WorldWideScience

Sample records for intelligent snow removal

  1. Artificial-intelligence-based optimization of the management of snow removal assets and resources.

    Science.gov (United States)

    2002-10-01

    Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent : snow removal asset management system (SRAMS). The system has been evaluated through a case study examining : snow removal from the ...

  2. User Oriented Climatic Information for Planning a Snow Removal Budget.

    Science.gov (United States)

    Cohen, Stewart J.

    1981-12-01

    Many activities associated with the transportation sector are weather sensitive. This study is concerned with highway maintenance activities, specifically snow removal, and the budgeting of same by the Illinois Department of Transportation (IDOT). During the 1978-79 winter, IDOT's snow removal budget was exhausted by the end of January, thereby necessitating the procurement of emergency funds. The following year, the Illinois State Water Survey (ISWS) was asked to provide specialized climatic design information that could be used to assist IDOT in its budget planning for snow removal.Snow removal is often accomplished by spreading road salt over snow- and ice-covered roads, thus improving traction and reducing the risk of vehicles skidding along slippery surfaces. This study demonstrates the computation of `salt days,' a user-oriented climatic variable that indicates the number of days when road salt is required. This variable is defined using certain temperature and snowfall criteria. Results of a pilot study indicate that it is possible to provide statistical outlooks for salt days two months in advance, using correlation analysis. The analysis for several Illinois stations indicates that at various intervals in the data records, November and December temperatures are significantly correlated with February salt days if short periods of record (5-20 years) are used.IDOT originally requested a `2- to 3-month projection.' However, it became clear that only projections of 12 months or longer could benefit annual budget preparation. Confusion existed between the user and the supplier of climatic information regarding the user's needs, and the applicability of the supplier's `climate products' to the user's budget planning procedure. This demonstrates the need for a prolonged effort by the supplier to fully acquaint the user with the various forms of climatic information available. This gap in communication must be overcome so that applied climatology can be integrated

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

    Science.gov (United States)

    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.

  4. Photovoltaic cell electrical heating system for removing snow on panel including verification.

    Science.gov (United States)

    Weiss, Agnes; Weiss, Helmut

    2017-11-16

    Small photovoltaic plants in private ownership are typically rated at 5 kW (peak). The panels are mounted on roofs at a decline angle of 20° to 45°. In winter time, a dense layer of snow at a width of e.g., 10 cm keeps off solar radiation from the photovoltaic cells for weeks under continental climate conditions. Practically, no energy is produced over the time of snow coverage. Only until outside air temperature has risen high enough for a rather long-time interval to allow partial melting of snow; the snow layer rushes down in an avalanche. Following this proposal, snow removal can be arranged electrically at an extremely positive energy balance in a fast way. A photovoltaic cell is a large junction area diode inside with a threshold voltage of about 0.6 to 0.7 V (depending on temperature). This forward voltage drop created by an externally driven current through the modules can be efficiently used to provide well-distributed heat dissipation at the cell and further on at the glass surface of the whole panel. The adhesion of snow on glass is widely reduced through this heating in case a thin water film can be produced by this external short time heating. Laboratory experiments provided a temperature increase through rated panel current of more than 10 °C within about 10 min. This heating can initiate the avalanche for snow removal on intention as described before provided the clamping effect on snow at the edge of the panel frame is overcome by an additional heating foil. Basics of internal cell heat production, heating thermal effects in time course, thermographic measurements on temperature distribution, power circuit opportunities including battery storage elements and snow-removal under practical conditions are described.

  5. Quantification of the removal of chemical species by snow

    Energy Technology Data Exchange (ETDEWEB)

    Schwikowski, M.; Baltensperger, U.; Bruetsch, S.; Keil, R.; Gaeggeler, H.W. [Paul Scherrer Inst. (PSI), Villigen (Switzerland); Poulida, O. [Frederick Research Center, Nicosia (Cyprus)

    1997-09-01

    In order to quantify the scavenging of chemical species in mixed phase clouds, in-cloud field experiments were conducted in October and November 1993 at the high-alpine research station Jungfraujoch. On the average, air to snow transfer fractions were rather low with the highest value of 0.5 for nitrate, thus, most of the air borne chemical mass remained in the air parcel after precipitation. (author) 1 fig., 4 refs.

  6. Removal of snow cover inhibits spring growth of Arctic ice algae through physiological and behavioral effects

    DEFF Research Database (Denmark)

    Lund-Hansen, L.C.; Hawes, Ian; Sorrell, Brian Keith

    2014-01-01

    The snow cover of Arctic sea ice has recently decreased, and climate models forecast that this will continue and even increase in future. We therefore tested the effect of snow cover on the optical properties of sea ice and the biomass, photobiology, and species composition of sea ice algae at Ka...... of the spring bloom is predominantly due to temperature effects on brine channel volume, and that the algal decline after snow removal was primarily due to emigration rather than photodamage.......The snow cover of Arctic sea ice has recently decreased, and climate models forecast that this will continue and even increase in future. We therefore tested the effect of snow cover on the optical properties of sea ice and the biomass, photobiology, and species composition of sea ice algae...... at Kangerlussuaq, West Greenland, during March 2011, using a snow-clearance experiment. Sea ice algae in areas cleared of snow was compared with control areas, using imaging variable fluorescence of photosystem II in intact, unthawed ice sections. The study coincided with the onset of spring growth of ice algae...

  7. Sulphur dioxide removal by turbulent transfer over grass, snow, and water surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Whelpdale, D M; Shaw, R W

    1974-01-01

    Vertical gradients of sulphur dioxide concentration have been measured over grass, snow, and water surfaces in order to assess the importance of these surfaces as SO/sub 2/ sinks. Concentrations were usually found to be lower near the surface indicating that removal occurs there. Vertical concentration gradients, normalized with repect to the concentration at 8 m, were generally greatest over water and least over snow, independent of meteorological conditions, suggesting that a water surface is the strongest SO/sub 2/ sink, with grass next, and snow weakest. The turbulent transfer of SO/sub 2/ to the interface is discussed in relation to stability of the lower atmosphere and physical and chemical properties of the surfaces. Using a bulk aerodynamic transfer approach similar to that for water vapour, values of SO/sub 2/ flux averaged over periods of from one to several hours were found to be of the order of 1 microgram/M/sup 2//S to the water and grass surfaces, and an order of magnitude smaller to the snow surface. Deposition velocities were found to be of the order of 1 cm/s.

  8. Optimizing winter/snow removal operations in MoDOT St. Louis district : includes outcome based evaluation of operations.

    Science.gov (United States)

    2011-10-01

    The objective of this project was to develop fleet location, route decision, material selection, and treatment procedures for winter snow removal operations to improve MoDOTs services and lower costs. This work uses a systematic, heuristic-based o...

  9. Algorithm for modelling the removal of snow from streches of the manoeuvring aera of an airport

    Energy Technology Data Exchange (ETDEWEB)

    Soriguera Marti, F.; Martinez-Diaz, M.; Perez Perez, I.

    2016-07-01

    This article presents an algorithm and a structured methodology to address the issue of the optimisation of resources when clearing snow from stretches of the manoeuvring area of an airport. This overall issue is how to best utilise limited resources to remove snow from taxiways and runways so as to leave surfaces in an acceptable state for aircraft operations. To achieve this the airfield is divided into subsets of significant stretches for the purpose of operations and target times are set at which these are to be open to aircraft traffic. The manoeuvring area is also divided into zones, with the condition that the subsets of significant stretches lie within just one of these zones. The mathematical model contains operating restrictions with regard to the fulfilment of partial operational targets applied to the subsets of significant stretches, and also concerning the snow-clearing machines. The problem is solved by an iterative optimisation process based on linear programming applied successively to the zones that make up the manoeuvring area during each iteration. The method is particularised for the case of the manoeuvring area of Adolfo Suarez Madrid - Barajas Airport. (Author)

  10. 49 CFR 1242.28 - Roadway machines, small tools and supplies, and snow removal (accounts XX-19-36 to XX-19-38...

    Science.gov (United States)

    2010-10-01

    ... snow removal (accounts XX-19-36 to XX-19-38, inclusive). 1242.28 Section 1242.28 Transportation Other... tools and supplies, and snow removal (accounts XX-19-36 to XX-19-38, inclusive). Separate common expenses according to distribution of common expenses listed in § 1242.10, Administration—Track (account XX...

  11. Winter ecology of a subalpine grassland: Effects of snow removal on soil respiration, microbial structure and function.

    Science.gov (United States)

    Gavazov, Konstantin; Ingrisch, Johannes; Hasibeder, Roland; Mills, Robert T E; Buttler, Alexandre; Gleixner, Gerd; Pumpanen, Jukka; Bahn, Michael

    2017-07-15

    Seasonal snow cover provides essential insulation for mountain ecosystems, but expected changes in precipitation patterns and snow cover duration due to global warming can influence the activity of soil microbial communities. In turn, these changes have the potential to create new dynamics of soil organic matter cycling. To assess the effects of experimental snow removal and advanced spring conditions on soil carbon (C) and nitrogen (N) dynamics, and on the biomass and structure of soil microbial communities, we performed an in situ study in a subalpine grassland in the Austrian Alps, in conjunction with soil incubations under controlled conditions. We found substantial winter C-mineralisation and high accumulation of inorganic and organic N in the topsoil, peaking at snowmelt. Soil microbial biomass doubled under the snow, paralleled by a fivefold increase in its C:N ratio, but no apparent change in its bacteria-dominated community structure. Snow removal led to a series of mild freeze-thaw cycles, which had minor effects on in situ soil CO 2 production and N mineralisation. Incubated soil under advanced spring conditions, however, revealed an impaired microbial metabolism shortly after snow removal, characterised by a limited capacity for C-mineralisation of both fresh plant-derived substrates and existing soil organic matter (SOM), leading to reduced priming effects. This effect was transient and the observed recovery in microbial respiration and SOM priming towards the end of the winter season indicated microbial resilience to short-lived freeze-thaw disturbance under field conditions. Bacteria showed a higher potential for uptake of plant-derived C substrates during this recovery phase. The observed temporary loss in microbial C-mineralisation capacity and the promotion of bacteria over fungi can likely impede winter SOM cycling in mountain grasslands under recurrent winter climate change events, with plausible implications for soil nutrient availability and

  12. Network resilience against intelligent attacks constrained by the degree-dependent node removal cost

    International Nuclear Information System (INIS)

    Annibale, A; Coolen, A C C; Bianconi, G

    2010-01-01

    We study the resilience of complex networks against attacks in which nodes are targeted intelligently, but where disabling a node has a cost to the attacker which depends on its degree. Attackers have to meet these costs with limited resources, which constrains their actions. A network's integrity is quantified in terms of the efficacy of the process that it supports. We calculate how the optimal attack strategy and the most attack-resistant network degree statistics depend on the node removal cost function and the attack resources. The resilience of networks against intelligent attacks is found to depend strongly on the node removal cost function faced by the attacker. In particular, if node removal costs increase sufficiently fast with the node degree, power law networks are found to be more resilient than Poissonian ones, even against optimized intelligent attacks. For cost functions increasing quadratically in the node degrees, intelligent attackers cannot damage the network more than random damages would.

  13. Early thawing after snow removal and no straw mulching accelerates organic carbon cycling in a paddy soil in Northeast China.

    Science.gov (United States)

    Zhang, Hao; Tang, Jie; Liang, Shuang; Li, Zhaoyang; Wang, Jingjing; Wang, Sining

    2018-03-01

    Variations in soil organic carbon (SOC) have implications for atmospheric CO 2 concentrations and the greenhouse effect. However, the effects of snow cover and straw mulching on the variations in SOC fractions across winter remain largely unknown. In this study, soil samples were collected during different stages of winter from an in situ experiment comprising three treatments: 1) snow removal with no straw mulching (Sn-SM-); 2) snow cover with no straw mulching (SC), and; 3) snow cover with straw mulching (SC + SM+). Results showed that labile organic carbon, semi-labile organic carbon, recalcitrant organic carbon (ROC), the light fraction of organic carbon (LFOC), and easily oxidized organic carbon (EOC) contents did not vary significantly (P > .05) during the unfrozen to hard frost stages. Compared to the unfrozen stage, microbial biomass carbon (MBC) contents decreased by 519.03 mg kg -1 , 325.21 mg kg -1 , and 244.09 mg kg -1 and dissolved organic carbon (DOC) contents increased by 473.36 mg kg -1 , 348.10 mg kg -1 , and 258.89 mg kg -1  at the hard frost stage in Sn-SM-, SC, and SC + SM + treatments, respectively. Throughout all thawing stages, > 61% and 59% of SOC and ROC accumulation, respectively in the three treatments were observed in thawing stage II, indicating that higher temperatures and microbial activities in thawing stage II accelerated the inputs of SOC and ROC. ROC accumulation accounted for >65% of the SOC accumulation and the proportions of ROC in SOC increased in the three treatments during the thawing stages. SC + SM + treatment maintained lower EOC contents during thawing stages than other treatments. The observation of lowest SOC and LFOC accumulation and contents in the SC + SM + treatment during thawing stages showed that SC + SM + experienced the least inputs of SOC in the soil. Copyright © 2018 Elsevier Ltd. All rights reserved.

  14. Snow clearance

    CERN Multimedia

    Mauro Nonis

    2005-01-01

    In reply to the numerous questions received, we should like to inform you of the actions and measures taken in an effort to maintain the movements of vehicles and pedestrians since the heavy snow fall on Sunday 23 January. Our contractor's employees began clearing the snow during the morning of Sunday 23 January on the main CERN sites (Meyrin, Prévessin), but an accident prevented them from continuing. The vehicle in question was repaired by Monday morning when two other vehicles joined it to resume snow clearing; priority was given to access points to the main sites and the LHC sites, as well as to the main roads inside the sites. The salt sprinklers were also brought into action that same day; the very low temperature during the night from Monday to Tuesday prevented the snow from melting and compacted the ice; the continuing cold during the day on Tuesday (-6°C at 10:00 on the Meyrin site) meant that all efforts to remove the ice were doomed to failure. In order to ensure more efficie...

  15. Application of the artificial intelligence to estimate the constructed wetland response to heavy metal removal

    Energy Technology Data Exchange (ETDEWEB)

    Elektorowicz, M. [Concordia Univ., Building, Civil and Environmental Engineering, Montreal, Quebec (Canada)]. E-mail: mariae@civil.concordia.ca; Balanzinski, M. [Ecole Polytechnique de Montreal, Mechnical Engineering, Montreal, Quebec (Canada); Qasaimeh, A. [Concordia Univ., Building, Civil and Environmental Engineering, Montreal, Quebec (Canada)

    2002-06-15

    Current design approaches lack essential parameters necessary to evaluate the removal of metals contained in wastewater which is discharged to constructed wetlands. As a result, there is no guideline for an accurate design of constructed wetlands. An artificial intelligence approach was used to assess constructed wetland design. For this purpose concentrations of bioavailable mercury were evaluated in conditions where initial concentrations of inorganic mercury, chloride concentrations and pH values changed. Fuzzy knowledge base was built based on results obtained from previous investigations performed in a greenhouse for floating plants, and from computations for mercury speciation. The Fuzzy Decision Support System (FDSS) used the knowledge base to find parameters that permit to generate the highest amount of mercury available for plants. The findings of this research can be applied to wetlands and all natural processes where correlations between them are uncertain. (author)

  16. Application of the artificial intelligence to estimate the constructed wetland response to heavy metal removal

    International Nuclear Information System (INIS)

    Elektorowicz, M.; Balanzinski, M.; Qasaimeh, A.

    2002-01-01

    Current design approaches lack essential parameters necessary to evaluate the removal of metals contained in wastewater which is discharged to constructed wetlands. As a result, there is no guideline for an accurate design of constructed wetlands. An artificial intelligence approach was used to assess constructed wetland design. For this purpose concentrations of bioavailable mercury were evaluated in conditions where initial concentrations of inorganic mercury, chloride concentrations and pH values changed. Fuzzy knowledge base was built based on results obtained from previous investigations performed in a greenhouse for floating plants, and from computations for mercury speciation. The Fuzzy Decision Support System (FDSS) used the knowledge base to find parameters that permit to generate the highest amount of mercury available for plants. The findings of this research can be applied to wetlands and all natural processes where correlations between them are uncertain. (author)

  17. Predicting adsorptive removal of chlorophenol from aqueous solution using artificial intelligence based modeling approaches.

    Science.gov (United States)

    Singh, Kunwar P; Gupta, Shikha; Ojha, Priyanka; Rai, Premanjali

    2013-04-01

    The research aims to develop artificial intelligence (AI)-based model to predict the adsorptive removal of 2-chlorophenol (CP) in aqueous solution by coconut shell carbon (CSC) using four operational variables (pH of solution, adsorbate concentration, temperature, and contact time), and to investigate their effects on the adsorption process. Accordingly, based on a factorial design, 640 batch experiments were conducted. Nonlinearities in experimental data were checked using Brock-Dechert-Scheimkman (BDS) statistics. Five nonlinear models were constructed to predict the adsorptive removal of CP in aqueous solution by CSC using four variables as input. Performances of the constructed models were evaluated and compared using statistical criteria. BDS statistics revealed strong nonlinearity in experimental data. Performance of all the models constructed here was satisfactory. Radial basis function network (RBFN) and multilayer perceptron network (MLPN) models performed better than generalized regression neural network, support vector machines, and gene expression programming models. Sensitivity analysis revealed that the contact time had highest effect on adsorption followed by the solution pH, temperature, and CP concentration. The study concluded that all the models constructed here were capable of capturing the nonlinearity in data. A better generalization and predictive performance of RBFN and MLPN models suggested that these can be used to predict the adsorption of CP in aqueous solution using CSC.

  18. Snow Matters

    DEFF Research Database (Denmark)

    Gyimóthy, Szilvia; Jensen, Martin Trandberg

    2018-01-01

    attribute of high altitude mountain destinations. Hitherto, researchers mostly engaged with snowclad landscapes as a backstage; trying to deconstruct the complex symbolism and representational qualities of this elusive substance. Despite snow being a strategically crucial condition for tourism in the Alps......This chapter explores the performative potential of snow for Alpine tourism, by drawing attention to its material and nonrepresentational significance for tourism practices. European imagination has been preoccupied with snow since medieval times and even today, snow features as the sine que non...

  19. Performance evaluation of snow and ice plows.

    Science.gov (United States)

    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...

  20. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  1. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  2. Snow Leopard

    Indian Academy of Sciences (India)

    adult females (dimorphic); a male on average weighing between. 45–55 kg, while a .... performance of wild prey, eventually leading to a decline in their population. Research .... working towards enhancing knowledge on snow leopard ecology.

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

    Science.gov (United States)

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

    2014-12-01

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

  4. Surface decontamination using dry ice snow

    International Nuclear Information System (INIS)

    Ryu, Jungdong; Park, Kwangheon; Lee, Bumsik; Kim Yangeun

    1999-01-01

    An adjustable nozzle for controlling the size of dry ice snow was developed. The converging/diverging nozzle can control the size of snows from sub-microns to 10 micron size. Using the nozzle, a surface decontamination device was made. The removal mechanisms of surface contaminants are mechanical impact, partial dissolving and evaporation process, and viscous flow. A heat supply system is added for the prevention of surface ice layer formation. The cleaning power is slightly dependent on the size of snow. Small snows are the better in viscous flow cleaning, while large snows are slightly better in dissolving and sublimation process. Human oils like fingerprints on glass were easy to remove. Decontamination ability was tested using a contaminated pump-housing surface. About 40 to 80% of radioactivity was removed. This device is effective in surface-decontamination of any electrical devices like detector, controllers which cannot be cleaned in aqueous solution. (author)

  5. A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence.

    Science.gov (United States)

    Fan, Mingyi; Hu, Jiwei; Cao, Rensheng; Ruan, Wenqian; Wei, Xionghui

    2018-06-01

    Water pollution occurs mainly due to inorganic and organic pollutants, such as nutrients, heavy metals and persistent organic pollutants. For the modeling and optimization of pollutants removal, artificial intelligence (AI) has been used as a major tool in the experimental design that can generate the optimal operational variables, since AI has recently gained a tremendous advance. The present review describes the fundamentals, advantages and limitations of AI tools. Artificial neural networks (ANNs) are the AI tools frequently adopted to predict the pollutants removal processes because of their capabilities of self-learning and self-adapting, while genetic algorithm (GA) and particle swarm optimization (PSO) are also useful AI methodologies in efficient search for the global optima. This article summarizes the modeling and optimization of pollutants removal processes in water treatment by using multilayer perception, fuzzy neural, radial basis function and self-organizing map networks. Furthermore, the results conclude that the hybrid models of ANNs with GA and PSO can be successfully applied in water treatment with satisfactory accuracies. Finally, the limitations of current AI tools and their new developments are also highlighted for prospective applications in the environmental protection. Copyright © 2018 Elsevier Ltd. All rights reserved.

  6. Neuron network training system for Robot responding intelligently to input light stimuli (notice of removal)

    Science.gov (United States)

    Xiao, Baoping; Xu, Chang; Xu, Lijun; Luo, Qinhua

    2007-11-01

    This paper (672414) was removed from the SPIE Digital Library on 13 April 2010 to discovery of plagiarism. As stated in the SPIE Guidelines for Professional Conduct and Publishing Ethics, SPIE defines plagiarism as the reuse of someone else's prior ideas, processes, results, or words without explicit attribution of the original author and source, or falsely representing someone else's work as one's own. SPIE considers plagiarism in any form, at any level, to be unacceptable and a serious breach of professional conduct. It is SPIE policy to remove such papers and to take appropriate corrective or disciplinary action against the offending author(s).

  7. An intelligent displacement pumping film system: A new concept for enhancing heavy metal ion removal efficiency from liquid waste

    International Nuclear Information System (INIS)

    Wang, Zhongde; Feng, Yanting; Hao, Xiaogang; Huang, Wei; Guan, Guoqing; Abudula, Abuliti

    2014-01-01

    Highlights: • A new concept for design of an intelligent displacement pumping film was proposed. • As-prepared ESIX hybrid film system showed excellent Ni 2+ uptake/exclude rate. • Piston-like proton pumping effect existed in the prepared ESIX hybrid film. • The mechanism of the ion pumping effect was proved by XPS analysis. - Abstract: A concept of electrochemically switched ion exchange (ESIX) hybrid film system with piston-like proton pumping effect for the removal of heavy metal ions was proposed. Based on this concept, a novel ESIX hybrid film composed of layered alpha zirconium phosphate (α-Zr(HPO 4 ) 2 ; α-ZrP) nanosheets intercalated with a potential-responsive conducting polyaniline (PANI) was developed for the removal of Ni 2+ ions from wastewater. It is expected that the space between α-ZrP nanosheets acts as the reservoir for the functional ions while the intercalated PANI works as the potential-sensitive function element for piston-like proton pumping in such ESIX hybrid films. The prepared ESIX hybrid film showed an excellent property of rapid removal of Ni 2+ ions from wastewater with a high selectivity. The used film was simply regenerated by only altering the applied potential. The ion pumping effect for the ESIX of Ni 2+ ions using this kind of film was proved via XPS analysis. The proposed ESIX hybrid film should have high potential for the removal of Ni 2+ ions and/or other heavy metal ions from wastewater in various industrial processes

  8. Intelligent optimization of common water treatment plant for the removal of organic carbon

    International Nuclear Information System (INIS)

    Ahmadzadeh, T.; Mehrdadi, N.; Ardestani, M.; Baghvand, A.

    2016-01-01

    Intelligent model optimization is a key factor in the improvement of water treatment. In the current study, we applied artificial neural networks modelling for the optimization of the coagulation and flocculation processes to achieve sufficient water quality control over the total organic carbon parameter. The ANN network consisted of a multilayer feed-forward structure with a back propagation learning algorithm with the output layer of ferric chloride and cationic polymer dosages. The results were simultaneously compared with the nonlinear multiple regression model. The model validation phase was performed using 94 unknown samples for which the prediction result was in good agreement with the observed values. Analysis of the results showed a determination coefficient of 0.85 for the cationic polymer and 0.97 for the ferric chloride models, respectively. He mean absolute percentage error and root mean square errors were calculated, consequently, as 5.8% and 0.96 for the polymer and 3.1% and 1.97 for the ferric chloride models, respectively. According to the results, artificial neural networks proved to be very promising for the optimization of water treatment processes.

  9. Intelligent Noise Removal from EMG Signal Using Focused Time-Lagged Recurrent Neural Network

    Directory of Open Access Journals (Sweden)

    S. N. Kale

    2009-01-01

    Full Text Available Electromyography (EMG signals can be used for clinical/biomedical application and modern human computer interaction. EMG signals acquire noise while traveling through tissue, inherent noise in electronics equipment, ambient noise, and so forth. ANN approach is studied for reduction of noise in EMG signal. In this paper, it is shown that Focused Time-Lagged Recurrent Neural Network (FTLRNN can elegantly solve to reduce the noise from EMG signal. After rigorous computer simulations, authors developed an optimal FTLRNN model, which removes the noise from the EMG signal. Results show that the proposed optimal FTLRNN model has an MSE (Mean Square Error as low as 0.000067 and 0.000048, correlation coefficient as high as 0.99950 and 0.99939 for noise signal and EMG signal, respectively, when validated on the test dataset. It is also noticed that the output of the estimated FTLRNN model closely follows the real one. This network is indeed robust as EMG signal tolerates the noise variance from 0.1 to 0.4 for uniform noise and 0.30 for Gaussian noise. It is clear that the training of the network is independent of specific partitioning of dataset. It is seen that the performance of the proposed FTLRNN model clearly outperforms the best Multilayer perceptron (MLP and Radial Basis Function NN (RBF models. The simple NN model such as the FTLRNN with single-hidden layer can be employed to remove noise from EMG signal.

  10. Intelligent Image Analysis for Image-Guided Laser Hair Removal and Skin Therapy

    Science.gov (United States)

    Walker, Brian; Lu, Thomas; Chao, Tien-Hsin

    2012-01-01

    We present the development of advanced automatic target recognition (ATR) algorithms for the hair follicles identification in digital skin images to accurately direct the laser beam to remove the hair. The ATR system first performs a wavelet filtering to enhance the contrast of the hair features in the image. The system then extracts the unique features of the targets and sends the features to an Adaboost based classifier for training and recognition operations. The ATR system automatically classifies the hair, moles, or other skin lesion and provides the accurate coordinates of the intended hair follicle locations. The coordinates can be used to guide a scanning laser to focus energy only on the hair follicles. The intended benefit would be to protect the skin from unwanted laser exposure and to provide more effective skin therapy.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-01-12

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

  12. ESA GlobSnow Snow Water Equivalent (SWE)

    Data.gov (United States)

    National Aeronautics and Space Administration — The European Space Agency (ESA) Global Snow Monitoring for Climate Research (GlobSnow) snow water equivalent (SWE) v2.0 data record contains snow information derived...

  13. A distributed snow-evolution modeling system (SnowModel)

    Science.gov (United States)

    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...

  14. Snow snake performance monitoring.

    Science.gov (United States)

    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...

  15. Modelling of snow exceedances

    Science.gov (United States)

    Jordanova, Pavlina K.; Sadovský, Zoltán; Stehlík, Milan

    2017-07-01

    Modelling of snow exceedances is of great importance and interest for ecology, civil engineering and general public. We suggest the favorable fit for exceedances related to the exceptional snow loads from Slovakia, assuming that the data is driven by Generalised Pareto Distribution or Generalized Extreme Value Distribution. Further, the statistical dependence between the maximal snow loads and the corresponding altitudes is studied.

  16. Simulating snow maps for Norway: description and statistical evaluation of the seNorge snow model

    Directory of Open Access Journals (Sweden)

    T. M. Saloranta

    2012-11-01

    Full Text Available Daily maps of snow conditions have been produced in Norway with the seNorge snow model since 2004. The seNorge snow model operates with 1 × 1 km resolution, uses gridded observations of daily temperature and precipitation as its input forcing, and simulates, among others, snow water equivalent (SWE, snow depth (SD, and the snow bulk density (ρ. In this paper the set of equations contained in the seNorge model code is described and a thorough spatiotemporal statistical evaluation of the model performance from 1957–2011 is made using the two major sets of extensive in situ snow measurements that exist for Norway. The evaluation results show that the seNorge model generally overestimates both SWE and ρ, and that the overestimation of SWE increases with elevation throughout the snow season. However, the R2-values for model fit are 0.60 for (log-transformed SWE and 0.45 for ρ, indicating that after removal of the detected systematic model biases (e.g. by recalibrating the model or expressing snow conditions in relative units the model performs rather well. The seNorge model provides a relatively simple, not very data-demanding, yet nonetheless process-based method to construct snow maps of high spatiotemporal resolution. It is an especially well suited alternative for operational snow mapping in regions with rugged topography and large spatiotemporal variability in snow conditions, as is the case in the mountainous Norway.

  17. NOAA's National Snow Analyses

    Science.gov (United States)

    Carroll, T. R.; Cline, D. W.; Olheiser, C. M.; Rost, A. A.; Nilsson, A. O.; Fall, G. M.; Li, L.; Bovitz, C. T.

    2005-12-01

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

  18. A Distributed Snow Evolution Modeling System (SnowModel)

    Science.gov (United States)

    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.

  19. 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.

    Science.gov (United States)

    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.

  20. Loropetalum chinense 'Snow Panda'

    Science.gov (United States)

    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...

  1. Artificial Intelligence Based Optimization for the Se(IV) Removal from Aqueous Solution by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron Composites.

    Science.gov (United States)

    Cao, Rensheng; Fan, Mingyi; Hu, Jiwei; Ruan, Wenqian; Wu, Xianliang; Wei, Xionghui

    2018-03-15

    Highly promising artificial intelligence tools, including neural network (ANN), genetic algorithm (GA) and particle swarm optimization (PSO), were applied in the present study to develop an approach for the evaluation of Se(IV) removal from aqueous solutions by reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) composites. Both GA and PSO were used to optimize the parameters of ANN. The effect of operational parameters (i.e., initial pH, temperature, contact time and initial Se(IV) concentration) on the removal efficiency was examined using response surface methodology (RSM), which was also utilized to obtain a dataset for the ANN training. The ANN-GA model results (with a prediction error of 2.88%) showed a better agreement with the experimental data than the ANN-PSO model results (with a prediction error of 4.63%) and the RSM model results (with a prediction error of 5.56%), thus the ANN-GA model was an ideal choice for modeling and optimizing the Se(IV) removal by the nZVI/rGO composites due to its low prediction error. The analysis of the experimental data illustrates that the removal process of Se(IV) obeyed the Langmuir isotherm and the pseudo-second-order kinetic model. Furthermore, the Se 3d and 3p peaks found in XPS spectra for the nZVI/rGO composites after removing treatment illustrates that the removal of Se(IV) was mainly through the adsorption and reduction mechanisms.

  2. Extraordinary blowing snow transport events in East Antarctica

    Energy Technology Data Exchange (ETDEWEB)

    Scarchilli, Claudio; Agnoletto, Lucia [ENEA, Rome (Italy); Universita di Siena, Dipartimento di Scienze della Terra, Siena (Italy); Frezzotti, Massimo; Grigioni, Paolo; Silvestri, Lorenzo de [ENEA, Rome (Italy); Dolci, Stefano [CNR, Rome (Italy); Consorzio P.N.R.A. S.C.r.l., Rome (Italy)

    2010-06-15

    In the convergence slope/coastal areas of Antarctica, a large fraction of snow is continuously eroded and exported by wind to the atmosphere and into the ocean. Snow transport observations from instruments and satellite images were acquired at the wind convergence zone of Terra Nova Bay (East Antarctica) throughout 2006 and 2007. Snow transport features are well-distinguished in satellite images and can extend vertically up to 200 m as first-order quantitatively estimated by driftometer sensor FlowCapt trademark. Maximum snow transportation occurs in the fall and winter seasons. Snow transportation (drift/blowing) was recorded for {proportional_to}80% of the time, and 20% of time recorded, the flux is >10{sup -2} kg m{sup -2} s{sup -1} with particle density increasing with height. Cumulative snow transportation is {proportional_to}4 orders of magnitude higher than snow precipitation at the site. An increase in wind speed and transportation ({proportional_to}30%) was observed in 2007, which is in agreement with a reduction in observed snow accumulation. Extensive presence of ablation surface (blue ice and wind crust) upwind and downwind of the measurement site suggest that the combine processes of blowing snow sublimation and snow transport remove up to 50% of the precipitation in the coastal and slope convergence area. These phenomena represent a major negative effect on the snow accumulation, and they are not sufficiently taken into account in studies of surface mass balance. The observed wind-driven ablation explains the inconsistency between atmospheric model precipitation and measured snow accumulation value. (orig.)

  3. Snow model analysis.

    Science.gov (United States)

    2014-01-01

    This study developed a new snow model and a database which warehouses geometric, weather and traffic : data on New Jersey highways. The complexity of the model development lies in considering variable road : width, different spreading/plowing pattern...

  4. Anoxia in the snow

    Science.gov (United States)

    Bristow, Laura A.

    2018-04-01

    Substantial amounts of denitrification and other anaerobic metabolisms can occur in anoxic microenvironments within marine snow particles, according to model simulations. This microbial activity may have a global impact on nitrogen cycling.

  5. Sentinels for snow science

    Science.gov (United States)

    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.

  6. Artificial intelligence based model for optimization of COD removal efficiency of an up-flow anaerobic sludge blanket reactor in the saline wastewater treatment.

    Science.gov (United States)

    Picos-Benítez, Alain R; López-Hincapié, Juan D; Chávez-Ramírez, Abraham U; Rodríguez-García, Adrián

    2017-03-01

    The complex non-linear behavior presented in the biological treatment of wastewater requires an accurate model to predict the system performance. This study evaluates the effectiveness of an artificial intelligence (AI) model, based on the combination of artificial neural networks (ANNs) and genetic algorithms (GAs), to find the optimum performance of an up-flow anaerobic sludge blanket reactor (UASB) for saline wastewater treatment. Chemical oxygen demand (COD) removal was predicted using conductivity, organic loading rate (OLR) and temperature as input variables. The ANN model was built from experimental data and performance was assessed through the maximum mean absolute percentage error (= 9.226%) computed from the measured and model predicted values of the COD. Accordingly, the ANN model was used as a fitness function in a GA to find the best operational condition. In the worst case scenario (low energy requirements, high OLR usage and high salinity) this model guaranteed COD removal efficiency values above 70%. This result is consistent and was validated experimentally, confirming that this ANN-GA model can be used as a tool to achieve the best performance of a UASB reactor with the minimum requirement of energy for saline wastewater treatment.

  7. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  8. Pavement Snow Melting

    Energy Technology Data Exchange (ETDEWEB)

    Lund, John W.

    2005-01-01

    The design of pavement snow melting systems is presented based on criteria established by ASHRAE. The heating requirements depends on rate of snow fall, air temperature, relative humidity and wind velocity. Piping materials are either metal or plastic, however, due to corrosion problems, cross-linked polyethylene pipe is now generally used instead of iron. Geothermal energy is supplied to systems through the use of heat pipes, directly from circulating pipes, through a heat exchanger or by allowing water to flow directly over the pavement, by using solar thermal storage. Examples of systems in New Jersey, Wyoming, Virginia, Japan, Argentina, Switzerland and Oregon are presented. Key words: pavement snow melting, geothermal heating, heat pipes, solar storage, Wyoming, Virginia, Japan, Argentina, Klamath Falls.

  9. Artificial intelligence models for predicting the performance of biological wastewater treatment plant in the removal of Kjeldahl Nitrogen from wastewater

    Science.gov (United States)

    Manu, D. S.; Thalla, Arun Kumar

    2017-11-01

    The current work demonstrates the support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) modeling to assess the removal efficiency of Kjeldahl Nitrogen of a full-scale aerobic biological wastewater treatment plant. The influent variables such as pH, chemical oxygen demand, total solids (TS), free ammonia, ammonia nitrogen and Kjeldahl Nitrogen are used as input variables during modeling. Model development focused on postulating an adaptive, functional, real-time and alternative approach for modeling the removal efficiency of Kjeldahl Nitrogen. The input variables used for modeling were daily time series data recorded at wastewater treatment plant (WWTP) located in Mangalore during the period June 2014-September 2014. The performance of ANFIS model developed using Gbell and trapezoidal membership functions (MFs) and SVM are assessed using different statistical indices like root mean square error, correlation coefficients (CC) and Nash Sutcliff error (NSE). The errors related to the prediction of effluent Kjeldahl Nitrogen concentration by the SVM modeling appeared to be reasonable when compared to that of ANFIS models with Gbell and trapezoidal MF. From the performance evaluation of the developed SVM model, it is observed that the approach is capable to define the inter-relationship between various wastewater quality variables and thus SVM can be potentially applied for evaluating the efficiency of aerobic biological processes in WWTP.

  10. Snow, ice and solar radiation

    NARCIS (Netherlands)

    Kuipers Munneke, P.

    2009-01-01

    The snow-covered ice sheets of Antarctica and Greenland reflect most of the incoming solar radiation. The reflectivity, commonly called the albedo, of snow on these ice sheets has been observed to vary in space and time. In this thesis, temporal and spatial changes in snow albedo is found to depend

  11. Snow-clearing operations

    CERN Multimedia

    EN Department

    2010-01-01

    To facilitate snow clearing operations, which commence at 4.30 in the morning, all drivers of CERN cars are kindly requested to park them together in groups. This will help us greatly assist us in our work. Thank-you for your help. Transport Group / EN-HE Tel. 72202

  12. Plant intelligence

    Science.gov (United States)

    Lipavská, Helena; Žárský, Viktor

    2009-01-01

    The concept of plant intelligence, as proposed by Anthony Trewavas, has raised considerable discussion. However, plant intelligence remains loosely defined; often it is either perceived as practically synonymous to Darwinian fitness, or reduced to a mere decorative metaphor. A more strict view can be taken, emphasizing necessary prerequisites such as memory and learning, which requires clarifying the definition of memory itself. To qualify as memories, traces of past events have to be not only stored, but also actively accessed. We propose a criterion for eliminating false candidates of possible plant intelligence phenomena in this stricter sense: an “intelligent” behavior must involve a component that can be approximated by a plausible algorithmic model involving recourse to stored information about past states of the individual or its environment. Re-evaluation of previously presented examples of plant intelligence shows that only some of them pass our test. “You were hurt?” Kumiko said, looking at the scar. Sally looked down. “Yeah.” “Why didn't you have it removed?” “Sometimes it's good to remember.” “Being hurt?” “Being stupid.”—(W. Gibson: Mona Lisa Overdrive) PMID:19816094

  13. Introduction to snow rheology

    International Nuclear Information System (INIS)

    Montmollin, Vincent de

    1978-01-01

    The tests described in the thesis are rotating shearing tests, with rotational constant speed ranging between 0.00075 rpm and 0.75 rpm. The results obtained are similar to those observed with compression tests at constant speed, except that shearing tests are carried out with densities nearly constant. So, we show three different domains when the rotation speed increases: 1) viscous (without failure) 2) brittle of first type (cycles of brittle failures) and 3) brittle of second type (only one brittle failure and solid friction). These results show clearly that the fundamental mechanism that rules the mechanisms of snow, is fast metamorphosis of bonds, binding ice grains: this metamorphosis is important when solicitation speeds are low (permanent rate of shearing in viscous domain, regeneration of the failure surfaces in the brittle domain of the first type) and this metamorphosis does not exist when speed increases (only one failure and solid friction in the brittle domain of second type). It is also included an important bibliographic analysis of the snow mechanics, and an experimental and theoretical study about shock wave propagation in natural snow covers. (author) [fr

  14. Snow accretion on overhead wires

    Energy Technology Data Exchange (ETDEWEB)

    Sakamoto, Y. [Meteorological Research Inst. for Technology Co. Ltd., Tokyo (Japan); Tachizaki, S.; Sudo, N. [Tohoku Electric Power Co. Ltd., Miyagi (Japan)

    2005-07-01

    Wet snow accretion can cause extensive damage to transmission systems. This paper reviewed some of the difficulties faced by researchers in the study of wet snow accretion on overhead lines in Japan. The study of snow accretion phenomena is complicated by the range of phase changes in water. Snowflakes produced in an upper atmospheric layer with a temperature below freezing do not melt when they go through a lower atmospheric layer with a temperature above freezing, but are in a mixed state of solid and liquid due to the latent heat of melting. The complicated properties of water make studies of snow accretion difficult, as well as the fact that snow changes its physical properties rapidly, due to the effects of ambient temperature, rainfall, and solar radiation. The adhesive forces that cause snow accretion include freezing; bonding through freezing; sintering; condensation and freezing of vapor in the air; mechanical intertwining of snowflakes; capillary action due to liquids; coherent forces between ice particles and water formed through the metamorphosis of snowflakes. In addition to these complexities, differences in laboratory room environments and natural snow environments can also pose difficulties for researchers. Equations describing the relationship between the density of accreted snow and the meteorological parameters involved were presented, as well as empirical equations which suggested that snow accretion efficiency has a dependency on air temperature. An empirical model for estimating snow loads in Japan was outlined, as well as various experiments observing show shedding. Correlations for wet snow accretion included precipitation intensity; duration of precipitation; air temperature; wind speed and wind direction in relation to the overhead line. Issues concerning topography and wet snow accretion were reviewed. It was concluded that studies of snow accretion will benefit by the collection of data in each matrix of the relevant parameters. 12 refs

  15. Measurement of snow interception and canopy effects on snow accumulation and melt in a mountainous maritime climate, Oregon, United States

    Science.gov (United States)

    Storck, Pascal; Lettenmaier, Dennis P.; Bolton, Susan M.

