探讨孕震过程中的非线性特征

应用谱分析方法,研究了海城、唐山和澜沧等7个大震前、后地震活动的功率谱特征.结果得到大震前、后地震活动都有连续的功率谱,表现为某种非周期行为.当距大震发生时间较远时,其活动特征均伴有明显的随机成分.主震前一年左右,在由谱幅度构造的相空间,运动轨道有收缩趋势,表现为一种闪变噪声.其它时间轨道几乎遍历整个相空间.主震后地震活动本质上为一种伴有许多噪声的浑沌态.      

不同地震区应力降分布与分形特征

利用 P 波初动半周期的方法测定了5个地震区的小震震源参数.所研究的5个地区和时间段,以及发生的主要地震是:鹤庆,1984-1986年,1986年3月发生5.6级地震:乌什,1985年1月-1987年9月,1987年1月发生6.7级地震;松潘,1975-1976年,1976年8月发生2次7.2级地震:唐山-卢龙,1980年1月-1984年6月,1982年10月发生6.2级地震;邢台,1976-1985年,1981年11月发生5.8级地震.结果表明:(1)5个地区的应力降数值分布和集中范围各不相同,说明积累应力的水平因地区而异,其中唐山-卢龙地区的应力水平最高.其次是邢台和鹤庆,乌什和松潘的应力水平低;(2)5个地区的应力降数值都具有分形的特征,但分维数 D 则因地区而异,其中乌什和松潘的 D 值高,约分别为1.42和1.24,其次是唐山-卢龙地区,D 值为1.06.邢台和鹤庆的 D 值低,约分别为0.73和0.84综上所述,乌什和松潘这两个7级左右大地震发生区的特点是低应力水平和高 D 值;邢台、鹤庆和唐山-卢龙这三个6级左右地震发生区的特点是,高应力水平和低 D 值.      

利用跨断层形变资料研究近期唐山断裂活动性

采用1999年1月～2012年9月唐山台跨断层基线和水准数据资料,计算出唐山断裂水平和垂直形变及断层活动速率.并求解了唐山台站的应变特征和主应变方向,研究了唐山断裂的活动特征,并探讨了唐山断裂活动与地震活动的关系.结果表明,较远区域的大震和本地区中强地震对唐山断裂的水平向张压运动和垂向运动都可能有一定的影响.2003年可能是唐山断裂周边应力场发生较大改变的一年.     

试论全天山地震活动的韵律性

对全天山地震带总体活动特征的科学认识是中亚各国正确认识本国局部天山地震活动规律的重要前提。在收集了较完整的全天山地震目录资料的基础上,研究分析了全天山地震活动的韵律特征,发现全天山存在100年左右的大震活动准周期和50年左右的地震活动幕;对天山年折合震级时间序列的AR谱分析和周期参数精估计证实了上述分析,并表明还可能存在与太阳黑子活动相关的周期。根据上述分析认为,天山在2000±12年期间处于新一轮百年尺度大震活跃年份,同时在2007年前处在50年尺度地震活动幕中的7级以上地震活跃时段;2007年前天山仍可能发生多次7级以上大震,最大可达7.5级以上。     

2020年河北唐山5.1级地震前震源参数变化

利用谱分析方法对河北省测震台网2016年1月—2020年7月唐山老震区(117.5°～119.5°E,39°～41°N)85次M_L≥2.5地震进行震源参数分析,发现该时段唐山老震区应力降范围在0.1～10.3MPa,主要集中在0.1～1.0MPa,其中应力降小于2MPa的地震占81%。当2.5≤M_L≤3.5时,应力降、拐角频率与震级之间无明显的对应关系;ML≥4.0地震较少,但应力降有随震级增大而增大的趋势,拐角频率有随震级增大而减小的趋势。2019年12月5日河北丰南M4.5地震和2020年7月12日唐山M5.1地震之间发生了 7次M_L≥2.5地震,震级范围为2.5≤M_L≤2.8,提取该震级范围的震源参数进行时空分析,发现唐山M5.1地震前有2次明显的高应力降事件,2次高应力降事件呈现出应力降数值高、拐角频率高、震源尺度小的特点,表明单位体积所释放能量较多。2次高应力降事件均发生在唐山M5.1地震震中17km范围内,可能是唐山M5.1地震前震源区构造应力较高的一个标志。     

