Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.     

Multifractal detrended fluctuation analysis for clustering structures of electricity price periods

A new model is proposed to investigate the structure of electricity price in different time periods. A popular method — the multifractal detrended fluctuation analysis (MF-DFA) method is employed to analyze the features achieved from three types of electricity price data after filtering some trends by Fourier detrended fluctuation function. Twelve multifractal parameters are calculated and selected as the characteristic indicators for comparison. Moreover, the minimum number of indicators is determined so that the discriminant accuracy reaches maximum based on Fisher’s linear discriminant algorithm (Fisher’s LDA) for each time period. These indicators form a multi-dimensional space, in which each point represents a price time series. This allows us to cluster the three price time periods, namely, the low price time periods, the average price time periods and the peak price time periods. Fisher’s LDA is employed to evaluate the discriminant accuracy on these three kinds of time periods. Our analysis is then applied to the data in California1999–2000 and PJM2001–2002 electricity markets to demonstrate the applicability of our methods.     

Correlation between detrended fluctuation analysis and the Lempel–Ziv complexity in nonlinear time series analysis

We focus on the study of the correlation between the detrended fluctuation analysis (DFA) and the Lempel-Ziv complexity (LZC) in nonlinear time series analysis in this paper. Typical dynamical systems including logistic map and Duffing model are investigated. Moreover, the influences of the Gaussian random noise on both DFA and LZC are analyzed. The results show a high correlation between DFA and LZC, which can quantify the non-stationarity and the nonlinearity of the time series, respectively. With the enhancement of the random component, the exponent α and the normalized complexity index C show increasing trends. In addition, C is found to be more sensitive to the fluctuation in the nonlinear time series than α. Finally, the correlation between DFA and LZC is applied to the feature extraction of vibration signals for a reciprocating compressor gas valve, and an effective fault diagnosis result is obtained.     

Surface ozone at mid latitudes in the past century

Summary Surface ozone observations were made from the second half of the past century up to the first decades of the present century at many observatories in the world using the Sch?nbein technique. Although there are some uncertainties about that technique and on possible interferences, accurate readings can be converted to present-time concentrations (p.p.b.v.). The analysis of data series gathered at some sites at mid-latitudes of the Northern and Southern hemispheres leads to the conclusion that a century ago the mean ozone level was about 10 p.p.b.v., the seasonal course changing in relation with local climatology. From that time anthropogenic emissions have increased the ozone level, more at Northern than at Southern latitudes.     

Temporal-spatial diversities of long-range correlation for relative humidity over China

Long-range correlations of daily relative humidity anomaly records from 191 weather stations over China during 1951-2000 are analyzed by means of fluctuation analysis (FA) and detrended fluctuation analysis (DFA). The information about trends in the relative humidity records can be obtained by comparing the FA curve with DFA curves. The daily relative humidity fluctuations are found to be power-law correlated and their average scaling exponent is higher than that of the temperature fluctuations, indicating that the relative humidity fluctuations take different statistical behavior from other meteorological quantities and there exists a stronger persistence in the relative humidity fluctuations. Furthermore, it is also found that these power-law scaling properties vary from station to station and show both spatial and temporal diversities, which may be explained by a proposed mechanism.     

Levels of complexity in turbulent time series for weakly and high Reynolds number

We use the detrended fluctuation analysis (DFA), the detrended cross correlation analysis (DCCA) and the magnitude and sign decomposition analysis to study the fluctuations in the turbulent time series and to probe long-term nonlinear levels of complexity in weakly and high turbulent flow. The DFA analysis indicate that there is a time scaling region in the fluctuation function, segregating regimes with different scaling exponents. We discuss that this time scaling region is related to inertial range in turbulent flows. The DCCA exponent implies the presence of power-law cross correlations. In addition, we conclude its multifractality for high Reynold’s number in inertial range. Further, we find that turbulent time series exhibit complex features by magnitude and sign scaling exponents.     

On the quality of the Nimbus 7 LIMS version 6 ozone for studies of the middle atmosphere

