405 resultados para Parameterized layouts


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A new model, RothPC-1, is described for the turnover of organic C in the top metre of soil. RothPC-1 is a version of RothC-26.3, an earlier model for the turnover of C in topsoils. In RothPC-1 two extra parameters are used to model turnover in the top metre of soil: one, p, which moves organic C down the profile by an advective process, and the other, s, which slows decomposition with depth. RothPC-1 is parameterized and tested using measurements (described in Part 1, this issue) of total organic C and radiocarbon on soil profiles from the Rothamsted long-term field experiments, collected over a period of more than 100 years. RothPC-1 gives fits to measurements of organic C and radiocarbon in the 0-23, 23-46, 46-69 and 69-92 cm layers of soil that are almost all within (or close to) measurement error in two areas of regenerating woodland (Geescroft and Broadbalk Wildernesses) and an area of cultivated land from the Broadbalk Continuous Wheat Experiment. The fits to old grassland (the Park Grass Experiment) are less close. Two other sites that provide the requisite pre- and post-bomb data are also fitted; a prairie Chernozem from Russia and an annual grassland from California. Roth-PC-1 gives a close fit to measurements of organic C and radiocarbon down the Chernozem profile, provided that allowance is made for soil age; with the annual grassland the fit is acceptable in the upper part of the profile, but not in the clay-rich Bt horizon below. Calculations suggest that treating the top metre of soil as a homogeneous unit will greatly overestimate the effects of global warming in accelerating the decomposition of soil C and hence on the enhanced release of CO2 from soil organic matter; more realistic estimates will be obtained from multi-layer models such as RothPC-1.

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Models of the dynamics of nitrogen in soil (soil-N) can be used to aid the fertilizer management of a crop. The predictions of soil-N models can be validated by comparison with observed data. Validation generally involves calculating non-spatial statistics of the observations and predictions, such as their means, their mean squared-difference, and their correlation. However, when the model predictions are spatially distributed across a landscape the model requires validation with spatial statistics. There are three reasons for this: (i) the model may be more or less successful at reproducing the variance of the observations at different spatial scales; (ii) the correlation of the predictions with the observations may be different at different spatial scales; (iii) the spatial pattern of model error may be informative. In this study we used a model, parameterized with spatially variable input information about the soil, to predict the mineral-N content of soil in an arable field, and compared the results with observed data. We validated the performance of the N model spatially with a linear mixed model of the observations and model predictions, estimated by residual maximum likelihood. This novel approach allowed us to describe the joint variation of the observations and predictions as: (i) independent random variation that occurred at a fine spatial scale; (ii) correlated random variation that occurred at a coarse spatial scale; (iii) systematic variation associated with a spatial trend. The linear mixed model revealed that, in general, the performance of the N model changed depending on the spatial scale of interest. At the scales associated with random variation, the N model underestimated the variance of the observations, and the predictions were correlated poorly with the observations. At the scale of the trend, the predictions and observations shared a common surface. The spatial pattern of the error of the N model suggested that the observations were affected by the local soil condition, but this was not accounted for by the N model. In summary, the N model would be well-suited to field-scale management of soil nitrogen, but suited poorly to management at finer spatial scales. This information was not apparent with a non-spatial validation. (c),2007 Elsevier B.V. All rights reserved.

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An efficient method is described for the approximate calculation of the intensity of multiply scattered lidar returns. It divides the outgoing photons into three populations, representing those that have experienced zero, one, and more than one forward-scattering event. Each population is parameterized at each range gate by its total energy, its spatial variance, the variance of photon direction, and the covariance, of photon direction and position. The result is that for an N-point profile the calculation is O(N-2) efficient and implicitly includes up to N-order scattering, making it ideal for use in iterative retrieval algorithms for which speed is crucial. In contrast, models that explicitly consider each scattering order separately are at best O(N-m/m!) efficient for m-order scattering and often cannot be performed to more than the third or fourth order in retrieval algorithms. For typical cloud profiles and a wide range of lidar fields of view, the new algorithm is as accurate as an explicit calculation truncated at the fifth or sixth order but faster by several orders of magnitude. (C) 2006 Optical Society of America.