1976年唐山地震前的中源地震前兆研究

研究了唐山地震发生前的12年以上h≥33．1km地震的活动特征,得知唐山地震前确实存在中源地震前兆MDE;其最主要的特点是：大地震发生前几年,发生多次h≥60km的中源地震,特别是100km左右或大于100km的中源地震,是可能发生板内大地震的前兆信号。文中还研究了唐山MDE的一些具体特征。     

唐山地震前的断层滑动及有关的倾斜和水位变化

分析了1976年唐山地震前趋势性的倾斜和水位变化.用传播的断层滑动模式计算了它们的理论波形,得出,除唐山附近的蠕动断层段外,在宁河附近还有一蠕动断层段,断层滑动在地面1公里之下进行,它于1975年2、3月份在塘沽和宁河之间开始,以后沿大致唐山断裂的方向(N30E)逐渐向北东方向扩展,滑动区前沿的传播速率为4——5公里/月,同时位移由0逐步增长到1米左右.最后讨论了唐山地震的震源过程,认为唐山地震(地震滑动)是南北两个蠕动断层段逐步逼近,最终连接致使位移率迅速增长的结果.      

唐山7.8级地震前后地磁总场异常变化

本文对1976年7月28日唐山Ms7.8级地震震中周围的昌黎、宝坻、青光及白家疃四个地磁台的总强度资料,用最小二乘法原理建立回归改正法,以消除地磁外空场干扰及长期变影响。处理结果,昌黎台总强度在唐山地震前出现一年左右的下降变化,最大变幅达-12.8nT,认为这可能属唐山地震的震磁异常.     

线性合成概率方法在华北地区地震趋势研究中的应用

华北地区历史地震频繁,2000年以来出现地震平静现象,为了更好地对这一现象进行分析,我们利用基于地震周期谱分析的线性合成概率预测方法,针对晋冀蒙交界地区、冀鲁豫交界地区、唐山老震区、阴山燕山地震带进行研究。研究结果表明,这一方法对这些地区的地震活动有一定的预测能力,并给出了R值评分检验效果。     

2012年5月28日河北省唐山4.8级地震

2012年5月28日河北省唐山市古冶区与滦县交界发生4.8级地震,地震宏观震中位于古冶区的王辇庄乡.震中烈度为V度,地震发生在NE走向的唐山断裂带附近.地震没有造成人员伤亡和经济损失.震源机制解P轴方位为SEE,T轴方位为SSW,接近水平,这与华北构造应力场的NE-NEE方向不一致.唐山4.8级地震是1976年唐山7.8级地震晚期余震的正常起伏,2004年以来唐山老震区的ML4.0以上地震呈现了很好的准周期性.唐山4.8级地震前地震活动性和测震学参数存在背景性异常,从不同角度反映了老震区地震活动平静、起伏的阶段性特征.前兆异常以中短期异常为主,其中地下流体异常、电磁异常表现更为突出.此次地震虽然震级不高,但无论是地震活动性还是前兆方面都出现了一定数量的异常.异常既有趋势性的,也有短临的,配套性很好.     

Moving AR spectrum analysis and earthquake information processing

The Zhangdaokou short-range repeated levelling data is analysed by the moving AR spectrum analysis. There are some anomalous changes of AR spectrum parameters during the Tangshan Earthquake. The period is aboutT=30 days which appeared since January 1975 till January 1977, meanwhile the optimum order of AR model fitting isP _oP ≥6, and the corresponding FPE value is high.     

On the use of maximum entropy/autoregressive spectrum in harmonic analysis of time series

The maximum entropy (ME) spectrum, or its equivalent form of the autoregressive (AR) spectrum, has been used as a tool for harmonic analysis of time series in geophysics. This paper critically examines its usage in estimating the amplitude and the exponential decay rate of a harmonic function. The argument is based upon Prony's relation, which relates a complex-conjugate pair of poles for the AR model of the time series on one hand, to the complex frequency of one harmonic component in the time series on the other. It is found that: (i) the ME spectrum can be used as an estimator for the decay rate in a way similar to the Fourier spectral analysis; (ii) the ME spectrum contains no information whatsoever about the amplitude, contrary to what has been claimed and practiced in geophysical applications.     

