on GCIP measurements is between 7.5 and 940 µm, and provides particle size spectra over 60 channels at 15 µm intervals, as well as particle shape. The GCIP measurements together with hydrometeor measurements obtained from a distrometer called laser precipitation monitor (LPM) were used in an integrated approach for snow precipitation analysis because of the measurements uncertainties in the particle sizes less than 500 µm. The results suggest that missing light snow depth measurement as less than 1 mm/d can affect the energy budget of Arctic environments over a 6 month time period up to -2 to -5 W/m2 if snow sublimates. These values can be comparable with other feedbacks in climate simulations such as aerosol effects. In this study, GCIP used for light snow measurements and ice fog will be discussed and challenges related to measurement of light snow precipitation microphysics will be emphasized.

  15. The impact of land initialization on seasonal forecasts of surface air temperature: role of snow data assimilation in the Northern Hemisphere

    NASA Astrophysics Data System (ADS)

    Lin, P.; Wei, J.; Zhang, Y.; Yang, Z. L.

    2015-12-01

    Land initializations (i.e., snow, soil moisture, leaf area index) have been recognized as important sources of seasonal climate predictability besides ocean and atmosphere initializations. However, studies focusing on assessing how land data assimilation (DA) contributes to seasonal forecast skills are still lacking due to the limited number of large-scale land DA studies. In this study, taking advantage of the snow outputs from a multivariate global land DA system (i.e., DART/CLM), we systematically investigated the role of large-scale snow DA in influencing seasonal forecasts of surface air temperature. Three suites of ensemble seasonal forecast experiments were performed using the Community Earth System Model (CESM v1.2.1), in which three different snow initialization datasets were used. They are (1) CLM4 simulation without DA, (2) CLM4 simulation with MODIS snow cover DA, and (3) CLM4 simulation with joint GRACE and MODIS snow DA. Each suite of the experiment starts from multiple initialization dates of eight years from 2003 to 2010 and has three-month lead times. All experiments used the same atmosphere initializations from ERA-Interim (perturbed to get 8 ensembles) and the same prescribed SSTs. Our results show that snow DA plays an important role in surface air temperature predictions in regions such as Europe, western Canada, northern Alaska, Mongolia Plateau, Tibetan Plateau, and the Rocky Mountains. The analyses also account for multiple lead times as snow can influence the atmosphere through immediate snow-albedo effect and through delayed snow hydrological effect after snow melts and wets the soil. This is a first study to quantify the impacts of snow initializations on seasonal forecasts of surface air temperature with an emphasis on large-scale snow DA. The insights are helpful to both land DA studies as well as research on seasonal climate forecasts.

  16. Snow Depth with GPS: Case Study from Minnesota 2010-2011

    NASA Astrophysics Data System (ADS)

    Bilich, A. L.; Slater, A. G.; Larson, K. M.

    2011-12-01

    Although originally designed to enable accurate positioning and time transfer, the Global Positioning System (GPS) has also proved useful for remote sensing applications. In this study, GPS signals are used to measure snow depth via GPS interferometric reflectometry (GPS-IR). In GPS-IR, a GPS antenna receives the desired direct signal as well as an indirect signal which reflects off of the ground or snow surface. These two signals interfere, and the composite signal recorded by the GPS receiver can be post-processed to yield the distance between the antenna and the reflecting surface, that is, distance to the snow surface. We present the results of a new snow depth product for the state of Minnesota over the winter of 2010-2011. Although single-station examples of GPS snow depth measurements can be found in the literature, this is one of the first studies to compute GPS snow depth over a large regional-scale network. We chose Minnesota because the state Department of Transportation runs a network of continuously operating reference stations (CORS) with many desired characteristics: freely available data, good GPS station distribution with good proximity to COOP weather stations, GPS stations located adjacent to farm fields with few sky obstructions, and receiver models known to have sufficient data quality for GPS-IR. GPS-IR with CORS has many advantages over traditional snow depth measurements. First, because we leverage existing CORS, no new equipment installations are required and data are freely available via the Internet. Second, GPS-IR with CORS measures a large area, approximately 100 m2 around the station and 20 m2 per satellite. We present snow depth results for over 30 GPS stations distributed across the state. We compare the GPS-IR snow depth product to COOP observations and SNODAS modeled estimates. GPS-IR snow depth is one of the few independent data sources available for assessment of SNODAS. Ideally snow depth via GPS-IR will be available for

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  18. Use of MODIS Snow-Cover Maps for Detecting Snowmelt Trends in North America

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Foster, James L.; Riggs, George A.; Robinson, David A.; Hoon-Starr, Jody A.

    2012-01-01

    Research has shown that the snow season in the Northern Hemisphere has been getting shorter in recent decades, consistent with documented global temperature increases. Specifically, the snow is melting earlier in the spring allowing for a longer growing season and associated land-cover changes. Here we focus on North America. Using the Moderate-Resolution Imaging Radiometer (MODIS) cloud-gap-filled standard snow-cover data product we can detect a trend toward earlier spring snowmelt in the approx 12 years since the MODIS launch. However, not all areas in North America show earlier spring snowmelt over the study period. We show examples of springtime snowmelt over North America, beginning in March 2000 and extending through the winter of 2012 for all of North America, and for various specific areas such as the Wind River Range in Wyoming and in the Catskill Mountains in New York. We also compare our approx 12-year trends with trends derived from the Rutgers Global Snow Lab snow cover climate-data record.

  19. Drifting and blowing snow, measurements and modelling

    NASA Astrophysics Data System (ADS)

    Gordon, Mark

    2007-12-01

    Blowing snow is a frequent and significant winter weather event, and there is currently a need for more observations and measurements of blowing snow, especially in arctic and subarctic environments. A camera system has been developed to measure the size and velocity of blowing snow particles. A second camera system has been developed to measure the relative blowing snow density profile near the snow surface. These systems have been used, along with standard meteorological instruments and optical particle counters, during field campaigns at Franklin Bay, NWT, and at Churchill, MB. An electric field mill was also deployed at Franklin Bay. Results demonstrate that the particle diameters follow a Gamma distribution with 103 < d¯ < 172 mum below a height of 0.15 m and 120 < d¯ < 154 mum between 0.2 m and 1.1 m. Within the saltation layer, the mass density can be approximated by a power-law (rhos ∝ z -gamma) with an exponent of gamma ≈ 1.5 for z < 40 mm. Between 40 < z < 100 mm, in the lower suspension layer, the value of the exponent increases to a range of 1.5 < gamma < 8. At greater heights, z > 100 mm, the exponent approaches gamma ≈ l. The height of saltation shows a very weak dependence on the friction velocity, a strong dependence on temperature and relative humidity, and a weak dependence on snow age. Electric field strengths as high as 2000 V m-1 were measured at a height of 0.5 m. A model to determine electric field strength based on the distribution of blowing snow particles shows a weak agreement with measurements. Results suggest the charge is most likely generated due to either fragmentation or asymmetric rubbing, which are both strongly dependent on wind speed. Modelling studies with the Canadian Land Surface Scheme (CLASS) and previous measurements of snow depth at Goose Bay, Hay River, the Beaufort Sea, Franklin Bay, and Resolute demonstrate that blowing snow sublimation can have a substantial effect on snow depth. Adding a blowing snow

  20. Defrosting Polar Dunes--'The Snow Leopard'

    NASA Technical Reports Server (NTRS)

    1999-01-01

    The patterns created by dark spots on defrosting south polar dunes are often strange and beautiful. This picture, which the Mars Orbiter Camera team has dubbed, 'the snow leopard,' shows a dune field located at 61.5oS, 18.9oW, as it appeared on July 1, 1999. The spots are areas where dark sand has been exposed from beneath bright frost as the south polar winter cap begins to retreat. Many of the spots have a diffuse, bright ring around them this is thought to be fresh frost that was re-precipitated after being removed from the dark spot. The spots seen on defrosting polar dunes are a new phenomenon that was not observed by previous spacecraft missions to Mars. Thus, there is much about these features that remains unknown. For example, no one yet knows why the dunes become defrosted by forming small spots that grow and grow over time. No one knows for sure if the bright rings around the dark spots are actually composed of re-precipitated frost. And no one knows for sure why some dune show spots that appear to be 'lined-up' (as they do in the picture shown here).

    This Mars Global Surveyor Mars Orbiter Camera image is illuminated from the upper left. North is toward the upper right. The scale bar indicates a distance of 200 meters (656 feet).

    Malin Space Science Systems and the California Institute of Technology built the MOC using spare hardware from the Mars Observer mission. MSSS operates the camera from its facilities in San Diego, CA. The Jet Propulsion Laboratory's Mars Surveyor Operations Project operates the Mars Global Surveyor spacecraft with its industrial partner, Lockheed Martin Astronautics, from facilities in Pasadena, CA and Denver, CO.

  1. Seasonal Snow Extent and Snow Volume in South America Using SSM/I Passive Microwave Data

    NASA Technical Reports Server (NTRS)

    Foster, James L.; Chang, A. T. C.; Hall, D. K.; Kelly, R.; Houser, Paul (Technical Monitor)

    2001-01-01

    Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1992-1998, both snow cover extent and snow depth (snow mass) were investigated during the winter months (May-August) in the Patagonia region of Argentina. Since above normal temperatures in this region are typically above freezing, the coldest winter month was found to be not only the month having the most extensive snow cover but also the month having the deepest snows. For the seven-year period of this study, the average snow cover extent (May-August) was about 0.46 million sq km and the average monthly snow mass was about 1.18 x 10(exp 13) kg. July 1992 was the month having the greatest snow extent (nearly 0.8 million sq km) and snow mass (approximately 2.6 x 10(exp 13) kg).

  2. Large scale snow water status monitoring: comparison of different snow water products in the upper Colorado basins

    USGS Publications Warehouse

    Artan, G.A.; Verdin, J.P.; Lietzow, R.

    2013-01-01

    We illustrate the ability to monitor the status of snowpack over large areas by using a~spatially distributed snow accumulation and ablation model in the Upper Colorado Basin. The model was forced with precipitation fields from the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) and the Tropical Rainfall Measuring Mission (TRMM) datasets; remaining meteorological model input data was from NOAA's Global Forecast System (GFS) model output fields. The simulated snow water equivalent (SWE) was compared to SWEs from the Snow Data Assimilation System (SNODAS) and SNOwpack TELemetry system (SNOTEL) over a~region of the Western United States that covers parts of the Upper Colorado Basin. We also compared the SWE product estimated from the Special Sensor Microwave Imager (SSM/I) and Scanning Multichannel Microwave Radiometer (SMMR) to the SNODAS and SNOTEL SWE datasets. Agreement between the spatial distribution of the simulated SWE with both SNODAS and SNOTEL was high for the two model runs for the entire snow accumulation period. Model-simulated SWEs, both with MPE and TRMM, were significantly correlated spatially on average with the SNODAS (r = 0.81 and r = 0.54; d.f. = 543) and the SNOTEL SWE (r = 0.85 and r = 0.55; d.f. = 543), when monthly basinwide simulated average SWE the correlation was also highly significant (r = 0.95 and r = 0.73; d.f. = 12). The SWE estimated from the passive microwave imagery was not correlated either with the SNODAS SWE or (r = 0.14, d.f. = 7) SNOTEL-reported SWE values (r = 0.08, d.f. = 7). The agreement between modeled SWE and the SWE recorded by SNODAS and SNOTEL weakened during the snowmelt period due to an underestimation bias of the air temperature that was used as model input forcing.

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

    NASA Astrophysics Data System (ADS)

    Vikhamar-Schuler, D.; Müller, K.

    2012-04-01

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

  4. 'Snow White' Trench After Scraping

    NASA Technical Reports Server (NTRS)

    2008-01-01

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

    The trench is 4 to 5 centimeters (about 2 inches) deep, about 23 centimeters (9 inches) wide and about 60 centimeters (24 inches) long.

    The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  5. Automated Propellant Blending

    NASA Technical Reports Server (NTRS)

    Hohmann, Carl W. (Inventor); Harrington, Douglas W. (Inventor); Dutton, Maureen L. (Inventor); Tipton, Billy Charles, Jr. (Inventor); Bacak, James W. (Inventor); Salazar, Frank (Inventor)

    2000-01-01

    An automated propellant blending apparatus and method that uses closely metered addition of countersolvent to a binder solution with propellant particles dispersed therein to precisely control binder precipitation and particle aggregation is discussed. A profile of binder precipitation versus countersolvent-solvent ratio is established empirically and used in a computer algorithm to establish countersolvent addition parameters near the cloud point for controlling the transition of properties of the binder during agglomeration and finishing of the propellant composition particles. The system is remotely operated by computer for safety, reliability and improved product properties, and also increases product output.

  6. Automated Propellant Blending

    NASA Technical Reports Server (NTRS)

    Hohmann, Carl W. (Inventor); Harrington, Douglas W. (Inventor); Dutton, Maureen L. (Inventor); Tipton, Billy Charles, Jr. (Inventor); Bacak, James W. (Inventor); Salazar, Frank (Inventor)

    1999-01-01

    An automated propellant blending apparatus and method uses closely metered addition of countersolvent to a binder solution with propellant particles dispersed therein to precisely control binder precipitation and particle aggregation. A profile of binder precipitation versus countersolvent-solvent ratio is established empirically and used in a computer algorithm to establish countersolvent addition parameters near the cloud point for controlling the transition of properties of the binder during agglomeration and finishing of the propellant composition particles. The system is remotely operated by computer for safety, reliability and improved product properties, and also increases product output.

  7. Light-absorbing impurities in Arctic snow

    NASA Astrophysics Data System (ADS)

    Doherty, S. J.; Warren, S. G.; Grenfell, T. C.; Clarke, A. D.; Brandt, R. E.

    2010-12-01

    Absorption of radiation by ice is extremely weak at visible and near-ultraviolet wavelengths, so small amounts of light-absorbing impurities in snow can dominate the absorption of solar radiation at these wavelengths, reducing the albedo relative to that of pure snow, contributing to the surface energy budget and leading to earlier snowmelt. In this study Arctic snow is surveyed for its content of light-absorbing impurities, expanding and updating the 1983-1984 survey of Clarke and Noone. Samples were collected in Alaska, Canada, Greenland, Svalbard, Norway, Russia, and the Arctic Ocean during 1998 and 2005-2009, on tundra, glaciers, ice caps, sea ice, frozen lakes, and in boreal forests. Snow was collected mostly in spring, when the entire winter snowpack is accessible for sampling. Sampling was carried out in summer on the Greenland Ice Sheet and on the Arctic Ocean, of melting glacier snow and sea ice as well as cold snow. About 1200 snow samples have been analyzed for this study. The snow is melted and filtered; the filters are analyzed in a specially designed spectrophotometer system to infer the concentration of black carbon (BC), the fraction of absorption due to non-BC light-absorbing constituents and the absorption Ångstrom exponent of all particles. This is done using BC calibration standards having a mass absorption efficiency of 6.0 m2 g-1 at 550 nm and by making an assumption that the absorption Angstrom exponent for BC is 1.0 and for non-BC light-absorbing aerosol is 5.0. The reduction of snow albedo is primarily due to BC, but other impurities, principally brown (organic) carbon, are typically responsible for ~40% of the visible and ultraviolet absorption. The meltwater from selected snow samples was saved for chemical analysis to identify sources of the impurities. Median BC amounts in surface snow are as follows (nanograms of carbon per gram of snow): Greenland 3, Arctic Ocean snow 7, melting sea ice 8, Arctic Canada 8, subarctic Canada 14

  8. A Blended Learning Framework for Curriculum Design and Professional Development

    ERIC Educational Resources Information Center

    Mirriahi, Negin; Alonzo, Dennis; Fox, Bob

    2015-01-01

    The need for flexibility in learning and the affordances of technology provided the impetus for the rise of blended learning (BL) globally across higher education institutions. However, the adoption of BL practices continues at a low pace due to academics' low digital fluency, various views and BL definitions, and limited standards-based tools to…

  9. The Snow Data System at NASA JPL

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  10. Blowing Snow Over the Antarctic Plateau

    NASA Technical Reports Server (NTRS)

    Mahesh, Ashwin; Eager, Rebecca; Campbell, James R.; Spinhirne, James D.

    2002-01-01

    Studies of blowing snow over Antarctica have been limited greatly by the remoteness and harsh conditions of the region. Space-based observations are also of lesser value than elsewhere, given the similarities between ice clouds and snow-covered surfaces, both at infrared and visible wavelengths. It is only in recent years that routine ground-based observation programs have acquired sufficient data to overcome the gap in our understanding of surface blowing snow. In this paper, observations of blowing snow from visual observers' records as well as ground-based spectral and lidar programs at South Pole station are analyzed to obtain the first climatology of blowing snow over the Antarctic plateau. Occurrence frequencies, correlation with wind direction and speed, typical layer heights, as well as optical depths are determined. Blowing snow is seen in roughly one third of the visual observations and occurs under a narrow range of wind directions. The near-surface layers typically a few hundred meters thick emit radiances similar to those from thin clouds. Because blowing snow remains close to the surface and is frequently present, it will produce small biases in space-borne altimetry; these must be properly estimated and corrected.

  11. Forest damage and snow avalanche flow regime

    NASA Astrophysics Data System (ADS)

    Feistl, T.; Bebi, P.; Christen, M.; Margreth, S.; Diefenbach, L.; Bartelt, P.

    2015-01-01

    Snow avalanches break, uproot and overturn trees causing damage to forests. The extent of forest damage provides useful information on avalanche frequency and intensity. However, impact forces depend on avalanche flow regime. In this paper, we define avalanche loading cases representing four different avalanche flow regimes: powder, intermittent, dry and wet. In the powder regime, the blast of the cloud can produce large bending moments in the tree stem because of the impact area extending over the entire tree crown. We demonstrate that intermittent granular loadings are equivalent to low-density uniform dry snow loadings under the assumption of homogeneous particle distributions. In the wet snow case, avalanche pressure is calculated using a quasi-static model accounting for the motion of plug-like wet snow flows. Wet snow pressure depends both on avalanche volume and terrain features upstream of the tree. Using a numerical model that simulates both powder and wet snow avalanches, we study documented events with forest damage. We find (1) powder clouds with velocities over 20 m s-1 can break tree stems, (2) the intermittent regime seldom controls tree breakage and (3) quasi-static pressures of wet snow avalanches can be much higher than pressures calculated using dynamic pressure formulas.