The Nimbus 7 Limb Infrared Monitor of the Stratosphere (LIMS) radiance profile dataset of 1978/79 was reconditioned and reprocessed to Version 6 (V6) profiles of temperature and species that are improved significantly over those from Version 5 (V5). The LIMS V6 dataset was archived for public use in 2002. Improvements for its ozone include: (1) a more accurate accounting for instrument and spacecraft motion effects in the radiances, (2) the use of better spectroscopic line parameters for its ozone forward model, (3) retrievals of all its scans, (4) more accurate and compatible temperature versus pressure profiles (or T(p)) that are needed for the registration of the ozone radiances and for the removal of temperature effects from them, and (5) a better accounting for interfering species in the lower stratosphere. The retrieved V6 ozone profiles extend from near cloud top altitudes to about 80 km and from 64S to 84N latitude with better sampling along the orbit than for the V5 dataset. Calculated estimates of the single-profile precision and accuracy are provided; precision estimates based on the data themselves are of order 3% or better from 1 to 30 hPa. Estimates of total systematic error are hard to generalize because the separate sources of error may not all be of the same sign, and they depend somewhat on the atmospheric state. It is estimated that the accuracy of the V6 zonal mean ozone distribution is within ±9% from 50-10 hPa, improving to ±7% in the uppermost stratosphere. Simulation studies show that the LIMS T(p) retrievals are underestimating slightly the small amplitudes of the atmospheric temperature tides, which affect the retrieved day/night ozone differences. There are also small biases in the middle to lower stratosphere for the ascending versus descending node LIMS ozone, due principally to not accounting for the asymmetric weighting of its radiance within the tangent layer. The total accuracy for the LIMS ozone was assessed by comparing its daily zonal mean, daytime distributions against those from the Nimbus 7 SBUV Version 8 (V8) dataset for the same period. The LIMS V6 ozone agrees well with SBUV, except between 2 and 5 hPa where the LIMS ozone is greater. That bias is related to the differing vertical resolutions and forward models for the two experiments. The accuracy for LIMS V6 ozone in the lower stratosphere is improved over that reported for V5, as indicated by a small set of V6 comparisons with ECC ozonesonde profiles. Comparisons of diurnal, photochemical model calculations with the monthly-averaged, upper stratospheric ozone obtained with LIMS V6 indicate only a slight ozone deficit for the model at about 2 hPa. However, that deficit exhibits little to no seasonal variation and is in good agreement with similar model comparisons for a seasonal time series of ozone obtained with ground-based microwave instruments. Because the LIMS V6 ozone has improved accuracy and sampling versus that of V5 for the lower stratosphere it should now be possible to conduct quantitative studies of ozone transport and chemistry for the northern hemisphere, polar winter/spring of 1978/79—a time period when the catalytic loss of ozone due to reactive chlorine should not have been a major factor for the Arctic stratosphere.     

基于双树复小波变换的非平稳时间序列去趋势波动分析方法

多重分形去趋势波动分析是研究非平稳时间序列非均匀性和奇异性的有效工具, 针对该方法中趋势项难以确定的问题, 提出一种基于双树复小波变换的方法, 实现了非平稳信号的多重分形自适应去趋势波动分析. 利用双树复小波变换提取信号的多尺度趋势和波动信息, 通过小波系数的希尔伯特变换确定每个时间尺度不重叠子区间的长度, 使多重分形分析具有信号自适应性及较高的计算效率. 以具有解析形式分形特征的倍增级联信号和分数布朗运动时间序列为例验证本文方法的有效性, 所得结果与解析解相吻合. 与传统的多项式去趋势多重分形方法相比, 本文方法根据信号自身特点自适应地确定信号的趋势和不重叠等长度子区间长度, 所得结果更加精确. 对倍增级联信号时间序列取不同的长度, 验证了算法的稳定性. 分别与基于极大重叠离散小波变换和离散小波变换多重分形方法进行比较, 表明本文方法具有更精确的结果和更快的运算速度.     

Turbulence over arrays of obstacles in low temperature helium gas

Turbulence produced in low temperature helium gas flowing over arrays of rectangular- and triangular-shaped blunt obstacles is investigated experimentally. The set-up allows both low fluctuation rates (down to 8%), and high microscale Reynolds numbers, (up to 1 150). The forced Kolmogorov equation is found to apply accurately. Similar to another flow configuration (counter rotating flow case [1]), the analysis of the flatness factor evolution with the Reynolds number reveals a transitional behavior around 650. Received 26 August 1999 and Received in final form 28 August 2000     

Features of interannual variations of ozone in the middle stratosphere over Moscow according to observations at millimeter waves

The features of interannual variations of ozone in the middle stratosphere over Moscow in cold half-years since 1995 to 2015 are considered. These features are most pronounced in two separated groups of winters (six winters in each group) in December–January. It appeared that the seasonal variation of ozone averaged within each group is characterized by a higher ozone concentration \({C_{{O_3}}}\) in group I (in comparison with group II) in December and lower values in January. The differences in the seasonal variation of ozone between these groups at the level of 10 mbar in December and January exceed 2 ppm. A feature of the stratosphere circulation for half-year group I is the existence of a stable polar vortex and the absence of strong midwinter perturbations and sudden stratospheric warmings. On the contrary, for cold half-years of group II, the appearance of strong stratospheric warmings in January–February is in common. The results presented provide a quantitative estimate of the effect of these stratospheric warmings on ozone of the middle stratosphere overMoscow.     

