958 resultados para Unobserved-component model


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[ 1] A rapid increase in the variety, quality, and quantity of observations in polar regions is leading to a significant improvement in the understanding of sea ice dynamic and thermodynamic processes and their representation in global climate models. We assess the simulation of sea ice in the new Hadley Centre Global Environmental Model (HadGEM1) against the latest available observations. The HadGEM1 sea ice component uses elastic-viscous-plastic dynamics, multiple ice thickness categories, and zero-layer thermodynamics. The model evaluation is focused on the mean state of the key variables of ice concentration, thickness, velocity, and albedo. The model shows good agreement with observational data sets. The variability of the ice forced by the North Atlantic Oscillation is also found to agree with observations.

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The distribution of tracers in the ocean is often taken as an indication of the ventilation pathways for oceanic water masses. It has been suggested that under anthropogenic forcing heat will be taken up into the interior of the ocean along isopycnal ventilation pathways. This notion is investigated by examining distributions of potential temperature and a passive anomaly temperature tracer in a coupled climate experiment where CO2 is increased at a rate of 2% per year. We show that interior temperature changes cannot be explained solely by passive tracer transport along isopycnals. Heat uptake is strongly affected by changes in circulation and has a substantial diapycnal component.

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A systematic modular approach to investigate the respective roles of the ocean and atmosphere in setting El Niño characteristics in coupled general circulation models is presented. Several state-of-the-art coupled models sharing either the same atmosphere or the same ocean are compared. Major results include 1) the dominant role of the atmosphere model in setting El Niño characteristics (periodicity and base amplitude) and errors (regularity) and 2) the considerable improvement of simulated El Niño power spectra—toward lower frequency—when the atmosphere resolution is significantly increased. Likely reasons for such behavior are briefly discussed. It is argued that this new modular strategy represents a generic approach to identifying the source of both coupled mechanisms and model error and will provide a methodology for guiding model improvement.

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Measurements of anthropogenic tracers such as chlorofluorocarbons and tritium must be quantitatively combined with ocean general circulation models as a component of systematic model development. The authors have developed and tested an inverse method, using a Green's function, to constrain general circulation models with transient tracer data. Using this method chlorofluorocarbon-11 and -12 (CFC-11 and -12) observations are combined with a North Atlantic configuration of the Miami Isopycnic Coordinate Ocean Model with 4/3 degrees resolution. Systematic differences can be seen between the observed CFC concentrations and prior CFC fields simulated by the model. These differences are reduced by the inversion, which determines the optimal gas transfer across the air-sea interface, accounting for uncertainties in the tracer observations. After including the effects of unresolved variability in the CFC fields, the model is found to be inconsistent with the observations because the model/data misfit slightly exceeds the error estimates. By excluding observations in waters ventilated north of the Greenland-Scotland ridge (sigma (0) < 27.82 kg m(-3); shallower than about 2000 m), the fit is improved, indicating that the Nordic overflows are poorly represented in the model. Some systematic differences in the model/data residuals remain and are related, in part, to excessively deep model ventilation near Rockall and deficient ventilation in the main thermocline of the eastern subtropical gyre. Nevertheless, there do not appear to be gross errors in the basin-scale model circulation. Analysis of the CFC inventory using the constrained model suggests that the North Atlantic Ocean shallower than about 2000 m was near 20% saturated in the mid-1990s. Overall, this basin is a sink to 22% of the total atmosphere-to-ocean CFC-11 flux-twice the global average value. The average water mass formation rates over the CFC transient are 7.0 and 6.0 Sv (Sv = 10(6) m(3) s(-1)) for subtropical mode water and subpolar mode water, respectively.

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None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture–recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture–recapture models. Alternative methods, still under the capture–recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture–recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao’s lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates—in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

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It is well established that crop production is inherently vulnerable to variations in the weather and climate. More recently the influence of vegetation on the state of the atmosphere has been recognized. The seasonal growth of crops can influence the atmosphere and have local impacts on the weather, which in turn affects the rate of seasonal crop growth and development. Considering the coupled nature of the crop-climate system, and the fact that a significant proportion of land is devoted to the cultivation of crops, important interactions may be missed when studying crops and the climate system in isolation, particularly in the context of land use and climate change. To represent the two-way interactions between seasonal crop growth and atmospheric variability, we integrate a crop model developed specifically to operate at large spatial scales (General Large Area Model for annual crops) into the land surface component of a global climate model (GCM; HadAM3). In the new coupled crop-climate model, the simulated environment (atmosphere and soil states) influences growth and development of the crop, while simultaneously the temporal variations in crop leaf area and height across its growing season alter the characteristics of the land surface that are important determinants of surface fluxes of heat and moisture, as well as other aspects of the land-surface hydrological cycle. The coupled model realistically simulates the seasonal growth of a summer annual crop in response to the GCM's simulated weather and climate. The model also reproduces the observed relationship between seasonal rainfall and crop yield. The integration of a large-scale single crop model into a GCM, as described here, represents a first step towards the development of fully coupled crop and climate models. Future development priorities and challenges related to coupling crop and climate models are discussed.

