313 resultados para Enunciative heterogeneities
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In the Radiative Atmospheric Divergence Using ARM Mobile Facility GERB and AMMA Stations (RADAGAST) project we calculate the divergence of radiative flux across the atmosphere by comparing fluxes measured at each end of an atmospheric column above Niamey, in the African Sahel region. The combination of broadband flux measurements from geostationary orbit and the deployment for over 12 months of a comprehensive suite of active and passive instrumentation at the surface eliminates a number of sampling issues that could otherwise affect divergence calculations of this sort. However, one sampling issue that challenges the project is the fact that the surface flux data are essentially measurements made at a point, while the top-of-atmosphere values are taken over a solid angle that corresponds to an area at the surface of some 2500 km2. Variability of cloud cover and aerosol loading in the atmosphere mean that the downwelling fluxes, even when averaged over a day, will not be an exact match to the area-averaged value over that larger area, although we might expect that it is an unbiased estimate thereof. The heterogeneity of the surface, for example, fixed variations in albedo, further means that there is a likely systematic difference in the corresponding upwelling fluxes. In this paper we characterize and quantify this spatial sampling problem. We bound the root-mean-square error in the downwelling fluxes by exploiting a second set of surface flux measurements from a site that was run in parallel with the main deployment. The differences in the two sets of fluxes lead us to an upper bound to the sampling uncertainty, and their correlation leads to another which is probably optimistic as it requires certain other conditions to be met. For the upwelling fluxes we use data products from a number of satellite instruments to characterize the relevant heterogeneities and so estimate the systematic effects that arise from the flux measurements having to be taken at a single point. The sampling uncertainties vary with the season, being higher during the monsoon period. We find that the sampling errors for the daily average flux are small for the shortwave irradiance, generally less than 5 W m−2, under relatively clear skies, but these increase to about 10 W m−2 during the monsoon. For the upwelling fluxes, again taking daily averages, systematic errors are of order 10 W m−2 as a result of albedo variability. The uncertainty on the longwave component of the surface radiation budget is smaller than that on the shortwave component, in all conditions, but a bias of 4 W m−2 is calculated to exist in the surface leaving longwave flux.
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The difference between cirrus emissivities at 8 and 11 μm is sensitive to the mean effective ice crystal size of the cirrus cloud, De. By using single scattering properties of ice crystals shaped as planar polycrystals, diameters of up to about 70 μm can be retrieved, instead of up to 45 μm assuming spheres or hexagonal columns. The method described in this article is used for a global determination of mean effective ice crystal sizes of cirrus clouds from TOVS satellite observations. A sensitivity study of the De retrieval to uncertainties in hypotheses on ice crystal shape, size distributions, and temperature profiles, as well as in vertical and horizontal cloud heterogeneities shows that uncertainties can be as large as 30%. However, the TOVS data set is one of few data sets which provides global and long-term coverage. Having analyzed the years 1987–1991, it was found that measured effective ice crystal diameters De are stable from year to year. For 1990 a global median De of 53.5 μm was determined. Averages distinguishing ocean/land, season, and latitude lie between 23 μm in winter over Northern Hemisphere midlatitude land and 64 μm in the tropics. In general, larger Des are found in regions with higher atmospheric water vapor and for cirrus with a smaller effective emissivity.
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An extensive off-line evaluation of the Noah/Single Layer Urban Canopy Model (Noah/SLUCM) urban land-surface model is presented using data from 15 sites to assess (1) the ability of the scheme to reproduce the surface energy balance observed in a range of urban environments, including seasonal changes, and (2) the impact of increasing complexity of input parameter information. Model performance is found to be most dependent on representation of vegetated surface area cover; refinement of other parameter values leads to smaller improvements. Model biases in net all-wave radiation and trade-offs between turbulent heat fluxes are highlighted using an optimization algorithm. Here we use the Urban Zones to characterize Energy partitioning (UZE) as the basis to assign default SLUCM parameter values. A methodology (FRAISE) to assign sites (or areas) to one of these categories based on surface characteristics is evaluated. Using three urban sites from the Basel Urban Boundary Layer Experiment (BUBBLE) dataset, an independent evaluation of the model performance with the parameter values representative of each class is performed. The scheme copes well with both seasonal changes in the surface characteristics and intra-urban heterogeneities in energy flux partitioning, with RMSE performance comparable to similar state-of-the-art models for all fluxes, sites and seasons. The potential of the methodology for high-resolution atmospheric modelling application using the Weather Research and Forecasting (WRF) model is highlighted. This analysis supports the recommendations that (1) three classes are appropriate to characterize the urban environment, and (2) that the parameter values identified should be adopted as default values in WRF.
