Food, energy, and water in an era of disappearing snow

NASA Astrophysics Data System (ADS)

Mote, P.; Lettenmaier, D. P.; Li, S.; Xiao, M.

2017-12-01

Mountain snowpack stores a significant quantity of water in the western US, accumulating during the wet season and melting during the dry summers and supplying more than 65% of the water used for irrigated agriculture, energy production (both hydropower and thermal), and municipal and industrial uses. The importance of snow to western agriculture is demonstrated by the fact that most snow monitoring is performed by the US Department of Agriculture. In a paper published in 2005, we showed that roughly 70% of monitoring sites showed decreasing trends through 2002. Now, with 14 additional years of data, over 90% of snow monitoring sites with long records across the western US show declines through 2016, of which 33% are significant (vs 5% expected by chance) and 2% are significant and positive (vs 5% expected by chance). Declining trends are observed across all months, states, and climates, but are largest in spring, in the Pacific states, and in locations with mild winter climate. We corroborate and extend these observations using a gridded hydrology model, which also allows a robust estimate of total western snowpack and its decline. Averaged across the western US, the decline in total April 1 snow water equivalent since mid-century is roughly 15-30% or 25-50 km3, comparable in volume to the West's largest man-made reservoir, Lake Mead. In the absence of rapid reductions in emissions of greenhouse gases, these losses will accelerate; snow losses on this scale demonstrate the necessity of rethinking water storage, policy, and usage.

Food production & availability - Essential prerequisites for sustainable food security

PubMed Central

Swaminathan, M.S.; Bhavani, R.V.

2013-01-01

Food and nutrition security are intimately interconnected, since only a food based approach can help in overcoming malnutrition in an economically and socially sustainable manner. Food production provides the base for food security as it is a key determinant of food availability. This paper deals with different aspects of ensuring high productivity and production without associated ecological harm for ensuring adequate food availability. By mainstreaming ecological considerations in technology development and dissemination, we can enter an era of evergreen revolution and sustainable food and nutrition security. Public policy support is crucial for enabling this. PMID:24135188

A Distributed Snow Evolution Modeling System (SnowModel)

NASA Astrophysics Data System (ADS)

Liston, G. E.; Elder, K.

2004-12-01

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

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.

Ecosystem water availability in juniper versus sagebrush snow-dominated rangelands

USDA-ARS?s Scientific Manuscript database

Western Juniper (J. occidentalis Hook.) now dominates over 3.6 million ha of rangeland in the Intermountain Western US. Critical ecological relationships among snow distribution, water budgets, plant community transitions, and habitat requirements for wildlife, such as sage grouse, remain poorly und...

A distributed snow-evolution modeling system (SnowModel)

Treesearch

Glen E. Liston; Kelly Elder

2006-01-01

SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D...

Improving snow density estimation for mapping SWE with Lidar snow depth: assessment of uncertainty in modeled density and field sampling strategies in NASA SnowEx

NASA Astrophysics Data System (ADS)

Raleigh, M. S.; Smyth, E.; Small, E. E.

2017-12-01

The spatial distribution of snow water equivalent (SWE) is not sufficiently monitored with either remotely sensed or ground-based observations for water resources management. Recent applications of airborne Lidar have yielded basin-wide mapping of SWE when combined with a snow density model. However, in the absence of snow density observations, the uncertainty in these SWE maps is dominated by uncertainty in modeled snow density rather than in Lidar measurement of snow depth. Available observations tend to have a bias in physiographic regime (e.g., flat open areas) and are often insufficient in number to support testing of models across a range of conditions. Thus, there is a need for targeted sampling strategies and controlled model experiments to understand where and why different snow density models diverge. This will enable identification of robust model structures that represent dominant processes controlling snow densification, in support of basin-scale estimation of SWE with remotely-sensed snow depth datasets. The NASA SnowEx mission is a unique opportunity to evaluate sampling strategies of snow density and to quantify and reduce uncertainty in modeled snow density. In this presentation, we present initial field data analyses and modeling results over the Colorado SnowEx domain in the 2016-2017 winter campaign. We detail a framework for spatially mapping the uncertainty in snowpack density, as represented across multiple models. Leveraging the modular SUMMA model, we construct a series of physically-based models to assess systematically the importance of specific process representations to snow density estimates. We will show how models and snow pit observations characterize snow density variations with forest cover in the SnowEx domains. Finally, we will use the spatial maps of density uncertainty to evaluate the selected locations of snow pits, thereby assessing the adequacy of the sampling strategy for targeting uncertainty in modeled snow density.

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.

MODIS Snow and Ice Production

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

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).

Modeling the influence of snow cover temperature and water content on wet-snow avalanche runout

NASA Astrophysics Data System (ADS)

Valero, Cesar Vera; Wever, Nander; Christen, Marc; Bartelt, Perry

2018-03-01

Snow avalanche motion is strongly dependent on the temperature and water content of the snow cover. In this paper we use a snow cover model, driven by measured meteorological data, to set the initial and boundary conditions for wet-snow avalanche calculations. The snow cover model provides estimates of snow height, density, temperature and liquid water content. This information is used to prescribe fracture heights and erosion heights for an avalanche dynamics model. We compare simulated runout distances with observed avalanche deposition fields using a contingency table analysis. Our analysis of the simulations reveals a large variability in predicted runout for tracks with flat terraces and gradual slope transitions to the runout zone. Reliable estimates of avalanche mass (height and density) in the release and erosion zones are identified to be more important than an exact specification of temperature and water content. For wet-snow avalanches, this implies that the layers where meltwater accumulates in the release zone must be identified accurately as this defines the height of the fracture slab and therefore the release mass. Advanced thermomechanical models appear to be better suited to simulate wet-snow avalanche inundation areas than existing guideline procedures if and only if accurate snow cover information is available.

Simulation of water available for runoff in clearcut forest openings during rain-on-snow events in the western Cascade Range of Oregon and Washington

USGS Publications Warehouse

van Heeswijk, Marijke; Kimball, J.S.; Marks, Danny

1996-01-01

Rain-on-snow events are common on mountain slopes within the transient-snow zone of the Pacific Northwest. These events make more water available for runoff than does precipitation alone by melting the snowpack and by adding a small amount of condensate to the snowpack. In forest openings (such as those resulting from clearcut logging), the amount of snow that accumulates and the turbulent- energy input to the snowpack are greater than below forest stands. Both factors are believed to contribute to a greater amount of water available for runoff during rain-on-snow events in forest openings than forest stands. Because increased water available for runoff may lead to increased downstream flooding and erosion, knowledge of the amount of snowmelt that can occur during rain on snow and the processes that control snowmelt in forest openings is useful when making land-use decisions. Snow accumulation and melt were simulated for clearcut conditions only, using an enery- balance approach that accounts for the most important energy and mass exchanges between a snowpack and its environment. Meteorological measurements provided the input for the simulations. Snow accumulation and melt were not simulated in forest stands because interception of precipitation processes are too complex to simulate with a numerical model without making simplifying assumptions. Such a model, however, would need to be extensively tested against representative observations, which were not available for this study. Snowmelt simulated during three rain-on-snow events (measured in a previous study in a clearcut in the transient-snow zone of the H.J. Andrews Experimental Forest in Oregon) demonstrated that melt generation is most sensitive to turbulent- energy exchanges between the air and the snowpack surface. As a result, the most important climate variable that controls snowmelt is wind speed. Air temperature, however, is a significant variable also. The wind speeds were light, with a maximum of 3

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

PubMed

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

2015-01-01

Cryophilic algae thrive in liquid water within snow and ice in alpine and polar regions worldwide. Blooms of these algae lower albedo (reflection of sunlight), thereby altering melting patterns (Kohshima, Seko & Yoshimura, 1993; Lutz et al., 2014; Thomas & Duval, 1995). Here metagenomic DNA analysis and satellite imaging were used to investigate red snow in Franz Josef Land in the Russian Arctic. Franz Josef Land red snow metagenomes confirmed that the communities are composed of the autotroph Chlamydomonas nivalis that is supporting a complex viral and heterotrophic bacterial community. Comparisons with white snow communities from other sites suggest that white snow and ice are initially colonized by fungal-dominated communities and then succeeded by the more complex C. nivalis-heterotroph red snow. Satellite image analysis showed that red snow covers up to 80% of the surface of snow and ice fields in Franz Josef Land and globally. Together these results show that C. nivalis supports a local food web that is on the rise as temperatures warm, with potential widespread impacts on alpine and polar environments worldwide.

Everywhere and nowhere: snow and its linkages

NASA Astrophysics Data System (ADS)

Hiemstra, C. A.

2017-12-01

Interest has grown in quantifying higher latitude precipitation change and snow-related ecosystem and economic impacts. There is a high demand for creating and using snow-related datasets, yet available datasets contain limitations, aren't scale appropriate, or lack thorough validation. Much of the uncertainty in snow estimates relates to ongoing snow measurement problems that are chronic and pervasive in windy, Arctic environments. This, coupled with diminishing support for long-term snow field observations, creates formidable hydrologic gaps in snow dominated landscapes. Snow touches most aspects of high latitude landscapes and spans albedo, ecosystems, soils, permafrost, and sea ice. In turn, snow can be impacted by disturbances, landscape change, ecosystem, structure, and later arrival of sea or lake ice. Snow, and its changes touch infrastructure, housing, and transportation. Advances in snow measurements, modeling, and data assimilation are under way, but more attention and a concerted effort is needed in a time of dwindling resources to make required advances during a time of rapid change.

Neighborhood impact on healthy food availability and pricing in food stores.

PubMed

Krukowski, Rebecca A; West, Delia Smith; Harvey-Berino, Jean; Elaine Prewitt, T

2010-06-01

Availability and price of healthy foods in food stores has the potential to influence purchasing patterns, dietary intake, and weight status of individuals. This study examined whether demographic factors of the store neighborhood or store size have an impact on the availability and price of healthy foods in sample of grocery stores and supermarkets. The Nutrition Environment Measures Study-Store (NEMS-S) instrument, a standardized observational survey, was utilized to evaluate food stores (N = 42) in a multi-site (Vermont and Arkansas) study in 2008. Census data associated with store census tract (median household income and proportion African-American) were used to characterize store neighborhood and number of cash registers was used to quantify store size. Median household income was significantly associated with the NEMS healthy food availability score (r = 0.36, P < 0.05); neither racial composition (r = -0.23, P = 0.14) nor store size (r = 0.27, P = 0.09) were significantly related to the Availability score. Larger store size (r = 0.40, P < 0.01) was significantly associated with the NEMS-S Price scores, indicating more favorable prices for healthier items; neither racial composition nor median household income were significantly related to the Price score (P's > 0.05). Even among supermarkets, healthier foods are less available in certain neighborhoods, although, when available, the quality of healthier options did not differ, suggesting that targeting availability may offer promise for policy initiatives. Furthermore, increasing access to larger stores that can offer lower prices for healthier foods may provide another avenue for enhancing food environments to lower disease risk.

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.

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.

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

Transport of intercepted snow from trees during snow storms

Treesearch

David H. Miller

1966-01-01

Five principal processes by which intercepted snow in trees is removed during snow storms are described and evaluated as far as data permit: vapor flux from melt water, vapor flux from bodies of snow, stem flow and dripping of melt water, sliding of bodies of intercepted snow from branches, and wind erosion and transport of intercepted snow. Further research is...

Snow depth evolution on sea ice from Snow Buoy measurement

NASA Astrophysics Data System (ADS)

Nicolaus, M.; Arndt, S.; Hendricks, S.; Hoppmann, M.; Katlein, C.; König-Langlo, G.; Nicolaus, A.; Rossmann, H. L.; Schiller, M.; Schwegmann, S.; Langevin, D.

2016-12-01

Snow cover is an Essential Climate Variable. On sea ice, snow dominates the energy and momentum exchanges across the atmosphere-ice-ocean interfaces, and actively contributes to sea ice mass balance. Yet, snow depth on sea ice is one of the least known and most difficult to observe parameters of the Arctic and Antarctic; mainly due to its exceptionally high spatial and temporal variability. In this study; we present a unique time series dataset of snow depth and air temperature evolution on Arctic and Antarctic sea ice recorded by autonomous instruments. Snow Buoys record snow depth with four independent ultrasonic sensors, increasing the reliability of the measurements and allowing for additional analyses. Auxiliary measurements include surface and air temperature, barometric pressure and GPS position. 39 deployments of such Snow Buoys were achieved over the last three years either on drifting pack ice, on landfast sea ice or on an ice shelf. Here we highlight results from two pairs of Snow Buoys installed on drifting pack ice in the Weddell Sea. The data reveals large regional differences in the annual cycle of snow depth. Almost no reduction in snow depth (snow melt) was observed in the inner and southern part of the Weddell Sea, allowing a net snow accumulation of 0.2 to 0.9 m per year. In contrast, summer snow melt close to the ice edge resulted in a decrease of about 0.5 m during the summer 2015/16. Another array of eight Snow Buoys was installed on central Arctic sea ice in September 2015. Their air temperature record revealed exceptionally high air temperatures in the subsequent winter, even exceeding the melting point but with almost no impact on snow depth at that time. Future applications of Snow Buoys on Arctic and Antarctic sea ice will allow additional inter-annual studies of snow depth and snow processes, e.g. to support the development of snow depth data products from airborne and satellite data or though assimilation in numerical models.

A novel linear physical model for remote sensing of snow wetness and snow density using the visible and infrared bands

NASA Astrophysics Data System (ADS)

Varade, D. M.; Dikshit, O.

2017-12-01

Modeling and forecasting of snowmelt runoff are significant for understanding the hydrological processes in the cryosphere which requires timely information regarding snow physical properties such as liquid water content and density of snow in the topmost layer of the snowpack. Both the seasonal runoffs and avalanche forecasting are vastly dependent on the inherent physical characteristics of the snowpack which are conventionally measured by field surveys in difficult terrains at larger impending costs and manpower. With advances in remote sensing technology and the increase in the availability of satellite data, the frequency and extent of these surveys could see a declining trend in future. In this study, we present a novel approach for estimating snow wetness and snow density using visible and infrared bands that are available with most multi-spectral sensors. We define a trapezoidal feature space based on the spectral reflectance in the near infrared band and the Normalized Differenced Snow Index (NDSI), referred to as NIR-NDSI space, where dry snow and wet snow are observed in the left diagonal upper and lower right corners, respectively. The corresponding pixels are extracted by approximating the dry and wet edges which are used to develop a linear physical model to estimate snow wetness. Snow density is then estimated using the modeled snow wetness. Although the proposed approach has used Sentinel-2 data, it can be extended to incorporate data from other multi-spectral sensors. The estimated values for snow wetness and snow density show a high correlation with respect to in-situ measurements. The proposed model opens a new avenue for remote sensing of snow physical properties using multi-spectral data, which were limited in the literature.

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.

Changes in agriculture and abundance of snow geese affect carrying capacity of sandhill cranes in Nebraska

USGS Publications Warehouse

Pearse, A.T.; Krapu, G.L.; Brandt, D.A.; Kinzel, P.J.

2010-01-01

The central Platte River valley (CPRV) in Nebraska, USA, is a key spring-staging area for approximately 80 of the midcontinent population of sandhill cranes (Grus canadensis; hereafter cranes). Evidence that staging cranes acquired less lipid reserves during the 1990s compared to the late 1970s and increases in use of the CPRV by snow geese (Chen caerulescens) prompted us to investigate availability of waste corn and quantify spatial and temporal patterns of crane and waterfowl use of the region. We developed a predictive model to assess impacts of changes in availability of corn and snow goose abundance under past, present, and potential future conditions. Over a hypothetical 60-day staging period, predicted energy demand of cranes and waterfowl increased 87 between the late 1970s and 19982007, primarily because peak abundances of snow geese increased by 650,000 and cranes by 110,000. Compared to spring 1979, corn available when cranes arrived was 20 less in 1998 and 68 less in 1999; consequently, the area of cornfields required to meet crane needs increased from 14,464 ha in 1979 to 32,751 ha in 1998 and 90,559 ha in 1999. Using a pooled estimate of 88 kg/ha from springs 19981999 and 20052007, the area of cornfields needed to supply food requirements of cranes and waterfowl increased to 65,587 ha and was greatest in the eastern region of the CPRV, where an estimated 54 of cranes, 47 of Canada geese (Branta canadensis), 45 of greater white-fronted geese (Anser albifrons), and 46 of snow geese occurred during ground surveys. We estimated that a future reduction of 25 in available corn or cornfields would increase daily foraging flight distances of cranes by 2738. Crane use and ability of cranes to store lipid reserves in the CPRV could be reduced substantially if flight distance required to locate adequate corn exceeded a physiological maximum distance cranes could fly in search of food. Options to increase carrying capacity for cranes include increasing

A Comprehensive Snow Density Model for Integrating Lidar-Derived Snow Depth Data into Spatial Snow Modeling

NASA Astrophysics Data System (ADS)

Marks, D. G.; Kormos, P.; Johnson, M.; Bormann, K. J.; Hedrick, A. R.; Havens, S.; Robertson, M.; Painter, T. H.

2017-12-01

Lidar-derived snow depths when combined with modeled or estimated snow density can provide reliable estimates of the distribution of SWE over large mountain areas. Application of this approach is transforming western snow hydrology. We present a comprehensive approach toward modeling bulk snow density that is reliable over a vast range of weather and snow conditions. The method is applied and evaluated over mountainous regions of California, Idaho, Oregon and Colorado in the western US. Simulated and measured snow density are compared at fourteen validation sites across the western US where measurements of snow mass (SWE) and depth are co-located. Fitting statistics for ten sites from three mountain catchments (two in Idaho, one in California) show an average Nash-Sutcliff model efficiency coefficient of 0.83, and mean bias of 4 kg m-3. Results illustrate issues associated with monitoring snow depth and SWE and show the effectiveness of the model, with a small mean bias across a range of snow and climate conditions in the west.

Snow Ecology

NASA Astrophysics Data System (ADS)

Jones, H. G.; Pomeroy, J. W.; Walker, D. A.; Hoham, R. W.

2001-01-01

In this volume, a multidisciplinary group of acknowledged experts fully intergrate the physical, chemical, and biological sciences to provide a complete understanding of the interrelationships between snow structure and life. This volume opens a new perspecitve on snow cover as a habitat for organisms under extreme environmental conditions and as a key factor in the ecology of much of the Earth's surface. The contributors describe the fundamental physical and small-scale chemical processes that characterize the evolution of snow and their influence on the life cycles of true snow organisms and the biota of cold regions with extended snow cover. The book further expands on the role of snow in the biosphere by the study of the relationship between snow and climate and the paleo-ecological evidence for the influence of past snow regimes on plant communities. Snow Ecology will form a main textbook on advanced courses in biology, ecology, geography, environmental science, and earth science where an important component is devoted to the study of the cryosphere. It will also be useful as a reference text for graduate students, researchers, and professionals at academic institutions and in government and nongovernmental agencies with environmental concerns.

Invertebrate response to snow goose herbivory on moist-soil vegetation

USGS Publications Warehouse

Sherfy, M.H.; Kirkpatrick, R.L.

2003-01-01

Foraging activity by snow geese (Chen caerulescens) often creates large areas devoid of vegetation ("eat-outs") in moist-soil impoundments and coastal wetlands. Open-water habitats that result from eat-outs may be valuable foraging areas for other wetland-dependent birds (i.e., waterfowl and shorebirds). However, few studies have examined the effects of goose-induced habitat changes on invertebrates, an important food source for both waterfowl and shorebirds. We quantified changes in abundance and composition of benthic invertebrates in response to snow goose herbivory in moist-soil impoundments at Prime Hook National Wildlife Refuge, Delaware, USA. We found invertebrate taxon richness and diversity and abundance of Chironomidae, Coleoptera, and Total Invertebrates to be higher in goose-excluded sites than in adjacent eat-outs. These effects were most pronounced during January, February, and early April. We also measured invertebrate abundance in shorebird exclosures in eat-outs but found few detectable effects of shorebird predation on invertebrates. Our study demonstrated that abundant snow geese may negatively influence availability of invertebrates for other nonbreeding waterbirds, suggesting that management actions to reduce local goose populations or deter feeding in impoundments may be warranted.

Food availability/convenience and obesity.

PubMed

Gordon-Larsen, Penny

2014-11-01

Neighborhood environments have received considerable attention in recent local, state, and national obesity prevention initiatives, with a particular focus on food deserts, or areas with poor access to healthy foods. Yet, there are inconsistencies in the evidence base, suggesting a nuanced association between neighborhood environment, food availability, diet behaviors, and obesity. There is heterogeneity in associations between environmental exposures and health outcomes across race/ethnicity, gender, region, and urbanicity, which results in complexity in the interpretation of findings. There are several limitations in the literature, including a predominance of cross-sectional studies, reliance on commercial business listings, lack of attention to the process by which diet resources are established and expanded within neighborhoods and the potential for individuals to selectively migrate to locate near such facilities, a predominant focus on residential neighborhoods, and lack of information about the decision-making process underlying purchasing patterns. More research is needed to address the complexity of individual-level residential decision making as well as the purposeful placement of food environment resources across social and geographic space using longitudinal data and complex statistical approaches. In addition, improvements in data quality and depth related to food access and availability are needed, including behavioral data on purchase patterns and interactions with the food environment, and greater attention to heterogeneity across subpopulations. As policy changes to the food environment move forward, it is critical that there is rigorous and scientific evaluation of environmental changes and their impact on individual-level diet choices and behaviors, and their further influence on body weight. © 2014 American Society for Nutrition.

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

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.

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).

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.

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.

Snow water equivalent mapping in Norway

NASA Astrophysics Data System (ADS)

Tveito, O. E.; Udnæs, H.-C.; Engeset, R.; Førland, E. J.; Isaksen, K.; Mengistu, Z.

2003-04-01

In high latitude area snow covers the ground large parts of the year. Information about the water volume as snow is of major importance in many respects. Flood forecasters at NVE need it in order to assess possible flood risks. Hydropower producers need it to plan the most efficient production of the water in their reservoirs, traders to estimate the potential energy available for the market. Meteorologists on their side use the information as boundary conditions in weather forecasting models. The Norwegian meteorological institute has provided snow accumulation maps for Norway for more than 50 years. These maps are now produced twice a month in the winter season. They show the accumulated precipitation in the winter season from the day the permanent snow cover is established. They do however not take melting into account, and do therefore not give a good description of the actual snow amounts during and after periods with snowmelt. Due to an increased need for a direct measure of water volumes as snow cover, met.no and NVE initialized a joint project in order to establish maps of the actual snow cover expressed in water equivalents. The project utilizes recent developments in the use of GIS in spatial modeling. Daily precipitation and temperature are distributed in space by using objective spatial interpolation methods. The interpolation considers topographical and other geographical parameters as well as weather type information. A degree-day model is used at each modeling point to calculate snow-accumulation and snowmelt. The maps represent a spatial scale of 1x1 km2. The modeled snow reservoir is validated by snow pillow values as well traditional snow depth observations. Preliminary results show that the new snow modeling approach reproduces the snow water equivalent well. The spatial approach also opens for a wide use in the terms of areal analysis.

NOHRSC Interactive Snow Information

Science.gov Websites

-present) RFC Basin Other (non-RFC) Basin State NSA region (Discussion) NSA subregion (Disc.) Basins by None Snow Water Equivalent Snow Depth Shallow SWE Shallow Snow Depth Snow Temperature Snow Density Snow Melt Snow Precipitation Non-Snow Precipitation Air Temperature Solar Radiation Relative Humidity

Calculation of new snow densities from sub-daily automated snow measurements

NASA Astrophysics Data System (ADS)

Helfricht, Kay; Hartl, Lea; Koch, Roland; Marty, Christoph; Lehning, Michael; Olefs, Marc

2017-04-01

In mountain regions there is an increasing demand for high-quality analysis, nowcasting and short-range forecasts of the spatial distribution of snowfall. Operational services, such as for avalanche warning, road maintenance and hydrology, as well as hydropower companies and ski resorts need reliable information on the depth of new snow (HN) and the corresponding water equivalent (HNW). However, the ratio of HNW to HN can vary from 1:3 to 1:30 because of the high variability of new snow density with respect to meteorological conditions. In the past, attempts were made to calculate new snow densities from meteorological parameters mainly using daily values of temperature and wind. Further complex statistical relationships have been used to calculate new snow densities on hourly to sub-hourly time intervals to drive multi-layer snow cover models. However, only a few long-term in-situ measurements of new snow density exist for sub-daily time intervals. Settling processes within the new snow due to loading and metamorphism need to be considered when computing new snow density. As the effect of these processes is more pronounced for long time intervals, a high temporal resolution of measurements is desirable. Within the pluSnow project data of several automatic weather stations with simultaneous measurements of precipitation (pluviometers), snow water equivalent (SWE) using snow pillows and snow depth (HS) measurements using ultrasonic rangers were analysed. New snow densities were calculated for a set of data filtered on the basis of meteorological thresholds. The calculated new snow densities were compared to results from existing new snow density parameterizations. To account for effects of settling of the snow cover, a case study based on a multi-year data set using the snow cover model SNOWPACK at Weissfluhjoch was performed. Measured median values of hourly new snow densities at the different stations range from 54 to 83 kgm-3. This is considerably lower than a 1

Snow Water Equivalent Pressure Sensor Performance in a Deep Snow Cover

NASA Astrophysics Data System (ADS)

Johnson, J. B.; Gelvin, A. B.; Schaefer, G. L.

2006-12-01

Accurate measurements of snow water equivalent are important for a variety of water resource management operations. In the western US, real-time SWE measurements are made using snow pillows that can experience errors from snow-bridging, poor installation configuration, and enhanced solar radiation absorption. Snow pillow installations that place the pillow abnormally above or below the surrounding terrain can affect snow catchment. Snow pillows made from dark materials can preferentially absorb solar radiation penetrating the snow causing accelerated melt. To reduce these problems, the NRCS and CRREL developed an electronic SWE sensor to replace the snow pillow. During the winter of 2005-2006 the NRCS/CRREL electronic sensor was deployed at Hogg Pass, Oregon, with a total SWE accumulation of about 1000 mm. The NRCS/CRREL sensor consists of a center panel surrounded by eight outer panels whose purpose is to buffer snow bridging loads. By separately monitoring load cell outputs from the sensor, snow-bridging events are directly measured. A snow-bridging event associated with a 180 mm SWE accumulation in a 24-hour period exhibited a SWE over-measurement of 60% at the sensor edge while the center panel showed less than a 10% effect. Individual load cell outputs were used to determine the most representative SWE value, which was within 5% of the adjacent snow pillow value. During the spring melt the NRCS/CRREL sensor melt recession lagged that of the snow pillow by about a week. Physical examination of the Hogg Pass site indicated that the CRREL sensor results were consistent with snow-on-the-ground observations. The snow pillow experienced accelerated melt because it was installed on a mound above the surrounding terrain and absorbed solar radiation through the snow. SWE pressure sensor accuracy is significantly improved by using an active center panel surrounded by buffer panels, monitoring several individual load cell to detect and correct snow-bridging errors, and

A Look at Seasonal Snow Cover and Snow Mass in the Southern Hemisphere from 1979-2006 Using SMMR and SSM/I Passive Microwave Data

NASA Technical Reports Server (NTRS)

Foster, James

2009-01-01

Seasonal snow cover in extra-tropical areas of South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and from the Special Sensor Microwave Imagers (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow mass were estimated for the months of May-September. Most of the seasonal snow in South America occurs in the Patagonia region of Argentina. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 sq km. The seasonal (May-September) 2 average snow cover extent was greatest in 1984 (464,250 sq km) and least in 1990 (69,875 sq km). In terms of snow mass, 1984 was also the biggest year (1.19 x 10(exp 13) kg) and 1990 was the smallest year (0.12 X 10(exp 13) kg). A strong relationship exists between the snow cover area and snow mass, correlated at 0.95, though no significant trend was found over the 28 year record for either snow cover extent or snow mass. For this long term climatology, snow mass and snow cover extent are shown to vary considerably from month to month and season to season. This analysis presents a consistent approach to mapping and measuring snow in South America utilizing an appropriate and readily available long term snow satellite dataset. This is the optimal dataset available, thus far, for deriving seasonal snow cover and snow mass in this region. Nonetheless, shallow snow, wet snow, snow beneath forests, as well as snow along coastal areas all may confound interpretation using passive microwave approaches. More work needs to be done to reduce the uncertainties in the data and hence, increase the confidence of the interpretation

Monitoring Food Security Indicators from Remote Sensing and Predicting Cereal Production in Afghanistan

NASA Astrophysics Data System (ADS)

Pervez, M. S.; Budde, M. E.; Rowland, J.

2015-12-01

We extract percent of basin snow covered areas above 2500m elevation from Moderate Resolution Imaging Spectroradiometer (MODIS) 500-meter 8-day snow cover composites to monitor accumulation and depletion of snow in the basin. While the accumulation and depletion of snow cover extent provides an indication of the temporal progression of the snow pack, it does not provide insight into available water for irrigation. Therefore, we use snow model results from the National Operational Hydrologic Remote Sensing Center to quantify snow water equivalent and volume of water available within the snowpack for irrigation. In an effort to understand how water availability, along with its inter-annual variability, relates to the food security of the country, we develop a simple, effective, and easy-to-implement model to identify irrigated areas across the country on both annual and mid-season basis. The model is based on applying thresholds to peak growing season vegetation indices—derived from 250-meter MODIS images—in a decision-tree classifier to separate irrigated crops from non-irrigated vegetation. The spatial distribution and areal estimates of irrigated areas from these maps compare well with irrigated areas classified from multiple snap shots of the landscape from Landsat 5 optical and thermal images over selected locations. We observed that the extents of irrigated areas varied depending on the availability of snowmelt and can be between 1.35 million hectares in a year with significant water deficit and 2.4 million hectares in a year with significant water surplus. The changes in the amount of available water generally can contribute up to a 30% change in irrigated areas. We also observed that the strong correlation between inter-annual variability of irrigated areas and the variability in the country's cereal production could be utilized to predict an annual estimate of cereal production, providing early indication of food security scenarios for the country.

Estimating snow load in California for three recurrence intervals

Treesearch

David L. Azuma

1985-01-01

A key to designing facilities in snowbound areas is knowing what the expected snow load levels are for given recurrence intervals. In California, information about snow load is available only for the Lake Tahoe Basin. About 280 snow courses in the State were analyzed, and snow load estimated and related to elevation on a river basin and statewide level. The tabulated...

Combining snow depth and innovative skier flow measurements in order to improve snow grooming techniques

NASA Astrophysics Data System (ADS)

Carmagnola, Carlo Maria; Albrecht, Stéphane; Hargoaa, Olivier

2017-04-01

In the last decades, ski resort managers have massively improved their snow management practices, in order to adapt their strategies to the inter-annual variability in snow conditions and to the effects of climate change. New real-time informations, such as snow depth measurements carried out on the ski slopes by grooming machines during their daily operations, have become available, allowing high saving, efficiency and optimization gains (reducing for instance the groomer fuel consumption and operation time and the need for machine-made snow production). In order to take a step forward in improving the grooming techniques, it would be necessary to keep into account also the snow erosion by skiers, which depends mostly on the snow surface properties and on the skier attendance. Today, however, most ski resort managers have only a vague idea of the evolution of the skier flows on each slope during the winter season. In this context, we have developed a new sensor (named Skiflux) able to measure the skier attendance using an infrared beam crossing the slopes. Ten Skiflux sensors have been deployed during the 2016/17 winter season at Val Thorens ski area (French Alps), covering a whole sector of the resort. A dedicated software showing the number of skier passages in real time as been developed as well. Combining this new Skiflux dataset with the snow depth measurements from grooming machines (Snowsat System) and the snow and meteorological conditions measured in-situ (Liberty System from Technoalpin), we were able to create a "real-time skiability index" accounting for the quality of the surface snow and its evolution during the day. Moreover, this new framework allowed us to improve the preparation of ski slopes, suggesting new strategies for adapting the grooming working schedule to the snow quality and the skier attendance. In the near future, this work will benefit from the advances made within the H2020 PROSNOW project ("Provision of a prediction system allowing

Food and Beverage Availability in Small Food Stores Located in Healthy Food Financing Initiative Eligible Communities.

PubMed

Singleton, Chelsea R; Li, Yu; Duran, Ana Clara; Zenk, Shannon N; Odoms-Young, Angela; Powell, Lisa M

2017-10-18

Food deserts are a major public health concern. This study aimed to assess food and beverage availability in four underserved communities eligible to receive funding from the Healthy Food Financing Initiative (HFFI). Data analyzed are part of a quasi-experimental study evaluating the impact of the HFFI on the retail food environment in selected Illinois communities. In 2015, 127 small grocery and limited service stores located in the four selected communities were audited. All communities had a large percentage of low-income and African-American residents. Differences in food and beverage item availability (e.g., produce, milk, bread, snack foods) were examined by store type and community location. Food stores had, on average, 1.8 fresh fruit and 2.9 fresh vegetable options. About 12% of stores sold low-fat milk while 86% sold whole milk. Only 12% of stores offered 100% whole wheat bread compared to 84% of stores offering white bread. Almost all (97%) stores offered soda and/or fruit juice. In summary, we found limited availability of healthier food and beverage items in the communities identified for HFFI support. Follow up findings will address how the introduction of new HFFI-supported supermarkets will affect food and beverage availability in these communities over time.

Food and Beverage Availability in Small Food Stores Located in Healthy Food Financing Initiative Eligible Communities

PubMed Central

Li, Yu; Duran, Ana Clara; Zenk, Shannon N.; Odoms-Young, Angela; Powell, Lisa M.

2017-01-01

Food deserts are a major public health concern. This study aimed to assess food and beverage availability in four underserved communities eligible to receive funding from the Healthy Food Financing Initiative (HFFI). Data analyzed are part of a quasi-experimental study evaluating the impact of the HFFI on the retail food environment in selected Illinois communities. In 2015, 127 small grocery and limited service stores located in the four selected communities were audited. All communities had a large percentage of low-income and African-American residents. Differences in food and beverage item availability (e.g., produce, milk, bread, snack foods) were examined by store type and community location. Food stores had, on average, 1.8 fresh fruit and 2.9 fresh vegetable options. About 12% of stores sold low-fat milk while 86% sold whole milk. Only 12% of stores offered 100% whole wheat bread compared to 84% of stores offering white bread. Almost all (97%) stores offered soda and/or fruit juice. In summary, we found limited availability of healthier food and beverage items in the communities identified for HFFI support. Follow up findings will address how the introduction of new HFFI-supported supermarkets will affect food and beverage availability in these communities over time. PMID:29057794

Healthy food availability in small urban food stores: a comparison of four US cities.

PubMed

Laska, Melissa Nelson; Borradaile, Kelley E; Tester, June; Foster, Gary D; Gittelsohn, Joel

2010-07-01

Given that small food stores may be important retail food sources in low-income urban communities, our objective was to examine cross-city comparative data documenting healthy food availability within such facilities, particularly those located in low-income areas and nearby schools. Food stores in Baltimore, Maryland; Minneapolis/St. Paul, Minnesota; Oakland, California; and Philadelphia, Pennsylvania were selected for assessment based on proximity to low-income schools. Stores were defined as: (i) single-aisle (n 45); (ii) small (2-5 aisles; n 52); and (iii) large (> or = 6 aisles; n 8). Staff conducted in-store audits to assess the presence/absence of twenty-eight healthy items, organized within five categories: (i) fresh fruits/vegetables, (ii) processed fruits/vegetables, (iii) healthy beverages/low-fat dairy, (iv) healthy snacks and (v) other healthy staple foods. The availability of healthy food items was low, particularly in single-aisle and small stores, and there was significant cross-site variability in the availability of healthy snacks (P < 0.0001) and other healthy staple foods (P < 0.0001). No cross-site differences existed for fruits/vegetables or healthy beverages/low-fat dairy availability. Healthy food availability scores increased significantly with store size for nearly all food/beverage categories (P < 0.01). Overall, healthy food availability in these venues was limited. Region-specific factors may be important to consider in understanding factors influencing healthy food availability in small urban markets. Data suggest that efforts to promote healthy diets in low-income communities may be compromised by a lack of available healthy foods. Interventions targeting small stores need to be developed and tailored for use in urban areas across the USA.

Prepared Food Availability in U.S. Food Stores: A National Study.