  12. Applications of remote sensing and GIS in surface hydrology: Snow cover, soil moisture and precipitation

    NASA Astrophysics Data System (ADS)

    Wang, Xianwei

    Studies on surface hydrology can generally be classified into two categories, observation for different components of surface water, and modeling their dynamic movements. This study only focuses on observation part of surface water components: snow cover, soil moisture, and precipitation. Moreover, instead of discussion on the detailed algorithm and instrument technique behind each component, this dissertation pours efforts on analysis of the standard remotely sensed products and their applications under different settings. First in Chapter 2, validation of MODIS Terra 8-day maximum snow cover composite (MOD10A2) in the Northern Xinjiang, China, from 2000-2006, shows that the 8-day MODIS/Terra product has high agreements with in situ measurements as the in situ snow depth is larger or equal to 4 cm, while the agreement is low for the patchy snow as the in situ snow depth less than 4 cm. According to the in situ observation, this chapter develops an empirical algorithm to separate the cloud-covered pixels into snow and no snow. Continued long-term production of MODIS-type snow cover product is critical to assess water resources of the study area, as well as other larger scale global environment monitoring. Terra and Aqua satellites carry the same MODIS instrument and provide two parallel MODIS daily snow cover products at different time (local time 10:30 am and 1:30 pm, respectively). Chapter 3 develops an algorithm and automated scripts to combine the daily MODIS Terra (MOD10A1) and Aqua (MYD10A1) snow cover products, and to automatically generate multi-day Terra-Aqua snow cover image composites, with flexible starting and ending dates and a user-defined cloud cover threshold. Chapter 4 systematically compares the difference between MODIS Terra and Aqua snow cover products within a hydrologic year of 2003-2004, validates the MODIS Terra and Aqua snow cover products using in situ measurements in Northern Xinjiang, and compares the accuracy among the standard MODIS

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  14. BOREAS HYD-4 Standard Snow Course Data

    NASA Technical Reports Server (NTRS)

    Metcalfe, John R.; Goodison, Barry E.; Walker, Anne; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Smith, David E. (Technical Monitor)

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-4 work was focused on collecting data during the winter focused field campaign (FFC-W) to improve the understanding of winter processes within the boreal forest. Knowledge of snow cover and its variability in the boreal forest is fundamental if BOREAS is to achieve its goals of understanding the processes and states involved in the exchange of energy and water. The development and validation of remote sensing algorithms will provide the means to extend the knowledge of these processes and states from the local to the regional scale. A specific thrust of the research is the development and validation of snow cover algorithms from airborne passive microwave measurements. Snow surveys were conducted at special snow courses throughout the 1993/94, 1994/95, 1995/96, and 1996/97 winter seasons. These snow courses were located in different boreal forest land cover types (i.e., old aspen, old black spruce, young jack pine, forest clearing, etc.) to document snow cover variations throughout the season as a function of different land cover. Measurements of snow depth, density, and water equivalent were acquired on or near the first and fifteenth of each month during the snow cover season. The data are provided in tabular ASCII files. The HYD-4 standard snow course data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

  15. Dynamics of glide avalanches and snow gliding

    NASA Astrophysics Data System (ADS)

    Ancey, Christophe; Bain, Vincent

    2015-09-01

    In recent years, due to warmer snow cover, there has been a significant increase in the number of cases of damage caused by gliding snowpacks and glide avalanches. On most occasions, these have been full-depth, wet-snow avalanches, and this led some people to express their surprise: how could low-speed masses of wet snow exert sufficiently high levels of pressure to severely damage engineered structures designed to carry heavy loads? This paper reviews the current state of knowledge about the formation of glide avalanches and the forces exerted on simple structures by a gliding mass of snow. One particular difficulty in reviewing the existing literature on gliding snow and on force calculations is that much of the theoretical and phenomenological analyses were presented in technical reports that date back to the earliest developments of avalanche science in the 1930s. Returning to these primary sources and attempting to put them into a contemporary perspective are vital. A detailed, modern analysis of them shows that the order of magnitude of the forces exerted by gliding snow can indeed be estimated correctly. The precise physical mechanisms remain elusive, however. We comment on the existing approaches in light of the most recent findings about related topics, including the physics of granular and plastic flows, and from field surveys of snow and avalanches (as well as glaciers and debris flows). Methods of calculating the forces exerted by glide avalanches are compared quantitatively on the basis of two case studies. This paper shows that if snow depth and density are known, then certain approaches can indeed predict the forces exerted on simple obstacles in the event of glide avalanches or gliding snow cover.

  16. Propagation characteristics of acoustic waves in snow

    NASA Astrophysics Data System (ADS)

    Capelli, Achille; Kapil, Jagdish Chandra; Reiweger, Ingrid; Schweizer, Jürg; Or, Dani

    2015-04-01

    Acoustic emission analysis is a promising technique for monitoring snow slope stability with potential for application in early warning systems for avalanches. Current research efforts focus on identification and localization of acoustic emission features preceding snow failure and avalanches. However, our knowledge of sound propagation characteristics in snow is still limited. A review of previous studies showed that significant gaps exist and that the results of the various studies are partly contradictory. Furthermore, sound velocity and attenuation have been determined for the frequency range below 10 kHz, while recent snow failure experiments suggest that the peak frequency is in the ultrasound range between 30 kHz to 500 kHz. We therefore studied the propagation of pencil lead fracture (PLF) signals through snow in the ultrasound frequency range. This was achieved by performing laboratory experiments with columns of artificially produced snow of varying density and temperature. The attenuation constant was obtained by varying the size of the columns to eliminate possible influences of the snow-sensor coupling. The attenuation constant was measured for the entire PLF burst signal and for single frequency components. The propagation velocity was calculated from the arrival time of the acoustic signal. We then modelled the sound propagation for our experimental setup using Biot's model for wave propagation in porous media. The Model results were in good agreement with our experimental results. For the studied samples, the acoustic signals propagated as fast and slow longitudinal waves, but the main part of the energy was carried by the slow waves. The Young's modulus of our snow samples was determined from the sound velocity. This is highly relevant, as the elastic properties of snow are not well known.

  17. Charred Forests Increase Snow Albedo Decay: Watershed-Scale Implications of the Postfire Snow Albedo Effect

    NASA Astrophysics Data System (ADS)

    Gleason, K. E.; Nolin, A. W.

    2014-12-01

    Recent work shows that after a high severity forest fire, approximately 60% more solar radiation reaches the snow surface due to the reduction in canopy density. Also, significant amounts of black carbon (BC) particles and larger burned woody debris (BWD) are shed from standing charred trees, which concentrate on the snowpack, darken its surface, and reduce snow albedo by 50% during ablation. The postfire forest environment drives a substantial increase in net shortwave radiation at the snowpack surface, driving earlier and more rapid melt, however hydrologic models do not explicitly incorporate forest fire disturbance effects to snowpack dynamics. In this study we characterized, parameterized, and validated the postfire snow albedo effect: how the deposition and concentration of charred forest debris decreases snow albedo, increases snow albedo decay rates, and drives an earlier date of snow disappearance. For three study sites in the Oregon High Cascade Mountains, a 2-yr old burned forest, a 10-yr burned forest, and a nearby unburned forest, we used a suite of empirical data to characterize the magnitude and duration of the postfire effect to snow albedo decay. For WY 2012, WY2013, and WY2014 we conducted spectral albedo measurements, snow surface sampling, in-situ snow and meteorological monitoring, and snow energy balance modeling. From these data we developed a new parameterization which represents the postfire effect to snow albedo decay as a function of days-since-snowfall. We validated our parameterization using a physically-based, spatially-distributed snow accumulation and melt model, in-situ snow monitoring, net snowpack radiation, and remote sensing data. We modeled snow dynamics across the extent of all burned area in the headwaters of the McKenzie River Basin and validated the watershed-scale implications of the postfire snow albedo effect using in-situ micrometeorological and remote sensing data. This research quantified the watershed scale postfire

  18. Using snowboards and lysimeters to constrain snow model choices in a rain-snow transitional environment

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    Physically based models of the hydrological cycle are critical for testing our understanding of the natural world and enabling forecasting of extreme events. Previous intercomparison studies (i.e. SNOWMIP I & II, PILPS) of existing snow models that vary in complexity have been hampered by multiple differences in model structure. Recent efforts to encompass multiple model hypothesizes into a single framework (i.e. the Structure for Understanding Multiple Modeling Alternatives [SUMMA] model), have provided the tools necessary for a more rigorous validation of process representation. However, there exist few snow observatories that measure sufficient physical states and fluxes to fully constrain the possible combinations within these multiple model frameworks. In practice, observations of bulk snow states, such as the snow water equivalent (SWE) or snow depth, are most commonly available. The downfall of calibrating a snow model using such single bulk variables can lead to parameter equanimity and compensatory errors, which ultimately impacts the skill of a model as a predictive tool. This study provides two examples of diagnosing modeled snow processes through novel error source identification. Simulations were performed at a recently upgraded (Oct. 2012) snow study site located at Snoqualmie Pass (917 m), in the Washington Cascades, USA. We focused on two physical processes, new snow accumulation and snowpack outflow during mid-winter rain-on-snow events, for their importance towards controlling runoff and flooding in this rain-snow transitional basin. Main results were: 1) modifying the snow model structure to match what was actually observed (i.e. a snow board), allowed the attribution of daily errors in model new snow accumulation to either partitioning, new snow density, or compaction. 2) Observed snow pit temperature profiles from infrared cameras and manual thermometers found that cold biases in the model snowpack temperature prior to rain-on-snow events could

  19. Recent progress in snow and ice research

    SciTech Connect

    Richter-menge, J.A.; Colbeck, S.C.; Jezek, K.C. )

    1991-01-01

    A review of snow and ice research in 1987-1990 is presented, focusing on the effects of layers in seasonal snow covers, ice mechanics on fresh water and sea ice, and remote sensig of polar ice sheets. These topics provide useful examples of general needs in snow and ice research applicable to most areas, such as better representation in models of detailed processes, controlled laboratory experiments to quantify processes, and field studies to provide the appropriate context for interpretation of processes from remote sensing.

  20. PHYSICS UPDATE: Production of artificial snow crystals

    NASA Astrophysics Data System (ADS)

    Kagawa, S.; Ito, F.; Kagawa, K.

    1999-03-01

    Artificial snow crystals can be produced by a fairly simple method in a small closed cylindrical chamber made by combining an aluminium tube and a plastic tube. The chamber is set horizontally at room temperature and the end of the aluminium tube is cooled by dry ice. Water vapour is supplied by a diffusion process from the end of the plastic tube for a suitable time after cooling. The snow crystals are formed on a black sheet inside the end of the aluminium tube. The artificial snow crystals were observed at room temperature using our partial cooling method.

  1. "Proximal Sensing" capabilities for snow cover monitoring

    NASA Astrophysics Data System (ADS)

    Valt, Mauro; Salvatori, Rosamaria; Plini, Paolo; Salzano, Roberto; Giusti, Marco; Montagnoli, Mauro; Sigismondi, Daniele; Cagnati, Anselmo

    2013-04-01

    The seasonal snow cover represents one of the most important land cover class in relation to environmental studies in mountain areas, especially considering its variation during time. Snow cover and its extension play a relevant role for the studies on the atmospheric dynamics and the evolution of climate. It is also important for the analysis and management of water resources and for the management of touristic activities in mountain areas. Recently, webcam images collected at daily or even hourly intervals are being used as tools to observe the snow covered areas; those images, properly processed, can be considered a very important environmental data source. Images captured by digital cameras become a useful tool at local scale providing images even when the cloud coverage makes impossible the observation by satellite sensors. When suitably processed these images can be used for scientific purposes, having a good resolution (at least 800x600x16 million colours) and a very good sampling frequency (hourly images taken through the whole year). Once stored in databases, those images represent therefore an important source of information for the study of recent climatic changes, to evaluate the available water resources and to analyse the daily surface evolution of the snow cover. The Snow-noSnow software has been specifically designed to automatically detect the extension of snow cover collected from webcam images with a very limited human intervention. The software was tested on images collected on Alps (ARPAV webcam network) and on Apennine in a pilot station properly equipped for this project by CNR-IIA. The results obtained through the use of Snow-noSnow are comparable to the one achieved by photo-interpretation and could be considered as better as the ones obtained using the image segmentation routine implemented into image processing commercial softwares. Additionally, Snow-noSnow operates in a semi-automatic way and has a reduced processing time. The analysis

  2. Snow cover in the Siberian forest-steppe

    NASA Technical Reports Server (NTRS)

    Zykov, I. V.

    1985-01-01

    A study is made of the snow cover on an experimental agricultural station in Mariinsk in the winter of 1945 to 1946. Conditions of snow cover formation, and types and indicators of snow cover are discussed. Snow cover structure and conditions and nature of thawing are described.

  3. Classifying K-12 Blended Learning

    ERIC Educational Resources Information Center

    Staker, Heather; Horn, Michael B.

    2012-01-01

    The growth of online learning in the K-12 sector is occurring both remotely through virtual schools and on campuses through blended learning. In emerging fields, definitions are important because they create a shared language that enables people to talk about the new phenomena. The blended-learning taxonomy and definitions presented in this paper…

  4. FLOW BEHAVIOR OF PROTEIN BLENDS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Blending proteins can increase textural strength or enhance taste or mouth feel, such as blending soy with whey to improve taste. In this study, we measured the viscosity of various combinations of six proteins (whey protein isolates, calcium caseinate, soy protein isolates, wheat gluten, egg album...

  5. Can "Blended Learning" Be Redeemed?

    ERIC Educational Resources Information Center

    Oliver, Martin; Trigwell, Keith

    2005-01-01

    Although the term "blended learning" is widely used, this article argues against it. Two arguments are advanced. The first is primarily philosophical, although it has several pragmatic implications. It proposes that "blending" either relies on the idea of dichotomies which are suspect within the context of learning with technology or else becomes…

  6. Blended Learning: A Dangerous Idea?

    ERIC Educational Resources Information Center

    Moskal, Patsy; Dziuban, Charles; Hartman, Joel

    2013-01-01

    The authors make the case that implementation of a successful blended learning program requires alignment of institutional, faculty, and student goals. Reliable and robust infrastructure must be in place to support students and faculty. Continuous evaluation can effectively track the impact of blended learning on students, faculty, and the…

  7. Blended Learning Improves Science Education.

    PubMed

    Stockwell, Brent R; Stockwell, Melissa S; Cennamo, Michael; Jiang, Elise

    2015-08-27

    Blended learning is an emerging paradigm for science education but has not been rigorously assessed. We performed a randomized controlled trial of blended learning. We found that in-class problem solving improved exam performance, and video assignments increased attendance and satisfaction. This validates a new model for science communication and education.

  8. The Basics of Blended Instruction

    ERIC Educational Resources Information Center

    Tucker, Catlin R.

    2013-01-01

    Even though many of teachers do not have technology-rich classrooms, the rapidly evolving education landscape increasingly requires them to incorporate technology to customize student learning. Blended learning, with its mix of technology and traditional face-to-face instruction, is a great approach. Blended learning combines classroom learning…

  9. Quantifying scale relationships in snow distributions

    NASA Astrophysics Data System (ADS)

    Deems, Jeffrey S.

    2007-12-01

    Spatial distributions of snow in mountain environments represent the time integration of accumulation and ablation processes, and are strongly and dynamically linked to mountain hydrologic, ecologic, and climatic systems. Accurate measurement and modeling of the spatial distribution and variability of the seasonal mountain snowpack at different scales are imperative for water supply and hydropower decision-making, for investigations of land-atmosphere interaction or biogeochemical cycling, and for accurate simulation of earth system processes and feedbacks. Assessment and prediction of snow distributions in complex terrain are heavily dependent on scale effects, as the pattern and magnitude of variability in snow distributions depends on the scale of observation. Measurement and model scales are usually different from process scales, and thereby introduce a scale bias to the estimate or prediction. To quantify this bias, or to properly design measurement schemes and model applications, the process scale must be known or estimated. Airborne Light Detection And Ranging (lidar) products provide high-resolution, broad-extent altimetry data for terrain and snowpack mapping, and allow an application of variogram fractal analysis techniques to characterize snow depth scaling properties over lag distances from 1 to 1000 meters. Snow depth patterns as measured by lidar at three Colorado mountain sites exhibit fractal (power law) scaling patterns over two distinct scale ranges, separated by a distinct break at the 15-40 m lag distance, depending on the site. Each fractal range represents a range of separation distances over which snow depth processes remain consistent. The scale break between fractal regions is a characteristic scale at which snow depth process relationships change fundamentally. Similar scale break distances in vegetation topography datasets suggest that the snow depth scale break represents a change in wind redistribution processes from wind

  10. An electrostatic charge measurement of blowing snow particles focusing on collision frequency to the snow surface

    NASA Astrophysics Data System (ADS)

    Omiya, S.; Sato, A.

    2010-12-01

    Blowing snow particles are known to have an electrostatic charge. This charge may be a contributing factor in the formation of snow drifts and snow cornices and changing of the trajectory of blowing snow particles. These formations and phenomena can cause natural disaster such as an avalanche and a visibility deterioration, and obstruct transportation during winter season. Therefore, charging phenomenon of the blowing snow particles is an important issue in terms of not only precise understanding of the particle motion but disaster prevention. The primary factor of charge accumulation to the blowing snow particles is thought to be due to “saltation” of them. The “saltation” is one of movement forms of blowing snow: when the snow particles are transported by the wind, they repeat frictional collisions with the snow surface. In previous studies, charge-to-mass ratios measured in the field were approximately -50 to -10 μC/kg, and in the wind tunnel were approximately -0.8 to -0.1 μC/kg. While there were qualitatively consistent in sign, negative, there were huge gaps quantitatively between them. One reason of those gaps is speculated to be due to differences in fetch. In other words, the difference of the collision frequency of snow particles to the snow surface has caused the gaps. But it is merely a suggestion and that has not been confirmed. The purpose of this experiment is to measure the charge of blowing snow particles focusing on the collision frequency and clarify the relationship between them. Experiments were carried out in the cryogenic wind tunnel of Snow and Ice Research Center (NIED, JAPAN). A Faraday cage and an electrometer were used to measure the charge of snow particles. These experiments were conducted over the hard snow surface condition to prevent the erosion of the snow surface and the generation of new snow particles from the surface. The collision frequency of particle was controlled by changing the wind velocity (4.5 to 7 m/s) under

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

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  12. Research on the seasonal snow of the Arctic Slope

    SciTech Connect

    Benson, C.S.

    1986-01-01

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

  13. Research on the seasonal snow of the Arctic Slope

    SciTech Connect

    Benson, C.S.

    1991-01-01

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

  14. Research on the seasonal snow of the Arctic Slope

    SciTech Connect

    Benson, C.S.

    1989-01-01

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

  15. Research on the seasonal snow of the Arctic Slope

    SciTech Connect

    Benson, C.S.

    1987-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Micheletty, P. D.; Kinoshita, A. M.; Hogue, T. S.

    2014-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Micheletty, P. D.; Kinoshita, A. M.; Hogue, T. S.

    2014-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Dziubanski, David J.; Franz, Kristie J.

    2016-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Dziubanski, D.; Franz, K.