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This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR). Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.
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Highly heterogeneous mountain snow distributions strongly affect soil moisture patterns; local ecology; and, ultimately, the timing, magnitude, and chemistry of stream runoff. Capturing these vital heterogeneities in a physically based distributed snow model requires appropriately scaled model structures. This work looks at how model scale—particularly the resolutions at which the forcing processes are represented—affects simulated snow distributions and melt. The research area is in the Reynolds Creek Experimental Watershed in southwestern Idaho. In this region, where there is a negative correlation between snow accumulation and melt rates, overall scale degradation pushed simulated melt to earlier in the season. The processes mainly responsible for snow distribution heterogeneity in this region—wind speed, wind-affected snow accumulations, thermal radiation, and solar radiation—were also independently rescaled to test process-specific spatiotemporal sensitivities. It was found that in order to accurately simulate snowmelt in this catchment, the snow cover needed to be resolved to 100 m. Wind and wind-affected precipitation—the primary influence on snow distribution—required similar resolution. Thermal radiation scaled with the vegetation structure (~100 m), while solar radiation was adequately modeled with 100–250-m resolution. Spatiotemporal sensitivities to model scale were found that allowed for further reductions in computational costs through the winter months with limited losses in accuracy. It was also shown that these modeling-based scale breaks could be associated with physiographic and vegetation structures to aid a priori modeling decisions.
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Using digitized images of the three-dimensional, branching structures for root systems of bean seedlings, together with analytical and numerical methods that map a common susceptible-infected- recovered (`SIR`) epidemiological model onto the bond percolation problem, we show how the spatially correlated branching structures of plant roots affect transmission efficiencies, and hence the invasion criterion, for a soil-borne pathogen as it spreads through ensembles of morphologically complex hosts. We conclude that the inherent heterogeneities in transmissibilities arising from correlations in the degrees of overlap between neighbouring plants render a population of root systems less susceptible to epidemic invasion than a corresponding homogeneous system. Several components of morphological complexity are analysed that contribute to disorder and heterogeneities in the transmissibility of infection. Anisotropy in root shape is shown to increase resilience to epidemic invasion, while increasing the degree of branching enhances the spread of epidemics in the population of roots. Some extension of the methods for other epidemiological systems are discussed.
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We design and investigate a sequential discontinuous Galerkin method to approximate two-phase immiscible incompressible flows in heterogeneous porous media with discontinuous capillary pressures. The nonlinear interface conditions are enforced weakly through an adequate design of the penalties on interelement jumps of the pressure and the saturation. An accurate reconstruction of the total velocity is considered in the Raviart-Thomas(-Nedelec) finite element spaces, together with diffusivity-dependent weighted averages to cope with degeneracies in the saturation equation and with media heterogeneities. The proposed method is assessed on one-dimensional test cases exhibiting rough solutions, degeneracies, and capillary barriers. Stable and accurate solutions are obtained without limiters. (C) 2010 Elsevier B.V. All rights reserved.