PubMed

Zenk, Shannon N; Powell, Lisa M; Isgor, Zeynep; Rimkus, Leah; Barker, Dianne C; Chaloupka, Frank J

2015-10-01

Prepared, ready-to-eat foods comprise a significant part of Americans' diets and are increasingly obtained from food stores. Yet, little is known about the availability and healthfulness of prepared, ready-to-eat food offerings at stores. This study examines associations among community characteristics (racial/ethnic composition, poverty level, urbanicity) and availability of both healthier and less-healthy prepared foods in U.S. supermarkets, grocery stores, and convenience stores. Observational data were collected from 4,361 stores in 317 communities spanning 42 states in 2011 and 2012. Prepared food availability was assessed via one healthier food (salads or salad bar), three less-healthy items (pizza, hot dog/hamburger, taco/burrito/taquito), and one cold sandwich item. In 2014, multivariable generalized linear models were used to test associations with community characteristics. Overall, 63.6% of stores sold prepared foods, with 20.0% offering prepared salads and 36.4% offering at least one less-healthy item. Rural stores were 26% less likely to carry prepared salads (prevalence ratio [PR]=0.74, 95% CI=0.62, 0.88) and 14% more likely to carry at least one less-healthy prepared food item (PR=1.14, 95% CI=1.00, 1.30). Convenience stores in high-poverty communities were less likely to carry prepared salads than those in low-poverty communities (PR=0.64, 95% CI=0.47, 0.87). Among supermarkets, prepared salads were more likely to be carried in majority-white, low-poverty communities than in non-white, high-poverty communities. Increasing the healthfulness of prepared foods within stores may offer an important opportunity to improve the food environment. Copyright © 2015 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

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+).

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Dining Dovekies Demand, "When, Where and What's for Dinner?" The Impact of Seasonal Changes in Snow Melt and the Development of the Arctic Marine Food Web on Seabirds.

NASA Astrophysics Data System (ADS)

Karnovsky, N. J.; Harding, A.; Welcker, J.; Brown, Z. W.; Kitaysky, A.; Kwasniewski, S.; Walkusz, W.; Gremillet, D.

2011-12-01

The Atlantic sector of the Arctic is undergoing widespread climate change with increases in air and sea temperatures which impact the timing of ice retreat, snow melt and the development of the marine food web. Dovekies (Alle alle) are small seabirds that migrate to the Atlantic Sector of the Arctic to feed in ice free waters that have abundant lipid-rich zooplankton. In the Greenland Sea, the dovekies are largely dependent on the advection of Calanus copepods into the area. We hypothesized that dovekies breeding adjacent to water masses which bring smaller, less energy-rich prey into the region (Calanus finmarchicus), work harder to find food and have higher stress levels. We tested this hypothesis by attaching time-depth recorders to provisioning dovekies at three colonies adjacent to different water masses (the West Spistbergen Current, the East Greenland Current, and the Sorkapp Current). We determined the length of time dovekies at different colonies spent at-sea collecting food for themselves and their chicks. We measured circulating corticosteroid hormone levels in their blood to assess stress levels. We collected chick meals to determine the energetic content of prey fed chicks at the different colonies. We found that dovekies are sensitive to the quality of prey available to them. Dovekies exposed to less profitable prey made longer foraging trips and worked harder while at-sea to collect prey for themselves and their chicks. Furthermore, over the past 50 years, dovekies breeding along the western shores of Spitsbergen have initiated breeding earlier in spring as their nest sites have become snow-free at earlier dates. We evaluate the impact of earlier breeding and the timing of the development of the marine food web within different currents which advect and/or support Calanus copepods into the Greenland Sea. Future possible declines in dovekies may impact terrestrial food webs which are highly influenced by the annual input of nitrogen rich guano on the

Long-term analyses of snow dynamics within the french Alps on the 1900-2100 period. Analyses of historical snow water equivalent observations, modelisations and projections of a hundred of snow courses.

NASA Astrophysics Data System (ADS)

Mathevet, T.; Joel, G.; Gottardi, F.; Nemoz, B.

2017-12-01

The aim of this communication is to present analyses of climate variability and change on snow water equivalent (SWE) observations, reconstructions (1900-2016) and scenarii (2020-2100) of a hundred of snow courses dissiminated within the french Alps. This issue became particularly important since a decade, in regions where snow variability had a large impact on water resources availability, poor snow conditions in ski resorts and artificial snow production. As a water resources manager in french mountainuous regions, EDF (french hydropower company) has developed and managed a hydrometeorological network since 1950. A recent data rescue research allowed to digitize long term SWE manual measurments of a hundred of snow courses within the french Alps. EDF have been operating an automatic SWE sensors network, complementary to the snow course network. Based on numerous SWE observations time-series and snow accumulation and melt model (Garavaglia et al., 2017), continuous daily historical SWE time-series have been reconstructed within the 1950-2016 period. These reconstructions have been extented to 1900 using 20 CR reanalyses (ANATEM method, Kuentz et al., 2015) and up to 2100 using GIEC Climate Change scenarii. Considering various mountainous areas within the french Alps, this communication focuses on : (1) long term (1900-2016) analyses of variability and trend of total precipitation, air temperature, snow water equivalent, snow line altitude, snow season length , (2) long term variability of hydrological regime of snow dominated watersheds and (3) future trends (2020 -2100) using GIEC Climate Change scenarii. Comparing historical period (1950-1984) to recent period (1984-2016), quantitative results within a region in the north Alps (Maurienne) shows an increase of air temperature by 1.2 °C, an increase of snow line height by 200m, a reduction of SWE by 200 mm/year and a reduction of snow season length by 15 days. These analyses will be extended from north to south

Federal nutrition program changes and healthy food availability.

PubMed

Havens, Erin K; Martin, Katie S; Yan, Jun; Dauser-Forrest, Deborah; Ferris, Ann M

2012-10-01

Literature on food environments is expanding rapidly, yet a gap exists regarding the role of the U.S. Department of Agriculture's Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) on healthy food availability. In October 2009, the U.S. Department of Agriculture revised the WIC food package, requiring certified stores to stock fresh produce, whole grains, and lower-fat milk. The goal of this study is to compare availability of foods in stores that are versus those that are not WIC-certified before and after the policy change. Store inventories were collected in 45 corner stores in Hartford CT with four inventories each (180 total inventories) from January 2009 to January 2010. Data on availability and variety of fresh fruits, fresh vegetables, whole grains, and lower-fat milk were recorded. Analyses were completed in 2012 using Fisher's exact test, chi-square, and t-tests for descriptive analyses and multilevel models to measure food availability longitudinally (significance at p<0.05). Controlling for covariates, WIC-certified vendors carried more varieties of fresh fruit (p<0.01); a greater proportion of lower-fat milk (p<0.01); and had greater availability of whole grain bread (p<0.01) and brown rice (p<0.05) than vendors without WIC authorization after the policy change. Conversely, for all outcomes, stores without WIC authorization did not significantly increase healthy food availability. The 2009 WIC revisions increased availability of healthy foods among WIC-certified vendors compared to those without WIC authorization in Hartford CT. For many residents without a car, these changes can create a convenient shopping location for healthy foods when a larger supermarket is not nearby. Copyright © 2012 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

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.

From the clouds to the ground - snow precipitation patterns vs. snow accumulation patterns

NASA Astrophysics Data System (ADS)

Gerber, Franziska; Besic, Nikola; Mott, Rebecca; Gabella, Marco; Germann, Urs; Bühler, Yves; Marty, Mauro; Berne, Alexis; Lehning, Michael

2017-04-01

Knowledge about snow distribution and snow accumulation patterns is important and valuable for different applications such as the prediction of seasonal water resources or avalanche forecasting. Furthermore, accumulated snow on the ground is an important ground truth for validating meteorological and climatological model predictions of precipitation in high mountains and polar regions. Snow accumulation patterns are determined by many different processes from ice crystal nucleation in clouds to snow redistribution by wind and avalanches. In between, snow precipitation undergoes different dynamical and microphysical processes, such as ice crystal growth, aggregation and riming, which determine the growth of individual particles and thereby influence the intensity and structure of the snowfall event. In alpine terrain the interaction of different processes and the topography (e.g. lifting condensation and low level cloud formation, which may result in a seeder-feeder effect) may lead to orographic enhancement of precipitation. Furthermore, the redistribution of snow particles in the air by wind results in preferential deposition of precipitation. Even though orographic enhancement is addressed in numerous studies, the relative importance of micro-physical and dynamically induced mechanisms on local snowfall amounts and especially snow accumulation patterns is hardly known. To better understand the relative importance of different processes on snow precipitation and accumulation we analyze snowfall and snow accumulation between January and March 2016 in Davos (Switzerland). We compare MeteoSwiss operational weather radar measurements on Weissfluhgipfel to a spatially continuous snow accumulation map derived from airborne digital sensing (ADS) snow height for the area of Dischma valley in the vicinity of the weather radar. Additionally, we include snow height measurements from automatic snow stations close to the weather radar. Large-scale radar snow accumulation

Simulating Snow in Canadian Boreal Environments with CLASS for ESM-SnowMIP

NASA Astrophysics Data System (ADS)

Wang, L.; Bartlett, P. A.; Derksen, C.; Ireson, A. M.; Essery, R.

2017-12-01

The ability of land surface schemes to provide realistic simulations of snow cover is necessary for accurate representation of energy and water balances in climate models. Historically, this has been particularly challenging in boreal forests, where poor treatment of both snow masking by forests and vegetation-snow interaction has resulted in biases in simulated albedo and snowpack properties, with subsequent effects on both regional temperatures and the snow albedo feedback in coupled simulations. The SnowMIP (Snow Model Intercomparison Project) series of experiments or `MIPs' was initiated in order to provide assessments of the performance of various snow- and land-surface-models at selected locations, in order to understand the primary factors affecting model performance. Here we present preliminary results of simulations conducted for the third such MIP, ESM-SnowMIP (Earth System Model - Snow Model Intercomparison Project), using the Canadian Land Surface Scheme (CLASS) at boreal forest sites in central Saskatchewan. We assess the ability of our latest model version (CLASS 3.6.2) to simulate observed snowpack properties (snow water equivalent, density and depth) and above-canopy albedo over 13 winters. We also examine the sensitivity of these simulations to climate forcing at local and regional scales.

Blowing snow detection from ground-based ceilometers: application to East Antarctica

NASA Astrophysics Data System (ADS)

Gossart, Alexandra; Souverijns, Niels; Gorodetskaya, Irina V.; Lhermitte, Stef; Lenaerts, Jan T. M.; Schween, Jan H.; Mangold, Alexander; Laffineur, Quentin; van Lipzig, Nicole P. M.

2017-12-01

Blowing snow impacts Antarctic ice sheet surface mass balance by snow redistribution and sublimation. However, numerical models poorly represent blowing snow processes, while direct observations are limited in space and time. Satellite retrieval of blowing snow is hindered by clouds and only the strongest events are considered. Here, we develop a blowing snow detection (BSD) algorithm for ground-based remote-sensing ceilometers in polar regions and apply it to ceilometers at Neumayer III and Princess Elisabeth (PE) stations, East Antarctica. The algorithm is able to detect (heavy) blowing snow layers reaching 30 m height. Results show that 78 % of the detected events are in agreement with visual observations at Neumayer III station. The BSD algorithm detects heavy blowing snow 36 % of the time at Neumayer (2011-2015) and 13 % at PE station (2010-2016). Blowing snow occurrence peaks during the austral winter and shows around 5 % interannual variability. The BSD algorithm is capable of detecting blowing snow both lifted from the ground and occurring during precipitation, which is an added value since results indicate that 92 % of the blowing snow is during synoptic events, often combined with precipitation. Analysis of atmospheric meteorological variables shows that blowing snow occurrence strongly depends on fresh snow availability in addition to wind speed. This finding challenges the commonly used parametrizations, where the threshold for snow particles to be lifted is a function of wind speed only. Blowing snow occurs predominantly during storms and overcast conditions, shortly after precipitation events, and can reach up to 1300 m a. g. l. in the case of heavy mixed events (precipitation and blowing snow together). These results suggest that synoptic conditions play an important role in generating blowing snow events and that fresh snow availability should be considered in determining the blowing snow onset.

Improvement of a snow albedo parameterization in the Snow-Atmosphere-Soil Transfer model: evaluation of impacts of aerosol on seasonal snow cover

NASA Astrophysics Data System (ADS)

Zhong, Efang; Li, Qian; Sun, Shufen; Chen, Wen; Chen, Shangfeng; Nath, Debashis

2017-11-01

The presence of light-absorbing aerosols (LAA) in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take this into consideration. To better represent the snow process and to evaluate the impacts of LAA on snow, this study presents an improved snow albedo parameterization in the Snow-Atmosphere-Soil Transfer (SAST) model, which includes the impacts of LAA on snow. Specifically, the Snow, Ice and Aerosol Radiation (SNICAR) model is incorporated into the SAST model with an LAA mass stratigraphy scheme. The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot (SASP), Colorado, USA. Results show that the snow albedo and snow depth are better reproduced than those in the original SAST, particularly during the period of snow ablation. Furthermore, the impacts of LAA on snow are estimated in the coupled model through case comparisons of the snowpack, with or without LAA. The LAA particles directly absorb extra solar radiation, which accelerates the growth rate of the snow grain size. Meanwhile, these larger snow particles favor more radiative absorption. The average total radiative forcing of the LAA at the SASP is 47.5 W m-2. This extra radiative absorption enhances the snowmelt rate. As a result, the peak runoff time and "snow all gone" day have shifted 18 and 19.5 days earlier, respectively, which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.

Folate content and availability in Malaysian cooked foods.

PubMed

Chew, S C; Khor, G L; Loh, S P

2012-12-01

Data on folate availability of Malaysian cooked foods would be useful for estimation of dietary folate intake; however such information is scarce. A total of 53 samples of frequently consumed foods in Malaysia were selected from the Nutrient Composition of Malaysian Foods. Folate content was determined using HPLC method hyphenated with a stainless steel C18 column and ultraviolet detector (lambda = 280 nm). The index of folate availability was defined as the proportion of folate identified as monoglutamyl derivatives from the total folate content. Total folate content of different food samples varied from 30-95 microg/100g fresh weight. Among rice-based dishes, the highest and the lowest total folate was in coconut milk rice (nasi lemak) and ghee rice (nasi minyak), respectively. In noodle dishes, fried rice noodle (kuey teow goreng) and curry noodle (mee kari) had the highest folate contents. The highest index of folate availability was in a flat rice noodle dish (kuey teow bandung) (12.13%), while the lowest was in a festival cake (kuih bakul) (0.13%). Folate content was found to be negatively related to its availability. This study determined folate content and folate availability in commonly consumed cooked foods in Malaysia. The uptake of folate from foods with high folate content may not be necessarily high as folate absorption also depends on the capacity of intestinal deconjugation and the presence of high fibre in the foods.

A statistical estimation of Snow Water Equivalent coupling ground data and MODIS images

NASA Astrophysics Data System (ADS)

Bavera, D.; Bocchiola, D.; de Michele, C.

2007-12-01

The Snow Water Equivalent (SWE) is an important component of the hydrologic balance of mountain basins and snow fed areas in general. The total cumulated snow water equivalent at the end of the accumulation season represents the water availability at melt. Here, a statistical methodology to estimate the Snow Water Equivalent, at April 1st, is developed coupling ground data (snow depth and snow density measurements) and MODIS images. The methodology is applied to the Mallero river basin (about 320 km²) located in the Central Alps, northern Italy, where are available 11 snow gauges and a lot of sparse snow density measurements. The application covers 7 years from 2001 to 2007. The analysis has identified some problems in the MODIS information due to the cloud cover and misclassification for orographic shadow. The study is performed in the framework of AWARE (A tool for monitoring and forecasting Available WAter REsource in mountain environment) EU-project, a STREP Project in the VI F.P., GMES Initiative.

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

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

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.

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

National Snow Analyses - NOHRSC - The ultimate source for snow information

Science.gov Websites

Equivalent Thumbnail image of Modeled Snow Water Equivalent Animate: Season --- Two weeks --- One Day Snow Depth Thumbnail image of Modeled Snow Depth Animate: Season --- Two weeks --- One Day Average Snowpack Temp Thumbnail image of Modeled Average Snowpack Temp Animate: Season --- Two weeks --- One Day SWE

The AMSR2 Satellite-based Microwave Snow Algorithm (SMSA) to estimate regional to global snow depth and snow water equivalent

NASA Astrophysics Data System (ADS)

Kelly, R. E. J.; Saberi, N.; Li, Q.

2017-12-01

With moderate to high spatial resolution (<1 km) regional to global snow water equivalent (SWE) observation approaches yet to be fully scoped and developed, the long-term satellite passive microwave record remains an important tool for cryosphere-climate diagnostics. A new satellite microwave remote sensing approach is described for estimating snow depth (SD) and snow water equivalent (SWE). The algorithm, called the Satellite-based Microwave Snow Algorithm (SMSA), uses Advanced Microwave Scanning Radiometer - 2 (AMSR2) observations aboard the Global Change Observation Mission - Water mission launched by the Japan Aerospace Exploration Agency in 2012. The approach is unique since it leverages observed brightness temperatures (Tb) with static ancillary data to parameterize a physically-based retrieval without requiring parameter constraints from in situ snow depth observations or historical snow depth climatology. After screening snow from non-snow surface targets (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]), moderate and shallow snow depths are estimated by minimizing the difference between Dense Media Radiative Transfer model estimates (Tsang et al., 2000; Picard et al., 2011) and AMSR2 Tb observations to retrieve SWE and SD. Parameterization of the model combines a parsimonious snow grain size and density approach originally developed by Kelly et al. (2003). Evaluation of the SMSA performance is achieved using in situ snow depth data from a variety of standard and experiment data sources. Results presented from winter seasons 2012-13 to 2016-17 illustrate the improved performance of the new approach in comparison with the baseline AMSR2 algorithm estimates and approach the performance of the model assimilation-based approach of GlobSnow. Given the variation in estimation power of SWE by different land surface/climate models and selected satellite-derived passive microwave approaches, SMSA provides

Microbial Community Analysis of Colored Snow from an Alpine Snowfield in Northern Japan Reveals the Prevalence of Betaproteobacteria with Snow Algae.

PubMed

Terashima, Mia; Umezawa, Kazuhiro; Mori, Shoichi; Kojima, Hisaya; Fukui, Manabu

2017-01-01

Psychrophilic algae blooms can be observed coloring the snow during the melt season in alpine snowfields. These algae are important primary producers on the snow surface environment, supporting the microbial community that coexists with algae, which includes heterotrophic bacteria and fungi. In this study, we analyzed the microbial community of green and red-colored snow containing algae from Mount Asahi, Japan. We found that Chloromonas spp. are the dominant algae in all samples analyzed, and Chlamydomonas is the second-most abundant genus in the red snow. For the bacterial community profile, species belonging to the subphylum Betaproteobacteria were frequently detected in both green and red snow, while members of the phylum Bacteroidetes were also prominent in red snow. Furthermore, multiple independently obtained strains of Chloromonas sp. from inoculates of red snow resulted in the growth of Betaproteobacteria with the alga and the presence of bacteria appears to support growth of the xenic algal cultures under laboratory conditions. The dominance of Betaproteobacteria in algae-containing snow in combination with the detection of Chloromonas sp. with Betaproteobacteria strains suggest that these bacteria can utilize the available carbon source in algae-rich environments and may in turn promote algal growth.

Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014

NASA Astrophysics Data System (ADS)

Alonso-González, Esteban; López-Moreno, J. Ignacio; Gascoin, Simon; García-Valdecasas Ojeda, Matilde; Sanmiguel-Vallelado, Alba; Navarro-Serrano, Francisco; Revuelto, Jesús; Ceballos, Antonio; Jesús Esteban-Parra, María; Essery, Richard

2018-02-01

We present snow observations and a validated daily gridded snowpack dataset that was simulated from downscaled reanalysis of data for the Iberian Peninsula. The Iberian Peninsula has long-lasting seasonal snowpacks in its different mountain ranges, and winter snowfall occurs in most of its area. However, there are only limited direct observations of snow depth (SD) and snow water equivalent (SWE), making it difficult to analyze snow dynamics and the spatiotemporal patterns of snowfall. We used meteorological data from downscaled reanalyses as input of a physically based snow energy balance model to simulate SWE and SD over the Iberian Peninsula from 1980 to 2014. More specifically, the ERA-Interim reanalysis was downscaled to 10 km × 10 km resolution using the Weather Research and Forecasting (WRF) model. The WRF outputs were used directly, or as input to other submodels, to obtain data needed to drive the Factorial Snow Model (FSM). We used lapse rate coefficients and hygrobarometric adjustments to simulate snow series at 100 m elevations bands for each 10 km × 10 km grid cell in the Iberian Peninsula. The snow series were validated using data from MODIS satellite sensor and ground observations. The overall simulated snow series accurately reproduced the interannual variability of snowpack and the spatial variability of snow accumulation and melting, even in very complex topographic terrains. Thus, the presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism, and risk management. The data presented here are freely available for download from Zenodo (https://doi.org/10.5281/zenodo.854618). This paper fully describes the work flow, data validation, uncertainty assessment, and possible applications and limitations of the database.

Validation of snow characteristics and snow albedo feedback in the Canadian Regional Climate Model simulations over North America

NASA Astrophysics Data System (ADS)

Fang, B.; Sushama, L.; Diro, G. T.

2015-12-01

Snow characteristics and snow albedo feedback (SAF) over North America, as simulated by the fifth-generation Canadian Regional Climate Model (CRCM5), when driven by ERA-40/ERA-Interim, CanESM2 and MPI-ESM-LR at the lateral boundaries, are analyzed in this study. Validation of snow characteristics is performed by comparing simulations against available observations from MODIS, ISCCP and CMC. Results show that the model is able to represent the main spatial distribution of snow characteristics with some overestimation in snow mass and snow depth over the Canadian high Arctic. Some overestimation in surface albedo is also noted for the boreal region which is believed to be related to the snow unloading parameterization, as well as the overestimation of snow albedo. SAF is assessed both in seasonal and climate change contexts when possible. The strength of SAF is quantified as the amount of additional net shortwave radiation at the top of the atmosphere as surface albedo decreases in association with a 1°C increase in surface temperature. Following Qu and Hall (2007), this is expressed as the product of the variation in planetary albedo with surface albedo and the change in surface albedo for 1°C change in surface air temperature during the season, which in turn is determined by the strength of the snow cover and snowpack metamorphosis feedback loops. Analysis of the latter term in the seasonal cycle suggests that for CRCM5 simulations, the snow cover feedback loop is more dominant compared to the snowpack metamorphosis feedback loop, whereas for MODIS, the two feedback loops have more or less similar strength. Moreover, the SAF strength in the climate change context appears to be weaker than in the seasonal cycle and is sensitive to the driving GCM and the RCP scenario.

Optimizing placements of ground-based snow sensors for areal snow cover estimation using a machine-learning algorithm and melt-season snow-LiDAR data

NASA Astrophysics Data System (ADS)

Oroza, C.; Zheng, Z.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2016-12-01

We present a structured, analytical approach to optimize ground-sensor placements based on time-series remotely sensed (LiDAR) data and machine-learning algorithms. We focused on catchments within the Merced and Tuolumne river basins, covered by the JPL Airborne Snow Observatory LiDAR program. First, we used a Gaussian mixture model to identify representative sensor locations in the space of independent variables for each catchment. Multiple independent variables that govern the distribution of snow depth were used, including elevation, slope, and aspect. Second, we used a Gaussian process to estimate the areal distribution of snow depth from the initial set of measurements. This is a covariance-based model that also estimates the areal distribution of model uncertainty based on the independent variable weights and autocorrelation. The uncertainty raster was used to strategically add sensors to minimize model uncertainty. We assessed the temporal accuracy of the method using LiDAR-derived snow-depth rasters collected in water-year 2014. In each area, optimal sensor placements were determined using the first available snow raster for the year. The accuracy in the remaining LiDAR surveys was compared to 100 configurations of sensors selected at random. We found the accuracy of the model from the proposed placements to be higher and more consistent in each remaining survey than the average random configuration. We found that a relatively small number of sensors can be used to accurately reproduce the spatial patterns of snow depth across the basins, when placed using spatial snow data. Our approach also simplifies sensor placement. At present, field surveys are required to identify representative locations for such networks, a process that is labor intensive and provides limited guarantees on the networks' representation of catchment independent variables.

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

Application of snow models to snow removal operations on the Going-to-the-Sun Road, Glacier National Park

USGS Publications Warehouse

Fagre, Daniel B.; Klasner, Frederick L.

2000-01-01

Snow removal, and the attendant avalanche risk for road crews, is a major issue on mountain highways worldwide. The Going-to-the-Sun Road is the only road that crosses Glacier National Park, Montana. This 80-km highway ascends over 1200m along the wall of a glaciated basin and crosses the continental divide. The annual opening of the road is critical to the regional economy and there is public pressure to open the road as early as possible. Despite the 67-year history of snow removal activities, few stat on snow conditions at upper elevations were available to guide annual planning for the raod opening. We examined statistical relationships between the opening date and nearby SNOTEL data on snow water equivalence (WE) for 30 years. Early spring SWE (first Monday in April) accounted for only 33% of the variance in road opening dates. Because avalanche spotters, used to warn heavy equipment operators of danger, are ineffective during spring storms or low-visibility conditions, we incorporated the percentage of days with precipitation during plowing as a proxy for visibility. This improved the model's predictive power to 69%/ A mountain snow simulator (MTSNOW) was used to calculate the depth and density of snow at various points along the road and field data were collected for comparison. MTSNOW underestimated the observed snow conditions, in part because it does not yet account for wind redistribution of snow. The severe topography of the upper reaches of the road are subjected to extensive wind redistribution of snow as evidence by the formation of "The Big Drift" on the lee side of Logan Pass.

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

Water availability and management for food security

USDA-ARS?s Scientific Manuscript database

Food security is directly linked to water security for food production. Water availability for crop production will be dependent upon precipitation or irrigation, soil water holding capacity, and crop water demand. The linkages among these components in rainfed agricultural systems shows the impact ...

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

Profits, commercial food supplier involvement, and school vending machine snack food availability: implications for implementing the new competitive foods rule.

PubMed

Terry-McElrath, Yvonne M; Hood, Nancy E; Colabianchi, Natalie; O'Malley, Patrick M; Johnston, Lloyd D

2014-07-01

The 2013-2014 school year involved preparation for implementing the new US Department of Agriculture (USDA) competitive foods nutrition standards. An awareness of associations between commercial supplier involvement, food vending practices, and food vending item availability may assist schools in preparing for the new standards. Analyses used 2007-2012 questionnaire data from administrators of 814 middle and 801 high schools in the nationally representative Youth, Education, and Society study to examine prevalence of profit from and commercial involvement with vending machine food sales, and associations between such measures and food availability. Profits for the school district were associated with decreased low-nutrient, energy-dense (LNED) food availability and increased fruit/vegetable availability. Profits for the school and use of company suppliers were associated with increased LNED availability; company suppliers also were associated with decreased fruit/vegetable availability. Supplier "say" in vending food selection was associated with increased LNED availability and decreased fruit/vegetable availability. Results support (1) increased district involvement with school vending policies and practices, and (2) limited supplier "say" as to what items are made available in student-accessed vending machines. Schools and districts should pay close attention to which food items replace vending machine LNED foods following implementation of the new nutrition standards. © 2014, American School Health Association.

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…

Seasonal food use by white-tailed deer at Valley Forge National Historical Park, Pennsylvania, USA

NASA Astrophysics Data System (ADS)

Cypher, Brian L.; Yahner, Richard H.; Cypher, Ellen A.

1988-03-01

Food habits of white-tailed deer ( Odocoileus virginianus) were examined from January to November 1984 via fecal-pellet analysis at Valley Forge National Historical Park (VFNHP), which represents an “island” habitat for deer surrounded by extensive urbanization, in southeastern Pennsylvania. In addition, use of fields by deer was compared to food habits. Herbaceous vegetation (forbs, leaves of woody plants, and conifer needles) was the predominant food type in all seasons except fall. Acorns and graminoids (grasses and sedges) were important food resources in fall and spring, respectively. Use of woody browse (twigs) was similar among seasons. Field use was relatively high during fall, winter without snow cover (<20 cm), and spring when food resources in fields were readily available. In contrast, use of fields was lowest in summer when preferred woodland foods were available and in winter with snow cover when food in fields was not readily accessible. Patterns of food-type use by deer at VFNHP indicate the year-round importance of nonwoody foods and field habitats to deer populations on public lands such as national parks in the northeastern United States.

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

The Impact Of Snow Melt On Surface Runoff Of Sava River In Slovenia

NASA Astrophysics Data System (ADS)

Horvat, A.; Brilly, M.; Vidmar, A.; Kobold, M.

2009-04-01

Snow is a type of precipitation in the form of crystalline water ice, consisting of a multitude of snowflakes that fall from clouds. Snow remains on the ground until it melts or sublimates. Spring snow melt is a major source of water supply to areas in temperate zones near mountains that catch and hold winter snow, especially those with a prolonged dry summer. In such places, water equivalent is of great interest to water managers wishing to predict spring runoff and the water supply of cities downstream. In temperate zone like in Slovenia the snow melts in the spring and contributes certain amount of water to surface flow. This amount of water can be great and can cause serious floods in case of fast snow melt. For this reason we tried to determine the influence of snow melt on the largest river basin in Slovenia - Sava River basin, on surface runoff. We would like to find out if snow melt in Slovenian Alps can cause spring floods and how serious it can be. First of all we studied the caracteristics of Sava River basin - geology, hydrology, clima, relief and snow conditions in details for each subbasin. Furtermore we focused on snow and described the snow phenomenom in Slovenia, detailed on Sava River basin. We collected all available data on snow - snow water equivalent and snow depth. Snow water equivalent is a much more useful measurement to hydrologists than snow depth, as the density of cool freshly fallen snow widely varies. New snow commonly has a density of between 5% and 15% of water. But unfortunately there is not a lot of available data of SWE available for Slovenia. Later on we compared the data of snow depth and river runoff for some of the 40 winter seasons. Finally we analyzed the use of satellite images for Slovenia to determine the snow cover for hydrology reason. We concluded that snow melt in Slovenia does not have a greater influence on Sava River flow. The snow cover in Alps can melt fast due to higher temperatures but the water distributes

The significance of vertical moisture diffusion on drifting snow sublimation near snow surface

NASA Astrophysics Data System (ADS)

Huang, Ning; Shi, Guanglei

2017-12-01

Sublimation of blowing snow is an important parameter not only for the study of polar ice sheets and glaciers, but also for maintaining the ecology of arid and semi-arid lands. However, sublimation of near-surface blowing snow has often been ignored in previous studies. To study sublimation of near-surface blowing snow, we established a sublimation of blowing snow model containing both a vertical moisture diffusion equation and a heat balance equation. The results showed that although sublimation of near-surface blowing snow was strongly reduced by a negative feedback effect, due to vertical moisture diffusion, the relative humidity near the surface does not reach 100 %. Therefore, the sublimation of near-surface blowing snow does not stop. In addition, the sublimation rate near the surface is 3-4 orders of magnitude higher than that at 10 m above the surface and the mass of snow sublimation near the surface accounts for more than half of the total snow sublimation when the friction wind velocity is less than about 0.55 m s-1. Therefore, the sublimation of near-surface blowing snow should not be neglected.

75 FR 59268 - Draft Guidance for Industry: Acidified Foods; Availability

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-27

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2010-D-0434] Draft Guidance for Industry: Acidified Foods; Availability AGENCY: Food and Drug Administration, HHS. ACTION: Notice. SUMMARY: The Food and Drug Administration (FDA) is announcing the availability of a draft...

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).

Mapping snow depth from stereo satellite imagery

NASA Astrophysics Data System (ADS)

Gascoin, S.; Marti, R.; Berthier, E.; Houet, T.; de Pinel, M.; Laffly, D.

2016-12-01

To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. Here, we examine the potential of very-high-resolution (VHR) optical stereo satellites to this purpose. Two triplets of 0.70 m resolution images were acquired by the Pléiades satellite over an open alpine catchment (14.5 km²) under snow-free and snow-covered conditions. The open-source software Ame's Stereo Pipeline (ASP) was used to match the stereo pairs without ground control points to generate raw photogrammetric clouds and to convert them into high-resolution digital elevation models (DEMs) at 1, 2, and 4 m resolutions. The DEM differences (dDEMs) were computed after 3-D coregistration, including a correction of a -0.48 m vertical bias. The bias-corrected dDEM maps were compared to 451 snow-probe measurements. The results show a decimetric accuracy and precision in the Pléiades-derived snow depths. The median of the residuals is -0.16 m, with a standard deviation (SD) of 0.58 m at a pixel size of 2 m. We compared the 2 m Pléiades dDEM to a 2 m dDEM that was based on a winged unmanned aircraft vehicle (UAV) photogrammetric survey that was performed on the same winter date over a portion of the catchment (3.1 km²). The UAV-derived snow depth map exhibits the same patterns as the Pléiades-derived snow map, with a median of -0.11 m and a SD of 0.62 m when compared to the snow-probe measurements. The Pléiades images benefit from a very broad radiometric range (12 bits), allowing a high correlation success rate over the snow-covered areas. This study demonstrates the value of VHR stereo satellite imagery to map snow depth in remote mountainous areas even when no field data are available. Based on this method we have initiated a multi-year survey of the peak snow depth in the Bassiès catchment.

The Airborne Snow Observatory: fusion of imaging spectrometer and scanning lidar for studies of mountain snow cover (Invited)

NASA Astrophysics Data System (ADS)

Painter, T. H.; Andreadis, K.; Berisford, D. F.; Goodale, C. E.; Hart, A. F.; Heneghan, C.; Deems, J. S.; Gehrke, F.; Marks, D. G.; Mattmann, C. A.; McGurk, B. J.; Ramirez, P.; Seidel, F. C.; Skiles, M.; Trangsrud, A.; Winstral, A. H.; Kirchner, P.; Zimdars, P. A.; Yaghoobi, R.; Boustani, M.; Khudikyan, S.; Richardson, M.; Atwater, R.; Horn, J.; Goods, D.; Verma, R.; Boardman, J. W.

2013-12-01

Snow cover and its melt dominate regional climate and water resources in many of the world's mountainous regions. However, we face significant water resource challenges due to the intersection of increasing demand from population growth and changes in runoff total and timing due to climate change. Moreover, increasing temperatures in desert systems will increase dust loading to mountain snow cover, thus reducing the snow cover albedo and accelerating snowmelt runoff. 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 poorly quantified in the US and not at all in most of the globe, leaving runoff models poorly constrained. Recognizing this need, JPL developed the Airborne Snow Observatory (ASO), an imaging spectrometer and imaging LiDAR system, to quantify snow water equivalent and snow albedo, provide unprecedented knowledge of snow properties, and provide complete, robust inputs to snowmelt runoff models, water management models, and systems of the future. Critical in the design of the ASO system is the availability of snow water equivalent and albedo products within 24 hours of acquisition for timely constraint of snowmelt runoff forecast models. In spring 2013, ASO was deployed for its first year of a multi-year Demonstration Mission of weekly acquisitions in the Tuolumne River Basin (Sierra Nevada) and monthly acquisitions in the Uncompahgre River Basin (Colorado). The ASO data were used to constrain spatially distributed models of varying complexities and integrated into the operations of the O'Shaughnessy Dam on the Hetch Hetchy reservoir on the Tuolumne River. Here we present the first results from the ASO Demonstration Mission 1 along with modeling results with and without the constraint by the ASO's high spatial resolution and spatially

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.

Energy expenditure and clearing snow: a comparison of shovel and snow pusher.

PubMed

Smolander, J; Louhevaara, V; Ahonen, E; Polari, J; Klen, T

1995-04-01

In order to assess the energy demands of manual clearing of snow, nine men did snow clearing work for 15 min with a shovel and a snow pusher. The depth of the snowcover was 400-600 mm representing a very heavy snowfall. Heart rate (HR), oxygen consumption (VO2), pulmonary ventilation (VE), respiratory exchange ratio (R), and rating of perceived exertion (RPE) were determined during the work tasks. HR, VE, R, and RPE were not significantly different between the shovel and snow pusher. HR averaged (+/- SD) 141 +/- 20 b min-1 with the shovel, and 142 +/- 19 beats.min-1 with the snow pusher. VO2 was 2.1 +/- 0.41.min-1 (63 +/- 12%VO2 max) in shovelling and 2.6 +/- 0.51.min-1 (75 +/- 14%VO2max) in snow pushing (p < 0.001). In conclusion manual clearing of snow in conditions representing heavy snowfalls was found to be strenuous physical work, not suitable for persons with cardiac risk factors, but which may serve as a mode of physical training in healthy adults.

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,

"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

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. Copyright © 2015 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

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).

[Effect of different snow depth and area on the snow cover retrieval using remote sensing data].