    2002-11-01

    The results of a 3 year field study to observe the processes controlling snow interception by forest canopies and under canopy snow accumulation and ablation in mountain maritime climates are reported. The field study was further intended to provide data to develop and test models of forest canopy effects on beneath-canopy snowpack accumulation and melt and the plot and stand scales. Weighing lysimeters, cut-tree experiments, and manual snow surveys were deployed at a site in the Umpqua National Forest, Oregon (elevation 1200 m). A unique design for a weighing lysimeter was employed that allowed continuous measurements of snowpack evolution beneath a forest canopy to be taken at a scale unaffected by variability in canopy throughfall. Continuous observations of snowpack evolution in large clearings were made coincidentally with the canopy measurements. Large differences in snow accumulation and ablation were observed at sites beneath the forest canopy and in large clearings. These differences were not well described by simple relationships between the sites. Over the study period, approximately 60% of snowfall was intercepted by the canopy (up to a maximum of about 40 mm water equivalent). Instantaneous sublimation rates exceeded 0.5 mm per hour for short periods. However, apparent average sublimation from the intercepted snow was less than 1 mm per day and totaled approximately 100 mm per winter season. Approximately 72 and 28% of the remaining intercepted snow was removed as meltwater drip and large snow masses, respectively. Observed differences in snow interception rate and maximum snow interception capacity between Douglas fir (Pseudotsuga menziesii), white fir (Abies concolor), ponderosa pine (Pinus ponderosa), and lodgepole pine (Pinus contorta) were minimal.

  16. Antarctic snow and global climate

    International Nuclear Information System (INIS)

    Granberg, H.B.

    2001-01-01

    Global circulation models (GCM) indicate that global warming will be most pronounced at polar regions and high latitudes, causing concern about the stability of the Antarctic ice cap. A project entitled the Seasonal Snow in Antarctica examined the properties of the near surface snow to determine the current conditions that influence snow cover development. The goal was to assess the response of the snow cover in Queen Maud Land (QML) to an increased atmospheric carbon dioxide content. The Antarctic snow cover in QML was examined as part of the FINNARP expeditions in 1999 and 2000 which examined the processes that influence the snow cover. Its energy and mass balance were also assessed by examining the near surface snow strata in shallow (1-2 m) pits and by taking measurements of environmental variables. This made it possible to determine if the glacier is in danger of melting at this northerly location in the Antarctic. The study also made it possible to determine which variables need to change and by how much, for significant melting to occur. It was shown that the Antarctic anticyclone creates particular conditions that protect the snow cover from melting. The anticyclone brings dry air from the stratosphere during most of the year and is exempt from the water vapour feedback. It was concluded that even a doubling of atmospheric carbon dioxide will not produce major snow melt runoff. 8 refs

  17. A Bayesian spatial assimilation scheme for snow coverage observations in a gridded snow model

    Directory of Open Access Journals (Sweden)

    S. Kolberg

    2006-01-01

    Full Text Available A method for assimilating remotely sensed snow covered area (SCA into the snow subroutine of a grid distributed precipitation-runoff model (PRM is presented. The PRM is assumed to simulate the snow state in each grid cell by a snow depletion curve (SDC, which relates that cell's SCA to its snow cover mass balance. The assimilation is based on Bayes' theorem, which requires a joint prior distribution of the SDC variables in all the grid cells. In this paper we propose a spatial model for this prior distribution, and include similarities and dependencies among the grid cells. Used to represent the PRM simulated snow cover state, our joint prior model regards two elevation gradients and a degree-day factor as global variables, rather than describing their effect separately for each cell. This transformation results in smooth normalised surfaces for the two related mass balance variables, supporting a strong inter-cell dependency in their joint prior model. The global features and spatial interdependency in the prior model cause each SCA observation to provide information for many grid cells. The spatial approach similarly facilitates the utilisation of observed discharge. Assimilation of SCA data using the proposed spatial model is evaluated in a 2400 km2 mountainous region in central Norway (61° N, 9° E, based on two Landsat 7 ETM+ images generalized to 1 km2 resolution. An image acquired on 11 May, a week before the peak flood, removes 78% of the variance in the remaining snow storage. Even an image from 4 May, less than a week after the melt onset, reduces this variance by 53%. These results are largely improved compared to a cell-by-cell independent assimilation routine previously reported. Including observed discharge in the updating information improves the 4 May results, but has weak effect on 11 May. Estimated elevation gradients are shown to be sensitive to informational deficits occurring at high altitude, where snowmelt has not started

  18. Snow and SMOW

    International Nuclear Information System (INIS)

    1967-01-01

    In the midst of Vienna's hottest weather spell this year, members of the Agency's headquarters laboratory staff found themselves unpacking a consignment of fresh snow from the Antarctic. It had been sent by air through Los Angeles, not for cooling purposes, but to assist in making more accurate measurements as part of the study of the world's water distribution and movement. The same research also involves SMOW (Standard Mean Ocean Water) and samples of water from the mid-Pacific will also soon arrive for scientific examination

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

    Science.gov (United States)

    ... to mention a few. Plus, someone has to shovel the snow, right? Once outdoors, however, take precautions ... re going to get the family outside to shovel the snow? Fine, but take care. Snow shoveling ...

  20. Is Snow Gliding a Major Soil Erosion Agent in Steep Alpine Areas?

    International Nuclear Information System (INIS)

    Meusburger, K.; Walter, A.; Alewell, C.; Leitinger, G.; Mabit, L.; Mueller, M.H.

    2015-01-01

    Snow cover is a key hydrological characteristic of mountain areas. Nevertheless, a majority of studies focused on quantifying rates of soil erosion and sediment transport in steep mountain areas has largely neglected the role of snow cover on soil erosion rates (Stanchi et al., 2014). Soil erosion studies have focused almost exclusively on the snow-free periods even though it is well known that wet avalanches can yield enormous erosive forces (Freppaz et al., 2010; Korup and Rixen, 2014). This raises the question whether annual snow cover and particularly the slow movement of snow packages over the soil surface, termed ‘‘snow gliding’’, contribute significantly to the total soil loss in these areas. Three different approaches to estimate soil erosion rates were used to address this question. These include (1) the anthropogenic soil tracer 137 Cs, (2) the Revised Universal Soil Loss Equation (RUSLE), and (3) direct sediment yield measurements of snow glide deposits. The fallout radionuclide 137 Cs integrates total soil loss due to all erosion agents involved, the RUSLE model is suitable to estimate soil loss by water erosion and the sediment yield measurements yield represents a direct estimate of soil removal by snow gliding. Moreover, cumulative snow glide distance was measured for 14 sites and modelled for the surrounding area with the Spatial Snow Glide Model (Leitinger et al., 2008)

  1. Remote sensing, hydrological modeling and in situ observations in snow cover research: A review

    Science.gov (United States)

    Dong, Chunyu

    2018-06-01

    Snow is an important component of the hydrological cycle. As a major part of the cryosphere, snow cover also represents a valuable terrestrial water resource. In the context of climate change, the dynamics of snow cover play a crucial role in rebalancing the global energy and water budgets. Remote sensing, hydrological modeling and in situ observations are three techniques frequently utilized for snow cover investigations. However, the uncertainties caused by systematic errors, scale gaps, and complicated snow physics, among other factors, limit the usability of these three approaches in snow studies. In this paper, an overview of the advantages, limitations and recent progress of the three methods is presented, and more effective ways to estimate snow cover properties are evaluated. The possibility of improving remotely sensed snow information using ground-based observations is discussed. As a rapidly growing source of volunteered geographic information (VGI), web-based geotagged photos have great potential to provide ground truth data for remotely sensed products and hydrological models and thus contribute to procedures for cloud removal, correction, validation, forcing and assimilation. Finally, this review proposes a synergistic framework for the future of snow cover research. This framework highlights the cross-scale integration of in situ and remotely sensed snow measurements and the assimilation of improved remote sensing data into hydrological models.

  2. Development of probabilistic risk assessment methodology against extreme snow for sodium-cooled fast reactor

    Energy Technology Data Exchange (ETDEWEB)

    Yamano, Hidemasa, E-mail: yamano.hidemasa@jaea.go.jp; Nishino, Hiroyuki; Kurisaka, Kenichi

    2016-11-15

    Highlights: • Snow PRA methodology was developed. • Snow hazard category was defined as the combination of daily snowfall depth (speed) and snowfall duration. • Failure probability models of snow removal action, manual operation of the air cooler dampers and the access route were developed. • Snow PRA showed less than 10{sup −6}/reactor-year of core damage frequency. - Abstract: This paper describes snow probabilistic risk assessment (PRA) methodology development through external hazard and event sequence evaluations mainly in terms of decay heat removal (DHR) function of a sodium-cooled fast reactor (SFR). Using recent 50-year weather data at a typical Japanese SFR site, snow hazard categories were set for the combination of daily snowfall depth (snowfall speed) and snowfall duration which can be calculated by dividing the snow depth by the snowfall speed. For each snow hazard category, the event sequence was evaluated by event trees which consist of several headings representing the loss of DHR. Snow removal action and manual operation of the air cooler dampers were introduced into the event trees as accident managements. Access route failure probability model was also developed for the quantification of the event tree. In this paper, the snow PRA showed less than 10{sup −6}/reactor-year of core damage frequency. The dominant snow hazard category was the combination of 1–2 m/day of snowfall speed and 0.5–0.75 day of snowfall duration. Importance and sensitivity analyses indicated a high risk contribution of the securing of the access routes.

  3. Development of probabilistic risk assessment methodology against extreme snow for sodium-cooled fast reactor

    International Nuclear Information System (INIS)

    Yamano, Hidemasa; Nishino, Hiroyuki; Kurisaka, Kenichi

    2016-01-01

    Highlights: • Snow PRA methodology was developed. • Snow hazard category was defined as the combination of daily snowfall depth (speed) and snowfall duration. • Failure probability models of snow removal action, manual operation of the air cooler dampers and the access route were developed. • Snow PRA showed less than 10"−"6/reactor-year of core damage frequency. - Abstract: This paper describes snow probabilistic risk assessment (PRA) methodology development through external hazard and event sequence evaluations mainly in terms of decay heat removal (DHR) function of a sodium-cooled fast reactor (SFR). Using recent 50-year weather data at a typical Japanese SFR site, snow hazard categories were set for the combination of daily snowfall depth (snowfall speed) and snowfall duration which can be calculated by dividing the snow depth by the snowfall speed. For each snow hazard category, the event sequence was evaluated by event trees which consist of several headings representing the loss of DHR. Snow removal action and manual operation of the air cooler dampers were introduced into the event trees as accident managements. Access route failure probability model was also developed for the quantification of the event tree. In this paper, the snow PRA showed less than 10"−"6/reactor-year of core damage frequency. The dominant snow hazard category was the combination of 1–2 m/day of snowfall speed and 0.5–0.75 day of snowfall duration. Importance and sensitivity analyses indicated a high risk contribution of the securing of the access routes.

  4. The value of snow cover

    Science.gov (United States)

    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

  5. Snow farming: conserving snow over the summer season

    Science.gov (United States)

    Grünewald, Thomas; Wolfsperger, Fabian; Lehning, Michael

    2018-01-01

    Summer storage of snow for tourism has seen an increasing interest in the last years. Covering large snow piles with materials such as sawdust enables more than two-thirds of the initial snow volume to be conserved. We present detailed mass balance measurements of two sawdust-covered snow piles obtained by terrestrial laser scanning during summer 2015. Results indicate that 74 and 63 % of the snow volume remained over the summer for piles in Davos, Switzerland and Martell, Italy. If snow mass is considered instead of volume, the values increase to 83 and 72 %. The difference is attributed to settling and densification of the snow. Additionally, we adapted the one-dimensional, physically based snow cover model SNOWPACK to perform simulations of the sawdust-covered snow piles. Model results and measurements agreed extremely well at the point scale. Moreover, we analysed the contribution of the different terms of the surface energy balance to snow ablation for a pile covered with a 40 cm thick sawdust layer and a pile without insulation. Short-wave radiation was the dominant source of energy for both scenarios, but the moist sawdust caused strong cooling by long-wave emission and negative sensible and latent heat fluxes. This cooling effect reduces the energy available for melt by up to a factor of 12. As a result only 9 % of the net short-wave energy remained available for melt. Finally, sensitivity studies of the parameters thickness of the sawdust layer, air temperature, precipitation and wind speed were performed. We show that sawdust thickness has a tremendous effect on snow loss. Higher air temperatures and wind speeds increase snow ablation but less significantly. No significant effect of additional precipitation could be found as the sawdust remained wet during the entire summer with the measured quantity of rain. Setting precipitation amounts to zero, however, strongly increased melt. Overall, the 40 cm sawdust provides sufficient protection for mid

  6. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  7. Unexpected Patterns in Snow and Dirt

    Science.gov (United States)

    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…

  8. Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

    NARCIS (Netherlands)

    Stigter, Emmy E.; Wanders, Niko; Saloranta, Tuomo M.; Shea, Joseph M.; Bierkens, M.F.P.; Immerzeel, W.W.

    2017-01-01

    Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water

  9. The stepwise discriminant algorithm for snow cover mapping based on FY-3/MERSI data

    Science.gov (United States)

    Han, Tao; Wang, Dawei; Jiang, Youyan; Wang, Xiaowei

    2013-10-01

    Medium Resolution Spectral Imager (MERSI) on board China's new generation polar orbit meteorological satellite FY- 3A provides a new data source for snow monitoring in large area. As a case study, the typical snow cover of Qilian Mountains in northwest China was selected in this paper to develop the algorithm to map snow cover using FY- 3A/MERSI. By analyzing the spectral response characteristics of snow and other surface elements, as well as each channel image quality on FY-3A/MERSI, the widely used Normalized Difference Snow Index (NDSI) was defined to be computed from channel 2 and channel 7 for this satellite data. Basing on NDSI, a tree-structure prototype version of snow identification model was proposed, including five newly-built multi-spectral indexes to remove those pixels such as forest, cloud shadow, water, lake ice, sand (salty land), or cloud that are usually confused with snow step by step, especially, a snow/cloud discrimination index was proposed to eliminate cloud, apart from use of cloud mask product in advance. Furthermore, land cover land use (LULC) image has been adopted as auxiliary dataset to adjust the corresponding LULC NDSI threshold constraints for snow final determination and optimization. This model is composed as the core of FY-3A/MERSI snow cover mapping flowchart, to produce daily snow map at 250m spatial resolution, and statistics can be generated on the extent and persistence of snow cover in each pixel for time series maps. Preliminary validation activities of our snow identification model have been undertaken. Comparisons of the 104 FY- 3A/MERSI snow cover maps in 2010-2011 snow season with snow depth records from 16 meteorological stations in Qilian Mountains region, the sunny snow cover had an absolute accuracy of 92.8%. Results of the comparison with the snow cover identified from 6 Terra/MODIS scenes showed that they had consistent pixels about 85%. When the two satellite resultant snow cover maps compared with the 6

  10. [Was Snow White a transsexual?].

    Science.gov (United States)

    Michel, A; Mormont, C

    2002-01-01

    The Rorschach Ink Blot test is considered to be an essential analytical instrument when studying the personalities of individuals presenting identity disorders, in particular, in the context of a sex change request. Nevertheless, there exist less than 20 studies of transsexualism utilising the Rorschach since the creation of this diagnostic category in 1953. This research has mostly concerned itself with relations between psychopathology and transsexualism. Practically non-existent are studies investigating the psychological conditions that permit, shape or induce sex change requests in individuals. Transsexuals request the removal of their genitals through mutilation surgery, which can be seen as subjects literally crying out to be castrated. This request is all the more surprising given that castration, in psychoanalytic terms, is considered to be the most severe punishment that an individual (woman or man) can be threatened with. Therefore, we asked ourselves which psychic conditions could motivate such as request. Based on any earlier study where answers (some explicit, others symbolic) given by sex-change applicants tested on the Rorschach were analysed, results seemed to suggest a counter-phobic attitude underlying sex-reassignment requests (28). According to these hypotheses, the fear of castration (banal as such) can only be overcome through the active search for castration itself. In opting for castration, the transsexual puts an end to the states of anxious waiting that are dominated by feelings of the incertitude and unpredictability of an eventual castration. Once obtained, the threat it constituted disappears, and with it so does the fear. Thus, by taking this active and voluntary step, the subject is no longer exposed to an imminent danger in a passive manner. This in itself creates a great feeling of relief, if not of actual pleasure in the subject (28). In this article, we postulated in a purely speculative manner, the existence of one or several

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

    Science.gov (United States)

    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.

  12. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  13. Intelligent mechatronics; Intelligent mechatronics

    Energy Technology Data Exchange (ETDEWEB)

    Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

    1995-10-01

    Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

  14. Assimilation of snow cover and snow depth into a snow model to estimate snow water equivalent and snowmelt runoff in a Himalayan catchment

    Directory of Open Access Journals (Sweden)

    E. E. Stigter

    2017-07-01

    Full Text Available Snow is an important component of water storage in the Himalayas. Previous snowmelt studies in the Himalayas have predominantly relied on remotely sensed snow cover. However, snow cover data provide no direct information on the actual amount of water stored in a snowpack, i.e., the snow water equivalent (SWE. Therefore, in this study remotely sensed snow cover was combined with in situ observations and a modified version of the seNorge snow model to estimate (climate sensitivity of SWE and snowmelt runoff in the Langtang catchment in Nepal. Snow cover data from Landsat 8 and the MOD10A2 snow cover product were validated with in situ snow cover observations provided by surface temperature and snow depth measurements resulting in classification accuracies of 85.7 and 83.1 % respectively. Optimal model parameter values were obtained through data assimilation of MOD10A2 snow maps and snow depth measurements using an ensemble Kalman filter (EnKF. Independent validations of simulated snow depth and snow cover with observations show improvement after data assimilation compared to simulations without data assimilation. The approach of modeling snow depth in a Kalman filter framework allows for data-constrained estimation of snow depth rather than snow cover alone, and this has great potential for future studies in complex terrain, especially in the Himalayas. Climate sensitivity tests with the optimized snow model revealed that snowmelt runoff increases in winter and the early melt season (December to May and decreases during the late melt season (June to September as a result of the earlier onset of snowmelt due to increasing temperature. At high elevation a decrease in SWE due to higher air temperature is (partly compensated by an increase in precipitation, which emphasizes the need for accurate predictions on the changes in the spatial distribution of precipitation along with changes in temperature.

  15. Artificial Intelligence and Moral intelligence

    OpenAIRE

    Laura Pana

    2008-01-01

    We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

  16. Development and testing of a snow interceptometer to quantify canopy water storage and interception processes in the rain/snow transition zone of the North Cascades, Washington, USA

    Science.gov (United States)

    Martin, Kael A.; Van Stan, John T.; Dickerson-Lange, Susan E.; Lutz, James A.; Berman, Jeffrey W.; Gersonde, Rolf; Lundquist, Jessica D.

    2013-06-01

    Tree canopy snow interception is a significant hydrological process, capable of removing up to 60% of snow from the ground snowpack. Our understanding of canopy interception has been limited by our ability to measure whole canopy water storage in an undisturbed forest setting. This study presents a relatively inexpensive technique for directly measuring snow canopy water storage using an interceptometer, adapted from Friesen et al. (2008). The interceptometer is composed of four linear motion position sensors distributed evenly around the tree trunk. We incorporate a trunk laser-mapping installation method for precise sensor placement to reduce signal error due to sensor misalignment. Through calibration techniques, the amount of canopy snow required to produce the measured displacements can be calculated. We demonstrate instrument performance on a western hemlock (Tsuga heterophylla) for a snow interception event in November 2011. We find a snow capture efficiency of 83 ± 15% of accumulated ground snowfall with a maximum storage capacity of 50 ± 8 mm snow water equivalent (SWE). The observed interception event is compared to simulated interception, represented by the variable infiltration capacity (VIC) hydrologic model. The model generally underreported interception magnitude by 33% using a leaf area index (LAI) of 5 and 16% using an LAI of 10. The interceptometer captured intrastorm accumulation and melt rates up to 3 and 0.75 mm SWE h-1, respectively, which the model failed to represent. While further implementation and validation is necessary, our preliminary results indicate that forest interception magnitude may be underestimated in maritime areas.

  17. New Technology and Experimental Study on Snow-Melting Heated Pavement System in Tunnel Portal

    OpenAIRE

    Lai, Jinxing; Qiu, Junling; Chen, Jianxun; Fan, Haobo; Wang, Ke

    2015-01-01

    In recent years, with the rapid growth of economy and sharp rise of motor vehicles in China, the pavement skid resistance in tunnel portals has become increasingly important in cold region. However, the deicing salt, snow removal with machine, and other antiskid measures adopted by highway maintenance division have many limitations. To improve the treatment effect, we proposed a new snow-melting approach employing electric heat tracing, in which heating cables are installed in the structural ...

  18. Removal of Crystal Violet by Using Reduced-Graphene-Oxide-Supported Bimetallic Fe/Ni Nanoparticles (rGO/Fe/Ni): Application of Artificial Intelligence Modeling for the Optimization Process.

    Science.gov (United States)

    Ruan, Wenqian; Hu, Jiwei; Qi, Jimei; Hou, Yu; Cao, Rensheng; Wei, Xionghui

    2018-05-22

    Reduced-graphene-oxide-supported bimetallic Fe/Ni nanoparticles were synthesized in this study for the removal of crystal violet (CV) dye from aqueous solutions. This material was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS), Raman spectroscopy, N₂-sorption, and X-ray photoelectron spectroscopy (XPS). The influence of independent parameters (namely, initial dye concentration, initial pH, contact time, and temperature) on the removal efficiency were investigated via Box⁻Behnken design (BBD). Artificial intelligence (i.e., artificial neural network, genetic algorithm, and particle swarm optimization) was used to optimize and predict the optimum conditions and obtain the maximum removal efficiency. The zero point of charge (pH ZPC ) of rGO/Fe/Ni composites was determined by using the salt addition method. The experimental equilibrium data were fitted well to the Freundlich model for the evaluation of the actual behavior of CV adsorption, and the maximum adsorption capacity was estimated as 2000.00 mg/g. The kinetic study discloses that the adsorption processes can be satisfactorily described by the pseudo-second-order model. The values of Gibbs free energy change (Δ G ⁰), entropy change (Δ S ⁰), and enthalpy change (Δ H ⁰) demonstrate the spontaneous and endothermic nature of the adsorption of CV onto rGO/Fe/Ni composites.

  19. Removal of Crystal Violet by Using Reduced-Graphene-Oxide-Supported Bimetallic Fe/Ni Nanoparticles (rGO/Fe/Ni: Application of Artificial Intelligence Modeling for the Optimization Process

    Directory of Open Access Journals (Sweden)

    Wenqian Ruan

    2018-05-01

    Full Text Available Reduced-graphene-oxide-supported bimetallic Fe/Ni nanoparticles were synthesized in this study for the removal of crystal violet (CV dye from aqueous solutions. This material was characterized by X-ray diffraction (XRD, scanning electron microscopy (SEM coupled with energy dispersive spectroscopy (EDS, Raman spectroscopy, N2-sorption, and X-ray photoelectron spectroscopy (XPS. The influence of independent parameters (namely, initial dye concentration, initial pH, contact time, and temperature on the removal efficiency were investigated via Box–Behnken design (BBD. Artificial intelligence (i.e., artificial neural network, genetic algorithm, and particle swarm optimization was used to optimize and predict the optimum conditions and obtain the maximum removal efficiency. The zero point of charge (pHZPC of rGO/Fe/Ni composites was determined by using the salt addition method. The experimental equilibrium data were fitted well to the Freundlich model for the evaluation of the actual behavior of CV adsorption, and the maximum adsorption capacity was estimated as 2000.00 mg/g. The kinetic study discloses that the adsorption processes can be satisfactorily described by the pseudo-second-order model. The values of Gibbs free energy change (ΔG0, entropy change (ΔS0, and enthalpy change (ΔH0 demonstrate the spontaneous and endothermic nature of the adsorption of CV onto rGO/Fe/Ni composites.

  20. Unexpected Patterns in Snow and Dirt

    Science.gov (United States)

    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.

  1. [Snow cover pollution monitoring in Ufa].

    Science.gov (United States)

    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.

  2. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  3. Competitive Intelligence.

    Science.gov (United States)

    Bergeron, Pierrette; Hiller, Christine A.

    2002-01-01

    Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

  4. Velocity distribution in snow avalanches

    Science.gov (United States)

    Nishimura, K.; Ito, Y.

    1997-12-01

    In order to investigate the detailed structure of snow avalanches, we have made snow flow experiments at the Miyanomori ski jump in Sapporo and systematic observations in the Shiai-dani, Kurobe Canyon. In the winter of 1995-1996, a new device to measure static pressures was used to estimate velocities in the snow cloud that develops above the flowing layer of avalanches. Measurements during a large avalanche in the Shiai-dani which damaged and destroyed some instruments indicate velocities increased rapidly to more than 50 m/s soon after the front. Velocities decreased gradually in the following 10 s. Velocities of the lower flowing layer were also calculated by differencing measurement of impact pressure. Both recordings in the snow cloud and in the flowing layer changed with a similar trend and suggest a close interaction between the two layers. In addition, the velocity showed a periodic change. Power spectrum analysis of the impact pressure and the static pressure depression showed a strong peak at a frequency between 4 and 6 Hz, which might imply the existence of either ordered structure or a series of surges in the flow.

  5. Photopolarimetric Retrievals of Snow Properties

    Science.gov (United States)

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

    2015-01-01

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

  6. Intelligence Ethics:

    DEFF Research Database (Denmark)

    Rønn, Kira Vrist

    2016-01-01

    Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...

  7. Review of ice and snow runway pavements

    Directory of Open Access Journals (Sweden)

    Greg White

    2018-05-01

    Full Text Available Antarctica is the highest, driest, coldest, windiest, most remote and most pristine place on Earth. Polar operations depend heavily on air transportation and support for personnel and equipment. It follows that improvement in snow and ice runway design, construction and maintenance will directly benefit polar exploration and research. Current technologies and design methods for snow and ice runways remain largely reliant on work performed in the 1950s and 1960s. This paper reviews the design and construction of polar runways using snow and ice as geomaterials. The inability to change existing snow and ice thickness or temperature creates a challenge for polar runway design and construction, as does the highly complex mechanical behaviour of snow, including the phenomena known as sintering. It is recommended that a modern approach be developed for ice and snow runway design, based on conventional rigid and flexible pavement design principles. This requires the development on an analytical model for the prediction of snow strength, based on snow age, temperature history and density. It is also recommended that the feasibility of constructing a snow runway at the South Pole be revisited, in light of contemporary snow sintering methods. Such a runway would represent a revolutionary advance for the logistical support of Antarctic research efforts. Keywords: Runway, Pavement, Snow, Ice, Antarctic

  8. MODIS Snow and Sea Ice Products

    Science.gov (United States)

    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.

  9. Intelligence Naturelle et Intelligence Artificielle

    OpenAIRE

    Dubois, Daniel

    2011-01-01

    Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...

  10. Identification of mineral dust layers in high alpine snow packs

    Science.gov (United States)

    Greilinger, Marion; Kau, Daniela; Schauer, Gerhard; Kasper-Giebl, Anne

    2017-04-01

    Deserts serve as a major source for aerosols in the atmosphere with mineral dust as a main contributor to primary aerosol mass. Especially the Sahara, the largest desert in the world, contributes roughly half of the primarily emitted aerosol mass found in the atmosphere [1]. The eroded Saharan dust is episodically transported over thousands of kilometers with synoptic wind patterns towards Europe [2] and reaches Austria about 20 to 30 days per year. Once the Saharan dust is removed from the atmosphere via dry or wet deposition processes, the chemical composition of the precipitation or the affected environment is significantly changed. Saharan dust serves on the one hand as high ionic input leading to an increase of ionic species such as calcium, magnesium or sulfate. On the other hand Saharan dust provides a high alkaline input neutralizing acidic components and causing the pH to increase [3]. Based on these changes in the ion composition, the pH and cross plots of the ion and conductivity balance [4] we tried to develop a method to identify Saharan dust layers in high alpine snow packs. We investigated seasonal snow packs of two high alpine sampling sites situated on the surrounding glaciers of the meteorological Sonnblick observatory serving as a global GAW (Global Atmospheric Watch) station located in the National Park Hohe Tauern in the Austrian Alps. Samples with 10 cm resolution representing the whole winter accumulation period were taken just prior to the start of snow melt at the end of April 2016. In both snow packs two layers with clearly different chemical behavior were observed. In comparison with the aerosol data from the Sonnblick observatory, these layers could be clearly identified as Saharan dust layers. Identified Saharan dust layers in the snow pack allow calculations of the ecological impact of deposited ions, with and without Saharan dust, during snow melt. Furthermore the chemical characteristics for the identification of Saharan dust layers

  11. Snow and ice: Chapter 3

    Science.gov (United States)

    Littell, Jeremy; McAfee, Stephanie A.; O'Neel, Shad; Sass, Louis; Burgess, Evan; Colt, Steve; Clark, Paul; Hayward, Gregory D.; Colt, Steve; McTeague, Monica L.; Hollingsworth, Teresa N.

    2017-01-01

    Temperature and precipitation are key determinants of snowpack levels. Therefore, climate change is likely to affect the role of snow and ice in the landscapes and hydrology of the Chugach National Forest region.Downscaled climate projections developed by Scenarios Network for Alaska and Arctic Planning (SNAP) are useful for examining projected changes in snow at relatively fine resolution using a variable called “snowday fraction (SDF),” the percentage of days with precipitation falling as snow.We summarized SNAP monthly SDF from five different global climate models for the Chugach region by 500 m elevation bands, and compared historical (1971–2000) and future (2030–2059) SDF. We found that:Snow-day fraction and snow-water equivalent (SWE) are projected to decline most in late autumn (October to November) and at lower elevations.Snow-day fraction is projected to decrease 23 percent (averaged across five climate models) from October to March, between sea level and 500 m. Between sea level and 1000 m, SDF is projected to decrease by 17 percent between October and March.Snow-water equivalent is projected to decrease most in autumn (October and November) and at lower elevations (below 1500 m), an average of -26 percent for the 2030–2059 period compared to 1971– 2000. Averaged across the cool season and the entire domain, SWE is projected to decrease at elevations below 1000 m because of increased temperature, but increase at higher elevations because of increased precipitation.Compared to 1971–2000, the percentage of the landscape that is snowdominant in 2030–2059 is projected to decrease, and the percentage in which rain and snow are co-dominant (transient hydrology) is projected to increase from 27 to 37 percent. Most of this change is at lower elevations.Glaciers on the Chugach National Forest are currently losing about 6 km3 of ice per year; half of this loss comes from Columbia Glacier (Berthier et al. 2010).Over the past decade, almost all

  12. Digging of 'Snow White' Begins

    Science.gov (United States)

    2008-01-01

    NASA's Phoenix Mars Lander began excavating a new trench, dubbed 'Snow White,' in a patch of Martian soil located near the center of a polygonal surface feature, nicknamed 'Cheshire Cat.' The trench is about 2 centimeters (.8 inches) deep and 30 centimeters (about 12 inches) long. The 'dump pile' is located at the top of the trench, the side farthest away from the lander, and has been dubbed 'Croquet Ground.' The digging site has been named 'Wonderland.' At this early stage of digging, the Phoenix team did not expect to find any of the white material seen in the first trench, now called 'Dodo-Goldilocks.' That trench showed white material at a depth of about 5 centimeters (2 inches). More digging of Snow White is planned for coming sols, or Martian days. The dark portion of this image is the shadow of the lander's solar panel; the bright areas within this region are not in shadow. Snow White was dug on Sol 22 (June 17, 2008) with Phoenix's Robotic Arm. This picture was acquired on the same day by the lander's Surface Stereo Imager. This image has been enhanced to brighten shaded areas. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  13. Nitrate photolysis in salty snow

    Science.gov (United States)

    Donaldson, D. J.; Morenz, K.; Shi, Q.; Murphy, J. G.

    2016-12-01

    Nitrate photolysis from snow can have a significant impact on the oxidative capacity of the local atmosphere, but the factors affecting the release of gas phase products are not well understood. Here, we report the first systematic study of the amounts of NO, NO2, and total nitrogen oxides (NOy) emitted from illuminated snow samples as a function of both nitrate and total salt (NaCl and Instant Ocean) concentration. We show that the release of nitrogen oxides to the gas phase is directly related to the expected nitrate concentration in the brine at the surface of the snow crystals, increasing to a plateau value with increasing nitrate, and generally decreasing with increasing NaCl or Instant Ocean (I.O.). In frozen mixed nitrate (25 mM) - salt (0-500 mM) solutions, there is an increase in gas phase NO2 seen at low added salt amounts: NO2 production is enhanced by 35% at low prefreezing [NaCl] and by 70% at similar prefreezing [I.O.]. Raman microscopy of frozen nitrate-salt solutions shows evidence of stronger nitrate exclusion to the air interface in the presence of I.O. than with added NaCl. The enhancement in nitrogen oxides emission in the presence of salts may prove to be important to the atmospheric oxidative capacity in polar regions.

  14. Everywhere and nowhere: snow and its linkages

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    Grünewald, Thomas; Wolfsperger, Fabian

    2016-04-01

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

  16. Power System for Intelligent House

    Directory of Open Access Journals (Sweden)

    Michal Jahelka

    2010-01-01

    Full Text Available Power supply of intelligent houses or house phones is possible to do with standard transformer with voltage stabilizer or with intelligent power supply. Standard solution can has as a result of failure fuse blown or fire occurrence. Intelligent power supply switch off power and tests with little current whether short circuit is removed. After it resume system power supply. At the same time it cares of system backup with accumulator, informs control system about short circuit or failure net power supply, or can switch off all system power after command from control system.

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

    Science.gov (United States)

    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

  18. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  19. Intelligent Design

    DEFF Research Database (Denmark)

    Hjorth, Poul G.

    2005-01-01

    Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig.......Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig....

  20. Snow cover as a source of technogenic pollution of surface water during the snow melting period

    OpenAIRE

    Labuzova Olga; Noskova Tatyana; Lysenko Maria; Ovcharenko Elena; Papina Tatyana

    2016-01-01

    The study of pollutants in melt water of snow cover and snow disposal sites in the city of Barnaul showed that during the snow melting period the surface water is not subjected to significant technogenic impact according to a number of studied indices. The oils content is an exception: it can exceed MAC more than 20 times in river- water due to the melting of city disposal sites. Environmental damage due to an oils input into water resources during the snow melting period...

  1. New nitrogen uptake strategy: specialized snow roots.

    Science.gov (United States)

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

    2009-08-01

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

  2. Snow Water Equivalent SAR and Radiometer

    Data.gov (United States)

    National Aeronautics and Space Administration — After nearly four decades of international effort developing remote sensing techniques, measurement of land surface snow remains a significant challenge. Developing...

  3. Surface energy balance of seasonal snow cover for snow-melt ...

    Indian Academy of Sciences (India)

    This study describes time series analysis of snow-melt, radiation data and energy balance for a seasonal snow cover at Dhundi field station of SASE, which lies in Pir Panjal range of the. N–W Himalaya, for a winter season from 13 January to 12 April 2005. The analysis shows that mean snow surface temperature remains ...

  4. Water losses during technical snow production

    Science.gov (United States)

    Grünewald, Thomas; Wolfsperger, Fabian

    2017-04-01

    These days, the production of technical snow can be seen as a prerequisite for winter tourism. Huge amounts of water are used for technical snow production by ski resorts, especially in the beginning of the winter season. The aim is to guarantee an appropriate amount of snow to reliably provide optimal ski runs until the date of season opening in early December. Technical snow is generated by pumping pressurized water through the nozzles of a snow machine and dispersing the resulting spray of small water droplets which freeze during their travel to the ground. Cooling and freezing of the droplets can only happen if energy is emitted to the air mass surrounding the droplets. This heat transfer is happening through convective cooling and though evaporation and sublimation of water droplets and ice particles. This means that also mass is lost from the droplets and added in form of vapor to the air. It is important to note that not all water that is pumped through the snow machine is converted to snow distributed on the ground. Significant amounts of water are lost due to wind drift, sublimation and evaporation while droplets are traveling through the air or to draining of water which is not fully frozen when arriving at the ground. Studies addressing this question are sparse and the quantity of the water losses is still unclear. In order to assess this question in more detail, we obtained several systematic field observations at a test site near Davos, Switzerland. About a dozen of snow making tests had been performed during the last winter seasons. We compare the amount of water measured at the intake of the snow machine with the amount of snow accumulating at the ground during a night of snow production. The snow mass was calculated from highly detailed repeated terrestrial laser scanning measurements in combination with manually gathered snow densities. In addition a meteorological station had been set up in the vicinity observing all relevant meteorological

  5. A simple algorithm for identifying periods of snow accumulation on a radiometer

    Science.gov (United States)

    Lapo, Karl E.; Hinkelman, Laura M.; Landry, Christopher C.; Massmann, Adam K.; Lundquist, Jessica D.

    2015-09-01

    Downwelling solar, Qsi, and longwave, Qli, irradiances at the earth's surface are the primary energy inputs for many hydrologic processes, and uncertainties in measurements of these two terms confound evaluations of estimated irradiances and negatively impact hydrologic modeling. Observations of Qsi and Qli in cold environments are subject to conditions that create additional uncertainties not encountered in other climates, specifically the accumulation of snow on uplooking radiometers. To address this issue, we present an automated method for estimating these periods of snow accumulation. Our method is based on forest interception of snow and uses common meteorological observations. In this algorithm, snow accumulation must exceed a threshold to obscure the sensor and is only removed through scouring by wind or melting. The algorithm is evaluated at two sites representing different mountain climates: (1) Snoqualmie Pass, Washington (maritime) and (2) the Senator Beck Basin Study Area, Colorado (continental). The algorithm agrees well with time-lapse camera observations at the Washington site and with multiple measurements at the Colorado site, with 70-80% of observed snow accumulation events correctly identified. We suggest using the method for quality controlling irradiance observations in snow-dominated climates where regular, daily maintenance is not possible.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  8. Estimation of snow cover distribution in Beas basin, Indian Himalaya ...

