61 resultados para Frequency Response Functions


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To study the transient atmospheric response to midlatitude SST anomalies, a three-layer quasigeostrophic (QG) model coupled to a slab oceanic mixed layer in the North Atlantic is used. As diagnosed from a coupled run in perpetual winter conditions, the first two modes of SST variability are linked to the model North Atlantic Oscillation (NAO) and eastern Atlantic pattern (EAP), respectively, the dominant atmospheric modes in the Atlantic sector. The two SST anomaly patterns are then prescribed as fixed anomalous boundary conditions for the model atmosphere, and its transient responses are established from a large ensemble of simulations. In both cases, the tendency of the air–sea heat fluxes to damp the SST anomalies results in an anomalous diabatic heating of the atmosphere that, in turn, forces a baroclinic response, as predicted by linear theory. This initial response rapidly modifies the transient eddy activity and thus the convergence of eddy momentum and heat fluxes. The latter transforms the baroclinic response into a growing barotropic one that resembles the atmospheric mode that had created the SST anomaly in the coupled run and is thus associated with a positive feedback. The total adjustment time is as long as 3–4 months for the NAO-like response and 1–2 months for the EAP-like one. The positive feedback, in both cases, is dependent on the polarity of the SST anomaly, but is stronger in the NAO case, thereby contributing to its predominance at low frequency in the coupled system. However, the feedback is too weak to lead to an instability of the atmospheric modes and primarily results in an increase of their amplitude and persistence and a weakening of the heat flux damping of the SST anomaly.

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Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator.

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Model studies do not agree on future changes in tropical cyclone (TC) activity on regional scales. We aim to shed further light on the distribution, frequency, intensity, and seasonality of TCs that society can expect at the end of the twenty-first century in the Southern hemisphere (SH). Therefore, we investigate TC changes simulated by the atmospheric model ECHAM5 with T213 (~60 km) horizontal resolution. We identify TCs in present-day (20C; 1969–1990) and future (21C; 2069–2100) time slice simulations, using a tracking algorithm based on vorticity at 850 hPa. In contrast to the Northern hemisphere (NH), where tropical storm numbers reduce by 6 %, there is a more dramatic 22 % reduction in the SH, mainly in the South Indian Ocean. While an increase of static stability in 21C may partly explain the reduction in tropical storm numbers, stabilization cannot alone explain the larger SH drop. Large-scale circulation changes associated with a weakening of the Tropical Walker Circulation are hypothesized to cause the strong decrease of cyclones in the South Indian Ocean. In contrast the decrease found over the South Pacific appears to be partly related to increased vertical wind shear, which is possibly associated with an enhanced meridional sea surface temperature gradient. We find the main difference between the hemispheres in changes of the tropical cyclones of intermediate strength with an increase in the NH and a decrease in the SH. In both hemispheres the frequency of the strongest storms increases and the frequency of the weakest storms decreases, although the increase in SH intense storms is marginal.

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Single-carrier (SC) block transmission with frequency-domain equalisation (FDE) offers a viable transmission technology for combating the adverse effects of long dispersive channels encountered in high-rate broadband wireless communication systems. However, for high bandwidthefficiency and high power-efficiency systems, the channel can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such nonlinear Hammerstein channels, the standard SC-FDE scheme no longer works. This paper advocates a complex-valued (CV) B-spline neural network based nonlinear SC-FDE scheme for Hammerstein channels. Specifically, We model the nonlinear HPA, which represents the CV static nonlinearity of the Hammerstein channel, by a CV B-spline neural network, and we develop two efficient alternating least squares schemes for estimating the parameters of the Hammerstein channel, including both the channel impulse response coefficients and the parameters of the CV B-spline model. We also use another CV B-spline neural network to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard least squares algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse B-spline neural network model obtained in time domain. Extensive simulation results are included to demonstrate the effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels.

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In this paper we propose and analyse a hybrid numerical-asymptotic boundary element method for the solution of problems of high frequency acoustic scattering by a class of sound-soft nonconvex polygons. The approximation space is enriched with carefully chosen oscillatory basis functions; these are selected via a study of the high frequency asymptotic behaviour of the solution. We demonstrate via a rigorous error analysis, supported by numerical examples, that to achieve any desired accuracy it is sufficient for the number of degrees of freedom to grow only in proportion to the logarithm of the frequency as the frequency increases, in contrast to the at least linear growth required by conventional methods. This appears to be the first such numerical analysis result for any problem of scattering by a nonconvex obstacle. Our analysis is based on new frequency-explicit bounds on the normal derivative of the solution on the boundary and on its analytic continuation into the complex plane.