PubMed

Jiang, Hong-bo; Qin, Qi-ming; Zhang, Ning; Dong, Heng; Chen, Chao

2011-12-01

For the needs of snow cover monitoring using multi-source remote sensing data, in the present article, based on the spectrum analysis of different depth and area of snow, the effect of snow depth on the results of snow cover retrieval using normalized difference snow index (NDSI) is discussed. Meanwhile, taking the HJ-1B and MODIS remote sensing data as an example, the snow area effect on the snow cover monitoring is also studied. The results show that: the difference of snow depth does not contribute to the retrieval results, while the snow area affects the results of retrieval to some extents because of the constraints of spatial resolution.

MODSNOW-Tool: an operational tool for daily snow cover monitoring using MODIS data

NASA Astrophysics Data System (ADS)

Gafurov, Abror; Lüdtke, Stefan; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Schöne, Tilo; Schmidt, Sebastian; Kalashnikova, Olga; Merz, Bruno

2017-04-01

Spatially distributed snow cover information in mountain areas is extremely important for water storage estimations, seasonal water availability forecasting, or the assessment of snow-related hazards (e.g. enhanced snow-melt following intensive rains, or avalanche events). Moreover, spatially distributed snow cover information can be used to calibrate and/or validate hydrological models. We present the MODSNOW-Tool - an operational monitoring tool offers a user-friendly application which can be used for catchment-based operational snow cover monitoring. The application automatically downloads and processes freely available daily Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data. The MODSNOW-Tool uses a step-wise approach for cloud removal and delivers cloud-free snow cover maps for the selected river basins including basin specific snow cover extent statistics. The accuracy of cloud-eliminated MODSNOW snow cover maps was validated for 84 almost cloud-free days in the Karadarya river basin in Central Asia, and an average accuracy of 94 % was achieved. The MODSNOW-Tool can be used in operational and non-operational mode. In the operational mode, the tool is set up as a scheduled task on a local computer allowing automatic execution without user interaction and delivers snow cover maps on a daily basis. In the non-operational mode, the tool can be used to process historical time series of snow cover maps. The MODSNOW-Tool is currently implemented and in use at the national hydrometeorological services of four Central Asian states - Kazakhstan, Kyrgyzstan, Uzbekistan and Turkmenistan and used for seasonal water availability forecast.

Snow as Field-Teaching Medium for Earth Science.

ERIC Educational Resources Information Center

Custer, Stephan Gregory

1991-01-01

Snow is a widely available earth-science teaching medium which can be used to explore scientific concepts in the field, either directly or by analogy. Snow can be considered a mineral, sediment, sedimentary rock, or metamorphic rock. Natural processes such as crystal growth, melting, sedimentation, and metamorphism can be studied in practical time…

Snow mechanics and avalanche formation: field experiments on the dynamic response of the snow cover

NASA Astrophysics Data System (ADS)

Schweizer, Jürg; Schneebeli, Martin; Fierz, Charles; Föhn, Paul M. B.

1995-11-01

Knowledge about snow mechanics and snow avalanche formation forms the basis of any hazard mitigation measures. The crucial point is the snow stability. The most relevant mechanical properties - the compressive, tensile and shear strength of the individual snow layers within the snow cover - vary substantially in space and time. Among other things the strength of the snow layers depends strongly on the state of stress and the strain rate. The evaluation of the stability of the snow cover is hence a difficult task involving many extrapolations. To gain insight in the release mechanism of slab avalanches triggered by skiers, the skier's impact is measured with a load cell at different depths within the snow cover and for different snow conditions. The study focused on the effects of the dynamic loading and of the damping by snow compaction. In accordance with earlier finite-element (FE) calculations the results show the importance of the depth of the weak layer or interface and the snow conditions, especially the sublayering. In order to directly measure the impact force and to study the snow properties in more detail, a new instrument, called rammrutsch was developed. It combines the properties of the rutschblock with the defined impact properties of the rammsonde. The mechanical properties are determined using (i) the impact energy of the rammrutsch and (ii) the deformations of the snow cover measured with accelerometers and digital image processing of video sequences. The new method is well suited to detect and to measure the mechanical processes and properties of the fracturing layers. The duration of one test is around 10 minutes and the method seems appropriate for determining the spatial variability of the snow cover. A series of experiments in a forest opening showed a clear difference in the snow stability between sites below trees and ones in the free field of the opening.

Experimental and model based investigation of the links between snow bidirectional reflectance and snow microstructure

NASA Astrophysics Data System (ADS)

Dumont, M.; Flin, F.; Malinka, A.; Brissaud, O.; Hagenmuller, P.; Dufour, A.; Lapalus, P.; Lesaffre, B.; Calonne, N.; Rolland du Roscoat, S.; Ando, E.

2017-12-01

Snow optical properties are unique among Earth surface and crucial for a wide range of applications. The bi-directional reflectance, hereafter BRDF, of snow is sensible to snow microstructure. However the complex interplays between different parameters of snow microstructure namely size parameters and shape parameters on reflectance are challenging to disentangle both theoretically and experimentally. An accurate understanding and modelling of snow BRDF is required to correctly process satellite data. BRDF measurements might also provide means of characterizing snow morphology. This study presents one of the very few dataset that combined bi-directional reflectance measurements over 500-2500 nm and X-ray tomography of the snow microstructure for three different snow samples and two snow types. The dataset is used to evaluate the approach from Malinka, 2014 that relates snow optical properties to the chord length distribution in the snow microstructure. For low and medium absorption, the model accurately reproduces the measurements but tends to slightly overestimate the anisotropy of the reflectance. The model indicates that the deviation of the ice chord length distribution from an exponential distribution, that can be understood as a characterization of snow types, does not impact the reflectance for such absorptions. The simulations are also impacted by the uncertainties in the ice refractive index values. At high absorption and high viewing/incident zenith angle, the simulations and the measurements disagree indicating that some of the assumptions made in the model are not met anymore. The study also indicates that crystal habits might play a significant role for the reflectance under such geometries and wavelengths. However quantitative relationship between crystal habits and reflectance alongside with potential optical methodologies to classify snow morphology would require an extended dataset over more snow types. This extended dataset can likely be obtained

Snow [Chapter 10

Treesearch

R. A. Sommerfeld

1994-01-01

Generally, the annual snowpack at GLEES is established in November and lasts into July. Figure 10.1 is the 1987-91 recession curve of the snow-covered area fraction versus degree days. About 20% of the area consists of rocks, which are usually blown clear of snow, and trees. The trees may hide some of the snow in the aerial photographs that were used to develop the...

Characterizing 2-D snow stratigraphy in forests based on high-resolution snow penetrometry

NASA Astrophysics Data System (ADS)

Teich, M.; Loewe, H.; Jenkins, M. J.; Schneebeli, M.

2016-12-01

Snow stratigraphy, the characteristic layering within a seasonal snowpack, has important implications for snow remote sensing, hydrology and avalanches. Forests modify snowpack properties through interception of falling snow by tree crowns, the reduction of near-surface wind speeds, and changes to the energy balance beneath and around trees leading to a highly variable stratigraphy in space and time. The lack of snowpack observations in forests limits our ability to understand the spatio-temporal evolution of snow stratigraphy as a function of forest structure and to observe snowpack response to changes in forest cover. We examined the snowpack in field campaigns using the SnowMicroPen (SMP) under tree canopies in an Engelmann spruce forest in the central Rocky Mountains in Utah, USA. Data were collected in plots beneath canopies of undisturbed, bark beetle-disturbed and salvage logged forest stands, and a non-forested meadow. In 2015 weekly-repeated SMP penetration measurements were taken along 10 m transects at 0.3 m intervals. In the winter of 2016 bi-weekly measurements were collected along 20 m transects every 0.5 m. Using a statistical model, we derived 2-D snow density profiles as a measure of stratigraphy. The small-scale patterns in snow density revealed a more heterogeneous stratigraphy in undisturbed dense stands and also beneath bark beetle-disturbed forest. In contrast, snow stratigraphy was more homogeneous in the harvested plot despite standing small diameter trees and woody debris with effective heights up to 95 cm. As expected, snow depth and layering in non-forested plots varied only slightly over the small spatial extent sampled. Observed patterns changed throughout the snow season dependent upon snow and meteorological conditions. The results contribute to the general understanding of forest-snowpack interactions at high spatial resolution, and can be used to validate snowpack and microwave models for avalanche formation processes and SWE

River Flow Advisory Commission: Snow Survey

Science.gov Websites

Survey River Watch Home → Snow Survey RFAC Information About Us Reports Maine Cooperative Snow Survey About the Snow Survey Snow Survey Map Compare Snow Survey Data Snow Survey Graphs River Watch MEMA Home USGS (Maine) Home Maine Cooperative Snow Survey This information is provided by a partnership with

Snow snake performance monitoring.

DOT National Transportation Integrated Search

2008-12-01

A recent study, Three-Dimensional Roughness Elements for Snow Retention (FHWA-WY-06/04F) (Tabler 2006), demonstrated : positive evidence for the effectiveness of Snow Snakes, a new type of snow fence suitable for use within the highway right-of...

Snow Coverage Analysis Using ASTER over the Sierra Nevada Mountain Range

NASA Astrophysics Data System (ADS)

Ross, B.

2017-12-01

Snow has strong impacts on human behavior, state and local activities, and the economy. The Sierra Nevada snowpack is California's most important natural reservoir of water. Such snow is melting sooner and faster. A recent California drought study showed that there was a deficit of 1.5 million acre-feet of water in 2014 due to the fast melting rates. Scientists have been using the Moderate Resolution Imaging Spectrometer (MODIS) which is available at the spatial resolution of 500-meter, to analyze the changes in snow coverage. While such analysis provides us with the valuable information, it would be more beneficial to employ the imageries at a higher spatial resolution for snow studies. Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER), which acquires the high-resolution imageries ranging from 15-meter to 90-meter, has recently become freely available to the public. Our study utilized two scenes obtained from ASTER to investigate the changes in snow extent over the Sierra Nevada's mountain area for an 8-year period. These two scenes were collected on April 11, 2007 and April 16, 2015 covering the same geographic region. Normalized Difference Snow Index (NDSI) was adopted to delineate the snow coverage in each scene. Our study shows a substantial decrease of snow coverage in the studied geographic region by pixel count.

Competitive foods available in Pennsylvania public high schools.

PubMed

Probart, Claudia; McDonnell, Elaine; Weirich, J Elaine; Hartman, Terryl; Bailey-Davis, Lisa; Prabhakher, Vaheedha

2005-08-01

This study examined the types and extent of competitive foods available in public high schools in Pennsylvania. We developed, pilot tested, and distributed surveys to school foodservice directors in a random sample of 271 high schools in Pennsylvania. Two hundred twenty-eight surveys were returned, for a response rate of 84%. Statistical analyses were performed: Descriptive statistics were used to examine the extent of competitive food sales in Pennsylvania public high schools. The survey data were analyzed using SPSS software version 11.5.1 (2002, SPSS base 11.0 for Windows, SPSS Inc, Chicago, IL). A la carte sales provide almost dollar 700/day to school foodservice programs, almost 85% of which receive no financial support from their school districts. The top-selling a la carte items are "hamburgers, pizza, and sandwiches." Ninety-four percent of respondents indicated that vending machines are accessible to students. The item most commonly offered in vending machines is bottled water (71.5%). While food items are less often available through school stores and club fund-raisers, candy is the item most commonly offered through these sources. Competitive foods are widely available in high schools. Although many of the items available are low in nutritional value, we found several of the top-selling a la carte options to be nutritious and bottled water the item most often identified as available through vending machines.

Integration of MODIS Snow, Cloud and Land Area Coverage Data with SNOTEL to Generate Inter-Annual and Within-Season Snow Depletion Curves and Maps

NASA Astrophysics Data System (ADS)

Qualls, R. J.; Woodruff, C.

2017-12-01

The behavior of inter-annual trends in mountain snow cover would represent extremely useful information for drought and climate change assessment; however, individual data sources exhibit specific limitations for characterizing this behavior. For example, SNOTEL data provide time series point values of Snow Water Equivalent (SWE), but lack spatial content apart from that contained in a sparse network of point values. Satellite observations in the visible spectrum can provide snow covered area, but not SWE at present, and are limited by cloud cover which often obscures visibility of the ground, especially during the winter and spring in mountainous areas. Cloud cover, therefore, often limits both temporal and spatial coverage of satellite remote sensing of snow. Among the platforms providing the best combination of temporal and spatial coverage to overcome the cloud obscuration problem by providing frequent overflights, the Aqua and Terra satellites carrying the MODIS instrument package provide 500 m, daily resolution observations of snow cover. These were only launched in 1999 and the early 2000's, thus limiting the historical period over which these data are available. A hybrid method incorporating SNOTEL and MODIS data has been developed which accomplishes cloud removal, and enables determination of the time series of watershed spatial snow cover when either SNOTEL or MODIS data are available. This allows one to generate spatial snow cover information for watersheds with SNOTEL stations for periods both before and after the launch of the Aqua and Terra satellites, extending the spatial information about snow cover over the period of record of the SNOTEL stations present in a watershed. This method is used to quantify the spatial time series of snow over the 9000 km2 Upper Snake River watershed and to evaluate inter-annual trends in the timing, rate, and duration of melt over the nearly 40 year period from the early 1980's to the present, and shows promise for

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

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.

Estimation of Snow Particle Model Suitable for a Complex and Forested Terrain: Lessons from SnowEx

NASA Astrophysics Data System (ADS)

Gatebe, C. K.; Li, W.; Stamnes, K. H.; Poudyal, R.; Fan, Y.; Chen, N.

2017-12-01

SnowEx 2017 obtained consistent and coordinated ground and airborne remote sensing measurements over Grand Mesa in Colorado, which feature sufficient forested stands to have a range of density and height (and other forest conditions); a range of snow depth/snow water equivalent (SWE) conditions; sufficiently flat snow-covered terrain of a size comparable to airborne instrument swath widths. The Cloud Absorption Radiometer (CAR) data from SnowEx are unique and can be used to assess the accuracy of Bidirectional Reflectance-Distribution Functions (BRDFs) calculated by different snow models. These measurements provide multiple angle and multiple wavelength data needed for accurate surface BRDF characterization. Such data cannot easily be obtained by current satellite remote sensors. Compared to ground-based snow field measurements, CAR measurements minimize the effect of self-shading, and are adaptable to a wide variety of field conditions. We plan to use the CAR measurements as the validation data source for our snow modeling effort. By comparing calculated BRDF results from different snow models to CAR measurements, we can determine which model best explains the snow BRDFs, and is therefore most suitable for application to satellite remote sensing of snow parameters and surface energy budget calculations.

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

Estimated snow parameters for vehicle mobility modeling in Korea, Germany and interior Alaska

DOT National Transportation Integrated Search

1995-09-01

Snow is a crucial factor affecting the U.S. Army's operations in cold regions. Values for snow depth and snow density are needed for vehicle mobility studies, but unfortunately the available historical records of these parameters tend to be relativel...

Deriving Snow-Cover Depletion Curves for Different Spatial Scales from Remote Sensing and Snow Telemetry Data

NASA Technical Reports Server (NTRS)

Fassnacht, Steven R.; Sexstone, Graham A.; Kashipazha, Amir H.; Lopez-Moreno, Juan Ignacio; Jasinski, Michael F.; Kampf, Stephanie K.; Von Thaden, Benjamin C.

2015-01-01

During the melting of a snowpack, snow water equivalent (SWE) can be correlated to snow-covered area (SCA) once snow-free areas appear, which is when SCA begins to decrease below 100%. This amount of SWE is called the threshold SWE. Daily SWE data from snow telemetry stations were related to SCA derived from moderate-resolution imaging spectro radiometer images to produce snow-cover depletion curves. The snow depletion curves were created for an 80,000 sq km domain across southern Wyoming and northern Colorado encompassing 54 snow telemetry stations. Eight yearly snow depletion curves were compared, and it is shown that the slope of each is a function of the amount of snow received. Snow-cover depletion curves were also derived for all the individual stations, for which the threshold SWE could be estimated from peak SWE and the topography around each station. A stations peak SWE was much more important than the main topographic variables that included location, elevation, slope, and modelled clear sky solar radiation. The threshold SWE mostly illustrated inter-annual consistency.

Snow geese

USGS Publications Warehouse

Hupp, Jerry W.; Robertson, Donna G.; Brackney, Alan W.; Douglas, David C.; Reynolds, Patricia E.; Rhode, E.B.

2002-01-01

Part of the coastal plain of the Arctic National Wildlife Refuge, Alaska, is used as an autumn staging area by lesser snow geese (Chen caerulescens caerulescens) from the Western Canadian Arctic population (hereafter called the Western Arctic population). There were approximately 200,000 breeding adults in the Western Arctic population through the mid-1980s (Johnson and Herter 1989), but the population has recently increased to about 500,000 breeding adults (Kerbes et al. 1999).Early in their autumn migration, adult and juvenile snow geese from the Western Arctic population feed intensively while staging on the Beaufort Sea coastal plain in Canada and Alaska to build fat reserves needed for migration. Aerial censuses from 1973 to 1985 indicated that up to 600,000 adult and juvenile snow geese used the coastal plain for 2-4 weeks in late August until mid-September (Oates et al. 1987).We studied annual variation in numbers and spatial distribution of snow geese that staged on the coastal plain of the Arctic Refuge.

Facilitating the exploitation of ERTS imagery using snow enhancement techniques

NASA Technical Reports Server (NTRS)

Wobber, F. J. (Principal Investigator); Martin, K. R.; Sheffield, C.; Russell, O.; Amato, R. V.

1972-01-01

The author has identified the following significant results. Analysis of all available (Gemini, Apollo, Nimbus, NASA aircraft) small scale snow covered imagery has been conducted to develop and refine snow enhancement techniques. A detailed photographic interpretation of ERTS-simulation imagery covering the Feather River/Lake Tahoe area was completed and the 580-680nm. band was determined to be the optimum band for fracture detection. ERTS-1 MSS bands 5 and 7 are best suited for detailed fracture mapping. The two bands should provide more complete fracture detail when utilized in combination. Analysis of early ERTS-1 data along with U-2 ERTS simulation imagery indicates that snow enhancement is a viable technique for geological fracture mapping. A wealth of fracture detail on snow-free terrain was noted during preliminary analysis of ERTS-1 images 1077-15005-6 and 7, 1077-15011-5 and 7, and 1079-15124-5 and 7. A direct comparison of data yield on snow-free versus snow-covered terrain will be conducted within these areas following receipt of snow-covered ERTS-1 imagery.

BOREAS RSS-8 Snow Maps Derived from Landsat TM Imagery

NASA Technical Reports Server (NTRS)

Hall, Dorothy; Chang, Alfred T. C.; Foster, James L.; Chien, Janeet Y. L.; Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Remote Sensing Science (RSS)-8 team utilized Landsat Thematic Mapper (TM) images to perform mapping of snow extent over the Southern Study Area (SSA). This data set consists of two Landsat TM images that were used to determine the snow-covered pixels over the BOREAS SSA on 18 Jan 1993 and on 06 Feb 1994. The data are stored in binary image format files. The RSS-08 snow map 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).

Towards a well-founded and reproducible snow load map for Austria

NASA Astrophysics Data System (ADS)

Winkler, Michael; Schellander, Harald

2017-04-01

"EN 1991-1-3 Eurocode 1: Part 1-3: Snow Loads" provides standard for the determination of the snow load to be used for the structural design of buildings etc. Since 2006 national specifications for Austria define a snow load map with four "load zones", allowing the calculation of the characteristic ground snow load sk for locations below 1500 m asl. A quadratic regression between altitude and sk is used, as suggested by EN 1991-1-3. The actual snow load map is based on best meteorological practice, but still it is somewhat subjective and non-reproducible. Underlying snow data series often end in the 1980s; in the best case data until about 2005 is used. Moreover, extreme value statistics only rely on the Gumbel distribution and the way in which snow depths are converted to snow loads is generally unknown. This might be enough reasons to rethink the snow load standard for Austria, all the more since today's situation is different to what it was some 15 years ago: Firstly, Austria is rich of multi-decadal, high quality snow depth measurements. These data are not well represented in the actual standard. Secondly, semi-empirical snow models allow sufficiently precise calculations of snow water equivalents and snow loads from snow depth measurements without the need of other parameters like temperature etc. which often are not available at the snow measurement sites. With the help of these tools, modelling of daily snow load series from daily snow depth measurements is possible. Finally, extreme value statistics nowadays offers convincing methods to calculate snow depths and loads with a return period of 50 years, which is the base of sk, and allows reproducible spatial extrapolation. The project introduced here will investigate these issues in order to update the Austrian snow load standard by providing a well-founded and reproducible snow load map for Austria. Not least, we seek for contact with standards bodies of neighboring countries to find intersections as well

The impact of snow on orthopaedic trauma referrals.

PubMed

Weston-Simons, John; Jack, Christopher M; Doctor, Cyrus; Brogan, Kit; Reed, Daniel; Ricketts, David

2012-07-01

Adverse weather has been shown to increase orthopaedic referrals and place strain on services. This retrospective study undertaken at a teaching hospital concerned referrals between April 2009 and April 2010 comparing days when snow fell to days when it did not. Referrals increased significantly on snow days (to 74.9 per day) in comparison to normal weather days (33.5 per day). During snow days there were significant increases in the number of distal radius and ankle fractures referred but not of fractured necks of femur. Complications during the snow fall period were related to procedures performed outside of the trauma unit with further difficulties related to a lack of operating equipment and implant availability. As a result of our study, we recommend that during periods of heavy snow fall orthopaedic and trauma units should place senior orthopaedic trainees in Accident and Emergency to review patients as a triage service, organise trauma lists related to surgeon specific expertise and avoid sending trauma patients outside the unit for operation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Antarctic Sea Ice Thickness and Snow-to-Ice Conversion from Atmospheric Reanalysis and Passive Microwave Snow Depth

NASA Technical Reports Server (NTRS)

Markus, Thorsten; Maksym, Ted

2007-01-01

Passive microwave snow depth, ice concentration, and ice motion estimates are combined with snowfall from the European Centre for Medium Range Weather Forecasting (ECMWF) reanalysis (ERA-40) from 1979-200 1 to estimate the prevalence of snow-to-ice conversion (snow-ice formation) on level sea ice in the Antarctic for April-October. Snow ice is ubiquitous in all regions throughout the growth season. Calculated snow- ice thicknesses fall within the range of estimates from ice core analysis for most regions. However, uncertainties in both this analysis and in situ data limit the usefulness of snow depth and snow-ice production to evaluate the accuracy of ERA-40 snowfall. The East Antarctic is an exception, where calculated snow-ice production exceeds observed ice thickness over wide areas, suggesting that ERA-40 precipitation is too high there. Snow-ice thickness variability is strongly controlled not just by snow accumulation rates, but also by ice divergence. Surprisingly, snow-ice production is largely independent of snow depth, indicating that the latter may be a poor indicator of total snow accumulation. Using the presence of snow-ice formation as a proxy indicator for near-zero freeboard, we examine the possibility of estimating level ice thickness from satellite snow depths. A best estimate for the mean level ice thickness in September is 53 cm, comparing well with 51 cm from ship-based observations. The error is estimated to be 10-20 cm, which is similar to the observed interannual and regional variability. Nevertheless, this is comparable to expected errors for ice thickness determined by satellite altimeters. Improvement in satellite snow depth retrievals would benefit both of these methods.

Food availability of glucose and fat, but not fructose, increased in the US between 1970 and 2009: analysis of the USDA food availability data system

PubMed Central

2013-01-01

Background Obesity rates in the United States have risen consistently over the last four decades, increasing from about 13% of the population in 1970 to more than 34% in 2009. Dietary fructose has been blamed as a possible contributor to the obesity increase, although the consumption pattern of fructose and other key nutrients during this 40 year period remains a topic of debate. Therefore, we analyzed the USDA Loss-Adjusted Food Availability Database in combination with the USDA Nutrient Database for Standard Reference (Release 24) to determine whether fructose consumption in the US has increased sufficiently to be a casual factor in the rise in obesity prevalence. Methods Per capita loss-adjusted food availability data for 132 individual food items were compiled and analyzed. Nutrient profiles for each of these foods were used to determine the availability of energy as well as macronutrients and monosaccharides during the years 1970-2009. The percent change in energy from food groups and individual nutrients was determined by using the year 1970 as the baseline and area-under-the-curve analysis of food trends. Results Our findings indicate that during this 40 year period the percent change in total energy availability increased 10.7%, but that the net change in total fructose availability was 0%. Energy available from total glucose (from all digestible food sources) increased 13.0%. Furthermore, glucose availability was more than 3-times greater than fructose. Energy available from protein, carbohydrate and fat increased 4.7%, 9.8% and 14.6%, respectively. Conclusions These data suggest that total fructose availability in the US did not increase between 1970 and 2009 and, thus, was unlikely to have been a unique causal factor in the increased obesity prevalence. We conclude that increased total energy intake, due to increased availability of foods providing glucose (primarily as starch in grains) and fat, to be a significant contributor to increased obesity in

Food Availability in School Stores in Seoul, South Korea After Implementation of Food- and Nutrient-Based Policies.

PubMed

Choi, Seul Ki; Frongillo, Edward A; Blake, Christine E; Thrasher, James F

2017-07-01

To improve school store food environments, the South Korean government implemented 2 policies restricting unhealthy food sales in school stores. A food-based policy enacted in 2007 restricts specific food sales (soft drinks); and a nutrient-based policy enacted in 2009 restricts energy-dense and nutrient-poor (EDNP) food sales. The purpose of the study was to assess how the 2 policies have changed the school store food environment. Foods sold in school stores in Seoul, South Korea were observed before (2006, 15 stores) and after (2013, 12 stores) implementation of the school store policies. Food availability in school stores in 2006 and 2013 was compared and EDNP food availability in 2013 was examined. When controlling the total number of foods sold in school stores and school characteristics, the mean number of soft drinks sold in a school store in 2013 (0.3 items) was significantly lower than in 2006 (1.9 items, p = .032). Soft drinks were still available in 50% of school stores observed in 2013, with all school stores selling EDNP foods in 2013. South Korean policies have had a modest influence on availability of unhealthy school store foods. Alternative strategies to improve school store food environments are needed. © 2017, American School Health Association.

Evaluation of forest snow processes models (SnowMKIP2)

Treesearch

Nick Rutter; Richard Essery; John Pomeroy; Nuria Altimir; Kostas Andreadis; Ian Baker; Alan Barr; Paul Bartlett; Aaron Boone; Huiping Deng; Herve Douville; Emanuel Dutra; Kelly Elder; others

2009-01-01

Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation...

The availability and cost of healthier food alternatives.

PubMed

Jetter, Karen M; Cassady, Diana L

2006-01-01

Many people, especially low-income consumers, do not successfully follow dietary recommendations to eat more whole grains and less fat and added sugar. The food environment may have a significant impact on the choice by low-income consumers to eat healthier foods, as both the availability and price of healthier food items may limit their ability to eat a healthier diet. We investigated the cost and availability of a standard market basket of foods, and a healthier basket that included low-fat meat and dairy and whole grain products. Market-basket surveys were conducted in 25 stores in Los Angeles and Sacramento. Stores were selected from neighborhoods that were varied by income and surveyed three times from September 2003 to June 2004. The average cost of a standard market basket (based on the U.S. Department of Agriculture's Thrifty Food Plan [TFP]) and a healthier market basket was calculated from these prices and compared using a standard t-test to determine if they were significantly different from each other. The analysis was conducted in 2005. In neighborhoods served by smaller grocery stores, access to whole-grain products, low-fat cheeses, and ground meat with <10% fat is limited. Among all items that were unavailable, 64% were in small grocery stores. For the 2-week shopping list, the average TFP market-basket cost was $194, and the healthier market-basket cost was $230. The average cost of the healthier market basket was more expensive by $36 due to higher costs of whole grains, lean ground beef, and skinless poultry. The higher cost of the healthier basket is equal to about 35% to 40% of low-income consumers' food budgets of $2410 a year. The lack of availability in small grocery stores located in low-income neighborhoods, and the higher cost of the healthier market basket may be a deterrent to eating healthier among very low-income consumers. Public policies should take the food environment into account in order to develop successful strategies to

Applications systems verification and transfer project. Volume 1: Operational applications of satellite snow cover observations: Executive summary. [usefulness of satellite snow-cover data for water yield prediction

NASA Technical Reports Server (NTRS)

Rango, A.

1981-01-01

Both LANDSAT and NOAA satellite data were used in improving snowmelt runoff forecasts. When the satellite snow cover data were tested in both empirical seasonal runoff estimation and short term modeling approaches, a definite potential for reducing forecast error was evident. A cost benefit analysis run in conjunction with the snow mapping indicated a $36.5 million annual benefit accruing from a one percent improvement in forecast accuracy using the snow cover data for the western United States. The annual cost of employing the system would be $505,000. The snow mapping has proven that satellite snow cover data can be used to reduce snowmelt runoff forecast error in a cost effective manner once all operational satellite data are available within 72 hours after acquisition. Executive summaries of the individual snow mapping projects are presented.

Availability of limited service food outlets surrounding schools in British Columbia.

PubMed

Black, Jennifer L; Day, Meghan

2012-06-05

The purpose of this study was to provide a descriptive profile of the availability of limited service food outlets surrounding public schools in British Columbia, Canada. Data from the 2010 Canadian Business Data Files were used to identify limited service food outlets including fast food outlets, beverage and snack food stores, delis and convenience stores. The number of food outlets within 800 metres of 1,392 public schools and the distance from schools to the nearest food outlets were assessed. Multivariate regression models examined the associations between food outlet availability and school-level characteristics. In 2010, over half of the public schools in BC (54%) were located within a 10-12 minute walk from at least one limited service food outlet. The median closest distance to a food outlet was just over 1 km (1016 m). Schools comprised of students living in densely populated urban neighbourhoods and neighbourhoods characterized by lower socio-economic status were more likely to have access to limited service food outlets within walking distance. After adjusting for school-level median family income and population density, larger schools had higher odds of exposure to food vendors compared to schools with fewer students. The availability of and proximity to limited service food outlets vary widely across schools in British Columbia and school-level characteristics are significantly associated with food outlet availability. Additional research is needed to understand how food environment exposures inside and surrounding schools impact students' attitudes, food choices and dietary quality.

Snow In the Sahara

NASA Image and Video Library

2017-12-08

In December 2016, snow fell in the Sahara for the first time since 1979. In 1984, the charitable supergroup Band Aid sang: “There won’t be snow in Africa this Christmas time.” In fact, it does snow in Africa at high elevations. Kilimanjaro has long had a cap of snow and ice, though it has been shrinking. Skiiers travel for natural and manufactured snow in the Atlas Mountains of Morocco and Algeria, as well as a few spots in South Africa and Lesotho. Nonetheless, snow on the edge of the Sahara Desert is rare. On December 19, 2016, snow fell on the Algerian town of Ain Sefra, which is sometimes referred to as the “gateway to the desert.” The town of roughly 35,000 people sits between the Atlas Mountains and the northern edge of the Sahara. The last recorded snowfall in Ain Sefra occurred in February 1979. The Enhanced Thematic Mapper Plus (ETM+) on the Landsat 7 satellite acquired this natural-color image of snow in North Africa on December 19, 2016. This scene shows an area near the border of Morocco and Algeria, south of the city of Bouarfa and southwest of Ain Sefra. Though the news has been dominated by snow in the Saharan city, a review of several years of satellite data suggests that snow is also pretty rare in this section of the Atlas range. Read more: go.nasa.gov/2hIH4Xe NASA Earth Observatory image by Joshua Stevens, using Landsat data from the U.S. Geological Survey. Caption by Mike Carlowicz. b>NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

To eat or not to eat: Effects of food availability on reward system activity during food picture viewing.

PubMed

Blechert, Jens; Klackl, Johannes; Miedl, Stephan F; Wilhelm, Frank H

2016-04-01

Neuroimaging studies have started to explore the role of food characteristics (e.g., calorie-content) and psychological factors (e.g., restrained eating, craving) for the human appetitive system, motivated by the significant health implications of food-choice, overeating and overweight/obesity. However, one key aspect of modern food environments, food availability, especially of high energy foods, has not been adequately modeled in experimental research. Food that is immediately available for consumption could elicit stronger reward system activity and associated cognitive control than food that is not currently available for consumption and this could vary as a function of energy density. To examine this question, 32 healthy participants (16 women) underwent functional magnetic resonance imaging while passively viewing available foods - i.e. foods that could be eaten during and after the experiment - and unavailable foods of either high or low-caloric density in a 2 × 2 design. Available compared to unavailable foods elicited higher palatability ratings as well as stronger neural activation in the orbitofrontal cortex (OFC), amygdala, and left caudate nucleus as well as in the anterior cingulate cortex (ACC) - and thus structures implicated in reward and appetitive motivation as well as cognitive control, respectively. Availability effects in the caudate were mainly attributable to the high calorie condition (availability × calorie density interaction). These neuroimaging results support the contention that foods are particularly rewarding when immediately available and particularly so when high in caloric density. Thus, our results are consistent with health promoting interventions utilizing a nudging approach, i.e. aiming at decreasing accessibility of high calorie and increasing accessibility of low calorie foods in daily life. Results also imply that controlling/manipulating food availability may be an important methodological aspect in neuroscientific

Wet Snow Mapping in Southern Ontario with Sentinel-1A Observations

NASA Astrophysics Data System (ADS)

Chen, H.; Kelly, R. E. J.

2017-12-01

Wet snow is defined as snow with liquid water present in an ice-water mix. It is can be an indicator for the onset of the snowmelt period. Knowledge about the extent of wet snow area can be of great importance for the monitoring of seasonal snowmelt runoff with climate-induced changes in snowmelt duration having implications for operational hydrological and ecological applications. Spaceborne microwave remote sensing has been used to observe seasonal snow under all-weather conditions. Active microwave observations of snow at C-band are sensitive to wet snow due to the high dielectric contrast with non-wet snow surfaces and synthetic aperture radar (SAR) is now openly available to identify and map the wet snow areas globally at relatively fine spatial resolutions ( 100m). In this study, a semi-automated workflow is developed from the change detection method of Nagler et al. (2016) using multi-temporal Sentinel-1A (S1A) dual-polarization observations of Southern Ontario. Weather station data and visible-infrared satellite observations are used to refine the wet snow area estimates. Wet snow information from National Operational Hydrologic Remote Sensing Center (NOHRSC) is used to compare with the S1A estimates. A time series of wet snow maps shows the variations in backscatter from wet snow on a pixel basis. Different land cover types in Southern Ontario are assessed with respect to their impacts on wet snow estimates. While forests and complex land surfaces can impact the ability to map wet snow, the approach taken is robust and illustrates the strong sensitivity of the approach to wet snow backscattering characteristics. The results indicate the feasibility of the change detection method on non-mountainous large areas and address the usefulness of Sentinel-1A data for wet snow mapping.

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?

Estimating Snow Water Storage in North America Using CLM4, DART, and Snow Radiance Data Assimilation

NASA Technical Reports Server (NTRS)

Kwon, Yonghwan; Yang, Zong-Liang; Zhao, Long; Hoar, Timothy J.; Toure, Ally M.; Rodell, Matthew

2016-01-01

This paper addresses continental-scale snow estimates in North America using a recently developed snow radiance assimilation (RA) system. A series of RA experiments with the ensemble adjustment Kalman filter are conducted by assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature T(sub B) at 18.7- and 36.5-GHz vertical polarization channels. The overall RA performance in estimating snow depth for North America is improved by simultaneously updating the Community Land Model, version 4 (CLM4), snow/soil states and radiative transfer model (RTM) parameters involved in predicting T(sub B) based on their correlations with the prior T(sub B) (i.e., rule-based RA), although degradations are also observed. The RA system exhibits a more mixed performance for snow cover fraction estimates. Compared to the open-loop run (0.171m RMSE), the overall snow depth estimates are improved by 1.6% (0.168m RMSE) in the rule-based RA whereas the default RA (without a rule) results in a degradation of 3.6% (0.177mRMSE). Significant improvement of the snow depth estimates in the rule-based RA as observed for tundra snow class (11.5%, p < 0.05) and bare soil land-cover type (13.5%, p < 0.05). However, the overall improvement is not significant (p = 0.135) because snow estimates are degraded or marginally improved for other snow classes and land covers, especially the taiga snow class and forest land cover (7.1% and 7.3% degradations, respectively). The current RA system needs to be further refined to enhance snow estimates for various snow types and forested regions.

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

NASA Astrophysics Data System (ADS)

Rikiishi, K.

2008-12-01

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

Unexpected Patterns in Snow and Dirt

NASA Astrophysics Data System (ADS)

Ackerson, Bruce J.