    Indian Academy of Sciences (India)

    In the present paper, a methodology has been developed for the mapping of snow cover in Beas ... Different snow cover mapping methods using snow indices are compared to find the suitable ... cover are important factors for human activities,.

  9. (NDSI) and Normalised Difference Principal Component Snow Index

    African Journals Online (AJOL)

    Phila Sibandze

    According to Bonan (2002), snow plays a significant role in influencing heat regimes and local, regional ... sensitive indicator to climate change. In South Africa, snow is .... This image was captured on the earliest cloud free day after a snow fall.

  10. Intelligent playgrounds

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2009-01-01

    This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

  11. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  12. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  13. Livestock Husbandry and Snow Leopard Conservation

    NARCIS (Netherlands)

    Mohammad, Ghulam; Mostafawi, Sayed Naqibullah; Dadul, Jigmet; Rosen, Tatjana; Mishra, Charudutt; Bhatnagar, Yash Veer; Trivedi, Pranav; Timbadia, Radhika; Bijoor, Ajay; Murali, Ranjini; Sonam, Karma; Thinley, Tanzin; Namgail, Tsewang; Prins, Herbert H.T.; Nawaz, Muhammad Ali; Ud Din, Jaffar; Buzdar, Hafeez

    2016-01-01

    Livestock depredation is a key source of snow leopard mortality across much of the species' range. Snow leopards break into livestock corrals, killing many domestic animals and thereby inflicting substantial economic damage. Locals may retaliate by killing the cat and selling its parts.

  14. Brilliant Colours from a White Snow Cover

    Science.gov (United States)

    Vollmer, Michael; Shaw, Joseph A

    2013-01-01

    Surprisingly colourful views are possible from sparkling white snow. It is well known that similarly colourful features can exist in the sky whenever appropriate ice crystals are around. However, the transition of light reflection and refraction from ice crystals in the air to reflection and refraction from those in snow on the ground is not…

  15. Prevent Snow from Blocking your Tailpipe

    Centers for Disease Control (CDC) Podcasts

    2014-12-11

    If it's snowing, make sure your vehicle’s tailpipe is clear of snow before starting the engine to prevent carbon monoxide poisoning.  Created: 12/11/2014 by National Center for Environmental Health (NCEH).   Date Released: 12/11/2014.

  16. Modelling stable atmospheric boundary layers over snow

    NARCIS (Netherlands)

    Sterk, H.A.M.

    2015-01-01

    Thesis entitled:

    Modelling Stable Atmospheric Boundary Layers over Snow

    H.A.M. Sterk

    Wageningen, 29th of April, 2015

    Summary

    The emphasis of this thesis is on the understanding and forecasting of the Stable Boundary Layer (SBL) over snow-covered surfaces. SBLs

  17. Sublimation From Snow in Northern Environments

    Science.gov (United States)

    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.

  18. Major ions in spitsbergen snow samples

    International Nuclear Information System (INIS)

    Semb, A.; Braekkan, R.; Joranger, E.

    1984-01-01

    Chemical analysis of Spitsbergen snow cores sampled in spring 1983, reveals a spatial pattern consistent with orographic deposition of major anthropogenic pollutants with air movements from southeast towards northwest. The highest concentrations of pollutant species were found at an altitude of 700 metres above sea level, and are higher than for any other recorded snow samples from the Arctic

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

    Science.gov (United States)

    Kamtekar, Rachana

    2015-01-01

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

  20. Regime shift of snow days in Switzerland

    Science.gov (United States)

    Marty, Christoph

    2008-06-01

    The number of days with a snow depth above a certain threshold is the key factor for winter tourism in an Alpine country like Switzerland. An investigation of 34 long-term stations between 200 and 1800 m asl (above sea level) going back for at least the last 60 years (1948-2007) shows an unprecedented series of low snow winters in the last 20 years. The signal is uniform despite high regional differences. A shift detection analysis revealed a significant step-like decrease in snow days at the end of the 1980's with no clear trend since then. This abrupt change resulted in a loss of 20% to 60% of the total snow days. The stepwise increase of the mean winter temperature at the end of the 1980's and its close correlation with the snow day anomalies corroborate the sensitivity of the mid-latitude winter to the climate change induced temperature increase.

  1. Intelligent Environmental Nanomaterials

    KAUST Repository

    Chang, Jian

    2018-01-30

    Due to the inherent complexity of environmental problems, especially water and air pollution, the utility of single-function environmental nanomaterials used in conventional and unconventional environmental treatment technologies are gradually reaching their limits. Intelligent nanomaterials with environmentally-responsive functionalities have shown potential to improve the performance of existing and new environmental technologies. By rational design of their structures and functionalities, intelligent nanomaterials can perform different tasks in response to varying application scenarios for the purpose of achieving the best performance. This review offers a critical analysis of the design concepts and latest progresses on the intelligent environmental nanomaterials in filtration membranes with responsive gates, materials with switchable wettability for selective and on-demand oil/water separation, environmental materials with self-healing capability, and emerging nanofibrous air filters for PM2.5 removal. We hope that this review will inspire further research efforts to develop intelligent environmental nanomaterials for the enhancement of the overall quality of environmental or human health.

  2. Intelligent Environmental Nanomaterials

    KAUST Repository

    Chang, Jian; Zhang, Lianbin; Wang, Peng

    2018-01-01

    Due to the inherent complexity of environmental problems, especially water and air pollution, the utility of single-function environmental nanomaterials used in conventional and unconventional environmental treatment technologies are gradually reaching their limits. Intelligent nanomaterials with environmentally-responsive functionalities have shown potential to improve the performance of existing and new environmental technologies. By rational design of their structures and functionalities, intelligent nanomaterials can perform different tasks in response to varying application scenarios for the purpose of achieving the best performance. This review offers a critical analysis of the design concepts and latest progresses on the intelligent environmental nanomaterials in filtration membranes with responsive gates, materials with switchable wettability for selective and on-demand oil/water separation, environmental materials with self-healing capability, and emerging nanofibrous air filters for PM2.5 removal. We hope that this review will inspire further research efforts to develop intelligent environmental nanomaterials for the enhancement of the overall quality of environmental or human health.

  3. Intelligent Advertising

    OpenAIRE

    Díaz Pinedo, Edilfredo Eliot

    2012-01-01

    Intelligent Advertisement diseña e implementa un sistema de publicidad para dispositivos móviles en un centro comercial, donde los clientes reciben publicidad de forma pasiva en sus dispositivos mientras están dentro.

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

    Science.gov (United States)

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

    2013-04-01

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

  5. BUSINESS INTELLIGENCE

    OpenAIRE

    Bogdan Mohor Dumitrita

    2011-01-01

    The purpose of this work is to present business intelligence systems. These systems can be extremely complex and important in modern market competition. Its effectiveness also reflects in price, so we have to exlore their financial potential before investment. The systems have 20 years long history and during that time many of such tools have been developed, but they are rarely still in use. Business intelligence system consists of three main areas: Data Warehouse, ETL tools and tools f...

  6. Intelligent indexing

    International Nuclear Information System (INIS)

    Farkas, J.

    1992-01-01

    In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space ι 2 to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs

  7. Intelligent indexing

    Energy Technology Data Exchange (ETDEWEB)

    Farkas, J

    1993-12-31

    In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space {iota}{sup 2} to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs.

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

    Directory of Open Access Journals (Sweden)

    M. G. Flanner

    2012-05-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-05-30

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  12. Spatial and temporal variability in seasonal snow density

    KAUST Repository

    Bormann, Kathryn J.

    2013-03-01

    Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

  13. Spatial and temporal variability in seasonal snow density

    KAUST Repository

    Bormann, Kathryn J.; Westra, Seth; Evans, Jason P.; McCabe, Matthew

    2013-01-01

    Snow density is a fundamental physical property of snowpacks used in many aspects of snow research. As an integral component in the remote sensing of snow water equivalent and parameterisation of snow models, snow density may be used to describe many important features of snowpack behaviour. The present study draws on a significant dataset of snow density and climate observations from the United States, Australia and the former Soviet Union and uses regression-based techniques to identify the dominant climatological drivers for snow densification rates, characterise densification rate variability and estimate spring snow densities from more readily available climate data. Total winter precipitation was shown to be the most prominent driver of snow densification rates, with mean air temperature and melt-refreeze events also found to be locally significant. Densification rate variance is very high at Australian sites, very low throughout the former Soviet Union and between these extremes throughout much of the US. Spring snow densities were estimated using a statistical model with climate variable inputs and best results were achieved when snow types were treated differently. Given the importance of snow density information in many snow-related research disciplines, this work has implications for current methods of converting snow depths to snow water equivalent, the representation of snow dynamics in snow models and remote sensing applications globally. © 2013 Elsevier B.V.

  14. Intelligent Flow Control Valve

    Science.gov (United States)

    Kelley, Anthony R (Inventor)

    2015-01-01

    The present invention is an intelligent flow control valve which may be inserted into the flow coming out of a pipe and activated to provide a method to stop, measure, and meter flow coming from the open or possibly broken pipe. The intelligent flow control valve may be used to stop the flow while repairs are made. Once repairs have been made, the valve may be removed or used as a control valve to meter the amount of flow from inside the pipe. With the addition of instrumentation, the valve may also be used as a variable area flow meter and flow controller programmed based upon flowing conditions. With robotic additions, the valve may be configured to crawl into a desired pipe location, anchor itself, and activate flow control or metering remotely.

  15. Linking Changes in Snow Cover with Nitrogen Cycling and Microbial Abundance and Functional Gene Expression in Agricultural Soils

    Science.gov (United States)

    Goyer, C.; Brin, L.; Zebarth, B.; Burton, D.; Wertz, S.; Chantigny, M.

    2016-12-01

    In eastern Canada, climate change-related warming and increased precipitation may alter winter snow cover, with potential consequences for soil conditions, microbes, and N2O fluxes. We conducted a two-year field study with snow removal, passive snow addition, and ambient treatments in a potato-barley crop system. We measured in situ greenhouse gas (N2O and CO2) fluxes and belowground gas accumulation, and quantified abundance and expression of denitrifier (nirS, nirK, nosZ) and nitrifier (ammonium oxidizing archaeal (AOA) and bacterial (AOB) amoA) genes. Soil gas accumulated throughout winter, and surface fluxes were greatest during spring thaw. Greatest mid-winter soil N2O accumulation and spring thaw N2O fluxes were associated with snow removal in winter 1 and ambient snow in winter 2. High N2O accumulation and fluxes may have been due to increased substrate availability with increased frost intensity in removal plots in winter 1, but with greatest water content in ambient plots in winter 2. In each winter, greatest abundances of nirS, nirK gene denitrifiers and/or amoA gene of AOA were observed in the treatments with the greatest N2O accumulation and fluxes. Gene expression did not vary with treatment, but highest expression of amoA gene of AOA and AOB, and nosZ gene was measured near 0ºC, indicating activity during periods of stable snow cover and spring thaw. Results suggest that the magnitude of fluxes during spring thaw were related to soil conditions and microbial communities present during the prior winter, and not solely those during thaw. Furthermore, the effects of changing snow cover on microbes and N2O fluxes were not a straightforward effect of snow depth, but were likely mediated by temperature and moisture.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  18. Mac OS X Snow Leopard pocket guide

    CERN Document Server

    Seiblod, Chris

    2009-01-01

    Whether you're new to the Mac or a longtime user, this handy book is the quickest way to get up to speed on Snow Leopard. Packed with concise information in an easy-to-read format, Mac OS X Snow Leopard Pocket Guide covers what you need to know and is an ideal resource for problem-solving on the fly. This book goes right to the heart of Snow Leopard, with details on system preferences, built-in applications, and utilities. You'll also find configuration tips, keyboard shortcuts, guides for troubleshooting, lots of step-by-step instructions, and more. Learn about new features and changes s

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    1985-01-01

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

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

    Science.gov (United States)

    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.

  2. Proposal of an intelligent wayside monitoring system for detection of critical ice accumulations on railway vehicles

    Science.gov (United States)

    Michelberger, Frank; Wagner, Adrian; Ostermann, Michael; Maly, Thomas

    2017-09-01

    At railway lines with ballasted tracks, under unfavourable conditions, the so-called flying ballast can occur predominantly for trains driving at high speeds. Especially in wintertime, it is highly likely that the causes are adhered snow or ice deposits, which are falling off the vehicle. Due to the high kinetic energy, the impact can lead to the removal of ballast stones from the structure of the ballasted track. If the stones reach the height of vehicles underside, they may be accelerated significantly due to the collision with the vehicle or may detach further ice blocks. In the worst case, a reinforcing effect occurs, which can lead to considerable damage to railway vehicles (under-floor-area, vehicle exteriors, etc.) and infrastructure (signal masts, noise barriers, etc.). Additionally the flying gravel is a significant danger to people in the nearby area of the tracks. With this feasibility study the applicability and meaningfulness of an intelligent monitoring system for identification of the critical ice accumulation to prevent the ballast fly induced by ice dropping was examined. The key findings of the research are that the detection of ice on railway vehicles and the development of an intelligent monitoring seem to be possible with existing technologies, but a proof of concept in terms of field tests is necessary.

  3. New Technology and Experimental Study on Snow-Melting Heated Pavement System in Tunnel Portal

    Directory of Open Access Journals (Sweden)

    Jinxing Lai

    2015-01-01

    Full Text Available In recent years, with the rapid growth of economy and sharp rise of motor vehicles in China, the pavement skid resistance in tunnel portals has become increasingly important in cold region. However, the deicing salt, snow removal with machine, and other antiskid measures adopted by highway maintenance division have many limitations. To improve the treatment effect, we proposed a new snow-melting approach employing electric heat tracing, in which heating cables are installed in the structural layer of road. Through the field experiment, laboratory experiment, and numerical investigation, structure type, heating power, and preheating time of the flexible pavement heating system in tunnel portal were systematically analyzed, and advantages of electric heat tracing technology in improving the pavement skid resistance in tunnel portal were also presented. Therefore, such new technology, which offers new snow-melting methods for tunnel portal, bridge, mountainous area, and large longitudinal slope in cold region, has promising prospect for extensive application.

  4. Total mineral material, acidity, sulphur, and nitrogen in rain and snow at Kentville, Nova Scotia

    Energy Technology Data Exchange (ETDEWEB)

    Herman, F A; Gorham, E

    1957-01-01

    Analyses of total ash, sulphur, ph, ammonia, and nitrate nitrogen have been made on 23 monthly precipitation samples and 17 individual snow samples collected between June 1952 and May 1954 at Kentville, Nova Scotia, in a predominantly agricultural area. Mean annual supply of total mineral ash was 95 kg/ha, of sulphur 9.1 hg/ha, of ammonia nitrogen 2.8 kg/ha, and of nitrate nitrogen 1.1 kg/ha. Average pH was 5.7, and rains more acid than this exhibited higher levels of both nitrate and sulphur, and a marked correlation between the latter and ammonia. Snow samples had much lower concentrations of ash, sulphur, and nitrogen than rain samples collected in the same months, which may perhaps indicate a lower efficiency of snow flakes in removing materials from the atmosphere.

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

    Science.gov (United States)

    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

  6. Intelligent systems

    CERN Document Server

    Irwin, J David

    2011-01-01

    Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system

  7. Intelligent Universe

    Energy Technology Data Exchange (ETDEWEB)

    Hoyle, F

    1983-01-01

    The subject is covered in chapters, entitled: chance and the universe (synthesis of proteins; the primordial soup); the gospel according to Darwin (discussion of Darwin theory of evolution); life did not originate on earth (fossils from space; life in space); the interstellar connection (living dust between the stars; bacteria in space falling to the earth; interplanetary dust); evolution by cosmic control (microorganisms; genetics); why aren't the others here (a cosmic origin of life); after the big bang (big bang and steady state); the information rich universe; what is intelligence up to; the intelligent universe.

  8. Artificial intelligence

    International Nuclear Information System (INIS)

    Perret-Galix, D.

    1992-01-01

    A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

  9. Artificial Intelligence and Moral intelligence

    Directory of Open Access Journals (Sweden)

    Laura Pana

    2008-07-01

    Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

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

    Directory of Open Access Journals (Sweden)

    C. Vera Valero

    2018-03-01

    Full Text Available 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.

  11. Snow cover as a source of technogenic pollution of surface water during the snow melting period

    Directory of Open Access Journals (Sweden)

    Labuzova Olga

    2016-10-01

    Full Text Available The study of pollutants in melt water of snow cover and snow disposal sites in the city of Barnaul showed that during the snow melting period the surface water is not subjected to significant technogenic impact according to a number of studied indices. The oils content is an exception: it can exceed MAC more than 20 times in river- water due to the melting of city disposal sites. Environmental damage due to an oils input into water resources during the snow melting period can be more than 300000 thousand rubles.

  12. Is Eurasian October snow cover extent increasing?

    International Nuclear Information System (INIS)

    Brown, R D; Derksen, C

    2013-01-01

    A number of recent studies present evidence of an increasing trend in Eurasian snow cover extent (SCE) in the October snow onset period based on analysis of the National Oceanic and Atmospheric Administration (NOAA) historical satellite record. These increases are inconsistent with fall season surface temperature warming trends across the region. Using four independent snow cover data sources (surface observations, two reanalyses, satellite passive microwave retrievals) we show that the increasing SCE is attributable to an internal trend in the NOAA CDR dataset to chart relatively more October snow cover extent over the dataset overlap period (1982–2005). Adjusting the series for this shift results in closer agreement with other independent datasets, stronger correlation with continentally-averaged air temperature anomalies, and a decrease in SCE over 1982–2011 consistent with surface air temperature warming trends over the same period. (letter)

  13. Central Asian Snow Cover from Hydrometeorological Surveys

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Central Asian Snow Cover from Hydrometeorological Surveys data are based on observations made by personnel for three river basins: Amu Darya, Sir Darya, and...

  14. SNOW CLEARING SERVICE WINTER 2001-2002

    CERN Multimedia

    ST-HM Group; Tel. 72202

    2001-01-01

    As usual at this time of the year, the snowing clearing service, which comes under the control of the Transport Group (ST-HM), is preparing for the start of snow-clearing operations (timetable, stand-by service, personnel responsible for driving vehicles and machines, preparation of useful and necessary equipment, work instructions, etc.) in collaboration with the Cleaning Service (ST-TFM) and the Fire Brigade (TIS-FB). The main difficulty for the snow-clearing service is the car parks, which cannot be properly cleared because of the presence of CERN and private vehicles parked there overnight in different parts of the parking areas. The ST-HM Transport Group would therefore like to invite you to park vehicles together in order to facilitate the access of the snow ploughs, thus allowing the car parks to be cleared more efficiently before the personnel arrives for work in the mornings.

  15. Rand Corporation Mean Monthly Global Snow Depth

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — All available monthly snow depth climatologies were integrated by the Rand Corporation, in the early 1980s, into one global (excluding Africa and South America)...

  16. Sustainable Block Design Process for High-Rise and High-Density Districts with Snow and Wind Simulations for Winter Cities

    Directory of Open Access Journals (Sweden)

    Norihiro Watanabe

    2017-11-01

    Full Text Available Urban designs that consider regional climatic conditions are one of the most important approaches for developing sustainable cities. In cities that suffer from heavy snow and cold winds in winter, an urban design approach different than that used for warm cities should be used. This study presents a scientific design process (the sustainable design approach that incorporates environmental and energy assessments that use snow and wind simulations to establish guidelines for the design of urban blocks in high-rise and high-density districts so that the impact of snow and wind can be minimized in these cities. A city block in downtown Sapporo, Japan, was used as a case study, and we evaluated four conceptual models. The four models were evaluated for how they impacted the snow and wind conditions in the block as well as the snow removal energy. Based on the results, we were able to identify the design guidelines in downtown Sapporo: an urban block design with higher building height ratio without the mid-rise part can reduce the snowdrifts and lower the snow removal energy. The proposed sustainable urban design approach would be effective in improving the quality of public spaces and reducing snow removal energy in winter cities.

  17. Photochemical degradation of PCBs in snow.

    Science.gov (United States)

    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

  18. Snow management practices in French ski resorts

    Science.gov (United States)

    Spandre, Pierre; Francois, Hugues; George-Marcelpoil, Emmanuelle; Morin, Samuel

    2016-04-01

    Winter tourism plays a fundamental role in the economy of French mountain regions but also in other countries such as Austria, USA or Canada. Ski operators originally developed grooming methods to provide comfortable and safe skiing conditions. The interannual variability of snow conditions and the competition with international destinations and alternative tourism activities encouraged ski resorts to mitigate their dependency to weather conditions through snowmaking facilities. However some regions may not be able to produce machine made snow due to inadequate conditions and low altitude resorts are still negatively impacted by low snow seasons. In the meantime, even though the operations of high altitude resorts do not show any dependency to the snow conditions they invest in snowmaking facilities. Such developments of snowmaking facilities may be related to a confused and contradictory perception of climate change resulting in individualistic evolutions of snowmaking facilities, also depending on ski resorts main features such as their altitude and size. Concurrently with the expansion of snowmaking facilities, a large range of indicators have been used to discuss the vulnerability of ski resorts such as the so-called "100 days rule" which was widely used with specific thresholds (i.e. minimum snow depth, dates) and constraints (i.e. snowmaking capacity). The present study aims to provide a detailed description of snow management practices and major priorities in French ski resorts with respect to their characteristics. We set up a survey in autumn 2014, collecting data from 56 French ski operators. We identify the priorities of ski operators and describe their snowmaking and grooming practices and facilities. The operators also provided their perception of the ski resort vulnerability to snow and economic challenges which we could compare with the actual snow conditions and ski lift tickets sales during the period from 2001 to 2012.

  19. Snow Drift Management: Summit Station Greenland

    Science.gov (United States)

    2016-05-01

    management Snow surveys Transport analysis Winds -- Speed 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF...that about 25% of the estimated snow that the wind transports to Summit each winter is deposited and forms drifts, mostly in close proxim- ity to...the structures. This analysis demonstrates that weather data ( wind speed and direction) and a transport analysis can aid in estimating the vol- ume of

  20. Acid Rain and Snow in Kashiwazaki City.

    OpenAIRE

    小野寺, 正幸; 富永, 禎秀; 竹園, 恵; 大金, 一二; Onodera, Masayuki; Tominaga, Yoshihide; Takesono, Satoshi; Oogane, Katsuji

    2002-01-01

    This paper described the actual condition of acid rain and snow and their influence of a winter monsoon in Kashiwazaki city. For 7 months from September in 2001 to March in 2002, the pH value was measured in rain or snow. The minimum of pH value observed was 3.9 for the 7 months. The day which observed pH

  1. Bike2Work: Rolling in the SNOW

    CERN Document Server

    2018-01-01

    This team is obviously cycling around the year! Unless the association to snow is purely linked to the fact that the team works in Service Management providing support for the ServiceNow, which computer platform is known as SNOW. The team members are from left to right Iban Eguia Moraza, Petar Tonkovic and Africa Santos. David Martin Clavo, the forth member, was absent on the day of the photo.

  2. Estimating Snow Cover from Publicly Available Images

    OpenAIRE

    Fedorov, Roman; Camerada, Alessandro; Fraternali, Piero; Tagliasacchi, Marco

    2016-01-01

    In this paper we study the problem of estimating snow cover in mountainous regions, that is, the spatial extent of the earth surface covered by snow. We argue that publicly available visual content, in the form of user generated photographs and image feeds from outdoor webcams, can both be leveraged as additional measurement sources, complementing existing ground, satellite and airborne sensor data. To this end, we describe two content acquisition and processing pipelines that are tailored to...

  3. The cumulative effect of consecutive winters' snow depth on moose and deer populations: a defence

    Science.gov (United States)

    McRoberts, R.E.; Mech, L.D.; Peterson, R.O.

    1995-01-01

    1. L. D. Mech et al. presented evidence that moose Alces alces and deer Odocoileus virginianus population parameters re influenced by a cumulative effect of three winters' snow depth. They postulated that snow depth affects adult ungulates cumulatively from winter to winter and results in measurable offspring effects after the third winter. 2. F. Messier challenged those findings and claimed that the population parameters studied were instead affected by ungulate density and wolf indexes. 3. This paper refutes Messier's claims by demonstrating that his results were an artifact of two methodological errors. The first was that, in his main analyses, Messier used only the first previous winter's snow depth rather than the sum of the previous three winters' snow depth, which was the primary point of Mech et al. Secondly, Messier smoothed the ungulate population data, which removed 22-51% of the variability from the raw data. 4. When we repeated Messier's analyses on the raw data and using the sum of the previous three winter's snow depth, his findings did not hold up.

  4. Snow darkening caused by black carbon emitted from fires

    Science.gov (United States)

    Engels, Jessica; Kloster, Silvia; Bourgeois, Quentin

    2014-05-01

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

  5. Snow as a habitat for microorganisms

    Science.gov (United States)

    Hoham, Ronald W.

    1989-01-01

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

  6. Snow model design for operational purposes

    Science.gov (United States)

    Kolberg, Sjur

    2017-04-01

    A parsimonious distributed energy balance snow model intended for operational use is evaluated using discharge, snow covered area and grain size; the latter two as observed from the MODIS sensor. The snow model is an improvement of the existing GamSnow model, which is a part of the Enki modelling framework. Core requirements for the new version have been: 1. Reduction of calibration freedom, motivated by previous experience of non-identifiable parameters in the existing version 2. Improvement of process representation based on recent advances in physically based snow modelling 3. Limiting the sensitivity to forcing data which are poorly known over the spatial domain of interest (often in mountainous areas) 4. Preference for observable states, and the ability to improve from updates. The albedo calculation is completely revised, now based on grain size through an emulation of the SNICAR model (Flanner and Zender, 2006; Gardener and Sharp, 2010). The number of calibration parameters in the albedo model is reduced from 6 to 2. The wind function governing turbulent energy fluxes has been reduced from 2 to 1 parameter. Following Raleigh et al (2011), snow surface radiant temperature is split from the top layer thermodynamic temperature, using bias-corrected wet-bulb temperature to model the former. Analyses are ongoing, and the poster will bring evaluation results from 16 years of MODIS observations and more than 25 catchments in southern Norway.

  7. Speech Intelligibility

    Science.gov (United States)

    Brand, Thomas

    Speech intelligibility (SI) is important for different fields of research, engineering and diagnostics in order to quantify very different phenomena like the quality of recordings, communication and playback devices, the reverberation of auditoria, characteristics of hearing impairment, benefit using hearing aids or combinations of these things.

  8. Understanding snow-transport processes shaping the mountain snow-cover

    Directory of Open Access Journals (Sweden)

    R. Mott

    2010-12-01

    Full Text Available Mountain snow-cover is normally heterogeneously distributed due to wind and precipitation interacting with the snow cover on various scales. The aim of this study was to investigate snow deposition and wind-induced snow-transport processes on different scales and to analyze some major drift events caused by north-west storms during two consecutive accumulation periods. In particular, we distinguish between the individual processes that cause specific drifts using a physically based model approach. Very high resolution wind fields (5 m were computed with the atmospheric model Advanced Regional Prediction System (ARPS and used as input for a model of snow-surface processes (Alpine3D to calculate saltation, suspension and preferential deposition of precipitation. Several flow features during north-west storms were identified with input from a high-density network of permanent and mobile weather stations and indirect estimations of wind directions from snow-surface structures, such as snow dunes and sastrugis. We also used Terrestrial and Airborne Laser Scanning measurements to investigate snow-deposition patterns and to validate the model. The model results suggest that the in-slope deposition patterns, particularly two huge cross-slope cornice-like drifts, developed only when the prevailing wind direction was northwesterly and were formed mainly due to snow redistribution processes (saltation-driven. In contrast, more homogeneous deposition patterns on a ridge scale were formed during the same periods mainly due to preferential deposition of precipitation. The numerical analysis showed that snow-transport processes were sensitive to the changing topography due to the smoothing effect of the snow cover.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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...

  11. Snow Monitoring Using Remote Sensing Data: Modification of Normalized Difference Snow Index

    Science.gov (United States)

    Kaplan, G.; Avdan, U.

    2016-12-01

    Snow cover is an important part of the Earth`s climate system so its continuous monitoring is necessary to map snow cover in high resolution. Satellite remote sensing can successfully fetch land cover and land cover changes. Although normalized difference snow index NDSI has quite good accuracy, topography shadow, water bodies and clouds can be easily misplaced as snow. Using Landsat TM, +ETM and TIRS/OLI satellite images, the NDSI was modified for more accurate snow mapping. In this paper, elimination of the misplaced water bodies was made using the high reflectance of the snow in the blue band. Afterwards, the modified NDSI (MNDSI) was used for estimating snow cover through the years on the highest mountains in Republic of Macedonia. The results from this study show that the MNDSI accuracy is bigger than the NDSI`s, totally eliminating the misplaced water bodies, and partly the one caused from topography and clouds. Also, it was noticed that the snow cover in the study area has been lowered through the years. For future studies, the MNDSI should be validated on different study areas with different characteristics.

  12. Iron snow in the Martian core?

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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

  14. Monitoring Forsmark. Snow depth, snow water content and ice cover during the winter 2010/2011

    International Nuclear Information System (INIS)

    Wass, Eva

    2011-07-01

    Snow depth and ice cover have been measured and observed during the winter 2010/2011. This type of measurements started in the winter 2002/2003 and has been ongoing since then. In addition to these parameters, the water content of the snow was calculated at each measurement occasion from the weight of a snow sample. Measurements and observations were conducted on a regular basis from the beginning of November 2010 until the middle of April 2011. A persistent snow cover was established in the end of November 2010 and remained until the beginning of April 2011 at the station with longest snow cover duration. The period of ice cover was 160 days in Lake Eckarfjaerden, whereas the sea bay at SFR was ice covered for 135 days

  15. Monitoring Forsmark. Snow depth, snow water content and ice cover during the winter 2010/2011

    Energy Technology Data Exchange (ETDEWEB)

    Wass, Eva (Geosigma AB (Sweden))

    2011-07-15

    Snow depth and ice cover have been measured and observed during the winter 2010/2011. This type of measurements started in the winter 2002/2003 and has been ongoing since then. In addition to these parameters, the water content of the snow was calculated at each measurement occasion from the weight of a snow sample. Measurements and observations were conducted on a regular basis from the beginning of November 2010 until the middle of April 2011. A persistent snow cover was established in the end of November 2010 and remained until the beginning of April 2011 at the station with longest snow cover duration. The period of ice cover was 160 days in Lake Eckarfjaerden, whereas the sea bay at SFR was ice covered for 135 days

  16. Artificial Intelligence.

    Science.gov (United States)

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

  17. Determining Snow Depth Using Airborne Multi-Pass Interferometric Synthetic Aperture Radar

    Science.gov (United States)

    2013-09-01

    Snow Water Equivalent xxiii ACKNOWLEDGMENTS An intelligent heart acquires knowledge, and the ear of the wise seeks knowledge. ( Proverbs 18:15...the phase and elevation. y = 2.3575x + 4.8809 R² = 0.9386 0 2 4 6 8 10 -1 -0.5 0 0.5 1 1.5 2 E le va tio n D ev ia tio n (m et er s) Phase...5 6 7 8 9 10 0 0.5 1 1.5 2 2.5 3 E le va tio n D ev ia tio n (m et er s) Phase Deviation (radians) Phase to Elevation Linear Regression

  18. Intelligent Tutor

    Science.gov (United States)

    1990-01-01

    NASA also seeks to advance American education by employing the technology utilization process to develop a computerized, artificial intelligence-based Intelligent Tutoring System (ITS) to help high school and college physics students. The tutoring system is designed for use with the lecture and laboratory portions of a typical physics instructional program. Its importance lies in its ability to observe continually as a student develops problem solutions and to intervene when appropriate with assistance specifically directed at the student's difficulty and tailored to his skill level and learning style. ITS originated as a project of the Johnson Space Center (JSC). It is being developed by JSC's Software Technology Branch in cooperation with Dr. R. Bowen Loftin at the University of Houston-Downtown. Program is jointly sponsored by NASA and ACOT (Apple Classrooms of Tomorrow). Other organizations providing support include Texas Higher Education Coordinating Board, the National Research Council, Pennzoil Products Company and the George R. Brown Foundation. The Physics I class of Clear Creek High School, League City, Texas are providing the classroom environment for test and evaluation of the system. The ITS is a spinoff product developed earlier to integrate artificial intelligence into training/tutoring systems for NASA astronauts flight controllers and engineers.

  19. Modelling snow accumulation and snow melt in a continuous hydrological model for real-time flood forecasting

    International Nuclear Information System (INIS)

    Stanzel, Ph; Haberl, U; Nachtnebel, H P

    2008-01-01

    Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.

  20. Modelling snow accumulation and snow melt in a continuous hydrological model for real-time flood forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Stanzel, Ph; Haberl, U; Nachtnebel, H P [Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Applied Life Sciences, Muthgasse 18, 1190 Vienna (Austria)], E-mail: philipp.stanzel@boku.ac.at

    2008-11-01

    Hydrological models for flood forecasting in Alpine basins need accurate representation of snow accumulation and snow melt processes. A continuous, semi-distributed rainfall-runoff model with snow modelling procedures using only precipitation and temperature as input is presented. Simulation results from an application in an Alpine Danube tributary watershed are shown and evaluated with snow depth measurements and MODIS remote sensing snow cover information. Seasonal variations of runoff due to snow melt were simulated accurately. Evaluation of simulated snow depth and snow covered area showed strengths and limitations of the model and allowed an assessment of input data quality. MODIS snow cover images were found to be valuable sources of information for hydrological modelling in alpine areas, where ground observations are scarce.

  1. Hair Removal

    Science.gov (United States)

    ... Staying Safe Videos for Educators Search English Español Hair Removal KidsHealth / For Teens / Hair Removal What's in ... you need any of them? Different Types of Hair Before removing hair, it helps to know about ...

  2. Intelligent Design and Intelligent Failure

    Science.gov (United States)

    Jerman, Gregory

    2015-01-01

    Good Evening, my name is Greg Jerman and for nearly a quarter century I have been performing failure analysis on NASA's aerospace hardware. During that time I had the distinct privilege of keeping the Space Shuttle flying for two thirds of its history. I have analyzed a wide variety of failed hardware from simple electrical cables to cryogenic fuel tanks to high temperature turbine blades. During this time I have found that for all the time we spend intelligently designing things, we need to be equally intelligent about understanding why things fail. The NASA Flight Director for Apollo 13, Gene Kranz, is best known for the expression "Failure is not an option." However, NASA history is filled with failures both large and small, so it might be more accurate to say failure is inevitable. It is how we react and learn from our failures that makes the difference.

  3. Deriving Snow Cover Metrics for Alaska from MODIS

    Directory of Open Access Journals (Sweden)

    Chuck Lindsay

    2015-09-01

    Full Text Available Moderate Resolution Imaging Spectroradiometer (MODIS daily snow cover products provide an opportunity for determining snow onset and melt dates across broad geographic regions; however, cloud cover and polar darkness are limiting factors at higher latitudes. This study presents snow onset and melt dates for Alaska, portions of western Canada and the Russian Far East derived from Terra MODIS snow cover daily 500 m grid data (MOD10A1 and evaluates our method for filling data gaps caused by clouds or polar darkness. Pixels classified as cloud or no data were reclassified by: spatial filtering using neighboring pixel values; temporal filtering using pixel values for days before/after cloud cover; and snow-cycle filtering based on a time series assessment of a pixel’s position within snow accumulation, cover or melt periods. During the 2012 snow year, these gap-filling methods reduced cloud pixels from 27.7% to 3.1%. A total of 12 metrics (e.g., date of first and last snow, date of persistent snow cover and periods of intermittence for each pixel were calculated by snow year. A comparison of MODIS-derived snow onset and melt dates with in situ observations from 244 weather stations generally showed an early bias in MODIS-derived dates and an effect of increasing cloudiness exacerbating bias. Our results show that mean regional duration of seasonal snow cover is 179–311 days/year and that snow cover is often intermittent, with 41% of the area experiencing ≥2 snow-covered periods during a snow season. Other regional-scale patterns in the timing of snow onset and melt are evident in the yearly 500 m gridded products publically available at http://static.gina.alaska.edu/NPS_products/MODIS_snow/.

  4. Learn Mac OS X Snow Leopard

    CERN Document Server

    Meyers, Scott

    2009-01-01

    You're smart and savvy, but also busy. This comprehensive guide to Apple's Mac OS X 10.6, Snow Leopard, gives you everything you need to know to live a happy, productive Mac life. Learn Mac OS X Snow Leopard will have you up and connected lickity split. With a minimum of overhead and a maximum of useful information, you'll cover a lot of ground in the time it takes other books to get you plugged in. If this isn't your first experience with Mac OS X, skip right to the "What's New in Snow Leopard" sections. You may also find yourself using this book as a quick refresher course or a way

  5. Snow Precipitation and Snow Cover Climatic Variability for the Period 1971–2009 in the Southwestern Italian Alps: The 2008–2009 Snow Season Case Study

    Directory of Open Access Journals (Sweden)

    Simona Fratianni

    2010-10-01

    Full Text Available Snow cover greatly influences the climate in the Alpine region and is one of the most relevant parameters for the climate change analysis. Nevertheless, snow precipitation variability is a relatively underexplored field of research because of the lack of long-term, continuous and homogeneous time series. After a historical research aiming to recover continuous records, three high quality time series of snow precipitation and snow depth recorded in the southwestern Italian Alps were analyzed. The comparison between the climatological indices over the 30 years reference period 1971–2000 and the decade 2000–2009 outlined a general decrease in the amount of snow precipitation, and a shift in the seasonal distribution of the snow precipitation in the most recent period. In the analysis of the last decade snow seasons characteristics, the attention was focused on the heavy snowfalls that occurred in Piedmont during the 2008–2009 snow season: MODerate resolution Imager Spectroradiometer (MODIS snow cover products were used to evaluate snow cover extension at different times during the snow season, and the results were set in relation to the temperatures.

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

    Science.gov (United States)

    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.

  7. Assessment of the Performance of Several Roadway Mixes under Rain, Snow, and Winter Maintenance Activities

    OpenAIRE

    Flintsch, Gerardo W.

    2004-01-01

    The purpose of this study was to assess the relative functional performance, including skid resistance and splash and spray, of five hot-mix-asphalt (HMA) surfaces and a tinned portland cement concrete highway surface during controlled wet and wintry weather events. The study compared the way that these surfaces respond to various deicing and anti-icing snow removal and ice control techniques under artificial wintry conditions. In addition, the splash and spray characteristics of the surfaces...

  8. Snow and ice blocking of tunnels

    Energy Technology Data Exchange (ETDEWEB)

    Lia, Leif

    1998-12-31

    Hydroelectric power development in cold regions causes much concern about operational reliability and dam safety. This thesis studies the temperature distribution in tunnels by means of air temperature measurements in six tunnel spillways and five diversion tunnels. The measurements lasted for two consecutive winters. The air through flow tunnel is used as it causes cooling of both rock and water. In open spillway tunnels, frost reaches the entire tunnel. In spillway tunnels with walls, the frost zones reach about 100 m from the downstream end. In mildly-inclined diversion tunnels, a frost free zone is located in the middle of the tunnel and snow and ice problems were only observed in the inlet and outlet. Severe aufeis is accumulation is observed in the frost zones. The heat transfer from rock to air, water and ice is calculated and used in a prediction model for the calculation of aufeis build-up together with local field observation data. The water penetration of snow plugs is also calculated, based on the heat balance. It takes 20 to 50 days for water to enter the blocked tunnel. The empirical values are 30 to 60 days, but only 1 day if the temperature of the snow pack is 0{sup o}C. Sensitivity analyses are carried out for temperature variations in rock, snow, water and ice. Systematic field observation shows that it is important for hydropower companies to know about the effects of snow and ice blocking in an area. A risk analysis of dam safety is presented for a real case. Finally, the thesis proposes solutions which can reduce the snow and ice problems. 79 refs., 63 figs., 11 tabs.

