105 resultados para DYNAMICAL TRANSITIONS


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We use new neutron scattering instrumentation to follow in a single quantitative time-resolving experiment, the three key scales of structural development which accompany the crystallisation of synthetic polymers. These length scales span 3 orders of magnitude of the scattering vector. The study of polymer crystallisation dates back to the pioneering experiments of Keller and others who discovered the chain-folded nature of the thin lamellae crystals which are normally found in synthetic polymers. The inherent connectivity of polymers makes their crystallisation a multiscale transformation. Much understanding has developed over the intervening fifty years but the process has remained something of a mystery. There are three key length scales. The chain folded lamellar thickness is ~ 10nm, the crystal unit cell is ~ 1nm and the detail of the chain conformation is ~ 0.1nm. In previous work these length scales have been addressed using different instrumention or were coupled using compromised geometries. More recently researchers have attempted to exploit coupled time-resolved small-angle and wide-angle x-ray experiments. These turned out to be challenging experiments much related to the challenge of placing the scattering intensity on an absolute scale. However, they did stimulate the possibility of new phenomena in the very early stages of crystallisation. Although there is now considerable doubt on such experiments, they drew attention to the basic question as to the process of crystallisation in long chain molecules. We have used NIMROD on the second target station at ISIS to follow all three length scales in a time-resolving manner for poly(e-caprolactone). The technique can provide a single set of data from 0.01 to 100Å-1 on the same vertical scale. We present the results using a multiple scale model of the crystallisation process in polymers to analyse the results.

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Spontaneous activity of the brain at rest frequently has been considered a mere backdrop to the salient activity evoked by external stimuli or tasks. However, the resting state of the brain consumes most of its energy budget, which suggests a far more important role. An intriguing hint comes from experimental observations of spontaneous activity patterns, which closely resemble those evoked by visual stimulation with oriented gratings, except that cortex appeared to cycle between different orientation maps. Moreover, patterns similar to those evoked by the behaviorally most relevant horizontal and vertical orientations occurred more often than those corresponding to oblique angles. We hypothesize that this kind of spontaneous activity develops at least to some degree autonomously, providing a dynamical reservoir of cortical states, which are then associated with visual stimuli through learning. To test this hypothesis, we use a biologically inspired neural mass model to simulate a patch of cat visual cortex. Spontaneous transitions between orientation states were induced by modest modifications of the neural connectivity, establishing a stable heteroclinic channel. Significantly, the experimentally observed greater frequency of states representing the behaviorally important horizontal and vertical orientations emerged spontaneously from these simulations. We then applied bar-shaped inputs to the model cortex and used Hebbian learning rules to modify the corresponding synaptic strengths. After unsupervised learning, different bar inputs reliably and exclusively evoked their associated orientation state; whereas in the absence of input, the model cortex resumed its spontaneous cycling. We conclude that the experimentally observed similarities between spontaneous and evoked activity in visual cortex can be explained as the outcome of a learning process that associates external stimuli with a preexisting reservoir of autonomous neural activity states. Our findings hence demonstrate how cortical connectivity can link the maintenance of spontaneous activity in the brain mechanistically to its core cognitive functions.

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This study considers the strength of the Northern Hemisphere Holton-Tan effect (HTE) in terms of the phase alignment of the quasi-biennial oscillation (QBO) with respect to the annual cycle. Using the ERA-40 Reanalysis, it is found that the early winter (Nov–Dec) and late winter (Feb–Mar) relation between QBO phase and the strength of the stratospheric polar vortex is optimized for subsets of the 44-year record that are chosen on the basis of the seasonality of QBO phase transitions at the 30 hPa level. The timing of phase transitions serves as a proxy for changes in the vertical structure of the QBO over the whole depth of the tropical stratosphere. The statistical significance of the Nov–Dec (Feb–Mar) HTE is greatest when 30 hPa QBO phase transitions occur 9–14 (4–9) months prior to the January of the NH winter in question. This suggests that there exists for both early and late winter a vertical structure of tropical stratospheric winds that is most effective at influencing the interannual variability of the polar vortex, and that an early (late) winter HTE is associated with an early (late) progression of QBO phase towards that structure. It is also shown that the seasonality of QBO phase transitions at 30 hPa varies on a decadal timescale, with transitions during the first half of the calendar year being relatively more common during the first half of the tropical radiosonde wind record. Combining these two results suggests that decadal changes in HTE strength could result from the changing seasonality of QBO phase transitions. Citation: Anstey, J. A., and T. G. Shepherd (2008), Response of the northern stratospheric polar vortex to the seasonal alignment of QBO phase transitions, Geophys. Res. Lett., 35, L22810, doi:10.1029/2008GL035721.