2018-01-01

For more than 30 years, Albert A. Bartlett published "Thermal patterns in the snow" in this journal. These are patterns produced by heat sources underneath the snow. Bartlett's articles encouraged me to pay attention to patterns in snow and to understanding them. At winter's end the last snow becomes dirty and is heaped into piles. This snow comes from the final clearing of sidewalks and driveways. The patterns observed in these piles defied my intuition. This melting snow develops edges where dirt accumulates, in contrast to ice cubes, which lose sharp edges and become more spherical upon melting. Furthermore, dirt absorbs more radiation than snow and yet doesn't melt and round the sharp edges of snow, where dirt accumulates.

Impact of the snow cover scheme on snow distribution and energy budget modeling over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xie, Zhipeng; Hu, Zeyong; Xie, Zhenghui; Jia, Binghao; Sun, Genhou; Du, Yizhen; Song, Haiqing

2018-02-01

This paper presents the impact of two snow cover schemes (NY07 and SL12) in the Community Land Model version 4.5 (CLM4.5) on the snow distribution and surface energy budget over the Tibetan Plateau. The simulated snow cover fraction (SCF), snow depth, and snow cover days were evaluated against in situ snow depth observations and a satellite-based snow cover product and snow depth dataset. The results show that the SL12 scheme, which considers snow accumulation and snowmelt processes separately, has a higher overall accuracy (81.8%) than the NY07 (75.8%). The newer scheme performs better in the prediction of overall accuracy compared with the NY07; however, SL12 yields a 15.1% underestimation rate while NY07 overestimated the SCF with a 15.2% overestimation rate. Both two schemes capture the distribution of the maximum snow depth well but show large positive biases in the average value through all periods (3.37, 3.15, and 1.48 cm for NY07; 3.91, 3.52, and 1.17 cm for SL12) and overestimate snow cover days compared with the satellite-based product and in situ observations. Higher altitudes show larger root-mean-square errors (RMSEs) in the simulations of snow depth and snow cover days during the snow-free period. Moreover, the surface energy flux estimations from the SL12 scheme are generally superior to the simulation from NY07 when evaluated against ground-based observations, in particular for net radiation and sensible heat flux. This study has great implications for further improvement of the subgrid-scale snow variations over the Tibetan Plateau.

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.

Polar View Snow Service- Operational Snow Cover Mapping for Downstream Runoff Modeling and Hydropower Predictions

NASA Astrophysics Data System (ADS)

Bach, Heike; Appel, Florian; Rust, Felix; Mauser, Wolfram

2010-12-01

Information on snow cover and snow properties are important for hydrology and runoff modelling. Frequent updates of snow cover observation, especially for areas characterized by short-term snow dynamics, can help to improve water balance and discharge calculations. Within the GMES service element Polar View, VISTA offers a snow mapping service for Central Europe since several years [1, 2]. We outline the use of this near-real- time product for hydrological applications in Alpine environment. In particular we discuss the integration of the Polar View product into a physically based hydrological model (PROMET). This allows not only the provision of snow equivalent values, but also enhances river runoff modelling and its use in hydropower energy yield prediction. The GMES snow products of Polar View are thus used in a downstream service for water resources management, providing information services for renewable energy suppliers and energy traders.

Using crowdsourced web content for informing water systems operations in snow-dominated catchments

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Castelletti, Andrea; Fedorov, Roman; Fraternali, Piero

2016-12-01

Snow is a key component of the hydrologic cycle in many regions of the world. Despite recent advances in environmental monitoring that are making a wide range of data available, continuous snow monitoring systems that can collect data at high spatial and temporal resolution are not well established yet, especially in inaccessible high-latitude or mountainous regions. The unprecedented availability of user-generated data on the web is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatiotemporally dense. In this paper, we contribute a novel crowdsourcing procedure for extracting snow-related information from public web images, either produced by users or generated by touristic webcams. A fully automated process fetches mountain images from multiple sources, identifies the peaks present therein, and estimates virtual snow indexes representing a proxy of the snow-covered area. Our procedure has the potential for complementing traditional snow-related information, minimizing costs and efforts for obtaining the virtual snow indexes and, at the same time, maximizing the portability of the procedure to several locations where such public images are available. The operational value of the obtained virtual snow indexes is assessed for a real-world water-management problem, the regulation of Lake Como, where we use these indexes for informing the daily operations of the lake. Numerical results show that such information is effective in extending the anticipation capacity of the lake operations, ultimately improving the system performance.

Snow measurement Using P-Band Signals of Opportunity Reflectometry

NASA Astrophysics Data System (ADS)

Shah, R.; Yueh, S. H.; Xu, X.; Elder, K.

2017-12-01

Snow water storage in land is a critical parameter of the water cycle. In this study, we develop methods for estimating reflectance from bistatic scattering of digital communication Signals of Opportunity (SoOp) across the available microwave spectrum from VHF to Ka band and show results from proof-of-concept experiments at the Fraser Experimental Forest, Colorado to acquire measurements to relate the SoOp phase and reflectivity to a snow-covered soil surface. The forward modeling of this scenario will be presented and multiple sensitivities were conducted. Available SoOp receiver data along with a network of in situ sensor measurements collected since January 2016 will be used to validate theoretical modeling results. In the winter season of 2016 and 2017, we conducted a field experiment using VHF/UHF-band illuminating sources to detect SWE and surface reflectivity. The amplitude of the reflectivity showed sensitivity to the wetness of snow pack and ground reflectivity while the phase showed sensitivity to SWE. This use of this concept can be helpful to measure the snow water storage in land globally.

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

PubMed

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

2014-11-06

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

Retail Food Availability, Obesity, and Cigarette Smoking in Rural Communities

ERIC Educational Resources Information Center

Hosler, Akiko S.

2009-01-01

Context: Disparities in the availability of nutritionally important foods and their influence on health have been studied in US urban communities. Purpose: To assess the availability of selected retail foods and cigarettes, and explore ecologic relationships of the availability with obesity and smoking in rural communities. Methods: Inventories of…

Response of snow-dependent hydrologic extremes to continued global warming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diffenbaugh, Noah; Scherer, Martin; Ashfaq, Moetasim

2012-01-01

Snow accumulation is critical for water availability in the Northern Hemisphere1,2, raising concern that global warming could have important impacts on natural and human systems in snow-dependent regions1,3. Although regional hydrologic changes have been observed (for example, refs 1,3 5), the time of emergence of extreme changes in snow accumulation and melt remains a key unknown for assessing climate- change impacts3,6,7. We find that the CMIP5 global climate model ensemble exhibits an imminent shift towards low snow years in the Northern Hemisphere, with areas of western North America, northeastern Europe and the Greater Himalaya showing the strongest emergence during themore » near- termdecadesandat2 Cglobalwarming.Theoccurrenceof extremely low snow years becomes widespread by the late twenty-first century, as do the occurrences of extremely high early-season snowmelt and runoff (implying increasing flood risk), and extremely low late-season snowmelt and runoff (implying increasing water stress). Our results suggest that many snow-dependent regions of the Northern Hemisphere are likely to experience increasing stress from low snow years within the next three decades, and from extreme changes in snow-dominated water resources if global warming exceeds 2 C above the pre-industrial baseline.« less

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).

76 FR 51935 - Availability to School Food Authorities of Nutrition Information and Ingredient Lists for Foods...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-19

... DEPARTMENT OF AGRICULTURE Food and Nutrition Service Availability to School Food Authorities of Nutrition Information and Ingredient Lists for Foods Used in School Food Service: Request for Information AGENCY: Food and Nutrition Service, USDA. ACTION: Request for information from the public. SUMMARY...

School wellness policies and foods and beverages available in schools.

PubMed

Hood, Nancy E; Colabianchi, Natalie; Terry-McElrath, Yvonne M; O'Malley, Patrick M; Johnston, Lloyd D

2013-08-01

Since 2006-2007, education agencies (e.g., school districts) participating in U.S. federal meal programs are required to have wellness policies. To date, this is the only federal policy that addresses foods and beverages sold outside of school meals (in competitive venues). To examine the extent to which federally required components of school wellness policies are associated with availability of foods and beverages in competitive venues. Questionnaire data were collected in 2007-2008 through 2010-2011 school years from 892 middle and 1019 high schools in nationally representative samples. School administrators reported the extent to which schools had required wellness policy components (goals, nutrition guidelines, implementation plan/person responsible, stakeholder involvement) and healthier and less-healthy foods and beverages available in competitive venues. Analyses were conducted in 2012. About one third of students (31.8%) were in schools with all four wellness policy components. Predominantly white schools had higher wellness policy scores than other schools. After controlling for school characteristics, higher wellness policy scores were associated with higher availability of low-fat and whole-grain foods and lower availability of regular-fat/sugared foods in middle and high schools. In middle schools, higher scores also were associated with lower availability of 2%/whole milk. High schools with higher scores also had lower sugar-sweetened beverage availability and higher availability of 1%/nonfat milk, fruits/vegetables, and salad bars. Because they are associated with lower availability of less-healthy and higher availability of healthier foods and beverages in competitive venues, federally required components of school wellness policies should be encouraged in all schools. Copyright © 2013 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Food availability and foraging near human developments by black bears

USGS Publications Warehouse

Merkle, Jerod A.; Robinson, Hugh S.; Krausman, Paul R.; Alaback, Paul B.

2013-01-01

Understanding the relationship between foraging ecology and the presence of human-dominated landscapes is important, particularly for American black bears (Ursus americanus), which sometimes move between wildlands and urban areas to forage. The food-related factors influencing this movement have not been explored, but can be important for understanding the benefits and costs to black bear foraging behavior and the fundamental origins of bear conflicts. We tested whether the scarcity of wildland foods or the availability of urban foods can explain when black bears forage near houses, examined the extent to which male bears use urban areas in comparison to females, and identified the most important food items influencing bear movement into urban areas. We monitored 16 collared black bears in and around Missoula, Montana, during 2009 and 2010, while quantifying the rate of change in green vegetation and the availability of 5 native berry-producing species outside the urban area, the rate of change in green vegetation, and the availability of apples and garbage inside the urban area. We used parametric time-to-event models in which an event was a bear location collected within 100 m of a house. We also visited feeding sites located near houses and quantified food items bears had eaten. The probability of a bear being located near a house was 1.6 times higher for males, and increased during apple season and the urban green-up. Fruit trees accounted for most of the forage items at urban feeding sites (49%), whereas wildland foods composed <10%. Black bears foraged on human foods near houses even when wildland foods were available, suggesting that the absence of wildland foods may not influence the probability of bears foraging near houses. Additionally, other attractants, in this case fruit trees, appear to be more important than the availability of garbage in influencing when bears forage near houses.

Simulating the Dependence of Aspen on Redistributed Snow

NASA Astrophysics Data System (ADS)

Soderquist, B.; Kavanagh, K.; Link, T. E.; Seyfried, M. S.; Winstral, A. H.

2013-12-01

In mountainous regions across the western USA, the distribution of aspen (Populus tremuloides) is often directly 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) in southwest Idaho provides a unique opportunity to study the relationship between aspen and redistributed snow. Within the RCEW, the total amount of precipitation has not changed in the past 50 years, but there are sharp declines in the percentage of the precipitation falling as snow. As shifts in the distribution of available moisture continue, future trends in aspen net primary productivity (NPP) remain uncertain. In order to assess the importance of snowdrift subsidies, NPP of three aspen stands was simulated at sites spanning elevational and precipitation gradients using the biogeochemical process model BIOME-BGC. At the aspen site experiencing the driest climate and lowest amount of precipitation from snow, approximately 400 mm of total precipitation was measured from November to March of 2008. However, peak measured snow water equivalent (SWE) held in drifts directly upslope of this stand was approximately 2100 mm, 5 times more moisture than the uniform winter precipitation layer initially assumed by BIOME-BGC. BIOME-BGC simulations in dry years forced by adjusted precipitation data resulted in NPP values approximately 30% higher than simulations assuming a uniform precipitation layer. Using BIOME-BGC and climate data from 1985-2011, the relationship between simulated NPP and measured basal area increments (BAI) improved after accounting for redistributed snow, indicating increased simulation representation. In addition to improved simulation capabilities, soil moisture data, diurnal branch water potential, and stomatal conductance observations at each site detail the use of soil moisture in the rooting zone and the onset

Iron snow in the Martian core?

NASA Astrophysics Data System (ADS)

Davies, Christopher J.; Pommier, Anne

2018-01-01

The decline of Mars' global magnetic field some 3.8-4.1 billion years ago is thought to reflect the demise of the dynamo that operated in its liquid core. The dynamo was probably powered by planetary cooling and so its termination is intimately tied to the thermochemical evolution and present-day physical state of the Martian core. Bottom-up growth of a solid inner core, the crystallization regime for Earth's core, has been found to produce a long-lived dynamo leading to the suggestion that the Martian core remains entirely liquid to this day. Motivated by the experimentally-determined increase in the Fe-S liquidus temperature with decreasing pressure at Martian core conditions, we investigate whether Mars' core could crystallize from the top down. We focus on the "iron snow" regime, where newly-formed solid consists of pure Fe and is therefore heavier than the liquid. We derive global energy and entropy equations that describe the long-timescale thermal and magnetic history of the core from a general theory for two-phase, two-component liquid mixtures, assuming that the snow zone is in phase equilibrium and that all solid falls out of the layer and remelts at each timestep. Formation of snow zones occurs for a wide range of interior and thermal properties and depends critically on the initial sulfur concentration, ξ0. Release of gravitational energy and latent heat during growth of the snow zone do not generate sufficient entropy to restart the dynamo unless the snow zone occupies at least 400 km of the core. Snow zones can be 1.5-2 Gyrs old, though thermal stratification of the uppermost core, not included in our model, likely delays onset. Models that match the available magnetic and geodetic constraints have ξ0 ≈ 10% and snow zones that occupy approximately the top 100 km of the present-day Martian core.

Evaluation of snow cover and snow depth on the Qinghai-Tibetan Plateau derived from passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Dai, Liyun; Che, Tao; Ding, Yongjian; Hao, Xiaohua

2017-08-01

Snow cover on the Qinghai-Tibetan Plateau (QTP) plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW) remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow depth across the QTP, new algorithms

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

Household availability of ultra-processed foods and obesity in nineteen European countries.

PubMed

Monteiro, Carlos Augusto; Moubarac, Jean-Claude; Levy, Renata Bertazzi; Canella, Daniela Silva; Louzada, Maria Laura da Costa; Cannon, Geoffrey

2018-01-01

To assess household availability of NOVA food groups in nineteen European countries and to analyse the association between availability of ultra-processed foods and prevalence of obesity. Ecological, cross-sectional study. Europe. Estimates of ultra-processed foods calculated from national household budget surveys conducted between 1991 and 2008. Estimates of obesity prevalence obtained from national surveys undertaken near the budget survey time. Across the nineteen countries, median average household availability amounted to 33·9 % of total purchased dietary energy for unprocessed or minimally processed foods, 20·3 % for processed culinary ingredients, 19·6 % for processed foods and 26·4 % for ultra-processed foods. The average household availability of ultra-processed foods ranged from 10·2 % in Portugal and 13·4 % in Italy to 46·2 % in Germany and 50·4 % in the UK. A significant positive association was found between national household availability of ultra-processed foods and national prevalence of obesity among adults. After adjustment for national income, prevalence of physical inactivity, prevalence of smoking, measured or self-reported prevalence of obesity, and time lag between estimates on household food availability and obesity, each percentage point increase in the household availability of ultra-processed foods resulted in an increase of 0·25 percentage points in obesity prevalence. The study contributes to a growing literature showing that the consumption of ultra-processed foods is associated with an increased risk of diet-related non-communicable diseases. Its findings reinforce the need for public policies and actions that promote consumption of unprocessed or minimally processed foods and make ultra-processed foods less available and affordable.

Remote sensing: Snow monitoring tool for today and tomorrow

NASA Technical Reports Server (NTRS)

Rango, A.

1977-01-01

Various types of remote sensing are now available or will be in the future for snowpack monitoring. Aircraft reconnaissance is now used in a conventional manner by various water resources agencies to obtain information on snowlines, depth, and melting of the snowpack for forecasting purposes. The use of earth resources satellites for mapping snowcovered area, snowlines, and changes in snowcover during the spring has increased during the last five years. Gamma ray aircraft flights, although confined to an extremely low altitude, provide a means for obtaining valuable information on snow water equivalent. The most recently developed remote sensing technology for snow, namely, microwave monitoring, has provided initial results that may eventually allow us to infer snow water equivalent or depth, snow wetness, and the hydrologic condition of the underlying soil.

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.

The ASMEx snow slab experiment: snow microwave radiative transfer (SMRT) model evaluation

NASA Astrophysics Data System (ADS)

Sandells, Melody; Löwe, Henning; Picard, Ghislain; Dumont, Marie; Essery, Richard; Floury, Nicolas; Kontu, Anna; Lemmetyinen, Juha; Maslanka, William; Mätzler, Christian; Morin, Samuel; Wiesmann, Andreas

2017-04-01

A major uncertainty in snow microwave modelling to date has been the treatment of the snow microstructure. Although observations of microstructural parameters such as the optical grain diameter, specific surface area and correlation length have improved drastically over the last few years, scale factors have been used to derive the parameters needed in microwave emission models from these observations. Previous work has shown that a major difference between electromagnetic models of scattering coefficients is due to the specific snow microstructure models used. The snow microwave radiative transfer model (SMRT) is a new model developed to advance understanding of the role of microstructure and isolate different assumptions in existing microwave models that collectively hinder interpretation of model intercomparison studies. SMRT is implemented in Python and is modular, thus allows switching between different representations in its various components. Here, the role of microstructure is examined with the Improved Born Approximation electromagnetic model. The model is evaluated against scattering and absorption coefficients derived from radiometer measurements of snow slabs taken as part of the Arctic Snow Microstructure Experiment (ASMEx), which took place in Sodankylä, Finland over two seasons. Microtomography observations of slab samples were used to determine parameters for five microstructure models: spherical, exponential, sticky hard sphere, Teubner-Strey and Gaussian random field. SMRT brightness temperature simulations are also compared with radiometric observations of the snow slabs over a reflector plate and an absorber substrate. Agreement between simulations and observations is generally good except for slabs that are highly anisotropic.

Snow Depth Depicted on Mt. Lyell by NASA Airborne Snow Observatory

NASA Image and Video Library

2013-05-02

A natural color image of Mt. Lyell, the highest point in the Tuolumne River Basin top image is compared with a three-dimensional color composite image of Mt. Lyell from NASA Airborne Snow Observatory depicting snow depth bottom image.

Wetlands or aquatic ape? Availability of food resources.

PubMed

Ellis, D V

1993-01-01

A human evolutionary scenario including an ape inhabiting marine wetlands is rational in a number of contexts. The concept is viable ecologically due to the availability of abundant animal foods in a variety of habitats ranging from mangrove forests to coral reefs. The food resources include mollusks, crustacea and fish abundant in wet zones and pools between high and low tide levels. There is seasonal abundance of swarming marsh insects, turtles, eggs and chicks of colonial birds, and occasional beached and dying marine mammals. Some of these foods would provide an enriched source of polyunsaturated essential fatty acids needed for brain development, and thus allow a spiral of increasing brain development, tool utilisation for better food gathering, and vocal communication for group action. The concept is viable also in terms of availability of the ape-human stock in the African Rift Valley, isolated from montane forests during the late Pliocene, and as an adaptive explanation for many of the species-specific human characters not found in other ground living primates.

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.

Comparing different snow products to assess spatio-temporal snow cover patterns in the Central Taurus Mountains, Turkey

NASA Astrophysics Data System (ADS)

Sturm, K.; Helmschrot, J.

2013-12-01

Snow and its spatial and temporal patterns are important for catchment hydrology in the semi-arid eastern Mediterranean. Since most of the annual rainfall is stored as snow during winter and released during drier conditions in spring and summer, downstream regions of the Taurus Mountains relying on snow water temporarily stored in reservoirs for agricultural use are heavily dependent on the timing of snowmelt discharge. Runoff is controlled by the amount of accumulated snow, its distribution, and the climatic conditions controlling spring snowmelt. Thus, knowledge about spatial and temporal snow cover dynamics is essential for sustainable water resources management. The lack of observations in high-altitude regions reinforces the application of different snow products for a better assessment of spatio-temporal snow cover patterns. To better assess the quality of such products, simulated daily snow cover and EO-based snow cover products were compared for the Egribuk subcatchment, in the Central Taurus Mountains, Turkey. Daily information on snow cover, depths, and snow water equivalent was derived from distributed hydrological modeling using the J2000 model. Furthermore, 8-day MODIS snow cover data from Terra (MOD10A2) and Aqua (MYD10A2) satellites at a spatial resolution of 500 m were synchronized to receive cloud-free images. From this effort, 253 images covering the period between 07/04/2002 and 12/27/2007 were used for further analyses. The products were analyzed individually to determine the number of snow-covered days in relation to freezing days, spring snowmelt onsets, and temporal patterns, reflecting the effect of altitude on the percentage snow-covered area (SCA) along a topographic gradient at various time-steps. Monthly and 8-day spatial patterns of a single snow season were also examined. When SCA peaks at all altitudes, in February and March, the results of both products show a good agreement regarding SCA extent. In contrast, the extent of SCA

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.

Snow Water Equivalent Retrieval By Markov Chain Monte Carlo Based on Memls and Hut Snow Emission Model

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Vanderjagt, B. J.

2014-12-01

The Markov chain Monte Carlo (MCMC) method had been proved to be successful in snow water equivalent retrieval based on synthetic point-scale passive microwave brightness temperature (TB) observations. This method needs only general prior information about distribution of snow parameters, and could estimate layered snow properties, including the thickness, temperature, density and snow grain size (or exponential correlation length) of each layer. In this study, the multi-layer HUT (Helsinki University of Technology) model and the MEMLS (Microwave Emission Model of Layered Snowpacks) will be used as observation models to assimilate the observed TB into snow parameter prediction. Previous studies had shown that the multi-layer HUT model tends to underestimate TB at 37 GHz for deep snow, while the MEMLS does not show sensitivity of model bias to snow depth. Therefore, results using HUT model and MEMLS will be compared to see how the observation model will influence the retrieval of snow parameters. The radiometric measurements at 10.65, 18.7, 36.5 and 90 GHz at Sodankyla, Finland will be used as MCMC input, and the statistics of all snow property measurement will be used to calculate the prior information. 43 dry snowpits with complete measurements of all snow parameters will be used for validation. The entire dataset are from NorSREx (Nordic Snow Radar Experiment) experiments carried out by Juha Lemmetyinen, Anna Kontu and Jouni Pulliainen in FMI in 2009-2011 winters, and continued two more winters from 2011 to Spring of 2013. Besides the snow thickness and snow density that are directly related to snow water equivalent, other parameters will be compared with observations, too. For thin snow, the previous studies showed that influence of underlying soil is considerable, especially when the soil is half frozen with part of unfrozen liquid water and part of ice. Therefore, this study will also try to employ a simple frozen soil permittivity model to improve the

[Food and beverages available in automatic food dispensers in health care facilities of the Portugal North Health Region].

PubMed

Rodrigues, Filipa Gomes; Ramos, Elisabete; Freitas, Mário; Neto, Maria

2010-01-01

Patients and health staff frequently need to stay in health care facilities for quite a long time. Therefore, it's necessary to create the conditions that allow the ingestion of food during those periods, namely through the existence of automatic food dispensers. However, the available food and beverages might not always be compatible with a healthy diet. The aim of this work was to evaluate if the food and beverages available in automatic food dispensers in public Ambulatory Care Facilities (ACF) and Hospitals of the Portugal North Health Region were contributing to a healthy diet, during the year of 2007. A questionnaire was elaborated and sent to the Coordinators of the Health Sub-Regions and to the Hospital Administrators. The questionnaire requested information about the existence of automatic food dispensers in the several departments of each health care facility, as well as which food and beverages were available and most sold. Afterwards, the pre-processing of the results involved the classification of the food and beverages in three categories: recommended, sometimes recommended and not recommended. The questionnaire reply ratio was 71% in ACF and 83% in Hospitals. Automatic food dispensers were available in all the Hospitals and 86.5% of ACF. It wasn't possible to acquire food in 37% of the health facility departments. These departments were all located in ACF. The more frequently available beverages in departments with automatic food dispensers were coffee, still water, tea, juices and nectars and soft drinks. Still water, coffee, yogurt, juices and nectars and soft drinks were reported as the most sold. The more frequently avaliable food items were chocolate, recommended cookies, not recommended cakes, recommended sandwiches and sometimes recommended croissants. The food items reported as being the most sold were recommended sandwiches, chocolate, recommended cookies, sometimes recommended croissants and not recommended cookies. The beverages in the

Snow Micro-Structure Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Micah Johnson, Andrew Slaughter

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:more » 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

Measuring Snow Liquid Water Content with Low-Cost GPS Receivers

PubMed Central

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

2014-01-01

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

Improving the Terrain-Based Parameter for the Assessment of Snow Redistribution in the Col du Lac Blanc Area and Comparisons with TLS Snow Depth Data

NASA Astrophysics Data System (ADS)

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

2014-05-01

Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns, but has failed to quantitatively describe the snow redistribution, and correlations with measured snow heights were poor. The objective of our research was to a) identify the sources of poor correlations between predicted and measured snow re-distribution and b) improve the parameters ability to qualitatively and quantitatively describe snow redistribution in our research area, the Col du Lac Blanc in the French Alps. The area is at an elevation of 2700 m and particularly suited for our study due to its constant wind direction and the availability of data from a meteorological station. Our work focused on areas with terrain edges of approximately 10 m height, and we worked with 1-2 m resolution digital terrain and snow surface data. We first compared the results of the terrain-based parameter calculations to measured snow-depths, obtained by high-accuracy terrestrial laser scan measurements. The results were similar to previous studies: The parameter was able to reproduce observed patterns in snow distribution, but regression analyses showed poor correlations between terrain-based parameter and measured snow-depths. We demonstrate how the correlations between measured and calculated snow heights improve if the parameter is calculated based on a snow surface model instead of a digital terrain model. We show how changing the parameter's search distance and how raster re-sampling and raster smoothing improve the results. To improve the parameter

Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Resolving Size Distribution of Black Carbon Internally Mixed With Snow: Impact on Snow Optical Properties and Albedo

NASA Astrophysics Data System (ADS)

He, Cenlin; Liou, Kuo-Nan; Takano, Yoshi

2018-03-01

We develop a stochastic aerosol-snow albedo model that explicitly resolves size distribution of aerosols internally mixed with various snow grains. We use the model to quantify black carbon (BC) size effects on snow albedo and optical properties for BC-snow internal mixing. Results show that BC-induced snow single-scattering coalbedo enhancement and albedo reduction decrease by a factor of 2-3 with increasing BC effective radii from 0.05 to 0.25 μm, while polydisperse BC results in up to 40% smaller visible single-scattering coalbedo enhancement and albedo reduction compared to monodisperse BC with equivalent effective radii. We further develop parameterizations for BC size effects for application to climate models. Compared with a realistic polydisperse assumption and observed shifts to larger BC sizes in snow, respectively, assuming monodisperse BC and typical atmospheric BC effective radii could lead to overestimates of 24% and 40% in BC-snow albedo forcing averaged over different BC and snow conditions.

A new perspective on John Snow's communicable disease theory.

PubMed

Winkelstein, W

1995-11-01

When John Snow undertook the studies of the cholera epidemic of 1854 in London, he was testing his theory of communicable disease, which had been enunciated in an oration delivered at the 80th anniversary of the Medical Society of London. Snow had been elected orator of the year for 1853 and, according to his biographer, had spent the better part of a year in preparation. The oration was titled, "On Continuous Molecular Changes, More Particularly in Their Relation to Epidemic Diseases." Although the text of this oration is readily available in the 1936 Commonwealth Fund facsimile reprint of Snow's more famous cholera studies, few modern epidemiologists are familiar with the work. In it, Snow lays out a theory which includes recognition that for each communicable disease there is a distinct and specific cause, that the causal agent is a living organism which is stable over many generations of propagation, that infection is necessary for communication to occur, and that the quantity of infectious material transmitted is increased by multiplication after infection to produce disease manifestations. Although Snow's theory is similar to Jacob Henle's formulations of a decade earlier, it is more precise, more comprehensive, and more explicit. On the basis of this work alone, Snow deserves broader recognition than he has received.

Spatial properties of snow cover in the Upper Merced River Basin: implications for a distributed snow measurement network

NASA Astrophysics Data System (ADS)

Bouffon, T.; Rice, R.; Bales, R.

2006-12-01

The spatial distributions of snow water equivalent (SWE) and snow depth within a 1, 4, and 16 km2 grid element around two automated snow pillows in a forested and open- forested region of the Upper Merced River Basin (2,800 km2) of Yosemite National Park were characterized using field observations and analyzed using binary regression trees. Snow surveys occurred at the forested site during the accumulation and ablation seasons, while at the open-forest site a survey was performed only during the accumulation season. An average of 130 snow depth and 7 snow density measurements were made on each survey, within the 4 km2 grid. Snow depth was distributed using binary regression trees and geostatistical methods using the physiographic parameters (e.g. elevation, slope, vegetation, aspect). Results in the forest region indicate that the snow pillow overestimated average SWE within the 1, 4, and 16 km2 areas by 34 percent during ablation, but during accumulation the snow pillow provides a good estimate of the modeled mean SWE grid value, however it is suspected that the snow pillow was underestimating SWE. However, at the open forest site, during accumulation, the snow pillow was 28 percent greater than the mean modeled grid element. In addition, the binary regression trees indicate that the independent variables of vegetation, slope, and aspect are the most influential parameters of snow depth distribution. The binary regression tree and multivariate linear regression models explain about 60 percent of the initial variance for snow depth and 80 percent for density, respectively. This short-term study provides motivation and direction for the installation of a distributed snow measurement network to fill the information gap in basin-wide SWE and snow depth measurements. Guided by these results, a distributed snow measurement network was installed in the Fall 2006 at Gin Flat in the Upper Merced River Basin with the specific objective of measuring accumulation and ablation

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.

A lee-side eddy and its influence on snow accumulation

NASA Astrophysics Data System (ADS)

Gerber, Franziska; Mott, Rebecca; Hoch, Sebastian W.; Lehning, Michael

2016-04-01

additional flow component around the eastern edge of Sattelhorn introduces a cross-loading component along the Sattelhorn ridge. Snow depth data is, however, only available for the slope and thus covers only the upper part of the eddy. Thus, this winter we will collect more complete snow depth data to reveal the overall influence of the eddy on snow accumulation.

What Does a Multilayer Canopy Model Tell Us About Our Current Understanding of Snow-Canopy Unloading?

NASA Astrophysics Data System (ADS)

McGowan, L. E.; Paw U, K. T.; Dahlke, H. E.

2017-12-01

In the Western U.S., future water resources depend on the forested mountain snowpack. The variations in and estimates of forest mountain snow volume are vital to projecting annual water availability; yet, snow forest processes are not fully known. Most snow models calculate snow-canopy unloading based on time, temperature, Leaf Area Index (LAI), and/or wind speed. While models crudely consider the canopy shape via LAI, current models typically do not consider the vertical canopy structure or varied energetics within multiple canopy layers. Vertical canopy structure influences the spatiotemporal distribution of snow, and therefore ultimately determines the degree and extent by which snow alters both the surface energy balance and water availability. Within the canopy both the snowpack and energetic exposures to the snowpack (wind, shortwave and longwave radiation, turbulent heat fluxes etc.) vary widely in the vertical. The water and energy balance in each layer is dependent on all other layers. For example, increased snow canopy content in the top of the canopy will reduce available shortwave radiation at the bottom and snow unloading in a mid-layer can cascade and remove snow from all the lower layers. We examined vertical interactions and structures of the forest canopy on the impact of unloading utilizing the Advanced Canopy-Atmosphere-Soil-Algorithm (ACASA), a multilayer soil-vegetation-atmosphere numerical model based on higher-order closure of turbulence equations. Our results demonstrate how a multilayer model can be used to elucidate the physical processes of snow unloading, and could help researchers better parameterize unloading in snow-hydrology models.

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

NASA Astrophysics Data System (ADS)

Koch, Franziska; Schmid, Lino; Prasch, Monika; Heilig, Achim; Eisen, Olaf; Schweizer, Jürg; Mauser, Wolfram

2015-04-01

The temporal evolution of Alpine snowpacks is important for assessing water supply, hydropower generation, flood predictions and avalanche forecasts. Especially in high mountain regions with an extremely varying topography, it is until now often difficult to derive continuous and non-destructive information on snow parameters. Since autumn 2012, we are running a new low-cost GPS (Global Positioning System) snow measurement experiment at the high alpine study site Weissfluhjoch (2450 m a.s.l.) in Switzerland. The globally and freely broadcasted GPS L1-band (1.57542 GHz) was continuously recorded with GPS antennas, which are installed at the ground surface underneath the snowpack. GPS raw data, containing carrier-to-noise power density ratio (C/N0) as well as elevation and azimuth angle information for each time step of 1 s, was stored and analyzed for all 32 GPS satellites. Since the dielectric permittivity of an overlying wet snowpack influences microwave radiation, the bulk volumetric liquid water content as well as daily melt-freeze cycles can be derived non-destructively from GPS signal strength losses and external snow height information. This liquid water content information is qualitatively in good accordance with meteorological and snow-hydrological data and quantitatively highly agrees with continuous data derived from an upward-looking ground-penetrating radar (upGPR) working in a similar frequency range. As a promising novelty, we combined the GPS signal strength data with upGPR travel-time information of active impulse radar rays to the snow surface and back from underneath the snow cover. This combination allows determining liquid water content, snow height and snow water equivalent from beneath the snow cover without using any other external information. The snow parameters derived by combining upGPR and GPS data are in good agreement with conventional sensors as e.g. laser distance gauges or snow pillows. As the GPS sensors are cheap, they can easily

Estimation of daily Snow Cover Area combining MODIS and LANDSAT information by using cellular automata

NASA Astrophysics Data System (ADS)

Pardo-Iguzquiza, Eulogio; Juan Collados Lara, Antonio; Pulido-Velazquez, David

2016-04-01

The snow availability in Alpine catchments is essential for the economy of these areas. It plays an important role in tourist development but also in the management of the Water Resources Snow is an important water resource in many river basins with mountains in the catchment area. The determination of the snow water equivalent requires the estimation of the evolution of the snow pack (cover area, thickness and snow density) along the time. Although there are complex physical models of the dynamics of the snow pack, sometimes the data available are scarce and a stochastic model like the cellular automata (CA) can be of great practical interest. CA can be used to model the dynamics of growth and wane of the snow pack. The CA is calibrated with historical data. This requires the determination of transition rules that are capable of modeling the evolution of the spatial pattern of snow cover area. Furthermore, CA requires the definition of states and neighborhoods. We have included topographical variables and climatological variables in order to define the state of each pixel. The evolution of snow cover in a pixel depends on its state, the state of the neighboring pixels and the transition rules. The calibration of the CA is done using daily MODIS data, available for the period 24/02/2002 to present with a spatial resolution of 500 m, and the LANDSAT information available with a sixteen-day periodicity from 1984 to the present and with spatial resolution of 30 m. The methodology has been applied to estimation of the snow cover area of Sierra Nevada mountain range in the Southern of Spain to obtain snow cover area daily information with 500 m spatial resolution for the period 1980-2014. Acknowledgments: This research has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank NASA DAAC and LANDSAT project for the data provided for this study.

[Characteristics of mercury exchange flux between soil and atmosphere under the snow retention and snow melting control].

PubMed

Zhang, Gang; Wang, Ning; Ai, Jian-Chao; Zhang, Lei; Yang, Jing; Liu, Zi-Qi

2013-02-01

Jiapigou gold mine, located in the upper Songhua River, was once the largest mine in China due to gold output, where gold extraction with algamation was widely applied to extract gold resulting in severe mercury pollution to ambient environmental medium. In order to study the characteristics of mercury exchange flux between soil (snow) and atmosphere under the snow retention and snow melting control, sampling sites were selected in equal distances along the slope which is situated in the typical hill-valley terrain unit. Mercury exchange flux between soil (snow) and atmosphere was determined with the method of dynamic flux chamber and in all sampling sites the atmosphere concentration from 0 to 150 cm near to the earth in the vertical direction was measured. Furthermore, the impact factors including synchronous meteorology, the surface characteristics under the snow retention and snow melting control and the mercury concentration in vertical direction were also investigated. The results are as follows: During the period of snow retention and melting the air mercury tends to gather towards valley bottom along the slope and an obvious deposit tendency process was found from air to the earth's surface under the control of thermal inversion due to the underlying surface of cold source (snow surface). However, during the period of snow melting, mercury exchange flux between the soil and atmosphere on the surface of the earth with the snow being melted demonstrates alternative deposit and release processes. As for the earth with snow covered, the deposit level of mercury exchange flux between soil and atmosphere is lower than that during the period of snow retention. The relationship between mercury exchange flux and impact factors shows that in snow retention there is a remarkable negative linear correlation between mercury exchange flux and air mercury concentration as well as between the former and the air temperature. In addition, in snow melting mercury exchange

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.

