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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. 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.

  5. Importance of snow to global precipitation

    NASA Astrophysics Data System (ADS)

    Field, P. R.; Heymsfield, A. J.

    2015-11-01

    Precipitation controls the availability of drinking water and viability of the land to support agriculture. Failure to accurately predict the location, magnitude, and frequency of precipitation impacts not only numerical weather forecasting but also climate modeling. It has been proposed that most rainfall events originate from ice that has melted to form rain. Here we use remote sensing from spaceborne cloud radar to quantify that idea. A new metric is constructed to quantify the fraction of rain events at the surface that are linked to snow melting at a higher altitude. CloudSat is used to show the global variation of the importance of snow in the precipitation process. In the tropics, subtropics, midlatitude and polar regions 0.3, 0.4, 0.8, and >0.9, respectively, of all precipitation events (>1 mm/d) are linked to the production of snow in clouds.

  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. Estimation of global snow cover using passive microwave data

    NASA Astrophysics Data System (ADS)

    Chang, Alfred T. C.; Kelly, Richard E.; Foster, James L.; Hall, Dorothy K.

    2003-04-01

    This paper describes an approach to estimate global snow cover using satellite passive microwave data. Snow cover is detected using the high frequency scattering signal from natural microwave radiation, which is observed by passive microwave instruments. Developed for the retrieval of global snow depth and snow water equivalent using Advanced Microwave Scanning Radiometer EOS (AMSR-E), the algorithm uses passive microwave radiation along with a microwave emission model and a snow grain growth model to estimate snow depth. The microwave emission model is based on the Dense Media Radiative Transfer (DMRT) model that uses the quasi-crystalline approach and sticky particle theory to predict the brightness temperature from a single layered snowpack. The grain growth model is a generic single layer model based on an empirical approach to predict snow grain size evolution with time. Gridding to the 25 km EASE-grid projection, a daily record of Special Sensor Microwave Imager (SSM/I) snow depth estimates was generated for December 2000 to March 2001. The estimates are tested using ground measurements from two continental-scale river catchments (Nelson River and the Ob River in Russia). This regional-scale testing of the algorithm shows that for passive microwave estimates, the average daily snow depth retrieval standard error between estimated and measured snow depths ranges from 0 cm to 40 cm of point observations. Bias characteristics are different for each basin. A fraction of the error is related to uncertainties about the grain growth initialization states and uncertainties about grain size changes through the winter season that directly affect the parameterization of the snow depth estimation in the DMRT model. Also, the algorithm does not include a correction for forest cover and this effect is clearly observed in the retrieval. Finally, error is also related to scale differences between in situ ground measurements and area-integrated satellite estimates. With AMSR

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

    NASA Technical Reports Server (NTRS)

    Walsh, John E.

    1991-01-01

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

  9. Simulation of black carbon in snow and effects on snow albedo in the Canadian Global Climate Model

    NASA Astrophysics Data System (ADS)

    Namazi, M.; von Salzen, K.; Cole, J. N.

    2013-12-01

    Black carbon (BC) aerosol forms through the incomplete combustion of fossil fuels, biofuel, and biomass. BC plays an essential role in the Earth's climate through absorption of solar radiation in the air and by snow. We developed a new physically based parameterization of BC concentration in snow by considering deposition rates of black carbon and snow, properties of the snow layer, and scavenging of BC through melting. The parameterization was implemented in the latest version of the Canadian Global Climate Model, CanAM4. Simulated results for BC snow mixing ratio are in good agreement with measurements reported in recent studies. Furthermore, we investigate effects of BC in snow on snow albedo and radiative forcing. We validate and compare our model results with other studies.

  10. 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

  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.

    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.

  13. 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

  14. Using Spaceborne Ku-Band Scatterometer for Global Snow Cover Monitoring

    NASA Technical Reports Server (NTRS)

    Nghiem, S. V.; Tsai, W.-Y.

    1999-01-01

    We demonstrate for the first time the utility of spaceborne Ku-band scatterometer for global snow cover monitoring. Satellite radar data were collected over the globe by the NASA Scatterometer (NSCAT) operated at 14 GHz on board the Japanese ADEOS spacecraft from September 1996 to June 1997, spanning the 1997 seasonal snow season. First, we present backscatter signature of dry and wet snow to facilitate the interpretation of NSCAT backscatter evolution over snow cover regions. Surface field experiments indicated that dry snow backscatter at Ku band is approximately 40 times stronger than that at C band. Thus, Ku-band scatterometer measurements are sensitive to snow cover, which is typically transparent to C-band scatterometer returns. Furthermore, Ku-band backscatter does not saturate for most of natural snow depths as compared to radar responses at 19 GHz and 37 GHz or higher frequencies which have more limited penetration depths into snow. Ku-band backscatter is also sensitive to wetness in snow, which is appropriate to detect early snow melt conditions. Using the snow backscatter characteristics, we investigate NSCAT backscatter evolution over global snow cover regions throughout the 1997 snow season. The results reveal detail delineations between different regional snow areas. We show the correlation of these delineations with the boundaries of different global snow classes defined by the U.S. Army Cold Regions Research and Engineering Laboratory snow classification system. Using in-situ snow depth data from the U.S. National Climatic Data Center, we show that Ku-band backscatter corresponds very well to the trend of snow melt while snow mapping products (U.S. Climate Prediction Center gridded snow charts) from visible sensors does not reflect the fast snow melt trend. To illustrate the practical application of global snow monitoring with spaceborne Ku-band scatterometer, we present NSCAT backscatter response corresponding to the snow event leading to the 1997

  15. 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

  16. 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

  17. 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

  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. Preliminary snow products from the Global Change Observation Mission (GCOM) AMSR2 instrument

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Preliminary snow products will be presented based on the Advanced Microwave Scanning Radiometer 2 (AMSR2) measurements. The AMSR2 instrument was launched on May 18, 2012 onboard the Global Change Observation Mission 1st - Water "SHIZUKU" (GCOM-W1) satellite. It has the heritage of microwave measurements of the Scanning Multi-channel Microwave Radiometer (SMMR), the Special Sensor Microwave Imager (SSM/I), and the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) for snow measurements in near all sky conditions. This study will describe the suite of AMSR2 snow cover detection, snow depth, and snow water equivalent (SWE) algorithms being developed for operational use by NOAA. The snow cover detection algorithm utilizes the brightness temperature based decision tree approach (Grody, 1991; Grody and Basist, 1996) with additional climatology tests as enhancements. The snow depth algorithm is based on the dynamic empirical approach (Kelly, 2009). The SWE is calculated by applying the snow density lookup table (Brown and Mote, 2009) for the global seasonal snow classification (Sturm et al. 1995) to the snow depth.

  20. 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+).

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    Snow accumulation is critical for water availability in the Northern Hemisphere, raising concern that global warming could have important impacts on natural and human systems in snow-dependent regions. Although regional hydrologic changes have been observed (for example, refs , , , ), the time of emergence of extreme changes in snow accumulation and melt remains a key unknown for assessing climate-change impacts. 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 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.

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

    PubMed

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

    2013-04-01

    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-21(st) 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

  4. Snow characterization at a global scale with passive microwave satellite observations

    NASA Astrophysics Data System (ADS)

    Cordisco, E.; Prigent, C.; Aires, F.

    2006-10-01

    The sensitivity of passive microwave satellite observations to snow characteristics is evaluated, between 19 and 85 GHz, for a winter season, for the Northern Hemisphere. The surface emissivities derived from the Special Sensor Microwave/Imager measurements are systematically compared with in situ snow measurements at 2784 stations, in North America and Eurasia. In addition, coincident satellite responses from active microwave sensors (ERS scatterometer) and visible observations (AVHRR) are also analyzed. Vegetation interferes with the signal that is received by the satellites. Snow emissivities also react to scattering by the snow grain growth that is related to the snow metamorphism during the winter. This phenomenon increases with frequency and is already very sensitive at 37 GHz. Passive microwaves at high frequency (85 GHz) are very sensitive to the presence of snow on the ground, even for very low snow depth. None of the tested satellite measurements is well correlated to the snow depth at a global scale, making snow depth retrieval from these observations very difficult on a global basis. The sensitivity of the satellite observations to snow characteristics depends on local conditions. To partly alleviate these difficulties, a neural network inversion scheme based on local statistics is developed to combine satellite observations, in situ measurements, and land surface model outputs. The combination of different wavelengths partly limits the ambiguities related to the individual sensitivity of each satellite observation to the various sources of variabilities. The final retrieval algorithm is compatible with an assimilation strategy that would better constrain the behavior of surface models. Finally, a clustering algorithm is applied to the suite of satellite observations and clearly shows a strong sensitivity to the snow characteristics and metamorphism during the winter. Characterization of the snowpack using satellite observation classification can yield

  5. 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.

  6. Satellites - New global observing techniques for ice and snow

    NASA Technical Reports Server (NTRS)

    Gloersen, P.; Salomonson, V. V.

    1975-01-01

    The possibility that the variation in areal extent of the snow cover may be related by empirical means to the average monthly run-off in a given watershed was demonstrated by comparing run-off records from the Indus River Basin in south-east Asia with a series of snow-cover maps obtained from Nimbus-3 and 4 imagery. Similar studies using the higher spatial resolution available with ERTS-1 imagery were carried out for the Wind River Mountains watersheds in Wyoming, where it was found that the empirical relationship varied with mean elevation of the watershed. In addition, digital image enhancement techniques are shown to be useful for identifying glacier features thought to be related to extent of snow cover, moraine characteristics, debris coverage, and the like. Finally, longer wavelength observations using sensors on board the Nimbus-5 satellite are shown to be useful for indicating crystal size distributions and onset of melting on glacier snow cover.

  7. 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.

  8. 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.

  9. 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…

  10. 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

  11. 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. PMID:27297721

  12. 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.

  13. 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.

  14. Beyond peak water storage? A global estimate of declining water storage in reservoirs and snow packs

    NASA Astrophysics Data System (ADS)

    Wisser, D.; Frolking, S.; Wada, Y.; Bierkens, M. F.

    2012-12-01

    Water storage is one of the primary mechanisms for coping with increasing variability of water supply and demand that can be expected with growing population and a changing climate. Man-made reservoirs can currently store about 15% of the global annual runoff. A similar amount of water is stored in one of the most important natural storage components - seasonal snow packs. The amount of water stored in each of those man-made and natural systems is roughly equivalent to the total annual anthropogenic water withdrawals. Storage in seasonal snow packs is declining as a result of climate-driven changes in snowfall and snowmelt. At the same time, reservoir storage is declining as a result of sedimentation and limited construction of new reservoirs. We use a global hydrological model, combined with a global data set of ~6000 large reservoirs to simulate changes in reservoir and snow pack water storage and analyze impacts of those changes on seasonal water availability using a set of scenarios for changing climate conditions. Reservoir sedimentation is simulated using global erosion and sedimentation data sets and validated with observed reservoir storage loss. Results indicate annual loss rates between 0.5 and 1.0% of the installed capacity for most reservoirs, outpacing the storage increases through the construction of new reservoirs for the last decades so that reservoir storage is declining globally. With most reservoirs being about 50 years old, these losses threaten the sustainability of reservoir operation and can pose significant challenges to water resources management. Similarly, seasonal snow storage is declining at about 0.5% per year for the last 20 years. Even without changes in the magnitude of total precipitation, there can be significant changes in basin hydrology if there are climate-driven changes in snowfall and snowmelt, potentially away from the period (summer) when demand for irrigation, water supply, or hydropower production is high. These shifts

  15. Theoretical Accuracy of Global Snow-Cover Mapping Using Satellite Data in the Earth Observing System (EOS) Era

    NASA Technical Reports Server (NTRS)

    Hall, D. K.; Foster, J. L.; Salomonson, V. V.; Klein, A. G.; Chien, J. Y. L.

    1998-01-01

    Following the launch of the Earth Observing System first morning (EOS-AM1) satellite, daily, global snow-cover mapping will be performed automatically at a spatial resolution of 500 m, cloud-cover permitting, using Moderate Resolution Imaging Spectroradiometer (MODIS) data. A technique to calculate theoretical accuracy of the MODIS-derived snow maps is presented. Field studies demonstrate that under cloud-free conditions when snow cover is complete, snow-mapping errors are small (less than 1%) in all land covers studied except forests where errors are greater and more variable. The theoretical accuracy of MODIS snow-cover maps is largely determined by percent forest cover north of the snowline. Using the 17-class International Geosphere-Biosphere Program (IGBP) land-cover maps of North America and Eurasia, the Northern Hemisphere is classified into seven land-cover classes and water. Snow-mapping errors estimated for each of the seven land-cover classes are extrapolated to the entire Northern Hemisphere for areas north of the average continental snowline for each month. Average monthly errors for the Northern Hemisphere are expected to range from 5 - 10%, and the theoretical accuracy of the future global snow-cover maps is 92% or higher. Error estimates will be refined after the first full year that MODIS data are available.

  16. 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

  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.

    2014-12-01

    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. Here we employ global sensitivity analysis to explore how different error types (i.e., bias, random errors), different error distributions, and different error magnitudes influence physically based simulations of four snow variables (snow water equivalent, ablation rates, snow disappearance, and sublimation). We use Sobol' global sensitivity analysis, which is typically used for model parameters, but adapted here for testing model sensitivity to co-existing errors in all forcings. We quantify the Utah Energy Balance model's sensitivity to forcing errors with 1 520 000 Monte Carlo simulations across four sites and four different scenarios. Model outputs were generally (1) more sensitive to forcing biases than random errors, (2) less sensitive to forcing error distributions, and (3) sensitive to different forcings depending on the relative magnitude of errors. For typical error magnitudes, precipitation bias was the most important factor for snow water equivalent, ablation rates, and snow disappearance timing, but other forcings had a significant impact depending on forcing error magnitudes. 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. Performance of and Uncertainties in the Global Precipitation Measurement (GPM) Microwave Imager Retrieval Algorithm for Falling Snow Estimates

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    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 early post-launch testing of retrieval algorithms for the 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. Throughout 2014, the at-launch GMI precipitation algorithms, based on a Bayesian framework, have been used with the new GPM data. 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. 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 values and also updated Bayesian channel weights for various surface types. We will evaluate the algorithm that was released to the public in July 2014 and has already shown that it can detect and estimate falling snow. Performance factors to be investigated include the ability to detect falling snow at various rates, causes of errors, and performance for various surface types. A major source of ground validation data will be the NOAA NMQ dataset. We will also provide qualitative information on known uncertainties and errors associated with both the satellite retrievals and the ground validation measurements. We will report on the analysis of our falling snow validation completed by the time of the AGU conference.

  19. 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.

  20. 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.

  1. 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).

  2. 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

  3. Global mountain snow and ice loss driven by dust and black carbon radiative forcing

    NASA Astrophysics Data System (ADS)

    Painter, T. H.

    2014-12-01

    Changes in mountain snow and glaciers have been our strongest indicators of the effects of changing climate. Earlier melt of snow and losses of glacier mass have perturbed regional water cycling, regional climate, and ecosystem dynamics, and contributed strongly to sea level rise. Recent studies however have revealed that in some regions, the reduction of albedo by light absorbing impurities in snow and ice such as dust and black carbon can be distinctly more powerful than regional warming at melting snow and ice. In the Rocky Mountains, dust deposition has increased 5 to 7 fold in the last 150 years, leading to ~3 weeks earlier loss of snow cover from forced melt. In absolute terms, in some years dust radiative forcing there can shorten snow cover duration by nearly two months. Remote sensing retrievals are beginning to reveal powerful dust and black carbon radiative forcing in the Hindu Kush through Himalaya. In light of recent ice cores that show pronounced increases in loading of dust and BC during the Anthropocene, these forcings may have contributed far more to glacier retreat than previously thought. For example, we have shown that the paradoxical end of the Little Ice Age in the European Alps beginning around 1850 (when glaciers began to retreat but temperatures continued to decline and precipitation was unchanged) very likely was driven by the massive increases in deposition to snow and ice of black carbon from industrialization in surrounding nations. A more robust understanding of changes in mountain snow and ice during the Anthropocene requires that we move past simplistic treatments (e.g. temperature-index modeling) to energy balance approaches that assess changes in the individual forcings such as the most powerful component for melt - net solar radiation. Remote sensing retrievals from imaging spectrometers and multispectral sensors are giving us more powerful insights into the time-space variation of snow and ice albedo.

  4. 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

  5. Scattering optics of snow.

    PubMed

    Kokhanovsky, Alexander A; Zege, Eleonora P

    2004-03-01

    Permanent snow and ice cover great portions of the Arctic and the Antarctic. It appears in winter months in northern parts of America, Asia, and Europe. Therefore snow is an important component of the hydrological cycle. Also, it is a main regulator of the seasonal variation of the planetary albedo. This seasonal change in albedo is determined largely by the snow cover. However, the presence of pollutants and the microstructure of snow (e.g., the size and shape of grains, which depend also on temperature and on the age of the snow) are also of importance in the variation of the snow's spectral albedo. The snow's spectral albedo and its bidirectional reflectance are studied theoretically. The albedo also determines the spectral absorptance of snow, which is of importance, e.g., in studies of the heating regime in snow. We investigate the influence of the nonspherical shape of grains and of close-packed effects on snow's reflectance in the visible and the near-infrared regions of the electromagnetic spectrum. The rate of the spectral transition from highly reflective snow in the visible to almost totally absorbing black snow in the infrared is governed largely by the snow's grain sizes and by the load of pollutants. Therefore both the characteristics of snow and its concentration of impurities can be monitored on a global scale by use of spectrometers and radiometers placed on orbiting satellites. PMID:15015542

  6. 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

  7. Snow and glacier change in koshi Basin Himalaya and its response to global warming

    NASA Astrophysics Data System (ADS)

    Gao, Y.; Yang, X.; Yao, T.; Yufeng, D.

    2010-12-01

    Recently, the argument that Himalayan glaciers will completely melt is rather controversial and the U.N.'s leading panel on climate change has apologized for misleading data published in a 2007 report that warned Himalayan glaciers could melt by 2035. Why the gradual melting of Himalayan glaciers makes most of the major media headlines? This is because Himalayan glacier is the headstream of major rivers in South Asia and Southeast Asia and more than 1/6 people live there. If mass of the glaciers melt or even disappear, people who rely on those rivers will be at risk. After this dispute, we need to realize that:”Although the melting rate still need to further study, the Himalayan glaciers are indeed melting. And in these areas, there are more uncertainties to affect water resource, such as snow fall, precipitation, regional temperature changes and so on”. Koshi Basin Himalaya, located in the boundary between China and Nepal, consist of three rivers i.e. Sun Koshi, Arun river (the headwaters of arun river in China called Pengqu) and Tamur. All of them converge to India Ganga River. The total area of Koshi Basin is about ~57,870 km2 and elevation ranges from 21 m (plain) to 8825m (Mountain glacier). This basin has the typical vertical zonation of Himalaya, so we choose it as the study area. Based on the snow cover data observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Terra spacecraft from 2000-2010, the spatial-temporal distribution and variation of snow cover over the koshi basin are statistical analyzed. Glacier changes are also detected from Landsat images in 2000, 2005 and 2010. It is found that snow cover areas are mainly concentrated in the Ridge of Himalaya Mountain. And there are more persistently snow covered areas and glaciers in the South Slope of Himalaya Mountain with aspect to the North Slope, although the mean elevation of the North Slope is higher than south slope. During the decade of 2000-2010, a slight decreasing

  8. A Distributed Snow Evolution Modeling System (SnowModel)

    NASA Astrophysics Data System (ADS)

    Liston, G. E.; Elder, K.

    2004-12-01

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

  9. Satellites: New global observing techniques for ice and snow. [using erts-1 and nimbus 5 satellite

    NASA Technical Reports Server (NTRS)

    Gloersen, P.; Salomonson, V. V.

    1974-01-01

    The relation of aereal extent of snow cover to the average monthly runoff in a given watershed was investigated by comparing runoff records with a series of snowcover maps. Studies using the high spatial resolution available with ERTS-1 imagery were carried out for the Wind River Mountains watersheds in Wyoming, where it was found that the empirical relationship varied with mean elevation of the watershed. In addition, digital image enhancement techniques are shown to be useful for identifying glacier features related to extent of snowcover, moraine characteristics, and debris average. Longer wavelength observations using sensors on board the Nimbus 5 Satellite are shown to be useful for indicating crystal size distributions and onset of melting on glacier snow cover.

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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 ...

  16. 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.

  17. Snow surface temperature, radiative forcing and snow depth as determinants of snow density

    NASA Astrophysics Data System (ADS)

    Kirchner, P. B.; Painter, T. H.; Skiles, M.; Deems, J. S.

    2014-12-01

    Watershed scale observations of snow water equivalence (SWE) are becoming increasingly important globally as the quantity and timing of snowmelt has become less predictable. In the Colorado River watershed, where dust deposition can hasten snowmelt by several weeks, the need for these observations is critical. While advances in measuring snow depth and albedo from the NASA Airborne Snow Observatory have greatly improved our ability to constrain snow depth and radiative forcing, we have yet to develop a method for remotely observing snow density, which is required for calculating SWE. We evaluate measured and modeled variables of snow- infrared surface temperature, radiative forcing and snow depth as predictors of snow density. We use 10 seasons of in situ measured snow surface temperature, cumulative modeled dust in snow radiative forcing, snow depth and manually measured snow density from locations in the Rocky Mountains of southwestern Colorado. We also use measured snow depth and SWE from the 2013 and 2014 water years, from 23-35 locations stratified by modeled downwelling short wave radiation, and evaluate them as predictors of snow density. Our analysis shows that daily mean snow surface temperature (R2 0.61, p = <0.001) and cumulative radiative forcing (R2 0.54, p = <0.001) individually have significant coefficients of determination whereas snow depth alone was not significant. Multiple regression with all three variables (R2 0.84, p = <0.001) was the best predictor of density. Furthermore, when snowpack conditions were isothermal at 0° C, the diurnal coefficient of variation, of measured hourly surface temperature, exhibited consistently high variance. In 2013 we found significant correlations between spatially distributed measurements of snow density (R2 0.33, p = <0.001) and modeled downwelling short wave radiation. However, in 2014 the correlation was very low, supporting our hypothesis that seasonal differences in dust driven radiative forcing are also

  18. 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.

  19. 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.

  20. MODIS Snow and Ice Production

    NASA Technical Reports Server (NTRS)

    Hall, Dorthoy K.; Hoser, Paul (Technical Monitor)

    2002-01-01

    Daily, global snow cover maps, and sea ice cover and sea ice surface temperature (IST) maps are derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), are available at no cost through the National Snow and Ice Data Center (NSIDC). Included on this CD-ROM are samples of the MODIS snow and ice products. In addition, an animation, done by the Scientific Visualization studio at Goddard Space Flight Center, is also included.

  1. 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…

  2. 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.

  3. 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.

  4. SnowClim: Snow climate monitoring for Europe

    NASA Astrophysics Data System (ADS)

    Bissolli, P.; Maier, U.

    2009-09-01

    Snow cover, particularly its depth and its frequency, is a very essential climate element. It influences the earth's surface radiation budget considerably due to its reflectivity properties and also it has large impact on economy and daily life (e.g. traffic, tourism). Although a lot of research and many national activities of snow monitoring have been done, there are very few products describing an integrated snow monitoring for whole Europe. In the light of a foreseen future Regional Climate Centre on Climate Monitoring (RCC-CM), the German Meteorological Service (Deutscher Wetterdienst, DWD) has established some first operational snow climate monitoring activities for the WMO Region VI (Europe and the Middle East). First selected key elements are the number of snowdays with a snow cover > 1 cm, the mean and the maximum snow depth per month. Results are presented in form of monthly and climatological maps, tables and diagrams of time series starting in 1981. Data presently are taken from observations at synoptical stations, received by the Global Telecommunication System. A first quality control based on threshold tests has been developed. The snow climate monitoring products are currently under further development. New evaluations will be carried out also on a daily data basis, additional satellite data, and also the quality control procedure will be extended. Some operational SnowClim products are available on the DWD web site: www.dwd.de/snowclim

  5. 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

  6. 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

  7. Challenges in simulation of snow microstructure and implications for remote sensing of snow mass

    NASA Astrophysics Data System (ADS)

    Sandells, M. J.; Essery, R.; Leppänen, L.; Lemmetyinen, J.; Rutter, N.