Application of the radial basis function neural network to the short term prediction of the Earth’s polar motion

By a number of test cases using different sample numbers and sample lengths, we obtain a Radial Basis Function Neural Network (RBFNN) model that is suitable for the short-term forecast of polar motion, especially for the ultra-short-term forecast. By using the same data sample of Earth’s polar motion, this RBFNN model can achieve better short-term prediction accuracy than the least-squares+autoregressive (LS+AR) method, and better ultra-short-term prediction accuracy than the LS+AR+Kalman method. Using this model to forecast the polar motion data from January 1, 2002 to December 30, 2007 and from January 1, 2010 to December 30, 2016, respectively, experimental results show that the ultra-short-term forecast accuracy of this RBFNN model is within a precision of 3.15 and 3.08 milliseconds of arc (mas) in polar motion x direction, 2.02 and 2.04 mas in polar motion y direction; the short-term forecast accuracy of RBFNN model is within a precision of 8.83 and 8.69 mas in polar motion x direction, and 5.59 and 5.85 mas in polar motion y direction. As is stated above, this RBFNN model is well capable of forecasting the short-term of polar motion, especially the ultra-short-term.     

地球转速率变化主要中短周期的分析

利用新的世界时高精度观测资料序列分析讨论了地球自转速率的变化特征，采用最大熵谱分析的方法得到这一运动中主要中短周期的参数，而利用小波分析的方法发现某些周期具有明显的时变特征，是值得深入研究的。     

呼图壁断层形变仪的周期参数地震前兆异常

用分辨率较高的ＡＲ谱分析及周期参数精估计法对呼图壁地震台跨断层形变仪的观测资料进行定量分析，发现１９９０年１０月２５日乌苏南５．２级地震和１９９１年６月６日呼图壁东南５．２级地震前，资料的周期、振幅、位相和变化趋势均存在明显的前兆异常。     

Real-time prediction of near-future seismic excitation adapting AR model to preceding information

This paper examines a real-time prediction method, aimed at application in active structural control. The examined method applies preceding seismic excitation information at a certain moment to a time-variant AutoRegressive (AR) model and uses it to predict near-future excitation information. The performances of this method and appropriate identification parameters are examined by numerical experiments. In fact, the results of these experiments show that a time-variant AR model with appropriate identification parameters has little change in low-frequency components despite change in AR coefficients. The performance of a fixed-coefficient AR model is thus examined. The results show that even a fixed-coefficient AR model can sufficiently predict 0·05-s-future excitation information. Copyright © 1999 John Wiley & Sons Ltd.     

Further improvement of temporal resolution of seismic data by autoregressive (AR) spectral extrapolation

Seismic data have still no enough temporal resolution because of band-limited nature of available data even if it is deconvolved. However, lower and higher frequency information belonging to seismic data is missing and it is not directly recovered from seismic data. In this paper, a method originally applied by Honarvar et al. [Honarvar, F., Sheikhzadeh, H., Moles, M., Sinclair, A.N., 2004. Improving the time-resolution and signal–noise ratio of ultrasonic NDE signals. Ultrasonics 41, 755–763.] which is the combination of the most widely used Wiener deconvolution and AR spectral extrapolation in frequency domain is briefly reviewed and is applied to seismic data to improve temporal resolution further. The missing frequency information is optimally recovered by forward and backward extrapolation based on the selection of a high signal–noise ratio (SNR) of signal spectrum deconvolved in signal processing technique. The combination of the two methods is firstly tested on a variety of synthetic examples and then applied to a stacked real trace. The selection of necessary parameters in Wiener filtering and in extrapolation are discussed in detail. It is used an optimum frequency windows between 3 and 10 dB drops by comparing results from these drops, while frequency windows are used as standard between 2.8 and 3.2 dB drops in study of Honarvar et al. [Honarvar, F., Sheikhzadeh, H., Moles, M., Sinclair, A.N., 2004. Improving the time-resolution and signal–noise ratio of ultrasonic NDE signals. Ultrasonics 41, 755–763.]. The results obtained show that the application of the purposed signal processing technique considerably improves temporal resolution of seismic data when compared with the original seismic data. Furthermore, AR based spectral extrapolated data can be almost considered as reflectivity sequence of layered medium. Consequently, the combination of Wiener deconvolution and AR spectral extrapolation can reveal some details of seismic data that cannot be observed in raw signal or which lost during the previous processing.     

