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Sample records for 8-day composite snow

  1. Improving the accuracy of MODIS 8-day snow products with in situ temperature and precipitation data

    NASA Astrophysics Data System (ADS)

    Dong, Chunyu; Menzel, Lucas

    2016-03-01

    MODIS snow data are appropriate for a wide range of eco-hydrological studies and applications in the fields of snow-related hazards, early warning systems and water resources management. However, the high spatio-temporal resolution of the remotely sensed data is often biased by snow misclassifications, and cloud cover frequently limits the availability of the MODIS-based snow cover information. In this study, we applied a four-step methodology that aims to optimize the accuracy of MODIS snow data. To reduce the cloud fraction, 8-day MODIS data from both the Aqua and Terra satellites were combined. Neighborhood analysis was applied as well for this purpose, and it also contributed to the retrieval of some omitted snow. Two meteorological filters were then applied to combine information from station-based measurements of minimum ground temperature, precipitation and air temperature. This procedure helped to reduce the overestimation of snow cover. To test this technique, the methodology was applied to the Rhineland-Palatinate region in southwestern Germany (approximately 20,000 km2), where cloud cover is especially high during winter and surface heterogeneity is complex. The results show that mean annual cloud coverage (reference period 2002-2013) of the 8-day MODIS snow maps could be reduced using this methodology from approximately 14% to 4.5%. During the snow season, obstruction by clouds could be reduced by even a higher degree, but still remains at about 11%. Further, the overall snow overestimation declined from 11.0-11.9% (using the original Aqua-Terra data) to 1.0-1.5%. The method is able to improve the overall accuracy of the 8-day MODIS snow product from originally 78% to 89% and even to 93% during cloud free periods.

  2. What controls the isotopic composition of Greenland surface snow?

    NASA Astrophysics Data System (ADS)

    Steen-Larsen, H. C.; Masson-Delmotte, V.; Hirabayashi, M.; Winkler, R.; Satow, K.; Prié, F.; Bayou, N.; Brun, E.; Cuffey, K. M.; Dahl-Jensen, D.; Dumont, M.; Guillevic, M.; Kipfstuhl, J.; Landais, A.; Popp, T.; Risi, C.; Steffen, K.; Stenni, B.; Sveinbjörnsdottír, A.

    2013-10-01

    Water stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically-enabled atmospheric models. However, post-deposition processes linked with snow metamorphism remain poorly documented. For this purpose, a monitoring of the isotopic composition (δ18O, δD) of surface water vapor, precipitation and samples of top (0.5 cm) snow surface has been conducted during two summers (2011-2012) at NEEM, NW Greenland. The measurements also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between surface vapor δ18O and air temperature (0.85 ± 0.11 ‰ °C-1 (R = 0.76) for 2012). The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess) is strongly anti-correlated with δ18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1-5 days periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated that 6 to 20% of the surface snow mass is exchanged with the atmosphere using the CROCUS snow model. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or condensation. Comparisons with atmospheric models show that day-to-day variations in surface vapor isotopic composition are driven by synoptic weather and changes in air mass trajectories and distillation histories. We suggest that, in-between precipitation events, changes in the surface snow isotopic composition are driven by these changes in surface vapor isotopic composition. This

  3. What controls the isotopic composition of Greenland surface snow?

    NASA Astrophysics Data System (ADS)

    Steen-Larsen, H. C.; Masson-Delmotte, V.; Hirabayashi, M.; Winkler, R.; Satow, K.; Prié, F.; Bayou, N.; Brun, E.; Cuffey, K. M.; Dahl-Jensen, D.; Dumont, M.; Guillevic, M.; Kipfstuhl, S.; Landais, A.; Popp, T.; Risi, C.; Steffen, K.; Stenni, B.; Sveinbjörnsdottír, A. E.

    2014-02-01

    Water stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically enabled atmospheric models. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, monitoring of the isotopic composition (δ18O, δD) of near-surface water vapor, precipitation and samples of the top (0.5 cm) snow surface has been conducted during two summers (2011-2012) at NEEM, NW Greenland. The samples also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between near-surface vapor δ18O and air temperature (0.85 ± 0.11‰ °C-1 (R = 0.76) for 2012). The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess) is strongly anti-correlated with δ18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1-5-day periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface vapor

  4. 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.

  5. Chemical composition of fresh snow on Mount Everest

    NASA Astrophysics Data System (ADS)

    Jenkins, Mark D.; Drever, James I.; Reider, Richard G.; Buchanan, Thomas

    1987-09-01

    One hundred freshly fallen snow samples were collected from the north side of Mount Everest between 5600 and 7100 m elevation in April and May of 1986. Compared to snow from the Rocky Mountains of Wyoming, the Everest samples have lower sulfate and nitrate concentrations, reflecting a lesser anthropogenic input and much higher calcium concentrations and pH. The calcium concentrations and high pH presumably reflect a large but variable input of calcium carbonate dust either from arid areas to the west and north or from more local glacial deposits.

  6. Chemical compositions of snow from Mt. Yulong, southeastern Tibetan Plateau

    NASA Astrophysics Data System (ADS)

    Niu, Hewen; He, Yuanqing; Kang, Shichang; Lu, Xixi; Shi, Xiaoyi; Wang, Shijin

    2016-03-01

    The snow and ice in Mt. Yulong offer a unique opportunity to investigate changes in climate and large scale atmospheric circulations over Asia. During February and April 2012, surface snow samples were collected from the Baishui Glacier No. 1 at different altitudes along the eastern slope of Mt. Yulong. Two snowpits were also excavated from Mt. Yulong at altitudes of 4780 and 4730 m a.s.l. in February 2012. The concentrations of inorganic ions were higher at an elevation of 4506 m a.s.l. in the glacier with significant contribution of anthropogenic (mainly NH4+, SO4^{2-}, NO3-) and crustal (mainly Ca 2+) constituents. Concentration of HCOO - in surface snow exhibited large variability, ranging from 0.04 to 6.8 μeq L -1, attributed to dominant contribution from biomass burning emissions. Ion balance (ΔC) and Na +/Cl - calculations indicated an excess of cations (particularly higher Ca 2+ concentrations) and Cl - in snow, considering the sea-salt ratio, respectively. Monsoon season (June-September) ion concentrations in snowpit samples were generally two-fold lower than in other seasons. Principal component analysis was used to identify different sources of ions. Three main factors, accounting for more than 80% of the total variance, were related to different sources, including agricultural activities, biomass burning, and crustal aerosols.

  7. Absence of snow cover reduces understory plant cover and alters plant community composition in boreal forests.

    PubMed

    Kreyling, Juergen; Haei, Mahsa; Laudon, Hjalmar

    2012-02-01

    Snow regimes affect biogeochemistry of boreal ecosystems and are altered by climate change. The effects on plant communities, however, are largely unexplored despite their influence on relevant processes. Here, the impact of snow cover on understory community composition and below-ground production in a boreal Picea abies forest was investigated using a long-term (8-year) snow cover manipulation experiment consisting of the treatments: snow removal, increased insulation (styrofoam pellets), and control. The snow removal treatment caused longer (118 vs. 57 days) and deeper soil frost (mean minimum temperature -5.5 vs. -2.2°C) at 10 cm soil depth in comparison to control. Understory species composition was strongly altered by the snow cover manipulations; vegetation cover declined by more than 50% in the snow removal treatment. In particular, the dominant dwarf shrub Vaccinium myrtillus (-82%) and the most abundant mosses Pleurozium schreberi (-74%) and Dicranum scoparium (-60%) declined strongly. The C:N ratio in V. myrtillus leaves and plant available N in the soil indicated no altered nitrogen nutrition. Fine-root biomass in summer, however, was negatively affected by the reduced snow cover (-50%). Observed effects are attributed to direct frost damage of roots and/ or shoots. Besides the obvious relevance of winter processes on plant ecology and distribution, we propose that shifts in the vegetation caused by frost damage may be an important driver of the reported alterations in biogeochemistry in response to altered snow cover. Understory plant performance clearly needs to be considered in the biogeochemistry of boreal systems in the face of climate change. PMID:21850524

  8. The spatial and seasonal variations in mineral particle composition on the snow surface and their possible effect on snow algae in the Tateyama Mountains, Japan

    NASA Astrophysics Data System (ADS)

    Umino, T.; Takeuchi, N.

    2012-12-01

    Snow algae are autotrophic microbes and play an important role as primary producers in food chain of glaciers and snowfield. Although their reproduction requires nutrients, snow and ice is extreamly poor in nutrients. One of the possible sources of nutrients is mineral particles blown by wind and deposited on the snow. They may contain variable elements and provide nutrients for snow algae. However, we scarcely know about the relationship between mineral particles and snow algae. In this study, we described spatial and seasonal variations in mineral particle composition and also snow algae on the snow surface in the Tateyama Mountains, Japan. We discussed the possible effect of mineral particles on snow algae. Tateyama Mountains are located in middle-north part of Japan ranging from 2000 - 3000 m above sea level and have heavy snow fall in winter due to strong monsoon wind from Siberia. The snow starts to thaw in April and remains until late summer as perennial snow patches in some valleys. Kosa eolian dust is known to be blown from Chinese deserts and deposited on the snow every spring. Also, snow algal bloom is often observed as red-colored snow in summer. Samples were collected from the snow surface during summer in 2008 - 2011 at four different sites (A - D) in this area. We examined them by X-ray diffractometer (XRD) and microscope to obtain composition of mineral particles and structure of snow algae community. XRD analysis revealed mineral particles on the snow surface were mainly composed of quartz, plagioclase, hornblende, mica, chlorite, and amorphous. In April, mineral compositions of all sites were almost similar to that of Kosa eolian dust, indicating that these mineral particles were derived from Chinese arid regions. After May, the mineral compositions changed according to sites. The proportion of hornblende at the site C significantly increased whereas that of mica increased at the site D. Since the site C was located near geological features mainly

  9. Elemental and fatty acid composition of snow algae in Arctic habitats

    PubMed Central

    Spijkerman, Elly; Wacker, Alexander; Weithoff, Guntram; Leya, Thomas

    2012-01-01

    Red, orange or green snow is the macroscopic phenomenon comprising different eukaryotic algae. Little is known about the ecology and nutrient regimes in these algal communities. Therefore, eight snow algal communities from five intensively tinted snow fields in western Spitsbergen were analysed for nutrient concentrations and fatty acid (FA) composition. To evaluate the importance of a shift from green to red forms on the FA-variability of the field samples, four snow algal strains were grown under nitrogen replete and moderate light (+N+ML) or N-limited and high light (−N+HL) conditions. All eight field algal communities were dominated by red and orange cysts. Dissolved nutrient concentration of the snow revealed a broad range of NH+4 (<0.005–1.2 mg N l−1) and only low PO3−4 (<18 μg P l−1) levels. The external nutrient concentration did not reflect cellular nutrient ratios as C:N and C:P ratios of the communities were highest at locations containing relatively high concentrations of NH+4 and PO3−4. Molar N:P ratios ranged from 11 to 21 and did not suggest clear limitation of a single nutrient. On a per carbon basis, we found a 6-fold difference in total FA content between the eight snow algal communities, ranging from 50 to 300 mg FA g C−1. In multivariate analyses total FA content opposed the cellular N:C quota and a large part of the FA variability among field locations originated from the abundant FAs C18:1n-9, C18:2n-6, and C18:3n-3. Both field samples and snow algal strains grown under −N+HL conditions had high concentrations of C18:1n-9. FAs possibly accumulated due to the cessation of growth. Differences in color and nutritional composition between patches of snow algal communities within one snow field were not directly related to nutrient conditions. We propose that the highly patchy distribution of snow algae within and between snow fields may also result from differences in topographical and geological parameters such as slope, melting

  10. Acquisition of isotopic composition for surface snow in East Antarctica and the links to climatic parameters

    NASA Astrophysics Data System (ADS)

    Touzeau, A.; Landais, A.; Stenni, B.; Uemura, R.; Fukui, K.; Fujita, S.; Guilbaud, S.; Ekaykin, A.; Casado, M.; Barkan, E.; Luz, B.; Magand, O.; Teste, G.; Le Meur, E.; Baroni, M.; Savarino, J.; Bourgeois, I.; Risi, C.

    2015-11-01

    The isotopic composition of oxygen and hydrogen in ice cores are invaluable tools for the reconstruction of past climate variations. Used alone, they give insights into the variations of the local temperature, whereas taken together they can provide information on the climatic conditions at the point of origin of the moisture. However, recent analyses of snow from shallow pits indicate that the climatic signal can become erased in very low accumulation regions, due to local processes of snow reworking. The signal to noise ratio decreases and the climatic signal can then only be retrieved using stacks of several snow pits. Obviously, the signal is not completely lost at this stage, otherwise it would be impossible to extract valuable climate information from ice cores as has been done, for instance, for the last glaciation. To better understand how the climatic signal is passed from the precipitation to the snow, we present here results from varied snow samples from East Antarctica. First, we look at the relationship between isotopes and temperature from a geographical point of view, using results from three traverses across Antarctica, to see how the relationship is built up through the distillation process. We also take advantage of these measures to see how second order parameters (d-excess and 17O-excess) are related to δ18O and how they are controlled. d-excess increases in the interior of the continent (i.e. when δ18O decreases), due to the distillation process, whereas 17O-excess decreases in remote areas, due to kinetic fractionation at low temperature. In both cases, these changes are associated with the loss of original information regarding the source. Then, we look at the same relationships in precipitation samples collected over one year at Dome C and Vostok, as well as in surface snow at Dome C. We note that the slope of the δ18O / T relationship decreases in these samples compared to those from the traverses, and thus advocate caution when using

  11. Long-term increase in snow depth leads to compositional changes in arctic ectomycorrhizal fungal communities.

    PubMed

    Morgado, Luis N; Semenova, Tatiana A; Welker, Jeffrey M; Walker, Marilyn D; Smets, Erik; Geml, József

    2016-09-01

    Many arctic ecological processes are regulated by soil temperature that is tightly interconnected with snow cover distribution and persistence. Recently, various climate-induced changes have been observed in arctic tundra ecosystems, e.g. shrub expansion, resulting in reduction in albedo and greater C fixation in aboveground vegetation as well as increased rates of soil C mobilization by microbes. Importantly, the net effects of these shifts are unknown, in part because our understanding of belowground processes is limited. Here, we focus on the effects of increased snow depth, and as a consequence, increased winter soil temperature on ectomycorrhizal (ECM) fungal communities in dry and moist tundra. We analyzed deep DNA sequence data from soil samples taken at a long-term snow fence experiment in Northern Alaska. Our results indicate that, in contrast with previously observed responses of plants to increased snow depth at the same experimental site, the ECM fungal community of the dry tundra was more affected by deeper snow than the moist tundra community. In the dry tundra, both community richness and composition were significantly altered while in the moist tundra, only community composition changed significantly while richness did not. We observed a decrease in richness of Tomentella, Inocybe and other taxa adapted to scavenge the soil for labile N forms. On the other hand, richness of Cortinarius, and species with the ability to scavenge the soil for recalcitrant N forms, did not change. We further link ECM fungal traits with C soil pools. If future warmer atmospheric conditions lead to greater winter snow fall, changes in the ECM fungal community will likely influence C emissions and C fixation through altering N plant availability, fungal biomass and soil-plant C-N dynamics, ultimately determining important future interactions between the tundra biosphere and atmosphere. PMID:27004610

  12. 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.

  13. Spring snow goose hunting influences body composition of waterfowl staging in Nebraska

    USGS Publications Warehouse

    Pearse, Aaron T.; Krapu, Gary L.; Cox, Robert R., Jr.

    2012-01-01

    A spring hunt was instituted in North America to reduce abundance of snow geese (Chen caerulescens) by increasing mortality of adults directly, yet disturbance from hunting activities can indirectly influence body condition and ultimately, reproductive success. We estimated effects of hunting disturbance by comparing body composition of snow geese and non-target species, greater white-fronted geese (Anser albifrons) and northern pintails (Anas acuta) collected in portions of south-central Nebraska that were open (eastern Rainwater Basin, ERB) and closed (western Rainwater Basin, WRB; and central Platte River Valley, CPRV) to snow goose hunting during springs 1998 and 1999. Lipid content of 170 snow geese was 25% (57 g) less in areas open to hunting compared to areas closed during hunting season but similar in all areas after hunting was concluded in the ERB. Protein content of snow geese was 3% (14 g) less in the region open to hunting. Greater white-fronted geese had 24% (76 g; n = 129) less lipids in the hunted portion of the study area during hunting season, and this difference persisted after conclusion of hunting season. We found little difference in lipid or protein content of northern pintails in relation to spring hunting. Indirect effects of spring hunting may be considered a collateral benefit regarding efforts to reduce overabundant snow goose populations. Disrupted nutrient storage observed in greater white-fronted geese represents an unintended consequence of spring hunting that has potential to adversely affect reproduction for this and other species of waterbirds staging in the region.

  14. A novel approach to identifying the elemental composition of individual residue particles retained in single snow crystals.

    PubMed

    Ma, Chang-Jin; Hwang, Kyung-Chul; Kim, Ki-Hyun

    2013-01-01

    This study was carried out to describe the chemical characteristics of individual residual particles in hexagonal snow crystals, which can provide a clue to the aerosol removal mechanism during snowfall. In the present study, to collect snow crystal individually and to identify the elemental composition of individual residues retained in a hexagonal crystal, an orchestration of the replication technique and micro-particle induced X-ray emission (micro-PIXE) analysis was carried out. Information concerning the elemental compositions and their abundance in the snow crystals showed a severe crystal-to-crystal fluctuation. The residues retained in the hexagonal snow crystals were dominated primarily by mineral components, such as silica and calcium. Based on the elemental mask and the spectrum of micro-PIXE, it was possible to presume the chemical inner-structure as well as the elemental mixing state in and/or on the individual residues retained in single snow crystals. PMID:23934568

  15. 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.

  16. Acquisition of isotopic composition for surface snow in East Antarctica and the links to climatic parameters

    NASA Astrophysics Data System (ADS)

    Touzeau, Alexandra; Landais, Amaëlle; Stenni, Barbara; Uemura, Ryu; Fukui, Kotaro; Fujita, Shuji; Guilbaud, Sarah; Ekaykin, Alexey; Casado, Mathieu; Barkan, Eugeni; Luz, Boaz; Magand, Olivier; Teste, Grégory; Le Meur, Emmanuel; Baroni, Mélanie; Savarino, Joël; Bourgeois, Ilann; Risi, Camille

    2016-04-01

    The isotopic compositions of oxygen and hydrogen in ice cores are invaluable tools for the reconstruction of past climate variations. Used alone, they give insights into the variations of the local temperature, whereas taken together they can provide information on the climatic conditions at the point of origin of the moisture. However, recent analyses of snow from shallow pits indicate that the climatic signal can become erased in very low accumulation regions, due to local processes of snow reworking. The signal-to-noise ratio decreases and the climatic signal can then only be retrieved using stacks of several snow pits. Obviously, the signal is not completely lost at this stage, otherwise it would be impossible to extract valuable climate information from ice cores as has been done, for instance, for the last glaciation. To better understand how the climatic signal is passed from the precipitation to the snow, we present here results from varied snow samples from East Antarctica. First, we look at the relationship between isotopes and temperature from a geographical point of view, using results from three traverses across Antarctica, to see how the relationship is built up through the distillation process. We also take advantage of these measures to see how second-order parameters (d-excess and 17O-excess) are related to δ18O and how they are controlled. d-excess increases in the interior of the continent (i.e., when δ18O decreases), due to the distillation process, whereas 17O-excess decreases in remote areas, due to kinetic fractionation at low temperature. In both cases, these changes are associated with the loss of original information regarding the source. Then, we look at the same relationships in precipitation samples collected over 1 year at Dome C and Vostok, as well as in surface snow at Dome C. We note that the slope of the δ18O vs. temperature (T) relationship decreases in these samples compared to those from the traverses, and thus caution is

  17. Chemical composition of snow in the northern Sierra Nevada and other areas

    USGS Publications Warehouse

    Feth, John Henry Frederick; Rogers, S.M.; Roberson, Charles Elmer

    1964-01-01

    Melting snow provides a large part of the water used throughout the western conterminous United States for agriculture, industry, and domestic supply. It is an active agent in chemical weathering, supplies moisture for forest growth, and sustains fish and wildlife. Despite its importance, virtually nothing has been known of the chemical character of snow in the western mountains until the present study. Analysis of more than 100 samples, most from the northern Sierra Nevada, but some from Utah, Denver, Colo., and scattered points, shows that melted snow is a dilute solution containing measurable amounts of some or all of the inorganic constituents commonly found in natural water. There are significant regional differences in chemical composition; the progressive increase in calcium content with increasing distance eastward from the west slope of the Sierra Nevada is the most pronounced. The chemical character of individual snowfalls is variable. Some show predominant influence of oceanic salt; others show strong effects of mineralization from continental sources, probably largely dust. Silica and boron were found in about half the samples analyzed for these constituents; precipitation is seldom analyzed for these substances. Results of the chemical analyses for major constituents in snow samples are summarized in the following table. The median and mean values for individual constituents are derived from 41-78 samples of Sierra Nevada snow, 6-18 samples of Utah snow, and 6-17 samples of Denver, Colo., snow. [Table] The sodium, chloride, and perhaps boron found in snow are probably incorporated in moisture-laden air masses as they move over the Pacific Ocean. Silica, although abundant in the silicate-mineral nuclei found in some snowflakes, may be derived in soluble form largely from dust. Calcium, magnesium, and some bicarbonate are probably added by dust of continental origin. The sources of the other constituents remain unknown. When snowmelt comes in contact

  18. Composition of atmospheric suspensions of Ussuriisk City according to snow pollution

    NASA Astrophysics Data System (ADS)

    Golokhvast, Kirill S.; Soboleva, Elena V.; Borisovsky, Andrey O.; Khristoforova, Nadezhda K.

    2014-11-01

    The results of the study by scanning electron microscopy with energy dispersive analysis of microparticles of atmospheric suspensions contained in Ussuriysk winter snows (2012/2013) are presented. Particles of rocks and technogenic (mainly metal and soot) formations to prevail in the atmospheric suspensions of Ussuriysk are shown. There is a large amount of metal particles of automobile and industrial - Fe, Au, Pt, Pd, Cu, Sn, Pb, Ti, W. The analysis of the qualitative composition of atmospheric suspensions Ussuriysk confirms its status as a city with a strong impact of automobile transportation and high levels of air pollution.

  19. Composition of dust deposited to snow cover in the Wasatch Range (Utah, USA): Controls on radiative properties of snow cover and comparison to some dust-source sediments

    NASA Astrophysics Data System (ADS)

    Reynolds, Richard L.; Goldstein, Harland L.; Moskowitz, Bruce M.; Bryant, Ann C.; Skiles, S. McKenzie; Kokaly, Raymond F.; Flagg, Cody B.; Yauk, Kimberly; Berquó, Thelma; Breit, George; Ketterer, Michael; Fernandez, Daniel; Miller, Mark E.; Painter, Thomas H.

    2014-12-01

    Dust layers deposited to snow cover of the Wasatch Range (northern Utah) in 2009 and 2010 provide rare samples to determine the relations between their compositions and radiative properties. These studies are required to comprehend and model how such dust-on-snow (DOS) layers affect rates of snow melt through changes in the albedo of snow surfaces. We evaluated several constituents as potential contributors to the absorption of solar radiation indicated by values of absolute reflectance determined from bi-conical reflectance spectroscopy. Ferric oxide minerals and carbonaceous matter appear to be the primary influences on lowering snow-cover albedo. Techniques of reflectance and Mössbauer spectroscopy as well as rock magnetism provide information about the types, amounts, and grain sizes of ferric oxide minerals. Relatively high amounts of ferric oxide, indicated by hard isothermal remanent magnetization (HIRM), are associated with relatively low average reflectance (<0.25) across the visible wavelengths of the electromagnetic spectrum. Mössbauer spectroscopy indicates roughly equal amounts of hematite and goethite, representing about 35% of the total Fe-bearing phases. Nevertheless, goethite (α-FeOOH) is the dominant ferric oxide found by reflectance spectroscopy and thus appears to be the main iron oxide control on absorption of solar radiation. At least some goethite occurs as nano-phase grain coatings less than about 50 nm thick. Relatively high amounts of organic carbon, indicating as much as about 10% organic matter, are also associated with lower reflectance values. The organic matter, although not fully characterized by type, correlates strongly with metals (e.g., Cu, Pb, As, Cd, Mo, Zn) derived from distal urban and industrial settings, probably including mining and smelting sites. This relation suggests anthropogenic sources for at least some of the carbonaceous matter, such as emissions from transportation and industrial activities. The composition of

  20. Coupled long-term summer warming and deeper snow alters species composition and stimulates gross primary productivity in tussock tundra.

    PubMed

    Leffler, A Joshua; Klein, Eric S; Oberbauer, Steven F; Welker, Jeffrey M

    2016-05-01

    Climate change is expected to increase summer temperature and winter precipitation throughout the Arctic. The long-term implications of these changes for plant species composition, plant function, and ecosystem processes are difficult to predict. We report on the influence of enhanced snow depth and warmer summer temperature following 20 years of an ITEX experimental manipulation at Toolik Lake, Alaska. Winter snow depth was increased using snow fences and warming was accomplished during summer using passive open-top chambers. One of the most important consequences of these experimental treatments was an increase in active layer depth and rate of thaw, which has led to deeper drainage and lower soil moisture content. Vegetation concomitantly shifted from a relatively wet system with high cover of the sedge Eriophorum vaginatum to a drier system, dominated by deciduous shrubs including Betula nana and Salix pulchra. At the individual plant level, we observed higher leaf nitrogen concentration associated with warmer temperatures and increased snow in S. pulchra and B. nana, but high leaf nitrogen concentration did not lead to higher rates of net photosynthesis. At the ecosystem level, we observed higher GPP and NEE in response to summer warming. Our results suggest that deeper snow has a cascading set of biophysical consequences that include a deeper active layer that leads to altered species composition, greater leaf nitrogen concentration, and higher ecosystem-level carbon uptake. PMID:26747269

  1. 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.

  2. Colonization in the photic zone and subsequent changes during sinking determine bacterial community composition in marine snow.

    PubMed

    Thiele, Stefan; Fuchs, Bernhard M; Amann, Rudolf; Iversen, Morten H

    2015-02-01

    Due to sampling difficulties, little is known about microbial communities associated with sinking marine snow in the twilight zone. A drifting sediment trap was equipped with a viscous cryogel and deployed to collect intact marine snow from depths of 100 and 400 m off Cape Blanc (Mauritania). Marine snow aggregates were fixed and washed in situ to prevent changes in microbial community composition and to enable subsequent analysis using catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH). The attached microbial communities collected at 100 m were similar to the free-living community at the depth of the fluorescence maximum (20 m) but different from those at other depths (150, 400, 550, and 700 m). Therefore, the attached microbial community seemed to be “inherited” from that at the fluorescence maximum. The attached microbial community structure at 400 m differed from that of the attached community at 100 m and from that of any free-living community at the tested depths, except that collected near the sediment at 700 m. The differences between the particle-associated communities at 400 m and 100 m appeared to be due to internal changes in the attached microbial community rather than de novo colonization, detachment, or grazing during the sinking of marine snow. The new sampling method presented here will facilitate future investigations into the mechanisms that shape the bacterial community within sinking marine snow, leading to better understanding of the mechanisms which regulate biogeochemical cycling of settling organic matter. PMID:25527538

  3. Colonization in the Photic Zone and Subsequent Changes during Sinking Determine Bacterial Community Composition in Marine Snow

    PubMed Central

    Thiele, Stefan; Fuchs, Bernhard M.; Amann, Rudolf

    2014-01-01

    Due to sampling difficulties, little is known about microbial communities associated with sinking marine snow in the twilight zone. A drifting sediment trap was equipped with a viscous cryogel and deployed to collect intact marine snow from depths of 100 and 400 m off Cape Blanc (Mauritania). Marine snow aggregates were fixed and washed in situ to prevent changes in microbial community composition and to enable subsequent analysis using catalyzed reporter deposition fluorescence in situ hybridization (CARD-FISH). The attached microbial communities collected at 100 m were similar to the free-living community at the depth of the fluorescence maximum (20 m) but different from those at other depths (150, 400, 550, and 700 m). Therefore, the attached microbial community seemed to be “inherited” from that at the fluorescence maximum. The attached microbial community structure at 400 m differed from that of the attached community at 100 m and from that of any free-living community at the tested depths, except that collected near the sediment at 700 m. The differences between the particle-associated communities at 400 m and 100 m appeared to be due to internal changes in the attached microbial community rather than de novo colonization, detachment, or grazing during the sinking of marine snow. The new sampling method presented here will facilitate future investigations into the mechanisms that shape the bacterial community within sinking marine snow, leading to better understanding of the mechanisms which regulate biogeochemical cycling of settling organic matter. PMID:25527538

  4. Responses of Plant Community Composition to Long-term Changes in Snow Depth at the Great Basin Desert - Sierra Nevada ecotone.

    NASA Astrophysics Data System (ADS)

    Loik, M. E.

    2015-12-01

    Snowfall is the dominant hydrologic input for many high-elevation ecosystems of the western United States. Many climate models envision changes in California's Sierra Nevada snow pack characteristics, which would severely impact the storage and release of water for one of the world's largest economies. Given the importance of snowfall for future carbon cycling in high elevation ecosystems, how will these changes affect seedling recruitment, plant mortality, and community composition? To address this question, experiments utilize snow fences to manipulate snow depth and melt timing at a desert-montane ecotone in eastern California, USA. Long-term April 1 snow pack depth averages 1344 mm (1928-2015) but is highly variable from year to year. Snow fences increased equilibrium drift snow depth by 100%. Long-term changes in snow depth and melt timing are associated with s shift from shurbs to graminoids where snow depth was increased for >50 years. Changes in snow have impacted growth for only three plant species. Moreover, annual growth ring increments of the conifers Pinus jeffreyi and Pi. contorta were not equally sensitive to snow depth. There were over 8000 seedlings of the shrubs Artemisia tridentata and Purshia tridentata found in 6300 m2 in summer 2009, following about 1400 mm of winter snow and spring rain. The frequency of seedlings of A. tridentata and P. tridentata were much lower on increased-depth plots compared to ambient-depth, and reduced-depth plots. Survival of the first year was lowest for A. tridentata. Survival of seedlings from the 2008 cohort was much higher for P. tridentata than A. tridentata during the 2011-2015 drought. Results indicate complex interactions between snow depth and plant community characteristics, and that responses of plants at this ecotone may not respond similarly to increases vs. decreases in snow depth. These changes portend altered carbon uptake in this region under future snowfall scenarios.

  5. Associations between body composition and helminths of lesser snow geese during winter and spring migration.

    PubMed

    Shutler, Dave; Alisauskas, Ray T; Daniel McLaughlin, J

    2012-07-01

    Costs of parasitism are predicted to be higher with greater parasite intensities and higher inter-parasite competition (diversity). We tested whether greater helminth intensities and diversity were associated with poorer body composition (whole-body fat, protein, mineral and true body mass) in lesser snow geese, Chen caerulescens caerulescens. As part of a larger study on nutritional ecology, 828 wintering or migrating geese were shot between January and May 1983 in 27 different date-locations (samples) during their northward migration through mid-continental North America. A large proportion of overall variation in body composition and parasite communities was among samples, so we analyzed data within each of the 27 samples, controlling for structural body size (the first principal component of 10 body size measurements), sex and the age of geese. There was no compelling evidence that cestodes, trematodes or helminth diversity were associated with variation in body composition but nematodes had several negative associations with fat reserves. However, negative associations between fat reserves and nematodes occurred most often in geese collected between March and May when nematode prevalences and intensities were relatively low. This suggests several possibilities: that the most common nematodes (Heterakis dispar and Trichostrongylus tenuis) were more virulent at this time, that infected individuals had been chronically infected and suffered cumulative nutrient deficits that lasted until late in the spring migration, or that geese became more vulnerable to the effects of parasites at this time of year, possibly because they redirected resources away from immunity toward fat storage in preparation for reproduction. PMID:22713759

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  7. Snow Water Equivalent distribution in the Western Alps: the activities in Aosta Valley

    NASA Astrophysics Data System (ADS)

    Morra di Cella, Umberto; Cremonese, Edoardo; Diotri, Fabrizio; Pogliotti, Paolo; Galvagno, Marta

    2010-05-01

    Snow can be seen as a water reservoir; it plays an important role in the hydrological cycle and climatology of the Earth. Its importance is enhanced in mountainous region where yearly streamflow is strongly controlled by snowmelt dynamics. Climate Change can influence precipitation distribution and snow cover persistence and thus can negatively affect water availability. The knowledge of the amount of water stored in the snow, its spatial distribution and its temporal evolution dynamics, is an issue of increasing importance. The Aosta Valley is a region in the western Italian Alps with a continental climate which can be strongly affected by a reduction of water availabilty. For these reasons, from 2006, the Environmental Protection Agency of Aosta Valley (ARPA Valle d'Aosta) is developping modelling activities aiming to monitor Snow Water Equivalent (SWE) distribution at regional scale (3000 Km2). To estimate SWE distribution we need to know the extent of the snow covered area (SCA) and how snow height (SH) and snow density (SD) are distributed in space. Because of the specific spectral reflectance of snow, SCA can be discriminated from snow-free areas using optical remote sensing methods. The MODIS standard snow-cover products (MOD10A2 maximum snow extent - 8 days composite) can be freely downloaded from the web and their spatial resolution (500 m) is well suited for the application at regional scale. Snow height data can be obtained from automatic measurements (ultrasonic distance sensors) done by the regional meteorological station networks or by manual measurements of snow depth, while snow density has to be manually measured in snow pits. It follows that SH dataset are often more data-rich than SD ones. Snow height and snow density spatial distribution is modelled using multiple regression models between the snow parameters and many morphological variables (e.g. elevation, slope, incoming solar radiation, topographical parameters, ...). Regression models are

  8. Snow cover variations in Gansu, China, from 2002 to 2013

    NASA Astrophysics Data System (ADS)

    Liu, Xun; Ke, Chang-Qing; Shao, Zhu-De

    2015-11-01

    Gansu is an inland province located in the northwest of China with an arid to semi-arid climate and a developed animal husbandry. Snowmelt in Gansu is an important source of water for rivers and plays an important role in ecological environment and social-economic activities. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day composite snow products MOD10A2 and MYD10A2 are combined to analyse snow cover variations during the snow season (October to March) period from 2002 to 2013. We define the snow area percentage (SAP) and snow cover occurrence percentage (SCOP) to analyse the spatial and temporal characteristics of the snow cover variation in Gansu. In addition, we apply the Mann-Kendall test to verify the SAP inter-annual variation. The results indicate that the SAP in Gansu remained above 5 % with three peaks in November, December and January. SAP varies a lot in the four sub-regions of Gansu, with the highest in the Gannan Plateau sub-region and the lowest in the Longzhong Loess Plateau sub-region in most of the snow seasons examined. The SCOP is high in the southwest mountains and low in the northeast Gobi and desert. The SCOP is highly related to elevation in most of Gansu, with an exception in the high mountains. In the Hexi Desert and oasis region, the SAP significantly decreases during the snow season, particularly in February and March. We find that there are a significantly negative correlation between SCOP and temperature during the snow season and a significantly positive correlation between SCOP and precipitation in December.

  9. Composition of microbial communities in aerosol, snow and ice samples from remote glaciated areas (Antarctica, Alps, Andes)

    NASA Astrophysics Data System (ADS)

    Elster, J.; Delmas, R. J.; Petit, J.-R.; Řeháková, K.

    2007-06-01

    Taxonomical and ecological analyses were performed on micro-autotrophs (cyanobacteria and algae together with remnants of diatom valves), micro-fungi (hyphae and spores), bacteria (rod, cocci and red clusters), yeast, and plant pollen extracted from various samples: Alps snow (Mt. Blank area), Andean snow (Illimani, Bolivia), Antarctic aerosol filters (Dumont d'Urville, Terre Adélie), and Antarctic inland ice (Terre Adélie). Three methods for ice and snow sample's pre-concentration were tested (filtration, centrifugation and lyophilisation). Afterwards, cultivation methods for terrestrial, freshwater and marine microorganisms (micro-autotrophs and micro-fungi) were used in combination with liquid and solid media. The main goal of the study was to find out if micro-autotrophs are commonly transported by air masses, and later stored in snow and icecaps around the world. The most striking result of this study was the absence of culturable micro-autotrophs in all studied samples. However, an unusual culturable pigmented prokaryote was found in both alpine snow and aerosol samples. Analyses of many samples and proper statistical analyses (PCA, RDA- Monte Carlo permutation tests) showed that studied treatments highly significantly differ in both microbial community and biotic remnants composition F=9.33, p=0.001. In addition, GLM showed that studied treatments highly significantly differ in numbers of categories of microorganisms and remnants of biological material F=11.45, p=0.00005. The Antarctic aerosol samples were characterised by having red clusters of bacteria, the unusual prokaryote and yeasts. The high mountain snow from the Alps and Andes contained much more culturable heterotrophs. The unusual prokaryote was very abundant, as were coccoid bacteria, red clusters of bacteria, as well as yeasts. The Antarctic ice samples were quite different. These samples had higher numbers of rod bacteria and fungal hyphae. The microbial communities and biological remnants of

  10. Composition and sources of atmospheric dusts in snow at 3200 meters in the St. Elias Range, southeastern Alaska, USA

    USGS Publications Warehouse

    Hinkley, T.K.