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A version of the Canadian Middle Atmosphere Model that is coupled to an ocean is used to investigate the separate effects of climate change and ozone depletion on the dynamics of the Southern Hemisphere (SH) stratosphere. This is achieved by performing three sets of simulations extending from 1960 to 2099: 1) greenhouse gases (GHGs) fixed at 1960 levels and ozone depleting substances (ODSs) varying in time, 2) ODSs fixed at 1960 levels and GHGs varying in time, and 3) both GHGs and ODSs varying in time. The response of various dynamical quantities to theGHGand ODS forcings is shown to be additive; that is, trends computed from the sum of the first two simulations are equal to trends from the third. Additivity is shown to hold for the zonal mean zonal wind and temperature, the mass flux into and out of the stratosphere, and the latitudinally averaged wave drag in SH spring and summer, as well as for final warming dates. Ozone depletion and recovery causes seasonal changes in lower-stratosphere mass flux, with reduced polar downwelling in the past followed by increased downwelling in the future in SH spring, and the reverse in SH summer. These seasonal changes are attributed to changes in wave drag caused by ozone-induced changes in the zonal mean zonal winds. Climate change, on the other hand, causes a steady decrease in wave drag during SH spring, which delays the breakdown of the vortex, resulting in increased wave drag in summer

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An El Niño-like steady response is found in a greenhouse warming simulation resulting from coupled ocean-atmosphere dynamical feedbacks similar to those producing the present-day El Niños. There is a strong negative cloud-radiation feedback on the sea surface temperature (SST) anomaly associated with this enhanced eastern equatorial Pacific warm pattern. However, this negative feedback is overwhelmed by the positive dynamical feedbacks and cannot diminish the sensitivity of the tropical SST to enhanced greenhouse gas concentrations. The enhanced eastern-Pacific warming in the coupled ocean-atmosphere system suggests that coupled dynamics can strengthen this sensitivity.

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A system for continuous data assimilation is presented and discussed. To simulate the dynamical development a channel version of a balanced barotropic model is used and geopotential (height) data are assimilated into the models computations as data become available. In the first experiment the updating is performed every 24th, 12th and 6th hours with a given network. The stations are distributed at random in 4 groups in order to simulate 4 areas with different density of stations. Optimum interpolation is performed for the difference between the forecast and the valid observations. The RMS-error of the analyses is reduced in time, and the error being smaller the more frequent the updating is performed. The updating every 6th hour yields an error in the analysis less than the RMS-error of the observation. In a second experiment the updating is performed by data from a moving satellite with a side-scan capability of about 15°. If the satellite data are analysed at every time step before they are introduced into the system the error of the analysis is reduced to a value below the RMS-error of the observation already after 24 hours and yields as a whole a better result than updating from a fixed network. If the satellite data are introduced without any modification the error of the analysis is reduced much slower and it takes about 4 days to reach a comparable result to the one where the data have been analysed.

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A recently proposed mean-field theory of mammalian cortex rhythmogenesis describes the salient features of electrical activity in the cerebral macrocolumn, with the use of inhibitory and excitatory neuronal populations (Liley et al 2002). This model is capable of producing a range of important human EEG (electroencephalogram) features such as the alpha rhythm, the 40 Hz activity thought to be associated with conscious awareness (Bojak & Liley 2007) and the changes in EEG spectral power associated with general anesthetic effect (Bojak & Liley 2005). From the point of view of nonlinear dynamics, the model entails a vast parameter space within which multistability, pseudoperiodic regimes, various routes to chaos, fat fractals and rich bifurcation scenarios occur for physiologically relevant parameter values (van Veen & Liley 2006). The origin and the character of this complex behaviour, and its relevance for EEG activity will be illustrated. The existence of short-lived unstable brain states will also be discussed in terms of the available theoretical and experimental results. A perspective on future analysis will conclude the presentation.

