817 research outputs found

    The CLIC Programme: Towards a Staged e+e- Linear Collider Exploring the Terascale : CLIC Conceptual Design Report

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    This report describes the exploration of fundamental questions in particle physics at the energy frontier with a future TeV-scale e+e- linear collider based on the Compact Linear Collider (CLIC) two-beam acceleration technology. A high-luminosity high-energy e+e- collider allows for the exploration of Standard Model physics, such as precise measurements of the Higgs, top and gauge sectors, as well as for a multitude of searches for New Physics, either through direct discovery or indirectly, via high-precision observables. Given the current state of knowledge, following the observation of a 125 GeV Higgs-like particle at the LHC, and pending further LHC results at 8 TeV and 14 TeV, a linear e+e- collider built and operated in centre-of-mass energy stages from a few-hundred GeV up to a few TeV will be an ideal physics exploration tool, complementing the LHC. In this document, an overview of the physics potential of CLIC is given. Two example scenarios are presented for a CLIC accelerator built in three main stages of 500 GeV, 1.4 (1.5) TeV, and 3 TeV, together with operating schemes that will make full use of the machine capacity to explore the physics. The accelerator design, construction, and performance are presented, as well as the layout and performance of the experiments. The proposed staging example is accompanied by cost estimates of the accelerator and detectors and by estimates of operating parameters, such as power consumption. The resulting physics potential and measurement precisions are illustrated through detector simulations under realistic beam conditions.Comment: 84 pages, published as CERN Yellow Report https://cdsweb.cern.ch/record/147522

    The benefits of spatial resolution increase in global simulations of the hydrological cycle evaluated for the Rhine and Mississippi basins

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    To study the global hydrological cycle and its response to a changing climate, we rely on global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. Increase in computer power therefore permits increase in resolution, but it is an open question where this resolution is invested best: in the GCM or GHM. In this study, we evaluated the benefits of increased resolution, without modifying the representation of physical processes in the models. By doing so, we can evaluate the benefits of resolution alone. We assess and compare the benefits of an increased resolution for a GCM and a GHM for two basins with long observational records: the Rhine and Mississippi basins. Increasing the resolution of a GCM (1.125 to 0.25∘) results in an improved precipitation budget over the Rhine basin, attributed to a more realistic large-scale circulation. These improvements with increased resolution are not found for the Mississippi basin, possibly because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of the GCM improved the simulations of the monthly-averaged discharge for the Rhine, but did not improve the representation of extreme streamflow events. For the Mississippi basin, no substantial differences in precipitation and discharge were found with the higher-resolution GCM and GHM. Increasing the resolution of parameters describing vegetation and orography in the high-resolution GHM (from 0.5 to 0.05∘) shows no significant differences in discharge for both basins. A straightforward resolution increase in the GHM is thus most likely not the best method to improve discharge predictions, which emphasizes the need for better representation of processes and improved parameterizations that go hand in hand with resolution increase in a GHM.</p

    Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

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    This is the published version. Copyright 2014 American Geophysical UnionThis paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models

    Estimation of uncertainty in flood forecasts - a comparison of methods

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    The scientific literature has many methods for estimating uncertainty, however, there is a lack of information about the characteristics, merits and limitations of the individual methods, particularly for making decisions in practice. This paper provides an overview of the different uncertainty methods for flood forecasting that are reported in literature, concentrating on two established approaches defined as the ensemble and the statistical approach. Owing to the variety of flood forecasting and warning systems in operation, the question ‘which uncertainty method is most suitable for which application’ is difficult to answer readily. The paper aims to assist practitioners in understanding how to match an uncertainty quantification method to their particular application using two flood forecasting system case studies in Belgium and Canada. These two specific applications of uncertainty estimation from the literature are compared, illustrating statistical and ensemble methods, and indicating the information and output that these two types of methods offer. The advantages, disadvantages and application of the two different types of method are identified. Although there is no one ‘best’ uncertainty method to fit all forecasting systems, this review helps to explain the current commonly used methods from the available literature for the non-specialist