    1994-01-01

    Dusts in snow from the accumulation zone in the St. Elias Range appear from their chemical compositions to have come from terranes of rocks of ferromagnesian composition. These dusts, with respect to their composition and to the moderate degree of variation that occurs through a depositional year, are similar those deposited in Greenland. The high portion of the St. Elias Range is isolated from dominance by any local dust source terranes, because of altitude and the extent of the surrounding glacierized and snow-covered region. In Greenland the altitude is typically lower, but local sources are even less likely to dominate the character of the dusts deposited into the ice record there. The similar compositions and moderate compositional variations of dusts from these two places bear on the question of whether the dusts that are transported over long distances by the atmosphere under modern and glacial-period conditions are uniform and representative of a broad regional or even hemispheric background dust. The dusts in the snow were measured by means of a suite of major, minor, and trace rock-forming metals chosen to give information about rock types, their constituent minerals, degree of degradation (weathering), and energies of atmospheric uptake from source. The variations in amounts of rock dust through the year in the St. Elias Range snowpack have no time-stratigraphic correspondence to the also large variations in concentrations of other species that are not constituents of rock-derived dusts, such the anions chloride, sulfate, and nitrate; the highs and lows of the two types of materials are apparently completely independent. The structure revealed by the moderately fine-scale sampling of the present study (??? 10 increments/y) serves as a background for the interpretation of analysis of ice core samples, in which annual layers may be too compressed to permit analysis of sub-annual samples. ?? 1994.

  11. Spatial and seasonal variations of elemental composition in Mt. Everest (Qomolangma) snow/firn

    NASA Astrophysics Data System (ADS)

    Kang, Shichang; Zhang, Qianggong; Kaspari, Susan; Qin, Dahe; Cong, Zhiyuan; Ren, Jiawen; Mayewski, Paul A.

    In May 2005, a total of 14 surface snow (0-10 cm) samples were collected along the climbing route from the advanced base camp to the summit (6500-8844 m a.s.l.) on the northern slope of Mt. Everest (Qomolangma). A 108 m firn/ice core was retrieved from the col of the East Rongbuk Glacier (28.03°N, 86.96°E, 6518 m a.s.l.) on the north eastern saddle of Mt. Everest in September 2002. Surface snow and the upper 3.5 m firn samples from the core were analyzed for major and trace elements by inductively coupled plasma mass spectroscopy (ICP-MS). Measurements show that crustal elements dominated both surface snow and the firn core, suggesting that Everest snow chemistry is mainly influenced by crustal aerosols from local rock or prevalent spring dust storms over southern/central Asia. There are no clear trends for element variations with elevation due to local crustal aerosol inputs or redistribution of surface snow by strong winds during the spring. Seasonal variability in snow/firn elements show that high elemental concentrations occur during the non-monsoon season and low values during the monsoon season. Ca, Cr, Cs, and Sr display the most distinct seasonal variations. Elemental concentrations (especially for heavy metals) at Mt. Everest are comparable with polar sites, generally lower than in suburban areas, and far lower than in large cities. This indicates that anthropogenic activities and heavy metal pollution have little effect on the Mt. Everest atmospheric environment. Everest firn core REE concentrations are the first reported in the region and seem to be comparable with those measured in modern and Last Glacial Maximum snow/ice samples from Greenland and Antarctica, and with precipitation samples from Japan and the East China Sea. This suggests that REE concentrations measured at Everest are representative of the background atmospheric environment.

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

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  13. Spatial and temporal variability of snow chemical composition and accumulation rate at Talos Dome site (East Antarctica).

    PubMed

    Caiazzo, Laura; Becagli, Silvia; Frosini, Daniele; Giardi, Fabio; Severi, Mirko; Traversi, Rita; Udisti, Roberto

    2016-04-15

    Five snow pits and five firn cores were sampled during the 2003-2004 Italian Antarctic Campaign at Talos Dome (East Antarctica), where a deep ice core (TALDICE, TALos Dome Ice CorE, 1650m depth) was drilled in 2005-2008 and analyzed for ionic content. Particular attention is spent in applying decontamination procedures to the firn cores, as core sections were stored for approximately 10years before analysis. By considering the snow pit samples to be unperturbed, the comparison with firn core samples from the same location shows that ammonium, nitrate and MSA are affected by storage post-depositional losses. All the other measured ions are confirmed to be irreversibly deposited in the snow layer. The removal of the most external layers (few centimeters) from the firn core sections is proved to be an effective decontamination procedure. High-resolution profiles of seasonal markers (nitrate, sulfate and MSA) allow a reliable stratigraphic dating and a seasonal characterization of the samples. The calculated mean accumulation-rate values range from 70 to 85mmw.e.year(-1), in the period 2003-1973 with small differences between two sectors: 70-74mmw.e.year(-1) in the NNE sector (spanning 2003-1996years) and 81-92mmw.e.year(-1) in the SSW sector (spanning 2003-1980years). This evidence is interpreted as a coupled effect of wind-driven redistribution processes in accumulation/ablation areas. Statistical treatment applied to the concentration values of the snow pits and firn cores samples collected in different points reveals a larger temporal variability than spatial one both in terms of concentration of chemical markers and annual accumulation. The low spatial variability of the accumulation rate and chemical composition measured in the five sites demonstrates that the TALDICE ice core paleo-environmental and paleo-climatic stratigraphies can be considered as reliably representative for the Talos Dome area. PMID:26849319

  14. Insight into biogeochemical inputs and composition of Greenland Ice Sheet surface snow and glacial forefield river catchment environments.

    NASA Astrophysics Data System (ADS)

    Cameron, Karen; Hagedorn, Birgit; Dieser, Markus; Christner, Brent; Choquette, Kyla; Sletten, Ronald; Lui, Lu; Junge, Karen

    2014-05-01

    The volume of freshwater transported from Greenland to surrounding marine waters has tended to increase annually over the past four decades as a result of warmer surface air temperatures (Bamber et al 2012, Hanna et al 2008). Ice sheet run off is estimated to make up approximately of third of this volume (Bamber et al 2012). However, the biogeochemical composition and seeding sources of the Greenland Ice Sheet supraglacial landscape is largely unknown. In this study, the structure and diversity of surface snow microbial assemblages from two regions of the western Greenland Ice Sheet ice-margin was investigated through the sequencing of small subunit rRNA genes. Furthermore, the origins of microbiota were investigated by examining correlations to molecular data obtained from marine, soil, freshwater and atmospheric environments and to geochemical analytes measured in the snow. Snow was found to contain a diverse assemblage of bacteria (Alphaproteobacteria, Betaproteobacteria and Gammaproteobacteria) and eukarya (Alveolata, Fungi, Stramenopiles and Viridiplantae). Phylotypes related to archaeal Thaumarchaeota and Euryarchaeota phyla were also identified. The structure of microbial assemblages was found to have strong similarities to communities sampled from marine and air environments, and sequences obtained from the South-West region, near Kangerlussuaq, which is bordered by an extensive periglacial expanse, had additional resemblances to soil originating communities. Strong correlations were found between bacterial beta diversity and Na+ and Cl- concentrations. These data suggest that surface snow from western regions of Greenland contain microbiota that are most likely derived from exogenous, wind transported sources. Downstream of the supraglacial environment, Greenland's rivers likely influence the ecology of localized estuary and marine systems. Here we characterize the geochemical and biotic composition of a glacial and glacial forefield fed river catchment in

  15. Spatial-temporal dynamics of chemical composition of surface snow in East Antarctic along the transect Station Progress-Station Vostok

    NASA Astrophysics Data System (ADS)

    Khodzher, T. V.; Golobokova, L. P.; Shibaev, Y. A.; Lipenkov, V. Y.; Petit, J. R.

    2013-05-01

    This paper presents data on chemical composition of the Antarctic snow sampled during the 53rd Russian Antarctic Expedition (RAE, 2008) along the first tractor traverse (TT) from Station Progress to Station Vostok (East Antarctica). Snow samples were obtained from the cores drilled at 55.3, 253, 337, 369, 403, 441, 480, 519, 560, 618, 819, and 1276 km from Station Progress. Data on horizontal and deep distribution of chemical components in the snow provide evidence of spatial and temporal variations of conditions for the snow cover formation along the transect under study. Sea salt was the main source for chemical composition of snow cover near the ice edge. Concentrations of marine-derived components decreased further inland. A hypothesis was put forward that some ions in the snow cover of the central part of East Antarctica were likely to be of continental origin. Elevated concentrations of sulphate ions of continental origin were recorded in some profiles of the transect at a depth of 130-150 cm which was attributed to buried signals of the Pinatubo volcano eruption (1991).

  16. Snow-borne nanosized particles: Abundance, distribution, composition, and significance in ice nucleation processes

    NASA Astrophysics Data System (ADS)

    Rangel-Alvarado, Rodrigo Benjamin; Nazarenko, Yevgen; Ariya, Parisa A.

    2015-11-01

    Physicochemical processes of nucleation constitute a major uncertainty in understanding aerosol-cloud interactions. To improve the knowledge of the ice nucleation process, we characterized physical, chemical, and biological properties of fresh snow using a suite of state-of-the-art techniques based on mass spectrometry, electron microscopy, chromatography, and optical particle sizing. Samples were collected at two North American Arctic sites, as part of international campaigns (2006 and 2009), and in the city of Montreal, Canada, over the last decade. Particle size distribution analyses, in the range of 3 nm to 10 µm, showed that nanosized particles are the most numerous (38-71%) in fresh snow, with a significant portion (11 to 19%) less than 100 nm in size. Particles with diameters less than 200 nm consistently exhibited relatively high ice-nucleating properties (on average ranged from -19.6 ± 2.4 to -8.1 ± 2.6°C). Chemical analysis of the nanosized fraction suggests that they contain bioorganic materials, such as amino acids, as well as inorganic compounds with similar characteristics to mineral dust. The implication of nanoparticle ubiquity and abundance in diverse snow ecosystems are discussed in the context of their importance in understanding atmospheric nucleation processes.

  17. 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 ...

  18. "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.

  19. Element composition of insoluble fraction of aerosols in snow in the vicinity of oil chemistry refinery (Pavlodar City, Kazakhstan) and petrochemical plant (Tomsk City, Russia)

    NASA Astrophysics Data System (ADS)

    Talovskaya, Anna V.; Filimonenko, Ekaterina A.; Yazikov, Egor G.; Shakhova, Tatyana S.; Parygina, Irina A.

    2015-11-01

    Tomsk petrochemical plant (Russia) and Pavlodar oil chemistry refinery (Kazakhstan) are the sources of air contamination in Tomsk and Pavlodar respectively. Therefore, it is very important to study the level of air contamination with particulate matter as well as ultimate composition of these particles. Disposable solid particles fall out to the snow cover, so snow is an accumulator of the particles. The article deals with the study results of dust load and concentrations of Br, Sb, La, Ce, Sm and Nd in insoluble fraction of aerosols in snow in the vicinity of Pavlodar oil chemistry refinery and Tomsk petrochemical plant. The instrumental neutron activation analysis was used for the ultimate composition detection. Results were shown that the dust load in the vicinity of Tomsk petrochemical plant is higher than in Pavlodar. We have detected high concentrations of La, Br and Sm in insoluble fraction of aerosols in snow in the vicinity of Pavlodar refinery and high concentrations of Sb and Ce in Tomsk. Moreover, we have detected high Br concentration in insoluble fraction of aerosols in snow of the vicinity of both plants. Gas burning on the flares of these enterprises is likely a potential source of Br. La to light lanthanoids ratio have shown La is of anthropogenic origin. In addition, enrichment factor estimation reflects an anthropogenic origin of La, Sm, Br, Ce and Sb as well. These elements might be emitted from different production facilities of the plants.

  20. Sulfur isotopic composition of surface snow along a latitudinal transect in East Antarctica

    NASA Astrophysics Data System (ADS)

    Uemura, Ryu; Masaka, Kosuke; Fukui, Kotaro; Iizuka, Yoshinori; Hirabayashi, Motohiro; Motoyama, Hideaki

    2016-06-01

    The sulfur stable isotopic values (δ34S) of sulfate aerosols can be used to assess oxidation pathways and contributions from various sources, such as marine biogenic sulfur, volcanoes, and sea salt. However, because of a lack of observations, the spatial distribution of δ34S values in Antarctic sulfate aerosols remains unclear. Here we present the first sulfur isotopic values from surface snow samples along a latitudinal transect in eastern Dronning Maud Land, East Antarctica. The δ34S values of sulfate showed remarkably uniform values, in the range of 14.8-16.9‰, and no significant decrease toward the inland part of the transect was noted. These results suggest that net isotopic fractionation during long-range transport is insignificant. Thus, the δ34S values can be used to infer source contributions. The δ34S values suggest that marine biogenic sulfur is the dominant source of sulfate aerosols, with a fractional contribution of 84 ± 16%.

  1. The chemical composition of rivers and snow affected by the 2014/2015 Bárðarbunga eruption, Iceland

    NASA Astrophysics Data System (ADS)

    Galeczka, Iwona; Sigurdsson, Gunnar; Eiriksdottir, Eydis Salome; Oelkers, Eric H.; Gislason, Sigurdur R.

    2016-04-01

    The 2014/15 Bárðarbunga volcanic eruption was the largest in Iceland for more than 200 years. This eruption released into the atmosphere on average 60,000 tonnes/day of SO2, 30,000 tonnes/day of CO2, and 500 tonnes/day of HCl affecting the chemical composition of rain, snow, and surface water. The interaction of these volcanic gases with natural waters, decreases fluid pH and accelerates rock dissolution. This leads to the enhanced release of elements, including toxic metals such as aluminium, to these waters. River monitoring, including spot and continuous osmotic sampling, shows that although the water conductivity was relatively stable during the volcanic unrest, the dissolution of volcanic gases increased the SO4, F, and Cl concentrations of local surface waters by up to two orders of magnitude decreasing the carbon alkalinity. In addition the concentration of SiO2, Ca, Mg, Na and trace metals rose considerably due to the water-molten lava and hot solid lava interaction. The presence of pristine lava and acidic gases increased the average chemical denudation rate, calculated based on Na flux, within Jökulsá á Fjöllum catchment by a factor of two compared to the background flux. Melted snow samples collected at the eruption site were characterised by a strong dependence of the pH on SO4, F and Cl and metal concentrations, indicating that volcanic gases and aerosols acidified the snow. Protons balanced about half of the negatively charged anions; the rest was balanced by water-soluble salts and aerosols containing a variety of metals including Al, Fe, Na, Ca, and Mg. The concentrations of F, Al, Fe, Mn, Cd, Cu, and Pb in the snowmelt water surpassed drinking- and surface water standards. Snowmelt-river water mixing calculations indicate that low alkalinity surface waters, such as numerous salmon rivers in East Iceland, will be more affected by polluted snowmelt waters than high alkalinity spring and glacier fed rivers.

  2. 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

  3. The Effect of Aerosol Deposition on Snow Albedo Reduction in the Sierra Nevada Mountains

    NASA Astrophysics Data System (ADS)

    Lee, W.; Liou, K.

    2008-12-01

    We investigate snow cover and albedo changes in the Sierra Nevada regions due to deposition of black carbon and dust particles from East Asia. We note that coal combustion reaches maximum in the winter, while dust storms originate in the Gobi Desert occur most frequently in April. We selected snow and albedo data from MODIS/Terra to examine albedo reduction in March and April from 2000 to 2008. To eliminate the contamination of albedo by bare land, only the pixels with 100% snow cover in the entire period were used. Analysis using the 8-day average snow cover and 16-day average surface albedo reveals that there is a small increasing trend of albedo reduction. We also show that a large snow albedo reduction in 2001 is possibly due to the strong dust storm event that occurred in April, 2001. Finally, composite time series have been made using daily data to demonstrate decrease in snow albedo after each snowfall event. We illustrate that the rate of albedo reduction increases by 0.01/day per year from 2000 to 2008.

  4. Seasonal and geographical variations of sterol composition in snow crab hepatopancreas and pelagic fish viscera from Eastern Quebec.

    PubMed

    Souchet, Nathalie; Laplante, Serge

    2007-07-01

    Sterol composition was determined in snow crab hepatopancreas and mackerel and herring viscera for various locations and collection periods. A simple and valuable method, using direct saponification and extraction with water-cyclohexane has been optimized to recover total sterol. They were identified and quantified as trimethylsilyl ether derivatives by GC-MS analysis. Method validation indicated excellent sensitivity (limit of quantification: 1.25 mg/100 g wet basis for cholesterol and desmosterol; 0.03-0.05 mg/100 g for other sterols), good reproducibility (CV%: 1.5-6.8) and accuracy (recovery%: 94-107). In crab hepatopancreas, cholesterol was the main sterol (67-76%), followed by desmosterol (19-24%). Phytosterols and molluscan sterols were also present in low quantity. A lower total sterol content with different composition was found in crabs from Magdalen Islands compared to those from Gaspé Peninsula or North Shore of the St-Lawrence Gulf. No seasonal variation was observed between collection periods, which were probably too close. Mackerel and herring viscera contained the same sterols as crab except for campesterol and sitosterol, but the cholesterol proportion was higher (93-98%). The higher abundance of sterols in herring caught in September vs. May would be related to an increase of the body lipid content during the summer. PMID:17374564

  5. 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…

  6. 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.

  7. Monitoring Vegetation Phenology and Snow Free Periods with the Daily MODIS BRDF/albedo Product

    NASA Astrophysics Data System (ADS)

    Wang, Z.; Schaaf, C.; Strahler, A. H.; Zhang, X.; Shuai, Y.; YANG, Y.

    2012-12-01

    The effects of rapidly changing events such as vegetation phenology and seasonal snowfall play important roles in the annual terrestrial energy and carbon cycles and serve as indicators of climate change. The timing of vegetation greenup and senescence impacts essential ecosystem processes while snow free surfaces absorb more solar radiation than high albedo snow covered regions. Recent research has indicated that the duration of the snow-free period at high northern latitudes has increased due to climate change and the longer snow-free periods have affected the composition and extent of vegetation at high latitudes. The MODerate resolution Imaging Spectroradiometer (MODIS) BRDF/albedo product has provided measures of surface albedo and vegetation phenology for more than 12 years. The standard V005 product makes use of a linear "kernel-driven" RossThick-LiSparse Reciprocal (RTLSR) BRDF model to describe the reflectance anisotropy of each pixel at a 500-m gridded resolution. In the past this multi-day product was only retrieved every 8 days which has limited its ability to capture rapidly changing events such as ephemeral snow fall and melt and vegetation emergence and senescence. A daily version of the MODIS product still uses all MODIS observations acquired during a 16-day period but utilizes a moving window to improve on the 8-day temporal resolution of the standard V005 NASA data products and allows daily monitoring of land surface change phenomena. Individual observations are weighted by their quality, observation coverage, and proximity to the production date of interest. In this study, we monitor the phenology dynamics over forest, grass and tundra sites and the extent of the snow free period over high latitude areas by using the daily MODIS Nadir BRDF-Adjusted Reflectance (NBAR) data from MODIS BRDF/albedo product.

  8. Detection of changes in snow line elevation from MODIS imagery in the Romanian Carpathians

    NASA Astrophysics Data System (ADS)

    Micu, Mihai; Micu, Dana; Sandric, Ionut; Mihalache, Sorin

    2015-04-01

    Mountain snow cover is particularly sensitive to the observed shifts in the regime of its two determinants (air temperature and precipitation), in response to climate warming. The climate of the Romanian Carpathians became warmer particularly in winter, spring and summer, exibiting an increasing frequency of hot extremes and a decrease of freezing days. There is also an obvious trend towards a late snowpack onset in Autumn, more evident in the areas below 1,700 m, and towards an earlier Spring snowmelting, generalized across the entire region. The observed changes in the timing of snowmelt due to milder winters, are explaining most of the decline of snow cover duration in the areas below 2,000 m. Snow line, separating snow covered from snow free areas, is considered a key indicator for monitoring the changes in snow coverage under the changing climate behavior. This study aims at deriving and analysing the changes in snowline elevation (SLE) using the multi-temporal Moderate-resolution Imaging Spectrometer (MODIS) reflectance products (MYD10 and MOD10 daily and 8-day composite) and a high-resolution Digital Elevation Model (DEM) of the Romanian Carpathians (30 m). The changes in SLE were analyzed in relation to the shifts in freezing height (FH) across the Romanian Carpathians, derived from MYD11A1, MYD11A2, MOD11A1 and MOD11A2 daily and 8-day composite products, available at a spatial resolution of 1 km. Python batch scripts using Esri ArcPy were developed and applied to download, subset, reproject and mask each MODIS product. The analyses were focused on producing and using daily and 8-day composites time series from both Terra and Aqua MODIS products for a period of about 12 years, starting from 2002 up to present day. The variability of snow cover persistence was investigated at both monthly and seasonal time steps, allowing to identify the trends in SLE and FH, as well as the changes in the timing of snow melt across the region. The paper is revealing the

  9. Isotope and chemical compositions of meteoric and thermal waters and snow from the greater Yellowstone National Park region

    USGS Publications Warehouse

    Kharaka, Yousif K.; Thordsen, James J.; White, Lloyd D.

    2002-01-01

    An intensive hydrogeologic investigation, mandated by U.S. Congress and centered on the Norris-Mammoth corridor was conducted by USGS and other scientists during 1988-90 to determine the effects of using thermal water from a private well located in the Corwin Springs Known Geothermal Resources Area, Montana, on the thermal springs of Yellowstone National Park (YNP), especially Mammoth Hot Springs. As part of this investigation, we carried out a detailed study of the isotopic and chemical compositions of meteoric water from cold springs and wells, of thermal water, especially from the Norris-Mammoth corridor and of snow. Additional sampling of meteoric and thermal waters from YNP and surrounding region in northwest Wyoming, southwest Montana and southeast Idaho was carried out in 1991-92 to characterize the distribution of water isotopes in this mountainous region and to determine the origin and possible recharge locations of thermal waters in and adjacent to the Park. The D and 18O values for 40 snow samples range from ?88 to ?178? and ?12.5 to ?23.9?, respectively, and define a well constrained line given by D = 8.2 18O + 14.7 (r2 = 0.99) that is nearly identical to the Global Meteoric Water Line. The D and 18O values of 173 cold water samples range from ?115 to ?153? and ?15.2 to ?20.2?, respectively, and exhibit a similar relationship although with more scatter and with some shift to heavier isotopes, most likely due to evaporation effects. The spatial distribution of cold-water isotopes shows a roughly circular pattern with isotopically lightest waters centered on the mountains and high plateau in the northwest corner of Yellowstone National Park and becoming heavier in all directions. The temperature effect due to altitude is the dominant control on stable water isotopes throughout the region; however, this effect is obscured in narrow 'canyons' and areas of high topographic relief. The effects due to distance (i.e. 'continental') and latitude on water

  10. Spatial Drivers in the Origin and Composition of Dissolved Organic Matter in Snow: Implications for Proglacial Stream Biogeochemistry

    NASA Astrophysics Data System (ADS)

    Fellman, J.; Hood, E. W.; Raymond, P. A.; Stubbins, A.; Spencer, R. G.

    2014-12-01

    The Coast Mountains of southeast Alaska are currently experiencing high rates of glacier volume loss. Continued glacier wastage therefore has the potential to decrease the proportion of streamflow derived from glacial runoff, which could alter the nature of dissolved organic matter (DOM) delivered to proglacial streams. We collected snow from ten locations along a transect that extended from the coast 47 km across the Juneau Icefield, southeast Alaska and analyzed the snow for δ18O and DOM for 13C, 14C and fluorescence characteristics. Our goal was to assess the origin and quality of DOM in snow to better understand how continued glacial recession in the region may influence the transfer of organic matter to proglacial aquatic ecosystems. The δ18O of snow decreased with distance from the coast (r2=84, p<0.01) indicative of the natural fractionation or fallout of heavy δ18O that occurs along elevation or spatial gradients. This depletion in the isotopic signature of snow across the Icefield transect was reflected in the origin and quality of DOM. Concentrations of dissolved organic carbon (DOC) varied from 0.13 to 0.29 mg C L-1 and progressively decreased (r2=43, p<0.05) as δ18O became more depleted. The Δ14C-DOC varied from -742 to -420‰ and showed progressive depletion with decreasing δ18O (r2=56, p<0.01). Older DOC corresponded to a decrease in the percent contribution of humic-like fluorescence (r2=74, p<0.01) suggesting an overall decrease in modern continental DOM across the transect. A three-source isotope mixing model showed that DOM in snow originates mainly from anthropogenic aerosols from fossil fuel combustion (45-74%) and marine sources (17-34%). These results suggest that anthropogenic aerosols are a quantitatively important source of relic DOM to the glacier ecosystem. Given relic DOM exported from glaciers is highly bioavailable, anthropogenic aerosols could profoundly influence the transfer of DOM from glaciers to proglacial aquatic

  11. First data on the composition of atmospheric dust responsible for yellow snow in Northern European Russia in March 2008

    NASA Astrophysics Data System (ADS)

    Shevchenko, V. P.; Korobov, V. B.; Lisitzin, A. P.; Aleshinskaya, A. S.; Bogdanova, O. Yu.; Goryunova, N. V.; Grishchenko, I. V.; Dara, O. M.; Zavernina, N. N.; Kurteeva, E. I.; Novichkova, E. A.; Pokrovsky, O. S.; Sapozhnikov, F. V.

    2010-04-01

    The descent of a large quantity of dust responsible for bright colors of atmospheric precipitation in the temperate, subpolar, and polar zones of the northern hemisphere is rarely observed [1-5]. In the twentieth century and in the beginning of the twenty-first century in the northern part of European Russia, such events had not been registered right up to March 25-26, 2008. At that time in some parts of the Arkhangelsk region, Komi Republic, and Nenets Autonomous Area, atmospheric precipitation as moist snow and rain responsible for sand and saffron colors of ice crust formation on the snow surface was observed. Thus, due to detailed mineralogical, geochemical, pollen, diatom, and meteorological investigations, it was established that the main source of the yellow dust is the semidesert and steppe regions of the Northwest Kazakhstan, and the Volgograd and Astrakhan regions, Kalmykia.

  12. 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.

  13. 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

  14. 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.

  15. 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…

  16. Study on short term prediction using observed water quality from 8-day intervals in Nakdong river

    NASA Astrophysics Data System (ADS)

    Kim, M.; Shon, T.; Joo, J.; Kim, J.; Shin, H.

    2012-12-01

    There are lots of accidents on water quality, like green algal blooms, occurring in Nakdong river which is one of the largest river in Korea. This is because of climate change around the world. It is essential to develop scientific and quantitative assessment methods. In this study, artificial neural network based on back propagation algorithm, which is simple and flexible method, was used for forecasting the water quality on the purpose of water resources management. Especially, as used observed water quality data from 8-day intervals in Nakdong river, it makes to increase the accuracy of water quality forecast over short term. This was established for predicting the water quality factors 1, 3, and 7 days ahead. The best model, as evaluated by its performance functions with RMSE and R2, was selected and applied to established models of BOD, DO, COD, and Chl-a using artificial neural network. The results showed that the models were suitable for 1 and 3 days forecasts in particular. This method is strong and convenient to predict water quality factors over the short term easily based on observed data. It is possible to overcome and manage problems related to the water resources. In the future, this will be a powerful method because it is basically based on observed water quality data.

  17. Time-dependent analysis of 8 days of CN spatial profiles in comet P/Halley

    NASA Technical Reports Server (NTRS)

    Combi, Michael; Huang, Bormin; Cochran, Anita; Fink, Uwe; Schulz, Rita

    1994-01-01

    CN profiles in comet P/Halley were constructed from observations taken at three observatories during an 8 day period in April 1986. These data provide a time series of CN spatial profiles spanning just over one 7.37 day period from 1986 April 7 to April 15 and sample distances from the nucleus from just over 10(exp 3) km to 10(exp 6) km. The effect of the 7.37 day periodic variation on the CN distribution in P/Halley has been examined by using the time-dependent model applied earlier to a subset of the data. Because of the large spatial scale of the data on April 7, 8, and 9 (approx. 10(exp 6) km), and the corresponding transport time in the coma, information present in the spatial profiles regarding the gas production rate actually covers nearly two full periods. These spatially extended profiles clearly show the wavy structures outside 10(exp 5) km. Such structures were predicted in a previous analysis (Combi & Fink 1993) that was based solely on the photometric light curve and on profiles which only extended to distances less than 10(exp 5) km. We are now able to reproduce the highly variable Halley correction for the variation in gas production rate.

  18. Snow particle speeds in drifting snow

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  19. 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

  20. Integrated simulation of snow and glacier melt in water and energy balance-based, distributed hydrological modeling framework at Hunza River Basin of Pakistan Karakoram region

    NASA Astrophysics Data System (ADS)

    Shrestha, Maheswor; Koike, Toshio; Hirabayashi, Yukiko; Xue, Yongkang; Wang, Lei; Rasul, Ghulam; Ahmad, Bashir

    2015-05-01

    Energy budget-based distributed modeling of snow and glacier melt runoff is essential in a hydrologic model to accurately describe hydrologic processes in cold regions and high-altitude catchments. We developed herein an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers, and multilayer scheme for seasonal snow over glacier, soil, and forest within a distributed biosphere hydrological modeling framework. Model capability is demonstrated for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan on a 500 m grid for 3 hydrologic years (2002-2004). Discharge simulation results show good agreement with observations (Nash-Sutcliffe efficiency = 0.93). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt). Pixel-by-pixel evaluation of the simulated spatial distribution of snow-covered area against Moderate Resolution Imaging Spectroradiometer-derived 8 day maximum snow cover extent data indicates that the areal extent of snow cover is reproduced well, with average accuracy 84% and average absolute bias 7%. The 3 year mean value of net mass balance (NMB) was estimated at +0.04 myr-1. It is interesting that individual glaciers show similar characteristics of NMB over 3 years, suggesting that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region toward simulating snow and glacier hydrologic processes within a water and energy balance-based, distributed hydrological modeling framework.

  1. 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)

  2. Camping in the Snow.

    ERIC Educational Resources Information Center

    Brown, Constance

    1979-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. 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…

  7. Frost flowers growing in the Arctic ocean-atmosphere-sea ice-snow interface: 1. Chemical composition

    NASA Astrophysics Data System (ADS)

    Douglas, Thomas A.; Domine, Florent; Barret, Manuel; Anastasio, Cort; Beine, Harry J.; Bottenheim, Jan; Grannas, Amanda; Houdier, Stephan; Netcheva, Stoyka; Rowland, Glenn; Staebler, Ralf; Steffen, Alexandra

    2012-07-01

    Frost flowers, intricate featherlike crystals that grow on refreezing sea ice leads, have been implicated in lower atmospheric chemical reactions. Few studies have presented chemical composition information for frost flowers over time and many of the chemical species commonly associated with Polar tropospheric reactions have never been reported for frost flowers. We undertook this study on the sea ice north of Barrow, Alaska to quantify the major ion, stable oxygen and hydrogen isotope, alkalinity, light absorbance by soluble species, organochlorine, and aldehyde composition of seawater, brine, and frost flowers. For many of these chemical species we present the first measurements from brine or frost flowers. Results show that major ion and alkalinity concentrations, stable isotope values, and major chromophore (NO3- and H2O2) concentrations are controlled by fractionation from seawater and brine. The presence of these chemical species in present and future sea ice scenarios is somewhat predictable. However, aldehydes, organochlorine compounds, light absorbing species, and mercury (part 2 of this research and Sherman et al. (2012)) are deposited to frost flowers through less predictable processes that probably involve the atmosphere as a source. The present and future concentrations of these constituents in frost flowers may not be easily incorporated into future sea ice or lower atmospheric chemistry scenarios. Thinning of Arctic sea ice will likely present more open sea ice leads where young ice, brine, and frost flowers form. How these changing ice conditions will affect the interactions between ice, brine, frost flowers and the lower atmosphere is unknown.

  8. 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

  9. 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].

  10. 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

  11. Spatial-temporal dynamics of chemical composition of surface snow in East Antarctica along the Progress station-Vostok station transect

    NASA Astrophysics Data System (ADS)

    Khodzher, T. V.; Golobokova, L. P.; Osipov, E. Yu.; Shibaev, Yu. A.; Lipenkov, V. Ya.; Osipova, O. P.; Petit, J. R.

    2014-05-01

    In January of 2008, during the 53rd Russian Antarctic Expedition, surface snow samples were taken from 13 shallow (0.7 to 1.5 m depth) snow pits along the first tractor traverse from Progress to Vostok stations, East Antarctica. Sub-surface snow/firn layers are dated from 2.1 to 18 yr. The total length of the coast to inland traverse is more than 1280 km. Here we analysed spatial variability of concentrations of sulphate ions and elements and their fluxes in the snow deposited within the 2006-2008 time interval. Anions were analysed by high-performance liquid chromatography (HPLC), and the determination of selected metals, including Na, K, Mg, Ca and Al, was carried out by mass spectroscopy with atomization by induced coupled plasma (ICP-MS). Surface snow concentration records were examined for trends versus distance inland, elevation, accumulation rate and slope gradient. Na shows a significant positive correlation with accumulation rate, which decreases as distance from the sea and altitude increase. K, Ca and Mg concentrations do not show any significant relationship either with distance inland or with elevation. Maximal concentrations of these elements with a prominent Al peak are revealed in the middle part of the traverse (500-600 km from the coast). Analysis of element correlations and atmospheric circulation patterns allow us to suggest their terrestrial origin (e.g. aluminosilicates carried as a continental dust) from the Antarctic nunatak areas. Sulphate concentrations show no significant relationship with distance inland, elevation, slope gradient and accumulation rate. Non-sea salt secondary sulphate is the most important contribution to the total sulphate budget along the traverse. Sulphate of volcanic origin attributed to the Pinatubo eruption (1991) was revealed in the snow pit at 1276 km (depth 120-130 cm).

  12. "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…

  13. 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.

  14. 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

    NOAA's National Operational Hydrologic Remote Sensing Center (NOHRSC) routinely ingests all of the electronically available, real-time, ground-based, snow data; airborne snow water equivalent data; satellite areal extent of snow cover information; and numerical weather prediction (NWP) model forcings for the coterminous U.S. The NWP model forcings are physically downscaled from their native 13 km2 spatial resolution to a 1 km2 resolution for the CONUS. The downscaled NWP forcings drive an energy-and-mass-balance snow accumulation and ablation model at a 1 km2 spatial resolution and at a 1 hour temporal resolution for the country. The ground-based, airborne, and satellite snow observations are assimilated into the snow model's simulated state variables using a Newtonian nudging technique. The principle advantages of the assimilation technique are: (1) approximate balance is maintained in the snow model, (2) physical processes are easily accommodated in the model, and (3) asynoptic data are incorporated at the appropriate times. The snow model is reinitialized with the assimilated snow observations to generate a variety of snow products that combine to form NOAA's NOHRSC National Snow Analyses (NSA). The NOHRSC NSA incorporate all of the available information necessary and available to produce a "best estimate" of real-time snow cover conditions at 1 km2 spatial resolution and 1 hour temporal resolution for the country. The NOHRSC NSA consist of a variety of daily, operational, products that characterize real-time snowpack conditions including: snow water equivalent, snow depth, surface and internal snowpack temperatures, surface and blowing snow sublimation, and snowmelt for the CONUS. The products are generated and distributed in a variety of formats including: interactive maps, time-series, alphanumeric products (e.g., mean areal snow water equivalent on a hydrologic basin-by-basin basis), text and map discussions, map animations, and quantitative gridded products

  15. 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...

  16. 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...

  17. 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.

  18. Validating the EUMETSAT HSAF Snow Recognition Product over Mountainous Areas of Turkey

    NASA Astrophysics Data System (ADS)

    Surer, S.; Akyurek, Z.; Sorman, A. U.

    2009-12-01

    An algorithm has been running in order to produce real-time snow cover maps from MSG-SEVIRI sensor imagery, covering whole Europe, for more than two years under the framework of EUMETSAT Hydrology-SAF (HSAF) Project. Hydrological processes and climate in the mountainous areas are highly affected by the seasonal snow cover. Due to lack of enough field observations because of the inaccessibility of high mountains, it is convenient to monitor the amount of snow with remote sensing satellite data besides setting up and managing ground weather stations. Developed algorithm is based on a multi-spectral thresholding method which uses visible, shortwave-infrared and near-infrared channels of MSG-SEVIRI. For a single day, 32 successive satellite images which have 15 minutes time interval between each of them are interpreted in order to produce a daily snow cover map. The algorithm uses Nowcasting-SAF (SAFNWC) cloud products in classifying the clouds. In this study 2007-2008 and 2008-2009 snow melting seasons are considered for the validation and evaluation purposes of the HSAF snow recognition product. The validation is performed for the mountainous region in the eastern part of Turkey on a daily basis by using the ground observations from 30 climate stations operated by Turkish State Meteorological Service (TSMS). The snow depth was recorded to the nearest 1 cm and reported in integer form. Besides the validation of snow product with ground data, the utility of the snow product in deriving the snow depletion curves (SDC) is evaluated. Other satellite snow products namely, MODIS 8-day snow cover data (MOD10C2) are also used in deriving the snow depletion curves. Results show high agreement between ground snow measurements and HSAF snow recognition product. The overall accuracies for 2008 and 2009 are calculated as 90.96 % and 80.59 % respectively. The commission error for 2008 is 8.12 % whereas for 2009 it is calculated as 17.03 %. The high cloud coverage percentage

  19. 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).

