7 resultados para frequency coupling

em CentAUR: Central Archive University of Reading - UK


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We propose a mechanism to explain suggested links between seismic activity and ionospheric changes detected overhead. Specifically, we explain changes in the natural extremely low-frequency (ELF) radio noise recently observed in the topside ionosphere aboard the DEMETER satellite at night, before major earthquakes. Our mechanism utilises increased electrical conductivity of surface layer air before a major earthquake, which reduces the surface-ionosphere electrical resistance. This increases the vertical fair weather current, and (to maintain continuity of electron flow) lowers the ionosphere. Magnitudes of crucial parameters are estimated and found to be consistent with observations. Natural variability in ionospheric and atmospheric electrical properties is evaluated, and may be overcome using a hybrid detection approach. Suggested experiments to investigate the mechanism involve measuring the cut-off frequency of ELF “tweeks”, the amplitude and phase of very low frequency radio waves in the Earth–ionosphere waveguide, or medium frequency radar, incoherent scatter or rocket studies of the lower ionospheric electron density.

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The new HadKPP atmosphere–ocean coupled model is described and then used to determine the effects of sub-daily air–sea coupling and fine near-surface ocean vertical resolution on the representation of the Northern Hemisphere summer intra-seasonal oscillation. HadKPP comprises the Hadley Centre atmospheric model coupled to the K Profile Parameterization ocean-boundary-layer model. Four 30-member ensembles were performed that varied in oceanic vertical resolution between 1 m and 10 m and in coupling frequency between 3 h and 24 h. The 10 m, 24 h ensemble exhibited roughly 60% of the observed 30–50 day variability in sea-surface temperatures and rainfall and very weak northward propagation. Enhancing either only the vertical resolution or only the coupling frequency produced modest improvements in variability and only a standing intra-seasonal oscillation. Only the 1 m, 3 h configuration generated organized, northward-propagating convection similar to observations. Sub-daily surface forcing produced stronger upper-ocean temperature anomalies in quadrature with anomalous convection, which likely affected lower-atmospheric stability ahead of the convection, causing propagation. Well-resolved air–sea coupling did not improve the eastward propagation of the boreal summer intra-seasonal oscillation in this model. Upper-ocean vertical mixing and diurnal variability in coupled models must be improved to accurately resolve and simulate tropical sub-seasonal variability. In HadKPP, the mere presence of air–sea coupling was not sufficient to generate an intra-seasonal oscillation resembling observations.

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Starting from the classical Saltzman two-dimensional convection equations, we derive via a severe spectral truncation a minimal 10 ODE system which includes the thermal effect of viscous dissipation. Neglecting this process leads to a dynamical system which includes a decoupled generalized Lorenz system. The consideration of this process breaks an important symmetry and couples the dynamics of fast and slow variables, with the ensuing modifications to the structural properties of the attractor and of the spectral features. When the relevant nondimensional number (Eckert number Ec) is different from zero, an additional time scale of O(Ec−1) is introduced in the system, as shown with standard multiscale analysis and made clear by several numerical evidences. Moreover, the system is ergodic and hyperbolic, the slow variables feature long-term memory with 1/f3/2 power spectra, and the fast variables feature amplitude modulation. Increasing the strength of the thermal-viscous feedback has a stabilizing effect, as both the metric entropy and the Kaplan-Yorke attractor dimension decrease monotonically with Ec. The analyzed system features very rich dynamics: it overcomes some of the limitations of the Lorenz system and might have prototypical value in relevant processes in complex systems dynamics, such as the interaction between slow and fast variables, the presence of long-term memory, and the associated extreme value statistics. This analysis shows how neglecting the coupling of slow and fast variables only on the basis of scale analysis can be catastrophic. In fact, this leads to spurious invariances that affect essential dynamical properties (ergodicity, hyperbolicity) and that cause the model losing ability in describing intrinsically multiscale processes.

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Observations of noctilucent clouds have revealed a surprising coupling between the winter stratosphere and the summer polar mesopause region. In spite of the great distance involved, this inter-hemispheric link has been suggested to be the principal reason for both the year-to-year variability and the hemispheric differences in the frequency of occurrence of these high-altitude clouds. In this study, we investigate the dynamical influence of the winter stratosphere on the summer mesosphere using simulations from the vertically extended version of the Canadian Middle Atmosphere Model (CMAM). We find that for both Northern and Southern Hemispheres, variability in the summer polar mesopause region from one year to another can be traced back to the planetary-wave flux entering the winter stratosphere. The teleconnection pattern is the same for both positive and negative wave-flux anomalies. Using a composite analysis to isolate the events, it is argued that the mechanism for interhemispheric coupling is a feedback between summer mesosphere gravity-wave drag (GWD) and zonal wind, which is induced by an anomaly in mesospheric cross-equatorial flow, the latter arising from the anomaly in winter hemisphere GWD induced by the anomaly in stratospheric conditions.