  9. Designing, developing and implementing a living snow fence program for New York state.

    Science.gov (United States)

    2015-07-01

    Living snow fences (LSF) are a form of passive snow control designed to mitigate blowing and drifting snow problems : on roadways. Blowing and drifting snow can increase the cost of highway maintenance and create hazardous driving : conditions when s...

  10. Can GRACE detect winter snows in Japan?

    Science.gov (United States)

    Heki, Kosuke

    2010-05-01

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

  11. Development of road hydronic snow-ice melting system with solar energy and seasonal underground thermal energy storage

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Q.; Liu, Y.; Ma, C.Q.; Li, M.; Huang, Y.; Yu, M. [Jilin Univ., Changchun (China). Dept. of Thermal Energy Engineering; Liu, X.B. [Climate Master Inc., OK (United States)

    2008-07-01

    Snow and ice melting technologies that used thermal energy storage were explored. The study included analyses of solar heat slab, seasonal underground thermal energy storage, and embedded pipe technologies. Different road materials, roadbed construction methods, and underground rock and soil conditions were also discussed. New processes combining all 3 of the main technologies were also reviewed. Other thermal ice melting technologies included conductive concrete and asphalt; heating cables, and hydronic melting systems. Geothermal energy is increasingly being considered as a means of melting snow and ice from roads and other infrastructure. Researchers have also been focusing on simulating heat transfer in solar collectors and road-embedded pipes. Demonstration projects in Japan, Switzerland, and Poland are exploring the use of combined geothermal and solar energy processes to remove snow and ice from roads. Research on hydronic melting technologies is also being conducted in the United States. The study demonstrated that snow-ice melting energy storage systems will become an important and sustainable method of snow and ice removal in the future. The technology efficiently uses renewable energy sources, and provides a cost-effective means of replacing or reducing chemical melting agents. 33 refs., 1 fig.

  12. Merging datasets from NASA SnowEx to better understand how snow falls and moves.

    Science.gov (United States)

    Gongora, J. A.; Marshall, H. P.; Glenn, N. F.

    2017-12-01

    A modelers ability to estimated snow depth and snow water equivalent (SWE) for mountain snow depends strongly on their understanding of snowpack spatial distribution and the soundness of the models initial conditions. This work focuses on the application of data science and efficient algorithms to find optimal locations in mountainous terrain to act as initital conditions for machine driven interpolation methods. By using graphs, collections of pairwise relationships between objects, to describe our data we were able to efficiently search, partition, and understand snowpack from the persepetive of this data structure.

  13. Moving sidewalk for snow board gelande; Snow board gerendemuke ugoku hodo

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-04-20

    This is a moving sidewalk installed on the indoor type artificial snow board gelande at Shigenobu-cho, Ehime prefecture, constructed for the first time in Shikoku. It carries snow boarders in gelande. The main specifications are as follows. Type: 800 type. Sidewalk width: 600mm. Length: 76.0m. Speed: 30m/min. Inclination angle: 13 degrees (inclination type). The features are as follows. (1) The tread is rubber-belt made and skid-resistant if it gets wet. (2) It is equipped with the each-part antifreezer, considering the snow quality and the environment where it is used at low temperature. (translated by NEDO)

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

    Science.gov (United States)

    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

  15. Estonian Mean Snow Depth and Duration (1891-1994)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains the number of days of snow cover in days per year, and three 10-day snow depth means per month in centimeters from stations across Estonia....

  16. Heavy metals in the snow pack of Semey town

    International Nuclear Information System (INIS)

    Panin, M.S.; Esenzholova, A.Zh.; Toropov, A.S.

    2008-01-01

    The data about the maintenance of heavy metals in the snow pack in various zones of Semey and biogeochemical operation factors of snow pack in Semey are presented in this work. Also the correlation connection between elements is calculated.

  17. Russian Federation Snow Depth and Ice Crust Surveys

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Russian Federation Snow Depth and Ice Crust Surveys, dataset DSI-9808, contains routine snow surveys that run throughout the cold season every 10 days (every five...

  18. [Characteristics of chemical pollution of snow cover in Aktobe areas].

    Science.gov (United States)

    Iskakov, A Zh

    2010-01-01

    The paper gives data on the nature of snow cover pollution in the urbanized areas in relation to the remoteness from the basic sources of ambient air pollution. The total snow content of carcinogens has been estimated.

  19. Western Italian Alps Monthly Snowfall and Snow Cover Duration

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of snow observations for 18 stations in the western Italian Alps. Two types of data are included: monthly snowfall amounts and monthly snow...

  20. GPM GROUND VALIDATION GCPEX SNOW MICROPHYSICS CASE STUDY V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GPM Ground Validation GCPEX Snow Microphysics Case Study characterizes the 3-D microphysical evolution and distribution of snow in context of the thermodynamic...

  1. SNOW THICKNESS ON AUSTRE GRØNFJORDBREEN, SVALBARD, FROM RADAR MEASUREMENTS AND STANDARD SNOW SURVEYS

    Directory of Open Access Journals (Sweden)

    I. I. Lavrentiev

    2018-01-01

    Full Text Available Summary Comparison of two methods of measurements of snow cover thickness on the glacier Austre Grønfjordbreen, Svalbard was performed in the spring of 2014. These methods were the radar (500 MHz observations and standard snow surveys. Measurements were conducted in 77 different points on the surface of the glacier. A good correlation (R2 = 0.98 was revealed. In comparison with the data of snow surveys, the radar measurements show a similar but more detailed pattern of the distribution of the snow cover depth. The discrepancy between the depths of snow cover on maps plotted from data of both methods did not exceed 30 cm in most parts of the glacier. The standard error of interpolation of the radar data onto the entire glacier surface amounts, on average, to 18 cm. This corresponds to the error of radar measurements of 18.8% when an average snow depth is about 160 cm and 9.4% at its maximum thickness of 320 cm. The distance between the measurement points at which the spatial covariance of the snow depth disappears falls between 236 and 283 m along the glacier, and between 117 and 165 m across its position. We compared the results of radar measurements of the pulse-delay time of reflections from the base of the snow cover with the data of manual probe measurements at 10 points and direct measurements of snow depth and average density in 12 snow pits. The average speed of radio waves propagation in the snow was determined as Vcr = 23.4±0.2 cm ns−1. This magnitude and the Looyenga and Kovacs formulas allowed estimating the average density of snow cover ρL = 353.1±13.1 kg m−3 and ρK = 337.4±12.9 kg m−3. The difference from average density measured in 12 pits ρav.meas = 387.4±12.9 kg m−3 amounts to −10.8% and −14.8%. In 2014, according to snow and radar measurements, altitudinal gradient of snow accumulation on the glacier Austre Grønfjordbreen was equal to 0.21 m/100 m, which is smaller than the

  2. Three-dimensional structural image analysis and mechanics of snow

    OpenAIRE

    Theile, Thiemo

    2011-01-01

    Summary This work deals with the problem of predicting the mechanical behaviour of dry snow based on the geometries and properties of its constituents. This approach is known as homogenisation. The main constituents of dry snow are ice and air. Their geometry, i.e. the microstructure, varies widely depending on the type of snow. The shape of individual, sintered snow grains varies and may take the form of stellar crystals, rounded and facetted grains or depth hoar crystals. ...

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

    Science.gov (United States)

    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.

  4. Collaborative Research: Snow Accumulation and Snow Melt in a Mixed Northern Hardwood-Conifer Forest, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains snow depth, Snow Water Equivalent (SWE), and forest cover characteristics for sites at the Hubbard Brook Experimental Forest in northern New...

  5. Assessment and placement of living snow fences to reduce highway maintenance costs and improve safety (living snow fences).

    Science.gov (United States)

    2015-05-01

    Living snow fences (LSF) are designed plantings of trees and/or shrubs and native grasses along highways, roads : and ditches that create a vegetative buffer that traps and controls blowing and drifting snow. These strategically : placed fences have ...

  6. Business Intelligence

    OpenAIRE

    Petersen, Anders

    2001-01-01

    Cílem této bakalářské práce je seznámení s Business Intelligence a zpracování vývojového trendu, který ovlivňuje podobu řešení Business Intelligence v podniku ? Business Activity Monitoring. Pro zpracování tohoto tématu byla použita metoda studia odborných pramenů, a to jak v českém, tak v anglickém jazyce. Hlavním přínosem práce je ucelený, v českém jazyce zpracovaný materiál pojednávající o Business Activity Monitoring. Práce je rozdělena do šesti hlavních kapitol. Prvních pět je věnováno p...

  7. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  8. "Snow Soup" Students Take on Animation Creation

    Science.gov (United States)

    Nikirk, Martin

    2009-01-01

    This article describes the process of producing "Snow Soup"--the 2009 Adobe Flash animation produced by the Computer Game Development and Animation seniors of Washington County Technical High School in Hagerstown, Maryland, for libraries in their area. In addition to the Flash product, the students produced two related Game Maker games, a printed…

  9. Evaluation of alternative snow plow cutting edges.

    Science.gov (United States)

    2009-05-01

    With approximately 450 snow plow trucks, the Maine Department of Transportation (MaineDOT) uses in : excess of 10,000 linear feet of plow cutting edges each winter season. Using the 2008-2009 cost per linear : foot of $48.32, the Departments total co...

  10. Snow as an accumulator of air pollutants

    Science.gov (United States)

    Robert T. Brown

    1976-01-01

    Using simple analytical techniques, the amounts of air pollutants accumulated in winter snow were determined and the results correlated with lichen survival on trees. Pollutants measured were particulate matter, sulfate, and chloride. An inverse relationship was found between amounts of each of these pollutants and the abundance of various lichens.

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

    Science.gov (United States)

    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

  12. Planetesimal formation starts at the snow line

    Science.gov (United States)

    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

  13. MODIS Snow Cover Recovery Using Variational Interpolation

    Science.gov (United States)

    Tran, H.; Nguyen, P.; Hsu, K. L.; Sorooshian, S.

    2017-12-01

    Cloud obscuration is one of the major problems that limit the usages of satellite images in general and in NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) global Snow-Covered Area (SCA) products in particular. Among the approaches to resolve the problem, the Variational Interpolation (VI) algorithm method, proposed by Xia et al., 2012, obtains cloud-free dynamic SCA images from MODIS. This method is automatic and robust. However, computational deficiency is a main drawback that degrades applying the method for larger scales (i.e., spatial and temporal scales). To overcome this difficulty, this study introduces an improved version of the original VI. The modified VI algorithm integrates the MINimum RESidual (MINRES) iteration (Paige and Saunders., 1975) to prevent the system from breaking up when applied to much broader scales. An experiment was done to demonstrate the crash-proof ability of the new algorithm in comparison with the original VI method, an ability that is obtained when maintaining the distribution of the weights set after solving the linear system. After that, the new VI algorithm was applied to the whole Contiguous United States (CONUS) over four winter months of 2016 and 2017, and validated using the snow station network (SNOTEL). The resulting cloud free images have high accuracy in capturing the dynamical changes of snow in contrast with the MODIS snow cover maps. Lastly, the algorithm was applied to create a Cloud free images dataset from March 10, 2000 to February 28, 2017, which is able to provide an overview of snow trends over CONUS for nearly two decades. ACKNOWLEDGMENTSWe would like to acknowledge NASA, NOAA Office of Hydrologic Development (OHD) National Weather Service (NWS), Cooperative Institute for Climate and Satellites (CICS), Army Research Office (ARO), ICIWaRM, and UNESCO for supporting this research.

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

    Science.gov (United States)

    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.

  15. Variability of snow line elevation, snow cover area and depletion in the main Slovak basins in winters 2001–2014

    Directory of Open Access Journals (Sweden)

    Krajčí Pavel

    2016-03-01

    Full Text Available Spatial and temporal variability of snow line (SL elevation, snow cover area (SCA and depletion (SCD in winters 2001–2014 is investigated in ten main Slovak river basins (the Western Carpathians. Daily satellite snow cover maps from MODIS Terra (MOD10A1, V005 and Aqua (MYD10A1, V005 with resolution 500 m are used.

  16. Estimation of the condition of snow cover in Voronezh according to the chemical analysis of water from melted snow

    OpenAIRE

    Prozhorina Tatyana Ivanovna; Bespalova Elena Vladimirovna; Yakunina Nadezhda

    2014-01-01

    Snow cover possesses high sorption ability and represents informative object to identify technogenic pollution of an urban environment. In this article the investigation data of a chemical composition of snow fallen in Voronezh during the winter period of 2014 are given. Relationships between existence of pollutants in snow and the level of technogenic effect are analyzed.

  17. Snowscape Ecology: Linking Snow Properties to Wildlife Movements and Demography

    Science.gov (United States)

    Prugh, L.; Verbyla, D.; van de Kerk, M.; Mahoney, P.; Sivy, K. J.; Liston, G. E.; Nolin, A. W.

    2017-12-01

    Snow enshrouds up to one third of the global land mass annually and exerts a major influence on animals that reside in these "snowscapes," (landscapes covered in snow). Dynamic snowscapes may have especially strong effects in arctic and boreal regions where dry snow persists for much of the year. Changes in temperature and hydrology are transforming northern regions, with profound implications for wildlife that are not well understood. We report initial findings from a NASA ABoVE project examining effects of snow properties on Dall sheep (Ovis dalli dalli). We used the MODSCAG snow fraction product to map spring snowline elevations and snow-off dates from 2000-2015 throughout the global range of Dall sheep in Alaska and northwestern Canada. We found a negative effect of spring snow cover on Dall sheep recruitment that increased with latitude. Using meteorological data and a daily freeze/thaw status product derived from passive microwave remote sensing from 1983-2012, we found that sheep survival rates increased in years with higher temperatures, less winter precipitation, fewer spring freeze-thaw events, and more winter freeze-thaw events. To examine the effects of snow depth and density on sheep movements, we used location data from GPS-collared sheep and a snowpack evolution model (SnowModel). We found that sheep selected for shallow, fluffy snow at high elevations, but they selected for denser snow as depth increased. Our field measurements identified a critical snow density threshold of 329 (± 18 SE) kg/m3 to support the weight of Dall sheep. Thus, sheep may require areas of shallow, fluffy snow for foraging, while relying on hard-packed snow for winter travel. These findings highlight the importance of multiple snowscape properties on wildlife movements and demography. The integrated study of snow properties and ecological processes, which we call snowscape ecology, will greatly improve global change forecasting.

  18. Intelligent it outsourcing

    CERN Document Server

    Willcocks, Leslie

    2013-01-01

    Intelligent IT Outsourcing enables practitioners to focus in on the essential issues that need to be addressed so that the fundamental structure of their sourcing strategy and its implementation is sound. The authors provide insight into the challenges likely to be faced and give detailed advice on how to pre-empt and manage these.IT and outsourcing continue to be problematic, not least because fundamental learning about this subject fails to be applied systematically, and because IT is inherently difficult to manage. The economics are not obvious and emerging technologies have to be addressed, therefore IT goes to the heart of many enterprises and interfaces with multiple business units and processes, and there are continuous skills shortages.Unfortunately complexities are not removed in outsourced situations where additional problems come into play, for example the supplier''s capabilities, whether the IT is right for an outsourcing solution, and whether the contract is robust but flexible enough to allow f...

  19. Intelligence and negotiating

    International Nuclear Information System (INIS)

    George, D.G.

    1990-01-01

    This paper discusses the role of US intelligence during arms control negotiations between 1982 and 1987. It also covers : the orchestration of intelligence projects; an evaluation of the performance of intelligence activities; the effect intelligence work had on actual arms negotiations; and suggestions for improvements in the future

  20. Intelligent products : A survey

    NARCIS (Netherlands)

    Meyer, G.G.; Främling, K.; Holmström, J.

    This paper presents an overview of the field of Intelligent Products. As Intelligent Products have many facets, this paper is mainly focused on the concept behind Intelligent Products, the technical foundations, and the achievable practical goals of Intelligent Products. A novel classification of

  1. Intelligence Issues for Congress

    Science.gov (United States)

    2013-04-23

    open source information— osint (newspapers...by user agencies. Section 1052 of the Intelligence Reform Act expressed the sense of Congress that there should be an open source intelligence ...center to coordinate the collection, analysis, production, and dissemination of open source intelligence to other intelligence agencies. An Open Source

  2. Water and life from snow: A trillion dollar science question

    Science.gov (United States)

    Sturm, Matthew; Goldstein, Michael A.; Parr, Charles

    2017-05-01

    Snow provides essential resources/services in the form of water for human use, and climate regulation in the form of enhanced cooling of the Earth. In addition, it supports a thriving winter outdoor recreation industry. To date, the financial evaluation of the importance of snow is incomplete and hence the need for accelerated snow research is not as clear as it could be. With snow cover changing worldwide in several worrisome ways, there is pressing need to determine global, regional, and local rates of snow cover change, and to link these to financial analyses that allow for rational decision making, as risks related to those decisions involve trillions of dollars.

  3. Snow observations in Mount Lebanon (2011-2016)

    Science.gov (United States)

    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

  4. Intelligent Governmentality

    Directory of Open Access Journals (Sweden)

    Willem de Lint

    2008-10-01

    Full Text Available Recently, within liberal democracies, the post-Westphalian consolidation of security and intelligence has ushered in the normalization not only of security in ‘securitization’ but also of intelligence in what is proposed here as ‘intelligencification.’ In outlining the features of intelligencified governance, my aim is to interrogate the view that effects or traces, and productivity rather than negation is as persuasive as commonly thought by the constructivists. After all, counter-intelligence is both about purging and reconstructing the archive for undisclosed values. In practice, what is being normalized is the authorized and legalized use of release and retention protocols of politically actionable information. The intelligencification of governmentality affords a sovereignty shell-game or the instrumentalization of sovereign power by interests that are dependent on, yet often inimical to, the power of state, national, and popular sovereignty. On voit le politique et le social comme dépendant de contingences exclusives. Récemment, au sein des démocraties libérales, la consolidation de la sécurité et des services de renseignements de sécurité qui a suivi les traités de la Westphalie a donné lieu à la normalisation non seulement de la sécurité en «sécurisation» mais aussi des services de renseignements de sécurité en ce qui est proposé ici comme «intelligencification» [terme anglais créé par l’auteur, dérivé du mot anglais «intelligence» dans le sens de renseignements des écurité]. En particulier, ce que l’on normalise dans le but de contourner des contingences exclusives est l’utilisation autorisée et légalisée de protocoles de communication et de rétention d’information qui, politiquement, pourrait mener à des poursuites. En esquissant les traits de la gouvernance «intelligencifiée», mon but est d’interroger le point de vue que les effets ou les traces, et la productivité plutôt que la

  5. Pathogen intelligence

    Directory of Open Access Journals (Sweden)

    Michael eSteinert

    2014-01-01

    Full Text Available Different species inhabit different sensory worlds and thus have evolved diverse means of processing information, learning and memory. In the escalated arms race with host defense, each pathogenic bacterium not only has evolved its individual cellular sensing and behaviour, but also collective sensing, interbacterial communication, distributed information processing, joint decision making, dissociative behaviour, and the phenotypic and genotypic heterogeneity necessary for epidemiologic success. Moreover, pathogenic populations take advantage of dormancy strategies and rapid evolutionary speed, which allow them to save co-generated intelligent traits in a collective genomic memory. This review discusses how these mechanisms add further levels of complexity to bacterial pathogenicity and transmission, and how mining for these mechanisms could help to develop new anti-infective strategies.

  6. Intelligent Routines

    CERN Document Server

    Anastassiou, George A

    Intelligent Routines II: Solving Linear Algebra and Differential Geometry with Sage” contains numerous of examples and problems as well as many unsolved problems. This book extensively applies the successful software Sage, which can be found free online http://www.sagemath.org/. Sage is a recent and popular software for mathematical computation, available freely and simple to use. This book is useful to all applied scientists in mathematics, statistics and engineering, as well for late undergraduate and graduate students of above subjects. It is the first such book in solving symbolically with Sage problems in Linear Algebra and Differential Geometry. Plenty of SAGE applications are given at each step of the exposition.

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

    Science.gov (United States)

    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.

  8. Soot in the atmosphere and snow surface of Antarctica

    International Nuclear Information System (INIS)

    Warren, S.G.; Clarke, A.D.

    1990-01-01

    Samples of snow collected near the south pole during January and February 1986 were analyzed for the presence of light-absorbing particles by passing the melted snow through a nuclepore filter. Transmission of light through the filter showed that snow far from the station contains the equivalent of 0.1-0.3 ng of carbon per gram of snow (ng/g). Samples of ambient air were filtered and found to contain about 1-2 ng of carbon per kilogram of air, giving a scavenging ratio of about 150. The snow downwind of the station exhibited a well-defined plume of soot due to the burning of diesel fuel, but even in the center of the plume 1 km downwind, the soot concentration was only 3 ng/g, too small to affect snow albedo significantly. Measurements of snow albedo near large inland stations are therefore probably representative of their surrounding regions

  9. Objective Characterization of Snow Microstructure for Microwave Emission Modeling

    Science.gov (United States)

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

    2012-01-01

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

  10. Intelligence: Real or artificial?

    OpenAIRE

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

  11. An AeroCom Assessment of Black Carbon in Arctic Snow and Sea Ice

    Science.gov (United States)

    Jiao, C.; Flanner, M. G.; Balkanski, Y.; Bauer, S. E.; Bellouin, N.; Bernsten, T. K.; Bian, H.; Carslaw, K. S.; Chin, M.; DeLuca, N.; hide

    2014-01-01

    Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are -4.4 (-13.2 to +10.7) ng/g for an earlier phase of AeroCom models (phase I), and +4.1 (-13.0 to +21.4) ng/g for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng/g. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model-measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60-90degN) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates

  12. An AeroCom assessment of black carbon in Arctic snow and sea ice

    Energy Technology Data Exchange (ETDEWEB)

    Jiao, C.; Flanner, M. G.; Balkanski, Y.; Bauer, S. E.; Bellouin, N.; Berntsen, T. K.; Bian, H.; Carslaw, K. S.; Chin, M.; De Luca, N.; Diehl, T.; Ghan, S. J.; Iversen, T.; Kirkevåg, A.; Koch, D.; Liu, X.; Mann, G. W.; Penner, J. E.; Pitari, G.; Schulz, M.; Seland, Ø.; Skeie, R. B.; Steenrod, S. D.; Stier, P.; Takemura, T.; Tsigaridis, K.; van Noije, T.; Yun, Y.; Zhang, K.

    2014-01-01

    Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. In this paper, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are -4.4 (-13.2 to +10.7) ng g-1 for an earlier phase of AeroCom models (phase I), and +4.1 (-13.0 to +21.4) ng g-1 for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng g-1. Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model–measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60–90° N) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with

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

    Science.gov (United States)

    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.

  14. Winter survival of Scots pine seedlings under different snow conditions.

    Science.gov (United States)

    Domisch, Timo; Martz, Françoise; Repo, Tapani; Rautio, Pasi

    2018-04-01

    Future climate scenarios predict increased air temperatures and precipitation, particularly at high latitudes, and especially so during winter. Soil temperatures, however, are more difficult to predict, since they depend strongly on the fate of the insulating snow cover. 'Rain-on-snow' events and warm spells during winter can lead to thaw-freeze cycles, compacted snow and ice encasement, as well as local flooding. These adverse conditions could counteract the otherwise positive effects of climatic changes on forest seedling growth. In order to study the effects of different winter and snow conditions on young Scots pine (Pinus sylvestris L.) seedlings, we conducted a laboratory experiment in which 80 1-year-old Scots pine seedlings were distributed between four winter treatments in dasotrons: ambient snow cover (SNOW), compressed snow and ice encasement (ICE), flooded and frozen soil (FLOOD) and no snow (NO SNOW). During the winter treatment period and a 1.5-month simulated spring/early summer phase, we monitored the needle, stem and root biomass of the seedlings, and determined their starch and soluble sugar concentrations. In addition, we assessed the stress experienced by the seedlings by measuring chlorophyll fluorescence, electric impedance and photosynthesis of the previous-year needles. Compared with the SNOW treatment, carbohydrate concentrations were lower in the FLOOD and NO SNOW treatments where the seedlings had almost died before the end of the experiment, presumably due to frost desiccation of aboveground parts during the winter treatments. The seedlings of the ICE treatment showed dead needles and stems only above the snow and ice cover. The results emphasize the importance of an insulating and protecting snow cover for small forest tree seedlings, and that future winters with changed snow patterns might affect the survival of tree seedlings and thus forest productivity.

  15. A probabilistic model for snow avalanche occurrence

    Science.gov (United States)

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

    2009-04-01

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

  16. Texture operator for snow particle classification into snowflake and graupel

    Science.gov (United States)

    Nurzyńska, Karolina; Kubo, Mamoru; Muramoto, Ken-ichiro

    2012-11-01

    In order to improve the estimation of precipitation, the coefficients of Z-R relation should be determined for each snow type. Therefore, it is necessary to identify the type of falling snow. Consequently, this research addresses a problem of snow particle classification into snowflake and graupel in an automatic manner (as these types are the most common in the study region). Having correctly classified precipitation events, it is believed that it will be possible to estimate the related parameters accurately. The automatic classification system presented here describes the images with texture operators. Some of them are well-known from the literature: first order features, co-occurrence matrix, grey-tone difference matrix, run length matrix, and local binary pattern, but also a novel approach to design simple local statistic operators is introduced. In this work the following texture operators are defined: mean histogram, min-max histogram, and mean-variance histogram. Moreover, building a feature vector, which is based on the structure created in many from mentioned algorithms is also suggested. For classification, the k-nearest neighbourhood classifier was applied. The results showed that it is possible to achieve correct classification accuracy above 80% by most of the techniques. The best result of 86.06%, was achieved for operator built from a structure achieved in the middle stage of the co-occurrence matrix calculation. Next, it was noticed that describing an image with two texture operators does not improve the classification results considerably. In the best case the correct classification efficiency was 87.89% for a pair of texture operators created from local binary pattern and structure build in a middle stage of grey-tone difference matrix calculation. This also suggests that the information gathered by each texture operator is redundant. Therefore, the principal component analysis was applied in order to remove the unnecessary information and

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  19. Dorsolateral Prefrontal Contributions to Human Intelligence

    Science.gov (United States)

    Barbey, Aron K.; Colom, Roberto; Grafman, Jordan

    2012-01-01

    Although cognitive neuroscience has made remarkable progress in understanding the involvement of the prefrontal cortex in executive control functions for human intelligence, the necessity of the dorsolateral prefrontal cortex (dlPFC) for key competencies of general intelligence and executive function remains to be well established. Here we studied human brain lesion patients with dlPFC lesions to investigate whether this region is computationally necessary for performance on neuropsychological tests of general intelligence and executive function, administering the Wechsler Adult Intelligence Scale (WAIS) and subtests of the Delis Kaplan Executive Function System (D-KEFS) to three groups: dlPFC lesions (n = 19), non-dlPFC lesions (n = 152), and no brain lesions (n = 55). The key results indicate that: (1) patients with focal dlPFC damage exhibit lower scores, at the latent variable level, than controls in general intelligence (g) and executive function; (2) dlPFC patients demonstrate lower scores than controls in several executive measures; and (3) these latter differences are no longer significant when the pervasive influence of the general factor of intelligence (g) is statistically removed. The observed findings support a central role for the dlPFC in general intelligence and make specific recommendations for the interpretation and application of the WAIS and D-KEFS to the study of high-level cognition in health and disease. PMID:22634247

  20. Using multi-source satellite data to assess snow-cover change in Qinghai-Tibetan Plateau in last decade

    Science.gov (United States)

    Jiang, Y.; Chen, F.; Gao, Y.; Barlage, M. J.

    2017-12-01

    Snow cover in Qinghai-Tibetan Plateau (QTP) is a critical component of water cycle and affects regional climate of East Asia. Satellite data from three different sources (i.e., FY3A/B/C, MODIS and IMS) were used to analyze the QTP fractional-snow-cover (FSC) change and associated uncertainties in the last decade. To reduce the high percentage of cloud in FY3A/B/C and MODIS, a four-step cloud removal procedure was applied and effectively reduced the cloud percentage from 40.8-56.1% to 2.2­-­3.3%. The averaged error introduced by the cloud removal procedure was about 2% estimated by a random sampling method. Results show that the snow cover in QTP significantly decreased in recent 5 years. Three data sets (FY3B, MODIS and IMS) showed significant decreased annual FSC at all elevation bands from 2012-2016, and a significant shorter snow season with delayed snow onset and earlier melting. Both IMS and MODIS had a slightly decline annual FSC from 2000 to 3000 m, while MODIS FSC slightly decreased in 2002-2016 and IMS FSC slightly increased from 2006-2016 in the region with elevation higher than 3000 m. Results also show significant uncertainties among the five data sets (FY3A/B/C, MODIS, IMS), although they showed similar fluctuations of daily FSC. IMS had largest snow-cover extent and highest daily FSC due to its multi data sources. FY3A/C and MODIS (observed in the morning) had around 5% higher mean FSC than FY3B (observed in the afternoon) due to the 3 hours detection time gap. The relative error of daily FSC (taking MODIS as `truth') between FY3A/B/C, IMS and MODIS is 23%, -35%, 8% and 63%, respectively, averaged in five elevation bands in 2015-2017.

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

    Directory of Open Access Journals (Sweden)

    L. Dai

    2017-08-01

    Full Text Available 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

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

    Science.gov (United States)

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

    2017-12-01

    With moderate to high spatial resolution (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 SWE estimates that are independent of real or near real

  3. Global warming: Sea ice and snow cover

    International Nuclear Information System (INIS)

    Walsh, J.E.

    1993-01-01

    In spite of differences among global climate simulations under scenarios where atmospheric CO 2 is doubled, all models indicate at least some amplification of greenouse warming at the polar regions. Several decades of recent data on air temperature, sea ice, and snow cover of the high latitudes of the Northern Hemisphere are summarized to illustrate the general compatibility of recent variations in those parameters. Despite a data void over the Arctic Ocean, some noteworthy patterns emerge. Warming dominates in winter and spring, as projected by global climate models, with the warming strongest over subpolar land areas of Alaska, northwestern Canada, and northern Eurasia. A time-longitude summary of Arctic sea ice variations indicates that timescales of most anomalies range from several months to several years. Wintertime maxima of total sea ice extent contain no apparent secular trends. The statistical significance of trends in recent sea ice variations was evaluated by a Monte Carlo procedure, showing a statistically significant negative trend in the summer. Snow cover data over the 20-y period of record show a noticeable decrease of Arctic snow cover in the late 1980s. This is of potential climatic significance since the accompanying decrease of surface albedo leads to a rapid increase of solar heating. 21 refs., 3 figs., 1 tab

  4. Effects of dirty snow in nuclear winter simulations

    International Nuclear Information System (INIS)

    Vogelmann, A.M.; Robock, A.; Ellingson, R.G.

    1988-01-01

    A large-scale nuclear war would inject smoke into the atmosphere from burning forests, cities, and industries in targeted areas. This smoke could fall out onto snow and ice and would lower cryospheric albedos by as much as 50%. A global energy balance climate model is used to investigate the maximum effect these ''dirty snow'' albedos have on the surface temperature in nuclear winter simulations which span several years. These effects are investigated for different nuclear winter scenarios, snow precipitation rates, latitudinal distributions of smoke, and seasonal timings. We find that dirty snow, in general, would have a small temperature effect at mid- and low latitudes but could have a large temperature effect at polar latitudes, particularly if the soot is able to reappear significantly in later summers. Factors which limit the climatic importance of the dirty snow are (1) the dirty snow albedo is lowest when the atmosphere still contains a large amount of light-absorbing smoke; (2) even with dirty snow, sea ice areas can still increase, which helps maintain colder temperatures through the sea ice thermal inertial feedback; (3) the snow and ice areas affected by the dirty snow albedos are largest when there is little seasonal solar insolation; and (4) the area affected by the dirty snow is relatively small under all circumstances. copyright American Geophysical Union 1988

  5. Snow cover distribution over elevation zones in a mountainous catchment

    Science.gov (United States)

    Panagoulia, D.; Panagopoulos, Y.

    2009-04-01

    A good understanding of the elevetional distribution of snow cover is necessary to predict the timing and volume of runoff. In a complex mountainous terrain the snow cover distribution within a watershed is highly variable in time and space and is dependent on elevation, slope, aspect, vegetation type, surface roughness, radiation load, and energy exchange at the snow-air interface. Decreases in snowpack due to climate change could disrupt the downstream urban and agricultural water supplies, while increases could lead to seasonal flooding. Solar and longwave radiation are dominant energy inputs driving the ablation process. Turbulent energy exchange at the snow cover surface is important during the snow season. The evaporation of blowing and drifting snow is strongly dependent upon wind speed. Much of the spatial heterogeneity of snow cover is the result of snow redistribution by wind. Elevation is important in determining temperature and precipitation gradients along hillslopes, while the temperature gradients determine where precipitation falls as rain and snow and contribute to variable melt rates within the hillslope. Under these premises, the snow accumulation and ablation (SAA) model of the US National Weather Service (US NWS) was applied to implement the snow cover extent over elevation zones of a mountainous catchment (the Mesochora catchment in Western-Central Greece), taking also into account the indirectly included processes of sublimation, interception, and snow redistribution. The catchment hydrology is controlled by snowfall and snowmelt and the simulated discharge was computed from the soil moisture accounting (SMA) model of the US NWS and compared to the measured discharge. The elevationally distributed snow cover extent presented different patterns with different time of maximization, extinction and return during the year, producing different timing of discharge that is a crucial factor for the control and management of water resources systems.

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

    Science.gov (United States)

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

    2016-04-01

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

  7. Monitoring Areal Snow Cover Using NASA Satellite Imagery

    Science.gov (United States)

    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

  8. Age-Related Decline in Spelling Ability: A Link with Fluid Intelligence?

    Science.gov (United States)

    Stuart-Hamilton, Ian; Rabbitt, Patrick

    1997-01-01

    On spelling tests taken by 159 adults over 50, younger subjects had significantly higher scores. Statistically removing effects of crystallized intelligence and education had no effect, but removing effects of fluid intelligence made the difference insignificant. Although spelling is considered a crystallized skill, in older people it may rely…

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

    Science.gov (United States)

    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...

  10. Educational Programs for Intelligence Professionals.

    Science.gov (United States)

    Miller, Jerry P.

    1994-01-01

    Discusses the need for education programs for competitive intelligence professionals. Highlights include definitions of intelligence functions, focusing on business intelligence; information utilization by decision makers; information sources; competencies for intelligence professionals; and the development of formal education programs. (38…

  11. A New Dimension of Business Intelligence: Location-based Intelligence

    OpenAIRE

    Zeljko Panian

    2012-01-01

    Through the course of this paper we define Locationbased Intelligence (LBI) which is outgrowing from process of amalgamation of geolocation and Business Intelligence. Amalgamating geolocation with traditional Business Intelligence (BI) results in a new dimension of BI named Location-based Intelligence. LBI is defined as leveraging unified location information for business intelligence. Collectively, enterprises can transform location data into business intelligence applic...

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2015-11-01

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

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    Thomas, W.H.; Duval, B.

    1995-01-01

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

  16. Intelligent Extruder

    Energy Technology Data Exchange (ETDEWEB)

    AlperEker; Mark Giammattia; Paul Houpt; Aditya Kumar; Oscar Montero; Minesh Shah; Norberto Silvi; Timothy Cribbs

    2003-04-24

    ''Intelligent Extruder'' described in this report is a software system and associated support services for monitoring and control of compounding extruders to improve material quality, reduce waste and energy use, with minimal addition of new sensors or changes to the factory floor system components. Emphasis is on process improvements to the mixing, melting and de-volatilization of base resins, fillers, pigments, fire retardants and other additives in the :finishing'' stage of high value added engineering polymer materials. While GE Plastics materials were used for experimental studies throughout the program, the concepts and principles are broadly applicable to other manufacturers materials. The project involved a joint collaboration among GE Global Research, GE Industrial Systems and Coperion Werner & Pleiderer, USA, a major manufacturer of compounding equipment. Scope of the program included development of a algorithms for monitoring process material viscosity without rheological sensors or generating waste streams, a novel detection scheme for rapid detection of process upsets and an adaptive feedback control system to compensate for process upsets where at line adjustments are feasible. Software algorithms were implemented and tested on a laboratory scale extruder (50 lb/hr) at GE Global Research and data from a production scale system (2000 lb/hr) at GE Plastics was used to validate the monitoring and detection software. Although not evaluated experimentally, a new concept for extruder process monitoring through estimation of high frequency drive torque without strain gauges is developed and demonstrated in simulation. A plan to commercialize the software system is outlined, but commercialization has not been completed.

  17. Intelligent Mission Controller Node

    National Research Council Canada - National Science Library

    Perme, David

    2002-01-01

    The goal of the Intelligent Mission Controller Node (IMCN) project was to improve the process of translating mission taskings between real-world Command, Control, Communications, Computers, and Intelligence (C41...

  18. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Verhaegh, W.F.J.; Aarts, E.H.L.; Korst, J.H.M.

    2004-01-01

    In this chapter, we discuss the new paradigm for user-centered computing known as ambient intelligence and its relation with methods and techniques from the field of computational intelligence, including problem solving, machine learning, and expert systems.

  19. Advanced intelligent systems

    CERN Document Server

    Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

    2014-01-01

    Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

  20. Validation of MODIS snow cover images over Austria

    Directory of Open Access Journals (Sweden)

    J. Parajka

    2006-01-01

    Full Text Available This study evaluates the Moderate Resolution Imaging Spectroradiometer (MODIS snow cover product over the territory of Austria. The aims are (a to analyse the spatial and temporal variability of the MODIS snow product classes, (b to examine the accuracy of the MODIS snow product against in situ snow depth data, and (c to identify the main factors that may influence the MODIS classification accuracy. We use daily MODIS grid maps (version 4 and daily snow depth measurements at 754 climate stations in the period from February 2000 to December 2005. The results indicate that, on average, clouds obscured 63% of Austria, which may significantly restrict the applicability of the MODIS snow cover images to hydrological modelling. On cloud-free days, however, the classification accuracy is very good with an average of 95%. There is no consistent relationship between the classification errors and dominant land cover type and local topographical variability but there are clear seasonal patterns to the errors. In December and January the errors are around 15% while in summer they are less than 1%. This seasonal pattern is related to the overall percentage of snow cover in Austria, although in spring, when there is a well developed snow pack, errors tend to be smaller than they are in early winter for the same overall percent snow cover. Overestimation and underestimation errors balance during most of the year which indicates little bias. In November and December, however, there appears to exist a tendency for overestimation. Part of the errors may be related to the temporal shift between the in situ snow depth measurements (07:00 a.m. and the MODIS acquisition time (early afternoon. The comparison of daily air temperature maps with MODIS snow cover images indicates that almost all MODIS overestimation errors are caused by the misclassification of cirrus clouds as snow.

  1. Small scale variability of snow density on Antarctic sea ice

    Science.gov (United States)

    Wever, N.; Leonard, K. C.; Paul, S.; Jacobi, H. W.; Proksch, M.; Lehning, M.

