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国际地震中心(ISC)是一个非政府的、非营利性机构,它的首要任务是产出权威的地球地震活动性报告。《国际地震中心公报》报道了50年(1960~2011年)的地震活动性。近年来由于全球台站日益增加,使得报告的地震事件尤其是事件的震相数量急剧增加。相似的射线路径会引起相关的走时预测误差,这些误差归因于:模型中没有加入地球非均匀性,这导致了对定位不确定性的低估和不利的台网几何结构以及定位偏差。因此,全球的台站分布越密集和越不均衡,大多数定位算法中所做出的假设(观测数据是独立的)越不成立。为了应对这一挑战,我们为国际地震中心开发了一种新的定位算法,这种算法考虑了相关误差结构。我们采用国际地震学与地球内部物理学协会(IASPEI)所有的在ak135模型中有有效走时预测的标准震相来得到更精确的事件定位。本文中,我们阐述了新的国际地震中心定位方法,为检验此方法的可靠性,我们用该方法重新定位在国际地震学与地球内部物理学协会参考事件表中的地面真实事件,我们也对整个《国际地震中心公报》做了重新定位。我们的定位算法虽然只有很小的改进,但是对定位结果的改进却很显著,尤其是在深度的确定上和更精确的形式不确定性分析上。我们论证了新的定位算法;通过后续震相的使用和深度解的测试,相当多的地震震群变得更紧密了;因此该算法为地球地震活动性提供了一个改进的观点。
The International Seismological Center (ISC) is a non-governmental, non-profit organization whose primary mission is to produce authoritative Earth Seismic Activity Reporting. Seismological Center of the International Seismological Center reported seismicity for 50 years (1960-2011). In recent years, due to the increasing number of global stations, the number of seismic phases reported, especially the number of events, has dramatically increased. Similar ray paths can cause associated travel time prediction errors due to the absence of global inhomogeneities in the model, leading to underestimation of positioning uncertainty and adverse network geometry and positioning deviations. As a result, the more distributed and unevenly distributed stations around the world, the less assumptions made in most localization algorithms (observed data are independent). In response to this challenge, we developed a new localization algorithm for the International Seismological Center, which takes into account the relative error structure. We use the standard seismograms of all IASPEI models that have valid travel-time predictions in the ak135 model to obtain more accurate event location. In this paper, we describe a new method of locating international centers of seismic data. To test the reliability of this method, we use this method to relocate the true ground events in the ISFA reference event table The entire “International Seismological Center Bulletin” has been repositioned. Although our localization algorithm has only a small improvement, the improvement of the localization result is significant, especially in the determination of depth and in the analysis of more precise forms of uncertainty. We demonstrate a new localization algorithm; a considerable number of earthquake swarms have become tighter by the use of subsequent facies and deep solution tests; hence this algorithm provides an improved view of Earth’s seismicity.