    2015-12-01

    Accurately initializing snow model states, and in particular snow water equivalent (SWE), in hydrologic prediction models is important for predicting future snowmelt, water supplies and flooding potential. While ground-based snow observations give the most reliable information about snowpack conditions, they are spatially limited and quite sparse in regions such as the north-central USA. Satellites are the most likely source of snow observations to fill this data gap. Using the ensemble Kalman filter (EnKF) assimilation framework, we test the assimilation of AMSR-E SWE into the US National Weather Service (NWS) SNOW17 model for seven watersheds in the Upper Mississippi River basin. SNOW17 is coupled with the NWS Sacramento Soil Moisture Accounting (SACSMA) model, and both simulated SWE and discharge are evaluated. Prior to assimilation, AMSR-E data is bias corrected using data from the National Operational Hydrologic Remote Sensing Center (NOHRSC) airborne snow survey program. Updating occurs on a daily cycle for water years 2006-2011. Results show improved discharge for five of the seven study sites as compared to the SNOW17 without assimilation. The assimilation of AMSR-E SWE produced high skill for peak flows during periods of snow melt, with one study site displaying a 36% improvement in simulated peak flow. As calibrated, the SNOW17 consistently underestimates the SWE and snow melt rates in these basins. Overall results indicate that updating SNOW17 SWE with AMRS-E data is a viable and effective solution for improving simulations of the operational forecast models.

  20. Modeling liquid water transport in snow under rain-on-snow conditions considering preferential flow

    NASA Astrophysics Data System (ADS)

    Würzer, Sebastian; Wever, Nander; Juras, Roman; Lehning, Michael; Jonas, Tobias

    2016-04-01

    Rain-on-snow (ROS) has caused severe flood events in Europe in the recent past. Thus, precisely forecasting snowpack runoff during ROS events is very important. Data analyses from past ROS events have shown that the release of snow cover runoff is often delayed relative to the onset of rainfall. This delay is influenced by the refreeze of liquid water inside the snowpack, as well as by the water transport mechanisms. Water percolation in turn depends on snow grain size but also on the presence of structures such as ice lenses or capillary barriers. Further, during sprinkling experiments, preferential flow was found to be a main mechanism to determine the generation of snow cover runoff. However, current 1D snow cover models are not capable of addressing this phenomenon correctly. For this study, the detailed physics-based snow cover model SNOWPACK has been extended with a water transport scheme accounting for preferential flow. The implemented Richardś Equation solver was modified based on a dual-domain approach to simulate water transport under preferential flow conditions. This transport model is used to simulate liquid water transport within the snow cover during ROS events. To validate the presented approach, we used an extensive data set of approximately 100 historic ROS events at different locations between 950 m and 2540 m elevation in the Alps. The data set comprises meteorological and snow cover measurements as well as snow lysimeter runoff data. Additionally, experimental sprinkling of dye tracer colored water was conducted on snow cover, where runoff was measured by snow lysimeters. The model was tested under a variety of ROS events including cold, ripe, stratified and homogeneous initial snow cover conditions. Preliminary results show an improvement in temporal runoff representation as well as in total runoff amount for several ROS events.

  1. A passive microwave snow depth algorithm with a proxy for snow metamorphism

    USGS Publications Warehouse

    Josberger, E.G.; Mognard, N.M.

    2002-01-01

    Passive microwave brightness temperatures of snowpacks depend not only on the snow depth, but also on the internal snowpack properties, particularly the grain size, which changes through the winter. Algorithms that assume a constant grain size can yield erroneous estimates of snow depth or water equivalent. For snowpacks that are subject to temperatures well below freezing, the bulk temperature gradient through the snowpack controls the metamorphosis of the snow grains. This study used National Weather Service (NWS) station measurements of snow depth and air temperature from the Northern US Great Plains to determine temporal and spatial variability of the snow depth and bulk snowpack temperature gradient. This region is well suited for this study because it consists primarily of open farmland or prairie, has little relief, is subject to very cold temperatures, and has more than 280 reporting stations. A geostatistical technique called Kriging was used to grid the randomly spaced snow depth measurements. The resulting snow depth maps were then compared with the passive microwave observations from the Special Sensor Microwave Imager (SSM/I). Two snow seasons were examined: 1988-89, a typical snow year, and 1996-97, a record year for snow that was responsible for extensive flooding in the Red River Basin. Inspection of the time series of snow depth and microwave spectral gradient (the difference between the 19 and 37 GHz bands) showed that while the snowpack was constant, the spectral gradient continued to increase. However, there was a strong correlation (0.6 < R2 < 0.9) between the spectral gradient and the cumulative bulk temperature gradient through the snowpack (TGI). Hence, TGI is an index of grain size metamorphism that has occurred within the snowpack. TGI time series from 21 representative sites across the region and the corresponding SSM/I observations were used to develop an algorithm for snow depth that requires daily air temperatures. Copyright ?? 2002

  2. Organic contaminant release from melting snow. 2. Influence of snow pack and melt characteristics.

    PubMed

    Meyer, Torsten; Lei, Ying Duan; Muradi, Ibrahim; Wania, Frank

    2009-02-01

    Large reservoirs of organic contaminants in seasonal snowpack can be released in short pulses during spring snowmelt, potentially impacting the receiving ecosystems. Laboratory experiments using artificial snow spiked with organic target substances were conducted to investigate the behavior of six organic contaminants with widely variable distribution properties in melting snow. Whereas the influence of a chemical's equilibrium phase partitioning on the elution behavior is explored in a companion paper, we discuss here the impact of snow properties and melt features, including the snowpack depth, the temperature at the interface between soil and snow, the meltwater content the internal ice surface area, and the existence of distinct snow layers. Water-soluble organic substances are released in high concentrations at the beginning of a melt period when a deep and aged snowpack undergoes intense melting. Warm ground can cause notable melting at the snow bottom leading to a delayed and dampened concentration peak. Hydraulic barriers in layered snow packs cause preferential meltwater flow which also mitigates the early contaminant flush. Hydrophobic organic pollutants that are associated with particles accumulate near the snow surface and are released at the end of melting. Dirt cones at the surface of a dense snowpack enhance this enrichment. The findings of this laboratory study will aid in the understanding of the behavior of organic pollutants during the melting of more complex, natural snow covers.

  3. Photoreducible Mercury Loss from Arctic Snow Is Influenced by Temperature and Snow Age.

    PubMed

    Mann, Erin A; Mallory, Mark L; Ziegler, Susan E; Avery, Trevor S; Tordon, Rob; O'Driscoll, Nelson J

    2015-10-20

    Mercury (Hg) is an important environmental contaminant, due to its neurotoxicity and ability to bioaccumulate. The Arctic is a mercury-sensitive region, where organisms can accumulate high Hg concentrations. Snowpack mercury photoredox reactions may control how much Hg is transported with melting Arctic snow. This work aimed to (1) determine the significance of temperature combined with UV irradiation intensity and snow age on Hg(0) flux from Arctic snow and (2) elucidate the effect of temperature on snowpack Hg photoreduction kinetics. Using a Teflon flux chamber, snow temperature, UV irradiation, and snow age were found to significantly influence Hg(0) flux from Arctic snow. Cross-correlation analysis results suggest that UV radiation has a direct effect on Hg(0)flux, while temperature may indirectly influence flux. Laboratory experiments determined that temperature influenced Hg photoreduction kinetics when snow approached the melting point (>-2 °C), where the pseudo-first-order reduction rate constant, k, decreased twofold, and the photoreduced Hg amount, Hg(II)red, increased 10-fold. This suggests that temperature influences Hg photoreduction kinetics indirectly, likely by altering the solid:liquid water ratio. These results imply that large mass transfers of Hg from snow to air may take place during the Arctic snowmelt period, altering photoreducible Hg retention and transport with snow meltwater.

  4. Organic contaminant release from melting snow. 2. Influence of snow pack and melt characteristics.

    PubMed

    Meyer, Torsten; Lei, Ying Duan; Muradi, Ibrahim; Wania, Frank

    2009-02-01

    Large reservoirs of organic contaminants in seasonal snowpack can be released in short pulses during spring snowmelt, potentially impacting the receiving ecosystems. Laboratory experiments using artificial snow spiked with organic target substances were conducted to investigate the behavior of six organic contaminants with widely variable distribution properties in melting snow. Whereas the influence of a chemical's equilibrium phase partitioning on the elution behavior is explored in a companion paper, we discuss here the impact of snow properties and melt features, including the snowpack depth, the temperature at the interface between soil and snow, the meltwater content the internal ice surface area, and the existence of distinct snow layers. Water-soluble organic substances are released in high concentrations at the beginning of a melt period when a deep and aged snowpack undergoes intense melting. Warm ground can cause notable melting at the snow bottom leading to a delayed and dampened concentration peak. Hydraulic barriers in layered snow packs cause preferential meltwater flow which also mitigates the early contaminant flush. Hydrophobic organic pollutants that are associated with particles accumulate near the snow surface and are released at the end of melting. Dirt cones at the surface of a dense snowpack enhance this enrichment. The findings of this laboratory study will aid in the understanding of the behavior of organic pollutants during the melting of more complex, natural snow covers. PMID:19244999

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

    SciTech Connect

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

    2010-01-12

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

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

    USGS Publications Warehouse

    Zhang, J.-H.; Zhou, Z.-M.; Wang, P.-J.; Yao, F.-M.; Yang, L.

    2011-01-01

    The field spectroradiometer was used to measure spectra of different snow and snow-covered land surface objects in Beijing area. The result showed that for a pure snow spectrum, the snow reflectance peaks appeared from visible to 800 nm band locations; there was an obvious absorption valley of snow spectrum near 1030 nm wavelength. Compared with fresh snow, the reflection peaks of the old snow and melting snow showed different degrees of decline in the ranges of 300~1300, 1700~1800 and 2200~2300 nm, the lowest was from the compacted snow and frozen ice. For the vegetation and snow mixed spectral characteristics, it was indicated that the spectral reflectance increased for the snow-covered land types(including pine leaf with snow and pine leaf on snow background), due to the influence of snow background in the range of 350~1300 nm. However, the spectrum reflectance of mixed pixel remained a vegetation spectral characteristic. In the end, based on the spectrum analysis of snow, vegetation, and mixed snow/vegetation pixels, the mixed spectral fitting equations were established, and the results showed that there was good correlation between spectral curves by simulation fitting and observed ones(correlation coefficient R2=0.9509).

  7. Application of a Coupled Multiscale Atmospheric-Land Surface Model to Simulate the Snow Circulation in a Mountain Basin

    NASA Astrophysics Data System (ADS)

    Herrera, E.; Pomeroy, J.; Pietroniro, A.

    2009-05-01

    Snow cover spatial variability and snowmelt runoff are greatly influenced by the snow advected due to the wind- flow in the atmospheric boundary layer. Typically this has been accomplished by considering the snow as a subgrid scale problem in the atmospheric models. However, this subgrid scale approach can not be sufficient to explain the snow dynamics. Therefore a multiscale strategy where the hydrological, climatological, meteorological and physiographic conditions of a basin are related should improve the understanding of snow dynamics. This methodology was developed coupling the Global Environmental Multiscale Limited Area Model (GEM-LAM) with the Cold Regions Hydrological Model (CRHM). The GEM-LAM was used on a one-way nesting configuration to simulate the atmospheric-land fields at 100m of resolution with the Interactions between Soil, Biosphere, and Atmosphere (ISBA) soil scheme. The CRHM is used as a snow transport model at the hydrometeorological stations located in the basin. The case of study is the 4th November 2007 at Marmot Creek (50° 57' N, 115° 10' W), Alberta, Canada. This strategy has proved to be a physics based procedure to describe the snow dynamics without interpolation methods.

  8. Assimilating Spaceborne Passive Microwave Measurements into a Land Surface Model to Estimate Snow Water Equivalent in the Yampa River Basin

    NASA Astrophysics Data System (ADS)

    Kim, R. S.; Li, D.; Durand, M. T.

    2014-12-01

    Acquiring accurate spatiotemporal snow information over large areas for understanding snowcover in the global and regional water and energy balances is crucial and has motivated snow characterization via remote sensing. The passive microwave (PM) measurements have been widely used and invested in order to obtain information about snowpack properties. In this paper, we utilize a snow data assimilation system to estimate snow water equivalent (SWE) in the Yampa River basin in the Colorado Rockies within the NASA Cold Land Processes Experiment (CLPX) area of 2002-2003. The Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) observations were used. Forcing data were derived from the North American Land Data Assimilation v2 (NLDAS-2) dataset. Also, the Microwave Emission Model of Layered Snowpacks (MEMLS) was used to convert the snow state variables to brightness temperatures. The ensemble Kalman filter was directly employed to assimilate PM brightness temperature data into a land surface model snow scheme. Assimilation results are compared with SNOTEL and snow course observations.

  9. The GOddard SnoW Impurity Module (GOSWIM) for the NASA GEOS-5 Earth System Model: Preliminary Comparisons with Observations in Sapporo, Japan

    NASA Technical Reports Server (NTRS)

    Yasunari, Teppei J.; Lau, K.-M.; Mahanama, Sarith P. P.; Colarco, Peter R.; daSilva, Arlindo M.; Aoki, Teruo; Aoki, Kazuma; Murao, Naoto; Yamagata, Sadamu; Kodama, Yuji

    2014-01-01

    The snow darkening module evaluating dust, black carbon, and organic carbon depositions on mass and albedo has been developed for the NASA Goddard Earth Observing System, Version 5 (GEOS-5) Earth System Model, as the GOddard SnoW Impurity Module (GOSWIM). GOSWIM consists of the snow albedo scheme from a previous study (Yasunari et al. 2011) with updates and a newly developed mass concentration scheme, using aerosol depositions from the chemical transport model (GOCART) in GEOS-5. Compared to observations at Sapporo, the numerical experiments, forced by observation-based meteorology and aerosol depositions from GOES-5, better simulated the seasonal migration of snow depth, albedos, and impurities of dust, BC, and OC in the snow surface. However, the magnitude of the impurities is underestimated, compared to the sporadic snow impurity measurements. Increasing the deposition rates of dust and BC could explain the differences on the snow darkening effect between observation and simulation. Ignoring BC deposition can possibly lead to an extension of snow cover duration in Sapporo for four days. Comparing the off-line GOSWIM and the GEOS-5 global simulations, we found that determining better local precipitation and deposition rates of the aerosols are key factors in generating better GOSWIM snow darkening simulation in NASA GEOS-5.

  10. Development of a one-dimensional electro-thermophysical model of the snow sea-ice system: Arctic climate processes and microwave remote sensing applications

    NASA Astrophysics Data System (ADS)

    Hanesiak, John Michael

    Snow covered sea ice plays a crucial role in the earth's climate. This includes polar biology, local, regional and world weather and ocean circulations as well as indigenous people's way of life. Recent research has indicated significant climate change in the polar regions, especially the Canadian arctic. Polar climate processes are also among the most poorly misrepresented within global circulation models (GCMs). The goal of this thesis is to improve our understanding and capability to simulate arctic climate processes in a predictive sense. An electro-thermophysical relationship exists between the thermophysical characteristics (climate variables and processes) and electrical properties (dielectrics) that control microwave remote sensing of snow-covered first- year sea ice (FYI). This work explicitly links microwave dielectrics and a thermodynamic model of snow and sea ice by addressing four key issues. These includes: (1)ensure the existing one-dimensional sea ice models treat the surface energy balance (SEB) and snow/ice thermodynamics in the appropriate time scales we see occurring in field experiments, (2)ensure the snow/ice thermodynamics are not compromised by differences in environmental and spatial representation within components of the SEB, (3)ensure the snow layer is properly handled in the modeling environment, and (4)how we can make use of satellite microwave remote sensing data within the model environment. Results suggest that diurnal processes are critical and need to be accounted for in modeling snow-covered FYI, similar to time scales acting in microwave remote sensing signatures. Output from the coupled snow sea-ice model provides the required input to microwave dielectric models of snow and sea ice to predict microwave penetration depths within the snow and sea ice (an Electro-Thermophysical model of the Snow Sea Ice System (ETSSIS)). Results suggest ETSSIS can accurately simulate microwave penetration depths in the cold dry snow season and

  11. A snow wetness retrieval algorithm for SAR

    NASA Technical Reports Server (NTRS)

    Shi, Jian-Cheng; Dozier, Jeff

    1992-01-01

    The objectives of this study are: (1) to evaluate the backscattering signals response to snow wetness; and (2) to develop an algorithm for snow wetness measurement using C-band polarimetric synthetic aperture radar (SAR). In hydrological investigations, modeling and forecasting of snowmelt runoff requires information about snowpack properties and their spatial variability. In particular, timely measurement of snow parameters is needed for operational hydrology. The liquid water content of snowpack is one of the important parameters. Active microwave sensors are highly sensitive to liquid water in the snowpack because of the large dielectric contrast between ice and water in the microwave spectrum. They are not affected by weather and have a spatial resolution compatible with the topographic variation in alpine regions. However, a quantitative algorithm for retrieval snow wetness has not yet been developed.

  12. A High School Snow Ecology Unit

    ERIC Educational Resources Information Center

    Phillips, R. E.; Watson, C. A.

