958 resultados para electrostatic precipitation


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Some of the trends and characteristics of the isotopic composition oh precipitation in tropical stations are discussed. Stations in small Pacific islands show a variation with latitude, with lower 8-values between 15°N and 1S°S and higher values at higher. Inland stations are depleted in heavy isotopes with respect to coastal stations but sometimes this continental effect is rather complex, as f,or instance in África. Mean monthly 8-values show a remarkable correlation with the amount of precipitation, but the slope variations do not show a clear dependence on the mean long term 8-value,as should be expected theoretically. In Southern American stations the seasonal variations of the meanmonthly 5-values are correlated and they are greater in inland stations due to con-tinentaly. The possible effects of recycling of water vapour by evapotranspiration are also discussed.

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During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.

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The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.

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[Excerpt] Hydroxyapatite Ca10(PO4)6(OH)2 (HAp) has been widely used for biomedical purposes because of its exceptional biocompatibility, bioactivity and osteoconductivity [1]. As these properties are directly related to HAp particles characteristics (size, morphology and purity), a very good control of the reaction conditions is required to obtain particles with the desired properties. Usually, HAp is synthesized by wet chemical precipitation in stirred tank batch reactors that often lead to inconsistencies in product specifications due to their low mixing efficiency [2]. (...)

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Supplementary data associated with this article can be found, in the online version, at: http://dx.doi.org/10.1016/j.cej.2016.03.148.

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Nanopartikel, BaSO4, Mikroemulsion, Fällung, Modellierung

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Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2012

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The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

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A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .

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Gumbel analyses were carried out on rainfall time-series at 151 locations in Switzerland for 4 different periods of 30 years in order to estimate daily extreme precipitation for a return period of 100 years. Those estimations were compared with maximal daily values measured during the last 100 years (1911-2010) to test the efficiency of these analyses. This comparison shows that these analyses provide good results for 50 to 60% locations in this country from rainfall time-series 1961-1990 and 1980-2010. On the other hand, daily precipitation with a return period of 100 years is underestimated at most locations from time-series 1931-1960 and especially 1911-1940. Such underestimation results from the increase of maximal daily precipitation recorded from 1911 to 2010 at 90% locations in Switzerland.

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An adaptation technique based on the synoptic atmospheric circulation to forecast local precipitation, namely the analogue method, has been implemented for the western Swiss Alps. During the calibration procedure, relevance maps were established for the geopotential height data. These maps highlight the locations were the synoptic circulation was found of interest for the precipitation forecasting at two rain gauge stations (Binn and Les Marécottes) that are located both in the alpine Rhône catchment, at a distance of about 100 km from each other. These two stations are sensitive to different atmospheric circulations. We have observed that the most relevant data for the analogue method can be found where specific atmospheric circulation patterns appear concomitantly with heavy precipitation events. Those skilled regions are coherent with the atmospheric flows illustrated, for example, by means of the back trajectories of air masses. Indeed, the circulation recurrently diverges from the climatology during days with strong precipitation on the southern part of the alpine Rhône catchment. We have found that for over 152 days with precipitation amount above 50 mm at the Binn station, only 3 did not show a trajectory of a southerly flow, meaning that such a circulation was present for 98% of the events. Time evolution of the relevance maps confirms that the atmospheric circulation variables have significantly better forecasting skills close to the precipitation period, and that it seems pointless for the analogue method to consider circulation information days before a precipitation event as a primary predictor. Even though the occurrence of some critical circulation patterns leading to heavy precipitation events can be detected by precursors at remote locations and 1 week ahead (Grazzini, 2007; Martius et al., 2008), time extrapolation by the analogue method seems to be rather poor. This would suggest, in accordance with previous studies (Obled et al., 2002; Bontron and Obled, 2005), that time extrapolation should be done by the Global Circulation Model, which can process atmospheric variables that can be used by the adaptation method.

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This paper describes a maximum likelihood method using historical weather data to estimate a parametric model of daily precipitation and maximum and minimum air temperatures. Parameter estimates are reported for Brookings, SD, and Boone, IA, to illustrate the procedure. The use of this parametric model to generate stochastic time series of daily weather is then summarized. A soil temperature model is described that determines daily average, maximum, and minimum soil temperatures based on air temperatures and precipitation, following a lagged process due to soil heat storage and other factors.