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The problem of modeling solar energetic particle (SEP) events is important to both space weather research and forecasting, and yet it has seen relatively little progress. Most important SEP events are associated with coronal mass ejections (CMEs) that drive coronal and interplanetary shocks. These shocks can continuously produce accelerated particles from the ambient medium to well beyond 1 AU. This paper describes an effort to model real SEP events using a Center for Integrated Space weather Modeling (CISM) MHD solar wind simulation including a cone model of CMEs to initiate the related shocks. In addition to providing observation-inspired shock geometry and characteristics, this MHD simulation describes the time-dependent observer field line connections to the shock source. As a first approximation, we assume a shock jump-parameterized source strength and spectrum, and that scatter-free transport occurs outside of the shock source, thus emphasizing the role the shock evolution plays in determining the modeled SEP event profile. Three halo CME events on May 12, 1997, November 4, 1997 and December 13, 2006 are used to test the modeling approach. While challenges arise in the identification and characterization of the shocks in the MHD model results, this approach illustrates the importance to SEP event modeling of globally simulating the underlying heliospheric event. The results also suggest the potential utility of such a model for forcasting and for interpretation of separated multipoint measurements such as those expected from the STEREO mission.

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The objective of this work was to construct a dynamic model of hepatic amino acid metabolism in the lactating dairy cow that could be parameterized using net flow data from in vivo experiments. The model considers 22 amino acids, ammonia, urea, and 13 energetic metabolites, and was parameterized using a steady-state balance model and two in vivo, net flow experiments conducted with mid-lactation dairy cows. Extracellular flows were derived directly from the observed data. An optimization routine was used to derive nine intracellular flows. The resulting dynamic model was found to be stable across a range of inputs suggesting that it can be perturbed and applied to other physiological states. Although nitrogen was generally in balance, leucine was in slight deficit compared to predicted needs for export protein synthesis, suggesting that an alternative source of leucine (e.g. peptides) was utilized. Simulations of varying glucagon concentrations indicated that an additional 5 mol/d of glucose could be synthesized at the reference substrate concentrations and blood flows. The increased glucose production was supported by increased removal from blood of lactate, glutamate, aspartate, alanine, asparagine, and glutamine. As glucose Output increased, ketone body and acetate release increased while CO2 release declined. The pattern of amino acids appearing in hepatic vein blood was affected by changes in amino acid concentration in portal vein blood, portal blood flow rate and glucagon concentration, with methionine and phenylalanine being the most affected of essential amino acids. Experimental evidence is insufficient to determine whether essential amino acids are affected by varying gluconeogenic demands. (C) 2004 Published by Elsevier Ltd.

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The results from three types of study with broilers, namely nitrogen (N) balance, bioassays and growth experiments, provided the data used herein. Sets of data on N balance and protein accretion (bioassay studies) were used to assess the ability of the monomolecular equation to describe the relationship between (i) N balance and amino acid (AA) intake and (ii) protein accretion and AA intake. The model estimated the levels of isoleucine, lysine, valine, threonine, methionine, total sulphur AAs and tryptophan resulting in zero balance to be 58, 59, 80, 96, 23, 85 and 32 mg/kg live weight (LW)/day, respectively. These estimates show good agreement with those obtained in previous studies. For the growth experiments, four models, specifically re-parameterized for analysing energy balance data, were evaluated for their ability to determine crude protein (CP) intake at maintenance and efficiency of utilization of CP intake for producing gain. They were: a straight line, two equations representing diminishing returns behaviour (monomolecular and rectangular hyperbola) and one equation describing smooth sigmoidal behaviour with a fixed point of inflexion (Gompertz). The estimates of CP requirement for maintenance and efficiency of utilization of CP intake for producing gain varied from 5.4 to 5.9 g/kg LW/day and 0.60 to 0.76, respectively, depending on the models.

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Data from six studies with male broilers fed diets covering a wide range of energy and protein were used in the current two analyses. In the first analysis, five models, specifically re-parameterized for analysing energy balance data, were evaluated for their ability to determine metabolizable energy intake at maintenance and efficiency of utilization of metabolizable energy intake for producing gain. In addition to the straight line, two types of functional form were used. They were forms describing (i) diminishing returns behaviour (monomolecular and rectangular hyperbola) and (ii) sigmoidal behaviour with a fixed point of inflection (Gompertz and logistic). These models determined metabolizable energy requirement for maintenance to be in the range 437-573 kJ/kg of body weight/day depending on the model. The values determined for average net energy requirement for body weight gain varied from 7(.)9 to 11(.)2 kJ/g of body weight. These values show good agreement with previous studies. In the second analysis, three types of function were assessed as candidates for describing the relationship between body weight and cumulative metabolizable energy intake. The functions used were: (a) monomolecular (diminishing returns behaviour), (b) Gompertz (smooth sigmoidal behaviour with a fixed point of inflection) and (c) Lopez, France and Richards (diminishing returns and sigmoidal behaviour with a variable point of inflection). The results of this analysis demonstrated that equations capable of mimicking the law of diminishing returns describe accurately the relationship between body weight and cumulative metabolizable energy intake in broilers.