    1976-01-01

    Suggests that snow ecology be added to the high school curriculum and center around winter abiotic factors and biotic components, winter survival, case studies, winter research and arctic ecology. (LS)

  13. To Blend or Not to Blend: Online and Blended Learning Environments in Undergraduate Teacher Education

    ERIC Educational Resources Information Center

    Collopy, Rachel M. B.; Arnold, Jackie Marshall

    2009-01-01

    Research comparing student experiences with online-only and blended delivery has often concentrated on graduate students and nontraditional programs. However, the effectiveness of online and blended delivery depends on audience and subject matter, suggesting that findings based on data from graduate and nontraditional programs may not hold true…

  14. Winter precipitation and snow accumulation drive the methane sink or source strength of Arctic tussock tundra.

    PubMed

    Blanc-Betes, Elena; Welker, Jeffrey M; Sturchio, Neil C; Chanton, Jeffrey P; Gonzalez-Meler, Miquel A

    2016-08-01

    Arctic winter precipitation is projected to increase with global warming, but some areas will experience decreases in snow accumulation. Although Arctic CH4 emissions may represent a significant climate forcing feedback, long-term impacts of changes in snow accumulation on CH4 fluxes remain uncertain. We measured ecosystem CH4 fluxes and soil CH4 and CO2 concentrations and (13) C composition to investigate the metabolic pathways and transport mechanisms driving moist acidic tundra CH4 flux over the growing season (Jun-Aug) after 18 years of experimental snow depth increases and decreases. Deeper snow increased soil wetness and warming, reducing soil %O2 levels and increasing thaw depth. Soil moisture, through changes in soil %O2 saturation, determined predominance of methanotrophy or methanogenesis, with soil temperature regulating the ecosystem CH4 sink or source strength. Reduced snow (RS) increased the fraction of oxidized CH4 (Fox) by 75-120% compared to Ambient, switching the system from a small source to a net CH4 sink (21 ± 2 and -31 ± 1 mg CH4  m(-2)  season(-1) at Ambient and RS). Deeper snow reduced Fox by 35-40% and 90-100% in medium- (MS) and high- (HS) snow additions relative to Ambient, contributing to increasing the CH4 source strength of moist acidic tundra (464 ± 15 and 3561 ± 97 mg CH4  m(-2)  season(-1) at MS and HS). Decreases in Fox with deeper snow were partly due to increases in plant-mediated CH4 transport associated with the expansion of tall graminoids. Deeper snow enhanced CH4 production within newly thawed soils, responding mainly to soil warming rather than to increases in acetate fermentation expected from thaw-induced increases in SOC availability. Our results suggest that increased winter precipitation will increase the CH4 source strength of Arctic tundra, but the resulting positive feedback on climate change will depend on the balance between areas with more or less snow accumulation than they are currently

  15. Winter precipitation and snow accumulation drive the methane sink or source strength of Arctic tussock tundra.

    PubMed

    Blanc-Betes, Elena; Welker, Jeffrey M; Sturchio, Neil C; Chanton, Jeffrey P; Gonzalez-Meler, Miquel A

    2016-08-01

    Arctic winter precipitation is projected to increase with global warming, but some areas will experience decreases in snow accumulation. Although Arctic CH4 emissions may represent a significant climate forcing feedback, long-term impacts of changes in snow accumulation on CH4 fluxes remain uncertain. We measured ecosystem CH4 fluxes and soil CH4 and CO2 concentrations and (13) C composition to investigate the metabolic pathways and transport mechanisms driving moist acidic tundra CH4 flux over the growing season (Jun-Aug) after 18 years of experimental snow depth increases and decreases. Deeper snow increased soil wetness and warming, reducing soil %O2 levels and increasing thaw depth. Soil moisture, through changes in soil %O2 saturation, determined predominance of methanotrophy or methanogenesis, with soil temperature regulating the ecosystem CH4 sink or source strength. Reduced snow (RS) increased the fraction of oxidized CH4 (Fox) by 75-120% compared to Ambient, switching the system from a small source to a net CH4 sink (21 ± 2 and -31 ± 1 mg CH4  m(-2)  season(-1) at Ambient and RS). Deeper snow reduced Fox by 35-40% and 90-100% in medium- (MS) and high- (HS) snow additions relative to Ambient, contributing to increasing the CH4 source strength of moist acidic tundra (464 ± 15 and 3561 ± 97 mg CH4  m(-2)  season(-1) at MS and HS). Decreases in Fox with deeper snow were partly due to increases in plant-mediated CH4 transport associated with the expansion of tall graminoids. Deeper snow enhanced CH4 production within newly thawed soils, responding mainly to soil warming rather than to increases in acetate fermentation expected from thaw-induced increases in SOC availability. Our results suggest that increased winter precipitation will increase the CH4 source strength of Arctic tundra, but the resulting positive feedback on climate change will depend on the balance between areas with more or less snow accumulation than they are currently

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

    NASA Astrophysics Data System (ADS)

    Bippus, Gabriele; Nagler, Thomas

    2013-04-01

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

  17. Hyphomycetes in the snow from gymnosperm trees.

    PubMed

    Czeczuga, B; Orłowska, M

    1998-01-01

    The presence of 26 hyphomycete species was noted in snow water collected from coniferous trees. Camposporium pellucidum, Monodictys peruviana, Polystratorictus fusarioideus, Sporidesmium moniliforme, Tripospermum acerinum and Veronaea botryosa were recorded for the first time to Poland. Among the 26 species found in snow water from coniferous trees predominance of the socalled aero-aquatic hyphomycetes and only a few species belong to the group of aquatic hyphomycetes.

  18. Snow management practices in French ski resorts

    NASA Astrophysics Data System (ADS)

    Spandre, Pierre; Francois, Hugues; George-Marcelpoil, Emmanuelle; Morin, Samuel

    2016-04-01

    Winter tourism plays a fundamental role in the economy of French mountain regions but also in other countries such as Austria, USA or Canada. Ski operators originally developed grooming methods to provide comfortable and safe skiing conditions. The interannual variability of snow conditions and the competition with international destinations and alternative tourism activities encouraged ski resorts to mitigate their dependency to weather conditions through snowmaking facilities. However some regions may not be able to produce machine made snow due to inadequate conditions and low altitude resorts are still negatively impacted by low snow seasons. In the meantime, even though the operations of high altitude resorts do not show any dependency to the snow conditions they invest in snowmaking facilities. Such developments of snowmaking facilities may be related to a confused and contradictory perception of climate change resulting in individualistic evolutions of snowmaking facilities, also depending on ski resorts main features such as their altitude and size. Concurrently with the expansion of snowmaking facilities, a large range of indicators have been used to discuss the vulnerability of ski resorts such as the so-called "100 days rule" which was widely used with specific thresholds (i.e. minimum snow depth, dates) and constraints (i.e. snowmaking capacity). The present study aims to provide a detailed description of snow management practices and major priorities in French ski resorts with respect to their characteristics. We set up a survey in autumn 2014, collecting data from 56 French ski operators. We identify the priorities of ski operators and describe their snowmaking and grooming practices and facilities. The operators also provided their perception of the ski resort vulnerability to snow and economic challenges which we could compare with the actual snow conditions and ski lift tickets sales during the period from 2001 to 2012.

  19. Effects of soot-induced snow albedo change on snowpack and hydrological cycle in western United States based on Weather Research and Forecasting chemistry and regional climate simulations

    SciTech Connect

    Qian, Yun; Gustafson, William I.; Leung, Lai-Yung R.; Ghan, Steven J.

    2009-02-14

    Radiative forcing induced by soot on snow is a major anthropogenic forcing affecting the global climate. However, it is uncertain how the soot-induced snow albedo perturbation affects regional snowpack and the hydrological cycle. In this study we simulated the deposition of soot aerosol on snow and investigated the resulting impact on snowpack and the surface water budget in the western United States. A yearlong simulation was performed using the chemistry version of the Weather Research and Forecasting model (WRF-Chem) to determine an annual budget of soot deposition, followed by two regional climate simulations using WRF in meteorology-only mode, with and without the soot-induced snow albedo perturbations. The chemistry simulation shows large spatial variability in soot deposition that reflects the localized emissions and the influence of the complex terrain. The soot-induced snow albedo perturbations increase the net solar radiation flux at the surface during late winter to early spring, increase the surface air temperature, reduce snow water equivalent amount, and lead to reduced snow accumulation and less spring snowmelt. These effects are stronger over the central Rockies and southern Alberta, where soot deposition and snowpack overlap the most. The indirect forcing of soot accelerates snowmelt and alters stream flows, including a trend toward earlier melt dates in the western United States. The soot-induced albedo reduction initiates a positive feedback process whereby dirty snow absorbs more solar radiation, heating the surface and warming the air. This warming causes reduced snow depth and fraction, which further reduces the regional surface albedo for the snow covered regions. Our simulations indicate that the change of maximum snow albedo induced by soot on snow contributes to 60% of the net albedo reduction over the central Rockies. Snowpack reduction accounts for the additional 40%.

  20. Snow as a habitat for microorganisms

    NASA Technical Reports Server (NTRS)

    Hoham, Ronald W.

    1989-01-01

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

  1. The structure of powder snow avalanches

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  2. Interpretation of snow-climate feedback as produced by 17 general circulation models

    NASA Technical Reports Server (NTRS)

    Cess, R. D.; Zhang, M.-H.; Potter, G. L.; Blanchet, J.-P.; Chalita, S.; Colman, R.; Dazlich, D. A.; Del Genio, A. D.; Lacis, A. A.; Dymnikov, V.

    1991-01-01

    Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

  3. Snow in Southwest United States

    NASA Technical Reports Server (NTRS)

    2002-01-01

    In late December, the Southwest was blanketed with snow, and this scence was captured by MODIS on December 27, 2001. The white drape contrasts sharply with the red rock of the Colorado Plateau, a geologic region made up of a succession of plateaus and mesas composed mostly of sedimentary rock, whose reddish hues indicate the presence of oxidized iron. The Plateau covers the Four Corners area of the Southwest, including (clockwise from upper left) southern Utah, Colorado, New Mexico, and Arizona. The region gets its name from the Colorado River, seen most prominently as a dark ribbon running southwest through southern Utah. At the upper left of the image, a bank of low clouds partially obscures Utah's Great Salt Lake, but its faint outline is still visible. To the east and southeast of the lake, some high peaks of the Wasatch Mountain range break free of the clouds. The Park City area, one of the 2002 Winter Olympic venues, can be seen poking through the cloud deck about 75km southeast of the lake. Farther east, the dark Uinta Mountains follow the border between Colorado and Wyoming. The Uinta are one of the rare east-west running ranges of the Rocky Mountains.

  4. [Was Snow White a transsexual?].

    PubMed

    Michel, A; Mormont, C

    2002-01-01

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

  5. Evaluation of SNODAS snow depth and snow water equivalent estimates for the Colorado Rocky Mountains, USA

    USGS Publications Warehouse

    Clow, David W.; Nanus, Leora; Verdin, Kristine L.; Schmidt, Jeffrey

    2012-01-01

    The National Weather Service's Snow Data Assimilation (SNODAS) program provides daily, gridded estimates of snow depth, snow water equivalent (SWE), and related snow parameters at a 1-km2 resolution for the conterminous USA. In this study, SNODAS snow depth and SWE estimates were compared with independent, ground-based snow survey data in the Colorado Rocky Mountains to assess SNODAS accuracy at the 1-km2 scale. Accuracy also was evaluated at the basin scale by comparing SNODAS model output to snowmelt runoff in 31 headwater basins with US Geological Survey stream gauges. Results from the snow surveys indicated that SNODAS performed well in forested areas, explaining 72% of the variance in snow depths and 77% of the variance in SWE. However, SNODAS showed poor agreement with measurements in alpine areas, explaining 16% of the variance in snow depth and 30% of the variance in SWE. At the basin scale, snowmelt runoff was moderately correlated (R2 = 0.52) with SNODAS model estimates. A simple method for adjusting SNODAS SWE estimates in alpine areas was developed that uses relations between prevailing wind direction, terrain, and vegetation to account for wind redistribution of snow in alpine terrain. The adjustments substantially improved agreement between measurements and SNODAS estimates, with the R2 of measured SWE values against SNODAS SWE estimates increasing from 0.42 to 0.63 and the root mean square error decreasing from 12 to 6 cm. Results from this study indicate that SNODAS can provide reliable data for input to moderate-scale to large-scale hydrologic models, which are essential for creating accurate runoff forecasts. Refinement of SNODAS SWE estimates for alpine areas to account for wind redistribution of snow could further improve model performance. Published 2011. This article is a US Government work and is in the public domain in the USA.

  6. Hydrogen-bonded polymer blends

    NASA Astrophysics Data System (ADS)

    Guigley, Kevin Scott

    This thesis discusses three topics in the general area of hydrogen bonded polymer blends. The first pertains to the blending of flame retardant polyphosphazenes. Poly[bis(n-alkyoxy)phosphazenes] blends with poly(butyl methacrylate- co-4-vinyl phenol) (BMAVPh) were initially studied. These results were compared to BMAVPh blends of analogous poly (vinyl n-alkyl ethers) and the phase behavior was similar. Next, poly[bis(carboxylatophenoxy)phosphazene] blends with a structural polyurethane foam were prepared via reactive mixing. The combustion behavior of these foams was analyzed qualitatively, by a horizontal flame test, and quantitatively, by oxygen index (OI) measurements. Both of these tests indicated a modest increase in flame resistance at loadings of 20 wt% and above. In the second topic, equilibrium constants determined from low molecular weight mixtures were used to successfully predict the phase behavior of analogous polymer blends. Due consideration was given to intramolecular screening and functional group accessibility, factors that are a direct consequence of chain connectivity. In the third topic, polymer blends involving an alternating 1:1 copolymer of tetrafluoroethylene (TFE) and a hexafluoroisopropanol modified vinyl ether (HFIPVE) were studied. This copolymer is interesting for both experimental and theoretical studies of the phase behavior of polymer blends because (1) it is amorphous and has a relatively low glass transition temperature (12°C); (2) it has a relatively low solubility parameter (≈7 (cal.cm-3)-0.5); (3) it is soluble in moderately polar solvents, and (4) it contains the hexafluoroisopropanol group that is a strong hydrogen bond donor. Experimental infrared and thermal analysis studies of polymer blends with (co)polymers containing acetoxy, methacrylate and aliphatic ether groups were studied and compared to theoretical predictions of miscibility maps.

  7. Measurements of Black Carbon Induced Snow-Albedo Reduction

    NASA Astrophysics Data System (ADS)

    Hadley, O. L.; Kirchstetter, T. W.

    2011-12-01

    Several modeling studies have indicated that black carbon (BC) reduces the albedo of snow and ice and appreciably contributes to Northern Hemisphere warming and glacier retreat. Observations of the BC impact on snow albedo are needed to verify model predictions. Whereas field studies dating back to the early 1980s measured BC concentrations in snow and ice in the arctic, the BC effect on snow albedo and melting has been difficult to observe directly because the albedo reduction is small and often masked by other natural variables. This study evaluates both the initial impact of BC on snow albedo, as well as associated feedbacks due to snow age and BC scavenging during snow melting. The first feedback is related to the increasing grain size of snow as it ages. Larger snow grains allow sunlight to penetrate farther, where it is exposed to and may be increasingly absorbed by BC. This enhances the albedo reduction attributable to the mass of BC present in the snow and deposits energy at greater depths in the snowpack, potentially increasing the melt rate and therefore the growth rate of the snow grains. The second potential feedback, associated with BC transport through a melting snowpack, occurs if BC is scavenged from the melt water by the ice grains thus increasing the BC concentration in the remaining snow. Measurement of pristine and sooty snow made in the laboratory verifies that BC reduces snow albedo to a greater extent for larger-grained snow. Experimental observations yield an empirical model of the BC snow albedo reduction. Measurements of BC transport in both laboratory and natural snow were used to develop a model of the evolution of the vertical distribution of BC in melting snow. These measurements provide the first quantification of a BC concentration enhancement in melting snow.

  8. Modeling snow season controls on northern net ecosystem exchange

    NASA Astrophysics Data System (ADS)

    Luus, K. A.; Lin, J. C.; Kelly, R. E.

    2011-12-01

    Recent field studies have indicated that the timing of snow melt and snow fall, the quantity of snow, and soil temperature are important controls on snow season net ecosystem exchange (NEE). The low thermal conductivity of snow reduces soil heat loss, thereby enabling a greater rate of subnivean respiration under deeper snowpacks, whereas snow melt and snow fall alter the seasonal timing of photosynthetic uptake. Although a substantial portion of annual NEE in northern regions occurs during the snow season, model estimates have not previously included representations of snow season controls on NEE. The objective of this study was therefore to 1) incorporate remotely sensed estimates of snow water equivalent, soil temperature, and the timing of initial snow fall and final snow melt into model estimates of northern NEE; and 2) examine whether incorporating representations of key snow season variables reduces model uncertainty. NEE was estimated using the Vegetation Photosynthesis Respiration Model (VPRM), a simple diagnostic biosphere model that relies on a remote sensing based approach. Findings indicate that a potential exists to improve northern estimates of NEE by incorporating information on snow season controls from remote sensing observations. Soil respiration can be better assessed using soil temperature rather than surface air temperature. The influence of changes in snow water equivalent on soil temperature dynamics can be assessed using remotely sensed estimates of snow water equivalent. Incorporating remotely sensed estimates of snow cover area can improve the timing of seasonal changes in photosynthetic uptake. Furthermore, including snow season controls on northern NEE can enable experiments to be run analyzing the influence of changes in snowpack dynamics, the frequency of extreme winter warming events, and the timing of the snow season on northern NEE.

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

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

    NASA Astrophysics Data System (ADS)

    Raleigh, Mark S.

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

  11. Inter-Model Diagnostics for Two Snow Models Across Multiple Western U.S. Locations and Implications for Management

    NASA Astrophysics Data System (ADS)

    Houle, E. S.; Livneh, B.; Kasprzyk, J. R.

    2014-12-01

    In the western United States, water resource management is increasingly reliant on numerical modeling of hydrological processes, namely snow accumulation and ablation. We seek to advance a framework for providing model diagnostics for such systems by combining an improved understanding of model structural differences (i.e., conceptual vs. physically based) and parameter sensitivities. The two snow models used in this study are SNOW-17, a conceptual degree-day model, and the Variable Infiltration Capacity (VIC) snow model, which is physically based and solves the full water and energy balances. To better understand the performance of these models, several approaches will be used. For the conceptual model, global sensitivity analysis methods (e.g., Sobol' and Method of Morris), and a multi-objective calibration will be applied to identify important parameters and show calibrated parameter values. For the physically based model, we will contribute a novel exploration of some parameters that can be adjusted within the model, including the liquid water holding capacity, the density of newly fallen snow, and the snow roughness. Additionally, the VIC model will be run with explicit radiation inputs at selected sites. For each model run, snow sensitivities and errors (i.e., snow water equivalent results) will be translated into estimated changes in annual water yield for the study areas. Accurately predicting water yield is essential for water management, and it is used here as a practical measure to determine the importance of model parameter sensitivity and calibration. The analysis will be conducted across a range of snow-dominated locations representing a variety of climates across the western United States (e.g. continental, maritime, alpine).

  12. Blends of zein and nylon-6

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Blends of zein and nylon-6(55k)were used to produce solution cast films and electrospun fibers. Zein was blended with nylon-6 in formic acid solution. When the amount of nylon-6 was 8% or less a compatible blend formed. The blend was determined to be compatible based on physical property measurement...

  13. Retrieval of aerosol optical thickness over snow using AATSR observations

    NASA Astrophysics Data System (ADS)

    Istomina, Larysa; von Hoyningen-Huene, Wolfgang; Rozanov, Vladimir; Kokhanovsky, Alexander; Burrows, John P.

    Remote sensing of aerosols experiences lack of products over very bright surfaces, such as deserts and snow, due to difficulties with the subtraction of the surface reflection contribution, when a small error in accounting for surface reflectance can cause a large error in retrieved aerosol optical thickness (AOT). Cloud screening over bright surface is also not easy because of low contrast between clouds and surface in visible range of spectrum, and additional infrared chan-nels are not always available. Luckily, AATSR instrument onboard ENVISAT has necessary features to solve both of these problems. In current work we present an improved version of discussed earlier [1,2] dual-view algorithm to retrieve AOT over snow. The retrieval algorithm still consists of cloud screening, based on spectral shape analysis of AATSR pixel in order to extract clear snow pixels, and of AOT retrieval over snow and water. Current version of AOT retrieval over open ocean now contains improved accounting for ocean reflectance (in previous version the ocean was assumed to be absolutely black). The AOT retrieval over snow has been improved to account more accurately for the bidirectional features of the surface reflection function. For this we now use the approach described in [4] instead of [3], which has been used in the previous version of the retrieval. The accuracy of both approaches [3] and [4] has been evaluated via comparison to forward radiative-transfer model for the case of a very bright surface. The new algorithm has been applied to various scenes in European Arctic and Alaska in different scales, up to global AOT maps. The correspondence of AOT over snow to AOT over water is quite good, which proves the reliability of the retrieval. The algorithm has been validated against AERONET and other Arctic ground based AOT data and shows reasonably good correlation. The presented cloud screening method has been validated via comparison to MODIS cloud mask and Micro Pulse Lidar data

  14. Variability in the annual cycle of Northern Hemisphere snow extent, using a newly completed climate data record

    NASA Astrophysics Data System (ADS)

    Henderson, G. R.; Leathers, D. J.; Robinson, D. A.