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadley, O.L.; Corrigan, C.E.; Kirchstetter, T.W.

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 atmore » 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.« less

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)

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.

Spatiotemporal variability of snow cover and snow water equivalent in the last three decades over Eurasia

NASA Astrophysics Data System (ADS)

Zhang, Yinsheng; Ma, Ning

2018-04-01

Changes in the extent and amount of snow cover in Eurasia are of great interest because of their vital impacts on the global climate system and regional water resource management. This study investigated the spatial and temporal variability of the snow cover extent (SCE) and snow water equivalent (SWE) of the continental Eurasia using the Northern Hemisphere Equal-Area Scalable Earth Grid (EASE-Grid) Weekly SCE data for 1972-2006 and the Global Monthly EASE-Grid SWE data for 1979-2004. The results indicated that, in general, the spatial extent of snow cover significantly decreased during spring and summer, but varied little during autumn and winter over Eurasia in the study period. The date at which snow cover began to disappear in spring has significantly advanced, whereas the timing of snow cover onset in autumn did not vary significantly during 1972-2006. The snow cover persistence period declined significantly in the western Tibetan Plateau as well as partial area of Central Asia and northwestern Russia, but varied little in other parts of Eurasia. "Snow-free breaks" (SFBs) with intermittent snow cover in the cold season were principally observed in the Tibetan Plateau and Central Asia, causing a low sensitivity of snow cover persistence period to the timings of snow cover onset and disappearance over the areas with shallow snow. The averaged SFBs were 1-14 weeks during the study period and the maximum intermittence could even reach 25 weeks in certain years. At a seasonal scale, SWE usually peaked in February or March, but fell gradually since April across Eurasia. Both annual mean and annual maximum SWE decreased significantly during 1979-2004 in most parts of Eurasia except for eastern Siberia as well as northwestern and northeastern China. The possible cross-platform inconsistencies between two passive microwave radiometers may cause uncertainties in the detected trends of SWE here, suggesting an urgent need of producing a long-term, more homogeneous SWE

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

Iron snow in the Martian Core?

NASA Astrophysics Data System (ADS)

Davies, C. J.; Pommier, A.

2017-12-01

The decline of Mars' global magnetic field some 3.8-4.1 billion years ago is thought to reflect the demise of the dynamo that operated in its liquid core. The termination of the dynamo is intimately tied to the thermochemical evolution of the core-mantle system and therefore to the present-day physical state of the Martian core. The standard model predicts that the Martian dynamo failed because thermal convection stopped and the core remained entirely liquid until the present. Here we consider an alternative hypothesis that the Martian core crystallized from the top down in the so-called iron snow regime. We derive energy-entropy equations describing the long-timescale thermal and magnetic evolution of the core that incorporate the self-consistent formation of a snow layer that freezes out pure iron and is assumed to be on the liquidus; the iron sinks and remelts in the deeper core, acting as a possible source for magnetic field generation. Compositions are in the FeS system, with a sulfur content up to 16 wt%. The values of the different parameters (core radius, density and CMB pressure) are varied within bounds set by recent internal structure models that satisfy existing geodetic constraints (planetary mass, moment of inertia and tidal Love number). The melting curve and adiabat, CMB heat flow and thermal conductivity were also varied, based on previous experimental and numerical works. We observe that the formation of snow zones occurs for a wide range of interior and thermal structure properties and depends critically on the initial sulfur concentration. Gravitational energy release and latent heat effects arising during growth of the snow zone do not generate sufficient entropy to restart the dynamo unless the snow zone occupies a significant fraction of the core. Our results suggest that snow zones can be 1.5-2 Gyrs old, though thermal stratification of the uppermost core, not included in our model, likely delays onset. Models that match the available

Snow observations in Mount Lebanon (2011-2016)

NASA Astrophysics Data System (ADS)

Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; Fanise, Pascal; Drapeau, Laurent; Somma, Janine; Fadel, Ali; Bitar, Ahmad Al; Escadafal, Richard

2017-08-01

We present a unique meteorological and snow observational dataset in Mount Lebanon, a mountainous region with a Mediterranean climate, where snowmelt is an essential water resource. The study region covers the recharge area of three karstic river basins (total area of 1092 km2 and an elevation up to 3088 m). The dataset consists of (1) continuous meteorological and snow height observations, (2) snowpack field measurements, and (3) medium-resolution satellite snow cover data. The continuous meteorological measurements at three automatic weather stations (MZA, 2296 m; LAQ, 1840 m; and CED, 2834 m a.s.l.) include surface air temperature and humidity, precipitation, wind speed and direction, incoming and reflected shortwave irradiance, and snow height, at 30 min intervals for the snow seasons (November-June) between 2011 and 2016 for MZA and between 2014 and 2016 for CED and LAQ. Precipitation data were filtered and corrected for Geonor undercatch. Observations of snow height (HS), snow water equivalent, and snow density were collected at 30 snow courses located at elevations between 1300 and 2900 m a.s.l. during the two snow seasons of 2014-2016 with an average revisit time of 11 days. Daily gap-free snow cover extent (SCA) and snow cover duration (SCD) maps derived from MODIS snow products are provided for the same period (2011-2016). We used the dataset to characterize mean snow height, snow water equivalent (SWE), and density for the first time in Mount Lebanon. Snow seasonal variability was characterized with high HS and SWE variance and a relatively high snow density mean equal to 467 kg m-3. We find that the relationship between snow depth and snow density is specific to the Mediterranean climate. The current model explained 34 % of the variability in the entire dataset (all regions between 1300 and 2900 m a.s.l.) and 62 % for high mountain regions (elevation 2200-2900 m a.s.l.). The dataset is suitable for the investigation of snow dynamics and for the forcing

City Level of Income and Urbanization and Availability of Food Stores and Food Service Places in China.

PubMed

Liao, Chunxiao; Tan, Yayun; Wu, Chaoqun; Wang, Shengfeng; Yu, Canqing; Cao, Weihua; Gao, Wenjing; Lv, Jun; Li, Liming

2016-01-01

The contribution of unhealthy dietary patterns to the epidemic of obesity has been well recognized. Differences in availability of foods may have an important influence on individual eating behaviors and health disparities. This study examined the availability of food stores and food service places by city characteristics on city level of income and urbanization. The cross-sectional survey was comprised of two parts: (1) an on-site observation to measure availability of food stores and food service places in 12 cities of China; (2) an in-store survey to determine the presence of fresh/frozen vegetables or fruits in all food stores. Trained investigators walked all the streets/roads within study tracts to identify all the food outlets. An observational survey questionnaire was used in all food stores to determine the presence of fresh/frozen vegetables or fruits. Urbanization index was determined for each city using a principal components factor analysis. City level of income and urbanization and numbers of each type of food stores and food service places were examined using negative binomial regression models. Large-sized supermarkets and specialty retailers had higher number of fresh/frozen vegetables or fruits sold compared to small/medium-sized markets. High-income versus low-income, high urbanized versus low urbanized areas had significantly more large-sized supermarkets and fewer small/medium-sized markets. In terms of restaurants, high urbanized cities had more western fast food restaurants and no statistically significant difference in the relative availability of any type of restaurants was found between high- and low-income areas. The findings suggested food environment disparities did exist in different cities of China.

City Level of Income and Urbanization and Availability of Food Stores and Food Service Places in China

PubMed Central

Liao, Chunxiao; Tan, Yayun; Wu, Chaoqun; Wang, Shengfeng; Yu, Canqing; Cao, Weihua; Gao, Wenjing; Lv, Jun; Li, Liming

2016-01-01

Objective The contribution of unhealthy dietary patterns to the epidemic of obesity has been well recognized. Differences in availability of foods may have an important influence on individual eating behaviors and health disparities. This study examined the availability of food stores and food service places by city characteristics on city level of income and urbanization. Methods The cross-sectional survey was comprised of two parts: (1) an on-site observation to measure availability of food stores and food service places in 12 cities of China; (2) an in-store survey to determine the presence of fresh/frozen vegetables or fruits in all food stores. Trained investigators walked all the streets/roads within study tracts to identify all the food outlets. An observational survey questionnaire was used in all food stores to determine the presence of fresh/frozen vegetables or fruits. Urbanization index was determined for each city using a principal components factor analysis. City level of income and urbanization and numbers of each type of food stores and food service places were examined using negative binomial regression models. Results Large-sized supermarkets and specialty retailers had higher number of fresh/frozen vegetables or fruits sold compared to small/medium-sized markets. High-income versus low-income, high urbanized versus low urbanized areas had significantly more large-sized supermarkets and fewer small/medium-sized markets. In terms of restaurants, high urbanized cities had more western fast food restaurants and no statistically significant difference in the relative availability of any type of restaurants was found between high- and low-income areas. Conclusions The findings suggested food environment disparities did exist in different cities of China. PMID:26938866

Basic Snow Pressure Calculation

NASA Astrophysics Data System (ADS)

Hao, Shouzhi; Su, Jian

2018-03-01

As extreme weather rising in recent years, the damage of large steel structures caused by weather is frequent in China. How to consider the effect of wind and snow loads on the structure in structural design has become the focus of attention in engineering field. In this paper, based on the serious snow disasters in recent years and comparative analysis of some scholars, influence factors and the value of the snow load, the probability model are described.

Healthful Nutrition of Foods in Navajo Nation Stores: Availability and Pricing.

PubMed

Kumar, Gayathri; Jim-Martin, Sonlatsa; Piltch, Emily; Onufrak, Stephen; McNeil, Carrie; Adams, Laura; Williams, Nancy; Blanck, Heidi M; Curley, Larry

2016-09-01

Low availability and affordability of healthier foods in food stores on the Navajo Nation (NN) may be a community-level risk factor for the high prevalence of obesity among the Navajo people. This study assessed the availability and pricing of foods and beverages in supermarkets and convenience stores throughout the NN. Descriptive study design using the Nutrition Environment Measurement Survey in Stores audit tool. Supermarkets (n = 13) and convenience stores (n = 50) on NN and border-town supermarkets (n = 9). Not applicable. Availability and pricing of healthy and less-healthy foods. Descriptive and χ(2) analyses. Navajo convenience stores offered fewer healthier food options compared to Navajo supermarkets. In Navajo convenience stores, 100% whole grain products, reduced-fat cheese, lean meats, reduced-fat chips, and fat-free or light hot dogs were available in fewer stores than their corresponding less-healthy versions (all with p < .05). In both Navajo supermarkets and convenience stores, 100% whole wheat bread, lean cold cuts, and reduced-fat cheese were all more expensive per unit than their corresponding less-healthy versions (all with p < .05). According to this study, healthier foods are not as readily available in Navajo convenience stores as they are in Navajo supermarkets. Improving access to and affordability of healthier foods in reservation stores of all sizes may support healthy eating among Navajo residents. © 2016 by American Journal of Health Promotion, Inc.

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…

How Much Water is in That Snowpack? Improving Basin-wide Snow Water Equivalent Estimates from the Airborne Snow Observatory

NASA Astrophysics Data System (ADS)

Bormann, K.; Painter, T. H.; Marks, D. G.; Kirchner, P. B.; Winstral, A. H.; Ramirez, P.; Goodale, C. E.; Richardson, M.; Berisford, D. F.

2014-12-01

In the western US, snowmelt from the mountains contribute the vast majority of fresh water supply, in an otherwise dry region. With much of California currently experiencing extreme drought, it is critical for water managers to have accurate basin-wide estimations of snow water content during the spring melt season. At the forefront of basin-scale snow monitoring is the Jet Propulsion Laboratory's Airborne Snow Observatory (ASO). With combined LiDAR /spectrometer instruments and weekly flights over key basins throughout California, the ASO suite is capable of retrieving high-resolution basin-wide snow depth and albedo observations. To make best use of these high-resolution snow depths, spatially distributed snow density data are required to leverage snow water equivalent (SWE) from the measured depths. Snow density is a spatially and temporally variable property and is difficult to estimate at basin scales. Currently, ASO uses a physically based snow model (iSnobal) to resolve distributed snow density dynamics across the basin. However, there are issues with the density algorithms in iSnobal, particularly with snow depths below 0.50 m. This shortcoming limited the use of snow density fields from iSnobal during the poor snowfall year of 2014 in the Sierra Nevada, where snow depths were generally low. A deeper understanding of iSnobal model performance and uncertainty for snow density estimation is required. In this study, the model is compared to an existing climate-based statistical method for basin-wide snow density estimation in the Tuolumne basin in the Sierra Nevada and sparse field density measurements. The objective of this study is to improve the water resource information provided to water managers during ASO operation in the future by reducing the uncertainty introduced during the snow depth to SWE conversion.

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.

Unexpected Patterns in Snow and Dirt

ERIC Educational Resources Information Center

Ackerson, Bruce J.

2018-01-01

For more than 30 years, Albert A. Bartlett published "Thermal patterns in the snow" in this journal. These are patterns produced by heat sources underneath the snow. Bartlett's articles encouraged me to pay attention to patterns in snow and to understanding them. At winter's end the last snow becomes dirty and is heaped into piles. This…

Healthful food availability in stores and restaurants--American Samoa, 2014.

PubMed

Lee-Kwan, Seung Hee; Kumar, Gayathri; Ayscue, Patrick; Santos, Marjorie; McGuire, Lisa C; Blanck, Heidi M; Nua, Motusa Tuileama

2015-03-20

American Samoa, one of the U.S.-affiliated Pacific Islands, has documented the highest prevalence of adults with obesity (75%) in the world. The nutritionally poor food and beverage environment of food retail venues has been suspected to be a contributing factor, although an evaluation of these venues in American Samoa has not been conducted. In January 2014, American Samoa established an Obesity Task Force to develop policies and strategies to combat obesity. To inform the efforts of the task force, the American Samoa Department of Health and CDC conducted a baseline assessment of the availability, pricing, and promotion of healthful foods at retail food venues. Previously validated food environment assessment tools were modified to incorporate American Samoa foods and administered in a geographically representative sample of 70 stores (nine grocery stores and 61 convenience stores) and 20 restaurants. In convenience stores, healthful items were not found as available as less healthful counterparts, and some healthful items were more expensive than their less healthful counterparts. For restaurants, 70% offered at least one healthful entrée, whereas only 30% had healthful side dishes, such as vegetables. Actions to promote healthy eating, such as providing calorie information, were rare among restaurants. Improving availability, affordability, and the promotion of healthful foods in American Samoa stores and restaurants could support healthy eating among American Samoa residents.

Testing a blowing snow model against distributed snow measurements at Upper Sheep Creek, Idaho, United States of America

Treesearch

Rajiv Prasad; David G. Tarboton; Glen E. Liston; Charles H. Luce; Mark S. Seyfried

2001-01-01

In this paper a physically based snow transport model (SnowTran-3D) was used to simulate snow drifting over a 30 m grid and was compared to detailed snow water equivalence (SWE) surveys on three dates within a small 0.25 km2 subwatershed, Upper Sheep Creek. Two precipitation scenarios and two vegetation scenarios were used to carry out four snow transport model runs in...

Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

NASA Astrophysics Data System (ADS)

Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

2018-04-01

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their

Satellite and Surface Perspectives of Snow Extent in the Southern Appalachian Mountains

NASA Technical Reports Server (NTRS)

Sugg, Johnathan W.; Perry, Baker L.; Hall, Dorothy K.

2012-01-01

Assessing snow cover patterns in mountain regions remains a challenge for a variety of reasons. Topography (e.g., elevation, exposure, aspect, and slope) strongly influences snowfall accumulation and subsequent ablation processes, leading to pronounced spatial variability of snow cover. In-situ observations are typically limited to open areas at lower elevations (<1000 m). In this paper, we use several products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to assess snow cover extent in the Southern Appalachian Mountains (SAM). MODIS daily snow cover maps and true color imagery are analyzed after selected snow events (e.g., Gulf/Atlantic Lows, Alberta Clippers, and Northwest Upslope Flow) from 2006 to 2012 to assess the spatial patterns of snowfall across the SAM. For each event, we calculate snow cover area across the SAM using MODIS data and compare with the Interactive Multi-sensor Snow and ice mapping system (IMS) and available in-situ observations. Results indicate that Gulf/Atlantic Lows are typically responsible for greater snow extent across the entire SAM region due to intensified cyclogenesis associated with these events. Northwest Upslope Flow events result in snow cover extent that is limited to higher elevations (>1000 m) across the SAM, but also more pronounced along NW aspects. Despite some limitations related to the presence of ephemeral snow or cloud cover immediately after each event, we conclude that MODIS products are useful for assessing the spatial variability of snow cover in heavily forested mountain regions such as the SAM.

Food venue choice, consumer food environment, but not food venue availability within daily travel patterns are associated with dietary intake among adults, Lexington Kentucky 2011.

PubMed

Gustafson, Alison; Christian, Jay W; Lewis, Sarah; Moore, Kate; Jilcott, Stephanie

2013-01-29

The retail food environment may be one important determinant of dietary intake. However, limited research focuses on individuals' food shopping behavior and activity within the retail food environment. This study's aims were to determine the association between six various dietary indicators and 1) food venue availability; 2) food venue choice and frequency; and 3) availability of healthy food within food venue. In Fall, 2011, a cross-sectional survey was conducted among adults (n=121) age 18 years and over in Lexington, Kentucky. Participants wore a global position system (GPS) data logger for 3-days (2 weekdays and 1 weekend day) to track their daily activity space, which was used to assess food activity space. They completed a survey to assess demographics, food shopping behaviors, and dietary outcomes. Food store audits were conducted using the Nutrition Environment Measurement Survey-Store Rudd (NEMS-S) in stores where respondents reported purchasing food (n=22). Multivariate logistic regression was used to examine associations between six dietary variables with food venue availability within activity space; food venue choice; frequency of shopping; and availability of food within food venue. 1) Food venue availability within activity space - no significant associations. 2) Food Venue Choice - Shopping at farmers' markets or specialty grocery stores reported higher odds of consuming fruits and vegetables (OR 1.60 95% CI [1.21, 2.79]). Frequency of shopping - Shopping at a farmers' markets and specialty stores at least once a week reported higher odds of consumption of fruits and vegetables (OR 1.55 95% CI [1.08, 2.23]). Yet, shopping frequently at a super market had higher odds of consuming sugar-sweetened beverages (OR 1.39 95% CI [1.03, 1.86]). 3) Availability of food within store - those who shop in supermarkets with high availability of healthy food has lower odds of consuming sugar-sweetened beverages (OR 0.65 95% CI [0.14, 0.83]). Interventions aimed at

Sentinels for snow science

NASA Astrophysics Data System (ADS)

Gascoin, S.; Grizonnet, M.; Baba, W. M.; Hagolle, O.; Fayad, A.; Mermoz, S.; Kinnard, C.; Fatima, K.; Jarlan, L.; Hanich, L.

2017-12-01

Current spaceborne sensors do not allow retrieving the snow water equivalent in mountain regions, "the most important unsolved problem in snow hydrology" (Dozier, 2016). While the NASA is operating an airborne mission to survey the SWE in the western USA, elsewhere, however, snow scientists and water managers do not have access to routine SWE measurements at the scale of a mountain range. In this presentation we suggest that the advent of the Copernicus Earth Observation programme opens new perspectives to address this issue in mountain regions worldwide. The Sentinel-2 mission will provide global-scale multispectral observations at 20 m resolution every 5-days (cloud permitting). The Sentinel-1 mission is already imaging the global land surface with a C-band radar at 10 m resolution every 6 days. These observations are unprecedented in terms of spatial and temporal resolution. However, the nature of the observation (radiometry, wavelength) is in the continuity of previous and ongoing missions. As a result, it is relatively straightforward to re-use algorithms that were developed by the remote sensing community over the last decades. For instance, Sentinel-2 data can be used to derive maps of the snow cover extent from the normalized difference snow index, which was initially proposed for Landsat. In addition, the 5-days repeat cycle allows the application of gap-filling algorithms, which were developed for MODIS based on the temporal dimension. The Sentinel-1 data can be used to detect the wet snow cover and track melting areas as proposed for ERS in the early 1990's. Eventually, we show an example where Sentinel-2-like data improved the simulation of the SWE in the data-scarce region of the High Atlas in Morocco through assimilation in a distributed snowpack model. We encourage snow scientists to embrace Sentinel-1 and Sentinel-2 data to enhance our knowledge on the snow cover dynamics in mountain regions.

Improving snow water equivalent simulations in an alpine basin using blended gage precipitation and snow pillow measurements

NASA Astrophysics Data System (ADS)

Sohrabi, M.; Safeeq, M.; Conklin, M. H.

2017-12-01

Snowpack is a critical freshwater reservoir that sustains ecosystem, natural habitat, hydropower, agriculture, and urban water supply in many areas around the world. Accurate estimation of basin scale snow water equivalent (SWE), through both measurement and modeling, has been significantly recognized to improve regional water resource management. Recent advances in remote data acquisition techniques have improved snow measurements but our ability to model snowpack evolution is largely hampered by poor knowledge of inherently variable high-elevation precipitation patterns. For a variety of reasons, majority of the precipitation gages are located in low and mid-elevation range and function as drivers for basin scale hydrologic modeling. Here, we blend observed gage precipitation from low and mid-elevation with point observations of SWE from high-elevation snow pillow into a physically based snow evolution model (SnowModel) to better represent the basin-scale precipitation field and improve snow simulations. To do this, we constructed two scenarios that differed in only precipitation. In WTH scenario, we forced the SnowModel using spatially distributed gage precipitation data. In WTH+SP scenario, the model was forced with spatially distributed precipitation data derived from gage precipitation along with observed precipitation from snow pillows. Since snow pillows do not directly measure precipitation, we uses positive change in SWE as a proxy for precipitation. The SnowModel was implemented at daily time step and 100 m resolution for the Kings River Basin, USA over 2000-2014. Our results show an improvement in snow simulation under WTH+SP as compared to WTH scenario, which can be attributed to better representation in high-elevation precipitation patterns under WTH+SP. The average Nash Sutcliffe efficiency over all snow pillow and course sites was substantially higher for WTH+SP (0.77) than for WTH scenario (0.47). The maximum difference in observed and simulated

Seasonal Snow Extent and Snow Mass in South America Using SMMR and SSM/I Passive Microwave Data (1979-2003)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Chiu, L.; Kelly, R. E.; Powell, H.; Chiu, L.

2007-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-satellite and the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2003, both snow cover extent and snow depth (snow mass) were investigated during coldest months (May-September), primarily in the Patagonia area of Argentina and in Chile. Most of the seasonal snow in South America is in the Patagonia region of Argentina. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and also usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average snow extent during the 25-year period of record, is 320,700 km(exp 2). In July of 1984, the average monthly snow cover was 701,250 km(exp 2) - the most extensive coverage observed between 1979 and 2003. However, in July of 1989, snow cover extent was only 120 km(exp 2). The 25-year period of record shows a sinusoidal like pattern, though there appears to be no obvious trend in either increasing or decreasing snow extent or snow mass between 1979 and 2003.

Food availability is expressed through physiological stress indicators in nestling white ibis: A food supplementation experiment

USGS Publications Warehouse

Herring, G.; Cook, Mark I.; Gawlik, D.E.; Call, Erynn M.

2011-01-01

Physiological responses to environmental stress such as adrenocortical hormones and cellular stress proteins have recently emerged as potentially powerful tools for investigating physiological effects of avian food limitation. However, little is known about the physiological stress responses of free-living nestling birds to environmental variation in food availability. We experimentally tested how hydrologically mediated changes in food availability affect the physiological stress responses of juvenile white ibises Eudocimus albus in a fluctuating wetland. We provided supplementary food to free-living nestlings during 2years with contrasting hydrologic and food availability conditions, and used plasma (PCORT) and faecal (FCORT) corticosterone and heat shock proteins (HSP60 and HSP70) from first-hatched (A-nestlings) and second-hatched (B-nestlings) to detect relatively short- to long-term responses to food limitation. Nestling physiological stress responses were relatively low in all treatments during the year with optimal food availability, but PCORT, FCORT and HSP60 levels increased during the poor food year. FCORT and HSP60 responses were clearly due to nutritional condition as elevated concentrations were evident primarily in control nestlings. Significant year by hatch order interactions for both FCORT and HSP60 revealed that these increases were largely incurred by B-nestlings. FCORT and HSP60 responses were also well developed early in neonatal development and remained elevated for the duration of the experiment suggesting a chronic stress response. PCORT and HSP70 were less informative stress responses. The nutritionally mediated increases in FCORT and HSP60 provide compelling evidence that white ibis nestlings can be physiologically affected by environmental food levels. FCORT and HSP60 are effective indicators of nutritional mediated stress for nestling white ibises and potentially for other species prone to capture or handling stress. ?? 2010 The Authors

Potential and limitations of webcam images for snow cover monitoring in the Swiss Alps

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Hüsler, Fabia; Wunderle, Stefan

2017-04-01

In Switzerland, several thousands of outdoor webcams are currently connected to the Internet. They deliver freely available images that can be used to analyze snow cover variability on a high spatio-temporal resolution. To make use of this big data source, we have implemented a webcam-based snow cover mapping procedure, which allows to almost automatically derive snow cover maps from such webcam images. As there is mostly no information about the webcams and its parameters available, our registration approach automatically resolves these parameters (camera orientation, principal point, field of view) by using an estimate of the webcams position, the mountain silhouette, and a high-resolution digital elevation model (DEM). Combined with an automatic snow classification and an image alignment using SIFT features, our procedure can be applied to arbitrary images to generate snow cover maps with a minimum of effort. Resulting snow cover maps have the same resolution as the digital elevation model and indicate whether each grid cell is snow-covered, snow-free, or hidden from webcams' positions. Up to now, we processed images of about 290 webcams from our archive, and evaluated images of 20 webcams using manually selected ground control points (GCPs) to evaluate the mapping accuracy of our procedure. We present methodological limitations and ongoing improvements, show some applications of our snow cover maps, and demonstrate that webcams not only offer a great opportunity to complement satellite-derived snow retrieval under cloudy conditions, but also serve as a reference for improved validation of satellite-based approaches.

Snow in Italy

NASA Image and Video Library

2012-02-24

NASA image acquired February 24, 2012 By late February, 2012, the great European cold wave had begun to loosen its frigid grip, but significant snow still remained in the region. The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite captured this true-color image of snow in Italy on February 24 at 12:35 UTC (1:30 p.m. local time). In the north of the image, bright white clouds blanket the region in a broad arc. Snow, which tends to be generally less bright that clouds, covers the Alps in the north of Italy. The Apennine Mountains, which form the backbone of the Italian peninsula, also carry a blanket of snow. Although clouds and snow can, at times, be distinguished visually in a true-color image, sometimes they can appear very similar. When it is important to clearly define snow from cloud, false color images are often helpful. Rome, which can be seen as a gray smudge on the southwestern coast of the peninsula, recorded highs of a spring-like 50°F the day this image was captured, but earlier in the month the temperatures dove as low as 26°F on February 5. During that cold snap a rare intense snowfall blanketed Rome, causing the closure of the Colosseum, the Roman Forum and the Palatine Hill due to concerns of the risk of icy footing for tourists, and roads became impassible. Further north, temperatures plummeted to −21 °C (−6 °F) on 7 February. On February 11, news media reported over 2 meters (6.5 feet) of snow had fallen in Urbino, a walled town situated on a high sloping hillside on the eastern side of the Apennine Mountains. That same snowfall cut access to many remote towns in the Apennines, blocking roads and trapping some people in the homes. Credit: NASA/GSFC/Jeff Schmaltz/MODIS Land Rapid Response Team NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA�

Sublimation From Snow in Northern Environments

NASA Astrophysics Data System (ADS)

Pomeroy, J. W.

2002-12-01

Sublimation from snow is an often neglected component of water and energy balances. Research under the Mackenzie GEWEX Study has attempted to understand the snow and atmospheric processes controlling sublimation and to estimate the magnitude of sublimation in high latitude catchments. Eddy correlation units were used to measure vertical water vapour fluxes from a high latitude boreal forest, snow-covered tundra and shrub-covered tundra in Wolf Creek Research Basin, near Whitehorse Yukon, Territory Canada. Over Jan-Apr. water vapour fluxes from the forest canopy amounted to 18.3 mm, a significant loss from winter snowfall of 54 mm. Most of this loss occurred when the canopy was snow-covered. The weight of snow measured on a suspended, weighed tree indicates that this flux is dominated by sublimation of intercepted snow. In the melt period (April), water vapour fluxes were uniformly small ranging from 0.21 mm/day on the tundra slope, 0.23 mm/day for the forest and 0.27 mm/day for the shrub-tundra. During the melt period the forest and shrub canopies was snow-free and roots were frozen, so the primary source of water vapour from all sites was the surface snow.

Evidence for a photoprotective function for secondary carotenoids of snow algae

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bidigare, R.R.; Ondrusek, M.E.; Kennicutt, M.C. II

Snow algae occupy a unique habitat in high altitude and polar environments. These algae are often subject to extremes in nutrient availability, acidity, solar irradiance, desiccation, and ambient temperature. This report documents the accumulation of secondary carotenoids by snow algae in response to the availability of nitrogenous nutrients. Unusually large accumulations of astaxanthin esters in extra-chloroplastic lipid globules produce the characteristic red pigmentation typical of some snow algae (e.g., Chlamydomonas nivalis (Bauer) Wille). Consequently, these compounds greatly reduce the amount of light available for absorption by the light-harvesting pigment-protein complexes, thus potentially limiting photoinhibition and photodamage caused by intense solarmore » radiation. The esterification of astaxanthin with fatty acids represents a possible mechanism by which this chromophore can be concentrated within cytoplasmic globules to maximize its photoprotective efficiency. 53 refs., 2 figs., 4 tabs.« less

[Snow cover pollution monitoring in Ufa].

PubMed

Daukaev, R A; Suleĭmanov, R A

2008-01-01

The paper presents the results of examining the snow cover polluted with heavy metals in the large industrial town of Ufa. The level of man-caused burden on the snow cover of the conventional parts of the town was estimated and compared upon exposure to a wide range of snow cover pollutants. The priority snow cover pollutants were identified among the test heavy metals.

Effects of multilayer snow scheme on the simulation of snow: Offline Noah and coupled with NCEP CFSv2

NASA Astrophysics Data System (ADS)

Saha, Subodh Kumar; Sujith, K.; Pokhrel, Samir; Chaudhari, Hemantkumar S.; Hazra, Anupam

2017-03-01

The Noah version 2.7.1 is a moderately complex land surface model (LSM), with a single layer snowpack, combined with vegetation and underlying soil layer. Many previous studies have pointed out biases in the simulation of snow, which may hinder the skill of a forecasting system coupled with the Noah. In order to improve the simulation of snow by the Noah, a multilayer snow scheme (up to a maximum of six layers) is introduced. As Noah is the land surface component of the Climate Forecast System version 2 (CFSv2) of the National Centers for Environmental Prediction (NCEP), the modified Noah is also coupled with the CFSv2. The offline LSM shows large improvements in the simulation of snow depth, snow water equivalent (SWE), and snow cover area during snow season (October to June). CFSv2 with the modified Noah reveals a dramatic improvements in the simulation of snow depth and 2 m air temperature and moderate improvements in SWE. As suggested in the previous diagnostic and sensitivity study, improvements in the simulation of snow by CFSv2 have lead to the reduction in dry bias over the Indian subcontinent (by a maximum of 2 mm d-1). The multilayer snow scheme shows promising results in the simulation of snow as well as Indian summer monsoon rainfall and hence this development may be the part of the future version of the CFS.

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.

Assessment of the Relative Accuracy of Hemispheric-Scale Snow-Cover Maps

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Kelly, Richard E.; Riggs, George A.; Chang, Alfred T. C.; Foster, James L.; Houser, Paul (Technical Monitor)

2001-01-01

There are several hemispheric-scale satellite-derived snow-cover maps available, but none has been fully validated. For the period October 23 - December 25, 2000, we compare snow maps of North America derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the National Oceanic and Atmospheric Administration (NOAA) National Operational Hydrologic Remote Sensing Center (NOHRSC), which both rely on satellite data from the visible and near-infrared parts of the spectrum; we also compare MODIS and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave snow maps. The maps derived from visible and near-infrared data are more accurate for mapping snow cover than are the passive-microwave-derived maps, however discrepancies exist as to the location and extent of the snow cover among those maps. The large (approx. 30 km) footprint of the SSM/I data and the difficulty in distinguishing wet and shallow snow from wet or snow-free ground, reveal differences up to 5.32 million sq km in the amount of snow mapped using MODIS versus SSM/I data. Algorithms that utilize both visible and passive-microwave data, which would take advantage of the all-weather mapping ability of the passive-microwave data, will be refined following the launch of the Advanced Microwave Scanning Radiometer (AMSR) in the fall of 2001.

Availability of more healthful food alternatives in traditional, convenience, and nontraditional types of food stores in two rural Texas counties.

PubMed

Bustillos, Brenda; Sharkey, Joseph R; Anding, Jenna; McIntosh, Alex

2009-05-01

Limited research has focused on the availability of more healthful food alternatives in traditional food stores (supermarkets and grocery stores) in rural areas. Current market trends suggest that food items may be available for purchase in stores other than traditional food stores. An observational survey was developed and used on-site to document the availability and variety of fruit and vegetables (fresh, canned, and frozen), meats (meat, poultry, fish, and eggs), dairy (milk, yogurt, and cheese), and grains (whole grains and refined grains) in all traditional food stores, convenience stores, and nontraditional food stores (dollar stores and mass merchandisers) in two rural Texas counties. Descriptive statistics and t tests identified that although the widest selection of more healthful food items was available in supermarkets, not all supermarkets carried all items. Grocery stores carried less variety of fresh fruits (8+/-0.7 vs 4.7+/-0.3; P<0.01) and vegetables (10.7+/-0.2 vs 6+/-0; P<0.001) than supermarkets. Fresh fruits and vegetables were not readily available in convenience or nontraditional food stores. Among convenience and nontraditional food stores, "dollar" stores offered the best variety of more healthful canned fruits and vegetables, whole-wheat bread, and whole-grain cereal. Mass merchandisers and dollar stores offered a greater variety of more healthful types of canned tuna and poultry, reduced-fat and skim milk, and low-fat tortillas. In these rural counties, traditional food stores offered greater availability of more healthful food choices across food groups. More healthful food choices in canned fruits and vegetables, canned meat and fish, milk, and grains were also available in dollar stores, mass merchandisers, and convenience stores. Results suggest that a complete understanding of the food environment, especially in rural areas, requires knowledge of the availability and variety of healthful food in all types of stores that are accessible

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Exploitation of ERTS-1 imagery utilizing snow enhancement techniques

NASA Technical Reports Server (NTRS)

Wobber, F. J.; Martin, K. R.

1973-01-01

Photogeological analysis of ERTS-simulation and ERTS-1 imagery of snowcovered terrain within the ERAP Feather River site and within the New England (ERTS) test area provided new fracture detail which does not appear on available geological maps. Comparative analysis of snowfree ERTS-1 images has demonstrated that MSS Bands 5 and 7 supply the greatest amount of geological fracture detail. Interpretation of the first snow-covered ERTS-1 images in correlation with ground snow depth data indicates that a heavy blanket of snow (more than 9 inches) accentuates major structural features while a light "dusting", (less than 1 inch) accentuates more subtle topographic expressions. An effective mail-based method for acquiring timely ground-truth (snowdepth) information was established and provides a ready correlation of fracture detail with snow depth so as to establish the working limits of the technique. The method is both efficient and inexpensive compared with the cost of similarly scaled direct field observations.

Impact of Snow Grain Shape and Internal Mixing with Black Carbon Aerosol on Snow Optical Properties for use in Climate Models

NASA Astrophysics Data System (ADS)

He, C.; Liou, K. N.; Takano, Y.; Yang, P.; Li, Q.; Chen, F.

2017-12-01

A set of parameterizations is developed for spectral single-scattering properties of clean and black carbon (BC)-contaminated snow based on geometric-optic surface-wave (GOS) computations, which explicitly resolves BC-snow internal mixing and various snow grain shapes. GOS calculations show that, compared with nonspherical grains, volume-equivalent snow spheres show up to 20% larger asymmetry factors and hence stronger forward scattering, particularly at wavelengths <1 mm. In contrast, snow grain sizes have a rather small impact on the asymmetry factor at wavelengths <1 mm, whereas size effects are important at longer wavelengths. The snow asymmetry factor is parameterized as a function of effective size, aspect ratio, and shape factor, and shows excellent agreement with GOS calculations. According to GOS calculations, the single-scattering coalbedo of pure snow is predominantly affected by grain sizes, rather than grain shapes, with higher values for larger grains. The snow single-scattering coalbedo is parameterized in terms of the effective size that combines shape and size effects, with an accuracy of >99%. Based on GOS calculations, BC-snow internal mixing enhances the snow single-scattering coalbedo at wavelengths <1 mm, but it does not alter the snow asymmetry factor. The BC-induced enhancement ratio of snow single-scattering coalbedo, independent of snow grain size and shape, is parameterized as a function of BC concentration with an accuracy of >99%. Overall, in addition to snow grain size, both BC-snow internal mixing and snow grain shape play critical roles in quantifying BC effects on snow optical properties. The present parameterizations can be conveniently applied to snow, land surface, and climate models including snowpack radiative transfer processes.