    2016-12-01

    Snow on sea ice plays an important role in air-ice-sea interactions. For example, snow may smooth the ice surface when snow drift is occurring, while at the same time it may also generate roughness elements by interactions with the wind. Snow density is a key property in many processes, for example by influencing the thermal conductivity of the snow layer, radiative transfer inside the snow as well as the effects of aerodynamic forcing on the snowpack. We present data from an in-situ measurement campaign in the Weddell Sea during two subsequent cruises of RV Polarstern. By comparing snow density from snow pits and snow micro penetrometer (SMP) measurements, augmented by terrestrial laser scanning (TLS) on an area of 50x50 m2, highly resolved density profiles and surface topology were acquired at a horizontal resolution of approximately 30 cm. Average snow densities are about 280 kg/m3, but the analysis also reveals a high spatial variability in snow density on sea ice in both horizontal and vertical direction, ranging from roughly 170 to 360 kg/m3. This variability is expressed by coherent snow structures over several meters, which disappear over larger distances. A comparison with TLS data indicates that the spatial variability is related to deviations in surface topology. This suggests a strong influence from surface processes, for example wind, on the temporal development of density profiles. The fundamental relationship between density variations, surface roughness and changes therein as investigated in this study are interpreted with respect to larger-scale ice-movement and the ice mass balance.

  2. Artificial Intelligence Project

    Science.gov (United States)

    1990-01-01

    Symposium on Aritificial Intelligence and Software Engineering Working Notes, March 1989. Blumenthal, Brad, "An Architecture for Automating...Artificial Intelligence Project Final Technical Report ARO Contract: DAAG29-84-K-OGO Artificial Intelligence LaboratO"ry The University of Texas at...Austin N>.. ~ ~ JA 1/I 1991 n~~~ Austin, Texas 78712 ________k A,.tificial Intelligence Project i Final Technical Report ARO Contract: DAAG29-84-K-0060

  3. Snow hydrology in Mediterranean mountain regions: A review

    Science.gov (United States)

    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

  4. Snow reliability in ski resorts considering artificial snowmaking

    Science.gov (United States)

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

    2009-04-01

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

  5. Effect of snow cover on soil frost penetration

    Science.gov (United States)

    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.

  6. Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths

    Science.gov (United States)

    Kang, Do Hyuk; Barros, Ana P.; Kim, Edward J.

    2016-01-01

    This study investigates the sensitivity of multispectral reflectivity to changing snow correlation lengths. Matzler's ice-lamellae radiative transfer model was implemented and tested to evaluate the reflectivity of snow correlation lengths at multiple frequencies from the ultraviolet (UV) to the microwave bands. The model reveals that, in the UV to infrared (IR) frequency range, the reflectivity and correlation length are inversely related, whereas reflectivity increases with snow correlation length in the microwave frequency range. The model further shows that the reflectivity behavior can be mainly attributed to scattering rather than absorption for shallow snowpacks. The largest scattering coefficients and reflectivity occur at very small correlation lengths (approximately 10(exp -5 m) for frequencies higher than the IR band. In the microwave range, the largest scattering coefficients are found at millimeter wavelengths. For validation purposes, the ice-lamella model is coupled with a multilayer snow physics model to characterize the reflectivity response of realistic snow hydrological processes. The evolution of the coupled model simulated reflectivities in both the visible and the microwave bands is consistent with satellite-based reflectivity observations in the same frequencies. The model results are also compared with colocated in situ snow correlation length measurements (Cold Land Processes Field Experiment 2002-2003). The analysis and evaluation of model results indicate that the coupled multifrequency radiative transfer and snow hydrology modeling system can be used as a forward operator in a data-assimilation framework to predict the status of snow physical properties, including snow correlation length.

  7. Scales of snow depth variability in high elevation rangeland sagebrush

    Science.gov (United States)

    Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

    2017-09-01

    In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

  8. Research of Snow-Melt Process on a Heated Platform

    Directory of Open Access Journals (Sweden)

    Vasilyev Gregory P.

    2016-01-01

    Full Text Available The article has shown the results of experimental researches of the snow-melt on a heated platform-near building heat-pump snow-melt platform. The near-building (yard heat pump platforms for snow melt with the area up to 10-15 m2 are a basis of the new ideology of organization of the street cleaning of Moscow from snow in the winter period which supposes the creation in the megalopolis of the «distributed snow-melt system» (DSMS using non-traditional energy sources. The results of natural experimental researches are presented for the estimation of efficiency of application in the climatic conditions of Moscow of heat pumps in the snow-melt systems. The researches were conducted on a model sample of the near-building heat-pump platform which uses the low-potential thermal energy of atmospheric air. The conducted researches have confirmed experimentally in the natural conditions the possibility and efficiency of using of atmospheric air as a source of low-potential thermal energy for evaporation of the snow-melt heat pump systems in the climatic conditions of Moscow. The results of laboratory researches of snow-melt process on a heated horizontal platform are presented. The researches have revealed a considerable dependence of efficiency of the snow-melt process on its piling mode (form-building and the organization of the process of its piling mode (form-building and the organization of the process of its (snow mass heat exchange with the surface of the heated platform. In the process of researches the effect of formation of an «ice dome» under the melting snow mass called by the fact that in case of the thickness of snow loaded on the platform more than 10 cm the water formed from the melting snow while the contact with the heating surface don’t spread on it, but soaks into the snow, wets it due to capillary effect and freezes. The formation of «ice dome» leads to a sharp increase of snow-melt period and decreases the operating

  9. Orchestrating Multiple Intelligences

    Science.gov (United States)

    Moran, Seana; Kornhaber, Mindy; Gardner, Howard

    2006-01-01

    Education policymakers often go astray when they attempt to integrate multiple intelligences theory into schools, according to the originator of the theory, Howard Gardner, and his colleagues. The greatest potential of a multiple intelligences approach to education grows from the concept of a profile of intelligences. Each learner's intelligence…

  10. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Weber, W.; Rabaey, J.M.; Aarts, E.

    2005-01-01

    We briefly review the concept of ambient intelligence and discuss its relation with the domain of intelligent algorithms. By means of four examples of ambient intelligent systems, we argue that new computing methods and quantification measures are needed to bridge the gap between the class of

  11. Designing with computational intelligence

    CERN Document Server

    Lopes, Heitor; Mourelle, Luiza

    2017-01-01

    This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also presents a concise and efficient synthesis of different systems using computationally intelligent techniques.

  12. Reflection on robotic intelligence

    NARCIS (Netherlands)

    Bartneck, C.

    2006-01-01

    This paper reflects on the development or robots, both their physical shape as well as their intelligence. The later strongly depends on the progress made in the artificial intelligence (AI) community which does not yet provide the models and tools necessary to create intelligent robots. It is time

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

    Science.gov (United States)

    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

  14. Silvering substrates after CO2 snow cleaning

    Science.gov (United States)

    Zito, Richard R.

    2005-09-01

    There have been some questions in the astronomical community concerning the quality of silver coatings deposited on substrates that have been cleaned with carbon dioxide snow. These questions center around the possible existence of carbonate ions left behind on the substrate by CO2. Such carbonate ions could react with deposited silver to produce insoluble silver carbonate, thereby reducing film adhesion and reflectivity. Carbonate ions could be produced from CO2 via the following mechanism. First, during CO2 snow cleaning, a small amount of moisture can condense on a surface. This is especially true if the jet of CO2 is allowed to dwell on one spot. CO2 gas can dissolve in this moisture, producing carbonic acid, which can undergo two acid dissociations to form carbonate ions. In reality, it is highly unlikely that charged carbonate ions will remain stable on a substrate for very long. As condensed water evaporates, Le Chatelier's principle will shift the equilibrium of the chain of reactions that produced carbonate back to CO2 gas. Furthermore, the hydration of CO2 reaction of CO2 with H20) is an extremely slow process, and the total dehydrogenation of carbonic acid is not favored. Living tissues that must carry out the equilibration of carbonic acid and CO2 use the enzyme carbonic anhydrase to speed up the reaction by a factor of one million. But no such enzymatic action is present on a clean mirror substrate. In short, the worst case analysis presented below shows that the ratio of silver atoms to carbonate radicals must be at least 500 million to one. The results of chemical tests presented here support this view. Furthermore, film lift-off tests, also presented in this report, show that silver film adhesion to fused silica substrates is actually enhanced by CO2 snow cleaning.

  15. Modeling the isotopic composition of Antarctic snow using backward trajectories: simulation of snow pit records

    NARCIS (Netherlands)

    Helsen, M.M.; van de Wal, R.S.W.; van den Broeke, M.R.; Masson-Delmotte, V.; Meijer, H.A.J.; Scheele, M.P.; Werner, M.

    2006-01-01

    The quantitative interpretation of isotope records (d18O, dD, and d excess) in ice cores can benefit from a comparison of observed meteorology with associated isotope variability. For this reason we studied four isotope records from snow pits in western Dronning Maud Land (DML), Antarctica, covering

  16. Take control of upgrading to Snow Leopard

    CERN Document Server

    Kissell, Joe

    2009-01-01

    Installing a major new version of Mac OS X should be exciting and fun, but without proper guidance you may find it nerve-wracking or even risk losing valuable files. Fortunately, many thousands of people have upgraded Mac OS X calmly and successfully with Joe Kissell's previous best-selling Take Control of Upgrading... titles. Joe's friendly, expert steps-developed over innumerable test installations-help you to avoid trouble, understand what's going on when you install Snow Leopard, and easily recover from problem

  17. SAR Tomography for Terrestrial Snow Stratigraphy

    Science.gov (United States)

    Lei, Y.; Xu, X.; Baldi, C.; Bleser, J. W. D.; Yueh, S. H.; Elder, K.

    2017-12-01

    Traditional microwave observation of snowpack includes brightness temperature and backscatter. The single baseline configuration and loss of phase information hinders the retrieval of snow stratigraphy information from microwave observations. In this paper, we are investigating the tomography of polarimetric SAR to measure snow stratigraphy. In the past two years, we have developed a homodyne frequency modulated continuous wave radar (FMCW), operation at three earth exploration satellite bands within the X-band and Ku-band spectrums (centered at 9.6 GHz, 13.5 GHz, and 17.2 GHz) at Jet Propulsion Laboratory. The transceiver is mounted to a dual-axis planar scanner (60cm in each direction), which translates the antenna beams across the target area creating a tomographic baseline in two directions. Dual-antenna architecture was implemented to improve the isolation between the transmitter and receiver. This technique offers a 50 dB improvement in signal-to-noise ratio versus conventional single-antenna FMCW radar systems. With current setting, we could have around 30cm vertical resolution. The system was deployed on a ground based tower at the Fraser Experimental Forest (FEF) Headquarters, near Fraser, CO, USA (39.847°N, 105.912°W) from February 1 to April 30, 2017 and run continuously with some gaps for required optional supports. FEF is a 93-km2 research watershed in the heart of the central Rocky Mountains approximately 80-km West of Denver. During the campaign, in situ measurements of snow depth and other snowpack properties were performed every week for comparison with the remotely sensed data. A network of soil moisture sensors, time-lapse cameras, acoustic depth sensors, laser depth sensor and meteorological instruments was installed next to the site to collect in situ measurements of snow, weather, and soil conditions. Preliminary tomographic processing of ground based SAR data of snowpack at X- and Ku- band has revealed the presence of multiple layers within

  18. Translating Chicana Rap: Snow Tha Product

    Directory of Open Access Journals (Sweden)

    Adriana Onita

    2017-06-01

    Full Text Available This project examines rap lyrics, interviews, and music videos by Chicana artist Snow Tha Product to show how rap has been culturally translated, performed, and appropriated by females in order to “flip the script,” or subvert the dichotomous model of female sexuality that has been imposed upon them. Weaving insights from three academic fields (cultural translation, Chican@ studies, and hip-hop feminism, this paper also aims to creatively expand the definition of translation by positioning rap music as a performative language in its own right, capable of encoding and translating complex cultural issues related to race, gender, and sexuality.

  19. Introducing artificial intelligence into structural optimization programs

    International Nuclear Information System (INIS)

    Jozwiak, S.F.

    1987-01-01

    Artificial Intelligence /AI/ is defined as the branch of the computer science concerned with the study of the ideas that enable computers to be intelligent. The main purpose of the application of AI in engineering is to develop computer programs which function better as tools for engineers and designers. Many computer programs today have properties which make them inconvenient to their final users and the research carried within the field of AI provides tools and techniques so that these restriction can be removed. The continuous progress in computer technology has lead to developing efficient computer systems which can be applied to more than simple solving sets of equations. (orig.)

  20. Snow loads in a changing climate: new risks?

    Directory of Open Access Journals (Sweden)

    U. Strasser

    2008-01-01

    Full Text Available In January/February 2006, heavy snowfalls in Bavaria (Germany lead to a series of infrastructural damage of catastrophic nature. Since on many collapsed roofs the total snow load was not exceptional, serious engineering deficiencies in roof construction and a sudden rise in the total snow load were considered to be the trigger of the events. An analysis of the then meteorological conditions reveals, that the early winter of 2005/2006 was characterised by an exceptional continuous snow cover, temperatures remained around the freezing point and no significant snowmelt was evident. The frequent freezing/thawing cycles were followed by a general compaction of the snow load. This resulted in a re-distribution and a new concentration of the snow load on specific locations on roofs. With respect to climate change, the question arises as to whether the risks relating to snow loads will increase. The future probability of a continuous snow cover occurrence with frequent freezing/thawing cycles will probably decline due to predicted higher temperatures. However, where temperatures remain low, an increase in winter precipitation will result in increased snow loads. Furthermore, the variability of extremes is predicted to increase. If heavy snowfall events are more frequent, the risk of a trigger event will likely increase. Finally, an attempt will be made here in this paper to outline a concept for an operational warning system for the Bavarian region. This system envisages to predict the development and risk of critical snow loads for a 3-day time period, utilising a combination of climate and snow modelling data and using this together with a snow pillow device (located on roofs and the results of which.

  1. Airborne Surveys of Snow Depth over Arctic Sea Ice

    Science.gov (United States)

    Kwok, R.; Panzer, B.; Leuschen, C.; Pang, S.; Markus, T.; Holt, B.; Gogineni, S.

    2011-01-01

    During the spring of 2009, an ultrawideband microwave radar was deployed as part of Operation IceBridge to provide the first cross-basin surveys of snow thickness over Arctic sea ice. In this paper, we analyze data from three approx 2000 km transects to examine detection issues, the limitations of the current instrument, and the regional variability of the retrieved snow depth. Snow depth is the vertical distance between the air \\snow and snow-ice interfaces detected in the radar echograms. Under ideal conditions, the per echogram uncertainty in snow depth retrieval is approx 4 - 5 cm. The finite range resolution of the radar (approx 5 cm) and the relative amplitude of backscatter from the two interfaces limit the direct retrieval of snow depths much below approx 8 cm. Well-defined interfaces are observed over only relatively smooth surfaces within the radar footprint of approx 6.5 m. Sampling is thus restricted to undeformed, level ice. In early April, mean snow depths are 28.5 +/- 16.6 cm and 41.0 +/- 22.2 cm over first-year and multiyear sea ice (MYI), respectively. Regionally, snow thickness is thinner and quite uniform over the large expanse of seasonal ice in the Beaufort Sea, and gets progressively thicker toward the MYI cover north of Ellesmere Island, Greenland, and the Fram Strait. Snow depth over MYI is comparable to that reported in the climatology by Warren et al. Ongoing improvements to the radar system and the utility of these snow depth measurements are discussed.

  2. Impact of climate change in Switzerland on socioeconomic snow indices

    Science.gov (United States)

    Schmucki, Edgar; Marty, Christoph; Fierz, Charles; Weingartner, Rolf; Lehning, Michael

    2017-02-01

    Snow is a key element for many socioeconomic activities in mountainous regions. Due to the sensitivity of the snow cover to variations of temperature and precipitation, major changes caused by climate change are expected to happen. We analyze the evolution of some key snow indices under future climatic conditions. Ten downscaled and postprocessed climate scenarios from the ENSEMBLES database have been used to feed the physics-based snow model SNOWPACK. The projected snow cover has been calculated for 11 stations representing the diverse climates found in Switzerland. For the first time, such a setup is used to reveal changes in frequently applied snow indices and their implications on various socioeconomic sectors. Toward the end of the twenty-first century, a continuous snow cover is likely only guaranteed at high elevations above 2000 m a.s.l., whereas at mid elevations (1000-1700 m a.s.l.), roughly 50 % of all winters might be characterized by an ephemeral snow cover. Low elevations (below 500 m a.s.l.) are projected to experience only 2 days with snowfall per year and show the strongest relative reductions in mean winter snow depth of around 90 %. The range of the mean relative reductions of the snow indices is dominated by uncertainties from different GCM-RCM projections and amounts to approximately 30 %. Despite these uncertainties, all snow indices show a clear decrease in all scenario periods and the relative reductions increase toward lower elevations. These strong reductions can serve as a basis for policy makers in the fields of tourism, ecology, and hydropower.

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

    Science.gov (United States)

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

    2016-10-01

    A long-term study of adult non-biting midges (Chironomidae) active in winter on the snow in mountain areas and lowlands in Poland yielded 35 species. The lowland and mountain communities differed significantly in their specific composition. The mountain assemblage was found to be more diverse and abundant, with a substantial contribution from the subfamily Diamesinae, whereas Orthocladiinae predominated in the lowlands. Orthocladius wetterensis Brundin was the most characteristic and superdominant species in the winter-active chironomid communities in both areas. Only a few specimens and species of snow-active chironomids were recorded in late autumn and early winter. The abundance of chironomids peaked in late February in the mountain and lowland areas with an additional peak in the mountain areas in early April. However, this second peak of activity consisted mainly of Orthocladiinae, as Diamesinae emerged earliest in the season. Most snow-active species emerged in mid- and late winter, but their seasonal patterns differed between the 2 regions as a result of the different species composition and the duration of snow cover in these regions. Spearman's rank correlation coefficient tests yielded positive results between each season and the number of chironomid individuals recorded in the mountain area. A positive correlation between air temperature, rising to +3.5 °C, and the number of specimens recorded on the snow in the mountain community was statistically significant. The winter emergence and mate-searching strategies of chironomids are discussed in the light of global warming, and a brief compilation of most important published data on the phenomena studied is provided. © 2015 Institute of Zoology, Chinese Academy of Sciences.

  4. Social intelligence, human intelligence and niche construction.

    Science.gov (United States)

    Sterelny, Kim

    2007-04-29

    This paper is about the evolution of hominin intelligence. I agree with defenders of the social intelligence hypothesis in thinking that externalist models of hominin intelligence are not plausible: such models cannot explain the unique cognition and cooperation explosion in our lineage, for changes in the external environment (e.g. increasing environmental unpredictability) affect many lineages. Both the social intelligence hypothesis and the social intelligence-ecological complexity hybrid I outline here are niche construction models. Hominin evolution is hominin response to selective environments that earlier hominins have made. In contrast to social intelligence models, I argue that hominins have both created and responded to a unique foraging mode; a mode that is both social in itself and which has further effects on hominin social environments. In contrast to some social intelligence models, on this view, hominin encounters with their ecological environments continue to have profound selective effects. However, though the ecological environment selects, it does not select on its own. Accidents and their consequences, differential success and failure, result from the combination of the ecological environment an agent faces and the social features that enhance some opportunities and suppress others and that exacerbate some dangers and lessen others. Individuals do not face the ecological filters on their environment alone, but with others, and with the technology, information and misinformation that their social world provides.

  5. Early results from NASA's SnowEx campaign

    Science.gov (United States)

    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

  6. The Modification of Orographic Snow Growth Processes by Cloud Nucleating Aerosols

    Science.gov (United States)

    Cotton, W. R.; Saleeby, S.

    2011-12-01

    synoptic flow simply provides the background dynamics and moisture that impinge upon the steep terrain. The addition of cloud nucleating aerosols to this scenario tends to reduce the amount of riming and leads to greater snow vapor growth. Increased vapor growth leads to larger snow crystals but does not necessarily increase their density or fall speed. There is frequently a zone on the periphery of the orographic cloud where water saturation is low and ice saturation remains high. Here the Bergeron process allows for snow to continue growing at the expense of the cloud water. Furthermore, since less cloud water is removed by riming, and droplets are smaller in polluted conditions, there is an increase in cloud water evaporation along the lee slope. This enhanced droplet evaporation in polluted conditions allows for more saturated air to persist to the lee of the ridge. Higher saturation reduces the amount of snow crystal sublimation prior to surface deposition. In very moist winter events, the lee slope evaporation relative to the primary mountain barrier can saturate the air relative to a downstream ridge and aid in further orographic cloud development. The combination of reduced riming, the Bergeron process, and reduced lee-side sublimation leads to the snowfall spillover effect under polluted conditions.

  7. Dynamic-stochastic modeling of snow cover formation on the European territory of Russia

    OpenAIRE

    A. N. Gelfan; V. M. Moreido

    2014-01-01

    A dynamic-stochastic model, which combines a deterministic model of snow cover formation with a stochastic weather generator, has been developed. The deterministic snow model describes temporal change of the snow depth, content of ice and liquid water, snow density, snowmelt, sublimation, re-freezing of melt water, and snow metamorphism. The model has been calibrated and validated against the long-term data of snow measurements over the territory of the European Russia. The model showed good ...

  8. Personality assessment in snow leopards (Uncia uncia).

    Science.gov (United States)

    Gartner, Marieke Cassia; Powell, David

    2012-01-01

    Knowledge of individual personality is a useful tool in animal husbandry and can be used effectively to improve welfare. This study assessed personality in snow leopards (Uncia uncia) by examining their reactions to six novel objects and comparing them to personality assessments based on a survey completed by zookeepers. The objectives were to determine whether these methods could detect differences in personality, including age and sex differences, and to assess whether the two methods yielded comparable results. Both keeper assessments and novel object tests identified age, sex, and individual differences in snow leopards. Five dimensions of personality were found based on keepers' ratings: Active/Vigilant, Curious/Playful, Calm/Self-Assured, Timid/Anxious, and Friendly to Humans. The dimension Active/Vigilant was significantly positively correlated with the number of visits to the object, time spent locomoting, and time spent in exploratory behaviors. Curious/Playful was significantly positively correlated with the number of visits to the object, time spent locomoting, and time spent in exploratory behaviors. However, other dimensions (Calm/Self-Assured, Friendly to Humans, and Timid/Anxious) did not correlate with novel-object test variables and possible explanations for this are discussed. Thus, some of the traits and behaviors were correlated between assessment methods, showing the novel-object test to be useful in assessing an animal's personality should a keeper be unable to, or to support a keeper's assessment. © 2011 Wiley Periodicals, Inc.

  9. The Snow Data System at NASA JPL

    Science.gov (United States)

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

    2014-12-01

    NASA JPL's Snow Data System has a data-processing pipeline powered by Apache OODT, an open source software tool. The pipeline has been running for several years and has successfully generated a significant amount of cryosphere data, including MODIS-based products such as MODSCAG, MODDRFS and MODICE, with historical and near-real time windows and covering regions such as the Artic, Western US, Alaska, Central Europe, Asia, South America, Australia and New Zealand. The team continues to improve the pipeline, using monitoring tools such as Ganglia to give an overview of operations, and improving fault-tolerance with automated recovery scripts. Several alternative adaptations of the Snow Covered Area and Grain size (SCAG) algorithm are being investigated. These include using VIIRS and Landsat TM/ETM+ satellite data as inputs. Parallel computing techniques are being considered for core SCAG processing, such as using the PyCUDA Python API to utilize multi-core GPU architectures. An experimental version of MODSCAG is also being developed for the Google Earth Engine platform, a cloud-based service.

  10. Kinetic Friction of Sport Fabrics on Snow

    Directory of Open Access Journals (Sweden)

    Werner Nachbauer

    2016-03-01

    Full Text Available After falls, skiers or snowboarders often slide on the slope and may collide with obstacles. Thus, the skier’s friction on snow is an important factor to reduce incidence and severity of impact injuries. The purpose of this study was to measure snow friction of different fabrics of ski garments with respect to roughness, speed, and contact pressure. Three types of fabrics were investigated: a commercially available ski overall, a smooth downhill racing suit, and a dimpled downhill racing suit. Friction was measured for fabrics taped on a short ski using a linear tribometer. The fabrics’ roughness was determined by focus variation microscopy. Friction coefficients were between 0.19 and 0.48. Roughness, friction coefficient, and friction force were highest for the dimpled race suit. The friction force of the fabrics was higher for the higher contact pressure than for the lower one at all speeds. It was concluded that the main friction mechanism for the fabrics was dry friction. Only the fabric with the roughest surface showed friction coefficients, which were high enough to sufficiently decelerate a sliding skier on beginner and intermediate slopes.

  11. [An overview of snow-boarding injuries].

    Science.gov (United States)

    Biasca, N; Battaglia, H; Simmen, H P; Disler, P; Trentz, O

    1995-01-01

    Snowboarding is increasing dramatically in popularity in Switzerland as well as other countries. Work aimed at improving the design of the boards and of the boots and bindings has also increased rapidly during recent years. Most injured snowboarders are fit young men and boys who describe themselves as beginners and have had a minimal amount of instruction at an officially approved training centre. Appropriate snowboard training has mostly been quite inadequate, and protective devices (e.g. waterproofed support gloves). The anatomical distribution and the types of injuries sustained in snowboarding differ from those in alpine skiing. The wrist (and forearm) and the ankle are the most frequent locations of injuries (23%) as against the knee and thumb in alpine skiing. Sprains and strains were the most frequent types of injuries (46%), followed by fractures (28%) and contusions (13.5%). The snowboard injury rate was higher than in alpine skiing (1.7-8/1000 snowboard days versus 2-4/1000 ski days). Falling forward on the slope was the major mechanism of injury (80%), and torsion the next most frequent (20%). Snowboarding injuries were sustained most often on ice and hardpacked snow, compared with soft powder snow for alpine skiing injuries. Appropriate preseason conditioning, snowboarding lessons from a certified instructor, appropriate selection of rigorously tested equipment and use of protective devices are the main steps that must be taken to prevent injuries.

  12. Energy and dissipated work in snow avalanches

    Science.gov (United States)

    Bartelt, P.; Buser, O.

    2004-12-01

    Using the results of large scale avalanche experiments at the Swiss Vallée de la Sionne test site, the energy balance of several snow avalanches is determined. Avalanches convert approximately one-seventh of their potential energy into kinetic energy. The total potential energy depends strongly on the entrained snowcover, indicating that entrainment processes cannot be ignored when predicting terminal velocities and runout distances. We find energy dissipation rates on the order of 1 GW. Fluidization of the fracture slab can be identified in the experiments as an increase in dissipation rate, thereby explaining the initial and rapid acceleration of avalanches after release. Interestingly, the dissipation rates appear to be constant along the track, although large fluctuations in internal velocity exist. Thus, we can demonstrate within the context of non-equilibrium thermodynamics that -- in space -- granular snow avalanches are irreversible, dissipative systems that minimize entropy production because they appear to reach a steady-state non-equilibrium. A thermodynamic analysis reveals that fluctuations in velocity depend on the roughness of the flow surface and viscosity of the granular system. We speculate that this property explains the transition from flowing avalanches to powder avalanches.

  13. Quality control of intelligence research

    International Nuclear Information System (INIS)

    Lu Yan; Xin Pingping; Wu Jian

    2014-01-01

    Quality control of intelligence research is the core issue of intelligence management, is a problem in study of information science This paper focuses on the performance of intelligence to explain the significance of intelligence research quality control. In summing up the results of the study on the basis of the analysis, discusses quality control methods in intelligence research, introduces the experience of foreign intelligence research quality control, proposes some recommendations to improve quality control in intelligence research. (authors)

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

    Science.gov (United States)

    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

  15. Seasonal snow accumulation in the mid-latitude forested catchment

    Czech Academy of Sciences Publication Activity Database

    Šípek, Václav; Tesař, Miroslav

    2014-01-01

    Roč. 69, č. 11 (2014), s. 1562-1569 ISSN 0006-3088 R&D Projects: GA TA ČR TA02021451 Institutional support: RVO:67985874 Keywords : snow depth * snow water equivalent * forested catchment Subject RIV: DA - Hydrology ; Limnology Impact factor: 0.827, year: 2014

  16. Prevent Snow from Blocking your Tailpipe PSA (:30)

    Centers for Disease Control (CDC) Podcasts

    2014-12-11

    If it's snowing, make sure your vehicle’s tailpipe is clear of snow before starting the engine to prevent carbon monoxide poisoning.  Created: 12/11/2014 by National Center for Environmental Health (NCEH).   Date Released: 12/11/2014.

  17. Student Leadership Development within Student Government at Snow College

    Science.gov (United States)

    Wilson, Gordon Ned

    2010-01-01

    The purpose of this study was to describe the leadership development process of former student leaders at Snow College. More specifically, the study focused on understanding how, when, and where leadership development took place in their "lived experience" within the student government at Snow College (Van Manen, 1998). Examining the lived…

  18. DISCOVERY OF A TRANSITING PLANET NEAR THE SNOW-LINE

    DEFF Research Database (Denmark)

    Kipping, D. M.; Torres, G.; Buchhave, L. A.

    2014-01-01

    In most theories of planet formation, the snow-line represents a boundary between the emergence of the interior rocky planets and the exterior ice giants. The wide separation of the snow-line makes the discovery of transiting worlds challenging, yet transits would allow for detailed subsequent...

  19. Consistent seasonal snow cover depth and duration variability over ...

    Indian Academy of Sciences (India)

    Decline in consistent seasonal snow cover depth, duration and changing snow cover build- up pattern over the WH in recent decades indicate that WH has undergone considerable climate change and winter weather patterns are changing in the WH. 1. Introduction. Mountainous regions around the globe are storehouses.

  20. Modeling Snow Regime in Cores of Small Planetary Bodies

    Science.gov (United States)

    Boukaré, C. E.; Ricard, Y. R.; Parmentier, E.; Parman, S. W.

    2017-12-01

    Observations of present day magnetic field on small planetary bodies such as Ganymede or Mercury challenge our understanding of planetary dynamo. Several mechanisms have been proposed to explain the origin of magnetic fields. Among the proposed scenarios, one family of models relies on snow regime. Snow regime is supported by experimental studies showing that melting curves can first intersect adiabats in regions where the solidifying phase is not gravitationaly stable. First solids should thus remelt during their ascent or descent. The effect of the snow zone on magnetic field generation remains an open question. Could magnetic field be generated in the snow zone? If not, what is the depth extent of the snow zone? How remelting in the snow zone drive compositional convection in the liquid layer? Several authors have tackled this question with 1D-spherical models. Zhang and Schubert, 2012 model sinking of the dense phase as internally heated convection. However, to our knowledge, there is no study on the convection structure associated with sedimentation and phase change at planetary scale. We extend the numerical model developped in [Boukare et al., 2017] to model snow dynamics in 2D Cartesian geometry. We build a general approach for modeling double diffusive convection coupled with solid-liquid phase change and phase separation. We identify several aspects that may govern the convection structure of the solidifying system: viscosity contrast between the snow zone and the liquid layer, crystal size, rate of melting/solidification and partitioning of light components during phase change.

  1. A comparison of Normalised Difference Snow Index (NDSI) and ...

    African Journals Online (AJOL)

    As an alternative, thematic cover–types based on remotely sensed data-sets are becoming popular. In this study we hypothesise that the reduced dimensionality using Principal Components Analysis (PCA) in concert Normalized Difference Snow Index (NDSI) is valuable for improving the accuracy of snow cover maps.

  2. Spectral characterization of soil and coal contamination on snow

    Indian Academy of Sciences (India)

    Snow is a highly reflecting object found naturally on the Earth and its albedo is highly influenced by the amount and type of contamination. In the present study, two major types of contaminants (soil and coal) have been used to understand their effects on snow reflectance in the Himalayan region. These contaminants were ...

  3. Snow Leopard: Ecology and Conservation Issues in India

    Indian Academy of Sciences (India)

    Owing to their secretive nature and inaccessible habitat,little is known about its ecology and distribution. Due toits endangered status and high aesthetic value, the snow leopardis considered as an 'umbrella species' for wildlife conservationin the Indian Himalayas. This article summarizes thecurrent knowledge on snow ...

  4. Spleen removal

    Science.gov (United States)

    ... spleen. Sickle cell anemia . Splenic artery aneurysm (rare). Trauma to the spleen. Risks Risks for anesthesia and surgery in general ... removal - series References Brandow AM, Camitta BM. Hyposplenism, splenic trauma, and splenectomy. In: Kliegman RM, Stanton BF, St. ...

  5. High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

    Science.gov (United States)

    Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

    2017-12-01

    Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential

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

    Directory of Open Access Journals (Sweden)

    H. C. Steen-Larsen

    2014-02-01

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

  7. Variability in snow depth time series in the Adige catchment

    Directory of Open Access Journals (Sweden)

    Giorgia Marcolini

    2017-10-01

    New hydrological insights for the region: Stations located above and below 1650 m a.s.l. show different dynamics, with the latter experiencing in the last decades a larger reduction of average snow depth and snow cover duration, than the former. Wavelet analyses show that snow dynamics change with elevation and correlate differently with climatic indices at multiple temporal scales. We also observe that starting from the late 1980s snow cover duration and mean seasonal snow depth are below the average in the study area. We also identify an elevation dependent correlation with the temperature. Moreover, correlation with the Mediterranean Oscillation Index and with the North Atlantic Oscillation Index is identified.

  8. On the impact of snow cover on daytime pollution dispersion

    Science.gov (United States)

    Segal, M.; Garratt, J. R.; Pielke, R. A.; Hildebrand, P.; Rogers, F. A.; Cramer, J.; Schanot, A.

    A preliminary evaluation of the impact of snow cover on daytime pollutant dispersion conditions is made by using conceptual, scaling, and observational analyses. For uniform snow cover and synoptically unperturbed sunny conditions, observations indicate a considerate suppression of the surface sensible heat flux, the turbulence, and the development of the daytime atmospheric boundary layer (ABL) when compared to snow-free conditions. However, under conditions of non-uniform snow cover, as in urban areas, or associated with vegetated areas or bare ground patches, a milder effect on pollutant dispersion conditions would be expected. Observed concentrations of atmospheric particles within the ABL, and surface pollutant concentrations in urban areas, reflect the impact of snow cover on the modification of ABL characteristics.

  9. Snow cover and temperature relationships in North America and Eurasia

    Science.gov (United States)

    Foster, J.; Owe, M.; Rango, A.

    1983-01-01

    In this study the snow cover extent during the autumn months in both North America and Eurasia has been related to the ensuing winter temperature as measured at several locations near the center of each continent. The relationship between autumn snow cover and the ensuing winter temperatures was found to be much better for Eurasia than for North America. For Eurasia the average snow cover extent during the autumn explained as much as 52 percent of the variance in the winter (December-February) temperatures compared to only 12 percent for North America. However, when the average winter snow cover was correlated with the average winter temperature it was found that the relationship was better for North America than for Eurasia. As much as 46 percent of the variance in the winter temperature was explained by the winter snow cover in North America compared to only 12 percent in Eurasia.

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

    Science.gov (United States)

    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

  11. Resilience to Changing Snow Depth in a Shrubland Ecosystem.

    Science.gov (United States)

    Loik, M. E.

    2008-12-01

    Snowfall is the dominant hydrologic input for high elevations and latitudes of the arid- and semi-arid western United States. Sierra Nevada snowpack provides numerous important services for California, but is vulnerable to anthropogenic forcing of the coupled ocean-atmosphere system. GCM and RCM scenarios envision reduced snowpack and earlier melt under a warmer climate, but how will these changes affect soil and plant water relations and ecosystem processes? And, how resilient will this ecosystem be to short- and long-term forcing of snow depth and melt timing? To address these questions, our experiments utilize large- scale, long-term roadside snow fences to manipulate snow depth and melt timing in eastern California, USA. Interannual snow depth averages 1344 mm with a CV of 48% (April 1, 1928-2008). Snow fences altered snow melt timing by up to 18 days in high-snowfall years, and affected short-term soil moisture pulses less in low- than medium- or high-snowfall years. Sublimation in this arid location accounted for about 2 mol m- 2 of water loss from the snowpack in 2005. Plant water potential increased after the ENSO winter of 2005 and stayed relatively constant for the following three years, even after the low snowfall of winter 2007. Over the long-term, changes in snow depth and melt timing have impacted cover or biomass of Achnatherum thurberianum, Elymus elemoides, and Purshia tridentata. Growth of adult conifers (Pinus jeffreyi and Pi. contorta) was not equally sensitive to snow depth. Thus, complex interactions between snow depth, soil water inputs, physiological processes, and population patterns help drive the resilience of this ecosystem to changes in snow depth and melt timing.

  12. SWEAT: Snow Water Equivalent with AlTimetry

    Science.gov (United States)

    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.

  13. Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes

    Science.gov (United States)

    Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.

    2014-12-01

    Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.

  14. Assessing the controls of the snow energy balance and water available for runoff in a rain-an-snow environment

    Science.gov (United States)

    Adam B. Mazurkiewicz; David G. Callery; Jeffrey J. McDonnell

    2008-01-01

    Rain-on-snow (ROS) melt production and its contribution to water available for runoff is poorly understood. In the Pacific Northwest (PNW) of the USA, ROS drives many runoff events with turbulent energy exchanges dominating the snow energy balance (EB). While previous experimental work in the PNW (most notably the H.J. Andrews Experimental Forest (HJA» has quantified...

  15. Brain Intelligence: Go Beyond Artificial Intelligence

    OpenAIRE

    Lu, Huimin; Li, Yujie; Chen, Min; Kim, Hyoungseop; Serikawa, Seiichi

    2017-01-01

    Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication ...

  16. Application of machine/statistical learning, artificial intelligence and statistical experimental design for the modeling and optimization of methylene blue and Cd(ii) removal from a binary aqueous solution by natural walnut carbon.

    Science.gov (United States)

    Mazaheri, H; Ghaedi, M; Ahmadi Azqhandi, M H; Asfaram, A

    2017-05-10

    Analytical chemists apply statistical methods for both the validation and prediction of proposed models. Methods are required that are adequate for finding the typical features of a dataset, such as nonlinearities and interactions. Boosted regression trees (BRTs), as an ensemble technique, are fundamentally different to other conventional techniques, with the aim to fit a single parsimonious model. In this work, BRT, artificial neural network (ANN) and response surface methodology (RSM) models have been used for the optimization and/or modeling of the stirring time (min), pH, adsorbent mass (mg) and concentrations of MB and Cd 2+ ions (mg L -1 ) in order to develop respective predictive equations for simulation of the efficiency of MB and Cd 2+ adsorption based on the experimental data set. Activated carbon, as an adsorbent, was synthesized from walnut wood waste which is abundant, non-toxic, cheap and locally available. This adsorbent was characterized using different techniques such as FT-IR, BET, SEM, point of zero charge (pH pzc ) and also the determination of oxygen containing functional groups. The influence of various parameters (i.e. pH, stirring time, adsorbent mass and concentrations of MB and Cd 2+ ions) on the percentage removal was calculated by investigation of sensitive function, variable importance rankings (BRT) and analysis of variance (RSM). Furthermore, a central composite design (CCD) combined with a desirability function approach (DFA) as a global optimization technique was used for the simultaneous optimization of the effective parameters. The applicability of the BRT, ANN and RSM models for the description of experimental data was examined using four statistical criteria (absolute average deviation (AAD), mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R 2 )). All three models demonstrated good predictions in this study. The BRT model was more precise compared to the other models and this showed

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  19. Parameterizations for narrowband and broadband albedo of pure snow and snow containing mineral dust and black carbon

    Science.gov (United States)

    Dang, Cheng; Brandt, Richard E.; Warren, Stephen G.

