33 resultados para Large detector systems for particle and astroparticle physics


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Soils represent a large carbon pool, approximately 1500 Gt, which is equivalent to almost three times the quantity stored in terrestrial biomass and twice the amount stored in the atmosphere. Any modification of land use or land management can induce variations in soil carbon stocks, even in agricultural systems that are perceived to be in a steady state. Tillage practices often induce soil aerobic conditions that are favourable to microbial activity and may lead to a degradation of soil structure. As a result, mineralisation of soil organic matter increases in the long term. The adoption of no-tillage systems and the maintenance of a permanent vegetation cover using Direct seeding Mulch-based Cropping system or DMC, may increase carbon levels in the topsoil. In Brazil, no-tillage practices (mainly DMC), were introduced approximately 30 years ago in the south in the Parana state, primarily as a means of reducing erosion. Subsequently, research has begun to study the management of the crop waste products and their effects on soil fertility, either in terms of phosphorus management, as a means of controlling soil acidity, or determining how manures can be applied in a more localised manner. The spread of no-till in Brazil has involved a large amount of extension work. The area under no-tillage is still increasing in the centre and north of the country and currently occupies ca. 20 million hectares, covering a diversity of environmental conditions, cropping systems and management practices. Most studies of Brazilian soils give rates of carbon storage in the top 40 cm of the soil of 0.4 to 1.7 t C ha(-1) per year, with the highest rates in the Cerrado region. However, caution must be taken when analysing DMC systems in terms of carbon sequestration. Comparisons should include changes in trace gas fluxes and should not be limited to a consideration of carbon storage in the soil alone if the full implications for global warming are to be assessed.

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For the very large nonlinear dynamical systems that arise in a wide range of physical, biological and environmental problems, the data needed to initialize a numerical forecasting model are seldom available. To generate accurate estimates of the expected states of the system, both current and future, the technique of ‘data assimilation’ is used to combine the numerical model predictions with observations of the system measured over time. Assimilation of data is an inverse problem that for very large-scale systems is generally ill-posed. In four-dimensional variational assimilation schemes, the dynamical model equations provide constraints that act to spread information into data sparse regions, enabling the state of the system to be reconstructed accurately. The mechanism for this is not well understood. Singular value decomposition techniques are applied here to the observability matrix of the system in order to analyse the critical features in this process. Simplified models are used to demonstrate how information is propagated from observed regions into unobserved areas. The impact of the size of the observational noise and the temporal position of the observations is examined. The best signal-to-noise ratio needed to extract the most information from the observations is estimated using Tikhonov regularization theory. Copyright © 2005 John Wiley & Sons, Ltd.

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Particle filters are fully non-linear data assimilation techniques that aim to represent the probability distribution of the model state given the observations (the posterior) by a number of particles. In high-dimensional geophysical applications the number of particles required by the sequential importance resampling (SIR) particle filter in order to capture the high probability region of the posterior, is too large to make them usable. However particle filters can be formulated using proposal densities, which gives greater freedom in how particles are sampled and allows for a much smaller number of particles. Here a particle filter is presented which uses the proposal density to ensure that all particles end up in the high probability region of the posterior probability density function. This gives rise to the possibility of non-linear data assimilation in large dimensional systems. The particle filter formulation is compared to the optimal proposal density particle filter and the implicit particle filter, both of which also utilise a proposal density. We show that when observations are available every time step, both schemes will be degenerate when the number of independent observations is large, unlike the new scheme. The sensitivity of the new scheme to its parameter values is explored theoretically and demonstrated using the Lorenz (1963) model.

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A quantitative model of wheat root systems is developed that links the size and distribution of the root system to the capture of water and nitrogen (which are assumed to be evenly distributed with depth) during grain filling, and allows estimates of the economic consequences of this capture to be assessed. A particular feature of the model is its use of summarizing concepts, and reliance on only the minimum number of parameters (each with a clear biological meaning). The model is then used to provide an economic sensitivity analysis of possible target characteristics for manipulating root systems. These characteristics were: root distribution with depth, proportional dry matter partitioning to roots, resource capture coefficients, shoot dry weight at anthesis, specific root weight and water use efficiency. From the current estimates of parameters it is concluded that a larger investment by the crop in fine roots at depth in the soil, and less proliferation of roots in surface layers, would improve yields by accessing extra resources. The economic return on investment in roots for water capture was twice that of the same amount invested for nitrogen capture. (C) 2003 Annals of Botany Company.

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By making use of TOVS Path-B satellite retrievals and ECMWF reanalyses, correlations between bulk microphysical properties of large-scale semi-transparent cirrus (visible optical thickness between 0.7 and 3.8) and thermodynamic and dynamic properties of the surrounding atmosphere have been studied on a global scale. These clouds constitute about half of all high clouds. The global averages (from 60°N to 60°S) of mean ice crystal diameter, De, and ice water path (IWP) of these clouds are 55 μm and 30 g m−2, respectively. IWP of these cirrus is slightly increasing with cloud-top temperature, whereas De of cold cirrus does not depend on this parameter. Correlations between De and IWp of large-scale cirrus seem to be different in the midlatitudes and in the tropics. However, we observe in general stronger correlations between De and IWP and atmospheric humidity and winds deduced from the ECMWF reanalyses: De and IWP increase both with increasing atmospheric water vapour. There is also a good distinction between different dynamical situations: In humid situations, IWP is on average about 10 gm−2 larger in regions with strong large-scale vertical updraft only that in regions with strong large-scale horizontal winds only, whereas the mean De of cold large-scale cirrus decreases by about 10 μm if both strong large-scale updraft and horizontal winds are present.

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At the end of its tether! The fusion of a six-membered ring onto the four-carbon-atom tether of substrate 1 provides an efficient approach toward the polycyclic ring systems of the natural products aphidicolin and stemodinone. The reaction represents a unique example of a preference for product formation from an endo exciplex in an intramolecular system (exo:endo 2:3=1.0:1.2).