Soil Biogeochemistry in a Changing Climate: Effect of Snow Removal

NASA Astrophysics Data System (ADS)

Patel, K.; Tatariw, C.; Fernandez, I. J.; Macrae, J. D.; Ohno, T.

2016-12-01

Winter snowpack plays an important role in ecosystem functioning, thermally insulating the subnivean soil from freezing temperatures. Wintertime microbial mineralization of organic material results in accumulation of nutrients under the snowpack, which are available post-melt for plant root uptake. The northeastern United States has experienced declining snow accumulation, and climate models project this trend will continue in the future. Intermittent and reduced snow cover increases soil freezing and frost damage, which can have implications on spring nutrient availability and forest productivity. We conducted a 2-year snow removal experiment in the Dwight B. DeMeritt Forest at the University of Maine to study subnivean winter processes, and to examine the effect of a decreased snowpack on soil winter and spring biogeochemistry. Surface organic soils were collected during winter and spring of 2015 and 2016, years with sharply contrasting snow accumulation, to track temporal changes in nutrient dynamics as the system evolved from under the snowpack. Laboratory extractions and incubations were performed to quantify the inorganic available nitrogen, dissolved organic carbon (DOC), and potential net N-mineralization (PNNM) in field moist soils. Snow removal resulted in decreased winter soil temperatures (2-8°C colder than the reference plots). There was an increased incidence of rain-on-soil events in the winter, forming concrete frost. Freeze-thaw cycles in the treatment plots resulted in higher NH4-N and DOC concentrations, but lower PNNM, compared to the reference plots. Treatment effects on DOC and NH4-N concentrations were not seen in the spring, although the effects on PNNM persisted. Our findings demonstrated that freeze-thaw cycles play an important role in the timing and magnitude of soil nutrient availability during the vernal transition. Understanding these processes becomes increasingly important when defining forest ecosystem response to a changing

Food venue choice, consumer food environment, but not food venue availability within daily travel patterns are associated with dietary intake among adults, Lexington Kentucky 2011

PubMed Central

2013-01-01

Objective The retail food environment may be one important determinant of dietary intake. However, limited research focuses on individuals’ food shopping behavior and activity within the retail food environment. This study’s aims were to determine the association between six various dietary indicators and 1) food venue availability; 2) food venue choice and frequency; and 3) availability of healthy food within food venue. Methods In Fall, 2011, a cross-sectional survey was conducted among adults (n=121) age 18 years and over in Lexington, Kentucky. Participants wore a global position system (GPS) data logger for 3-days (2 weekdays and 1 weekend day) to track their daily activity space, which was used to assess food activity space. They completed a survey to assess demographics, food shopping behaviors, and dietary outcomes. Food store audits were conducted using the Nutrition Environment Measurement Survey-Store Rudd (NEMS-S) in stores where respondents reported purchasing food (n=22). Multivariate logistic regression was used to examine associations between six dietary variables with food venue availability within activity space; food venue choice; frequency of shopping; and availability of food within food venue. Results 1) Food venue availability within activity space – no significant associations. 2) Food Venue Choice – Shopping at farmers’ markets or specialty grocery stores reported higher odds of consuming fruits and vegetables (OR 1.60 95% CI [1.21, 2.79]). Frequency of shopping - Shopping at a farmers’ markets and specialty stores at least once a week reported higher odds of consumption of fruits and vegetables (OR 1.55 95% CI [1.08, 2.23]). Yet, shopping frequently at a super market had higher odds of consuming sugar-sweetened beverages (OR 1.39 95% CI [1.03, 1.86]). 3) Availability of food within store – those who shop in supermarkets with high availability of healthy food has lower odds of consuming sugar-sweetened beverages (OR 0.65 95

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.

Snow micro-structure at Kongsvegen glacier, Svalbard

NASA Astrophysics Data System (ADS)

Bilgeri, F.; Karner, F.; Steinkogler, W.; Fromm, R.; Obleitner, F.; Kohler, J.

2012-04-01

Measurements of physical snow properties have been performed at several sites at Kongsvegen glacier, which is a key Arctic glacier in western Spitzbergen (79N, 13E). The data were collected at six locations along the flow line of the glacier at different elevations (161 to 741m asl.) and describe snow that was deposited during winter 2010/11. We basically consider the vertical profiles of snow temperature, density, hardness, grain size and crystal shapes derived from standard stratigraphic methods (snow pits)and measurements using advanced instruments like Snow Micropen® and NIR imagery. Some parameters were measured repeatedly and with different instruments which proves a high quality as well as long-term and spatial representativeness of the data. The general snow conditions at the end of winter are characterized by a linear increase of snow depth and water equivalent with elevation. Snow hardness also increases with elevation while density remains remarkably constant. At most sites the snow temperature, density, hardness and grain size increase from the surface towards the snow-ice interface. The surface and the bottom layers stand out by specific changes in snow signature (crystal types) and delineate the bulk of the snow pack which itself features a rather complex layering. Comparison of the high-resolution profiles measured at different elevations at the glacier suggests some principal correlations of the signatures of hardness, grain size and crystal type. Thus, some major features (e.g. particularly hard layers) can be traced along the glacier, but the high-resolution layering can not straightforwardly be related from one site to the other. This basically reflects a locally different history of the snow pack in terms of precipitation events and post-depositional snow metamorphism. The issue is investigated more quantitatively by enhanced statistical processing of the observed signatures and simulation of the history of individual layers. These studies are

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.

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

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Silver nanoparticle release from commercially available plastic food containers into food simulants

NASA Astrophysics Data System (ADS)

Mackevica, Aiga; Olsson, Mikael Emil; Hansen, Steffen Foss

2016-01-01

Silver nanoparticles (AgNPs) are currently being used in many different kinds of consumer products in order to take advantage of their antimicrobial properties. However, the potential migration of silver nanoparticles into food and subsequent consumer exposure has hardly been addressed. In the current study, we investigated four brands of commercially available plastic food storage containers and measured the total amount of silver, particle size and number concentration, and the migration rates into three different food simulants (Milli-Q grade water, 10 % ethanol, and 3 % acetic acid) for 10 days at 40 °C. The experimental setup was made according to the European Commission Directive (EU 10/2011) for articles intended to be in contact with food. The total amount of silver in plastic containers and migration solutions was quantified by ICP-MS analysis, and the size of the migrated particles was investigated by single particle ICP-MS and TEM-EDS. The total mass and median size of released particulate Ag were generally highest in 3 % acetic acid for three out of four food container brands. The total content of silver in the containers varied from 13 to 42 µg/g. The highest migration was observed in the 3 % acetic acid food simulant for all four brands of containers, with total silver release up to 3.1 ng/cm2 after 10 days. In conclusion, the experimental results show that silver has the potential of migrating into food, especially when in contact with more acidic substances.

Seasonal Snow Extent and Snow Mass in South America using SMMR and SSM/I Passive Microwave Data (1979-2006)

NASA Technical Reports Server (NTRS)

Foster, J. L.; Hall, D. K.; Kelly, R. E. J.; Chiu, L.

2008-01-01

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and the Special Sensor Microwave Imagers (SSM/I) onboard Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow water equivalent (snow mass) were investigated during the coldest months (May-September), primarily in the Patagonia area of Argentina and in the Andes of Chile, Argentina and Bolivia, where most of the seasonal snow is found. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 km(exp 2). In July of 1984, the average monthly snow cover extent was 701,250 km(exp 2) the most extensive coverage observed between 1979 and 2006. However, in July of 1989, snow cover extent was only 120,000 km(exp 2). The 28-year period of record shows a sinusoidal like pattern for both snow cover and snow mass, though neither trend is significant at the 95% level.

Profits, Commercial Food Supplier Involvement, and School Vending Machine Snack Food Availability: Implications for Implementing the New Competitive Foods Rule

ERIC Educational Resources Information Center

Terry-McElrath, Yvonne M.; Hood, Nancy E.; Colabianchi, Natalie; O'Malley, Patrick M.; Johnston, Lloyd D.

2014-01-01

Background: The 2013-2014 school year involved preparation for implementing the new US Department of Agriculture (USDA) competitive foods nutrition standards. An awareness of associations between commercial supplier involvement, food vending practices, and food vending item availability may assist schools in preparing for the new standards.…

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

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.

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.

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

NASA Astrophysics Data System (ADS)

Painter, T.; Mattmann, C. A.; Brodzik, M.; Bryant, A. C.; Goodale, C. E.; Hart, A. F.; Ramirez, P.; Rittger, K. E.; Seidel, F. C.; Zimdars, P. A.

2012-12-01

The response of the cryosphere to climate forcings largely determines Earth's climate sensitivity. However, our understanding of the strength of the simulated snow albedo feedback varies by a factor of three in the GCMs used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, mainly caused by uncertainties in snow extent and the albedo of snow-covered areas from imprecise remote sensing retrievals. Additionally, the Western US and other regions of the globe depend predominantly on snowmelt for their water supply to agriculture, industry and cities, hydroelectric power, and recreation, against rising demand from increasing population. In the mountains of the Upper Colorado River Basin, dust radiative forcing in snow shortens snow cover duration by 3-7 weeks. Extended to the entire upper basin, the 5-fold increase in dust load since the late-1800s results in a 3-week earlier peak runoff and a 5% annual loss of total runoff. The remotely sensed dynamics of snow cover duration and melt however have not been factored into hydrological modeling, operational forecasting, and policymaking. To address these deficiencies in our understanding of snow properties, we have developed and validated a suite of MODIS snow products that provide accurate fractional snow covered area and radiative forcing of dust and carbonaceous aerosols in snow. The MODIS Snow Covered Area and Grain size (MODSCAG) and MODIS Dust Radiative Forcing in Snow (MODDRFS) algorithms, developed and transferred from imaging spectroscopy techniques, leverage the complete MODIS surface reflectance spectrum. The two most critical properties for understanding snowmelt runoff and timing are the spatial and temporal distributions of snow water equivalent (SWE) and snow albedo. We have created the Airborne Snow Observatory (ASO), an imaging spectrometer and scanning LiDAR system, to quantify SWE and snow albedo, generate unprecedented knowledge of snow properties, and provide complete

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

NASA Technical Reports Server (NTRS)

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

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

NASA Astrophysics Data System (ADS)

Aalstad, Kristoffer; Westermann, Sebastian; Vikhamar Schuler, Thomas; Boike, Julia; Bertino, Laurent

2018-01-01

With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least

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

Climate warming enhances snow avalanche risk in the Western Himalayas

PubMed Central

Ballesteros-Cánovas, J. A.; Trappmann, D.; Madrigal-González, J.; Eckert, N.; Stoffel, M.

2018-01-01

Ongoing climate warming has been demonstrated to impact the cryosphere in the Indian Himalayas, with substantial consequences for the risk of disasters, human well-being, and terrestrial ecosystems. Here, we present evidence that the warming observed in recent decades has been accompanied by increased snow avalanche frequency in the Western Indian Himalayas. Using dendrogeomorphic techniques, we reconstruct the longest time series (150 y) of the occurrence and runout distances of snow avalanches that is currently available for the Himalayas. We apply a generalized linear autoregressive moving average model to demonstrate linkages between climate warming and the observed increase in the incidence of snow avalanches. Warming air temperatures in winter and early spring have indeed favored the wetting of snow and the formation of wet snow avalanches, which are now able to reach down to subalpine slopes, where they have high potential to cause damage. These findings contradict the intuitive notion that warming results in less snow, and thus lower avalanche activity, and have major implications for the Western Himalayan region, an area where human pressure is constantly increasing. Specifically, increasing traffic on a steadily expanding road network is calling for an immediate design of risk mitigation strategies and disaster risk policies to enhance climate change adaption in the wider study region. PMID:29535224

Physiological assessment of deer populations by analysis of urine in snow

USGS Publications Warehouse

DelGiudice, G.D.; Mech, L.D.; Seal, U.S.

1989-01-01

We compared the nutritional status of free-ranging white-tailed deer (Odocoileus virginianus) in 3 natural yards and 1 yard where deer were supplementally fed from 1 January to 31 March 1985 in northeastern Minnesota. We monitored deer nutritonal status by sequential collection and chemical analysis of urine in snow (snow-urine) for urea nitrogen (U), sodium (Na), potassium (K), calcium (Ca), and phosphorus (P). Dilution of urine by snow was corrected by comparing these data as ratios to creatinine (C). All deer remained in an early phase of undernutrition; however, declining trends of U:C, Na:C, and K:C in 2 natural yards indicated increasingly inadequate nutrition as winter progressed. Unaltered values of these ratios and P.C in snow-urine collected from the third natural yard reflected stable levels of nutrient availability. Significant (P < 0.05) elevations of Na:C, K:C, and P:C in 2 natural yards with similar snow regimes suggested initiation of nutritional recovery in deer during late March. In contrast, deep snow in the third natural yard restricted feeding activity and was associated with ratios that remained diminished. Elevated U:C, Na:C, and K:C provided physiological evidence of the higher nutritional status of supplementally fed deer throughout winter and their ability to increase nutrient intake during late March despite prolonged deep snow cover. Frequent and quantitative assessments of the physiological status of deer by snow-urine analysis provided an improved understanding of the relationship between snow cover and the nutritional well-being of these deer.

Catchment-scale snow depth monitoring with balloon photogrammetry

NASA Astrophysics Data System (ADS)

Durand, M. T.; Li, D.; Wigmore, O.; Vanderjagt, B. J.; Molotch, N. P.; Bales, R. C.

2016-12-01

Field campaigns and permanent in-situ facilities provide extensive measurements of snowpack properties at catchment (or smaller) scales, and have consistently improved our understanding of snow processes and the estimation of snow water resources. However, snow depth, one of the most important snow states, has been measured almost entirely with discrete point-scale samplings in field measurements; spatiotemporally continuous snow depth measurements are nearly nonexistent, mainly due to the high cost of airborne flights and the ban of Unmanned Aerial Systems in many areas (e.g. in all the national parks). In this study, we estimate spatially continuous snow depth from photogrammetric reconstruction of aerial photos taken from a weather balloon. The study was conducted in a 0.2 km2 watershed in Wolverton, Sequoia National Park, California. We tied a point-and-shoot camera on a helium-inflated weather balloon to take aerial images; the camera was scripted to automatically capture images every 3 seconds and to record the camera position and orientation at the imaging times using a built-in GPS. With the 2D images of the snow-covered ground and the camera position and orientation data, the 3D coordinates of the snow surface were reconstructed at 10 cm resolution using photogrammetry software PhotoScan. Similar measurements were taken for the snow-free ground after snowmelt, and the snow depth was estimated from the difference between the snow-on and snow-off measurements. Comparing the photogrammetric-estimated snow depths with the 32 manually measured depths, taken at the same time as the snow-on balloon flight, we find the RMSE of the photogrammetric snow depth is 7 cm, which is 2% of the long-term peak snow depth in the study area. This study suggests that the balloon photogrammetry is a repeatable, economical, simple, and environmental-friendly method to continuously monitor snow at small-scales. Spatiotemporally continuous snow depth could be regularly measured in

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.

Overview of SnowEx Year 1 Activities

NASA Technical Reports Server (NTRS)

Kim, Edward; Gatebe, Charles; Hall, Dorothy; Newlin, Jerry; Misakonis, Amy; Elder, Kelly; Marshall, Hans Peter; Heimstra, Chris; Brucker, Ludovic; De Marco, Eugenia;

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.

Baltimore City Stores Increased The Availability Of Healthy Food After WIC Policy Change.

PubMed

Cobb, Laura K; Anderson, Cheryl A M; Appel, Lawrence; Jones-Smith, Jessica; Bilal, Usama; Gittelsohn, Joel; Franco, Manuel

2015-11-01

As part of a 2009 revision to the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) program, the Department of Agriculture required WIC-authorized stores to stock additional varieties of healthy food. The long-term effects of this policy on access to healthy food are unknown. Using surveys conducted in 118 Baltimore City, Maryland, food stores in 2006 and 2012, we examined associations of the change in healthy food availability with store type, neighborhood demographics, and the 2009 WIC policy change. Overall, healthy food availability improved significantly between 2006 and 2012, with the greatest increases in corner stores and in census tracts with more than 60 percent black residents. On an 11-point scale measuring availability of fruit (3 points), vegetables (4 points), bread (2 points), and milk (2 points), the WIC policy change was associated with a 0.72-point increase in WIC-relevant healthy food availability, while joining WIC was associated with a 0.99-point increase. Stores that carry a limited variety of food items may be more receptive to stocking healthier food than previously thought, particularly within neighborhoods with a majority of black residents. Policies targeting healthy food availability have the potential to increase availability and decrease health disparities. Project HOPE—The People-to-People Health Foundation, Inc.

a Physical Parameterization of Snow Albedo for Use in Climate Models.

NASA Astrophysics Data System (ADS)

Marshall, Susan Elaine

The albedo of a natural snowcover is highly variable ranging from 90 percent for clean, new snow to 30 percent for old, dirty snow. This range in albedo represents a difference in surface energy absorption of 10 to 70 percent of incident solar radiation. Most general circulation models (GCMs) fail to calculate the surface snow albedo accurately, yet the results of these models are sensitive to the assumed value of the snow albedo. This study replaces the current simple empirical parameterizations of snow albedo with a physically-based parameterization which is accurate (within +/- 3% of theoretical estimates) yet efficient to compute. The parameterization is designed as a FORTRAN subroutine (called SNOALB) which can be easily implemented into model code. The subroutine requires less then 0.02 seconds of computer time (CRAY X-MP) per call and adds only one new parameter to the model calculations, the snow grain size. The snow grain size can be calculated according to one of the two methods offered in this thesis. All other input variables to the subroutine are available from a climate model. The subroutine calculates a visible, near-infrared and solar (0.2-5 μm) snow albedo and offers a choice of two wavelengths (0.7 and 0.9 mu m) at which the solar spectrum is separated into the visible and near-infrared components. The parameterization is incorporated into the National Center for Atmospheric Research (NCAR) Community Climate Model, version 1 (CCM1), and the results of a five -year, seasonal cycle, fixed hydrology experiment are compared to the current model snow albedo parameterization. The results show the SNOALB albedos to be comparable to the old CCM1 snow albedos for current climate conditions, with generally higher visible and lower near-infrared snow albedos using the new subroutine. However, this parameterization offers a greater predictability for climate change experiments outside the range of current snow conditions because it is physically-based and

Rocky Mountain Snow

NASA Image and Video Library

2017-12-08

NASA image acquired December 19, 2012 In time for the 2012 winter solstice, a storm dropped snow over most of the Rocky Mountains in the United States. On December 20, the National Weather Service reported snow depths exceeding 100 centimeters (39 inches) in some places—the result of the recent snowfall plus accumulation from earlier storms. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite captured this natural-color image on December 19, 2012. Clouds had mostly cleared from the region, though some cloud cover lingered over parts of the Pacific Northwest and Colorado. Showing more distinct contours than the clouds, the snow cover stretched across the Rocky Mountains and the surrounding region, from Idaho to Arizona and from California to Colorado. Snowfall did not stop in Colorado, as the storm continued moving eastward across the Midwest. By December 20, 2012, a combination of heavy snow and strong winds had closed schools, iced roads, and delayed flights, complicating plans for holiday travelers. Though troublesome for travel, the snow brought much-needed moisture; multiple cities had set new records for consecutive days without measurable snow, CBS news reported. As of December 18, the U.S. Drought Monitor stated that a substantial portion of the continental United States continued to suffer from drought, and “exceptional” drought conditions extended from South Dakota to southern Texas. NASA image courtesy Jeff Schmaltz, LANCE MODIS Rapid Response. Caption by Michon Scott. Instrument: Aqua - MODIS To read more go to: earthobservatory.nasa.gov/IOTD/view.php?id=80035 Credit: NASA Earth Observatory NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission

European In-Situ Snow Measurements: Practices and Purposes.

PubMed

Pirazzini, Roberta; Leppänen, Leena; Picard, Ghislain; Lopez-Moreno, Juan Ignacio; Marty, Christoph; Macelloni, Giovanni; Kontu, Anna; von Lerber, Annakaisa; Tanis, Cemal Melih; Schneebeli, Martin; de Rosnay, Patricia; Arslan, Ali Nadir

2018-06-22

In-situ snow measurements conducted by European institutions for operational, research, and energy business applications were surveyed in the framework of the European Cooperation in Science and Technology (COST) Action ES1404, called "A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology, and numerical weather prediction". Here we present the results of this survey, which was answered by 125 participants from 99 operational and research institutions, belonging to 38 European countries. The typologies of environments where the snow measurements are performed range from mountain to low elevated plains, including forests, bogs, tundra, urban areas, glaciers, lake ice, and sea ice. Of the respondents, 93% measure snow macrophysical parameters, such as snow presence, snow depth (HS), snow water equivalent (SWE), and snow density. These describe the bulk characteristics of the whole snowpack or of a snow layer, and they are the primary snow properties that are needed for most operational applications (such as hydrological monitoring, avalanche forecast, and weather forecast). In most cases, these measurements are done with manual methods, although for snow presence, HS, and SWE, automatized methods are also applied by some respondents. Parameters characterizing precipitating and suspended snow (such as the height of new snow, precipitation intensity, flux of drifting/blowing snow, and particle size distribution), some of which are crucial for the operational services, are measured by 74% of the respondents. Parameters characterizing the snow microstructural properties (such as the snow grain size and shape, and specific surface area), the snow electromagnetic properties (such as albedo, brightness temperature, and backscatter), and the snow composition (such as impurities and isotopes) are measured by 41%, 26%, and 13% of the respondents, respectively, mostly for research applications. The results of this survey

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.

Early results from NASA's SnowEx campaign

NASA Astrophysics Data System (ADS)

Kim, Edward; Gatebe, Charles; Hall, Dorothy; Misakonis, Amy; Elder, Kelly; Marshall, Hans Peter; Hiemstra, Chris; Brucker, Ludovic; Crawford, Chris; Kang, Do Hyuk; De Marco, Eugenia; Beckley, Matt; Entin, Jared

2017-04-01

SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earth's terrestrial snow-covered regions? Year 1 (2016-17) focuses on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site is Grand Mesa and the secondary site is the Senator Beck Basin, both in western, Colorado, USA. Ten core sensors on four core aircraft will make observations using a broad suite of airborne sensors including active and passive microwave, and active and passive optical/infrared sensing techniques to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also includes an extensive range of ground truth measurements—in-situ samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some early results will be presented. Seasonal snow cover is the largest single component of the cryosphere in areal extent (covering an average of 46M km2 of Earth's surface (31 % of land areas) each year). This seasonal snow has major societal impacts in the areas of water resources, natural hazards (floods and droughts), water security, and weather and climate. The only practical way to estimate the quantity of snow on a consistent global basis is through satellites. Yet, current space-based techniques underestimate storage of snow water equivalent (SWE) by as much as 50%, and model-based estimates can differ greatly vs. estimates based on remotely-sensed observations. At peak coverage, as much as half of snow-covered terrestrial areas involve forested areas, so quantifying the challenge represented by forests is important to plan any future snow mission. Single-sensor approaches may work for certain snow types and certain conditions, but not for others

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

A webgis supported snow information system with long time satellite data for Turkey

NASA Astrophysics Data System (ADS)

Surer, S.; Bolat, K.; Akyurek, Z.

2012-04-01

KARBILSIS is an online platform which is developed in order to provide end-users with daily remote sensing snow products for Turkey (www.karbilsis.com). The project has been started as a research activity after an award by Ministry of Science and Technology has been granted to our company. At the first stage of our project MODIS atmospherically corrected reflectance data has been downloaded covering the period of 2000-2011 which makes more than ten years of satellite imagery for Turkey. The archived MODIS data that have been obtained from National Snow and Ice Data Center (NSIDC) is mainly MOD09GA product that includes seven spectral bands. Only the tiles which are covering Turkey have been archived namely 19&20 horizontal and 4&5 vertical ones. In order to provide scientists with a website giving the availability of analysis of snow covered area for long terms based on their area of interests, a fractional snow extent (FSE) product has been generated. For FSE product a normalized difference snow index (NDSI) based algorithm has been developed using daily land surface reflectance values (MOD09GA). In addition to MODIS data, four different Landsat images belonging to different days of snowy period (January, March, and May) have been used during algorithm development taking into account a better representation of different reflectance values of snow which highly varies depending on the accumulation and melting periods. Landsat images were used as reference images. First the Landsat images were orthorectified and mapped to a cartographic projection. Then image segmentation was applied to obtain homogeneous tiles, where the homogeneity is defined as similarity in pixel values. The mean-shift segmentation approach, where each pixel was associated with a significant mode of the joint domain density located in its neighborhood, was applied. After segmentation, the image was classified into snow and no-snow classes with Maximum Likelihood Classification Method. FSE

Progress in radar snow research. [Brookings, South Dakota

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Availability of healthier options in traditional and nontraditional rural fast-food outlets

PubMed Central

Creel, Jennifer S; Sharkey, Joseph R; McIntosh, Alex; Anding, Jenna; Huber, J Charles

2008-01-01

Background Food prepared away from home has become increasingly popular to U.S. families, and may contribute to obesity. Sales have been dominated by fast food outlets, where meals are purchased for dining away from home or in the home. Although national chain affiliated fast-food outlets are considered the main source for fast food, fast foods are increasingly available in convenience stores and supermarkets/grocery stores. In rural areas, these nontraditional fast-food outlets may provide most of the opportunities for procurement of fast foods. Methods Using all traditional and nontraditio nal fast-food outlets identified in six counties in rural Texas, the type and number of regular and healthiermenu options were surveyed using on-site observation in all food venues that were primarily fast food, supermarket/grocery store, and convenience store and compared with 2005 Dietary Guidelines. Results Traditional fast-food outlets represented 84 (41%) of the 205 opportunities for procurement of fast food; 109 (53.2%) were convenience stores and 12 (5.8%) supermarkets/grocery stores. Although a s imilar variety of regular breakfast and lunch/dinner entrées were available in traditional fast-food outlets and convenience stores, the variety of healthier breakfast and lunch/dinner entrées was significantly greater in fast food outlets. Compared with convenience stores, supermarkets/grocery stores provided a greater variety of regular and healthier entrées and lunch/dinner side dishes. Conclusion Convenience stores and supermarkets/grocery stores more than double the potential access to fast foods in this rural area than traditional fast-food outlets alone; however, traditional fast food outlets offer greater opportunity for healthier fast food options than convenience stores. A complete picture of fast food environment and the availability of healthier fast food options are essential to understand environmental influences on diet and health outcomes, and identify

Snow and Dust over Inner Mongolia

NASA Technical Reports Server (NTRS)

2002-01-01

A severe snow-and-sand storm hit an 80,000 square-mile (205,000-square-km) stretch of the Chinese province of Mongolia on New Year's Eve, killing 21 people and leaving thousands of people to face possible starvation. The affected area is located about 250 miles (400 km) northwest of Beijing. It is the worst snowstorm to hit the region in more than 50 years. Lasting about 3 days, the storm dumped 24 inches (60 cm) of snow mixed with sand from the Gobi Desert, stranding many residents in deep drifts. The Chinese Red Cross reports that almost 1 million people were affected by the storm and at least 10,000 head of livestock are confirmed dead. As many as 120,000 residents are in need of food and other supplies. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS), flying aboard the OrbView-2 satellite, acquired this image of the storm on January 2, 2001, as it approached China's eastern provinces. You can see storm clouds (white pixels) and windblown dust (brownish pixels) crossing the Yellow Sea and East China Sea toward Japan and the western Pacific. Provided by the SeaWiFS Project, NASA/Goddard Space Flight Center, and ORBIMAGE

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.

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;

Advances in Airborne Altimetric Techniques for the Measurement of Snow on Arctic Sea Ice

NASA Astrophysics Data System (ADS)

Newman, T.; Farrell, S. L.; Richter-Menge, J.; Elder, B. C.; Ruth, J.; Connor, L. N.

2014-12-01

Current sea ice observations and models indicate a transition towards a more seasonal Arctic ice pack with a smaller, and geographically more variable, multiyear ice component. To gain a comprehensive understanding of the processes governing this transition it is important to include the impact of the snow cover, determining the mechanisms by which snow is both responding to and forcing changes to the sea ice pack. Data from NASA's Operation IceBridge (OIB) snow radar system, which has been making yearly surveys of the western Arctic since 2009, offers a key resource for investigating the snow cover. In this work, we characterize the OIB snow radar instrument response to ascertain the location of 'side-lobes', aiding the interpretation of snow radar data. We apply novel wavelet-based techniques to identify the primary reflecting interfaces within the snow pack from which snow depth estimates are derived. We apply these techniques to the range of available snow radar data collected over the last 6 years during the NASA OIB mission. Our results are validated through comparison with a range of in-situ data. We discuss the impact of sea ice surface morphology on snow radar returns (with respect to ice type) and the topographic conditions over which accurate snow-radar-derived snow depths may be obtained. Finally we present improvements to in situ survey design that will allow for both an improved sampling of the snow radar footprint and more accurate assessment of the uncertainties in radar-derived snow depths in the future.

Dry Snow Metamorphism

DTIC Science & Technology

2012-09-19

behavior of snow during metamorphism and grain sintering using mathematical models. 2 Approach Our approach involved the collection and...examination of both types of specimens at various stages of metamorphism using the SEM and micro-CT. More specifically, the above approach involved...than 10ºC·m-1). 5. High-resolution images and X-ray spectra of snow specimens at various metamorphism stages were obtained using an SEM and EDS. 6

21 CFR 20.120 - Records available in Food and Drug Administration Public Reading Rooms.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 1 2013-04-01 2013-04-01 false Records available in Food and Drug Administration Public Reading Rooms. 20.120 Section 20.120 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PUBLIC INFORMATION Availability of Specific Categories of Records § 20.120 Records available in Food and Drug...

21 CFR 20.120 - Records available in Food and Drug Administration Public Reading Rooms.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 1 2014-04-01 2014-04-01 false Records available in Food and Drug Administration Public Reading Rooms. 20.120 Section 20.120 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PUBLIC INFORMATION Availability of Specific Categories of Records § 20.120 Records available in Food and Drug...

21 CFR 20.120 - Records available in Food and Drug Administration Public Reading Rooms.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 1 2012-04-01 2012-04-01 false Records available in Food and Drug Administration Public Reading Rooms. 20.120 Section 20.120 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PUBLIC INFORMATION Availability of Specific Categories of Records § 20.120 Records available in Food and Drug...

Monitoring the availability of healthy and unhealthy foods and non-alcoholic beverages in community and consumer retail food environments globally.

PubMed

Ni Mhurchu, C; Vandevijvere, S; Waterlander, W; Thornton, L E; Kelly, B; Cameron, A J; Snowdon, W; Swinburn, B

2013-10-01

Retail food environments are increasingly considered influential in determining dietary behaviours and health outcomes. We reviewed the available evidence on associations between community (type, availability and accessibility of food outlets) and consumer (product availability, prices, promotions and nutritional quality within stores) food environments and dietary outcomes in order to develop an evidence-based framework for monitoring the availability of healthy and unhealthy foods and non-alcoholic beverages in retail food environments. Current evidence is suggestive of an association between community and consumer food environments and dietary outcomes; however, substantial heterogeneity in study designs, methods and measurement tools makes it difficult to draw firm conclusions. The use of standardized tools to monitor local food environments within and across countries may help to validate this relationship. We propose a step-wise framework to monitor and benchmark community and consumer retail food environments that can be used to assess density of healthy and unhealthy food outlets; measure proximity of healthy and unhealthy food outlets to homes/schools; evaluate availability of healthy and unhealthy foods in-store; compare food environments over time and between regions and countries; evaluate compliance with local policies, guidelines or voluntary codes of practice; and determine the impact of changes to retail food environments on health outcomes, such as obesity. © 2013 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of the International Association for the Study of Obesity.

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

USGS Publications Warehouse

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

2003-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Snow Mold Investigations in Eastern Washington

Treesearch

T. H. Filer; A. G. Law

1961-01-01

"Snow mold of turf" in the Pacific Northwest must include both Fusarium Patch caused by Calonectria graminicola (Berk and Br.) (conidial stage Fusarium nivale (Fr. ) CES.), and Gray snow mold caused by Typhula itoana Imai, which occur together to give a disease complex. Snow mold of turf is the most...

Photochemical degradation of PCBs in snow.

PubMed

Matykiewiczová, Nina; Klánová, Jana; Klán, Petr

2007-12-15

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

Loropetalum chinense 'Snow Panda'

USDA-ARS?s Scientific Manuscript database

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...

Relating trophic resources to community structure: a predictive index of food availability

PubMed Central

Edgar, Graham J.

2017-01-01

The abundance and the distribution of trophic resources available for consumers influence the productivity and the diversity of natural communities. Nevertheless, assessment of the actual abundance of food items available for individual trophic groups has been constrained by differences in methods and metrics used by various authors. Here we develop an index of food abundance, the framework of which can be adapted for different ecosystems. The relative available food index (RAFI) is computed by considering standard resource conditions of a habitat and the influence of various generalized anthropogenic and natural factors. RAFI was developed using published literature on food abundance and validated by comparison of predictions versus observed trophic resources across various marine sites. RAFI tables here proposed can be applied to a range of marine ecosystems for predictions of the potential abundance of food available for each trophic group, hence permitting exploration of ecological theories by focusing on the deviation from the observed to the expected. PMID:28386417

Unusually Low Snow Cover in the U.S.

NASA Technical Reports Server (NTRS)

2002-01-01

New maps of snow cover produced by NASA's Terra satellite show that this year's snow line stayed farther north than normal. When combined with land surface temperature measurements, the observations confirm earlier National Oceanic and Atmospheric Administration reports that the United States was unusually warm and dry this past winter. The above map shows snow cover over the continental United States from February 2002 and is based on data acquired by the Moderate-Resolution Imaging Spectroradiometer (MODIS). The amount of land covered by snow during this period was much lower than usual. With the exception of the western mountain ranges and the Great Lakes region, the country was mostly snow free. The solid red line marks the average location of the monthly snow extent; white areas are snow-covered ground. Snow was mapped at approximately 5 kilometer pixel resolution on a daily basis and then combined, or composited, every eight days. If a pixel was at least 50 percent snow covered during all of the eight-day periods that month, it was mapped as snow covered for the whole month. For more information, images, and animations, read: Terra Satellite Data Confirm Unusually Warm, Dry U.S. Winter Image by Robert Simmon, based on data from the MODIS Snow/Ice Global Mapping Project

MODIS Collection 6 Data at the National Snow and Ice Data Center (NSIDC)

NASA Astrophysics Data System (ADS)

Fowler, D. K.; Steiker, A. E.; Johnston, T.; Haran, T. M.; Fowler, C.; Wyatt, P.

2015-12-01

For over 15 years, the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) has archived and distributed snow and sea ice products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the NASA Earth Observing System (EOS) Aqua and Terra satellites. Collection 6 represents the next revision to NSIDC's MODIS archive, mainly affecting the snow-cover products. Collection 6 specifically addresses the needs of the MODIS science community by targeting the scenarios that have historically confounded snow detection and introduced errors into the snow-cover and fractional snow-cover maps even though MODIS snow-cover maps are typically 90 percent accurate or better under good observing conditions, Collection 6 uses revised algorithms to discriminate between snow and clouds, resolve uncertainties along the edges of snow-covered regions, and detect summer snow cover in mountains. Furthermore, Collection 6 applies modified and additional snow detection screens and new Quality Assessment protocols that enhance the overall accuracy of the snow maps compared with Collection 5. Collection 6 also introduces several new MODIS snow products, including a daily Climate Modelling Grid (CMG) cloud gap-filled (CGF) snow-cover map which generates cloud-free maps by using the most recent clear observations.. The MODIS Collection 6 sea ice extent and ice surface temperature algorithms and products are much the same as Collection 5; however, Collection 6 updates to algorithm inputs—in particular, the L1B calibrated radiances, land and water mask, and cloud mask products—have improved the sea ice outputs. The MODIS sea ice products are currently available at NSIDC, and the snow cover products are soon to follow in 2016 NSIDC offers a variety of methods for obtaining these data. Users can download data directly from an online archive or use the NASA Reverb Search & Order Tool to perform spatial, temporal, and parameter

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.

