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Sample records for 8-day composite snow

  1. 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

  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. MODIS Snow-Cover Products

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  4. Microbial community structure, pigment composition, and nitrogen source of red snow in Antarctica.

    PubMed

    Fujii, Masanori; Takano, Yoshinori; Kojima, Hisaya; Hoshino, Tamotsu; Tanaka, Ryouichi; Fukui, Manabu

    2010-04-01

    "Red snow" refers to red-colored snow, caused by bloom of cold-adapted phototrophs, so-called snow algae. The red snow found in Langhovde, Antarctica, was investigated from several viewpoints. Various sizes of rounded red cells were observed in the red snow samples under microscopy. Pigment analysis demonstrated accumulation of astaxanthin in the red snow. Community structure of microorganisms was analyzed by culture-independent methods. In the analyses of small subunit rRNA genes, several species of green algae, fungus, and various phylotypes of bacteria were detected. The detected bacteria were closely related to psychrophilic or psychrotolerant heterotrophic strains, or sequences detected from low-temperature environments. As predominant lineage of bacteria, members of the genus Hymenobacter were consistently detected from samples obtained in two different years. Nitrogen isotopic compositions analysis indicated that the red snow was significantly 15N-enriched. Based on an estimation of trophic level, it was suggested that primary nitrogen sources of the red snow were supplied from fecal pellet of seabirds including a marine top predator of Antarctica.

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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

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

    USGS Publications Warehouse

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

    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.

  12. 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.

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

    Hinkley, Todd K.

    1994-08-01

    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.

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

    PubMed

    Ermakov, A A; Karpova, E A; Malysheva, A G; Mikhaylova, R I; Ryzhova, I N

    2014-01-01

    Monitoring of snow cover pollution as an indicator of ambient air pollution in 20 districts in the Moscow region during 2009-2013 was performed. The identification with a quantitative assessment of a wide array of organic compounds and the control of the main physical and chemical and inorganic indices of snow water pollution were carried out. More than 60 organic substances for most of which there are no the hygienic standards were established. The assessment of pollution levels of basic inorganic indices was given by means of the comparing them with the average values in the snow cover in the European territory of Russia and natural content in areas not been exposed to human impact.

  10. Characterization of organic composition in snow and surface waters in the Athabasca Oil Sands Region, using ultrahigh resolution Fourier transform mass spectrometry.

    PubMed

    Yi, Y; Birks, S J; Cho, S; Gibson, J J

    2015-06-15

    This study was conducted to characterize the composition of dissolved organic compounds present in snow and surface waters in the Athabasca Oil Sands Region (AOSR) with the goal of identifying whether atmospherically-derived organic compounds present in snow are a significant contributor to the compounds detected in surface waters (i.e., rivers and lakes). We used electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICR MS) to characterize the dissolved organic compound compositions of snow and surface water samples. The organic profiles obtained for the snow samples show compositional differences between samples from near-field sites (<5 km from oil sands activities) and those from more distant locations (i.e., far-field sites). There are also significant compositional differences between samples collected in near-field sites and surface water samples in the AOSR. The composition of dissolved organic compounds at the upstream Athabasca River site (i.e., Athabasca River at Athabasca) is found to be different from samples obtained from downstream sites in the vicinity of oil sands operations (i.e., Athabasca River at Fort McMurray and Athabasca River at Firebag confluence). The upstream Athabasca River sites tended to share some compositional similarities with far-field snow deposition, while the downstream Athabasca River sites are more similar to local lakes and tributaries. This contrast likely indicates the relative role of regional snowmelt contributions to the Athabasca River vs inputs from local catchments in the reach downstream of Fort McMurray.

  11. 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.

  12. Concentration and composition of dust particles in surface snow at Urumqi Glacier No. 1, Eastern Tien Shan

    NASA Astrophysics Data System (ADS)

    Wu, Guangjian; Zhang, Xuelei; Zhang, Chenglong; Gao, Shaopeng; Li, Zhongqin; Wang, Feiteng; Wang, Wenbin

    2010-10-01

    Major, trace, and rare earth elements (REE) were determined by inductively coupled plasma-mass spectrometer (ICP-MS) for dust particles that were extracted from fresh surface snow samples collected weekly or biweekly between March 2006 and January 2008 at Urumqi Glacier No. 1 (UG1) in Eastern Tien Shan, Central Asia. The UG1 dust shows average Fe/Al ratios of 0.7, Ca/Al ratios of 0.35, La/Th ratios of 2.62, Th/U ratios of 3.31, an Eu anomaly of 0.63, and L/HREE ratios of 7.87. Seasonal variation is significant in dust concentration, but is not observed in dust composition, which remains rather uniform throughout the sampling period. The compositional homogeneity suggests that dust materials in UG1 are well mixed from their possible source areas. Fine materials from the Junggar Basin, and to a less extend from Tarim Basin, more closely resemble UG1 dust properties in their REE composition than do the local moraines, indicating that the dust in UG1 snow mainly comes from mid- to long-range source areas. The HYSPLIT model results suggest that the Westerlies, Arctic air masses and local winds are the main circulations for dust transport to Eastern Tien Shan.

  13. 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

  14. 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.

  15. Snow composition in eight catchments in the central barents Euro-Arctic region

    NASA Astrophysics Data System (ADS)

    Caritat, Patrice De; Äyräs, Matti; Niskavaara, Heikki; Chekushin, Viktor; Bogatyrev, Igor; Reimann, Clemens

    Snowpack samples representing atmospheric deposition during winter 1993-1994 were taken in eight catchments at different distances to the industry on the Kola Peninsula, NW Russia, and in contiguous areas of Norway and Finland. Snow was collected at 7-13 stations per catchment and delivered frozen to the laboratory. There, the samples were melted and filtered (<0.45 μm) on-line. Meltwater (MW) and filter residue (FR) fractions were analysed separately using ICP-MS and ICP-AES techniques. The ratios of FR to FR+MW concentrations show very characteristic patterns for the different industrial sources in the area. Nickel smelting at Monchegorsk results for example in predominantly water soluble deposition of Cu and S, while close to the ore roasting plant at Zapoljarniy these elements are mainly deposited in particulate form. For many elements more than 60% of the total deposition is particular in all catchments. The FR/(FR+MW) ratio of snow appears to be a useful tool to fingerprint pollution sources.

  16. 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.

  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. Temperature dependence of photosynthesis and thylakoid lipid composition in the red snow alga Chlamydomonas cf. nivalis (Chlorophyceae).

    PubMed

    Lukeš, Martin; Procházková, Lenka; Shmidt, Volha; Nedbalová, Linda; Kaftan, David

    2014-08-01

    Here, we report an effect of short acclimation to a wide span of temperatures on photosynthetic electron transfer, lipid and fatty acid composition in the snow alga Chlamydomonas cf. nivalis. The growth and oxygen evolution capacity were low at 2 °C yet progressively enhanced at 10 °C and were significantly higher at temperatures from 5 to 15 °C in comparison with the mesophilic control Chlamydomonas reinhardtii. In search of the molecular mechanisms responsible for the adaptation of photosynthesis to low temperatures, we have found unprecedented high rates of QA to QB electron transfer. The thermodynamics of the process revealed the existence of an increased structural flexibility that we explain with the amino acid changes in the D1 protein combined with the physico-chemical characteristics of the thylakoid membrane composed of > 80% negatively charged phosphatidylglycerol.

  19. 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%.

  20. 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.

  1. 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

  2. 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.

  3. 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…

  4. Regional variation in the chemical composition of winter snow pack and terricolous lichens in relation to sources of acid emissions in the Usa river basin, northeast European Russia.

    PubMed

    Walker, T R; Crittenden, P D; Young, S D

    2003-01-01

    The chemical composition of snow and terricolous lichens was determined along transects through the Subarctic towns of Vorkuta (130 km west-east), Inta (240 km south-north) and Usinsk (140 km, southwest-northeast) in the Usa river basin, northeast European Russia. Evidence of pollution gradients was found on two spatial scales. First, on the Inta transect, northward decreases in concentrations of N in the lichen Cladonia stellaris (from 0.57 mmol N g(-1) at 90 km south to 0.43 mmol N g(-1) at 130 km north of Inta) and winter deposition of non-sea salt sulphate (from 29.3 to 12.8 mol ha(-1) at 90 km south and 110 km north of Inta, respectively) were attributed to long range transport of N and S from lower latitudes. Second, increased ionic content (SO42-, Ca2+, K+) and pH of snow, and modified N concentration and the concentration ratios K+:Mg2+ and K+: (Mg2++Ca2+) in lichens (Cladonia arbuscula and Flavocetraria cucullata) within ca. 25-40 km of Vorkuta and Inta were largely attributed to local deposition of alkaline coal ash. Total sulphate concentrations in snow varied from ca. 5 micromol l(-1) at remote sites to ca. 19 micromol l(-1) near Vorkuta. Nitrate concentration in snow (typically ca. 9 micromol l(-1)) did not vary with proximity to perceived pollution sources.

  5. 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

  6. 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

  7. 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.

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

    NASA Astrophysics Data System (ADS)

    Ge, Y.; Gong, G.

    2006-12-01

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

  9. Snow Avalanches

    NASA Astrophysics Data System (ADS)

    Ancey, C.

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

  10. 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.

  11. 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.

  12. 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…

  13. 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.

  14. 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.

  15. 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)

  16. 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.

  17. 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…

  18. Spatial and temporal variation in Snow cover in Himalayas with Remotely sensed data

    NASA Astrophysics Data System (ADS)

    Ojha, S.

    2013-05-01

    Satellite remote sensing is an effective tool for monitoring snow covered area. However, complex terrain and heterogeneous land cover and the presence of clouds, impose challenges to snow cover mapping. This research analyzes snow cover and glaciers with a perspective of climate change in Himalayan Regions using remote sensing techniques. The remote sensing snow cover data from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite from 2000 to 2010 have been used to analyze some climate change indicators. In particular, the variability in the maximum snow extent with elevations, its temporal variability (8-day, monthly, seasonal and annual), its variation trend and its relation with temperature have been analyzed. The snow products used in this study are the maximum snow extent and fractional snow covers, which come in 8-day temporal and 500m and 0.05 degree spatial resolutions respectively. The results showed a tremendous potential of the MODIS snow product for studying the spatial and temporal variability of snow as well as the study of climate change impact in large and inaccessible regions like the Himalayas. The snow area extent (SAE) (%) time series exhibits similar patterns during seven hydrological years, even though there are some deviations in the accumulation and melt periods. The analysis showed relatively well inverse relation between the daily mean temperature and SAE during the melting period. Some important trends of snow fall are also observed. In particular, the decreasing trend in January and increasing trend in late winter and early spring may be interpreted as a signal of a possible seasonal shift. However, it requires more years of data to verify this conclusion. Significant coverage of lake ice was found in lower elevation zone which is due to flat terrain in this zone. Key Words: Climate change, Himalayas, MODIS, remote sensing, snow, lake ice.

  19. The impact of an 8-day intensive treatment for adolescent panic disorder and agoraphobia on comorbid diagnoses.

    PubMed

    Gallo, Kaitlin P; Chan, Priscilla T; Buzzella, Brian A; Whitton, Sarah W; Pincus, Donna B

    2012-03-01

    Previous research findings have shown positive effects of cognitive-behavioral therapy for primary anxiety disorders as well as for nonprimary, co-occurring anxiety disorders. In this study, we analyzed data from an existing randomized controlled trial of intensive treatment for panic disorder with or without agoraphobia (PDA) to examine the effects of the treatment on comorbid psychiatric diagnoses. The overall frequency and severity of aggregated comorbid diagnoses decreased in a group of adolescents who received an 8-day treatment for PDA. Results suggest that an 8-day treatment for PDA can alleviate the symptoms of some specific comorbid clinical diagnoses; in particular specific phobias, generalized anxiety disorder, and social phobia. These findings suggest that an intensive treatment for PDA is associated with reductions in comorbid symptoms even though disorders other than PDA are not specific treatment targets.

  20. 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).

  1. Microwave emissions from snow

    NASA Technical Reports Server (NTRS)

    Chang, A. T. C.

    1984-01-01

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

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

    PubMed

    Matsumoto, Naoyuki

    2009-01-01

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

  3. "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…

  4. 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

  5. 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...

  6. Let It Snow!

    NASA Astrophysics Data System (ADS)

    Williams, Kathryn R.

    2000-02-01

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

  7. Snow and Ice.

    ERIC Educational Resources Information Center

    Minneapolis Independent School District 275, Minn.

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

  8. Snow and Glacier Hydrology

    NASA Astrophysics Data System (ADS)

    Brubaker, Kaye

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

  9. 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.

  10. 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).

  11. 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…

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  13. 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

  14. 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).

  15. 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

  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. 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.

  18. Nordic Snow Radar Experiment

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  19. 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

  20. 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

  1. 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.

  2. 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...

  3. 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.

  4. 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.

  5. Snow White II.

    ERIC Educational Resources Information Center

    Gundy, Jan

    1978-01-01

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

  6. Snow White 5 Trench

    NASA Technical Reports Server (NTRS)

    2008-01-01

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

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

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

    This image has been enhanced to brighten shaded areas.

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

  7. '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.

  8. Saline Snow Surfaces and Arctic Bromine Activation

    NASA Astrophysics Data System (ADS)

    Pratt, K. A.; Custard, K. D.; Shepson, P.; Douglas, T. A.; Pöhler, D.; General, S.; Zielcke, J.; Platt, U.; Carlsen, M. S.; Tanner, D.; Huey, L. G.; Stirm, B.

    2012-12-01

    Following polar sunrise, tropospheric ozone levels often decrease rapidly to near zero, concurrent with mercury depletion and deposition. Despite our increasing understanding of the spatial variability of BrO and possible mechanisms based on laboratory studies, important questions remain regarding the most efficient sources of and mechanisms for Arctic halogen activation, leading to tropospheric ozone depletion. Rapid sea ice decline in the Arctic is expected to influence halogen activation and corresponding ozone and mercury depletion events. Therefore, an improved understanding of halogen activation is necessary to predict future changes in atmospheric chemical composition. During the March-April 2012 BRomine, Ozone, and Mercury EXperiment (BROMEX) in Barrow, Alaska, outdoor chamber experiments with snow and ice samples were conducted. Ozone was added as the precursor oxidant, and the samples were investigated with and without ambient sunlight. Samples included first-year sea ice, brine icicles, several layers of snow above first-year sea ice, and seasonal snow above the tundra. Chemical ionization mass spectrometry was utilized to monitor Br2 production, and ion chromatography was utilized to measure the bromide, chloride, nitrate, and sulfate content of the melted snow/ice samples. Surprisingly, tundra snow and drifting snow above sea ice produced the most Br2, with no production resulting from sea ice and basal snow directly above sea ice, suggesting more efficient production from samples characterized by greater acidity and lower chloride/bromide ratios. In addition, Br2 was only observed in the presence of sunlight, indicating the role of snowpack photolysis and the hydroxyl radical in its production. The observed trends in Br2 production may also help explain observations of inland hotspots in measured BrO by aircraft-based nadir MAX-DOAS (Multi Axis-Differential Optical Absorption Spectroscopy) measurements, conducted during the same field campaign. The

  9. 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

    2016-10-01

    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 ice. 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 have relied on strong assumptions to characterise snow reactive properties, which are not well defined. Air-snow exchange processes such as adsorption, solid-state diffusion, or co-condensation also affect snow chemical composition. Here, we present a physically based model of these processes for nitrate. Using as input a 1-year-long time series of atmospheric nitrate concentration measured at Dome C, Antarctica, our model reproduces with good agreement the nitrate measurements in the surface snow. By investigating the relative importance of the main exchange processes, this study shows that, on the one hand, the combination of bulk diffusion and co-condensation allows a good reproduction of the measurements (correlation coefficient r = 0.95), with a correct amplitude and timing of summer peak concentration of nitrate in snow. During winter, nitrate concentration in surface snow is mainly driven by thermodynamic equilibrium, whilst the peak observed in summer is explained by the kinetic process of co-condensation. On the other hand, the adsorption of nitric acid on the surface of the snow grains, constrained by an already existing parameterisation for the isotherm, fails to fit the observed variations. During winter and spring, the modelled concentration of adsorbed nitrate is respectively 2.5 and 8.3-fold higher than the measured one. A strong diurnal variation driven by the temperature cycle and a peak occurring in early spring are two other

  10. Evaluating observational methods to quantify snow duration under diverse forest canopies

    NASA Astrophysics Data System (ADS)

    Dickerson-Lange, Susan E.; Lutz, James A.; Martin, Kael A.; Raleigh, Mark S.; Gersonde, Rolf; Lundquist, Jessica D.

