长白山天池火山区的地震活动特征分析

2002年6月以来,长白山天池火山区的地震活动明显增强。利用长白山火山中心站的观测资料对长白山天池火山地震的活动特征进行了研究。火山地震的频谱分析和时频分析结果表明,自1999年以来发生的火山地震主要为构造型火山地震。对这些火山地震进行了尾波Q值分析并与四川地区的Q值进行了对比,结果表明长白山火山区尾波Q值偏低,说明这一地区构造活动水平相对较强     

火山地震监测在火山喷发预测中的应用

火山地震学是火山监测的一种重要方法,同时也是预测火山喷发最有效的方法。本文首先回顾了火山地震监测的历史,分析汇总了火山地震的类型和特征,并介绍了各类地震的形成机理。然后,对近年来发展起来的火山地震学方法进行了简要介绍,如地震活动性分析、实时振幅比测量、地震波速度变化和重复地震等,同时列举了具体的应用实例。最后,介绍了火山地震学方法在中国大陆火山监测中的应用。     

从历史记录看地震与火山喷发关系

史料记载表明，五大连池火山1720~1721年喷发期间有大量地震活动.本文从描述这些地震活动的文字记录入手，并结合国际火山地震研究的新成果，探讨了地震类型及地震与火山喷发关系，指出震群是火山喷发的重要前兆指标，强调火山地震的监测对火山喷发预报的意义.      

长白山天池火山地震类型及火山活动性的初步研究

2002年以来，长白山天池火山区出现了地震活动增强、地形变加剧和多种地球化学异常等现象，火山口附近发生的多次有感地震在社会上产生了较大影响。本文利用2002年以来的流动地震观测资料，采用频谱分析、时频分析和多台站资料对比的方法，对火山区地震事件的类型进行了分析；对火山活动的危险性进行了初步研究。结果表明，目前天池火山区出现的大量地震活动仍然属于火山构造地震，少量台站地震记录中表现出的低频特征主要是由于局部介质影响造成的，排除了长周期地震引起的可能。尽管长白山天池火山地震活动明最增强，震群活动较为频繁，但仍属于岩浆活动的早期阶段，短期内发生火山喷发的危险性较小。     

长白山天池火山2002~2005年火山扰动机制研究

地震、形变、火山气体地球化学等观测结果表明2002~2005年长白山天池火山经历了1次扰动事件。长白山站地震台（CBS台）记录到了扰动事件前后连续稳定的宽频带地震观测资料。前人的观测研究结果认为长白山天池火山扰动期间的火山地震类型主要为构造型火山地震，伴随少量的谐频型地震。本文通过匹配滤波技术，对1999~2007年扰动事件前后CBS台单台三分量地震观测数据进行模板扫描，获得3763个清晰的火山地震事件，其中谐频（HS）事件125个，构造（VT）事件3618个，并发现长周期（LP）事件20个。进而将火山扰动期间火山地震事件分为3种类型：构造型事件、长周期事件和谐频型事件，并提出2002~2005年长白山天池火山扰动机制模型：深源地震-火山能量传递模型，即汪清深源地震能量释放和传递，引发长白山火山区岩石圈应力状态波动。地幔岩浆房受应力干扰后，岩浆通道打开，少量岩浆侵入地壳岩浆房。岩浆混合脱气导致地壳岩浆房升压，引起顶部岩石微破裂，产生构造型火山地震，气体和流体填充这些裂隙，从而产生LP和HS型火山地震事件。     

长白山天池火山地震活动机理研究

对1999年以来长白山火山观测站记录到的火山地震活动进行了研究,发现在西北太平洋5.0级以上中深源地震发生前后,均有火山地震活动发生变化。我们统计发现有以下三种情况:第一种是深源地震发生后火山地震随之增强;第二种是火山震群活动结束后发生中深源地震;第三种是深源地震前后火山地震活动频繁,在火山地震活动较少时发生中深源地震。本文通过对近年来长白山火山地震活动与西北太平洋俯冲板块的中、深源地震关系以及火山玄武岩地幔性质和长白山地热活动等资料并参考前人研究成果,建立了长白山地幔柱模型,对长白山火山地震活动机制进行了初步探讨。     

东北火山分布及火山地震特征浅析

火山与地震都是地球内部物质运动的结果和表现。把火山作为和地震一样的自然灾害予以研究,也引起人们的格外注意。本文叙述了东北火山分布及火山地震的特征。指出深入研究火山地震对火山灾害的预报具有重要意义。     

日本火山、火山地震研究综述

“为探测我国火山地震活动特征和规律,借鉴国内外成果,进一步论证我国火山地震监测研究的方向和科学思路”仅就搜集到日本的有关地震的火山研究资料:包括日本火山概况,火山及火山地震;着重介绍了日本火山学研究及发展状况;陈列了火山地震学术研究机构设置、研究方向,研究课题以及知名学者,工作人员等,做一剪辑。值得提出的是,火山及火山地震做为一种自然灾害,已被列入国际减轻自然灾害十年(英文名为International Decade for Natural Disaster Reduction,缩写成IDNDR)顾问委员会的研究计划。文中介绍了在国际减轻自然灾害十年(1990——2000年)期间,可以执行的计划。介绍日本火山、地震研究综述,旨在“他山之石,可以攻玉”,以期我国第一个火山地震监测站在火山研究监测与研究中,为地震预报做出应有的贡献!     

