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

时空聚簇是强相关过程的特征，是地震活动性的一个有据可查的特征。 这些模式提供了关于地震震源过程的重要信息，这里将使用几种不同的先进数据集和新的创新分析方法进行研究，这些方法是在研究平均场系统的物理学的同时开发的。 开发了一种用于识别概率增加的区域的方法，PI指数（Tiampo等人，2002 a，B），是基于最近的观测证据，地震断层的特点是强相关的时空动力学，以及地震的数值模拟，也表明，时空模式结构是非本地的，在底层动力学的强相关性的结果。 在最近的工作中，这项技术已被应用于地震活动从世界各地的各种构造区域，以检测系统的变化，在这些地区的地震矩释放。 长期目标是建立这些时空模式和潜在的非线性动力学之间的明确关系。

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.