    2015-02-01

    Forests cover almost 40% of the seasonally snow-covered regions in North America. However, operational snow networks are located primarily in forest clearings, and optical remote sensing cannot see through tree canopies to detect forest snowpack. Due to the complex influence of the forest on snowpack duration, ground observations in forests are essential. We therefore consider the effectiveness of different strategies to observe snow-covered area under forests. At our study location in the Pacific Northwest, we simultaneously deployed fiber-optic cable, stand-alone ground temperature sensors, and time-lapse digital cameras in three diverse forest treatments: control second-growth forest, thinned forest, and forest gaps (one tree height in diameter). We derived fractional snow-covered area and snow duration metrics from the colocated instruments to assess optimal spatial resolution and sampling configuration, and snow duration differences between forest treatments. The fiber-optic cable and the cameras indicated that mean snow duration was 8 days longer in the gap plots than in the control plots (p < 0.001). We conducted Monte Carlo experiments for observing mean snow duration in a 40 m forest plot, and found the 95% confidence interval was ±5 days for 10 m spacing between instruments and ±3 days for 6 m spacing. We further tested the representativeness of sampling one plot per treatment group by observing snow duration across replicated forest plots at the same elevation, and at a set of forest plots 250 m higher. Relative relationships between snow duration in the forest treatments are consistent between replicated plots, elevation, and two winters of data.

  11. 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.

  12. Snow Radiance Assimilation Studies

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  13. '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.

  14. 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.

  15. Snow White Trenches

    NASA Technical Reports Server (NTRS)

    2008-01-01

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

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

    This image has been enhanced to brighten shaded areas.

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

  16. Community variability of bacteria in alpine snow (Mont Blanc) containing Saharan dust deposition and their snow colonisation potential.

    PubMed

    Chuvochina, Maria S; Marie, Dominique; Chevaillier, Servanne; Petit, Jean-Robert; Normand, Philippe; Alekhina, Irina A; Bulat, Sergey A

    2011-01-01

    Microorganisms uplifted during dust storms survive long-range transport in the atmosphere and could colonize high-altitude snow. Bacterial communities in alpine snow on a Mont Blanc glacier, associated with four depositions of Saharan dust during the period 2006-2009, were studied using 16S rRNA gene sequencing and flow cytometry. Also, sand from the Tunisian Sahara, Saharan dust collected in Grenoble and Mont Blanc snow containing no Saharan dust (one sample of each) were analyzed. The bacterial community composition varied significantly in snow containing four dust depositions over a 3-year period. Out of 61 phylotypes recovered from dusty snow, only three phylotypes were detected in more than one sample. Overall, 15 phylotypes were recognized as potential snow colonizers. For snow samples, these phylotypes belonged to Actinobacteria, Proteobacteria and Cyanobacteria, while for Saharan sand/dust samples they belonged to Actinobacteria, Bacteroidetes, Deinococcus-Thermus and Proteobacteria. Thus, regardless of the time-scale, Saharan dust events can bring different microbiota with no common species set to alpine glaciers. This seems to be defined more by event peculiarities and aeolian transport conditions than by the bacterial load from the original dust source.

  17. 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+).

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  19. 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.

  20. Evaluating Observational Methods to Quantify Snow Duration under Diverse Forest Canopies

    NASA Astrophysics Data System (ADS)

    Dickerson-Lange, S. E.; Lutz, J. A.; Martin, K.; Raleigh, M. S.; Gersonde, R.; Lundquist, J. D.

    2014-12-01

    Forests cover over 40% of the seasonally snow-covered regions in North America. However, operational snow networks are located primarily in forest clearings, and optical remote sensing cannot see through tree canopies to detect forest snowpack. Due to the complex influence of the forest on snowpack duration, ground observations in forests are essential. We therefore consider the effectiveness of different strategies to observe snow covered area under forests. At our study location in the Pacific Northwest, we simultaneously deployed fiber-optic cable, stand-alone ground temperature sensors, and time-lapse digital cameras in three different forest treatments: control second-growth forest, thinned forest, and forest gaps (one tree height in diameter). We derived fractional snow covered area and snow duration metrics from the co-located instruments to assess optimal spatial resolution and sampling configuration. The fiber-optic cable and the camera detected a significant difference of 8 days in mean snow duration between the gap and control plots. Monte Carlo experiments based on our results suggest that 10 m spacing of self-recording ground temperature sensors across a 40 m forest plot will capture mean snow duration to ± 5 days whereas 6 m spacing reduces the 95% confidence interval to ± 3 days. We further tested the representativeness of sampling one plot per treatment group by observing snow duration across replicated forest plots at the same elevation, and at a set of forest plots 250 m higher. Relative relationships between snow duration in the forest treatments are consistent between replicated plots, elevation, and two winters of data.

  1. Snow White Trench (Animation)

    NASA Technical Reports Server (NTRS)

    2008-01-01

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

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

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

  2. '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.

  3. Phoenix's Snow White Trench

    NASA Technical Reports Server (NTRS)

    2008-01-01

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

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

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

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

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

    PubMed

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

    2016-10-01

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

  5. Tyzzer's disease in snow leopards.

    PubMed

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

    1984-01-01

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

  6. Tyzzer's disease in snow leopards.

    PubMed

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

    1984-01-01

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

  7. 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

  8. 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.

  9. 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

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

    PubMed

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

    2014-01-01

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

  11. Comparison of Northern Hemisphere Snow Cover Data Sets.

    NASA Astrophysics Data System (ADS)

    Scialdone, John; Robock, Alan

    1987-01-01

    Four Northern Hemisphere snow cover data sets are compared on a weekly basis for the 25-month period, July 1981 through July 1983. The data sets are the NOAA/NESDIS Weekly Snow and Ice Chart, the Composite Minimum Brightness (CMB) Chart, the U.S. Weekly Weather and Crop Bulletin (data only for North America), and Air Form data. The NOAA/NESDIS chart is produced through the use of photo-interpretation of visible satellite imagery and ground observations. The U.S. Crop Bulletin is also done manually, using only ground observations. The CMB chart and the Air Force data are both produced using automated processes, the first by way of visible satellite imagery and the second by way of ground observations, climatology, satellite observations and persistence. Since the NOAA/NESDIS chart is the only standard and complete data set dating back to the mid 1960s, it is used as the basis for the study. The main emphasis of this paper is a comparison of the CMB and the NOAA/NESDIS chart.The CMB frequently overestimated snow cover, especially the southward extent of the main snow boundary and area far from the snow boundary which were not present on the NOAA/NESDIS chart. On numerous occasions, the outline of mountain ranges was either distorted or totally missed by the CMB. The CMB also underestimated snow cover, especially in densely forested areas. Other regions of underestimation by the CMB can be attributed to the bias factor of the NOAA/NESDIS chart. (The NOAA/NESDIS chart uses the latest snow cover information while the CMB is composited over a week.) The U.S. Crop Bulletin agreed fairly well with the NOAA/NESDIS chart cast of the Rockies, but often differed to the west. The Air Force data set, an undocumented operational product, differed quite a bit from the NOAA/NESDIS chart.

  12. 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.

  13. 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

  14. Microbial preference for different size classes of organic carbon: a study from Antarctic snow.

    PubMed

    Antony, Runa; Mahalinganathan, K; Krishnan, K P; Thamban, Meloth

    2012-10-01

    Significance of carbon cycling in polar ecosystems is well recognized. Yet, bacteria in surface snow have received less attention in terms of their potential in carbon cycling. Here, we present results on carbon utilization by bacterial communities in three surface snow samples from Antarctica collected along a coastal to inland transect. Microcosm studies were conducted over 8 days at 5 ± 1°C to study carbon metabolism in different combinations of added low molecular weight (LMW (glucose, <1 kDa)) and high molecular weight (HMW (starch, >1 kDa)) substrates (final 20 ppm). The total organic carbon (TOC) in the snow samples decreased with time at rates ranging from non-detectable to 1.4 ppm day(-1) with rates highest in snow samples from inland region. In addition, carbon utilization studies were also carried out with bacterial isolates LH1, LH2, and LH4 belonging to the genus Cellulosimicrobium, Bacillus, and Ralstonia, respectively, isolated from the snow samples. Studies with strain LH2 in different amendments of glucose and starch showed that TOC decreased with time in all amendments at a rate of 0.9-1.5 ppm day(-1) with highest rates of 1.4-1.5 ppm day(-1) in amendments containing a higher proportion of starch. The bacterial isolates were also studied to determine their ability to utilize other LMW and HMW compounds. They utilized diverse substrates like carbohydrates, amino acids, amines, amides, complex polymers, etc., of molecular mass <100 Da, 100-500 Da, >500 Da-1 kDa, and >1 kDa preferring (up to 31 times) substrates with mass of >1 kDa than <1 kDa. The ability of bacteria in snow to utilize diverse LMW and HMW substrates indicates that they could be important in the uptake of similar compounds in snow and therefore potentially govern snow chemistry.

  15. Seasonal variations of snow chemistry and mineral dust in the snow pit at GV7, Antarctica

    NASA Astrophysics Data System (ADS)

    Kang, Jung-Ho; Hwang, Heejin; Han, Yongchoul; Hong, Sang Bum; Lee, Khanghyun; Do Hur, Soon; Frezzotti, Massimo; Narcisi, Biancamaria

    2015-04-01

    We conducted the scientific ice coring project led by PNRA and KOPRI during the 2013/2014 Italian-Korean Antarctic Expedition in the framework of International Partnerships in Ice Core Science (IPICS) to understand the climatic variability in the last 2000 years. In the part of project, we collected a 3.0 m-depth snow pit at the site of GV7 (S 70° 41'17.1", E 158° 51'48.9", 1950 m a.s.l.), Antarctica. Here, we present the results obtained from the analysis of the water isotope compositions, the major ion concentrations, and the mineral dust concentrations from the snow pit. Snow densities and temperatures also measured in the field. At KOPRI, the samples were melted, then the stable water isotopes, major ions, and particle size distribution were analyzed with the cavity ring-down spectrometers (L1102-i, Piccaro), ion chromatography (ICS-2100, Thermo), and coulter counter (Multisizer 3, Beckman Coulter), respectively. The δ18O varies between -38.3 and -24.1o with a mean value of -31.0o. The δD ranges between -331 and -186o with a mean value of -243o. Among the ion concentrations (Na+, Ca2+, Mg2+, Cl-, SO42-, CH3SO3-(MSA)) from the snow pit, MSA concentrations show a clear seasonal variation. The mineral dust in the pit characterized with the differences of the concentration and the particle size distribution by the seasonality. These data allow us to assume about 4.5 years of snow deposition covered from 2009 to 2013 by these oscillations of the isotopes and geochemical characteristics.

  16. 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 ...

  17. 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

  18. 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)

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Schneider, D.; Molotch, N. P.

    2015-12-01

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

  1. 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.

  2. 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.

  3. 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.

  4. Snow Bedforms Create the Surface Roughness of Polar Snow

    NASA Astrophysics Data System (ADS)

    Filhol, S.; Sturm, M.

    2015-12-01

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

  5. Black carbon aerosol size in snow.

    PubMed

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

    2013-01-01

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

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. Effect of 8 days of a hypergravity condition on the sprinting speed and lower-body power of elite rugby players.

    PubMed

    Barr, Matthew J; Gabbett, Tim J; Newton, Robert U; Sheppard, Jeremy M

    2015-03-01

    -Sprinting speed and lower-body power are considered to be key physical abilities for rugby players. A method of improving the lower-body power of athletes is simulated hypergravity. This method involves wearing a weighted vest at all times during the day for an extended period of time. There are no studies that have examined the effect of hypergravity on speed or the benefit for rugby players. An experimental group (n = 8) and a control group (n = 7) of national team rugby players took part in the study, which consisted of rugby, conditioning, speed, and strength sessions. The experimental group wore a weighted vest equating to 12% of their body mass for 8 days. All players were tested for speed and lower-body power before, 2 days after, and 9 days after the intervention. Speed testing involved the athletes completing 40-m sprints with timing lights and high-speed video cameras assessing acceleration and maximal velocity sprinting kinematics. Lower-body power was assessed using weighted countermovement jumps (CMJs). No group differences were found for sprinting speed at any point. The experimental group displayed a large decrease in acceleration ground contact time (-0.01 ± 0.005 s, d = 1.07) and a moderate increase in 15-kg CMJ velocity (0.07 ± 0.11 m·s, d = 0.71). Individual responses showed that players in the experimental group had both negative and positive speed and power responses to the training intervention. Simulated hypergravity for 8 days is likely ineffective at improving sprinting speed while undergoing standard rugby training.

  11. Snow Micro-Structure Model

    2014-06-25

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

  12. Snow Micro-Structure Model

    SciTech Connect

    Micah Johnson, Andrew Slaughter

    2014-06-25

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

  13. 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‰).

  14. Winter stream temperature in the rain-on-snow zone

    NASA Astrophysics Data System (ADS)

    Leach, J. A.; Moore, R. D.

    2012-12-01

    Stream temperature is a principal determinant of aquatic ecosystem composition and productivity. There are increasing concerns that changes in land cover and climatic conditions could produce changes in stream thermal regimes that would be deleterious to existing aquatic communities. Most stream temperature research has focused on summer periods and few studies have examined winter periods despite the growing recognition of its biological importance. The winter thermal regimes of Pacific Northwest headwater streams, which provide vital winter habitat for salmonids and their food sources, may be particularly sensitive to changes in climate because they can remain ice-free throughout the year and are often located in rain-on-snow zones. This study examined winter stream temperature patterns and controls in small headwater catchments within the rain-on-snow zone at the Malcolm Knapp Research Forest, near Vancouver, British Columbia, Canada. Two working hypotheses were addressed by this study: (1) winter stream temperatures are primarily controlled by advective fluxes associated with runoff processes and (2) stream temperatures should be depressed during rain-on-snow events, compared to rain on bare ground, due to the cooling effect of rain passing through the snowpack prior to infiltrating the soil or being delivered to the stream as saturation-excess overland flow. These hypotheses were tested statistically using historical stream temperature data and modelled snowpack dynamics for a forested headwater catchment. When snow was not present, daily stream temperature during winter rain events tended to increase with increasing air temperature. However, when snow was present, stream temperature was capped at about 5 °C, regardless of air temperature. This historical analysis was complemented with detailed field data collected during the winter of 2011-2012 from an ongoing field study in a partially logged catchment. Stream temperature response to a large rain-on-snow

  15. 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.

  16. Mercury fate in ageing and melting snow: development and testing of a controlled laboratory system.

    PubMed

    Mann, Erin; Meyer, Torsten; Mitchell, Carl P J; Wania, Frank

    2011-10-01

    A snow cover can modify when, to what extent, and in what form atmospherically deposited mercury is released to the underlying surface media and/or back to the atmosphere. Investigations of mercury transport and transformation processes in snow packs are hampered by the difficulty in controlling experimental and melt conditions and due to the huge variability in the composition and physical structure of environmental snow packs. A method was developed that allows the detailed mechanistic investigation of mercury fate in snow that is made, aged and melted under controlled laboratory conditions. A number of control samples established that mercury in indoor air, scavenged during the snow making process, constitutes the dominant source of mercury in the artificial snow. No addition of mercury is required. The amount of mercury in fresh snow was quantitatively (102 and 106% in two experiments) recovered in the dissolved and particulate fractions of the melt water and the vessel head space, confirming a mass balance for mercury and the absence of unquantifiable mercury sources and sinks in the experimental system. In snow made from unmodified tap water, more than half of the mercury present in the snowpack was recovered from the bottom of the snow vessel after all of the snow had melted. Such late elution is indicative of mercury being mostly associated with particles that are filtered by, and retained in, the shrinking snowpack. Addition of salt to the snow-making water at an environmentally realistic pH notably shifted the distribution of mercury in the snowpack from the particulate to the dissolved phase, resulting in more than 60% of the mercury eluting in the dissolved phase of early melt water fractions.

  17. Lake Effect Snow Covers Buffalo

    NASA Technical Reports Server (NTRS)

    2002-01-01

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

  18. 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

  19. 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.

  20. Periodontal status in snow leopards.

    PubMed

    Cook, R A; Stoller, N H

    1986-11-01

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

  1. Summer C Fixation of Salix arctic is Altered by Prior Winter Snow Regimes: Photosynthetic Responses to Long-Term Snow Increases in the High Arctic of NW Greenland

    NASA Astrophysics Data System (ADS)

    Leffler, A.; Welker, J. M.; Sullivan, P. F.; Maseyk, K. S.