Parametrization of spectra of plasma bubble induced VHF satellite scintillations and its geophysical significance

An important component of ionospheric plasma irregularity studies in the Indian low latitudes involves the study of the plasma bubbles which produce intense scintillations of the transionospheric satellite signals. Many such plasma bubble induced (FBI) scintillation events were identified while recording 244 MHz signal from the geostationary satellite Fleetsat (73°E) at Delhi (28.6°N, 77.2°E) during March-April 1991. This type of scintillations represents changes in plasma processes. These scintillations are spectrally analyzed using an autoregressive (AR) scheme, which is equivalent to maximum entropy method of spectrum analysis, amenable to extracting optimum spectral content from short data lengths (20–40 s). Each spectrum is assigned a level of detectability using the final prediction error (FPE) derived from the optimum filter order required to resolve the spectrum. Lower detectability together with a higher order filter indicate a higher level of coherence for the plasma irregularities (discrete structures). Consistent patterns for these scintillations emerge from the present analysis as follows: (1) the initial and final phases of a scintillation patch display quasiperiodic oscillations. Their corresponding spectra show dominant (Gaussian shaped) spectral features with detectability levels of –6 dB to –12 dB and requiring a higher order (>6) AR filter for their spectral resolution. These are most likely associated with discrete filament-like or sheet-like plasma structures that exist near the bubble walls. (2) Two main features of the scintillation spectra could be positively associated with the well-developed plasma bubble stage: (a) spectra displaying a power-law process with a single component spectral slope between 1.6 to 3.0. Generally such spectra are resolved with a 2nd order filter and have a 1 dB to 6 dB of detectability. (b) Spectra displaying a double slope, indicating an inner and an outer scale regime for the power-law irregularities. These spectra are resolved with higher order filters (>3 but <7) and possess detectability levels of –1 dB to 3 dB. These spectra display finer spectral changes, perhaps indicative of the nature of continuously evolving plasma irregularities. As an example, an analysis of a single scintillation patch is presented to highlight the geophysical significance of the present approach. Some important parameters used in the AR scheme of spectral analysis are given in the Appendix.     

Some Features of the Variation of the Magnetic Field Characteristics in the Umbra of Sunspots During Flares and Coronal Mass Ejections

The observed variations of the magnetic properties of sunspots during eruptive events (solar flares and coronal mass ejections (CMEs)) are discussed. Variations of the magnetic field characteristics in the umbra of the sunspots of active regions (ARs) recorded during eruptive events on August 2, 2011, March 9, 2012, April 11, 2013, January 7, 2014, and June 18, 2015, are studied. The behavior of the maximum of the total field strength B_max, the minimum inclination angle of the field lines to the radial direction from the center of the Sun α_min (i.e., the inclination angle of the axis of the magnetic tube from the sunspot umbra), and values of these parameters B_mean and α_mean mean within the umbra are analyzed. The main results of our investigation are discussed by the example of the event on August 2, 2011, but, in general, the observed features of the variation of magnetic field properties in AR sunspots are similar for all of the considered eruptive events. It is shown that, after the flare onset in six AR sunspots on August 2, 2011, the behavior of the specified magnetic field parameters changes in comparison with that observed before the flare onset.     

利用超导重力数据探测Slichter模三重分裂信号

本文基于2004苏门答腊地震后全球地球动力学计划观测网中9台超导重力仪13200h的连续重力观测数据,联合利用整体经验模态分解(EEMD)、最优序列估计(OSE)、积谱密度分析(PSA)和自回归估计(AR)方法,探测地球固态内核平动振荡模态(Slichter模)的三重分裂信号.利用EEMD提取常规预处理后的重力残差中包含目标频段的本征模态函数(IMFs)作为最终的重力残差之后,将每个台站的重力残差平均分成无重叠的3个子数据块,再应用OSE和PSA方法获取Slichter模三重分裂谱线的积谱密度,并采用AR方法估计各积谱中弱共振信号的中心频率及其误差.结果表明,结合OSE和PSA方法探测到三个清晰的谱峰,周期分别为5.8307±7.1×10-4h、5.2161±8.1×10-4 h和4.7536±5.2×10-4 h,分别对应Slichter模三重分裂谱线m=-1、m=0和m=+1,且三个谱峰的周期与Crossley(1992)、Rochester和Peng(1993)、Peng(1997)和Rogister(2003)基于PREM地球模型给出的Slichter模理论周期非常接近,也与Ding和Shen(2013)建议的"可能的观测结果"较为接近.参考现有的理论和观测结果,本文认为这三个信号可能是Slichter模三重分裂谱线.