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The suitability of models specifically re-parameterized for analyzing energy balance data relating metabolizable energy intake to growth rate has recently been investigated in male broilers. In this study, the more adequate of those models was applied to growing turkeys to provide estimates of their energy needs for maintenance and growth. Three functional forms were used. They were: two equations representing diminishing returns behaviour (monomolecular and rectangular hyperbola); and one equation describing smooth sigmoidal behaviour with a fixed point of inflexion (Gompertz). The models estimated the metabolizable energy requirement for maintenance in turkeys to be 359-415 kJ/kg of live-weight/day. The predicted values of average net energy requirement for producing 1 g of gain in live-weight, between 1 and 4 times maintenance, varied from 8.7 to 10.9 kJ. These results and those previously reported for broilers are a basis for accepting the general validity of these models.

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Evolutionary theory predicts that individuals, in order to increase their relative fitness, can evolve behaviours that are detrimental for the group or population. This mismatch is particularly visible in social organisms. Despite its potential to affect the population dynamics of social animals, this principle has not yet been applied to real-life conservation. Social group structure has been argued to stabilize population dynamics due to the buffering effects of nonreproducing subordinates. However, competition for breeding positions in such species can also interfere with the reproduction of breeding pairs. Seychelles magpie robins, Copsychus sechellarum, live in social groups where subordinate individuals do not breed. Analysis of long-term individual-based data and short-term behavioural observations show that subordinates increase the territorial takeover frequency of established breeders. Such takeovers delay offspring production and decrease territory productivity. Individual-based simulations of the Seychelles magpie robin population parameterized with the long-term data show that this process has significantly postponed the recovery of the species from the Critically Endangered status. Social conflict thus can extend the period of high extinction risk, which we show to have population consequences that should be taken into account in management programmes. This is the first quantitative assessment of the effects of social conflict on conservation.

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Accurate knowledge of lactation curves has an important relevance to management and research of dairy production systems. A number of equations have been proposed to describe the lactation curve, the most widely applied being the gamma equation. The objective of this work was to compare and evaluate candidate functions for their predictive ability in describing lactation curves from central Mexican dairy cows reared under 2 contrasting management systems. Five equations were considered: Gaines ( exponential decay), Wood ( gamma equation), Rook ( Michaelis-Menten x exponential), and 2 more mechanistic ones (Dijkstra and Pollott). A database consisting of 701 and 1283 records of cows in small-scale and intensive systems, respectively, was used in the analysis. Before analysis, the database was divided into 6 groups representing first, second, and third and higher parity cows in both systems. In all cases except second and above parity cows in small-scale systems, all models improved on the Gaines equation. The Wood equation explained much of the variation, but its parameters do not have direct biological interpretation. Although the Rook equation fitted the data well, some of the parameter estimates were not significant. The Dijkstra equation consistently gave better predictions, and its parameters were usually statistically significant and lend themselves to physiological interpretation. As such, the differences between systems and parity could be explained due to variations in theoretical initial milk production at parturition, specific rates of secretory cell proliferation and death, and rate of decay, all of which are parameters in the model. The Pollott equation, although containing the most biology, was found to be over-parameterized and resulted in nonsignificant parameter estimates. For central Mexican dairy cows, the Dijkstra equation was the best option to use in describing the lactation curve.

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Landscape narrative, combining landscape and narrative, has been employed to create storytelling layouts and interpretive information in some famous botanic gardens. In order to assess the educational effectiveness of using "landscape narrative" in landscape design, the Heng-Chun Tropical Botanical Garden in Taiwan was chosen as research target for an empirical study. Based on cognitive theory and the affective responses of environmental psychology, computer simulations and video recordings were used to create five themed display areas with landscape narrative elements. Two groups of pupils watched simulated films. The pupils were then given an evaluation test and questionnaire, to determine the effectiveness of the landscape narrative. When the content was well associated and matched with the narrative landscape, the comprehension and retention of content was increased significantly. The results also indicated that visual preference of narrative landscape scenes was increased. This empirical study can be regarded as a successful model of integrating landscape narrative and interpretation practice that can be applied to the design of new theme displays in botanic gardens to improve both the effectiveness of interpretation plans and the visual preference of visitors. (c) 2008 Elsevier B.V. All rights reserved.