    2012-12-01

    Climate models and snow measurements on Greenland show increased precipitation in addition to warming in the High Arctic. Because polar semi-deserts may be water limited, additional snow and snow melt water, may alleviate mid-summer drought and promote additional carbon fixation. We investigated the long-term (10 years of experimental snow increases) consequences of additional winter snow as it effects subsequent summer gas exchange of Salix arctica in a polar semi-desert tundra ecosystem in NW Greenland (76.6N, 68.6W). In 2011, measurements of gas exchange physiology were conducted along a transect from high to ambient snow accumulation in mid-July. In 2012, gas exchange was measured in high and ambient snow zones between late June and early August. In 2012, the seasonal patterns of δ18O of xylem water and soil water between 5 and 20 cm below the soil surface was measured to determine if snow accumulation influences the water sources and depth of water used by S. arctica. In 2011, photosynthesis in the deep snow zones was lower than in the ambient snow zone; similar results were observed for leaf N content. Carbon isotope composition (δ13C) of S. arctica leaves did not differ between deep and ambient snow zones suggesting a similar season-long relationship between photosynthesis and stomatal conductance in both locations. In 2012, there was a trend towards higher photosynthesis at the height of the growing season in the deep snow zones. Light response curves in 2012 suggest higher maximum photosynthesis in the deep snow zones compared to the ambient zones. Regardless of prior winter snow accumulation, S. arctica appears to derive nearly all its xylem water from the top 5 cm of the soil. There is little evidence that differences in photosynthetic physiology result directly from increased soil moisture associated with high snow, rather the effect appears more complex. Much of the increased snow accumulation will run-off of these systems when the soils are still

  2. New Energy-efficient Snow production

    NASA Astrophysics Data System (ADS)

    Rhyner, H.

    2009-04-01

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

  3. 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.

  4. Microwave scattering properties of snow fields

    NASA Technical Reports Server (NTRS)

    Angelakos, D. J.

    1977-01-01

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

  5. 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.

  6. Progress in AMSR Snow Algorithm Development

    NASA Technical Reports Server (NTRS)

    Chang, Alfred; Koike, Toshio

    1998-01-01

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

  7. 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 ...

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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.

  14. 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.

  15. 'Snow White' and Language Awareness.

    ERIC Educational Resources Information Center

    Larson, Deborah Aldrich

    1987-01-01

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

  16. 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

  17. Modeling of photochemical reactions in surface snow: Comparison with field measurements obtained during the OASIS spring campaign 2009 at Barrow, AK

    NASA Astrophysics Data System (ADS)

    Bock, Josué; Jacobi, Hans-Werner

    2010-05-01

    The boundary layer composition in polar or snow covered regions is strongly affected by physical and chemical processes, which take place in the surface snow. Photolysis reactions initiated by solar radiation are particularly important. Among the reactive chemical species present in snow, nitrate can be ubiquitously found and is known to be photolyzed to produce nitrogen oxides, which are subsequently released to the overlying atmosphere. We developed a reaction mechanism for N-containing species in snow to describe the transformation of nitrate to NOx. Laboratory experiments using artificial snow were used to constrain a box model including the snow nitrate chemistry. This allowed to identify major reactions occurring after the photolysis of nitrate as an initial step. The mechanism was further extended to include reactions of hydrogen peroxide and formaldehyde. Finally, the box model was applied to investigate the surface snow chemistry in a natural, polar environment. The model was compared to results obtained in a 36-hour experiment carried out during the OASIS spring campaign 2009 at Barrow, AK. During this period, surface snow samples were collected every 2 hours in order to monitor the concentration evolution of the major reactive species in the snow. The samples were analyzed for compounds like nitrate, nitrite, formaldehyde, hydrogen peroxide, and further non-reactive sea salt components. Moreover, photolysis rates of nitrate, nitrite, and hydrogen peroxide in the snow were calculated based on measurements of in-snow spectral irradiance at different depths within the snow. The box model for snow chemistry was applied to this data set and used to elucidate the role of the various (photo)chemical reactions in the overall budgets of the measured species. Moreover, the effect of the chemical and physical processes on the composition of snow and the exchange of reactive compounds between the surface snow and the atmospheric boundary layer will be presented.

  18. 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.

  19. Heat generation during metamorphic processes in snow

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  20. 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

  1. 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

  2. A stable snow-atmosphere coupled mode

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  3. 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.

  4. 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.

  5. Microbial diversity in alpine tundra soils correlates with snow cover dynamics.

    PubMed

    Zinger, Lucie; Shahnavaz, Bahar; Baptist, Florence; Geremia, Roberto A; Choler, Philippe

    2009-07-01

    The temporal and spatial snow cover dynamics is the primary factor controlling the plant communities' composition and biogeochemical cycles in arctic and alpine tundra. However, the relationships between the distribution of snow and the diversity of soil microbial communities remain largely unexplored. Over a period of 2 years, we monitored soil microbial communities at three sites, including contiguous alpine meadows of late and early snowmelt locations (LSM and ESM, respectively). Bacterial and fungal communities were characterized by using molecular fingerprinting and cloning/sequencing of microbial ribosomal DNA extracted from the soil. Herein, we show that the spatial and temporal distribution of snow strongly correlates with microbial community composition. High seasonal contrast in ESM is associated with marked seasonal shifts for bacterial communities; whereas less contrasted seasons because of long-lasting snowpack in LSM is associated with increased fungal diversity. Finally, our results indicate that, similar to plant communities, microbial communities exhibit important shifts in composition at two extremes of the snow cover gradient. However, winter conditions lead to the convergence of microbial communities independently of snow cover presence. This study provides new insights into the distribution of microbial communities in alpine tundra in relation to snow cover dynamics, and may be helpful in predicting the future of microbial communities and biogeochemical cycles in arctic and alpine tundra in the context of a warmer climate.

  6. The Inverted Snow Globe Shadow

    NASA Astrophysics Data System (ADS)

    Ribeiro, Jair Lúcio Prados

    2015-01-01

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

  7. Dirty snow after nuclear war

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  8. 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.

  9. [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.

  10. Digging of 'Snow White' Begins

    NASA Technical Reports Server (NTRS)

    2008-01-01

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

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

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

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

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

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

    PubMed

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

    2014-10-01

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

  12. 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.

  13. Long-term increases in snow pack elevate leaf N and photosynthesis in Salix arctica: responses to a snow fence experiment in the High Arctic of NW Greenland

    NASA Astrophysics Data System (ADS)

    Leffler, A. Joshua; Welker, Jeffery M.

    2013-06-01

    We examine the influence of altered winter precipitation on a High Arctic landscape with continuous permafrost. Gas exchange, leaf tissue element and isotopic composition (N, δ13C, δ15N), and plant water sources derived from stem and soil water δ18O were examined in Salix arctica (arctic willow) following a decade of snow-fence-enhanced snow pack in NW Greenland. Study plots in ambient and +snow conditions were sampled in summer 2012. Plants experiencing enhanced snow conditions for 10 years had higher leaf [N], photosynthetic rate, and more enriched leaf δ15N. Enhanced snow did not influence stomatal conductance or depth of plant water use. We attribute the higher photosynthetic rate in S. arctica exposed to deeper snow pack to altered biogeochemical cycles which yielded higher leaf [N] rather than to enhanced water availability. These data demonstrate the complexity of High Arctic plant responses to changes in winter conditions. Furthermore, our data depict the intricate linkages between winter and summer conditions as they regulate processes such as leaf gas exchange that may control water vapor and CO2 feedbacks between arctic tundra and the surrounding atmosphere.

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

    NASA Astrophysics Data System (ADS)

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

    2010-07-01

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

  15. 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

  16. 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

  17. Observing and documenting the snow surface processes creating the isotopic signal in the snow at Summit, Greenland

    NASA Astrophysics Data System (ADS)

    Steen-Larsen, H. C.; Noone, D.; Berkelhammer, M.; Schneider, D.; White, J.; Steffen, K.

    2012-04-01

    Only very limited understanding of the physical processes influencing the formation of the isotopic signal observed in the snow in Greenland and Antarctica exist. Current knowledge is to a large extend based on more or less ad hoc assumptions and observed empirical relations. During the spring of 2011 a suite of state of the art instruments were installed at the NSF-operated station, Summit, on top of the Greenland Ice Sheet. The instruments package includes measurements performed at several heights (from 0.1 m to 50 meter) above the snow surface by sonic anemometers, high precision temperature sensors, particle size and shape spectrometers, and isotopic water vapor spectrometers. To support the interpretation of the above snow surface measurements an array of temperature and pressure sensors as well as inlets for measuring the interstitial isotopic water vapor composition were installed to a depth of 1.0 meter. We present here the setup and the preliminary results that have come out of the installed suite of instruments together with the projection of these observations. Especially we focus on the following three questions: 1) What is the variation in isotopic composition caused by changes in source conditions? 2) What is the influence of differing cloud microphysics on the isotopic composition of snow? 3) To what degree are the aspects of the atmospheric hydrology masked in the ice core record due to post-depositional processes. The instruments installed at Summit is planned to be continuously operational for the following three years thereby providing key information of the year round processes.

  18. 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

  19. 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.

  20. 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.

  1. New nitrogen uptake strategy: specialized snow roots.

    PubMed

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

    2009-08-01

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

  2. Remotely Measuring Snow Depth in Inaccessible Terrain

    NASA Astrophysics Data System (ADS)

    Dixon, D.; Boon, S.

    2010-12-01

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

  3. 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.

  4. 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

  5. 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

  6. Snow Cover Mapping in the Northern Area of Pakistan and Jammu Kashmir (hindu Kush Himalayas) Using Ndsi, Unmixing Method and Srtm dem Data

    NASA Astrophysics Data System (ADS)

    Kim, H.; Din, A. U.; Oki, K.; Takeuchi, W.; Oki, T.

    2015-12-01

    Snow area measurement is very important for hydrologists, glaciologists and for climate change researchers. Field measurement is very difficult as in case of a steep and in a complex terrain such as Himalayas, therefore we rely on remote sensing (both active and passive) data. Usually snow area is calculated from reflectance data using different snow index e.g. Normalize difference snow index (NDSI) and then it is translated into snow area. However, in most cases we are actually calculating the planimetric area or grid area of every pixel. The actual snow is along the surface of the terrain and proper estimation can only be done if actual surface area is calculated along the slope within each pixel. In the past, some researchers have introduced methodologies and optimized old mechanisms. However, the orographical impact in calculating snow area (fraction), especially in steep mountainous regions, still has many problems, and many times these problems are usually ignored which leads to under estimation of total snow amount. In this study we calculated the actual surface area from SRTM version 4.1 90m (at equator) processed DEM data provided by CGIAR-CSI. MODIS Reflectance (MOD09A1 L3 Product) composite data of 500m resolution for 2010 and 2011 in the northern areas of Pakistan, Jammu & Kashmir region where great Himalayas are stretched was used to calculate snow cover using NDSI index. Threshold of NDSI>0.4 was set to classify snow or no snow for the clear pixels and for further classification, unmixing method (subjective pixel method only) was used to calculate snow fraction within each pixel. Results shows that in a complex terrain such as Himalayas, ratio of surface to planimetric snow area is more than 50%. This means that it should be taken into consideration for more realistic snow amount estimation. Seasonal snow fraction histogram from unmixing method indicates that NDSI measures snow cover area by 1.86 times more in cold season (maximum snow area) and 1

  7. 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.

  8. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1996-01-01

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

  10. 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.

  11. Digging in 'Snow White' Trench

    NASA Technical Reports Server (NTRS)

    2008-01-01

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

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

  12. 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.

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-05-01

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

  15. 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

  16. 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.

  17. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  3. 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.

  4. 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.

  5. A drought index accounting for snow

    NASA Astrophysics Data System (ADS)

    Staudinger, Maria; Stahl, Kerstin; Seibert, Jan

    2015-04-01

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

  6. 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…

  7. Blast noise propagation above a snow cover.

    PubMed

    Albert, D G; Hole, L R

    2001-06-01

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

  8. 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)

  9. 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…

  10. 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.

  11. Utilizing the effective xanthophyll cycle for blooming of Ochromonas smithii and O. itoi (Chrysophyceae) on the snow surface.

    PubMed

    Tanabe, Yukiko; Shitara, Tomofumi; Kashino, Yasuhiro; Hara, Yoshiaki; Kudoh, Sakae

    2011-02-23

    Snow algae inhabit unique environments such as alpine and high latitudes, and can grow and bloom with visualizing on snow or glacier during spring-summer. The chrysophytes Ochromonas smithii and Ochromonas itoi are dominant in yellow-colored snow patches in mountainous heavy snow areas from late May to early June. It is considered to be effective utilizing the xanthophyll cycle and holding sunscreen pigments as protective system for snow algae blooming in the vulnerable environment such as low temperature and nutrients, and strong light, however the study on the photoprotection of chrysophytes snow algae has not been shown. To dissolve how the chrysophytes snow algae can grow and bloom under such an extreme environment, we studied with the object of light which is one point of significance to this problem. We collected the yellow snows and measured photosynthetically active radiation at Mt. Gassan in May 2008 when the bloom occurred, then tried to establish unialgal cultures of O. smithii and O. itoi, and examined their photosynthetic properties by a PAM chlorophyll fluorometer and analyzed the pigment compositions before and after illumination with high-light intensities to investigate the working xanthophyll cycle. This experimental study using unialgal cultures revealed that both O. smithii and O. itoi utilize only the efficient violaxanthin cycle for photoprotection as a dissipation system of surplus energy under prolonged high-light stress, although they possess chlorophyll c with diadinoxanthin.

  12. Diversity and potential sources of microbiota associated with snow on western portions of the Greenland Ice Sheet.

    PubMed

    Cameron, Karen A; Hagedorn, Birgit; Dieser, Markus; Christner, Brent C; Choquette, Kyla; Sletten, Ronald; Crump, Byron; Kellogg, Colleen; Junge, Karen

    2015-03-01

    Snow overlays the majority of the Greenland Ice Sheet (GrIS). However, there is very little information available on the microbiological assemblages that are associated with this vast and climate-sensitive landscape. In this study, the structure and diversity of snow microbial assemblages from two regions of the western GrIS ice margin were investigated through the sequencing of small subunit ribosomal RNA genes. The origins of the microbiota were investigated by examining correlations to molecular data obtained from marine, soil, freshwater and atmospheric environments and 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 Chloroplastida). Phylotypes related to archaeal Thaumarchaeota and Euryarchaeota phyla were also identified. The snow microbial assemblages were more similar to communities characterized in soil than to those documented in marine ecosystems. Despite this, the chemical composition of snow samples was consistent with a marine contribution, and strong correlations existed between bacterial beta diversity and the concentration of Na(+) and Cl(-) . These results suggest that surface snow from western regions of Greenland contains exogenous microbiota that were likely aerosolized from more distant soil sources, transported in the atmosphere and co-precipitated with the snow.

  13. 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

  14. 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

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  18. 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

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

    NASA Astrophysics Data System (ADS)

    Strasser, Ulrich; Marke, Thomas; Hanzer, Florian; Ragg, Hansjörg; Kleindienst, Hannes; Wilcke, Renate; Gobiet, Andreas

    2013-04-01

    This study has the goal to simulate the evolution of the Austrian snow cover from 1971 to 2050 by means of a coupled modelling scheme, and to estimate the effect of climate change on the evolution of the natural snow cover. The model outcomes are interepreted with focus on both the future natural snow conditions, and the effects on winter skiing tourism. Therefore the regional temperature-index snow model SNOWREG is applied, providing snow maps with a spatial resolution of 250 m. The model is trained by means of assimilating local measurements and observed natural snow cover patterns. Meteorological forcing consists of the output of four realizations of the ENSEMBLES project for the A1B emission scenario. The meteorological variables are downscaled and error corrected with a quantile based empirical-statistical method on a daily time basis. The control simulation is 1971-2000, and the scenario simulation 2021-2050. Spatial interpolation is performed on the basis of parameter-elevation relations. We compare the four different global/regional climate model combinations and their effect on the snow modelling, and we explain the patterns of the resulting snow cover by means of regional climatological characteristics. The provinces Tirol and Styria serve as test regions, being typical examples for the two climatic subregions of Austria. To support the interpretation of the simulation results we apply indicators which enable to define meaningful measures for the comparison of the different periods and regions. Results show that the mean duration of the snow cover will decrease by 15 to 30 days per winter season, mostly in elevations between 2000 and 2500 m. Above 3000 m the higher winter precipitation can compensate this effect, and mean snow cover duration may even slightly increase. We also investigate the local scale by application of the physically based mountain snow model AMUNDSEN. This model is capable of producing 50 m resolution output maps for indicators

  20. 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

  1. 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

  2. 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.

  3. Snow Avalanche Disturbance Ecology: Examples From the San Juan Mountains, Colorado.

    NASA Astrophysics Data System (ADS)

    Simonson, S.; Fassnacht, S. R.