    2014-12-01

    One of the greatest challenges for global measurement of snow mass is quantification of the snow microstructure. Radiative transfer models are more sensitive to the snow structure metrics used than to snow depth, so microstructure must be well quantified in order to retrieve snow mass from satellite observations. Principles of physics have been used to simulate microstructure in many years of avalanche and climate research, although these have different accuracy requirements to remote sensing applications. Growth of snow crystals is dependent primarily on the snow temperature gradient, but also the temperature and density of the snow. Forced with the same meteorological data, different models simulate different snow temperatures. Even with the same grain growth assumptions, this leads to different rates of microstructure evolution. This must be taken into consideration if snow models are to be used to give the necessary parameters for retrieval of snow water equivalent. The JULES Investigation Model snow model (JIM) has a highly configurable structure that allows different layering assumptions to be used. It incorporates all major components from existing snow models, which enables the simulation of an ensemble of 1701 members. JIM was used to quantify the impact of different model parameterizations such as snow compaction and thermal conductivity on simulated microstructure (previously referred to as 'grain size') for each of four different grain size parameterizations from the Crocus, MOSES, SNICAR and SNTHERM models. The Helsinki University of Technology snow microwave emission model was then used to demonstrate the impact of different snow model assumptions on the simulation of microwave brightness temperature. This paper discusses potential snow mass retrieval errors due to uncertainties in snow parameters from snow evolution models, and how these may be mitigated through techniques such as data assimilation.

  8. Snow complexity representation and GCM climate

    NASA Astrophysics Data System (ADS)

    Dutra, Emanuel; Viterbo, Pedro; Miranda, Pedro M. A.; Balsamo, Gianpaolo

    2010-05-01

    Accurate simulations of the snow cover strongly impact on the quality of weather and climate predictions as the solar radiation absorption at land-atmosphere interface is modified by a factor up to 4 in response to snow presence (albedo effect). In Northern latitudes and Mountainous regions snow acts also as an important energy and water reservoir and a correct representation of snow mass and snow density is crucial for temperature predictions at all time-scales, with direct consequences for soil hydrology (thermal insulation effect). Three different complexity snow schemes implemented in the ECMWF land surface scheme HTESSEL are tested within the EC-EARTH framework. The snow schemes are: 1) OLD, the original HTESSEL single bulk layer snow scheme (same as in the ERA-40 and ERA-Interim reanalysis); 2) OPER, a new snow scheme in operations since September 2009, with a liquid water reservoir and revised formulations of snow density, fractional cover and snow albedo; and 3) ML3, a multi-layer version of OPER. All three snow schemes in HTESSEL are energy- and mass- balance models. The multi-layer snow scheme, ML3, was validated in offline mode covering several spatial and temporal scales: (i) site simulations for several observation locations from the Snow Models intercomparison project-2 (SnowMip2) and (ii) global simulations driven by the meteorological forcing from the Global Soil Wetness Project-2 (GSWP2) and the ECMWF ERA-Interim re-analysis. On point locations ML3 improve snow mass simulations, while on a global scale the impacts are residual pointing to the need of coupled atmosphere simulations. The 3 schemes are compared in the framework of the atmospheric model of EC-EARTH, based on the current seasonal forecast system of ECMWF. The standard configuration runs at T159 horizontal spectral resolution with 62 vertical levels. Three member ensembles of 30 years (1979-2008) simulations, with prescribed SSTs and sea ice, were performed for each of the snow schemes

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Respective influence of global pollution and volcanic eruptions on the past variations of the trace metals content of Antarctic snows since 1880's

    SciTech Connect

    Boutron, C.

    1980-01-01

    Forty-eight successive dated snow samples collected in central east Antarctica covering a continuous time sequence between 1880's and 1977 have been analysed for Na, Mg, K, Ca, Fe, Al, Mn, Pb, Cd, Cu, Zn, and Ag in ultraclean conditions. For all the elements, both the concentrations and the enrichment factors observed in 1977 are very close to the ones observed 100 years ago, then confirming that the influence of global pollution is actually negligible for these elements in the remote areas of the southern hemisphere. During the last 100 years, the variations of the enrichment factors of Pb and Zn are shown to parallel rather well those of the global volcanic activity, which suggests that the high atmospheric enrichments observed presently for these two metals are likely linked with volcanism. Between 1912 and 1916 (+ or -5 years), there is a very strong signal showing a definite peak for the concentrations of most of the elements, it could be linked with a major Antarctic volcanic eruption.

  14. 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.

  15. 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

  16. 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.

  17. City snow's physicochemical property affects snow disposal

    NASA Astrophysics Data System (ADS)

    Dovbysh, V. O.; Sharukha, A. V.; Evtin, P. V.; Vershinina, S. V.

    2015-10-01

    At the present day the industrial cities run into severe problem: fallen snow in a city it's a concentrator of pollutants and their quantity is constantly increasing by technology development. Pollution of snow increases because of emission of gases to the atmosphere by cars and factories. Large accumulation of polluted snow engenders many vexed ecological problems. That's why we need a new, non-polluting, scientifically based method of snow disposal. This paper investigates polluted snow's physicochemical property effects on snow melting. A distinctive feature of the ion accelerators with self-magnetically insulated diode is that there.

  18. 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.

  19. 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…

  20. 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,

  1. 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.

  2. Mapping "At Risk" Snow in the Pacific Northwest

    NASA Astrophysics Data System (ADS)

    Nolin, A. W.; Daly, C.

    2005-12-01

    One of the most visible and widely felt impacts of climate change is the change (mostly loss) of low elevation snow cover in the mid-latitudes. Snow cover that accumulates at temperatures close to the ice-water phase transition is at greater risk to climate warming than cold climate snow packs because it affects both precipitation phase and ablation rates. Changes in such climatologically sensitive snow packs can impact hydropower generation, reservoir storage, rain-on-snow floods, and winter recreation. Using a climatologically based global snow cover classification (Sturm et al., 1995) "at risk" snow is defined as lower elevation maritime and alpine snow classes. This original classification was produced globally at 0.5-degree resolution and used monthly means of temperature and precipitation as well as vegetation cover to map snow climates. In this work, the classification is updated for the Pacific Northwest region using fields of temperature and precipitation from PRISM as well as MODIS-derived global maps of vegetation cover. This new classification has significantly improved grid resolution (4 km x 4 km) and is able to clearly identify regions of ephemeral and lower elevation maritime and alpine snow that are thought to be at risk in a climate warming scenario. Results indicate that the economic impacts of this shift from snow- to rain-dominated winter precipitation that lower elevation ski areas in the region would experience significant negative impacts.

  3. 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

  4. 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

  5. The Winter Environment: Snow

    ERIC Educational Resources Information Center

    Murphy, James E.

    1974-01-01

    Discusses the structure and formation of snow crystals, outlines the history of snow removal, and describes techniques that can be used by students for studying snowflakes and relating their structure to the conditions under which they were formed. (JR)

  6. 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)

  7. Remote sensing of snow

    NASA Technical Reports Server (NTRS)

    Foster, J. L.; Hall, D. K.; Chang, A. T. C.

    1987-01-01

    The snow parameters affecting sensor responses at different wavelengths are discussed. The effects of snow depth and background radiation on gamma ray sensors and of crystal size, contaminants, snow depth, liquid water, and surface roughness on visible and near-infrared sensors are considered. The influence of temperature, crystal size, and liquid water on thermal infrared sensors and of liquid water, crystal size, water equivalent depth, stratification, snow surface roughness, density, temperature, and soil condition on microwave sensors are addressed.

  8. 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…

  9. 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.

  10. 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.

  11. Land-atmosphere coupling associated with snow cover

    NASA Astrophysics Data System (ADS)

    Dutra, Emanuel; Schär, Christoph; Viterbo, Pedro; Miranda, Pedro M. A.

    2011-08-01

    This study investigates the role of interannual snow cover variability in controlling the land-atmosphere coupling and its relation with near surface (T2M) and soil temperature (STL1). Global atmospheric simulations are carried out with the EC-EARTH climate model using climatological sea surface temperature and sea ice distributions. Snow climatology, derived from a control run (COUP), is used to replace snow evolution in the snow-uncoupled simulation (UNCOUP). The snow cover and depth variability explains almost 60% of the winter T2M variability in predominantly snow-covered regions. During spring the differences in interannual variability of T2M are more restricted to the snow line regions. The variability of soil temperature is also damped in UNCOUP. However, there are regions with a pronounced signal in STL1 with no counterpart in T2M. These regions are characterized by a significant interannual variability in snow depth, rather than snow cover (almost fully snow covered during winter). These results highlight the importance of both snow cover and snow depth in decoupling the soil temperature evolution from the overlying atmosphere.

  12. 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.

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

    ScienceCinema

    Barry, Roger G.

    2009-09-01

    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.

  14. 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.

  15. 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…

  16. 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…

  17. 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

  18. 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

  19. [Hyperspectral remote sensing estimation models for snow grain size].

    PubMed

    Wang, Jian-Geng; Feng, Xue-Zhi; Xiao, Peng-Feng; Liang, Ji; Zhang, Xue-Liang; Li, Hai-Xing; Li, Yun

    2013-01-01

    Snow grain size is a key parameter not only to affect the energy budget of the global or local region but also characterizing the status of snow vapor transport and temperature gradient. It is significant to monitor and estimate the snow grain size in large area for global or local climate change and water resource management. Recently, remote sensing technology has become a useful tool for snow grain size monitoring and estimating. In the present paper, the estimate models were built based on simulating the snow surface spectral reflectance curve in visible-infrared region and the sensitive bands and snow indices for snow grain size were selected. These models help estimate snow grain size by hyperspectral remote sensing. Through validating with ground true data, the results show that these models have higher explorative accuracy using 1 030, 1 260 nm and normalized difference snow index (460 and 1 030 nm). In addition, the correlation slopes of estimated and observed valves are 1.37, 0.61 and 0.62, respectively. R2 are 0.82, 0.86 and 0.93 and RMSE are 55.65, 50.83 and 35.91 microm, respectively. The result can provide a scientific basis for snow grain size monitoring and estimating. PMID:23586251

  20. 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.

  1. 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

  2. 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

  3. 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.

  4. "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…

  5. 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

  6. 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...

  7. "Snowing" Core in Earth?

    NASA Astrophysics Data System (ADS)

    Li, J.; Chen, B.; Cormier, V.; Gao, L.; Gubbins, D.; Kharlamova, S. A.; He, K.; Yang, H.

    2008-12-01

    As a planet cools, an initially molten core gradually solidifies. Solidification occurs at shallow depths in the form of "snow", if the liquidus temperature gradient of the core composition is smaller than the adiabatic temperature gradient in the core. Experimental data on the melting behavior of iron-sulfur binary system suggest that the cores of Mercury and Ganymede are probably snowing at the present time. The Martian core is predicted to snow in the future, provided that the sulfur content falls into the range of 10 to 14 weight percent. Is the Earth's core snowing? If so, what are the surface manifestations? If the Earth's core snowed in the past, how did it affect the formation of the solid inner core and the geodynamo? Here, we evaluate the likelihood and consequences of a snowing core throughout the Earth's history, on the basis of mineral physics data describing the melting behavior, equation-of-state, and thermodynamic properties of iron-rich alloys at high pressures. We discuss if snowing in the present-day Earth can reproduce the shallow gradients of compressional wave velocity above the inner-core boundary, and whether or not snowing in the early Earth may reconcile the apparent young age of the solid inner core with a long-lived geodynamo.

  8. GulfSnow Peach

    Technology Transfer Automated Retrieval System (TEKTRAN)

    GulfSnow peach is jointly released for grower trial by the U.S. Department of Agriculture, Agricultural Research Service (Byron, GA), Georgia Agricultural Experiment Station and Florida Agricultural Experiment Station. GulfSnow was previously tested as AP06-09W and originated from a cross of AP98-3...

  9. 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

  10. 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. PMID:26408452

  11. 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).

  12. 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...

  13. 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…

  14. ESA Globsnow - Hemispherical Snow Extent and Snow Water Equivalent Records for Climate Research Purposes

    NASA Astrophysics Data System (ADS)

    Luojus, K.; Pulliainen, J. T.; Takala, M.; Lemmetyinen, J.; Derksen, C.; Bojkov, B. R.

    2011-12-01

    The efforts of the European Space Agency (ESA) Data User Element (DUE) funded GlobSnow project has resulted in two new global records of snow parameters intended for climate research purposes. The datasets contains satellite-retrieved information on snow extent (SE) and snow water equivalent (SWE) extending 15 and 30 years respectively. The dataset on snow extent is based on optical data of Envisat AATSR and ERS-2 ATSR-2 sensors covering Northern Hemisphere between years 1995 to 2010. The record on snow water equivalent is based on satellite-based radiometer measurements (SMMR, SSM/I and AMSR-E) combined with ground-based weather station data, starting from 1979 and extending to present day. The GlobSnow SWE product is the first satellite-based dataset of snow water equivalent information on a daily basis at a hemispherical scale for 30+ years. In addition to the SE and SWE time-series, an operational near-real time (NRT) snow information service has been implemented. The current data, including the prototype products and the used validation data are available for all interested parties through the GlobSnow www-pages (http://www.globsnow.info). Extensive algorithm evaluation efforts were carried out for the candidate SWE and SE algorithms using ground truth data gathered from Canada, Scandinavia, Russia and the Alps. The acquired evaluation results enabled the selection of the final algorithms to be utilized for the GlobSnow products. The SWE product is derived using an assimilation algorithm by FMI and the SE product is a combination of NR and SYKE developed algorithms utilizing optical data. Both algorithms showed enhanced estimation characteristics when compared with currently available existing products. Prototype SE and SWE products were released for user evaluation during November 2009 covering the years 2003-2008 for SWE and 2004-2006 for SE. The final SWE product covers the Northern Hemisphere, spanning 1979 - 2010. The SE product covers the Northern

  15. Evaluation of MODIS snow cover products in the Upper Rio Grande River Basin

    NASA Astrophysics Data System (ADS)

    Klein, A.; Barnett, A.; Lee, S.

    2003-04-01

    Snow cover is an important water resource for the Upper Rio Grande River Basin of Colorado and New Mexico. Global daily snow cover maps currently are produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data and are freely distributed by the National Snow and Ice Data Center (NSIDC). The classification accuracy of these daily snow maps was assessed by comparing MODIS snow cover maps with operational snow cover maps produced by the National Operational Hydrologic Remote Sensing Center (NOHRSC) and against in situ SNOTEL (Snowpack Telemetry) measurements for the 2000-2001 snow season. For days during the 2000-2001 snow season where both MODIS and NOHRSC snow maps exist the overall snow classification agreement is 86 percent. Comparisons of both snow maps against in situ SNOTEL measurements for the same days indicate snow mapping accuracies of 94 percent and 76 percent for MODIS and NOHRSC, respectively. A lengthened comparison of MODIS against SNOTEL measurements which increases the number of comparisons for snow-free conditions indicates a slightly lower overall classification accuracy of 88 percent. In addition, assessment of the usefulness of these two snow cover products as inputs into the Snowmelt Runoff Model (SRM) for streamflow prediction in the Upper Rio Grande River Basin is ongoing.

  16. 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

  17. 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

  18. 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).

  19. 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

  20. 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).

  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. A Prototype MODI- SSM/I Snow Mapping Algorithm

    NASA Technical Reports Server (NTRS)

    Tait, Andrew B.; Barton, Jonathan S.; Hall, Dorothy K.

    1999-01-01

    Data in the wavelength range 0.545 - 1.652 microns from the Moderate Resolution Imaging Spectroradiometer (MODIS), to be launched aboard the Earth Observing System (EOS) Terra in the fall of 1999, will be used to map daily global snow cover at 500m resolution. However, during darkness, or when the satellite's view of the surface is obscured by cloud, snow cover cannot be mapped using MODIS data. We show that during these conditions, it is possible to supplement the MODIS product by mapping the snow cover using passive microwave data from the Special Sensor Microwave Imager (SSM/I), albeit with much poorer resolution. For a 7-day time period in March 1999, a prototype MODIS snow-cover product was compared with a prototype MODIS-SSM/I product for the same area in the mid-western United States. The combined MODIS-SSM/I product mapped 9% more snow cover than the MODIS-only product.

  3. 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., 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

  4. Comparison of Snow Mass Estimates from a Prototype Passive Microwave Snow Algorithm, a Revised Algorithm and a Snow Depth Climatology

    NASA Technical Reports Server (NTRS)

    Foster, J. L.; Chang, A. T. C.; Hall, D. K.

    1997-01-01

    While it is recognized that no single snow algorithm is capable of producing accurate global estimates of snow depth, for research purposes it is useful to test an algorithm's performance in different climatic areas in order to see how it responds to a variety of snow conditions. This study is one of the first to develop separate passive microwave snow algorithms for North America and Eurasia by including parameters that consider the effects of variations in forest cover and crystal size on microwave brightness temperature. A new algorithm (GSFC 1996) is compared to a prototype algorithm (Chang et al., 1987) and to a snow depth climatology (SDC), which for this study is considered to be a standard reference or baseline. It is shown that the GSFC 1996 algorithm compares much more favorably to the SDC than does the Chang et al. (1987) algorithm. For example, in North America in February there is a 15% difference between the GSFC 198-96 Algorithm and the SDC, but with the Chang et al. (1987) algorithm the difference is greater than 50%. In Eurasia, also in February, there is only a 1.3% difference between the GSFC 1996 algorithm and the SDC, whereas with the Chang et al. (1987) algorithm the difference is about 20%. As expected, differences tend to be less when the snow cover extent is greater, particularly for Eurasia. The GSFC 1996 algorithm performs better in North America in each month than dose the Chang et al. (1987) algorithm. This is also the case in Eurasia, except in April and May when the Chang et al.(1987) algorithms is in closer accord to the SDC than is GSFC 1996 algorithm.

  5. Potential for Using Satellite Lidar for Seasonal Snow Depth Estimation

    NASA Astrophysics Data System (ADS)

    Jasinski, M. F.; Stoll, J.; Harding, D. J.; Fassnacht, S. R.; Carabajal, C. C.; Markus, T.

    2013-12-01

    This study evaluates the potential for estimating snow depth in complex mountainous terrain using high resolution satellite lidar. For over three decades, satellite remote sensing of snow depth and water equivalent has relied primarily on passive microwave sensors with an approximately 25 km footprint. While successfully employed in many global water balance analyses, their large footprints, necessary to capture the natural emission of the surface, are too coarse to define the spatial heterogeneity of mountain watershed-scale snow due to variable topography and vegetation. In this study, the capability of satellite lidar altimetry for estimating snow depth was evaluated primarily using surface elevations observed by the Geoscience Laser Altimeter Sensor (GLAS) flown on board the Ice, Cloud, and land Elevation Satellite from 2003-2009, with a footprint size of ~70m. The evaluation includes the analysis of GLAS waveforms at near-repeat locations during snow-off and snow on conditions, using several snow depth estimation approaches, focusing on the Uinta Mountains of NE Utah. Also presented is the concept for the ICESat-2 Advanced Topographic Laser Altimeter System (ATLAS), currently set to launch in July 2016, and its potential capability for characterizing snow depth. The opportunity for partnering through NASA's Early Adopter Program using prototype aircraft observations also is presented.

  6. 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

  7. 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.

  8. 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...

  9. 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. PMID:24951969

  10. 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.

  11. Principles of Snow Hydrology

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Snow hydrology is a specialized field of hydrology that is of particular importance for high latitudes and mountainous terrain. In many parts of the world, river and groundwater supplies for domestic, irrigation, industrial and ecosystem needs are generated from snowmelt, and an in-depth understand...

  12. Improving WEPP snow simulation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Snow simulation is essential to reliable prediction of runoff and erosion, particularly in high-latitude areas in the northern tier of states and forested watersheds at high elevations. The Water Erosion Prediction Project (WEPP) model is one of a few including a component for winter hydrology simul...

  13. Producing Snow Extent and Snow Water Equivalent Information for Climate Research Purposes - ESA DUE Globsnow Effort

    NASA Astrophysics Data System (ADS)

    Luojus, Kari; Pulliainen, Jouni; Rott, Helmut; Nagler, Thomas; Solberg, Rune; Wiesmann, Andreas; Derksen, Chris; Metsämäki, Sari; Malnes, Eirik; Bojkov, Bojan

    2010-05-01

    The European Space Agency (ESA) Data User Element (DUE) funded GlobSnow project aims at creating a global database of snow parameters for climate research purposes. The main objective is to create a long term dataset on two essential snow parameters. The project will provide information concerning the areal extent of snow (SE) on a global scale and snow water equivalent (SWE) for the Northern Hemisphere. Both products will include the end product derived from the satellite data along with accuracy information for each snow parameter. The temporal span of the SE product will be 15 years and the span for the SWE product will be 30 years. A key improvement of the snow products, when compared with the currently available data sets, will be the inclusion of a statistically derived accuracy estimate accompanying each SE or SWE estimate (on a pixel level). In addition to the SE and SWE time-series, an operational near-real time (NRT) snow information service will be implemented. The service will provide daily snow maps for hydrological, meteorological, and climate research purposes. The snow products will be based on data acquired from optical and passive microwave-based spaceborne sensors combined with ground-based weather station observations. The work was initiated in November 2008, and is being coordinated by the Finnish Meteorological Institute (FMI). Other project partners involved are NR (Norwegian Computing Centre), ENVEO IT GmbH, GAMMA Remote Sensing AG, Finnish Environment Institute (SYKE), Environment Canada (EC) and Northern Research Institute (Norut). Extensive algorithm evaluation efforts were carried out for the candidate SWE and SE algorithms during 2009 using ground truth data gathered from Canada, Scandinavia, Russia and the Alps. The acquired evaluation results have enabled the selection of the algorithms to be utilized for the GlobSnow SE and SWE products. The SWE product is derived using the FMI Algorithm and the SE product is a combination of NR and

  14. Recent increase in snow-melt area in the Greenland Ice sheet as an indicator of the effect of reduced surface albedo by snow impurities

    NASA Astrophysics Data System (ADS)

    Rikiishi, K.

    2008-12-01

    Recent rapid decline of cryosphere including mountain glaciers, sea ice, and seasonal snow cover tends to be associated with global warming. However, positive feedback is likely to operate between the cryosphere and air temperature, and then it may not be so simple to decide the cause-and-effect relation between them. The theory of heat budget for snow surface tells us that sensible heat transfer from the air to the snow by atmospheric warming by 1°C is about 10 W/m2, which is comparable with heat supply introduced by reduction of the snow surface albedo by only 0.02. Since snow impurities such as black carbon and soil- origin dusts have been accumulated every year on the snow surface in snow-melting season, it is very important to examine whether the snow-melting on the ice sheets, mountain glaciers, and sea ice is caused by global warming or by accumulated snow impurities originated from atmospheric pollutants. In this paper we analyze the dataset of snow-melt area in the Greenland ice sheet for the years 1979 - 2007 (available from the National Snow and Ice Data Center), which is reduced empirically from the satellite micro-wave observations by SMMR and SMM/I. It has been found that, seasonally, the snow-melt area extends most significantly from the second half of June to the first half of July when the sun is highest and sunshine duration is longest, while it doesn't extend any more from the second half of July to the first half of August when the air temperature is highest. This fact may imply that sensible heat required for snow-melting comes from the solar radiation rather than from the atmosphere. As for the interannual variation of snow-melt area, on the other hand, we have found that the growth rate of snow-melt area gradually increases from July, to August, and to the first half of September as the impurities come out to and accumulated at the snow surface. However, the growth rate is almost zero in June and the second half of September when fresh snow

  15. '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.

  16. 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

  17. 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.

  18. 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.

  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. '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.

  1. 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

  2. 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

  3. 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.