    2015-06-01

    The reduction of snow spectral albedo by black carbon (BC) and mineral dust, both alone and in combination, is computed using radiative transfer modeling. Broadband albedo is shown for mass fractions covering the full range from pure snow to pure BC and pure dust, and for snow grain radii from 5 µm to 2500 µm, to cover the range of possible grain sizes on planetary surfaces. Parameterizations are developed for opaque homogeneous snowpacks for three broad bands used in general circulation models and several narrower bands. They are functions of snow grain radius and the mass fraction of BC and/or dust and are valid up to BC content of 10 ppm, needed for highly polluted snow. A change of solar zenith angle can be mimicked by changing grain radius. A given mass fraction of BC causes greater albedo reduction in coarse-grained snow; BC and grain radius can be combined into a single variable to compute the reduction of albedo relative to pure snow. The albedo reduction by BC is less if the snow contains dust, a common situation on mountain glaciers and in agricultural and grazing lands. Measured absorption spectra of mineral dust are critically reviewed as a basis for specifying dust properties for modeling. The effect of dust on snow albedo at visible wavelengths can be represented by an "equivalent BC" amount, scaled down by a factor of about 200. Dust has little effect on the near-IR albedo because the near-IR albedo of pure dust is similar to that of pure snow.

  20. Data Fusion of Gridded Snow Products Enhanced with Terrain Covariates and a Simple Snow Model

    Science.gov (United States)

    Snauffer, A. M.; Hsieh, W. W.; Cannon, A. J.

    2017-12-01

    Hydrologic planning requires accurate estimates of regional snow water equivalent (SWE), particularly areas with hydrologic regimes dominated by spring melt. While numerous gridded data products provide such estimates, accurate representations are particularly challenging under conditions of mountainous terrain, heavy forest cover and large snow accumulations, contexts which in many ways define the province of British Columbia (BC), Canada. One promising avenue of improving SWE estimates is a data fusion approach which combines field observations with gridded SWE products and relevant covariates. A base artificial neural network (ANN) was constructed using three of the best performing gridded SWE products over BC (ERA-Interim/Land, MERRA and GLDAS-2) and simple location and time covariates. This base ANN was then enhanced to include terrain covariates (slope, aspect and Terrain Roughness Index, TRI) as well as a simple 1-layer energy balance snow model driven by gridded bias-corrected ANUSPLIN temperature and precipitation values. The ANN enhanced with all aforementioned covariates performed better than the base ANN, but most of the skill improvement was attributable to the snow model with very little contribution from the terrain covariates. The enhanced ANN improved station mean absolute error (MAE) by an average of 53% relative to the composing gridded products over the province. Interannual peak SWE correlation coefficient was found to be 0.78, an improvement of 0.05 to 0.18 over the composing products. This nonlinear approach outperformed a comparable multiple linear regression (MLR) model by 22% in MAE and 0.04 in interannual correlation. The enhanced ANN has also been shown to estimate better than the Variable Infiltration Capacity (VIC) hydrologic model calibrated and run for four BC watersheds, improving MAE by 22% and correlation by 0.05. The performance improvements of the enhanced ANN are statistically significant at the 5% level across the province and

  1. Rainwater propagation through snowpack during rain-on-snow sprinkling experiments under different snow conditions

    Directory of Open Access Journals (Sweden)

    R. Juras

    2017-09-01

    Full Text Available The mechanisms of rainwater propagation and runoff generation during rain-on-snow (ROS events are still insufficiently known. Understanding storage and transport of liquid water in natural snowpacks is crucial, especially for forecasting of natural hazards such as floods and wet snow avalanches. In this study, propagation of rainwater through snow was investigated by sprinkling experiments with deuterium-enriched water and applying an alternative hydrograph separation technique on samples collected from the snowpack runoff. This allowed us to quantify the contribution of rainwater, snowmelt and initial liquid water released from the snowpack. Four field experiments were carried out during winter 2015 in the vicinity of Davos, Switzerland. Blocks of natural snow were isolated from the surrounding snowpack to inhibit lateral exchange of water and were exposed to artificial rainfall using deuterium-enriched water. The experiments were composed of four 30 min periods of sprinkling, separated by three 30 min breaks. The snowpack runoff was continuously gauged and sampled periodically for the deuterium signature. At the onset of each experiment antecedent liquid water was first pushed out by the sprinkling water. Hydrographs showed four pronounced peaks corresponding to the four sprinkling bursts. The contribution of rainwater to snowpack runoff consistently increased over the course of the experiment but never exceeded 86 %. An experiment conducted on a non-ripe snowpack suggested the development of preferential flow paths that allowed rainwater to efficiently propagate through the snowpack limiting the time for mass exchange processes to take effect. In contrast, experiments conducted on ripe isothermal snowpack showed a slower response behaviour and resulted in a total runoff volume which consisted of less than 50 % of the rain input.

  2. Aerial view of CERN under the snow

    CERN Multimedia

    CERN PhotoLab

    1963-01-01

    In this photograph taken in the winter of 1963, CERN still looks quite bare under its mantle of snow. The Proton Synchrotron (PS), resembling a bicycle wheel in shape, had been in operation since the summer of 1959. A proposal had just been made for the site of CERN's second large project, the Intersecting Storage Rings (ISR): France was to house the world's first proton-proton collider. In September 1965, the French authorities signed an agreement making more than 40 hectares of land available for the extension of the CERN site established in Switzerland into French territory. The ISR project received final approval from the CERN Council in December 1965. The civil engineering work on the French part began in November 196

  3. Frost seen on Snow White Trench

    Science.gov (United States)

    2008-01-01

    The Surface Stereo Imager (SSI) on NASA's Phoenix Mars Lander took this shadow-enhanced false color image of the 'Snow White' trench, on the eastern end of Phoenix's digging area. The image was taken on Sol 144, or the 144th day of the mission, Oct. 20, 2008. Temperatures measured on Sol 151, the last day weather data were received, showed overnight lows of minus128 Fahrenheit (minus 89 Celsius) and day time highs in the minus 50 F (minus 46 C) range. The last communication from the spacecraft came on Nov. 2, 2008. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver.

  4. Brightness temperature simulation of snow cover based on snow grain size evolution using in situ data

    Science.gov (United States)

    Wu, Lili; Li, Xiaofeng; Zhao, Kai; Zheng, Xingming; Jiang, Tao

    2016-07-01

    Snow depth parameter inversion from passive microwave remote sensing is of great significance to hydrological process and climate systems. The Helsinki University of Technology (HUT) model is a commonly used snow emission model. Snow grain size (SGS) is one of the important input parameters, but SGS is difficult to obtain in broad areas. The time series of SGS are first evolved by an SGS evolution model (Jordan 91) using in situ data. A good linear relationship between the effective SGS in HUT and the evolution SGS was found. Then brightness temperature simulations are performed based on the effective SGS and evolution SGS. The results showed that the biases of the simulated brightness temperatures based on the effective SGS and evolution SGS were -6.5 and -3.6 K, respectively, for 18.7 GHz and -4.2 and -4.0 K for 36.5 GHz. Furthermore, the model is performed in six pixels with different land use/cover type in other areas. The results showed that the simulated brightness temperatures based on the evolution SGS were consistent with those from the satellite. Consequently, evolution SGS appears to be a simple method to obtain an appropriate SGS for the HUT model.

  5. Quo Vadis, Artificial Intelligence?

    OpenAIRE

    Berrar, Daniel; Sato, Naoyuki; Schuster, Alfons

    2010-01-01

    Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervou...

  6. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

  7. Intelligence of programs

    Energy Technology Data Exchange (ETDEWEB)

    Novak, D

    1982-01-01

    A general discussion about the level of artificial intelligence in computer programs is presented. The suitability of various languages for the development of complex, intelligent programs is discussed, considering fourth-generation language as well as the well established structured COBOL language. It is concluded that the success of automation in many administrative fields depends to a large extent on the development of intelligent programs.

  8. Hair Removal

    DEFF Research Database (Denmark)

    Hædersdal, Merete

    2011-01-01

    Hair removal with optical devices has become a popular mainstream treatment that today is considered the most efficient method for the reduction of unwanted hair. Photothermal destruction of hair follicles constitutes the fundamental concept of hair removal with red and near-infrared wavelengths...... suitable for targeting follicular and hair shaft melanin: normal mode ruby laser (694 nm), normal mode alexandrite laser (755 nm), pulsed diode lasers (800, 810 nm), long-pulse Nd:YAG laser (1,064 nm), and intense pulsed light (IPL) sources (590-1,200 nm). The ideal patient has thick dark terminal hair......, white skin, and a normal hormonal status. Currently, no method of lifelong permanent hair eradication is available, and it is important that patients have realistic expectations. Substantial evidence has been found for short-term hair removal efficacy of up to 6 months after treatment with the available...

  9. Hair removal

    DEFF Research Database (Denmark)

    Haedersdal, Merete; Haak, Christina S

    2011-01-01

    Hair removal with optical devices has become a popular mainstream treatment that today is considered the most efficient method for the reduction of unwanted hair. Photothermal destruction of hair follicles constitutes the fundamental concept of hair removal with red and near-infrared wavelengths...... suitable for targeting follicular and hair shaft melanin: normal mode ruby laser (694 nm), normal mode alexandrite laser (755 nm), pulsed diode lasers (800, 810 nm), long-pulse Nd:YAG laser (1,064 nm), and intense pulsed light (IPL) sources (590-1,200 nm). The ideal patient has thick dark terminal hair......, white skin, and a normal hormonal status. Currently, no method of lifelong permanent hair eradication is available, and it is important that patients have realistic expectations. Substantial evidence has been found for short-term hair removal efficacy of up to 6 months after treatment with the available...

  10. Intelligence analysis – the royal discipline of Competitive Intelligence

    OpenAIRE

    František Bartes

    2011-01-01

    The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in busines...

  11. Machine listening intelligence

    Science.gov (United States)

    Cella, C. E.

    2017-05-01

    This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.

  12. STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

    Science.gov (United States)

    ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

  13. Intelligent Optics Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Intelligent Optics Laboratory supports sophisticated investigations on adaptive and nonlinear optics; advancedimaging and image processing; ground-to-ground and...

  14. Intelligence and childlessness.

    Science.gov (United States)

    Kanazawa, Satoshi

    2014-11-01

    Demographers debate why people have children in advanced industrial societies where children are net economic costs. From an evolutionary perspective, however, the important question is why some individuals choose not to have children. Recent theoretical developments in evolutionary psychology suggest that more intelligent individuals may be more likely to prefer to remain childless than less intelligent individuals. Analyses of the National Child Development Study show that more intelligent men and women express preference to remain childless early in their reproductive careers, but only more intelligent women (not more intelligent men) are more likely to remain childless by the end of their reproductive careers. Controlling for education and earnings does not at all attenuate the association between childhood general intelligence and lifetime childlessness among women. One-standard-deviation increase in childhood general intelligence (15 IQ points) decreases women's odds of parenthood by 21-25%. Because women have a greater impact on the average intelligence of future generations, the dysgenic fertility among women is predicted to lead to a decline in the average intelligence of the population in advanced industrial nations. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. Identifying oil/marine snow associations in mesocosm simulations of the Deepwater Horizon oil spill event using solid-state 13C NMR spectroscopy.

    Science.gov (United States)

    Hatcher, Patrick G; Obeid, Wassim; Wozniak, Andrew S; Xu, Chen; Zhang, Saijin; Santschi, Peter H; Quigg, Antonietta

    2018-01-01

    The Deepwater Horizon oil spill stimulated the release of marine snow made up of dead/living plankton/bacteria and their exopolymeric polysaccharide substances (EPS), termed marine oil snow (MOS), promoting rapid removal of oil from the water column into sediments near the well site. Mesocosm simulations showed that Macondo surrogate oil readily associates with the marine snow. Quantitative solid-state 13 C NMR readily distinguishes this oil from naturally formed marine snow and reveals that adding the dispersant Corexit enhances the amount of oil associated with the MOS, thus contributing to rapid removal from the water column. Solvent extraction of MOS removes the oil-derived compounds for analysis by one and two-dimensional GC/MS and evaluation of potential transformations they undergo when associated with the EPS. The results reveal that the oil associated with EPS is subjected to rapid transformation, in a matter of days, presumably by bacteria and fungi associated with EPS. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Routledge companion to intelligence studies

    CERN Document Server

    Dover, Robert; Hillebrand, Claudia

    2013-01-01

    The Routledge Companion to Intelligence Studies provides a broad overview of the growing field of intelligence studies. The recent growth of interest in intelligence and security studies has led to an increased demand for popular depictions of intelligence and reference works to explain the architecture and underpinnings of intelligence activity. Divided into five comprehensive sections, this Companion provides a strong survey of the cutting-edge research in the field of intelligence studies: Part I: The evolution of intelligence studies; Part II: Abstract approaches to intelligence; Part III: Historical approaches to intelligence; Part IV: Systems of intelligence; Part V: Contemporary challenges. With a broad focus on the origins, practices and nature of intelligence, the book not only addresses classical issues, but also examines topics of recent interest in security studies. The overarching aim is to reveal the rich tapestry of intelligence studies in both a sophisticated and accessible way. This Companion...

  17. UAS applications in high alpine, snow-covered terrain

    Science.gov (United States)

    Bühler, Y.; Stoffel, A.; Ginzler, C.

    2017-12-01

    Access to snow-covered, alpine terrain is often difficult and dangerous. Hence parameters such as snow depth or snow avalanche release and deposition zones are hard to map in situ with adequate spatial and temporal resolution and with spatial continuous coverage. These parameters are currently operationally measured at automated weather stations and by observer networks. However such isolated point measurements are not able to capture the information spatial continuous and to describe the high spatial variability present in complex mountain topography. Unmanned Aerial Systems (UAS) have the potential to fill this gap by frequently covering selected high alpine areas with high spatial resolution down to ground resolutions of even few millimeters. At the WSL Institute for Snow and Avalanche Research SLF we test different photogrammetric UAS with visual and near infrared bands. During the last three years we were able to gather experience in more than 100 flight missions in extreme terrain. By processing the imagery applying state-of-the-art structure from motion (SfM) software, we were able to accurately document several avalanche events and to photogrammetrically map snow depth with accuracies from 1 to 20 cm (dependent on the flight height above ground) compare to manual snow probe measurements. This was even possible on homogenous snow surfaces with very little texture. A key issue in alpine terrain is flight planning. We need to cover regions at high elevations with large altitude differences (up to 1 km) with high wind speeds (up to 20 m/s) and cold temperatures (down to - 25°C). Only a few UAS are able to cope with these environmental conditions. We will give an overview on our applications of UAS in high alpine terrain that demonstrate the big potential of such systems to acquire frequent, accurate and high spatial resolution geodata in high alpine, snow covered terrain that could be essential to answer longstanding questions in avalanche and snow hydrology

  18. Use of machine learning techniques for modeling of snow depth

    Directory of Open Access Journals (Sweden)

    G. V. Ayzel

    2017-01-01

    Full Text Available Snow exerts significant regulating effect on the land hydrological cycle since it controls intensity of heat and water exchange between the soil-vegetative cover and the atmosphere. Estimating of a spring flood runoff or a rain-flood on mountainous rivers requires understanding of the snow cover dynamics on a watershed. In our work, solving a problem of the snow cover depth modeling is based on both available databases of hydro-meteorological observations and easily accessible scientific software that allows complete reproduction of investigation results and further development of this theme by scientific community. In this research we used the daily observational data on the snow cover and surface meteorological parameters, obtained at three stations situated in different geographical regions: Col de Porte (France, Sodankyla (Finland, and Snoquamie Pass (USA.Statistical modeling of the snow cover depth is based on a complex of freely distributed the present-day machine learning models: Decision Trees, Adaptive Boosting, Gradient Boosting. It is demonstrated that use of combination of modern machine learning methods with available meteorological data provides the good accuracy of the snow cover modeling. The best results of snow cover depth modeling for every investigated site were obtained by the ensemble method of gradient boosting above decision trees – this model reproduces well both, the periods of snow cover accumulation and its melting. The purposeful character of learning process for models of the gradient boosting type, their ensemble character, and use of combined redundancy of a test sample in learning procedure makes this type of models a good and sustainable research tool. The results obtained can be used for estimating the snow cover characteristics for river basins where hydro-meteorological information is absent or insufficient.

  19. A Particle Batch Smoother Approach to Snow Water Equivalent Estimation

    Science.gov (United States)

    Margulis, Steven A.; Girotto, Manuela; Cortes, Gonzalo; Durand, Michael

    2015-01-01

    This paper presents a newly proposed data assimilation method for historical snow water equivalent SWE estimation using remotely sensed fractional snow-covered area fSCA. The newly proposed approach consists of a particle batch smoother (PBS), which is compared to a previously applied Kalman-based ensemble batch smoother (EnBS) approach. The methods were applied over the 27-yr Landsat 5 record at snow pillow and snow course in situ verification sites in the American River basin in the Sierra Nevada (United States). This basin is more densely vegetated and thus more challenging for SWE estimation than the previous applications of the EnBS. Both data assimilation methods provided significant improvement over the prior (modeling only) estimates, with both able to significantly reduce prior SWE biases. The prior RMSE values at the snow pillow and snow course sites were reduced by 68%-82% and 60%-68%, respectively, when applying the data assimilation methods. This result is encouraging for a basin like the American where the moderate to high forest cover will necessarily obscure more of the snow-covered ground surface than in previously examined, less-vegetated basins. The PBS generally outperformed the EnBS: for snow pillows the PBSRMSE was approx.54%of that seen in the EnBS, while for snow courses the PBSRMSE was approx.79%of the EnBS. Sensitivity tests show relative insensitivity for both the PBS and EnBS results to ensemble size and fSCA measurement error, but a higher sensitivity for the EnBS to the mean prior precipitation input, especially in the case where significant prior biases exist.

  20. PERSPECTIVE: Snow matters in the polar regions

    Science.gov (United States)

    Sodeau, John

    2010-03-01

    Antarctica is not quite as chemically pristine as might sometimes be thought (Jones et al 2008). For example, as elsewhere, reduced sulfur species such as dimethylsulfide (DMS) are emitted from biogenic marine sources at the poles (Read et al 2008). Somewhat less well known is that inland (as opposed to coastal) field campaigns have also detected, within the Antarctic boundary layer (ABL), emissions containing unexpectedly high levels of diverse, oxidizing chemicals such as NOx, nitrate ions, formaldehyde, ozone and hydrogen peroxide (Honrath et al 1999, Hutterli et al 2004, Sumner and Shepson 1999). And then there are the halogen-containing compounds (Simpson et al 2007). The transformation of DMS to sulfate aerosols capable of acting as cloud condensation nuclei often proceeds via one main oxidized product of DMS, namely methanesulfonic acid (MSA). Two specific reactions have been well studied to date in this regard, namely DMS plus either OH or NO3 radicals. Corresponding reactions with halogen radicals, which also contribute to the oxidizing capacity of our atmosphere, have generally been considered to be of less importance. The reason for this view is that even though the reactivity of bromine- and iodine-containing radicals is much greater than that of OH, the halogens were thought to be relatively scarce in the polar atmosphere. However both BrO (and IO) have been detected in the Antarctic CHABLIS campaign, as discussed in depth in the Atmospheric Chemistry and Physics special issue of 2008, see Jones et al (2008). It was subsequently shown that calculated MSA production from the DMS/BrO reaction may be about an order of magnitude greater than when the OH radical was the oxidizing reactant. The recent analytical measurements by Antony et al (2010) of MSA, Br and NO3 found in snow along the Ingrid Christensen Coast of East Antarctica are important in the above field context. Hence it would appear that the concentrations of these ions in ice-cap sites are up

  1. Artificial Consciousness or Artificial Intelligence

    OpenAIRE

    Spanache Florin

    2017-01-01

    Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

  2. 2015 Chinese Intelligent Systems Conference

    CERN Document Server

    Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15

    2016-01-01

    This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

  3. Mac OS X Snow Leopard Server For Dummies

    CERN Document Server

    Rizzo, John

    2009-01-01

    Making Everything Easier!. Mac OS® X Snow Leopard Server for Dummies. Learn to::;. Set up and configure a Mac network with Snow Leopard Server;. Administer, secure, and troubleshoot the network;. Incorporate a Mac subnet into a Windows Active Directory® domain;. Take advantage of Unix® power and security. John Rizzo. Want to set up and administer a network even if you don't have an IT department? Read on!. Like everything Mac, Snow Leopard Server was designed to be easy to set up and use. Still, there are so many options and features that this book will save you heaps of time and effort. It wa

  4. Snow chemistry of high altitude glaciers in the French Alps

    OpenAIRE

    MAUPETIT, FRANÇOIS; DELMAS, ROBERT J.

    2011-01-01

    Snow samples were collected as snowcores in the accumulation zone of four high altitude glaciers (2980–3540 m.a.s.l.) from each of the 4 highest mountain areas of the French Alps, during 3 consecutive years: 1989, 1990 and 1991. Sampling was performed in spring (∼ May), before the onset of late spring–summer percolation. The accumulated snow therefore reflects winter and spring conditions. A complementary sampling of fresh-snow was performed on an event basis, on one of the studied glaciers, ...

  5. Use of urine in snow to indicate condition of wolves

    Science.gov (United States)

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

    1987-01-01

    Urine deposited in snow by wild gray wolves (Canis lupus) and by fed and fasted captive wolves was analyzed for urea nitrogen, calcium, sodium, potassium, and creatinine. Ratios of the elements with creatinine were considerably higher for fed than for fasted animals, and ratios for fed wolves compared favorably with ratios from wolf urine in snow along trails leading from kills. Thus, wolf urine in the snow can indicate whether wolves have fed recently, and a series of such urine collections from any given pack can indicate relative nutritional state.

  6. Dynamics of actual aggregation of petroleum products in snow cover

    Science.gov (United States)

    Begunova, L. A.; Kuznetsova, O. V.; Begunov, D. A.; Kuznetsova, A. N.

    2017-11-01

    The paper presents issues of snow cover pollution by petroleum products. Petroleum products content was determined using the fluorimetric method of analysis. The samples of snow were selected on the territory of Angarsk and Irkutsk cities. According to the obtained data, the content of petroleum products in the analyzed samples exceeds the background value up to 6 times. Analysis of the reference data for similar research confirms need for creation of an environmental monitoring centralized system to monitor atmospheric precipitation and, particularly, snow cover.

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

    Science.gov (United States)

    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.

  8. Blowing snow detection from ground-based ceilometers : Application to East Antarctica

    NARCIS (Netherlands)

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

    2017-01-01

    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

  9. Analysis of the snow-atmosphere energy balance during wet-snow instabilities and implications for avalanche prediction

    Directory of Open Access Journals (Sweden)

    C. Mitterer

    2013-02-01

    Full Text Available Wet-snow avalanches are notoriously difficult to predict; their formation mechanism is poorly understood since in situ measurements representing the thermal and mechanical evolution are difficult to perform. Instead, air temperature is commonly used as a predictor variable for days with high wet-snow avalanche danger – often with limited success. As melt water is a major driver of wet-snow instability and snow melt depends on the energy input into the snow cover, we computed the energy balance for predicting periods with high wet-snow avalanche activity. The energy balance was partly measured and partly modelled for virtual slopes at different elevations for the aspects south and north using the 1-D snow cover model SNOWPACK. We used measured meteorological variables and computed energy balance and its components to compare wet-snow avalanche days to non-avalanche days for four consecutive winter seasons in the surroundings of Davos, Switzerland. Air temperature, the net shortwave radiation and the energy input integrated over 3 or 5 days showed best results in discriminating event from non-event days. Multivariate statistics, however, revealed that for better predicting avalanche days, information on the cold content of the snowpack is necessary. Wet-snow avalanche activity was closely related to periods when large parts of the snowpack reached an isothermal state (0 °C and energy input exceeded a maximum value of 200 kJ m−2 in one day, or the 3-day sum of positive energy input was larger than 1.2 MJ m−2. Prediction accuracy with measured meteorological variables was as good as with computed energy balance parameters, but simulated energy balance variables accounted better for different aspects, slopes and elevations than meteorological data.

  10. Distributed intelligence in CAMAC

    International Nuclear Information System (INIS)

    Kunz, P.F.

    1977-01-01

    The CAMAC digital interface standard has served us well since 1969. During this time there have been enormous advances in digital electronics. In particular, low cost microprocessors now make it feasible to consider use of distributed intelligence even in simple data acquisition systems. This paper describes a simple extension of the CAMAC standard which allows distributed intelligence at the crate level

  11. Intelligent design som videnskab?

    DEFF Research Database (Denmark)

    Klausen, Søren Harnow

    2007-01-01

    Diskuterer hvorvidt intelligent design kan betegnes som videnskab; argumenterer for at dette grundet fraværet af klare demarkationskriterier næppe kan afvises.......Diskuterer hvorvidt intelligent design kan betegnes som videnskab; argumenterer for at dette grundet fraværet af klare demarkationskriterier næppe kan afvises....

  12. Distributed intelligence in CAMAC

    International Nuclear Information System (INIS)

    Kunz, P.F.

    1977-01-01

    A simple extension of the CAMAC standard is described which allows distributed intelligence at the crate level. By distributed intelligence is meant that there is more than one source of control in a system. This standard is just now emerging from the NIM Dataway Working Group and its European counterpart. 1 figure

  13. Intelligence and treaty ratification

    International Nuclear Information System (INIS)

    Cahn, A.H.

    1990-01-01

    This paper reports that there are two sets of questions applicable to the ratification phase: what is the role of intelligence in the ratification process? What effect did intelligence have on that process. The author attempts to answer these and other questions

  14. Applying Multiple Intelligences

    Science.gov (United States)

    Christodoulou, Joanna A.

    2009-01-01

    The ideas of multiple intelligences introduced by Howard Gardner of Harvard University more than 25 years ago have taken form in many ways, both in schools and in other sometimes-surprising settings. The silver anniversary of Gardner's learning theory provides an opportunity to reflect on the ways multiple intelligences theory has taken form and…

  15. Next generation Emotional Intelligence

    Science.gov (United States)

    J. Saveland

    2012-01-01

    Emotional Intelligence has been a hot topic in leadership training since Dan Goleman published his book on the subject in 1995. Emotional intelligence competencies are typically focused on recognition and regulation of emotions in one's self and social situations, yielding four categories: self-awareness, self-management, social awareness and relationship...

  16. Intelligence by consent

    DEFF Research Database (Denmark)

    Diderichsen, Adam; Rønn, Kira Vrist

    2017-01-01

    This article contributes to the current discussions concerning an adequate framework for intelligence ethics. The first part critically scrutinises the use of Just War Theory in intelligence ethics with specific focus on the just cause criterion. We argue that using self-defence as justifying cau...

  17. Intelligence and Physical Attractiveness

    Science.gov (United States)

    Kanazawa, Satoshi

    2011-01-01

    This brief research note aims to estimate the magnitude of the association between general intelligence and physical attractiveness with large nationally representative samples from two nations. In the United Kingdom, attractive children are more intelligent by 12.4 IQ points (r=0.381), whereas in the United States, the correlation between…

  18. Intelligence and treaty ratification

    International Nuclear Information System (INIS)

    Naftzinger, J.E.

    1990-01-01

    This paper describes the atmosphere leading up to the Senate INF hearings and then surveys the broad issues they raised. After that, the author highlights several aspects of the intelligence community's involvement and discusses the specific intelligence-related issues as the Senate committees saw them, notes their impact on the outcome, and finally draws several conclusions and lessons pertinent to the future

  19. Intelligence, Race, and Genetics

    Science.gov (United States)

    Sternberg, Robert J.; Grigorenko, Elena L.; Kidd, Kenneth K.

    2005-01-01

    In this article, the authors argue that the overwhelming portion of the literature on intelligence, race, and genetics is based on folk taxonomies rather than scientific analysis. They suggest that because theorists of intelligence disagree as to what it is, any consideration of its relationships to other constructs must be tentative at best. They…

  20. Multiple Intelligences in Action.

    Science.gov (United States)

    Campbell, Bruce

    1992-01-01

    Describes the investigation of the effects of a four-step model program used with third through fifth grade students to implement Gardener's concepts of seven human intelligences--linguistic, logical/mathematical, visual/spatial, musical, kinesthetic, intrapersonal, and interpersonal intelligence--into daily learning. (BB)

  1. The Reproduction of Intelligence

    Science.gov (United States)

    Meisenberg, Gerhard

    2010-01-01

    Although a negative relationship between fertility and education has been described consistently in most countries of the world, less is known about the relationship between intelligence and reproductive outcomes. Also the paths through which intelligence influences reproductive outcomes are uncertain. The present study uses the NLSY79 to analyze…

  2. Intelligent robot action planning

    Energy Technology Data Exchange (ETDEWEB)

    Vamos, T; Siegler, A

    1982-01-01

    Action planning methods used in intelligent robot control are discussed. Planning is accomplished through environment understanding, environment representation, task understanding and planning, motion analysis and man-machine communication. These fields are analysed in detail. The frames of an intelligent motion planning system are presented. Graphic simulation of the robot's environment and motion is used to support the planning. 14 references.

  3. Computational Intelligence in Intelligent Data Analysis

    CERN Document Server

    Nürnberger, Andreas

    2013-01-01

    Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intell...

  4. Snow noise disturbance in Antarctic radio communications and development of mobile antenna for snow vehicle in Antarctica

    Directory of Open Access Journals (Sweden)

    Isao Fukushima

    1997-07-01

    Full Text Available Radio operators of the Japanese Antarctic Research Expedition (JARE have encountered critical radio noise disturbances caused by blizzards during oversnow travel. This noise appears to be caused by corona discharge at the edges of the vertical whip antenna. This paper describes several examples of snow noise experienced in Antarctica by JARE, the mechanism of generation of the noise, and a method of reducing the intensity of the noise. It also describes a High Effeciency Transmission Line Antenna which is small enough to mount on a snow vehicle and reduces the intensity of the snow noise.

  5. Evaluation and Application of Gridded Snow Water Equivalent Products for Improving Snowmelt Flood Predictions in the Red River Basin of the North

    Science.gov (United States)

    Schroeder, R.; Jacobs, J. M.; Vuyovich, C.; Cho, E.; Tuttle, S. E.

    2017-12-01

    Each spring the Red River basin (RRB) of the North, located between the states of Minnesota and North Dakota and southern Manitoba, is vulnerable to dangerous spring snowmelt floods. Flat terrain, low permeability soils and a lack of satisfactory ground observations of snow pack conditions make accurate predictions of the onset and magnitude of major spring flood events in the RRB very challenging. This study investigated the potential benefit of using gridded snow water equivalent (SWE) products from passive microwave satellite missions and model output simulations to improve snowmelt flood predictions in the RRB using NOAA's operational Community Hydrologic Prediction System (CHPS). Level-3 satellite SWE products from AMSR-E, AMSR2 and SSM/I, as well as SWE computed from Level-2 brightness temperatures (Tb) measurements, including model output simulations of SWE from SNODAS and GlobSnow-2 were chosen to support the snowmelt modeling exercises. SWE observations were aggregated spatially (i.e. to the NOAA North Central River Forecast Center forecast basins) and temporally (i.e. by obtaining daily screened and weekly unscreened maximum SWE composites) to assess the value of daily satellite SWE observations relative to weekly maximums. Data screening methods removed the impacts of snow melt and cloud contamination on SWE and consisted of diurnal SWE differences and a temperature-insensitive polarization difference ratio, respectively. We examined the ability of the satellite and model output simulations to capture peak SWE and investigated temporal accuracies of screened and unscreened satellite and model output SWE. The resulting SWE observations were employed to update the SNOW-17 snow accumulation and ablation model of CHPS to assess the benefit of using temporally and spatially consistent SWE observations for snow melt predictions in two test basins in the RRB.

  6. Intelligence and Prosocial Behavior

    DEFF Research Database (Denmark)

    Han, Ru; Shi, Jiannong; Yong, W.

    2012-01-01

    Results of prev ious studies of the relationship between prosocial behav ior and intelligence hav e been inconsistent. This study attempts to distinguish the dif f erences between sev eral prosocial tasks, and explores the way s in which cognitiv e ability inf luences prosocial behav ior. In Study...... One and Two, we reexamined the relationship between prosocial behav ior and intelligence by employ ing a costly signaling theory with f our games. The results rev ealed that the prosocial lev el of smarter children is higher than that of other children in more complicated tasks but not so in simple...... tasks. In Study Three, we tested the moderation ef f ect of the av erage intelligence across classes, and the results did not show any group intelligence ef f ect on the relationship between intelligence and prosocial behav ior....

  7. Business Intelligence Systems

    Directory of Open Access Journals (Sweden)

    Bogdan NEDELCU

    2014-02-01

    Full Text Available The aim of this article is to show the importance of business intelligence and its growing influence. It also shows when the concept of business intelligence was used for the first time and how it evolved over time. The paper discusses the utility of a business intelligence system in any organization and its contribution to daily activities. Furthermore, we highlight the role and the objectives of business intelligence systems inside an organization and the needs to grow the incomes and reduce the costs, to manage the complexity of the business environment and to cut IT costs so that the organization survives in the current competitive climate. The article contains information about architectural principles of a business intelligence system and how such a system can be achieved.

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

    Science.gov (United States)

    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

  9. Reconstructed North American Snow Extent, 1900-1993

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains reconstructed monthly North American snow extent values for November through March, 1900-1993. Investigators used a combination of satellite...

  10. Some attributes of snow occurrence and snowmelt/sublimation rates ...

    African Journals Online (AJOL)

    2017-04-02

    Apr 2, 2017 ... regions may be strongly influenced by seasonal fluctuations in ... accurate snow mapping and modelling of snowmelt/runoff are ... regional climate and hydrology, earth surface processes, and rural livelihoods .... from clouds.

  11. J-SEx : The Jollie Snow Experiment, New Zealand

    Science.gov (United States)

    Kerr, T.; Singh, S.; Kees, L.; Webster, C.; Clark, M.; Hendrikx, J.; Woods, R.

    2012-04-01

    Intensive snow observations have been collected in a steep alpine catchment (the Jollie Valley) in the Southern Alps of New Zealand for four years at the time of maximum snow storage. The campaign, called the Jollie Snow Experiment (J-SEx), was undertaken to improve understanding of snow variability in a steep alpine landscape. Observation methods included manual depth-probing at hundreds of locations with associated snowpit-digging, and surface and air-borne ground penetrating radar. In addition, repeat (daily) oblique photography was carried out on a subcatchment for two of the years. Analysis of the observations, in conjunction with similar observations from around the world has enabled direction to be given for selecting optimal modelling scales, and an indication of what processes need to be resolved at the different scales. For instance, if models are to operate at sub-100 m horizontal scales, they need to resolve drifting, sloughing and avalanching processes. Binary regression tree methods have been applied to identify terrain variables which explain the observed snow mass variability. This has enabled an assessment of total catchment snow storage to be established for each year. This assessment showed that the controlling variables change from year to year, so that no single terrain-based interpolation method may be generally applied. The change in the terrain relationships each year has been taken as an indication that the different frequencies of snowfall-related climate types from one year to the next affects which terrain characteristics have the greatest impact on snow variability. Assessment of terrain effects at the slope scale indicates that slope angle has the potential to be a strong influence on snow variability in that steep slopes do not build up large accumulations, and that low-angled regions below steep areas become areas of large snow build-up. This "slope" effect is clearly evident from the repeat photography, with the last areas to melt

  12. Operational Bright-Band Snow Level Detection Using Doppler Radar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A method to detect the bright-band snow level from radar reflectivity and Doppler vertical velocity data collection with an atmospheric profiling Doppler radar. The...

  13. Former Soviet Union Hydrological Snow Surveys, 1966-1996

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Former Soviet Union Hydrological Snow Surveys are based on observations made by personnel at 1,345 sites throughout the Former Soviet Union between 1966 and...

  14. Allegheny County Snow Route Centerlines (2017-2018)

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — This dataset shows snow route responsibilities of Allegheny County-owned roads.Category: TransportationOrganization: Allegheny CountyDepartment: Geographic...

  15. Snowfall and Snow Depth for Canada 1943-1982

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Data include monthly snowfall and end-of-month snow depth for 140 stations across Canada. Stations that maintained at least 20 years of data were chosen. The...

  16. Some attributes of snow occurrence and snowmelt/sublimation rates ...

    African Journals Online (AJOL)

    Some attributes of snow occurrence and snowmelt/sublimation rates in the Lesotho ... and trimmed MODIS SNOMAP image using the ArcGIS Spatial Analyst tool. ... and hydrology, earth surface processes, and rural livelihoods in the Lesotho ...

  17. SnowEx17 Cloud Absorption Radiometer BRDF V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains measurements of the bidirectional reflectance distribution function (BRDF) for two locations in Colorado, USA: Grand Mesa, a snow-covered,...

  18. Laboratory study of nitrate photolysis in Antarctic snow

    DEFF Research Database (Denmark)

    Berhanu, Tesfaye A.; Meusinger, Carl; Erbland, Joseph

    2014-01-01

    in Antarctic snow. I. Observed quantum yield, domain of photolysis, and secondary chemistry," J. Chem. Phys. 140, 244305 (2014)]) is to characterize nitrate photochemistry and improve the interpretation of the nitrate ice core record. Naturally occurring stable isotopes in nitrate (15N, 17O, and 18O) provide...... additional information concerning post-depositional processes. Here, we present results from studies of the wavelength-dependent isotope effects from photolysis of nitrate in a matrix of natural snow. Snow from Dome C, Antarctica was irradiated in selected wavelength regions using a Xe UV lamp and filters....... The irradiated snow was sampled and analyzed for nitrate concentration and isotopic composition (δ 15N, δ 18O, and Δ 17O). From these measurements an average photolytic isotopic fractionation of 15ε = (- 15 ± 1.2)‰ was found for broadband Xe lamp photolysis. These results are due in part to excitation...

  19. Analysis of the Lake Superior Watershed Seasonal Snow Cover

    National Research Council Canada - National Science Library

    Daly, Steven F; Baldwin, Timothy B; Weyrick, Patricia

    2007-01-01

    Daily estimates of the snow water equivalent (SWE) distribution for the period from 1 December through 30 April for each winter season from 1979 80 through 2002 03 were calculated for the entire Lake Superior watershed...

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

    Science.gov (United States)

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

    2011-05-01

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

  1. Historical Soviet Daily Snow Depth (HSDSD), Version 2

    Data.gov (United States)

    National Aeronautics and Space Administration — The Historical Soviet Daily Snow Depth (HSDSD) product is based on observations from 284 World Meteorological Organization (WMO) stations throughout Russia and the...