    2008-12-01

    We evaluated landscape ecology approaches to characterize snow avalanche paths based on patterns of plant species composition and evidence of disturbance. Historical records of avalanche incidents, patterns in the annual growth layers of woody plants, and distributions of plant species can be used to quantify and map the frequency and magnitude of snow slide events. Near Silverton, Colorado, a series of snow storms in January of 2005 resulted in many avalanche paths running full track at 30 and 100 year return frequency. Many avalanches cut fresh trimlines, widening their tracks by uprooting, stripping, and breaking mature trees. Powerful avalanches deposited massive piles of snow, rocks, and woody debris in their runout zones. We used cross-section discs and cores of representative downed trees to detect dendro-ecological signals of past snow avalanche disturbance. Avalanche signals included impact scars from the moving snow and associated wind blast, relative width of annual growth rings, and development of reaction wood in response to tilting. Initial measurements of plant diversity and disturbance along the elevation gradient of an avalanche path near Silverton indicate that avalanche activity influences patterns of forest cover, contributes to the high local plant species diversity, and provides opportunities for new seedling establishment.

  4. 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

  5. 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).

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

    NASA Astrophysics Data System (ADS)

    Vikhamar-Schuler, D.; Müller, K.

    2012-04-01

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

  7. 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

  8. 'Snow White' Trench After Scraping

    NASA Technical Reports Server (NTRS)

    2008-01-01

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

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

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

  9. 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

  10. Light-absorbing impurities in Arctic snow

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  11. 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.

  12. 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.

  13. Snow cover and land surface temperature assessment of Gangotri basin in the Indian Himalayan Region (IHR) using MODIS satellite data for climate change inferences

    NASA Astrophysics Data System (ADS)

    Krishna, Akhouri P.; Sharma, Anurag

    2013-10-01

    Climate change has become a cause of concern as well as the challenge of this century. Himalayan mountain ranges with high snow fields and numerous valley glaciers may bear the brunt of such changes already being reported including Intergovernmental Panel on Climate Change (IPCC). Gangotri is one of the most prominent snow-fed catchments of Indian Himalayan Region (IHR) due to origin of river Ganga situated within it. Spatio-temporal changes in snow covered area of this basin were examined for melting seasons of the years 2006 to 2010 and a latest reference year of 2012 as a special test case. Standard snow data products (MOD10A2) of Moderate Resolution Imaging Spectroradiometer (MODIS)-Terra sensor with spatial resolution of 500 m were used. For all the years of reference, snow covered area percentage was derived for respective months representing usual ablation or melting periods. Snow depletion curves (SDCs) were generated for such periods of the respective years. CARTOSAT digital elevation model (DEM) was used for topographic information of terrain. Relationship of SDCs with the land surface temperatures (LST) of the basin was worked upon using MODIS-Terra LST (MOD11A2) product (version 5) with 1 km resolution at 8-day interval for the day time temperature for respective months of above reference years. Thereafter, interpolation and simulation of snow covered areas was carried out on the basis of LST data. The study thus produced snow cover maps for the years of reference as well as their relationship with LST for climate change inferences.

  14. BOREAS HYD-4 Standard Snow Course Data

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  15. Dynamics of glide avalanches and snow gliding

    NASA Astrophysics Data System (ADS)

    Ancey, Christophe; Bain, Vincent

    2015-09-01

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

  16. Propagation characteristics of acoustic waves in snow

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  17. 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

  18. 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

  19. 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

  20. 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.

  1. PHYSICS UPDATE: Production of artificial snow crystals

    NASA Astrophysics Data System (ADS)

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

    1999-03-01

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

  2. "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

  3. 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.

  4. Quantifying scale relationships in snow distributions

    NASA Astrophysics Data System (ADS)

    Deems, Jeffrey S.

    2007-12-01

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

  5. 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

  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. Time-Lapse Micro-Tomography Measurements and Determination of Effective Transport Properties of Snow Metamorphism Under Advective Conditions

    NASA Astrophysics Data System (ADS)

    Ebner, P. P.; Grimm, S.; Steen-Larsen, H. C.; Schneebeli, M.; Steinfeld, A.

    2014-12-01

    The metamorphism of snow under advective air flow, with and without temperature gradient, was never experimentally investigated. We developed a new sample holder where metamorphism under advective conditions can be observed and measured using time-lapse micro-tomography [1]. Long-term experiments were performed and direct pore-level simulation (DPLS) [2,3] was directly applied on the extracted 3D digital geometry of the snow to calculate the effective transport properties by solving the governing fluid flow equations. The results showed no effect of isothermal advection, compared to rates typical for isothermal metamorphism. Appling a temperature gradient, the results showed increased snow metamorphism compared to rates typical for temperature gradient metamorphism. However, for both cases a change in the isotopic composition in the air as well as in the snow sample could be observed. These measurements could be influential to better understand snow-air exchange processes relevant for atmospheric chemistry and isotopic composition. REFERENCES[1] Ebner P. P., Grimm S., Schneebeli M., and Steinfeld A.: An instrumented sample holder for time-lapse micro-tomography measurements of snow under advective airflow. Geoscientific Instrumentation, Methods and Data Systems 4(2014), 353-373. [2] Zermatten E., Haussener S., Schneebeli M., and Steinfeld A.: Tomography-based determination of permeability and Dupuit-Forchheimer coefficient of characteristic snow samples. Journal of Glaciology 57(2011), 811-816. [3] Zermatten E., Schneebeli M., Arakawa H., and Steinfeld A.: Tomography-based determination of porosity, specific area and permeability of snow and comparison with measurements. Cold Regions Science and Technology 97 (2014), 33-40. Fig. 1: 3-D surface rendering of a refrozen wet snow sample with fluid flow streamline.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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

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

    PubMed

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

    2009-02-01

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

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

    PubMed

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

    2015-10-20

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

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

    PubMed

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

    2009-02-01

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

  3. 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.

  4. 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).

  5. A snow wetness retrieval algorithm for SAR

    NASA Technical Reports Server (NTRS)

    Shi, Jian-Cheng; Dozier, Jeff

    1992-01-01

    The objectives of this study are: (1) to evaluate the backscattering signals response to snow wetness; and (2) to develop an algorithm for snow wetness measurement using C-band polarimetric synthetic aperture radar (SAR). In hydrological investigations, modeling and forecasting of snowmelt runoff requires information about snowpack properties and their spatial variability. In particular, timely measurement of snow parameters is needed for operational hydrology. The liquid water content of snowpack is one of the important parameters. Active microwave sensors are highly sensitive to liquid water in the snowpack because of the large dielectric contrast between ice and water in the microwave spectrum. They are not affected by weather and have a spatial resolution compatible with the topographic variation in alpine regions. However, a quantitative algorithm for retrieval snow wetness has not yet been developed.

  6. 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.

  7. 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)

  8. 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

  9. 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.

  10. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  12. 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.

  13. Hyphomycetes in the snow from gymnosperm trees.

    PubMed

    Czeczuga, B; Orłowska, M

    1998-01-01

    The presence of 26 hyphomycete species was noted in snow water collected from coniferous trees. Camposporium pellucidum, Monodictys peruviana, Polystratorictus fusarioideus, Sporidesmium moniliforme, Tripospermum acerinum and Veronaea botryosa were recorded for the first time to Poland. Among the 26 species found in snow water from coniferous trees predominance of the socalled aero-aquatic hyphomycetes and only a few species belong to the group of aquatic hyphomycetes.

  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 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.

  16. Winter precipitation and snow accumulation drive the methane sink or source strength of Arctic tussock tundra.

    PubMed

    Blanc-Betes, Elena; Welker, Jeffrey M; Sturchio, Neil C; Chanton, Jeffrey P; Gonzalez-Meler, Miquel A

    2016-08-01

    Arctic winter precipitation is projected to increase with global warming, but some areas will experience decreases in snow accumulation. Although Arctic CH4 emissions may represent a significant climate forcing feedback, long-term impacts of changes in snow accumulation on CH4 fluxes remain uncertain. We measured ecosystem CH4 fluxes and soil CH4 and CO2 concentrations and (13) C composition to investigate the metabolic pathways and transport mechanisms driving moist acidic tundra CH4 flux over the growing season (Jun-Aug) after 18 years of experimental snow depth increases and decreases. Deeper snow increased soil wetness and warming, reducing soil %O2 levels and increasing thaw depth. Soil moisture, through changes in soil %O2 saturation, determined predominance of methanotrophy or methanogenesis, with soil temperature regulating the ecosystem CH4 sink or source strength. Reduced snow (RS) increased the fraction of oxidized CH4 (Fox) by 75-120% compared to Ambient, switching the system from a small source to a net CH4 sink (21 ± 2 and -31 ± 1 mg CH4  m(-2)  season(-1) at Ambient and RS). Deeper snow reduced Fox by 35-40% and 90-100% in medium- (MS) and high- (HS) snow additions relative to Ambient, contributing to increasing the CH4 source strength of moist acidic tundra (464 ± 15 and 3561 ± 97 mg CH4  m(-2)  season(-1) at MS and HS). Decreases in Fox with deeper snow were partly due to increases in plant-mediated CH4 transport associated with the expansion of tall graminoids. Deeper snow enhanced CH4 production within newly thawed soils, responding mainly to soil warming rather than to increases in acetate fermentation expected from thaw-induced increases in SOC availability. Our results suggest that increased winter precipitation will increase the CH4 source strength of Arctic tundra, but the resulting positive feedback on climate change will depend on the balance between areas with more or less snow accumulation than they are currently

  17. 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

  18. 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.

  19. 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.

  20. [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

  1. Evaluation of SNODAS snow depth and snow water equivalent estimates for the Colorado Rocky Mountains, USA

    USGS Publications Warehouse

    Clow, David W.; Nanus, Leora; Verdin, Kristine L.; Schmidt, Jeffrey

    2012-01-01

    The National Weather Service's Snow Data Assimilation (SNODAS) program provides daily, gridded estimates of snow depth, snow water equivalent (SWE), and related snow parameters at a 1-km2 resolution for the conterminous USA. In this study, SNODAS snow depth and SWE estimates were compared with independent, ground-based snow survey data in the Colorado Rocky Mountains to assess SNODAS accuracy at the 1-km2 scale. Accuracy also was evaluated at the basin scale by comparing SNODAS model output to snowmelt runoff in 31 headwater basins with US Geological Survey stream gauges. Results from the snow surveys indicated that SNODAS performed well in forested areas, explaining 72% of the variance in snow depths and 77% of the variance in SWE. However, SNODAS showed poor agreement with measurements in alpine areas, explaining 16% of the variance in snow depth and 30% of the variance in SWE. At the basin scale, snowmelt runoff was moderately correlated (R2 = 0.52) with SNODAS model estimates. A simple method for adjusting SNODAS SWE estimates in alpine areas was developed that uses relations between prevailing wind direction, terrain, and vegetation to account for wind redistribution of snow in alpine terrain. The adjustments substantially improved agreement between measurements and SNODAS estimates, with the R2 of measured SWE values against SNODAS SWE estimates increasing from 0.42 to 0.63 and the root mean square error decreasing from 12 to 6 cm. Results from this study indicate that SNODAS can provide reliable data for input to moderate-scale to large-scale hydrologic models, which are essential for creating accurate runoff forecasts. Refinement of SNODAS SWE estimates for alpine areas to account for wind redistribution of snow could further improve model performance. Published 2011. This article is a US Government work and is in the public domain in the USA.

  2. 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.

  3. Measurements of Black Carbon Induced Snow-Albedo Reduction

    NASA Astrophysics Data System (ADS)

    Hadley, O. L.; Kirchstetter, T. W.

    2011-12-01

    Several modeling studies have indicated that black carbon (BC) reduces the albedo of snow and ice and appreciably contributes to Northern Hemisphere warming and glacier retreat. Observations of the BC impact on snow albedo are needed to verify model predictions. Whereas field studies dating back to the early 1980s measured BC concentrations in snow and ice in the arctic, the BC effect on snow albedo and melting has been difficult to observe directly because the albedo reduction is small and often masked by other natural variables. This study evaluates both the initial impact of BC on snow albedo, as well as associated feedbacks due to snow age and BC scavenging during snow melting. The first feedback is related to the increasing grain size of snow as it ages. Larger snow grains allow sunlight to penetrate farther, where it is exposed to and may be increasingly absorbed by BC. This enhances the albedo reduction attributable to the mass of BC present in the snow and deposits energy at greater depths in the snowpack, potentially increasing the melt rate and therefore the growth rate of the snow grains. The second potential feedback, associated with BC transport through a melting snowpack, occurs if BC is scavenged from the melt water by the ice grains thus increasing the BC concentration in the remaining snow. Measurement of pristine and sooty snow made in the laboratory verifies that BC reduces snow albedo to a greater extent for larger-grained snow. Experimental observations yield an empirical model of the BC snow albedo reduction. Measurements of BC transport in both laboratory and natural snow were used to develop a model of the evolution of the vertical distribution of BC in melting snow. These measurements provide the first quantification of a BC concentration enhancement in melting snow.

  4. Modeling snow season controls on northern net ecosystem exchange

    NASA Astrophysics Data System (ADS)

    Luus, K. A.; Lin, J. C.; Kelly, R. E.

    2011-12-01

    Recent field studies have indicated that the timing of snow melt and snow fall, the quantity of snow, and soil temperature are important controls on snow season net ecosystem exchange (NEE). The low thermal conductivity of snow reduces soil heat loss, thereby enabling a greater rate of subnivean respiration under deeper snowpacks, whereas snow melt and snow fall alter the seasonal timing of photosynthetic uptake. Although a substantial portion of annual NEE in northern regions occurs during the snow season, model estimates have not previously included representations of snow season controls on NEE. The objective of this study was therefore to 1) incorporate remotely sensed estimates of snow water equivalent, soil temperature, and the timing of initial snow fall and final snow melt into model estimates of northern NEE; and 2) examine whether incorporating representations of key snow season variables reduces model uncertainty. NEE was estimated using the Vegetation Photosynthesis Respiration Model (VPRM), a simple diagnostic biosphere model that relies on a remote sensing based approach. Findings indicate that a potential exists to improve northern estimates of NEE by incorporating information on snow season controls from remote sensing observations. Soil respiration can be better assessed using soil temperature rather than surface air temperature. The influence of changes in snow water equivalent on soil temperature dynamics can be assessed using remotely sensed estimates of snow water equivalent. Incorporating remotely sensed estimates of snow cover area can improve the timing of seasonal changes in photosynthetic uptake. Furthermore, including snow season controls on northern NEE can enable experiments to be run analyzing the influence of changes in snowpack dynamics, the frequency of extreme winter warming events, and the timing of the snow season on northern NEE.

  5. Fungal growth and biomass development is boosted by plants in snow-covered soil.

    PubMed

    Kuhnert, Regina; Oberkofler, Irmgard; Peintner, Ursula

    2012-07-01

    Soil microbial communities follow distinct seasonal cycles which result in drastic changes in processes involving soil nutrient availability. The biomass of fungi has been reported to be highest during winter, but is fungal growth really occurring in frozen soil? And what is the effect of plant cover on biomass formation and on the composition of fungal communities? To answer these questions, we monitored microbial biomass N, ergosterol, and the amount of fungal hyphae during summer and winter in vegetated and unvegetated soils of an alpine primary successional habitat. The winter fungal communities were identified by rDNA ITS clone libraries. Winter soil temperatures ranged between -0.6°C and -0.1°C in snow-covered soil. We found distinct seasonal patterns for all biomass parameters, with highest biomass concentrations during winter in snow-covered soil. The presence of plant cover had a significant positive effect on the amount of biomass in the soil, but the type of plant cover (plant species) was not a significant factor. A mean hyphal ingrowth of 5.6 m g(-1) soil was detected in snow-covered soil during winter, thus clearly proving fungal growth during winter in snow-covered soil. Winter fungal communities had a typical species composition: saprobial fungi were dominating, among them many basidiomycete yeasts. Plant cover had no influence on the composition of winter fungal communities.

  6. Quantification of uncertainties in snow accumulation, snowmelt, and snow disappearance dates

    NASA Astrophysics Data System (ADS)

    Raleigh, Mark S.

