Statistical techniques analysis of SST and SLP in the Persian Gulf

Thirty-four years of data (1967-2000) are used to investigate the variability pattern relevant to air-sea interaction in the Persian Gulf. The patterns are derived using statistical techniques, such as empirical orthogonal function (EOF) and singular value decomposition (SVD). Statistical analysis methods are applied to determine the coupled modes of variability of monthly sea surface temperature (SST) and sea level pressure (SLP). The significant of the air-sea interaction is found by a strong resemblance between EOF and SVD eigenvectors and expansion coefficients of SST and SLP. We find that the four leading EOF patterns of SST together account for 99.8% of the total monthly SST variance and 94.4% of the SLP variance. The zero contour in the first SST EOF identified the front which separates the Persian Gulf cyclonic gyres.The SVD modes provide more information on the coupling between the fields than the modes obtained by EOF methods. Lagged correlation analysis between SVD1(SLP) and SVD1(SST) indicates that the coupling is strongest when SLP leads SST by −12, −6, 6 and 12 months. Therefore, the first mode of the SVD analysis seems to depict an air-to-sea forcing, in which the sea response to the atmospheric changes appears with an semiannual and interannual time lag.The two leading SVD modes of variability of the coupled SST and SLP fields account for 99.6% of the total variance. The main patterns of both variables of variability of both variables independently provide considerable information on the coupling, but only one of the two variables dominates each of the two first coupled modes.The first coupled mode of variability between the SST and atmospheric pressure can be described as a strengthening and weakening of the cyclonic gyres, which seems to force fluctuations in a north-south dipole structure in the SST by Ekman upwelling which is a wind-related process. The atmospheric forcing of the SST changes is detectable in the sea with a lag of 1 and 6 months.     

基于贝叶斯理论的全球海温异常对500 hPa 温度场的影响分析

本文利用经验正交函数(EOF) 将海表温度(SST) 距平场进行分解, 得到一组相互正交的模态构成重构空间, 然后在该空间中展开500 hPa温度场, 进一步借助贝叶斯分析方法定义各个模态对温度场的影响指数, 并研究指数随不同海温分布型(模态) 的变化特征. 结果发现SST场在4-6月份对500 hPa温度场的影响较大, 且气候发生转变后, 不同海温分布型对温度场的影响不同.     

PRESSURE FLUCTUATION AND FLOW REGIMES OF AIR-WATER FLOW IN A SMALL TUBE

Previous studies have shown that flow regimes of gas-liquid flow in small tubes and channels are related to pressure drop fluctuations along the flow passages, and some flow regimes exhibit characteristic pressure fluctuation patterns. This has led to the possibility of using pressure fluctuations to identify flow patterns. This article presents a test program to show experimentally the relationship of pressure fluctuations to gas bubbles, liquid slugs, and waves on a gas-liquid interface in small tubes and channels. In the experiment, a high-speed video camera was used to examine flow mixture passing a pressure tap. Pressure fluctuation at the tap was measured simultaneously using a pressure transducer. The results have shown that high-frequency pressure fluctuation is related to gas bubbles, liquid slugs, or waves on a gas-liquid interface passing the pressure tap. It has found that low-frequency pressure waves are related to flow regimes in the test tube. This research has provided further information for flow regime identification using pressure fluctuation traces.     

Successive bifurcations in a simple model of atmospheric zonal-flow vacillation

Low-frequency variability of the atmospheric flow in the Southern Hemisphere is dominated by irregular changes in the latitude and intensity of the mid-latitude eastward jet about its climatological mean state. This phenomenon, known as atmospheric zonal-flow vacillation, is characterized by the existence of two persistent states of the zonal (i.e., east-west oriented) jet and irregular transitions between them. Nonlinear interactions between the mean flow and the waves play a key role in the dynamics of this vacillation. In the present study, we develop a low-order, deterministic model for the nonlinear dynamics of atmospheric zonal-flow vacillation. Multiple equilibria arise in this model's zonal-mean flow, that is, in the longitudinal flow averaged along a given latitude circle. These equilibria bear a strong resemblance to the two persistent flow regimes found in Southern Hemisphere observations. The two equilibrium states are maintained by wave forcing against surface drag, as in the observations. Successive bifurcations to periodic and chaotic zonal-mean flow regimes occur as the model's dissipation parameter is reduced. (c) 2002 American Institute of Physics.     