  4. 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

  5. [Research on hyperspectral remote sensing in monitoring snow contamination concentration].

    PubMed

    Tang, Xu-guang; Liu, Dian-wei; Zhang, Bai; Du, Jia; Lei, Xiao-chun; Zeng, Li-hong; Wang, Yuan-dong; Song, Kai-shan

    2011-05-01

    Contaminants in the snow can be used to reflect regional and global environmental pollution caused by human activities. However, so far, the research on space-time monitoring of snow contamination concentration for a wide range or areas difficult for human to reach is very scarce. In the present paper, based on the simulated atmospheric deposition experiments, the spectroscopy technique method was applied to analyze the effect of different contamination concentration on the snow reflectance spectra. Then an evaluation of snow contamination concentration (SCC) retrieval methods was conducted using characteristic index method (SDI), principal component analysis (PCA), BP neural network and RBF neural network method, and the estimate effects of four methods were compared. The results showed that the neural network model combined with hyperspectral remote sensing data could estimate the SCC well. PMID:21800591

  6. 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

  7. Modeling and Prediction of Snow Cover over the Tibetan Plateau

    NASA Astrophysics Data System (ADS)

    Jin, J.; Zhuo, H.; Liu, Y.; Wu, G.

    2012-12-01

    Snow-atmosphere interactions are very important to weather and climate predictions for the Tibetan Plateau (TP) and its downwind regions in eastern Asia. In this study, the next generation Weather Research and Forecasting (WRF) model coupled with the Community Land Model (CLM) version 3.5 was used to improve simulations of regional-scale snow processes and related cold-season hydroclimate for the TP. CLM physically describes mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. Interactions among the snow, soil, and vegetation are characterized by the CLM mass and energy equations. A sophisticated surface albedo scheme is adopted to improve simulations of the surface energy balance. The introduction of a maximum of ten sub-cells within each CLM cell improves the accuracy of land surface characterization and the water and energy fluxes between the land surface and the atmosphere. The first set of simulations was carried out with the coupled WRF-CLM forced with the Climate Forecast System (CFS) Reanalysis data, and these simulations were evaluated against snow cover, temperature, and precipitation observations from satellites and meteorological stations located in the TP. Our model evaluation showed that WRF-CLM was able to reasonably reproduce the observed data. Snow cover on the TP was then predicted with a 10 km resolution WRF-CLM driven with the global forecasts made by the CFS version 2. Comparing these high-resolution snow predictions with observations and the simulations that were forced with the Reanalysis data demonstrated that the spatial distribution of snow cover was realistically predicted at both seasonal and interannual scales. The detailed physical processes that control snow forecasts for the TP were also examined, and the model uncertainties were quantified. From these modeling results, we can clearly see that the coupled WRF-CLM provides an important tool for weather and climate forecasts for the

  8. '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.

  9. Quantifying Snow Transport Using Snow Fences and Sonic Sensors

    NASA Astrophysics Data System (ADS)

    Sturm, M.; Berezovskaya, S.; Hiemstra, C.; Gelvin, A.

    2010-12-01

    Accurate assessment of snow transport (T) during wind events is a prerequisite to reliable estimation of snow loads on infrastructure and prediction of avalanche danger in the mountains. It is also a critical term in the winter water balance, affecting snow sublimation. To assess T we constructed two snow fences in northern Alaska and used an existing municipal fence near Barrow, Alaska to trap the wind-blown flux of snow. On the leeward side of each fence we installed a line of SR50 sonic ranging sensors that could be used to track the increase in snow height with time. We also installed web-cameras to monitor changes in drift shape. Periodic snow surface elevation surveys using a DGPS system provided more detailed drift profiles during the winter. Wind speed and direction were monitored near the fences. The sonic sensor results have been combined with the DGPS surveys to produce a time series of drift cross-section from which the flux has been computed. We have related this flux to individual wind events in an effort to identify the optimal conditions for blowing snow transport and to derive an empirical expression for T from weather measurements.

  10. Snow Cover Changes over Northern Eurasia from in Situ Observations

    NASA Astrophysics Data System (ADS)

    Bulygina, O. N.; Razuvaev, V. N.; Groisman, P. Ya; Korshunova, N. N.

    2012-04-01

    . This approach provides a more uniform spatial field for averaging. Results. In the recent decades, the Russian territory has experienced an increase in snow depth, both winter average and maximum snow depths, against the background of global temperature rise and sea ice reduction in the Arctic Ocean. Generalized regional characteristics of maximum snow water equivalent show an increase in water supply in the north of the East European Plain (by 4.5%/10yr in the west and by 6%/10yr in the east). This characteristic also increases in the southern forest zone of West Siberia and in the Far East (by approximately 6%/10yr ) and in central Eastern Siberia (by 3.4%/10yr). Only in the southwest of the East European Plain, we found a tendency for decrease in water supply (by -6.4%/10yr) along the forested snow courses. Among the two competing factors that can cause a systematic change in the maximum and mean snowpack density over Northern Eurasia, increase in maximum snow depth and a decrease in number of days with snow cover, the second factor (that causes a decrease in snow density) appeared to be more significant during the past 43 years.

  11. Microtomography of macroscopic snow samples

    NASA Astrophysics Data System (ADS)

    Matzl, M.; Schneebeli, M.; Steinfeld, D.; Steiner, S.; Heggli, M.

    2010-12-01

    During the last 10 years X-ray microtomography (micro-CT) has proved to be the first successful method to measure the true three-dimensional (3-D) structure of snow on the ground. Micro-CT is used to reconstruct 3-D microstructures as a source for numerical simulations, to conduct long-term observations of metamorphism or the behavior of snow under stress and to derive macroscopic parameters describing the microstructure of snow like specific surface area or density. However, micro-CT was confined to small samples with a typically evaluated size of 5 x 5 x 5 mm3. One reason for the small size was the limited computational power, the other the sample preparation. Based on the replica method for 3-D micro-CT samples introduced by Heggli et al. (2009), we are now able to visualize snow samples up to 70 mm height, and about 10 mm diameter, with a resolution of 10 μm. Because inclusion of small air bubbles during the casting process can not be avoided, we make two scans, one before and one after sublimation, the two scans are then registered and subtracted. After image segmentation and morphological image processing the replica can be analysed in the same way as direct snow measurements. Based on such samples, we imaged highly fragile snow samples, like new snow, buried surface hoar and other weak layers. The samples show a fascinating new image of how complex snow layers are. Most samples show strong density gradients within a structurally similar layer. We think that this technique will improve our understanding of snow metamorphism and snow properties. Heggli, M.; Frei, E.; Schneebeli, M., 2009: Instruments and Methods. Snow Replica method for three-dimensional X-ray microtomographic imaging. J. Glaciol. 55, 192: 631-639.

  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. Parameterizations for Narrowband and Broadband Albedo of Pure Snow, and Snow Containing Mineral Dust and Black Carbon

    NASA Astrophysics Data System (ADS)

    Dang, C.; Brandt, R.; Warren, S. G.

    2014-12-01

    The reduction of snow spectral albedo by black carbon(BC) and mineral dust, both alone and in combination, is computed using radiative-transfer modeling. Several size distributions of BC are examined; one is chosen to represent ambient soot. Many measurements of absorption spectra of mineral dust are critically reviewed as a basis for specifying dust properties for modeling. Two standard solar spectra are used: clear sky with the global average(insolation-weighted) solar zenith angle ~50 degrees, and the spectrum under an overcast cloud of optical thickness 11. The primary variables for the parameterizations are the radiatively-effective snow grain radius (r) and BC mass mixing ratio (C) in snow (and/or dust mixing ratio). A change of solar zenith angle can be mimicked by changing the snow grain radius. Results are shown for all mass-mixing ratios (MMR) covering the full range from pure snow to pure soot and pure dust, and for snow grain radii from 5 to 2500 mm, to cover the range of possible grain sizes on planetary surfaces. To keep the parameterizations simple, only opaque homogeneous snowpacks are considered. Parameterizations are developed for three broad bands used in GCMs as well as several narrower bands; quadratic or cubic functions of log r and log C are generally adequate. The parameterizations are valid up to BC content of 10 ppm, which is needed for highly polluted snow, for example as found in northeast China. A given MMR of BC causes greater albedo reduction in coarse-grained snow; BC and r can be combined into a single variable to compute the reduction of albedo relative to pure snow. For allwave albedo or visible albedo, a twofold increase of C results in the same change in BC-caused albedo reduction as multiplying r by 2.6. The near-IR albedo is less sensitive to BC content; there a twofold increase of C can be mimicked by a fivefold increase of r.The albedo reduction by soot is less if the snow already contains dust, a common situation on

  14. 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

  15. 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

  16. 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.

  17. Effective Blended Learning Techniques

    ERIC Educational Resources Information Center

    Gill, Deborah

    2009-01-01

    Blended learning is becoming more prevalent in higher education courses. Reasons for blending range from accommodating more students to improving the quality of courses offered. The purpose of this paper is twofold: (1) to discuss student attitudes towards blended courses versus face-to-face versus completely online courses, and (2) to consider…

  18. On the evolution of the Snow Line in Protoplanetary Discs

    NASA Astrophysics Data System (ADS)

    Martin, Rebecca G.; Livio, Mario

    2014-01-01

    We examine the evolution of the snow line in a protoplanetary disc. If the magneto-rotational instability (MRI) drives turbulence throughout the disc, there is a unique snow line outside of which the disc is icy. The snow line moves closer to the star as the infall accretion rate drops. Because the snow line moves inside the radius of the Earth's orbit, the formation of our water-devoid planet is difficult with this model. However, protoplanetary discs are not likely to be sufficiently ionised to be fully turbulent. A dead zone at the mid-plane slows the flow of material through the disc and a global steady state cannot be achieved. We model the evolution of the snow line also in a disc with a dead zone. As the mass is accumulating, the outer parts of the dead zone become self gravitating, heat the massive disc and thus the outer snow line does not come inside the radius of the Earth's orbit. With this model there is sufficient time and mass in the disc for the Earth to form from water-devoid planetesimals at a radius of 1AU. Furthermore, the additional inner icy region within the dead zone predicted by this model may allow for the formation of giant planets close to their host star without the need for much migration.

  19. Influence of climate change predictions on snow in Sierra Nevada Mountains (Spain)

    NASA Astrophysics Data System (ADS)

    José Pérez-Palazón, María; Pimentel, Rafael; Herrero, Javier; María Perales, José; José Polo, María

    2015-04-01

    Snow is a basic component in Earth's surface energy balance. Its importance is greater in mountainous areas and therefore, its study is crucial to obtain conclusion about water resources over these areas. Moreover these regions are more vulnerable to climate variations. Sierra Nevada National Park (Southern Spain), with altitudes range from 2000 to 3500 m.a.s.l., is part of the global climate change observatories network and a clear example of snow regions in a semiarid environment. This work estimates the impact of climate change on snow dynamics and its influence on mountain hydrology in this area. Precipitation and temperature datasets from three different scenarios (A1B, A2, B1) proposed by the Fifth Assessment Report of IPCC (Intergovernmental Panel on Climate Change) were used as forcing meteorological sequences to simulate selected snow variables (snow water equivalent, daily snow cover area, annual number of days with snow and annual snowmelt and evaporation volumes). The associated results were compared for each scenario, and the snow behavior and evolution over the 2046-2100 periods were assessed. The results point to a higher decrease on snow cover extension, than those estimated for other snow variables. As expected, this variation is greater from the worst of the scenarios analyzed (A2). Furthermore, the comparison of the driving meteorological datasets throughout the reference period (1960-2000) with the real observations has allowed the introduction of another term of uncertainty in the estimations, not considered in a simple scenario analysis.

  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. 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

  2. The Snows of Enceladus

    NASA Astrophysics Data System (ADS)

    Schenk, P.; Schmidt, J.; White, O.

    2011-10-01

    The icy south polar plumes of Enceladus make for a spectacular effect in the Saturn system (e.g., the Ering), but also profoundly alter the surface of Enceladus itself. Recent models of the plume particle dynamics predict that the heavier particles will reaccrete, effectively "snowing" fine-grained debris back onto the surface in discrete patterns [1], depending on the actual distribution of ejection sites. The densest fallout pattern is dominated by two scytheshaped lobes extending northward from the South-Polar-Terrains along the 40 and 220W longitudes. Recent color mapping of Enceladus demonstrates that IR/UV color asymmetries across the surface match these predicted patterns astonishingly well [2]. Theory and observation therefore confirm the apparent formation of a blanket of very small particles covering most of the surface of Enceladus to different depths, depending on location and plume source changes.

  3. A New Approach to Measuring Precipitation over Snow Cover

    NASA Astrophysics Data System (ADS)

    Tian, Y.; Liu, Y.; Arsenault, K. R.; Behrangi, A.

    2013-12-01

    One of the great challenges for truly global precipitation measurement is the remote sensing of precipitation over snow cover. Due to the physical limitation in the current retrieval methodology, satellite-based measurements of precipitation over snow-covered areas are unreliable and largely unavailable. In this presentation, a new satellite-based approach to the estimation of precipitation over snow cover is proposed and tested. The method is based on the principle that precipitation can be inferred by the changes in the water content of the snowpack. During the EOS era operational remote sensing of snow water equivalent is available, with similar spatial and temporal resolutions of the precipitation-sensing passive microwave sensors. With these satellite-based snow water equivalent measurements, daily precipitation amounts can be derived. We tested the method for the Northern Hemisphere for three snow-accumulation seasons, with AMSR-E snow water equivalent data, and compared with existing datasets, including CPC gauge analysis and GPCP. The new precipitation estimates captured natural- and realistic-looking storm events over largely under-instrumented regions. The spatial distribution appeared more reasonable than existing global datasets over many boreal inland areas. The results indicate this approach is feasible and promising. Besides the capability to estimate precipitation over snow cover, this new approach has the following additional advantages over the conventional methods: 1. The relationship between precipitation and the observed variable (i.e., SWE) is more direct than the conventional methods, which have to rely on scattering signals from hydrometeors (passive microwave) or cloud top brightness temperatures (infrared) to infer precipitation; 2. Temporal sampling error is small. The method will not miss any precipitation amount even if there are no instantaneous satellite overpasses during the precipitation event. The memory of the snowpack stores the

  4. Eurasian snow cover and Indian monsoon : A new episode of a debated relationship

    NASA Astrophysics Data System (ADS)

    Peings, Y.; Douville, H.

    2009-04-01

    Since the pioneering works of Blanford at the end of the 19th century, suggesting that Indian monsoon rainfall could be sensitive to snow conditions over Himalaya, many studies have been devoted to a better understanding of the possible teleconnection between winter/spring Eurasian snow cover and the following Indian monsoon. This issue has been recently revisited at CNRM using a maximum covariance analysis. This statistical tool has been applied on both observations (summer precipitation over India on the one hand, satellite data of snow cover or in situ measurements of snow depth on the other hand) and a subset of global coupled ocean-atmosphere simulations from the CMIP3 database. In line with former studies, the observations suggest a link between an east-west snow dipole over Eurasia and the Indian summer monsoon precipitation. However, our results indicate that this relationship is neither statistically significant nor stationary over the last forty years. Moreover, the strongest signal appears over eastern Eurasia and is not consistent with the Blanford hypothesis whereby more snow should lead to a weaker monsoon. The 20th century CMIP3 simulations provide longer timeseries to look for robust snow-monsoon relationships. Some models do show an apparent influence of the Eurasian snow cover on the Indian summer monsoon precipitation, but the snow patterns are model-dependent and not the same as in the observations. Moreover, the apparent snow-monsoon relationship generally denotes a too strong ENSO (El Niño Southern Oscillation) influence on both winter snow cover and summer monsoon rainfall rather than a direct effect of the Eurasian snow cover on the Indian monsoon. New sensitivity studies with the ARPEGE-Climat model are needed to assess the potential impact of snow anomalies on the monsoon, using climatological sea surface temperature to get rid of the oceanic variability.

  5. Improved snow depth retrieval by combining SSM/I and MODIS data with SMO regression

    NASA Astrophysics Data System (ADS)

    Liang, J.; Huang, K.; Liu, X.; Li, X.

    2013-12-01

    The snow depth retrieval using passive microwave remote sensing heavily depends on the spatial and temporal snow characteristics. The acquisition of the snow parameters usually requires costly field work or complicated modeling. Given that snow characteristics can also be retrieved by visible/infrared sensors, the integration of microwave and visible/infrared data has the potential for improving the retrieval accuracy. The snow depth retrieval is performed by using microwave brightness temperature at 19 and 37 GHz from the Special Sensor Microwave / Imager (SSM/I) and surface visible/infrared reflectance from Moderate Resolution Imaging Spectroadiometer (MODIS) products. The microwave brightness temperature difference could help to estimate snow volume and the visible/infrared surface reflectance contains the information of snow grain size. With these integrated remote sensing data, snow depth is retrieved by a nonlinear data mining technique, the modified sequential minimal optimization (SMO) algorithm for support vector machine (SVM) regression. We tested the proposed method by using about 25000 records of snow depth measurements from 53 meteorological stations in Xinjiang from 2000 to 2010. The RMSE of SVM retrieved snow depth of our method is 6.49 cm and 0.73 respectively. They are better than those of using brightness temperature data solely (6.90 cm and 0.66), the traditional spectral polarization difference (SPD) algorithm (12.06 cm and 0.36), the modified Chang algorithm in WESTDC (8.51 cm and 0.57), and the multilayer perceptron classifier of artificial neural network (ANN) (7.08 cm and 0.63). The regional comparisons of the proposed method and the global snow products (GLOBSNOW and AMSR-E daily snow) are also presented. The study has shown that combining MODIS surface reflectance data and SSM/I brightness temperature with SVM regression can provide more accurate snow depth retrieval results. Experimental result of the proposed method in 2004

  6. 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

  7. 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

  8. 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 ...

  9. 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

  10. "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.

  11. 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)

  12. 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

  13. Snow density climatology across the former USSR

    NASA Astrophysics Data System (ADS)

    Zhong, X.; Zhang, T.; Wang, K.

    2014-04-01

    Snow density is one of the basic properties used to describe snow cover characteristics, and it is a key factor for linking snow depth and snow water equivalent, which are critical for water resources assessment and modeling inputs. In this study, we used long-term data from ground-based measurements to investigate snow density (bulk density) climatology and its spatiotemporal variations across the former Soviet Union (USSR) from 1966 to 2008. The results showed that the long-term monthly mean snow density was approximately 0.22 ± 0.05 g cm-3 over the study area. The maximum and minimum monthly mean snow density was about 0.33 g cm-3 in June, and 0.14 g cm-3 in October, respectively. Maritime and ephemeral snow had the highest monthly mean snow density, while taiga snow had the lowest. The higher values of monthly snow density were mainly located in the European regions of the former USSR, on the coast of Arctic Russia, and the Kamchatka Peninsula, while the lower snow density occurred in central Siberia. Significant increasing trends of snow density from September through June of the next year were observed, however, the rate of the increase varied with different snow classes. The long-term (1966-2008) monthly and annual mean snow densities had significant decreasing trends, especially during the autumn months. Spatially, significant positive trends in monthly mean snow density lay in the southwestern areas of the former USSR in November and December and gradually expanded in Russia from February through April. Significant negative trends mainly lay in the European Russia and the southern Russia. There was a high correlation of snow density with elevation for tundra snow and snow density was highly correlated with latitude for prairie snow.

  14. The Fallacy of Drifting Snow

    NASA Astrophysics Data System (ADS)

    Andreas, Edgar L.

    2011-12-01

    A common parametrization over snow-covered surfaces that are undergoing saltation is that the aerodynamic roughness length for wind speed ( z 0) scales as {α u_ast^2/g}, where u * is the friction velocity, g is the acceleration of gravity, and α is an empirical constant. Data analyses seem to support this scaling: many published plots of z 0 measured over snow demonstrate proportionality to {u_ast^2 }. In fact, I show similar plots here that are based on two large eddy-covariance datasets: one collected over snow-covered Arctic sea ice; another collected over snow-covered Antarctic sea ice. But in these and in most such plots from the literature, the independent variable, u *, was used to compute z 0 in the first place; the plots thus suffer from fictitious correlation that causes z 0 to unavoidably increase with u * without any intervening physics. For these two datasets, when I plot z 0 against u * derived from a bulk flux algorithm—and thus minimize the fictitious correlation— z 0 is independent of u * in the drifting snow region, u * ≥ 0.30 ms-1. I conclude that the relation {z_0 = α u_ast^2/g} when snow is drifting is a fallacy fostered by analyses that suffer from fictitious correlation.

  15. Observation of Snow Cover Variations at Mt. Kilimanjaro Using Landsat TM and ETM+ Images

    NASA Astrophysics Data System (ADS)

    Park, S.; Jung, H.; Lee, M.; Jung, H.

    2012-12-01

    Since the industrial revolution began, CO2 levels have been increasing with climate change. The objectives of this study are to quantitatively analyze snow cover area and distribution according to height changes with respect to time and to statistically predict the date of snow cover disappearance using remote sensing data over Mt. Kilimanjaro, Tanzania. Total numbers of 23 Landsat-5 TM and Landsat-7 ETM+ images are used for observing the snow cover variation, spanning the 27 years from June 1984 to July 2011. For this observation of snow cover variations, the following steps are applied: 1) atmospheric correction is performed on each image using the cosine approximation (COST) atmospheric correction algorithm, 2) the snow cover area is extracted from the normalized difference snow index (NDSI) algorithm, 3) the minimum height is determined using SRTM DEM and extracted snow cover area, and 4) the date of snow cover disappearance is predicted using a linear regression model. Among 23 images, seventeen images of the dry season are used for analyzing snow cover changes. Results show that snow cover area for about 30 years are largely changed from 9.01 km2 to 2.54 km2, equivalent to a 73% reduction. The minimum height of snow cover increased by approximately 290 m, from 4,603 m to 4,893 m. Linear regression model result shows that the snow cover area decreased by about 0.34 km2/yr and the minimum height of snow cover increased by about 9.85 m/yr. Moreover, L-band synthetic aperture radar (SAR) images are used to analyze seasonal variation of snow cover from 2006 to 2011. The results indicate that snow cover area of Mt. Kilimanjaro has fast decreased according to global warming. *This work was researched by the supporting project to educate GIS experts; Distribution of elevations for snow-covered area: (a) 24 Jun. 1984 and (b) 21 Jul. 2011 ; Changes of snow-covered area with respect to surface elevation: (a) 24 Jun. 1984 and (b) 21 Jul. 2011

  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. 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.

  18. 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.

  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. 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.

  1. Quantifying the crucial role of snow in supplying human water demand

    NASA Astrophysics Data System (ADS)

    Mankin, J. S.; Viviroli, D.; Mekonnen, M. M.; Hoekstra, A. Y. Y.; Diffenbaugh, N. S.

    2014-12-01

    Snow is considered essential to ecosystems, people, and climate, regulating water availability by mediating runoff and soil moisture throughout the year, and altering planetary radiative balance. Like canary in a coalmine, snow also serves as a kind of sentinel system, providing a benchmark by which we can measure the advance of global warming. Yet recent analyses reveal that the relationship between snow and warming is more complex: Despite warming, for example, the magnitude of internal climate variability suggests some Northern Hemisphere regions may experience snow increases for at least the next 50 years. While studies demonstrate that snow supply is vital and in critical danger, such assessments are based only on projections of annualized supply-side changes, such as the fraction of total annual runoff coming from snowfall. These measures do not consider a region's unique seasonal patterns of water supply and, in particular, water demand. We therefore do not know snow's relative importance to each region's water supply portfolio, and thus how great a risk global warming presents to regional water availability. Here we present the first quantification of snow's observed role in fulfilling monthly water demand for people in the Northern Hemisphere given each basin's unique sub-annual patterns of snow accumulation and melt. This quantification also reconciles the requirements of ecosystems and includes the buffering capacity of existing artificial storage, such as dams and reservoirs. Our results provide a meaningful baseline against which projected snow changes (from global warming) or demand changes (from population or land-use change) can be evaluated to identify regions at acute risk of disequilibria between future snow water supply and its demand.