    Seasonal mountain snowpack holds hydrologic and ecologic significance worldwide. However, observation networks in complex terrain are typically sparse and provide minimal information about prevailing conditions. Snow patterns and processes in this data sparse environment can be characterized with numerical models and satellite-based remote sensing, and thus it is essential to understand their reliability. This research quantifies model and remote sensing uncertainties in snow accumulation, snowmelt, and snow disappearance as revealed through comparisons with unique ground-based measurements. The relationship between snow accumulation uncertainty and model configuration is assessed through a controlled experiment at 154 snow pillow sites in the western United States. To simulate snow water equivalent (SWE), the National Weather Service SNOW-17 model is tested as (1) a traditional "forward" model based primarily on precipitation, (2) a reconstruction model based on total snowmelt before the snow disappearance date, and (3) a combination of (1) and (2). For peak SWE estimation, the reliability of the parent models was indistinguishable, while the combined model was most reliable. A sensitivity analysis demonstrated that the parent models had opposite sensitivities to temperature that tended to cancel in the combined model. Uncertainty in model forcing and parameters significantly controlled model accuracy. Uncertainty in remotely sensed snow cover and snow disappearance in forested areas is enhanced by canopy obstruction but has been ill-quantified due to the lack of sub-canopy observations. To better quantify this uncertainty, dense networks of near-surface temperature sensors were installed at four study areas (≤ 1 km2) with varying forest cover in the Sierra Nevada, California. Snow presence at each sensor was detected during periods when temperature was damped, which resulted from snow cover insulation. This methodology was verified using time-lapse analysis and

  7. 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.

  8. On the Evolution of the CO Snow Line in Protoplanetary Disks

    NASA Astrophysics Data System (ADS)

    Martin, Rebecca G.; Livio, Mario

    2014-03-01

    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.

  9. 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.

  10. 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.

  11. 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.

  12. Ensemble-based snow data assimilation for an operational snow model

    NASA Astrophysics Data System (ADS)

    Liu, Y.; He, M.; Seo, D.; Laurine, D.; Lee, H.

    2010-12-01

    In mountainous regions of the western United States, seasonal snow pack evolution dominates the generation of snowmelt and streamflow. In the National Weather Service (NWS), the conceptual SNOW-17 model is used for operational forecasting of snowmelt, which then serves as an input to a rainfall-runoff model for streamflow forecasts in snow-affected areas. To improve snowmelt estimates and therefore streamflow forecasts, some River Forecast Centers (RFCs) of the NWS operate a snow updating system to update areal Snow Water Equivalent (SWE) estimates by using a regression technique to reconcile the differences between the observed SWE (e.g., from SNOTEL stations) and the modeled SWE. While this method is parsimonious and easy to use in operations, it does not capitalize on the full capabilities offered by advanced data assimilation techniques to quantify, reduce, and propagate forecast uncertainty in a statistically and dynamically consistent fashion. This study describes an application of the ensemble Kalman filter (EnKF) which automatically and systematically assimilates SNOTEL SWE observations into the SNOW-17 model to reduce uncertainties in model initial conditions. The robustness of the ensemble filter as compared to the operational regression-based method is evaluated for both snow and streamflow forecasts at several operational basins in the service area of the Northwest River Forecast Center (NWRFC). This presentation describes the implementation of the EnKF into the SNOW-17 model and summarizes the preliminary evaluation results.

  13. Reconstructing MODIS Snow Cover Fraction Using Snow Meltout Dates From Snowpack Telemetry (SNOTEL) Data

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    Information on snow-covered area has been an important input for snowmelt runoff models in the prediction of runoff and simulation of streamflow. Several advanced methods of snow mapping exist today that can be used in determining the progressive reduction of snow cover during snowmelt; however, some of these advanced methods of snow mapping, such as the Moderate-Resolution Imagine Spectroradiometer (MODIS) satellite sensor, did not exist before 1999. The non-availability of MODIS prior to its launch in 1999, sometimes limits the use of this remote sensing tool in developing historical snow depletion curves that are needed to provide base period perturbations for climate change snowmelt runoff simulations. These historical depletion curves, among many other uses, provide snow cover information for snowmelt runoff modeling in hydrologic models such as snowmelt runoff model (SRM). A method is presented in this study that makes use of the available remotely sensed and ground based data to construct a single dimensionless snow depletion curve that is subsequently used with historical SNOTEL data to reconstruct MODIS snow depletion curves for base periods preceding the availability of current satellite remote sensing, and for future periods associated with climate scenarios.

  14. The role of mercury redox reactions in snow on snow-to-air mercury transfer.

    PubMed

    Lalonde, Janick D; Poulain, Alexandre J; Amyot, Marc

    2002-01-15

    Wet deposition of Hg in snow represents a major air-to-land flux of Hg in temperate and polar environments. However, the chemical speciation of Hg in snow and its chemical and physical behavior after deposition are poorly understood. To investigate Hg dynamics in snow, we followed Hg0 and total Hg concentrations in a snowpack above a frozen lake over 1 month. Our results indicate that newly deposited Hg is highly labile in snowpacks. On average, Hg levels in particular snow episodes decrease by 54% within 24 h after deposition. We hypothesize that Hg depletion in snow could be caused by a rapid snow-to-air Hg transfer resulting from Hg(II) photoinduced reduction to volatile Hg0. Both snowmelt incubated under a UV lamp at 17 degrees C and solid snow incubated under the sun at -10 degrees C in clear reaction vessels yielded a statistically significant increase in Hg0(aq) with time of exposure, while the Hg0(aq) levels remained constant in the dark controls. The snow-to-air Hg transfer we observed in this study suggests that the massive Hg deposition events observed in springtime in northern environments may have less impact than previously anticipated, since once deposited, Hg could be rapidly reduced and re-emitted.

  15. Recovery of tall cotton-grass following real and simulated feeding by snow geese

    USGS Publications Warehouse

    Hupp, J.W.; Robertson, Donna G.; Schmutz, J.A.

    2000-01-01

    Lesser snow geese Anser caerulescens caerulescens from the western Canadian Arctic feed on underground parts of tall cotton-grass Eriophorum angustifolium during autumn staging on the coastal plain of the Beaufort Sea in Canada and Alaska. We studied revegetation of sites where cotton-grass had been removed either by human-imprinted snow geese or by hand to simulate snow goose feeding. Aerial cover of cotton-grass at sites (n = 4) exploited by human-imprinted snow geese averaged 60 and 39% lower than in undisturbed control plots during the first and second year after feeding, respectively. Underground biomass of cotton-grass stembases and rhizomes in hand-treated plots was 80 and 62% less than in control plots 2 and 4 yr after removal, respectively (n = 10 yr-1). Aerial cover and biomass of common non-forage species such as Carex aquatilis did not increase on treated areas. Removal of cotton-grass by geese likely reduces forage availability at exploited sites for at least 2-4 yr after feeding but probably does not affect long-term community composition. Temporal heterogeneity in forage abundance likely contributes to the large spatial requirement of snow geese during staging.

  16. 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.

  17. Evidence for a Significant Source of Sea Salt Aerosol from Blowing Snow Above Sea Ice in the Southern Ocean

    NASA Astrophysics Data System (ADS)

    Frey, M. M.; Brooks, I. M.; Anderson, P. A.; Nishimura, K.; Yang, X.; Jones, A. E.; Wolff, E. W.

    2014-12-01

    Over most of the Earth, sea salt aerosol (SSA) derives from sea spray and bubble bursting at the open ocean surface. SSA as the major component of marine aerosol contributes directly to the radiative balance and can act as cloud condensation nuclei. SSA can also significantly impact the lifetime of methane, ozone or mercury through the photochemical release of reactive halogens. A recent model study suggested that the sublimation of saline blowing snow above sea ice can generate more SSA than is produced from a similar area of open ocean. A winter cruise through the Weddell Sea during June - August 2013 provided unique access to a potential SSA source region in the Antarctic sea ice zone to test this hypothesis.Reported are first measurements of snow particle as well as aerosol concentrations, size distributions and chemical composition, during blowing snow events above sea ice. Snow particle spectra are found to be similar to those observed on the continent. Even though the salinity of surface and blowing snow was very low (<0.1 psu) a significant increase of aerosol in the SSA size range was observed during and after blowing snow events. This is consistent with model runs including a blowing snow parameterisation which suggest low sensitivity of SSA number densities to snow salinity within the observed range. First estimates of SSA flux from blowing snow using eddy correlation are significant, although falling below published values of the sea spray source function. We discuss the dependance of observed SSA production rates on ambient conditions as well as the significance to the Southern Ocean environment.

  18. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  20. Statistical model for the correlation length of snow derived from SnowMicroPen measurements.

    NASA Astrophysics Data System (ADS)

    Proksch, M.; Loewe, H.; Schneebeli, M.

    2012-12-01

    The SnowMicroPen (SMP) allows to retrieve mechanical parameters from the snowpack. However, remote sensing applications rely on structural parameters of snow such as the correlation length. Due to the complexity of the physical connection between structural and mechanical parameters we derived a statistical model for the correlation length from SMP measurements. To this end we have analyzed snow samples of many different snow classes and densities by micro computer-tomography (CT) and SMP. We correlated the SMP-derived structural element length with the CT-derived correlation length and validated the model using field data taken during the NoSREx - III campaign in Sodankylä, Finland. Further, we employ the statistical model to estimate the specific surface area from combined SMP and density measurement from natural snow profiles. We compare this SSA estimate to independent SSA measurements by near-infrared photography and discuss potential and limitation of the method.

  1. Statistical model for the correlation length of snow derived from Snow-Micro-Pen measurements.

    NASA Astrophysics Data System (ADS)

    Proksch, M.; Loewe, H.; Schneebeli, M.

    2012-04-01

    The Snow-Micro-Pen (SMP) allows to retrieve various mechanical parameters from the snowpack. However, remote sensing applications rely on structural parameters of snow such as the correlation length. In the absence of a sound physical connection between structural and mechanical parameters we derive a statistical model for the correlation length from SMP measurements. To this end we have analyzed 22 snow samples of various snow types by computer tomography (CT) and SMP. We correlate the SMP-derived structural element length with the CT-derived correlation length. For validation we employ the statistical model to estimate the specific surface area from combined SMP and density measurement from natural snow profiles. We compare this SSA estimate to independent SSA measurements by Near-Infrared-Photography and discuss potentials and limitations of the method.

  2. 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.

  3. Simulation of Snow Dynamics in Response to Climate Variability

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Wang, S.; Trishchenko, A.

    2004-05-01

    Snow dynamics not only affects the energy dissipation in northern ecosystems during non-growing season, but also affects plant growth through its impact on the soil water conditions of early growing season. To better simulate the snow and soil dynamics, a multiple-layer snow and soil interaction module has been recently developed within the Ecological Assimilation of Land and Climate Observations (EALCO) model. Up to 6 snow layers and 6 soil layers with flexible depth are currently represented in the module. Soil or snow skin temperature is obtained by numerically solving the surface energy balance equation. Energy dissipation to latent, sensible and soil/snow surface heat fluxes are thus calculated. Snow density is simulated in consideration of both compaction and destructive metamorphism, which depends on snow age, temperature and the residing weight above. The snow surface albedo, thermal and water properties and change of snow depth are updated in each time step and snow layers are re-calculated accordingly. The temperatures of snow and soil layers are implicitly solved in a tridiagonal linear system for thermal conduction equations. Freezing and thawing are computed according to the solved layer temperature and the existing water phase in the layer. Water movement between snow layers is computed according to the liquid water content and water holding capacity. Soil Water movement is simulated using Richard's equation and Darcy's law. The soil water content of each layer is thus implicitly solved as for temperatures. The model runs in half-hourly time step and main outputs include snow depth, snow water equivalent, and the temperature and water profiles for both snow and soil. In this study, the model was tested using data collected from several Canadian sites in the prairie and boreal forest region. The observed snow depth and temperature were compared with the corresponding model outputs. Sensitivities of snow cover change and soil thermal and moisture regime

  4. Estimating maritime snow density from seasonal climate variables

    NASA Astrophysics Data System (ADS)

    Bormann, K. J.; Evans, J. P.; Westra, S.; McCabe, M. F.; Painter, T. H.

    2013-12-01

    Snow density is a complex parameter that influences thermal, optical and mechanical snow properties and processes. Depth-integrated properties of snowpacks, including snow density, remain very difficult to obtain remotely. Observations of snow density are therefore limited to in-situ point locations. In maritime snowfields such as those in Australia and in parts of the western US, snow densification rates are enhanced and inter-annual variability is high compared to continental snow regions. In-situ snow observation networks in maritime climates often cannot characterise the variability in snowpack properties at spatial and temporal resolutions required for many modelling and observations-based applications. Regionalised density-time curves are commonly used to approximate snow densities over broad areas. However, these relationships have limited spatial applicability and do not allow for interannual variability in densification rates, which are important in maritime environments. Physically-based density models are relatively complex and rely on empirical algorithms derived from limited observations, which may not represent the variability observed in maritime snow. In this study, seasonal climate factors were used to estimate late season snow densities using multiple linear regressions. Daily snow density estimates were then obtained by projecting linearly to fresh snow densities at the start of the season. When applied spatially, the daily snow density fields compare well to in-situ observations across multiple sites in Australia, and provide a new method for extrapolating existing snow density datasets in maritime snow environments. While the relatively simple algorithm for estimating snow densities has been used in this study to constrain snowmelt rates in a temperature-index model, the estimates may also be used to incorporate variability in snow depth to snow water equivalent conversion.

  5. 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

  6. Chemistry of small organic molecules on snow grains: the applicability of artificial snow for environmental studies.

    PubMed

    Kurková, Romana; Ray, Debajyoti; Nachtigallová, Dana; Klán, Petr

    2011-04-15

    The utilization of artificial snow for environmentally relevant (photo)chemical studies was systematically investigated. Contaminated snow samples were prepared by various methods: by shock freezing of the aqueous solutions sprayed into liquid nitrogen or inside a large walk-in cold chamber at -35 °C, or by adsorption of gaseous contaminants on the surface of artificially prepared pure or natural urban snow. The specific surface area of artificial snow grains produced in liquid nitrogen was determined using valerophenone photochemistry (400-440 cm(2) g(-1)) to estimate the surface coverage by small hydrophobic organic contaminants. The dynamics of recombination/dissociation (cage effect) of benzyl radical pairs, photochemically produced from 4-methyldibenzyl ketone on the snow surface, was investigated. The initial ketone loading, c = 10(-6)-10(-8) mol kg(-1), only about 1-2 orders of magnitude higher than the contaminant concentrations commonly found in nature, was already well below monolayer coverage. We found that the efficiency of out-of-cage reactions decreased at much higher temperatures than those previously determined for frozen solutions; however, the cage effect was essentially the same no matter what technique of snow production or ketone deposition/uptake was used, including the experiments with collected natural snow. The experimental observation that the contaminant molecules are initially self-associated even at the lowest concentrations was supported by DFT calculations. We conclude that, contrary to frozen aqueous solutions, in which the impurities reside in a 3D cage (micropocket), contaminant molecules located on the artificial snow grain surface at low concentrations can be visualized in terms of a 2D cage. Artificial snow thus represents a readily available study matrix that can be used to emulate the natural chemical processes of trace contaminants occurring in natural snow.

  7. 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.

  8. 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.

  9. Modeling the snow cover in climate studies: 2. The sensitivity to internal snow parameters and interface processes

    NASA Astrophysics Data System (ADS)

    Loth, Bettina; Graf, Hans-F.

    1998-05-01

    In order to find an optimal complexity for snow-cover models in climate studies, the influence of single snow processes on both the snow mass balance and the energy fluxes between snow surface and atmosphere has been investigated. Using a sophisticated model, experiments were performed under several different atmospheric and regional conditions (Arctic, midlatitudes, alpine regions). A high simulation quality can be achieved with a multilayered snow-cover model resolving the internal snow processes (cf. part 1,[Loth and Graf, this issue]). Otherwise, large errors can occur, mostly in zones which are of paramount importance for the entire climate dynamics. Owing to simplifications of such a model, the mean energy balance of the snow cover, the turbulent heat fluxes, and the long-wave radiation at the snow surface may alter by between 1 W/m2 and 8 W/m2. The snow-surface temperatures can be systematically changed by about 10 K.

  10. 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.