    2012-12-01

    Variability in the annual cycle of Northern Hemisphere snow cover extent (SCE) may have important impacts on the global climate system through a number of potential feedback mechanisms. Motivated by recent snow literature heralding reports ranging from earlier spring melt, to an overall seasonal decrease in SCE, both spatial and temporal variability in extent are explored using a newly completed SCE climate data record (CDR). From a hydrologic standpoint, such shifts have huge implications to the overall climatology of any region with snow present in its seasonal cycle. The SCE CDR utilized in this study is the result of a reanalysis of NOAA satellite-derived maps of NH continental SCE and begins in 1966. The earlier 33 years of data are drawn from coarse-scale weekly NOAA maps, whilst recent years are based on a downgraded version of the IMS 24 km NOAA product, currently produced by the National Ice Center. The Rutgers Global Snow Lab undertook reanalysis and merging of the different resolution datasets as part of the NASA MEaSUREs project. Principal component (PC) analysis was performed on the annual cycle of NH, and individual continental snow extent totals. Close to 75% of variance was explained by the first three PCs, in the case of NH and Eurasia snow extents. Snow composite analysis based on positive PC scores time series years displays greater snow extent, in excess of 4 × 106 km2 in the case of the NH alone. Preliminary assessment of associations with large-scale atmospheric patterns (e.g. surface air temperature, mid-tropospheric geopotential height), yielded patterns indicative of know teleconnection patterns such as the AO and NAO indices. Results from additional PC analysis performed spatially on the SCE CDR will be discussed.

  15. Snow measurement system for airborne snow surveys (GPR system from helicopter) in high mountian areas.

    NASA Astrophysics Data System (ADS)

    Sorteberg, Hilleborg K.

    2010-05-01

    In the hydropower industry, it is important to have precise information about snow deposits at all times, to allow for effective planning and optimal use of the water. In Norway, it is common to measure snow density using a manual method, i.e. the depth and weight of the snow is measured. In recent years, radar measurements have been taken from snowmobiles; however, few energy supply companies use this method operatively - it has mostly been used in connection with research projects. Agder Energi is the first Norwegian power producer in using radar tecnology from helicopter in monitoring mountain snow levels. Measurement accuracy is crucial when obtaining input data for snow reservoir estimates. Radar screening by helicopter makes remote areas more easily accessible and provides larger quantities of data than traditional ground level measurement methods. In order to draw up a snow survey system, it is assumed as a basis that the snow distribution is influenced by vegetation, climate and topography. In order to take these factors into consideration, a snow survey system for fields in high mountain areas has been designed in which the data collection is carried out by following the lines of a grid system. The lines of this grid system is placed in order to effectively capture the distribution of elevation, x-coordinates, y-coordinates, aspect, slope and curvature in the field. Variation in climatic conditions are also captured better when using a grid, and dominant weather patterns will largely be captured in this measurement system.

  16. Ensemble-based snow data assimilation for an operational snow model

    NASA Astrophysics Data System (ADS)

    Liu, Y.; He, M.; Seo, D.; Laurine, D.; Lee, H.

    2010-12-01

    In mountainous regions of the western United States, seasonal snow pack evolution dominates the generation of snowmelt and streamflow. In the National Weather Service (NWS), the conceptual SNOW-17 model is used for operational forecasting of snowmelt, which then serves as an input to a rainfall-runoff model for streamflow forecasts in snow-affected areas. To improve snowmelt estimates and therefore streamflow forecasts, some River Forecast Centers (RFCs) of the NWS operate a snow updating system to update areal Snow Water Equivalent (SWE) estimates by using a regression technique to reconcile the differences between the observed SWE (e.g., from SNOTEL stations) and the modeled SWE. While this method is parsimonious and easy to use in operations, it does not capitalize on the full capabilities offered by advanced data assimilation techniques to quantify, reduce, and propagate forecast uncertainty in a statistically and dynamically consistent fashion. This study describes an application of the ensemble Kalman filter (EnKF) which automatically and systematically assimilates SNOTEL SWE observations into the SNOW-17 model to reduce uncertainties in model initial conditions. The robustness of the ensemble filter as compared to the operational regression-based method is evaluated for both snow and streamflow forecasts at several operational basins in the service area of the Northwest River Forecast Center (NWRFC). This presentation describes the implementation of the EnKF into the SNOW-17 model and summarizes the preliminary evaluation results.

  17. Reconstructing MODIS Snow Cover Fraction Using Snow Meltout Dates From Snowpack Telemetry (SNOTEL) Data

    NASA Astrophysics Data System (ADS)

    Arogundade, A. B.; Qualls, R. J.

    2011-12-01

    Information on snow-covered area has been an important input for snowmelt runoff models in the prediction of runoff and simulation of streamflow. Several advanced methods of snow mapping exist today that can be used in determining the progressive reduction of snow cover during snowmelt; however, some of these advanced methods of snow mapping, such as the Moderate-Resolution Imagine Spectroradiometer (MODIS) satellite sensor, did not exist before 1999. The non-availability of MODIS prior to its launch in 1999, sometimes limits the use of this remote sensing tool in developing historical snow depletion curves that are needed to provide base period perturbations for climate change snowmelt runoff simulations. These historical depletion curves, among many other uses, provide snow cover information for snowmelt runoff modeling in hydrologic models such as snowmelt runoff model (SRM). A method is presented in this study that makes use of the available remotely sensed and ground based data to construct a single dimensionless snow depletion curve that is subsequently used with historical SNOTEL data to reconstruct MODIS snow depletion curves for base periods preceding the availability of current satellite remote sensing, and for future periods associated with climate scenarios.

  18. The role of mercury redox reactions in snow on snow-to-air mercury transfer.

    PubMed

    Lalonde, Janick D; Poulain, Alexandre J; Amyot, Marc

    2002-01-15

    Wet deposition of Hg in snow represents a major air-to-land flux of Hg in temperate and polar environments. However, the chemical speciation of Hg in snow and its chemical and physical behavior after deposition are poorly understood. To investigate Hg dynamics in snow, we followed Hg0 and total Hg concentrations in a snowpack above a frozen lake over 1 month. Our results indicate that newly deposited Hg is highly labile in snowpacks. On average, Hg levels in particular snow episodes decrease by 54% within 24 h after deposition. We hypothesize that Hg depletion in snow could be caused by a rapid snow-to-air Hg transfer resulting from Hg(II) photoinduced reduction to volatile Hg0. Both snowmelt incubated under a UV lamp at 17 degrees C and solid snow incubated under the sun at -10 degrees C in clear reaction vessels yielded a statistically significant increase in Hg0(aq) with time of exposure, while the Hg0(aq) levels remained constant in the dark controls. The snow-to-air Hg transfer we observed in this study suggests that the massive Hg deposition events observed in springtime in northern environments may have less impact than previously anticipated, since once deposited, Hg could be rapidly reduced and re-emitted.

  19. Evolution of the surface area of a snow layer

    SciTech Connect

    Hanot, L.; Domine, F.

    1999-12-01

    Atmospheric trace gases can partition between the atmosphere and the snow surface. Because snow has a large surface-to-volume ratio, an important interaction potential between ice and atmospheric trace gases exists. Quantifying this partitioning requires the knowledge of the surface area (SA) of snow. Eleven samples were taken from a 50 cm thick snow fall at Col de Porte, near Grenoble (French Alps) between January 20 and February 4, 1998. Fresh snow and 3, 8, and 15-day-old snow were sampled at three different depths. Surface hoar, formed after the fall, was also sampled. Air and surface snow temperature, snow density, and snow fall rate were measured. Snow temperature always remained below freezing. Snow SA was measured using methane adsorption at 77.15 K. Values ranged from 2.25 m{sup 2}/g for fresh snow to 0.25 m{sup 2}/g for surface hoar and surface snow after 15 days. These values are much too high to be explained by the macroscopic aspect of snow crystals, and microstructures such as small rime droplets must have been present. Large decrease in SA with time were observed. The first meter of snowpack had a total surface area of about 50,000 m{sup 2} per m{sup 2} of ground. Reduction in SA will lead to the emission of adsorbed species by the snowpack, with possible considerable increase in atmospheric concentrations.

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

    NASA Astrophysics Data System (ADS)

    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

  1. Shifting mountain snow patterns in a changing climate from remote sensing retrieval.

    PubMed

    Dedieu, J P; Lessard-Fontaine, A; Ravazzani, G; Cremonese, E; Shalpykova, G; Beniston, M

    2014-09-15

    Observed climate change has already led to a wide range of impacts on environmental systems and society. In this context, many mountain regions seem to be particularly sensitive to a changing climate, through increases in temperature coupled with changes in precipitation regimes that are often larger than the global average (EEA, 2012). In mid-latitude mountains, these driving factors strongly influence the variability of the mountain snow-pack, through a decrease in seasonal reserves and earlier melting of the snow pack. These in turn impact on hydrological systems in different watersheds and, ultimately, have consequences for water management. Snow monitoring from remote sensing provides a unique opportunity to address the question of snow cover regime changes at the regional scale. This study outlines the results retrieved from the MODIS satellite images over a time period of 10 hydrological years (2000-2010) and applied to two case studies of the EU FP7 ACQWA project, namely the upper Rhone and Po in Europe and the headwaters of the Syr Darya in Kyrgyzstan (Central Asia). The satellite data were provided by the MODIS Terra MOD-09 reflectance images (NASA) and MOD-10 snow products (NSIDC). Daily snow maps were retrieved over that decade and the results presented here focus on the temporal and spatial changes in snow cover. This paper highlights the statistical bias observed in some specific regions, expressed by the standard deviation values (STD) of annual snow duration. This bias is linked to the response of snow cover to changes in elevation and can be used as a signal of strong instability in regions sensitive to climate change: with alternations of heavy snowfalls and rapid snow melting processes. The interest of the study is to compare the methodology between the medium scales (Europe) and the large scales (Central Asia) in order to overcome the limits of the applied methodologies and to improve their performances. Results show that the yearly snow cover

  2. Shifting mountain snow patterns in a changing climate from remote sensing retrieval.

    PubMed

    Dedieu, J P; Lessard-Fontaine, A; Ravazzani, G; Cremonese, E; Shalpykova, G; Beniston, M

    2014-09-15

    Observed climate change has already led to a wide range of impacts on environmental systems and society. In this context, many mountain regions seem to be particularly sensitive to a changing climate, through increases in temperature coupled with changes in precipitation regimes that are often larger than the global average (EEA, 2012). In mid-latitude mountains, these driving factors strongly influence the variability of the mountain snow-pack, through a decrease in seasonal reserves and earlier melting of the snow pack. These in turn impact on hydrological systems in different watersheds and, ultimately, have consequences for water management. Snow monitoring from remote sensing provides a unique opportunity to address the question of snow cover regime changes at the regional scale. This study outlines the results retrieved from the MODIS satellite images over a time period of 10 hydrological years (2000-2010) and applied to two case studies of the EU FP7 ACQWA project, namely the upper Rhone and Po in Europe and the headwaters of the Syr Darya in Kyrgyzstan (Central Asia). The satellite data were provided by the MODIS Terra MOD-09 reflectance images (NASA) and MOD-10 snow products (NSIDC). Daily snow maps were retrieved over that decade and the results presented here focus on the temporal and spatial changes in snow cover. This paper highlights the statistical bias observed in some specific regions, expressed by the standard deviation values (STD) of annual snow duration. This bias is linked to the response of snow cover to changes in elevation and can be used as a signal of strong instability in regions sensitive to climate change: with alternations of heavy snowfalls and rapid snow melting processes. The interest of the study is to compare the methodology between the medium scales (Europe) and the large scales (Central Asia) in order to overcome the limits of the applied methodologies and to improve their performances. Results show that the yearly snow cover

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

    NASA Astrophysics Data System (ADS)

    Naha, Shaini; Thakur, Praveen K.; Aggarwal, S. P.

    2016-06-01

    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 using observed

  4. Statistical model for the correlation length of snow derived from SnowMicroPen measurements.

    NASA Astrophysics Data System (ADS)

    Proksch, M.; Loewe, H.; Schneebeli, M.

    2012-12-01

    The SnowMicroPen (SMP) allows to retrieve mechanical parameters from the snowpack. However, remote sensing applications rely on structural parameters of snow such as the correlation length. Due to the complexity of the physical connection between structural and mechanical parameters we derived a statistical model for the correlation length from SMP measurements. To this end we have analyzed snow samples of many different snow classes and densities by micro computer-tomography (CT) and SMP. We correlated the SMP-derived structural element length with the CT-derived correlation length and validated the model using field data taken during the NoSREx - III campaign in Sodankylä, Finland. Further, we employ the statistical model to estimate the specific surface area from combined SMP and density measurement from natural snow profiles. We compare this SSA estimate to independent SSA measurements by near-infrared photography and discuss potential and limitation of the method.

  5. Statistical model for the correlation length of snow derived from Snow-Micro-Pen measurements.

    NASA Astrophysics Data System (ADS)

    Proksch, M.; Loewe, H.; Schneebeli, M.

    2012-04-01

    The Snow-Micro-Pen (SMP) allows to retrieve various mechanical parameters from the snowpack. However, remote sensing applications rely on structural parameters of snow such as the correlation length. In the absence of a sound physical connection between structural and mechanical parameters we derive a statistical model for the correlation length from SMP measurements. To this end we have analyzed 22 snow samples of various snow types by computer tomography (CT) and SMP. We correlate the SMP-derived structural element length with the CT-derived correlation length. For validation we employ the statistical model to estimate the specific surface area from combined SMP and density measurement from natural snow profiles. We compare this SSA estimate to independent SSA measurements by Near-Infrared-Photography and discuss potentials and limitations of the method.

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

    NASA Astrophysics Data System (ADS)

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

    2003-04-01

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

  7. Simulation of Snow Dynamics in Response to Climate Variability

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Wang, S.; Trishchenko, A.

    2004-05-01

    Snow dynamics not only affects the energy dissipation in northern ecosystems during non-growing season, but also affects plant growth through its impact on the soil water conditions of early growing season. To better simulate the snow and soil dynamics, a multiple-layer snow and soil interaction module has been recently developed within the Ecological Assimilation of Land and Climate Observations (EALCO) model. Up to 6 snow layers and 6 soil layers with flexible depth are currently represented in the module. Soil or snow skin temperature is obtained by numerically solving the surface energy balance equation. Energy dissipation to latent, sensible and soil/snow surface heat fluxes are thus calculated. Snow density is simulated in consideration of both compaction and destructive metamorphism, which depends on snow age, temperature and the residing weight above. The snow surface albedo, thermal and water properties and change of snow depth are updated in each time step and snow layers are re-calculated accordingly. The temperatures of snow and soil layers are implicitly solved in a tridiagonal linear system for thermal conduction equations. Freezing and thawing are computed according to the solved layer temperature and the existing water phase in the layer. Water movement between snow layers is computed according to the liquid water content and water holding capacity. Soil Water movement is simulated using Richard's equation and Darcy's law. The soil water content of each layer is thus implicitly solved as for temperatures. The model runs in half-hourly time step and main outputs include snow depth, snow water equivalent, and the temperature and water profiles for both snow and soil. In this study, the model was tested using data collected from several Canadian sites in the prairie and boreal forest region. The observed snow depth and temperature were compared with the corresponding model outputs. Sensitivities of snow cover change and soil thermal and moisture regime

  8. Estimating maritime snow density from seasonal climate variables

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  9. Origin Story: Blended Wing Body

    NASA Video Gallery

    NASA is partnering with the Boeing Company, among others, to develop and test the blended wing body aircraft. The BWB has the potential to significantly reduce fuel use and noise. In this video, Bo...

  10. Ultrathin POSS-Polymer Blends

    NASA Astrophysics Data System (ADS)

    Polidan, Joe; Vastine, Ben; Deng, Jianjun; Esker, Alan; Viers, Brent

    2003-03-01

    Polyhedral oligomeric silsesquioxane (POSS) derivatives serving as nanofillers in polymer blends have potential aerospace engineering applications such as space-survivable coatings, ablative insulation in solid rocket motor casings, and lightweight polymer composites to replace metal components. Understanding how POSS structure affects dispersion within polymeric matrices provides a challenging scientific problem for developing heat-resistant coatings. Several strategies exist for dispersing POSS in a polymer matrix including direct blending, POSS-co-polymers, and the blending of POSS-co-polymers with another polymer. Model systems of trisilanol-POSS derivatives and poly(t-butyl acrylate) have been used to study POSS-polymer blends at the air/water interface and as Langmuir-Blodgett films on solid surfaces. Brewster angle microscopy and atomic force microscopy studies characterizing these systems will be discussed.

  11. Chemistry of small organic molecules on snow grains: the applicability of artificial snow for environmental studies.

    PubMed

    Kurková, Romana; Ray, Debajyoti; Nachtigallová, Dana; Klán, Petr

    2011-04-15

    The utilization of artificial snow for environmentally relevant (photo)chemical studies was systematically investigated. Contaminated snow samples were prepared by various methods: by shock freezing of the aqueous solutions sprayed into liquid nitrogen or inside a large walk-in cold chamber at -35 °C, or by adsorption of gaseous contaminants on the surface of artificially prepared pure or natural urban snow. The specific surface area of artificial snow grains produced in liquid nitrogen was determined using valerophenone photochemistry (400-440 cm(2) g(-1)) to estimate the surface coverage by small hydrophobic organic contaminants. The dynamics of recombination/dissociation (cage effect) of benzyl radical pairs, photochemically produced from 4-methyldibenzyl ketone on the snow surface, was investigated. The initial ketone loading, c = 10(-6)-10(-8) mol kg(-1), only about 1-2 orders of magnitude higher than the contaminant concentrations commonly found in nature, was already well below monolayer coverage. We found that the efficiency of out-of-cage reactions decreased at much higher temperatures than those previously determined for frozen solutions; however, the cage effect was essentially the same no matter what technique of snow production or ketone deposition/uptake was used, including the experiments with collected natural snow. The experimental observation that the contaminant molecules are initially self-associated even at the lowest concentrations was supported by DFT calculations. We conclude that, contrary to frozen aqueous solutions, in which the impurities reside in a 3D cage (micropocket), contaminant molecules located on the artificial snow grain surface at low concentrations can be visualized in terms of a 2D cage. Artificial snow thus represents a readily available study matrix that can be used to emulate the natural chemical processes of trace contaminants occurring in natural snow.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Loth, Bettina; Graf, Hans-F.