  20. Retrieval of Secchi disk depth in the Yellow Sea and East China Sea using 8-day MODIS data

    NASA Astrophysics Data System (ADS)

    Yu, D. F.; Xing, Q. G.; Lou, M. J.; Shi, P.

    2014-03-01

    Secchi disk depth (SDD), is widely used as an indicator of water clarity. The traditional sampling method is not only time-consuming and labor-intensive but also limited in terms of temporal and spatial coverage. Remote sensing technology may deal with these limitations. In this paper, the applicability of 8-day MODIS-Aqua remote sensing reflectance data with 4 km spatial resolution for estimating water clarity in the Yellow Sea and the East China Sea was investigated. Field data such as Secchi depths were collected from two cruises conducted in the Yellow Sea and the East China Sea from 5 May to 7 June 2009. A three-band algorithm to retrieve SDD was developed based on remote sensing reflectance at bands of 488, 555, and 678 nm, which performed better than single-band model and band ratio algorithm, with a determination coefficient of 0.72 and a mean relative error of 19%. This suggests that 8-day MODIS-Aqua products of remote sensing reflectance could be used to assess water transparency in the study area.

  1. 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…

  2. 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).

  3. Effect of Sodium Phosphate Supplementation on Cycling Time Trial Performance and VO2 1 and 8 Days Post Loading

    PubMed Central

    Brewer, Cameron P.; Dawson, Brian; Wallman, Karen E.; Guelfi, Kym J.

    2014-01-01

    This study examined the effect of 6 days of sodium phosphate (SP) (50 mg·kg·FFM-1·day-1) or placebo (PL) supplementation in trained cyclists on either 100 kJ (23.9 Kcal) (~3-4 min) or 250 kJ (59.7 Kcal) (~10-12 min) time trials performances both 1 and 8 days post-supplementation. Trials were performed in a counterbalanced crossover design, with a 28-day washout period between supplementation phases. No significant differences, moderate-large ES (d) or likely (or greater) smallest worthwhile change (SWC) values were recorded for time to completion and mean power output on days 1 and 8 post-supplementation, both within and between SP and PL for either the 100 or 250 kJ (23.9 or 59.7 Kcal) trials. In the 100 kJ (23.9 Kcal) trial (only) first minute VO2 tended to be higher in SP8 than both PL8 (d = 0.60; 88/10/2 SWC) and SP1 (d = 0.47: 82/15/3 SWC), as was mean VO2 (PL8: d = 0.77; 93/6/1 SWC and SP1: d = 0.84; 90/8/3 SWC). No significant differences were found for heart rate, ratings of perceived exertion and blood lactate post-exercise within or between any trials, while serum phosphate values were not different before or after supplementation with SP or PL. In conclusion, this study showed a tendency for increased VO2 in a short duration (100 kJ/ 23.9 Kcal: ~3-4 min) cycling test on day 8 after SP supplementation, but no differences in 100 or 250 kJ (23.9 or 59.7 Kcal) time trials performances were observed. Key Points Studies investigating the effects of sodium phosphate loading on shorter duration (<15 min) and higher intensity exercise performance are lacking, as is research on how long any ergogenic effect may last. Loading did not improve cycling time trial (~3-4 min and 10-12 min) performance either 1 or 8 days after supplementation. Future studies should investigate the effect of sodium phosphate loading on repeated sprints and simulated cycling road race performance over extended durations (>30 min), where it may be likely to have a more beneficial effect

  4. Air-snow exchange of nitrate: a modelling approach to investigate physicochemical processes in surface snow at Dome C, Antarctica

    NASA Astrophysics Data System (ADS)

    Bock, Josué; Savarino, Joël; Picard, Ghislain

    2016-04-01

    Snowpack is a multiphase (photo)chemical reactor that strongly influences the air composition in polar and snow-covered regions. Snowpack plays a special role in the nitrogen cycle, as it has been shown that nitrate undergoes numerous recycling stages (including photolysis) in the snow before being permanently buried in the firn. However, the current understanding of these physicochemical processes remains very poor. Several modelling studies have attempted to reproduce (photo)chemical reactions inside snow grains, but these required strong assumptions to characterise snow reactive properties, which are not well defined. Physical processes such as adsorption, solid state diffusion and co-condensation also affect snow chemical composition. We developed a model including a physically based parameterisation of these air-snow exchange processes for nitrate. This modelling study divides into two distinct parts: firstly, surface concentration of nitrate adsorbed onto snow is calculated using existing isotherm parametrisation. Secondly, bulk concentration of nitrate in solid solution into the ice matrix is modelled. In this second approach, solid state diffusion drives the evolution of nitrate concentration inside a layered spherical snow grain. A physically-based parameterisation defining the concentration at the air-snow interface was developed to account for the the co-condensation process. The model uses as input a one-year long time series of atmospheric nitrate concentration measured at Dome C, Antarctica. The modelled nitrate concentration in surface snow is compared to field measurements. We show that on the one hand, the adsorption of nitric acid on the surface of the snow grains fails to fit the observed variations. During winter and spring, the modelled adsorbed concentration of nitrate is 2.5 and 8.3-fold higher than the measured one, respectively. A strong diurnal variation driven by the temperature cycle and a peak occurring in early spring are two other

  5. Live birth following early follicular phase oocyte collection and vitrified-warmed embryo transfer 8 days later.

    PubMed

    Hatırnaz, Safak; Hatırnaz, Ebru; Ata, Baris

    2015-12-01

    A 30-year-old woman with premature ovarian insufficiency had two follicles measuring 17 mm and 14 mm on day 3 of her menstrual cycle. Serum oestradiol concentration was 210 pg/ml. Recombinant human chorionic gonadotrophin was given and 5 mg/day letrozole started orally. One metaphase II oocyte was collected 36 h later. A 4-cell embryo was vitrified on the second day after fertilization. Letrozole was stopped on cycle day 8 due to absence of any other visible antral follicles. Oestradiol valerate 6 mg/day was started and the endometrium was 9.2 mm on cycle day 11. The embryo was warmed and transferred on cycle day 13, the 8th day after oocyte retrieval. Luteal phase support with progesterone, oestradiol and low molecular weight heparin was started on the day of transfer and continued until the 10th gestational week. A healthy girl weighing 3200 g was born at term. Early follicular phase oocyte collection did not result in early opening of the implantation window. Apparently secretory transformation was not started until luteal phase support, enabling a cleavage stage embryo transferred 8 days later to implant. Either corpus luteum formation could be disrupted or the endometrium could remain unresponsive to progesterone during the early follicular phase. PMID:26507278

  6. Snow cover monitoring in the Kyrgyz Republic through MODIS time series (2000-2010)

    NASA Astrophysics Data System (ADS)

    Dedieu, J.-P.; Doutreleau, V.; Lessard-Fontaine, A.; Shalpykova, G.

    2012-04-01

    The Kyrgyz Republic is located at the convergence of two mountain systems (Tien Shan and Pamirs) in Central Asia. The region is of great interest all of Central Asia because of its consequent capital in water resources. Theses resources are of importance for electricity production (~15 TWH/year) and irrigation of agricultural land. Over 50% of the 52 km3 of Kyrgyz runoff water irrigates the Syr Darya River which flows over 2200 km from the confluence of Naryn and Kara Darya rivers to the Aral Sea. Around 40% of the Kyrgyz territory lies above 3000m; part of the water resource is cumulated as snow during large periods of the year. Snow cover is thus an important part of the Kyrgyz hydrological cycle. In this already water-stressed region, both climate change and irrigation expansion could trigger a greater scarcity of the resource in the future. One of the major impact could be a modification of the melting season period and the snow melt behavior. The use of passive optical remote sensing data could provide helpful complementary information for hydrological modeling of these effects, but currently, very few scientific publications concerning the Syr Darya headwaters in Kyrgyztan exist. Integrated in the EU-FP7 ACQWA Project (www.acqwa.ch), this study proposes 11 years of snow cover analysis using MODIS snow cover product data. The following parameters are retrieved from MODIS data: Snow Cover Area (SCA), Snow Fraction (FRA), snow cover duration and depletion maps. A Digital Elevation Model (DEM) from the NASA-SRTM database is used to better understand the topographic influence on snow melt behavior and a Land Use database (GlobCover 2009) for the environmental context of snow cover evolution. A statistical analysis of snow cover dynamics is performed on a 2000-2010 8-days temporal resolution dataset. Yearly mean snow cover is 40 ± 5 % and melting runs with 5%.8j-1 average velocity. We observe a greater variation of the inter-annual snow cover extent in winter

  7. Can we model snow photochemistry? Problems with the current approaches.

    PubMed

    Domine, Florent; Bock, Josué; Voisin, Didier; Donaldson, D J

    2013-06-13

    Snow is a very active photochemical reactor that considerably affects the composition and chemistry of the lower troposphere in polar regions. Snow photochemistry models have therefore been recently developed to describe these processes. In all those models, the chemically active medium is a brine formed at the surface of snow crystals by impurities whose presence cause surface melting. Reaction and photolysis rate coefficients are those measured in dilute liquid solutions. Here, we critically examine the basis for these models by considering the structure of ice crystal surfaces, the processes involved in the interactions between impurities and ice crystals, the location of impurities in snow, and the reactivity of impurities in the various media present in snow. We conclude that the brine formed by impurities can only be present in grooves at grain boundaries and cannot cover ice crystal surfaces because of insufficient ice wettability. It is then very likely that most reactions in snow do not take place in liquids, but rather either on an actual ice surface highly different from a liquid or in particulate matter contained in snow, such as organic particles that are thought to contain most snow chromophores. We discuss why some snow models appear to adequately reproduce some observations, concluding that they are insufficiently constrained and that the use of adjustable parameters allows acceptable fits. We discuss the complexity of developing a snow model without adjustable parameters and with a predictive value. We conclude that reaching this goal in the near future is a tremendous challenge. Modeling attempts focused on snow where the impact of organic particles is minimal, such as on the east Antarctic plateau, represents the best chance of midterm success. PMID:23597185

  8. 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.

  9. 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...

  10. Spatial distribution of stable water isotopes in alpine snow cover

    NASA Astrophysics Data System (ADS)

    Dietermann, N.; Weiler, M.

    2013-07-01

    The aim of this study was to analyse and predict the mean stable water isotopic composition of the snow cover at specific geographic locations and altitudes. In addition, the dependence of the isotopic composition of the entire snow cover on altitude was analysed. Snow in four Swiss catchments was sampled at the end of the accumulation period in April 2010 and a second time during snowmelt in May 2010 and analysed for stable isotope composition of 2H and 18O. The sampling was conducted at both south-facing and north-facing slopes at elevation differences of 100 m, for a total altitude difference of approximately 1000 m. The observed variability of isotopic composition of the snow cover was analysed with stepwise multiple linear regression models. The analysis indicated that there is only a limited altitude effect on the isotopic composition when considering all samples. This is due to the high variability of the isotopic composition of the precipitation during the winter months and, in particular in the case of south-facing slopes, an enrichment of heavy isotopes due to intermittent melting processes. This enrichment effect could clearly be observed in the samples which were taken later in the year. A small altitudinal gradient of the isotopic composition could only be observed at some north-facing slopes. However, the dependence of snow depth and the day of the year were significant predictor variables in all models. This study indicates the necessity to further study the variability of water isotopes in the snow cover to increase prediction for isotopic composition of snowmelt and hence increase model performance of residence time models for alpine areas in order to better understand the accumulation processes and the sources of water in the snow cover of high mountains.

  11. Spatial distribution of stable water isotopes in alpine snow cover

    NASA Astrophysics Data System (ADS)

    Dietermann, N.; Weiler, M.

    2013-03-01

    The aim of this study was to analyze and predict the mean stable water isotopic composition of the snow cover at specific geographic locations and altitudes. In addition, the dependence of the isotopic composition of the entire snow cover on altitude was analyzed. Snow in four Swiss catchments was sampled at the end of the accumulation period in April 2010 and a second time in Mai 2010 and analyzed for stable isotope composition of 2H and 18O. The sampling was conducted at both south-facing and north-facing slopes at elevation differences of 100 m for a total altitude difference of approximately 1000 m. The observed variability of isotopic composition of the snow cover was analyzed with stepwise multiple linear regression models. The analysis indicated that there is only a limited altitude effect on the isotopic composition when considering all samples. This is due to the high variability of the isotopic composition of the precipitation during the winter months and, in particular in the case of south-facing slopes, an enrichment of heavy isotopes due to intermittent melting processes. This enrichment effect could clearly be observed in the samples which were taken later in the year. A small altitudinal gradient of the isotopic composition could only be observed at some north-facing slopes. However, the dependence of snow depth and the day of the year were significant predictor variables in all models. This study indicates the necessity to further study the variability of water isotopes in the snow cover to increase prediction for isotopic composition of snowmelt and hence increase model performance of residence time models in alpine areas and to better understand the accumulation processes and the sources of water in the snow cover of high mountains.

  12. 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.

  13. 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.

  14. Assessing Landscape Connectivity and River Water Quality Changes Using an 8-Day, 30-Meter Land Cover Dataset

    NASA Astrophysics Data System (ADS)

    Kamarinas, I.; Julian, J.; Owsley, B.; de Beurs, K.; Hughes, A.

    2014-12-01

    Water quality is dictated by interactions among geomorphic processes, vegetation characteristics, weather patterns, and anthropogenic land uses over multiple spatio-temporal scales. In order to understand how changes in climate and land use impact river water quality, a suite of data with high temporal resolution over a long period is needed. Further, all of this data must be analyzed with respect to connectivity to the river, thus requiring high spatial resolution data. Here, we present how changes in climate and land use over the past 25 years have affected water quality in the 268 sq. km Hoteo River catchment in New Zealand. Hydro-climatic data included daily solar radiation, temperature, soil moisture, rainfall, drought indices, and runoff at 5-km resolution. Land cover changes were measured every 8 days at 30-m resolution by fusing Landsat and MODIS satellite imagery. Water quality was assessed using 15-min turbidity (2011-2014) and monthly data for a suite of variables (1990-2014). Watershed connectivity was modeled using a corrected 15-m DEM and a high-resolution drainage network. Our analyses revealed that this catchment experiences cyclical droughts which, when combined with intense land uses such as livestock grazing and plantation forest harvesting, leaves many areas in the catchment disturbed (i.e. exposed soil) that are connected to the river through surface runoff. As a result, flow-normalized turbidity was elevated during droughts and remained relatively low during wet periods. For example, disturbed land area decreased from 9% to 4% over 2009-2013, which was a relatively wet period. During the extreme drought of 2013, disturbed area increased to 6% in less than a year due mainly to slow pasture recovery after heavy stocking rates. The relationships found in this study demonstrate that high spatiotemporal resolution land cover datasets are very important to understanding the interactions between landscape and climate, and how these interactions

  15. Evidence For And Against 8-day Planetary Waves In Ground-based Cloud-tracking Observations Of Venus' Nightside

    NASA Astrophysics Data System (ADS)

    Young, Eliot F.; Bullock, M. A.; Limaye, S.; Bailey, J.; Tsang, C. C. C.

    2010-10-01

    Several groups have estimated wind fields on Venus by tracking clouds that appear as silhouettes on Venus’ nightside in CO2 windows at 1.74 or 2.3 microns. In 2008, we presented 10 days of cloud-tracking results from July 2004 that suggested the presence of an 8-day wave manifested by velocity variations in clouds presumed to be at altitudes of 48 - 55 km. A variety of waves are key predictions of recent Venus GCMs (e.g., Yamamoto and Takahashi 2006, Lebonnois et al. 2010) and important areas of comparison between observations and modeling efforts. Although we have measured equatorial zonal wind velocity variations of 15 m/s for observations separated by 24 hours, Hueso, Peralta and Sanchez-Lavega (2010) presented cloud-tracking results from VIRTIS-M image sequences in which velocities are mostly confined to 55 to 65 m/s in the 30°S - 10°S latitude range. We now present cloud-tracking results from ground-based observations obtained during July and September 2007. On some dates we are able to combine observations between the AAT and IRTF to increase the time baseline between images to roughly 4 hours and reduce the errors by about a factor of two. Akatsuki image sequences should resolve the question of zonal velocity variations in the near future. --- References Hueso, Peralta and Sanchez-Lavega, 2010, "Temporal and spatial variability of Venus winds at cloud level from VIRTIS during the Venus Express mission.” Presented at the Venus Express Workshop in Aussois, June 2010. Lebonnois et al., 2010, "Superrotation of Venus’ atmosphere analyzed with a full general circulation model.” JGR 115, E06006. Yamamoto and Takahashi, 2006, "Superrotation maintained by meridional circulation and waves in a Venus-like AGCM.” J. Amtos Sci., 63, 3296.

  16. Landsat-ABI (L-ABI) Enables 8-day Revisits and Increased Science Content with a Single Instrument

    NASA Astrophysics Data System (ADS)

    Woody, L. M.; Griffith, P. C.; Wirth, S. M.

    2014-12-01

    In addition to the on-going uses of Landsat data for land use and land cover change assessment, crop monitoring, ecosystem evaluation, and water use mapping, the increasing number of severe environmental events (storms, droughts, floods, and fires) has intensified the demand for land imaging data. Users desire more data and, more importantly, more frequent data to better understand the trends and impacts of these extreme events. Additionally, the Sustainable Land Imaging (SLI) thrust faces the difficult task of providing continuity of measurements in a strict budget-constrained environment. To that end, the desire is to reduce the size, mass, and - most importantly - cost of future US land imaging capability, without impacting the continuity of the SLI data with past Landsat archives. During our exploration of possible alternatives for future Landsat missions, we re-opened the trade space to include scanned options. The Advanced Baseline Imager (ABI) has been delivered to NASA/NOAA for flight on GOES-R, and additional models are in fabrication for various customers. Adapting this in-production instrument to flight at low-Earth orbit is relatively straightforward, and leads to a simple, high-heritage (low-risk) concept for a full-spectrum Landsat instrument that would meet virtually all of the Landsat 8 Reference Performance Parameters at significantly lower cost than the Landsat-8 (LDCM) payload. It would also be smaller than the L-8 payload, about half the mass, and require lower power. In addition, it could offer the option for spectral enhancement of Landsat through additional LWIR and/or MWIR bands. Finally, the L-ABI can offer larger swath coverage, driving the SLI system towards the desired 8-day repeat coverage.

  17. 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...

  18. 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...

  19. 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

  20. '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.

  1. Remote Sensing of Snow in the Cariboo Mountains of British Columbia, Canada

    NASA Astrophysics Data System (ADS)

    Tong, Jinjun; Dery, Stephen; Jackson, Peter; Derksen, Chris

    2010-05-01

    This presentation will review some recent work examining the validation and application of remote sensing snow products in the Cariboo Mountains of British Columbia, Canada. Various remote sensing products are utilized to investigate snow distribution, duration and accumulation in the region. We will first introduce Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day maximum snow cover extent products (MOD10A2) from 2000-2007 that are filtered to reduce cloud coverage and evaluated with ground-based snow measurements. The resulting data are used to monitor snow cover duration (SCD) and snow cover fraction (SCF) in the Cariboo Mountains where elevations range from about 500 m to 3000 m above sea level. Elevation, slope, and aspect greatly influence the distribution and duration of snow cover in the watershed. For instance, the gradient of SCF with elevation (d(SCF)/dz) during the snowmelt season is 8% (100 m)-1. The average ablation rates of SCF are similar for different 100 m elevation bands at about 5.5% (8 days)-1 for altitudes < 1500 m with decreasing values with elevation to near 0% (8 days)-1 for altitudes > 2500 m where perennial snow and glaciers dominate the landscape. We will then discuss brightness temperatures (TB) from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Scanning Radiometer (AMSR-E) from 2003-2007 that are utilized to retrieve and evaluate the snow water equivalent (SWE) over the Cariboo Mountains. Various algorithms including the Environment Canada (EC) algorithms, the spectral polarization difference and an artificial neural network for both SSM/I and AMSR-E are evaluated against in-situ SWE observations by several statistical metrics. The results show that the EC algorithms developed specifically for the southern prairies and boreal forest of Canada perform poorly across the complex topography and generally deep snowpack of the region. For other frequency combinations of SSM/I and AMSR-E measurements

  2. Features of Terra MOD11A2DAY in Operational Forecastof Grain Crops Yield in Kazakhstan with AN 8 Day Renewal

    NASA Astrophysics Data System (ADS)

    Terekhov, A.

    2011-08-01

    The Kazakhstan, with export capacity of 6-8 million tons, is one of the largest wheat exporter in the world. About 16 million hectares of unirrigated land is used for monocultural cultivation of cereals (wheat and barley). Most of the cropland is located in the steppe and forest steppe zone. The moisture deficit limits the crop productivity and creates a strong dependency of its state of the moisture conditions during vegetation season. In Kazakhstan, the average grain yield variations are sufficiently large, from 0.9 (2010) to 1.4 tonha (2007). Given the high volatility of the gross grain harvest and export potential, respectively, methods of early satellite forecast of grain yield with high frequency of the renewal are of the great interest. In Kazakhstan, the variations in the weather growing season determine the yield of grain crops. By significant weather parameters include: the spring soil moisture, humidity and air temperature, rainfall, and several others. Plants respond to the sum of all parameters through the volume of green biomass. The regional cereal state can be estimated from satellite vegetation indices, which are particularly informative in the period of its seasonal peak. Another satellite parameter closely related to humidity conditions may be the land surface temperature (LST). Product USGS: TERRA MOD11A2DAY represents the 8-days LST composite was tested in the task of estimating of arable lands temperature in Northern Kazakhstan. The description of the temperature conditions of the growing season based on the temperature calibrated index (TCI), which was introduced by Kogan. TCI provides a weighted assessment of the current LST on a scale of 0-100, where 0 - the lowest, respectively, 100 as a high temperature, recorded during the observation period at a given location at a given time window. The monitoring period included 2004-2010 years. During the beginning of the growing season was taken on April 15, season end on 20 August - ripeness stage

  3. 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.

  4. '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.

  5. 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

  6. 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.

  7. 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+).

  8. 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.

  9. '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.

  10. 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.

  11. 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

  12. 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.

  13. Desert dust deposition on Mt. Elbrus, Caucasus Mountains, Russia in 2009-2012 as recorded in snow and shallow ice core: high-resolution "provenancing", transport patterns, physical properties and soluble ionic composition

    NASA Astrophysics Data System (ADS)

    Kutuzov, S.; Shahgedanova, M.; Mikhalenko, V.; Lavrentiev, I.; Kemp, S.

    2013-04-01

    A record of dust deposition events between 2009 and 2012 on Mt. Elbrus, Caucasus Mountains derived from a snow pit and a shallow ice core is presented for the first time for this region. A combination of isotopic analysis, SEVIRI red-green-blue composite imagery, MODIS atmospheric optical depth fields derived using the Deep Blue algorithm, air mass trajectories derived using the HYSPLIT model and analysis of meteorological data enabled identification of dust source regions with high temporal (hours) and spatial (cf. 20-100 km) resolution. Seventeen dust deposition events were detected; fourteen occurred in March-June, one in February and two in October. Four events originated in the Sahara, predominantly in north-eastern Libya and eastern Algeria. Thirteen events originated in the Middle East, in the Syrian Desert and northern Mesopotamia, from a mixture of natural and anthropogenic sources. Dust transportation from Sahara was associated with vigorous Saharan depressions, strong surface winds in the source region and mid-tropospheric south-westerly flow with daily winds speeds of 20-30 m s-1 at 700 hPa level and, although these events were less frequent, they resulted in higher dust concentrations in snow. Dust transportation from the Middle East was associated with weaker depressions forming over the source region, high pressure centered over or extending towards the Caspian Sea and a weaker southerly or south-easterly flow towards the Caucasus Mountains with daily wind speeds of 12-18 m s-1 at 700 hPa level. Higher concentrations of nitrates and ammonium characterise dust from the Middle East deposited on Mt. Elbrus in 2009 indicating contribution of anthropogenic sources. The modal values of particle size distributions ranged between 1.98 μm and 4.16 μm. Most samples were characterised by modal values of 2.0-2.8 μm with an average of 2.6 μm and there was no significant difference between dust from the Sahara and the Middle East.

  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. 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.

  18. The Fe snow regime in Ganymede's core: A deep-seated dynamo below a stable snow zone

    NASA Astrophysics Data System (ADS)

    Rückriemen, T.; Breuer, D.; Spohn, T.

    2015-06-01

    Ganymede shows signs of a present-day magnetic field, whose origin is thought to be in its core. The Fe snow regime has been suggested to be vital in Ganymede's history. In this regime, Fe crystals first form at the core-mantle boundary and later settle to the deeper core due to their higher density (Fe snow). A stable chemical gradient arises within the liquid of the snow zone. Below the snow zone the Fe particles remelt. We propose that the remelting of Fe in the deeper, entirely liquid core initiates compositional convection, which could be the origin of the dynamo. Such a dynamo is restricted by the period of time the snow zone needs to grow across the core. We investigate this time period with a 1-D core evolution model by varying the initial sulfur concentration, the core heat flux, and the thermal conductivity of the core. For the proposed dynamo in the deeper liquid core, we obtain necessary time periods of between 320 and 800 Myr and magnetic field strengths at the surface that match the observed value of 719 nT. To explain the present magnetic field, we favor cores with high sulfur concentrations because those lead to a late start and a long duration of the dynamo. Furthermore, a present dynamo below the snow zone suggests the absence of an inner core.

  19. 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

  20. 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 ...

  1. 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

  2. Ice nucleation: elemental identification of particles in snow crystals.

    PubMed

    Parungo, F P; Pueschel, R F

    1973-06-01

    A scanning field-emission electron microscope combined with an x-ray analyzer is used to locate the ice nucleus within a three-dimensional image of a snow crystal and determine the chemical composition of the nucleus. This makes it possible to better understand the effect of nuclei in cloud seeding. PMID:17806581

  3. 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)

  4. 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.

  5. 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.

  6. 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.

  7. Relating Snow Transport to Ecosystem Structure and Function: Lessons from Libby Flats

    NASA Astrophysics Data System (ADS)

    Hiemstra, C. A.; Reiners, W. A.

    2003-12-01

    The effects of variable snow cover on ecosystem structure and function have been well-documented in cold, temperate ecosystems, especially in high-elevation treeline and alpine landscapes where long, windy winters can produce dramatic variations in snow depths over short distances. Additionally, wind directions, snowfall, and resultant snow-distribution patterns are essentially the same year after year, allowing for relatively steady state environmental conditions and ecosystem properties. These chronic and heterogeneous snow-cover patterns have been associated with ecosystem structure (e.g., plant species distributions, soil characteristics) and function (e.g., decomposition, primary production, nutrient cycling, water balance) in systems where winters are long and most precipitation falls as snow. We sought to determine the impacts of a heterogeneous snow distribution on ecosystem properties in a 6.25 km2 upper-treeline ecotone, called Libby Flats, in south-central Wyoming. This involved modeling and validating snow accumulation, ablation, and meltwater flow spatially coupled with observations of snow depth and density, soil moisture, soil temperature, plant species composition and cover, biomass, gross decomposition, and gopher activity. Model simulations successfully represented the general spatial patterns of snow redistribution and ablation, but field measurements pointed the way for model improvements. Dominant cover types varied with snow depth, meltwater flow, and soil temperature. Decomposition rates changed with soil moisture, soil temperature, snow depth, and length of time covered by snow. Gopher activity was inversely related to soil moisture and positively related to soil depth, soil temperature, snow water equivalent, and graminoid biomass. The role of snow in this landscape is best understood as a function of transport. Transport of snow and snow meltwater play distinctive roles in the spatial patterns of cover within the Libby Flats landscape

  8. Evaluation of Snow Cover Depletion to Support Snowmelt Runoff Prediction for the Cache la Poudre River, Colorado

    NASA Astrophysics Data System (ADS)

    Richer, E. E.; Kampf, S. K.; Fassnacht, S. R.

    2008-12-01

    The Cache la Poudre River in northeastern Colorado is a source of water for many agricultural, municipal, and industrial users. Most runoff in the basin is generated from snowmelt, but snow measurements are sparse, located only at a few high elevation SNOTEL stations and snow courses. Over much of the watershed, no snow measurements are available to support runoff forecasts. For this study we analyzed snow covered area (SCA) depletion characteristics to evaluate whether SCA data could improve snowmelt runoff prediction. Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day snow-cover products were obtained for the Cache la Poudre basin from 2000 to 2006 for March through June of each year. We analyzed snow cover depletion characteristics for spatial subsets of the basin, including sub-basins and elevation bands. Regression analyses compare the 8-day SCA images to 8-day average stream flow at the USGS canyon mouth gauge (the forecasting location). Results from regression analyses show a wide range of relationships between SCA and streamflow (0.032<0.92), mostly as a result of high inter- annual variability in the flow regime. SCA image impairment from cloud cover was generally low but did impact results in some years. For sub-basins, the strongest correlations between SCA and streamflow were for high elevation sub-basins (0.602<0.92), whereas for elevation bands, the strongest correlations were for a mid-elevation band, 2680-3042 m (0.602<0.92). The poorest relationships between SCA and streamflow occurred for low elevation bands, 1591-1953 m and 1954-2315 m, and very high elevation bands, 3406-3768 m and 3769-4131 m. The strong relationship between SCA and discharge at middle elevations suggests that runoff prediction can be improved by monitoring snow cover within these areas. The initial rise in the snowmelt hydrograph correlates well with SCA depletion at middle elevations, whereas the onset of peak flow does not occur until a significant change in snow

  9. 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

    data from BBMB (Bhakra Beas Management Board) and coefficient of Correlation(R2) measured for (2003-2006) was 0.67 and 0.61 for the year 2006.But as VIC does not consider snowmelt runoff as a part of the total discharge, snowmelt runoff has been estimated for the simulation both with and without D.A. The snow fluxes as generated from VIC gives basin average estimates of Snow Cover, SWE, Snow Depth and Snow melt. It has been observed to be overestimated when model predicted snow cover is compared with MODIS SCA of 500 m resolution from MOD10A2 for each year. So MODIS 8-day snow cover area has been assimilated directly into the model state as well as by using EnKF after every 8 days for the year 2006.D.I Technique performed well as compared to EnKF. R2 between Model SCA and MODIS SCA is estimated as 0.73 after D.I with Root Mean Square Error (RMSE) of +0.19. After direct Insertion of D.A, SCA has been reduced comparatively which resulted in 7% reduction of annual snowmelt contribution to total discharge.The assimilation of MODIS SCA data hence improved the snow cover area (SCA) fraction and finally updated other snow components.

  10. A multipoint (49 points) study of dry deposition of polycyclic aromatic hydrocarbons (PAHs) in Erzurum, Turkey by using surrogated snow surface samplers.

    PubMed

    Bayraktar, Hanefi; Paloluoğlu, Cihan; Turalioğlu, Fatma S; Gaga, Eftade O

    2016-06-01

    Dry deposition of atmospheric 18 polycyclic aromatic hydrocarbon (PAH) components was investigated in the scope of the study by using surrogate snow samplers at 49 different sampling points in and around the city center of Erzurum, Turkey. Snow was sampled twice, the first of which was taken immediately after the first fresh snow cover and placed into aluminum trays to obtain dry deposition surface while the second sample was taken from the snow cover (accumulated snow) exposed to an 8-day dry deposition period and then analyzed and extracted. All the samples taken from the samplers were extracted using solid and liquid phase extraction and analyzed through GC-MS. It was observed that at the end of an 8-day dry period, snow samples enriched 5.5 times more in PAH components than the baseline. PAH deposition was determined to be influenced mainly by coal, mixed source, traffic, diesel fuel, and petrol fuel at 43, 27, 20, 8, and 2 % of sampling points, respectively. Local polluting sources were found to be effective on the spatial distribution of dry deposition of PAH components in urban area. PMID:26983812

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. Autumn diet of lesser snow geese staging in northeastern Alaska

    USGS Publications Warehouse

    Brackney, Alan W.; Hupp, J.W.

    1993-01-01

    The coastal plain of the Arctic National Wildlife Refuge (ANWR) is used by lesser snow geese (Chen caerulescens caerulescens) in autumn for premigratory staging. To better understand the potential impacts of human disturbance on snow geese, we investigated species composition of, and temporal and age-related variation in, their diet during staging. Depending on age and time of collection, between 35.2 and 94.1% of the diet (aggregate percent wet mass, n = 75) consisted of 2 species of plants; underground stems of tall cotton-grass (Eriophorum angustifolium), and aerial shoots of northern scouring rush (Equisetum variegatum). The diet varied between August and September (P = 0.0089), morning and afternoon (P < 0.0001), but not between age classes (P = 0.066). Throughout staging, snow geese consumed more tall cotton-grass during the afternoon than during the morning (P < 0.05). Tall cotton-grass was a larger component of the afternoon diet in September than in August (P < 0.05). In September, snow geese consumed more northern scouring rush in the mornings than in the afternoon (P < 0.05). Nighttime freezing, interspecific differences in nutritional quality, and plant senescence likely constrained the diet of snow geese to a small number of food items. Because alternative foods may not be available, human disturbance should be minimized in areas that provide these forage species.

  16. Snow Micro-Structure Model

    2014-06-25

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

  17. 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.

  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. Analysis of nitrate in the snow and atmosphere at Summit, Greenland: Chemistry and transport

    NASA Astrophysics Data System (ADS)

    Fibiger, Dorothy L.; Dibb, Jack E.; Chen, Dexian; Thomas, Jennie L.; Burkhart, John F.; Huey, L. Gregory; Hastings, Meredith G.

    2016-05-01

    As a major sink of atmospheric nitrogen oxides (NOx = NO + NO2), nitrate (NO3-) in polar snow can reflect the long-range transport of NOx and related species (e.g., peroxyacetyl nitrate). On the other hand, because NO3- in snow can be photolyzed, potentially producing gas phase NOx locally, NO3- in snow (and thus, ice) may reflect local processes. Here we investigate the relationship between local atmospheric composition at Summit, Greenland (72°35'N, 38°25'W) and the isotopic composition of NO3- to determine the degree to which local processes influence atmospheric and snow NO3-. Based on snow and atmospheric observations during May-June 2010 and 2011, we find no connection between the local atmospheric concentrations of a suite of gases (BrO, NO, NOy, HNO3, and nitrite (NO2-)) and the NO3- isotopic composition or concentration in snow. This suggests that (1) the snow NO3- at Summit is primarily derived from long-range transport and (2) this NO3- is largely preserved in the snow. Additionally, three isotopically distinct NO3- sources were found to be contributing to the NO3- in the snow at Summit during both 2010 and 2011. Through the complete isotopic composition of NO3-, we suggest that these sources are local anthropogenic particulate NO3- from station activities (δ15N = 16‰, Δ17O = 4‰, and δ18O = 23‰), NO3- formed from midlatitude NOx (δ15N = -10‰, Δ17O = 29‰, δ18O = 78‰) and a NO3- source that is possibly influenced by or derived from stratospheric ozone NO3- (δ15N = 5‰, Δ17O = 39‰, δ18O = 100‰).

  1. 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

  2. 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.

  3. Integrated 'Omics', Targeted Metabolite and Single-cell Analyses of Arctic Snow Algae Functionality and Adaptability.

    PubMed

    Lutz, Stefanie; Anesio, Alexandre M; Field, Katie; Benning, Liane G

    2015-01-01

    Snow algae are poly-extremophilic microalgae and important primary colonizers and producers on glaciers and snow fields. Depending on their pigmentation they cause green or red mass blooms during the melt season. This decreases surface albedo and thus further enhances snow and ice melting. Although the phenomenon of snow algal blooms has been known for a long time, large aspects of their physiology and ecology sill remain cryptic. This study provides the first in-depth and multi-omics investigation of two very striking adjacent green and red snow fields on a glacier in Svalbard. We have assessed the algal community composition of green and red snow including their associated microbiota, i.e., bacteria and archaea, their metabolic profiles (targeted and non-targeted metabolites) on the bulk and single-cell level, and assessed the feedbacks between the algae and their physico-chemical environment including liquid water content, pH, albedo, and nutrient availability. We demonstrate that green and red snow clearly vary in their physico-chemical environment, their microbial community composition and their metabolic profiles. For the algae this likely reflects both different stages of their life cycles and their adaptation strategies. Green snow represents a wet, carbon and nutrient rich environment and is dominated by the algae Microglena sp. with a metabolic profile that is characterized by key metabolites involved in growth and proliferation. In contrast, the dry and nutrient poor red snow habitat is colonized by various Chloromonas species with a high abundance of storage and reserve metabolites likely to face upcoming severe conditions. Combining a multitude of techniques we demonstrate the power of such complementary approaches in elucidating the function and ecology of extremophiles such as green and red snow algal blooms, which play crucial roles in glacial ecosystems. PMID:26635781

  4. 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.