  11. 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

  12. Black Carbon Measurements in Arctic Snow

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

    A survey of the black carbon (BC) content of Arctic snow is underway, updating and expanding the 1983/84 survey of Clarke and Noone. Samples of snow are collected in mid to late spring when the entire winter snowpack is accessible. The samples are melted and filtered, and the filters are analyzed for absorptive impurities. Snow has been sampled on tundra, glaciers, ice caps, and sea ice, and in forests. To date about one thousand snow samples have been melted and filtered. The sampling effort has been assisted by IPY collaborations with S. Gerland (Svalbard), K. Steffen and C. Boeggild (Greenland), M. Sturm (Canada), V. Radionov (Russia), and J. Morison (North Pole), as well as several other volunteers. Two expeditions to arctic Russia were carried out, across longitudes 50-170 E, to cover a region that had not been sampled in the 1983/84 survey. The filters are examined with a spectrophotometer, scanning wavelengths 450-900 nm. The relative contributions of BC and soil dust to the absorption can be estimated from the spectral dependence of transmission. Calibration is achieved with use of several standard filters containing measured amounts of a commercial soot with a mass absorption cross-section of about 6 square meters per gram. Preliminary results indicate that the snow cover in Alaska, Canada, and the Arctic Ocean has lower BC concentrations now than 20 years ago (5-10 ppb instead of 15-30 ppb), consistent with the declining trend of BC found in air samples at Alert. Background levels of BC in arctic Russia, distant from sources of local pollution, have median values 20-30 ppb, but with higher concentrations at the surface at some locations, and lower concentrations in newly fallen snow. In some regions, particularly the Canadian Arctic islands and the Arctic coast of northeast Siberia, the snow cover, even at its maximum depth in April before melting began, was thin and patchy; in these regions the albedo is determined more by snow thickness than by

  13. 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,

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

    NASA Astrophysics Data System (ADS)

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

    2010-06-01

    The snow physics of a distributed biosphere hydrological model, referred to as the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) is improved by incorporating the three-layer physically based energy balance snowmelt model of Simplified Simple Biosphere 3 (SSiB3) and the Biosphere-Atmosphere Transfer Scheme (BATS) albedo scheme. WEB-DHM with improved snow physics (WEB-DHM-S) can simulate the variability of snow density, snow depth and snow water equivalent, liquid water and ice content in each layer, prognostic snow albedo, diurnal variation in snow surface temperature, thermal heat due to conduction and liquid water retention. The performance of WEB-DHM-S is evaluated at two alpine sites of the Snow Model Intercomparison Project with different climate characteristics: Col de Porte in France and Weissfluhjoch in Switzerland. The simulation results of the snow depth, snow water equivalent, surface temperature, snow albedo and snowmelt runoff reveal that WEB-DHM-S is capable of simulating the internal snow process better than the original WEB-DHM, with the root mean square error and bias error being remarkably reduced. Although WEB-DHM-S is only evaluated at a point scale for the simulation of snow processes, this study provides a benchmark for the application of WEB-DHM-S in cold regions in the assessment of the basin-scale snow water equivalent and seasonal discharge simulation for water resources management.

  15. 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.

  16. 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.

  17. 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.

  18. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

    The seasonal snow in the Pyrenees is critical for hydropower production, crop irrigation and tourism in France, Spain and Andorra. Complementary to in situ observations, satellite remote sensing is useful to monitor the effect of climate on the snow dynamics. The MODIS daily snow products (Terra/MOD10A1 and Aqua/MYD10A1) are widely used to generate snow cover climatologies, yet it is preferable to assess their accuracies prior to their use. Here, we use both in situ snow observations and remote sensing data to evaluate the MODIS snow products in the Pyrenees. First, we compare the MODIS products to in situ snow depth (SD) and snow water equivalent (SWE) measurements. We estimate the values of the SWE and SD best detection thresholds to 40 mm water equivalent (we) and 105 mm respectively, for both MOD10A1 and MYD10A1. Kappa coefficients are within 0.74 and 0.92 depending on the product and the variable. Then, a set of Landsat images is used to validate MOD10A1 and MYD10A1 for 157 dates between 2002 and 2010. The resulting accuracies are 97% (κ = 0.85) for MOD10A1 and 96% (κ = 0.81) for MYD10A1, which indicates a good agreement between both datasets. The effect of vegetation on the results is analyzed by filtering the forested areas using a land cover map. As expected, the accuracies decreases over the forests but the agreement remains acceptable (MOD10A1: 96%, κ = 0.77; MYD10A1: 95%, κ = 0.67). We conclude that MODIS snow products have a sufficient accuracy for hydroclimate studies at the scale of the Pyrenees range. Using a gapfilling algorithm we generate a consistent snow cover climatology, which allows us to compute the mean monthly snow cover duration per elevation band. We finally analyze the snow patterns for the atypical winter 2011-2012. Snow cover duration anomalies reveal a deficient snowpack on the Spanish side of the Pyrenees, which seems to have caused a drop in the national hydropower production.

  20. Weak snow layer detection based on relative differences in snow properties between layers

    NASA Astrophysics Data System (ADS)

    Monti, Fabiano; Schweizer, Jürg

    2013-04-01

    Snow stratigraphy information plays a prominent role in avalanche forecasting. Therefore, it is important how both manually collected and simulated snow profiles are interpreted in regard to snow stability. In the last few years several semi-quantitative methods have been developed to reduce the subjectivity of stability evaluation derived from snow profiles. One of them is the threshold sum approach (TSA), which identifies structural discontinuities related to mechanical stability within snow profiles by analyzing snow layers (i.e. grain size, type, hardness) and their interface properties (i.e. depth, difference in grain size and hardness). The threshold values identifying the structural properties were defined statistically and are optimized for the data sets they were based on. Since this approach relies entirely on absolute thresholds, problems arise, if properties (e.g. grain size estimation) are collected in a different way. Even though guidelines for collecting snow profiles are internationally defined, slight differences between observers of different avalanche services exist. The same problem arises when using this approach for simulated snow profiles. We propose a revised threshold sum approach for snow profile interpretation. Instead of using absolute values, we applied relative differences and values to the snow profiles, e.g. it was not considered how soft a snow layer is, but rather how soft it was compared to the weighted average value of the profile. This method allows the detection of potential weak layers within a snow profile but does not give an absolute estimation of their weakness. In other words, we give a probability that a particular layer is a weak layer. We tested this relative threshold approach (RTA) on a data set consisting of 128 manually recorded snow profiles, which were collected near the fracture line of or on slopes adjacent to skier-triggered avalanches. Results are encouraging since the RTA detected the weak layers related to

  1. Estimate of snow density knowing grain and share hardness

    NASA Astrophysics Data System (ADS)

    Valt, Mauro; Cianfarra, Paola; Cagnati, Anselmo; Chiambretti, Igor; Moro, Daniele

    2010-05-01

    Alpine avalanche warning services produces, weekly, snow profiles. Usually such profiles are made in horizontal snow fields, homogenously distributed by altitude and climatic micro-areas. Such profile allows grain shape, dimension and hardness (hand test) identification. Horizontal coring of each layer allows snow density identification. Such data allows the avalanche hazard evaluation and an estimation of the Snow Water Equivalent (SWE). Nevertheless the measurement of snow density, by coring, of very thin layers (less than 5 cm of thickness) is very difficult and are usually not measured by snow technicians. To bypass such problems a statistical analysis was performed to assign density values also to layers which cannot be measured. This system allows, knowing each layer thickness and its density, to correctly estimate SWE. This paper presents typical snow density values for snow hardness values and grain types for the Eastern Italian Alps. The study is based onto 2500 snow profiles with 17000 sampled snow layers from the Dolomites and Venetian Prealps (Eastern Alps). The table of typical snow density values for each grain type is used by YETI Software which elaborate snow profiles and automatically evaluate SWE. This method allows a better use of Avalanche Warning Services datasets for SWE estimation and local evaluation of SWE yearly trends for each snow field.

  2. 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.

  3. 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.

  4. Snow and glacier mapping with polarimetric SAR

    NASA Technical Reports Server (NTRS)

    Shi, Jiancheng; Dozier, Jeff; Rott, Helmut; Davis, Robert E.

    1991-01-01

    The objective of this study was to examine the capability of mapping snow and glaciers in alpine regions using synthetic aperture radar (SAR) imagery when topographic information is not available. The topographic effects on the received power for a resolution cell can be explained by the change in illumination area and incidence angle in a slant-rante representation of SAR imagery. The specific polarization signatures and phase difference between HH and VV components are relatively independent of the illuminated are, and the incidence angle has only a small effect on these parameters. They provide a suitable measurement data set for snow and glacier mapping in a high-relief area. The results show that the C-band images of the enhancement factor, the phase difference between HH and VV scattering components, and the normalized cross product of VV scattering elements provide the capability to discriminate among snow with different wetnesses, glaciers, and rocky regions.

  5. 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.

  6. 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.

  7. 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

  8. Our sense of Snow: the myth of John Snow in medical geography.

    PubMed

    McLeod, K S

    2000-04-01

    In 1854, Dr. John Snow identified the Broad Street pump as the source of an intense cholera outbreak by plotting the location of cholera deaths on a dot-map. He had the pump handle removed and the outbreak ended...or so one version of the story goes. In medical geography, the story of Snow and the Broad Street cholera outbreak is a common example of the discipline in action. While authors in other health-related disciplines focus on Snow's "shoe-leather epidemiology", his development of a water-borne theory of cholera transmission, and/or his pioneering role in anaesthesia, it is the dot-map that makes him a hero in medical geography. The story forms part of our disciplinary identity. Geographers have helped to shape the Snow narrative: the map has become part of the myth. Many of the published accounts of Snow are accompanied by versions of the map, but which map did Snow use? What happens to the meaning of our story when the determinative use of the map is challenged? In his book On the Mode of Communication of Cholera (2nd ed., John Churchill, London, 1855), Snow did not write that he used a map to identify the source of the outbreak. The map that accompanies his text shows cholera deaths in Golden Square (the subdistrict of London's Soho district where the outbreak occurred) from August 19 to September 30, a period much longer than the intense outbreak. What happens to the meaning of the myth when the causal connection between the pump's disengagement and the end of the outbreak is examined? Snow's data and text do not support this link but show that the number of cholera deaths was abating before the handle was removed. With the drama of the pump handle being questioned and the map, our artifact, occupying a more illustrative than central role, what is our sense of Snow?

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. 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

  14. 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

  15. Microwave remote sensing of snow-covered sea ice

    NASA Technical Reports Server (NTRS)

    Borgeaud, M.; Kong, J. A.; Lin, F. C.

    1986-01-01

    Snow and ice are modeled as random media characterized by different dielectric constants and correlation functions. In order to model the brine inclusions of sea ice, the random medium is assumed to be anisotropic. A three-layer model is used to simulate a snow-covered ice field with the top layer being snow, the middle layer being ice, and the bottom layer being sea water. The theoretical results are illustrated for thick first-year sea ice covered by dry snow, and for artificial, thin first-year sea ice covered by wet snow as measured in controlled model tank experiments. The radar backscattering cross sections are seen to increase with snow cover for snow-covered sea ice owing to large volume scattering effects of snow.

  16. 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.

  17. 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.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  20. 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.

  1. 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.

  2. CHEMICAL IMAGING OF THE CO SNOW LINE IN THE HD 163296 DISK

    SciTech Connect

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

    2015-11-10

    The condensation fronts (snow lines) of H{sub 2}O, 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 N{sub 2}H{sup +} J = 3−2 and DCO{sup +} 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 N{sub 2}H{sup +} 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 C{sup 18}O data, which implies a sharp drop in CO abundance at 90 AU. Thus N{sub 2}H{sup +} appears to be a robust tracer of the midplane CO snow line. The DCO{sup +} 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{sup +} 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.

  3. Impact of Springtime NAO on Weather Conditions and Snow Melting in the Southwestern US

    NASA Astrophysics Data System (ADS)

    Myoung, B.; Kim, S. H.; Kim, J.; Kafatos, M.

    2015-12-01

    It is reported in this study that the North Atlantic Oscillation (NAO), which has been known to directly affect winter weather conditions in western Europe and the eastern United States, is also linked to surface air temperature and snow melting over the broad southwestern U.S. (SWUS) region in the early warm season. Monthly time-scale correlation and composite analyses using three different multidecadal temperature datasets reveal that NAO-related upstream circulation positively affects not only the means, but also the extremes, of the daily maximum and minimum temperatures in the SWUS. This NAO effect is primarily linked with the positioning of upper-tropospheric anticyclones over the western United States that are associated with development of the positive NAO phase. This link has been strengthened in the last 30-yr period (1980-2009), compared to the previous 30-yr period (1950-79). We further examine the impact of NAO on snow melting using snow equivalent water (SWE) of automated snow telemetry (SNOTEL) over SWUS. The significant negative correlations widespread in SWUS between the NAO average and zero-SWE date during snow melting periods, indicate that frequent positive (negative) NAO phases enhance (delay) snow melting inter-annually. This linkage is found to be stronger at the low-elevation sites below 3200 m. The underlying mechanism for this linkage is that positive (negative) NAO phases tend to bring not only warmer (colder) but also drier (wetter) weather conditions to the SWUS region in spring. These results emphasize the role of NAO on springtime weather conditions, snowpack characteristics, and related water resource over the SWUS region.

  4. 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.

  5. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  6. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  7. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  8. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  9. 14 CFR 139.313 - Snow and ice control.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ...) Positioning snow off the movement area surfaces so all air carrier aircraft propellers, engine pods, rotors... portion of the movement area; (3) Selection and application of authorized materials for snow and ice... contain methods and procedures for snow and ice control equipment, materials, and removal that...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. Polarimetric analysis of snow-covered and bare lake ice from Ku and X-band scatterometer data

    NASA Astrophysics Data System (ADS)

    Ben Khadhra, K.; Gunn, G. E.; Duguay, C. R.; Kelly, R. E.

    2011-12-01

    Lake ice plays a key role in regional climate, and has significant physical, biological and socio-economic impacts (e.g. fish overwintering habitat, winter-road transportation, public safety). In the last two decades, there has been growing interest by the international remote sensing community to explore radar polarimetry for glaciological investigations, mainly for glaciers and ice sheet. Polarimetric synthetic aperture radar (SAR) could be a potential tool for lake ice cover mapping and ice thickness estimation. In this paper, we represent results from the first investigation of fully polarimetric Ku and X-band (9.6 and 17.2 GHz, respectively) scatterometer data collected over lake near Churchill, Manitoba. Several controlled and calibrated experimental measurements were carried out during winter 2010-2011, as a contribution to the Cold Regions Hydrology High-resolution Observatory (CoReH2O) candidate mission of the European Space Agency (ESA). Scatterometer scans were made on several occasions at five undisturbed static sites on Ramsey Lake. Measurements characterizing snow and ice properties were also gathered immediately after scatterometer scans. Snow depth and density, snow water equivalent, gain size, ice thickness, ice composition and air inclusion in ice volume were determined at each site. This field data set was very important for the interpretation of the polarimetric parameters, e.g. the copolarization ratio, the copolarization phase and the depolarization ratio. First, the polarimetric parameters have been analysed for the two layers (snow and ice) covariance matrix and where snow subsequently removed. Thus, the influence of the snow layer on the polarimetric data could be quantified. Also, the Pauli and Cloude/Pottier polarimetric decompositions were applied for the two-layer and one-layer scattering mechanisms (removed snow) to quantify the effectiveness of these decompositions. Results show that the polarimetric SAR could explain the different

  16. Variability in the annual cycle of Northern Hemisphere snow extent, using a newly completed climate data record

    NASA Astrophysics Data System (ADS)

    Henderson, G. R.; Leathers, D. J.; Robinson, D. A.

    2012-12-01

    Variability in the annual cycle of Northern Hemisphere snow cover extent (SCE) may have important impacts on the global climate system through a number of potential feedback mechanisms. Motivated by recent snow literature heralding reports ranging from earlier spring melt, to an overall seasonal decrease in SCE, both spatial and temporal variability in extent are explored using a newly completed SCE climate data record (CDR). From a hydrologic standpoint, such shifts have huge implications to the overall climatology of any region with snow present in its seasonal cycle. The SCE CDR utilized in this study is the result of a reanalysis of NOAA satellite-derived maps of NH continental SCE and begins in 1966. The earlier 33 years of data are drawn from coarse-scale weekly NOAA maps, whilst recent years are based on a downgraded version of the IMS 24 km NOAA product, currently produced by the National Ice Center. The Rutgers Global Snow Lab undertook reanalysis and merging of the different resolution datasets as part of the NASA MEaSUREs project. Principal component (PC) analysis was performed on the annual cycle of NH, and individual continental snow extent totals. Close to 75% of variance was explained by the first three PCs, in the case of NH and Eurasia snow extents. Snow composite analysis based on positive PC scores time series years displays greater snow extent, in excess of 4 × 106 km2 in the case of the NH alone. Preliminary assessment of associations with large-scale atmospheric patterns (e.g. surface air temperature, mid-tropospheric geopotential height), yielded patterns indicative of know teleconnection patterns such as the AO and NAO indices. Results from additional PC analysis performed spatially on the SCE CDR will be discussed.

  17. Enhancement of the MODIS Daily Snow Albedo Product

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  18. Trends of perchlorate in Antarctic snow: Implications for atmospheric production and preservation in snow

    NASA Astrophysics Data System (ADS)

    Jiang, Su; Cox, Thomas S.; Cole-Dai, Jihong; Peterson, Kari M.; Shi, Guitao

    2016-09-01

    Perchlorate concentration ranges from a few to a few hundred ng kg-1 in surface and shallow-depth snow at three Antarctic locations (South Pole, Dome A, and central West Antarctica), with significant spatial variations dependent on snow accumulation rate and/or atmospheric production rate. An obvious trend of increasing perchlorate since the 1970s is seen in South Pole snow. The trend is possibly the result of stratospheric chlorine levels elevated by anthropogenic chlorine emissions; this is supported by the timing of a similar trend at Dome A. Alternatively, the trend may stem from postdepositional loss of snowpack perchlorate or a combination of both. The possible impact of stratospheric chlorine is consistent with evidence of perchlorate production in the stratosphere. Additionally, perchlorate concentration appears to be directly affected by the springtime Antarctic ozone hole. Therefore, perchlorate variations in Antarctic snow are likely linked to stratospheric chemistry and ozone over the Antarctic.