Changing characteristics and spatial differentiation of spring precipitation in Southwest China during 1961-2012

In this study,we analyze spring precipitation from 92 meteorological stations spanning between 1961 and 2012 to understand temporal-spatial variability and change of spring precipitation over Southwest China.Various analysis methods are used for different purposes,including empirical orthogonal function(EOF) analysis and rotated EOF(REOF) for analyzing spatial structure change of precipitation anomaly,and the Mann-Kendall testing method to determine whether there were abrupt changes during the analyzed time span.We find that the first spatial mode of the precipitation has a domain uniform structure;the second is dominated by a spatial dipole;and the third contains five variability centers.The 2000 s is the decade with the largest amount of precipitation while the 1990 s is the decade with the smallest amount of precipitation.The year-to-year difference of that region is large:the amount of the largest precipitation year doubles that of the smallest precipitation year.We also find that spring precipitation in Southwest China experienced a few abrupt changes:a sudden increase at 1966,a sudden decrease at 1979,and a sudden increase at 1995.We speculate that the spring precipitation will increase gradually in the next two decades.     

Similar patterns of learning and performance variability for human discrimination of interaural time differences at high and low frequencies

Sound source localization on the horizontal plane is primarily determined by interaural time differences (ITDs) for low-frequency stimuli and by interaural level differences (ILDs) for high-frequency stimuli, but ITDs in high-frequency complex stimuli can also be used for localization. Of interest here is the relationship between the processing of high-frequency ITDs and that of low-frequency ITDs and high-frequency ILDs. A few similarities in human performance with high- and low-frequency ITDs have been taken as evidence for similar ITD processing across frequency regions. However, such similarities, unless accompanied by differences between ITD and ILD performance on the same measure, could potentially reflect processing attributes common to both ITDs and ILDs rather than to ITDs only. In the present experiment, both learning and variability patterns in human discrimination of ITDs in high-frequency amplitude-modulated tones were examined and compared to previously obtained data with low-frequency ITDs and high-frequency ILDs. Both patterns for high-frequency ITDs were more similar to those for low-frequency ITDs than for high-frequency ILDs. These results thus add to the evidence supporting similar ITD processing across frequency regions, and further suggest that both high- and low-frequency ITD processing is less modifiable and more noisy than ILD processing.     

Reduced models of atmospheric low-frequency variability: Parameter estimation and comparative performance

Low-frequency variability (LFV) of the atmosphere refers to its behavior on time scales of 10–100 days, longer than the life cycle of a mid-latitude cyclone but shorter than a season. This behavior is still poorly understood and hard to predict. The present study compares various model reduction strategies that help in deriving simplified models of LFV.Three distinct strategies are applied here to reduce a fairly realistic, high-dimensional, quasi-geostrophic, 3-level (QG3) atmospheric model to lower dimensions: (i) an empirical–dynamical method, which retains only a few components in the projection of the full QG3 model equations onto a specified basis, and finds the linear deterministic and the stochastic corrections empirically as in Selten (1995) [5]; (ii) a purely dynamics-based technique, employing the stochastic mode reduction strategy of Majda et al. (2001) [62]; and (iii) a purely empirical, multi-level regression procedure, which specifies the functional form of the reduced model and finds the model coefficients by multiple polynomial regression as in Kravtsov et al. (2005) [3]. The empirical–dynamical and dynamical reduced models were further improved by sequential parameter estimation and benchmarked against multi-level regression models; the extended Kalman filter was used for the parameter estimation.Overall, the reduced models perform better when more statistical information is used in the model construction. Thus, the purely empirical stochastic models with quadratic nonlinearity and additive noise reproduce very well the linear properties of the full QG3 model’s LFV, i.e. its autocorrelations and spectra, as well as the nonlinear properties, i.e. the persistent flow regimes that induce non-Gaussian features in the model’s probability density function. The empirical–dynamical models capture the basic statistical properties of the full model’s LFV, such as the variance and integral correlation time scales of the leading LFV modes, as well as some of the regime behavior features, but fail to reproduce the detailed structure of autocorrelations and distort the statistics of the regimes. Dynamical models that use data assimilation corrections do capture the linear statistics to a degree comparable with that of empirical–dynamical models, but do much less well on the full QG3 model’s nonlinear dynamics. These results are discussed in terms of their implications for a better understanding and prediction of LFV.     

