The interanual rainfall variability in Indonesia corresponding to El Niño Southern Oscillation and Indian Ocean Dipole

The Impact of the Indian Ocean Dipole(IOD) and the El Ni?o Southern Oscillation(ENSO) event for Indonesian rainfall has been investigated for the period from 1950 to 2011. Inter-annual change of IOD and ENSO indices are used to investigate their relationship with Indonesian rainfall. By using the wavelet transform method, we found a positive significant correlation between IOD and Indonesian rainfall on the time scale of nearly 2.5–4 years.Furthermore, the positive significant correlation between ENSO(sea surface temperature anomaly at Ni?o3.4 area indices) and Indonesian rainfall exists for shorter than 2 years and between 5.5 to 6.5-year time scales.     

基于遥感数据和表层声速的全海深声速剖面反演

海洋声速剖面严重影响着水下声传播特性,近实时地获取声速剖面对水下声通信、水下定位、鱼群探测等都有重要意义。单经验正交函数回归（single Empirical Orthogonal Function regression,sEOF-r）方法通过建立声速剖面的经验正交系数与海面遥感数据之间的线性回归关系来反演声速剖面。但是,海洋是一个复杂的动力系统,声速与海面遥感数据并不是简单的线性关系,因此,本文基于Argo历史网格数据,通过自组织映射（Self-Organizing Map,SOM）生成海平面高度异常（Sea Level Anomaly,SLA）、海表面温度（Sea Surface Temperature,SST）等海表遥感数据以及表层声速仪测量的表层声速与声速剖面异常之间的非线性映射;然后利用近实时的海表遥感数据和表层声速反演三维海洋声速场。声速剖面反演的结果表明,在多源信息融合的优势下,本文方法的反演性能最稳定且精度最高,声速剖面的平均反演精度比经典sEOF-r方法提高约2 m/s,比未考虑表层声速的经典SOM方法提高约1 m/s。     

基于文献记录的黑河流域历史时期旱涝特征分析

流域的旱涝灾害特征及其变化规律是流域水资源演变研究的重要内容。利用历史文献资料重建了西北内陆河黑河流域公元0-1949年的旱涝灾害等级序列,结合滑动平均、小波变换处理等方法,探讨了流域历史时期旱涝等级的频数特征、旱涝变化的周期特征及其与气候冷暖和人类活动之间的关系。对公元1000年以后的旱涝灾害规律进行分析,结果表明：流域存在5个旱灾高发阶段（1230-1270年、1430-1530年、1640-1760年、1860-1890年、1900-1940年）,3个涝灾高发期（1650-1690年、1730-1790年、1830-1910年）,并呈现出旱涝灾害频发的态势;1000-1949年期间,流域旱涝灾害存在4个准周期变化,对比发现这与太阳黑子活动等环境变化周期有紧密的联系;1580年以前,气候冷暖是影响旱涝灾害发生的主要因子,但16世纪以后,旱涝灾害交替频发,很可能是人类活动加剧了该现象。所以,定量辨析自然因素和人类活动对流域旱涝灾害的影响将是未来研究的重点方向。     

基于小波包变换的面波分离技术研究

依据面波视速度的分布范围,提出一种新的叠前面波分离技术,即把地震波场分成不受面波影响的波场和受面波影响的波场,然后利用小波包变换对受面波影响的波场进行时频分析,通过分解与重构,从中提取有效波,再将其与不受面波影响的波场合并,就可得到面波分离后的地震波场。该方法在成功分离面波的同时,可使有效波的能量(尤其是其低频能量)不受损失,既有效地保持信号的频宽不变,又提高了记录的信噪比。实际资料的处理结果表明:此方法在叠前面波分离方面具有有良好的效果。     

Detecting multi-scale riverine topographic variability and its influence on Chinook salmon habitat selection