  5. Effects of Easy-to-Use Protein-Rich Energy Bar on Energy Balance, Physical Activity and Performance during 8 Days of Sustained Physical Exertion

    PubMed Central

    Tanskanen, Minna M.; Westerterp, Klaas R.; Uusitalo, Arja L.; Atalay, Mustafa; Häkkinen, Keijo; Kinnunen, Hannu O.; Kyröläinen, Heikki

    2012-01-01

    Background Previous military studies have shown an energy deficit during a strenuous field training course (TC). This study aimed to determine the effects of energy bar supplementation on energy balance, physical activity (PA), physical performance and well-being and to evaluate ad libitum fluid intake during wintertime 8-day strenuous TC. Methods Twenty-six men (age 20±1 yr.) were randomly divided into two groups: The control group (n = 12) had traditional field rations and the experimental (Ebar) group (n = 14) field rations plus energy bars of 4.1 MJ•day−1. Energy (EI) and water intake was recorded. Fat-free mass and water loss were measured with deuterium dilution and elimination, respectively. The energy expenditure was calculated using the intake/balance method and energy availability as (EI/estimated basal metabolic rate). PA was monitored using an accelerometer. Physical performance was measured and questionnaires of upper respiratory tract infections (URTI), hunger and mood state were recorded before, during and after TC. Results Ebar had a higher EI and energy availability than the controls. However, decreases in body mass and fat mass were similar in both groups representing an energy deficit. No differences were observed between the groups in PA, water balance, URTI symptoms and changes in physical performance and fat-free mass. Ebar felt less hunger after TC than the controls and they had improved positive mood state during the latter part of TC while controls did not. Water deficit associated to higher PA. Furthermore, URTI symptoms and negative mood state associated negatively with energy availability and PA. Conclusion An easy-to-use protein-rich energy bars did not prevent energy deficit nor influence PA during an 8-day TC. The high content of protein in the bars might have induced satiation decreasing energy intake from field rations. PA and energy intake seems to be primarily affected by other factors than energy supplementation such

  6. 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.

  7. 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).

  8. 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.

  9. 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...

  10. 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 ...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. Different time and energy budgets of Lesser Snow Geese in rice-prairies and coastal marshes in southwest Louisiana

    USGS Publications Warehouse

    Jonsson, J.E.; Afton, A.D.

    2006-01-01

    Many bird species use human-made habitats and an important issue is whether these are equally suitable foraging habitats as are historical, natural habitats. Historically, Lesser Snow Geese (Chen caerulescens caerulescens, hereafter Snow Geese) wintered in coastal marshes in Louisiana but began using rice-prairies within the last 60 years. Time spent feeding was used as an indicator of habitat suitability and time and energy budgets of Snow Geese were compared between rice-prairies and coastal marshes in southwest Louisiana. Composite diets of Snow Geese have a lower energy density in the rice-prairies than in coastal marshes; thus, we predicted that Snow Geese would spend relatively more time feeding in rice-praires to obtain existence energy. However, time spent feeding was higher in coastal marshes and thus, not proportional to energy density of composite diets. Snow Geese in coastal marshes ingested less apparent metabolizable energy than did Snow Geese in rice-prairies. In rice-prairies, juveniles spent more time feeding than did adults; however, time spent feeding was similar between age classes in coastal marshes. Undeveloped foraging skills probably cause juvenile Snow Geese to forage less efficiently in coastal marshes than in rice-prairies. These findings are consistent with recent trends in Snow Goose numbers, which increased in rice-prairies but remained stable in coastal marshes.

  20. 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.

  1. 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.

  2. Imaging of the CO snow line in a solar nebula analog.

    PubMed

    Qi, Chunhua; Öberg, Karin I; Wilner, David J; D'Alessio, Paola; Bergin, Edwin; Andrews, Sean M; Blake, Geoffrey A; Hogerheijde, Michiel R; van Dishoeck, Ewine F

    2013-08-01

    Planets form in the disks around young stars. Their formation efficiency and composition are intimately linked to the protoplanetary disk locations of "snow lines" of abundant volatiles. We present chemical imaging of the carbon monoxide (CO) snow line in the disk around TW Hya, an analog of the solar nebula, using high spatial and spectral resolution Atacama Large Millimeter/Submillimeter Array observations of diazenylium (N2H(+)), a reactive ion present in large abundance only where CO is frozen out. The N2H(+) emission is distributed in a large ring, with an inner radius that matches CO snow line model predictions. The extracted CO snow line radius of ~30 astronomical units helps to assess models of the formation dynamics of the solar system, when combined with measurements of the bulk composition of planets and comets. PMID:23868917

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. The Arctic seasonal snow pack as a transfer mechanism and a reactor for lower atmosphere chemical compounds (Invited)

    NASA Astrophysics Data System (ADS)

    Douglas, T. A.

    2013-12-01

    The Polar Regions are snow covered for two thirds of the year (or longer) and in many locations there are few melt events during the winter. As a consequence, the late winter snow pack presents a spatial and temporal archive of the previous winter's precipitation, snow-atmosphere exchange, and within snow pack physical and chemical processes. However, to use the snow pack as a 'sensor' we have to understand the physical and chemical exchange processes between atmospheric compounds and snow and ice surfaces. Of equal importance is knowledge of the reactions that occur in and on snow and ice particle surfaces. Recent research has provided insights on the pathways individual compounds take from the lower atmosphere to snow and on the physical and chemical processes occurring within the snow pack at a variety of scales. Snow on or near sea ice has markedly higher major ion concentrations than snow on the terrestrial snow pack, most notably for chloride and bromide. This difference in chemical composition can be dramatic even in coastal regions where the land is only hundreds of meters away. As a consequence, we have to treat chemical cycling processes in/on snow on sea ice and snow on land differently. Since these halogens, particularly bromine, play critical roles in the spring time photochemical reactions that oxidize ozone and mercury their presence and fate on the sea ice snow pack is of particular interest. A future Arctic is expected to have a thinner, more dynamic sea ice cover that will arrive later and melt earlier. The areal extent of young ice production will likely increase markedly. This would lead to a different snow depositional and chemical regime on sea ice with potential ramifications for chemical exchange with the lower atmosphere. The roles of clear sky precipitation ('diamond dust') and surface hoar deposition in providing a unique lower atmospheric 'reactor' and potential source of water equivalence have been largely overlooked. This despite the

  9. Using scale-dependent observational data for snow modelling in a glacierized catchment

    NASA Astrophysics Data System (ADS)

    Engel, Michael; Bertoldi, Giacomo; Endrizzi, Stefano; Notarnicola, Claudia; Niedrist, Georg; Comiti, Francesco

    2014-05-01

    Snow cover distribution and melt are essential to understand and to predict runoff. However, the spatial heterogeneity of snow cover in complex terrain and the limited availability of observational data make distributed modelling of snow covered area (SCA) and of snow water equivalent (SWE) in alpine regions still a challenging task. A promising approach is the application of physically based distributed hydrological models coupled with ground observations and with new satellite products. However, the inherent complexity of advanced models and satellite products requires an accurate evaluation both at plot and at catchment scale before their operational use. In this context we evaluate the capability of the new model GEOtop 2.0 for the first time to simulate snow dynamics at plot and at catchment scale. Our study was performed in the upper Saldur basin (61 km²) in the Eastern Italian Alps during the period 2010 - 2013. At plot scale, simulated snow depths and SWE were calibrated against measured snow depth data from multiple measuring sites at different elevations (at 1930 m, at 1998 m, at 2450 m, and 3035 m a.s.l.) in and close to the Saldur basin. The evaluation was quantified by the statistical indices R² and the Nash-Sutcliffe efficiency. Different model parameterisations were evaluated by a manual sensitivity analysis of 11 key parameters controlling the snowpack and the meteorological input data. Most of these key parameters found to be sensitive for SWE and for snow depth were the ones controlling albedo decreasing and precipitation input. At catchment scale, simulated SCA of the upper Saldur basin was calibrated against the daily composite 250 m EURAC MODIS SCA (Notarnicola et al. 2013) and then validated against Landsat 7 ETM+ SCA (at 30 m resolution). The model evaluation was supported by a pixel-based calculation of overall accuracy (Parajka and Blöschl 2008) of total SCA in the upper Saldur basin. Additionally, the snow presence derived from

  10. Application of Snpp/viirs Data in Near Real-Time Supra-Snow Flood Detection

    NASA Astrophysics Data System (ADS)

    Li, S.; Sun, D.; Goldberg, M.; Sjoberg, B.; Plumb, E. W.; Holloway, E.; Lindsey, S.; Kreller, M.

    2015-12-01

    Supra-snow/ice flood is very common in high latitude areas from winter to spring break-up seasons along rivers flowing to even higher latitude areas, but this flood type doesn't draw much attention due to poor ground conditions for river watch and ground observations. Satellite data from SNPP/VIIRS (Suomi-National Polar-orbit Partnership/Visible/Infrared Imager Radiometer Suite) instead have shown great advantages in supra-snow/ice flood detection due to its large swath coverage, multiple daily observations in high latitude areas and moderate spatial resolution. Thus, methods for supra-snow/ice water detection were developed to detect near real-time supra-snow/ice floods automatically using SNPP/VIIRS imagery. The methods were mainly based on spectral features of supra-snow/ice floodwater, assisting by geometry-based algorithm and object-based algorithm to remove cloud shadows and terrain shadows over snow/ice surface. The detected supra-snow/ice floodwater was further applied in water fraction retrieval for better representation of flood extent using a modified histogram method based on linear combination model. The developed methods were successfully applied in dynamic monitoring of 2015's supra-snow/ice flood along Sag River in Alaska, which was claimed as a state disaster by Alaska state government, and further tested with more than 1000 VIIRS granules year around. Analyses through visual inspection with VIIRS false-color composite images and quantitative comparison with Landsat-8 OLI images show promising and robust performance in detection of supra-snow/ice floodwater, indicating a high feasibility for the method to be applied in operations for near real-time supra-snow/ice flood detection.

  11. 1D Chemical Modeling of coupled snow-atmosphere chemistry at Dome C Antarctica

    NASA Astrophysics Data System (ADS)

    Gil, Jaime E.; Thomas, Jennie; von Glasgow, Roland; Bekki, Slimane; Kukui, Alexandre; Frey, Markus; Jourdain, Bruno; Kerbrat, Michel; Genthon, Christophe; Preuknert, Susanne; Legrand, Michel

    2013-04-01

    High levels of nitrogen oxides NOx (NOx=NO+NO2) generated by the photolysis of nitrate present in surface snow profoundly impact atmospheric composition and oxidizing capacity in the Antarctic boundary layer. In particular, NOx emissions from sunlit snow increase OH values by effectively recycling HO2 to OH. In order to better characterize this chemistry the OPALE campaign was conducted in December 2011/January 2012 at Dome C, Antarctica (altitude of 3,233 meters, 75 ° S, 123 ° E). The campaign included boundary layer profiling, measurements of the physical properties of snow, as well as a comprehensive suite of atmospheric chemistry measurements (including NOx, HONO, OH and RO2, H2O2, CH2O, O3). We present results using the 1-D coupled snow-boundary layer model MISTRA-SNOW in combination with observations made during the measurement campaign to understand this chemistry. The model includes both chemistry at the surface of snow grains (aqueous chemistry), in firn air (gas phase chemistry), and gas/aerosol chemistry in the boundary layer. Model predictions of NOx mixing ratios using a model sensitivity analysis approach are presented. The model was initialized using measured snow properties, including temperature, density, and snow grain size. In addition, the model dynamics are driven using the measured surface temperature at Dome C. To calculate the rate of snowpack ventilation, measured wind speeds during the campaign were used. The model was run varying the amount of nitrate and bromide available for reaction at the surface of snow grains and results are compared to measurements made in the atmospheric boundary from 2-4 January 2012. We test the hypothesis that very low concentrations of bromine may alter the ratio of NO/NO2. We also investigate the influence of NOx emissions from snow, and bromine (if present), on OH concentrations in the boundary layer on the Antarctic plateau.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. [Monitoring on spatial and temporal changes of snow cover in the Heilongjiang Basin based on remote sensing].

    PubMed

    Yu, Ling-Xue; Zhang, Shu-Wen; Guan, Cong; Yan, Feng-Qin; Yang, Chao-Bin; Bu, Kun; Yang, Jiu-Chun; Chang, Li-Ping

    2014-09-01

    This paper extracted and verified the snow cover extent in Heilongjiang Basin from 2003 to 2012 based on MODIS Aqua and Terra data, and the seasonal and interannual variations of snow cover extent were analyzed. The result showed that the double-star composite data reduced the effects of clouds and the overall accuracy was more than 91%, which could meet the research requirements. There existed significant seasonal variation of snow cover extent. The snow cover area was almost zero in July and August while in January it expanded to the maximum, which accounted for more than 80% of the basin. According to the analysis on the interannual variability of snow cover, the maximum winter snow cover areas in 2003-2004 and 2009-2010 (>180 x 10(4) km2) were higher than that of 2011 (150 x 10(4) km2). Meanwhile, there were certain correlations between the interannual fluctuations of snow cover and the changes of average annual temperature and precipitation. The year with the low snow cover was corresponding to less annual rainfall and higher average temperature, and vice versa. The spring snow cover showed a decreasing trend from 2003 to 2012, which was closely linked with decreasing precipitation and increasing temperature. PMID:25757300

  2. Analysis of snow bidirectional reflectance from ARCTAS spring-2008 campaign

    NASA Astrophysics Data System (ADS)

    Lyapustin, A.; Gatebe, C. K.; Kahn, R.; Brandt, R.; Redemann, J.; Russell, P.; King, M. D.; Pedersen, C. A.; Gerland, S.; Poudyal, R.; Marshak, A.; Wang, Y.; Schaaf, C.; Hall, D.; Kokhanovsky, A.

    2009-10-01

    The spring 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) experiment was one of the major intensive field campaigns of the International Polar Year, aimed at detailed characterization of atmospheric physical and chemical processes in the Arctic region. Part of this campaign was a unique snow bidirectional reflectance experiment on the NASA P-3B aircraft conducted on 7 and 15 April by the Cloud Absorption Radiometer (CAR) jointly with airborne Ames Airborne Tracking Sunphotometer (AATS) and ground-based Aerosol Robotic Network (AERONET) sunphotometers. The CAR data were atmospherically corrected to derive snow bidirectional reflectance at high 1° angular resolution in view zenith and azimuthal angles along with surface albedo. The derived albedo was generally in good agreement with ground albedo measurements collected on 15 April. The CAR snow bidirectional reflectance factor (BRF) was used to study the accuracy of analytical Ross-Thick Li-Sparse (RTLS), Modified Rahman-Pinty-Verstraete (MRPV) and Asymptotic Analytical Radiative Transfer (AART) BRF models. Except for the glint region (azimuthal angles φ<40°), the best fit MRPV and RTLS models fit snow BRF to within ±0.05. The plane-parallel radiative transfer (PPRT) solution was also analyzed with the models of spheres, spheroids, randomly oriented fractal crystals, and with a synthetic phase function. The latter merged the model of spheroids for the forward scattering angles with the fractal model in the backscattering direction. The PPRT solution with synthetic phase function provided the best fit to measured BRF in the full range of angles. Regardless of the snow grain shape, the PPRT model significantly over-/underestimated snow BRF in the glint/backscattering regions, respectively, which agrees with other studies. To improve agreement with the experiment, we introduced a model of macroscopic snow surface roughness by averaging the PPRT solution over the

  3. Analysis of snow bidirectional reflectance from ARCTAS Spring-2008 Campaign

    NASA Astrophysics Data System (ADS)

    Lyapustin, A.; Gatebe, C. K.; Kahn, R.; Brandt, R.; Redemann, J.; Russell, P.; King, M. D.; Pedersen, C. A.; Gerland, S.; Poudyal, R.; Marshak, A.; Wang, Y.; Schaaf, C.; Hall, D.; Kokhanovsky, A.

    2010-05-01

    The spring 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) experiment was one of major intensive field campaigns of the International Polar Year aimed at detailed characterization of atmospheric physical and chemical processes in the Arctic region. A part of this campaign was a unique snow bidirectional reflectance experiment on the NASA P-3B aircraft conducted on 7 and 15 April by the Cloud Absorption Radiometer (CAR) jointly with airborne Ames Airborne Tracking Sunphotometer (AATS) and ground-based Aerosol Robotic Network (AERONET) sunphotometers. The CAR data were atmospherically corrected to derive snow bidirectional reflectance at high 1° angular resolution in view zenith and azimuthal angles along with surface albedo. The derived albedo was generally in good agreement with ground albedo measurements collected on 15 April. The CAR snow bidirectional reflectance factor (BRF) was used to study the accuracy of analytical Ross-Thick Li-Sparse (RTLS), Modified Rahman-Pinty-Verstraete (MRPV) and Asymptotic Analytical Radiative Transfer (AART) BRF models. Except for the glint region (azimuthal angles φ<40°), the best fit MRPV and RTLS models fit snow BRF to within ±0.05. The plane-parallel radiative transfer (PPRT) solution was also analyzed with the models of spheres, spheroids, randomly oriented fractal crystals, and with a synthetic phase function. The latter merged the model of spheroids for the forward scattering angles with the fractal model in the backscattering direction. The PPRT solution with synthetic phase function provided the best fit to measured BRF in the full range of angles. Regardless of the snow grain shape, the PPRT model significantly over-/underestimated snow BRF in the glint/backscattering regions, respectively, which agrees with other studies. To improve agreement with experiment, we introduced a model of macroscopic snow surface roughness by averaging the PPRT solution over the slope

  4. Analysis of Snow BRF from Spring-2008 ARCTAS Campaign

    NASA Astrophysics Data System (ADS)

    Lyapustin, A.; Gatebe, C. K.; Kahn, R. A.; Brandt, R. E.; Redemann, J.; Russell, P. B.; King, M. D.; Pedersen, C. A.; Gerland, S.; Poudyal, R.; Marshak, A.; Wang, Y.; Schaaf, C.; Hall, D. K.; Kokhanovsky, A. A.

    2009-12-01

    The spring 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) experiment was one of major intensive field campaigns of the International Polar Year aimed at detailed characterization of atmospheric physical and chemical processes in the Arctic region. A part of this campaign was a unique snow bidirectional reflectance experiment on the NASA P-3B aircraft conducted on April 7 and 15 by the Cloud Absorption Radiometer (CAR) jointly with the Ames Airborne Tracking Sunphotometer (AATS) and ground-based AERONET sunphotometers. The CAR data were atmospherically corrected to derive snow bidirectional reflectance at high 1o angular resolution in view zenith and azimuthal angles along with surface albedo. The derived albedo was in a good agreement with ground albedo measurements collected on April 15. The CAR snow bidirectional reflectance factor (BRF) was used to study accuracy of analytical Li Sparse-Ross Thick (LSRT), Modified Rahman-Pinty-Verstraete (MRPV) and Analytical Asymptotic Radiative Transfer (AART) BRF models. Except for the glint region (azimuthal angles j < 40°), the best fit MRPV and LSRT models fit snow BRF to within ±0.05. The plane-parallel radiative transfer (PPRT) solution was also analyzed with the models of spheres, spheroids, randomly oriented fractal crystals, and with a synthetic phase function. The latter merged the model of spheroids for the forward scattering angles with the fractal model in the backscattering directions. The PPRT solution with synthetic phase function provided the best fit to measured BRF in the full range of angles. Regardless of the snow grain shape, the PPRT model significantly over-/underestimated snow BRF in the glint/backscattering regions, respectively, which agrees with other studies. To improve agreement with experiment, we introduced a model of macroscopic snow surface roughness by averaging the PPRT solution over the slope distribution function and by adding a simple

  5. Analysis of Snow Bidirectional Reflectance from ARCTAS Spring-2008 Campaign

    NASA Technical Reports Server (NTRS)

    Lyapustin, A.; Gatebe, C. K.; Redemann, J.; Kahn, R.; Brandt, R.; Russell, P.; King, M. D.; Pedersen, C. A.; Gerland, S.; Poudyal, R.; Marshak, A.; Wang, Y.; Schaaf, C.; Hall, D.; Kokhanovsky, A.

    2010-01-01

    The spring 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) experiment was one of major intensive field campaigns of the International Polar Year aimed at detailed characterization of atmospheric physical and chemical processes in the Arctic region. A part of this campaign was a unique snow bidirectional reflectance experiment on the NASA P-3B aircraft conducted on 7 and 15 April by the Cloud Absorption Radiometer (CAR) jointly with airborne Ames Airborne Tracking Sunphotometer (AATS) and ground-based Aerosol Robotic Network (AERONET) sunphotometers. The CAR data were atmospherically corrected to derive snow bidirectional reflectance at high 1 degree angular resolution in view zenith and azimuthal angles along with surface albedo. The derived albedo was generally in good agreement with ground albedo measurements collected on 15 April. The CAR snow bidirectional reflectance factor (BRF) was used to study the accuracy of analytical Ross-Thick Li-Sparse (RTLS), Modified Rahman-Pinty-Verstraete (MRPV) and Asymptotic Analytical Radiative Transfer (AART) BRF models. Except for the glint region (azimuthal angles phi less than 40 degrees), the best fit MRPV and RTLS models fit snow BRF to within 0.05. The plane-parallel radiative transfer (PPRT) solution was also analyzed with the models of spheres, spheroids, randomly oriented fractal crystals, and with a synthetic phase function. The latter merged the model of spheroids for the forward scattering angles with the fractal model in the backscattering direction. The PPRT solution with synthetic phase function provided the best fit to measured BRF in the full range of angles. Regardless of the snow grain shape, the PPRT model significantly over-/underestimated snow BRF in the glint/backscattering regions, respectively, which agrees with other studies. To improve agreement with experiment, we introduced a model of macroscopic snow surface roughness by averaging the PPRT solution

  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. Optical remote sensing of snow on sea ice: Ground measurements, satellite data analysis, and radiative transfer modeling

    NASA Astrophysics Data System (ADS)

    Zhou, Xiaobing

    2002-01-01

    The successful launch of the Terra satellite on December 18, 1999 opened a new era of earth observation from space. This thesis is motivated by the need for validation and promotion of the use of snow and sea ice products derived from MODIS, one of the main sensors aboard the Terra and Aqua satellites. Three cruises were made in the Southern Ocean, in the Ross, Amundsen and Bellingshausen seas. Measurements of all-wave albedo, spectral albedo, BRDF, snow surface temperature, snow grain size, and snow stratification etc. were carried out on pack ice floes and landfast ice. In situ measurements were also carried out concurrently with MODIS. The effect of snow physical parameters on the radiative quantities such as all-wave albedo, spectral albedo and bidirectional reflectance are studied using statistical techniques and radiative transfer modeling, including single scattering and multiple scattering. The whole thesis consists of six major parts. The first part (chapter 1) is a review of the present research work on the optical remote sensing of snow. The second part (chapter 2) describes the instrumentation and data-collection of ground measurements of all-wave albedo, spectral albedo and bidirectional reflectance distribution function (BRDF) of snow and sea ice in the visible-near-infrared (VNIR) domain in Western Antarctica. The third part (chapter 3) contains a detailed multivariate correlation and regression analysis of the measured radiative quantities with snow physical parameters such as snow density, surface temperature, single and composite grain size and number density. The fourth part (chapter 4) describes the validation of MODIS satellite data acquired concurrently with the ground measurements. The radiances collected by the MODIS sensor are converted to ground snow surface reflectances by removing the atmospheric effect using a radiative transfer algorithm (6S). Ground measured reflectance is corrected for ice concentration at the subpixel level so that

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. Brine-Wetted Snow on the Surface of Sea Ice: A Potentially Vast and Overlooked Microbial Habitat

    NASA Astrophysics Data System (ADS)

    Deming, J. W.; Ewert, M.; Bowman, J. S.; Colangelo-Lillis, J.; Carpenter, S. D.

    2010-12-01

    On the hemispheric scale, snow on the surface of sea ice significantly impacts the exchange of mass and energy across the ocean-ice-atmosphere interface. The snow cover over Arctic sea ice plays a central role in Arctic photochemistry, including atmospheric depletion events at the onset of spring, and in ecosystem support, by determining the availability of photosynthetically active radiation for algal primary production at the bottom of the ice. Among the non-uniformities of snow relevant to its larger-scale roles is salt content. When snow is deposited on the surface of new sea ice, brine expelled onto the ice surface during ice formation wicks into the snow by capillary action, forming a brine-wetted or saline snow layer at the ice-snow interface. A typical salinity for this basal snow layer in the Arctic (measured on a 3-cm depth interval of melted snow) is about 20 (ppt by optical salinometer), with maxima approaching 30 ppt, thus higher than the salinity of melted surface sea ice (< 12 ppt). Although the physical-chemical properties of this brine-wetted layer have been examined in recent years, and the (assumed) air-derived microbial content of overlying low-salinity snow is known to be low in winter, basal saline snow is essentially unexplored as a microbial habitat. As part of an NSF-supported project on frost flowers, we investigated snow overlying coastal sea ice off Barrow, Alaska, in February 2010 (since snow buries frost flowers). Sterile (ethanol-rinsed) tools were used to open snow pits 60 cm wide, record temperature by thermoprobe at 3-cm depth intervals, and collect samples from newly exposed snow walls for salinity (3-cm intervals) and biological measurements (6-cm intervals). The latter included counts of bacterial abundance by epifluorescence microscopy and assays of extracellular polysaccharide substances (EPS). We also sampled snow on a larger scale to extract sufficient DNA to analyze microbial community composition (ongoing work), as well as

  17. 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.

  18. 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.

  19. Nitrate chemistry in the snow and atmosphere at Summit, Greenland

    NASA Astrophysics Data System (ADS)

    Fibiger, D. L.; Hastings, M. G.; Dibb, J. E.; Nenes, A.; Chen, D.

    2013-12-01

    Atmospheric nitrate deposition to snow surfaces results from reactions of NOx (NO + NO2) with oxidants to produce HNO3. There has been enormous interest in using the isotopic composition of nitrate in ice cores to trace past NOx chemistry and sources. With the rapid cycling of NO and NO2, the oxygen isotopic signal reflects the oxidants that NOx reacts with to form nitrate, while the nitrogen isotopes could contain information about the NOx sources. In two spring/summer field seasons at Summit, Greenland (May-June 2010 and 2011), surface snow was collected at high time resolution and was measured for the complete N and O isotopic composition of nitrate. The oxygen isotopes (δ18O and Δ17O = δ17O - 0.52*δ18O) display the same very strong linear relationship (Δ17O = 0.46 * δ18O - 6.9, R2 = 0.9) in both seasons. This relationship indicates that there is very little photolysis of the nitrate at Summit and an unaltered nitrate signal is preserved in the snowpack. In addition, a suite of atmospheric measurements was made at Summit and none of the constituents measured show any correlation with concentration or isotopes of nitrate in the snow. This indicates that local chemistry is not contributing significantly to the nitrate in the snow. The combination of nitrogen and oxygen isotopes provides a richer picture of the data. There are three nitrate signatures that contribute to total nitrate deposition to Summit in both seasons. These sources can be described by the following isotopic compositions: δ15N, Δ17O, δ18O (per mil vs. air N2 or VSMOW): (1) -8, 27, 74 (2) 6, 40, 100 and (3) 16, 0, 23. While the same three nitrate sources are contributing in the two years, there is a very different balance of importance in 2010 compared to 2011. With limited source δ15N data it is difficult to assign each point to a specific NOx source, however the complete isotopic composition, atmospheric measurements and differences between the two seasons allow for tentative source

  20. Experimental investigation of road snow-melting based on CNFP self-heating concrete

    NASA Astrophysics Data System (ADS)

    Zhang, Qiangqiang; Li, Hui

    2011-04-01

    In this study, the road snow-melting system consisted of CNFP thermal source, AlN/Epoxy-based insulated-encapsulated layer and MWCNT/cement-based thermal conductive layer, was fabricated. The carbon nano-fiber paper (CNFP) taken excellent thermal and electrical properties was integrated into snow-melting system as the high-efficient thermal source. The remarkable electro-thermal and resistive properties of CNFP with the thickness of 0.38mm were investigated, and verified much higher efficiency electro-thermal property than other papery materials. The linearly temperature-dependent effect of CNFP resistivity was founded in certain temperature scope and met the line model as a function of temperature. Carbon nanotubes (CNT) attracted many filed scholars' focus based on its unique thermal conduction as a strong thermal-transferring candidate since it was founded. A new approach, named electric repulsion/high-frequency oscillatory dispersion, was proposed to fabricate the MWCNT/cement-based composites. The sample, filled with 3% MWCNT by the amount of cement, presents the significant improvement of thermal conductive property in contrast with other fillers and dispersing methods, which was integrated into snow-melting system with other parts as the thermal conductive layer material. The AlN/Epoxy-based composite, filled with 20% micron-AlN by the weight of mixture as the best candidate of insulated-capsulation material, would be used to guarantee the insulation. Due to the snow-melting field test, the snow-melting characteristics of integrated snow-melting system, dependent on the ambient temperature, wind speed, heat flux density and snow thickness, were investigated. The results not only verified the high-efficient, stable, feasible and economic properties, but also provided the valuable parameters for further snow-melting or ice-deicing investigation.

  1. Effect of long-term snow climate change on C and N cycling in the Great Basin Desert, USA

    NASA Astrophysics Data System (ADS)

    Loik, Michael

    2010-05-01

    (particularly under the canopies of a N-fixing shrub) interacted to affect long-term patterns of snow depth forcing on total C and NO3-. Results indicate that snow depth affects water, carbon, and nitrogen dynamics in both winter and the subsequent spring and summer, and that plant community composition will feedback on water cycling, carbon storage, and N availability over longer time scales. Interactions between species responses and ecosystem processes may help maintain resilience to snow climate change at this widespread shrub-conifer ecotone.

  2. 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.

  3. 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

  4. 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.

  5. Snow extent measurements from geostationary satellites using an interactive computer system. [Salt and Verde River Basins, Arizona

    NASA Technical Reports Server (NTRS)

    Gird, R. S. (Principal Investigator)

    1980-01-01

    The author has identified the following significant results. A time series of GOES full resolution visible image sectors was viewed on the McIDAS video component in chronological order and registered to within plus or minus 1 image pixel to compute real time snow melting rates. Synoptic scale clouds were eliminated to create a snow covered area from a composite image. Results show good agreement with NESS products although a significant difference was noted for one two-day period when the NESS products showed an increase in the snow cover for the Verde Basin, while the GOES/McIDAS product implied no change in the snow cover for approximately the same period. A check of NWS radar reports indicated no precipitation had occurred within the Verde basin. The use of the registered image sequence eliminates instrument error since small changes in the snow cover between any two days are easily detected.

  6. 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

  7. Increased photosynthesis compensates for shorter growing season in subarctic tundra - seven years of snow accumulation manipulations

    NASA Astrophysics Data System (ADS)

    Bosiö, Julia; Johansson, Margareta; Njuabe, Herbert; Christensen, Torben R.

    2013-04-01

    This study was initiated to analyze the effect of snow cover on photosynthesis and plant growth in subarctic mires underlain by permafrost. Due to their narrow environmental window these raised bogs, often referred to as palsa mires, are highly sensitive to climatic changes. In Fennoscandia palsa mires are currently subjected to climate related thawing and shift in vegetational and hydrological patterns. Yet, we know little of how these subarctic permafrost mires react and feed back to such changes. By using snow fences to hinder snow drift the accumulation of snow was increased in six plots (10x20 m) in a snow manipulation experiment on a subarctic permafrost mire in northern Sweden. The thicker snow pack prolongs the duration of the snow cover in spring, causing a delay in the onset, as well as an overall shortening of the growing season. By measuring incoming and reflected photosynthetic active radiation (PAR) we wanted to address the question whether the increased snow thickness and associated delay of the growing season start affected the absorbed PAR and the accumulated gross primary production (GPP) over the season. The reflected PAR was measured at twelve plots where six of the plots experienced increased snow accumulation (treatment), and remaining six plots were untreated (control). Minikin QT sensors with integrated data loggers logged incoming and reflected PAR hourly throughout the growing seasons of 2011 and 2012. In July - September 2010 PAR measurements were coupled with flux chamber measurements to assess GPP and light use efficiency of the plots. The increased accumulation of snow prolonged the duration of the snow cover in spring, causing a delay in the onset, as well as an overall shortening of the growing season in the treated plots. The end of the growing season was not affected by the snow manipulation. The delay of the growing season start and hence overall shortening of the growing season in the treatment plots was 18 days in 2011 and 3

  8. Laboratory Study of Nitrate Photolysis in Antarctic Snow: Quantum Yield and Isotope Effects

    NASA Astrophysics Data System (ADS)

    Meusinger, C.; Berhanu, T. A.; Erbland, J.; Jost, R.; Bhattacharya, S. K.; Savarino, J. P.; Johnson, M. S.

    2013-12-01

    Post-depositional processes alter the nitrate concentration and its isotopic composition in the top layers of snow at low snow accumulation sites, such as Dome C, Antarctica. Available nitrate ice core records can provide input for studying past atmospheres and climate if such processes are understood. Photolysis of nitrate in the snowpack was shown to be the major nitrate loss mechanism from the snowpack. Here a laboratory study is presented that uses snow from Dome C and minimizes effects of desorption by flushing the snow with pure N2 at 100 % humidity during irradiation with UV light from a Xenon lamp. A selection of UV filters allowed examination of the 200 and 300 nm absorption bands of nitrate and to emulate actinic fluxes similar to those in Dome C. Irradiated snow was sampled in 1 cm sections and analyzed for nitrate concentration and isotopic composition (δ15N, δ18O and Δ17O); the actinic flux was measured at similar sections in the snow. The quantum yield was observed to decrease from 0.44 to 0.05 within what corresponds to weeks of UV exposure in Antarctica. The superposition of photolysis in two photochemical domains of nitrate in snow is proposed: one of photolabile nitrate and one of trapped or buried nitrate. The difference lies in the ability of reaction products to escape the snow crystal, versus undergoing secondary (recombination) chemistry. Modeled NOx emissions may be increased significantly due to the observed quantum yield in this study influencing predicted boundary layer chemistry including ozone concentrations. An average photolytic isotopic fractionation of 15ɛ = -15×1.2 ‰ was found for the experiments without a wavelength filter. These results are ascribed to excitation of the 200 nm nitrate absorption band. Blocking wavelengths shorter than 320 nm, approximating the actinic flux spectrum at Dome C, showed a photolytic fractionation constant of 15ɛ = -47.9 × 6.8 ‰ which lies within the fractionation determined in the field

  9. 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

  10. Evaluation of MODIS Albedo Product (MCD43A) over Grassland, Agriculture and Forest Surface Types During Dormant and Snow-Covered Periods

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

    This study assesses the Moderate-resolution Imaging Spectroradiometer (MODIS) BRDF/albedo 8 day standard product and products from the daily Direct Broadcast BRDF/albedo algorithm, and shows that these products agree well with ground-based albedo measurements during the more difficult periods of vegetation dormancy and snow cover. Cropland, grassland, deciduous and coniferous forests are considered. Using an integrated validation strategy, analyses of the representativeness of the surface heterogeneity under both dormant and snow-covered situations are performed to decide whether direct comparisons between ground measurements and 500-m satellite observations can be made or whether finer spatial resolution airborne or spaceborne data are required to scale the results at each location. Landsat Enhanced Thematic Mapper Plus (ETM +) data are used to generate finer scale representations of albedo at each location to fully link ground data with satellite data. In general, results indicate the root mean square errors (RMSEs) are less than 0.030 over spatially representative sites of agriculture/grassland during the dormant periods and less than 0.050 during the snow-covered periods for MCD43A albedo products. For forest, the RMSEs are less than 0.020 during the dormant period and 0.025 during the snow-covered periods. However, a daily retrieval strategy is necessary to capture ephemeral snow events or rapidly changing situations such as the spring snow melt.

  11. 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…

  12. 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...

  13. 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)

  14. 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.

  15. 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…

  16. 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.

  17. 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.

  18. 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.

  19. Integrated ‘Omics’, Targeted Metabolite and Single-cell Analyses of Arctic Snow Algae Functionality and Adaptability

    PubMed Central

    Lutz, Stefanie; Anesio, Alexandre M.; Field, Katie; Benning, Liane G.

    2015-01-01

    Snow algae are poly-extremophilic microalgae and important primary colonizers and producers on glaciers and snow fields. Depending on their pigmentation they cause green or red mass blooms during the melt season. This decreases surface albedo and thus further enhances snow and ice melting. Although the phenomenon of snow algal blooms has been known for a long time, large aspects of their physiology and ecology sill remain cryptic. This study provides the first in-depth and multi-omics investigation of two very striking adjacent green and red snow fields on a glacier in Svalbard. We have assessed the algal community composition of green and red snow including their associated microbiota, i.e., bacteria and archaea, their metabolic profiles (targeted and non-targeted metabolites) on the bulk and single-cell level, and assessed the feedbacks between the algae and their physico-chemical environment including liquid water content, pH, albedo, and nutrient availability. We demonstrate that green and red snow clearly vary in their physico-chemical environment, their microbial community composition and their metabolic profiles. For the algae this likely reflects both different stages of their life cycles and their adaptation strategies. Green snow represents a wet, carbon and nutrient rich environment and is dominated by the algae Microglena sp. with a metabolic profile that is characterized by key metabolites involved in growth and proliferation. In contrast, the dry and nutrient poor red snow habitat is colonized by various Chloromonas species with a high abundance of storage and reserve metabolites likely to face upcoming severe conditions. Combining a multitude of techniques we demonstrate the power of such complementary approaches in elucidating the function and ecology of extremophiles such as green and red snow algal blooms, which play crucial roles in glacial ecosystems. PMID:26635781

  20. 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.

