949 resultados para Integral Time Scales
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This paper is concerned with a generalization of the Riemann- Stieltjes integral on time scales for deal with some aspects of discontinuous dynamic equations in which Riemann-Stieltjes integral does not works. © 2011 Academic Publications.
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The play operator has a fundamental importance in the theory of hysteresis. It was studied in various settings as shown by P. Krejci and Ph. Laurencot in 2002. In that work it was considered the Young integral in the frame of Hilbert spaces. Here we study the play in the frame of the regulated functions (that is: the ones having only discontinuities of the first kind) on a general time scale T (that is: with T being a nonempty closed set of real numbers) with values in a Banach space. We will be showing that the dual space in this case will be defined as the space of operators of bounded semivariation if we consider as the bilinearity pairing the Cauchy-Stieltjes integral on time scales.
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The purpose of the present paper is to study some properties of solutions of Volterra integral equations on time scales. We generalize to a time scale some known properties concerning continuity and convergence of solutions from the continuous case.
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This work formulates existence theorems for solutions to two-point boundary value problems on time scales. The methods used include maximum principles, a priori bounds and topological degree theory.
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The role of nutrients, such as phosphorus (P), and their impact on primary productivity and the fluctuations in atmospheric CO2 over glacial-interglacial periods are intensely debated. Suggestions as to the importance of P evolved from an earlier proposal that P actively participated in changing productivity rates and therefore climate change, to most recent ones that changes in the glacial ocean inventory of phosphorus were important but not influential if compared to other macronutrients, such as nitrate. Using new data coming from a selection of ODP sites, we analyzed the distribution of oceanic P sedimentary phases and calculate reactive P burial fluxes, and we show how P burial fluxes changed over the last glacial-interglacial period at these sites. Concentrations of reactive P are generally lower during glacial times, while mass accumulation rates (MAR) of reactive P show higher variability. If we extrapolate for the analyzed sites, we may assume that in general glacial burial fluxes of reactive P are lower than those during interglacial periods by about 8%, because the lack of burial of reactive P on the glacial shelf reduced in size, was apparently not compensated by burial in other regions of the ocean. Using the calculated changes in P burial, we evaluate their possible impact on the phosphate inventory in the world oceans. Using a simple mathematical approach, we find that these changes alone could have increased the phosphate inventory of glacial ocean waters by 17-40% compared to interglacial stages. Variations in the distribution of sedimentary P phases at the investigated sites seem to indicate that at the onset of interglacial stages, shallower sites experienced an increase in reactive P concentrations, which seems to point to P-richer waters at glacial terminations. All these findings would support the Shelf-Nutrient Hypothesis, which assumes that during glacial low stands nutrients are transferred from shallow sites to deep sea with possible feedback on the carbon cycle.
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We study the effect of parameter fluctuations and the resultant multiplicative noise on the synchronization of coupled chaotic systems. We introduce a new quantity, the fluctuation rate Ф as the number of perturbations occurring to the parameter in unit time. It is shown that ϕ is the most significant quantity that determines the quality of synchronization. It is found that parameter fluctuations with high fluctuation rates do not destroy synchronization, irrespective of the statistical features of the fluctuations. We also present a quasi-analytic explanation to the relation between ϕ and the error in synchrony.
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We propose to show in this paper, that the time series obtained from biological systems such as human brain are invariably nonstationary because of different time scales involved in the dynamical process. This makes the invariant parameters time dependent. We made a global analysis of the EEG data obtained from the eight locations on the skull space and studied simultaneously the dynamical characteristics from various parts of the brain. We have proved that the dynamical parameters are sensitive to the time scales and hence in the study of brain one must identify all relevant time scales involved in the process to get an insight in the working of brain.