    1998-05-01

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

  14. First Moderate Resolution Imaging Spectroradiometer (MODIS) Snow and Ice Workshop

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K. (Editor)

    1995-01-01

    This document is a compilation of summaries of talks presented at a 2-day workshop on Moderate Resolution maging Spectroradiometer (MODIS) snow and ice products. The objectives of the workshop were to: inform the snow and ce community of potential MODIS products, seek advice from the participants regarding the utility of the products, and letermine the needs for future post-launch MODIS snow and ice products. Four working groups were formed to discuss at-launch snow products, at-launch ice products, post-launch snow and ice products and utility of MODIS snow and ice products, respectively. Each working group presented recommendations at the conclusion of the workshop.

  15. Black Carbon Measurements in Arctic Snow

    NASA Astrophysics Data System (ADS)

    Warren, S. G.; Grenfell, T. C.; Doherty, S. J.; Hegg, D. A.; Clarke, A. D.; Brandt, R. E.; Adames, A. F.

    2008-12-01

    A survey of the black carbon (BC) content of Arctic snow is underway, updating and expanding the 1983/84 survey of Clarke and Noone. Samples of snow are collected in mid to late spring when the entire winter snowpack is accessible. The samples are melted and filtered, and the filters are analyzed for absorptive impurities. Snow has been sampled on tundra, glaciers, ice caps, and sea ice, and in forests. To date about one thousand snow samples have been melted and filtered. The sampling effort has been assisted by IPY collaborations with S. Gerland (Svalbard), K. Steffen and C. Boeggild (Greenland), M. Sturm (Canada), V. Radionov (Russia), and J. Morison (North Pole), as well as several other volunteers. Two expeditions to arctic Russia were carried out, across longitudes 50-170 E, to cover a region that had not been sampled in the 1983/84 survey. The filters are examined with a spectrophotometer, scanning wavelengths 450-900 nm. The relative contributions of BC and soil dust to the absorption can be estimated from the spectral dependence of transmission. Calibration is achieved with use of several standard filters containing measured amounts of a commercial soot with a mass absorption cross-section of about 6 square meters per gram. Preliminary results indicate that the snow cover in Alaska, Canada, and the Arctic Ocean has lower BC concentrations now than 20 years ago (5-10 ppb instead of 15-30 ppb), consistent with the declining trend of BC found in air samples at Alert. Background levels of BC in arctic Russia, distant from sources of local pollution, have median values 20-30 ppb, but with higher concentrations at the surface at some locations, and lower concentrations in newly fallen snow. In some regions, particularly the Canadian Arctic islands and the Arctic coast of northeast Siberia, the snow cover, even at its maximum depth in April before melting began, was thin and patchy; in these regions the albedo is determined more by snow thickness than by

  16. Improving the snow physics of WEB-DHM and its point evaluation at two SnowMIP alpine sites

    NASA Astrophysics Data System (ADS)

    Shrestha, M.; Wang, L.; Koike, T.; Xue, Y.; Hirabayashi, Y.

    2010-06-01

    The snow physics of a distributed biosphere hydrological model, referred to as the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) is improved by incorporating the three-layer physically based energy balance snowmelt model of Simplified Simple Biosphere 3 (SSiB3) and the Biosphere-Atmosphere Transfer Scheme (BATS) albedo scheme. WEB-DHM with improved snow physics (WEB-DHM-S) can simulate the variability of snow density, snow depth and snow water equivalent, liquid water and ice content in each layer, prognostic snow albedo, diurnal variation in snow surface temperature, thermal heat due to conduction and liquid water retention. The performance of WEB-DHM-S is evaluated at two alpine sites of the Snow Model Intercomparison Project with different climate characteristics: Col de Porte in France and Weissfluhjoch in Switzerland. The simulation results of the snow depth, snow water equivalent, surface temperature, snow albedo and snowmelt runoff reveal that WEB-DHM-S is capable of simulating the internal snow process better than the original WEB-DHM, with the root mean square error and bias error being remarkably reduced. Although WEB-DHM-S is only evaluated at a point scale for the simulation of snow processes, this study provides a benchmark for the application of WEB-DHM-S in cold regions in the assessment of the basin-scale snow water equivalent and seasonal discharge simulation for water resources management.

  17. Blended Learning (BL) as Pedagogical Alternative to Teach Business Communication Course: Case Study of UUM Executive Diploma Program

    ERIC Educational Resources Information Center

    Dzakiria, Hisham; Don @ A. Wahab, Mohd Sobri; Abdul Rahman, Hamzah Dato'

    2012-01-01

    Globally, blended learning (BL) technologies have been increasingly applied in a variety of fields, both public and private sectors. In recent years, universities, public and private businesses and organizations are among those employing blended learning methods and technologies in training and re-training of professionals in the workforce. In…

  18. Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological Impact

    SciTech Connect

    Qian, Yun; Yasunari, Teppei J.; Doherty, Sarah J.; Flanner, M. G.; Lau, William K.; Ming, J.; Wang, Hailong; Wang, Mo; Warren, Stephen G.; Zhang, Rudong

    2015-01-01

    Light absorbing particles (LAP, e.g., black carbon, brown carbon, and dust) influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance (a.k.a., surface darkening), which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice (LAPSI) has been identified as one of major forcings affecting climate change, e.g. in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, andclimatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.

  19. Forest damage and snow avalanche flow regime

    NASA Astrophysics Data System (ADS)

    Feistl, T.; Bebi, P.; Christen, M.; Margreth, S.; Diefenbach, L.; Bartelt, P.

    2015-06-01

    Snow avalanches break, uproot and overturn trees causing damage to forests. The extent of forest damage provides useful information on avalanche frequency and intensity. However, impact forces depend on avalanche flow regime. In this paper, we define avalanche loading cases representing four different avalanche flow regimes: powder, intermittent, dry and wet. Using a numerical model that simulates both powder and wet snow avalanches, we study documented events with forest damage. First we show that in the powder regime, although the applied impact pressures can be small, large bending moments in the tree stem can be produced due to the torque action of the blast. The impact area of the blast extends over the entire tree crown. We find that, powder clouds with velocities over 20 m s-1 can break tree stems. Second we demonstrate that intermittent granular loadings are equivalent to low-density uniform dry snow loadings under the assumption of homogeneous particle distributions. The intermittent regime seldom controls tree breakage. Third we calculate quasi-static pressures of wet snow avalanches and show that they can be much higher than pressures calculated using dynamic pressure formulas. Wet snow pressure depends both on avalanche volume and terrain features upstream of the tree.

  20. Validation and Further Development of HUT Snow Emission Model for Satellite Microwave Radiometer Data Inversion and Assimilation

    NASA Astrophysics Data System (ADS)

    Pulliainen, J.; Kontu, A.; Lemmetyinen, J.; Takala, M.; Luojus, K.

    2008-12-01

    Global mapping of terrestrial snow cover and sea ice is an important application area for space-borne microwave radiometry. The algorithms applied e.g. for estimating snow water equivalent (SWE) oare typically empirical formulas obtained by data delineation or by fitting a regression model to brightness temperatures simulated by a physical forward model. On the other hand, algorithms based on the inversion of a forward brightness temperature model have been also applied. In all cases, an essential factor determining the performance of inversion algorithms or giving information on the validity of empirical approaches is the accuracy of forward brightness temperature modelling. The techniques used for modeling the brightness temperature of snow pack are typically based on the radiative transfer equation. In semi-empirical approaches, some simplifications are made to avoid numerical integration, which enables the use of forward models e.g. in iterative inversion algorithms. Relevant semi- empirical models include the HUT snow emission model and the MEMLS model. They consider snow pack as a single layer (HUT model) or as a multi-layer structure (MEMLS). In practice, the use of any model with space-borne or airborne radiometer data requires that snow ground-interactions as well as influence of vegetation and atmosphere have to be considered. This significantly complicates the modeling task. The HUT snow emission model was developed in 1998 to describe the microwave brightness temperature of snow covered forested terrain. Revisions to improve the consideration of snow extinction coefficient have been made in recent years by different research groups. The model treats different emission contributions and their interactions with simple analytical formulas that are derived either through empirical or semi- theoretical considerations. As the model is relatively simple, it can be used for the inversion of space-borne data in the estimation of quantitative snow pack

  1. Converting Snow Depth to SWE: The Fusion of Simulated Data with Remote Sensing Retrievals and the Airborne Snow Observatory

    NASA Astrophysics Data System (ADS)

    Bormann, K.; Marks, D. G.; Painter, T. H.; Hedrick, A. R.; Deems, J. S.

    2015-12-01

    Snow cover monitoring has greatly benefited from remote sensing technology but, despite their critical importance, spatially distributed measurements of snow water equivalent (SWE) in mountain terrain remain elusive. Current methods of monitoring SWE rely on point measurements and are insufficient for distributed snow science and effective management of water resources. Many studies have shown that the spatial variability in SWE is largely controlled by the spatial variability in snow depth. JPL's Airborne Snow Observatory mission (ASO) combines LiDAR and spectrometer instruments to retrieve accurate and very high-resolution snow depth measurements at the watershed scale, along with other products such as snow albedo. To make best use of these high-resolution snow depths, spatially distributed snow density data are required to leverage SWE from the measured snow depths. Snow density is a spatially and temporally variable property that cannot yet be reliably extracted from remote sensing techniques, and is difficult to extrapolate to basin scales. However, some physically based snow models have shown skill in simulating bulk snow densities and therefore provide a pathway for snow depth to SWE conversion. Leveraging model ability where remote sensing options are non-existent, ASO employs a physically based snow model (iSnobal) to resolve distributed snow density dynamics across the basin. After an adjustment scheme guided by in-situ data, these density estimates are used to derive the elusive spatial distribution of SWE from the observed snow depth distributions from ASO. In this study, we describe how the process of fusing model data with remote sensing retrievals is undertaken in the context of ASO along with estimates of uncertainty in the final SWE volume products. This work will likely be of interest to those working in snow hydrology, water resource management and the broader remote sensing community.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    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 (we) and 105 mm respectively, for both MOD10A1 and MYD10A1. Kappa coefficients are within 0.74 and 0.92 depending on the product and the variable. 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 datasets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decreases 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 gapfilling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band. We finally analyze the snow patterns for the atypical winter 2011-2012. Snow cover duration anomalies reveal a deficient snowpack on the Spanish side of the Pyrenees, which seems to have caused a drop in the national hydropower production.

  3. Weak snow layer detection based on relative differences in snow properties between layers

    NASA Astrophysics Data System (ADS)

    Monti, Fabiano; Schweizer, Jürg

    2013-04-01

    Snow stratigraphy information plays a prominent role in avalanche forecasting. Therefore, it is important how both manually collected and simulated snow profiles are interpreted in regard to snow stability. In the last few years several semi-quantitative methods have been developed to reduce the subjectivity of stability evaluation derived from snow profiles. One of them is the threshold sum approach (TSA), which identifies structural discontinuities related to mechanical stability within snow profiles by analyzing snow layers (i.e. grain size, type, hardness) and their interface properties (i.e. depth, difference in grain size and hardness). The threshold values identifying the structural properties were defined statistically and are optimized for the data sets they were based on. Since this approach relies entirely on absolute thresholds, problems arise, if properties (e.g. grain size estimation) are collected in a different way. Even though guidelines for collecting snow profiles are internationally defined, slight differences between observers of different avalanche services exist. The same problem arises when using this approach for simulated snow profiles. We propose a revised threshold sum approach for snow profile interpretation. Instead of using absolute values, we applied relative differences and values to the snow profiles, e.g. it was not considered how soft a snow layer is, but rather how soft it was compared to the weighted average value of the profile. This method allows the detection of potential weak layers within a snow profile but does not give an absolute estimation of their weakness. In other words, we give a probability that a particular layer is a weak layer. We tested this relative threshold approach (RTA) on a data set consisting of 128 manually recorded snow profiles, which were collected near the fracture line of or on slopes adjacent to skier-triggered avalanches. Results are encouraging since the RTA detected the weak layers related to

  4. Comparison of various remote sensing snow products in a distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Berezowski, Tomasz; Chormański, Jarosław; Batelaan, Okke

    2014-05-01

    With the development of remote sensing, more and more data series with spatially distributed snow cover become available. These data can be obtained for free, from many sources varying in spatial and temporal resolution, the length of the time series and the method of acquisition (VIS-NIR or microwave sensors). A popular use of remotely sensed snow distribution data is in hydrological modelling. However, a suitability test of different remote sensing snow products for hydrological models was so far not conducted. In this work, some of the most common remote sensing snow products (MOD10A1, IMS , GLOBSNOW and AMSR-E_DySno) are used as input data in the WetSpa distributed hydrological model. Each of the snow products has different properties and is based on different algorithms, which makes the analysis interesting and multidimensional. The area of research is the Biebrza River catchment - located in north-eastern Poland, comprising approximately 7000 km2. Biebrza is a natural river with a snow melt regime, making it very suitable for this kind of analysis. In total 6 modelling scenarios were conducted (4 with remote sensing data, 1 standard approach - temperature threshold for snow accumulation and melting, 1 based on snow data from meteorological stations). Each model was calibrated against discharge with the Shuffled Complex Evolution (SCE) algorithm. The calibration was repeated three times for each model to make sure that the global optimum was found. The calibration and validation periods were both 3 years long. The next stage was a comparison with the GLUE uncertainty analysis for each of the models, on a shorter, one-year period. The best model in terms of Nash-Sutcliffe efficiency and r2 was using the MOD10A1 data; however, the models using GLOBSNOW SWE and the standard approach received similar scores. In terms of the model bias the best results were obtained for the IMS and MOD10A1 data. Nevertheless, the lowest root mean square error was found for the

  5. New snow thermodynamics for the Louvain-la-Neuve Sea Ice Model (LIM)

    NASA Astrophysics Data System (ADS)

    Lecomte, Olivier; Fichefet, Thierry

    2010-05-01

    The Louvain-la-Neuve sea Ice Model (LIM) is a three-dimensional global model for sea ice dynamics and thermodynamics that has been specifically designed for climate studies and that is fully coupled with the oceanic general circulation model OPA on the modelling platform NEMO. This study presents and assesses the skills of a new one-dimensional snow model developed for the thermodynamic component of LIM, by comparison with the former model thermodynamics and observations. Snow is a key element in sea ice physics and in the interactions between sea ice and atmosphere. Owing to its low thermal conductivity and hight albedo, the snow cover is a very efficient insulator and it contributes directly and indirectly to the sea ice mass balance. Given the high variability and heterogeneity of the snow cover above sea ice, it is necessary to represent different types of snow, depending on their characteristics. A multilayer approach has been chosen for the model, with time varying temperature, density and thermal conductivity for each layer. Vertical heat diffusion, surface and internal melt, precipitations, snow ice formation and a parameterisation for melt pond albedo are included in the model. The model has been validated at Ice Station POLarstern (ISPOL) in the western Weddell Sea during summer and at Point Barrow (Alaska) during winter. The new model simulates better temperature profiles, with an amount of good correlations between modelled and observed profiles increasing from 12% to 42% for the 2-layer and 6-layer configurations, respectively. Conductive fluxes and temperatures are highly sensitive to albedo and ocean heat flux during summer, and to the thermal conductivity parameterisation during winter. Ice ablation rate is quite insensitive to snow thermal conductivity in summer because almost all the variability at the surface is absorbed by snow, making the temperature gradient in the ice relatively small and steady. Nevertheless, during winter, when the air

  6. Estimate of snow density knowing grain and share hardness

    NASA Astrophysics Data System (ADS)

    Valt, Mauro; Cianfarra, Paola; Cagnati, Anselmo; Chiambretti, Igor; Moro, Daniele

    2010-05-01

    Alpine avalanche warning services produces, weekly, snow profiles. Usually such profiles are made in horizontal snow fields, homogenously distributed by altitude and climatic micro-areas. Such profile allows grain shape, dimension and hardness (hand test) identification. Horizontal coring of each layer allows snow density identification. Such data allows the avalanche hazard evaluation and an estimation of the Snow Water Equivalent (SWE). Nevertheless the measurement of snow density, by coring, of very thin layers (less than 5 cm of thickness) is very difficult and are usually not measured by snow technicians. To bypass such problems a statistical analysis was performed to assign density values also to layers which cannot be measured. This system allows, knowing each layer thickness and its density, to correctly estimate SWE. This paper presents typical snow density values for snow hardness values and grain types for the Eastern Italian Alps. The study is based onto 2500 snow profiles with 17000 sampled snow layers from the Dolomites and Venetian Prealps (Eastern Alps). The table of typical snow density values for each grain type is used by YETI Software which elaborate snow profiles and automatically evaluate SWE. This method allows a better use of Avalanche Warning Services datasets for SWE estimation and local evaluation of SWE yearly trends for each snow field.

  7. LANDSAT-D investigations in snow hydrology

    NASA Technical Reports Server (NTRS)

    Dozier, J. (Principal Investigator)

    1982-01-01

    The sample LANDSAT-4 TM tape (7 bands) of NE Arkansas/Tennessee area was received and displayed. Snow reflectance in all 6 TM reflective bands, i.e. 1, 2, 3, 4, 5, and 7 was simulated, using Wiscombe and Warren's (1980) delta-Eddington model. Snow reflectance in bands 4, 5, and 7 appear sensitive to grain size. One of the objectives is to interpret surface optical grain size of snow, for spectral extension of albedo. While TM data of the study area are not received, simulation results are encouraging. It also appears that the TM filters resemble a "square-wave" closely enough to permit assuming a square-wave in calculations. Integrated band reflectance over the actual response functions was simulated, using sensor data supplied by Santa Barbara Research Center. Differences between integrating over the actual response functions and the equivalent square wave were negligible.

  8. The solar reflectance of a snow field

    NASA Technical Reports Server (NTRS)

    Choudhury, B. J.; Chang, A. T. C.

    1978-01-01

    The radiative transfer equation was solved using a modified Schuster-Schwartzschild approximation to obtain an expression for the solar reflectance of a snow field. The parameters in the reflectance formula are the single scattering albedo and the fraction of energy scattered in the backward direction. The single scattering albedo is calculated from the crystal size using a geometrical optics formula and the fraction of energy scattered in the backward direction is calculated from the Mie scattering theory. Numerical results for reflectance are obtained for visible and near infrared radiation for different snow conditions. Good agreement was found with the whole spectral range. The calculation also shows the observed effect of aging on the snow reflectance.

  9. Snow and glacier mapping with polarimetric SAR

    NASA Technical Reports Server (NTRS)

    Shi, Jiancheng; Dozier, Jeff; Rott, Helmut; Davis, Robert E.

    1991-01-01

    The objective of this study was to examine the capability of mapping snow and glaciers in alpine regions using synthetic aperture radar (SAR) imagery when topographic information is not available. The topographic effects on the received power for a resolution cell can be explained by the change in illumination area and incidence angle in a slant-rante representation of SAR imagery. The specific polarization signatures and phase difference between HH and VV components are relatively independent of the illuminated are, and the incidence angle has only a small effect on these parameters. They provide a suitable measurement data set for snow and glacier mapping in a high-relief area. The results show that the C-band images of the enhancement factor, the phase difference between HH and VV scattering components, and the normalized cross product of VV scattering elements provide the capability to discriminate among snow with different wetnesses, glaciers, and rocky regions.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  11. Nitrate postdeposition processes in Svalbard surface snow

    NASA Astrophysics Data System (ADS)

    Björkman, Mats P.; Vega, Carmen P.; Kühnel, Rafael; Spataro, Francesca; Ianniello, Antonietta; Esposito, Giulio; Kaiser, Jan; Marca, Alina; Hodson, Andy; Isaksson, Elisabeth; Roberts, Tjarda J.