  1. 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

  2. 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

  3. 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

  4. 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.

  5. 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.

  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. 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.

  8. Forward and Inverse Modeling of GPS Multipath for Snow Monitoring

    NASA Astrophysics Data System (ADS)

    Nievinski, Felipe Geremia

    Snowpacks provide reservoirs of freshwater, storing solid precipitation and delaying runoff to be released later in the spring and summer when it is most needed. The goal of this dissertation is to develop the technique of GPS multipath reflectometry (GPS-MR) for ground-based measurement of snow depth. The phenomenon of multipath in GPS constitutes the reception of reflected signals in conjunction with the direct signal from a satellite. As these coherent direct and reflected signals go in and out of phase, signal-to-noise ratio (SNR) exhibits peaks and troughs that can be related to land surface characteristics. In contrast to other GPS reflectometry modes, in GPS-MR the poorly separated composite signal is collected utilizing a single antenna and correlated against a single replica. SNR observations derived from the newer L2-frequency civilian GPS signal (L2C) are used, as recorded by commercial off-the-shelf receivers and geodetic-quality antennas in existing GPS sites. I developed a forward/inverse approach for modeling GPS multipath present in SNR observations. The model here is unique in that it capitalizes on known information about the antenna response and the physics of surface scattering to aid in retrieving the unknown snow conditions in the antenna surroundings. This physically-based forward model is utilized to simulate the surface and antenna coupling. The statistically-rigorous inverse model is considered in two parts. Part I (theory) explains how the snow characteristics are parameterized; the observation/parameter sensitivity; inversion errors; and parameter uncertainty, which serves to indicate the sensing footprint where the reflection originates. Part II (practice) applies the multipath model to SNR observations and validates the resulting GPS retrievals against independent in situ measurements during a 1-3 year period in three different environments---grasslands, alpine, and forested. The assessment yields a correlation of 0.98 and an RMS error

  9. Remote sensing of snow and its application to hydrometeorological studies in western Canada

    NASA Astrophysics Data System (ADS)

    Tong, Jinjun

    also investigated in the MRB. The main findings of this thesis are as follows. Firstly, the SF method reduces the average cloud coverage in the QRB from 15% for MODIS 8-day snow products to 9%. The overall accuracy (OA) of MODIS snow products achieves ≈ 90% accuracy in the QRB. Secondly, the SCF and snow cover duration (SCD) are largely controlled by the topography of this alpine watershed. For example, the gradient of SCF with elevation (d(SCF)/dz) during the snowmelt season is 8% (100 m)-1 in the QRB. Mean gradients of SCD with elevation are 3.8, 4.3, and 11.6 days (100 m)-1 for the snow onset season, snowmelt season, and entire year, respectively in the QRB. Thirdly, for SWE retrieval algorithms from microwave remote sensing, significant relationships between brightness temperatures (TB) difference and in-situ SWE exist only when the snow accumulation is less than a threshold of 250 mm or 400 mm that varies at the different in-situ stations in the QRB. Overall, AMSR-E provides better estimates of retrieved SWE than SSM/I. Compared to the algorithms based on TB difference, the artificial neural network (ANN) for SSM/I and AMSR-E performs much better in the QRB. At last, significant relationships exist between the snow distribution and hydrometeorology of western Canada watersheds. For example, an aggregated 1°C rise in average air temperature during spring leads to a 10-day advance in reaching 50% SCF (SCF50%) in the QRB. The correlation coefficient between normalized SCE of the SF and normalized streamflow is -0.84 (p<0.001) for snow ablation seasons in the QRB. The correlation coefficients between SCF and discharge and between SWE and discharge are 0.87 (p<0.001) and 0.84 (p<0.001) in the MRB, respectively. The studies in this thesis will contribute to the monitoring of snow in remote northern areas where observation stations are sparse and the analyses of the relationships between the snow and hydrometeorology in western Canada are not well understood.

  10. Using continuous measurements of near-surface atmospheric water vapor isotopes to document snow-air interactions

    NASA Astrophysics Data System (ADS)

    Steen-Larsen, Hans Christian; Masson-Delmotte, Valerie; Hirabayashi, Motohiro; Winkler, Renato; Satow, Kazuhide; Prie, Frederic; Bayou, Nicolas; Brun, Eric; Cuffey, Kurt; Dahl-Jensen, Dorthe; Dumont, Marie; Guillevic, Myriam; Kipfstuhl, Sepp; Landais, Amaelle; Popp, Trevor; Risi, Camille; Steffen, Konrad; Stenni, Barbara; Sveinbjornsdottir, Arny

    2014-05-01

    Water stable isotope data from Greenland ice cores provide key paleoclimatic information. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, a monitoring of the isotopic composition δ18O and δD at several height levels (up to 13 meter) of near-surface water vapor, precipitation and snow in the first 0.5 cm from the surface has been conducted during three summers (2010-2012) at NEEM, NW Greenland. We observe a clear diurnal cycle in both the value and gradient of the isotopic composition of the water vapor above the snow surface. The diurnal amplitude in δD is found to be ~15‰. The diurnal isotopic composition follows the absolute humidity cycle. This indicates a large flux of vapor from the snow surface to the atmosphere during the daily warming and reverse flux during the daily cooling. The isotopic measurements of the flux of water vapor above the snow give new insights into the post depositional processes of the isotopic composition of the snow. During nine 1-5 days periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in-between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface vapor isotopic composition. This is consistent with an estimated 60% mass turnover of surface snow per day driven by snow

  11. 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

  12. 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).

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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).

  19. 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.

  20. Snow Model for the F-Layer

    NASA Astrophysics Data System (ADS)

    Lasbleis, M.; Hernlund, J. W.; Labrosse, S.

    2015-12-01

    Seismic observations of the Earth's core reveal a complex structure: radial and lateral heterogeneities in seismic anisotropy and attenuation in the solid inner core, but also discrepancies between observed P-wave velocity and homogeneous PREM model in the deep liquid outer core. In this work, we focus on the 200km anomalous layer at the bottom of the outer core that exhibits seismic velocities lower than the PREM model. It has been interpreted as a layer depleted in light elements, whereas the usual model considers that light elements are expelled at the surface of the inner core by freezing of the outer core alloy. Recent models of core formation argued for an early stratified liquid core, and the stratified layers at the top and bottom of the outer core would be a vestige of this primordial stratification. However, freezing of the inner core at the inner core boundary releases light elements that provide buoyancy fluxes that would mix the stratified liquid above with small scale buoyant plumes. To model the F-layer, we consider that the freezing of the iron alloy and the release of light elements have to occur in the bulk of the layer. Iron snow forms and settles in the layer, buffering the thermal and chemical profile to the liquidus. We show that this dynamics can both sustain and stabilize the stratified layer in the liquid outer core while simultaneously matching the seismic observations. However, the expected layer is stable only for a given set of parameters, in particular when a high thermal diffusivity (>100 W/m/K) is employed. If freezing of the iron alloy of the outer core occurs in the bulk of the layer, several assumptions for both the outer and inner core has to be discussed: the F-layer acts as a boundary layer for both composition and temperature, and modifies the quantity of light elements expelled into the outer core as well as the composition that freezes to form the inner core.

  1. 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

    Monitoring of snow cover extent and snow water equivalent (SWE) in boreal forests is important for determining the amount of potential runoff and beginning date of snowmelt. The great expanse of the boreal forest necessitates the use of satellite measurements to monitor snow cover. Snow cover in the boreal forest can be mapped with either the Moderate Resolution Imaging Spectroradiometer (MODIS) or the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) microwave instrument. The extent of snow cover is estimated from the MODIS data and SWE is estimated from the AMSR-E. Environmental limitations affect both sensors in different ways to limit their ability to detect snow in some situations. Forest density, snow wetness, and snow depth are factors that limit the effectiveness of both sensors for snow detection. Cloud cover is a significant hindrance to monitoring snow cover extent Using MODIS but is not a hindrance to the use of the AMSR-E. These limitations could be mitigated by combining MODIS and AMSR-E data to allow for improved interpretation of snow cover extent and SWE on a daily basis and provide temporal continuity of snow mapping across the boreal forest regions in Canada. The purpose of this study is to investigate if temporal monitoring of snow cover using a combination of MODIS and AMSR-E data could yield a better interpretation of changing snow cover conditions. The MODIS snow mapping algorithm is based on snow detection using the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to enhance snow detection in dense vegetation. (Other spectral threshold tests are also used to map snow using MODIS.) Snow cover under a forest canopy may have an effect on the NDVI thus we use the NDVI in snow detection. A MODIS snow fraction product is also generated but not used in this study. In this study the NDSI and NDVI components of the snow mapping algorithm were calculated and analyzed to determine how they changed

  2. 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

  3. 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

  4. 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.

  5. "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

  6. 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

  7. 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.

  8. 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.

  9. Analysis of element accumulation in cell wall attached and intracellular particles of snow algae by EELS and ESI.

    PubMed

    Lütz-Meindl, Ursula; Lütz, Cornelius

    2006-01-01

    Snow algae frequently occur in alpine and polar permanent snow ecosystems and have developed adaptations to their harsh environment, where extreme temperature regimes high irradiation and low nutrient levels prevail. They live in a unique microhabitat, namely the liquid water between snow crystals. The predominant form appears as 'red snow' and in polar environment also 'green snow' frequently occurs. Light microscopy showed that most cells are densely covered by non-biotic particles of so far unknown composition. As snow normally contains very low amounts of nutrients, introduced mainly airborne like dust and precipitation, the inorganic particles at the surface of the snow algae may be important for their survival. By using electron energy loss spectroscopy (EELS) and electron spectroscopic imaging (ESI), we investigated element distribution in ultrathin sections of snow algae from different polar (Svalbard, 5 m a.s.l., 79 degrees N and maritime Antarctic, King George Island, 10 m a.s.l., 62 degrees S) and alpine habitats (2400-3100 m a.s.l. Tyrol) for the present study. It turned out that the main elements of the cell wall attached particles are Si, Al, Fe and O independently from the origin of the snow algae. Interestingly, the same elements were also found in vacuolar compartments inside the cells. These vacuoles contain electron dense granules or crystals and are frequently found to be connected to the cortical cytoplasm. This finding suggests an uptake mechanism of the respective elements by pinocytosis. Co-transport of toxic aluminium together with silicon may be unavoidable as the inorganic nutrient uptake of the snow algae is limited to the thin water layer between the ice crystals. However, formation of insoluble aluminium silicates may serve as detoxification mechanism. PMID:16376553

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. Simulating the Dependence of Sagebrush Steppe Vegetation on Redistributed Snow in a Semi-Arid Watershed.

    NASA Astrophysics Data System (ADS)

    Soderquist, B.; Kavanagh, K.; Link, T. E.; Strand, E. K.; Seyfried, M. S.

    2014-12-01

    In mountainous regions across the western USA, the composition of aspen (Populus tremuloides) and sagebrush steppe plant communities is often closely related to heterogeneous soil moisture subsidies resulting from redistributed snow. With decades of climate and precipitation data across elevational and precipitation gradients, the Reynolds Creek Experimental Watershed (RCEW) and critical zone observatory (CZO) in southwest Idaho provides a unique opportunity to study the relationship between vegetation types and redistributed snow. Within the RCEW, the total amount of precipitation has remained unchanged over the past 50 years, however the percentage of the precipitation falling as snow has declined by approximately 4% per decade at mid-elevation sites. As shifts in precipitation phase continue, future trends in vegetation composition and net primary productivity (NPP) of different plant functional types remains a critical question. We hypothesize that redistribution of snow may supplement drought sensitive species like aspen more so than drought tolerant species like mountain big sagebrush (Artemisia tridentata spp. vaseyana). To assess the importance of snowdrift subsidies on sagebrush steppe vegetation, NPP of aspen, shrub, and grass species was simulated at three sites using the biogeochemical process model BIOME-BGC. Each site is located directly downslope from snowdrifts providing soil moisture inputs to aspen stands and neighboring vegetation. Drifts vary in size with the largest containing up to four times the snow water equivalent (SWE) of a uniform precipitation layer. Precipitation inputs used by BIOME-BGC were modified to represent the redistribution of snow and simulations were run using daily climate data from 1985-2013. Simulated NPP of annual grasses at each site was not responsive to subsidies from drifting snow. However, at the driest site, aspen and shrub annual NPP was increased by as much as 44 and 30%, respectively, with the redistribution of

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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)

  7. 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.

  8. 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.

  9. 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).

  10. 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

  11. 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

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. Probing the methanol and CO snow lines in young protostars

    NASA Astrophysics Data System (ADS)

    Anderl, S.; Maret, S.

    2016-05-01

    "Snow lines", marking regions where abundant volatiles freeze out onto the surface of dust grains, play an important role for planet growth and bulk composition in protoplanetary disks. However, they can already be observed in the envelopes of the much younger, low-mass Class 0 protostars that are still in their early phase of heavy accretion. The information on the sublimation regions of different kinds of ices can be used to understand the chemistry of the envelope, its temperature and density structure, and may even hint at the history of the accretion process. As part of the CALYPSO Large Program, we have obtained observations of C18O, N2H+ and CH3OH towards the nearest low-luminosity Class 0 protostars with the IRAM Plateau de Bure interferometer at sub-arcsecond resolution. We observe an anti-correlation of C18O and N2H+ in four of these sources, with N2H+ forming a ring (perturbed by the outflow) around the centrally peaked C18O emission. This reveals the CO snow line in these protostellar envelopes with unprecedented resolution. In addition, we observe compact methanol emission towards three of the sources. We have modeled the emission using a chemical model coupled with a radiative transfer module, using the temperature and density profiles self-consistently determined by Kristensen et al. ([4]). We find that for all four sources the CO snow line appears further inwards than expected from the binding energy of pure CO ices. This may hint at CO being frozen out on H2O surfaces or in mixed ices. Our observations can thereby yield clues on the widely unknown composition of interstellar ices, being the initial seeds of complex organic chemistry.

  20. Snow as a habitat for microorganisms

    NASA Technical Reports Server (NTRS)

    Hoham, Ronald W.

    1989-01-01

    There are three major habitats involving ice and snow, and the microorganisms studied from these habitats are most eukaryotic. Sea ice is inhabited by algae called diatoms, glacial ice has sparse populations of green algai cal desmids, and the temporary and permanent snows in mountainous regions and high latitudes are inhabited mostly by green algal flagellates. The life cycle of green algal flagellates is summarized by discussing the effects of light, temperature, nutrients, and snow melts. Specific examples of optimal conditions and environmental effects for various snow algae are given. It is not likely that the eukaryotic snow algae presented are candidated for life on the planet Mars. Evolutionally, eukaryotic cells as know on Earth may not have had the opportunity to develop on Mars (if life evolved at all on Mars) since eukaryotes did not appear on Earth until almost two billion years after the first prokaryotic organisms. However, the snow/ice ecosystems on Earth present themselves as extreme habitats were there is evidence of prokaryotic life (eubacteria and cyanbacteria) of which literally nothing is known. Any future surveillances of extant and/or extinct life on Mars should include probes (if not landing sites) to investigate sites of concentrations of ice water. The possibility of signs of life in Martian polar regions should not be overlooked.

  1. 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.

  2. [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

  3. 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.

  4. 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

  5. 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

    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 is ground-based radar composites. 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 EGU conference including the first complete northern hemisphere winter season. If available, results from improvements in the Bayesian database will be reported.

  6. Consequences of declining snow accumulation for water balance of mid-latitude dry regions

    USGS Publications Warehouse

    Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

    2012-01-01

    Widespread documentation of positive winter temperature anomalies, declining snowpack and earlier snow melt in the Northern Hemisphere have raised concerns about the consequences for regional water resources as well as wildfire. A topic that has not been addressed with respect to declining snowpack is effects on ecosystem water balance. Changes in water balance dynamics will be particularly pronounced at low elevations of mid-latitude dry regions because these areas will be the first to be affected by declining snow as a result of rising temperatures. As a model system, we used simulation experiments to investigate big sagebrush ecosystems that dominate a large fraction of the semiarid western United States. Our results suggest that effects on future ecosystem water balance will increase along a climatic gradient from dry, warm and snow-poor to wet, cold and snow-rich. Beyond a threshold within this climatic gradient, predicted consequences for vegetation switched from no change to increasing transpiration. Responses were sensitive to uncertainties in climatic prediction; particularly, a shift of precipitation to the colder season could reduce impacts of a warmer and snow-poorer future, depending on the degree to which ecosystem phenology tracks precipitation changes. Our results suggest that big sagebrush and other similar semiarid ecosystems could decrease in viability or disappear in dry to medium areas and likely increase only in the snow-richest areas, i.e. higher elevations and higher latitudes. Unlike cold locations at high elevations or in the arctic, ecosystems at low elevations respond in a different and complex way to future conditions because of opposing effects of increasing water-limitation and a longer snow-free season. Outcomes of such nonlinear interactions for future ecosystems will likely include changes in plant composition and productivity, dynamics of water balance, and availability of water resources.

  7. Fractional snow cover estimation in complex alpineforested environments using remotely sensed data and artificial neural networks

    NASA Astrophysics Data System (ADS)

    Czyzowska-Wisniewski, Elzbieta Halina Magdalena

    There is an undisputed need to increase accuracy of snow cover estimation in regions comprised of complex terrain, especially in areas dependent on winter snow accumulation for a substantial portion of their annual water supply, such as the Western United States, Central Asia, and the Andes. Presently, the most pertinent monitoring and research needs related to alpine snow cover area (SCA) are: (1) to improve SCA monitoring by providing detailed fractional snow cover (FSC) products which perform well in temporal/spatial heterogeneous forested and/or alpine terrains; and (2) to provide accurate measurements of FSC at the watershed scale for use in snow water equivalent (SWE) estimation for regional water management. To address the above, the presented research approach is based on Landsat Fractional Snow Cover (Landsat-FSC), as a measure of the temporal/spatial distribution of alpine SCA. A fusion methodology between remotely sensed multispectral input data from Landsat TM/ETM+, terrain information, and IKONOS are utilized at their highest respective spatial resolutions. Artificial Neural Networks (ANNs) are used to capture the multi-scale information content of the input data compositions by means of the ANN training process, followed by the ANN extracting FSC from all available information in the Landsat and terrain input data compositions. The ANN Landsat-FSC algorithm is validated (RMSE ~ 0.09; mean error ~ 0.001-0.01 FSC) in watersheds characterized by diverse environmental factors such as: terrain, slope, exposition, vegetation cover, and wide-ranging snow cover conditions. ANN input data selections are evaluated to determine the nominal data information requirements for FSC estimation. Snow/non-snow multispectral and terrain input data are found to have an important and multi-faced impact on FSC estimation. Constraining the ANN to linear modeling, as opposed to allowing unconstrained function shapes, results in a weak FSC estimation performance and therefore

  8. Composition.

    ERIC Educational Resources Information Center

    Nemanich, Donald, Ed.

    1974-01-01

    The articles in this special issue of the "Illinois English Bulletin" concern the state of composition instruction at the secondary and college levels. The titles and authors are "Monologues or Dialogues? A Plea for Literacy" by Dr. Alfred J. Lindsey, "Teaching Composition: Curiouser and Curiouser" by Denny Brandon, and "Teaching Writing to High…

  9. 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.

  10. Hydrometeorological characteristics of rain-on-snow events associated with atmospheric rivers

    NASA Astrophysics Data System (ADS)

    Guan, Bin; Waliser, Duane E.; Ralph, F. Martin; Fetzer, Eric J.; Neiman, Paul J.

    2016-03-01

    Atmospheric rivers (ARs) are narrow, elongated, synoptic corridors of enhanced water vapor transport that play an important role in regional weather/hydrology. Rain-on-snow (ROS) events during ARs present enhanced flood risks due to the combined effects of rainfall and snowmelt. Focusing on California's Sierra Nevada, the study identifies ROS occurrences and their connection with ARs during the 1998-2014 winters. AR conditions, which occur during 17% of all precipitation events, are associated with 50% of ROS events (25 of 50). Composite analysis shows that compared to ARs without ROS, ARs with ROS are on average warmer by ~2 K, with snow water equivalent loss of ~0.7 cm/d (providing 20% of the combined water available for runoff) and ~50% larger streamflow/precipitation ratios. Atmospheric Infrared Sounder retrievals reveal distinct offshore characteristics of the two types of ARs. The results highlight the potential value of observing these events for snow, rain, and flood prediction.

  11. ON THE EVOLUTION OF THE CO SNOW LINE IN PROTOPLANETARY DISKS

    SciTech Connect

    Martin, Rebecca G.; Livio, Mario

    2014-03-10

    CO is thought to be a vital building block for prebiotic molecules that are necessary for life. Thus, understanding where CO existed in a solid phase within the solar nebula is important for understanding the origin of life. We model the evolution of the CO snow line in a protoplanetary disk. We find that the current observed location of the CO snow line in our solar system, and in the solar system analog TW Hydra, cannot be explained by a fully turbulent disk model. With time-dependent disk models we find that the inclusion of a dead zone (a region of low turbulence) can resolve this problem. Furthermore, we obtain a fully analytic solution for the CO snow line radius for late disk evolutionary times. This will be useful for future observational attempts to characterize the demographics and predict the composition and habitability of exoplanets.

  12. Snow cover retrieval over Rhone and Po river basins from MODIS optical satellite data (2000-2009).

    NASA Astrophysics Data System (ADS)

    Dedieu, Jean-Pierre, ,, Dr.; Boos, Alain; Kiage, Wiliam; Pellegrini, Matteo

    2010-05-01

    retrieve (i) Fractional Snow cover at sub-pixel scale, and (ii) maximum snow cover. All products were retrieved at 8-days over a complete time period of 10 years (2000-2009), giving 500 images for each river basin. Digital Model Elevation was given by NASA/SRTM database at 90-m resolution and used (i) for illumination versus topography correction on snow cover, (ii) geometric rectification of images. Geographic projection is WGS84, UTM 32. Fractional Snow cover mapping was derived from the NDSI linear regression method (Salomonson et al., 2004). Cloud mask was given by MODIS-NASA library (radiometric threshold) and completed by inverse slope regression to avoid lowlands fog confusing with thin snow cover (Po river basin). Maximum Snow Cover mapping was retrieved from the NSIDC database classification (Hall et al., 2001). Validation step was processed using comparison between MODIS Snow maps outputs and meteorological data provided by network of 87 meteorological stations: temperature, precipitation, snow depth measurement. A 0.92 correlation was observed for snow/non snow cover and can be considered as quite satisfactory, given the radiometric problems encountered in mountainous areas, particularly in snowmelt season. The 10-years time period results indicates a main difference between (i) regular snow accumulation and depletion in Rhone and (ii) the high temporal and spatial variability of snow cover for Po. Then, a high sensitivity to low variation of air temperature, often close to 1° C was observed. This is the case in particular for the beginning and the end of the winter season. The regional snow cover depletion is both influenced by thermal positives anomalies (e.g. 2000 and 2006), and the general trend of rising atmospheric temperatures since the late 1980s, particularly for Po river basin. Results will be combined with two hydrological models: Topkapi and Fest.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. Changes in diversity and biomass of bacteria along a shallow snow pit from Kuytun 51 Glacier, Tianshan Mountains, China

    NASA Astrophysics Data System (ADS)

    Xiang, Shu-Rong; Shang, Tian-Cui; Chen, Yong; Jing, Z.-F.; Yao, Tandong

    2009-12-01

    Microorganisms vary in both biomass and diversity composition along glacial depth profiles. However, it is not well known about the major processes controlling the structure diversity shift of microorganisms in a glacier, although, aeolian deposition has been widely accepted as one mechanism regulating the distribution of microorganisms in snow. To better understand the distribution of microorganisms in a glacier, variations in bacterial diversity and biomass along a pit profile from the Kuytun 51 Glacier in the Tianshan Mountains in China were investigated by using 16S rRNA gene library sequencing and flow cytometric analysis with cell sorting markers. Four clone libraries were established from each of the different sampling depths from the snow pit. A total of 311 insert clones were preliminarily screened by HaeIII-based amplified rRNA restriction analysis (ARDRA), and 83 representatives of the unique ARDRA patterns were sequenced. Sequence analysis showed that the bacteria in the snow pit were affiliated with 23 known subphyla within the members of the Proteobacteria, Bacteroidetes, Actinobacteria, Firmicutes, and Cyanobacteria phyla. To examine diversity shifts in snow, the diversity structures from the snow pit were also compared with those previously recovered from the different habitats along the Kuytun 51 Glacier surface and from the deep Malan Glacier. The results showed structure shift patterns in bacterial diversity among the surface, deep snow, and deep ice. Sequence analysis displayed a dramatic diversity shift from a mixture of Cyanobacteria and other eubacteria across the glacial surface to other eubacteria without Cyanobacteria in the deep snow. However, the biogeochemical analyses showed great variability in the measured abiotic and biotic components along the pit profile, which reinforced the idea of aeolian deposition being a dominant mechanism controlling the size and diversity of microorganisms in snow. Overall, the findings indicated a

  18. Key characteristics of the Fe-snow regime in Ganymede's core

    NASA Astrophysics Data System (ADS)

    Rückriemen, Tina; Breuer, Doris; Spohn, Tilman

    2014-05-01

    Ganymede shows signs of an internally produced dipolar magnetic field (|Bdip|≡719 nT) [1]. For small planetary bodies such as Ganymede the Fe-snow regime, i.e. the top-down solidification of iron, has been suggested to play an important role in the core cooling history [2,3]. In that regime, iron crystals form first at the core-mantle boundary (CMB) due to shallow or negative slopes of the melting temperature [2,3]. The solid iron particles are heavier than the surrounding Fe-FeS fluid, i.e. a snow zone forms, settle to deeper core regions, where the core temperature is higher than the melting temperature, and remelt again. As a consequence, a stable chemical gradient in the Fe-FeS fluid arises within the snow zone. We speculate this style of convection via sedimentation to be small scale, therefore it lacks an important criterion necessary for dynamo action [4]. Below this zone, whose thickness increases with time, the process of remelting of iron creates a gravitationally unstable situation. We propose that this could be the driving mechanism for a potential dynamo. However, dynamo action would be restricted to the time period the snow zone needs to grow across the core. With a 1D thermo-chemical evolution model, we investigate key characteristics of the Fe-snow regime within Ganymede's core: the compositional density gradient of the fluid Fe-FeS within the snow zone and the time period necessary to grow the snow zone across the core. Additionally, we determine the dipolar magnetic field strength associated with a dynamo in Ganymede's deeper fluid core. We vary important input paramters such as the initial sulfur concentration (7-19 wt.%), the core heat flux (2-6 mW/m2) and the thermal conductivity (20-60 W/mK) with the nominal model being: xs=10 wt.%, qcmb=4 mW/m2, kc=32 W/mK. We find, that heat fluxes higher than 6 or 22 mW/m2 are required for double-diffusive or overturning convection to overcome the compositional density gradient within the snow zone

  19. 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.

  20. 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.

  1. 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

  2. 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,

  3. 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.

  4. 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

  5. Laboratory study of nitrate photolysis in Antarctic snow. I. Observed quantum yield, domain of photolysis, and secondary chemistry

    NASA Astrophysics Data System (ADS)

    Meusinger, Carl; Berhanu, Tesfaye A.; Erbland, Joseph; Savarino, Joel; Johnson, Matthew S.

    2014-06-01

    Post-depositional processes alter nitrate concentration and nitrate isotopic composition in the top layers of snow at sites with low snow accumulation rates, such as Dome C, Antarctica. Available nitrate ice core records can provide input for studying past atmospheres and climate if such processes are understood. It has been shown that photolysis of nitrate in the snowpack plays a major role in nitrate loss and that the photolysis products have a significant influence on the local troposphere as well as on other species in the snow. Reported quantum yields for the main reaction spans orders of magnitude - apparently a result of whether nitrate is located at the air-ice interface or in the ice matrix - constituting the largest uncertainty in models of snowpack NOx emissions. Here, a laboratory study is presented that uses snow from Dome C and minimizes effects of desorption and recombination by flushing the snow during irradiation with UV light. A selection of UV filters allowed examination of the effects of the 200 and 305 nm absorption bands of nitrate. Nitrate concentration and photon flux were measured in the snow. The quantum yield for loss of nitrate was observed to decrease from 0.44 to 0.003 within what corresponds to days of UV exposure in Antarctica. The superposition of photolysis in two photochemical domains of nitrate in snow is proposed: one of photolabile nitrate, and one of buried nitrate. The difference lies in the ability of reaction products to escape the snow crystal, versus undergoing secondary (recombination) chemistry. Modeled NOx emissions may increase significantly above measured values due to the observed quantum yield in this study. The apparent quantum yield in the 200 nm band was found to be ˜1%, much lower than reported for aqueous chemistry. A companion paper presents an analysis of the change in isotopic composition of snowpack nitrate based on the same samples as in this study.

  6. Laboratory study of nitrate photolysis in Antarctic snow. I. Observed quantum yield, domain of photolysis, and secondary chemistry.

    PubMed

    Meusinger, Carl; Berhanu, Tesfaye A; Erbland, Joseph; Savarino, Joel; Johnson, Matthew S

    2014-06-28

    Post-depositional processes alter nitrate concentration and nitrate isotopic composition in the top layers of snow at sites with low snow accumulation rates, such as Dome C, Antarctica. Available nitrate ice core records can provide input for studying past atmospheres and climate if such processes are understood. It has been shown that photolysis of nitrate in the snowpack plays a major role in nitrate loss and that the photolysis products have a significant influence on the local troposphere as well as on other species in the snow. Reported quantum yields for the main reaction spans orders of magnitude - apparently a result of whether nitrate is located at the air-ice interface or in the ice matrix - constituting the largest uncertainty in models of snowpack NOx emissions. Here, a laboratory study is presented that uses snow from Dome C and minimizes effects of desorption and recombination by flushing the snow during irradiation with UV light. A selection of UV filters allowed examination of the effects of the 200 and 305 nm absorption bands of nitrate. Nitrate concentration and photon flux were measured in the snow. The quantum yield for loss of nitrate was observed to decrease from 0.44 to 0.003 within what corresponds to days of UV exposure in Antarctica. The superposition of photolysis in two photochemical domains of nitrate in snow is proposed: one of photolabile nitrate, and one of buried nitrate. The difference lies in the ability of reaction products to escape the snow crystal, versus undergoing secondary (recombination) chemistry. Modeled NOx emissions may increase significantly above measured values due to the observed quantum yield in this study. The apparent quantum yield in the 200 nm band was found to be ∼1%, much lower than reported for aqueous chemistry. A companion paper presents an analysis of the change in isotopic composition of snowpack nitrate based on the same samples as in this study. PMID:24985636

  7. Laboratory study of nitrate photolysis in Antarctic snow. I. Observed quantum yield, domain of photolysis, and secondary chemistry

    SciTech Connect

    Meusinger, Carl; Johnson, Matthew S.; Berhanu, Tesfaye A.; Erbland, Joseph; Savarino, Joel

    2014-06-28

    Post-depositional processes alter nitrate concentration and nitrate isotopic composition in the top layers of snow at sites with low snow accumulation rates, such as Dome C, Antarctica. Available nitrate ice core records can provide input for studying past atmospheres and climate if such processes are understood. It has been shown that photolysis of nitrate in the snowpack plays a major role in nitrate loss and that the photolysis products have a significant influence on the local troposphere as well as on other species in the snow. Reported quantum yields for the main reaction spans orders of magnitude – apparently a result of whether nitrate is located at the air-ice interface or in the ice matrix – constituting the largest uncertainty in models of snowpack NO{sub x} emissions. Here, a laboratory study is presented that uses snow from Dome C and minimizes effects of desorption and recombination by flushing the snow during irradiation with UV light. A selection of UV filters allowed examination of the effects of the 200 and 305 nm absorption bands of nitrate. Nitrate concentration and photon flux were measured in the snow. The quantum yield for loss of nitrate was observed to decrease from 0.44 to 0.003 within what corresponds to days of UV exposure in Antarctica. The superposition of photolysis in two photochemical domains of nitrate in snow is proposed: one of photolabile nitrate, and one of buried nitrate. The difference lies in the ability of reaction products to escape the snow crystal, versus undergoing secondary (recombination) chemistry. Modeled NO{sub x} emissions may increase significantly above measured values due to the observed quantum yield in this study. The apparent quantum yield in the 200 nm band was found to be ∼1%, much lower than reported for aqueous chemistry. A companion paper presents an analysis of the change in isotopic composition of snowpack nitrate based on the same samples as in this study.

  8. The preservation of long-range transported nitrate in snow at Summit, Greenland (Invited)

    NASA Astrophysics Data System (ADS)

    Hastings, M. G.

    2013-12-01

    Nitrate is one of the major anions found in polar and alpine snow, both today and in the past. Deposition of nitrate to snow surfaces results from reactions of nitrogen oxides (NOx) with oxidants in the atmosphere, resulting in the production of HNO3 that is incorporated into precipitation or reacts on the surface of particles. Several factors motivate studying nitrate concentration in ice cores including reconstructing past levels of NOx, tropospheric oxidant concentrations and natural variability in NOx sources. The link between the atmospheric concentration of NOx and nitrate concentration in ice core records is problematic because post-depositional processing, such as photolysis and evaporation, can impact the concentration of nitrate in snow. Recent work has shown that the isotopic ratios of nitrate (15N/14N, 18O/16O, 17O/16O) can be a powerful tool for tracing post-depositional loss of nitrate from surface snow. The isotopic composition of nitrate has been shown to contain information about the source of the nitrate (i.e, NOx sources) and the oxidation processes that convert NOx to nitrate in the atmosphere prior to deposition. Results from a number of studies at Summit, Greenland reveal limited loss of nitrate from surface snow during highly photoactive periods, and the oxygen isotopic signatures in snow nitrate appear to be representative of atmospheric deposition of nitrate from outside of Summit. Higher than expected oxygen isotope ratios (18O/16O, 17O/16O) found in Summit summertime nitrate were expected to be dependent upon local photochemistry in which nitrate in the snow is photolyzed to NOx that is then oxidized above the snow by BrO to reform nitrate (i.e., BrONO2). However, the oxygen isotopic composition of nitrate collected at high time resolution in surface snow does not show any link to local gas phase concentrations of a number of species, including BrO. Furthermore, the combination of nitrogen and oxygen isotope data reveals interesting

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Composites

    SciTech Connect

    Chou, T.; McCullough, R.L.; Pipes, R.B.

    1986-10-01

    The degree of control over material properties that is typified by hybrid composites is transforming engineering design. In part because homogeneous materials such as metals and alloys do not offer comparable control, specifying a material and designing a component have traditionally taken place separately. As composites begin to replace traditional materials in fields and such as aerospace, component design and the specification of a material are merging and becoming aspects of a single process. The controllable microstructure of a composite allows it to be tailored to match the distribution of stresses to which it will be subject. At the same time components must come to reflect the distinctive nature of composites: their directional properties and the intricate forms they can be given through processes such as injection molding, filament winding and three-dimensional weaving. The complexity inherent in conceiving components and their materials at the same time suggests engineering design will grow increasingly dependent on computers and multidisciplinary teams. Such an approach will harness the full potential of composites for the technologies of the future. 10 figures.