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The occurrence of mid-latitude windstorms is related to strong socio-economic effects. For detailed and reliable regional impact studies, large datasets of high-resolution wind fields are required. In this study, a statistical downscaling approach in combination with dynamical downscaling is introduced to derive storm related gust speeds on a high-resolution grid over Europe. Multiple linear regression models are trained using reanalysis data and wind gusts from regional climate model simulations for a sample of 100 top ranking windstorm events. The method is computationally inexpensive and reproduces individual windstorm footprints adequately. Compared to observations, the results for Germany are at least as good as pure dynamical downscaling. This new tool can be easily applied to large ensembles of general circulation model simulations and thus contribute to a better understanding of the regional impact of windstorms based on decadal and climate change projections.

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The development of a particular wintertime atmospheric circulation regime over the North Atlantic, comprising a northward shift of the North Atlantic eddy-driven jet stream and an associated strong and persistent ridge in the subtropics, is investigated. Several different methods of analysis are combined to describe the temporal evolution of the events and relate it to shifts in the phase of the North Atlantic Oscillation and East Atlantic pattern. First, the authors identify a close relationship between northward shifts of the eddy-driven jet, the establishment and maintenance of strong and persistent ridges in the subtropics, and the occurrence of upper-tropospheric anticyclonic Rossby wave breaking over Iberia. Clear tropospheric precursors are evident prior to the development of the regime, suggesting a preconditioning of the Atlantic jet stream and an upstream influence via a large-scale Rossby wave train from the North Pacific. Transient (2–6 days) eddy forcing plays a dual role, contributing to both the initiation and then the maintenance of the circulation anomalies. During the regime there is enhanced occurrence of anticyclonic Rossby wave breaking, which may be described as low-latitude blocking-like events over the southeastern North Atlantic. A strong ridge is already established at the time of wave-breaking onset, suggesting that the role of wave-breaking events is to amplify the circulation anomalies rather than to initiate them. Wave breaking also seems to enhance the persistence, since it is unlikely that a persistent ridge event occurs without being also accompanied by wave breaking.

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A statistical–dynamical regionalization approach is developed to assess possible changes in wind storm impacts. The method is applied to North Rhine-Westphalia (Western Germany) using the FOOT3DK mesoscale model for dynamical downscaling and ECHAM5/OM1 global circulation model climate projections. The method first classifies typical weather developments within the reanalysis period using K-means cluster algorithm. Most historical wind storms are associated with four weather developments (primary storm-clusters). Mesoscale simulations are performed for representative elements for all clusters to derive regional wind climatology. Additionally, 28 historical storms affecting Western Germany are simulated. Empirical functions are estimated to relate wind gust fields and insured losses. Transient ECHAM5/OM1 simulations show an enhanced frequency of primary storm-clusters and storms for 2060–2100 compared to 1960–2000. Accordingly, wind gusts increase over Western Germany, reaching locally +5% for 98th wind gust percentiles (A2-scenario). Consequently, storm losses are expected to increase substantially (+8% for A1B-scenario, +19% for A2-scenario). Regional patterns show larger changes over north-eastern parts of North Rhine-Westphalia than for western parts. For storms with return periods above 20 yr, loss expectations for Germany may increase by a factor of 2. These results document the method's functionality to assess future changes in loss potentials in regional terms.

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The Canadian Middle Atmosphere Modelling (MAM) project is a collaboration between thé Atmospheric Environment Service (AES) of Environment Canada and several Canadian universities. Its goal is thé development of a comprehensive General Circulation Model of the troposphere-stratosphere-mesosphere System, starting from the AES/CCCma third-generation atmospheric General Circulation Model. This paper describes the basic features of the first-generation Canadian MAM and some aspects of its radiative-dynamical climatology. Standard first-order mean diagnostics are presented for monthly means and for the annual cycle of zonal-mean winds and temperatures. The mean meridional circulation is examined, and comparison is made between thé steady diabatic, downward controlled, and residual stream functions. It is found that downward control holds quite well in the monthly mean through most of the middle atmosphere, even during equinoctal periods. The relative roles of different drag processes in determining the mean downwelling over the wintertime polar middle stratosphere is examined, and the vertical structure of the drag is quantified.