Prediction of UT1–UTC,LOD and AAM χ<Subscript>3</Subscript> by combination of least-squares and multivariate stochastic methods

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ ₃). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ ₃ time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ ₃ data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ ₃ predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ ₃ time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ ₃ reveal the best accuracy for LS + AR.     

Long-term prediction of intermediate depth earthquakes in the southern Aegean region based on a time-predictable model

Repeat times of strong intermediate depth (60 km h 180 km) earthquakes have been determined by the use of instrumental and historical data for six seismogenic sources in the Benioff zone of the southern Aegean area. For four of these sources, at least two interevent times (three mainshocks) are available for each source. By using the repeat times for these four sources, the following relation has been determined: logT _t = 0.20M _min + 0.19M _p +a, whereT _t is the repeat time (in years),M _min the surface wave magnitude of the smallest earthquake considered,M _p the magnitude of the preceding mainshock and a parameter which varies from source to source. A multilinear correlation coefficient equal to 0.91 was determined for this relation, which indicates that the time predictable model holds to a satisfactory degree for the strong mainshocks of intermediate focal depth in the southern Aegean.By assuming that the ratioT/T _t, whereT is the observed andT _t the calculated repeat time, follows a lognormal distribution, the conditional probabilities for the occurrence of strong (M _s 6.5) and very strong (M _s 7.5) earthquakes during the period 1991–2001 in these four seismogenic sources have been calculated. These probabilities are very high (P > 0.9) for the strong and high (P > 0.5) for the very strong intermediate depth earthquakes which occur in the three sources of the shallower (h < 100 km) part of the Benioff zone where coupling occurs between the front parts of the Mediterranean lithosphere (downgoing) and the Aegean lithosphere.     

Modeling the cyclic swelling pressure of mudrock using artificial neural networks

The stochastic nature of the cyclic swelling behavior of mudrock and its dependence on a large number of interdependent parameters was modeled using Time Delay Neural Networks (TDNNs). This method has facilitated predicting cyclic swelling pressure with an acceptable level of accuracy where developing a general mathematical model is almost impossible. A number of total pressure cells between shotcrete and concrete walls of the powerhouse cavern at Masjed–Soleiman Hydroelectric Powerhouse Project, South of Iran, where mudrock outcrops, confirmed a cyclic swelling pressure on the lining since 1999. In several locations, small cracks are generated which has raised doubts about long term stability of the powerhouse structure. This necessitated a study for predicting future swelling pressure. Considering the complexity of the interdependent parameters in this problem, TDNNs proved to be a powerful tool. The results of this modeling are presented in this paper.     

时间序列转折突变点检测的线性函数方法

根据转折突变的定义，在引入线性半截多项式的前提下，提出检测时间序列转折突变点的一种新方法。此方法不仅能找出时间序列中存在的多个转折突变点，而且使得检测到的突变点通过统计显著性检验。应用此方法对北半球1851—1990年年平均气温距平及其11年滑动平均序列，1901—1999年昆明5月降水及其11年滑动平均的降水序列分别进行了检测。发现北半球年平均气温距平在1879、1889、1939和1973年附近出现了年际转折突变，在1878、1888和1941年以及1972年出现了年代际尺度的转折突变；昆明5月雨量不存在年际转折突变点，但昆明5月雨量在1918、1966以及1978年附近出现了年代际尺度转折突变。     

无验潮模式下的GPS水下地形测量技术

传统的水下地形测量模式定型于利用GPS测定水底点的平面位置,利用测深仪测定水底点的深度,附之以瞬时潮位资料,获得点位的高程。这种模式在上述条件具备的情况下,可取得完满的结果。但当验潮条件不具备时,该模式将不能获得测点的高程。为了弥补这一缺陷,简化工作流程,提高水下地形测量的精度,本文提出了一种无验潮模式下的水下地形测量思想,该思想不用专门测定潮位,而直接利用GPS的RTK测量技术,辅之以姿态测量和补偿,从而获得高精度的水底点高程。该方法被验证是正确的,希望进一步推广应用。     

根据激光雷达观测结果研究中国武汉地区钠层的分布

通过大量钠层荧光激光雷达观测数据的分析研究，给出我国武汉地区钠层平均分布形态的基本特征. 结合钠层模型分析，指出大气微量元素分布的纬度变化可能是导致不同纬度地区钠层平均分布形态差异的主要原因,同时给出武汉地区随季节变化的钠层平均分布形态. 对武汉地区钠层分布形态时间变化的分析，发现其短期变化与重力波活动及夜间变化与潮汐波活动相关.     

时间域航空电磁法一维正演研究

基于电磁勘探理论，导出了层状大地条件下时间域航空电磁法（偶极-偶极装置）的正演计算公式和算法，编制了相应的计算机程序，对若干典型地电断面作了正演计算. 计算结果说明时间域航空电磁法的探测能力和探测条件，进而为时间域直升机航空电磁系统的设计方案提供了依据.     

构造机理与地震大形势分析

对全球大震时空特征的分析表明，北南半球大震分布与陆地面积成比例，全球强震活动具有35年的地极移周期，并对一些具有全球活动特征的构造事件进行了机理探讨，最后对大陆西部强震的活动规律．尤其是主体活动区的特点进点了仔细的研究。给出了未来一段时间内的预测结果。     

广东及邻区地震活动熵值的异常特征

应用文献」１「的方法，对广东及部分邻近地区进行了熵值计算和分析处理，结果表明，时间熵，频度熵和强度熵在ＭＬ≥４．７级地震之前，大都存在较明显的低值变化，即存在减熵现象，地震大多数以生在减熵的中，后期，少数发生在减熵初期。三种熵值变化基本同步，震级越大，熵值波动越大，其中尤以强度熵变化幅度最大，频度熵次之，时间熵最弱。     

华北地区大震前区域地震活动的中短期变化

对发生在华北地区３１个Ｍ≥５地震震前区域地震活动的时间序列进行的研究得出：（１）华北地区发生Ｍ≥５地震前，区域地震活动的短期平静现象与大震发生的相关性很强。３１个Ｍ≥５地震前的平静时间主要集中在２０～８７ｄ，１２０～２１０ｄ和大于２１０ｄ。同时还得出大震前的短期平静时间与震级大小无关的结论；（２）区域地震活动在短时间内出现增强趋势，与发生大震的相关性很弱，相关的仅占总数的６．４％