一种基于重标极差方法的动力学结构突变检测新方法

提出了一种针对相关性时间序列动力学结构突变检测的新方法——滑动移除重标极差分析.数值试验表明,新方法能够准确的检测出理想序列中的动力学结构突变,其检测结果对于子序列的长度依赖性较小,而且具有很强的抗噪能力,弥补了滑动去趋势波动分析的不足. 关键词： 标度指数 滑动移除重标极差分析 滑动去趋势波动分析 动力学结构突变     

Effect of electronegative impurities on the generation of ozone in air

A self-consistent numerical model is used to investigate the effect of electronegative impurities on the ozone yield in a dielectric barrier discharge with a pulsed voltage supply, and the range of impurity concentrations giving a substantial (two-or threefold) increase in the ozone yield is established. Sulfur hexafluoride is considered as a representative component having strong electronegative properties. It is shown that a tiny admixture [SF₆]<0.1% can have an appreciable effect on the characteristics of an ozonator. The calculations are compared with published experimental data and given an interpretation. Zh. Tekh. Fiz. 69, 49–52 (January 1999)     

Fractal analysis of river flow fluctuations

We use some fractal analysis methods to study river flow fluctuations. The result of the Multifractal Detrended Fluctuation Analysis (MF-DFA) shows that there are two crossover timescales at s_1×∼12 and s_2×∼130 months in the fluctuation function. We discuss how the existence of the crossover timescales are related to a sinusoidal trend. The first crossover is due to the seasonal trend and the value of second one is approximately equal to the well-known cycle of sun activity. Using Fourier Detrended Fluctuation Analysis, the sinusoidal trend is eliminated. The values of Hurst exponents of the runoff water of rivers without the sinusoidal trend show a long-range correlation behavior. For the Daugava river, the value of Hurst exponent is 0.52±0.01 and also we find that these fluctuations have multifractal nature. Comparing the MF-DFA results for the remaining data set of Daugava river to those for shuffled and surrogate series, we conclude that its multifractal nature is almost entirely due to the broadness of probability density function.     

Detrended fluctuation analysis on spot and futures markets of West Texas Intermediate crude oil

In this paper, we study the auto-correlations and cross-correlations of West Texas Intermediate (WTI) crude oil spot and futures return series employing detrended fluctuation analysis (DFA) and detrended cross-correlation analysis (DCCA). Scaling analysis shows that, for time scales smaller than a month, the auto-correlations and cross-correlations are persistent. For time scales larger than a month but smaller than a year, the correlations are anti-persistent, while, for time scales larger than a year, the series are neither auto-correlated nor cross-correlated, indicating the efficient operation of the crude oil markets. Moreover, for small time scales, the degree of short-term cross-correlations is higher than that of auto-correlations. Using the multifractal extension of DFA and DCCA, we find that, for small time scales, the correlations are strongly multifractal, while, for large time scales, the correlations are nearly monofractal. Analyzing the multifractality of shuffled and surrogated series, we find that both long-range correlations and fat-tail distributions make important contributions to the multifractality. Our results have important implications for market efficiency and asset pricing models.     

基于多分辨分析的高炉铁水含硅量波动多重分形辨识

以包钢6号高炉、邯钢7号高炉和莱钢1号高炉在线采集的铁水含硅量(［Si］)的时间序列为样本, 利用多分辨分析剔除样本的长期趋势,对样本保留的波动趋势进行多重分形特征辨识. 通过计算广义Hurst指数、尺度函数、多重分形谱, 全面、细致量化了序列的局部及不同层次的波动奇异性. 计算结果表明: 去除长期趋势后, 三座高炉［Si］序列的波动呈现显著多重分形特征, 这样的波动过程仅用单一的Hurst指数或box维数来描述是不够的. 关键词： 多分辨分析 铁水含硅量 波动 多重分形     

Long-range dependence in tree-ring width time series of Austrocedrus Chilensis revealed by means of the detrended fluctuation analysis

By using the detrended fluctuation analysis and detrended moving average method, 823 time series of tree-ring widths in Austrocedrus Chilensis in Patagonia were analyzed. The tree-ring widths of A. Chilensis have been widely used for climatological studies. The results point out to the presence of significant scaling in the temporal fluctuations of tree-ring, which is not due to singular probability density function of the widths but due to the presence of long-range correlations. Such results are in good agreement with those concerning the evidence of long-range dependencies in weather time series.     

Relationships of exponents in multifractal detrended fluctuation analysis and conventional multifractal analysis

Multifractal detrended fluctuation analysis (MF-DFA) is a relatively new method of multifractal analysis. It is extended from detrended fluctuation analysis (DFA), which was developed for detecting the long-range correlation and the fractal properties in stationary and non-stationary time series. Although MF-DFA has become a widely used method, some relationships among the exponents established in the original paper seem to be incorrect under the general situation. In this paper, we theoretically and experimentally demonstrate the invalidity of the expression τ(q)=qh(q)-1 stipulating the relationship between the multifractal exponent τ(q) and the generalized Hurst exponent h(q). As a replacement, a general relationship is established on the basis of the universal multifractal formalism for the stationary series as τ(q)=qh(q)-qH'-1, where H' is the nonconservation parameter in the universal multifractal formalism. The singular spectra, α and f(α), are also derived according to this new relationship.