Noble Gas Signatures in Snow: a New Experimental Investigation.

NASA Astrophysics Data System (ADS)

Amalberti, J.; Hall, C. M.; Castro, C.

2016-12-01

Dissolved noble gases in groundwater (He, Ne, Ar, Kr, and Xe) have been widely used to improve our knowledge of surface and groundwater dynamics. However, a recent rainwater study [1] recorded noble gas concentration anomalies originating from conditions at high altitude. Potential anomaly sources might include fog, orographic rain, synoptic rain and snow, depending on the region considered. Here, we outline a methodology for measuring noble gases in freshly collected snow samples. Their fine-grained nature leads to significant experimental challenges. Overall, our results (Fig. 1) show that snow has elevated He concentrations with depleted concentrations of all other noble gases. Similar results have been recorded in ice [2, 3]. In addition, our results show relatively homogeneous (< 14%) He and Ne concentrations while Ar, Kr and Xe display large concentration variability (> 80%). These observations led us to investigate the structure of snow and potential host-sites (available empty space) within the crystal structure. Noble gases are chemically inert and do not form bonds that could affect the ice crystal structure. Therefore, host-sites control the solubility of each noble gas. Our results show that He and Ne, which are known to have small atomic radii, are likely dissolved into the ice/snow crystal lattice, while heavy noble gas (Ar, Kr and Xe) are likely accommodated into defects. Consequently, smaller variability recorded in light noble gases, may result from He and Ne being hosted within the crystal lattice, whereas heavy noble gases rely on the presence of defects, which may randomly appear within the structure during snow formation. These new results can be used to better constrain the source of ground ice [3], groundwater systems and to investigate the structural transition mechanisms from snow to firn and ice. Figure 1: Noble gas concentrations (C) in snow (filled circles symbols) and ice (half-filled square symbols) normalized to air saturated water

Snow depth spatial structure from hillslope to basin scale

NASA Astrophysics Data System (ADS)

Deems, J. S.

2017-12-01

Knowledge of spatial patterns of snow accumulation is required for understanding the hydrology, climatology, and ecology of mountain regions. Spatial structure in snow accumulation patterns changes with the scale of observation, a feature that has been characterized using fractal dimensions calculated from lidar-derived snow depth maps: fractal scaling structure at short length scales, with a `scale break' transition to more stochastic patterns at longer separation distances. Previous work has shown that this fractal structure of snow depth distributions differs between sites with different vegetation and terrain characteristics. Forested areas showed a transition to a nearly random spatial distribution at a much shorter lag distance than do unforested sites, enabling a statistical characterization. Alpine areas, however, showed strong spatial structure for a much wider scale range, and were the source of the dominant spatial pattern observable over a wider area. These spatial structure characteristics suggest that the choice of measurement or model resolution (satellite sensor, DEM, field survey point spacing, etc.) will strongly affect the estimates of snow volume or mass, as well as the magnitude of spatial variability. These prior efforts used data sets that were high resolution ( 1 m laser point spacing) but of limited extent ( 1 km2), constraining detection of scale features such as fractal dimension or scale breaks to areas of relatively similar characteristics and to lag distances of under 500 m. New datasets available from the NASA JPL Airborne Snow Observatory (ASO) provide similar resolution but over large areas, enabling assessment of snow spatial structure across an entire watershed, or in similar vegetation or physiography but in different parts of the basin. Additionally, the multi-year ASO time series allows an investigation into the temporal stability of these scale characteristics, within a single snow season and between seasons of strongly

SMRT: A new, modular snow microwave radiative transfer model

NASA Astrophysics Data System (ADS)

Picard, Ghislain; Sandells, Melody; Löwe, Henning; Dumont, Marie; Essery, Richard; Floury, Nicolas; Kontu, Anna; Lemmetyinen, Juha; Maslanka, William; Mätzler, Christian; Morin, Samuel; Wiesmann, Andreas

2017-04-01

Forward models of radiative transfer processes are needed to interpret remote sensing data and derive measurements of snow properties such as snow mass. A key requirement and challenge for microwave emission and scattering models is an accurate description of the snow microstructure. The snow microwave radiative transfer model (SMRT) was designed to cater for potential future active and/or passive satellite missions and developed to improve understanding of how to parameterize snow microstructure. SMRT is implemented in Python and is modular to allow easy intercomparison of different theoretical approaches. Separate modules are included for the snow microstructure model, electromagnetic module, radiative transfer solver, substrate, interface reflectivities, atmosphere and permittivities. An object-oriented approach is used with carefully specified exchanges between modules to allow future extensibility i.e. without constraining the parameter list requirements. This presentation illustrates the capabilities of SMRT. At present, five different snow microstructure models have been implemented, and direct insertion of the autocorrelation function from microtomography data is also foreseen with SMRT. Three electromagnetic modules are currently available. While DMRT-QCA and Rayleigh models need specific microstructure models, the Improved Born Approximation may be used with any microstructure representation. A discrete ordinates approach with stream connection is used to solve the radiative transfer equations, although future inclusion of 6-flux and 2-flux solvers are envisioned. Wrappers have been included to allow existing microwave emission models (MEMLS, HUT, DMRT-QMS) to be run with the same inputs and minimal extra code (2 lines). Comparisons between theoretical approaches will be shown, and evaluation against field experiments in the frequency range 5-150 GHz. SMRT is simple and elegant to use whilst providing a framework for future development within the

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

USDA-ARS?s Scientific Manuscript database

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...

Variations in snow cover seasonality across the Kyrgyz Republic from 2000 to 2016 revealed through MODIS Terra and Aqua snow products

NASA Astrophysics Data System (ADS)

Tomaszewska, M. A.; Henebry, G. M.

2017-12-01

The vertical transhumance practiced by herders in the highlands of Kyrgyzstan is vulnerable to environmental change. Herd movements and pasture conditions are both affected by spatial and temporal variations in snow cover and the timing of snowmelt. Early growing season soil moisture conditions affect the phenology and growth of vegetation, especially in the high elevation pastures used for summer forage. To evaluate snow seasonality, we examined three snow cover variables—the first day of snow (FDoS), the last day of snow (LDoS), and the duration of snow cover (DoSC) over 17 years based on 8-day snow product from MODIS Terra and Aqua (MOD/MYD10A2) across the Kyrgyz Republic (KYR). To track the "snow season" efficiently in the presence of snow-capped peaks, we start each snow season at day of year (DOY) 169, approximately the summer solstice, and extend to DOY 168 of the following year. To track the interannual variation of these variables, we applied two nonparametric statistics: the Mann-Kendall trend test and the Theil-Sen linear trend estimator. Our preliminary results focusing on four rayons in two oblasts indicate both large swaths of positive and negative significant trends over the different regions of the country. Positive trends in FDoS, meaning later snow arrival, were detected in parts of central KYR. Negative trends in FDoS meaning earlier arrival were detected at lower elevations in southwestern KYR. Earlier snowmelt (negative trend in LDoS) in eastern KYR resulted in a shorter snow season (negative trend in DoSC); in contrast, later snowmelt in southwestern KYR (positive trend in LDoS) resulted in a longer period of snow cover (positive trend of DoSC). We extend the analysis to the entire country and explore the influence of terrain attribites (elevation, slope, and aspect) and MODIS IGBP land cover type (MCD12Q1) on trends in snow cover seasonality. Additionally, we ran the trend tests for the Terra and Aqua snow products separately to evaluate

Race and food store availability in an inner-city neighbourhood.

PubMed

Galvez, Maida P; Morland, Kimberly; Raines, Cherita; Kobil, Jessica; Siskind, Jodi; Godbold, James; Brenner, Barbara

2008-06-01

A growing body of research has shown that disparities in resources, including food stores, exist at the neighbourhood level and the greatest disparities are seen in minority neighbourhoods, the same neighbourhoods at increased risk of obesity and diabetes. Less is known about whether differences in availability of resources by African American or Latino race/ethnicity exist within a single minority community. The present study examined whether census blocks either 75% African American (AA) or 75% Latino (L) are associated with food store availability, as compared with racially mixed (RM) census blocks, in East Harlem, New York. A cross-sectional study utilising a walking survey of East Harlem was performed. Food stores were classified into: supermarkets, grocery stores, convenience stores, specialty stores, full-service restaurants and fast-food stores. One hundred and sixty-five East Harlem census blocks were examined; 17 were AA, 34 were L and 114 were RM. Of AA census blocks, 100% had neither supermarkets nor grocery stores. AA census blocks were less likely to have convenience stores (prevalence ratio (PR) = 0.25, 95% confidence interval (CI) 0.07-0.86) compared with RM census blocks. In contrast, predominantly L census blocks were more likely to have convenience stores (PR = 1.8, 95% CI 1.20-2.70), specialty food stores (PR = 3.74, 95% CI 2.06-7.15), full-service restaurants (PR = 1.87, 95% CI 1.04-3.38) and fast-food restaurants (PR = 2.14, 95% CI 1.33-3.44) compared with RM census blocks. We found that inequities in food store availability exist by race/ethnicity in East Harlem, New York. This has implications for racial/ethnic differences in dietary quality, obesity and obesity-related disorders.

Complementary feeding recommendations based on locally available foods in Indonesia.

PubMed

Fahmida, Umi; Santika, Otte; Kolopaking, Risatianti; Ferguson, Elaine

2014-12-01

Affordable, locally contextual complementary feeding recommendations (CFRs) that take into account cultural diversity and differences in food availability will be more likely to result in long-term improvements in complementary feeding practices than general recommendations. More objective approaches, such as linear programming (LP), have been recommended to identify optimal but CFRs to meet nutrient requirements given local food availability, food patterns, food portions, and cost. To present results of our previous studies in which we developed CFRs using LP and to provide an example of how these CFRs can be put into practice in a community intervention trial in Indonesia. Dietary data were obtained using single 24-hour dietary recall or 1-day weighed diet record combined with 1-day 24-hour recall and 5-day food intake tally. With the use of the LP approach, nutrient intakes were optimized while ensuring that a realistic diet was selected by using constraints such as the diet's energy content, food patterns, food portions, and cost. The price per 100 g of edible portion was obtained from market surveys in two or three local markets in each study area. LP analysis was performed using Super Solver in MS Excel or Optifood software. Iron, zinc, calcium, and niacin were problem nutrients in all age groups of children (6 to 8, 9 to 11, and 12 to 23 months) in both rural and periurban areas, except among children of higher socioeconomic status in urban areas. Thiamin and folate were also problem nutrients found in some settings. Animal-source foods (meat, fish, poultry, and eggs [MFPE] and fortified foods were the nutrient-dense foods identified by LP to fill the nutrient gaps of these problem nutrients. Iron, calcium, zinc, niacin, and potentially folate and thiamine are typical "problem nutrients" in complementary foods of Indonesian children. However, the extent of dietary inadequacy varies across age groups, area, and socioeconomic level. MFPE and fortified foods

[Analysis of influencing factors of snow hyperspectral polarized reflections].

PubMed

Sun, Zhong-Qiu; Zhao, Yun-Sheng; Yan, Guo-Qian; Ning, Yan-Ling; Zhong, Gui-Xin

2010-02-01

Due to the need of snow monitoring and the impact of the global change on the snow, on the basis of the traditional research on snow, starting from the perspective of multi-angle polarized reflectance, we analyzed the influencing factors of snow from the incidence zenith angles, the detection zenith angles, the detection azimuth angles, polarized angles, the density of snow, the degree of pollution, and the background of the undersurface. It was found that these factors affected the spectral reflectance values of the snow, and the effect of some factors on the polarization hyperspectral reflectance observation is more evident than in the vertical observation. Among these influencing factors, the pollution of snow leads to an obvious change in the snow reflectance spectrum curve, while other factors have little effect on the shape of the snow reflectance spectrum curve and mainly impact the reflection ratio of the snow. Snow reflectance polarization information has not only important theoretical significance, but also wide application prospect, and provides new ideas and methods for the quantitative research on snow using the remote sensing technology.

Evaluation and time series analysis of mountain snow from MODIS and VIIRS fractional snow cover products

NASA Astrophysics Data System (ADS)

Bormann, K.; Rittger, K.; Painter, T. H.

2016-12-01

The continuation of large-scale snow cover records into the future is crucial for monitoring the impacts of global pressures such as climate change and weather variability on the cryosphere. With daily MODIS records since 2000 from a now ageing MODIS constellation (Terra & Aqua) and daily VIIRS records since 2012 from the Suomi-NPP platform, the consistency of information between the two optical sensors must be understood. First, we evaluated snow cover maps derived from both MODIS and VIIRS retrievals with coincident cloud-free Landsat 8 OLI maps across a range of locations. We found that both MODIS and VIIRS snow cover maps show similar errors when evaluated with Landsat OLI retrievals. Preliminary results also show a general agreement in regional snowline between the two sensors that is maintained during the spring snowline retreat where the proportion of mixed pixels is increased. The agreement between sensors supports the future use of VIIRS snow cover maps to continue the long-term record beyond the lifetime of MODIS. Second, we use snowline elevation to quantify large scale snow cover variability and to monitor potential changes in the rain/snow transition zone where climate change pressures may be enhanced. Despite the large inter-annual variability that is often observed in snow metrics, we expect that over the 16-year time series we will see a rise in seasonal elevation of the snowline and consequently an increasing rain/snow transition boundary in mountain environments. These results form the basis for global snowline elevation monitoring using optical remote sensing data and highlight regional differences in snowline elevation dynamics. The long-term variability in observed snowline elevation provides a recent climatology of mountain snowpack across several regions that will likely to be of interest to those interested in climate change impacts in mountain environments. This work will also be of interest to existing users of MODSCAG and VIIRSCAG snow

Small food stores and availability of nutritious foods: a comparison of database and in-store measures, Northern California, 2009.

PubMed

Kersten, Ellen; Laraia, Barbara; Kelly, Maggi; Adler, Nancy; Yen, Irene H

2012-01-01

Small food stores are prevalent in urban neighborhoods, but the availability of nutritious food at such stores is not well known. The objective of this study was to determine whether data from 3 sources would yield a single, homogenous, healthful food store category that can be used to accurately characterize community nutrition environments for public health research. We conducted in-store surveys in 2009 on store type and the availability of nutritious food in a sample of nonchain food stores (n = 102) in 6 predominantly urban counties in Northern California (Alameda, Contra Costa, Marin, Sacramento, San Francisco, and Santa Clara). We compared survey results with commercial database information and neighborhood sociodemographic data by using independent sample t tests and classification and regression trees. Sampled small food stores yielded a heterogeneous group of stores in terms of store type and nutritious food options. Most stores were identified as convenience (54%) or specialty stores (22%); others were small grocery stores (19%) and large grocery stores (5%). Convenience and specialty stores were smaller and carried fewer nutritious and fresh food items. The availability of nutritious food and produce was better in stores in neighborhoods that had a higher percentage of white residents and a lower population density but did not differ significantly by neighborhood income. Commercial databases alone may not adequately categorize small food stores and the availability of nutritious foods. Alternative measures are needed to more accurately inform research and policies that seek to address disparities in diet-related health conditions.

Small Food Stores and Availability of Nutritious Foods: A Comparison of Database and In-Store Measures, Northern California, 2009

PubMed Central

Laraia, Barbara; Kelly, Maggi; Adler, Nancy; Yen, Irene H.

2012-01-01

Introduction Small food stores are prevalent in urban neighborhoods, but the availability of nutritious food at such stores is not well known. The objective of this study was to determine whether data from 3 sources would yield a single, homogenous, healthful food store category that can be used to accurately characterize community nutrition environments for public health research. Methods We conducted in-store surveys in 2009 on store type and the availability of nutritious food in a sample of nonchain food stores (n = 102) in 6 predominantly urban counties in Northern California (Alameda, Contra Costa, Marin, Sacramento, San Francisco, and Santa Clara). We compared survey results with commercial database information and neighborhood sociodemographic data by using independent sample t tests and classification and regression trees. Results Sampled small food stores yielded a heterogeneous group of stores in terms of store type and nutritious food options. Most stores were identified as convenience (54%) or specialty stores (22%); others were small grocery stores (19%) and large grocery stores (5%). Convenience and specialty stores were smaller and carried fewer nutritious and fresh food items. The availability of nutritious food and produce was better in stores in neighborhoods that had a higher percentage of white residents and a lower population density but did not differ significantly by neighborhood income. Conclusion Commercial databases alone may not adequately categorize small food stores and the availability of nutritious foods. Alternative measures are needed to more accurately inform research and policies that seek to address disparities in diet-related health conditions. PMID:22789445

Fast food for family meals: relationships with parent and adolescent food intake, home food availability and weight status.

PubMed

Boutelle, Kerri N; Fulkerson, Jayne A; Neumark-Sztainer, Dianne; Story, Mary; French, Simone A

2007-01-01

The purpose of the present study was to examine the prevalence of fast-food purchases for family meals and the associations with sociodemographic variables, dietary intake, home food environment, and weight status in adolescents and their parents. This study is a cross-sectional evaluation of parent interviews and adolescent surveys from Project EAT (Eating Among Teens). Subjects included 902 middle-school and high-school adolescents (53% female, 47% male) and their parents (89% female, 11% male). The adolescent population was ethnically diverse: 29% white, 24% black, 21% Asian American, 14% Hispanic and 12% other. Results showed that parents who reported purchasing fast food for family meals at least 3 times per week were significantly more likely than parents who reported purchasing fewer fast-food family meals to report the availability of soda pop and chips in the home. Adolescents in homes with fewer than 3 fast-food family meals per week were significantly more likely than adolescents in homes with more fast-food family meals to report having vegetables and milk served with meals at home. Fast-food purchases for family meals were positively associated with the intake of fast foods and salty snack foods for both parents and adolescents; and weight status among parents. Fast-food purchases for family meals were negatively associated with parental vegetable intake. Fast-food purchases may be helpful for busy families, but families need to be educated on the effects of fast food for family meals and how to choose healthier, convenient family meals.

The Kühtai data set: 25 years of lysimetric, snow pillow, and meteorological measurements

PubMed Central

Kirnbauer, R.; Parajka, J.; Schöber, J.; Blöschl, G.

2017-01-01

Abstract Snow measurements at the Kühtai station in Tirol, Austria, (1920 m.a.s.l.) are described. The data set includes snow water equivalent from a 10 m2 snow pillow, snow melt outflow from a 10 m2 snow lysimeter placed at the same location as the pillow, meteorological data (precipitation, incoming shortwave radiation, reflected shortwave radiation, air temperature, relative air humidity, and wind speed), and other data (snow depths, snow temperatures at seven heights) from the period October 1990 to May 2015. All data have been quality checked, and gaps in the meteorological data have been filled in. The data set is unique in that all data are available at a temporal resolution of 15 min over a period of 25 years with minimal changes in the experimental setup. The data set can therefore be used to analyze snow pack processes over a long‐time period, including their extremes and long‐term changes, in an Alpine climate. Analyses may benefit from the combined measurement of snow water equivalent, lysimeter outflow, and precipitation at a wind‐sheltered alpine site. An example use of data shows the temporal variability of daily and 1 April snow water equivalent observed at the Kühtai site. The results indicate that the snow water equivalent maximum varies between 200 and more than 500 mm w.e., but there is no statistically significant temporal trend in the period 1990–2015. PMID:28931957

Snow hydrology in Mediterranean mountain regions: A review

NASA Astrophysics Data System (ADS)

Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; López-Moreno, Juan Ignacio; Drapeau, Laurent; Page, Michel Le; Escadafal, Richard

2017-08-01

Water resources in Mediterranean regions are under increasing pressure due to climate change, economic development, and population growth. Many Mediterranean rivers have their headwaters in mountainous regions where hydrological processes are driven by snowpack dynamics and the specific variability of the Mediterranean climate. A good knowledge of the snow processes in the Mediterranean mountains is therefore a key element of water management strategies in such regions. The objective of this paper is to review the literature on snow hydrology in Mediterranean mountains to identify the existing knowledge, key research questions, and promising technologies. We collected 620 peer-reviewed papers, published between 1913 and 2016, that deal with the Mediterranean-like mountain regions in the western United States, the central Chilean Andes, and the Mediterranean basin. A large amount of studies in the western United States form a strong scientific basis for other Mediterranean mountain regions. We found that: (1) the persistence of snow cover is highly variable in space and time but mainly controlled by elevation and precipitation; (2) the snowmelt is driven by radiative fluxes, but the contribution of heat fluxes is stronger at the end of the snow season and during heat waves and rain-on-snow events; (3) the snow densification rates are higher in these regions when compared to other climate regions; and (4) the snow sublimation is an important component of snow ablation, especially in high-elevation regions. Among the pressing issues is the lack of continuous ground observation in high-elevation regions. However, a few years of snow depth (HS) and snow water equivalent (SWE) data can provide realistic information on snowpack variability. A better spatial characterization of snow cover can be achieved by combining ground observations with remotely sensed snow data. SWE reconstruction using satellite snow cover area and a melt model provides reasonable information that

Estimating the snow water equivalent on a glacierized high elevation site (Forni Glacier, Italy)

NASA Astrophysics Data System (ADS)

Senese, Antonella; Maugeri, Maurizio; Meraldi, Eraldo; Verza, Gian Pietro; Azzoni, Roberto Sergio; Compostella, Chiara; Diolaiuti, Guglielmina

2018-04-01

We present and compare 11 years of snow data (snow depth and snow water equivalent, SWE) measured by an automatic weather station (AWS) and corroborated by data from field campaigns on the Forni Glacier in Italy. The aim of the analysis is to estimate the SWE of new snowfall and the annual SWE peak based on the average density of the new snow at the site (corresponding to the snowfall during the standard observation period of 24 h) and automated snow depth measurements. The results indicate that the daily SR50 sonic ranger measurements and the available snow pit data can be used to estimate the mean new snow density value at the site, with an error of ±6 kg m-3. Once the new snow density is known, the sonic ranger makes it possible to derive SWE values with an RMSE of 45 mm water equivalent (if compared with snow pillow measurements), which turns out to be about 8 % of the total SWE yearly average. Therefore, the methodology we present is interesting for remote locations such as glaciers or high alpine regions, as it makes it possible to estimate the total SWE using a relatively inexpensive, low-power, low-maintenance, and reliable instrument such as the sonic ranger.

Plausibility check of a redesigned rain-on-snow simulator (RASA)

NASA Astrophysics Data System (ADS)

Rössler, Ole; Probst, Sabine; Weingartner, Rolf

2016-04-01

Rain-on-snow events are fascinating but still not completely understood processes. Although, several studies and equations have been published since decades that describe past events and theoretical descriptions, empirical data of what is happening in the snow cover is far less available. A way to fill this gap of empirical data, rain-on-snow-simulators might be of help. In 2013, Juras et al. published their inspiring idea of a portable rain-on-snow simulator. The huge advantage of this devise - in contrast to other purely field-based experiments - are their fixed, and mostly standardized conditions and the possibility to measure all required data to monitor the water fluxes and melting processes at a time. Mounted in a convenient location, a large number of experiments are relatively easy conductible. We applied and further developed the original device and plausified the results of this redesigned version, called RASA. The principal design was borrowed from the original version being a frame with a sprinkler on top and a snow sample in a box at the bottom, from which the outflow is measured with a tipping gauge. We added a moving sprinkling plate to ensure a uniform distribution of raindrops on the snow, and - most importantly - we suspended the watered snow sampled on weighting cells. The latter enables to continuous measurement of the snow sample throughout the experiment and thus the indirect quantification of liquid water saturation, water holding capacity, and snowmelt amount via balance equations. As it is remains unclear if this device is capable to reproduce known processes, a hypothesis based plausibility check was accomplished. Thus, eight hypothesizes were derived from literature and tested in 28 experiments with the RASA mounted at 2000 m elevation. In general, we were able to reproduce most of the hypotheses. The RASA proved to be a very valuable device that can generate suitable results and has the potential to extend the empirical-experimental data

Routine Mapping of the Snow Depth Distribution on Sea Ice

NASA Astrophysics Data System (ADS)

Farrell, S. L.; Newman, T.; Richter-Menge, J.; Dattler, M.; Paden, J. D.; Yan, S.; Li, J.; Leuschen, C.

2016-12-01

The annual growth and retreat of the polar sea ice cover is influenced by the seasonal accumulation, redistribution and melt of snow on sea ice. Due to its high albedo and low thermal conductivity, snow is also a controlling parameter in the mass and energy budgets of the polar climate system. Under a changing climate scenario it is critical to obtain reliable and routine measurements of snow depth, across basin scales, and long time periods, so as to understand regional, seasonal and inter-annual variability, and the subsequent impacts on the sea ice cover itself. Moreover the snow depth distribution remains a significant source of uncertainty in the derivation of sea ice thickness from remote sensing measurements, as well as in numerical model predictions of future climate state. Radar altimeter systems flown onboard NASA's Operation IceBridge (OIB) mission now provide annual measurements of snow across both the Arctic and Southern Ocean ice packs. We describe recent advances in the processing techniques used to interpret airborne radar waveforms and produce accurate and robust snow depth results. As a consequence of instrument effects and data quality issues associated with the initial release of the OIB airborne radar data, the entire data set was reprocessed to remove coherent noise and sidelobes in the radar echograms. These reprocessed data were released to the community in early 2016, and are available for improved derivation of snow depth. Here, using the reprocessed data, we present the results of seven years of radar measurements collected over Arctic sea ice at the end of winter, just prior to melt. Our analysis provides the snow depth distribution on both seasonal and multi-year sea ice. We present the inter-annual variability in snow depth for both the Central Arctic and the Beaufort/Chukchi Seas. We validate our results via comparison with temporally and spatially coincident in situ measurements gathered during many of the OIB surveys. The results

Estimation of snow line elevation changes from MODIS snow cover data

NASA Astrophysics Data System (ADS)

Parajka, Juraj; Bezak, Nejc; Burkhart, John; Holko, Ladislav; Hundecha, Yeshewa; Krajči, Pavel; Mangini, Walter; Molnar, Peter; Sensoy, Aynur; Riboust, Phillippe; Rizzi, Jonathan; Thirel, Guillaume; Arheimer, Berit

2017-04-01

This contribution evaluates changes in snowline elevation during snowmelt runoff events in selected basins from Austria, France, Norway, Slovakia, Slovenia, Sweden, Switzerland and Turkey. The main objectives are to investigate the spatial and temporal differences in regional snowline elevation (RSLE) across Europe and to discuss the factors which control its change. The analysis is performed in two steps. In the first, the regional snowline elevation is processed from daily MODIS snow cover data (MOD10A1) by using the methodology of Krajčí et al., (2014). In the second step, the changes in RSLE are analysed for selected flood events in the period 2000-2015. The snowmelt runoff events are extracted from Catalogue of identified flood peaks from GRDC dataset (FLOOD TYPE experiment) available at http://www.water-switch-on.eu/sip-webclient/byod/#/resource/12056. The results will be discussed in terms of: (a) availability and potential of MODIS snow cover data for identifying RSLE changes during snowmelt runoff events, (b) spatial and temporal patterns of RSLE changes across Europe and (c) factor controlling the RSLE change. The analysis is performed as an experiment in Virtual Water Science Laboratory of SWITCH-ON Project (http://www.water-switch-on.eu/). All data, tools and results of the analysis will be open and accessible through the Spatial Information Platform of the Project (http://www.water-switch-on.eu/sip-webclient/byod/). We believe that such strategy will allow to improve and forward comparative research and cooperation between different partners in hydrology (Ceola et al., 2015). References Ceola, S., Arheimer, B., Baratti, E., Blöschl, G., Capell, R., Castellarin, A., Freer, J., Han, D., Hrachowitz, M., Hundecha, Y., Hutton, C., Lindström, G., Montanari, A., Nijzink, R., Parajka, J., Toth, E., Viglione, A., and Wagener, T.: Virtual laboratories: new opportunities for collaborative water science, Hydrol. Earth Syst. Sci., 19, 2101-2117, doi:10

An Integrated Uncertainty Analysis and Ensemble-based Data Assimilation Framework for Operational Snow Predictions

NASA Astrophysics Data System (ADS)

He, M.; Hogue, T. S.; Franz, K.; Margulis, S. A.; Vrugt, J. A.

2009-12-01

The National Weather Service (NWS), the agency responsible for short- and long-term streamflow predictions across the nation, primarily applies the SNOW17 model for operational forecasting of snow accumulation and melt. The SNOW17-forecasted snowmelt serves as an input to a rainfall-runoff model for streamflow forecasts in snow-dominated areas. The accuracy of streamflow predictions in these areas largely relies on the accuracy of snowmelt. However, no direct snowmelt measurements are available to validate the SNOW17 predictions. Instead, indirect measurements such as snow water equivalent (SWE) measurements or discharge are typically used to calibrate SNOW17 parameters. In addition, the forecast practice is inherently deterministic, lacking tools to systematically address forecasting uncertainties (e.g., uncertainties in parameters, forcing, SWE and discharge observations, etc.). The current research presents an Integrated Uncertainty analysis and Ensemble-based data Assimilation (IUEA) framework to improve predictions of snowmelt and discharge while simultaneously providing meaningful estimates of the associated uncertainty. The IUEA approach uses the recently developed DiffeRential Evolution Adaptive Metropolis (DREAM) to simultaneously estimate uncertainties in model parameters, forcing, and observations. The robustness and usefulness of the IUEA-SNOW17 framework is evaluated for snow-dominated watersheds in the northern Sierra Mountains, using the coupled IUEA-SNOW17 and an operational soil moisture accounting model (SAC-SMA). Preliminary results are promising and indicate successful performance of the coupled IUEA-SNOW17 framework. Implementation of the SNOW17 with the IUEA is straightforward and requires no major modification to the SNOW17 model structure. The IUEA-SNOW17 framework is intended to be modular and transferable and should assist the NWS in advancing the current forecasting system and reinforcing current operational forecasting skill.

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.

The effect of fast-food availability on fast-food consumption and obesity among rural residents: an analysis by race/ethnicity.

PubMed

Dunn, Richard A; Sharkey, Joseph R; Horel, Scott

2012-01-01

Rural areas of the United States tend to have higher obesity rates than urban areas, particularly in regions with high proportions of non-white residents. This paper analyzes the effect of fast-food availability on the level of fast-food consumption and obesity risk among both white and non-white residents of central Texas. Potential endogeneity of fast-food availability is addressed through instrumental variables regression using distance to the nearest major highway as an instrument. We find that non-whites tend to exhibit higher obesity rates, greater access to fast-food establishments and higher consumption of fast-food meals compared to their white counterparts. In addition, we found that whites and non-whites respond differently to the availability of fast-food in rural environments. Greater availability is not associated with either greater consumption of fast-food meals or a higher obesity risk among the sample of whites. In contrast, greater availability of fast-food is positively associated with both the number of meals consumed for non-white rural residents and their obesity. While our results are robust to specification, the effect of availability on weight outcomes is notably weaker when indirectly calculated from the implied relationship between consumption and caloric intake. This highlights the importance of directly examining the proposed mechanism through which an environmental factor influences weight outcomes. Copyright © 2011 Elsevier B.V. All rights reserved.

Mapping snow depth in open alpine terrain from stereo satellite imagery

NASA Astrophysics Data System (ADS)

Marti, R.; Gascoin, S.; Berthier, E.; de Pinel, M.; Houet, T.; Laffly, D.

2016-07-01

To date, there is no definitive approach to map snow depth in mountainous areas from spaceborne sensors. Here, we examine the potential of very-high-resolution (VHR) optical stereo satellites to this purpose. Two triplets of 0.70 m resolution images were acquired by the Pléiades satellite over an open alpine catchment (14.5 km2) under snow-free and snow-covered conditions. The open-source software Ame's Stereo Pipeline (ASP) was used to match the stereo pairs without ground control points to generate raw photogrammetric clouds and to convert them into high-resolution digital elevation models (DEMs) at 1, 2, and 4 m resolutions. The DEM differences (dDEMs) were computed after 3-D coregistration, including a correction of a -0.48 m vertical bias. The bias-corrected dDEM maps were compared to 451 snow-probe measurements. The results show a decimetric accuracy and precision in the Pléiades-derived snow depths. The median of the residuals is -0.16 m, with a standard deviation (SD) of 0.58 m at a pixel size of 2 m. We compared the 2 m Pléiades dDEM to a 2 m dDEM that was based on a winged unmanned aircraft vehicle (UAV) photogrammetric survey that was performed on the same winter date over a portion of the catchment (3.1 km2). The UAV-derived snow depth map exhibits the same patterns as the Pléiades-derived snow map, with a median of -0.11 m and a SD of 0.62 m when compared to the snow-probe measurements. The Pléiades images benefit from a very broad radiometric range (12 bits), allowing a high correlation success rate over the snow-covered areas. This study demonstrates the value of VHR stereo satellite imagery to map snow depth in remote mountainous areas even when no field data are available.

Planetesimal formation starts at the snow line

NASA Astrophysics Data System (ADS)

Drążkowska, J.; Alibert, Y.

2017-12-01

Context. The formation stage of planetesimals represents a major gap in our understanding of the planet formation process. Late-stage planet accretion models typically make arbitrary assumptions about planetesimal and pebble distribution, while dust evolution models predict that planetesimal formation is only possible at some orbital distances. Aims: We wish to test the importance of the water snow line in triggering the formation of the first planetesimals during the gas-rich phase of a protoplanetary disk, when cores of giant planets have to form. Methods: We connected prescriptions for gas disk evolution, dust growth and fragmentation, water ice evaporation and recondensation, the transport of both solids and water vapor, and planetesimal formation via streaming instability into a single one-dimensional model for protoplanetary disk evolution. Results: We find that processes taking place around the snow line facilitate planetesimal formation in two ways. First, because the sticking properties between wet and dry aggregates change, a "traffic jam" inside of the snow line slows the fall of solids onto the star. Second, ice evaporation and outward diffusion of water followed by its recondensation increases the abundance of icy pebbles that trigger planetesimal formation via streaming instability just outside of the snow line. Conclusions: Planetesimal formation is hindered by growth barriers and radial drift and thus requires particular conditions to take place. The snow line is a favorable location where planetesimal formation is possible for a wide range of conditions, but not in every protoplanetary disk model, however. This process is particularly promoted in large cool disks with low intrinsic turbulence and an increased initial dust-to-gas ratio. The movie attached to Fig. 3 is only available at http://www.aanda.org

Putting humans in the loop: Using crowdsourced snow information to inform water management

NASA Astrophysics Data System (ADS)

Fedorov, Roman; Giuliani, Matteo; Castelletti, Andrea; Fraternali, Piero

2016-04-01

The unprecedented availability of user generated data on the Web due to the advent of online services, social networks, and crowdsourcing, is opening new opportunities for enhancing real-time monitoring and modeling of environmental systems based on data that are public, low-cost, and spatio-temporally dense, possibly contributing to our ability of making better decisions. In this work, we contribute a novel crowdsourcing procedure for computing virtual snow indexes from public web images, either produced by users or generated by touristic webcams, which is based on a complex architecture designed for automatically crawling content from multiple web data sources. The procedure retains only geo-tagged images containing a mountain skyline, identifies the visible peaks in each image using a public online digital terrain model, and classifies the mountain image pixels as snow or no-snow. This operation yields a snow mask per image, from which it is possible to extract time series of virtual snow indexes representing a proxy of the snow covered area. The value of the obtained virtual snow indexes is estimated in a real world water management problem. We consider the snow-dominated catchment of Lake Como, a regulated lake in Northern Italy, where snowmelt represents the most important contribution to seasonal lake storage, and we used the virtual snow indexes for informing the daily operation of the lake's dam. Numerical results show that such information is effective in extending the anticipation capacity of the lake operations, ultimately improving the system performance.

Effect of snow cover on soil frost penetration

NASA Astrophysics Data System (ADS)

Rožnovský, Jaroslav; Brzezina, Jáchym

2017-12-01

Snow cover occurrence affects wintering and lives of organisms because it has a significant effect on soil frost penetration. An analysis of the dependence of soil frost penetration and snow depth between November and March was performed using data from 12 automated climatological stations located in Southern Moravia, with a minimum period of measurement of 5 years since 2001, which belong to the Czech Hydrometeorological institute. The soil temperatures at 5 cm depth fluctuate much less in the presence of snow cover. In contrast, the effect of snow cover on the air temperature at 2 m height is only very small. During clear sky conditions and no snow cover, soil can warm up substantially and the soil temperature range can be even higher than the range of air temperature at 2 m height. The actual height of snow is also important - increased snow depth means lower soil temperature range. However, even just 1 cm snow depth substantially lowers the soil temperature range and it can therefore be clearly seen that snow acts as an insulator and has a major effect on soil frost penetration and soil temperature range.