  2. Removing Bureaucracy

    Science.gov (United States)

    2015-08-01

    11 Defense AT&L: July–August 2015 Removing Bureaucracy Katharina G. McFarland McFarland is Assistant Secretary of Defense for Acquisition. I once...involvement from all of the Service warfighting areas came together to scrub the program requirements due to concern over the “ bureaucracy ” and... Bureaucracy ” that focuses on reducing cycle time, staffing time and all forms of inefficiencies. This includes review of those burdens that Congress

  3. Springtime warming and reduced snow cover from carbonaceous particles

    Directory of Open Access Journals (Sweden)

    M. G. Flanner

    2009-04-01

    Full Text Available Boreal spring climate is uniquely susceptible to solar warming mechanisms because it has expansive snow cover and receives relatively strong insolation. Carbonaceous particles can influence snow coverage by warming the atmosphere, reducing surface-incident solar energy (dimming, and reducing snow reflectance after deposition (darkening. We apply a range of models and observations to explore impacts of these processes on springtime climate, drawing several conclusions: 1 Nearly all atmospheric particles (those with visible-band single-scatter albedo less than 0.999, including all mixtures of black carbon (BC and organic matter (OM, increase net solar heating of the atmosphere-snow column. 2 Darkening caused by small concentrations of particles within snow exceeds the loss of absorbed energy from concurrent dimming, thus increasing solar heating of snowpack as well (positive net surface forcing. Over global snow, we estimate 6-fold greater surface forcing from darkening than dimming, caused by BC+OM. 3 Equilibrium climate experiments suggest that fossil fuel and biofuel emissions of BC+OM induce 95% as much springtime snow cover loss over Eurasia as anthropogenic carbon dioxide, a consequence of strong snow-albedo feedback and large BC+OM emissions from Asia. 4 Of 22 climate models contributing to the IPCC Fourth Assessment Report, 21 underpredict the rapid warming (0.64°C decade−1 observed over springtime Eurasia since 1979. Darkening from natural and anthropogenic sources of BC and mineral dust exerts 3-fold greater forcing on springtime snow over Eurasia (3.9 W m−2 than North America (1.2 W m−2. Inclusion of this forcing significantly improves simulated continental warming trends, but does not reconcile the low bias in rate of Eurasian spring snow cover decline exhibited by all models, likely because BC deposition trends are negative or near-neutral over much of Eurasia. Improved Eurasian

  4. Spectral reflectance of solar light from dirty snow: a simple theoretical model and its validation

    OpenAIRE

    A. Kokhanovsky

    2013-01-01

    A simple analytical equation for the snow albedo as the function of snow grain size, soot concentration, and soot mass absorption coefficient is presented. This simple equation can be used in climate models to assess the influence of snow pollution on snow albedo. It is shown that the squared logarithm of the albedo (in the visible) is directly proportional to the soot concentration. A new method of the determination of the soot mass absorption coefficient in snow is proposed. The equations d...

  5. Prediction of Backscatter and Emissivity of Snow at Millimeter Wavelengths.

    Science.gov (United States)

    1980-01-01

    AD-AI16 9A MASSACHUISETTS IMST OF TECH CAMBRIDGE RESEARCH LAB OF-ETC F/6 17/9 PREDICTION OF BACKSCATTER AND EMISSIVITY OF SNOW AT MILLETER --ETC(U...emitting media such as snow. The emissivity in the Ray- leigh- Jeans approximation is then the microwave brightness tempera- ture T divided by an effective...resistivity, and thermal tempera- ture. Jean et al. (Reference 125) compared a theoretical expression for the total apparent temperature of a smooth surface

  6. SWANN: The Snow Water Artificial Neural Network Modelling System

    Science.gov (United States)

    Broxton, P. D.; van Leeuwen, W.; Biederman, J. A.

    2017-12-01

    Snowmelt from mountain forests is important for water supply and ecosystem health. Along Arizona's Mogollon Rim, snowmelt contributes to rivers and streams that provide a significant water supply for hydro-electric power generation, agriculture, and human consumption in central Arizona. In this project, we are building a snow monitoring system for the Salt River Project (SRP), which supplies water and power to millions of customers in the Phoenix metropolitan area. We are using process-based hydrological models and artificial neural networks (ANNs) to generate information about both snow water equivalent (SWE) and snow cover. The snow-cover data is generated with ANNs that are applied to Landsat and MODIS satellite reflectance data. The SWE data is generated using a combination of gridded SWE estimates generated by process-based snow models and ANNs that account for variations in topography, forest cover, and solar radiation. The models are trained and evaluated with snow data from SNOTEL stations as well as from aerial LiDAR and field data that we collected this past winter in northern Arizona, as well as with similar data from other sites in the Southwest US. These snow data are produced in near-real time, and we have built a prototype decision support tool to deliver them to SRP. This tool is designed to provide daily-to annual operational monitoring of spatial and temporal changes in SWE and snow cover conditions over the entire Salt River Watershed (covering 17,000 km2), and features advanced web mapping capabilities and watershed analytics displayed as graphical data.

  7. Snow Roads at McMurdo Station, Antarctica

    Science.gov (United States)

    2010-05-01

    is minimized distribution of low strength areas (also called “ holidays ”). Holidays are actually areas of pulverized snow that are missed or inade...quately processed. Though holidays usually occur sporadically, any single flaw may extend through the entire thickness of an unelevated road. The...Pegasus Road and the LDB pad. A few additional sites were chosen for comparison (Williams Field, virgin snow, etc.). Williams Field Road densities

  8. Inorganic carbon addition stimulates snow algae primary productivity

    Science.gov (United States)

    Hamilton, T. L.; Havig, J. R.

    2017-12-01

    Earth has experienced glacial/interglacial oscillations throughout its history. Today over 15 million square kilometers (5.8 million square miles) of Earth's land surface is covered in ice including glaciers, ice caps, and the ice sheets of Greenland and Antarctica, most of which are retreating as a consequence of increased atmospheric CO2. Glaciers are teeming with life and supraglacial snow and ice surfaces are often red due to blooms of photoautotrophic algae. Recent evidence suggests the red pigmentation, secondary carotenoids produced in part to thrive under high irradiation, lowers albedo and accelerates melt. However, there are relatively few studies that report the productivity of snow algae communities and the parameters that constrain their growth on snow and ice surfaces. Here, we demonstrate that snow algae primary productivity can be stimulated by the addition of inorganic carbon. We found an increase in light-dependent carbon assimilation in snow algae microcosms amended with increasing amounts of inorganic carbon. Our snow algae communities were dominated by typical cosmopolitan snow algae species recovered from Alpine and Arctic environments. The climate feedbacks necessary to enter and exit glacial/interglacial oscillations are poorly understood. Evidence and models agree that global Snowball events are accompanied by changes in atmospheric CO2 with increasing CO2 necessary for entering periods of interglacial time. Our results demonstrate a positive feedback between increased CO2 and snow algal productivity and presumably growth. With the recent call for bio-albedo effects to be considered in climate models, our results underscore the need for robust climate models to include feedbacks between supraglacial primary productivity, albedo, and atmospheric CO2.

  9. Global Precipitation Measurement (GPM) Core Observatory Falling Snow Estimates

    Science.gov (United States)

    Skofronick Jackson, G.; Kulie, M.; Milani, L.; Munchak, S. J.; Wood, N.; Levizzani, V.

    2017-12-01

    Retrievals of falling snow from space represent an important data set for understanding and linking the Earth's atmospheric, hydrological, and energy cycles. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. This work focuses on comparing the first stable falling snow retrieval products (released May 2017) for the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO), which was launched February 2014, and carries both an active dual frequency (Ku- and Ka-band) precipitation radar (DPR) and a passive microwave radiometer (GPM Microwave Imager-GMI). Five separate GPM-CO falling snow retrieval algorithm products are analyzed including those from DPR Matched (Ka+Ku) Scan, DPR Normal Scan (Ku), DPR High Sensitivity Scan (Ka), combined DPR+GMI, and GMI. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new, the different on-orbit instruments don't capture all snow rates equally, and retrieval algorithms differ. Thus a detailed comparison among the GPM-CO products elucidates advantages and disadvantages of the retrievals. GPM and CloudSat global snowfall evaluation exercises are natural investigative pathways to explore, but caution must be undertaken when analyzing these datasets for comparative purposes. This work includes outlining the challenges associated with comparing GPM-CO to CloudSat satellite snow estimates due to the different sampling, algorithms, and instrument capabilities. We will highlight some factors and assumptions that can be altered or statistically normalized and applied in an effort to make comparisons between GPM and CloudSat global satellite falling snow products as equitable as possible.

  10. The effects of changes in snow depth on winter recreation

    Czech Academy of Sciences Publication Activity Database

    Zahradníček, Pavel; Rožnovský, J.; Štěpánek, Petr; Farda, Aleš; Brzezina, J.

    2016-01-01

    Roč. 7, č. 1 (2016), s. 44-54 ISSN 1804-2821 R&D Projects: GA MŠk(CZ) LO1415; GA ČR GA13-04291S; GA ČR(CZ) GA14-12262S Institutional support: RVO:67179843 Keywords : new snow * total snow depth * climate change * climate models * winter recreations Subject RIV: EH - Ecology, Behaviour

  11. Towards Improved Snow Water Equivalent Estimation via GRACE Assimilation

    Science.gov (United States)

    Forman, Bart; Reichle, Rofl; Rodell, Matt

    2011-01-01

    Passive microwave (e.g. AMSR-E) and visible spectrum (e.g. MODIS) measurements of snow states have been used in conjunction with land surface models to better characterize snow pack states, most notably snow water equivalent (SWE). However, both types of measurements have limitations. AMSR-E, for example, suffers a loss of information in deep/wet snow packs. Similarly, MODIS suffers a loss of temporal correlation information beyond the initial accumulation and final ablation phases of the snow season. Gravimetric measurements, on the other hand, do not suffer from these limitations. In this study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation (DA) framework to better characterize SWE in the Mackenzie River basin located in northern Canada. Comparisons are made against independent, ground-based SWE observations, state-of-the-art modeled SWE estimates, and independent, ground-based river discharge observations. Preliminary results suggest improved SWE estimates, including improved timing of the subsequent ablation and runoff of the snow pack. Additionally, use of the DA procedure can add vertical and horizontal resolution to the coarse-scale GRACE measurements as well as effectively downscale the measurements in time. Such findings offer the potential for better understanding of the hydrologic cycle in snow-dominated basins located in remote regions of the globe where ground-based observation collection if difficult, if not impossible. This information could ultimately lead to improved freshwater resource management in communities dependent on snow melt as well as a reduction in the uncertainty of river discharge into the Arctic Ocean.

  12. Diurnal variations in the UV albedo of arctic snow

    Directory of Open Access Journals (Sweden)

    O. Meinander

    2008-11-01

    Full Text Available The relevance of snow for climate studies is based on its physical properties, such as high surface reflectivity. Surface ultraviolet (UV albedo is an essential parameter for various applications based on radiative transfer modeling. Here, new continuous measurements of the local UV albedo of natural Arctic snow were made at Sodankylä (67°22'N, 26°39'E, 179 m a.s.l. during the spring of 2007. The data were logged at 1-min intervals. The accumulation of snow was up to 68 cm. The surface layer thickness varied from 0.5 to 35 cm with the snow grain size between 0.2 and 2.5 mm. The midday erythemally weighted UV albedo ranged from 0.6 to 0.8 in the accumulation period, and from 0.5 to 0.7 during melting. During the snow melt period, under cases of an almost clear sky and variable cloudiness, an unexpected diurnal decrease of 0.05 in albedo soon after midday, and recovery thereafter, was detected. This diurnal decrease in albedo was found to be asymmetric with respect to solar midday, thus indicating a change in the properties of the snow. Independent UV albedo results with two different types of instruments confirm these findings. The measured temperature of the snow surface was below 0°C on the following mornings. Hence, the reversible diurnal change, evident for ~1–2 h, could be explained by the daily metamorphosis of the surface of the snowpack, in which the temperature of the surface increases, melting some of the snow to liquid water, after which the surface freezes again.

  13. Modeling snow accumulation and ablation processes in forested environments

    Science.gov (United States)

    Andreadis, Konstantinos M.; Storck, Pascal; Lettenmaier, Dennis P.

    2009-05-01

    The effects of forest canopies on snow accumulation and ablation processes can be very important for the hydrology of midlatitude and high-latitude areas. A mass and energy balance model for snow accumulation and ablation processes in forested environments was developed utilizing extensive measurements of snow interception and release in a maritime mountainous site in Oregon. The model was evaluated using 2 years of weighing lysimeter data and was able to reproduce the snow water equivalent (SWE) evolution throughout winters both beneath the canopy and in the nearby clearing, with correlations to observations ranging from 0.81 to 0.99. Additionally, the model was evaluated using measurements from a Boreal Ecosystem-Atmosphere Study (BOREAS) field site in Canada to test the robustness of the canopy snow interception algorithm in a much different climate. Simulated SWE was relatively close to the observations for the forested sites, with discrepancies evident in some cases. Although the model formulation appeared robust for both types of climates, sensitivity to parameters such as snow roughness length and maximum interception capacity suggested the magnitude of improvements of SWE simulations that might be achieved by calibration.

  14. Color Image of Snow White Trenches and Scraping

    Science.gov (United States)

    2008-01-01

    This image was acquired by NASA's Phoenix Mars Lander's Surface Stereo Imager on the 31st Martian day of the mission, or Sol 31 (June 26, 2008), after the May 25, 2008 landing. This image shows the trenches informally called 'Snow White 1' (left), 'Snow White 2' (right), and within the Snow White 2 trench, the smaller scraping area called 'Snow White 3.' The Snow White 3 scraped area is about 5 centimeters (2 inches) deep. The dug and scraped areas are within the diggiing site called 'Wonderland.' The Snow White trenches and scraping prove that scientists can take surface soil samples, subsurface soil samples, and icy samples all from one unit. Scientists want to test samples to determine if some ice in the soil may have been liquid in the past during warmer climate cycles. The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is led by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space Systems, Denver

  15. A Method for Snow Reanalysis: The Sierra Nevada (USA) Example

    Science.gov (United States)

    Girotto, Manuela; Margulis, Steven; Cortes, Gonzalo; Durand, Michael

    2017-01-01

    This work presents a state-of-the art methodology for constructing snow water equivalent (SWE) reanalysis. The method is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series. This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data from the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlation greater than 0.95 compared with in situ SWE observations. The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (31 years), and accuracy provide a unique dataset for investigating snow processes. This presentation illustrates how the reanalysis dataset was used to provide a basic accounting of the stored snowpack water in the Sierra Nevada over the last 31 years and ultimately improve real-time streamflow predictions.

  16. Modelling the snowmelt and the snow water equivalent by creating a simplified energy balance conceptual snow model

    Science.gov (United States)

    Riboust, Philippe; Thirel, Guillaume; Le Moine, Nicolas; Ribstein, Pierre

    2016-04-01

    A better knowledge of the accumulated snow on the watersheds will help flood forecasting centres and hydro-power companies to predict the amount of water released during spring snowmelt. Since precipitations gauges are sparse at high elevations and integrative measurements of the snow accumulated on watershed surface are hard to obtain, using snow models is an adequate way to estimate snow water equivalent (SWE) on watersheds. In addition to short term prediction, simulating accurately SWE with snow models should have many advantages. Validating the snow module on both SWE and snowmelt should give a more reliable model for climate change studies or regionalization for ungauged watersheds. The aim of this study is to create a new snow module, which has a structure that allows the use of measured snow data for calibration or assimilation. Energy balance modelling seems to be the logical choice for designing a model in which internal variables, such as SWE, could be compared to observations. Physical models are complex, needing high computational resources and many different types of inputs that are not widely measured at meteorological stations. At the opposite, simple conceptual degree-day models offer to simulate snowmelt using only temperature and precipitation as inputs with fast computing. Its major drawback is to be empirical, i.e. not taking into account all of the processes of the energy balance, which makes this kind of model more difficult to use when willing to compare SWE to observed measurements. In order to reach our objectives, we created a snow model structured by a simplified energy balance where each of the processes is empirically parameterized in order to be calculated using only temperature, precipitation and cloud cover variables. This model's structure is similar to the one created by M.T. Walter (2005), where parameterizations from the literature were used to compute all of the processes of the energy balance. The conductive fluxes into the

  17. Business Intelligence & Analytical Intelligence: hou het zakelijk

    OpenAIRE

    Van Nieuwenhuyse, Dries

    2013-01-01

    Technologie democratiseert, de markt consolideert, terwijl de hoeveelheid data explodeert. Het lijkt een ideale voedingsbodem voor projecten rond business intelligence en analytics. “Hoe minder de technologie het verschil zal maken, hoe prominenter de business aanwezig zal zijn.”

  18. Social Intelligence Design in Ambient Intelligence

    NARCIS (Netherlands)

    Nijholt, Antinus; Stock, Oliviero; Stock, O.; Nishida, T.; Nishida, Toyoaki

    2009-01-01

    This Special Issue of AI and Society contains a selection of papers presented at the 6th Social Intelligence Design Workshop held at ITC-irst, Povo (Trento, Italy) in July 2007. Being the 6th in a series means that there now is a well-established and also a growing research area. The interest in

  19. Spiritual Intelligence, Emotional Intelligence and Auditor’s Performance

    OpenAIRE

    Hanafi, Rustam

    2010-01-01

    The objective of this research was to investigate empirical evidence about influence audi-tor spiritual intelligence on the performance with emotional intelligence as a mediator variable. Linear regression models are developed to examine the hypothesis and path analysis. The de-pendent variable of each model is auditor performance, whereas the independent variable of model 1 is spiritual intelligence, of model 2 are emotional intelligence and spiritual intelligence. The parameters were estima...

  20. Naturalist Intelligence Among the Other Multiple Intelligences [In Bulgarian

    Directory of Open Access Journals (Sweden)

    R. Genkov

    2007-09-01

    Full Text Available The theory of multiple intelligences was presented by Gardner in 1983. The theory was revised later (1999 and among the other intelligences a naturalist intelligence was added. The criteria for distinguishing of the different types of intelligences are considered. While Gardner restricted the analysis of the naturalist intelligence with examples from the living nature only, the present paper considered this problem on wider background including objects and persons of the natural sciences.

  1. Intelligence and treaty ratification

    International Nuclear Information System (INIS)

    Sojka, G.L.

    1990-01-01

    What did the intelligence community and the Intelligence Committee di poorly in regard to the treaty ratification process for arms control? We failed to solve the compartmentalization problem/ This is a second-order problem, and, in general, analysts try to be very open; but there are problems nevertheless. There are very few, if any, people within the intelligence community who are cleared for everything relevant to our monitoring capability emdash short of probably the Director of Central Intelligence and the president emdash and this is a major problem. The formal monitoring estimates are drawn up by individuals who do not have access to all the information to make the monitoring judgements. This paper reports that the intelligence community did not present a formal document on either Soviet incentives of disincentives to cheat or on the possibility of cheating scenarios, and that was a mistake. However, the intelligence community was very responsive in producing those types of estimates, and, ultimately, the evidence behind them in response to questions. Nevertheless, the author thinks the intelligence community would do well to address this issue up front before a treaty is submitted to the Senate for advice and consent

  2. The Epistemic Status of Intelligence

    DEFF Research Database (Denmark)

    Rønn, Kira Vrist; Høffding, Simon

    2012-01-01

    We argue that the majority of intelligence definitions fail to recognize that the normative epistemic status of intelligence is knowledge and not an inferior alternative. We refute the counter-arguments that intelligence ought not to be seen as knowledge because of 1) its action-oriented scope...... and robustness of claims to intelligence-knowledge can be assessed....

  3. Moral Intelligence in the Schools

    Science.gov (United States)

    Clarken, Rodney H.

    2009-01-01

    Moral intelligence is newer and less studied than the more established cognitive, emotional and social intelligences, but has great potential to improve our understanding of learning and behavior. Moral intelligence refers to the ability to apply ethical principles to personal goals, values and actions. The construct of moral intelligence consists…

  4. Milk removal

    OpenAIRE

    Ferneborg, Sabine

    2016-01-01

    Milk from dairy cows is a staple dietary component for humans all over the world. Regardless of whether milk is consumed in its purest, unaltered form or as high-end products such as fine cheese or ice cream, it needs to be of high quality when taken from the cow, produced at a low price and produced in a system that consider aspects such as animal health, animal welfare and sustainability. This thesis investigated the role of milk removal and the importance of residual milk on milk yield...

  5. Advanced intelligence and mechanism approach

    Institute of Scientific and Technical Information of China (English)

    ZHONG Yixin

    2007-01-01

    Advanced intelligence will feature the intelligence research in next 50 years.An understanding of the concept of advanced intelligence as well as its importance will be provided first,and detailed analysis on an approach,the mechanism approach.suitable to the advanced intelligence research will then be flolowed.And the mutual relationship among mechanism approach,traditional approaches existed in artificial intelligence research,and the cognitive informatics will be discussed.It is interesting to discover that mechanism approach is a good one to the Advanced Intelligence research and a tmified form of the existed approaches to artificial intelligence.

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

    Science.gov (United States)

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

    2015-12-01

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

  7. Intelligent environmental sensing

    CERN Document Server

    Mukhopadhyay, Subhas

    2015-01-01

    Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include:   Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol  

  8. Is Intelligence Artificial?

    OpenAIRE

    Greer, Kieran

    2014-01-01

    Our understanding of intelligence is directed primarily at the level of human beings. This paper attempts to give a more unifying definition that can be applied to the natural world in general. The definition would be used more to verify a degree of intelligence, not to quantify it and might help when making judgements on the matter. A version of an accepted test for AI is then put forward as the 'acid test' for Artificial Intelligence itself. It might be what a free-thinking program or robot...

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

    Science.gov (United States)

    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

  10. Snow and Ice Crust Changes over Northern Eurasia since 1966

    Science.gov (United States)

    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

  11. Multiple Intelligences and quotient spaces

    OpenAIRE

    Malatesta, Mike; Quintana, Yamilet

    2006-01-01

    The Multiple Intelligence Theory (MI) is one of the models that study and describe the cognitive abilities of an individual. In [7] is presented a referential system which allows to identify the Multiple Intelligences of the students of a course and to classify the level of development of such Intelligences. Following this tendency, the purpose of this paper is to describe the model of Multiple Intelligences as a quotient space, and also to study the Multiple Intelligences of an individual in...

  12. Business Intelligence using Software Agents

    OpenAIRE

    Ana-Ramona BOLOGA; Razvan BOLOGA

    2011-01-01

    This paper presents some ideas about business intelligence today and the importance of developing real time business solutions. The authors make an exploration of links between business intelligence and artificial intelligence and focuses specifically on the implementation of software agents-based systems in business intelligence. There are briefly presented some of the few solutions proposed so far that use software agents properties for the benefit of business intelligence. The authors then...

  13. SMRT: A new, modular snow microwave radiative transfer model

    Science.gov (United States)

    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

  14. Canadian snow and sea ice: historical trends and projections

    Science.gov (United States)

    Mudryk, Lawrence R.; Derksen, Chris; Howell, Stephen; Laliberté, Fred; Thackeray, Chad; Sospedra-Alfonso, Reinel; Vionnet, Vincent; Kushner, Paul J.; Brown, Ross

    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. Here, we present an assessment from the CanSISE Network on trends in the historical record of snow cover (fraction, water equivalent) and sea ice (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea ice likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and ice is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer sea ice cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year ice loss in the Beaufort Sea and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020-2050 period shows reductions in fall and spring snow cover fraction and sea ice concentration of 5-10 % per decade (or 15-30 % in total), with similar reductions in winter sea ice concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10 % per decade (30 % in total) are projected across southern Canada.

  15. Snow in a very steep rock face: accumulation and redistribution during and after a snowfall event

    Directory of Open Access Journals (Sweden)

    Christian Gabriel Sommer

    2015-12-01

    Full Text Available Terrestrial laser scanning was used to measure snow thickness changes (perpendicular to the surface in a rock face. The aim was to investigate the accumulation and redistribution of snow in extremely steep terrain (>60°. The north-east face of the Chlein Schiahorn in the region of Davos in eastern Switzerland was scanned before and several times after a snowfall event. A summer scan without snow was acquired to calculate the total snow thickness. An improved postprocessing procedure is introduced. The data quality could be increased by using snow thickness instead of snow depth (measured vertically and by consistently applying Multi Station Adjustment to improve the registration.More snow was deposited in the flatter, smoother areas of the rock face. The spatial variability of the snow thickness change was high. The spatial patterns of the total snow thickness were similar to those of the snow thickness change. The correlation coefficient between them was 0.86. The fresh snow was partly redistributed from extremely steep to flatter terrain, presumably mostly through avalanching. The redistribution started during the snowfall and ended several days later. Snow was able to accumulate permanently at every slope angle. The amount of snow in extremely steep terrain was limited but not negligible. Areas steeper than 60° received 15% of the snowfall and contained 10% of the total amount of snow.

  16. INTELLIGENCE, COGNITION AND LANGUAGE OF GREEN PLANTS

    Directory of Open Access Journals (Sweden)

    Anthony eTrewavas

    2016-04-01

    Full Text Available A summary definition of some 70 descriptions of intelligence provides a definition for all other organisms including plants that stresses fitness. Barbara McClintock, a plant biologist, posed the notion of the ‘ thoughtful cell’ in her Nobel prize address. The systems structure necessary for a thoughtful cell is revealed by comparison of the interactome and connectome. The plant root cap, a group of some 200 cells that act holistically in responding to numerous signals, likely possesses a similar systems structure agreeing with Darwin’s description of acting like the brain of a lower organism. Intelligent behaviour requires assessment of different choices and taking the beneficial one. Decisions are constantly required to optimise the plant phenotype to a dynamic environment and the cambium is the assessing tissue diverting more or removing resources from different shoot and root branches through manipulation of vascular elements. Environmental awareness likely indicates consciousness. Spontaneity in plant behaviour, ability to count to five and error correction indicate intention. Volatile organic compounds are used as signals in plant interactions and being complex in composition may be the equivalent of language accounting for self and alien recognition by individual plants. Game theory describes competitive interactions. Interactive and intelligent outcomes emerge from application of various games between plants themselves and interactions with microbes. Behaviour profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.

  17. Intelligence, Cognition, and Language of Green Plants.

    Science.gov (United States)

    Trewavas, Anthony

    2016-01-01

    A summary definition of some 70 descriptions of intelligence provides a definition for all other organisms including plants that stresses fitness. Barbara McClintock, a plant biologist, posed the notion of the 'thoughtful cell' in her Nobel prize address. The systems structure necessary for a thoughtful cell is revealed by comparison of the interactome and connectome. The plant root cap, a group of some 200 cells that act holistically in responding to numerous signals, likely possesses a similar systems structure agreeing with Darwin's description of acting like the brain of a lower organism. Intelligent behavior requires assessment of different choices and taking the beneficial one. Decisions are constantly required to optimize the plant phenotype to a dynamic environment and the cambium is the assessing tissue diverting more or removing resources from different shoot and root branches through manipulation of vascular elements. Environmental awareness likely indicates consciousness. Spontaneity in plant behavior, ability to count to five and error correction indicate intention. Volatile organic compounds are used as signals in plant interactions and being complex in composition may be the equivalent of language accounting for self and alien recognition by individual plants. Game theory describes competitive interactions. Interactive and intelligent outcomes emerge from application of various games between plants themselves and interactions with microbes. Behavior profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.

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

    Science.gov (United States)

    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).

  19. Engineering general intelligence

    CERN Document Server

    Goertzel, Ben; Geisweiller, Nil

    2014-01-01

    The work outlines a novel conceptual and theoretical framework for understanding Artificial General Intelligence and based on this framework outlines a practical roadmap for the development of AGI with capability at the human level and ultimately beyond.

  20. Understanding US National Intelligence

    DEFF Research Database (Denmark)

    Leander, Anna

    2014-01-01

    In July 2010, the Washington Post (WP) published the results of a project on “Top Secret America” on which twenty investigative journalists had been working for two years. The project drew attention to the change and growth in National Intelligence following 9/11 (Washington Post 2010a......). The initial idea had been to work on intelligence generally, but given that this proved overwhelming, the team narrowed down to focus only on intelligence qualified as “top secret.” Even so, the growth in this intelligence activity is remarkable. This public is returning, or in this case expanding...... at an impressive speed confirming the general contention of this volume. Between 2001 and 2010 the budget had increased by 250 percent, reaching $75 billion (the GDP of the Czech Republic). Thirty-three building complexes for top secret work had been or were under construction in the Washington area; 1...

  1. Engineering general intelligence

    CERN Document Server

    Goertzel, Ben; Geisweiller, Nil

    2014-01-01

    The work outlines a detailed blueprint for the creation of an Artificial General Intelligence system with capability at the human level and ultimately beyond, according to the Cog Prime AGI design and the Open Cog software architecture.

  2. Intelligence Issues for Congress

    National Research Council Canada - National Science Library

    Best, Jr, Richard A

    2007-01-01

    To address the challenges facing the U.S. Intelligence Community in the 21st century, congressional and executive branch initiatives have sought to improve coordination among the different agencies and to encourage better analysis...

  3. Intelligence Issues for Congress

    National Research Council Canada - National Science Library

    Best, Jr, Richard A

    2006-01-01

    To address the challenges facing the U.S. Intelligence Community in the 21st Century, congressional and executive branch initiatives have sought to improve coordination among the different agencies and to encourage better analysis...

  4. Intelligence Issues for Congress

    National Research Council Canada - National Science Library

    Best, Jr, Richard A

    2008-01-01

    To address the challenges facing the U.S. Intelligence Community in the 21st century, congressional and executive branch initiatives have sought to improve coordination among the different agencies and to encourage better analysis...

  5. Intelligent Information Systems Institute

    National Research Council Canada - National Science Library

    Gomes, Carla

    2004-01-01

    ...) at Cornell during the first three years of operation. IISI's mandate is threefold: To perform and stimulate research in computational and data-intensive methods for intelligent decision making systems...

  6. Quo vadis, Intelligent Machine?

    Directory of Open Access Journals (Sweden)

    Rosemarie Velik

    2010-09-01

    Full Text Available Artificial Intelligence (AI is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this is no task easy to be solved. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in future. The goal is to mediate an understanding for the developments and changes in thinking in course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

  7. Bibliography: Artificial Intelligence.

    Science.gov (United States)

    Smith, Richard L.

    1986-01-01

    Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

  8. Handbook of Intelligent Vehicles

    CERN Document Server

    2012-01-01

    The Handbook of Intelligent Vehicles provides a complete coverage of the fundamentals, new technologies, and sub-areas essential to the development of intelligent vehicles; it also includes advances made to date, challenges, and future trends. Significant strides in the field have been made to date; however, so far there has been no single book or volume which captures these advances in a comprehensive format, addressing all essential components and subspecialties of intelligent vehicles, as this book does. Since the intended users are engineering practitioners, as well as researchers and graduate students, the book chapters do not only cover fundamentals, methods, and algorithms but also include how software/hardware are implemented, and demonstrate the advances along with their present challenges. Research at both component and systems levels are required to advance the functionality of intelligent vehicles. This volume covers both of these aspects in addition to the fundamentals listed above.

  9. Genes, evolution and intelligence.

    Science.gov (United States)

    Bouchard, Thomas J

    2014-11-01

    I argue that the g factor meets the fundamental criteria of a scientific construct more fully than any other conception of intelligence. I briefly discuss the evidence regarding the relationship of brain size to intelligence. A review of a large body of evidence demonstrates that there is a g factor in a wide range of species and that, in the species studied, it relates to brain size and is heritable. These findings suggest that many species have evolved a general-purpose mechanism (a general biological intelligence) for dealing with the environments in which they evolved. In spite of numerous studies with considerable statistical power, we know of very few genes that influence g and the effects are very small. Nevertheless, g appears to be highly polygenic. Given the complexity of the human brain, it is not surprising that that one of its primary faculties-intelligence-is best explained by the near infinitesimal model of quantitative genetics.

  10. Modelling intelligent behavior

    Science.gov (United States)

    Green, H. S.; Triffet, T.

    1993-01-01

    An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

  11. Emotional Intelligence: Requiring Attention

    Directory of Open Access Journals (Sweden)

    Monica Tudor

    2016-01-01

    Full Text Available This article aims to highlight the need for emotional intelligence. Two methods of measurementare presented in this research, in order to better understand the necessity of a correct result. Theresults of research can lead to recommendations for improving levels of emotional intelligence andare useful for obtaining data to better compare past and present result. The papers presented inthis research are significant for future study of this subject. The first paper presents the evolutionof emotional intelligence in the past two years, more specifically its decrease concerning certaincharacteristics. The second one presents a research on the differences between generations. Thethird one shows a difference in emotional intelligence levels of children from rural versus urbanenvironments and the obstacles that they encounter in their own development.

  12. Intelligence Issues for Congress

    National Research Council Canada - National Science Library

    Best. Jr, Richard A

    2006-01-01

    To address the challenges facing the U.S. Intelligence Community in the 21st century, congressional and executive branch initiatives have sought to improve coordination among the different agencies and to encourage better analysis...

  13. Towards Intelligent Supply Chains

    DEFF Research Database (Denmark)

    Siurdyban, Artur; Møller, Charles

    2012-01-01

    applied to the context of organizational processes can increase the success rate of business operations. The framework is created using a set of theoretical based constructs grounded in a discussion across several streams of research including psychology, pedagogy, artificial intelligence, learning...... of deploying inapt operations leading to deterioration of profits. To address this problem, we propose a unified business process design framework based on the paradigm of intelligence. Intelligence allows humans and human-designed systems cope with environmental volatility, and we argue that its principles......, business process management and supply chain management. It outlines a number of system tasks combined in four integrated management perspectives: build, execute, grow and innovate, put forward as business process design propositions for Intelligent Supply Chains....

  14. Business Intelligence Integrated Solutions

    Directory of Open Access Journals (Sweden)

    Cristescu Marian Pompiliu

    2017-01-01

    Full Text Available This paper shows how businesses make decisions better and faster in terms of customers, partners and operations by turning data into valuable business information. The paper describes how to bring together people's and business intelligence information to achieve successful business strategies. There is the possibility of developing business intelligence projects in large and medium-sized organizations only with the Microsoft product described in the paper, and possible alternatives can be discussed according to the required features.

  15. Artificial intelligence in medicine.

    OpenAIRE

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of ...

  16. Artificial Intelligence Study (AIS).

    Science.gov (United States)

    1987-02-01

    ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

  17. Artificial Intelligence in Astronomy

    Science.gov (United States)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  18. Minimally Naturalistic Artificial Intelligence

    OpenAIRE

    Hansen, Steven Stenberg

    2017-01-01

    The rapid advancement of machine learning techniques has re-energized research into general artificial intelligence. While the idea of domain-agnostic meta-learning is appealing, this emerging field must come to terms with its relationship to human cognition and the statistics and structure of the tasks humans perform. The position of this article is that only by aligning our agents' abilities and environments with those of humans do we stand a chance at developing general artificial intellig...

  19. Artificial intelligence in cardiology

    OpenAIRE

    Bonderman, Diana

    2017-01-01

    Summary Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiol...

  20. Intelligent distributed computing

    CERN Document Server

    Thampi, Sabu

    2015-01-01

    This book contains a selection of refereed and revised papers of the Intelligent Distributed Computing Track originally presented at the third International Symposium on Intelligent Informatics (ISI-2014), September 24-27, 2014, Delhi, India.  The papers selected for this Track cover several Distributed Computing and related topics including Peer-to-Peer Networks, Cloud Computing, Mobile Clouds, Wireless Sensor Networks, and their applications.

  1. The intelligent data recorder

    International Nuclear Information System (INIS)

    Kojima, Mamoru; Hidekuma, Sigeru.

    1985-01-01

    The intelligent data recorder has been developed to data acquisition for a microwave interferometer. The 'RS-232C' which is the standard interface is used for data transmission to the host computer. Then, it's easy to connect with any computer which has general purpose serial port. In this report, the charcteristics of the intelligent data recorder and the way of developing the software are described. (author)

  2. Intelligent Lighting Control System

    OpenAIRE

    García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

    2014-01-01

    This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

  3. Improving snow cover mapping in forests through the use of a canopy reflectance model

    International Nuclear Information System (INIS)

    Klein, A.G.; Hall, D.K.; Riggs, G.A.

    1998-01-01

    MODIS, the moderate resolution imaging spectro radiometer, will be launched in 1998 as part of the first earth observing system (EOS) platform. Global maps of land surface properties, including snow cover, will be created from MODIS imagery. The MODIS snow-cover mapping algorithm that will be used to produce daily maps of global snow cover extent at 500 m resolution is currently under development. With the exception of cloud cover, the largest limitation to producing a global daily snow cover product using MODIS is the presence of a forest canopy. A Landsat Thematic Mapper (TM) time-series of the southern Boreal Ecosystem–Atmosphere Study (BOREAS) study area in Prince Albert National Park, Saskatchewan, was used to evaluate the performance of the current MODIS snow-cover mapping algorithm in varying forest types. A snow reflectance model was used in conjunction with a canopy reflectance model (GeoSAIL) to model the reflectance of a snow-covered forest stand. Using these coupled models, the effects of varying forest type, canopy density, snow grain size and solar illumination geometry on the performance of the MODIS snow-cover mapping algorithm were investigated. Using both the TM images and the reflectance models, two changes to the current MODIS snow-cover mapping algorithm are proposed that will improve the algorithm's classification accuracy in forested areas. The improvements include using the normalized difference snow index and normalized difference vegetation index in combination to discriminate better between snow-covered and snow-free forests. A minimum albedo threshold of 10% in the visible wavelengths is also proposed. This will prevent dense forests with very low visible albedos from being classified incorrectly as snow. These two changes increase the amount of snow mapped in forests on snow-covered TM scenes, and decrease the area incorrectly identified as snow on non-snow-covered TM scenes. (author)

  4. Professionalizing Intelligence Analysis

    Directory of Open Access Journals (Sweden)

    James B. Bruce

    2015-09-01

    Full Text Available This article examines the current state of professionalism in national security intelligence analysis in the U.S. Government. Since the introduction of major intelligence reforms directed by the Intelligence Reform and Terrorism Prevention Act (IRTPA in December, 2004, we have seen notable strides in many aspects of intelligence professionalization, including in analysis. But progress is halting, uneven, and by no means permanent. To consolidate its gains, and if it is to continue improving, the U.S. intelligence community (IC should commit itself to accomplishing a new program of further professionalization of analysis to ensure that it will develop an analytic cadre that is fully prepared to deal with the complexities of an emerging multipolar and highly dynamic world that the IC itself is forecasting. Some recent reforms in intelligence analysis can be assessed against established standards of more fully developed professions; these may well fall short of moving the IC closer to the more fully professionalized analytical capability required for producing the kind of analysis needed now by the United States.

  5. GABA predicts visual intelligence.

    Science.gov (United States)

    Cook, Emily; Hammett, Stephen T; Larsson, Jonas

    2016-10-06

    Early psychological researchers proposed a link between intelligence and low-level perceptual performance. It was recently suggested that this link is driven by individual variations in the ability to suppress irrelevant information, evidenced by the observation of strong correlations between perceptual surround suppression and cognitive performance. However, the neural mechanisms underlying such a link remain unclear. A candidate mechanism is neural inhibition by gamma-aminobutyric acid (GABA), but direct experimental support for GABA-mediated inhibition underlying suppression is inconsistent. Here we report evidence consistent with a global suppressive mechanism involving GABA underlying the link between sensory performance and intelligence. We measured visual cortical GABA concentration, visuo-spatial intelligence and visual surround suppression in a group of healthy adults. Levels of GABA were strongly predictive of both intelligence and surround suppression, with higher levels of intelligence associated with higher levels of GABA and stronger surround suppression. These results indicate that GABA-mediated neural inhibition may be a key factor determining cognitive performance and suggests a physiological mechanism linking surround suppression and intelligence. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  6. Alzheimer's disease and intelligence.

    Science.gov (United States)

    Yeo, R A; Arden, R; Jung, R E

    2011-06-01

    A significant body of evidence has accumulated suggesting that individual variation in intellectual ability, whether assessed directly by intelligence tests or indirectly through proxy measures, is related to risk of developing Alzheimer's disease (AD) in later life. Important questions remain unanswered, however, such as the specificity of risk for AD vs. other forms of dementia, and the specific links between premorbid intelligence and development of the neuropathology characteristic of AD. Lower premorbid intelligence has also emerged as a risk factor for greater mortality across myriad health and mental health diagnoses. Genetic covariance contributes importantly to these associations, and pleiotropic genetic effects may impact diverse organ systems through similar processes, including inefficient design and oxidative stress. Through such processes, the genetic underpinnings of intelligence, specifically, mutation load, may also increase the risk of developing AD. We discuss how specific neurobiologic features of relatively lower premorbid intelligence, including reduced metabolic efficiency, may facilitate the development of AD neuropathology. The cognitive reserve hypothesis, the most widely accepted account of the intelligence-AD association, is reviewed in the context of this larger literature.