我国火山地震事例

概述了我国1597年10月6日吉林长白县望天鹅火山地震、 1720—1721年黑龙江五大连池老黑山和火烧山火山地震,以及1867年12月18日台湾基隆7级地震与海底火山喷发的事例。分析了1597年10月6日渤海7级地震与同日望天鹅火山喷发的关系等有关问题。分析表明:我国火山喷发现场考察的历史上溯至1720年,是世界上较早开展火山现场调查的国家之一。     

DCS-302数字地震仪在火山地震观测中的应用

火山地震是近年来世界各国地震专家特别感兴趣的课题之一。预测预报火山的喷发,减轻灾害损失,一直为我国政府和地震学界的专家们所重视。为了掌握火山研究的第一手资料,中国地震局地球物理研究所组织了长白山天池火山口附近的火山地震观测工作,环绕火山口设置了一个由...     

分析研究基于小波分析与谱分析提高重力异常的分辨能力

重力数据是所有地下场源产生的重力场的叠加,探测对象经常被淹没在区域背景场之中,因此剩余异常的分离对于重力资料研究至关重要,而近来被引入位场领域的小波算子作为了滤波器和场源分析工具,在这里我们分析研究基于小波分析与谱分析的二维离散小波变换用于提高重力异常的分辨能力,再现出由简单形状场源描述密度不均匀的几何特征.本文先介绍二维多分辨率分析小波的基本理论及其提升算法,利用对数功率谱估计平均深度方法理论,接着对理论模型数据进行多尺度异常分解,估计地质体的形状、大小和深度,最后又对实测重力数据进行分析,并与传统常规方法进行比较分析,结果表明对于实际数据分析其方法也是具有可行性的.     

What drives high flow events in the Swiss Alps? Recent developments in wavelet spectral analysis and their application to hydrology

Extreme hydrological events are often triggered by exceptional co-variations of the relevant hydrometeorological processes and in particular by exceptional co-oscillations at various temporal scales. Wavelet and cross wavelet spectral analysis offers promising time-scale resolved analysis methods to detect and analyze such exceptional co-oscillations. This paper presents the state-of-the-art methods of wavelet spectral analysis, discusses related subtleties, potential pitfalls and recently developed solutions to overcome them and shows how wavelet spectral analysis, if combined to a rigorous significance test, can lead to reliable new insights into hydrometeorological processes for real-world applications. The presented methods are applied to detect potentially flood triggering situations in a high Alpine catchment for which a recent re-estimation of design floods encountered significant problems simulating the observed high flows. For this case study, wavelet spectral analysis of precipitation, temperature and discharge offers a powerful tool to help detecting potentially flood producing meteorological situations and to distinguish between different types of floods with respect to the prevailing critical hydrometeorological conditions. This opens very new perspectives for the analysis of model performances focusing on the occurrence and non-occurrence of different types of high flow events. Based on the obtained results, the paper summarizes important recommendations for future applications of wavelet spectral analysis in hydrology.     

小波包去噪在地震信号预处理中的应用

本文将小波包去噪应用于地震信号的预处理中,并与信号功率谱分析相结合,取得了良好的效果。结果表明,该方法极大的削弱了地震信号中的高、低频干扰,具有一定的应用价值。     

Wavelet analysis of turbulence in cirrus clouds

Two flights of the UK Meteorological Offices Hercules aircraft through daytime frontal cirrus around Scotland have been analysed using wavelet analysis on the vertical velocity time-series from the horizontal runs. It is shown that wavelet analysis is a useful tool for analysing the turbulence data in cirrus clouds. It finds the largest scales involved in producing turbulence, as does Fourier analysis, such as the 2-km spectral peaks corresponding to convective activity during flight A283. Wavelet spectra have the added advantage that the position is shown, and so they identify smaller-scale, highly localised processes such as the production of turbulent kinetic energy by the breaking of Kelvin-Helmholtz waves due to the vertical shear in the horizontal wind. These may be lost in Fourier spectra obtained for long time-series, though they contribute something to the average spectral density at the appropriate scale. The main disadvantage of this technique is that only octave frequency bands are resolved.     