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Epigenetic modification of the genome via cytosine methylation is a dynamic process that responds to changes in the growing environment. This modification can also be heritable. The combination of both properties means that there is the potential for the life experiences of the parental generation to modify the methylation profiles of their offspring and so potentially to ‘pre-condition’ them to better accommodate abiotic conditions encountered by their parents. We recently identified high vapor pressure deficit (vpd)-induced DNA methylation at two gene loci in the stomatal development pathway and an associated reduction in leaf stomatal frequency.1 Here, we test whether this epigenetic modification pre-conditioned parents and their offspring to the more severe water stress of periodic drought. We found that three generations of high vpd-grown plants were better able to withstand periodic drought stress over two generations. This resistance was not directly associated with de novo methylation of the target stomata genes, but was associated with the cmt3 mutant’s inability to maintain asymmetric sequence context methylation. If our finding applies widely, it could have significant implications for evolutionary biology and breeding for stressful environments.

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Nine of the compounds [M(L2−)(p-cymene)] (M = Ru, Os, L2− = 4,6-di-tert-butyl-N-aryl-o-amidophenolate) were prepared and structurally characterized (Ru complexes) as coordinatively unsaturated, formally 16 valence electron species. On L2−-ligand based oxidation to EPR-active iminosemiquinone radical complexes, the compounds seek to bind a donor atom (if available) from the N-aryl substituent, as structurally certified for thioether and selenoether functions, or from the donor solvent. Simulated cyclic voltammograms and spectroelectrochemistry at ambient and low temperatures in combination with DFT results confirm a square scheme behavior (ECEC mechanism) involving the Ln ligand as the main electron transfer site and the metal with fractional (δ) oxidation as the center for redox-activated coordination. Attempts to crystallize [Ru(Cym)(QSMe)](PF6) produced single crystals of [RuIII(QSMe •−)2](PF6) after apparent dissociation of the arene ligand.

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The resonance effect of microcrystalline cellulose/castor oil electrorheological (ER) suspensions was studied in a compressed oscillatory squeeze flow under external electric fields. The resonance frequency first increases linearly with increasing external held, and then shift to high-field plateau. The amplitudes of resonance peak increase sharply with the applied fields in the range of 0.17-1.67kV/mm. The phase difference of the reduced displacement relative to the excitation force inverses in the case of resonance. A viscoelasticity model of the ER suspensions, which offers both the equivalent stiffness and the viscous damping, should be responsible for the appearance of resonance. The influence of the electric field on the resonance frequency and the resonance hump is consistent qualitatively with the interpretation of our proposed model. Storage modulus G' was presented for the purpose of investigating this influence.

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Transient responses of electrorheological fluids to square-wave electric fields in steady shear are investigated by computational simulation method. The structure responses of the fluids to the field with high frequency are found to be very similar to that to the field with very low frequency or the sudden applied direct current field. The stress rise processes are also similar in both cases and can be described by an exponential expression. The characteristic time tau of the stress response is found to decrease with the increase of the shear rate (gamma) over dot and the area fraction of the particles phi(2). The relation between them can be roughly expressed as tau proportional to(gamma) over dot(-3/4)phi(2)(-3/2). The simulation results are compared with experimental measurements. The aggregation kinetics of the particles in steady shear is also discussed according to these results.

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We propose and analyse a hybrid numerical–asymptotic hp boundary element method (BEM) for time-harmonic scattering of an incident plane wave by an arbitrary collinear array of sound-soft two-dimensional screens. Our method uses an approximation space enriched with oscillatory basis functions, chosen to capture the high-frequency asymptotics of the solution. We provide a rigorous frequency-explicit error analysis which proves that the method converges exponentially as the number of degrees of freedom N increases, and that to achieve any desired accuracy it is sufficient to increase N in proportion to the square of the logarithm of the frequency as the frequency increases (standard BEMs require N to increase at least linearly with frequency to retain accuracy). Our numerical results suggest that fixed accuracy can in fact be achieved at arbitrarily high frequencies with a frequency-independent computational cost, when the oscillatory integrals required for implementation are computed using Filon quadrature. We also show how our method can be applied to the complementary ‘breakwater’ problem of propagation through an aperture in an infinite sound-hard screen.

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A practical single-carrier (SC) block transmission with frequency domain equalisation (FDE) system can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such Hammerstein channels, the standard SC-FDE scheme no longer works. We propose a novel Bspline neural network based nonlinear SC-FDE scheme for Hammerstein channels. In particular, we model the nonlinear HPA, which represents the complex-valued static nonlinearity of the Hammerstein channel, by two real-valued B-spline neural networks, one for modelling the nonlinear amplitude response of the HPA and the other for the nonlinear phase response of the HPA. We then develop an efficient alternating least squares algorithm for estimating the parameters of the Hammerstein channel, including the channel impulse response coefficients and the parameters of the two B-spline models. Moreover, we also use another real-valued B-spline neural network to model the inversion of the HPA’s nonlinear amplitude response, and the parameters of this inverting B-spline model can be estimated using the standard least squares algorithm based on the pseudo training data obtained as a byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse Bspline neural network model obtained in time domain. The effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels is demonstrated in a simulation study.