    Attenuated live infectious bronchitis virus QX vaccine disseminates slowly to target organs distant from the site of inoculation

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    Infectious bronchitis (IB) is a highly contagious respiratory disease of poultry, caused by the avian coronavirus infectious bronchitis virus (IBV). Currently, one of the most relevant genotypes circulating worldwide is IBV-QX (GI-19), for which vaccines have been developed by passaging virulent QX strains in embryonated chicken eggs. Here we explored the attenuated phenotype of a commercially available QX live vaccine, IB Primo QX, in specific pathogens free broilers. At hatch, birds were inoculated with QX vaccine or its virulent progenitor IBV-D388, and postmortem swabs and tissues were collected each day up to eight days post infection to assess viral replication and morphological changes. In the trachea, viral RNA replication and protein expression were comparable in both groups. Both viruses induced morphologically comparable lesions in the trachea, albeit with a short delay in the vaccinated birds. In contrast, in the kidney, QX vaccine viral RNA was nearly absent, which coincided with the lack of any morphological changes in this organ. This was in contrast to high viral RNA titers and abundant lesions in the kidney after IBV D388 infection. Furthermore, QX vaccine showed reduced ability to reach and replicate in conjunctivae and intestines including cloaca, resulting in significantly lower titers and delayed protein expression, respectively. Nephropathogenic IBVs might reach the kidney also via an ascending route from the cloaca, based on our observation that viral RNA was detected in the cloaca one day before detection in the kidney. In the kidney distal tubular segments, collecting ducts and ureter were positive for viral antigen. Taken together, the attenuated phenotype of QX vaccine seems to rely on slower dissemination and lower replication in target tissues other than the site of inoculation

    Continental and global scale flood forecasting systems

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    Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centres are increasingly using the meteorological output from these to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Currently, operational systems have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products, in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale, alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction

    Global QCD Analysis and the CTEQ Parton Distributions

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    The CTEQ program for the determination of parton distributions through a global QCD analysis of data for various hard scattering processes is fully described. A new set of distributions, CTEQ3, incorporating several new types of data is reported and compared to the two previous sets of CTEQ distributions. Comparison with current data is discussed in some detail. The remaining uncertainties in the parton distributions and methods to further reduce them are assessed. Comparisons with the results of other global analyses are also presented.Comment: (Change in Latex style only: 2up style removed since many don't have it.) 35 pages, 23 figures separately submitted as uuencoded compressed ps-file; Michigan State Report # MSU-HEP/41024 and CTEQ 40

    Measuring Parton Densities in the Pomeron

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    We present a program to measure the parton densities in the pomeron using diffractive deep inelastic scattering and diffractive photoproduction, and to test the resulting parton densities by applying them to other processes such as the diffractive production of jets in hadron-hadron collisions. Since QCD factorization has been predicted NOT to apply to hard diffractive scattering, this program of fitting and using parton densities might be expected to fail. Its success or failure will provide useful information on the space-time structure of the pomeron.Comment: Contains revisions based on Phys. Rev. D referee comments. RevTeX version 3, epsf, 31 pages. Uuencoded compressed postscript figures appended. Uncompressed postscript files available at ftp://ftp.phys.psu.edu/pub/preprint/psuth136

    A vision for hydrological prediction

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    IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. Its aim was to improve society’s ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower, and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem solving in the water sector. The work and discussions carried out during the project nurtured further reflections towards a common vision for hydrological prediction. In this article, we summarize the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we firstly present a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learnt from IMPREX are discussed. The key findings are the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe, and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Lastly, a vision for how to improve these forecast systems/products in the future is expounded and these include advancing numerical weather and hydrological models, improved earth monitoring, and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and hydrological modelling will become more skilful, thus leading to socioeconomic benefits for the citizens of Europe and beyond
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