Should structure functions be used to estimate power laws in turbulence? A comparative study

Second-order structure functions are widely used to characterize turbulence in the inertial range because they are simple to estimate, particularly in comparison to spectral density functions and wavelet variances. Structure function estimators, however, are highly autocorrelated and, as a result, no suitable theory has been established to provide confidence intervals for turbulence parameters when determined via regression fits in log/log space. Monte Carlo simulations were performed to compare the performance of structure function estimators of turbulence parameters with corresponding multitaper spectral and wavelet variance estimators. The simulations indicate that these latter estimators have smaller variances than estimators based upon the structure function. In contrast to structure function estimators, the statistical properties of the multitaper spectral and wavelet variance estimators allow for the construction of confidence intervals for turbulence parameters. The Monte Carlo simulations also confirm the validity of the statistical theory behind the multitaper spectral and wavelet variance estimators. The strengths and weaknesses of the various estimators are further illustrated by analyzing an atmospheric temperature time series.     

一种快速稀疏分解图像去噪新方法*

提出了一种基于分层树型结构正交匹配追踪算法的快速图像去噪方法.通过选择高斯函数和墨西哥草帽小波母函数构建混合冗余字典,采用分层树状结构表示字典,结合构正交匹配追踪算法,实现图像稀疏表示,提高了图像表示的稀疏性,降低了算法的复杂度.依据噪音能量阈值,通过多次迭代达到图像去噪的目的.实验结果表明,在相同的噪音水平下,该迭代去噪算法取得了较高的较好的PSNR,获得更好的视觉效果.     

一种快速稀疏分解图像去噪新方法

提出了一种基于分层树型结构正交匹配追踪算法的快速图像去噪方法.通过选择高斯函数和墨西哥草帽小波母函数构建混合冗余字典,采用分层树状结构表示字典,结合构正交匹配追踪算法,实现图像稀疏表示,提高了图像表示的稀疏性,降低了算法的复杂度.依据噪音能量阈值,通过多次迭代达到图像去噪的目的.实验结果表明,在相同的噪音水平下,该迭代去噪算法取得了较高的较好的PSNR,获得更好的视觉效果.     

Hopping behavior in the Kuramoto-Sivashinsky equation

We report the first observations of numerical "hopping" cellular flame patterns found in computer simulations of the Kuramoto-Sivashinsky equation. Hopping states are characterized by nonuniform rotations of a ring of cells, in which individual cells make abrupt changes in their angular positions while they rotate around the ring. Until now, these states have been observed only in experiments but not in truly two-dimensional computer simulations. A modal decomposition analysis of the simulated patterns, via the proper orthogonal decomposition, reveals spatio-temporal behavior in which the overall temporal dynamics is similar to that of equivalent experimental states but the spatial dynamics exhibits a few more features that are not seen in the experiments. Similarities in the temporal behavior and subtle differences in the spatial dynamics between numerical hopping states and their experimental counterparts are discussed in more detail.     

On classification of flow regimes in a channel with sudden expansion

Supersonic flows of gas in the vicinity of the bottom region known as flows with sudden expansion have been considered. On the basis of extensive experimental studies, authors have proposed a complete classification of flow regimes: stationary, oscillating, and transient. Hysteresis of the regimes change at total gas pressure increasing and decreasing in front of the nozzle has been found. Typical shock-wave configurations emerging at the jet flowing in a channel at different modes have been determined. The type of shock-wave structure and the nature of interaction of the mixing layer of a jet with the wall or reverse flow flowing into the channel from ambient medium determine the appropriate mode. Combination of physical and numerical experiment with bottom pressure calculation according to the developed semi-empirical model have revealed new flow regimes that were not studied earlier.     