  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. 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

  3. 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

  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. Laboratory study of nitrate photolysis in Antarctic snow. II. Isotopic effects and wavelength dependence

    NASA Astrophysics Data System (ADS)

    Berhanu, Tesfaye A.; Meusinger, Carl; Erbland, Joseph; Jost, Rémy; Bhattacharya, S. K.; Johnson, Matthew S.; Savarino, Joël

    2014-06-01

    Atmospheric nitrate is preserved in Antarctic snow firn and ice. However, at low snow accumulation sites, post-depositional processes induced by sunlight obscure its interpretation. The goal of these studies (see also Paper I by Meusinger et al. ["Laboratory study of nitrate photolysis in Antarctic snow. I. Observed quantum yield, domain of photolysis, and secondary chemistry," J. Chem. Phys. 140, 244305 (2014)]) is to characterize nitrate photochemistry and improve the interpretation of the nitrate ice core record. Naturally occurring stable isotopes in nitrate (15N, 17O, and 18O) provide additional information concerning post-depositional processes. Here, we present results from studies of the wavelength-dependent isotope effects from photolysis of nitrate in a matrix of natural snow. Snow from Dome C, Antarctica was irradiated in selected wavelength regions using a Xe UV lamp and filters. The irradiated snow was sampled and analyzed for nitrate concentration and isotopic composition (δ15N, δ18O, and Δ17O). From these measurements an average photolytic isotopic fractionation of 15ɛ = (-15 ± 1.2)‰ was found for broadband Xe lamp photolysis. These results are due in part to excitation of the intense absorption band of nitrate around 200 nm in addition to the weaker band centered at 305 nm followed by photodissociation. An experiment with a filter blocking wavelengths shorter than 320 nm, approximating the actinic flux spectrum at Dome C, yielded a photolytic isotopic fractionation of 15ɛ = (-47.9 ± 6.8)‰, in good agreement with fractionations determined by previous studies for the East Antarctic Plateau which range from -40 to -74.3‰. We describe a new semi-empirical zero point energy shift model used to derive the absorption cross sections of 14NO3- and 15NO3- in snow at a chosen temperature. The nitrogen isotopic fractionations obtained by applying this model under the experimental temperature as well as considering the shift in width and center well

  8. Laboratory study of nitrate photolysis in Antarctic snow. II. Isotopic effects and wavelength dependence.

    PubMed

    Berhanu, Tesfaye A; Meusinger, Carl; Erbland, Joseph; Jost, Rémy; Bhattacharya, S K; Johnson, Matthew S; Savarino, Joël

    2014-06-28

    Atmospheric nitrate is preserved in Antarctic snow firn and ice. However, at low snow accumulation sites, post-depositional processes induced by sunlight obscure its interpretation. The goal of these studies (see also Paper I by Meusinger et al. ["Laboratory study of nitrate photolysis in Antarctic snow. I. Observed quantum yield, domain of photolysis, and secondary chemistry," J. Chem. Phys. 140, 244305 (2014)]) is to characterize nitrate photochemistry and improve the interpretation of the nitrate ice core record. Naturally occurring stable isotopes in nitrate ((15)N, (17)O, and (18)O) provide additional information concerning post-depositional processes. Here, we present results from studies of the wavelength-dependent isotope effects from photolysis of nitrate in a matrix of natural snow. Snow from Dome C, Antarctica was irradiated in selected wavelength regions using a Xe UV lamp and filters. The irradiated snow was sampled and analyzed for nitrate concentration and isotopic composition (δ(15)N, δ(18)O, and Δ(17)O). From these measurements an average photolytic isotopic fractionation of (15)ɛ = (-15 ± 1.2)‰ was found for broadband Xe lamp photolysis. These results are due in part to excitation of the intense absorption band of nitrate around 200 nm in addition to the weaker band centered at 305 nm followed by photodissociation. An experiment with a filter blocking wavelengths shorter than 320 nm, approximating the actinic flux spectrum at Dome C, yielded a photolytic isotopic fractionation of (15)ɛ = (-47.9 ± 6.8)‰, in good agreement with fractionations determined by previous studies for the East Antarctic Plateau which range from -40 to -74.3‰. We describe a new semi-empirical zero point energy shift model used to derive the absorption cross sections of (14)NO3 (-) and (15)NO3 (-) in snow at a chosen temperature. The nitrogen isotopic fractionations obtained by applying this model under the experimental temperature as well as considering the

  9. Laboratory study of nitrate photolysis in Antarctic snow. II. Isotopic effects and wavelength dependence

    SciTech Connect

    Berhanu, Tesfaye A.; Erbland, Joseph; Savarino, Joël; Meusinger, Carl; Johnson, Matthew S.; Jost, Rémy; Bhattacharya, S. K.

    2014-06-28

    Atmospheric nitrate is preserved in Antarctic snow firn and ice. However, at low snow accumulation sites, post-depositional processes induced by sunlight obscure its interpretation. The goal of these studies (see also Paper I by Meusinger et al. [“Laboratory study of nitrate photolysis in Antarctic snow. I. Observed quantum yield, domain of photolysis, and secondary chemistry,” J. Chem. Phys. 140, 244305 (2014)]) is to characterize nitrate photochemistry and improve the interpretation of the nitrate ice core record. Naturally occurring stable isotopes in nitrate ({sup 15}N, {sup 17}O, and {sup 18}O) provide additional information concerning post-depositional processes. Here, we present results from studies of the wavelength-dependent isotope effects from photolysis of nitrate in a matrix of natural snow. Snow from Dome C, Antarctica was irradiated in selected wavelength regions using a Xe UV lamp and filters. The irradiated snow was sampled and analyzed for nitrate concentration and isotopic composition (δ{sup 15}N, δ{sup 18}O, and Δ{sup 17}O). From these measurements an average photolytic isotopic fractionation of {sup 15}ε = (−15 ± 1.2)‰ was found for broadband Xe lamp photolysis. These results are due in part to excitation of the intense absorption band of nitrate around 200 nm in addition to the weaker band centered at 305 nm followed by photodissociation. An experiment with a filter blocking wavelengths shorter than 320 nm, approximating the actinic flux spectrum at Dome C, yielded a photolytic isotopic fractionation of {sup 15}ε = (−47.9 ± 6.8)‰, in good agreement with fractionations determined by previous studies for the East Antarctic Plateau which range from −40 to −74.3‰. We describe a new semi-empirical zero point energy shift model used to derive the absorption cross sections of {sup 14}NO{sub 3}{sup −} and {sup 15}NO{sub 3}{sup −} in snow at a chosen temperature. The nitrogen isotopic fractionations obtained by applying

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. An iron snow dynamo explains Mercury's peculiar field

    NASA Astrophysics Data System (ADS)

    Christensen, U. R.; Wicht, J.

    2014-12-01

    The Messenger mission confirmed that Mercury's magnetic field is relatively weak and dominantly dipolar, but also showed the presence of a strong axial quadrupole term. This can be described equivalently by an offset of the dipole along the rotation axis. Furthermore, nonzonal field components could not be unambiguously identified. If Mercury's core contains more than a few percent of sulfur, crystallization may start at the core-mantle boundary rather than at the center. In the outer parts of the core iron snow would form, sink and remelt deeper down where it enriches the fluid in iron and drives compositional convection from above. The snow forming layer grows inward over time and a gradient in sulfur concentration develops which strongly stabilizes this layer against convective overturn. We study this scenario in MHD dynamo models. Aside from geodynamo-like dipolar solutions we find hemispherical dynamos. Here magnetic field is generated predominantly in either the the northern or the southern hemisphere. The axial dipole and axial quadrupole are of comparable strength at the upper boundary of the unstable dynamo region. Systematic studies show that the hemispherical solutions are favored by slow rotation and by a thick stable layer above the dynamo. A thick layer also axisymmetrizes and weakens the field at the boundary of the core. Mercury's observed dipole moment and the quadrupole-to-dipole ratio can approximately be matched by a hemispherical dynamo when the stable layer thickness exceeds half of the core radius.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  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. Chemical Imaging of the CO Snow Line in the HD 163296 Disk

    NASA Astrophysics Data System (ADS)

    Qi, Chunhua; Öberg, Karin I.; Andrews, Sean M.; Wilner, David J.; Bergin, Edwin A.; Hughes, A. Meredith; Hogherheijde, Michiel; D’Alessio, Paola

    2015-11-01

    The condensation fronts (snow lines) of H2O, CO, and other abundant volatiles in the midplane of a protoplanetary disk affect several aspects of planet formation. Locating the CO snow line, where the CO gas column density is expected to drop substantially, based solely on CO emission profiles, is challenging. This has prompted an exploration of chemical signatures of CO freeze-out. We present ALMA Cycle 1 observations of the N2H+ J = 3‑2 and DCO+ J = 4‑3 emission lines toward the disk around the Herbig Ae star HD 163296 at ∼0.″5 (60 AU) resolution, and evaluate their utility as tracers of the CO snow line location. The N2H+ emission is distributed in a ring with an inner radius at 90 AU, corresponding to a midplane temperature of 25 K. This result is consistent with a new analysis of optically thin C18O data, which implies a sharp drop in CO abundance at 90 AU. Thus N2H+ appears to be a robust tracer of the midplane CO snow line. The DCO+ emission also has a ring morphology, but neither the inner nor the outer radius coincide with the CO snow line location of 90 AU, indicative of a complex relationship between DCO+ emission and CO freeze-out in the disk midplane. Compared to TW Hya, CO freezes out at a higher temperature in the disk around HD 163296 (25 versus 17 K in the TW Hya disk), perhaps due to different ice compositions. This highlights the importance of actually measuring the CO snow line location, rather than assuming a constant CO freeze-out temperature for all disks.

  12. Eco-geochemical peculiarities of mercury content in solid residue of snow in the industrial enterprises impacted areas of Tomsk

    NASA Astrophysics Data System (ADS)

    Filimonenko, E. A.; Lyapina, E. E.; Talovskaya, A. V.; Parygina, I. A.

    2014-11-01

    Snow, as short-term consignation Wednesday, has several properties that lead to its widespread use in ecologicalgeochemical and geological research. By studying the chemical composition of the dust fallout you can indirectly assess the condition of atmospheric air.1-2. Determining the content of mercury in snow cover, you can define its contribution for the longest period of the year in our region, with the most intensive use of various types of fuel (coal, gas, firewood), that puts a strain on urban ecosystems in terms of ecology.3-4. In addition, snow cleans the atmosphere of mercury, but it accumulates in the snow, and during the spring melting of snow hits the ground and rivers, polluting them. Part of the mercury back into the atmosphere. It should also be note the special nature of the circulation of air masses over the city in winter, creating a heat CAP, which contributes to air pollution of the city. 5-6-7. The high load areas of industrial impact were detected during the eco-geochemical investigations of mercury load index in the impacted areas of enterprises of Tomsk. It was found out, that aerosol particles of industrial emissions in Tomsk contain mercury. The contamination transfer character of mercury sources and occurrence modes of pollutants in snow solid residue were detected during the researches of industrial impact.

  13. 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

  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. Composites

    NASA Astrophysics Data System (ADS)

    Taylor, John G.

    The Composites market is arguably the most challenging and profitable market for phenolic resins aside from electronics. The variety of products and processes encountered creates the challenges, and the demand for high performance in critical operations brings value. Phenolic composite materials are rendered into a wide range of components to supply a diverse and fragmented commercial base that includes customers in aerospace (Space Shuttle), aircraft (interiors and brakes), mass transit (interiors), defense (blast protection), marine, mine ducting, off-shore (ducts and grating) and infrastructure (architectural) to name a few. For example, phenolic resin is a critical adhesive in the manufacture of honeycomb sandwich panels. Various solvent and water based resins are described along with resin characteristics and the role of metal ions for enhanced thermal stability of the resin used to coat the honeycomb. Featured new developments include pultrusion of phenolic grating, success in RTM/VARTM fabricated parts, new ballistic developments for military vehicles and high char yield carbon-carbon composites along with many others. Additionally, global regional market resin volumes and sales are presented and compared with other thermosetting resin systems.

  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.

  7. The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

    NASA Technical Reports Server (NTRS)

    Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

    2006-01-01

    Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

  8. [Hydrochemical Characteristics of Snow Meltwater and River Water During Snow-melting Period in the Headwaters of the Ertis River, Xinjiang].

    PubMed

    Wei, Hong; Wu, Jin-kui; Shen, Yong-ping; Zhang, Wei; Liu, Shi-wei; Zhou, Jia-xin

    2016-04-15

    To analyze the hydrochemical characteristics of river water and snow meltwater during snow-melting period in the Kayiertesi River, the headwaters of the Ertis River, samples of river water and meltwater were collected every day during March and April, 2014. Furthermore, the combination of descriptive statistics, Gibbs Figure and Piper Triangular diagrams of anions and cations were used for hydrochemical analyses. The results showed that the major ion compositions and hydrochemical types were significantly different between river water and snow meltwater. The total dissolved solid (TDS) in the river water ranged from 24.9 to 50.3 mg · L⁻¹. The major cations of river water were Ca²⁺ and Na⁺, accounting for 61% and 17% of the total cation equivalent concentration, respectively. Meanwhile, HCO₃⁻ constituted about 95% of the total anions concentration. The hydrochemical type of river water was HCO₃⁻-Ca²⁺. The chemical composition of river water samples located in the middle with a deviation to left of Gibbs model, indicating that the major chemical process of river water was controlled by rock weath ring and precipitation but rock weathering played a more important role. PMID:27548955

  9. Stereological characterization of dry alpine snow for microwave remote sensing

    NASA Technical Reports Server (NTRS)

    Davis, Robert E.; Dozier, Jeff

    1989-01-01

    A persistent problem in investigations of electromagnetic properties of snow, from reflectance at visible wavelengths to emission and backscattering in the microwave, has been the proper characterization of the snow's physical properties. It is suggested that the granular and laminar structure of snow can be measured in its aggregated state by stereology performed on sections prepared from snow specimens, and that these kinds of measurements can be incorporated into models of the electromagnetic properties. With careful sampling, anisotropy in the snow microstructure at various scales can be quantified. It is shown how stereological parameters can be averaged over orientation and optical depth for radiative transfer modeling.

  10. Use of supplemental food by breeding Ross's Geese and Lesser Snow Geese: Evidence for variable anorexia

    USGS Publications Warehouse

    Gloutney, M.L.; Alisauskas, R.T.; Hobson, K.A.; Afton, A.D.

    1999-01-01

    Recent research suggests that foods eaten during laying and incubation play a greater role in supplying energy and nutrients to arctic-nesting geese than previously believed. We conducted food-supplementation experiments with Ross's Geese (Chen rossii) and Lesser Snow Geese (C. caerulescens) geese to evaluate: (1) if supplemental food was consumed by laying and incubating geese, (2) how food consumption influenced mass dynamics of somatic tissues of breeding geese, (3) if patterns of mass loss were consistent with fasting adaptations, and (4) whether energetic constraints would cause smaller Ross's Geese to consume more food relative to their body size than would larger Snow Geese. Quantity of supplemental food eaten by both species during laying and incubation was highly variable among individuals. Consumption of supplemental food during laying resulted in differences in overall body composition between control and treatment females. Treatment female Ross's Geese completed laying at a higher mass and with more abdominal fat than controls, whereas treatment female Snow Geese completed laying with heavier breast muscles and hearts. Overall body composition did not differ between control and treatment geese (both sexes and species) at the end of incubation, but treatment geese had heavier hearts than control geese. This suggests that treatment females did not rely to the same extent on metabolic adaptations associated with anorexia to meet energetic costs of incubation as did controls. Stable-nitrogen isotope analysis revealed patterns of protein maintenance during incubation consistent with metabolic adaptations to prolonged fasting. Our prediction that energetic constraints would cause smaller Ross's Geese to consume more food relative to their size than would Snow Geese was not supported. Mass-specific food consumption by Ross's Geese was 30% lower than that of Snow Geese during laying and 48% higher during incubation.

  11. Snow Peak, Oregon: Latest Miocene low-K tholeiite volcanism in the Cascadia forearc

    NASA Astrophysics Data System (ADS)

    Hatfield, A. K.; Nielsen, R. L.; Kent, A. J. R.; Rowe, M. C.; Duncan, R. A.

    2015-12-01

    Snow Peak, Oregon, is a moderate size basaltic shield volcano (50-52 wt.% SiO2, > 7.4 km3) located within the forearc of the Cascadia subduction zone, ~ 50 km west of the current arc front. Herein we present new whole rock geochemistry, mineral chemistry and 11 new 40Ar/39Ar ages, together with petrologic modeling that allow us to constrain the timing and origin of volcanism. In contrast to previous K-Ar ages that suggested volcanism occurred at ~ 3 Ma, our new 40Ar/39Ar ages show that Snow Peak formed between 5.3 and 6 million years ago. The volcano lies unconformably on ~ 30 Ma volcanic rocks of the Western Cascades. Volcanism occurred over a total duration of < 0.5-1 Ma, and at eruption rates (~ 0.008-0.013 km3/ka), lower than those observed in large Cascade shield volcanoes. Snow Peak lavas derived from a single, or restricted set of primary magma compositions and evolved via crystal fractionation of olivine + pyroxene + plagioclase over a range of pressures equivalent to crustal depths of ~ 3-35 km, consistent with fractionation occurring primarily during crustal transit or residence. The most evolved Snow Peak lava can be produced by ~ 50% crystallization from a primary magma with > 14 wt.% MgO. Snow Peak lavas have trace element characteristics transitional between the calc-alkaline basalt (CAB) and low-K tholeiite (LKT) primary magma types recognized throughout the Cascade Range, but are closer to LKT and are classified as such. Estimates based on phase equilibria models and plagioclase hygrometers suggest that the primary magmas contained moderate amounts of water (1.5-2 wt.%), consistent with LILE/HFSE ratios that are greater than MORB values. Snow Peak is part of a widespread suite of LKT magmas that erupted between 5-8 Ma throughout the central Oregon Cascade Range in response to intra-arc rifting, and Snow Peak shows that LKT magmatism at this time extended well into the forearc of the central Oregon Cascade Range. Overall LKT magmas of this age occur

  12. Validation of the Snow Submodel of the Biosphere-Atmosphere Transfer Scheme with Russian Snow Cover and Meteorological Observational Data.

    NASA Astrophysics Data System (ADS)

    Yang, Zong-Liang; Dickinson, Robert E.; Robock, Alan; Vinnikov, K. Ya.

    1997-02-01

    Snow cover is one of the most important variables affecting agriculture, hydrology, and climate, but detailed measurements are not widely available. Therefore, the effectiveness and validity of snow schemes in general circulation models have been difficult to assess. Using long-term snow cover data from the former Soviet Union, this paper focuses on the validation of the snow submodel in the Biosphere-Atmosphere Transfer Scheme (BATS) using 6 years of data (1978-83) at six stations. Fundamental uncertainties in the datasets limit the accuracy of our assessment of the model's performance.In the absence of a wind correction for the gauge-measured precipitation and with the standard rain-snow transition criterion (2.2°C), the model gives reasonable simulations of snow water equivalent and surface temperature for all of the six stations and the six winters examined. In particular, the time of accumulation and the end of ablation and the alteration due to aging are well captured. With some simple modifications of the code, the model can also reproduce snow depth, snow cover fraction, and surface albedo. In view of the scheme's simplicity and efficiency, these results are encouraging.However, if a wind correction is applied to the gauge-measured precipitation, the model shows increased root-mean-square errors in snow water equivalent for all six stations except Tulun. Perhaps, the better agreement without wind correction means that the snow has blown beyond the area of snow measurement, as might be accounted for only by a detailed regional snow-wind distribution model.This study underlines four aspects that warrant special attention: (i) estimation of the downward longwave radiation, (ii) separation of the aging processes for snowpack density and snow surface albedo, (iii) parameterization of snow cover fraction, and (iv) choice of critical temperature for rain-snow transition.

  13. Rain-on-snow events in the western United States

    USGS Publications Warehouse

    McCabe, G.J.; Clark, M.P.; Hay, L.E.

    2007-01-01

    Rain-on-snow events pose a significant flood hazard in the western United States. This study provides a description of the spatial and temporal variability of the frequency of rain-on-snow events for 4318 sites in the western United States during water years (October through September) 1949-2003. Rain-on-snow events are found to be most common during the months of October through May; however, at sites in the interior western United States, rain-on-snow events can occur in substantial numbers as late as June and as early as September. An examination of the temporal variability of October through May rain-on-snow events indicates a mixture of increasing and decreasing trends in rain-on-snow events across the western United States. Decreasing trends in rain-on-snow events are most pronounced at lower elevations and are associated with trends toward fewer snowfall days and fewer precipitation days with snow on the ground. Rain-on-snow events are more (less) frequent in the northwestern (southwestern) United States during La Nin??a (El Nin??o) conditions. Additionally, increases in temperature in the western United States appear to be contributing to decreases in the number of rain-on-snow events for many sites through effects on the number of days with snowfall and the number of days with snow on the ground. ?? 2007 American Meteorological Society.

  14. Experimental investigation of drifting snow in a wind tunnel

    NASA Astrophysics Data System (ADS)

    Crivelli, Philip; Paterna, Enrico; Horender, Stefan; Lehning, Michael

    2015-11-01

    Drifting snow has a significant impact on snow distribution in mountains, prairies as well as on glaciers and polar regions. In all these environments, the local mass balance is highly influenced by drifting snow. Despite most of the model approaches still rely on the assumption of steady-state and equilibrium saltation, recent advances have proven the mass-transport of drifting snow events to be highly intermittent. A clear understanding of such high intermittency has not yet been achieved. Therefore in our contribution we investigate mass- and momentum fluxes during drifting snow events, in order to better understand that the link between snow cover erosion and deposition. Experiments were conducted in a cold wind tunnel, employing sensors for the momentum flux measurements, the mass flux measurement and for the snow depth estimation over a certain area upstream of the other devices. Preliminary results show that the mass flux is highly intermittent at scales ranging from eddy turnover time to much larger scales. The former scales are those that contribute the most to the overall intermittency and we observe a link between the turbulent flow structures and the mass flux of drifting snow at those scales. The role of varying snow properties in inducing drifting snow intermittency goes beyond such link and is expected to occur at much larger scales, caused by the physical snow properties such as density and cohesiveness.

  15. Spatial variability of snow physical properties across northwestern Greenland

    NASA Astrophysics Data System (ADS)

    Courville, Z.; Polashenski, C.; Dibb, J. E.; Domine, F.

    2013-12-01

    In the late spring and early summer of 2013, researchers on the SAGE (Sunlight Absorption on the Greenland ice sheet Experiment) Traverse, embarked on a 4000 km ground traverse across northwestern Greenland in an attempt to quantify spatial variability of snow chemistry, snow physical properties, and snow reflectance. The field team targeted sites first visited by Carl Benson during his series of traverses from 1952 to 1955 as part of his pioneering work to characterize the Greenland Ice Sheet. This route now represents a rapidly changing and variable area of Greenland, as the route passes through several of the ice sheet facies first delimited by Benson. Along the traverse, the SAGE field team made ground-based albedo measurements using a hand-held spectroradiometer and collected snow physical property samples to determine snow specific surface area (SSA) from shallow, 2m pits. In addition, snow density and stratigraphy were measured. Snow layers in the near-surface and at the previous season's melt layer were targeted for sampling. Here we present preliminary snow physical property results from the upper portion of the snow pits and relate these to surface albedo data collected over the route. Further measurements of snow properties in the 2012 melt layer will be analyzed to assess the potential role of snow chemical (see Dibb et al. for a discussion of chemical analysis) and physical property driven albedo feedbacks could have played in contributing to that event. Route of 2013 SAGE Traverse in northwestern Greenland.

  16. 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.

  17. Albedo reduction by dirty snow: measurements and implications

    NASA Astrophysics Data System (ADS)

    Zender, C. S.; Gallet, J.; Domine, F.; Picard, G.

    2008-12-01

    Industrial and biomass burning emissions of black carbon (BC) from low- and mid-latitudes dominate the radiative forcing by absorbing impurities trapped in snow and ice at mid- and high- northern latitudes. Correct model representation of albedo reduction by BC-contaminated snow is crucial because our GCM simulations show that dirty snow can explain about 30% of the observed 20th century Arctic warming. Until now, measurements of actual snow darkening by BC have been attempted only in the field, under non- reproducible conditions, and limited to the environmental BC concentration. We have conducted the first measurements of the direct effect of BC-contamination on snow albedo by in a controlled environment. We doped natural snow with a commercially available BC-analogue and measured the resulting albedo change at visible and near-infrared wavelengths. Snow albedo was measured in a (portable) integrating sphere system. Snow grain size is estimated from the near-infrared albedo. Snow density, temperature, and BC properties were known a priori. The albedo measurement reproducibility is about 1% for natural snow. Our measurements agree with model predictions that BC concentrations from 250 ppbm to 200 ppmm darken snow albedo by 1--70%. Our results lend confidence to the current model representations of surface darkening in the cryosphere. Applying these methods to impurity records in polar ice cores yields surface radiative forcing estimates that can be extrapolated to regional scales.

  18. 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.

  19. Objective Characterization of Snow Microstructure for Microwave Emission Modeling

    NASA Technical Reports Server (NTRS)

    Durand, Michael; Kim, Edward J.; Molotch, Noah P.; Margulis, Steven A.; Courville, Zoe; Malzler, Christian

    2012-01-01

    Passive microwave (PM) measurements are sensitive to the presence and quantity of snow, a fact that has long been used to monitor snowcover from space. In order to estimate total snow water equivalent (SWE) within PM footprints (on the order of approx 100 sq km), it is prerequisite to understand snow microwave emission at the point scale and how microwave radiation integrates spatially; the former is the topic of this paper. Snow microstructure is one of the fundamental controls on the propagation of microwave radiation through snow. Our goal in this study is to evaluate the prospects for driving the Microwave Emission Model of Layered Snowpacks with objective measurements of snow specific surface area to reproduce measured brightness temperatures when forced with objective measurements of snow specific surface area (S). This eliminates the need to treat the grain size as a free-fit parameter.

  20. Simulations of snow distribution and hydrology in a mountain basin

    USGS Publications Warehouse

    Hartman, M.D.; Baron, J.S.; Lammers, R.B.; Cline, D.W.; Band, L.E.; Liston, G.E.; Tague, C.

    1999-01-01

    We applied a version of the Regional Hydro-Ecologic Simulation System (RHESSys) that implements snow redistribution, elevation partitioning, and wind-driven sublimation to Loch Vale Watershed (LVWS), an alpine-subalpine Rocky Mountain catchment where snow accumulation and ablation dominate the hydrologic cycle. We compared simulated discharge to measured discharge and the simulated snow distribution to photogrammetrically rectified aerial (remotely sensed) images. Snow redistribution was governed by a topographic similarity index. We subdivided each hillslope into elevation bands that had homogeneous climate extrapolated from observed climate. We created a distributed wind speed field that was used in conjunction with daily measured wind speeds to estimate sublimation. Modeling snow redistribution was critical to estimating the timing and magnitude of discharge. Incorporating elevation partitioning improved estimated timing of discharge but did not improve patterns of snow cover since wind was the dominant controller of areal snow patterns. Simulating wind-driven sublimation was necessary to predict moisture losses.

  1. Instrumentation for Evaluating PV System Performance Losses from Snow

    SciTech Connect

    Marion, B.; Rodriguez, J.; Pruett, J.

    2009-01-01

    When designing a photovoltaic (PV) system for northern climates, the prospective installation should be evaluated with respect to the potentially detrimental effects of snow preventing solar radiation from reaching the PV cells. The extent to which snow impacts performance is difficult to determine because snow events also increase the uncertainty of the solar radiation measurement, and the presence of snow needs to be distinguished from other events that can affect performance. This paper describes two instruments useful for evaluating PV system performance losses from the presence of snow: (1) a pyranometer with a heater to prevent buildup of ice and snow, and (2) a digital camera for remote retrieval of images to determine the presence of snow on the PV array.

  2. Composites

    NASA Astrophysics Data System (ADS)

    Chmielewski, M.; Nosewicz, S.; Pietrzak, K.; Rojek, J.; Strojny-Nędza, A.; Mackiewicz, S.; Dutkiewicz, J.

    2014-11-01

    It is commonly known that the properties of sintered materials are strongly related to technological conditions of the densification process. This paper shows the sintering behavior of a NiAl-Al2O3 composite, and its individual components sintered separately. Each kind of material was processed via the powder metallurgy route (hot pressing). The progress of sintering at different stages of the process was tested. Changes in the microstructure were examined using scanning and transmission electron microscopy. Metal-ceramics interface was clean and no additional phases were detected. Correlation between the microstructure, density, and mechanical properties of the sintered materials was analyzed. The values of elastic constants of NiAl/Al2O3 were close to intermetallic ones due to the volume content of the NiAl phase particularly at low densities, where small alumina particles had no impact on the composite's stiffness. The influence of the external pressure of 30 MPa seemed crucial for obtaining satisfactory stiffness for three kinds of the studied materials which were characterized by a high dense microstructure with a low number of isolated spherical pores.

  3. Winter climate extremes and their role for priming SOM decomposition under the snow

    NASA Astrophysics Data System (ADS)

    Gavazov, Konstantin; Bahn, Michael

    2015-04-01

    The central research question of this project is how soil respiration and soil microbial community composition and activity of subalpine grasslands are affected by extreme winter climate events, such as mid-winter snowmelt and subsequent advanced growing season date. In the scope of this talk, focus will be laid on the assumptions that (1) reduced snow cover leads to intensive freeze-thaw cycles in the soil with larger amplitudes of microbial biomass, DOC and soil CO2 production and efflux over the course of winter, and shifts peak microbial activity to deeper soil layers with limited and recalcitrant substrate; (2) causes a shift in microbial community composition towards decreased fungal/bacterial ratios; and (3) results in a stronger incorporation of labile C in microbial biomass and more pronounced priming effects of soil organic matter turnover. Our findings indicate that snow removal, induces a strong and immediate negative effect on the physiology of soil microbes, impairing them in their capacity for turnover of SOM in the presence of labile substances (priming). This effect however is transient and soil microbes recover within the same winter. The reason for that is that snow removal did not produce any measurable (PLFA) changes in soil microbial community composition. The advanced start of the growing season, as a result of snow removal in mid-winter, granted the bacterial part of the microbial community more active in the uptake of labile substrates and the turnover of SOM than the fungal one. This finding is in line with the concept for a seasonal shift towards bacterial-dominated summer microbial community composition and could bring about implications for the plant-microbe competition for resources at the onset of the growing season.

  4. 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

  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. Snow and Vegetation Interactions at Boundaries in Alaska's Boreal Forest

    NASA Astrophysics Data System (ADS)

    Hiemstra, C. A.; Sturm, M.

    2012-12-01

    There has been increased attention on snow-vegetation interactions in Arctic tundra because of rapid climate-driven changes affecting that snow-dominated ecosystem. Yet, far less attention is paid to boreal forest snow-vegetation interactions even though climatic conditions are changing there as well. Further, it is the prevalent terrestrial biome on the planet. The forest is a variable patchwork of trees, shrubs, grasses, and forbs shaped by wind, fire, topography, water drainage, and permafrost. These patches and their boundaries have a corresponding effect on boreal snow distributions; however, measurements characterizing boreal snow are sparse and focus within patches (vs. between patches). Unfortunately, remote sensing approaches in such forested areas frequently fall short due to coarse footprint size and dense canopy cover. Over the last several years we have been examining the characteristics of snow cover within and across boundaries in the boreal forest, seeking to identify gradients in snow depth due to snow-vegetation interactions as well identifying methods whereby boreal forest surveys could be improved. Specifically, we collected end-of-season snow measurements in the Alaska boreal forest during long-distance traverses in the Tanana Basin in 2010 (26 sites) and within the Yukon Flats National Wildlife Refuge in 2011 (26 sites). At each site (all relatively flat), hundreds of snow depths were collected using a GPS-equipped Magnaprobe, which is an automated tool for measuring and locating individual snow depths. Corresponding canopy properties included NDVI determined from high-resolution satellite imagery; canopy properties were variable among the 1ha sites and some areas had recently burned. Among sites, NDVI had the largest correlation with snow depths; elevation was not significant. Vegetation transition zones play important roles in explaining observed snow depth. Similar to treeline work showing nutrient and energy gradients are influenced by

  7. Snow bedforms: A review, new data, and a formation model

    NASA Astrophysics Data System (ADS)

    Filhol, Simon; Sturm, Matthew

    2015-09-01

    Snow bedforms, like sand bedforms, consist of various shapes that form under the action of wind on mobile particles. Throughout a year, they can cover up to 11% of the Earth surface, concentrated toward the poles. These forms impact the local surface energy balance and the distribution of precipitation. Only a few studies have concentrated on their genesis. Their size ranges from 2 cm (ripple marks) to 2.5 m tall (whaleback dunes). We counted a total of seven forms that are widely recognized. Among them sastrugi, an erosional shape, is the most widespread. From laser scans, we compared scaling of snow versus sand barchan morphology. We found that both have proportionally the same footprint, but snow barchans are flatter. The key difference is that snow can sinter, immobilizing the bedform and creating an erodible material. Using a model, we investigated the effect of sintering on snow dune dynamics. We found that sintering limits their size because it progressively hardens the snow and requires an ever-increasing wind speed to maintain snow transport. From the literature and results from this model, we have reclassified snow bedforms based on two parameters: wind speed and snow surface conditions. The new data show that snow dune behavior mirrors that of sand dunes, with merging, calving, and collision. However, isolated snow barchans are rare, with most of the snow surfaces encountered in the field consisting of several superimposed bedforms formed sequentially during multiple weather events. Spatially variable snow properties and geometry can explain qualitatively these widespread compound snow surfaces.

  8. A probabilistic model for snow avalanche occurrence

    NASA Astrophysics Data System (ADS)

    Perona, P.; Miescher, A.; Porporato, A.

    2009-04-01

    Avalanche hazard forecasting is an important issue in relation to the protection of urbanized environments, ski resorts and of ski-touring alpinists. A critical point is to predict the conditions that trigger the snow mass instability determining the onset and the size of avalanches. On steep terrains the risk of avalanches is known to be related to preceding consistent snowfall events and to subsequent changes in the local climatic conditions. Regression analysis has shown that avalanche occurrence indeed correlates to the amount of snow fallen in consecutive three snowing days and to the state of the settled snow at the ground. Moreover, since different type of avalanches may occur as a result of the interactions of different factors, the process of snow avalanche formation is inherently complex and with some degree of unpredictability. For this reason, although several models assess the risk of avalanche by accounting for all the involved processes with a great detail, a high margin of uncertainty invariably remains. In this work, we explicitly describe such an unpredictable behaviour with an intrinsic noise affecting the processes leading snow instability. Eventually, this sets the basis for a minimalist stochastic model, which allows us to investigate the avalanche dynamics and its statistical properties. We employ a continuous time process with stochastic jumps (snowfalls), deterministic decay (snowmelt and compaction) and state dependent avalanche occurrence (renewals) as a minimalist model for the determination of avalanche size and related intertime occurrence. The physics leading to avalanches is simplified to the extent where only meteorological data and terrain data are necessary to estimate avalanche danger. We explore the analytical formulation of the process and the properties of the probability density function of the avalanche process variables. We also discuss what is the probabilistic link between avalanche size and preceding snowfall event and

  9. 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

  10. Brown snow: A long-range transport event in the Canadian Arctic

    SciTech Connect

    Welch, H.E.; Muir, D.C.G.; Billeck, B.N.; Lockhart, W.L.; Brunskill, G.J.; Kling, H.J. ); Olson, M.P. ); Lemoine, R.M. )

    1991-02-01

    The authors document the occurrence of a long-range transport event that deposited thousands of tons of fine particulates on the District of Keewatin, central Canadian Arctic, {approximately}63 N. Air mass trajectories, clay mineral composition, soot particles, and visible organic remains point to Asian sources for the brown snow material, probably western China. Semivolatile organic pollutants detected in the brown snow included polycyclic aromatic hydrocarbons ({Sigma}PAH), PCB congeners, and DDT-related compounds ({Sigma}DDT), polychlorinated camphenes (PCCs), as well as the herbicide trifuluralin and insecticides methoxychlor, endosulfan, and hexachlorocyclohexane (HCH). {Sigma}PAH, PCB, and PCC concentrations were within the range reported in other studies of Arctic snow but {Sigma}DDT levels were 2-10 times higher than previous reports. High molecular weight PAH may have been associated with soot particles in the brown snow but evidence for Asian sources of the pesticides was not strong because of unknown source signal strengths and possible atmospheric transformations of the compounds. Fluxes of these pollutants were also determined by analyzing sediment cores from two small headwater lakes near the sampling site. The quantities of pollutants deposited in this single event may have comprised a significant fraction (>10%) of total annual input {Sigma}PAH and {Sigma}DDT, as determined from lake sedimentation records.

  11. Chemical Atmosphere-Snow-Sea Ice Interactions: defining future research in the field, lab and modeling

    NASA Astrophysics Data System (ADS)

    Frey, Markus

    2015-04-01

    The air-snow-sea ice system plays an important role in the global cycling of nitrogen, halogens, trace metals or carbon, including greenhouse gases (e.g. CO2 air-sea flux), and therefore influences also climate. Its impact on atmospheric composition is illustrated for example by dramatic ozone and mercury depletion events which occur within or close to the sea ice zone (SIZ) mostly during polar spring and are catalysed by halogens released from SIZ ice, snow or aerosol. Recent field campaigns in the high Arctic (e.g. BROMEX, OASIS) and Antarctic (Weddell sea cruises) highlight the importance of snow on sea ice as a chemical reservoir and reactor, even during polar night. However, many processes, participating chemical species and their interactions are still poorly understood and/or lack any representation in current models. Furthermore, recent lab studies provide a lot of detail on the chemical environment and processes but need to be integrated much better to improve our understanding of a rapidly changing natural environment. During a 3-day workshop held in Cambridge/UK in October 2013 more than 60 scientists from 15 countries who work on the physics, chemistry or biology of the atmosphere-snow-sea ice system discussed research status and challenges, which need to be addressed in the near future. In this presentation I will give a summary of the main research questions identified during this workshop as well as ways forward to answer them through a community-based interdisciplinary approach.

  12. Snow-melt Runoff Simulation for Dam Reservoir in the Heavy Snow Region

    NASA Astrophysics Data System (ADS)

    Sato, Yoshinobu; Murai, Akihiro; Sumi, Tetsuya

    2014-05-01

    Increases in land surface temperature will have a significant affect on the hydrological cycle, particularly in regions where the available water resources are mainly dominated by the melting snow or ice. Thus, to clarify the impact of climate change on river discharge in cold and mountainous region is becoming one of the urgent issues for policy making and planning for the integrated river water management under the inevitable warming climate. However, in order to study climate change impacts on water resources in the heavy snow region, snow-melt runoff simulation for dam reservoir should be improved. Because, the available meteorological data for runoff simulation is quite limited, especially in a mountainous regions in Japan. In this study, we analyzed the inflow into the Okutadami Dam in the Agano River basin located in the northern mountainous region in Japan by a distributed hydrological model (Hydro-BEAM: Hydrological river Basin Environment Assessment Model). The Okutadami dam has an important role as one of the largest hydro-power generation dam in Japan. The result of our initial simulation underestimated the inflow significantly, especially in snow melting season, because of small input precipitation. We firstly modified the input precipitation by the JMA (Japan Meteorological Agency)'s climatic value 2010 (monthly 1km2 averaged mesh based precipitation dataset during the period from 1981 to 2010). Due to the modification, simulated annual mean river discharge (water balance) was improved significantly. Secondly, we modified the threshold temperature which distinguishes rainfall and snowfall improved the reproducibility slightly. Lastly, we modified the monthly discharge variation (seasonal change pattern) in snow melting period by considering the effect of heat supply by rainfall on snow surface layer. Consequently, we found that the calculated inflow to the Okutadami dam agreed well the observation. These methods will contribute to clarify the

  13. Snow specific surface area simulation using the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS)

    NASA Astrophysics Data System (ADS)

    Roy, A.; Royer, A.; Montpetit, B.; Bartlett, P. A.; Langlois, A.