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This brief proposes a new method for the identification of fractional order transfer functions based on the time response resulting from a single step excitation. The proposed method is applied to the identification of a three-dimensional RC network, which can be tailored in terms of topology and composition to emulate real time systems governed by fractional order dynamics. The results are in excellent agreement with the actual network response, yet the identification procedure only requires a small number of coefficients to be determined, demonstrating that the fractional order modelling approach leads to very parsimonious model formulations.

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Six Australian native herbaceous perennial legumes (Lotus australis, Swainsona colutoides, Swainsona swainsonioides, Cullen tenax, Glycine tabacina and Kennedia prorepens) were assessed in the glasshouse for nutritive value, soluble condensed tannins and production of herbage in response to three cutting treatments (regrowth harvested every 4 and 6 weeks and plants left uncut for 12 weeks). The Mediterranean perennial legumes Medicago sativa and Lotus corniculatus were also included. Dry matter (DM) yield of some native legumes was comparable to L. corniculatus, but M. sativa produced more DM than all species except S. swainsonioides after 12 weeks of regrowth. Dry matter yield of all native legumes decreased with increased cutting frequency, indicating a susceptibility to frequent defoliation. Shoot in vitro dry matter digestibility (DMD) was high (>70%) in most native legumes, except G. tabacina (65%) and K. prorepens (55%). Crude protein ranged from 21-28% for all legumes except K. prorepens (12%). More frequent cutting resulted in higher DMD and crude protein in all species, except for the DMD of C. tenax and L. australis, which did not change. Concentrations of soluble condensed tannins were 2-9 g/kg DM in the Lotus spp., 10-18 g/kg DM in K. prorepens and negligible (<1 g/kg) in the other legumes. Of the native species, C. tenax, S. swainsonioides and L. australis showed the most promise for use as forage plants and further evaluation under field conditions is now warranted.

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The El Niño/Southern Oscillation is Earth’s most prominent source of interannual climate variability, alternating irregularly between El Niño and La Niña, and resulting in global disruption of weather patterns, ecosystems, fisheries and agriculture1, 2, 3, 4, 5. The 1998–1999 extreme La Niña event that followed the 1997–1998 extreme El Niño event6 switched extreme El Niño-induced severe droughts to devastating floods in western Pacific countries, and vice versa in the southwestern United States4, 7. During extreme La Niña events, cold sea surface conditions develop in the central Pacific8, 9, creating an enhanced temperature gradient from the Maritime continent to the central Pacific. Recent studies have revealed robust changes in El Niño characteristics in response to simulated future greenhouse warming10, 11, 12, but how La Niña will change remains unclear. Here we present climate modelling evidence, from simulations conducted for the Coupled Model Intercomparison Project phase 5 (ref. 13), for a near doubling in the frequency of future extreme La Niña events, from one in every 23 years to one in every 13 years. This occurs because projected faster mean warming of the Maritime continent than the central Pacific, enhanced upper ocean vertical temperature gradients, and increased frequency of extreme El Niño events are conducive to development of the extreme La Niña events. Approximately 75% of the increase occurs in years following extreme El Niño events, thus projecting more frequent swings between opposite extremes from one year to the next.

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El Niño events are a prominent feature of climate variability with global climatic impacts. The 1997/98 episode, often referred to as ‘the climate event of the twentieth century’1, 2, and the 1982/83 extreme El Niño3, featured a pronounced eastward extension of the west Pacific warm pool and development of atmospheric convection, and hence a huge rainfall increase, in the usually cold and dry equatorial eastern Pacific. Such a massive reorganization of atmospheric convection, which we define as an extreme El Niño, severely disrupted global weather patterns, affecting ecosystems4, 5, agriculture6, tropical cyclones, drought, bushfires, floods and other extreme weather events worldwide3, 7, 8, 9. Potential future changes in such extreme El Niño occurrences could have profound socio-economic consequences. Here we present climate modelling evidence for a doubling in the occurrences in the future in response to greenhouse warming. We estimate the change by aggregating results from climate models in the Coupled Model Intercomparison Project phases 3 (CMIP3; ref. 10) and 5 (CMIP5; ref. 11) multi-model databases, and a perturbed physics ensemble12. The increased frequency arises from a projected surface warming over the eastern equatorial Pacific that occurs faster than in the surrounding ocean waters13, 14, facilitating more occurrences of atmospheric convection in the eastern equatorial region.