Multiscale analysis of a spatially heterogeneous microscopic traffic model

The microscopic Optimal Velocity (OV) model is posed on an inhomogeneous ring-road, consisting of two spatial regimes which differ by a scaled OV function. Parameters are chosen throughout for which all uniform flows are linearly stable. The large time behaviour of this discrete system is stationary and exhibits three types of macroscopic traffic pattern, each consisting of plateaus joined together by sharp interfaces. At a coarse level, these patterns are determined by simple flow and density balances, which in some cases have non-unique solutions. The theory of characteristics for the classical Lighthill-Whitham PDE model is then applied to explain which pattern the OV model selects. A global analysis of a second-order PDE model is then performed in an attempt to explain some qualitative details of interface structure. Finally, the full microscopic model is analysed at the linear level to explain features which cannot be described by the present macroscopic approaches.     

Influence of timing jitter on nonlinear dynamics of a photonic crystal fiber ring cavity

We demonstrate that timing jitter has a strong influence on supercontinua generated in a photonic crystal fiber ring cavity synchronously pumped by 140?fs pulses. The global dynamics with respect to cavity detuning is analyzed both numerically and experimentally by tracking the cavity pulse energy. The results show that low-frequency timing jitter, induced by both the pump oscillator and the external cavity, masks the fine underlying bifurcation structure of the system. Numerical simulations in the absence of timing jitter reveal that the system dynamics fall into four qualitatively different regimes. The existence of these regimes is experimentally observed in first-return diagrams.     

New nonlinear mechanisms of midlatitude atmospheric low-frequency variability

This paper studies the dynamical mechanisms potentially involved in the so-called atmospheric low-frequency variability, occurring at midlatitudes in the Northern Hemisphere. This phenomenon is characterised by recurrent non-propagating and temporally persistent flow patterns, with typical spatial and temporal scales of 6000-10 000 km and 10-50 days, respectively.We study a low-order model derived from the 2-layer shallow-water equations on a β-plane channel. The main ingredients of the low-order model are a zonal flow, a planetary scale wave, orography, and a baroclinic-like forcing.A systematic analysis of the dynamics of the low-order model is performed using techniques and concepts from dynamical systems theory. Orography height (h₀) and magnitude of zonal wind forcing (U₀) are used as control parameters to study the bifurcations of equilibria and periodic orbits. Along two curves of Hopf bifurcations an equilibrium loses stability () and gives birth to two distinct families of periodic orbits. These periodic orbits bifurcate into strange attractors along three routes to chaos: period doubling cascades, breakdown of 2-tori by homo- and heteroclinic bifurcations, or intermittency ( and ).The observed attractors exhibit spatial and temporal low-frequency patterns comparing well with those observed in the atmosphere. For the periodic orbits have a period of about 10 days and patterns in the vorticity field propagate eastward. For , the period is longer (30-60 days) and patterns in the vorticity field are non-propagating. The dynamics on the strange attractors are associated with low-frequency variability: the vorticity fields show weakening and strengthening of non-propagating planetary waves on time scales of 10-200 days. The spatio-temporal characteristics are “inherited” (by intermittency) from the two families of periodic orbits and are detected in a relatively large region of the parameter plane. This scenario provides a characterisation of low-frequency variability in terms of intermittency due to bifurcations of waves.     

Dynamics of transition processes and structure formation in critical heat-mass transfer regimes during liquid boiling and cavitation

The results of experimental studies concerning the development of critical phenomena and structure formation in the process of boiling in falling films and during liquid cavitation are given. In conditions of stepwise and periodic pulsed surges of a thermal load, the parameters of formed metastable regular structures and critical parameters of heat-releasing surface drying are shown to be determined by the dynamics of moving wetting boundaries in the process of system self-organization. In the case of high-intensity heat fluxes, decomposition of a falling film is determined by propagation regimes of self-maintaining boiling fronts with a complex shape of intermediate structures. The study of ultrasonic cavitation of water, glycerin, and vacuum oil shows that structures of interacting gas-vapor bubbles (having the form of fractal clusters) are formed near the emitter surface. Spatial structures are characterized by a low-frequency divergence of the power spectra and a scale-invariant function of the fluctuation distributions. The experimental results are in good qualitative agreement with the numerical simulations performed within the theory of 1/f fluctuations in the case of nonequilibrium phase transitions in a spatially distributed system.     