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Abstract: Microbial mats very efficiently cycle elements, such as C, 0, N, S and H, which makes them key players of redox processes at the biosphere-lithosphere interface. They are characterized by high metabolic activities and high turnover rates (production and consumption) of biomass, which mainly consists of cell material and of extracellular organic matter (EOM). The EOM forms a matrix, embedding the microbial cells and fulfilling various functions within the microbial mat, including: mat attachment to surfaces; creation of micro-domains within the mat; physical stabilization under hy- drodynamic stress and the protection of the cells in multiple other stress conditions. EOM mainly consists of polysaccharides, amino acids, and a variety of chemical func-tional groups {e.g., -C00H, - SH -OH). These groups strongly bind cations such as Ca2+ and Mg2+ and thus exert a strong control on carbonate mineral formation within the microbial mat. A feedback mechanism between community metabolisms, their prod¬ucts, and the surrounding physicochemical microenvironment thus influences the de¬gree of carbonate saturation favoring either carbonate precipitation or dissolution. We investigated the driving forces and mechanisms of microbialite formation in the Sari ne River, FR, Switzerland, the hypersaline lake, Big Pond, Bahamas and in labo¬ratory experiments. The two fundamentally different natural systems allowed us to compare the geochemical conditions and microbial metabolisms, necessary for car¬bonate formation in microbial mats. Although carbonates are oversaturated in both environments, precipitation does not occur on physicochemical substrates (i.e. out¬side the microbial mats). In the Sarine a high crystal nucleation threshold exceeds the carbonate saturation, despite the high carbonate alkalinity in the water column. Cyanobacterial photosynthesis strongly locally enhances the carbonate alkalinity, whereas the EOM attract and immobilize calcium, which increases the saturation state and finally leads to carbonate precipitation within the EOM (in this case the cyanobacterial sheath) as nucleation template. In Big Pond, the presence of calcium- chelating anions (i.e. sulfate) and EOM, as well as the presence of magnesium, lowers the calcium activity in the water column and mat, and thus inhibits carbonate pre¬cipitation. Coupled with other heterotrophic metabolisms, sulfate reduction uses the EOM as carbon source, degrading it. The resulting EOM consumption creates alkalin¬ity, releases calcium and consumes sulfate in mat-micro domains, which leads to the formation of carbonate layers at the top of the microbial mat. Résumé: Interface biosphère/lithosphère: médiation microbienne de la précipitation de CaC03 dans des environnements en eaux douces et hypersalines Les tapis microbiens engendrent une circulation très efficace des éléments, tels que C, 0, N, S et H, ce qui en fait des acteurs clé pour les processus d'oxydoréduction à l'inter¬face biosphère-lithosphère. Ils sont caractérisés par des taux élevés d'activité méta¬bolique, ainsi que par la production et la consommation de biomasse, principalement constituée de cellules microbiennes et de matière organique extracellulaire (MOE). Dans un tapis microbien, les cellules microbiennes sont enveloppées par une matrice de MOE qui a différentes fonctions dont l'attachement du tapis aux surfaces, la créa¬tion de micro-domaines dans le tapis, la stabilisation physique en situation de stress hydrodynamique, et la protection des cellules dans de multiples autres conditions de stress. La MOE se compose principalement de polysaccharides, d'acides aminés, et d'une variété de groupes fonctionnels chimiques (par exemple, COOH, -SH et -OH). Ces groupes se lient fortement aux cations, tels que Ca2+ et Mg2+, et exercent ainsi un contrôle fort sur la formation de CaC03 dans le tapis microbien. Un mécanisme de rétroaction, entre les métabolismes de la communauté microbienne, leurs produits, et le microenvironnement physico-chimique, influence le degré de saturation de car¬bonate, favorisant soit leur précipitation, soit leur dissolution. Nous avons étudié le moteur et les mécanismes de minéralisation dans des tapis de la Sarine, FR, Suisse et du lac hypersalin, Big Pond, aux Bahamas, ainsi que durant des expériences en laboratoire. Les deux systèmes naturels, fondamentalement dif¬férents, nous ont permis de comparer les conditions géochimiques et les métabolis¬mes nécessaires à la formation des carbonates dans des tapis microbiens. Bien que les carbonates soient sursaturés dans les deux environnements, la précipitation ne se produit pas sur des substrats physico-chimiques (en dehors du tapis microbien). Dans la Sarine, malgré un taux d'alcalinité élevé, les valeurs de seuil pour la nucléa- tion de carbonates sont plus hautes que la saturation du carbonate. La photosynthèse cyanobactérienne augmente localement l'alcalinité, alors que la MOE attire et immo¬bilise le calcium, ce qui augmente l'état de saturation et conduit finalement à la pré¬cipitation des carbonates, en utilisant la MOE comme substrat de nucléation. À Big Pond, la présence de chélateurs de calcium, notamment les anions (p.ex. le sulfate) et la MOE, ainsi que la présence de magnésium, réduit l'activité du calcium et inhibe en conséquence la précipitation des carbonates. Couplée avec d'autres métabolismes hétérotrophes, la réduction des sulfates utilise la MOE comme source de carbone, en la dégradant. Cette consommation de MOE crée l'alcalinité, consomme des sulfates et libère du calcium dans des micro-domaines, conduisant à la formation de couches de carbonates dans le haut du tapis microbien.

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Report produced by the The Department of Agriculture and Land Stewardship, Climatology Bureau.