Methods for Evaluation of Geodetic Data and Seismicity Developed with Numerical Simulations: Review and Applications
Department of Physics, Boston University, Boston, Massachusetts, United StatesPure and Applied Geophysics (Impact Factor: 1.62). 06/2004; 161(7):1489-1507. DOI: 10.1007/s00024-004-2516-3
In this work we review the development of both established and innovative analytical techniques using numerical simulations of the southern California fault system and demonstrate the viability of these methods with examples using actual data. The ultimate goal of these methods is to better understand how the surface of the Earth is changing on both long-and short-term time scales, and to use the resulting information to learn about the internal processes in the underlying crust and to predict future changes in the deformation and stress field. Three examples of the analysis and visualization techniques are discussed in this paper and include the Karhunen-Loeve (KL) decomposition technique, local Ginsberg criteria (LGC) analysis, and phase dynamical probability change (PDPC). Examples of the potential results from these methods are provided through their application to data from the Southern California Integrated GPS Network (SCIGN), historic seismicity data, and simulated InSAR data, respectively. These analyses, coupled with advances in modeling and simulation, will provide the capability to track changes in deformation and stress through time, and to relate these to the development of space-time correlations and patterns.
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ABSTRACT: In this work, we provide a joint study of the stress accumulation method (SAM) (King and Bowman, 2003) and the Pattern Informatics (PI) index (Tiampo et al., 2002b). We examine the theoretical underpinnings for the similarities between the two techniques, as well as the differences in their application. The SAM technique is employed to determine likely mechanisms for smaller areas of increased probability identified by the PI index, while a modified version of the PI index can be used to locate regions where the smaller magnitude associated with the anomaly is below the resolution of the SAM. Finally, we present three case studies from different regions of the San Andreas fault system to illustrate both their complementary nature, as well as the advantages to combining them in one synthesized analysis.
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