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OBJECTIVES: This contribution provides a unifying concept for meta-analysis integrating the handling of unobserved heterogeneity, study covariates, publication bias and study quality. It is important to consider these issues simultaneously to avoid the occurrence of artifacts, and a method for doing so is suggested here. METHODS: The approach is based upon the meta-likelihood in combination with a general linear nonparametric mixed model, which lays the ground for all inferential conclusions suggested here. RESULTS: The concept is illustrated at hand of a meta-analysis investigating the relationship of hormone replacement therapy and breast cancer. The phenomenon of interest has been investigated in many studies for a considerable time and different results were reported. In 1992 a meta-analysis by Sillero-Arenas et al. concluded a small, but significant overall effect of 1.06 on the relative risk scale. Using the meta-likelihood approach it is demonstrated here that this meta-analysis is due to considerable unobserved heterogeneity. Furthermore, it is shown that new methods are available to model this heterogeneity successfully. It is argued further to include available study covariates to explain this heterogeneity in the meta-analysis at hand. CONCLUSIONS: The topic of HRT and breast cancer has again very recently become an issue of public debate, when results of a large trial investigating the health effects of hormone replacement therapy were published indicating an increased risk for breast cancer (risk ratio of 1.26). Using an adequate regression model in the previously published meta-analysis an adjusted estimate of effect of 1.14 can be given which is considerably higher than the one published in the meta-analysis of Sillero-Arenas et al. In summary, it is hoped that the method suggested here contributes further to a good meta-analytic practice in public health and clinical disciplines.

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MOTIVATION: The accurate prediction of the quality of 3D models is a key component of successful protein tertiary structure prediction methods. Currently, clustering or consensus based Model Quality Assessment Programs (MQAPs) are the most accurate methods for predicting 3D model quality; however they are often CPU intensive as they carry out multiple structural alignments in order to compare numerous models. In this study, we describe ModFOLDclustQ - a novel MQAP that compares 3D models of proteins without the need for CPU intensive structural alignments by utilising the Q measure for model comparisons. The ModFOLDclustQ method is benchmarked against the top established methods in terms of both accuracy and speed. In addition, the ModFOLDclustQ scores are combined with those from our older ModFOLDclust method to form a new method, ModFOLDclust2, that aims to provide increased prediction accuracy with negligible computational overhead. RESULTS: The ModFOLDclustQ method is competitive with leading clustering based MQAPs for the prediction of global model quality, yet it is up to 150 times faster than the previous version of the ModFOLDclust method at comparing models of small proteins (<60 residues) and over 5 times faster at comparing models of large proteins (>800 residues). Furthermore, a significant improvement in accuracy can be gained over the previous clustering based MQAPs by combining the scores from ModFOLDclustQ and ModFOLDclust to form the new ModFOLDclust2 method, with little impact on the overall time taken for each prediction. AVAILABILITY: The ModFOLDclustQ and ModFOLDclust2 methods are available to download from: http://www.reading.ac.uk/bioinf/downloads/ CONTACT: l.j.mcguffin@reading.ac.uk.

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None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture-recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture-recapture models. Alternative methods, still under the capture-recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture-recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao's lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates-in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

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We focus on the comparison of three statistical models used to estimate the treatment effect in metaanalysis when individually pooled data are available. The models are two conventional models, namely a multi-level and a model based upon an approximate likelihood, and a newly developed model, the profile likelihood model which might be viewed as an extension of the Mantel-Haenszel approach. To exemplify these methods, we use results from a meta-analysis of 22 trials to prevent respiratory tract infections. We show that by using the multi-level approach, in the case of baseline heterogeneity, the number of clusters or components is considerably over-estimated. The approximate and profile likelihood method showed nearly the same pattern for the treatment effect distribution. To provide more evidence two simulation studies are accomplished. The profile likelihood can be considered as a clear alternative to the approximate likelihood model. In the case of strong baseline heterogeneity, the profile likelihood method shows superior behaviour when compared with the multi-level model. Copyright (C) 2006 John Wiley & Sons, Ltd.