  2. Increased snow facilitates plant invasion in mixedgrass prairie.

    PubMed

    Blumenthlal, D; Chimner, R A; Welker, J M; Morgan, J A

    2008-07-01

    Although global change is known to influence plant invasion, little is known about interactions between altered precipitation and invasion. In the North American mixedgrass prairie, invasive species are often abundant in wet and nitrogen (N)-rich areas, suggesting that predicted changes in precipitation and N deposition could exacerbate invasion. Here, this possibility was tested by seeding six invasive species into experimental plots of mixedgrass prairie treated with a factorial combination of increased snow, summer irrigation, and N addition. Without added snow, seeded invasive species were rarely observed. Snow addition increased average above-ground biomass of Centaurea diffusa from 0.026 to 66 g m(-2), of Gypsophila paniculata from 0.1 to 7.3 g m(-2), and of Linaria dalmatica from 5 to 101 g m(-2). Given added snow, summer irrigation increased the density of G. paniculata, and N addition increased the density and biomass of L. dalmatica. Plant density responses mirrored those of plant biomass, indicating that increases in biomass resulted, in part, from increases in recruitment. In contrast to seeded invasive species, resident species did not respond to snow addition. These results suggest that increases in snowfall or variability of snowfall may exacerbate forb invasion in the mixedgrass prairie. PMID:19086291

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

  4. Task Space Angular Velocity Blending for Real-Time Trajectory Generation

    NASA Technical Reports Server (NTRS)

    Volpe, Richard A. (Inventor)

    1997-01-01

    The invention is embodied in a method of controlling a robot manipulator moving toward a target frame F(sub 0) with a target velocity v(sub 0) including a linear target velocity v and an angular target velocity omega(sub 0) to smoothly and continuously divert the robot manipulator to a subsequent frame F(sub 1) by determining a global transition velocity v(sub 1), the global transition velocity including a linear transition velocity v(sub 1) and an angular transition velocity omega(sub 1), defining a blend time interval 2(tau)(sub 0) within which the global velocity of the robot manipulator is to be changed from a global target velocity v(sub 0) to the global transition velocity v(sub 1) and dividing the blend time interval 2(tau)(sub 0) into discrete time segments (delta)t. During each one of the discrete time segments delta t of the blend interval 2(tau)(sub 0), a blended global velocity v of the manipulator is computed as a blend of the global target velocity v(sub 0) and the global transition velocity v(sub 1), the blended global velocity v including a blended angular velocity omega and a blended linear velocity v, and then, the manipulator is rotated by an incremental rotation corresponding to an integration of the blended angular velocity omega over one discrete time segment (delta)t.

  5. Impact of the seasonal evolution of snow properties on microwave emission model performance

    NASA Astrophysics Data System (ADS)

    Fuller, M.; Derksen, C.; Lemmetyinen, J.; Yackel, J.

    2010-12-01

    Snow cover exhibits great spatio-temporal variability, and is dynamically coupled with global hydrological and climatological processes. Accounting for snowpack evolution related to snow accumulation, metamorphosis, and melt are essential for both modeling and remote sensing applications. Microwave emission has frequency dependant relationships with snow water equivalent (SWE), but snow grain-size, snowpack layering, and snow liquid-water content can confuse the estimation of snow parameters with empirical stand-alone algorithms. This work presents an overview of seasonal snow and multi-frequency dual-polarization microwave emission measurements collected during the 2009-2010 winter season at a network of sites near Churchill, Manitoba, Canada. These observations were used to parameterize and evaluate model simulations of microwave snow emission using the multiple-layer version of the Helsinki University of Technology (HUT) microwave emission model. The HUT model is utilized in the European Space Agency’s (ESA) GlobSnow global snow monitoring service, applied to SWE and snow depth (SD) retrievals for the Northern Hemisphere. The HUT model used for forward brightness temperature simulations in the GlobSnow retrieval scheme is currently limited to one layer which necessitates idealizing physical properties of the entire snow pack. In this study, we explore the performance of simulations with the addition of a depth hoar layer and, when appropriate, an ice lens. Simulations for forest, lake, and open environments were synthesized through a scene simulation formulation of the HUT model to produce output suitable for comparison with measured brightness temperatures from the Advanced Microwave Scanning Radiometer (AMSR-E). While the multi-layer model better represents the vertical complexities of grain size and layering, implementation of a multi-layer approach remains a challenge due to model sensitivity with regard to the method of generalization of a complex snow

  6. 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.

  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. 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

  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. Uncertainty analysis of the optical satellite data-derived snow products

    NASA Astrophysics Data System (ADS)

    Salminen, Miia; Pulliainen, Jouni; Metsämäki, Sari; Luojus, Kari; Böttcher, Kristin; Hannula, Henna-Reetta

    2014-05-01

    The behavior of the global snow cover can be effectively estimated using optical Earth Observation (EO) data, in particular during the end of the melting season. In addition to successful dry and continuous 100% (full) snow cover mapping, optical methods perform well over snowmelt regions with patchy wet snow. Long decadal scale time series of satellite data estimates on global Snow Extent (SE) or Fractional Snow Cover (FSC) and albedo are needed for constructing Climate Data Records (CDR). CDRs have a high relevance in climate research e.g. in climate monitoring including trend analysis and verification of climate models. Currently, the available optical satellite data records for hemispherical snow monitoring reach back for several decades, e.g. AVHRR (since ca 1980), ATSR (since ca 1990), AATSR and MODIS (since ca 2000). Also, the current VIIRS (since 2011) and the future Sentinel-3 both provide very potential data for global snow monitoring. It is fundamental to generate extensive CDRs with quality/estimation error information attached to each snow estimate, as the usefulness of the EO-based snow estimate is highly dependent on the quality of the interpretation. The objective of this work is to establish and develop a methodology to determine a dynamic retrieval error estimate for the optical satellite-retrieved FSC. This is performed by applying an error propagation analysis for the consideration of the statistical error of FSC estimation. The procedure is demonstrated here by using the SCAmod algoritm, which is suited for global snow detection and able to perform well also in forested regions. Apart from determining the statistical (random) error, we outline the procedure for the evaluation of the systematic error (biases) of FSC products, both of which are essential for the generation of snow cover CDR. As we focus here on determining the statistical random error, it is crucial to know the variability of the different factors affecting the satellite

  11. Merging the MODIS and NESDIS Monthly Snow-Cover Records to Study Decade-Scale Changes in Northern Hemisphere Snow Cover

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

    A decade-scale record of Northern Hemisphere snow cover has been available from the National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite Data and Information Service (NESDIS) and has been reconstructed and validated by Rutgers University following adjustments for inconsistencies that were discovered in the early years of the data set. This record provides weekly, monthly (and, in recent years, daily) snow cover from 1966 to the present for the Northern Hemisphere. With the December 1999 launch of NASA's Earth observing System (EOS) Terra satellite, snow maps are being produced globally, using automated algorithms, on a daily, weekly and monthly basis from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. The resolution of the MODIS monthly snow maps (0.05deg or about 5 km) is an improvement over that of the NESDIS-derived monthly snow maps (>approx.10 km) the maps, it is necessary to study the datasets carefully to determine if it is possible to merge the datasets into a continuous record. The months in which data are available for both the NESDIS and MODIS maps (March 2000 to the present) will be compared quantitatively to analyze differences in North American and Eurasian snow cover. Results from the NESDIS monthly maps show that for North America (including all 12 months), there is a trend toward slightly less snow cover in each succeeding decade. Interannual snow-cover extent has varied significantly since 2000 as seen in both the NESDIS and MODIS maps. As the length of the satellite record increases through the MODIS era, and into the National Polar-orbiting Environmental Satellite System (NPOESS) era, it should become easier to identify trends in areal extent of snow cover, if present, that may have climatic significance. Thus it is necessary to analyze the validity of merging the NESDIS and MODIS, and, in the future, the NPOESS datasets for determination of long-term continuity in measurement of Northern

  12. Snow Micro-Structure Model

    Energy Science and Technology Software Center (ESTSC)

    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

  13. 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.

  14. 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…

  15. 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…

  16. 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…

  17. Blended Teaching & Learning

    ERIC Educational Resources Information Center

    Pape, Liz

    2010-01-01

    Blended learning is using online tools to communicate, collaborate and publish, to extend the school day or year and to develop the 21st-century skills students need. With blended learning, teachers can use online tools and resources as part of their daily classroom instruction. Using many of the online tools and resources students already are…

  18. 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.

  19. Radar spectral observations of snow

    NASA Technical Reports Server (NTRS)

    Stiles, W. H.; Ulaby, F. T.; Fung, A. K.; Aslam, A.

    1981-01-01

    Radar remote sensing experiments have been conducted at test sites in Kansas, Colorado, and South Dakota over the last six years to examine backscatter coefficient response to snowcovered terrain. Truck-mounted 1-35 GHz scatterometers were employed in conjunction with detailed ground-truth measurements. From these experiments and associated modeling efforts, most of the fundamental questions concerning backscatter behavior in response to important snow parameters have been, at least qualitatively, answered. The optimum angular range seems to be between 20 and 50 deg and, for these angles, the results indicate that the radar backscatter generally: (1) increases with increasing water equivalent, (2) decreases with increasing liquid water, (3) increases with increasing crystal size, (4) is insensitive to surface roughness for dry snow conditions, and (5) can be sensitive to soil state if the snowcover is dry. This paper gives a summary of these results, along with empirical and theoretical models for describing the backscatter from snow.

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

    NASA Astrophysics Data System (ADS)

    Peings, Yannick; Douville, H.; Alkama, R.; Decharme, B.

    2011-09-01

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

  1. 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.

  2. 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

  3. Interpretation of AMSU microwave measurements for the retrievals of snow water equivalent and snow depth

    NASA Astrophysics Data System (ADS)

    Kongoli, Cezar; Grody, Norman C.; Ferraro, Ralph R.

    2004-12-01

    The objective of this paper is to interpret microwave scattering signatures over snow cover as observed by the Advanced Microwave Sounding Unit (AMSU) for the retrievals of snow water equivalent and snow depth. A case study involving seasonal snow cover over the U.S. Great Plains was analyzed in detail. Area-wide analysis of the relationship between snow depth and the AMSU scattering signatures in the 23-150 GHz window region showed weak correlation, deteriorated by the dependence of these signatures on snow metamorphism. The lower frequency scattering index, computed as the difference in the brightness temperature between 23 and 31 GHz channels, was low and insensitive to fresh snow predominant in December, but increased later in the season, and thus was more sensitive to snow depth for older snow cover. However, this seasonal increase in microwave scattering was observed for every snow depth range, suggesting a strong dependence on snow metamorphism. In contrast, the 89 GHz scattering index responded to relatively shallow snow cover in December, but was less sensitive to snow depth variability later in the season. A snow hydrology model was applied at specific locations to estimate snow water equivalent (other than snow depth) for comparisons with the AMSU measurements. Overall, the lower frequency index was the best predictor of snow water equivalent and snow depth. However, correlation was higher for snow density and snow water equivalent. This was attributed to the response of this scattering index to the grain size evolution with time, which correlated better with the snow density and water equivalent changes in the snow cover than snow depth. Correlation between the snow water equivalent and the lower frequency index for fresh snow cover was significantly improved by switching to the higher frequency index at 89 GHz as predictor when the lower frequency index at 31 GHz was less than the 5 K threshold. Correlation further improved for fresh snow cover

  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. 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

  6. 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.

  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. Snow Hydrology in a General Circulation Model.

    NASA Astrophysics Data System (ADS)

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

    1994-08-01

    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 snow pack. 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.

  9. Airborne radar surveys of snow depth over Antarctic sea ice during Operation IceBridge

    NASA Astrophysics Data System (ADS)

    Panzer, B.; Gomez-Garcia, D.; Leuschen, C.; Paden, J. D.; Gogineni, P. S.

    2012-12-01

    Over the last decade, multiple satellite-based laser and radar altimeters, optimized for polar observations, have been launched with one of the major objectives being the determination of global sea ice thickness and distribution [5, 6]. Estimation of sea-ice thickness from these altimeters relies on freeboard measurements and the presence of snow cover on sea ice affects this estimate. Current means of estimating the snow depth rely on daily precipitation products and/or data from passive microwave sensors [2, 7]. Even a small uncertainty in the snow depth leads to a large uncertainty in the sea-ice thickness estimate. To improve the accuracy of the sea-ice thickness estimates and provide validation for measurements from satellite-based sensors, the Center for Remote Sensing of Ice Sheets deploys the Snow Radar as a part of NASA Operation IceBridge. The Snow Radar is an ultra-wideband, frequency-modulated, continuous-wave radar capable of resolving snow depth on sea ice from 5 cm to more than 2 meters from long-range, airborne platforms [4]. This paper will discuss the algorithm used to directly extract snow depth estimates exclusively using the Snow Radar data set by tracking both the air-snow and snow-ice interfaces. Prior work in this regard used data from a laser altimeter for tracking the air-snow interface or worked under the assumption that the return from the snow-ice interface was greater than that from the air-snow interface due to a larger dielectric contrast, which is not true for thick or higher loss snow cover [1, 3]. This paper will also present snow depth estimates from Snow Radar data during the NASA Operation IceBridge 2010-2011 Antarctic campaigns. In 2010, three sea ice flights were flown, two in the Weddell Sea and one in the Amundsen and Bellingshausen Seas. All three flight lines were repeated in 2011, allowing an annual comparison of snow depth. In 2011, a repeat pass of an earlier flight in the Weddell Sea was flown, allowing for a

  10. Microwave emission from an irregular snow layer

    NASA Technical Reports Server (NTRS)

    Eom, H. J.; Lee, K. K.; Fung, A. K.

    1983-01-01

    Emission from an irregular snow layer is modeled by a layer of Mie scatterers using the radiative transfer method. Comparisons are made with measurements showing snow wetness effects and rough air-snow boundary effects. For convenience of reference, theoretical model behavior is also illustrated.

  11. Elevation dependency of mountain snow depth

    NASA Astrophysics Data System (ADS)

    Grünewald, T.; Bühler, Y.; Lehning, M.

    2014-12-01

    Elevation strongly affects quantity and distribution patterns of precipitation and snow. Positive elevation gradients were identified by many studies, usually based on data from sparse precipitation stations or snow depth measurements. We present a systematic evaluation of the elevation-snow depth relationship. We analyse areal snow depth data obtained by remote sensing for seven mountain sites near to the time of the maximum seasonal snow accumulation. Snow depths were averaged to 100 m elevation bands and then related to their respective elevation level. The assessment was performed at three scales: (i) the complete data sets (10 km scale), (ii) sub-catchments (km scale) and (iii) slope transects (100 m scale). We show that most elevation-snow depth curves at all scales are characterised through a single shape. Mean snow depths increase with elevation up to a certain level where they have a distinct peak followed by a decrease at the highest elevations. We explain this typical shape with a generally positive elevation gradient of snow fall that is modified by the interaction of snow cover and topography. These processes are preferential deposition of precipitation and redistribution of snow by wind, sloughing and avalanching. Furthermore, we show that the elevation level of the peak of mean snow depth correlates with the dominant elevation level of rocks (if present).

  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. 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...

  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, 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...

  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, 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...

  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. Seasonal variations of snow depth on Mars

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

    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.

  20. Communicators' perspective on snow avalanche risk communication

    NASA Astrophysics Data System (ADS)

    Charriere, M. K. M.; Bogaard, T.; Mostert, E.

    2014-12-01

    Among all the natural hazards, snow avalanches are the only ones for which a public danger scale is globally used. It consists of 5 levels of danger displayed with a given number and colour and for each of them, behavioural advices are provided. Even though this is standardized in most of the countries affected by this natural hazard, the tools (usually websites or smartphone applications) with which the information is disseminated to the general pubic differs, particularly in terms of target audience and level of details. This study aims at gathering the perspectives of several communicators that are responsible for these communication practices. The survey was created to assess how and why choices were made in the design process of the communication tools and to determine how their effectiveness is evaluated. Along with a review of existing avalanche risk communication tools, this study provides guidelines for communication and the evaluation of its effectiveness.

  1. 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. PMID:11739951

  2. Toward improving streamflow prediction in the Upper Colorado River Basin via assimilating bias-adjusted satellite snow depth retrievals

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Peters-Lidard, C. D.; Kumar, S.; Arsenault, K. R.; Mocko, D. M.

    2014-12-01

    In snowmelt-driven river systems, it is critical to enable reliable predictions of the spatiotemporal variability in the seasonal snowpack in order to support local and regional water management. Previous studies have shown that improved snow predictions can be achieved by assimilating bias corrected snow depth retrievals from satellite-based passive microwave (PMW) sensors. However, improved snow predictions do not necessarily always translate into improved predictions of streamflow on which water management heavily relies. In this presentation, we explore how the existing bias correction strategy based on the optimal interpolation algorithm can be enhanced to produce an improved satellite-gauge blended snow depth product, which, when assimilated into a distributed snowmelt-runoff model, can lead to consistently improved streamflow predictions. The methodology is applied to the bias reduction of the snow depth estimates from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), which is then assimilated into the Noah land surface model via an ensemble Kalman Filter (EnKF) for streamflow prediction in the Upper Colorado River Basin. Our results indicate that using observations from high-elevation stations (e.g., the Snow Telemetry (SNOTEL) stations) and terrain aspect information in the bias correction process is critically important in achieving desirable streamflow predictions. Incorporating snow cover information (e.g., from the Moderate Resolution Imaging Spectroradiometer (MODIS)) into bias correction can further improve the streamflow results. However, increasing the spatial resolution of bias correction tends to have mixed results on streamflow prediction.

  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. Photopolarimetric retrievals of snow properties

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

    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.

  5. Photopolarimetric retrievals of snow properties

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

    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 air- and space-borne 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 dataset, 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.

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

    NASA Astrophysics Data System (ADS)

    Engels, J.; Kloster, S.; Bourgeois, Q.

    2014-12-01

    We investigate the potential impact of snow darkening caused by pre-industrial and present-day black carbon (BC) emissions on snow albedo and subsequently climate. To assess this impact, we implemented the effect of snow darkening caused by BC emitted from natural as well as anthropogenic sources into the Max Planck Institute for Meteorology Earth System Model (MPI-M ESM). Considerable amounts of BC are emitted e.g. from fires and are transported through the atmosphere for several days before being removed by rain or snow precipitation in snow covered regions. Already very small quantities of BC reduce the snow reflectance significantly, with consequences for snow melting and snow spatial coverage. We implemented the snow albedo reduction caused by BC contamination and snow aging in the one layer land surface component (JSBACH) of the atmospheric general circulation model ECHAM6, developed at MPI-M. For this we used the single-layer simulator of the SNow, Ice, and Aerosol Radiation (SNICAR-Online (Flanner et al., 2007); http://snow.engin.umich.edu) model to derive snow albedo values for BC in snow concentrations ranging between 0 and 1500 ng(BC)/g(snow) for different snow grain sizes for the visible (0.3 - 0.7 μm) and near infrared range (0.7 - 1.5 μm). As snow grains grow over time, we assign different snow ages to different snow grain sizes (50, 150, 500, and 1000 μm). Here, a radius of 50 μm corresponds to new snow, whereas a radius of 1000 μm corresponds to old snow. The deposition rates of BC on snow are prescribed from previous ECHAM6-HAM simulations for two time periods, pre-industrial (1880-1889) and present-day (2000-2009), respectively. We perform a sensitivity study regarding the scavenging of BC by snow melt. To evaluate the newly implemented albedo scheme we will compare the modeled black carbon in snow concentrations to observed ones. Moreover, we will show the impact of the BC contamination and snow aging on the simulated snow albedo. The

  7. 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.

  8. Comparison of Coordinated Satellite and Ground-based X-Band Radar Collections for the Retrieval of Snow Parameters

    NASA Astrophysics Data System (ADS)

    Deeb, E. J.; Marshall, H.; LeWinter, A. L.; Finnegan, D. C.; Deems, J. S.; Landry, C.

    2012-12-01

    In many regions of the world, snow is a major source of runoff contributing to human existence/sustenance, agriculture, and industry. The uncertainties in quantifying snow mass at both spatial and temporal scales have limited the vital management of this significant component to the global water cycle. With the sensitivity of radar backscatter to physical properties of snow at higher frequencies and the availability of high resolution commercial satellite imaging radars at X-Band frequencies (e.g. 9.6 GHz), snow experiments have been conducted to examine these relationships at finer spatial and temporal scales. For the past several winters, satellite radar acquisitions (at X-Band with co- and cross-polarizations) have been coordinated with ground-based radar collections within a well-instrumented southwestern Colorado basin exhibiting a wide range of snow conditions. Snow-free satellite radar collections (at X-Band with the same viewing geometry) have also been acquired to separate the backscatter contributions of the snow volume from the underlying background target. Ancillary data sets including ground-based LiDAR-derived snow depths and scientific snow pit sampling are also incorporated into the analysis. Despite the fact that it may not be possible to retrieve snow water equivalent from multi-polarization X-Band frequency alone, preliminary results of these comparisons are shown where the ground-based radar transects overlap the satellite radar coverage. Snow parameters such as saturated surface or internal snow layers, snow surface and stratigraphic roughness, and grain size variations may be of particular interest.

  9. 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.

  10. The Effect of Black Carbon and Snow Grain Size on Snow Surface Albedo

    NASA Astrophysics Data System (ADS)

    Hadley, O. L.; Kirchstetter, T.; Flanner, M.

    2009-12-01

    Black carbon (BC) has been measured in snow and ice cores at levels that climate models predict are high enough to be the second leading cause in arctic ice melt and glacial retreat after greenhouse gas warming. BC deposited on snow reduces the snow surface albedo; however, in addition to BC content, snow albedo also depends on sky cover, solar angle, snow grain size and shape, surface roughness, and depth. Quantifying the albedo reduction due to BC separately from these other variables is difficult to achieve in field measurements. We are conducting laboratory experiments that isolate the effect of BC and snow grain size on snow albedo. Snow is made by spraying and freezing drops of water; BC contaminated snow is made from BC hydrosol. Snow albedo is measured with a spectrometer equipped with an integrating sphere over the entire visible spectrum (400-1000 nm). Snow grain size distribution and shape are characterized using a digital microscope to calculate the effective radius of the snow. Measured snow albedo is compared to that predicted using the Snow, Ice, and Aerosol Radiative Model. Preliminary results indicate good agreement between measured and modeled albedo for pure and BC contaminated snow.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. Elevation dependency of mountain snow depth

    NASA Astrophysics Data System (ADS)

    Grünewald, T.; Bühler, Y.; Lehning, M.

    2014-07-01

    Elevation strongly affects quantity and distribution of precipitation and snow. Positive elevation gradients were identified by many studies, usually based on data from sparse precipitation stations or snow depth measurements. We present a systematic evaluation of the elevation - snow depth relationship. We analyse areal snow depth data obtained by remote sensing for seven mountain sites. Snow depths were averaged to 100 m elevation bands and then related to their respective elevation level. The assessment was performed at three scales ranging from the complete data sets by km-scale sub-catchments to slope transects. We show that most elevation - snow depth curves at all scales are characterised through a single shape. Mean snow depths increase with elevation up to a certain level where they have a distinct peak followed by a decrease at the highest elevations. We explain this typical shape with a generally positive elevation gradient of snow fall that is modified by the interaction of snow cover and topography. These processes are preferential deposition of precipitation and redistribution of snow by wind, sloughing and avalanching. Furthermore we show that the elevation level of the peak of mean snow depth correlates with the dominant elevation level of rocks.

  16. 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

  17. Improving radiative transfer processes in snow-covered areas prone to dust loading using a regional climate model

    NASA Astrophysics Data System (ADS)

    Oaida, C. M.; Xue, Y.; Painter, T. H.; Flanner, M. G.; De Sales, F.