    2014-11-01

    The snowpack acts as a sink for atmospheric reactive nitrogen, but several postdeposition pathways have been reported to alter the concentration and isotopic composition of snow nitrate with implications for atmospheric boundary layer chemistry, ice core records, and terrestrial ecology following snow melt. Careful daily sampling of surface snow during winter (11-15 February 2010) and springtime (9 April to 5 May 2010) near Ny-Ålesund, Svalbard reveals a complex pattern of processes within the snowpack. Dry deposition was found to dominate over postdeposition losses, with a net nitrate deposition rate of (0.6 ± 0.2) µmol m-2 d-1 to homogeneous surface snow. At Ny-Ålesund, such surface dry deposition can either solely result from long-range atmospheric transport of oxidized nitrogen or include the redeposition of photolytic/bacterial emission originating from deeper snow layers. Our data further confirm that polar basin air masses bring 15N-depleted nitrate to Svalbard, while high nitrate δ(18O) values only occur in connection with ozone-depleted air, and show that these signatures are reflected in the deposited nitrate. Such ozone-depleted air is attributed to active halogen chemistry in the air masses advected to the site. However, here the Ny-Ålesund surface snow was shown to have an active role in the halogen dynamics for this region, as indicated by declining bromide concentrations and increasing nitrate δ(18O), during high BrO (low-ozone) events. The data also indicate that the snowpack BrO-NOx cycling continued in postevent periods, when ambient ozone and BrO levels recovered.

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

    PubMed

    McLeod, K S

    2000-04-01

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

  13. Rainwater propagation through snow during artificial rain-on-snow events

    NASA Astrophysics Data System (ADS)

    Juras, Roman; Würzer, Sebastian; Pavlasek, Jiri; Jonas, Tobias

    2016-04-01

    The mechanism of rainwater propagation and runoff generation during rain-on-snow (ROS) is still insufficiently known. Understanding rainwater behaviour within the natural snowpack is crucial especially for forecasting of natural hazards like floods and wet snow avalanches. In this study, rainwater percolation through snow was investigated by sprinkling the naturally stable isotope deuterium on snow and conduct hydrograph separation on samples collected from the snowpack runoff. This allowed quantifying the contribution of rainwater and snowmelt in the water released from the snowpack. Four field experiments were carried out during the winter 2015 in the vicinity of Davos, Switzerland. A 1 by 1 m block of natural snow cover was isolated from the surrounding snowpack to enable a closed water balance. This experimental snow sample was exposed to artificial rainfall with 41 mm of deuterium enriched water. The sprinkling was run in four 30 minutes intervals separated by three 30 minutes non-sprinkling intervals. The runoff from the snow cube was monitored quantitatively by a snow lysimeter and output water was continuously sampled for the deuterium concentration. Further, snowpack properties were analysed before and after the sprinkling, including vertical profiles of snow density, liquid water content (LWC) and deuterium concentration. One experiment conducted on cold snowpack showed that rainwater propagated much faster as compared to three experiments conducted on ripe isothermal snowpack. Our data revealed that sprinkled rainwater initially pushed out pre-event LWC or mixed with meltwater created within the snowpack. Hydrographs from every single experiment showed four pronounced peaks, with the first peak always consisted of less rainwater than the following ones. The partial contribution of rainwater to the total runoff consistently increased over the course of the experiment, but never exceeded 63 %. Moreover, the development of preferential paths after the first

  14. LANDSAT-D investigations in snow hydrology

    NASA Technical Reports Server (NTRS)

    Dozier, J.

    1983-01-01

    Progress on the registration of TM data to digital topographic data; on comparison of TM, MSS and NOAA meteorological satellite data for snowcover mapping; and on radiative transfer models for atmospheric correction is reported. Some methods for analyzing spatial contiguity of snow within the snow covered area were selected. The methods are based on a two-channel version of the grey level co-occurence matrix, combined with edge detection derived from an algorithm for computing slopes and exposures from digital terrain data.

  15. Snow in Time for the Solstice

    NASA Technical Reports Server (NTRS)

    2004-01-01

    In mid-December, the weather in eastern North America cooperated with the calendar, and a wintry blast from the Arctic delivered freezing cold air, blustery winds, and snow just in time for the Winter Solstice on December 21' the Northern Hemisphere's longest night of the year and the official start of winter. This image was captured by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on December 20, 2004, the day after an Arctic storm dove down into the United States, bringing snow to New England (upper right of top image); the coastal mid-Atlantic, including Washington, D.C.; and the southern Appalachian Mountains in Tennessee and North Carolina. Over the Atlantic Ocean (image right), the fierce Arctic winds were raking the clouds into rows, like a gardener getting ready to plant the seeds of winter. The detailed close-up at the bottom of this image pair shows the cloud and snow patterns around Lake Ontario, illustrating the occurrence of 'lake-effect snow.' Areas in western upstate New York often get as much as fifteen feet or more of snow each year as cold air from Canada and the Arctic sweeps down over the relatively warm waters of Lakes Ontario and Erie. Cold air plus moisture from the lakes equals heavy snow. Since the wind generally blows from west to east, it is the 'downwind' cities like Buffalo and Rochester that receive the heaping helpings of snowfall, while cities on the upwind side of the lake, such as Toronto, receive much less. Unlike storms that begin with specific low-pressure systems in the Pacific Ocean and march eastward across the Pacific Northwest, the Rockies, the Great Plains, and sometimes the East, the lake-effect snows aren't tied to a specific atmospheric disturbance. They are more a function of geography, which means that the lakes can keep fueling snow storms for as long as they remain ice-free in early winter, as well as when they begin to thaw in late winter and early spring. Image courtesy the SeaWiFS Project, NASA

  16. Saline Snow Surfaces and Arctic Bromine Activation

    NASA Astrophysics Data System (ADS)

    Pratt, K. A.; Custard, K. D.; Shepson, P.; Douglas, T. A.; Pöhler, D.; General, S.; Zielcke, J.; Platt, U.; Carlsen, M. S.; Tanner, D.; Huey, L. G.; Stirm, B.

    2012-12-01

    Following polar sunrise, tropospheric ozone levels often decrease rapidly to near zero, concurrent with mercury depletion and deposition. Despite our increasing understanding of the spatial variability of BrO and possible mechanisms based on laboratory studies, important questions remain regarding the most efficient sources of and mechanisms for Arctic halogen activation, leading to tropospheric ozone depletion. Rapid sea ice decline in the Arctic is expected to influence halogen activation and corresponding ozone and mercury depletion events. Therefore, an improved understanding of halogen activation is necessary to predict future changes in atmospheric chemical composition. During the March-April 2012 BRomine, Ozone, and Mercury EXperiment (BROMEX) in Barrow, Alaska, outdoor chamber experiments with snow and ice samples were conducted. Ozone was added as the precursor oxidant, and the samples were investigated with and without ambient sunlight. Samples included first-year sea ice, brine icicles, several layers of snow above first-year sea ice, and seasonal snow above the tundra. Chemical ionization mass spectrometry was utilized to monitor Br2 production, and ion chromatography was utilized to measure the bromide, chloride, nitrate, and sulfate content of the melted snow/ice samples. Surprisingly, tundra snow and drifting snow above sea ice produced the most Br2, with no production resulting from sea ice and basal snow directly above sea ice, suggesting more efficient production from samples characterized by greater acidity and lower chloride/bromide ratios. In addition, Br2 was only observed in the presence of sunlight, indicating the role of snowpack photolysis and the hydroxyl radical in its production. The observed trends in Br2 production may also help explain observations of inland hotspots in measured BrO by aircraft-based nadir MAX-DOAS (Multi Axis-Differential Optical Absorption Spectroscopy) measurements, conducted during the same field campaign. The

  17. Isothermal densification and metamorphism of new snow

    NASA Astrophysics Data System (ADS)

    Schleef, S.; Loewe, H.; Schneebeli, M.

    2012-12-01

    The interplay between overburden stress and surface energy induced growth and coarsening is relevant for the densification of snow and porous ice at all densities. The densification of new snow is amenable to high precision experiments on short time scales. To this end we investigate the coupling of densification and metamorphism of new snow via time-lapse tomography experiments in the laboratory. We compare the evolution of density, strain, and specific surface area to previous long-time metamorphism experiments of snow and creep of polycrystalline ice. Experimental conditions are tailored to the requirements of time-lapse tomography and the measurements are conducted under nearly isothermal conditions at -20°C with a duration of two days. Images were taken with temporal resolution of a few hours which reveal precise details of the microstructure evolution due to sintering and compaction. We used different crystal shapes of natural new snow and snow samples obtained by sieving crystals grown in a snowmaker in the laboratory. To simulate the effect of overburden stress due to an overlying snowpack additional weights were applied to the sample. As expected we find an influence of the densification rate on initial density and overburden stress. We calculated strain rates and identified a transient creep behavior with a similar power law for all crystal types which substantially differs from the Andrade creep of polycrystalline ice. As a main result we found that the evolution of the specific surface area is independent of the density and follows a unique decay form for all measurements of each crystal type. The accuracy of the measurements allows to obtain a decay exponent for the SSA which is the same as previously obtained from the long-time regime during isothermal metamorphism after several months. Our preliminary results for all available types of new snow suggest a correlation between the initial density and SSA. We also find snow samples which coincide in

  18. The impact of atmospheric mineral aerosol deposition on the albedo of snow & sea ice: are snow and sea ice optical properties more important than mineral aerosol optical properties?

    NASA Astrophysics Data System (ADS)

    Lamare, M. L.; Lee-Taylor, J.; King, M. D.

    2016-01-01

    Knowledge of the albedo of polar regions is crucial for understanding a range of climatic processes that have an impact on a global scale. Light-absorbing impurities in atmospheric aerosols deposited on snow and sea ice by aeolian transport absorb solar radiation, reducing albedo. Here, the effects of five mineral aerosol deposits reducing the albedo of polar snow and sea ice are considered. Calculations employing a coupled atmospheric and snow/sea ice radiative-transfer model (TUV-snow) show that the effects of mineral aerosol deposits are strongly dependent on the snow or sea ice type rather than the differences between the aerosol optical characteristics. The change in albedo between five different mineral aerosol deposits with refractive indices varying by a factor of 2 reaches a maximum of 0.0788, whereas the difference between cold polar snow and melting sea ice is 0.8893 for the same mineral loading. Surprisingly, the thickness of a surface layer of snow or sea ice loaded with the same mass ratio of mineral dust has little effect on albedo. On the contrary, the surface albedo of two snowpacks of equal depth, containing the same mineral aerosol mass ratio, is similar, whether the loading is uniformly distributed or concentrated in multiple layers, regardless of their position or spacing. The impact of mineral aerosol deposits is much larger on melting sea ice than on other types of snow and sea ice. Therefore, the higher input of shortwave radiation during the summer melt cycle associated with melting sea ice accelerates the melt process.

  19. Microwave remote sensing of snow-covered sea ice

    NASA Technical Reports Server (NTRS)

    Borgeaud, M.; Kong, J. A.; Lin, F. C.

    1986-01-01

    Snow and ice are modeled as random media characterized by different dielectric constants and correlation functions. In order to model the brine inclusions of sea ice, the random medium is assumed to be anisotropic. A three-layer model is used to simulate a snow-covered ice field with the top layer being snow, the middle layer being ice, and the bottom layer being sea water. The theoretical results are illustrated for thick first-year sea ice covered by dry snow, and for artificial, thin first-year sea ice covered by wet snow as measured in controlled model tank experiments. The radar backscattering cross sections are seen to increase with snow cover for snow-covered sea ice owing to large volume scattering effects of snow.

  20. Application of LANDSAT imagery for snow mapping in Norway

    NASA Technical Reports Server (NTRS)

    Odegaard, H. (Principal Investigator); Ostrem, G.

    1977-01-01

    The author has identified the following significant results. It was shown that if the snow cover extent was determined from all four LANDSAT bands, there were significant differences in results. The MSS 4 gave the largest snow cover, but only slightly more than MSS 5, whereas MSS 6 and 7 gave the smallest snow area. A study was made to show that there was a relationship between the last date of snow fall and the area covered with snow, as determined from different bands. Imagery obtained shortly after a snow fall showed no significant difference in the snow-covered area when the four bans were compared, whereas, pronounced differences in the snow-covered area were found in images taken after a long period without precipitation.

  1. Patterns of Snow Leopard Site Use in an Increasingly Human-Dominated Landscape.

    PubMed

    Alexander, Justine Shanti; Gopalaswamy, Arjun M; Shi, Kun; Hughes, Joelene; Riordan, Philip

    2016-01-01

    Human population growth and concomitant increases in demand for natural resources pose threats to many wildlife populations. The landscapes used by the endangered snow leopard (Panthera uncia) and their prey is increasingly subject to major changes in land use. We aimed to assess the influence of 1) key human activities, as indicated by the presence of mining and livestock herding, and 2) the presence of a key prey species, the blue sheep (Pseudois nayaur), on probability of snow leopard site use across the landscape. In Gansu Province, China, we conducted sign surveys in 49 grid cells, each of 16 km2 in size, within a larger area of 3392 km2. We analysed the data using likelihood-based habitat occupancy models that explicitly account for imperfect detection and spatial auto-correlation between survey transect segments. The model-averaged estimate of snow leopard occupancy was high [0.75 (SE 0.10)], but only marginally higher than the naïve estimate (0.67). Snow leopard segment-level probability of detection, given occupancy on a 500 m spatial replicate, was also high [0.68 (SE 0.08)]. Prey presence was the main determinant of snow leopard site use, while human disturbances, in the form of mining and herding, had low predictive power. These findings suggest that snow leopards continue to use areas very close to such disturbances, as long as there is sufficient prey. Improved knowledge about the effect of human activity on large carnivores, which require large areas and intact prey populations, is urgently needed for conservation planning at the local and global levels. We highlight a number of methodological considerations that should guide the design of such research.

  2. Patterns of Snow Leopard Site Use in an Increasingly Human-Dominated Landscape

    PubMed Central

    2016-01-01

    Human population growth and concomitant increases in demand for natural resources pose threats to many wildlife populations. The landscapes used by the endangered snow leopard (Panthera uncia) and their prey is increasingly subject to major changes in land use. We aimed to assess the influence of 1) key human activities, as indicated by the presence of mining and livestock herding, and 2) the presence of a key prey species, the blue sheep (Pseudois nayaur), on probability of snow leopard site use across the landscape. In Gansu Province, China, we conducted sign surveys in 49 grid cells, each of 16 km2 in size, within a larger area of 3392 km2. We analysed the data using likelihood-based habitat occupancy models that explicitly account for imperfect detection and spatial auto-correlation between survey transect segments. The model-averaged estimate of snow leopard occupancy was high [0.75 (SE 0.10)], but only marginally higher than the naïve estimate (0.67). Snow leopard segment-level probability of detection, given occupancy on a 500 m spatial replicate, was also high [0.68 (SE 0.08)]. Prey presence was the main determinant of snow leopard site use, while human disturbances, in the form of mining and herding, had low predictive power. These findings suggest that snow leopards continue to use areas very close to such disturbances, as long as there is sufficient prey. Improved knowledge about the effect of human activity on large carnivores, which require large areas and intact prey populations, is urgently needed for conservation planning at the local and global levels. We highlight a number of methodological considerations that should guide the design of such research. PMID:27171203

  3. Developing Temperature Forcing for Snow and Ice Melt Runoff Models in High Mountain Regions

    NASA Astrophysics Data System (ADS)

    Barrett, A. P.; Armstrong, R. L.; Brodzik, M. J.; Khalsa, S. J. S.; Raup, B. H.; Rittger, K.

    2014-12-01

    Glaciers and snow cover are natural storage reservoirs that delay runoff on seasonal and longer time-scales. Glacier wastage and reduced snow packs will impact the volume and timing of runoff from mountain basins. Estimates of the contributions of glacier and snow melt to runoff in river systems draining mountain regions are critical for water resources planning. The USAID funded CHARIS project aims to estimate the contributions of glacier and snow melt to streamflow in the Ganges, Indus, Brahmaputra, Amu Darya and Syr Darya rivers. Most efforts to estimate glacier and snow melt contributions use temperature-index or degree-day approaches. Near-surface air temperature is a key forcing variable for such models. As with all mountain regions, meteorological stations are sparse and may have short records. Few stations exist at high elevations, with most stations located in valleys below the elevations of glaciers and seasonal snow cover. Reanalyses offer an alternative source of temperature data. However, reanalyses have coarse resolution and simplified topography, especially in the Himalaya. Surface fields are often biased. Any reanalysis product must be both bias-corrected and "downscaled" to the resolution of the melt-runoff model. We present a combined empirically-based bias-correction and downscaling procedure that uses near-surface air temperature from global atmospheric reanalyses to generate near-surface temperature forcing fields for the five river basins in the CHARIS study area. We focus on three 3rd Generation reanalyses; NASA MERRA, NCEP CFSR and ECMWF ERA-Interim. Evaluation of reanalysis temperature fields reveals differences between seasonal means of 500 hPa air temperatures for the three products are of the order of 1 °C, indicating choice of reanalysis can impact model results. The procedure accounts for these seasonal variations in biases of the reanalysis products and in lapse rates.

  4. Patterns of Snow Leopard Site Use in an Increasingly Human-Dominated Landscape.

    PubMed

    Alexander, Justine Shanti; Gopalaswamy, Arjun M; Shi, Kun; Hughes, Joelene; Riordan, Philip

    2016-01-01

    Human population growth and concomitant increases in demand for natural resources pose threats to many wildlife populations. The landscapes used by the endangered snow leopard (Panthera uncia) and their prey is increasingly subject to major changes in land use. We aimed to assess the influence of 1) key human activities, as indicated by the presence of mining and livestock herding, and 2) the presence of a key prey species, the blue sheep (Pseudois nayaur), on probability of snow leopard site use across the landscape. In Gansu Province, China, we conducted sign surveys in 49 grid cells, each of 16 km2 in size, within a larger area of 3392 km2. We analysed the data using likelihood-based habitat occupancy models that explicitly account for imperfect detection and spatial auto-correlation between survey transect segments. The model-averaged estimate of snow leopard occupancy was high [0.75 (SE 0.10)], but only marginally higher than the naïve estimate (0.67). Snow leopard segment-level probability of detection, given occupancy on a 500 m spatial replicate, was also high [0.68 (SE 0.08)]. Prey presence was the main determinant of snow leopard site use, while human disturbances, in the form of mining and herding, had low predictive power. These findings suggest that snow leopards continue to use areas very close to such disturbances, as long as there is sufficient prey. Improved knowledge about the effect of human activity on large carnivores, which require large areas and intact prey populations, is urgently needed for conservation planning at the local and global levels. We highlight a number of methodological considerations that should guide the design of such research. PMID:27171203

  5. Observed high-altitude warming and snow cover retreat over Tibet and the Himalayas enhanced by black carbon aerosols

    NASA Astrophysics Data System (ADS)

    Xu, Y.; Ramanathan, V.; Washington, W. M.