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Inelastic neutron scattering spectroscopy has been used to observe and characterise hydrogen on the carbon component of a Pt/C catalyst. INS provides the complete vibration spectrum of coronene, regarded as a molecular model of a graphite layer. The vibrational modes are assigned with the aid of ab initio density functional theory calculations and the INS spectra by the a-CLIMAX program. A spectrum for which the H modes of coronene have been computationally suppressed, a carbon-only coronene spectrum, is a better representation of the spectrum of a graphite layer than is coronene itself. Dihydrogen dosing of a Pt/C catalyst caused amplification of the surface modes of carbon, an effect described as H riding on carbon. From the enhancement of the low energy carbon modes (100-600 cm(-1)) it is concluded that spillover hydrogen becomes attached to dangling bonds at the edges of graphitic regions of the carbon support. (C) 2003 Elsevier Science B.V. All rights reserved.

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Large scale air pollution models are powerful tools, designed to meet the increasing demand in different environmental studies. The atmosphere is the most dynamic component of the environment, where the pollutants can be moved quickly on far distnce. Therefore the air pollution modeling must be done in a large computational domain. Moreover, all relevant physical, chemical and photochemical processes must be taken into account. In such complex models operator splitting is very often applied in order to achieve sufficient accuracy as well as efficiency of the numerical solution. The Danish Eulerian Model (DEM) is one of the most advanced such models. Its space domain (4800 × 4800 km) covers Europe, most of the Mediterian and neighboring parts of Asia and the Atlantic Ocean. Efficient parallelization is crucial for the performance and practical capabilities of this huge computational model. Different splitting schemes, based on the main processes mentioned above, have been implemented and tested with respect to accuracy and performance in the new version of DEM. Some numerical results of these experiments are presented in this paper.

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The study examined: (a) the role of phonological, grammatical, and rapid automatized naming (RAN) skills in reading and spelling development; and (b) the component processes of early narrative writing skills. Fifty-seven Turkish-speaking children were followed from Grade 1 to Grade 2. RAN was the most powerful longitudinal predictor of reading speed and its effect was evident even when previous reading skills were taken into account. Broadly, the phonological and grammatical skills made reliable contributions to spelling performance but their effects were completely mediated by previous spelling skills. Different aspects of the narrative writing skills were related to different processing skills. While handwriting speed predicted writing fluency, spelling accuracy predicted spelling error rate. Vocabulary and working memory were the only reliable longitudinal predictors of the quality of composition content. The overall model, however, failed to explain any reliable variance in the structural quality of the compositions

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In addition to projected increases in global mean sea level over the 21st century, model simulations suggest there will also be changes in the regional distribution of sea level relative to the global mean. There is a considerable spread in the projected patterns of these changes by current models, as shown by the recent Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment (AR4). This spread has not reduced from that given by the Third Assessment models. Comparison with projections by ensembles of models based on a single structure supports an earlier suggestion that models of similar formulation give more similar patterns of sea level change. Analysing an AR4 ensemble of model projections under a business-as-usual scenario shows that steric changes (associated with subsurface ocean density changes) largely dominate the sea level pattern changes. The relative importance of subsurface temperature or salinity changes in contributing to this differs from region to region and, to an extent, from model-to-model. In general, thermosteric changes give the spatial variations in the Southern Ocean, halosteric changes dominate in the Arctic and strong compensation between thermosteric and halosteric changes characterises the Atlantic. The magnitude of sea level and component changes in the Atlantic appear to be linked to the amount of Atlantic meridional overturning circulation (MOC) weakening. When the MOC weakening is substantial, the Atlantic thermosteric patterns of change arise from a dominant role of ocean advective heat flux changes.

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The major component of skeletal muscle is the myofibre. Genetic intervention inducing over-enlargement of myofibres beyond a certain threshold through acellular growth causes a reduction in the specific tension generating capacity of the muscle. However the physiological parameters of a genetic model that harbours reduced skeletal muscle mass have yet to be analysed. Genetic deletion of Meox2 in mice leads to reduced limb muscle size and causes some patterning defects. The loss of Meox2 is not embryonically lethal and a small percentage of animals survive to adulthood making it an excellent model with which to investigate how skeletal muscle responds to reductions in mass. In this study we have performed a detailed analysis of both late foetal and adult muscle development in the absence of Meox2. In the adult, we show that the loss of Meox2 results in smaller limb muscles that harbour reduced numbers of myofibres. However, these fibres are enlarged. These myofibres display a molecular and metabolic fibre type switch towards a more oxidative phenotype that is induced through abnormalities in foetal fibre formation. In spite of these changes, the muscle from Meox2 mutant mice is able to generate increased levels of specific tension compared to that of the wild type.