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We present a dynamic causal model that can explain context-dependent changes in neural responses, in the rat barrel cortex, to an electrical whisker stimulation at different frequencies. Neural responses were measured in terms of local field potentials. These were converted into current source density (CSD) data, and the time series of the CSD sink was extracted to provide a time series response train. The model structure consists of three layers (approximating the responses from the brain stem to the thalamus and then the barrel cortex), and the latter two layers contain nonlinearly coupled modules of linear second-order dynamic systems. The interaction of these modules forms a nonlinear regulatory system that determines the temporal structure of the neural response amplitude for the thalamic and cortical layers. The model is based on the measured population dynamics of neurons rather than the dynamics of a single neuron and was evaluated against CSD data from experiments with varying stimulation frequency (1–40 Hz), random pulse trains, and awake and anesthetized animals. The model parameters obtained by optimization for different physiological conditions (anesthetized or awake) were significantly different. Following Friston, Mechelli, Turner, and Price (2000), this work is part of a formal mathematical system currently being developed (Zheng et al., 2005) that links stimulation to the blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal through neural activity and hemodynamic variables. The importance of the model described here is that it can be used to invert the hemodynamic measurements of changes in blood flow to estimate the underlying neural activity.

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Although promise exists for patterns of resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) brain connectivity to be used as biomarkers of early brain pathology, a full understanding of the nature of the relationship between neural activity and spontaneous fMRI BOLD fluctuations is required before such data can be correctly interpreted. To investigate this issue, we combined electrophysiological recordings of rapid changes in multi-laminar local field potentials from the somatosensory cortex of anaesthetized rats with concurrent two-dimensional optical imaging spectroscopy measurements of resting-state haemodynamics that underlie fluctuations in the BOLD fMRI signal. After neural ‘events’ were identified, their time points served to indicate the start of an epoch in the accompanying haemodynamic fluctuations. Multiple epochs for both neural ‘events’ and the accompanying haemodynamic fluctuations were averaged. We found that the averaged epochs of resting-state haemodynamic fluctuations taken after neural ‘events’ closely resembled the temporal profile of stimulus-evoked cortical haemodynamics. Furthermore, we were able to demonstrate that averaged epochs of resting-state haemodynamic fluctuations resembling the temporal profile of stimulus-evoked haemodynamics could also be found after peaks in neural activity filtered into specific electroencephalographic frequency bands (theta, alpha, beta, and gamma). This technique allows investigation of resting-state neurovascular coupling using methodologies that are directly comparable to that developed for investigating stimulus-evoked neurovascular responses.

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The role of air–sea coupling in the simulation of the Madden–Julian oscillation (MJO) is explored using two configurations of the Hadley Centre atmospheric model (AGCM), GA3.0, which differ only in F, a parameter controlling convective entrainment and detrainment. Increasing F considerably improves deficient MJO-like variability in the Indian and Pacific Oceans, but variability in and propagation through the Maritime Continent remains weak. By coupling GA3.0 in the tropical Indo-Pacific to a boundary-layer ocean model, KPP, and employing climatological temperature corrections, well resolved air–sea interactions are simulated with limited alterations to the mean state. At default F, when GA3.0 has a poor MJO, coupling produces a stronger MJO with some eastward propagation, although both aspects remain deficient. These results agree with previous sensitivity studies using AGCMs with poor variability. At higher F, coupling does not affect MJO amplitude but enhances propagation through the Maritime Continent, resulting in an MJO that resembles observations. A sensitivity experiment with coupling in only the Indian Ocean reverses these improvements, suggesting coupling in the Maritime Continent and West Pacific is critical for propagation. We hypothesise that for AGCMs with a poor MJO, coupling provides a “crutch” to artificially augment MJO-like activity through high-frequency SST anomalies. In related experiments, we employ the KPP framework to analyse the impact of air–sea interactions in the fully coupled GA3.0, which at default F shows a similar MJO to uncoupled GA3.0. This is due to compensating effects: an improvement from coupling and a degradation from mean-state errors. Future studies on the role of coupling should carefully separate these effects.