    2016-02-01

    Himalayan mountain glaciers and the snowpack over the Tibetan Plateau provide the headwater of several major rivers in Asia. In situ observations of snow cover extent since the 1960s suggest that the snowpack in the region have retreated significantly, accompanied by a surface warming of 2-2.5 °C observed over the peak altitudes (5000 m). Using a high-resolution ocean-atmosphere global climate model and an observationally constrained black carbon (BC) aerosol forcing, we attribute the observed altitude dependence of the warming trends as well as the spatial pattern of reductions in snow depths and snow cover extent to various anthropogenic factors. At the Tibetan Plateau altitudes, the increase in atmospheric CO2 concentration exerted a warming of 1.7 °C, BC 1.3 °C where as cooling aerosols cause about 0.7 °C cooling, bringing the net simulated warming consistent with the anomalously large observed warming. We therefore conclude that BC together with CO2 has contributed to the snow retreat trends. In particular, BC increase is the major factor in the strong elevation dependence of the observed surface warming. The atmospheric warming by BC as well as its surface darkening of snow is coupled with the positive snow albedo feedbacks to account for the disproportionately large role of BC in high-elevation regions. These findings reveal that BC impact needs to be properly accounted for in future regional climate projections, in particular on high-altitude cryosphere.

  6. On the sublimation of blowing snow and of snow in canopies

    NASA Astrophysics Data System (ADS)

    Taylor, P. A.; Simon, K.; Gordon, M.; Weng, W.

    2003-04-01

    Tests have been made within the Canadian Land Surface Scheme (CLASS) of various parameterizations of sublimation of blowing snow, and tested in the context of data from weather stations (Goose Bay and Resolute) in northern Canada. We will focus on parameterization schemes based on results obtained with the PIEKTUK model of blowing snow. In addition we will present preliminary results concerning the parameterization of sublimation of snow caught in tree canopies, using schemes similar to those for evaporation from wet canopies. This is considered to be a major factor in the water budgets of forested areas in northern Canada.

  7. Microwave emission from snow and glacier ice. [brightness temperature for snow fields

    NASA Technical Reports Server (NTRS)

    Chang, T. C.; Gloersen, P.; Schmugge, T.; Wilheit, T. T.; Zwally, H. J.

    1975-01-01

    The microwave brightness temperature for snow fields was studied assuming that the snow cover consists of closely packed scattering spheres which do not interact coherently. The Mie scattering theory was used to compute the volume scattering albedo. It is shown that in the wavelength range from 0.8 to 2.8 cm, most of the micro-radiation emanates from a layer 10 meters or less in thickness. It is concluded that it is possible to determine snow accumulation rates as well as near-surface temperature.

  8. Mineral dust impact on snow radiative properties in the European Alps combining ground, UAV, and satellite observations

    NASA Astrophysics Data System (ADS)

    Di Mauro, B.; Fava, F.; Ferrero, L.; Garzonio, R.; Baccolo, G.; Delmonte, B.; Colombo, R.

    2015-06-01

    In this paper, we evaluate the impact of mineral dust (MD) on snow radiative properties in the European Alps at ground, aerial, and satellite scale. A field survey was conducted to acquire snow spectral reflectance measurements with an Analytical Spectral Device (ASD) Field Spec Pro spectroradiometer. Surface snow samples were analyzed to determine the concentration and size distribution of MD in each sample. An overflight of a four-rotor Unmanned Aerial Vehicle (UAV) equipped with an RGB digital camera sensor was carried out during the field operations. Finally, Landsat 8 Operational Land Imager (OLI) data covering the central European Alps were analyzed. Observed reflectance evidenced that MD strongly reduced the spectral reflectance of snow, in particular, from 350 to 600 nm. Reflectance was compared with that simulated by parameterizing the Snow, Ice, and Aerosol Radiation radiative transfer model. We defined a novel spectral index, the Snow Darkening Index (SDI), that combines different wavelengths showing nonlinear correlation with measured MD concentrations (R2 = 0.87, root-mean-square error = 0.037). We also estimated a positive instantaneous radiative forcing that reaches values up to 153 W/m2 for the most concentrated sampling area. SDI maps at local scale were produced using the UAV data, while regional SDI maps were generated with OLI data. These maps show the spatial distribution of MD in snow after a natural deposition from the Saharan desert. Such postdepositional experimental data are fundamental for validating radiative transfer models and global climate models that simulate the impact of MD on snow radiative properties.

  9. The Snowtweets Project: communicating snow depth measurements from specialists and non-specialists via mobile communication technologies and social networks

    NASA Astrophysics Data System (ADS)

    King, J. M.; Cabrera, A. R.; Kelly, R. E.

    2009-12-01

    With the global decline of in situ snow measurements for hydrometeorological applications, there is an evolving need to find alternative ways to collect localized measurements of snow. The Snowtweets Project is an experiment aimed at providing a way for people interested in making snow measurements to quickly broadcast their measurements to the internet. The goal of the project is to encourage specialists and non-specialists alike to share simple snow depth measurements through widely available social networking sites. We are currently using the rapidly growing microblogging site Twitter (www.twitter.com) as a broadcasting vehicle to collect the snow depth measurements. Using 140 characters or less, users "tweet" their snow depth from their location through the Twitter website. This can be done from a computer or smartphone with internet access or through SMS messaging. The project has developed a Snowtweets web application that interrogates Twitter by parsing the 140 character string to obtain a geographic position and snow depth. GeoRSS and KML feeds are available to visualize the tweets in GoogleEarth or they can be viewed in our own visualiser, Snowbird. The emphasis is on achieving wide coverage to increase the number of microblogs. Furthermore, after some quality control filters, the project is able to combine the broadcast snow depths with traditional and objective satellite remote sensing-based observations or hydrologic model estimates. Our site, snowcore.uwaterloo.ca, was launched in July 2009 and is ready for the 2009-2010 northern hemisphere winter. We invite comments from experienced community participation projects to help improve our product.

  10. Polyolefin Blend Miscibility and Packing

    NASA Astrophysics Data System (ADS)

    Lohse, David J.

    2000-03-01

    Over the last several years data have been obtained on the miscibility of a wide range of polyolefins, covering some 200 blends involving about 75 different components. Despite the fact that there are no 'specific interactions' between these saturated hydrocarbon polymers, every kind of phase behavior has been observed, including UCST, LCST, and even negative values of the Flory interaction parameter. The key factor that determines how these polyolefins mix is the way that they pack. Very often, polyolefins mix regularly, that is, the interaction energy is determined by the cohesive energies of the pure components. When they do mix regularly, miscibility is achieved by a close match in the packing lengths of the components. Favorable irregular mixing appears to be the result of some specific packing arrangements. Recent data on the effects of pressure and temperature on the mixing of several polyolefin blends shows that the interaction energies depend only on density (and not on T and P independently) for UCST blends far from a critical point. As a result, the effects of pressure on miscibility can be predicted for such blends from knowledge of the effects of temperature on the interactions combined with PVT data. This remarkable simplification appears to be related to the van der Waals nature of the interactions between saturated hydrocarbons. Density dependence predicts the trends correctly for LCST polyolefin blends, but for these mixtures the interactions depend in a more complex way on T and P.

  11. Snow instability patterns at the scale of a small basin

    NASA Astrophysics Data System (ADS)

    Reuter, Benjamin; Richter, Bettina; Schweizer, Jürg

    2016-02-01

    Spatial and temporal variations are inherent characteristics of the alpine snow cover. Spatial heterogeneity is supposed to control the avalanche release probability by either hindering extensive crack propagation or facilitating localized failure initiation. Though a link between spatial snow instability variations and meteorological forcing is anticipated, it has not been quantitatively shown yet. We recorded snow penetration resistance profiles with the snow micropenetrometer at an alpine field site during five field campaigns in Eastern Switzerland. For each of about 150 vertical profiles sampled per day a failure initiation criterion and the critical crack length were calculated. For both criteria we analyzed their spatial structure and predicted snow instability in the basin by external drift kriging. The regression models were based on terrain and snow depth data. Slope aspect was the most prominent driver, but significant covariates varied depending on the situation. Residual autocorrelation ranges were shorter than the ones of the terrain suggesting external influences possibly due to meteorological forcing. To explore the causes of the instability patterns we repeated the geostatistical analysis with snow cover model output as covariate data for one case. The observed variations of snow instability were related to variations in slab layer properties which were caused by preferential deposition of precipitation and differences in energy input at the snow surface during the formation period of the slab layers. Our results suggest that 3-D snow cover modeling allows reproducing some of the snow property variations related to snow instability, but in future work all relevant micrometeorological spatial interactions should be considered.

  12. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  13. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  14. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  15. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  16. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  17. 24 CFR 3285.315 - Special snow load conditions.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Special snow load conditions. 3285... Special snow load conditions. (a) General. Foundations for homes designed for and located in areas with roof live loads greater than 40 psf must be designed by the manufacturer for the special snow...

  18. 24 CFR 3285.315 - Special snow load conditions.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 24 Housing and Urban Development 5 2012-04-01 2012-04-01 false Special snow load conditions. 3285... Special snow load conditions. (a) General. Foundations for homes designed for and located in areas with roof live loads greater than 40 psf must be designed by the manufacturer for the special snow...

  19. 24 CFR 3285.315 - Special snow load conditions.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 24 Housing and Urban Development 5 2014-04-01 2014-04-01 false Special snow load conditions. 3285... Special snow load conditions. (a) General. Foundations for homes designed for and located in areas with roof live loads greater than 40 psf must be designed by the manufacturer for the special snow...

  20. 24 CFR 3285.315 - Special snow load conditions.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 24 Housing and Urban Development 5 2013-04-01 2013-04-01 false Special snow load conditions. 3285... Special snow load conditions. (a) General. Foundations for homes designed for and located in areas with roof live loads greater than 40 psf must be designed by the manufacturer for the special snow...

  1. 24 CFR 3285.315 - Special snow load conditions.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 24 Housing and Urban Development 5 2011-04-01 2011-04-01 false Special snow load conditions. 3285... Special snow load conditions. (a) General. Foundations for homes designed for and located in areas with roof live loads greater than 40 psf must be designed by the manufacturer for the special snow...

  2. Analysis of ground-measured and passive-microwave-derived snow depth variations in midwinter across the Northern Great Plains

    USGS Publications Warehouse

    Chang, A.T.C.; Kelly, R.E.J.; Josberger, E.G.; Armstrong, R.L.; Foster, J.L.; Mognard, N.M.

    2005-01-01

    Accurate estimation of snow mass is important for the characterization of the hydrological cycle at different space and time scales. For effective water resources management, accurate estimation of snow storage is needed. Conventionally, snow depth is measured at a point, and in order to monitor snow depth in a temporally and spatially comprehensive manner, optimum interpolation of the points is undertaken. Yet the spatial representation of point measurements at a basin or on a larger distance scale is uncertain. Spaceborne scanning sensors, which cover a wide swath and can provide rapid repeat global coverage, are ideally suited to augment the global snow information. Satellite-borne passive microwave sensors have been used to derive snow depth (SD) with some success. The uncertainties in point SD and areal SD of natural snowpacks need to be understood if comparisons are to be made between a point SD measurement and satellite SD. In this paper three issues are addressed relating satellite derivation of SD and ground measurements of SD in the northern Great Plains of the United States from 1988 to 1997. First, it is shown that in comparing samples of ground-measured point SD data with satellite-derived 25 ?? 25 km2 pixels of SD from the Defense Meteorological Satellite Program Special Sensor Microwave Imager, there are significant differences in yearly SD values even though the accumulated datasets showed similarities. Second, from variogram analysis, the spatial variability of SD from each dataset was comparable. Third, for a sampling grid cell domain of 1?? ?? 1?? in the study terrain, 10 distributed snow depth measurements per cell are required to produce a sampling error of 5 cm or better. This study has important implications for validating SD derivations from satellite microwave observations. ?? 2005 American Meteorological Society.

  3. Trends of perchlorate in Antarctic snow: Implications for atmospheric production and preservation in snow

    NASA Astrophysics Data System (ADS)

    Jiang, Su; Cox, Thomas S.; Cole-Dai, Jihong; Peterson, Kari M.; Shi, Guitao

    2016-09-01

    Perchlorate concentration ranges from a few to a few hundred ng kg-1 in surface and shallow-depth snow at three Antarctic locations (South Pole, Dome A, and central West Antarctica), with significant spatial variations dependent on snow accumulation rate and/or atmospheric production rate. An obvious trend of increasing perchlorate since the 1970s is seen in South Pole snow. The trend is possibly the result of stratospheric chlorine levels elevated by anthropogenic chlorine emissions; this is supported by the timing of a similar trend at Dome A. Alternatively, the trend may stem from postdepositional loss of snowpack perchlorate or a combination of both. The possible impact of stratospheric chlorine is consistent with evidence of perchlorate production in the stratosphere. Additionally, perchlorate concentration appears to be directly affected by the springtime Antarctic ozone hole. Therefore, perchlorate variations in Antarctic snow are likely linked to stratospheric chemistry and ozone over the Antarctic.

  4. Pressure sensitive conductive rubber blends

    SciTech Connect

    Hassan, H.H. ); Abdel-Bary, E.M. ); El-Mansy, M.K.; Khodair, H.A. )

    1989-12-01

    Butadiene-acrylonitrile rubber (NBR) was blended with polychloroprene (CR) according to standard techniques. The blend was mixed with different concentrations of ZnO. The vulcanized sample was subjected to electrical conductivity ({sigma}) measurements while different values of static pressure were applied on the sample. It was found that samples containing 7.5 phr ZnO showed a reasonable pressure sensitive increase of {sigma}. Furthermore, the {sigma} vs pressure relationship of rubber blend mixed with different concentrations of Fast Extrusion Furnace black (FEF) was investigated. It was found that rubber vulcanizate containing 40 phr FEF resulted in a negative value of the pressure coefficient of conductivity {approx equal} {minus} 4.5 KPa{sup {minus}1}.

  5. The Life and Work of John Snow

    ERIC Educational Resources Information Center

    Melville, Wayne; Fazio, Xavier

    2007-01-01

    Due to his work to determine how cholera was spread in the 18th century, John Snow (1813-1858) has been hailed as the father of modern epidemiology. This article presents an inquiry model based on his life and work, which teachers can use to develop a series of biology lessons involving the history and nature of science. The lessons presented use…

  6. "Snow Soup" Students Take on Animation Creation

    ERIC Educational Resources Information Center

    Nikirk, Martin

    2009-01-01

    This article describes the process of producing "Snow Soup"--the 2009 Adobe Flash animation produced by the Computer Game Development and Animation seniors of Washington County Technical High School in Hagerstown, Maryland, for libraries in their area. In addition to the Flash product, the students produced two related Game Maker games, a printed…

  7. [Ocular injury by artificial snow spray].

    PubMed

    Ben-Nissan, D; Savir, H

    1990-12-01

    We treated the eyes of 12 children, aged 2.5-16 years, which were injured by artificial snow-spray during Israel's Independence Day festivities in 1987 and 1989. There was chemical damage to the conjunctiva and cornea which took 1-3 weeks to heal.

  8. LANDSAT-D investigations in snow hydrology

    NASA Technical Reports Server (NTRS)

    Dozier, J. (Principal Investigator)

    1982-01-01

    Snow reflectance in all 6 TM reflective bands, i.e., 1, 2, 3, 4, 5, and 7 was simulated using a delta-Eddington model. Snow reflectance in bands 4, 5, and 7 appear sensitive to grain size. It appears that the TM filters resemble a ""square-wave'' closely enough that a square-wave can be assumed in calculations. Integrated band reflectance over the actual response functions was calculated using sensor data supplied by Santa Barbara Research Center. Differences between integrating over the actual response functions and the equivalent square wave were negligible. Tables are given which show (1) sensor saturation radiance as a percentage of the solar constant, integrated through the band response function; (2) comparisons of integrations through the sensor response function with integrations over the equivalent square wave; and (3) calculations of integrated reflectance for snow over all reflective TM bands, and water and ice clouds with thickness of 1 mm water equivalent over TM bands 5 and 7. These calculations look encouraging for snow/cloud discrimination with TM bands 5 and 7.

  9. Estimating snow grain size using AVIRIS data

    NASA Technical Reports Server (NTRS)

    Nolin, Anne W.; Dozier, Jeff

    1993-01-01

    Estimates of snow grain size for the near-surface snow layer were calculated for the Tioga Pass region and Mammoth Mountain in the Sierra Nevada, California, using an inversion technique and data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The Tioga Pass and Mammoth Mountain single-band AVIRIS radiance images were atmospherically corrected to obtain surface reflectance. A discrete-ordinate model was used to calculate directional reflectance as a function of snowpack grain size for a wide range of snow grain radii. The resulting radius vs. reflectance curves were each fit using a nonlinear least squares technique which provided a means of transforming surface reflectance in each AVIRIS image to optically equivalent grain size on a per-pixel basis. The model results and grain size estimates derived from the AVIRIS data show that, for solar incidence angles between 0 and 30, the technique provides good estimates of grain size. This work provides the first quantitative estimates for grain size using data acquired from an airborne remote sensing instrument and is an important step in improving our ability to retrieve snow physical properties independent of field measurements.

  10. The Snow Day: One Tough Call.

    ERIC Educational Resources Information Center

    Dewar, Randy L.

    2003-01-01

    Describes eight common mistakes that beginning superintendents make when deciding whether the weather forecasts for snow and ice will make roads hazardous enough to cancel schools. For example, delaying an obvious decision to cancel schools until the morning or passing the responsibility to someone else. Describes several elements of an inclement…

  11. BOREAS HYD-4 Areal Snow Course Data

    NASA Technical Reports Server (NTRS)

    Hall, Forrest G. (Editor); Knapp, David E. (Editor); Metcalfe, John R.; Goodison, Barry E.; Walker, Anne; Smith, David E. (Technical Monitor)

    2000-01-01

    The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-4 team focused on collecting data during the 1994 winter focused field campaign (FFCW) to improve the understanding of winter processes within the boreal forest. Knowledge of snow cover and its variability in the boreal forest is fundamental if BOREAS is to achieve its goals of understanding the processes and states involved in the exchange of energy and water. The development and validation of remote sensing algorithms will provide the means to extend the knowledge of these processes and states from the local to the regional scale. A specific thrust of the hydrology research is the development and validation of snow cover algorithms from airborne passive microwave measurements. Airborne remote sensing data (gamma, passive microwave) were acquired along a series of flight lines established in the vicinity of the BOREAS study areas. Ground snow surveys were conducted along selected sections of these aircraft flight lines. These calibration segments were typically 10-20 km in length, and ground data were