    2011-12-01

    Radiative processes play an important role on both global and regional scales. This study focuses on their effects over snow-covered surfaces, both clean and dust loaded. It is well understood that dust in snow enhances solar radiation absorption, leading to a decrease in snow albedo. However, the quantitative assessment of dust's influence on radiative forcing and runoff timing in mountain snow packs has only been recently investigated. Painter et al. (2007) have shown that snow cover was shortened by 18 to 35 days due to dust radiative forcing in snow in the San Juan Mountains, Colorado, USA. This dust largely originates from the Colorado Plateau with increases of 5-7 fold in the last century and a half due to grazing and agricultural practices. For this study, we employ NCAR's WRF ARW v3.3+ model, which is coupled with a land surface model, Simplified Simple Biosphere version 3 (SSiB3). We first investigate the impact of different atmospheric radiative transfer schemes in WRF3.3+-SSiB3 on the regional climate downscaling. After conducting simulations over North America for the period March through June, we found substantial differences in the downscaling skills with different atmospheric radiative schemes. These differences indicate the uncertainty due to the atmospheric radiative transfer parameterizations. To develop a regional climate model that is capable of realistically simulating radiative forcing on snow covered areas with aerosol loading, we coupled WRF3.3+-SSiB3 with a snow-radiative transfer model, Snow, Ice, and Aerosol Radiative (SNICAR) model. SNICAR considers the effects of snow grain size and aerosol on snow albedo evolution. Snow grain size and growth is important in snow albedo feedbacks, especially when aerosols in snow are considered, because larger snow grains decrease snow albedo, and in the presence of dust, grain growth rates increase, decreasing snow reflectance even further than if the snow was pure. Our previous version of WRF3.3+-SSi

  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. Methaemoglobinaemia due to mephedrone ('snow').

    PubMed

    Ahmed, Noor; Hoy, Brent Philip Sew; McInerney, J

    2010-01-01

    Acquired methaemoglobinaemia is a serious complication caused by many oxidising drugs. It presents as cyanosis unresponsive to oxygen therapy. The case of 33-year-old male patient who presented in our department after noticing blue lips and fingers is presented. He had sniffed 1 g of 'snow' after buying it from a head shop. His oxygen saturation by pulse oximeter on room air at presentation was 90%, which did not improve with supplemental oxygen. Arterial blood gas analyses showed partial pressure of oxygen 37 kPa while on supplemental oxygen and a methaemoglobin concentration greater than 25%. The patient denied using any other recreational drugs and was not on regular treatment. Therefore, a diagnosis of methaemoglobinaemia due to mephedrone, which is the active ingredient of 'snow', was made. Treatment is with intravenous methylene blue. Our patient started to improve so methylene blue was not used and he was discharged after 8 h. PMID:22791577

  20. Snow Densification in Greenland (Invited)

    NASA Astrophysics Data System (ADS)

    Morris, E.; Wingham, D.

    2010-12-01

    As part of the calibration and validation experiments for the radar altimeter carried by the ESA Cryosat-2 satellite, snow density profiles have been measured along the EGIG line from Spring 2004 to Summer 2010. Repeated measurements at the same site allow the development of the characteristic stratigraphy of the dry snow zone to be observed and the rate of densification to be measured directly. Densification rates below the surface layer are found to be compatible with a physics-based grain boundary sliding model (Alley, 1987) but near-surface rates are enhanced. Alley, R.B. (1987). Firn densification by grain-boundary sliding: A First Model. J. de. Physique 48 (Coll. C1, Suppl. No.3) 249-256.

  1. 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.

  2. 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.

  3. Spatially continuous mapping of snow depth in high alpine catchments using digital photogrammetry

    NASA Astrophysics Data System (ADS)

    Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C.

    2014-06-01

    Information on snow depth and its spatial distribution is crucial for many applications in snow and avalanche research as well as in hydrology and ecology. Today snow depth distributions are usually estimated using point measurements performed by automated weather stations and observers in the field combined with interpolation algorithms. However, these methodologies are not able to capture the high spatial variability of the snow depth distribution present in alpine terrain. Continuous and accurate snow depth mapping has been done using laser scanning but this method can only cover limited areas and is expensive. We use the airborne ADS80 opto-electronic scanner with 0.25 m spatial resolution to derive digital surface models (DSMs) of winter and summer terrains in the neighborhood of Davos, Switzerland. The DSMs are generated using photogrammetric image correlation techniques based on the multispectral nadir and backward looking sensor data. We compare these products with the following independent datasets acquired simultaneously: (a) manually measured snow depth plots (b) differential Global Navigation Satellite System (dGNSS) points (c) Terrestrial Laser Scanning (TLS) and (d) Ground Penetrating Radar (GPR) datasets, to assess the accuracy of the photogrammetric products. The results of this investigation demonstrate the potential of optical scanners for wide-area, continuous and high spatial resolution snow-depth mapping over alpine catchments above tree line.

  4. 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.

  5. Newly Implemented Snow-Vegetation Representation in the Community Land Model

    NASA Astrophysics Data System (ADS)

    Perket, J.; Flanner, M.; Clark, M. P.; Lawrence, D. M.

    2014-12-01

    Boreal forests are a major source of surface albedo feedback spread in CMIP5 models. We've incorporated improvements into the Community Land Model (CLM) vegetation canopy snow treatment in order to more realistically represent boreal forest canopy albedo. Current CLM hydrology does not differentiate the phase of precipitation intercepted by vegetation. To represent canopy snow, there is a sharp temperature-dependent switch in canopy albedo parameters at 0 K. Snow immediately ceases to exist when vegetation temperature rises above freezing. We've separated phases in the CLM vegetation hydrology, allowing snow to have its own storage maximum and interception treatment. Wind and melt based unloading terms have also been incorporated to more accurately simulate canopy processes, creating a path for canopy snow loss in freezing temperatures. To evaluate the new treatment, we compared singe-point CLM 4.5 simulations with accumulated canopy snow mass measurements from Umpqua Forest, Oregon. Additionally, we have considered the effects of modifying snow cover fraction and latent heat fluxes from phase changes. Global CLM simulations evaluate the climatic differences between existing CLM and CLM with the new implementations for boreal forests.

  6. Analysis of climatic variability and snow cover in the Kaligandaki River Basin, Himalaya, Nepal

    NASA Astrophysics Data System (ADS)

    Mishra, Bhogendra; Babel, Mukand S.; Tripathi, Nitin K.

    2014-05-01

    Various remote sensing products and observed data sets were used to determine spatial and temporal trends in climatic variables and their relationship with snow cover area in the higher Himalayas, Nepal. The remote sensing techniques can detect spatial as well as temporal patterns in temperature and snow cover across the inaccessible terrain. Non-parametric methods (i.e. the Mann-Kendall method and Sen's slope) were used to identify trends in climatic variables. Increasing trends in temperature, approximately by 0.03 to 0.08 °C year-1 based on the station data in different season, and mixed trends in seasonal precipitation were found for the studied basin. The accuracy of MOD10A1 snow cover and fractional snow cover in the Kaligandaki Basin was assessed with respect to the Advanced Spaceborne Thermal Emission and Reflection Radiometer-based snow cover area. With increasing trends in winter and spring temperature and decreasing trends in precipitation, a significant negative trend in snow cover area during these seasons was also identified. Results indicate the possible impact of global warming on precipitation and snow cover area in the higher mountainous area. Similar investigations in other regions of Himalayas are warranted to further strengthen the understanding of impact of climate change on hydrology and water resources and extreme hydrologic events.

  7. 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.

  8. 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.

  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. Spatiotemporal analysis of snow trends in Austria

    NASA Astrophysics Data System (ADS)

    Koch, Roland; Schöner, Wolfgang

    2015-04-01

    This study presents the spatiotemporal analysis of Austrian snow observations. A set of consistent and reliable long-term time series of snow depth on a daily scale from selected meteorological sites across Austria is used. The time series were collected by the Central Institute for Meteorology and Geodynamics (ZAMG) and the Hydrographical Central Bureau of Austria (HZB). The data cover a time period from the late nineteenth century until today. In the first part of the study spatiotemporal characteristics of seasonal snow depth observations were investigated by the method of principal component analysis (PCA). Furthermore, the spatial patterns of variability have been used for a regionalisation, identifying regions with similar conditions during the base period 1961 to 2010. The results show a clear separation of four major regions including various sub-regions. However, the regionalisation was limited due to sparse data coverage. The non-parametric Mann-Kendall statistical test had been used to assess the significance of trends in snow indices, e.g. snow depth, maximum snow depth, snow cover duration, at monthly and seasonal time scales. In order to remove the influence of the lag-1 serial correlation from the snow data, the trend-free pre-whitening approach was applied. In the monthly and seasonal time series during the period 1961-2010, negative trends in snow indices were significant at the 95% confidence level primarily at stations in the Western and Southern part of Austria. In addition, the correlation between snow observations and gridded HISTALP winter temperature and precipitation fields was investigated. The analysis has shown an increased temperature and decreased precipitation during the 1990s, yielding a pronounced reduction in snow depth and duration. As a matter of fact, the results indicate major shifts of the snow depth and snow cover duration around the 1970s and especially the 1990s, which are predominantly responsible for trends.

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. Spatial and Temporal Variability of Surface Snow Accumulation and Snow Chemistry at East Antarctic Ice Sheet

    NASA Astrophysics Data System (ADS)

    Motoyama, H.; Ito, K.; Hirabayashi, M.

    2014-12-01

    Snow stakes along the traverse routes have been observed for long term monitoring program 'the variation of ice sheet surface mass balance' from the 1960's by the Japanese Antarctic Research Expedition in Shirase glacier drainage basin, East Antarctica. During the traverse route between coastal S16 point (69 02'S, 40 03'E, 580m a.s.l.) to inland Dome Fuji (77 22'S, 39 42'E, 3,810m a.s.l.), the snow stake observations every 2 km have been carried out from 1993. Yearly net snow accumulations from S16 to Dome Fuji were calculated. Heavy, modern and light snow events were observed. They were different in way accumulating spatial pattern depending on places. The yearly accumulation rates were compared with seasonal change of AAO-index (SAM). As a result, yearly accumulation rate and AAO-index showed the positive correlation.Surface snow samplings were conducted every 10km along the traverse route. Generally, the snow surface features are classified into three regions. (1) the coastal region: smooth surface, high snow accumulation (2) the katabatic slope region: rough sastrugi surface and smooth glazed surface(3) the high plateau region: smooth surface, little snow accumulation The chemistry of surface snow changes from the coast to inland. Furthermore, the chemical properties of snow are different for each surface at the same area. We can classify the surface snow with fresh drifting snow, deposited drift snow, soft and hard surface snow, sustrugi, surface hoar and so on. The value of each isotope ration and ion concentration greatly varied. Sometimes, snow might deposit thick equally. But the deposited snow was redistributed by the wind. When the snowstorm occurred, the blowing snow started to deposit in a certain opportunity. As for it, the area was not the uniform. It is necessary to discuss inhomogeneity of the depositional condition quantitatively.

  16. 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.

  17. Evaluating snow density models for integration in operational snow water resources monitoring

    NASA Astrophysics Data System (ADS)

    Jonas, T.; Magnusson, J.

    2012-12-01

    In the Alps, the distribution of seasonal snow is highly complex in time and space. Being able to monitor snow water resources is crucial for lake and reservoir management as well as for forecasting of snow-melt related spring floods. In Switzerland, while networks for periodic SWE measurements exist, they do not resolve the variability of snow at spatial and temporal scales as required by the national snow water resources monitoring program. However, there are hundreds of stations that provide daily snow depth information. Including these stations into SWE monitoring schemes requires the use of snow density models. In this study we first look at several model approaches to predict SWE under different scenarios regarding data availability: single snow depth reading, daily snow depth, daily snow and temperature data, etc. The model assessment is based on a large archive of snow pit data measured in the Swiss Alps over several decades. In a second step, we apply the above models to integrate daily snow depth readings in a data assimilation scheme to provide SWE distribution at medium to large scale. Finally, we compare the results of the data assimilation scheme intended for larger scale applications against field data from a 50 km2 test catchment that resolves the natural variability of snow depth and density at a smaller scale. This comparison reveals interesting differences in average density and depth from both data sets, suggesting that including a basic representation of small-scale variability may enhance larger-scale model approaches.

  18. Elemental carbon in snow at Changbai Mountain, northeastern China: concentrations, scavenging ratios, and dry deposition velocities

    NASA Astrophysics Data System (ADS)

    Wang, Z. W.; Gallet, J. C.; Pedersen, C. A.; Zhang, X. S.; Ström, J.; Ci, Z. J.

    2014-01-01

    Light-absorbing aerosol - particularly elemental carbon (EC) - while mixed with snow and ice is an important climate driver from the enhanced absorption of solar radiation. Currently, considerable efforts are being made to estimate its radiative forcing on a global scale, but several uncertainties remain, particularly those regarding its deposition processes. In this study, concurrent measurements of EC in air and snow are performed for three years (2009-2012) at Changbai station, northeastern China. The scavenging ratio and the wet- and dry-deposition fluxes of EC over the snow surface are estimated. The mean EC concentration in the surface snow is 1000 ± 1500 ng g-1, ranging from 7 to 7640 ng g-1. The mean value of the scavenging ratio of EC by snow is 140 ± 100, with a median value of 150, which is smaller than that reported in Arctic areas. A non-rimed snow process is a significant factor in interpreting differences with Arctic areas. Wet-deposition fluxes of EC are estimated to be 0.47 ± 0.37 μg cm-2 month-1 on average over the three snow seasons studied. Dry deposition is more than five times higher, with an average of 2.65 ± 1.93 μg cm-2 month-1; however, only winter period estimation is possible (December-February). During winter in Changbai, 87% of EC in snow is estimated to be due to dry deposition, with a mean dry deposition velocity of 6.44 × 10-3 m s-1 and median of 8.14 × 10-3 m s-1. Finally, the calculation of the radiative effect shows that 500 ng g-1 of dry-deposited EC to a snow surface absorbs three times more incoming solar energy than the same mass mixed in the snow through wet deposition. Deposition processes of an EC-containing snow surface are, therefore, crucial to estimate its radiative forcing better, particularly in northeastern China, where local emission strongly influences the level and gradient of EC in the snowpack, and snow-covered areas are cold and dry due to the atmospheric general circulation. Furthermore, this study

  19. 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

  20. 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

  1. 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

  2. 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

  3. Snow depth mapping in high-alpine catchments using digital photogrammetry

    NASA Astrophysics Data System (ADS)

    Bühler, Y.; Marty, M.; Egli, L.; Veitinger, J.; Jonas, T.; Thee, P.; Ginzler, C.

    2015-02-01

    Information on snow depth and its spatial distribution is crucial for numerous applications in snow and avalanche research as well as in hydrology and ecology. Today, snow depth distributions are usually estimated using point measurements performed by automated weather stations and observers in the field combined with interpolation algorithms. However, these methodologies are not able to capture the high spatial variability of the snow depth distribution present in alpine terrain. Continuous and accurate snow depth mapping has been successfully performed using laser scanning but this method can only cover limited areas and is expensive. We use the airborne ADS80 optoelectronic scanner, acquiring stereo imagery with 0.25 m spatial resolution to derive digital surface models (DSMs) of winter and summer terrains in the neighborhood of Davos, Switzerland. The DSMs are generated using photogrammetric image correlation techniques based on the multispectral nadir and backward-looking sensor data. In order to assess the accuracy of the photogrammetric products, we compare these products with the following independent data sets acquired simultaneously: (a) manually measured snow depth plots; (b) differential Global Navigation Satellite System (dGNSS) points; (c) terrestrial laser scanning (TLS); and (d) ground-penetrating radar (GPR) data sets. We demonstrate that the method presented can be used to map snow depth at 2 m resolution with a vertical depth accuracy of ±30 cm (root mean square error) in the complex topography of the Alps. The snow depth maps presented have an average accuracy that is better than 15 % compared to the average snow depth of 2.2 m over the entire test site.

  4. 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?

  5. 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

  6. Some fundamentals of handheld snow surface thermography

    NASA Astrophysics Data System (ADS)

    Shea, C.; Jamieson, B.

    2011-02-01

    This paper presents the concepts needed to perform snow surface thermography with a modern thermal imager. Snow-specific issues in the 7.5 to 13 μm spectrum such as ice emissivity, photographic angle, operator heating, and others receive detailed review and discussion. To illustrate the usefulness of this measurement technique, various applications are presented. These include detecting spatial temperature variation on snow pit walls and measuring the dependence of heat conduction on grain type.

  7. Some fundamentals of handheld snow surface thermography

    NASA Astrophysics Data System (ADS)

    Shea, C.; Jamieson, B.

    2010-08-01

    This paper presents the concepts needed to perform snow surface thermography with a modern thermal imager. Snow-specific issues in the 7.5 to 13 μm spectrum such as ice emissivity, photographic angle, operator heating, and others receive detailed review and discussion. To illustrate the usefulness of this measurement technique, various applications are presented. These include detecting spatial temperature variation on snow pit walls and measuring the dependence of heat conduction on grain type.

  8. 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.

  9. 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.

  10. Brief communication "Snow profile associated measurements (SPAM) - a new instrument for quick snow profile measurements"

    NASA Astrophysics Data System (ADS)

    Lahtinen, P.

    2011-06-01

    A new instrument concept (SPAM) for snow profile associated measurements is presented. The potential of the concept is demonstrated by presenting preliminary results obtained with the prototype instrument. With this concept it is possible to retrieve rapid snow profiles of e.g. light extinction, reflectance, temperature and snow layer structure with high vertical resolution. As a side-product, also snow depth is retrieved.

  11. Effect of unsteady wind on drifting snow

    NASA Astrophysics Data System (ADS)

    Cierco, F.-X.; Naaim-Bouvet, F.; Naaim, M.

    2003-04-01

    Wind is not always a steady flow. It can oscillate producing blasts. However most of the current numerical models of drifting snow are constrained by one major assumption : forcing winds are steady and uniform. Experiments done in the CSTB climatic wind tunnel (with a data acquisition frequency of 1 Hz both for wind and drifting snow) showed that drifting snow is in a state of permanent disequilibrium in the presence of fluctuating airflows : mass flux and velocity were poorly matched. However, the study of wind and drifting snow gust factors done at Col du Lac Blanc (parameters recorded every 15 min with a scan rate of 1 s) shown that the largest drifting snow episodes appear during periods of roughly constant strong wind whereas a short but strong blast does not produce significant drifting snow. In order to better understand the effect of unsteady wind on drifting snow processes, these first investigations have been completed during winter 2003 by increasing the acquisition frequency during snow storms at Col du Lac Blanc using an ultrasonic anemometer and a profile of six drifting snow acoustic sensors set up side by side.

  12. 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.

  13. The reflectance characteristics of snow covered surfaces

    NASA Technical Reports Server (NTRS)

    Batten, E. S.

    1979-01-01

    Data analysis techniques were developed to most efficiently use available satellite measurements to determine and understand components of the surface energy budget for ice and snow-covered areas. The emphasis is placed on identifying the important components of the heat budget related to snow surfaces, specifically the albedo and the energy consumed in the melting process. Ice and snow charts are prepared by NOAA from satellite observations which map areas into three relative reflectivity zones. Field measurements are analyzed of the reflectivity of an open snow field to assist in the interpretation of the NOAA reflectivity zones.

  14. 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

  15. 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.

  16. 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.

  17. Blending the Basics.

    ERIC Educational Resources Information Center

    McCampbell, Bill

    2001-01-01

    Blended e-learning approaches combine the power of the Internet with existing class events or assignments. Inexpensive tools include electronic mail, keyboarding instruction, online research, streamed video or audio clips, message boards, chat rooms, scanned class reading assignments, and online assessments. IT buzzwords are decoded. (MLH)

  18. 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

  19. 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

  20. Weekly LiDAR snow depth mapping for operational snow hydrology - the NASA JPL Airborne Snow Observatory (Invited)

    NASA Astrophysics Data System (ADS)

    Deems, J. S.; Painter, T. H.; McGurk, B. J.

    2013-12-01

    Operational hydrologic simulation and forecasting in snowmelt-dominated watersheds currently relies on indices of snow accumulation and melt from measurements at a small number of point locations or geographically-limited manual surveys. These data sources cannot adequately characterize the spatial distribution of snow depth/water equivalent, which is the primary determinant of snowpack volume and runoff rates. The NASA JPL Airborne Snow Observatory's airborne laser scanning system maps snow depth at high spatial and temporal resolutions, providing an unprecedented snowpack monitoring capability and enabling a new operational paradigm. In the Spring of 2013, the ASO mapped snow depth in the Tuolumne River Basin in California's Yosemite National Park on a nominally weekly basis, and provided fast-turnaround spatial snow depth and water equivalent maps to the operators of Hetch Hetchy Reservoir, the water supply for 2.5 million people on the San Francisco peninsula. These products enabled more accurate runoff simulation and optimal reservoir management in a year of very low snow accumulation. We present the initial results from this new application of multi-temporal LiDAR mapping in operational snow hydrology.

  1. The Persistent Life of Snow (Invited)

    NASA Astrophysics Data System (ADS)

    Hiemstra, C. A.; Liston, G. E.; Elder, K.; Sturm, M.

    2009-12-01

    Snow is an essential element linking mountains and poles. In high-elevation and high-latitude environments, snow is the dominant precipitation form, and observations suggest snowpacks in both these areas are being altered with climate change directly (higher temperatures) and indirectly (vegetation change). Snow’s substantial control on energy balance, water resources, and ecosystem processes make it a key variable in understanding climate change ramifications in both mountain and polar systems. In spite of its broad importance, snow remains difficult to accurately quantify on many landscapes and over a wide range of spatial and temporal scales. Because of its interactions with the atmosphere and surrounding landscape, snow is inherently dynamic and a challenge to measure and model. In both mountainous and Arctic domains, it is often transported by wind and interacts with topography and vegetation to form a heterogeneous distribution in both space and time. This heterogeneous distribution imparts numerous effects on ecosystem structure and function and land-atmosphere surface fluxes; it also obfuscates analyses of long-term trends. Both middle latitude mountains and the Arctic are experiencing changes in vegetation, precipitation, and air temperature. These accompany attendant changes in the timing and spatial distributions of snow properties, characteristics, and quantities. We will describe tools, techniques, challenges, and outcomes of measuring and modeling snow accumulation and ablation in snowy environments ranging from low to high elevations and middle to high northern latitudes, with a particular focus on the common snow-related impacts of climate and vegetation changes in these two environments. We will look at middle- and high-latitude snow-vegetation interactions within shrubland environments and present improved ways to represent snow-atmosphere interactions within these landscapes. We will describe the potential ramifications of widespread bark

  2. 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)

  3. 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.

  4. Model simulations of the modulating effect of the snow cover in a rain on snow event

    NASA Astrophysics Data System (ADS)

    Wever, N.; Jonas, T.; Fierz, C.; Lehning, M.

    2014-05-01

    In October 2011, the Swiss Alps encountered a marked rain on snow event when a large snowfall on 8 and 9 October was followed by intense rain on the 10th. This resulted in severe flooding in some parts of Switzerland. Model simulations were carried out for 14 meteorological stations in two regions of the Swiss Alps using the detailed physically-based snowpack model SNOWPACK. The results show that the snow cover has a strong modulating effect on the incoming rainfall signal on the sub-daily time scales. The snowpack runoff dynamics appears to be strongly dependent on the snow depth at the onset of the rain. Deeper snow covers have more storage potential and can absorb all rain and meltwater in the first hours, whereas the snowpack runoff from shallow snow covers reacts much quicker. It has been found that after about 4-6 h, the snowpack produced runoff and after about 11-13 h, total snowpack runoff becomes higher than total rainfall as a result of additional snow melt. These values are strongly dependent on the snow height at the onset of rainfall as well as precipitation and melt rates. An ensemble model study was carried out, in which meteorological forcing and rainfall from other stations were used for repeated simulations at a specific station. Using regression analysis, the individual contributions of rainfall, snow melt and the storage could be quantified. It was found that once the snowpack is producing runoff, deep snow covers produce more runoff than shallow ones. This could be associated with a higher contribution of the storage term. This term represents the recession curve from the liquid water storage and snowpack settling. In the event under study, snow melt in deep snow covers also turned out to be higher than in the shallow ones, although this is rather accidental. Our results show the dual nature of snow covers in rain on snow events. Snow covers initially absorb important amounts of rain water, but once meltwater is released by the snow cover, the

  5. 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…

  6. Sampling designs for heterogeneous snow distributions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Intensive snow surveys of mountain basins are the most accurate means of characterizing the heterogeneous mosaic of snow distribution typically present. The collection of survey data is however costly and time-consuming and important decisions are required to adequately sample larger basins. In this...