Self-organized criticality in 1D stochastic traffic flow model

Results of computer simulations of a 1D particle hopping model of traffic flow are presented. The model is characterized by parallel update and fully asymmetric stochastic hopping dynamics which allows unbounded series of jumps to empty neighbour sites on the right. The considered case of open boundary conditions can be used to model a “bottleneck” situation in traffic. Evidence for self-organized criticality is found in two aspects: the presence of long-range spatial correlations manifested in the shape of density profiles, and long-time temporal correlations showing up in the low-frequency behaviour of the spectral density of the total particle number and flow. A plausible conjecture is to interpret the observed qualitative changes in these features, as a function of the injection rate and the hopping probability, in terms of a nonequilibrium phase transition between a low-density phase and a maximal current phase. This conjecture is supported by the phase diagram obtained in mean-field approximation.     

Atmospheric greenhouse effect in the context of global climate change

Summary Great interest in the problem of the atmospheric greenhouse effect (not only in scientific publications, but also in mass media), on the one hand, and the undoubtfully overemphasised contribution of the greenhouse effect to the global climate change, on the other hand, motivate a necessity to analyse the role which the greenhouse effect plays as a factor of climate change. Significant progress in the analysis of existing observational data as well as succesful development of numerical climate modelling which have been achieved during the recent few years create a basis for a new survey of the atmospheric greenhouse effect in the context of global climate change. Such a survey is the principal purpose of this paper. After discussing a notion of the greenhouse effect, the detailed analysis of the present-day and paleoclimatic observational data has been conducted with subsequent consideration of numerical modelling results. A special attention has been paid to assessments of the greenhouse warmingvs. aerosol cooling. Then possibilities of the early detection of a greenhouse climate signal have been analysed and a few comments on the global climate observing system have been made with the general conclusion that more observations and further numerical modelling efforts are necessary to more reliably assess the contributions of various mechanisms to the observed global climate changes. It is only in the context of a coupled totality of significant climate forming factors and processes that the contribution of the greenhouse effect may be estimated.     

Radiative transfer due to atmospheric water vapor: Global considerations of the earth's energy balance

A simple analytical formulation is presented for describing radiative transfer due to atmospheric water vapor. The radiative model is then applied to a global energy balance for earth, and the net infrared flux to space is expressed in terms of the mean surface temperature and atmospheric lapse rate. Water vapor and clouds are assumed to be the only sources of infrared opacity. When compared with empirical information, and for a global mean surface temperature of 288 K, the radiative model indicates a cloud top altitude for a single effective cloud of 6·8 km. Alternatively, when applied to a more realistic three-cloud formulation, the model predicts a comparable value of 6·5 km for an average cloud top altitude.With respect to changes in mean surface temperature, again comparing with empirical results, a discussion relating to the model suggests that the cloud top altitude decreases with decreasing surface temperature, which results in the surface temperature being roughly twice as sensitive to changes in factors such as planetary albedo than for the conventional assumption of a fixed cloud top altitude. Implications of this are discussed with respect to possible albedo changes due to atmospheric particulate matter as well as cloudiness as a climate feedback mechanism.     

Calculations of internal-wave-induced fluctuations in ocean-acoustic propagation

Variability in the ocean sound-speed field on time scales of a few hours and horizontal spatial scales of a few kilometers is often dominated by the random, anisotropic fluctuations caused by the internal-wave field. Results have been compiled from analytical approaches and from numerical simulations using the parabolic approximation into an efficient set of algorithms for calculating approximations to internal-wave effects on temporal and spatial coherences, coherent bandwidths, and regimes of acoustic fluctuation behavior. These approximate formulas account for the background, deterministic, sound-speed profile and the anisotropy of the internal-wave field, and they also allow for the incorporation of experimentally determined profiles of sound speed, buoyancy frequency, and sound-speed variance. The algorithms start from the geometrical-acoustics approximation, in which the field transmitted from a source can be described completely in terms of rays whose characteristics are determined by the sound speed as a function of position. Ordinary integrals along these rays provide approximations to acoustic-fluctuation quantities due to the statistical effects of internal waves, including diffraction. The results from the algorithms are compared with numerical simulations and with experimental results for long-range propagation in the deep ocean.