    2012-12-01

    Snow grain size is a key parameter for modeling microwave snow emission properties and the surface energy balance because of its influence on the snow albedo, thermal conductivity and diffusivity. A model of the specific surface area (SSA) of snow was implemented in the one-layer snow model in the Canadian LAnd Surface Scheme (CLASS) version 3.4. This offline multilayer model (CLASS-SSA) simulates the decrease of SSA based on snow age, snow temperature and the temperature gradient under dry snow conditions, whereas it considers the liquid water content for wet snow metamorphism. We compare the model with ground-based measurements from several sites (alpine, Arctic and sub-Arctic) with different types of snow. The model provides simulated SSA in good agreement with measurements with an overall point-to-point comparison RMSE of 8.1 m2 kg-1, and a RMSE of 4.9 m2 kg-1 for the snowpack average SSA. The model, however, is limited under wet conditions due to the single-layer nature of the CLASS model, leading to a single liquid water content value for the whole snowpack. The SSA simulations are of great interest for satellite passive microwave brightness temperature assimilations, snow mass balance retrievals and surface energy balance calculations with associated climate feedbacks.

  14. 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.

  15. Blowing Snow - A Major Source of Aerosol in the Polar Regions?

    NASA Astrophysics Data System (ADS)

    Kalnajs, L.; DeCarlo, P. F.; Giordano, M.; Davis, S. M.; Deshler, T.; Johnson, A.; Goetz, J. D.; Mukherjee, A. D.; Slater, A. G.

    2015-12-01

    Sea salt aerosol is the dominant aerosol component in unpolluted Polar Regions, particularly in the sea ice zone. In the lower latitude liquid ocean, wave action and bubble bursting is thought to be the main mechanism for sea salt aerosol production. However there is growing evidence that in the Polar Regions, particularly near sea ice, that the sublimation of wind lofted salty snow may be a dominant source of sea salt aerosol. An extensive set of aerosol sizing and compositional measurements was made at sea ice location near Ross Island, Antarctica during two field measurement campaigns - a summer campaign in 2014 and late winter campaign in 2015. Sizing measurements from both open and closed path aerosol instruments, and compositional measurements from an Aerosol Mass Spectrometer suggest that there is a significant enhancement in both super and sub micron aerosol associated with high wind events and blowing snow in the boundary layer. While the composition of this aerosol indicates that it is primarily of marine origin, the ratios of the major sea salt ions suggest that processing in the snow pack significantly modifies the aerosol. This alternate sea salt aerosol production mechanism could have significant impact on the modeling of tropospheric halogen chemistry and on the interpretation of sea salt-based proxies in the ice core record.

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

    PubMed

    Zhang, Xinyue; Wang, Wei; Chen, Weile; Zhang, Naili; Zeng, Hui

    2014-01-01

    More than half of the earth's terrestrial surface currently experiences seasonal snow cover and soil frost. Winter compositional and functional investigations in soil microbial community are frequently conducted in alpine tundra and boreal forest ecosystems. However, little information on winter microbial biogeochemistry is known from seasonally snow-covered temperate ecosystems. As decomposer microbes may differ in their ability/strategy to efficiently use soil organic carbon (SOC) within different phases of the year, understanding seasonal microbial process will increase our knowledge of biogeochemical cycling from the aspect of decomposition rates and corresponding nutrient dynamics. In this study, we measured soil microbial biomass, community composition and potential SOC mineralization rates in winter and summer, from six temperate ecosystems in northern China. Our results showed a clear pattern of increased microbial biomass C to nitrogen (N) ratio in most winter soils. Concurrently, a shift in soil microbial community composition occurred with higher fungal to bacterial biomass ratio and gram negative (G-) to gram positive (G+) bacterial biomass ratio in winter than in summer. Furthermore, potential SOC mineralization rate was higher in winter than in summer. Our study demonstrated a distinct transition of microbial community structure and function from winter to summer in temperate snow-covered ecosystems. Microbial N immobilization in winter may not be the major contributor for plant growth in the following spring. PMID:24667929

  17. LANDSAT-D investigations in snow hydrology. [Sierra Nevada Mountains

    NASA Technical Reports Server (NTRS)

    Dozier, J.

    1983-01-01

    Thematic mapper data for the southern Sierra Nevada area were registered to digital topographic data and compared to LANDSAT MSS and NOAA-7 AVHRR data of snow covered areas in order to determine the errors associated with using coarser resolution and to qualify the information lost when high resolution data are not available. Both the zenith and the azimuth variations in the radiative field are considered in an atmospheric radiative transfer model which deals with a plane parallel structured atmosphere composed of different layers, each assumed to be homogeneous in composition and to have a linear in tau temperature profile. Astronomical parameters for each layer are Earth-Sun distance and solar flux at the top of the atmosphere. Atmospheric parameters include pressure temperature, chemical composition of the air molecules, and the composition and size of the aerosol, water droplets, and ice crystals. Outputs of the model are the monochromatic radiance and irradiance at each level. The use of the model in atmospheric correction of remotely sensed data is discussed.

  18. Role of snow cover on urban heat island intensity investigated by urban canopy model with snow effects

    NASA Astrophysics Data System (ADS)

    Sato, T.; Mori, K.

    2015-12-01

    Urban heat islands have been investigated around the world including snowy regions. However, the relationship between urban heat island and snow cover remains unclear. This study examined the effect of snow cover in urban canopy on energy budget in urban areas of Sapporo, north Japan by 1km mesh WRF experiments. The modified urban canopy model permits snow cover in urban canopy by the modification of surface albedo, surface emissivity, and thermal conductivity for roof and road according to snow depth and snow water equivalent. The experiments revealed that snow cover in urban canopy decreases urban air temperature more strongly for daily maximum temperature (0.4-0.6 K) than for daily minimum temperature (0.1-0.3 K). The high snow albedo reduces the net radiation at building roof, leading to decrease in sensible heat flux. Interestingly, the cooling effect of snow cover compensates the warming effect by anthropogenic heat release in Sapporo, suggesting the importance of snow cover treatment in urban canopy model as well as estimating accurate anthropogenic heat distributions. In addition, the effect of road snow clearance tends to increase nocturnal surface air temperature in urban areas. A possible role of snow cover on urban heat island intensity was evaluated by two experiments with snow cover (i.e., realistic condition) and without snow cover in entire numerical domain. The snow cover decreases surface air temperature more in rural areas than in urban areas, which was commonly seen throughout a day, with stronger magnitude during nighttime than daytime, resulting in intensifying urban heat island by 4.0 K for daily minimum temperature.

  19. Microwave Remote Sensing of Falling Snow

    NASA Technical Reports Server (NTRS)

    Kim, Min-Jeong; Wang, J. R.; Meneghini, R.; Johnson, B.; Tanelli, S.; Roman-Nieves, J. I.; Sekelsky, S. M.; Skofronick-Jackson, G.

    2005-01-01

    This study analyzes passive and active microwave measurements during the 2003 Wakasa Bay field experiment for understanding of the electromagnetic characteristics of frozen hydrometeors at millimeter-wave frequencies. Based on these understandings, parameterizations of the electromagnetic scattering properties of snow at millimeter-wave frequencies are developed and applied to the hydrometeor profiles obtained by airborne radar measurements. Calculated brightness temperatures and radar reflectivity are compared with the millimeter-wave measurements.

  20. Character change of New England snow

    USGS Publications Warehouse

    Huntington, T.G.; Hodgkins, G.A.; Keim, B.D.; Dudley, R.W.

    2004-01-01

    The annual ratio of snow to total precipitation (S/P) for 11 out of 21 US Historical Climatology Network (USHCN) sites in New England decreased significantly from 1949 through 2000. One possible explanation for the observed decrease in S/P ratio is that their temperature increased in New England during the 20th century. The results are consistent with published reports indicating lengthening of the growing season in New England.

  1. 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

  2. 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

  3. Intercomparison of Satellite-Derived Snow-Cover Maps

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Tait, Andrew B.; Foster, James L.; Chang, Alfred T. C.; Allen, Milan

    1999-01-01

    In anticipation of the launch of the Earth Observing System (EOS) Terra, and the PM-1 spacecraft in 1999 and 2000, respectively, efforts are ongoing to determine errors of satellite-derived snow-cover maps. EOS Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer-E (AMSR-E) snow-cover products will be produced. For this study we compare snow maps covering the same study area acquired from different sensors using different snow- mapping algorithms. Four locations are studied: 1) southern Saskatchewan; 2) a part of New England (New Hampshire, Vermont and Massachusetts) and eastern New York; 3) central Idaho and western Montana; and 4) parts of North and South Dakota. Snow maps were produced using a prototype MODIS snow-mapping algorithm used on Landsat Thematic Mapper (TM) scenes of each study area at 30-m and when the TM data were degraded to 1 -km resolution. National Operational Hydrologic Remote Sensing Center (NOHRSC) 1 -km resolution snow maps were also used, as were snow maps derived from 1/2 deg. x 1/2 deg. resolution Special Sensor Microwave Imager (SSM/1) data. A land-cover map derived from the International Geosphere-Biosphere Program (IGBP) land-cover map of North America was also registered to the scenes. The TM, NOHRSC and SSM/I snow maps, and land-cover maps were compared digitally. In most cases, TM-derived maps show less snow cover than the NOHRSC and SSM/I maps because areas of incomplete snow cover in forests (e.g., tree canopies, branches and trunks) are seen in the TM data, but not in the coarser-resolution maps. The snow maps generally agree with respect to the spatial variability of the snow cover. The 30-m resolution TM data provide the most accurate snow maps, and are thus used as the baseline for comparison with the other maps. Comparisons show that the percent change in amount of snow cover relative to the 3 0-m resolution TM maps is lowest using the TM I -km resolution maps, ranging from 0 to 40

  4. Snow depth and snow duration variability in Trentino (North-East Italy)

    NASA Astrophysics Data System (ADS)

    Marcolini, Giorgia; Bellin, Alberto; Disse, Markus; Chiogna, Gabriele

    2016-04-01

    Snowpack dynamics is an important indicator in assessing climate change in mountainous regions. In fact, it is strongly influenced by temperature and precipitation behavior and is the strongest single element controlling the hydrological cycle of Alpine catchments. Furthermore, related quantities, such as snow cover duration and extension, affect many aspects of life in mountainous regions, from economical activities, such as winter tourism and hydropower production, to water availability and ecosystem dynamics. Available data on snowpack are often heterogeneous and long time series, useful for climate analysis, are often obtained by merging data of different origins. This, among other factors, calls for robust homogenization techniques. We apply the Standard Normal Homogeneity Test (SNHT) to detect breakpoints in 109 timeseries of snowpack collected in Trentino (North-East Italy). After having performed the detection of anthropogenic breakpoints, we investigated the occurrence of anomalies and changes in the mean seasonal snow-depth, in the number of days with snowfall, in the snow cover duration and the correlation of these variables with the altitude of the sites. We mainly focus on the period 1950-2013, since it is the richest in terms of data availability. The analyses clearly indicate that the period 1990-2000 was critical in terms of seasonal mean snow depth and snow-cover duration, in particular for stations below 1600 m a.s.l.

  5. Research relative to angular distribution of snow reflectance/snow cover characterization and microwave emission

    NASA Technical Reports Server (NTRS)

    Dozier, Jeff; Davis, Robert E.

    1987-01-01

    Remote sensing has been applied in recent years to monitoring snow cover properties for applications in hydrologic and energy balance modeling. In addition, snow cover has been recently shown to exert a considerable local influence on weather variables. Of particular importance is the potential of sensors to provide data on the physical properties of snow with high spatial and temporal resolution. Visible and near-infrared measurements of upwelling radiance can be used to infer near-surface properties through the calculation of albedo. Microwave signals usually come from deeper within the snow pack and thus provide depth-integrated information, which can be measured through clouds and does not relay on solar illumination.Fundamental studies examining the influence of snow properties on signals from various parts of the electromagnetic spectrum continue in part because of the promise of new remote sensors with higher spectral and spatial accuracy. Information in the visible and near-infrared parts of the spectrum comprise nearly all available data with high spatial resolution. Current passive microwave sensors have poor spatial resolution and the data are problematic where the scenes consist of mixed landscape features, but they offer timely observations that are independent of cloud cover and solar illumination.

  6. Electrical charging of skis gliding on snow.

    PubMed

    Colbeck, S C

    1995-01-01

    Ski charging was measured using giant-slalom style skis as gliding capacitors. The voltage measured across the plates was proportional to the charge on the base. While resting on dry snow or suspended in the air, the voltage was slowly reduced by the data logger itself. On wet snow the decay was much faster. While stationary on powder snow the ski developed a slightly negative voltage, showed a small, transient positive peak when motion began, rapidly dropped to negative values, and then assumed a quasi-steady climb to positive voltages. A great deal of noise was superimposed on the general features of the signal when skiing on hard or bumpy surfaces. Thus, the accumulation of charge to high levels was only possible with long runs in deep powder. The rate of charging increased with speed but was not affected by use of one "antistatic" wax, and another such wax actually increased the measured voltage over that of an unwaxed base. PMID:7898330

  7. Snow From Great Lakes Covers Buffalo

    NASA Technical Reports Server (NTRS)

    2002-01-01

    On November 20, 2000, Buffalo, New York was blanketed by a late-autumn storm that left 25 inches of snow on the ground in a 24-hour period, most of it during the afternoon rush hour. Buffalo officials declared a state of emergency and New York National Guardsmen were called in to assist with clearing snow from roads. With the exception of essential vehicles or people retrieving stranded children, all driving was banned in the city. This SeaWiFS pass over the central United States and Canada depicts a source for all of the snow in Buffalo. Cold, dry Canadian air blowing toward the southeast picked up a lot of moisture from the relatively warm Great Lakes -- forming the clouds that lightened their loads over Buffalo. This image was acquired November 21, 2000, by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) flying aboard the Orbview-2 satellite. Image provided by the SeaWiFS Project, NASA/Goddard Space Flight Center, and ORBIMAGE

  8. Propagation style controls lava-snow interactions

    NASA Astrophysics Data System (ADS)

    Edwards, B. R.; Belousov, A.; Belousova, M.

    2014-12-01

    Understanding interactions between volcanic eruptions and the cryosphere (a.k.a. glaciovolcanism) is important for climate reconstructions as well as for hazard mitigation at ice-clad volcanoes. Here we present unique field observations of interactions between snowpack and advancing basaltic lava flows during the 2012-13 eruption at Tolbachik volcano, Kamchatka, Russia. Our observations show that lava-snow heat transfer is slow, and that styles of lava propagation control snowpack responses. ‧A‧a and sheet lava flows advance in a rolling caterpillar-track motion on top of the rigid, snowpack substrate with minor lava-snow interaction. In contrast, pahoehoe lava propagates by inflation of lobes beneath/inside the snowpack, producing rigorous lava-snow interaction via meltwater percolation down into the incandescent lava causing production of voluminous steam, rapid surface cooling and thermal shock fragmentation. The textures produced by pahoehoe-snowpack interactions are distinctive and, where observed at other sites, can be used to infer syn-eruption seasonality and climatic conditions.

  9. Propagation style controls lava-snow interactions.

    PubMed

    Edwards, B R; Belousov, A; Belousova, M

    2014-01-01

    Understanding interactions between volcanic eruptions and the cryosphere (a.k.a. glaciovolcanism) is important for climate reconstructions as well as for hazard mitigation at ice-clad volcanoes. Here we present unique field observations of interactions between snowpack and advancing basaltic lava flows during the 2012-13 eruption at Tolbachik volcano, Kamchatka, Russia. Our observations show that lava-snow heat transfer is slow, and that styles of lava propagation control snowpack responses. 'A'a and sheet lava flows advance in a rolling caterpillar-track motion on top of the rigid, snowpack substrate with minor lava-snow interaction. In contrast, pahoehoe lava propagates by inflation of lobes beneath/inside the snowpack, producing rigorous lava-snow interaction via meltwater percolation down into the incandescent lava causing production of voluminous steam, rapid surface cooling and thermal shock fragmentation. The textures produced by pahoehoe-snowpack interactions are distinctive and, where observed at other sites, can be used to infer syn-eruption seasonality and climatic conditions. PMID:25514031

  10. Phase-field modeling of dry snow metamorphism.

    PubMed

    Kaempfer, Thomas U; Plapp, Mathis

    2009-03-01

    Snow on the ground is a complex three-dimensional porous medium consisting of an ice matrix formed by sintered snow crystals and a pore space filled with air and water vapor. If a temperature gradient is imposed on the snow, a water vapor gradient in the pore space is induced and the snow microstructure changes due to diffusion, sublimation, and resublimation: the snow metamorphoses. The snow microstructure, in turn, determines macroscopic snow properties such as the thermal conductivity of a snowpack. We develop a phase-field model for snow metamorphism that operates on natural snow microstructures as observed by computed x-ray microtomography. The model takes into account heat and mass diffusion within the ice matrix and pore space, as well as phase changes at the ice-air interfaces. Its construction is inspired by phase-field models for alloy solidification, which allows us to relate the phase-field to a sharp-interface formulation of the problem without performing formal matched asymptotics. To overcome the computational difficulties created by the large difference between diffusional and interface-migration time scales, we introduce a method for accelerating the numerical simulations that formally amounts to reducing the heat- and mass-diffusion coefficients while maintaining the correct interface velocities. The model is validated by simulations for simple one- and two-dimensional test cases. Furthermore, we perform qualitative metamorphism simulations on natural snow structures to demonstrate the potential of the approach. PMID:19391945

  11. [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

  12. Seasonal Evolution of Snow Cover on Antarctic Sea Ice

    NASA Astrophysics Data System (ADS)

    Maksym, T.; Leonard, K. C.; Trujillo, E.; White, S.; Wilkinson, J.; Stammerjohn, S. E.; Mei, J.

    2015-12-01

    Snow cover on Antarctic sea ice plays a key role in the evolution of ice thickness, its estimation from space-borne altimeters, and structuring of sea ice ecosystems. Yet until recently, there have been very few continuous observations of the seasonal evolution of snow cover on Antarctic sea ice. We present observations of the seasonal evolution of the snow cover from ice mass balance buoys (IMBs) deployed between 2009 and 2013 in the Weddell, Bellingshausen, and Amundsen Seas and the East Antarctic sector. In addition, automatic weather stations that provided direct observations of precipitation, accumulation, and blowing snow were deployed alongside IMBs in October, 2012 in the East Antarctic during the Sea Ice Physics and Ecosystem eXperiment II (SIPEX II), and in July and August, 2013 in the Weddell Sea during the Antarctic Winter Ecosystem and Climate Study (AWECS). These buoys show markedly different snow accumulation regimes in each sector, although accumulation is also strongly controlled by the local morphology of the ice cover through snow erosion and deposition during blowing snow and precipitations events. Comparisons of snow accumulation from these buoys with estimates from atmospheric reanalysis and the direct measurements of precipitation and blowing snow show that precipitation is generally not a good estimator of snow accumulation. Improved treatment of blowing snow is needed if sea ice models are to accurately simulate Antarctic snow and sea ice mass balance. In summer, melting of the snow pack is relatively modest in most cases. Nevertheless, it appears to play an important role in governing sea ice hydrology and sea ice surface properties, and hence may play an important role in modulating sea ice primary productivity.

  13. Optical Properties of Snow and Sea-ice, Barrow Alaska

    NASA Astrophysics Data System (ADS)

    Reay, H. J.; France, J. L.; King, M. D.

    2009-12-01

    Sunlit snowpacks and sea-ice produce a flux of chemicals from the snow or ice to the atmosphere. The chemical flux (1) changes the oxidising capacity of the atmosphere above the snowpack (2) alters chemical concentrations in snow, via reaction with photo-generated hydroxyl radicals. Photochemistry in snow and ice affect concentration chemicals in ice cores which are used to infer past (and therefore future) climates. Impurities in snow changes the optical absorption properties of the snowpack and thus the efficiency with which they melt as highlighted by the IPCC. Measurements of the solar irradiance in the snow and above the snow were undertaken as part of the OASIS 2009 campaign Barrow, Alaska. A model has been used to compute the amount of chemistry driven by this sunlight in and above the snow and to calculate fluxes of NO, NO2 from the snow and depth integrated hydroxyl radical production rate. The values can be compared to measurements of these gases at Barrow as part of the large OASIS field campaign. We have studied the optical properties of different Arctic snowpacks at UV-visible wavelength (350-700nm) by measuring the e-folding depth and albedos of many windpacks. Optically the snowpacks can be classified into four main snowpack types: snow on sea-ice, snow inland, soft and hard windpack. The albedo was measured using nadir reflectance and the e-folding depth was measured by recording the diffuse irradiance using fibre optic probes inserted into the snow at known depths. Using the TUV-Snow radiative transfer model we have determined the optical variables for scattering and absorption. We have produce absorption spectra of the impurities in the snowpack demonstrating a combination of black carbon and humic-like material (fig1). Fig 1. Absorption spectrum of inland snow

  14. Small scale variability of snow properties on Antarctic sea ice

    NASA Astrophysics Data System (ADS)

    Wever, Nander; Leonard, Katherine; Paul, Stephan; Jacobi, Hans-Werner; Proksch, Martin; Lehning, Michael

    2016-04-01

    Snow on sea ice plays an important role in air-ice-sea interactions, as snow accumulation may for example increase the albedo. Snow is also able to smooth the ice surface, thereby reducing the surface roughness, while at the same time it may generate new roughness elements by interactions with the wind. Snow density is a key property in many processes, for example by influencing the thermal conductivity of the snow layer, radiative transfer inside the snow as well as the effects of aerodynamic forcing on the snowpack. By comparing snow density and grain size from snow pits and snow micro penetrometer (SMP) measurements, highly resolved density and grain size profiles were acquired during two subsequent cruises of the RV Polarstern in the Weddell Sea, Antarctica, between June and October 2013. During the first cruise, SMP measurements were done along two approximately 40 m transects with a horizontal resolution of approximately 30 cm. During the second cruise, one transect was made with approximately 7.5 m resolution over a distance of 500 m. Average snow densities are about 300 kg/m3, but the analysis also reveals a high spatial variability in snow density on sea ice in both horizontal and vertical direction, ranging from roughly 180 to 360 kg/m3. This variability is expressed by coherent snow structures over several meters. On the first cruise, the measurements were accompanied by terrestrial laser scanning (TLS) on an area of 50x50 m2. The comparison with the TLS data indicates that the spatial variability is exhibiting similar spatial patterns as deviations in surface topology. This suggests a strong influence from surface processes, for example wind, on the temporal development of density or grain size profiles. The fundamental relationship between variations in snow properties, surface roughness and changes therein as investigated in this study is interpreted with respect to large-scale ice movement and the mass balance.

  15. Monitoring Areal Snow Cover Using NASA Satellite Imagery

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  16. Numerical and experimental quantification of snow albedo reduction due to black carbon impurities for various snow types

    NASA Astrophysics Data System (ADS)

    Haussener, S.; Hadley, O. L.; Gergely, M.; Schneebeli, M.; Kirchstetter, T.

    2012-12-01

    The presence of black carbon (BC) and other impurities in snow changes its radiative properties, i.e. reduces the snow albedo, and consequently affects the energy and mass balance of the snowpack. The accurate quantification of BC-related snow albedo reduction is of interest in a wide range of areas such as climate modeling, remote sensing, and snow melting. The radiative behavior of BC-laden snow depends on the coupled influence of snow type, i.e. ice grain morphology, and spectral ice and BC characteristics (bulk properties and BC morphology). Correspondingly, the use of environmental measurement to understand the effect of BC on snow is questionable due to masking by variables like snow microstructure, impurity characteristics, and angular and spatial solar intensity. Similarly, numerical models using simplified snow morphology do not account for possible coupled morphology-impurity effects. We present a tomography-based multi-scale and multi-phase methodology for the numerical determination of the spectral macroscopic optical properties of BC-laden snow. The methodology consists of: (i) obtaining the 3D microstructure of snow samples by computed tomography; (ii) using the snow's digital 3D microstructure and the impurity characteristics in direct numerical simulations for solving the radiative transfer equations (RTEs) and determining the effective spectral radiative properties of the snowpack; (iii) incorporation of the effective radiative properties in the solution of the volume-averaged RTEs at the continuum scale to determine (surface) radiative properties such as albedo. The numerical effort is accompanied by complementary laboratory measurements of various natural BC-free snow types, and machine-made BC-laden snow. The machine-made snow samples are generated with aqueous suspensions of BC that are sprayed into a freezing chamber. The BC is produced by using an inverted methane flame. Spectrally resolved snow albedo is quantified with a calibrated

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

    PubMed Central

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

    2013-01-01

    Abstract The High Arctic winter is expected to be altered through ongoing and future climate change. Winter precipitation and snow depth are projected to increase and melt out dates change accordingly. Also, snow cover and depth will play an important role in protecting plant canopy from increasingly more frequent extreme winter warming events. Flower production of many Arctic plants is dependent on melt out timing, since season length determines resource availability for flower preformation. We erected snow fences to increase snow depth and shorten growing season, and counted flowers of six species over 5 years, during which we experienced two extreme winter warming events. Most species were resistant to snow cover increase, but two species reduced flower abundance due to shortened growing seasons. Cassiope tetragona responded strongly with fewer flowers in deep snow regimes during years without extreme events, while Stellaria crassipes responded partly. Snow pack thickness determined whether winter warming events had an effect on flower abundance of some species. Warming events clearly reduced flower abundance in shallow but not in deep snow regimes of Cassiope tetragona, but only marginally for Dryas octopetala. However, the affected species were resilient and individuals did not experience any long term effects. In the case of short or cold summers, a subset of species suffered reduced reproductive success, which may affect future plant composition through possible cascading competition effects. Extreme winter warming events were shown to expose the canopy to cold winter air. The following summer most of the overwintering flower buds could not produce flowers. Thus reproductive success is reduced if this occurs in subsequent years. We conclude that snow depth influences flower abundance by altering season length and by protecting or exposing flower buds to cold winter air, but most species studied are resistant to changes. Winter warming events, often

  18. Iodine speciation in rain, snow and aerosols

    NASA Astrophysics Data System (ADS)

    Gilfedder, B. S.; Lai, S. C.; Petri, M.; Biester, H.; Hoffmann, T.

    2008-10-01

    Iodine oxides, such as iodate, should be the only thermodynamically stable sink species for iodine in the troposphere. However, field observations have increasingly found very little iodate and significant amounts of iodide and soluble organically bound iodine (SOI) in precipitation and aerosols. The aim of this study was to investigate iodine speciation, including the organic fraction, in rain, snow, and aerosols in an attempt to further clarify aqueous phase iodine chemistry. Diurnal aerosol samples were taken with a 5 stage cascade impactor and a virtual impactor (PM2.5) from the Mace Head research station, Ireland, during summer 2006. Rain was collected from Australia, New Zealand, Patagonia, Germany, Ireland, and Switzerland and snow was obtained from Greenland, Germany, Switzerland, and New Zealand. Aerosols were extracted from the filters with water and all samples were analysed for total soluble iodine (TSI) by inductively coupled plasma mass spectrometry (ICP-MS) and iodine speciation was determined by coupling an ion chromatography unit to the ICP-MS. The median concentration of TSI in aerosols from Mace Head was 222 pmol m-3 (summed over all impactor stages) of which the majority was associated with the SOI fraction (median day: 90±4%, night: 94±2% of total iodine). Iodide exhibited higher concentrations than iodate (median 6% vs. 1.2% of total iodine), and displayed significant enrichment during the day compared to the night. Interestingly, up to 5 additional, presumably anionic iodo-organic peaks were observed in all IC-ICP-MS chromatograms, composing up to 15% of the TSI. Soluble organically bound iodine was also the dominant fraction in all rain and snow samples, with lesser amounts of iodide and iodate (iodate was particularly low in snow). Two of the same unidentified peaks found in aerosols were also observed in precipitation from both Southern and Northern Hemispheres. This suggests that these species are transferred from the aerosols into

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  20. Correlation and prediction of snow water equivalent from snow sensors. Forest Service research paper (Final)

    SciTech Connect

    McGurk, B.J.; Azuma, D.L.

    1992-01-01

    Since 1982, under an agreement between the California Department of Water Resources and the USDA Forest Service, snow sensors have been installed and operated in Forest Service-administered wilderness areas in the Sierra Nevada of California. Because analysis of snow water equivalent(SWE) data from these wilderness sensors would not be possible until just before they are due to be removed, surrogate pairs of high- and low-elevation snow sensors were selected to determine whether correlation and prediction might be achieved. Surrogate pairs of sensors with between 5 and 15 years of concurrent data were selected, and correlation and regression were used to examine the statistical feasibility of SWE prediction after removal of the wilderness sensors. Of the 10 pairs analyzed, two pairs achieved a correlation coefficient of 0.95 or greater.

  1. On the influence of recrystallization on snow fabric and microstructure: study of a snow profile in Central East Antarctica

    NASA Astrophysics Data System (ADS)

    Calonne, Neige; Schneebeli, Martin; Montagnat, Maurine; Matzl, Margret

    2016-04-01

    Temperature gradient metamorphism affects the Antarctic snowpack up to 5 meters depth, which lead to a recrystallization of the ice grains by sublimation of ice and deposition of water vapor. By this way, it is well known that the snow microstructure evolves (geometrical changes). Also, a recent study shows an evolution of the snow fabric, based on a cold laboratory experiment. Both fabric and microstructure are required to better understand mechanical behavior and densification of snow, firn and ice, given polar climatology. The fabric of firn and ice has been extensively investigated, but the publications by Stephenson (1967, 1968) are to our knowledge the only ones describing the snow fabric in Antarctica. In this context, our work focuses on snow microstructure and fabric in the first meters depth of the Antarctic ice sheet, where temperature gradients driven recrystallization occurs. Accurate details of the snow microstructure are observed using micro-computed tomography. Snow fabrics were measured at various depths from thin sections of impregnated snow with an Automatic Ice Texture Analyzer (AITA). A definite relationship between microstructure and fabric is found and highlights the influence of metamorphism on both properties. Our results also show that the metamorphism enhances the differences between the snow layers properties. Our work stresses the significant and complex evolution of snow properties in the upper meters of the ice sheet and opens the question of how these layer properties will evolve at depth and may influence the densification.

  2. Integrating snow albedo from the Airborne Snow Observatory into the distributed energy balance snowmelt model iSnobal

    NASA Astrophysics Data System (ADS)

    Skiles, M.; Painter, T. H.; Marks, D. G.; Hedrick, A. R.

    2015-12-01

    Since 2013 the Airborne Snow Observatory (ASO) has been measuring spatial and temporal distribution of both snow water equivalent and snow albedo, the two most critical properties for understanding snowmelt runoff and timing, across key basins in the Western US. It is generally understood that net solar radiation (as controlled by variations in snow albedo and irradiance) provides the energy available for melt in almost all snow-covered environments. Until now, sparse measurements have restricted the ability to utilize measured net solar radiation in energy balance models, and current process simulations and model prediction of albedo evolution rely on oversimplifications of the processes. Data from ASO offers the unprecedented opportunity to utilize weekly measurements of spatially extensive spectral snow albedo to constrain and update snow albedo in a distributed snowmelt model for the first time. Here, we first investigate the sensitivity of the snow energy balance model SNOBAL to prescribed changes in snow albedo at two instrumented alpine catchments: at the point scale across 10 years at Senator Beck Basin Study Area in the San Juan Mountains, southwestern Colorado, and at the distributed scale across 25 years at Reynolds Creek Experimental Watershed, Idaho. We then compare distributed energy balance and snowmelt results across the ASO measurement record in the Tuolumne Basin in the Sierra Nevada Mountains, California, for model runs with and without integrated snow albedo from ASO.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  4. Review of Electromagnetic Methods to Investigate Arctic and Antarctic Sea Ice and Snow

    NASA Astrophysics Data System (ADS)

    Pfaffling, A.; Haas, C.; Meil{\\Ae}Nder-Larsen, M.; Bishop, J.; Flinspach, D.; Otto, D.; Reid, J. E.; Worby, A. P.

    2007-12-01

    During the last 5 years we have applied a variety of near-surface electric (ie, resistivity) and electromagnetic methods to investigate sea ice and snow on sea ice in the Antarctic and Arctic. Here we present field cases and lessons learned on the applicability for resolving distinct target parameters. The geophysical challenges of sea ice include its composition of (a) homogeneous, vertically anisotropic, one-dimensional (level) ice 0.5 to 4 m thick, and (b) highly heterogeneous, partly water impregnated three-dimensional pressure ridge features 2 to 10 m thick. Snow on sea ice is generally dry (until melt onset) and spans a thickness range of some centimetres up to a few meters. We applied several different types of equipment covering the frequency range from DC to radar for different tasks and targets. Ground Penetrating Radar (GPR) proved to be fast and portable for snow thickness profiling with the limitation of a minimum snow thickness around 10 cm. Electromagnetic induction (EMI) is a classic sea ice thickness profiling method used hand held on the ice, ship-borne suspended from outrigger-like constructions as well as airborne as helicopter towed sensors. Mostly regional ice plus snow thickness is derived from EMI measurements. Attempts have been made to retrieve internal ice properties such as porosity or age (conductivity) from EM soundings. DC-resistivity sounding clearly shows the vertical conductivity anisotropy of level sea ice, due to its crystalline structure and aging processes. Electrical Resistivity Tomography was conducted on Baltic and Arctic sea ice to determine the porosity of pressure ridge keels. Our results show the potentials and limitations of the different methods for climate related and engineering sea ice studies. geophysics.com/projects

  5. Localized Detection of Frozen Precipitation Events and the Rain/Snow Transition

    NASA Astrophysics Data System (ADS)

    Strachan, S.

    2014-12-01

    Frozen precipitation in the mid-latitudes and semi-arid environments frequently serves a crucial role in the annual water budget. Often occurring along elevational gradients, the rain/snow transition (or, "snow line") in mountain systems determines the amount of water which enters the system slowly during melt phases as opposed to rain which immediately infiltrates or runs off to lower elevations. This in turn influences the location and composition of ecological communities such as conifer forests, as well as timing and nature of the entire mountain block annual hydrologic cycle. Characterization of the rain/snow transition is becoming a priority in mountainous semi-arid regions, as increasing human populations and repeated drought episodes combine to create water shortages. Atmospheric conditions (temperature and relative humidity) which signal the rain/snow transition have been described, but variability within the conditions window can create error in estimating true areal cover of frozen versus liquid precipitation. In populated, flood-prone regions, radar installations specifically tuned to the detection of the "bright band" transition elevation can be deployed; however these cannot be permanently installed at remote, solar-power-dependent climate stations or with fine geographical scale. Characterization of current trends in rain/snow transition can be made using automated weather stations placed along the elevational gradient fielding sensors for high-frequency (e.g. 1-10 minute) measurement of air temperature, relative humidity, liquid precipitation, and precipitation mass. Visual validation of precipitation modes detected through automated means is performed using time-series records from digital cameras placed at each station. Refinements of geographically-explicit relationships of atmospheric conditions to precipitation mode can be made over time, as well as detection of seasonally-anomalous but eco-hydrologically-significant frozen precipitation events

  6. Accumulation of perfluoroalkyl compounds in tibetan mountain snow: temporal patterns from 1980 to 2010.

    PubMed

    Wang, Xiaoping; Halsall, Crispin; Codling, Garry; Xie, Zhiyong; Xu, Baiqing; Zhao, Zhen; Xue, Yonggang; Ebinghaus, Ralf; Jones, Kevin C

    2014-01-01

    The use of snow and ice cores as recorders of environmental contamination is particularly relevant for per- and polyfluoroalky substances (PFASs) given their production history, differing source regions and varied mechanisms driving their global distribution. In a unique study perfluoroalkyl acids (PFAAs) were analyzed in dated snow-cores obtained from high mountain glaciers on the Tibetan Plateau (TP). One snow core was obtained from the Mt Muztagata glacier (accumulation period of 1980-1999), located in western Tibet and a second core from Mt. Zuoqiupo (accumulation period: 1996-2007) located in southeastern Tibet, with fresh surface snow collected near Lake Namco in 2010 (southern Tibet). The higher concentrations of ∑PFAAs were observed in the older Mt Muztagata core and dominated by perfluorooctanesulfonic acid (PFOS) (61.4-346 pg/L) and perfluorooctanoic acid (PFOA) (40.8-243 pg/L), whereas in the Mt Zuoqiupu core the concentrations were lower (e.g., PFOA: 37.8-183 pg/L) with PFOS below detection limits. These differences in PFAA concentrations and composition profile likely reflect the upwind sources affecting the respective sites (e.g., European/central Asian sources for Mt Muztagata and India sources for Mt Zuoqiupu). Perfluorobutanoic acid (PFBA) dominated the recent surface snowpack of Lake Namco which is mainly associated with India sources where the shorter chain volatile PFASs precursors predominate. The use of snow cores in different parts of Tibet provides useful recorders to examine the influence of different PFASs source regions and reflect changing PFAS production/use in the Northern Hemisphere. PMID:24320138

  7. Modeling bulk density and snow water equivalent using daily snow depth observations.

    NASA Astrophysics Data System (ADS)

    McCreight, J. L.; Small, E. E.