  7. 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)

  8. 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.

  9. 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…

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Measuring Wind Ventilation of Dense Surface Snow

    NASA Astrophysics Data System (ADS)

    Drake, S. A.; Huwald, H.; Selker, J. S.; Higgins, C. W.; Lehning, M.; Thomas, C. K.

    2014-12-01

    Wind ventilation enhances exposure of suspended, canopy-captured and corniced snow to subsaturated air and can significantly increase sublimation rate. Although sublimation rate may be high for highly ventilated snow this snow regime represents a small fraction snow that resides in a basin potentially minimizing its influence on snow mass balance. In contrast, the vast majority of a seasonal snowpack typically resides as poorly ventilated surface snow. The sublimation rate of surface snow is often locally so small as to defy direct measurement but regionally pervasive enough that the integrated mass loss of frozen water across a basin may be significant on a seasonal basis. In a warming climate, sublimation rate increases even in subfreezing conditions because the equilibrium water vapor pressure over ice increases exponentially with temperature. To better understand the process of wintertime surface snow sublimation we need to quantify the depth to which turbulent and topographically driven pressure perturbations effect air exchange within the snowpack. Hypothetically, this active layer depth increases the effective ventilated snow surface area, enhancing sublimation above that given by a plane, impermeable snow surface. We designed and performed a novel set of field experiments at two sites in the Oregon Cascades during the 2014 winter season to examine the spectral attenuation of pressure perturbations with depth for dense snow as a function of turbulence intensity and snow permeability. We mounted a Campbell Scientific Irgason Integrated CO2 and H2O Open Path Gas Analyzer and 3-D Sonic Anemometer one meter above the snow to capture mean and turbulent wind forcing and placed outlets of four high precision ParoScientific 216B-102 pressure transducers at different depths to measure the depth-dependent pressure response to wind forcing. A GPS antenna captured data acquisition time with sufficient precision to synchronize a Campbell Scientific CR-3000 acquiring

  16. 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

  17. 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

  18. 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

  19. Air-snow interactions and atmospheric chemistry.

    PubMed

    Dominé, Florent; Shepson, Paul B

    2002-08-30

    The presence of snow greatly perturbs the composition of near-surface polar air, and the higher concentrations of hydroxyl radicals (OH) observed result in a greater oxidative capacity of the lower atmosphere. Emissions of nitrogen oxides, nitrous acid, light aldehydes, acetone, and molecular halogens have also been detected. Photolysis of nitrate ions contained in the snow appears to play an important role in creating these perturbations. OH formed in the snowpack can oxidize organic matter and halide ions in the snow, producing carbonyl compounds and halogens that are released to the atmosphere or incorporated into snow crystals. These reactions modify the composition of the snow, of the interstitial air, and of the overlying atmosphere. Reconstructing the composition of past atmospheres from ice-core analyses may therefore require complex corrections and modeling for reactive species. PMID:12202818

  20. 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.

  1. 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.

  2. Air-Snow Interactions and Atmospheric Chemistry

    NASA Astrophysics Data System (ADS)

    Dominé, Florent; Shepson, Paul B.

    2002-08-01

    The presence of snow greatly perturbs the composition of near-surface polar air, and the higher concentrations of hydroxyl radicals (OH) observed result in a greater oxidative capacity of the lower atmosphere. Emissions of nitrogen oxides, nitrous acid, light aldehydes, acetone, and molecular halogens have also been detected. Photolysis of nitrate ions contained in the snow appears to play an important role in creating these perturbations. OH formed in the snowpack can oxidize organic matter and halide ions in the snow, producing carbonyl compounds and halogens that are released to the atmosphere or incorporated into snow crystals. These reactions modify the composition of the snow, of the interstitial air, and of the overlying atmosphere. Reconstructing the composition of past atmospheres from ice-core analyses may therefore require complex corrections and modeling for reactive species.

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. Impact of snow on surface brightness

    NASA Astrophysics Data System (ADS)

    Kukla, George J.; Brown, Jeffrey A.

    The snow-covered land surface has different albedo than the snow-free surface, depending primarily on the type and density of the vegetation, the relief, and the continuity and age of the snow blanket. This is clearly demonstrated by the winter mosaic of east central Asia shown on the front cover. It is a section of a larger composite assembled from cloud-free satellite images to portray the land surface under continuous snow cover. The mosaic is a valuable tool for distinguishing (from remote positions) snow from clouds and for charting snow cover where illumination is poor. It also can be used to determine relative sensitivity of surface albedo to the occurrence of snow.Segments with a minimum of clouds along the orbital subtrack were selected from the transparencies of the Defense Meteorological Satellite Program (DMSP). Satellite sensors record in the spectral band 0.4-1.2 µm. The satellite is in polar orbit at a mean altitude of 830 km (450 nm) and crosses the equator at approximately local noon. The spatial resolution along the orbital subtrack is about 0.6 km [Dickinson et al., 1974]. The mosaic is assembled from imagery taken between mid-January and mid-February of 1979. The original hard-copy transparencies (on loan from the DMSP library) were reproduced as contact negatives to preserve detail.The snow cover marks the land surface with a characteristic signature that depends on the distribution, density, and type of vegetation; relief; presence of water bodies; distribution and type of land use, etc. This signature can be readily utilized, among others, to distinguish snow-covered land from clouds and from snow-free land [Barnes et al., 1974; Lillesand et al., 1982]. We have compared the brightness fields in the imagery with the vegetation density and land-use patterns charted in the World Forestry Atlas [Wiebecke, 1971].

  8. 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.

  9. 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.

  10. 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.

  11. The impact of parameterising light penetration into snow on the photochemical production of NOx and OH radicals in snow

    NASA Astrophysics Data System (ADS)

    Chan, H. G.; King, M. D.; Frey, M. M.

    2015-03-01

    Snow photochemical processes drive production of chemical trace gases, including nitrogen oxides (NO and NO2), and HOx radicals in snowpacks which are then released to the lower atmosphere. Coupled atmosphere-snow modelling on global scales requires simple parameterisations of actinic flux in snow to reduce computational cost. The disagreement between a physical radiative transfer method and a method based upon the e-folding depth of light-in snow is evaluated. In particular for the photolysis of the nitrate anion (NO3-), the nitrite anion (NO2-) and hydrogen peroxide (H2O2) within snow and photolysis of gas-phase nitrogen dioxide (NO2) within the snowpack interstitial air are considered. The emission flux from the snowpack is estimated as the depth-integrated photolysis rate, v, calculated (a) explicitly with a physical radiative transfer model (TUV), vTUV and (b) with a simple parameterisation based on e-folding depth, vze. The evaluation is based upon the deviation of the ratio of depth-integrated photolysis rate determined by the two methods,vTUV/vze, from unity. The disagreement in depth-integrated photolysis rate between the RT model and e-folding depth parameterisation depends primarily on the photolysis action spectrum of chemical species, solar zenith angle and optical properties of the snowpack, (scattering cross-section and a weak dependence on light absorbing impurity (black carbon) and density). For photolysis of NO2, the NO2- anion, the NO3- anion and H2O2 the ratio vTUV/vze varies within the range of 0.82-1.35, 0.88-1.28 and 0.92-1.27 respectively. The e-folding depth parameterisation underestimates for small solar zenith angles and overestimates at solar zenith angles around 60°. A simple algorithm has been developed to improve the parameterisation which reduced the ratio vTUV/vze to 0.97-1.02, 0.99-1.02 and 0.99-1.03 for photolysis of NO2, the NO2- anion, the NO3- anion and

  12. 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.

  13. 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

  14. 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.

  15. Snow nitrate photolysis in polar regions and the mid-latitudes: Impact on boundary layer chemistry and implications for ice core records

    NASA Astrophysics Data System (ADS)

    Zatko, Maria C.

    The formation and recycling of nitrogen oxides (NOx=NO+NO 2) associated with snow nitrate photolysis has important implications for air quality and the preservation of nitrate in ice core records. This dissertation examines snow nitrate photolysis in polar and mid-latitude regions using field and laboratory based observations combined with snow chemistry column models and a global chemical transport model to explore the impacts of snow nitrate photolysis on boundary layer chemistry and the preservation of nitrate in polar ice cores. Chapter 1 describes how a global chemical transport model is used to calculate the photolysis-driven flux and redistribution of nitrogen across Antarctica, and Chapter 2 presents similar work for Greenland. Snow-sourced NOx is most dependent on the quantum yield for nitrate photolysis as well as the concentration of photolabile nitrate and light-absorbing impurities (e.g., black carbon, dust, organics) in snow. Model-calculated fluxes of snow-sourced NOx are similar in magnitude in Antarctica (0.5--7.8x108 molec cm-2 s -1) and Greenland (0.1--6.4x108 molec cm-2 s-1) because both nitrate and light-absorbing impurity concentrations in snow are higher (by factors of 2 and 10, respectively) in Greenland. Snow nitrate photolysis influences boundary layer chemistry and ice-core nitrate preservation less in Greenland compared to Antarctica largely due to Greenland's proximity to NOx-source regions. Chapter 3 describes how a snow chemistry column model combined with chemistry and optical measurements from the Uintah Basin Winter Ozone Study (UBWOS) 2014 is used to calculate snow-sourced NOx in eastern Utah. Daily-averaged fluxes of snow-sourced NOx (2.9x10 7--1.3x108 molec cm-2 s-1) are similar in magnitude to polar snow-sourced NO x fluxes, but are only minor components of the Uintah Basin boundary layer NOx budget and can be neglected when developing ozone reduction strategies for the region. Chapter 4 presents chemical and optical

  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. 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).

  20. 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.

  1. Snow Storm Blankets Southeastern U.S.

    NASA Technical Reports Server (NTRS)

    2002-01-01

    A new year's storm brought heavy snow to portions of the southeastern United States, with some regions receiving more than a foot in less than two days. By Friday, January 4, 2002, the skies had cleared, and MODIS captured this false-color image showing the extent of the snowfall. Snow cover is red, and extends all the way from Alabama (lower left), up through Georgia, South Carolina, North Carolina, Virginia, and Maryland, including the southern reaches of the Delmarva Peninsula (upper right). Beneath some clouds in West Virginia (top center), snow is also visible on the Allegheny Mountains and the Appalachian Plateau, although it did come from the same storm. Though red isn't the color we associate with snow, scientists often find 'false-color' images more useful than 'true-color' images in certain situations. True-color images are images in which the satellite data are made to look like what our eyes would see, using a combination of red, green, and blue. In a true-color image of this scene, cloud and snow would appear almost identical-both would be very bright white-and would be hard to distinguish from each other. However, at near-infrared wavelengths of light, snow cover absorbs sunlight and therefore appears much darker than clouds. So a false-color image in which one visible wavelength of the data is colored red, and different near-infrared wavelengths are colored green and blue helps show the snow cover most clearly.

  2. 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.

  3. 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.

  4. 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.

  5. Adsorption of phenanthrene on natural snow.

    PubMed

    Domine, Florent; Cincinelli, Alessandra; Bonnaud, Elodie; Martellini, Tania; Picaud, Sylvain

    2007-09-01

    The snowpack is a reservoir for semivolatile organic compounds (SVOCs) and, in particular, for persistent organic pollutants (POPs), which are sequestered in winter and released to the atmosphere or hydrosphere in the spring. Modeling these processes usually assumes that SVOCs are incorporated into the snowpack by adsorption to snow surfaces, but this has never been proven because the specific surface area (SSA) of snow has never been measured together with snow composition. Here we expose natural snow to phenanthrene vapors (one of the more volatile POPs) and measure for the first time both the SSA and the chemical composition of the snow. The results are consistent with an adsorption equilibrium. The measured Henry's law constant is H(Phen)(T) = 2.88 x 10(22) exp(-10660/7) Pa m2 mol(-1), with Tin Kelvin. The adsorption enthalpy is delta H(ads) = -89 +/- 18 kJ mol(-1). We also perform molecular dynamics calculations of phenanthrene adsorption to ice and obtain AHads = -85 +/- 8 kJ mol(-1), close to the experimental value. Results are applied to the adsorption of phenanthrene to the Arctic and subarctic snowpacks. The subarctic snowpack, with a low snow area index (SAI = 1000), is a negligible reservoir of phenanthrene, butthe colder Arctic snowpack, with SAI = 2500, sequesters most of the phenanthrene present in the (snow + boundary layer) system. PMID:17937278

  6. Modeling interannual variability in snow-cover development and melt for a semiarid mountain catchment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Observed changes in mid-elevation snowcover and duration have raised concerns over future impacts of global warming on snowpack dependent water resources and ecosystems. However, predictions of future changes in snow hydrology over mountain basins are complicated by natural variability in climate co...

  7. 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).

  8. 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.

  9. Extreme values of snow-related variables in Mediterranean regions: trends and long-term forecasting in Sierra Nevada (Spain)

    NASA Astrophysics Data System (ADS)

    Pérez-Palazón, M. J.; Pimentel, R.; Herrero, J.; Aguilar, C.; Perales, J. M.; Polo, M. J.

    2015-06-01

    Mountain areas in Mediterranean regions constitute key monitoring points for climate variability and its impacts, but long time datasets are not always available due to the difficult access to high areas, relevant for capturing temperature and precipitation regimes, and the predominance of cloudy remote sensing images during the snow season. Sierra Nevada National Park (South Spain), with altitudes higher than 3500 m a.s.l., is part of the Global Change in Mountain Regions network. Snow occurrence just 40 km from the seaside determines a wide range of biodiversity, a snowmelt fluvial regime, and the associated ecosystem services. This work presents the local trend analysis of weather variables at this area together with additional snow-related variables. For this, long term point and distributed observations from weather stations and remote sensing sources were studied and used as input and calibration datasets of a physically based snow model to derive long term series of mean and maximum daily fraction of snow covered area, annual number of days with snow, annual number of days with precipitation, mean and maximum mean daily snow water equivalent, and snowmelt and evaporation volumes. The joint analysis of weather and snow variables showed a decrease trend in the persistence and extent of the snow cover area. The precipitation regime, rather than the temperature trend, seems to be the most relevant driver on the snow regime forcing in Mediterranean areas. This poses a constraint for rigorous scenario analysis in these regions, since the precipitation pattern is poorly approximated by climatic models in these regions.

  10. 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

  11. 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

  12. 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

  13. 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.

  14. "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

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. The role of snow cover affecting boreal-arctic soil freeze-thaw and carbon dynamics

    NASA Astrophysics Data System (ADS)

    Yi, Y.; Kimball, J. S.; Rawlins, M. A.; Moghaddam, M.; Euskirchen, E. S.

    2015-10-01

    Northern Hemisphere permafrost affected land areas contain about twice as much carbon as the global atmosphere. This vast carbon pool is vulnerable to accelerated losses through mobilization and decomposition under projected global warming. Satellite data records spanning the past 3 decades indicate widespread reductions (~ 0.8-1.3 days decade-1) in the mean annual snow cover extent and frozen-season duration across the pan-Arctic domain, coincident with regional climate warming trends. How the soil carbon pool responds to these changes will have a large impact on regional and global climate. Here, we developed a coupled terrestrial carbon and hydrology model framework with a detailed 1-D soil heat transfer representation to investigate the sensitivity of soil organic carbon stocks and soil decomposition to climate warming and changes in snow cover conditions in the pan-Arctic region over the past 3 decades (1982-2010). Our results indicate widespread soil active layer deepening across the pan-Arctic, with a mean decadal trend of 6.6 ± 12.0 (SD) cm, corresponding to widespread warming. Warming promotes vegetation growth and soil heterotrophic respiration particularly within surface soil layers (≤ 0.2 m). The model simulations also show that seasonal snow cover has a large impact on soil temperatures, whereby increases in snow cover promote deeper (≥ 0.5 m) soil layer warming and soil respiration, while inhibiting soil decomposition from surface (≤ 0.2 m) soil layers, especially in colder climate zones (mean annual T ≤ -10 °C). Our results demonstrate the important control of snow cover on northern soil freeze-thaw and soil carbon decomposition processes and the necessity of considering both warming and a change in precipitation and snow cover regimes in characterizing permafrost soil carbon dynamics.

  20. 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.

  1. 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.

  2. 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

  3. Snow surface roughness as a function of terrain parameters and snow depth distribution

    NASA Astrophysics Data System (ADS)

    Veitinger, J.; Sovilla, B.; Purves, R.

    2012-12-01

    During and after a snowfall, wind, snow gliding and avalanches redistribute snow and smooth the geomorphology of the terrain by filling irregularities. Terrain smoothing is believed to be an important factor in avalanche formation. In avalanche release zones, it influences fracture initiation and propagation as well as the resistance to slab motion and thus affects its location and extension. In avalanche paths, terrain smoothing changes the terrain-avalanche friction and thus has an impact on avalanche dynamics. Moreover, smoothing of terrain irregularities by snow also affects surface heat transfer and energy balance as well as snow depth distribution. Thus, understanding snow smoothing on topography is very important in avalanche hazard assessment, run-off modelling and water resource management. To characterize the smoothing effect of snow on terrain we use the concept of roughness. Roughness is calculated for several snow surfaces and its corresponding underlying terrain within two selected high alpine test sites in the Swiss Alps. High resolution snow depth measurements were performed by airborne and terrestrial LIDAR to produce the elevation models of the snow covered terrain. The difference in surface roughness between snow cover and terrain is modelled as a function of geomorphological parameters (terrain roughness and slope) and snow depth (mean and standard deviation) and ultimately validated against the experimental data. The model uses a multi-scale approach in assessing the different parameters and results for different scales are presented. Finally, we discuss to which extent snow depth distribution can be explained by terrain parameters and in particular by terrain roughness.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Progress in radar snow research. [Brookings, South Dakota

    NASA Technical Reports Server (NTRS)

    Stiles, W. H.; Ulaby, F. T.; Fung, A. K.; Aslam, A.

    1981-01-01

    Multifrequency measurements of the radar backscatter from snow-covered terrain were made at several sites in Brookings, South Dakota, during the month of March of 1979. The data are used to examine the response of the scattering coefficient to the following parameters: (1) snow surface roughness, (2) snow liquid water content, and (3) snow water equivalent. The results indicate that the scattering coefficient is insensitive to snow surface roughness if the snow is drv. For wet snow, however, surface roughness can have a strong influence on the magnitude of the scattering coefficient. These observations confirm the results predicted by a theoretical model that describes the snow as a volume of Rayleig scatterers, bounded by a Gaussian random surface. In addition, empirical models were developed to relate the scattering coefficient to snow liquid water content and the dependence of the scattering coefficient on water equivalent was evaluated for both wet and dry snow conditions.

  12. 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…

  13. 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.

  14. 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.

  15. 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.

  16. Sierra Nevada snow melt from SMS-2

    NASA Technical Reports Server (NTRS)

    Breaker, L. C.; Mcmillan, M. C.

    1975-01-01

    A film loop from SMS-2 imagery shows snow melt over the Sierra Nevadas from May 10 to July 8, 1975. The sequence indicates a successful application of geostationary satellite data for monitoring dynamic hydrologic conditions.

  17. 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)

  18. Mount Everest snow plume: A case study

    NASA Astrophysics Data System (ADS)

    Moore, G. W. K.

    2004-11-01

    A plume of snow blowing from the summit of Mount Everest is one of the most iconic images of the world's highest mountain. Its presence provides evidence of the strong jet stream winds that can buffet the mountain. In January 2004, astronauts onboard the International Space Station (ISS) observed a 15 to 20 km long snow plume emanating from the summit of Mount Everest. Remarkably little is known about these plumes and the role that they play in the redistribution of snow in the high Himalaya. In this paper we use a variety of meteorological datasets to show that the observed plume was the combination of high winds associated with the East Asian Jet Stream (EAJS) and a heavy snowfall that had occurred over the Himalaya during the preceding week. A simple model of a blown snow plume is shown to be consistent with the observations made from the ISS.

  19. 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).

  20. Photochemical degradation of PCBs in snow.

    PubMed

    Matykiewiczová, Nina; Klánová, Jana; Klán, Petr

    2007-12-15

    This work represents the first laboratory study known to the authors describing photochemical behavior of persistent organic pollutants in snow at environmentally relevant concentrations. The snow samples were prepared by shock freezing of the corresponding aqueous solutions in liquid nitrogen and were UV-irradiated in a photochemical cold chamber reactor at -25 degrees C, in which simultaneous monitoring of snow-air exchange processeswas also possible. The main photodegradation pathway of two model snow contaminants, PCB-7 and PCB-153 (c approximately 100 ng kg(-1)), was found to be reductive dehalogenation. Possible involvement of the water molecules of snow in this reaction has been excluded by performing the photolyses in D2O snow. Instead, trace amounts of volatile organic compounds have been proposed to be the major source of hydrogen atom in the reduction, and this hypothesis was confirmed by the experiments with deuterated organic cocontaminants, such as d6-ethanol or d8-tetrahydrofuran. It is argued that bimolecular photoreduction of PCBs was more efficient or feasible than any other phototransformations under the experimental conditions used, including the coupling reactions. The photodegradation of PCBs, however, competed with a desorption process responsible for the pollutant loss from the snow samples, especially in case of lower molecular-mass congeners. Organic compounds, apparently largely located or photoproduced on the surface of snow crystals, had a predisposition to be released to the air but, at the same time, to react with other species in the gas phase. It is concluded that physicochemical properties of the contaminants and trace co-contaminants, their location and local concentrations in the matrix, and the wavelength and intensity of radiation are the most important factors in the evaluation of organic contaminants' lifetime in snow. Based on the results, it has been estimated that the average lifetime of PCBs in surface snow, connected

  1. Application of LANDSAT imagery for snow mapping in Norway

    NASA Technical Reports Server (NTRS)

    Odegaard, H.; Skorve, J. E. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. During the summer seasons of 1975 and 1976, the snow cover was successfully monitored and measured in the four basins. By using elevation distributions for these basins combined with the measured snow cover percentages, the equivalent snow line altitude was calculated. Equivalent snow line altitude was used in accordance with Mark Meier's definition. Cumulative runoff data were collected for the basins. Tables showing percentage snow cover versus cumulative runoff were worked out for 1975.

  2. Improved Sampling Strategy for Arctic Snow Distribution

    NASA Astrophysics Data System (ADS)

    Homan, J. W.; Kane, D. L.

    2012-12-01

    Watershed scale hydrologic models require good estimates of the spatially distributed snow water equivalent (SWE) at winter's end. Snow on the ground in treeless Arctic environments is susceptible to significant wind redistribution, which results in very heterogeneous snowpacks, with greater quantities of snow collection in depressions, valley bottoms and leeward sides of ridges. In the Arctic, precipitation and snow gauges are very poor indicators of the actual spatial snowpack distribution, particularly at winter's end when ablation occurs. Snow distribution patterns are similar from year to year because they are largely controlled by the interaction of topography, vegetation, and consistent weather patterns. From one year to the next, none of these controls radically change. Consequently, shallow and deep areas of snow tend to be spatially predetermined, resulting in depth (or SWE) differences that may vary as a whole, but not relative to each other, from year to year. This work attempts to identify snowpack distribution patterns at a watershed scale in the Arctic. Snow patterns are intended to be established by numerous field survey points from past end-of-winter field campaigns. All measured SWE values represent a certain percentage of a given watershed. Some may represent small-scale anomalies (local scale), while others might represent a large-scale area (regional scale). Since we are interested in identifying snowpack distribution patterns at a watershed scale, we aim to develop an improved point-source sampling strategy that only surveys regional representative areas. This will only be possible if the extreme high and low SWE measurements that represent local-scale snow conditions are removed in the sampled data set. The integration of these pattern identification methods will produce a hybrid approach to identifying snowpack distribution patterns. Improvement in our estimates of the snowpack distribution will aid in the forecasting of snowmelt runoff

  3. 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.