Snow multivariable data assimilation for hydrological predictions in mountain areas

NASA Astrophysics Data System (ADS)

Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

2016-04-01

The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground

Iowa's cooperative snow fence program.

DOT National Transportation Integrated Search

2005-06-01

While we cant keep it from blowing, there are ways to influence the wind that carries tons : of blowing and drifting snow. Periodically, severe winter storms will create large snow : drifts that close roads and driveways, isolate farmsteads and in...

BOREAS HYD-2 Estimated Snow Water Equivalent (SWE) from Microwave Measurements

NASA Technical Reports Server (NTRS)

Powell, Hugh; Chang, Alfred T. C.; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Smith, David E. (Technical Monitor)

2000-01-01

The surface meteorological data collected at the Boreal Ecosystem-Atmosphere Study (BOREAS) tower and ancillary sites are being used as inputs to an energy balance model to monitor the amount of snow storage in the boreal forest region. The BOREAS Hydrology (HYD)-2 team used Snow Water Equivalent (SWE) derived from an energy balance model and in situ observed SWE to compare the SWE inferred from airborne and spaceborne microwave data, and to assess the accuracy of microwave retrieval algorithms. The major external measurements that are needed are snowpack temperature profiles, in situ snow areal extent, and SWE data. The data in this data set were collected during February 1994 and cover portions of the Southern Study Area (SSA), Northern Study Area (NSA), and the transect areas. The data are available from BORIS as comma-delimited tabular ASCII files. The SWE 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).

[Effects of seasonal snow cover on soil nitrogen transformation in alpine ecosystem: a review].

PubMed

Liu, Lin; Wu, Yan; He, Yi-xin; Wu, Ning; Sun, Geng; Zhang, Lin; Xu, Jun-jun

2011-08-01

Seasonal snow cover has pronounced effects on the soil nitrogen concentration and transformation in alpine ecosystem. Snowfall is an important form of nitrogen deposition, which directly affects the content of soil available nitrogen. Different depths and different duration of snow cover caused by snowfall may lead the heterogeneity of abiotic factors (soil temperature and moisture) and biotic factors (soil microbes, alpine plants, and alpine animals), and further, produce complicated effects on the mineralization and immobilization of soil nitrogen. This paper introduced in emphasis the inherent mechanisms of soil nitrogen mineralization and leaching under the effects of frequent freeze-thaw events during the durative melting of snow cover, and summarized the main research results of field in situ experiments about the effects of seasonal snow cover on soil nitrogen in alpine ecosystem based on the possible changes in snow cover in the future. Some suggestions with regard to the effects of seasonal snow cover on soil nitrogen were put forward.

SWEAT: Snow Water Equivalent with AlTimetry

NASA Astrophysics Data System (ADS)

Agten, Dries; Benninga, Harm-Jan; Diaz Schümmer, Carlos; Donnerer, Julia; Fischer, Georg; Henriksen, Marie; Hippert Ferrer, Alexandre; Jamali, Maryam; Marinaci, Stefano; Mould, Toby JD; Phelan, Liam; Rosker, Stephanie; Schrenker, Caroline; Schulze, Kerstin; Emanuel Telo Bordalo Monteiro, Jorge

2017-04-01

To study how the water cycle changes over time, satellite and airborne remote sensing missions are typically employed. Over the last 40 years of satellite missions, the measurement of true water inventories stored in sea and land ice within the cryosphere have been significantly hindered by uncertainties introduced by snow cover. Being able to determine the thickness of this snow cover would act to reduce such error, improving current estimations of hydrological and climate models, Earth's energy balance (albedo) calculations and flood predictions. Therefore, the target of the SWEAT (Snow Water Equivalent with AlTimetry) mission is to directly measure the surface Snow Water Equivalent (SWE) on sea and land ice within the polar regions above 60°and below -60° latitude. There are no other satellite missions currently capable of directly measuring SWE. In order to achieve this, the proposed mission will implement a novel combination of Ka- and Ku-band radioaltimeters (active microwave sensors), capable of penetrating into the snow microstructure. The Ka-band altimeter (λ ≈ 0.8 cm) provides a low maximum snow pack penetration depth of up to 20 cm for dry snow at 37 GHz, since the volume scattering of snow dominates over the scattering caused by the underlying ice surface. In contrast, the Ku-band altimeter (λ ≈ 2 cm) provides a high maximum snowpack penetration depth of up to 15 m in high latitudes regions with dry snow, as volume scattering is decreased by a factor of 55. The combined difference in Ka- and Ku-band signal penetration results will provide more accurate and direct determination of SWE. Therefore, the SWEAT mission aims to improve estimations of global SWE interpreted from passive microwave products, and improve the reliability of numerical snow and climate models.

Aeolian snow transport from wind tunnel experiments

NASA Astrophysics Data System (ADS)

Paterna, E.; Crivelli, P.; Lehning, M.

2016-12-01

Aeolian snow transport 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 Aeolian snow transport. The dynamics of snow saltation has a high impact on the land surface processes shaping these regions. More specifically, the observed high intermittency of saltation fluxes poses a problem for saltation models and needs to be better understood. We therefore aimed at unveiling the mechanisms underlying snow saltation at different saltation strengths and its coupling with the turbulent fluctuations of the wind. We conducted wind tunnel measurements of the momentum and mass-fluxes during snow saltation. For the mass-flux measurements we employed a shadowgraphy system which acquires images of the snow particle's shadows at high spatial and temporal resolution. The size and displacement of the particles are then determined by means of image analysis and Particle Tracking Velocimetry (PTV), allowing to estimate both snow mass-flux and flow velocity. Our controlled wind tunnel experiments revealed the existence of two regimes of saltation. In a turbulence-dependent regime occurring during weak saltation activity, we observed a strong coupling between snow transport and turbulent flow. Conversely during stronger saltation activity a turbulence-independent regime emerges, where the saltation develops its own length scale and it efficiently decouples from the wind fluctuations. We argue that different entrainment mechanisms could explain the existence of the two different saltation regimes as well as the observed high level of mass-flux intermittency.

Snow Storm Blankets Southeastern U.S.

NASA Technical Reports Server (NTRS)

2002-01-01

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

Snow and Ice Crust Changes over Northern Eurasia since 1966

NASA Astrophysics Data System (ADS)

Bulygina, O.; Groisman, P. Y.; Razuvaev, V.; Radionov, V.

2009-12-01

When temperature of snow cover reaches zero Celsius first time since its establishment, snowmelt starts. In many parts of the world this process can be lengthy. The initial amount of heat that “arrives” to the snowpack might be insufficient for complete snowmelt, during the colder nights re-freeze of the melted snow may occur (thus creating the ice crust layers), and a new cold front (or the departure of the warm front that initiated melt) can decrease temperatures below the freezing point again and stop the snowmelt completely. It well can be that first such snowmelt occurs in winter (thaw day) and for several months thereafter snowpack stays on the ground. However, even the first such melt initiates a process of snow metamorphosis on its surface changing snow albedo and generating snow crust as well as on its bottom generating ice crust. Once emerged, the crusts will not disappear until the complete snowmelt. Furthermore, these crusts have numerous pathways of impact on the wild birds and animals in the Arctic environment as well as on domesticated reindeers. In extreme cases, the crusts may kill some wild species and prevent reindeers’ migration and feeding. Ongoing warming in high latitudes created situations when in the western half of Eurasian continent days with thaw became more frequent. Keeping in mind potential detrimental impacts of winter thaws and associated with them snow/ice crust development, it is worthwhile to study directly what are the major features of snow and ice crust over Eurasia and what is their dynamics. For the purpose of this study, we employed the national snow survey data set archived at the Russian Institute for Hydrometeorological Information. The dataset has routine snow surveys run throughout the cold season each decade (during the intense snowmelt, each 5 days) at all meteorological stations of the former USSR, thereafter, in Russia since 1966. Prior to 1966 snow surveys are also available but the methodology of

Growth of black brant and lesser snow goose goslings in northern Alaska

USGS Publications Warehouse

Hupp, Jerry W.; Ward, David H.; Hogrefe, Kyle R.; Sedinger, James S.; Martin, Philip D.; Stickney, Alice A; Obritschkewitsch, Tim

2017-01-01

Gosling body mass can affect first year survival, recruitment, adult body size, and future fecundity of geese, and can serve as an indicator of forage availability and quality on brood-rearing areas. From 2012–2014 we measured body mass of 76 black brant (Branta bernicla nigricans) and 268 lesser snow goose (Chen caerulescens caerulescens) goslings of known age on the Colville River Delta (CRD) of northern Alaska to determine if there was evidence of density-dependent declines in gosling growth following recent population increases of those species and sympatric greater white-fronted geese (Anser albifrons frontalis). We contrasted contemporary body mass of brant goslings and forage biomass in brood-rearing habitats that were shared by all species, with measures obtained on, and near the CRD in the 1990s, prior to the establishment of snow goose nesting colonies in the area. Body mass of brant goslings recaptured between 25 and 32 days of age had not changed over the past 2 decades, despite an influx of snow geese, and increases in populations of brant and white-fronted geese. At 30 days of age, body mass of brant goslings on the CRD was 100–400 g heavier than for brant goslings of the same age on the Yukon-Kuskokwim Delta (YKD), Alaska. Contemporary biomass of grazed Carex subspathacea on CRD brood-rearing areas was comparable to the 1990s and was 2–4 times greater than for the same plant community on the YKD. Historical data on growth of snow goose goslings were not available for the CRD. However, average body mass of 34-day-old snow goose goslings was >230 g heavier than for conspecifics of the same age in the Hudson Bay region. We conclude that the establishment of nesting snow geese on the CRD has not negatively affected brant gosling growth, and that recent population increases of all species have likely not been constrained by forage availability on brood-rearing areas. Barring demographic changes elsewhere in their annual cycles, we predict that

Performance evaluation of snow and ice plows.

DOT National Transportation Integrated Search

2015-11-01

Removal of ice and snow from road surfaces is a critical task in the northern tier of the United States, : including Illinois. Highways with high levels of traffic are expected to be cleared of snow and ice quickly : after each snow storm. This is ne...

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.

The potency of fluvoxamine to reduce ethanol self-administration decreases with concurrent availability of food.

PubMed

Ginsburg, Brett C; Pinkston, Jonathan W; Lamb, Richard J

2012-04-01

The selective serotonin reuptake inhibitor fluvoxamine reduces responding for ethanol at lower doses than responding for food when each is available in separate components or separate groups of rats. However, when both are available concurrently and deliveries earned per session are equal, this apparent selectivity inverts and food-maintained behavior is more sensitive than ethanol-maintained behavior to rate-decreasing effects of fluvoxamine. Here, we investigated further the impact that concurrent access to both food and ethanol has on the potency of fluvoxamine. Fluvoxamine (5.6-17.8 mg/kg) potency was assessed under conditions in which food and ethanol were available concurrently and response rates were equal [average variable intervals (VIs) 405 and 14 s for food and ethanol, respectively], as well as when density of food delivery was increased (average VI 60 s for food and VI 14 s for ethanol). The potency of fluvoxamine was also determined when only ethanol was available (food extinction and average VI 14 s for ethanol) and under multiple VIs (VI 30 s for food and ethanol) wherein either food or ethanol was the only programmed reinforcement available during each component. Fluvoxamine was less potent at decreasing ethanol self-administration when food was available concurrently {ED50 [95% confidence limit (CL): 8.2 (6.5-10.3) and 10.7 (7.9-14.4)]} versus when ethanol was available in isolation [ED50: 4.0 (2.7-5.9) and 5.1 (4.3-6.0)]. Effects on food were similar under each condition in which food was available. The results demonstrate that the potency of fluvoxamine in reducing ethanol-maintained behavior depends on whether ethanol is available in isolation or in the context of concurrently scheduled food reinforcement.

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.

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.

SnopViz, an interactive snow profile visualization tool

NASA Astrophysics Data System (ADS)

Fierz, Charles; Egger, Thomas; gerber, Matthias; Bavay, Mathias; Techel, Frank

2016-04-01

SnopViz is a visualization tool for both simulation outputs of the snow-cover model SNOWPACK and observed snow profiles. It has been designed to fulfil the needs of operational services (Swiss Avalanche Warning Service, Avalanche Canada) as well as offer the flexibility required to satisfy the specific needs of researchers. This JavaScript application runs on any modern browser and does not require an active Internet connection. The open source code is available for download from models.slf.ch where examples can also be run. Both the SnopViz library and the SnopViz User Interface will become a full replacement of the current research visualization tool SN_GUI for SNOWPACK. The SnopViz library is a stand-alone application that parses the provided input files, for example, a single snow profile (CAAML file format) or multiple snow profiles as output by SNOWPACK (PRO file format). A plugin architecture allows for handling JSON objects (JavaScript Object Notation) as well and plugins for other file formats may be added easily. The outputs are provided either as vector graphics (SVG) or JSON objects. The SnopViz User Interface (UI) is a browser based stand-alone interface. It runs in every modern browser, including IE, and allows user interaction with the graphs. SVG, the XML based standard for vector graphics, was chosen because of its easy interaction with JS and a good software support (Adobe Illustrator, Inkscape) to manipulate graphs outside SnopViz for publication purposes. SnopViz provides new visualization for SNOWPACK timeline output as well as time series input and output. The actual output format for SNOWPACK timelines was retained while time series are read from SMET files, a file format used in conjunction with the open source data handling code MeteoIO. Finally, SnopViz is able to render single snow profiles, either observed or modelled, that are provided as CAAML-file. This file format (caaml.org/Schemas/V5.0/Profiles/SnowProfileIACS) is an international

Genetic differentiation between sympatric and allopatric wintering populations of Snow Geese

USGS Publications Warehouse

Humphries, E.M.; Peters, J.L.; Jonsson, J.E.; Stone, R.; Afton, A.D.; Omland, K.E.

2009-01-01

Blackwater National Wildlife Refuge on the Delmarva Peninsula, Maryland, USA has been the wintering area of a small population of Lesser Snow Geese (Chen caerulescens caerulescens; LSGO) since the 1930s. Snow Geese primarily pair in wintering areas and gene flow could be restricted between this and other LSGO wintering populations. Winter pair formation also could facilitate interbreeding with sympatric but morphologically differentiated Greater Snow Geese (C. c. atlantica; GSGO).We sequenced 658 bp of the mitochondrial DNA control region for 68 Snow Geese from East Coast and Louisiana wintering populations to examine the level of genetic differentiation among populations and subspecies. We found no evidence for genetic differentiation between LSGO populations but, consistent with morphological differences, LSGO and GSGO were significantly differentiated. We also found a lack of genetic differentiation between different LSGO morphotypes from Louisiana. We examined available banding data and found the breeding range of Delmarva LSGO overlaps extensively with LSGO that winter in Louisiana, and documented movements between wintering populations. Our results suggest the Delmarva population of LSGO is not a unique population unit apart from Mid-Continent Snow Geese. ?? 2009 by the Wilson Ornithological Society.

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

USGS Publications Warehouse

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

1985-01-01

Snow-cover data are needed for many facets of hydrology. The variation in snow cover over small areas is the focus of this study. 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 was- evaluated. 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 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 coirse, about two-thirds of the aerial snow-survey data agreed with the ground snow-survey data within the accuracy of the aerial technique ( + 0.5 inch of the mean snow water equivalent).

Snow mapping from space platforms

NASA Technical Reports Server (NTRS)

Itten, K. I.

1980-01-01

The paper considers problems of optimum resolution, periodicity, and wavelength bands used for snow mapping. Analog and digital methods were used for application of satellite data; techniques were developed for producing steamflow forecasts, hydroelectric power generation regulation data, irrigation potentials, and information on the availability of drinking water supplies. Future systems will utilize improved spectral band selection, new spectral regions, higher repetition rates, and more rapid access to satellite data.

Mapping Access to Community-Developed Healthy Food Baskets Including Cost and Availability

ERIC Educational Resources Information Center

Ginn, Alison; Majumdar, Anne; Carr, Marimba; Eastwood, Ginny; Menger, Beth

2016-01-01

Background: Food security is a topical issue but one that can be difficult to measure. Objective: To develop a community-approved food basket tool and use this to investigate the availability and affordability of a healthy diet in a multicultural urban setting. Design: A 7-day healthy food basket (HFB) containing 96 foods for six household types…

Snow distribution and heat flow in the taiga

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 increasemore » can be a significant percentage of the total winter energy exchange.« less

Convenience stores are the key food environment influence on nutrients available from household food supplies in Texas Border Colonias.

PubMed

Sharkey, Joseph R; Dean, Wesley R; Nalty, Courtney C; Xu, Jin

2013-01-17

Few studies have focused on the relationship between the retail food environment and household food supplies. This study examines spatial access to retail food stores, food shopping habits, and nutrients available in household food supplies among 50 Mexican-origin families residing in Texas border colonias. The design was cross-sectional; data were collected in the home March to June 2010 by promotora-researchers. Ground-truthed methods enumerated traditional (supercenters, supermarkets, grocery stores), convenience (convenience stores and food marts), and non-traditional (dollar stores, discount stores) retail food stores. Spatial access was computed using the network distance from each participant's residence to each food store. Data included survey data and two household food inventories (HFI) of the presence and amount of food items in the home. The Spanish language interviewer-administered survey included demographics, transportation access, food purchasing, food and nutrition assistance program participation, and the 18-item Core Food Security Module. Nutrition Data Systems for Research (NDS-R) was used to calculate HFI nutrients. Adult equivalent adjustment constants (AE), based on age and gender calorie needs, were calculated based on the age- and gender composition of each household and used to adjust HFI nutrients for household composition. Data were analyzed using bivariate analysis and linear regression models to determine the association of independent variables with the availability of each AE-adjusted nutrient. Regression models showed that households in which the child independently purchased food from a convenience store at least once a week had foods and beverages with increased amounts of total energy, total fat, and saturated fat. A greater distance to the nearest convenience store was associated with reduced amounts of total energy, vitamin D, total sugar, added sugar, total fat, and saturated fat. Participation in the National School Lunch

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

Changing snow seasonality in the highlands of Kyrgyzstan

NASA Astrophysics Data System (ADS)

Tomaszewska, Monika A.; Henebry, Geoffrey M.

2018-06-01

Few studies have examined changing snow seasonality in Central Asia. Here, we analyzed changes in the seasonality of snow cover across Kyrgyzstan (KGZ) over 14 years from 2002/03–2015/16 using the most recent version (v006) of MODIS Terra and Aqua 8 day snow cover composites (MOD10A2/MYD10A2). We focused on three metrics of snow seasonality—first date of snow, last date of snow, and duration of snow season—and used nonparametric trends tests to assess the significance and direction of trends. We evaluated trends at three administration scales and across elevation. We used two techniques to assure that our identification of significant trends was not resulting from random spatial variation. First, we report only significant trends (positive or negative) that are at least twice as prevalent as the converse trends. Second, we use a two-stage analysis at the national scale to identify asymmetric directional changes in snow seasonality. Results show that more territory has been experiencing earlier onset of snow than earlier snowmelt, and roughly equivalent areas have been experiencing longer and shorter duration of snow seasons in the past 14 years. The changes are not uniform across KGZ, with significant shifts toward earlier snow arrival in western and central KGZ and significant shifts toward earlier snowmelt in eastern KGZ. The duration of the snow season has significantly shortened in western and eastern KGZ and significantly lengthened in northern and southwestern KGZ. Duration is significantly longer where the snow onset was significantly earlier or the snowmelt significantly later. There is a general trend of significantly earlier snowmelt below 3400 m and the area of earlier snowmelt is 15 times greater in eastern than western districts. Significant trends in the Aqua product were less prevalent than in the Terra product, but the general trend toward earlier snowmelt was also evident in Aqua data.

Merging a Terrain-Based Parameter and Snow Particle Counter Data for the Assessment of Snow Redistribution in the Col du Lac Blanc Area

NASA Astrophysics Data System (ADS)

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

2015-04-01

Wind and the associated snow drift are dominating factors determining the snow distribution and accumulation in alpine areas, resulting in a high spatial variability of snow depth that is difficult to evaluate and quantify. The terrain-based parameter Sx characterizes the degree of shelter or exposure of a grid point provided by the upwind terrain, without the computational complexity of numerical wind field models. The parameter has shown to qualitatively predict snow redistribution with good reproduction of spatial patterns. It does not, however, provide a quantitative estimate of changes in snow depths. The objective of our research was to introduce a new parameter to quantify changes in snow depths in our research area, the Col du Lac Blanc in the French Alps. The area is at an elevation of 2700 m and particularly suited for our study due to its consistently bi-modal wind directions. Our work focused on two pronounced, approximately 10 m high terrain breaks, and we worked with 1 m resolution digital snow surface models (DSM). The DSM and measured changes in snow depths were obtained with high-accuracy terrestrial laser scan (TLS) measurements. First we calculated the terrain-based parameter Sx on a digital snow surface model and correlated Sx with measured changes in snow-depths (Δ SH). Results showed that Δ SH can be approximated by Δ SHestimated = α * Sx, where α is a newly introduced parameter. The parameter α has shown to be linked to the amount of snow deposited influenced by blowing snow flux. At the Col du Lac Blanc test side, blowing snow flux is recorded with snow particle counters (SPC). Snow flux is the number of drifting snow particles per time and area. Hence, the SPC provide data about the duration and intensity of drifting snow events, two important factors not accounted for by the terrain parameter Sx. We analyse how the SPC snow flux data can be used to estimate the magnitude of the new variable parameter α . To simulate the development

Measuring snow water equivalent from common-offset GPR records through migration velocity analysis

NASA Astrophysics Data System (ADS)

St. Clair, James; Holbrook, W. Steven

2017-12-01

Many mountainous regions depend on seasonal snowfall for their water resources. Current methods of predicting the availability of water resources rely on long-term relationships between stream discharge and snowpack monitoring at isolated locations, which are less reliable during abnormal snow years. Ground-penetrating radar (GPR) has been shown to be an effective tool for measuring snow water equivalent (SWE) because of the close relationship between snow density and radar velocity. However, the standard methods of measuring radar velocity can be time-consuming. Here we apply a migration focusing method originally developed for extracting velocity information from diffracted energy observed in zero-offset seismic sections to the problem of estimating radar velocities in seasonal snow from common-offset GPR data. Diffractions are isolated by plane-wave-destruction (PWD) filtering and the optimal migration velocity is chosen based on the varimax norm of the migrated image. We then use the radar velocity to estimate snow density, depth, and SWE. The GPR-derived SWE estimates are within 6 % of manual SWE measurements when the GPR antenna is coupled to the snow surface and 3-21 % of the manual measurements when the antenna is mounted on the front of a snowmobile ˜ 0.5 m above the snow surface.

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

14 CFR 139.313 - Snow and ice control.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Snow and ice control. 139.313 Section 139... AIRPORTS Operations § 139.313 Snow and ice control. (a) As determined by the Administrator, each... carry out a snow and ice control plan in a manner authorized by the Administrator. (b) The snow and ice...

Bioavailability of mineral-bound iron to a snow algae-bacteria co-culture and implications for albedo-altering snow algae blooms.

PubMed

Harrold, Z R; Hausrath, E M; Garcia, A H; Murray, A E; Tschauner, O; Raymond, J; Huang, S

2018-01-26

Snow algae can form large-scale blooms across the snowpack surface and near-surface environments. These pigmented blooms can decrease snow albedo, increase local melt rates, and may impact the global heat budget and water cycle. Yet, underlying causes for the geospatial occurrence of these blooms remain unconstrained. One possible factor contributing to snow algae blooms is the presence of mineral dust as a micronutrient source. We investigated the bioavailability of iron (Fe) -bearing minerals, including forsterite (Fo 90 , Mg 1.8 Fe 0.2 SiO 4 ), goethite, smectite and pyrite as Fe sources for a Chloromonas brevispina - bacteria co-culture through laboratory-based experimentation. Fo 90 was capable of stimulating snow algal growth and increased the algal growth rate in otherwise Fe-depleted co-cultures. Fo 90 -bearing systems also exhibited a decrease in bacteria:algae ratios compared to Fe-depleted conditions, suggesting a shift in microbial community structure. The C. brevispina co-culture also increased the rate of Fo 90 dissolution relative to an abiotic control. Analysis of 16S rRNA genes in the co-culture identified Gammaproteobacteria , Betaprotoeobacteria and Sphingobacteria , all of which are commonly found in snow and ice environments. Archaea were not detected. Collimonas and Pseudomonas , which are known to enhance mineral weathering rates, comprised two of the top eight (> 1 %) OTUs. These data provide unequivocal evidence that mineral dust can support elevated snow algae growth under otherwise Fe-depleted growth conditions, and that snow algae can enhance mineral dissolution under these conditions. IMPORTANCE Fe, a key micronutrient for photosynthetic growth, is necessary to support the formation of high-density snow algae blooms. The laboratory experiments described herein allow for a systematic investigation of snow algae-bacteria-mineral interactions and their ability to mobilize and uptake mineral-bound Fe. Results provide unequivocal and

Next Generation Snow Cover Mapping: Can Future Hyperspectral Satellite Spectrometer Systems Improve Subpixel Snow-covered Area and Grain Size in the Sierra Nevada?

NASA Astrophysics Data System (ADS)

Hill, R.; Calvin, W. M.; Harpold, A.

2017-12-01

Mountain snow storage is the dominant source of water for humans and ecosystems in western North America. Consequently, the spatial distribution of snow-covered area is fundamental to both hydrological, ecological, and climate models. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were collected along the entire Sierra Nevada mountain range extending from north of Lake Tahoe to south of Mt. Whitney during the 2015 and 2016 snow-covered season. The AVIRIS dataset used in this experiment consists of 224 contiguous spectral channels with wavelengths ranging 400-2500 nanometers at a 15-meter spatial pixel size. Data from the Sierras were acquired on four days: 2/24/15 during a very low snow year, 3/24/16 near maximum snow accumulation, and 5/12/16 and 5/18/16 during snow ablation and snow loss. Building on previous retrieval of subpixel snow-covered area algorithms that take into account varying grain size we present a model that analyzes multiple endmembers of varying snow grain size, vegetation, rock, and soil in segmented regions along the Sierra Nevada to determine snow-cover spatial extent, snow sub-pixel fraction, and approximate grain size. In addition, varying simulated models of the data will compare and contrast the retrieval of current snow products such as MODIS Snow-Covered Area and Grain Size (MODSCAG) and the Airborne Space Observatory (ASO). Specifically, does lower spatial resolution (MODIS), broader resolution bandwidth (MODIS), and limited spectral resolution (ASO) affect snow-cover area and grain size approximations? The implications of our findings will help refine snow mapping products for planned hyperspectral satellite spectrometer systems such as EnMAP (slated to launch in 2019), HISUI (planned for inclusion on the International Space Station in 2018), and HyspIRI (currently under consideration).

The Snow Data System at NASA JPL

NASA Astrophysics Data System (ADS)

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

2017-12-01

The Snow Data System at NASA JPL includes data processing pipelines built with open source software, Apache 'Object Oriented Data Technology' (OODT). Processing is carried out in parallel across a high-powered computing cluster. The pipelines use input data from satellites such as MODIS, VIIRS and Landsat. They apply algorithms to the input data to produce a variety of outputs in GeoTIFF format. These outputs include daily data for SCAG (Snow Cover And Grain size) and DRFS (Dust Radiative Forcing in Snow), along with 8-day composites and MODICE annual minimum snow and ice calculations. This poster will describe the Snow Data System, its outputs and their uses and applications. It will also highlight recent advancements to the system and plans for the future.

The Snow Data System at NASA JPL

NASA Astrophysics Data System (ADS)

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

2016-12-01

The Snow Data System at NASA JPL includes data processing pipelines built with open source software, Apache 'Object Oriented Data Technology' (OODT). Processing is carried out in parallel across a high-powered computing cluster. The pipelines use input data from satellites such as MODIS, VIIRS and Landsat. They apply algorithms to the input data to produce a variety of outputs in GeoTIFF format. These outputs include daily data for SCAG (Snow Cover And Grain size) and DRFS (Dust Radiative Forcing in Snow), along with 8-day composites and MODICE annual minimum snow and ice calculations. This poster will describe the Snow Data System, its outputs and their uses and applications. It will also highlight recent advancements to the system and plans for the future.

MODIS-based Snow Cover Variability of the Upper River Grande Basin

NASA Astrophysics Data System (ADS)

Yu, B.; Wang, X.; Xie, H.

2007-12-01

Snow cover and its spring melting in the Upper Rio Grande Basin provides a major water source for the Upper to Middle Rio Grande valley and Elephant Butte Reservoir. Thus understanding the snowpack and its variability in the context of global climate change is crucial to the sustainable water resources for the region. MODIS instruments (on Terra and Aqua) have provided time series of snow cover products since 2000, but suffering with cloud contaminations. In this study, we evaluated four newly developed cloudless snow cover products (less than 10%) and four standard products: daily (MOD10A1, MYD10A1) and 8-day (MOD10A2, MYD10A2), in comparison with in situ Snowpack Telemetry (SNOTEL) measurements for the hydrological year 2003-2004. The four new products are daily composite of Terra and Aqua (MODMYD10DC), multi-day composites of Terra (MOD10MC), Aqua (MYD10MC), and Terra and Aqua (MODMYD10MC). The standard daily and 8-day products can classify land correctly, but had fairly low accuracy in snow classification due to cloud contamination (a average of 39.4% for Terra and 45% for Aqua in the year 2003-2004). All the new multi-day composite products tended to have high accuracy in classifying both snow and land (over 90%), as the cloud cover has been reduced to less than 10% (~5% for the year) under the new algorithm . This result is consistent with a previous study in the Xinjiang area, China (Wang and Xie, 2007). Therefore, MOD10MC (before the Aqua data available) and MODMYD10MC products are used to get the mean snow cover of the Upper Rio Grande Basin from 2000 to 2007. The snow depletion curve derived from the new cloud-free snow cover map will be used to examine its effect on stream discharge.

Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

NASA Technical Reports Server (NTRS)

Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick

2015-01-01

Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

Mapping snow depth distribution in forested terrain using unmanned aerial vehicles and structure-from-motion

NASA Astrophysics Data System (ADS)

Webster, C.; Bühler, Y.; Schirmer, M.; Stoffel, A.; Giulia, M.; Jonas, T.

2017-12-01

Snow depth distribution in forests exhibits strong spatial heterogeneity compared to adjacent open sites. Measurement of snow depths in forests is currently limited to a) manual point measurements, which are sparse and time-intensive, b) ground-penetrating radar surveys, which have limited spatial coverage, or c) airborne LiDAR acquisition, which are expensive and may deteriorate in denser forests. We present the application of unmanned aerial vehicles in combination with structure-from-motion (SfM) methods to photogrammetrically map snow depth distribution in forested terrain. Two separate flights were carried out 10 days apart across a heterogeneous forested area of 900 x 500 m. Corresponding snow depth maps were derived using both, LiDAR-based and SfM-based DTM data, obtained during snow-off conditions. Manual measurements collected following each flight were used to validate the snow depth maps. Snow depths were resolved at 5cm resolution and forest snow depth distribution structures such as tree wells and other areas of preferential melt were represented well. Differential snow depth maps showed maximum ablation in the exposed south sides of trees and smaller differences in the centre of gaps and on the north side of trees. This new application of SfM to map snow depth distribution in forests demonstrates a straightforward method for obtaining information that was previously only available through manual spatially limited ground-based measurements. These methods could therefore be extended to more frequent observation of snow depths in forests as well as estimating snow accumulation and depletion rates.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Parameterization of single-scattering properties of snow

NASA Astrophysics Data System (ADS)

Räisänen, Petri; Kokhanovsky, Alexander; Guyot, Gwennole; Jourdan, Olivier; Nousiainen, Timo

2015-04-01

Snow consists of non-spherical ice grains of various shapes and sizes, which are surrounded by air and sometimes covered by films of liquid water. Still, in many studies, homogeneous spherical snow grains have been assumed in radiative transfer calculations, due to the convenience of using Mie theory. More recently, second-generation Koch fractals have been employed. While they produce a relatively flat scattering phase function typical of deformed non-spherical particles, this is still a rather ad-hoc choice. Here, angular scattering measurements for blowing snow conducted during the CLimate IMpacts of Short-Lived pollutants In the Polar region (CLIMSLIP) campaign at Ny Ålesund, Svalbard, are used to construct a reference phase function for snow. Based on this phase function, an optimized habit combination (OHC) consisting of severely rough (SR) droxtals, aggregates of SR plates and strongly distorted Koch fractals is selected. The single-scattering properties of snow are then computed for the OHC as a function of wavelength λ and snow grain volume-to-projected area equivalent radius rvp. Parameterization equations are developed for λ=0.199-2.7 μm and rvp = 10-2000 μm, which express the single-scattering co-albedo β, the asymmetry parameter g and the phase function as functions of the size parameter and the real and imaginary parts of the refractive index. Compared to the reference values computed for the OHC, the accuracy of the parameterization is very high for β and g. This is also true for the phase function parameterization, except for strongly absorbing cases (β > 0.3). Finally, we consider snow albedo and reflected radiances for the suggested snow optics parameterization, making comparisons with spheres and distorted Koch fractals. Further evaluation and validation of the proposed approach against (e.g.) bidirectional reflectance and polarization measurements for snow is planned. At any rate, it seems safe to assume that the OHC selected here

#AskBerkeleyLab: Cost and Availability of Healthy Food

ScienceCinema

Buluswar, Shashi

2018-02-13

Shashi Buluswar, Executive Director at the LBNL Institute for Globally Transformative Technologies, answers a question from Ashley on why healthy food costs so much and is not available in low-income neighborhoods.

Using mid-altitude regions as observatories of change in snow areas: the Natural Park of Cazorla, Segura y las Villas (South Spain) as study case for early snow regression.

NASA Astrophysics Data System (ADS)

Montilla, Soledad; Pimentel, Rafael; José Pérez-Palazón, María; Aguillar, Cristina; José Polo, María

2017-04-01

available series of satellite images Landsat 8 OLI/TIRS, Landsat 7 ETM+ and Landsat 4-5 TM were used to obtain snow cover fraction maps with 30x30 m resolution. The study period 2010-2015 was simulated with the distributed snow model and the results were compared against these snow map series. Additionally, the annual and seasonal trends of precipitation, mean daily temperature and global radiation were obtained from the available local data sets. Globally, the simulated results overestimate the snow presence in the study area, very likely due to the estimation of snowfall. However, on a local scale, the model performance improves in the region between 1750 and 2250 m altitude. On the other hand, those zones at lower altitudes, which are a transition of the clearly alpine environment above, present a high variability of results related to the spatial patterns of precipitation, temperature and radiation. Regarding the precipitation-temperature regime, an increasing 0.05 °/yr over the last 30 years (1970-2010) was found, but no significant conclusion can be achieved on precipitation trends. This is also observed in the SNNP, which confirms the potential representativeness of PNCSV as an early warning site. Further work is being carried out to improve the snow modelling at this site and generate longer snow cover fraction maps series and other characteristic variables of the snow in this area.

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. © 2013 Society for Conservation Biology.

UWScat observations of snow on Grand Mesa, Colorado - Backscatter and polarimetric response of snow in a canopy and snow on the ground

NASA Astrophysics Data System (ADS)

Thompson, A. D.; Kelly, R. E. J.

2017-12-01

The ability to measure the amount of water stored in Earth's terrestrial snowpack is important for human development, resource management, and environmental modelling. Active microwave remote sensing offers the promise to do so however we must better understand how forest, which accounts for a large fraction of snow-covered land, affects the microwave retrieval of snow water equivalent (SWE). This is a fundamental goal of the NASA SnowEx mission and one we address using data collected during the February 2017 campaign in Grand Mesa, Colorado. We deployed UWScat, a ground-based, polarimetric scatterometer operating at 9.6 and 17.2 GHz frequencies, at 8 sites on Grand Mesa, including 2 sites observed from a platform approximately 9 m above the ground overlooking a coniferous canopy. Ancillary snowpit and snow microstructure measurements were also made and include traditional snowpit measurements along with measurements of snow specific surface area (SSA) using IRIS and IceCube systems. A snow micropenetrometer (SMP) was used to provide stratigraphic information. First, we show the influence of forest canopy on the microwave backscatter response, and how backscatter alone is insufficient to distinguish between forested and non-forested landscapes. Secondly, we show how polarimetric data can be used to identify the presence of forest canopy within the scene by revealing the depolarization that occurs in the interaction between the microwaves and the canopy structure. This result illustrates the benefits of a dual frequency polarimetric approach. While depolarization from a canopy is evident at X-band, there is less evidence of depolarization from a snowpack. At Ku-band frequencies, however, depolarization is evident both from interaction with the snowpack and the canopy. Finally we explore the relationship between SWE and backscatter in forested and un-forested environments. Together these results provide useful insights that increase our understanding of the radar