Stream flow characterization and feature detection using a discrete wavelet transform

An exploration of the wavelet transform as applied to daily river discharge records demonstrates its strong potential for quantifying stream flow variability. Both periodic and non-periodic features are detected equally, and their locations in time preserved. Wavelet scalograms often reveal structures that are obscure in raw discharge data. Integration of transform magnitude vectors over time yields wavelet spectra that reflect the characteristic time-scales of a river's flow, which in turn are controlled by the hydroclimatic regime. For example, snowmelt rivers in Colorado possess maximum wavelet spectral energy at time-scales on the order of 4 months owing to sustained high summer flows; Hawaiian streams display high energies at time-scales of a few days, reflecting the domination of brief rainstorm events. Wavelet spectral analyses of daily discharge records for 91 rivers in the US and on tropical islands indicate that this is a simple and robust way to characterize stream flow variability. Wavelet spectral shape is controlled by the distribution of event time-scales, which in turn reflects the timing, variability and often the mechanism of water delivery to the river. Five hydroclimatic regions, listed here in order of decreasing seasonality and increasing pulsatory nature, are described from the wavelet spectral analysis: (a) western snowmelt, (b) north-eastern snowmelt, (c) mid-central humid, (d) south-western arid and (e) ‘rainstorm island’. Spectral shape is qualitatively diagnostic for three of these regions. While more work is needed to establish the use of wavelets for hydrograph analysis, our results suggest that river flows may be effectively classified into distinct hydroclimatic categories using this approach. © 1998 John Wiley & Sons, Ltd.     

Improvement of HVSR technique by wavelet analysis

In this work we investigate the application of the wavelet analysis to improve the well-known horizontal to vertical spectral ratio (HVSR) technique for site effect estimation. Wavelet analysis has been widely used in the last decade for its capacity to localise the signal in both the time and frequency domains. The wavelet packet transform and the evaluation of a cost function for every node permit one to remove from the signal the least important components and lead to significant improvements in the identification of the fundamental frequency. In this paper a new algorithm is presented based on wavelet analysis, that allows, in some cases, to improve the identification of the peak in the QTS ratio. A number of examples of application are also presented.     

Study of hydro-sedimentary variability of the Radicatel karst system influenced by climate signal fluctuations (Normandy,France)

ABSTRACT

This study relies on the use and analysis of hydro-meteorological variables, long turbidity time series (from 1988 to 2009, 21 years) and a sedimentary record to provide better understanding of the hydro-sedimentary variability of the karst system near the town of Radicatel, France. Wavelet analysis of rainfall, piezometric level and turbidity, as well as the sediment archive, show common modes of variability. A common spectral composition emphasizes the influence of climate controls. Comparison of the wavelet spectra with the North Atlantic Oscillation (NAO) spectrum clearly highlights the control of the latter on hydro-meteorological variables at the regional level. Climatic fluctuations are recorded in the turbidity signal and in sedimentary fill, as revealed by the 5- to 8-year frequency band, which is characteristic of the NAO index. A climatic signal is recorded in both rainfall events and piezometric levels, and also in sediment transport and deposition at the scale of the local karst system. The overall climate control is also present beyond the local variations and heterogeneities.

EDITOR D. Koutsoyiannis ASSOCIATE EDITOR D. Yang     

测井多尺度分析方法用于准层序自动划分研究

多尺度分析方法实现了信号分析的时频局部化,是测井数据时频分析与地质解释恰当的数学工具.测井资料作为地层岩性、物性的反映,其中必然蕴含了大量与沉积地层旋回变化有关的信息.以胜坨油田某井为例,采用db4最佳小波基分别对自然伽马、自然电位和声波等测井曲线进行了多尺度分析,将一维测井数据拓展为二维深度-尺度空间,提取小波变换系数的时频色谱信息和能量信息,从而确定出测井曲线识别准层序界面的最佳尺度.依据最佳尺度下的小波系数幅度振荡特征和时频色谱信息实现了对准层序界面的自动划分,与传统方法所划分的界面基本一致.这些探索为层序地层的定量划分提供了一种新的思路.     

月球重力异常的小波多尺度分析

本文将小波多尺度分析引入月球重力场的研究,选取测量数据质量较好的月球近区作为实验区域,以“Clementine”探测器获得的自由空气重力异常作为原始数据对主要月海盆地进行了局部的重力异常分解,解释了月球内部基本分层结构,并利用主要月海盆地的实验结果分析了月海下部质量异常以及莫霍面的起伏形态,与已有研究成果进行比较证明了方法的适用性及结果的合理性.     

基于小波分析的结构损伤检测研究进展

近10几年来,在土木和机械领域结构损伤识别方法已引起不同领域的相关学者的极大研究兴趣。小波分析是一种新的数学分析和信号处理工具,可以对非稳态信号进行详细的时频分析,是传统傅里叶分析所不能及的,已广泛应用于土木、机械和航空工程领域中,特别是在结构损伤识别和健康监测中的应用尤为突出。本文回顾和总结了小波分析理论及其在结构损伤识别、损伤定位和损伤程度确定中的应用,对今后的研究进行了讨论和展望。