  7. Improved Micro Rain Radar snow measurements using Doppler spectra post-processing

    Directory of Open Access Journals (Sweden)

    M. Maahn

    2012-11-01

    Full Text Available The Micro Rain Radar 2 (MRR is a compact Frequency Modulated Continuous Wave (FMCW system that operates at 24 GHz. The MRR is a low-cost, portable radar system that requires minimum supervision in the field. As such, the MRR is a frequently used radar system for conducting precipitation research. Current MRR drawbacks are the lack of a sophisticated post-processing algorithm to improve its sensitivity (currently at +3 dBz, spurious artefacts concerning radar receiver noise and the lack of high quality Doppler radar moments. Here we propose an improved processing method which is especially suited for snow observations and provides reliable values of effective reflectivity, Doppler velocity and spectral width. The proposed method is freely available on the web and features a noise removal based on recognition of the most significant peak. A dynamic dealiasing routine allows observations even if the Nyquist velocity range is exceeded. Collocated observations over 115 days of a MRR and a pulsed 35.2 GHz MIRA35 cloud radar show a very high agreement for the proposed method for snow, if reflectivities are larger than −5 dBz. The overall sensitivity is increased to −14 and −8 dBz, depending on range. The proposed method exploits the full potential of MRR's hardware and substantially enhances the use of Micro Rain Radar for studies of solid precipitation.

  8. Snow multivariable data assimilation for hydrological predictions in mountain areas

    Science.gov (United States)

    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

  9. Drones application on snow and ice surveys in alpine areas

    Science.gov (United States)

    La Rocca, Leonardo; Bonetti, Luigi; Fioletti, Matteo; Peretti, Giovanni

    2015-04-01

    First results from Climate change are now clear in Europe, and in Italy in particular, with the natural disasters that damaged irreparably the territory and the habitat due to extreme meteorological events. The Directive 2007/60/EC highlight that an "effective natural hazards prevention and mitigation that requires coordination between Member States above all on natural hazards prevention" is necessary. A climate change adaptation strategy is identified on the basis of the guidelines of the European Community program 2007-2013. Following the directives provided in the financial instrument for civil protection "Union Civil Protection Mechanism" under Decision No. 1313/2013 / EU of the European Parliament and Council, a cross-cutting approach that takes into account a large number of implementation tools of EU policies is proposed as climate change adaptation strategy. In last 7 years a network of trans-Alpine area's authorities was created between Italy and Switzerland to define an adaptive strategy on climate change effects on natural enviroment based on non structural remedies. The Interreg IT - CH STRADA Project (STRategie di ADAttamento al cambiamento climatico) was born to join all the non structural remedies to climate change effects caused by snow and avalanches, on mountain sources, extreme hydrological events and to manage all transnational hydrological resources, involving all stakeholders from Italy and Switzerland. The STRADA project involved all civil protection authorities and all research centers in charge of snow, hydrology end civil protection. The Snow - meteorological center of the Regional Agency for Environment Protection (CNM of ARPA Lombardia) and the Civil Protection of Lombardy Region created a research team to develop tools for avalanche prediction and to observe and predict snow cover on Alpine area. With this aim a lot of aerial photo using Drone as been performed in unusual landscape. Results of all surveys were really interesting on a

  10. The seasonal cycle of snow cover, sea ice and surface albedo

    Science.gov (United States)

    Robock, A.

    1980-01-01

    The paper examines satellite data used to construct mean snow cover caps for the Northern Hemisphere. The zonally averaged snow cover from these maps is used to calculate the seasonal cycle of zonally averaged surface albedo. The effects of meltwater on the surface, solar zenith angle, and cloudiness are parameterized and included in the calculations of snow and ice albedo. The data allows a calculation of surface albedo for any land or ocean 10 deg latitude band as a function of surface temperature ice and snow cover; the correct determination of the ice boundary is more important than the snow boundary for accurately simulating the ice and snow albedo feedback.

  11. Spectral reflectance of solar light from dirty snow: a simple theoretical model and its validation

    Directory of Open Access Journals (Sweden)

    A. Kokhanovsky

    2013-08-01

    Full Text Available A simple analytical equation for the snow albedo as the function of snow grain size, soot concentration, and soot mass absorption coefficient is presented. This simple equation can be used in climate models to assess the influence of snow pollution on snow albedo. It is shown that the squared logarithm of the albedo (in the visible is directly proportional to the soot concentration. A new method of the determination of the soot mass absorption coefficient in snow is proposed. The equations derived are applied to a dusty snow layer as well.

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

    Science.gov (United States)

    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.

  13. Granulation of snow: From tumbler experiments to discrete element simulations

    Science.gov (United States)

    Steinkogler, Walter; Gaume, Johan; Löwe, Henning; Sovilla, Betty; Lehning, Michael

    2015-06-01

    It is well known that snow avalanches exhibit granulation phenomena, i.e., the formation of large and apparently stable snow granules during the flow. The size distribution of the granules has an influence on flow behavior which, in turn, affects runout distances and avalanche velocities. The underlying mechanisms of granule formation are notoriously difficult to investigate within large-scale field experiments, due to limitations in the scope for measuring temperatures, velocities, and size distributions. To address this issue we present experiments with a concrete tumbler, which provide an appropriate means to investigate granule formation of snow. In a set of experiments at constant rotation velocity with varying temperatures and water content, we demonstrate that temperature has a major impact on the formation of granules. The experiments showed that granules only formed when the snow temperature exceeded -1∘C. No evolution in the granule size was observed at colder temperatures. Depending on the conditions, different granulation regimes are obtained, which are qualitatively classified according to their persistence and size distribution. The potential of granulation of snow in a tumbler is further demonstrated by showing that generic features of the experiments can be reproduced by cohesive discrete element simulations. The proposed discrete element model mimics the competition between cohesive forces, which promote aggregation, and impact forces, which induce fragmentation, and supports the interpretation of the granule regime classification obtained from the tumbler experiments. Generalizations, implications for flow dynamics, and experimental and model limitations as well as suggestions for future work are discussed.

  14. Role of Marine Snows in Microplastic Fate and Bioavailability.

    Science.gov (United States)

    Porter, Adam; Lyons, Brett P; Galloway, Tamara S; Lewis, Ceri

    2018-06-01

    Microplastics contaminate global oceans and are accumulating in sediments at levels thought sufficient to leave a permanent layer in the fossil record. Despite this, the processes that vertically transport buoyant polymers from surface waters to the benthos are poorly understood. Here we demonstrate that laboratory generated marine snows can transport microplastics of different shapes, sizes, and polymers away from the water surface and enhance their bioavailability to benthic organisms. Sinking rates of all tested microplastics increased when incorporated into snows, with large changes observed for the buoyant polymer polyethylene with an increase in sinking rate of 818 m day -1 and for denser polyamide fragments of 916 m day -1 . Incorporation into snows increased microplastic bioavailability for mussels, where uptake increased from zero to 340 microplastics individual -1 for free microplastics to up to 1.6 × 10 5 microplastics individual -1 when incorporated into snows. We therefore propose that marine snow formation and fate has the potential to play a key role in the biogeochemical processing of microplastic pollution.

  15. First Gridded Spatial Field Reconstructions of Snow from Tree Rings

    Science.gov (United States)

    Coulthard, B. L.; Anchukaitis, K. J.; Pederson, G. T.; Alder, J. R.; Hostetler, S. W.; Gray, S. T.

    2017-12-01

    Western North America's mountain snowpacks provide critical water resources for human populations and ecosystems. Warmer temperatures and changing precipitation patterns will increasingly alter the quantity, extent, and persistence of snow in coming decades. A comprehensive understanding of the causes and range of long-term variability in this system is required for forecasting future anomalies, but snowpack observations are limited and sparse. While individual tree ring-based annual snowpack reconstructions have been developed for specific regions and mountain ranges, we present here the first collection of spatially-explicit gridded field reconstructions of seasonal snowpack within the American Rocky Mountains. Capitalizing on a new western North American snow-sensitive network of over 700 tree-ring chronologies, as well as recent advances in PRISM-based snow modeling, our gridded reconstructions offer a full space-time characterization of snow and associated water resource fluctuations over several centuries. The quality of reconstructions is evaluated against existing observations, proxy-records, and an independently-developed first-order monthly snow model.

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

    Science.gov (United States)

    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.

  17. 78 FR 90 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

    Science.gov (United States)

    2013-01-02

    ... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: National Intelligence University, Defense Intelligence... hereby given that a closed meeting of the National Intelligence University Board of Visitors has been...

  18. 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.

    Science.gov (United States)

    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

  19. Aerosol size-dependent below-cloud scavenging by rain and snow in the ECHAM5-HAM

    Directory of Open Access Journals (Sweden)

    R. Posselt

    2009-07-01

    Full Text Available Wet deposition processes are highly efficient in the removal of aerosols from the atmosphere, and thus strongly influence global aerosol concentrations, and clouds, and their respective radiative forcings. In this study, physically detailed size-dependent below-cloud scavenging parameterizations for rain and snow are implemented in the ECHAM5-HAM global aerosol-climate model. Previously, below-cloud scavenging by rain in the ECHAM5-HAM was simply a function of the aerosol mode, and then scaled by the rainfall rate. The below-cloud scavenging by snow was a function of the snowfall rate alone. The global mean aerosol optical depth, and sea salt burden are sensitive to the below-cloud scavenging coefficients, with reductions near to 15% when the more vigorous size-dependent below-cloud scavenging by rain and snow is implemented. The inclusion of a prognostic rain scheme significantly reduces the fractional importance of below-cloud scavenging since there is higher evaporation in the lower troposphere, increasing the global mean sea salt burden by almost 15%. Thermophoretic effects are shown to produce increases in the global and annual mean number removal of Aitken size particles of near to 10%, but very small increases (near 1% in the global mean below-cloud mass scavenging of carbonaceous and sulfate aerosols. Changes in the assumptions about the below-cloud scavenging by rain of particles with radius smaller than 10 nm do not cause any significant changes to the global and annual mean aerosol mass or number burdens, despite a change in the below-cloud number removal rate for nucleation mode particles by near to five-fold. Annual and zonal mean nucleation mode number concentrations are enhanced by up to 30% in the lower troposphere with the more vigourous size-dependent below-cloud scavenging. Closer agreement with different observations is found when the more physically detailed below-cloud scavenging parameterization is employed in the ECHAM5

  20. Snow sublimation in mountain environments and its sensitivity to forest disturbance and climate warming

    Science.gov (United States)

    Sexstone, Graham A.; Clow, David W.; Fassnacht, Steven R.; Liston, Glen E.; Hiemstra, Christopher A.; Knowles, John F.; Penn, Colin A.

    2018-01-01

    Snow sublimation is an important component of the snow mass balance, but the spatial and temporal variability of this process is not well understood in mountain environments. This study combines a process‐based snow model (SnowModel) with eddy covariance (EC) measurements to investigate (1) the spatio‐temporal variability of simulated snow sublimation with respect to station observations, (2) the contribution of snow sublimation to the ablation of the snowpack, and (3) the sensitivity and response of snow sublimation to bark beetle‐induced forest mortality and climate warming across the north‐central Colorado Rocky Mountains. EC‐based observations of snow sublimation compared well with simulated snow sublimation at stations dominated by surface and canopy sublimation, but blowing snow sublimation in alpine areas was not well captured by the EC instrumentation. Water balance calculations provided an important validation of simulated sublimation at the watershed scale. Simulated snow sublimation across the study area was equivalent to 28% of winter precipitation on average, and the highest relative snow sublimation fluxes occurred during the lowest snow years. Snow sublimation from forested areas accounted for the majority of sublimation fluxes, highlighting the importance of canopy and sub‐canopy surface sublimation in this region. Simulations incorporating the effects of tree mortality due to bark‐beetle disturbance resulted in a 4% reduction in snow sublimation from forested areas. Snow sublimation rates corresponding to climate warming simulations remained unchanged or slightly increased, but total sublimation losses decreased by up to 6% because of a reduction in snow covered area and duration.

  1. COSMO-SkyMed Image Investigation of Snow Features in Alpine Environment

    Directory of Open Access Journals (Sweden)

    Simonetta Paloscia

    2017-01-01

    Full Text Available In this work, X band images acquired by COSMO-SkyMed (CSK on alpine environment have been analyzed for investigating snow characteristics and their effect on backscattering variations. Preliminary results confirmed the capability of simultaneous optical and Synthetic Aperture Radar (SAR images (Landsat-8 and CSK in separating snow/no-snow areas and in detecting wet snow. The sensitivity of backscattering to snow depth has not always been confirmed, depending on snow characteristics related to the season. A model based on Dense Media Radiative Transfer theory (DMRT-QMS was applied for simulating the backscattering response on the X band from snow cover in different conditions of grain size, snow density and depth. By using DMRT-QMS and snow in-situ data collected on Cordevole basin in Italian Alps, the effect of grain size and snow density, beside snow depth and snow water equivalent, was pointed out, showing that the snow features affect the backscatter in different and sometimes opposite ways. Experimental values of backscattering were correctly simulated by using this model and selected intervals of ground parameters. The relationship between simulated and measured backscattering for the entire dataset shows slope >0.9, determination coefficient, R2 = 0.77, and root mean square error, RMSE = 1.1 dB, with p-value <0.05.

  2. Business Intelligence using Software Agents

    Directory of Open Access Journals (Sweden)

    Ana-Ramona BOLOGA

    2011-12-01

    Full Text Available This paper presents some ideas about business intelligence today and the importance of developing real time business solutions. The authors make an exploration of links between business intelligence and artificial intelligence and focuses specifically on the implementation of software agents-based systems in business intelligence. There are briefly presented some of the few solutions proposed so far that use software agents properties for the benefit of business intelligence. The authors then propose some basic ideas for developing real-time agent-based software system for business intelligence in supply chain management, using Case Base Reasoning Agents.

  3. Fluid intelligence: A brief history.

    Science.gov (United States)

    Kent, Phillip

    2017-01-01

    The concept of fluid and crystallized intelligence was introduced to the psychological community approximately 75 years ago by Raymond B. Cattell, and it continues to be an area of active research and controversy. The purpose of this paper is to provide a brief overview of the origin of the concept, early efforts to define intelligence and uses of intelligence tests to address pressing social issues, and the ongoing controversies associated with fluid intelligence and the structure of intelligence. The putative neuropsychological underpinnings and neurological substrates of fluid intelligence are discussed.

  4. Observational evidence of changes in global snow and ice cover

    International Nuclear Information System (INIS)

    Barry, R.G.

    1990-01-01

    Sources of observational data on recent variations in the seasonal extent of snow cover and sea ice, of the terminal position and volume of alpine glaciers, and of ground temperature profiles in areas of permafrost are briefly reviewed. Recent evidence of changes in these variables is then examined. The extent of seasonal snow cover in the Northern hemisphere and of sea ice in both hemispheres has fluctuated irregularly over the last 15-20 years with a range of about 10-15% in each case. There is no clear evidence of any recent trends, despite general global warming. In contrast, most glaciers retreated and thinned from before the turn of the century until the 1960s and alaskan permafrost temperatures have risen 2-4 C per century. Recently, glacier advances have been noted, perhaps in response to increased accumulation. Problems of linking climate forcing and snow/ice responses are discussed

  5. Estimating water equivalent snow depth from related meteorological variables

    International Nuclear Information System (INIS)

    Steyaert, L.T.; LeDuc, S.K.; Strommen, N.D.; Nicodemus, M.L.; Guttman, N.B.

    1980-05-01

    Engineering design must take into consideration natural loads and stresses caused by meteorological elements, such as, wind, snow, precipitation and temperature. The purpose of this study was to determine a relationship of water equivalent snow depth measurements to meteorological variables. Several predictor models were evaluated for use in estimating water equivalent values. These models include linear regression, principal component regression, and non-linear regression models. Linear, non-linear and Scandanavian models are used to generate annual water equivalent estimates for approximately 1100 cooperative data stations where predictor variables are available, but which have no water equivalent measurements. These estimates are used to develop probability estimates of snow load for each station. Map analyses for 3 probability levels are presented

  6. Fukushima Nuclear Accident Recorded in Tibetan Plateau Snow Pits

    Science.gov (United States)

    Wang, Ninglian; Wu, Xiaobo; Kehrwald, Natalie; Li, Zhen; Li, Quanlian; Jiang, Xi; Pu, Jianchen

    2015-01-01

    The β radioactivity of snow-pit samples collected in the spring of 2011 on four Tibetan Plateau glaciers demonstrate a remarkable peak in each snow pit profile, with peaks about ten to tens of times higher than background levels. The timing of these peaks suggests that the high radioactivity resulted from the Fukushima nuclear accident that occurred on March 11, 2011 in eastern Japan. Fallout monitoring studies demonstrate that this radioactive material was transported by the westerlies across the middle latitudes of the Northern Hemisphere. The depth of the peak β radioactivity in each snow pit compared with observational precipitation records, suggests that the radioactive fallout reached the Tibetan Plateau and was deposited on glacier surfaces in late March 2011, or approximately 20 days after the nuclear accident. The radioactive fallout existed in the atmosphere over the Tibetan Plateau for about one month. PMID:25658094

  7. Estimation of Snow Parameters from Dual-Wavelength Airborne Radar

    Science.gov (United States)

    Liao, Liang; Meneghini, Robert; Iguchi, Toshio; Detwiler, Andrew

    1997-01-01

    Estimation of snow characteristics from airborne radar measurements would complement In-situ measurements. While In-situ data provide more detailed information than radar, they are limited in their space-time sampling. In the absence of significant cloud water contents, dual-wavelength radar data can be used to estimate 2 parameters of a drop size distribution if the snow density is assumed. To estimate, rather than assume, a snow density is difficult, however, and represents a major limitation in the radar retrieval. There are a number of ways that this problem can be investigated: direct comparisons with in-situ measurements, examination of the large scale characteristics of the retrievals and their comparison to cloud model outputs, use of LDR measurements, and comparisons to the theoretical results of Passarelli(1978) and others. In this paper we address the first approach and, in part, the second.

  8. Quasi-steady temperature gradient metamorphism in idealized, dry snow

    International Nuclear Information System (INIS)

    Christon, M.

    1994-01-01

    A three-dimensional model for heat and mass transport in microscale ice lattices of dry snow is formulated consistent with conservation laws and solid-vapor interface constraints. A finite element model that employs continuous mesh deformation is developed, and calculation of the effective diffusion rates in snow, metamorphosing under a temperature gradient, is performed. Results of the research provide basic insight into the movement of heat and water vapor in seasonal snowcovers. Agreement between the numerical results and measured data of effective thermal conductivity is excellent. The enhancement to the water vapor diffusion rate in snow is bracketed in the range of 1.05--2.0 times that of water vapor in dry air

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

    Science.gov (United States)

    Walsh, John E.

    1991-01-01

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

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

    Science.gov (United States)

    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

  11. New Perspectives on Intelligence Collection and Processing

    Science.gov (United States)

    2016-06-01

    MASINT Measurement and Signature Intelligence NPS Naval Postgraduate School OSINT Open Source Intelligence pdf Probability Density Function SIGINT...MASINT): different types of sensors • Open Source Intelligence ( OSINT ): from all open sources • Signals Intelligence (SIGINT): intercepting the

  12. Trends in ambient intelligent systems the role of computational intelligence

    CERN Document Server

    Khan, Mohammad; Abraham, Ajith

    2016-01-01

    This book demonstrates the success of Ambient Intelligence in providing possible solutions for the daily needs of humans. The book addresses implications of ambient intelligence in areas of domestic living, elderly care, robotics, communication, philosophy and others. The objective of this edited volume is to show that Ambient Intelligence is a boon to humanity with conceptual, philosophical, methodical and applicative understanding. The book also aims to schematically demonstrate developments in the direction of augmented sensors, embedded systems and behavioral intelligence towards Ambient Intelligent Networks or Smart Living Technology. It contains chapters in the field of Ambient Intelligent Networks, which received highly positive feedback during the review process. The book contains research work, with in-depth state of the art from augmented sensors, embedded technology and artificial intelligence along with cutting-edge research and development of technologies and applications of Ambient Intelligent N...

  13. Distribution of VOCs between air and snow at the Jungfraujoch high alpine research station, Switzerland, during CLACE 5 (winter 2006

    Directory of Open Access Journals (Sweden)

    E. Starokozhev

    2009-05-01

    Full Text Available Volatile organic compounds (VOCs were analyzed in air and snow samples at the Jungfraujoch high alpine research station in Switzerland as part of CLACE 5 (CLoud and Aerosol Characterization Experiment during February/March 2006. The fluxes of individual compounds in ambient air were calculated from gas phase concentrations and wind speed. The highest concentrations and flux values were observed for the aromatic hydrocarbons benzene (14.3 μg.m−2 s−1, 1,3,5-trimethylbenzene (5.27 μg.m−2 s−1, toluene (4.40 μg.m−2 −1, and the aliphatic hydrocarbons i-butane (7.87 μg.m−2 s−1, i-pentane (3.61 μg.m−2 s−1 and n-butane (3.23 μg.m−2 s−1. The measured concentrations and fluxes were used to calculate the efficiency of removal of VOCs by snow, which is defined as difference between the initial and final concentration/flux values of compounds before and after wet deposition. The removal efficiency was calculated at −24°C (−13.7°C and ranged from 37% (35% for o-xylene to 93% (63% for i-pentane. The distribution coefficients of VOCs between the air and snow phases were derived from published poly-parameter linear free energy relationship (pp-LFER data, and compared with distribution coefficients obtained from the simultaneous measurements of VOC concentrations in air and snow at Jungfraujoch. The coefficients calculated from pp-LFER exceeded those values measured in the present study, which indicates more efficient snow scavenging of the VOCs investigated than suggested by theoretical predictions.

  14. Snow and Rain Modify Neighbourhood Walkability for Older Adults.

    Science.gov (United States)

    Clarke, Philippa; Hirsch, Jana A; Melendez, Robert; Winters, Meghan; Sims Gould, Joanie; Ashe, Maureen; Furst, Sarah; McKay, Heather

    2017-06-01

    The literature has documented a positive relationship between walkable built environments and outdoor mobility in older adults. Yet, surprisingly absent is any consideration of how weather conditions modify the impact of neighbourhood walkability. Using archived weather data linked to survey data collected from a sample of older adults in Vancouver, Canada, we found that car-dependent neighbourhoods (featuring longer block lengths, fewer intersections, and greater distance to amenities) became inaccessible in snow. Even older adults who lived in very walkable neighbourhoods walked to 25 per cent fewer destinations in snow. It is crucial to consider the impact of weather in the relationship between neighbourhood walkability and older adult mobility.

  15. Ultratrace analysis for organolead compounds in Greenland snow

    International Nuclear Information System (INIS)

    Lobinski, R.; Szpunar-Lobinska, J.; Adams, F.C.

    1994-01-01

    The degradation products of tetraalkyllead compounds used as antiknock additives are unique indicators of automotive environmental pollution by lead. Recent dramatic improvements in species-specific ultrasensitive analytical procedures enabled the identification and quantification of organolead compounds in ancient Greenland snow which is considered as the archives of northern hemispheric pollution records. Organolead species determined in fresh and ancient polar snow demonstrate unambiguously the global range of petrol-related pollution not only with ionic Pb 2+ but also with more toxic metalloorganic compounds. (authors). 9 refs., 5 figs

  16. Quantifying forest mortality with the remote sensing of snow

    Science.gov (United States)

    Baker, Emily Hewitt

    Greenhouse gas emissions have altered global climate significantly, increasing the frequency of drought, fire, and pest-related mortality in forests across the western United States, with increasing area affected each year. Associated changes in forests are of great concern for the public, land managers, and the broader scientific community. These increased stresses have resulted in a widespread, spatially heterogeneous decline of forest canopies, which in turn exerts strong controls on the accumulation and melt of the snowpack, and changes forest-atmosphere exchanges of carbon, water, and energy. Most satellite-based retrievals of summer-season forest data are insufficient to quantify canopy, as opposed to the combination of canopy and undergrowth, since the signals of the two types of vegetation greenness have proven persistently difficult to distinguish. To overcome this issue, this research develops a method to quantify forest canopy cover using winter-season fractional snow covered area (FSCA) data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) snow covered area and grain size (MODSCAG) algorithm. In areas where the ground surface and undergrowth are completely snow-covered, a pixel comprises only forest canopy and snow. Following a snowfall event, FSCA initially rises, as snow is intercepted in the canopy, and then falls, as snow unloads. A select set of local minima in a winter F SCA timeseries form a threshold where canopy is snow-free, but forest understory is snow-covered. This serves as a spatially-explicit measurement of forest canopy, and viewable gap fraction (VGF) on a yearly basis. Using this method, we determine that MODIS-observed VGF is significantly correlated with an independent product of yearly crown mortality derived from spectral analysis of Landsat imagery at 25 high-mortality sites in northern Colorado. (r =0.96 +/-0.03, p =0.03). Additionally, we determine the lag timing between green-stage tree mortality and

  17. Social Representations of Intelligence

    Directory of Open Access Journals (Sweden)

    Elena Zubieta

    2016-02-01

    Full Text Available The article stresses the relationship between Explicit and Implicit theories of Intelligence. Following the line of common sense epistemology and the theory of Social Representations, a study was carried out in order to analyze naive’s explanations about Intelligence Definitions. Based on Mugny & Carugati (1989 research, a self-administered questionnaire was designed and filled in by 286 subjects. Results are congruent with the main hyphotesis postulated: A general overlap between explicit and implicit theories showed up. According to the results Intelligence appears as both, a social attribute related to social adaptation and as a concept defined in relation with contextual variables similar to expert’s current discourses. Nevertheless, conceptions based on “gifted ideology” still are present stressing the main axes of Intelligence debate: biological and sociological determinism. In the same sense, unfamiliarity and social identity are reaffirmed as organizing principles of social representation. The distance with the object -measured as the belief in intelligence differences as a solve/non solve problem- and the level of implication with the topic -teachers/no teachers- appear as discriminating elements at the moment of supporting specific dimensions. 

  18. Reconstructed North American, Eurasian, and Northern Hemisphere Snow Cover Extent, 1915-1997

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains time series of monthly snow cover extent (SCE) for North America, Eurasia, and the Northern Hemisphere from 1915 to 1997, based on snow cover...

  19. Measurements of Air and Snow Photochemical Species at WAIS Divide, Antarctica, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains atmospheric mixing ratios of nitric oxide, ozone, hydrogen peroxide, methylhydroperoxide, and concentrations in surface snow and in snow pits...

  20. A Snow Density Dataset for Improving Surface Boundary Conditions in Greenland Ice Sheet Firn Modeling

    DEFF Research Database (Denmark)

    S. Fausto, Robert; E. Box, Jason; Vandecrux, Baptiste Robert Marcel

    2018-01-01

    The surface snow density of glaciers and ice sheets is of fundamental importance in converting volume to mass in both altimetry and surface mass balance studies, yet it is often poorly constrained. Site-specific surface snow densities are typically derived from empirical relations based...... on temperature and wind speed. These parameterizations commonly calculate the average density of the top meter of snow, thereby systematically overestimating snow density at the actual surface. Therefore, constraining surface snow density to the top 0.1 m can improve boundary conditions in high-resolution firn......-evolution modeling. We have compiled an extensive dataset of 200 point measurements of surface snow density from firn cores and snow pits on the Greenland ice sheet. We find that surface snow density within 0.1 m of the surface has an average value of 315 kg m−3 with a standard deviation of 44 kg m−3, and has...

  1. 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

    Science.gov (United States)

    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

  2. Modelling traffic flows with intelligent cars and intelligent roads

    NARCIS (Netherlands)

    van Arem, Bart; Tampere, Chris M.J.; Malone, Kerry

    2003-01-01

    This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed

  3. Intelligence analysis – the royal discipline of Competitive Intelligence

    Directory of Open Access Journals (Sweden)

    František Bartes

    2011-01-01

    Full Text Available The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in business practice, is the “forecasting of the future”. That is forecasting about the future, which forms the basis for strategic decisions made by the company’s top management. To implement that requirement in corporate practice, the author perceives Competitive Intelligence as a systemic application discipline. This approach allows him to propose a “Work Plan” for Competitive Intelligence as a fundamental standardized document to steer Competitive Intelligence team activities. The author divides the Competitive Intelligence team work plan into five basic parts. Those parts are derived from the five-stage model of the intelligence cycle, which, in the author’s opinion, is more appropriate for complicated cases of Competitive Intelligence.

  4. Casting of 3-dimensional footwear prints in snow with foam blocks.

    Science.gov (United States)

    Petraco, Nicholas; Sherman, Hal; Dumitra, Aurora; Roberts, Marcel

    2016-06-01

    Commercially available foam blocks are presented as an alternative material for the casting and preservation of 3-dimensional footwear impressions located in snow. The method generates highly detailed foam casts of questioned footwear impressions. These casts can be compared to the known outsole standards made from the suspects' footwear. Modification of the commercially available foam casting blocks is simple and fast. The foam block is removed and a piece of cardboard is secured to one side of the block with painter's masking tape. The prepared foam block is then placed back into its original box, marked appropriately, closed and stored until needed. When required the foam block is carefully removed from its storage box and gently placed, foam side down, over the questioned footwear impression. Next, the crime scene technician's hands are placed on top of the cardboard and pressure is gently applied by firmly pressing down onto the impression. The foam cast is removed, dried and placed back into its original container and sealed. The resulting 3D impressions can be directly compared to the outsole of known suspected item(s) of footwear. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. The Literature of Competitive Intelligence.

    Science.gov (United States)

    Walker, Thomas D.

    1994-01-01

    Describes competitive intelligence (CI) literature in terms of its location, quantity, authorship, length, and problems of bibliographic access. Highlights include subject access; competitive intelligence research; espionage and security; monographs; and journals. (21 references) (LRW)

  6. Application of radar polarimetry techniques for retrieval snow and rain characteristics in remote sensing

    Directory of Open Access Journals (Sweden)

    M. Darvishi

    2013-09-01

    Full Text Available The presence of snow cover has significant impacts on the both global and regional climate and water balance on earth. The accurate estimation of snow cover area can be used for forecasting runoff due to snow melt and output of hydroelectric power. With development of remote sensing techniques at different scopes in earth science, enormous algorithms for retrieval hydrometeor parameters have been developed. Some of these algorithms are used to provide snow cover map such as NLR with AVHRR/MODIS sensor for Norway, Finnish with AVHRR sensor for Finland and NASA with MODIS sensor for global maps. Monitoring snow cover at different parts of spectral electromagnetic is detectable (visible, near and thermal infrared, passive and active microwave. Recently, specific capabilities of active microwave remote sensing such as snow extent map, snow depth, snow water equivalent (SWE, snow state (wet/dry and discrimination between rain and snow region were given a strong impetus for using this technology in snow monitoring, hydrology, climatology, avalanche research and etc. This paper evaluates the potentials and feasibility of polarimetric ground microwave measurements of snow in active remote sensing field. We will consider the behavior co- and cross-polarized backscattering coefficients of snowpack response with polarimetric scatterometer in Ku and L band at the different incident angles. Then we will show how to retrieve snow cover depth, snow permittivity and density parameters at the local scale with ground-based SAR (GB-SAR. Finally, for the sake of remarkable significant the transition region between rain and snow; the variables role of horizontal reflectivity (ZHH and differential reflectivity (ZDR in delineation boundary between snow and rain and some others important variables at polarimetric weather radar are presented.

  7. Variability in snow cover phenology in China from 1952 to 2010

    OpenAIRE

    C. Q. Ke; X. C. Li; H. Xie; X. Liu; C. Kou

    2015-01-01

    Daily snow observation data from 672 stations, particularly the 352 stations with over ten annual mean snow cover days (SCD), during 1952–2010 in China, are used in this study. We first examine spatiotemporal variations and trends of SCD, snow cover onset date (SCOD), and snow cover end date (SCED). We then investigate SCD relationships with number of days with temperature below 0 °C (TBZD), mean air temperature (MAT), and Arctic Oscillation (AO) index, the ...

  8. Impacts of Synoptic Weather Patterns on Snow Albedo at Sites in New England

    Science.gov (United States)

    Adolph, A. C.; Albert, M. R.; Lazarcik, J.; Dibb, J. E.; Amante, J.; Price, A. N.

    2015-12-01

    Winter snow in the northeastern United States has changed over the last several decades, resulting in shallower snow packs, fewer days of snow cover and increasing precipitation falling as rain in the winter. In addition to these changes which cause reductions in surface albedo, increasing winter temperatures also lead to more rapid snow grain growth, resulting in decreased snow reflectivity. We present in-situ measurements and analyses to test the sensitivity of seasonal snow albedo to varying weather conditions at sites in New England. In particular, we investigate the impact of temperature on snow albedo through melt and grain growth, the impact of precipitation event frequency on albedo through snow "freshening," and the impact of storm path on snow structure and snow albedo. Over three winter seasons between 2013 and 2015, in-situ snow characterization measurements were made at three non-forested sites across New Hampshire. These near-daily measurements include spectrally resolved albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density and local meteorological parameters. Combining this information with storm tracks derived from HYSPLIT modeling, we quantify the current sensitivity of northeastern US snow albedo to temperature as well as precipitation type, frequency and path. Our analysis shows that southerly winter storms result in snow with a significantly lower albedo than storms which come from across the continental US or the Atlantic Ocean. Interannual variability in temperature and statewide spatial variability in snowfall rates at our sites show the relative importance of snowfall amount and temperatures in albedo evolution over the course of the winter.

  9. Improving Snow Modeling by Assimilating Observational Data Collected by Citizen Scientists

    Science.gov (United States)

    Crumley, R. L.; Hill, D. F.; Arendt, A. A.; Wikstrom Jones, K.; Wolken, G. J.; Setiawan, L.

    2017-12-01

    Modeling seasonal snow pack in alpine environments includes a multiplicity of challenges caused by a lack of spatially extensive and temporally continuous observational datasets. This is partially due to the difficulty of collecting measurements in harsh, remote environments where extreme gradients in topography exist, accompanied by large model domains and inclement weather. Engaging snow enthusiasts, snow professionals, and community members to participate in the process of data collection may address some of these challenges. In this study, we use SnowModel to estimate seasonal snow water equivalence (SWE) in the Thompson Pass region of Alaska while incorporating snow depth measurements collected by citizen scientists. We develop a modeling approach to assimilate hundreds of snow depth measurements from participants in the Community Snow Observations (CSO) project (www.communitysnowobs.org). The CSO project includes a mobile application where participants record and submit geo-located snow depth measurements while working and recreating in the study area. These snow depth measurements are randomly located within the model grid at irregular time intervals over the span of four months in the 2017 water year. This snow depth observation dataset is converted into a SWE dataset by employing an empirically-based, bulk density and SWE estimation method. We then assimilate this data using SnowAssim, a sub-model within SnowModel, to constrain the SWE output by the observed data. Multiple model runs are designed to represent an array of output scenarios during the assimilation process. An effort to present model output uncertainties is included, as well as quantification of the pre- and post-assimilation divergence in modeled SWE. Early results reveal pre-assimilation SWE estimations are consistently greater than the post-assimilation estimations, and the magnitude of divergence increases throughout the snow pack evolution period. This research has implications beyond the

  10. The chemical composition of the snow in urban environment in the Far North

    OpenAIRE

    Saltan N.V.; Shlapak E.P.; Zhirov V.K.; Gontar O.B.; Svyatkovskaya E.A.

    2015-01-01

    The paper presents experimental data of the chemical composition of snow cover of squares and streets in the polar cities. It has been revealed that the natural ratio of cations and anions is modified in the snow. Comparative assessment of the levels of concentration of metals in the snow showed higher values in squares than on the streets. It has been shown that the main share in the pollution of snow by heavy metals belongs to the dust of anthropogenic origin

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

    Science.gov (United States)

    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.

  12. Artificial intelligence in nanotechnology.

    Science.gov (United States)

    Sacha, G M; Varona, P

    2013-11-15

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  13. Artificial intelligence in nanotechnology

    Science.gov (United States)

    Sacha, G. M.; Varona, P.

    2013-11-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  14. Intelligent environmental data warehouse

    International Nuclear Information System (INIS)

    Ekechukwu, B.

    1998-01-01

    Making quick and effective decisions in environment management are based on multiple and complex parameters, a data warehouse is a powerful tool for the over all management of massive environmental information. Selecting the right data from a warehouse is an important factor consideration for end-users. This paper proposed an intelligent environmental data warehouse system. It consists of data warehouse to feed an environmental researchers and managers with desire environmental information needs to their research studies and decision in form of geometric and attribute data for study area, and a metadata for the other sources of environmental information. In addition, the proposed intelligent search engine works according to a set of rule, which enables the system to be aware of the environmental data wanted by the end-user. The system development process passes through four stages. These are data preparation, warehouse development, intelligent engine development and internet platform system development. (author)

  15. Intelligent control systems 1990

    International Nuclear Information System (INIS)

    Shoureshi, R.

    1991-01-01

    The field of artificial intelligence (Al) has generated many useful ideas and techniques that can be integrated into the design of control systems. It is believed and, for special cases, has been demonstrated, that integration of Al into control systems would provide the necessary tools for solving many of the complex problems that present control techniques and Al algorithms are unable to do, individually. However, this integration requires the development of basic understanding and new fundamentals to provide scientific bases for achievement of its potential. This book presents an overview of some of the latest research studies in the area of intelligent control systems. These papers present techniques for formulation of intelligent control, and development of the rule-based control systems. Papers present applications of control systems in nuclear power plants and HVAC systems

  16. Artificial Intelligence in Cardiology.

    Science.gov (United States)

    Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

    2018-06-12

    Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Artificial intelligence in nanotechnology

    International Nuclear Information System (INIS)

    Sacha, G M; Varona, P

    2013-01-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines. (topical review)

  18. Understanding the Globalization of Intelligence

    DEFF Research Database (Denmark)

    Svendsen, Adam David Morgan

    "This book provides an introduction to the complexities of contemporary Western Intelligence and its dynamics during an era of globalization. Towards an understanding of the globalization of intelligence process, Svendsen focuses on the secretive phenomenon of international or foreign intelligence...... cooperation ('liaison'), as it occurs in both theory and practice. Reflecting a complex coexistence plurality of several different and overlapping concepts in action, the challenging process of the globalization of intelligence emerges as essential for complex issue management purposes during a globalized era...

  19. Artificial Intelligence and Economic Theories

    OpenAIRE

    Marwala, Tshilidzi; Hurwitz, Evan

    2017-01-01

    The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence such as the swarming of birds, the working of the brain and the pathfinding of the ants. These techniques have impact on economic theories. This book studies the impact of artificial intelligence on economic theories, a subject that has not been extensively studied. The theories that...

  20. Collective Intelligence in Crises

    DEFF Research Database (Denmark)

    Büscher, Monika; Liegl, Michael; Thomas, Vanessa

    2014-01-01

    New practices of social media use in emergency response seem to enable broader `situation awareness' and new forms of crisis management. The scale and speed of innovation in this field engenders disruptive innovation or a reordering of social, political, economic practices of emergency response....... By examining these dynamics with the concept of social collective intelligence, important opportunities and challenges can be examined. In this chapter we focus on socio-technical aspects of social collective intelligence in crises to discuss positive and negative frictions and avenues for innovation...