Gaussianity and linearity tests of hydrologic time series

Although the non-Gaussian nature of many hydrologic time series is well recognized and their nonlinearity is suspected, neither property is well tested. This situation has existed partly because of a lack of appropriate tests. Recently Hinich (1982) has developed a test to test the linearity of time series which is based on the bispectral characteristics of the series. This test is used in this study to investigate the linearity and non-Gaussian characteristics of annual and daily rainfall and runoff series. The annual series may be modeled by linear models with Gaussian inputs. The daily data, on the other hand, often demonstrate nonlinear characteristics and are non-Gaussian as well.     

Study of the Probability Density Functions From a Large-Eddy Simulation for a Stably Stratified Boundary Layer

Turbulence in a non-strongly stably stratified large-eddy simulation (LES) case is studied through probability density functions (PDFs) to obtain additional information than that provided by classical LES averages. The PDFs are computed for one hour within the steady-state regime at three different levels: near the surface, in the middle and at the top of the boundary layer, for the wind components and the temperature. The physical significance of these PDFs from LES is discussed and they are compared to those obtained from observations. The analysis of the eddy structures within the stably stratified boundary layer is made through the combined study of the fields, the spectra and the statistical moments obtained from the PDFs and joint PDFs. The homogeneity of the fields is inspected through a comparison of the ensemble to the temporal and the spatial PDFs, showing that the ergodic theorem is not fulfilled. To this end, the sensitivity of the PDF moments to the LES resolution is explored.     

陆地地震勘探随机噪声统计特性

在地震勘探随机噪声压制领域,噪声通常被假设为平稳、高斯随机过程的信息.然而,在某些情况下,这样的假设并不准确.本文应用现代统计检验方法对地震勘探随机噪声的平稳性、高斯性和线性进行了研究.结果表明地震勘探随机噪声并不是传统意义上认为的平稳随机过程,其平稳性受到噪声时长和采集环境复杂程度的影响.发现噪声时间越长,采集环境越复杂,随机噪声的平稳性越差,但是对于短时长随机噪声而言,其可以近似认为是平稳的.同时,采集环境的复杂程度也影响着随机噪声的高斯性和线性特性,环境条件越复杂,随机噪声高斯性越好,线性特性越差,但总的来说随机噪声可以归为线性非高斯随机过程.     

CTD资料正态性检验方法的探讨

对经预处理并去倾后的ＣＴＤ温一深序列了正态性检验。检验时先用根据序列的自回归模型构成的滤波器去序列元素间之相关性产生白噪声序列，而后用Ｘ＾２－拟合优度检验法对此白噪声序列作正态性检验，得到了较合理的结果。     

南沙海区温度细结构正态性检验

对南沙海区观测得的部分温度脉动一深度序列作了正态检验。检验时先用根据序列的自回归模型构成的滤波器滤去序列元素间之相关性产生白噪声序列 ,而后用 χ2一拟合优度检验法对此白噪声序列作正态性独立同分布检验并对偏度与峰度作了检验。检验结果表明 ,除少数样本近似正态分布外 ,大多数样本的分布为非正态的 ,这是在样本内小于内波尺度的不可逆细结构所起的作用     

Statistical analysis of background noise in seismic prospecting

From a conventional viewpoint, seismic‐prospecting background noise is usually regarded as the product of a stationary and Gaussian stochastic process. In this paper, we use statistical methods to investigate the properties of the land‐seismic‐prospecting background noise on stationarity, Gaussianity, power spectral density, and spatial correlation. We use and analyse the passive noise records collected by receiver arrays at different typical geological environments (desert, steppe, and mountainous regions). Differences exist in the statistical properties of the background noise from different geological environments, but we still find some common characteristics. It is shown that the background noise is not strictly stationary and has different stationary properties over different timescales. Most of the noise records appear to be a Gaussian process when examined over a period of about 20 s but are found to be non‐Gaussian when examined over shorter periods of about 1 s. The background noise is a kind of colored noise, and its energy mainly concentrates in the low‐frequency bands. We also find that the spatial correlation of the background noise is weak. The results of this paper provide a scientific understanding about the properties of seismic‐prospecting background noise.