    2013-10-01

    Bulk density is a fundamental property of snow relating its depth and mass. Previously, two simple models of bulk density (depending on snow depth, date, and location) have been developed to convert snow depth observations to snow water equivalent (SWE) estimates. However, these models were not intended for application at the daily time step. We develop a new model of bulk density for the daily timestep and demonstrate its improved skill over the existing models. Snow depth and density are negatively correlated at short (10 days) timescales while positively correlated at longer (90 days) timescales. We separate these scales of variability by modeling smoothed, daily snow depth (long time scales) and the observed positive and negative anomalies from the smoothed timeseries (short timescales) as separate terms. A climatology of fit is also included as a predictor variable. Over a half-million, daily observations of depth and SWE at 345 SNOTEL sites are used to fit models and evaluate their performance. For each location, we train the three models to the neighboring stations within 70 km, transfer the parameters to the location to be modeled, and evaluate modeled timeseries against the observations at that site. Our model exhibits improved statistics and qualitatively more-realistic behavior at the daily time step when sufficient local training data are available. We reduce density RMSE by 9.6% and 4.2% compared to previous models. Similarly, R2 increases from 0.46 to 0.52 to 0.56 across models. Removing the challenge of parameter transfer increases R2 scores for both the existing and new models, but the gain is greatest for the new model (R2 = 0.75). Our model shows general improvement over the existing models when data are more frequent than once every 5 days and at least 3 stations are available for training.

  8. Sierra Nevada, California, U.S.A., Snow Algae: Snow albedo changes, algal-bacterial interrelationships and ultraviolet radiation effects

    SciTech Connect

    Thomas, W.H.; Duval, B.

    1995-11-01

    In the Tioga Pass area (upper LeeVining Creek watershed) of the Sierra Nevada (California), snow algae were prevalent in the early summers of 1993 and 1994. Significant negative correlations were found between snow water content. However, red snow caused by algal blooms did not decrease mean albedos in representative snowfields. This was due to algal patchiness; mean albedos would not decrease over the whole water catchment basin; and water supplies would not be affected by the presence of algae. Albedo was also reduced by dirt on the snow, and wind-blown dirt may provide a source of allochthonous organic matter for snow bacteria. However, several observations emphasize the importance of an autochthonous source for bacterial nutrition. Bacterial abundances and production rates were higher in red snow containing algae than in noncolored snow. Bacterial production was about two orders-of-magnitude lower than photosynthetic algal production. Bacteria were also sometimes attached to algal cells. In experiments where snow algae were contained in UV-transmitting quartz tubes, ultraviolet radiation inhibited red snow (collected form open, sunlit areas) photosynthesis about 25%, while green snow (collected from forested, shady locations) photosynthesis was inhibited by 85%. Methanol extracts of red snow algae had greater absorbances in blue and UV spectral regions than did algae from green snow. These differences in UV responses and spectra may be due to habitat (sun vs shade) differences, or may be genetic, since different species were found in the two snow types. However, both habitat and genetic mechanisms may be operating together to cause these differences. 53 refs., 5 figs., 5 tabs.

  9. Snow distribution and heat flow in the taiga

    SciTech Connect

    Sturm, M. )

    1992-05-01

    The trees of the taiga intercept falling snow and cause it to become distributed in an uneven fashion. Around aspen and birch, cone-shaped accumulations form. Beneath large spruce trees, the snow cover is depleted, forming a bowl-shaped depression called a tree well. Small spruce trees become covered with snow, creating cavities that funnel cold air to the snow/ground interface. The depletion of snow under large spruce trees results in greater heat loss from the ground. A finite difference model suggests that heat flow from tree wells can be more than twice that of undisturbed snow. In forested watersheds, this increase can be a significant percentage of the total winter energy exchange.

  10. Application of Bayesian decision theory to airborne gamma snow measurement

    NASA Technical Reports Server (NTRS)

    Bissell, V. C.

    1975-01-01

    Measured values of several variables are incorporated into the calculation of snow water equivalent as measured from an aircraft by snow attenuation of terrestrial gamma radiation. Bayesian decision theory provides a snow water equivalent measurement by taking into account the uncertainties in the individual measurement variables and filtering information about the measurement variables through prior notions of what the calculated variable (water equivalent) should be.

  11. Influence of snow-cover properties on avalanche dynamics

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    Snow avalanches with the potential of reaching traffic routes and settlements are a permanent winter threat for many mountain communities. Snow safety officers have to take the decision whether to close a road, a railway line or a ski slope. Those decisions are often very difficult as they demand the ability to interpret weather forecasts, to establish their implication for the stability and the structure of the snow cover and to evaluate the influence of the snow cover on avalanche run-out distances. In the operational programme 'Italy-Switzerland, project STRADA' we focus on the effects of snow cover on avalanche dynamics, and thus run-out distance, with the aim to provide a better understanding of this influence and to ultimately develop tools to support snow safety officers in their decision process. We selected five avalanches, measured at the Vallée de la Sionne field site, with similar initial mass and topography but different flow dynamics and run-out distances. Significant differences amongst the individual avalanches could be observed for front and internal velocities, impact pressures, flow regimes, deposition volumes and run-out distances. For each of these avalanches, the prevailing snow conditions at release were reconstructed using field data from local snowpits or were modeled with SNOWPACK. Combining flow dynamical data with snow cover properties shows that erodible snow depth, snow density and snow temperature in the snow pack along the avalanche track are among the decisive variables that appear to explain the observed differences. It is further discussed, how these influencing factors can be quantified and used for improved predictions of site and time specific avalanche hazard.

  12. Black Carbon Mass Concentration in California Mountain Snow

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

    Recent modeling studies have shown that deposition of black carbon (BC) to snow and ice lowers the albedo of snow and exerts a positive forcing on the climate. This effect is also a likely contributor to the observed ice and snow retreat in glaciers, ice sheets, and mountain snow pack. Observational data of actual BC concentrations in snow, which would help to constrain and validate these results, are scarce. This study presents the concentration of BC in fresh snow measured at two mountain locations in Northern California (Lassen Volcano Natl. Park and Donner Summit), as well as that in coastal rainfall at Trinidad Head, CA. These measurements are the first of this kind made in California. Average BC concentration at Lassen Natl. Park and Donner summit were respectively 6.8 and 9.7 ng per gram of snow. When placed in context with the modeled effect of BC on fresh snow albedo, these concentrations indicate a lowering of the snow albedo by 0.5 to 0.8%. As the snow pack ages, models predict that this effect will be increasingly amplified. Measurements of ambient aerosols during the rain events, as well as HySPLIT back-trajectories, provide additional information regarding possible sources of BC in California mountain snow packs. For the samples collected in this study, most of the soot in the snow appears to be of local origin. The average BC concentration in the coastal rain was 6.0 ng per gram of water, with the highest concentrations (12 ng/g) corresponding to the only back-trajectories clearly indicative of long-range trans-Pacific transport.

  13. 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).

  14. Spatial Scale for Modelling Blowing Snow on the Canadian Prairieis

    NASA Astrophysics Data System (ADS)

    Pomeroy, J. W.; Fang, X.

    2007-12-01

    Blowing snow transports and sometimes sublimates much of the seasonal snowfall in the Prairies of western Canada. Snow redistribution is an important feature of Prairie hydrology as deep snowdrifts provide a source of meltwater to replenish ponds and generate streamflow in this dry region. The spatial distribution of snow water equivalent in the spring is therefore of great interest for Prairie hydrology. A test of the appropriate spatial scale for modelling blowing snow redistribution and sublimation was conducted at St Denis National Wildlife Area in the rolling, internally drained prairie pothole region east of Saskatoon, Saskatchewan, Canada. A LiDAR based DEM and LANDSAT based vegetation map were available for this region. A coupled complex windflow and blowing snow model was run with ~250,000 6 m x 6 m grid cells to produce spatially distributed estimates of seasonal blowing snow transport and sublimation. The calculation was then aggregated, using 7 landscape units that represented the major influences of surface roughness, topography and fetch on blowing snow transport and sublimation. Both the distributed and aggregated simulations described similar end of winter snow water equivalent with substantive redistribution of blowing snow from exposed sparsley vegetated sites across topographic drainage divides to the densely vegetated pothole wetlands. Both simulations also agreed well with snow survey observations. While the distributed calculations provide a fascinating and detailed visual image of the interaction of complex landscapes and blowing snow redistribution and sublimation, it is clear that blowing snow transport and sublimation calculations can be successfully aggregated to the spatial scale of the major landscape units in this environment.

  15. Snow studies using thermal infrared observations from earth satellites

    NASA Technical Reports Server (NTRS)

    Barnes, J. C.

    1972-01-01

    The application of satellite high resolution infrared data was studied for mapping snow cover. The study has two objectives: (1) to determine whether existing radiometers onboard the Nimbus and ITOS satellites can provide hydrologically useful snow information, and (2) to develop analysis techniques applicable to future IR sensor systems on earth satellites. The IR measurements are being analyzed in conjunction with concurrent satellite photographs and conventional snow cover data.

  16. Snow and the ground temperature record of climate change

    NASA Astrophysics Data System (ADS)

    Bartlett, Marshall G.; Chapman, David S.; Harris, Robert N.

    2004-12-01

    Borehole temperature-depth profiles contain a record of surface ground temperature (SGT) changes with time and complement surface air temperature (SAT) analysis to infer climate change over multiple centuries. Ground temperatures are generally warmer than air temperatures due to solar radiation effects in the summer and the insulating effect of snow cover during the winter. The low thermal diffusivity of snow damps surface temperature variations; snow effectively acts as an insulator of the ground during the coldest part of the year. A numerical model of snow-ground thermal interactions is developed to investigate the effect of seasonal snow cover on annual ground temperatures. The model is parameterized in terms of three snow event parameters: onset time of the annual snow event, duration of the event, and depth of snow during the event. These parameters are commonly available from meteorological and remotely sensed data making the model broadly applicable. The model is validated using SAT, subsurface temperature from a depth of 10 cm, and snow depth data from the 6 years of observations at Emigrant Pass climate observatory in northwestern Utah and 217 station years of National Weather Service data from sites across North America. Measured subsurface temperature-time series are compared to changes predicted by the model. The model consistently predicts ground temperature changes that compare well with those observed. Sensitivity analysis of the model leads to a nonlinear relationship between the three snow event parameters (onset, duration, and depth of the annual snow event) and the influence snow has on mean annual SGT.

  17. Snow optical properties at Dome C (Concordia), Antarctica; implications for snow emissions and snow chemistry of reactive nitrogen

    NASA Astrophysics Data System (ADS)

    France, J. L.; King, M. D.; Frey, M. M.; Erbland, J.; Picard, G.; Preunkert, S.; MacArthur, A.; Savarino, J.

    2011-09-01

    Measurements of e-folding depth, nadir reflectivity and stratigraphy of the snowpack around Concordia station (Dome C, 75.10° S, 123.31° E) were undertaken to determine wavelength dependent coefficients (350 nm to 550 nm) for light scattering and absorption and to calculate potential fluxes (depth-integrated production rates) of nitrogen dioxide (NO2) from the snowpack due to nitrate photolysis within the snowpack. The stratigraphy of the top 80 cm of Dome C snowpack generally consists of three main layers:- a surface of soft windpack (not ubiquitous), a hard windpack, and a hoar-like layer beneath the windpack(s). The e-folding depths are ~10 cm for the two windpack layers and ~20 cm for the hoar-like layer for solar radiation at a wavelength of 400 nm; about a factor 2-4 larger than previous model estimates for South Pole. The absorption cross-section due to impurities in each snowpack layer are consistent with a combination of absorption due to black carbon and HULIS (HUmic LIke Substances), with amounts of 1-2 ng g-1 of black carbon for the surface snow layers. Depth-integrated photochemical production rates of NO2 in the Dome C snowpack were calculated as 5.3 × 1012 molecules m-2 s-1, 2.3 × 1012 molecules m-2 s-1 and 8 × 1011 molecules m-2 s-1 for clear skies and solar zenith angles of 60°, 70° and 80° respectively using the TUV-snow radiative-transfer model. Depending upon the snowpack stratigraphy, a minimum of 85% of the NO2 may originate from the top 20 cm of the Dome C snowpack. It is found that on a multi-annual time-scale photolysis can remove up to 80% of nitrate from surface snow, confirming independent isotopic evidence that photolysis is an important driver of nitrate loss occurring in the EAIS (East Antarctic Ice Sheet) snowpack. However, the model cannot completely account for the total observed nitrate loss of 90-95 % or the shape of the observed nitrate concentration depth profile. A more complete model will need to include also physical

  18. Improving the snow physics of WEB-DHM and its point evaluation at the SnowMIP sites

    NASA Astrophysics Data System (ADS)

    Shrestha, M.; Wang, L.; Koike, T.; Xue, Y.; Hirabayashi, Y.

    2010-12-01

    In this study, the snow physics of a distributed biosphere hydrological model, referred to as the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) is significantly improved by incorporating the three-layer physically based energy balance snowmelt model of Simplified Simple Biosphere 3 (SSiB3) and the Biosphere-Atmosphere Transfer Scheme (BATS) albedo scheme. WEB-DHM with improved snow physics is hereafter termed WEB-DHM-S. Since the in-situ observations of spatially-distributed snow variables with high resolution are currently not available over large regions, the new distributed system (WEB-DHM-S) is at first rigorously tested with comprehensive point measurements. The stations used for evaluation comprise the four open sites of the Snow Model Intercomparison Project (SnowMIP) phase 1 with different climate characteristics (Col de Porte in France, Weissfluhjoch in Switzerland, Goose Bay in Canada and Sleepers River in USA) and one open/forest site of the SnowMIP phase 2 (Hitsujigaoka in Japan). The comparisons of the snow depth, snow water equivalent, surface temperature, snow albedo and snowmelt runoff at the SnowMIP1 sites reveal that WEB-DHM-S, in general, is capable of simulating the internal snow process better than the original WEB-DHM. Sensitivity tests (through incremental addition of model processes) are performed to illustrate the necessity of improvements over WEB-DHM and indicate that both the 3-layer snow module and the new albedo scheme are essential. The canopy effects on snow processes are studied at the Hitsujigaoka site of the SnowMIP2 showing that the snow holding capacity of the canopy plays a vital role in simulating the snow depth on ground. Through these point evaluations and sensitivity studies, WEB-DHM-S has demonstrated the potential to address basin-scale snow processes (e.g., the snowmelt runoff), since it inherits the distributed hydrological framework from the WEB-DHM (e.g., the slope-driven runoff generation

  19. View Angle Effects on MODIS Snow Mapping in Forests

    NASA Technical Reports Server (NTRS)

    Xin, Qinchuan; Woodcock, Curtis E.; Liu, Jicheng; Tan, Bin; Melloh, Rae A.; Davis, Robert E.

    2012-01-01

    Binary snow maps and fractional snow cover data are provided routinely from MODIS (Moderate Resolution Imaging Spectroradiometer). This paper investigates how the wide observation angles of MODIS influence the current snow mapping algorithm in forested areas. Theoretical modeling results indicate that large view zenith angles (VZA) can lead to underestimation of fractional snow cover (FSC) by reducing the amount of the ground surface that is viewable through forest canopies, and by increasing uncertainties during the gridding of MODIS data. At the end of the MODIS scan line, the total modeled error can be as much as 50% for FSC. Empirical analysis of MODIS/Terra snow products in four forest sites shows high fluctuation in FSC estimates on consecutive days. In addition, the normalized difference snow index (NDSI) values, which are the primary input to the MODIS snow mapping algorithms, decrease as VZA increases at the site level. At the pixel level, NDSI values have higher variances, and are correlated with the normalized difference vegetation index (NDVI) in snow covered forests. These findings are consistent with our modeled results, and imply that consideration of view angle effects could improve MODIS snow monitoring in forested areas.

  20. 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.

  1. A theory of pressure sensor performance in snow

    NASA Astrophysics Data System (ADS)

    Johnson, Jerome B.

    2004-01-01

    A theory of pressure sensor response in snow is derived and used to examine the sources of measurement errors in snow water equivalent (SWE) pressure sensors. Measurement errors in SWE are caused by differences in the compressibility of the pressure sensor and the adjacent snow layer, which produces a shear stress along the perimeter of the sensor. When the temperature at the base of the snow cover equals 0 °C, differences in the snowmelt rate between the snow-SWE sensor interface and the adjacent snow-soil interface may also produce a shear stress along the sensor's perimeter. This shear stress perturbs the pressure field over the sensor, producing SWE measurement errors. Snow creep acts to reduce shear stresses along the SWE sensor's perimeter at a rate that is inversely proportional to the snow viscosity. For sustained periods of differential snowmelt, a difference in the mass of snow over the sensor compared with the surrounding soil will develop, producing additional permanent errors in SWE measurements. The theory indicates that SWE pressure sensor performance can be improved by designing a sensor with a high Young's modulus (low compressibility), low aspect ratio, large diameter and thermal properties that match those of the surrounding soil. Simulations of SWE pressure sensor errors using the theory are in close agreement with observed errors and may provide a means to correct historical SWE measurements for use in hydrological hindcast or climate studies. Published in 2003 by John Wiley & Sons, Ltd.

  2. Snow cover statistical model for assessment of vehicles mobility

    NASA Astrophysics Data System (ADS)

    Belyakov, Vladimir; Kurkin, Andrey; Zezyulin, Denis; Makarov, Vladimir

    2015-04-01

    Improvement of the infrastructure of the northern territories and efficiency of their industrial development can be achieved through the use of rationally designed vehicles with optimum parameters of the trafficability and performance. In the Russian Federation the significant volume of transportations is carried out in the winter time on snow-covered terrain (temporary winter roads, snowy deserts, the entrances to the mining areas, and the coast of the Arctic Ocean). The solution of questions of mobility in snow-covered terrain conditions from the scientific and technical point of view, mainly lies in the research of the vehicle-terrain interactions for snow. Thus, if one of the objectives is to ensure the vehicle trafficability on the virgin snow, the choice of vehicle must be associated with changing over the year weather conditions. When developing the model of the snow cover for prediction of the mobility of transportation and technological vehicles there were used statistical data on changes in snow depth and density depending on the duration of the winter period. The group of parameters that can be expressed through the snow density (rigidity, cohesion and angle of internal friction) was also considered. Furthermore, terrain features, microprofile, distribution of slopes, landscape peculiarities were also taken into account in the model. These data were obtained by processing information provided by the hydrometeorological stations. Thus, the developed stochastic model of the snow distribution in Russia, allows to make a valid prediction of the possibility of overcoming the snow-covered territories during the winter period.

  3. Understanding the Factors That Control Snow Albedo Over Central Greenland

    NASA Astrophysics Data System (ADS)

    Wright, P.; Bergin, M. H.; Dibb, J. E.; Domine, F.; Carmagnola, C.; Courville, Z.; Sokolik, I. N.; Lefer, B. L.

    2011-12-01

    Snow albedo plays a critical role in the energy balance of the Greenland Ice Sheet. In particular, the snow albedo influences the extent to which absorbing aerosols over Greenland (i.e. dust and black carbon) force climate. With this in mind the spectral snow albedo, physical snow properties, and snow chemistry were measured during May, June, and July 2011 at Summit, Greenland to investigate the variability in snow spectral albedo and its impact on aerosol direct radiative forcing. Optical and chemical properties of aerosol and aerosol optical depth were also measured as part of this study. Strellis et. al. will present a preliminary assessment of aerosol radiative forcing at Summit in summer 2011, in a separate presentation at this meeting. Spectral albedo was measured from 350-2500 nm with an ASD FieldSpec Pro spectroradiometer daily at four permanent sites and a moving fifth site where snow was sampled for characterization, as well as in more intensive diurnal and spatial surveys. Snow specific surface area (SSA), the ratio of snow crystal surface area to mass, was measured with a Dual Frequency Integrating Sphere (DUFISSS) at 1310 nm and 1550 nm, as well as with dyed and cast samples collected for stereology analysis. Snow stratigraphy, crystal size, and density were also measured on a daily basis, and snow samples will be analyzed for microstructural parameters determined from micro-CT imaging. Snow chemistry measurements include specific elements, major ions, and elemental and organic carbon. The time series of daily albedo measurements ranged from 0.88 to nearly 1.0 in visible wavelengths and from 0.42 to 0.65 in the near infrared. Changes as large as 0.1 were observed between consecutive daily measurements across the spectrum. Preliminary results show a strong correlation between variation in albedo and co-located measurements of snow specific surface area, specifically in the near infrared. By conducting our measurements near solar noon every day, and

  4. 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.

  5. Snow Water Equivalent estimation based on satellite observation

    NASA Astrophysics Data System (ADS)

    Macchiavello, G.; Pesce, F.; Boni, G.; Gabellani, S.

    2009-09-01

    The availability of remotely sensed images and them analysis is a powerful tool for monitoring the extension and typology of snow cover over territory where the in situ measurements are often difficult. Information on snow are fundamental for monitoring and forecasting the available water above all in regions at mid latitudes as Mediterranean where snowmelt may cause floods. The hydrological model requirements and the daily acquisitions of MODIS (Moderate Resolution Imaging Spectroradiometer), drove, in previous research activities, to the development of a method to automatically map the snow cover from multi-spectral images. But, the major hydrological parameter related to the snow pack is the Snow Water Equivalent (SWE). This represents a direct measure of stored water in the basin. Because of it, the work was focused to the daily estimation of SWE from MODIS images. But, the complexity of this aim, based only on optical data, doesn’t find any information in literature. Since, from the spectral range of MODIS data it is not possible to extract a direct relation between spectral information and the SWE. Then a new method, respectful of the physic of the snow, was defined and developed. Reminding that the snow water equivalent is the product of the three factors as snow density, snow depth and the snow covered areas, the proposed approach works separately on each of these physical behaviors. Referring to the physical characteristic of snow, the snow density is function of the snow age, then it was studied a new method to evaluate this. Where, a module for snow age simulation from albedo information was developed. It activates an age counter updated by new snow information set to estimate snow age from zero accumulation status to the end of melting season. The height of the snow pack, can be retrieved by adopting relation between vegetation and snow depth distributions. This computes snow height distribution by the relation between snow cover fraction and the

  6. The tiger genome and comparative analysis with lion and snow leopard genomes.

    PubMed

    Cho, Yun Sung; Hu, Li; Hou, Haolong; Lee, Hang; Xu, Jiaohui; Kwon, Soowhan; Oh, Sukhun; Kim, Hak-Min; Jho, Sungwoong; Kim, Sangsoo; Shin, Young-Ah; Kim, Byung Chul; Kim, Hyunmin; Kim, Chang-Uk; Luo, Shu-Jin; Johnson, Warren E; Koepfli, Klaus-Peter; Schmidt-Küntzel, Anne; Turner, Jason A; Marker, Laurie; Harper, Cindy; Miller, Susan M; Jacobs, Wilhelm; Bertola, Laura D; Kim, Tae Hyung; Lee, Sunghoon; Zhou, Qian; Jung, Hyun-Ju; Xu, Xiao; Gadhvi, Priyvrat; Xu, Pengwei; Xiong, Yingqi; Luo, Yadan; Pan, Shengkai; Gou, Caiyun; Chu, Xiuhui; Zhang, Jilin; Liu, Sanyang; He, Jing; Chen, Ying; Yang, Linfeng; Yang, Yulan; He, Jiaju; Liu, Sha; Wang, Junyi; Kim, Chul Hong; Kwak, Hwanjong; Kim, Jong-Soo; Hwang, Seungwoo; Ko, Junsu; Kim, Chang-Bae; Kim, Sangtae; Bayarlkhagva, Damdin; Paek, Woon Kee; Kim, Seong-Jin; O'Brien, Stephen J; Wang, Jun; Bhak, Jong

    2013-01-01

    Tigers and their close relatives (Panthera) are some of the world's most endangered species. Here we report the de novo assembly of an Amur tiger whole-genome sequence as well as the genomic sequences of a white Bengal tiger, African lion, white African lion and snow leopard. Through comparative genetic analyses of these genomes, we find genetic signatures that may reflect molecular adaptations consistent with the big cats' hypercarnivorous diet and muscle strength. We report a snow leopard-specific genetic determinant in EGLN1 (Met39>Lys39), which is likely to be associated with adaptation to high altitude. We also detect a TYR260G>A mutation likely responsible for the white lion coat colour. Tiger and cat genomes show similar repeat composition and an appreciably conserved synteny. Genomic data from the five big cats provide an invaluable resource for resolving easily identifiable phenotypes evident in very close, but distinct, species. PMID:24045858

  7. Non-ideal liquidus curve in the Fe-S system and Mercury's snowing core

    NASA Astrophysics Data System (ADS)

    Chen, Bin; Li, Jie; Hauck, Steven A.

    2008-04-01

    We conducted multi-anvil experiments to investigate the melting behavior of the iron-sulfur system at moderate pressures. Our data reveal a positive departure from ideal solution behavior at 14 GPa, as indicated by the presence of two inflection points on the liquidus curve of iron-rich compositions. In contrast, the shape of the liquidus curve at 10 GPa is consistent with nearly ideal mixing between end-member components. Combined with existing data at lower pressures and above 20 GPa, our results suggest a negative liquidus temperature gradient under conditions found at shallow depths in Mercury's core. At the present time, the core is most likely precipitating solid iron in the form of snow, at a single depth or in two distinct zones. Formation and segregation of iron snow would alter the thermal and chemical state of the core and influence the origin and surface expression of the planet's magnetic field.>

  8. The tiger genome and comparative analysis with lion and snow leopard genomes

    PubMed Central

    Cho, Yun Sung; Hu, Li; Hou, Haolong; Lee, Hang; Xu, Jiaohui; Kwon, Soowhan; Oh, Sukhun; Kim, Hak-Min; Jho, Sungwoong; Kim, Sangsoo; Shin, Young-Ah; Kim, Byung Chul; Kim, Hyunmin; Kim, Chang-uk; Luo, Shu-Jin; Johnson, Warren E.; Koepfli, Klaus-Peter; Schmidt-Küntzel, Anne; Turner, Jason A.; Marker, Laurie; Harper, Cindy; Miller, Susan M.; Jacobs, Wilhelm; Bertola, Laura D.; Kim, Tae Hyung; Lee, Sunghoon; Zhou, Qian; Jung, Hyun-Ju; Xu, Xiao; Gadhvi, Priyvrat; Xu, Pengwei; Xiong, Yingqi; Luo, Yadan; Pan, Shengkai; Gou, Caiyun; Chu, Xiuhui; Zhang, Jilin; Liu, Sanyang; He, Jing; Chen, Ying; Yang, Linfeng; Yang, Yulan; He, Jiaju; Liu, Sha; Wang, Junyi; Kim, Chul Hong; Kwak, Hwanjong; Kim, Jong-Soo; Hwang, Seungwoo; Ko, Junsu; Kim, Chang-Bae; Kim, Sangtae; Bayarlkhagva, Damdin; Paek, Woon Kee; Kim, Seong-Jin; O’Brien, Stephen J.; Wang, Jun; Bhak, Jong

    2013-01-01

    Tigers and their close relatives (Panthera) are some of the world’s most endangered species. Here we report the de novo assembly of an Amur tiger whole-genome sequence as well as the genomic sequences of a white Bengal tiger, African lion, white African lion and snow leopard. Through comparative genetic analyses of these genomes, we find genetic signatures that may reflect molecular adaptations consistent with the big cats’ hypercarnivorous diet and muscle strength. We report a snow leopard-specific genetic determinant in EGLN1 (Met39>Lys39), which is likely to be associated with adaptation to high altitude. We also detect a TYR260G>A mutation likely responsible for the white lion coat colour. Tiger and cat genomes show similar repeat composition and an appreciably conserved synteny. Genomic data from the five big cats provide an invaluable resource for resolving easily identifiable phenotypes evident in very close, but distinct, species. PMID:24045858

  9. Georectification and snow classification of webcam images: potential for complementing satellite-derrived snow maps over Switzerland

    NASA Astrophysics Data System (ADS)

    Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

    2016-04-01

    The spatial and temporal variability of snow cover has a significant impact on climate and environment and is of great socio-economic importance for the European Alps. Satellite remote sensing data is widely used to study snow cover variability and can provide spatially comprehensive information on snow cover extent. However, cloud cover strongly impedes the surface view and hence limits the number of useful snow observations. Outdoor webcam images not only offer unique potential for complementing satellite-derived snow retrieval under cloudy conditions but could also serve as a reference for improved validation of satellite-based approaches. Thousands of webcams are currently connected to the Internet and deliver freely available images with high temporal and spatial resolutions. To exploit the untapped potential of these webcams, a semi-automatic procedure was developed to generate snow cover maps based on webcam images. We used daily webcam images of the Swiss alpine region to apply, improve, and extend existing approaches dealing with the positioning of photographs within a terrain model, appropriate georectification, and the automatic snow classification of such photographs. In this presentation, we provide an overview of the implemented procedure and demonstrate how our registration approach automatically resolves the orientation of a webcam by using a high-resolution digital elevation model and the webcam's position. This allows snow-classified pixels of webcam images to be related to their real-world coordinates. We present several examples of resulting snow cover maps, which have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or not visible from webcams' positions. The procedure is expected to work under almost any weather condition and demonstrates the feasibility of using webcams for the retrieval of high-resolution snow cover information.

  10. SUBGRID PARAMETERIZATION OF SNOW DISTRIBUTION FOR AN ENERGY AND MASS BALANCE SNOW COVER MODEL. (R824784)

    EPA Science Inventory

    Representation of sub-element scale variability in snow accumulation and ablation is increasingly recognized as important in distributed hydrologic modelling. Representing sub-grid scale variability may be accomplished through numerical integration of a nested grid or through a l...

  11. Snow modeling in the Klamath River Basin: understanding the factors controlling snow distribution and melt

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Point and spatially distributed models have been applied to the 4053 km2 Sprague River Basin which is one of three main tributaries to the Upper Klamath Basin in Southern Oregon, USA. The simulations cover entire water years to understand the physics controlling snow distribution during the accumul...

  12. Interface control and snow crystal growth

    NASA Astrophysics Data System (ADS)

    Li, Jessica; Schaposnik, Laura P.

    2016-02-01

    The growth of snow crystals is dependent on the temperature and saturation of the environment. In the case of dendrites, Reiter's local two-dimensional model provides a realistic approach to the study of dendrite growth. In this paper we obtain a new geometric rule that incorporates interface control, a basic mechanism of crystallization that is not taken into account in the original Reiter model. By defining two new variables, growth latency and growth direction, our improved model gives a realistic model not only for dendrite but also for plate forms.

  13. Interface control and snow crystal growth.

    PubMed

    Li, Jessica; Schaposnik, Laura P

    2016-02-01

    The growth of snow crystals is dependent on the temperature and saturation of the environment. In the case of dendrites, Reiter's local two-dimensional model provides a realistic approach to the study of dendrite growth. In this paper we obtain a new geometric rule that incorporates interface control, a basic mechanism of crystallization that is not taken into account in the original Reiter model. By defining two new variables, growth latency and growth direction, our improved model gives a realistic model not only for dendrite but also for plate forms. PMID:26986434

  14. Systematics of snow voles (Chionomys, Arvicolinae) revisited.

    PubMed

    Yannic, Glenn; Burri, Reto; Malikov, Vladimir G; Vogel, Peter

    2012-03-01

    To elucidate the evolutionary history of snow voles, genus Chionomys, we studied the phylogeography of Chionomysnivalis across its range and investigated its relationships with two congeneric species, Chionomysgud and Chionomysroberti, using independent molecular markers. Analyses were based on mitochondrial (~940 bp cyt b) and Y-chromosomal (~2020 bp from three introns) genetic variation. Our data provide conclusive evidence for a Caucasian and Middle Eastern origin for the three species and a subsequent westward expansion of C.nivalis. In addition, we discuss the taxonomic status of the genus Chionomys in relation to the genus Microtus. PMID:22182990

  15. Propagation Tests in SnowPilot

    NASA Astrophysics Data System (ADS)

    Bair, N.; Birkeland, K.; Chabot, D.

    2013-12-01

    The Extended Column Test (ECT) and the Propagation Saw Test (PST) show crack propagation, a fundamental part of the avalanche process. Many studies have examined the accuracy of these tests at predicting stability, but only a few compare the tests side-by-side. Side-by-side tests are the only way to fully control for the many factors that affect crack propagation. Moreover, most of the comparisons have been from research data. We have limited knowledge of how these tests are being used by avalanche professionals and backcountry travelers. SnowPilot is the largest public database of stability tests in the world. In this study, we examine 256 snow pits from the SnowPilot database with 513 ECTs and 345 PSTs conducted side-by-side. Because results of the ECT and PST cannot be directly compared, we simplify test results by classifying them as unstable or stable. We classify a test result as unstable if it is 'ECTP/ECTPV' or 'PST End' with a cut length ≤ 50 cm; otherwise we classify a test result as stable. We find that: 1) PSTs showed unstable results more often than ECTs, 2) the subjective stability rating ('stability on similar slopes') was correlated with ECT stability, but not with PST stability, 3) PSTs were used on deeper slabs than ECTs, and 4) PST use increased with a decreasing stability rating, relative to ECT use. Result (1) is supported by 2 of 3 other studies with side-by-side tests. We suggest a potentially larger 'cracked' area in the PST as one cause, resulting in a larger crack nucleus and increased edge effects that promote propagation. Result (1) contradicts previous work that shows the PST has a higher false-stable rate than the ECT. One would expect Result (1) to cause a lower false-stable rate. Result (2) shows that either the ECT is an accurate test or that users are basing their stability assessment on ECT stability results. This correlation is problematic for studies that use SnowPilot's stability field to infer test accuracy. Result (3

  16. Spatial accounting for errors in LiDAR-derived products: Snow volume and snow water equivalent estimation

    NASA Astrophysics Data System (ADS)

    Tinkham, W. T.; Hoffman, C. M.; Falkowski, M. J.; Smith, A. M.; Link, T. E.; Marshall, H.

    2011-12-01

    Light Detection and Ranging (LiDAR) has become one of the most effective and reliable means of characterizing surface topography and vegetation structure. Most LiDAR-derived estimates such as vegetation height, snow depth, and floodplain boundaries rely on the accurate creation of digital terrain models (DTM). As a result of the importance of an accurate DTM in using LiDAR data to estimate snow depth, it is necessary to understand the variables that influence the DTM accuracy in order to assess snow depth error. A series of 4 x 4 m plots that were surveyed at 0.5 m spacing in a semi-arid catchment were used for training the Random Forests algorithm along with a series of 35 variables in order to spatially predict vertical error within a LiDAR derived DTM. The final model was utilized to predict the combined error resulting from snow volume and snow water equivalent estimates derived from a snow-free LiDAR DTM and a snow-on LiDAR acquisition of the same site. The methodology allows for a statistical quantification of the spatially-distributed error patterns that are incorporated into the estimation of snow volume and snow water equivalents from LiDAR.

  17. Simulation of Seasonal Snow Microwave TB Using Coupled Multi-Layered Snow Evolution and Microwave Emission Models

    NASA Technical Reports Server (NTRS)

    Brucker, Ludovic; Royer, Alain; Picard, Ghislain; Langlois, Alex; Fily, Michel

    2014-01-01

    The accurate quantification of SWE has important societal benefits, including improving domestic and agricultural water planning, flood forecasting and electric power generation. However, passive-microwave SWE algorithms suffer from variations in TB due to snow metamorphism, difficult to distinguish from those due to SWE variations. Coupled snow evolution-emission models are able to predict snow metamorphism, allowing us to account for emissivity changes. They can also be used to identify weaknesses in the snow evolution model. Moreover, thoroughly evaluating coupled models is a contribution toward the assimilation of TB, which leads to a significant increase in the accuracy of SWE estimates.

  18. Unmanned Aerial Vehicle Remote Sensing of Shallow Snow: Assessment and Possibilities for Improved Snow Depletion Prediction

    NASA Astrophysics Data System (ADS)

    Harder, P.; Pomeroy, J. W.; Helgason, W.

    2015-12-01

    Unmanned Aerial Vehicles (UAVs) have been enthusiastically adopted by many earth scientists due to their ability to provide Digital Surface Models (DSM) and orthomosaics of unprecedented spatial and temporal resolution. These datasets have great potential to advance the prediction of snow hydrology in particular but have had little testing in areas of shallow snowcover. To assess the utility and possibilities of UAV data products for quantifying and predicting the properties and processes of shallow snowcovers, an intensive field campaign took place during the 2015 melt season in a prairie agricultural field in Saskatchewan, Canada. The wheat field with standing stubble (15-35cm) had little topographic relief, a shallow snow (peak <40cm) and became patchy as snowcovered area declined during melt. Over the 25-day melt period 24 flights were performed with a Sensefly Ebee UAV to map the 120 hectare area. Structure from motion techniques, as implemented in Postflight Terra 3D software, generated DSMs and orthomosaics at a 3.5 cm resolution. Orthomosaic analysis quantified snowcovered area at unprecedented accuracy and frequency allowing for new insights into the spatial characteristics of the snowcover depletion process. However,