  19. 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.

  20. 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…

  1. "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…

  2. [Ocular injury by artificial snow spray].

    PubMed

    Ben-Nissan, D; Savir, H

    1990-12-01

    We treated the eyes of 12 children, aged 2.5-16 years, which were injured by artificial snow-spray during Israel's Independence Day festivities in 1987 and 1989. There was chemical damage to the conjunctiva and cornea which took 1-3 weeks to heal.

  3. 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.

  4. Estimating snow grain size using AVIRIS data

    NASA Technical Reports Server (NTRS)

    Nolin, Anne W.; Dozier, Jeff

    1993-01-01

    Estimates of snow grain size for the near-surface snow layer were calculated for the Tioga Pass region and Mammoth Mountain in the Sierra Nevada, California, using an inversion technique and data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The Tioga Pass and Mammoth Mountain single-band AVIRIS radiance images were atmospherically corrected to obtain surface reflectance. A discrete-ordinate model was used to calculate directional reflectance as a function of snowpack grain size for a wide range of snow grain radii. The resulting radius vs. reflectance curves were each fit using a nonlinear least squares technique which provided a means of transforming surface reflectance in each AVIRIS image to optically equivalent grain size on a per-pixel basis. The model results and grain size estimates derived from the AVIRIS data show that, for solar incidence angles between 0 and 30, the technique provides good estimates of grain size. This work provides the first quantitative estimates for grain size using data acquired from an airborne remote sensing instrument and is an important step in improving our ability to retrieve snow physical properties independent of field measurements.

  5. 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…

  6. 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).

  7. 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

  8. 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.

  9. Canopy Effects on Macroscale Snow Sublimation

    NASA Astrophysics Data System (ADS)

    Svoma, B. M.

    2015-12-01

    Sublimation of snow cover directly affects snow accumulation, impacting ecosystem processes, soil moisture, soil porosity, biogeochemical processes, wildfire, and water resources. Available energy, the exposed surface area of a snow cover, and exposure time with the atmosphere vary greatly in complex terrain (e.g., aspect, elevation, forest cover), with latitude, and with continentality. It is therefore difficult to scale up results from site specific short term studies. Using the 32-km NARR, the 4-km PRISM, with 30-m terrain and forest cover data, meteorological variables are downscaled to simulate sublimation from canopy intercepted snow and from the snowpack over the Salt River Basin in Arizona for a wet and dry year. Simulations indicate that: (1) total sublimation is highly variable in response to variability in both sublimation rate and snow cover duration; (2) total canopy sublimation is similar for both years while ground sublimation is considerably greater during the wet year; (3) sublimation is a relatively greater contribution to the snow water budget during the dry year (28% vs. 20% of total snowfall); (4) at high elevations, ground sublimation is less in open areas than forested areas during the dry year, while the reverse is evident during the wet year as snowpack lasted longer into spring. While a reduction in leaf area index leads to a reduction of total sublimation due to less interception in both years, ground sublimation increases during the dry year, possibly due to less sheltering from solar radiation and wind. This reduction in sheltering results in a large decrease in snowpack duration (i.e., ten days in spring) at mid-elevations for the wet year, leading to a decrease in ground sublimation. This results in a 500 meter difference in the elevation of maximum sublimation reduction upon reduced leaf area index between the two years. Forest cover properties can vary considerably on short and long time scales through natural (wildfire, bark beetle

  10. 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.

  11. Northern Hemisphere snow cover and atmospheric blocking variability

    NASA Astrophysics Data System (ADS)

    GarcíA-Herrera, Ricardo; Barriopedro, David

    2006-11-01

    The interseasonal relationship between Northern Hemisphere (NH) snow cover and regional blocking patterns is explored for a 31-year data set. It is found that snow cover exerts an important influence on regional atmospheric blocking, which, in turn, modulates snow cover extent at subcontinental scales. Observational results provide strong evidence of two primary linkages in the seasonal snow cover-blocking relationship that support an interannual persistence cycle: The first one links winter blocking over the Atlantic and the subsequent spring (summer) Eurasian (North American) snow cover anomalies; the second one implies that spring (summer) Eurasian (North American) snow cover precedes an anomalous winter Atlantic blocking activity. We describe the temporal stages of the snow cover-blocking relationship in the framework of a six-step conceptual model. According to that, an enhanced Atlantic blocking activity in winter favors a later spring snow disappearance through an enhanced cold advection toward western Eurasia. The resulting snow cover anomalies partially force an opposite-sign blocking response over west and central Pacific which is sustained through spring and early summer, presumably because of the persistence of snow cover anomalies. This anomalous pattern seems to play a role in the propagation of snow cover anomalies from Eurasia in spring to the Hudson's Bay region of North America in summer. The excessive snow cover over this region induces an asymmetrical temperature distribution, which, in turn, favors blocking activity over Europe and the West Pacific. The connection between autumn and winter climates is not clear but it could be related with the ability of autumn high ATL blocking activity to determine an early snow cover appearance in October over western Eurasia. This linkage completes a snow cover-blocking cycle of interactions which identifies snow cover as a candidate for the recently observed blocking trends and a contributor to the

  12. [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

  13. [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.

  14. 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.

  15. 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.

  16. Development of an Automatic Blowing Snow station

    NASA Astrophysics Data System (ADS)

    Nishimura, K.

    2010-12-01

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

  17. Manual Snow Removal and Sudden Death.

    PubMed

    Skavić, Petar; Stemberga, Valter; Duraković, Din

    2015-06-01

    The aim was to analyze the causes of sudden death in middle-aged and elderly men during manual snow removal. During snowy winter months in Zagreb, from January 2013 to January 2014, four males aged 52, 65, 72 and 81, died suddenly while manually removing snow. They were all autopsied. All of them have suffered from arterial hypertension and coronary heart disease, and one suffered from metabolic syndrome. The cause of death in two was probable malignant ventricular arrhythmia. In the third who fell down on the icy surface, consequences were cerebral contusion and neck vertebral luxation. In the fourth who fell down from the top of a 15 m tall building during snow removal, the cause of death were multiple injuries: fractures of both clavicles, ribs and vertebrae's Th5, Th6, hematothorax, cardiac contusion, hematopericardium, thoracic aorta rupture, contusions and ruptures of both lungs, rupture of the diaphragm, liver rupture, hematoperitoneum and cerebral edema. The estimated death rate in the City of Zagreb for males aged 30-64 years is 5.44/1,000,000 inhabitants, which is less than in those aged 65-85 years (40.03/1,000,000; p = 0.2269). Sudden strenuous physical effort due to manual snow removal in two non-trained persons, who have suffered from arterial hypertension and coronary heart disease, was the cause of sudden death. Manual snow removal is an important cause of sudden death, as it is a very arduous effort in non-adapted middle-aged and elderly persons. PMID:26753462

  18. Manual Snow Removal and Sudden Death.

    PubMed

    Skavić, Petar; Stemberga, Valter; Duraković, Din

    2015-06-01

    The aim was to analyze the causes of sudden death in middle-aged and elderly men during manual snow removal. During snowy winter months in Zagreb, from January 2013 to January 2014, four males aged 52, 65, 72 and 81, died suddenly while manually removing snow. They were all autopsied. All of them have suffered from arterial hypertension and coronary heart disease, and one suffered from metabolic syndrome. The cause of death in two was probable malignant ventricular arrhythmia. In the third who fell down on the icy surface, consequences were cerebral contusion and neck vertebral luxation. In the fourth who fell down from the top of a 15 m tall building during snow removal, the cause of death were multiple injuries: fractures of both clavicles, ribs and vertebrae's Th5, Th6, hematothorax, cardiac contusion, hematopericardium, thoracic aorta rupture, contusions and ruptures of both lungs, rupture of the diaphragm, liver rupture, hematoperitoneum and cerebral edema. The estimated death rate in the City of Zagreb for males aged 30-64 years is 5.44/1,000,000 inhabitants, which is less than in those aged 65-85 years (40.03/1,000,000; p = 0.2269). Sudden strenuous physical effort due to manual snow removal in two non-trained persons, who have suffered from arterial hypertension and coronary heart disease, was the cause of sudden death. Manual snow removal is an important cause of sudden death, as it is a very arduous effort in non-adapted middle-aged and elderly persons.

  19. 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.

  20. Snow property measurements correlative to microwave emission at 35 GHz

    NASA Technical Reports Server (NTRS)

    Davis, Robert E.; Dozier, Jeff; Chang, Alfred T. C.

    1987-01-01

    Snow microstructure, measured by plane section analysis, and snow wetness, measured by the dilution method, are used to calculate input parameters for a microwave emission model that uses the radiative transfer method. The scattering and absorbing properties are calculated by Mie theory. The effects of different equivalent sphere conversions, adjustments for near-field interference, and different snow wetness characterizations are compared for various snow conditions. The concentric shell geometry of liquid water in snow yields higher emissivities and better model results than the separate-sphere configuration for liquid water contents greater than 0.05, while at lower liquid water contents the separate-sphere treatment gives better results.

  1. Snow property measurements correlative to microwave emission at 35 GHz

    NASA Technical Reports Server (NTRS)

    Davis, R. E.; Dozier, J.; Chang, A. T. C.

    1986-01-01

    Snow microstructure, measured by plane section analysis, and snow wetness, measured by the dilution method, are used to calculate input parameters for a microwave emission model that uses the radiative transfer method. The scattering and absorbing properties are calculated by Mie theory. The effects of different equivalent sphere conversions, adjustments for near-field interference, and different snow wetness characterizations are compared for various snow conditions. The concentric shell geometry of liquid water in snow yields higher emissivities and better model results than the separate-sphere configuration for liquid water contents greater than 0.05, while at lower liquid water contents the separate-sphere treatment gives better results.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Research of microwave scattering properties of snow fields

    NASA Technical Reports Server (NTRS)

    Angelakos, D. J.

    1978-01-01

    The results obtained in the research program of microwave scattering properties of snow fields are presented. Experimental results are presented showing backscatter dependence on frequency (5.8-8.0 GHz), angle of incidence (0-60 degrees), snow wetness (time of day), and frequency modulation (0-500 MHz). Theoretical studies are being made of the inverse scattering problem yielding some preliminary results concerning the determination of the dielectric constant of the snow layer. The experimental results lead to the following conclusions: snow layering affects backscatter, layer response is significant up to 45 degrees of incidence, wetness modifies snow layer effects, frequency modulation masks the layer response, and for the proper choice of probing frequency and for nominal snow depths, it appears to be possible to measure the effective dielectric constant and the corresponding water content of a snow pack.

  8. 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.

  9. 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.

  10. 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.

  11. Analysis of snow feedbacks in 14 general circulation models

    NASA Technical Reports Server (NTRS)

    Randall, D. A.; Cess, R. D.; Blanchet, J. P.; Chalita, S.; Colman, R.; Dazlich, D. A.; Del Genio, A. D.; Keup, E.; Lacis, A.; Le Treut, H.

    1994-01-01

    Snow feedbacks produced by 14 atmospheric general circulation models have been analyzed through idealized numerical experiments. Included in the analysis is an investigation of the surface energy budgets of the models. Negative or weak positive snow feedbacks occurred in some of the models, while others produced strong positive snow feedbacks. These feedbacks are due not only to melting snow, but also to increases in boundary temperature, changes in air temperature, changes in water vapor, and changes in cloudiness. As a result, the net response of each model is quite complex. We analyze in detail the responses of one model with a strong positive snow feedback and another with a weak negative snow feedback. Some of the models include a temperature dependence of the snow albedo, and this has significantly affected the results.

  12. 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.

  13. 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.

  14. Comparison of Landsat and MODIS for assessing surface properties of snow and ice

    NASA Astrophysics Data System (ADS)

    Lhermitte, Stef; Van Lipzig, Nicole P. M.

    2014-05-01

    Assessment of the spatio-temporal variations in snow and ice properties provides valuable input for a variety of climatological, hydrological, glaciological applications ranging from energy and mass budget calculations to distributed snowmelt modelling. Within this context a variety of retrieval methods has been developed to assess surface properties from multi-spectral Landsat and MODIS data. These methods range from spectral index calculations and unmixing methods to combined remote sensing and radiative transfer approaches. This study provides a quantitative analysis of the trade-offs between the state-of-the-art retrieval methodologies applied on Landsat and MODIS data. Within this context, spatio-temporal patterns of surface properties (e.g., snow cover fraction, albedo, grain size, impurity load, ponding melt water, snow/ice classification) are derived from Landsat and MODIS reflectance data over two study areas covering parts of the Greenland Ice Sheet and the Chilean Andes from 2000 to present. The retrieved properties are subsequently compared and validated based on reference in-situ measurements. Analysis of the differences in derived surface properties from Landsat and MODIS reveals the importance of understanding the spatial and temporal scales at which variations occur. Large spatial variability within a MODIS pixel complicates the performance of retrieval methods for MODIS time series, especially for surface properties not related to snow cover fractions. Large temporal variability, on the other hand, constrains the validity of time series of Landsat retrievals and also has a large impact on the use of multi-day composite MODIS data.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. Small-area snow surveys on the northern plains of North Dakota

    USGS Publications Warehouse

    Emerson, D.G.; Carroll, T.R.; Steppuhn, Harold

    1985-01-01

    The variation in snow cover over small areas is the focus of this study of the feasibility of using aerial surveys to obtain information on the snow water equivalent of the snow cover in order to minimize the necessity of labor intensive ground snow surveys. A low-flying aircraft was used to measure attenuations of natural terrestrial gamma radiation by snow cover. Aerial and ground snow surveys of eight 1-mile snow courses and one 4-mile snow course in North Dakota were used in the evaluation, with ground snow surveys used as the base to evaluate aerial data. Each of the 1-mile snow courses consisted of a single land use and all had the same terrain type (plane). The 4-mile snow course consists of a variety of land uses and the same terrain type (plane). Using the aerial snow-survey technique, the snow water equivalent of the 1-mile snow courses was measured with three passes of the aircraft. Use of more than one pass did not improve the results. The mean absolute difference between the aerial- and ground-measured snow water equivalents for the 1-mile snow courses was 26 percent (0.77 inches). The aerial snow water equivalents determined for the 1-mile snow courses were used to estimate the variations in the snow water equivalents over the 4-mile snow course. The weighted mean absolute difference for the 4-mile snow course was 27 percent (0.8 inches). Variations in snow water equivalents could not be verified adequately by segmenting the aerial snow-survey data because of the uniformity found in the snow cover. On the 4-mile snow course, about two-thirds of the aerial snow-survey data agreed with the ground snow-survey data within the accuracy of the aerial technique (+or-0.5 inch of the mean snow water equivalent). (USGS)

  3. 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.

  4. 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.

  5. 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

  6. A Model for the Spectral Albedo of Snow. II: Snow Containing Atmospheric Aerosols.

    NASA Astrophysics Data System (ADS)

    Warren, Stephen G.; Wiscombe, Warren J.

    1980-12-01

    Small highly absorbing particles, present in concentrations of only 1 part per million by weight (ppmw) or less, can lower snow albedo in the visible by 5-15% from the high values (96-99%) predicted for pure snow in Part I. These particles have, however, no effect on snow albedo beyond 0.9 m wavelength where ice itself becomes a strong absorber. Thus we have an attractive explanation for the discrepancy between theory and observation described in Part I, a discrepancy which seemingly cannot be resolved on the basis of near-field scattering and nonsphericity effects.Desert dust and carbon soot are the most likely contaminants. But careful measurements of spectral snow albedo in the Arctic and Antarctic paint to a `grey' absorber, one whose imaginary refractive index is nearly constant across the visible spectrum. Thus carbon soot, rather than the red iron oxide normally present in desert dust, is strongly indicated at these sites. Soot particles of radius 0.1 m, in concentrations of only 0.3 ppmw, can explain the albedo measurements of Grenfell and Maykut on Arctic Ice Island T-3. This amount is consistent with some observations of soot in Arctic air masses. 1.5 ppmw of soot is required to explain the Antarctic observations of Kuhn and Siogas, which seemed an unrealistically large amount for the earth's most unpolluted continent until we learned that burning of camp heating fuel and aircraft exhaust indeed had contaminated the measurement site with soot.Midlatitude snowfields are likely to contain larger absolute amounts of soot and dust than their polar counterparts, but the snowfall is also much larger, so that the ppmw contamination does not differ drastically until melting begins. Nevertheless, the variations in absorbing particle concentration which will exist can help to explain the wide range of visible snow albedos reported in the literature.Longwave emissivity of snow is unaltered by its soot and dust content. Thus the depression of snow albedo in the

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. Quantitative stratigraphy of snow resolved by high-resolution penetrometry

    NASA Astrophysics Data System (ADS)

    Proksch, Martin; Reuter, Benjamin; Schneebeli, Martin; Löwe, Henning

    2014-05-01

    Precise measurements of snow structural parameters are essential to understand and model snow physical processes. Snow metamorphism, mass and energy balance of snow, radiative properties or the snowpack stability with respect to avalanche formation, all these processes depend on the snow structural parameters and the stratigraphy of the snowpack. However, most snow measurements are limited in spatial and temporal resolution and by extensive measurement times. For this reason, we developed a statistical model to derive three major snow structural parameters, density, correlation length and specific surface area (SSA) solely from a portable, high-resolution penetrometer. We demonstrate the potential of the method by a transect through Alpine snow in the Wannengrat study site, Davos, Switzerland. The two-dimensional plot of the transect reveals the depositional and metamorphic events. The results for the density are compared to independent density measurements from snow profiles. Based on these data, we are able to give a more complete interpretation of the snow stratigraphy and the underlying physical processes.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. [Psycrophilic organisms in snow and ice].