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Time scales of pedogenic calcrete development are quantified by subsampling carbonate from within a mature (stage V) pedogenic calcrete profile from southeast Spain and dating the material by U-series disequilibria. The location of the earliest and latest cements can be estimated by comparing previous studies of calcrete morphological development with micromorphological analysis of the study profile. Carbonate was sampled and dated from three locations within the profile: (1) below the lower surface of clasts within the hardpan (representing the earliest cement present-207 +/- 11 ka), (2) from the centre of cement filled pores within the hardpan (reflecting the final plugging of the calcrete hardpan-155 +/- 9 ka) and (3) from the laminar calcrete overlying the hardpan (representing the latest cement-112 +/- 15 ka). These results show that the hardpan took between 73 and 31 ka to form, whilst the mature stage V profile took between 121 and 69 ka to form. This is the first time that rates of mature calcrete development have been established by direct radiometric dating of the authigenic carbonate. The technique is appropriate for dating mature calcretes in dryland regions worldwide and offers the opportunity of increasing our understanding of the spatial and temporal variability in rates of pedogenic calcrete development. (C) 2004 Elsevier B.V. All rights reserved.
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The contributions of different time scales to extratropical teleconnections are examined. By applying empirical orthogonal functions and correlation analyses to reanalysis data, it is shown that eddies with periods shorter than 10 days have no linear contribution to teleconnectivity. Instead, synoptic variability follows wavelike patterns along the storm tracks, interpreted as propagating baroclinic disturbances. In agreement with preceding studies, it is found that teleconnections such as the North Atlantic Oscillation (NAO) and the Pacific–North America (PNA) pattern occur only at low frequencies, typically for periods more than 20 days. Low-frequency potential vorticity variability is shown to follow patterns analogous to known teleconnections but with shapes that differ considerably from them. It is concluded that the role, if any, of synoptic eddies in determining and forcing teleconnections needs to be sought in nonlinear interactions with the slower transients. The present results demonstrate that daily variability of teleconnection indices cannot be interpreted in terms of the teleconnection patterns, only the slow part of the variability.
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Many numerical models for weather prediction and climate studies are run at resolutions that are too coarse to resolve convection explicitly, but too fine to justify the local equilibrium assumed by conventional convective parameterizations. The Plant-Craig (PC) stochastic convective parameterization scheme, developed in this paper, solves this problem by removing the assumption that a given grid-scale situation must always produce the same sub-grid-scale convective response. Instead, for each timestep and gridpoint, one of the many possible convective responses consistent with the large-scale situation is randomly selected. The scheme requires as input the large-scale state as opposed to the instantaneous grid-scale state, but must nonetheless be able to account for genuine variations in the largescale situation. Here we investigate the behaviour of the PC scheme in three-dimensional simulations of radiative-convective equilibrium, demonstrating in particular that the necessary space-time averaging required to produce a good representation of the input large-scale state is not in conflict with the requirement to capture large-scale variations. The resulting equilibrium profiles agree well with those obtained from established deterministic schemes, and with corresponding cloud-resolving model simulations. Unlike the conventional schemes the statistics for mass flux and rainfall variability from the PC scheme also agree well with relevant theory and vary appropriately with spatial scale. The scheme is further shown to adapt automatically to changes in grid length and in forcing strength.
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Observational evidence is scarce concerning the distribution of plant pathogen population sizes or densities as a function of time-scale or spatial scale. For wild pathosystems we can only get indirect evidence from evolutionary patterns and the consequences of biological invasions.We have little or no evidence bearing on extermination of hosts by pathogens, or successful escape of a host from a pathogen. Evidence over the last couple of centuries from crops suggest that the abundance of particular pathogens in the spectrum affecting a given host can vary hugely on decadal timescales. However, this may be an artefact of domestication and intensive cultivation. Host-pathogen dynamics can be formulated mathematically fairly easily–for example as SIR-type differential equation or difference equation models, and this has been the (successful) focus of recent work in crops. “Long-term” is then discussed in terms of the time taken to relax from a perturbation to the asymptotic state. However, both host and pathogen dynamics are driven by environmental factors as well as their mutual interactions, and both host and pathogen co-evolve, and evolve in response to external factors. We have virtually no information about the importance and natural role of higher trophic levels (hyperpathogens) and competitors, but they could also induce long-scale fluctuations in the abundance of pathogens on particular hosts. In wild pathosystems the host distribution cannot be modelled as either a uniform density or even a uniform distribution of fields (which could then be treated as individuals). Patterns of short term density-dependence and the detail of host distribution are therefore critical to long-term dynamics. Host density distributions are not usually scale-free, but are rarely uniform or clearly structured on a single scale. In a (multiply structured) metapopulation with coevolution and external disturbances it could well be the case that the time required to attain equilibrium (if it exists) based on conditions stable over a specified time-scale is longer than that time-scale. Alternatively, local equilibria may be reached fairly rapidly following perturbations but the meta-population equilibrium be attained very slowly. In either case, meta-stability on various time-scales is a more relevant than equilibrium concepts in explaining observed patterns.
