Advanced analysis of geophysical data for improved understanding of the earthquake fault process

时空聚类是强相关过程的一个特征，是地震活动性的一个有充分证据的特征。这些模式提供了有关震源过程的重要信息，本文将使用几种不同的先进数据集和与平均场系统物理研究相结合而开发的新的创新分析方法来研究这些信息。PI指数（Tiampo et al., 2002a,b）是一种用于识别概率增加区域的方法，它基于最近的观测证据，即地震断层的特征是强相关的时空动力学，以及地震的数值模拟，这些证据也表明时空模式结构是非局部的，这是潜在动力学中强相关性的结果。在最近的工作中，该技术已应用于世界各地不同构造区的地震活动性，以检测这些区域地震矩释放的系统变化。长期目标是在这些时空模式和潜在的非线性动力学之间建立一个明确的关系。

Space-time clustering is a signature of strongly correlated processes, and is a well-documented feature of earthquake seismicity. These patterns provide important information about the earthquake source process, which will be studied here using several different advanced data sets and new, innovative analysis methods developed in the conjunction with the study of the physics of mean-field systems. A method developed for identifying areas of increased probability, the PI index (Tiampo et al., 2002a,b), is based upon recent observational evidence that earthquake faults are characterized by strongly correlated space-time dynamics, as well as numerical simulations of earthquakes that also suggest that space-time pattern structures are non-local, a consequence of strong correlations in the underlying dynamics. In recent work, this technique has been applied to seismicity from various tectonic regions around the world in order to detect systematic variations in seismic moment release in these regions. The long-term goal is to establish a clear relationship between these spatiotemporal patterns and the underlying nonlinear dynamics.