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This work analyzes the use of linear discriminant models, multi-layer perceptron neural networks and wavelet networks for corporate financial distress prediction. Although simple and easy to interpret, linear models require statistical assumptions that may be unrealistic. Neural networks are able to discriminate patterns that are not linearly separable, but the large number of parameters involved in a neural model often causes generalization problems. Wavelet networks are classification models that implement nonlinear discriminant surfaces as the superposition of dilated and translated versions of a single "mother wavelet" function. In this paper, an algorithm is proposed to select dilation and translation parameters that yield a wavelet network classifier with good parsimony characteristics. The models are compared in a case study involving failed and continuing British firms in the period 1997-2000. Problems associated with over-parameterized neural networks are illustrated and the Optimal Brain Damage pruning technique is employed to obtain a parsimonious neural model. The results, supported by a re-sampling study, show that both neural and wavelet networks may be a valid alternative to classical linear discriminant models.

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The atmospheric component of the United Kingdom’s new High-resolution Global Environmental Model (HiGEM) has been run with interactive aerosol schemes that include biomass burning and mineral dust. Dust emission, transport, and deposition are parameterized within the model using six particle size divisions, which are treated independently. The biomass is modeled in three nonindependent modes, and emissions are prescribed from an external dataset. The model is shown to produce realistic horizontal and vertical distributions of these aerosols for each season when compared with available satellite- and ground-based observations and with other models. Combined aerosol optical depths off the coast of North Africa exceed 0.5 both in boreal winter, when biomass is the main contributor, and also in summer, when the dust dominates. The model is capable of resolving smaller-scale features, such as dust storms emanating from the Bode´ le´ and Saharan regions of North Africa and the wintertime Bode´ le´ low-level jet. This is illustrated by February and July case studies, in which the diurnal cycles of model variables in relation to dust emission and transport are examined. The top-of-atmosphere annual mean radiative forcing of the dust is calculated and found to be globally quite small but locally very large, exceeding 20 W m22 over the Sahara, where inclusion of dust aerosol is shown to improve the model radiative balance. This work extends previous aerosol studies by combining complexity with increased global resolution and represents a step toward the next generation of models to investigate aerosol–climate interactions. 1. Introduction Accurate modeling of mineral dust is known to be important because of its radiative impact in both numerical weather prediction models (Milton et al. 2008; Haywood et

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The transport of stratospheric air into the troposphere within deep convection was investigated using the Met Office Unified Model version 6.1. Three cases were simulated in which convective systems formed over the UK in the summer of 2005. For each of these three cases, simulations were performed on a grid having 4 km horizontal grid spacing in which the convection was parameterized and on a grid having 1 km horizontal grid spacing, which permitted explicit representation of the largest energy-containing scales of deep convection. Cross-tropopause transport was diagnosed using passive tracers that were initialized above the dynamically defined tropopause (2 potential vorticity unit surface) with a mixing ratio of 1. Although the synoptic-scale environment and triggering mechanisms varied between the cases, the total simulated transport was similar in all three cases. The total stratosphere-to-troposphere transport over the lifetime of the convective systems ranged from 25 to 100 kg/m2 across the simulated convective systems and resolutions, which corresponds to ∼5–20% of the total mass located within a stratospheric column extending 2 km above the tropopause. In all simulations, the transport into the lower troposphere (defined as below 3.5 km elevation) accounted for ∼1% of the total transport across the tropopause. In the 4 km runs most of the transport was due to parameterized convection, whereas in the 1 km runs the transport was due to explicitly resolved convection. The largest difference between the simulations with different resolutions occurred in the one case of midlevel convection considered, in which the total transport in the 1 km grid spacing simulation with explicit convection was 4 times that in the 4 km grid spacing simulation with parameterized convection. Although the total cross-tropopause transport was similar, stratospheric tracer was deposited more deeply to near-surface elevations in the convection-parameterizing simulations than in convection-permitting simulations.

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In a recent study, Williams introduced a simple modification to the widely used Robert–Asselin (RA) filter for numerical integration. The main purpose of the Robert–Asselin–Williams (RAW) filter is to avoid the undesired numerical damping of the RA filter and to increase the accuracy. In the present paper, the effects of the modification are comprehensively evaluated in the Simplified Parameterizations, Primitive Equation Dynamics (SPEEDY) atmospheric general circulation model. First, the authors search for significant changes in the monthly climatology due to the introduction of the new filter. After testing both at the local level and at the field level, no significant changes are found, which is advantageous in the sense that the new scheme does not require a retuning of the parameterized model physics. Second, the authors examine whether the new filter improves the skill of short- and medium-term forecasts. January 1982 data from the NCEP–NCAR reanalysis are used to evaluate the forecast skill. Improvements are found in all the model variables (except the relative humidity, which is hardly changed). The improvements increase with lead time and are especially evident in medium-range forecasts (96–144 h). For example, in tropical surface pressure predictions, 5-day forecasts made using the RAW filter have approximately the same skill as 4-day forecasts made using the RA filter. The results of this work are encouraging for the implementation of the RAW filter in other models currently using the RA filter.