    PubMed

    Kohshima, S

    2000-12-01

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

  3. Limitations of modeling snow in ski resorts

    NASA Astrophysics Data System (ADS)

    Steiger, Robert; Abegg, Bruno

    2016-04-01

    The body of literature on snow modeling in a ski area operations context has been growing over the last decades in an accelerating speed. The majority of snow model applications for ski areas can be found in the climate change impacts literature. These studies differ in many aspects: the type of model used; the meteorological variables used in the models; the spatial and temporal resolution of the meteorological variables; the method how the climate change signal is derived and applied in the model concept; the number of climate models and emission scenarios used and consequently the handling of uncertainties; the indicators used to interpret the impacts for the skiing tourism industry; the incorporation of adaptation measures (e.g. snowmaking); and the geographical scale of analysis. In this contribution we will present a review of approaches used for modeling snow conditions in a ski area context. The major limitations both from a scientific as well as from a users' perspective will be discussed and solutions for shortcomings of existing approaches will be presented.

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

    PubMed

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

    2013-08-01

    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 occurring

  5. 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

  6. 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

  7. 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.

  8. 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...

  9. Snow depth and snow cover retrieval from FengYun3B microwave radiation imagery based on a snow passive microwave unmixing method in Northeast China

    NASA Astrophysics Data System (ADS)

    Gu, Lingjia; Ren, Ruizhi; Zhao, Kai; Li, Xiaofeng

    2014-01-01

    The precision of snow parameter retrieval is unsatisfactory for current practical demands. The primary reason is because of the problem of mixed pixels that are caused by low spatial resolution of satellite passive microwave data. A snow passive microwave unmixing method is proposed in this paper, based on land cover type data and the antenna gain function of passive microwaves. The land cover type of Northeast China is partitioned into grass, farmland, bare soil, forest, and water body types. The component brightness temperatures (CBT), namely unmixed data, with 1 km data resolution are obtained using the proposed unmixing method. The snow depth determined by the CBT and three snow depth retrieval algorithms are validated through field measurements taken in forest and farmland areas of Northeast China in January 2012 and 2013. The results show that the overall of the retrieval precision of the snow depth is improved by 17% in farmland areas and 10% in forest areas when using the CBT in comparison with the mixed pixels. The snow cover results based on the CBT are compared with existing MODIS snow cover products. The results demonstrate that more snow cover information can be obtained with up to 86% accuracy.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Microwave Radar Retrieval of Snow Water Equivalent

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  16. Modelling of microwave emission and scattering from snow and soil

    NASA Technical Reports Server (NTRS)

    Fung, Adrian K.; Chen, M. F.

    1989-01-01

    In the past a snow layer has been modeled as a homogeneous layer embedded with sparsely populated Rayleigh scatterers above an irregular ground surface. The effect of the ground surface can be ignored if the layer is sufficiently lossy due to wetness in the snow. The top surface of the snow layer may be treated as plane or irregular depending upon its actual shape and its wetness condition. For a dry snow condition where the electromagnetic wave can penetrate easily one can ignore the air-snow interface. As a result a variety of emission and scattering models exist. An improvement to the existing scattering or emission model would consist of an irregular layer with densely populated correlated scatterers. The development of this model and its application to scattering and emission from a snow layer are discussed. Also disucssed is a surface scattering model for a soil surface.

  17. 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.

  18. Impact of layering and microstructure on gas diffusion through snow

    NASA Astrophysics Data System (ADS)

    Whelsky, A. N.; Albert, M. R.

    2015-12-01

    Understanding relationships between snow structure and gas transport properties in seasonal snow is crucial for correctly quantifying gas fluxes through the snow. Wintertime soil respiration of CO2 has been estimated to significantly contribute to the carbon budget, but CO2 must first diffuse through the snowpack before being released to the atmosphere. The snowpack is not homogeneous; the structure varies both in space and in time, which can have profound impacts on the snow diffusivity. Former assessments of gas flux in seasonal snow apply empirical relations based on single, fixed conditions, which limits the accuracy of the assessment results. In this presentation we report on laboratory measurements through snow and firn samples that have various metamorphic properties. Diffusion coefficients determined from the measurements are used to investigate the impact of layering and inhomogeneous structure on diffusion rates on larger scales, through multidimensional numerical simulations.

  19. Acidobacteria dominate the active bacterial communities of Arctic tundra with widely divergent winter-time snow accumulation and soil temperatures.

    PubMed

    Männistö, Minna K; Kurhela, Emilia; Tiirola, Marja; Häggblom, Max M

    2013-04-01

    The timing and extent of snow cover is a major controller of soil temperature and hence winter-time microbial activity and plant diversity in Arctic tundra ecosystems. To understand how snow dynamics shape the bacterial communities, we analyzed the bacterial community composition of windswept and snow-accumulating shrub-dominated tundra heaths of northern Finland using DNA- and RNA-based 16S rRNA gene community fingerprinting (terminal restriction fragment polymorphism) and clone library analysis. Members of the Acidobacteria and Proteobacteria dominated the bacterial communities of both windswept and snow-accumulating habitats with the most abundant phylotypes corresponding to subdivision (SD) 1 and 2 Acidobacteria in both the DNA- and RNA-derived community profiles. However, different phylotypes within Acidobacteria were found to dominate at different sampling dates and in the DNA- vs. RNA-based community profiles. The results suggest that different species within SD1 and SD2 Acidobacteria respond to environmental conditions differently and highlight the wide functional diversity of these organisms even within the SD level. The acidic tundra soils dominated by ericoid shrubs appear to select for diverse stress-tolerant Acidobacteria that are able to compete in the nutrient poor, phenolic-rich soils. Overall, these communities seem stable and relatively insensitive to the predicted changes in the winter-time snow cover.

  20. Tracing the origin of pollution in French Alpine snow and aerosols using lead isotopic ratios.

    PubMed

    Veysseyre, A M; Bollhöfer, A F; Rosman, K J; Ferrari, C P; Boutron, C F

    2001-11-15

    Fresh snow samples collected at 15 remote locations and aerosols collected at one location in the French Alps between November 1998 and April 1999 have been analyzed for Pb concentration and isotopic composition by thermal ionization mass spectrometry. The snow samples contained 19-1300 pg/g of Pb with isotopic ratios 206Pb/207Pb (208Pb/207Pb) of 1.1279-1.1607 (2.3983-2.4302). Airborne Pb concentrations at one sampling site ranged from 0.42 to 6.0 ng/m3 with isotopic ratios of 1.1321-1.1427 (2.4029-2.4160). Air mass trajectory analysis combined with isotopic compositions of potential source regions did not show discernible evidence of the long-range atmospheric transport of pollutants. Isotopic ratios in the Alpine snow samples and thus the free troposphere were generally higher than airborne Pb isotopic ratios in urban France, which coupled with the relatively high Pb concentrations suggested a regional anthropogenic Pb source, probably Italy but possibly Eastern Europe.

  1. Accumulation of hydroxycinnamic acid amides in winter wheat under snow.

    PubMed

    Jin, Shigeki; Yoshida, Midori; Nakajima, Takashi; Murai, Akio

    2003-06-01

    It was found that the content of antifungal compounds p-coumaroylagmatine [1-(trans-4'-hydroxycinnamoylamino)-4-guanidinobutane] and p-coumaroyl-3-hydroxyagmatine [1-(trans-4'-hydroxycinnamoylamino)-3-hydroxy-4-guanidinobutane] in the crown of winter wheat (Triticum aestivum L. cv Chihokukomugi) significantly increased under snow cover. This finding suggests that the accumulation of these hydroxycinnamic acid amides was caused by winter stress and related to protecting the plant against snow mold under snow cover.

  2. 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).

  3. 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.

  4. 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

  5. Idiosyncratic responses of high Arctic plants to changing snow regimes.

    PubMed

    Rumpf, Sabine B; Semenchuk, Philipp R; Dullinger, Stefan; Cooper, Elisabeth J

    2014-01-01

    The Arctic is one of the ecosystems most affected by climate change; in particular, winter temperatures and precipitation are predicted to increase with consequent changes to snow cover depth and duration. Whether the snow-free period will be shortened or prolonged depends on the extent and temporal patterns of the temperature and precipitation rise; resulting changes will likely affect plant growth with cascading effects throughout the ecosystem. We experimentally manipulated snow regimes using snow fences and shoveling and assessed aboveground size of eight common high arctic plant species weekly throughout the summer. We demonstrated that plant growth responded to snow regime, and that air temperature sum during the snow free period was the best predictor for plant size. The majority of our studied species showed periodic growth; increases in plant size stopped after certain cumulative temperatures were obtained. Plants in early snow-free treatments without additional spring warming were smaller than controls. Response to deeper snow with later melt-out varied between species and categorizing responses by growth forms or habitat associations did not reveal generic trends. We therefore stress the importance of examining responses at the species level, since generalized predictions of aboveground growth responses to changing snow regimes cannot be made.

  6. Snow reliability in ski resorts considering artificial snowmaking

    NASA Astrophysics Data System (ADS)

    Hofstätter, M.; Formayer, H.; Haas, P.

    2009-04-01

    Snow reliability is the key factor to make skiing on slopes possible and to ensure added value in winter tourism. In this context snow reliability is defined by the duration of a snowpack on the ski runs of at least 50 mm snow water equivalent (SWE), within the main season (Dec-Mar). Furthermore the snowpack should form every winter and be existent early enough in season. In our work we investigate the snow reliability of six Austrian ski resorts. Because nearly all Austrian resorts rely on artificial snowmaking it is of big importance to consider man made snow in the snowpack accumulation and ablation in addition to natural snow. For each study region observed weather data including temperature, precipitation and snow height are used. In addition we differentiate up to three elevations on each site (valley, intermediate, mountain top), being aware of the typical local winter inversion height. Time periods suitable for artificial snow production, for several temperature threshold (-6,-4 or -1 degree Celsius) are calculated on an hourly base. Depending on the actual snowpack height, man made snow can be added in the model with different defined capacities, considering different technologies or the usage of additives. To simulate natural snowpack accumulation and ablation we a simple snow model, based on daily precipitation and temperature. This snow model is optimized at each site separately through certain parameterization factors. Based on the local observations and the monthly climate change signals from the climate model REMO-UBA, we generate long term time series of temperature and precipitation, using the weather generator LARS. Thereby we are not only able to simulate the snow reliability under current, but also under future climate conditions. Our results show significant changes in snow reliability, like an increase of days with insufficient snow heights, especially at mid and low altitudes under natural snow conditions. Artificial snowmaking can partly

  7. 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

  8. Enhancement of SnowScat for Tomographic Observation Capabilities

    NASA Astrophysics Data System (ADS)

    Frey, Othmar; Werner, Charles L.; Schneebeli, Martin; Macfarlane, Amy; Wiesmann, Andreas

    2015-05-01

    The SnowScat device, a tower-mounted fully polarimetric scatterometer for measurements of the radar cross-section of snow at X-band up to Ku-band, has recently been enhanced to also support a tomographic profiling mode. The new tomographic profiling capability of SnowScat allows for performing high-resolution observations providing further insights into the complex electromagnetic interaction within snowpacks. In this paper, we present first results obtained from a series of tomographic profiles of a snowpack acquired with the enhanced SnowScat device at a test site of SLF in Davos, Switzerland, between Dec. 2014 and March 2015.

  9. 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.

  10. 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.

  11. Phylogeny and biogeography of an uncultured clade of snow chytrids.

    PubMed

    Naff, C S; Darcy, J L; Schmidt, S K

    2013-10-01

    Numerous studies have shown that snow can contain a diverse array of algae known as 'snow algae'. Some reports also indicate that parasites of algae (e.g. chytrids) are also found in snow, but efforts to phylogenetically identify 'snow chytrids' have not been successful. We used culture-independent molecular approaches to phylogenetically identify chytrids that are common in long-lived snowpacks of Colorado and Europe. The most remarkable finding of the present study was the discovery of a new clade of chytrids that has representatives in snowpacks of Colorado and Switzerland and cold sites in Nepal and France, but no representatives from warmer ecosystems. This new clade ('Snow Clade 1' or SC1) is as deeply divergent as its sister clade, the Lobulomycetales, and phylotypes of SC1 show significant (P < 0.003) genetic-isolation by geographic distance patterns, perhaps indicating a long evolutionary history in the cryosphere. In addition to SC1, other snow chytrids were phylogenetically shown to be in the order Rhizophydiales, a group with known algal parasites and saprotrophs. We suggest that these newly discovered snow chytrids are important components of snow ecosystems where they contribute to snow food-web dynamics and the release of nutrients due to their parasitic and saprotrophic activities.

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

    ScienceCinema

    Barry, Roger G.

    2016-07-12

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

  13. 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

  14. 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.

  15. 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

  16. The sublimation temperature of the cometary nucleus Observational evidence for H2O snows

    NASA Technical Reports Server (NTRS)

    Delsemme, A. H.

    1985-01-01

    It is shown that information on the chemical composition of cometary snows can be inferred from the distance r(0) between sublimating states in the cometary nucleus. Consideration is given to three techniques for measuring r(0): estimation of the dependence on distance of non-gravitational forces (NGF); estimation of the dependence on distance of molecular emissions; and (3), analysis of the cometary light curve. The dependence on distance of the NGFs suggests that the observed sublimations of short-period coments are determined by water snow. Light curves of newly discovered comets appear to confirm this result. The large production rates of H and OH in cometary atmospheres suggest that they are due to dissociation of H2O in the vapor states. Estimates of r(0) for eleven different comets are given in a table.

  17. 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

  18. Modelling technical snow production for skiing areas in the Austrian Alps with the physically based snow model AMUNDSEN

    NASA Astrophysics Data System (ADS)

    Hanzer, F.; Marke, T.; Steiger, R.; Strasser, U.

    2012-04-01

    Tourism and particularly winter tourism is a key factor for the Austrian economy. Judging from currently available climate simulations, the Austrian Alps show a particularly high vulnerability to climatic changes. To reduce the exposure of ski areas towards changes in natural snow conditions as well as to generally enhance snow conditions at skiing sites, technical snowmaking is widely utilized across Austrian ski areas. While such measures result in better snow conditions at the skiing sites and are important for the local skiing industry, its economic efficiency has also to be taken into account. The current work emerges from the project CC-Snow II, where improved future climate scenario simulations are used to determine future natural and artificial snow conditions and their effects on tourism and economy in the Austrian Alps. In a first step, a simple technical snowmaking approach is incorporated into the process based snow model AMUNDSEN, which operates at a spatial resolution of 10-50 m and a temporal resolution of 1-3 hours. Locations of skiing slopes within a ski area in Styria, Austria, were digitized and imported into the model environment. During a predefined time frame in the beginning of the ski season, the model produces a maximum possible amount of technical snow and distributes the associated snow on the slopes, whereas afterwards, until to the end of the ski season, the model tries to maintain a certain snow depth threshold value on the slopes. Due to only few required input parameters, this approach is easily transferable to other ski areas. In our poster contribution, we present first results of this snowmaking approach and give an overview of the data and methodology applied. In a further step in CC-Snow, this simple bulk approach will be extended to consider actual snow cannon locations and technical specifications, which will allow a more detailed description of technical snow production as well as cannon-based recordings of water and energy

  19. 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.

  20. Isotopic exchange on the diurnal scale between near-surface snow and lower atmospheric water vapor at Kohnen station, East Antarctica

    NASA Astrophysics Data System (ADS)