Quantifying geomorphic conditions that impact riverine ecosystems is critical in river management due to degraded riverine habitat, changing flow and thermal conditions, and increasing anthropogenic pressure. Geomorphic complexity at different scales directly impacts habitat heterogeneity and affects aquatic biodiversity resilience. Here we showed that the combination of continuous spatial survey at high resolution, topobathymetric light detection and ranging (LiDAR), and continuous wavelet analysis can help identify and characterize that complexity. We used a continuous wavelet analysis on 1-m resolution topobathymetry in three rivers in the Salmon River Basin, Idaho (USA), to identify different scales of topographic variability and the potential effects of this variability on salmonid redd site selection. On each river, wavelet scales characterized the topographic variability by portraying repeating patterns in the longitudinal profile. We found three major representative spatial wavelet scales of topographic variability in each river: a small wavelet scale associated with local morphology such as pools and riffles, a mid-wavelet scale that identified larger channel unit features, and a large wavelet scale related to valley-scale controls. The small wavelet scale was used to identify pools and riffles along the entire lengths of each river as well as areas with differing riffle-pool development. Areas along the rivers with high local topographic variability (high wavelet power) at all wavelet scales contained the largest features (i.e., deepest or longest pools) in the systems. By comparing the wavelet power for each wavelet scale to Chinook salmon redd locations, we found that higher small-scale wavelet power, which is related to pool-riffle topography, is important for redd site selection. The continuous wavelet methodology objectively identified scales of topographic variability present in these rivers, performed efficient channel-unit identification, and provided geomorphic assessment without laborious field surveys.     

散射波积分方程的Adomian分解解法

在背景模型基础上,求解模型扰动后的地震波散射场,这是目前地震反演中的一个关键步骤.本文将计算数学中求解非线性积分方程的Adomian分解方法,应用到求解标量波散射场的Lippmann-Schwinger积分方程和Ricatti积分方程中,分别得到了散射场的Born序列解和Rytov序列解.通过一维和二维数值算例说明：在满足一定的条件下,散射场的这两种序列解稳定收敛,与传统的Born和Rytov近似解相比,引入散射序列中的高阶项可以更精确地描述地震波散射场.

     

A method for absorption compensation based on adaptive molecular decomposition

In this paper, we present a new method for seismic stratigraphic absorption compensation based on the adaptive molecular decomposition. Using this method, we can remove most of the effects resulting from wavelets truncation and interference which usually exist in the common time-frequency absorption compensation method. Based on the assumption that the amplitude spectrum of the source wavelet is smooth, we first construct a set of adaptive Gabor frames based on the time-variant properties of the seismic signal to transform the signal into the time-frequency domain and then extract the slowly varying component (the wavelet’s time-varying amplitude spectrum) in each window in the time-frequency domain. Then we invert the absorption compensation filter parameters with an objective function defined using the correlation coefficients in each window to get the corresponding compensation filters. Finally, we use these filters to compensate the time-frequency spectrum in each window and then transform the time-frequency spectrum to the time domain to obtain the absorption-compensated signal. By using adaptive molecular decomposition, this method can adapt to isolated and overlapped seismic signals from the complex layers in the inhomogeneous viscoelastic medium. The viability of the method is verified by synthetic and real data sets.     

基于AVO反演的频变流体识别方法

研究表明流体引起衰减与频散往往表现为频变AVO现象.一些频散地震属性,例如纵波频散,已经证实为可靠的碳氢指示因子.为了更有效地识别流体,基于f-μ-ρ近似构建了新的流体因子Df,即频变流体项.该属性的反演首先需要连续小波变换(CWT)谱分解得到不同频带地震数据,通过去相关与先验约束来保证反演结果可靠性.模型试算证实了频变反射系数近似公式的精度可靠性,Df可以识别出强衰减介质所引起的频散现象.实际数据试算中,Df可以较好地识别储层孔隙流体,尤其对于气层,具有较好的指示效果.该流体因子将Gassmann流体项的高孔隙流体敏感性与叠前数据丰富的振幅频率信息相结合,反演效果与岩石物理认识相符.此研究有助于利用衰减频散现象借助AVO反演实现流体识别.     

A consistent derivation of the wave-energy equation from basic hydrodynamic principles

Based on a decomposition of the velocity into mean flow, turbulent and wave components, momentum and hereafter a wave-energy equation is derived. It contains a turbulent energy dissipation term which is closed by applying a wave-related mixing length model and linear wave theory solutions. This closure produces a non-linear turbulent wave-energy dissipation including the wave energy in a 5/2 power law. The theory is able to predict correctly the shape of deep-water wave spectra according to Phillips' similarity law.Responsible Editor: Hans Burchard     

基于小波分析和神经网络的框架结构损伤诊断方法

本文提出了基于“能量—损伤”原理，综合利用小波包分析和神经网络的框架结构损伤诊断方法。在结构损伤诊断中，时域信号经小波分析后其缺损特征会更加明显，把分布在不同频带的结点能量作为神经网络的训练样本能够很好地反映结构缺损特征。以美国土木工程师学会提出的基准结构为例，阐述了结构损伤的发生、位置和程度诊断过程，取得了令人满意的结果。