  4. Snow darkening caused by black carbon emitted from fires

    NASA Astrophysics Data System (ADS)

    Engels, Jessica; Kloster, Silvia; Bourgeois, Quentin

    2014-05-01

    We implemented the effect of snow darkening caused by black carbon (BC) emitted from forest fires into the Max Planck Institute for Meteorology Earth System Model (MPI-M ESM) to estimate its potential climate impact of present day fire occurrence. Considerable amounts of black carbon emitted from fires are transported into snow covered regions. Already very small quantities of black carbon reduce the snow reflectance, with consequences for snow melting and snow spatial coverage. Therefore, the SNICAR (SNow And Ice Radiation) model (Flanner and Zender (2005)) is implemented in the land surface component (JSBACH) of the atmospheric general circulation model ECHAM6, developed at the MPI-M. The SNICAR model includes amongst other processes a complex calculation of the snow albedo depending on black carbon in snow and snow grain growth depending on water vapor fluxes for a five layer snow scheme. For the implementation of the SNICAR model into the one layer scheme of ECHAM6-JSBACH, we used the SNICAR-online version (http://snow.engin.umich.edu). This single-layer simulator provides the albedo of snow for selectable combinations of impurity content (e.g. black carbon), snow grain size, and incident solar flux characteristics. From this scheme we derived snow albedo values for black carbon in snow concentrations ranging between 0 and 1500 ng(BC)/g(snow) and for different snow grain sizes for the visible (0.3 - 0.7 µm) and near infrared range (0.7 - 1.5 µm). As snow grains grow over time, we assign different snow ages to different snow grain sizes (50, 150, 500, and 1000 µm). Here, a radius of 50 µm corresponds to new snow, whereas a radius of 1000 µm corresponds to old snow. The required snow age is taken from the BATS (Biosphere Atmosphere Transfer Scheme, Dickinson et al. (1986)) snow albedo implementation in ECHAM6-JSBACH. Here, we will present an extended evaluation of the model including a comparison of modeled black carbon in snow concentrations to observed

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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. PMID:26317458

  11. Viscoelastic Properties of Polymer Blends

    NASA Technical Reports Server (NTRS)

    Hong, S. D.; Moacanin, J.; Soong, D.

    1982-01-01

    Viscosity, shear modulus and other viscoelastic properties of multicomponent polymer blends are predicted from behavior of individual components, using a mathematical model. Model is extension of two-component-blend model based on Rouse-Bueche-Zimm theory of polymer viscoelasticity. Extension assumes that probabilities of forming various possible intracomponent and intercomponent entanglements among polymer molecules are proportional to relative abundances of components.

  12. 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…

  13. 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…

  14. 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...

  15. 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…

  16. 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

  17. 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.

  18. [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

  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. Simulation of snow cover in two non-monitored Andean catchments using VIC hydrological model with remote sensing validation

    NASA Astrophysics Data System (ADS)

    Vargas, Ximena; Paez, Felipe

    2014-05-01

    Snow plays a key role in the hydrologic cycle over mountainous areas of Central Chile. Its principal function is to store a large amount of water during winter season and release it in spring creating a time gap between precipitation and streamflow. Surface observations of snow like snow pillows or snow depths measurements are unable to capture fully the spatial and temporal variability of snow. Moreover, in this area is easy to find volcanoes and mountains over 6000 masl, but registers are found generally under 3000 masl. Nevertheless, additional information about snow can be obtained from hydrological models that are forced with surface meteorological variables (precipitation, air temperature, wind, etc.) and represent the effects of topography, soil and vegetation on snow processes, but these forcing registers are equally poor across this area. In this work, a combined in situ measurement and MODIS land surface temperature images were related to create daily maximum and minimum air temperature maps for two catchments of Central Chile located in Los Andes mountains, Colorado antes Junta Olivares and Olivares antes Junta Colorado, without any meteorological records available. To overcome the lack of this information we used the results of WRF (Weather Research and Forecasting) for wind and a vicinity gauge for precipitation. The aim of this work was to validate the dynamics of snow cover comparing MODIS snow cover images with hydrological model results once streamflow calibration was performed. In this case, a gridded or "checkerboard type" model was required to compare both results. The chosen model was the Variable Infiltration Capacity (VIC) because it grids spatially the results and recently was released the "Data Set Global VIC Input Parameters at 0.5-Degree Resolution" reducing calibration effort time. However, VIC model has been used to assess water availability on continental and global scales using mainly 0.125 to 2 degree resolutions, a very low

  1. 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.

  2. Long-term effects of a snow-pack model on Greenland melt

    NASA Astrophysics Data System (ADS)

    Krapp, Mario; Ganopolski, Andrey

    2013-04-01

    Meltwater from Greenland is expected to increase within the next centuries thereby affecting global sea level rise. However, the timing and magnitude of the Greenland melt remains rather unclear because of the different processes involved. During the ablation season, for example, meltwater can refreeze within the snow pack. Aging of snow and snow densification are other processes that need to be considered for future Greenland melt projections. Models that include these physical processes have been widely used for avalanche forecasts. These so-called snow-pack models are also included in Regional Climate Models (RCMs) which have been applied to the Greenland ice sheet. However, RCMs are computationally too expensive to resolve the dynamics of ice sheets on centennial to multi-millennial time scales. We present a setup for the Greenland melt on longer time scales using a snow-pack model based on surface mass and energy balance considerations. We compare our approach to simple melt parametrizations like the positive-degree-day approach or the insolation-temperature melt method to quantify the long-term effect on Greenland melt.

  3. 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…

  4. 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

  5. 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.

  6. 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).

  7. A spatial-temporal-spectral blending model using satellite images

    NASA Astrophysics Data System (ADS)

    Zhang, L.; Fu, D.; Sun, X.; Chen, H.; She, X.

    2016-04-01

    Due to the budget and technical limitations, remote sensing sensor designs trade spatial resolution, swath width and spectral resolution. Consequently, no sensor can provide high spatial resolution, high temporal resolution and high spectral resolution simultaneously. However, the ability of Earth observation at fine resolution is urgently needed for global change science. One possible solution is to “blend” the reflectance from a variety of satellite data sources, including those providing high spatial resolution and less frequent coverage (e.g., Landsat Thematic Mapper, TM), daily global data (e.g., Moderate Resolution Imaging Spectroradiometer, MODIS), and high spectral resolution and infrequent revisit cycle (e.g., Hyperion). However, the previous algorithms for blending multi-source remotely sensed data have some shortcomings, especially with regard to hyperspectral information. This study has developed a SPAtial-Temporal-Spectral blending model (SPATS) that can simulate surface reflectance with high spatial-temporal-spectral resolution. SPATS is based on an existing spatial-temporal image blending model and a spatial-spectral image blending model. The performance of SPATS was tested with both simulated and observed satellite data, using Landsat TM, Hyperion and MODIS data, as well as heterogeneous landscapes as examples. The results show that the high spatial-temporal-spectral resolution reflectance data can be applied to investigations of global landscapes that are changing at different temporal scales.

  8. 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.

  9. Snow Study at Centre for Atmospheric Research Experiments: Variability of snow fall velocity, density and shape

    NASA Astrophysics Data System (ADS)

    Jung, Eunsil

    In this work, snow data, collected at the Centre for Atmospheric Research Experiments (CARE) site during the winter of 2005/06 as part of the Canadian CALIPSO/CloudSat Validation Project (C3VP) were analyzed with various goals in mind: 1) investigate the effects of surface temperature and system depth on the snow fall velocity and particle size . . distribution, 2) find the variables that control the relationships between snow fall velocity and size (control variables), 3) retrieve the coefficient and the exponent in the power-law mass-size relations used in snow reflectivity, 4) estimate vertical air motion and 5) describe the shape of snowflakes that can be used in polarimetric studies of snow. It also includes considerable calibration work on the Hydrometeor Velocity and Shape Detector (HVSD); as well as sensitivity testing for radar calibration and Mie-scattering effect on snow density. Snow events were classified into several categories according to the radar echo vertical extent (H), surface and echo top temperatures (T s, Tt), to find their effects on snow fall velocity and particle size distribution. Several case studies, including situations of strong turbulence, were also examined. Simple and multiple correlation analyses between control variables and parameters of the power-law size-velocity relationship were carried out for 13 snow cases having a high R2 between their mean snowflakes fall velocity and the v-D fitted curve, in order to find the control variables of power-law v-D relations. Those cases were all characterized by single layered precipitation with different echo depth, surface and echo top temperatures. Results show that the exponent "b" in v-D power-law relationship has little effect on the variability of snow fall velocity; all control variables (T s, Tt, H) correlate much better to the coefficient "a" than to the exponent "b", leading to a snow fall velocity that can be simulated with a varying coefficient "a" and a fixed exponent "b" (v

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. The impact of parameterising light penetration into snow on the photochemical production of NOx and OH radicals in snow

    NASA Astrophysics Data System (ADS)

    Chan, H. G.; King, M. D.; Frey, M. M.

    2015-07-01

    Snow photochemical processes drive production of chemical trace gases in snowpacks, including nitrogen oxides (NOx = NO + NO2) and hydrogen oxide radical (HOx = OH + HO2), which are then released to the lower atmosphere. Coupled atmosphere-snow modelling of theses processes on global scales requires simple parameterisations of actinic flux in snow to reduce computational cost. The disagreement between a physical radiative-transfer (RT) method and a parameterisation based upon the e-folding depth of actinic flux in snow is evaluated. In particular, the photolysis of the nitrate anion (NO3-), the nitrite anion (NO2-) and hydrogen peroxide (H2O2) in snow and nitrogen dioxide (NO2) in the snowpack interstitial air are considered. The emission flux from the snowpack is estimated as the product of the depth-integrated photolysis rate coefficient, v, and the concentration of photolysis precursors in the snow. The depth-integrated photolysis rate coefficient is calculated (a) explicitly with an RT model (TUV), vTUV, and (b) with a simple parameterisation based on e-folding depth, vze. The metric for the evaluation is based upon the deviation of the ratio of the depth-integrated photolysis rate coefficient determined by the two methods, vTUV/vze, from unity. The ratio depends primarily on the position of the peak in the photolysis action spectrum of chemical species, solar zenith angle and physical properties of the snowpack, i.e. strong dependence on the light-scattering cross section and the mass ratio of light-absorbing impurity (i.e. black carbon and HULIS) with a weak dependence on density. For the photolysis of NO2, the NO2- anion, the NO3- anion and H2O2 the ratio vTUV/vze varies within the range of 0.82-1.35, 0.88-1.28, 0.93-1.27 and 0.91-1.28 respectively. The e-folding depth parameterisation underestimates for small solar zenith angles and overestimates at solar zenith angles around 60° compared to the RT method. A simple algorithm has been developed to improve

  15. 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.

  16. Impact of climate change on snow distribution in Japan estimated using data from the remote weather stations (AMeDAS) and Spot VGT

    NASA Astrophysics Data System (ADS)

    Kominami, Y.; Asaoka, Y.; Tsuyama, I.; Tanaka, N.

    2010-12-01

    Change of the amount of snow by climate change is possibly remarkable in Japan, because air temperature is relatively high as snowy area in the world. And the change of the amount of snow cover highly depends on the supply form of precipitation (rain or snow) in winter corresponding to the change of the temperature in addition to the change of precipitation. And vegetation distribution of Japan is highly affected by snow conditions (snow duration and snow accumulation). To evaluate the change of snow condition in Japan climate change, daily change of SWE of 1km mesh was estimated using daily precipitation and air temperature of AMeDAS(Automated Meteorological Data Acquisition System) data. And using this model, changes of SWE and snow cover period were estimated in condition of global warming. Daily air temperature and precipitation on 1km mesh were estimated over all of Japan by interpolation of the AMeDAS data. AMeDAS is a system that observes the temperature and precipitation, etc. per hour automatically in about 1,300 places (about 17km spacing) in Japan. And daily change of SWE of each point was calculated using degree-day method and threshold temperature for the distinction between snow and rain using these data. We used precipitation and air temperature data of AMeDAS for 23 years from 1980 to 2002. Snow melt coefficient and elevation dependency of winter precipitation of each grid were optimized by snow duration estimated using satellite data (S3 index of Spot VGT) from 1990 to 2000 To estimate the change in the snow accumulation for the years from 2031 to 2051 and from 2081 to 2100, we used the climate change scenario of a high-resolution Regional Climate Model with a 20-km mesh size (RCM20) developed at the Meteorological Research Institute based on the Special Report for Emission Scenario (SRES)-A2. Estimated snow duration was evaluated in 10 points of mountainous snow measurement stations. Averaged error was about 4 days from 1980 to 1999. And estimated

  17. Projection of snow cover changes over China under RCP scenarios

    NASA Astrophysics Data System (ADS)

    Ji, Z.; Kang, S.

    2012-12-01

    Snow cover changes in the middle (2040-2059) and end (2080-2099) of the 21st century over China were investigated with a regional climate model, nested within the global model BCC_CSM1.1. The simulations had been conducted for the period of 1950 to 2099 under the RCP4.5 and RCP8.5 scenarios. Results show that the model perform well in representing contemporary (1986-2005) spatial distributions of snow cover days (SCDs) and snow water equivalent (SWE). However, some differences between observation and simulation were detected. Under the RCP4.5 scenarios, SCDs are shortened by 10~20 and 20~40 days during the middle and end of the 21st century, respectively. Whereas simulated SWE is lowered by 0.1~10 mm in most areas over the Tibetan Plateau (TP). On the other hand, the spatial distributions of SWE are reversed between the middle and end terms in the northeast China. Furthermore, compared with the changes of RCP4.5 scenario, SCDs are reduced by 5~20 days in the middle period under RCP8.5 scenario with even larger decreasing amplitude in the end term. SWE was lowered by 0.1~2.5 mm in most areas except the northeast of China in middle term under RCP8.5 scenario. The great center of SCDs and SWE changes are always located over TP. The regional mean of SCDs and SWE for the TP and for China display a declining trend from 2006 to 2099 with more pronounced changes in the TP than in China as a whole. Under the RCP8.5 scenario, the changes are enhanced compared to those under RCP4.5.

  18. Projection of snow cover changes over China under RCP scenarios

    NASA Astrophysics Data System (ADS)

    Ji, Zhenming; Kang, Shichang

    2013-08-01

    Snow cover changes in the middle (2040-2059) and end (2080-2099) of the twenty-first century over China were investigated with a regional climate model, nested within the global model BCC_CSM1.1. The simulations had been conducted for the period of 1950-2099 under the RCP4.5 and RCP8.5 scenarios. Results show that the model perform well in representing contemporary (1986-2005) spatial distributions of snow cover days (SCDs) and snow water equivalent (SWE). However, some differences between observation and simulation were detected. Under the RCP4.5 scenarios, SCDs are shortened by 10-20 and 20-40 days during the middle and end of the twenty-first century, respectively. Whereas simulated SWE is lowered by 0.1-10 mm in most areas over the Tibetan Plateau (TP). On the other hand, the spatial distributions of SWE are reversed between the middle and end terms in the northeast China. Furthermore, compared with the changes of RCP4.5 scenario, SCDs are reduced by 5-20 days in the middle period under RCP8.5 scenario with even larger decreasing amplitude in the end term. SWE was lowered by 0.1-2.5 mm in most areas except the northeast of China in middle term under RCP8.5 scenario. The great center of SCDs and SWE changes are always located over TP. The regional mean of SCDs and SWE for the TP and for China display a declining trend from 2006 to 2099 with more pronounced changes in the TP than in China as a whole. Under the RCP8.5 scenario, the changes are enhanced compared to those under RCP4.5.

  19. A Microphysical Model of CO_2 Snow on Mars

    NASA Astrophysics Data System (ADS)

    Wood, S. E.; Richardson, M. I.; Paige, D. A.

    1996-09-01

    Atmospheric condensation of CO_2 is a critical but poorly understood part of the Martian seasonal CO_2 cycle. During polar night, the latent heat released by CO_2 condensation is the major heat source, and CO2 clouds can substantially reduce the infrared emission from the condensing seasonal CO_2 polar cap. The CO_2 snow which precipitates from the atmosphere may also help determine the radiative and physical characteristics of the seasonal CO_2 polar caps, depending on the relative amount of condensation which takes place in the atmosphere. Previous models of atmospheric CO_2 condensation on Mars have not taken into account the finite rates of nucleation, growth, and sedimentation, or the radiative effects of the CO_2 clouds themselves, and their results may be inconsistent with available data. In order to address these issues, we have developed a one-dimensional model of the growth and precipitation of CO_2 snow in the polar night atmosphere of Mars. The model includes a realistic treatment of the microphysical processes of heat and mass transfer in both the continuum and free molecular regimes, as well as the transition region. We have also taken into account surface kinetics, or the finite rate at which molecules can be incorporated into the crystal lattice. We will present model calculations of snow particle growth and sedimentation rates for different values of atmospheric supersaturation and nucleation height. These results are compared with Viking IRTM observations to place constraints on the amount of atmospheric condensation. We will also present predictions of what TES and MOLA will see on Mars Global Surveyor.

  20. Blended Families: Issues of Remarriage

    PubMed Central

    Sanders, Gary L.

    1984-01-01

    Canada's divorce rate increased by 50% between 1968 and 1982. This has resulted in new family forms. One of these, the family which has been `blended' through remarriage of a parent, has some unique developmental hardships and differences from traditional nuclear families. Blended families are subject to a number of myths that may adversely affect their formation. In addition, members of these families need more time and patience to form a stable and functioning family group than do traditional families. Family physicians can aid the blended family with frank discussion, preparation and specific information. PMID:21279000

  1. 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.

  2. 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.

  3. 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...

  4. 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.

  5. Relative levels of natural and anthropogenic lead in recent Antarctic snow

    SciTech Connect

    Boutron, C.F.; Patterson, C.C.

    1987-07-20

    Concentrations of lead have been measured by ultraclean isotope dilution mass spectrometry in large blocks of surface snow collected along a 433-km coast-interior axis in East Antarctica and near the geographic south pole. Slight contamination existed on the outside of the blocks, but concentration profiles from their exteriors to their interiors indicate that lead concentrations in the innermost parts of the blocks do represent the original concentrations in present-day Antarctic snow. Geographical variations of lead concentrations appear to be mainly due to local emissions from Dumont d'Urville and Amundsen Scott stations. The globally signifcant lead concentration in present-day Antarctic snow is found to be about 2 pg Pb/g. The corresponding value in Antarctic air is estimated to be about 7 pg Pb/mT STP, which is approximately fivefold larger than total natural lead contributed by soil dusts, volcanoes and sea salts. A tentative temporal curve of globally significant lead concentrations in Antarctic ice and snow for the last 13,000 years is given. It shows concentrations of about 0.4 pg Pb/g throughout most of the Holocene, with recent fivefold increases to about 2 pg Pb/g today. The general picture is then that four-fifths of total lead in the Antarctic troposphere today is anthropogenic. copyright American Geophysical Union 1987

  6. 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.

  7. The Snow Darkening Effect and the Simulation of Extremes over Eurasia

    NASA Astrophysics Data System (ADS)

    Yasunari, T. J.; Lau, W. K. M.; Kim, K. M.; Koster, R. D.

    2014-12-01

    We have recently completed an updated ensemble of NASA GEOS-5 simulations with a snow-darkening module (now officially named GOddard SnoW Impurity Module, or GOSWIM, and summarized in the published paper by Yasunari et al., SOLA, 2014; see at: https://www.jstage.jst.go.jp/article/sola/10/0/10_2014-011/_article). This ensemble ("snow-darkening case (SDC)"), consisting of ten parallel simulations (differing only in their initial conditions) spanning 2002-2011, is compared here to a corresponding ensemble with all snow-darkening effects disabled ("non-SDC"). We focus particularly on the production of extremes associated with snow darkening. To identify regions of interest over Eurasia, we first rank the 100 separate spring (MAM) or summer (JJA) values of a given quantity in each combined 100-yr data (i.e., 10-yr x 10-ensemble), and then compute the differences of the 90th percentile values between SDC and non-SDC. For spring, large differences are seen in a specific area of Europe and Central Asia (ECA), and for summer, they are seen for an area in the Russian Arctic (RA). The next step in our analysis addresses the month-by-month variation of the percentile differences within these identified regions - for each month, and for a given meteorological or hydrological variable, we determined the SDC percentile that corresponds to the 90th percentile value found for the non-SDC ensemble. For example, in the RA domain, the surface air temperature corresponding to the 90th percentile in the non-SDC ensemble has a consistently lower percentile in the SDC data - not only during spring and summer through the increased absorption of radiation by snow polluted with dust, black carbon, and organic carbon, but also in the post-snow season through some form of memory in the system. The temperature extremes in the SDC ensemble thus exceed those of the non-SDC ensemble throughout the year. This analysis supports the idea that the consideration of snow darkening effect in global

  8. 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

  9. Andes Mountain Snow Distribution, Properties, and Trend: 1979-2014

    NASA Astrophysics Data System (ADS)

    Mernild, Sebastian H.; Liston, Glen E.; Hiemstra, Christopher A.

    2015-04-01

    Andes snow presence, absence, properties, and water amount are key components of Earth's changing climate system that incur far-reaching physical ramifications. Modeling developments permit relatively high-resolution (4-km horizontal grid; 3-h time step) Andes snow estimates for 1979-2014. SnowModel, in conjunction with land cover, topography, and 35-years of NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) atmospheric reanalysis data, was used to create a spatially distributed, time-evolving, snow-related dataset that included air temperature, snow precipitation, snow-season timing and length, maximum snow water equivalent depth, and average snow density. Regional variability is a dominant feature of the modeled snow-property trends from an area northeast of Quito (latitude: 2.65°S to 0.23°N) to Patagonia (latitude: 52.15°S to 46.44°S). For example, the Quito area annual snow cover area changed -45%, -43% around Cusco (latitude: 14.75°S to 12.52°S), -5% east of Santiago (including the Olivares Basin), and 25% in Patagonia. The annual snow covered area for the entire Andes decreased 13%, mainly in the elevation band between 4,000-5,000 m a.s.l. In spite of strong regional variability, the data clearly show a general positive trend in mean annual air temperature and precipitation, and a decreasing trend in snow precipitation, snow precipitation days, and snow density. Also, the snow-cover onset is later and the snow-cover duration - the number of snow cover days - decreased.

  10. Compatibility of Canadian Snowfall and Snow Cover Data

    NASA Astrophysics Data System (ADS)

    Goodison, B. E.

    1981-08-01

    The accuracy and compatibility of Canadian snowfall and snow survey data were investigated in the Cold Creek research basin in southern Ontario. Problems in obtaining compatible point measurements of snowfall precipitation from gauge and ruler measurements are discussed. However, it is shown that correction of gauge measurements (MSC Nipher, Universal, Fischer and Porter) of snowfall water equivalent for catch variations caused by environmental factors, notably wind speed, results in compatible storm or seasonal totals. Accurate statistics of basin snow cover were determined from snow courses specifically sited in relation to basin land use. At the time of peak accumulation, which might occur at any time during the winter, there was a statistically significant difference in snow cover between land use categories. Mean basin snow cover was calculated by weighting the snow survey measurements in proportion to basin land use. The need to consider the effect of changing land use on snow course measurements is demonstrated. Results show that as an alternative to direct snow survey measurements, accumulated precipitation may be used to estimate snow cover up to peak accumulation. Net snow cover determined from accumulated corrected gauge data less short-term melt losses and snow evaporation was within the confidence limits of the basin mean snow cover measured during the winter. Compatible results are only achieved when precipitation measurements are corrected for gauge catch variations and snow survey data are representative of basin land use.

  11. 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.

  12. Correlation function studies for snow and ice

    NASA Technical Reports Server (NTRS)

    Vallese, F.; Kong, J. A.