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In this paper we investiga te the impact of initial wealth anel impatience heterogeneities, as wcll as differential access to financia! markets on povcrty anel inequality, anel cvaluate some mechanisms that could be used to alleviate situations in which these two issues are alarming. To address our qucstion we develop a dynamic stochastic general cquilibrium modo! of educational anel savings choicc with heterogeneous agents, where individuais differ in their initial wealth anel in their discount factor. We find that, in the long run, more patient households tend to be wealthier anel more educated. However, our baseline model is not able to give as much skewness to our income distribution as it is rcquircd. We then propose a novel returns structure based on empírica! observation of heterogeneous returns to different portfolios. This modification solves our previous problem, evidencing the importance of the changes made in explaining the existing levels of inequality. Finally, we introducc two kinds of cash transfers programs- one in which receiving thc benefit is conditional on educating the household's youngster (CCTS) anel one frec of conditionalities (CTS) - in order to evaluate the impact of these programs on the variables of concern1 Wc fine! that both policies have similar qualitativo rcsults. Quantitatively, howcvcr, the CCTS outperforms its unconclitional version in all fielcls analyzecl, revealing itself to be a preferable policy.
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MEDEIROS, A. L.; VANTI, Nadia. Vannevar Bush e as matrizes discursivas de As we may think: por uma possível história da Ciência da Informação. Informação & sociedade:Estudos. João Pessoa, v. 21, p. 31-39, 2011
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Due to reservoirs complexity and significantly large reserves, heavy oil recovery has become one of the major oil industry challenges. Thus, thermal methods have been widely used as a strategic method to improve heavy oil recovery. These methods improve oil displacement through viscosity reduction, enabling oil production in fields which are not considered commercial by conventional recovery methods. Among the thermal processes, steam flooding is the most used today. One consequence in this process is gravity segregation, given by difference between reservoir and injected fluids density. This phenomenon may be influenced by the presence of reservoir heterogeneities. Since most of the studies are carried out in homogeneous reservoirs, more detailed studies of heterogeneities effects in the reservoirs during steam flooding are necessary, since most oil reservoirs are heterogeneous. This paper presents a study of reservoir heterogeneities and their influence in gravity segregation during steam flooding process. In this study some heterogeneous reservoirs with physical characteristics similar those found in the Brazilian Northeast Basin were analyzed. To carry out the simulations, it was used the commercial simulator STARS by CMG (Computer Modeling Group) - version 2007.11. Heterogeneities were modeled with lower permeability layers. Results showed that the presence of low permeability barriers can improve the oil recovery, and reduce the effects of gravity segregation, depending on the location of heterogeneities. The presence of these barriers have also increased the recovered fraction even with the reduction of injected steam rate
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Nearly 3 x 1011 m3 of medium and light oils will remain in reservoirs worldwide after conventional recovery methods have been exhausted and much of this volume would be recovered by Enhanced Oil Recovery (EOR) methods. The in-situ combustion (ISC) is an EOR method in which an oxygen-containing gas is injected into a reservoir where it reacts with the crude oil to create a high-temperature combustion front that is propagated through the reservoir. The High Pressure Air Injection (HPAI) method is a particular denomination of the air injection process applied in light oil reservoirs, for which the combustion reactions are dominant between 150 and 300°C and the generation of flue gas is the main factor to the oil displacement. A simulation model of a homogeneous reservoir was built to study, which was initially undergone to primary production, for 3 years, next by a waterflooding process for 21 more years. At this point, with the mature condition established into the reservoir, three variations of this model were selected, according to the recovery factors (RF) reached, for study the in-situ combustion (HPAI) technique. Next to this, a sensitivity analysis on the RF of characteristic operational parameters of the method was carried out: air injection rate per well, oxygen concentration into the injected gas, patterns of air injection and wells perforations configuration. This analysis, for 10 more years of production time, was performed with assistance of the central composite design. The reservoir behavior and the impacts of chemical reactions parameters and of reservoir particularities on the RF were also evaluated. An economic analysis and a study to maximize the RF of the process were also carried out. The simulation runs were performed in the simulator of thermal processes in reservoirs STARS (Steam, Thermal, and Advanced Processes Reservoir Simulator) from CMG (Computer Modelling Group). The results showed the incremental RF were small and the net present value (NPV) is affected by high initial investments to compress the air. It was noticed that the adoption of high oxygen concentration into the injected gas and of the five spot pattern tends to improve the RF, and the wells perforations configuration has more influence with the increase of the oil thickness. Simulated cases relating to the reservoir particularities showed that smaller residual oil saturations to gas lead to greater RF and the presence of heterogeneities results in important variations on the RF and on the production curves
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The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.