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The Sun-Earth connection is studied using long-term measurements from the Sun and from the Earth. The auroral activity is shown to correlate to high accuracy with the smoothed sunspot numbers. Similarly, both geomagnetic activity and global surface temperature anomaly can be linked to cyclic changes in the solar activity. The interlinked variations in the solar magnetic activity and in the solar irradiance cause effects that can be observed both in the Earth's biosphere and in the electromagnetic environment. The long-term data sets suggest that the increase in geomagnetic activity and surface temperatures are related (at least partially) to longer-term solar variations, which probably include an increasing trend superposed with a cyclic behavior with a period of about 90 years.
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In this paper, the teleconnections from the tropical Atlantic to the Indo-Pacific region from inter-annual to centennial time scales will be reviewed. Identified teleconnections and hypotheses on mechanisms at work are reviewed and further explored in a century-long pacemaker coupled ocean-atmosphere simulation ensemble. There is a substantial impact of the tropical Atlantic on the Pacific region at inter-annual time scales. An Atlantic Niño (Niña) event leads to rising (sinking) motion in the Atlantic region, which is compensated by sinking (rising) motion in the central-western Pacific. The sinking (rising) motion in the central-western Pacific induces easterly (westerly) surface wind anomalies just to the west, which alter the thermocline. These perturbations propagate eastward as upwelling (downwelling) Kelvin-waves, where they increase the probability for a La Niña (El Niño) event. Moreover, tropical North Atlantic sea surface temperature anomalies are also able to lead La Niña/El Niño development. At multidecadal time scales, a positive (negative) Atlantic Multidecadal Oscillation leads to a cooling (warming) of the eastern Pacific and a warming (cooling) of the western Pacific and Indian Ocean regions. The physical mechanism for this impact is similar to that at inter-annual time scales. At centennial time scales, the Atlantic warming induces a substantial reduction of the eastern Pacific warming even under CO2 increase and to a strong subsurface cooling.
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It is argued that existing polar prediction systems do not yet meet users’ needs; and possible ways forward in advancing prediction capacity in polar regions and beyond are outlined. The polar regions have been attracting more and more attention in recent years, fuelled by the perceptible impacts of anthropogenic climate change. Polar climate change provides new opportunities, such as shorter shipping routes between Europe and East Asia, but also new risks such as the potential for industrial accidents or emergencies in ice-covered seas. Here, it is argued that environmental prediction systems for the polar regions are less developed than elsewhere. There are many reasons for this situation, including the polar regions being (historically) lower priority, with less in situ observations, and with numerous local physical processes that are less well-represented by models. By contrasting the relative importance of different physical processes in polar and lower latitudes, the need for a dedicated polar prediction effort is illustrated. Research priorities are identified that will help to advance environmental polar prediction capabilities. Examples include an improvement of the polar observing system; the use of coupled atmosphere-sea ice-ocean models, even for short-term prediction; and insight into polar-lower latitude linkages and their role for forecasting. Given the enormity of some of the challenges ahead, in a harsh and remote environment such as the polar regions, it is argued that rapid progress will only be possible with a coordinated international effort. More specifically, it is proposed to hold a Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 in which the international research and operational forecasting community will work together with stakeholders in a period of intensive observing, modelling, prediction, verification, user-engagement and educational activities.