    1981-01-01

    The random medium model is used to characterize snow and ice fields in the interpretation of active and passive microwave remote sensing data. A correlation function is used to describe the random permittivity fluctuations with the associated mean and variance and correlation lengths; and several samples are investigated to determine typical correlation functions for snow and ice. It is shown that correlation functions are extracted directly from appropriate ground truth data, and an exponential correlation function is observed for snow and ice with lengths corresponding to the actual size of ice particles or air bubbles. Thus, given that a medium has spatially stationary statistics and a small medium, the random medium model can interpret remote sensing data where theoretical parameters correspond to actual physical parameters of the terrain.

  13. 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.

  14. 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...

  15. 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.

  16. Testing of Cloud Microphysics Scheme with Snow Events

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Shi, Jainn Jong; Matsui, Toshihisa; Hou, Arthur; Lang, Stephen; Cifelli, Robert; Peters-Lidar, C.; Jackson, Gail; Rutledge, Steve; Petersen, Walter

    2008-01-01

    One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve precipitation measurements in mid- and high-latitudes during cold seasons through the use of high-frequency passive microwave radiometry. For this, the Weather Research Forecast (WRF) model with the Goddard microphysics scheme is coupled with the Satellite Data Simulation Unit (WRF-SDSU) that has been developed to facilitate the over-snowfall retrieval algorithm by providing virtual cloud library and microwave brightness temperature (To) measurements consistent to the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF in snowstorm events (January 20-22, 2007) over the Canadian CloudSat/CALIPSO Validation Project (C3VP) site up in Ontario, Canada. In this meeting, we will present the performance of the Goddard cloud microphysics scheme both with 2ice (ice and snow) and 3ice (ice, snow and graupel) as well as other WRF microphysics schemes. Results will be compared with the King Radar data. We will also use the WRF model outputs to drive the Goddard SDSU to calculate radiances and backscattering signals consistent to satellite direct observations. These simulated radiance are evaluated against the measurement from A-Train satellites.

  17. Thermal energy in dry snow avalanches

    NASA Astrophysics Data System (ADS)

    Steinkogler, W.; Sovilla, B.; Lehning, M.

    2015-09-01

    Avalanches can exhibit many different flow regimes from powder clouds to slush flows. Flow regimes are largely controlled by the properties of the snow released and entrained along the path. Recent investigations showed the temperature of the moving snow to be one of the most important factors controlling the mobility of the flow. The temperature of an avalanche is determined by the temperature of the released and entrained snow but also increases by frictional processes with time. For three artificially released avalanches, we conducted snow profiles along the avalanche track and in the deposition area, which allowed quantifying the temperature of the eroded snow layers. This data set allowed to calculate the thermal balance, from release to deposition, and to discuss the magnitudes of different sources of thermal energy of the avalanches. For the investigated dry avalanches, the thermal energy increase due to friction was mainly depending on the effective elevation drop of the mass of the avalanche with a warming of approximately 0.3 °C per 100 vertical metres. Contrarily, the temperature change due to entrainment varied for the individual avalanches, from -0.08 to 0.3 °C, and depended on the temperature of the snow along the path and the erosion depth. Infrared radiation thermography (IRT) was used to assess the surface temperature before, during and just after the avalanche with high spatial resolution. This data set allowed to identify the warmest temperatures to be located in the deposits of the dense core. Future research directions, especially for the application of IRT, in the field of thermal investigations in avalanche dynamics are discussed.

  18. 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.

  19. Method to blend separator powders

    DOEpatents

    Guidotti, Ronald A.; Andazola, Arthur H.; Reinhardt, Frederick W.

    2007-12-04

    A method for making a blended powder mixture, whereby two or more powders are mixed in a container with a liquid selected from nitrogen or short-chain alcohols, where at least one of the powders has an angle of repose greater than approximately 50 degrees. The method is useful in preparing blended powders of Li halides and MgO for use in the preparation of thermal battery separators.

  20. Automate small refinery blending operations

    SciTech Connect

    Bauman, D.E.; Mellott, M.T.

    1981-11-01

    More than ever, small refiners must become more efficient to remain competitive. Increased automation can contribute significantly to improving operations and reducing costs. Presented is a method of automating the blending operation which incorporates unique features and equipment. The system has proven successful in reducing costs and manpower, and improved product quality. The discussion is presented under headings - basic blending system; digital blender; knock engines and octave computer; programmable logic controller; flowmeters; lead additive systems.

  1. 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

  2. A newly developed snow vehicle (SM100S) for Antarctica. Part 4: Low temperature properties of crawler belt

    NASA Astrophysics Data System (ADS)

    Maekawa, Etsuji; Terayama, Yoshihide

    1992-11-01

    In order to discover a high cold-resistance material for use in the crawler belt of snow vehicles, the physical properties at very low temperatures of a recently developed material, isoprene/butadiene (70/30) random copolymer filled with carbon black, was investigated in comparison with a blended rubber NR (Natural Rubber) / BR (Butadiene Rubber) (65/35) as well as a currently used NR. It has been found that this material can keep rubber elasticity even at low temperatures below - 70 C, though it is somewhat inferior to the other two materials as to strengths such as stress-at-break and tear; and hence, it is considered as quite worthy of a practical test for a snow vehicle in the Antarctic area.

  3. Morphological possibilities in general crystallography. Snow crystals.

    PubMed

    Janner, A

    2002-07-01

    Morphological features of snow crystals are analyzed on the basis of concepts of a general crystallography, where point groups of infinite order are possible. The observations are first formulated in a set of rules, leading to a macroscopic growth lattice and to continuous growth boundaries. Both are brought in connection with two-dimensional integral invertible transformations. Families of boundaries are considered, labeled by a set of indices restricted by selection rules and generalizing the law of rational indices. These properties are indicated graphically on a sample of 12 natural snow crystals. Their geometric and arithmetic properties are summarized in a table. PMID:12089456

  4. 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

  5. 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.

  6. 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

  7. 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…

  8. 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.

  9. 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.

  10. 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.

  11. Assimilating MODIS Snow Covers into Land Surface Model: Validation with in-situ Snow Measurements in Northern Xinjiang, China

    NASA Astrophysics Data System (ADS)

    Huang, Chunlin; Hou, Jinliang; Wang, WeiZhen

    2016-04-01

    Accurate monitoring of the spatiotemporal distribution and variation of snow cover is important for snowmelt runoff simulation and water resources management especially in mountainous areas. In this work, we develop a snow data assimilation scheme based on Ensemble Kalman Filter (EnKF) algorithm and Common Land Model (CoLM), which can assimilate snow cover fraction (SCF) products from the Moderate resolution imaging Spectroradiometer (MODIS) into CoLM for improving snow depth (SD) and snow cover area simulations. An empirical model between SD and SCF has been built based on MODIS SCF and snow depth observations at meteorological stations located in study area, which is used as observation operator in snow data assimilation scheme. The assimilation experiment is conducted during 2004-2007, in Xingjiang province, west China. The preliminary assimilation results are very promising and show that the assimilation of SCF could significantly improve the CoLM capability of simulating snow cover area and snow depth. The assimilation results are more closer to those of observations, which have more reasonable and reliable snow accumulation and melting trends throughout the snow season. After assimilating MODIS SCF observations, the Root Mean Square Error (RMSE) and Mean Bias error (MBE) of snow cover or snow depth are significantly reduced compared to the results without assimilation.

  12. Advanced materials based on polymer blends/polymer blend nanocomposites

    NASA Astrophysics Data System (ADS)

    Shikaleska, A. V.; Pavlovska, F. P.

    2012-09-01

    Processability, morphology, mechanical properties and rheological behavior of poly(vinylchloride) (PVC)/poly(ethylmethacrylate) (PEMA) blends and PVC/PEMA/montmorillonite (MMT) composites, prepared by melt processing in a brabender mixer, were studied. Samples were characterized using SEM, mechanical testing, DMTA and a parallel plate rheometer. Plastograms show that there is noticeable drop of fusion times and increase in melt viscosity torque of both, polymer blend and polymer blend nanocomposite, in comparison with those of neat PVC. SEM images show that homogenous dispersions are obtained. Tensile tests indicate that PVC/PEMA and PVC/PEMA/MMT samples have greater tensile strength and elastic modulus and lower elongation compared to PVC. When solid viscoelastic properties are considered (DMTA), slightly higher storage moduli are obtained whereas more prominent increase of storage modulus is observed when nanoclay particles are added in a PVC/PEMA matrix. From the calculated area of tandelta peak of all tested samples, nanocomposites exhibit the lowest damping behavior. Oscillatory measurements in a molten state were used for determining the frequency dependencies of storage G' and loss G" moduli. It was found that G" curves of neat PVC lie above those of G' suggesting that PVC behaves like viscoelastic liquid. Similar results, but with significantly higher values of G' and G" over the whole frequency range for PVC/PEMA blends were obtained. Steady shear measurements show that the presence of PEMA and nanoclay particles increases the shear stress and shear viscosity of neat PVC. In order to define the rheological equations of state the three material functions were determined. According to these functions all samples exhibit shear thinning behavior and the curves obey the power law equation. As rheological behaviour was found to be strongly dependent on blend's micro and macro structure and it is one of the main factors defining the end properties, attempt was

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. Numerical simulation of drifting snow sublimation in the saltation layer

    PubMed Central

    Dai, Xiaoqing; Huang, Ning

    2014-01-01

    Snow sublimation is an important hydrological process and one of the main causes of the temporal and spatial variation of snow distribution. Compared with surface sublimation, drifting snow sublimation is more effective due to the greater surface exposure area of snow particles in the air. Previous studies of drifting snow sublimation have focused on suspended snow, and few have considered saltating snow, which is the main form of drifting snow. In this study, a numerical model is established to simulate the process of drifting snow sublimation in the saltation layer. The simulated results show 1) the average sublimation rate of drifting snow particles increases linearly with the friction velocity; 2) the sublimation rate gradient with the friction velocity increases with increases in the environmental temperature and the undersaturation of air; 3) when the friction velocity is less than 0.525 m/s, the snowdrift sublimation of saltating particles is greater than that of suspended particles; and 4) the snowdrift sublimation in the saltation layer is less than that of the suspended particles only when the friction velocity is greater than 0.625 m/s. Therefore, the drifting snow sublimation in the saltation layer constitutes a significant portion of the total snow sublimation. PMID:25312383

  18. 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.

  19. Saltating Snow Mechanics: High Frequency Particle Response to Mountain Wind

    NASA Astrophysics Data System (ADS)

    Aksamit, N. O.; Pomeroy, J. W.

    2015-12-01

    Blowing snow transport theory is currently limited by its dependency on the coupling of time-averaged measurements of particle saltation and suspension and wind speed. Details of the stochastic process of particle transport and complex bed interactions in the saltation layer, along with the influence of boundary-layer turbulence are unobservable with classic measurement techniques. In contrast, recent advances in two-phase sand transport understanding have been spurred by development of high-frequency wind and particle velocity measurement techniques. To advance the understanding of blowing snow, laser illuminated high-speed videography and ultrasonic anemometry were deployed in a mountain environment to examine saltation of snow over a natural snowpack in detail. A saltating snow measurement site was established at the Fortress Mountain Snow Laboratory, Alberta, Canada and instrumented with two Campbell CSAT3 ultrasonic anemometers, four Campbell SR50 ultrasonic snow depth sounders and a two dimensional Particle Tracking Velocimetry (PTV) system. Measurements were collected during nighttime blowing snow events, quantifying snow particle response to high frequency wind gusts. This novel approach permits PTV to step beyond mean statistics of snow transport by identifying sub-species of saltation motion in the first 20 mm above the surface, as well as previously overlooked initiation processes, such as tumbling aggregate snow crystals ejecting smaller grains, then eventually disintegrating and bouncing into entrainment. Spectral characteristics of snow particle ejection and saltation dynamics were also investigated. These unique observations are starting to inform novel conceptualizations of saltating snow transport mechanisms.

  20. Connecting European snow cover variability with large scale atmospheric patterns

    NASA Astrophysics Data System (ADS)

    Bartolini, E.; Claps, P.; D'Odorico, P.

    2010-09-01

    Winter snowfall and its temporal variability are important factors in the development of water management strategies for snow-dominated regions. For example, mountain regions of Europe rely on snow for recreation, and on snowmelt for water supply and hydropower. It is still unclear whether in these regions the snow regime is undergoing any major significant change. Moreover, snow interannual variability depends on different climatic variables, such as precipitation and temperature, and their interplay with atmospheric and pressure conditions. This paper uses the EASE Grid weekly snow cover and Ice Extent database from the National Snow and Ice Data Center to assess the possible existence of trends in snow cover across Europe. This database provides a representation of snow cover fields in Europe for the period 1972-2006 and is used here to construct snow cover indices, both in time and space. These indices allow us to investigate the historical spatial and temporal variability of European snow cover fields, and to relate them to the modes of climate variability that are known to affect the European climate. We find that both the spatial and temporal variability of snow cover are strongly related to the Arctic Oscillation during wintertime. In the other seasons, weaker correlation appears between snow cover and the other patterns of climate variability, such as the East Atlantic, the East Atlantic West Russia, the North Atlantic Oscillation, the Polar Pattern and the Scandinavian Pattern.

  1. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  2. 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...

  3. 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...

  4. 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...

  5. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  6. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  7. 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...

  8. 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...

  9. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  10. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each certificate holder whose airport is located where snow and icing conditions occur must prepare, maintain,...

  11. 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.

  12. 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.

  13. Communicators' perspective on snow avalanche risk communication using smartphone applications

    NASA Astrophysics Data System (ADS)

    Charrière, Marie; Bogaard, Thom; Junier, Sandra; Mostert, Erik

    2015-04-01

    Among all the natural hazards, snow avalanches are the only ones for which a public danger scale is used globally. It consists of 5 levels of danger displayed with a given number and colour, and for each of them behavioural advices are provided. Even though this is standardized in most of the countries affected by this natural hazard, the smartphone applications with which the information is disseminated to the general public differ, particularly in terms of target audience and level of details. This study aims to gather the perspectives of several persons that are responsible for these avalanche risk communication practices. The survey was created to assess how and why choices were made in the design process of the applications and to determine how their effectiveness is evaluated. Along with a review of existing avalanche risk communication smartphone applications, this study provides guidelines for communication and the evaluation of its effectiveness.

  14. 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…

  15. 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 collected at one to two kilometer intervals. The data are provided in tabular ASCII files. The HYD-04 areal 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).

  16. 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.

  17. "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…

  18. 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…

  19. Black Carbon and Dust in Snow and Ice on Snow Dome, Mt. Olympus

    NASA Astrophysics Data System (ADS)

    Kaspari, S.; Delaney, I.; Skiles, M.; Dixon, D. A.

    2012-12-01

    Deposition of black carbon (BC) and dust on highly reflective snow and glacier ice causes darkening of the surface, resulting in greater absorption of solar energy, heating of the snow/ice, and accelerated snow and glacier melt. The deposition of BC and dust may be affecting the timing and availability of water resources in the Pacific Northwest where the majority of runoff comes from snow and glacier melt, but minimal related research has taken place in this region. A recent modeling study suggested that BC deposition is causing a decrease in spring snow water equivalent and a shift to earlier peak runoff in the spring in the Western United States. Additionally, limited observations made in the early 1980s in Washington State determined that light absorbing impurities (e.g., BC and dust) were reducing the snow albedo. Since 2009, we have collected snow and ice samples from glaciers and the seasonal snowpack from spatially distributed sites in Washington State to determine impurity content, and to assess how impurity concentrations vary in relation to emission source proximity. Here we present results from the summer 2012 fieldwork on Snow Dome, Mt. Olympus in Washington State. Mt. Olympus is located upwind from major regional sources of BC and dust, but may receive BC from ocean shipping and trans-Pacific transport of BC and dust from large Asian sources. We used a field spectrometer to measure spectral albedo on Snow Dome, and analyzed surface snow samples and shallow ice cores to characterize the spatial and temporal variability of impurity deposition. Total impurity load was determined gravimetrically. Dust concentrations are inferred from ICPMS analyses and BC concentrations are determined using a Single Particle Soot Photometer (SP2), with select samples also analyzed for BC using a Sunset EC-OC to facilitate method inter-comparison. We assess the role that absorbing impurities may play in accelerating melt at Snow Dome, and briefly compare our results to

  20. Climate sensitivity of snow regimes simulated by physically based snow models (Invited)

    NASA Astrophysics Data System (ADS)

    Pomeroy, J. W.; Fang, X.; Sabourin, A.; Ellis, C. R.

    2009-12-01

    Seasonal snow regimes consist of snowfall, snow redistribution by wind, snow interception and snowmelt. Sublimation can be an important ablation mechanism under highly ventilated conditions. All of these processes are strongly controlled by the energy inputs and energy state of the snowpack. Warmer winter temperatures have been observed and are predicted for many cold regions environments. The Cold Regions Hydrological Model (CRHM) has the capability to successfully model the major snow processes in a physically based manner. It is used here to explore the sensitivity of snow regimes in three environments to warmer winter temperatures. The windswept alpine and mountain spruce forest environments use baseline data from Marmot Creek Research Basin in the Rocky Mountains of Alberta, Canada and the prairie cropland environments use data from Bad Lake Research Basin in the semi-arid prairies of Saskatchewan, Canada. Under current conditions blowing snow in both alpine and prairie environments redistributes most snowfall from wind exposed ridge and fallow-field surfaces and deposits transported snow in drifts on lee slopes, gullies and treed or shrub areas. Sublimation losses are substantial. Melt occurs in May-June in the alpine and in March-April on the Prairie. Currently, snow interception and sublimation are major losses of seasonal snowpack in mountain forest environments due to high sublimation losses. Forest melt occurs in April-May. Warming is shown to reduce sublimation losses - its restriction of wind redistribution and interception overcomes the additional energy available for sublimation. Warming also advances the timing of snowmelt initiation to varying degrees, but its effects on the rate and duration of melt are equivocal. In certain environments melt is faster and shorter in duration as warming occurs, but in others the rate diminishes with warming and so duration is not strongly affected. These results have important implications for determining the

  1. FTS (Fog To Snow) Conversion Process During the SNOW-V10 Project

    NASA Astrophysics Data System (ADS)

    Gultepe, I.; Zhou, B.

    2012-05-01

    The objective of this work is to understand how winter fog which occurred on Whistler Mountain on 3-4 March 2010 developed into a snow event by the means of the FTS (Fog To Snow) process. This event was documented using data collected during the Science of Nowcasting Winter Weather for Vancouver 2010 (SNOW-V10) project that was supported by the Fog Remote Sensing and Modelling (FRAM) project. The FTS resulted in a snow event at about 1,850 m altitude where the RND (Roundhouse) meteorological station was located. For both days, there was no large scale system that affected local fog formation and its development into snow. Patchy fog occurred in the early hours of both days and was based below 1,500 m. Clear skies at night likely resulted in cooling, the valley temperature (T) was about -1°C in the early morning, and snow was on the ground. Winds were relatively calm (<1 m s-1). At the RND site, T was about -3°C. Weather at RND was clear and sunny till noon. When fog moved over the mountain peak/near RND, light snow started and lasted for about 4-5 h and was not detected by precipitation sensors except the Ground Cloud Imaging Probe (GCIP) and Laser Precipitation Sensor (LPM). In this work, the FTS process is conceptually summarized. Because clear weather conditions over the high mountain tops can become hazardous with low visibilities and significant snow amounts (<1.0 mm h-1), such events are important and need to be predicted.

  2. FTS (Fog To Snow) Conversion Process During The SNOW-V10 Project

    NASA Astrophysics Data System (ADS)

    Gultepe, I.; Isaac, G. A.

    2010-07-01

    The objective of this work is to understand how winter fog which occurred on Whistler Mountain on 3-4 March 2010 developed into a snow event by the means of the FTS (Fog_To_Snow) process. This event was documented using data collected during the Science of Nowcasting Winter Weather for Vancouver 2010 (SNOW-V10) project that was supported by the Fog Remote Sensing and Modeling (FRAM) project. The FTS resulted in a snow event at about 1850 m height where the RND (Roundhouse) meteorological station was located. For both days, there was no large scale system that affected local fog formation and its development into snow. The patchy fog occurred in the early hours of both days and was based below 1500 m. Clear skies at night likely resulted in cooling, the valley temperature (T) was about +3C in the early morning, and snow was on the ground. Winds were relatively calm (<1 m/s). At the RND site, T was about -3C. Weather at RND was clear and sunny till noon. When shortwave (SW) radiation provided additional heat at the low levels and sloping surfaces, fog started to lift up over a 3-4 hr time period gaining additional moisture from melting snow. Then, the fog layers were eventually converted to cumulus/altocumulus. Afternoon, at about 01:30 PM, the entire valley was filled up with a fog/cloud mixture. When fog moved over the mountain peak/near RND, light snow started and lasted for about 4-5 hrs and was not detected by precipitation sensors except the Ground Cloud Imaging Probe (GCIP) and Laser Precipitation Sensor (LPM). In the presentation, observations collected during the FTS process will be summarized, and it will be proposed as an important winter and forecasting event over high elevations.

  3. Measurement of snow particle size and speed in powder snow avalanches

    NASA Astrophysics Data System (ADS)

    Ito, Yoichi; Nishimura, Kouichi; Naaim-Bouvet, Florence; Bellot, Hervé; Thibert, Emmanuel; Ravanat, Xavier; Fontaine, Firmin

    2015-04-01

    Generally snow avalanches consist a dense-flow layer at the bottom and a powder snow cloud on top. Snow particle size and speed are key parameters to describe the turbulent condition in the powder cloud, however, the information on the particles were not well investigated. In this study, we observed powder snow avalanches using a snow particle counter (SPC) to measure the particle size and speed. The SPC is an optical device consisting a laser diode and photodiode; a pulse signal proportional to its diameter is generated resulting from a snow particle passing through the sensing volume. In general use, the signals are sent to a transducer and divided into 32 size classes based on particle diameter to observe the snow particle size distribution and mass flux at 1-s intervals. In this study, the direct output signal from the transducer was also acquired at a high frequency to obtain the original pulse signal produced by each snow particle. Then the speed of each particle can be calculated using the peak of the pulse, which corresponds to particle diameter and the duration over which the particle passes through the sampling area. We also employed an ultrasonic anemometer to measure air flow speed. Both sensors were installed at the Col du Lautaret Pass in the French Alps. The results of the particle size and speed distribution were then compared with airflow movement in the powder cloud. The ratio of the particle and airflow speeds changed by the particle size distribution and the distance from the dense-flow layer.

  4. 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.

  5. Merging a Terrain-Based Parameter with Drifting Snow Fluxes for Assessing Snow Redistribution in Mountainous Areas

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Wind and the associated snow transport are dominating factors determining the snow distribution and accumulation in alpine areas. These factors result in a high spatial variability of snow heights that is difficult to evaluate and quantify. We merge a terrain-based parameter Sxm, which characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, with snow particle counter (SPC) data. SPC estimate the snow flux, the mass of drifting snow particles per time and area. From the SPCs' point measurements of horizontal snow flux, a quantity of transported snow is derived, which is distributed over the terrain in dependency of Sxm. Estimated changes in snow heights due to wind redistribution are compared with measured changes, obtained with terrestrial laser scanning (TLS). Data and results are from the Col du Lac Blanc research site in the French Alps. We use a high raster resolution of 1 m, which is required when assessing the snow-redistribution situation in highly structured terrain or in the starting zones of small and medium-sized avalanches. Results show that the model works in principle. It could reproduce patterns of snow redistribution and estimate changes in snow heights reasonably well, as shown by good regression quality (r² values of 0.60 to 0.76). The derivation of Sxm and the amount of transport have shown to be not generally applicable, however, but rather are formulations that must be calibrated when applied in studies with other terrain and weather characteristics.

  6. Arctic Snow Microstructure Experiment for the development of snow emission modelling

    NASA Astrophysics Data System (ADS)

    Maslanka, W.; Leppänen, L.; Kontu, A.; Sandells, M.; Lemmetyinen, J.; Schneebeli, M.; Hannula, H.-R.; Gurney, R.

    2015-12-01

    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 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.