AGU 2003 Fall Meeting          

Cite abstracts as Eos Trans. AGU, 84(47),
Fall Meet. Suppl., Abstract S22D-06, 2003

HR: 15:05h
AN: S22D-06
TI: Probabilistic earthquake location and 3-D velocity models in routine earthquake location
AU: * Lomax, A
AF: Scientific Software, 161 Allee du Micocoulier, Mouans-Sartoux, 06370 France
AU: Husen, S
AF: Swiss Seismological Service, ETH Hoenggerberg, Zurich, 8093 Switzerland
AB: Earthquake monitoring agencies, such as local networks or CTBTO, are faced with the dilemma of providing routine earthquake locations in near real-time with high precision and meaningful uncertainty information. Traditionally, routine earthquake locations are obtained from linearized inversion using layered seismic velocity models. This approach is fast and simple. However, uncertainties derived from a linear approximation to a set of non-linear equations can be imprecise, unreliable, or even misleading. In addition, 1-D velocity models are a poor approximation to real Earth structure in tectonically complex regions. In this paper, we discuss the routine location of earthquakes in near real-time with high precision using non-linear, probabilistic location methods and 3-D velocity models. The combination of non-linear, global search algorithms with probabilistic earthquake location provides a fast and reliable tool for earthquake location that can be used with any kind of velocity model. The probabilistic solution to the earthquake location includes a complete description of location uncertainties, which may be irregular and multimodal. We present applications of this approach to determine seismicity in Switzerland and in Yellowstone National Park, WY. Comparing our earthquake locations to earthquake locations obtained using linearized inversion and 1-D velocity models clearly demonstrates the advantages of probabilistic earthquake location and 3-D velocity models. For example, the more complete and reliable uncertainty information of non-linear, probabilistic earthquake location greatly facilitates the identification of poorly constrained hypocenters. Such events are often not identified in linearized earthquake location, since the location uncertainties are determined with a simplified, localized and approximate Gaussian statistic.
DE: 7215 Earthquake parameters
DE: 7230 Seismicity and seismotectonics
DE: 7260 Theory and modeling
MN: 2003 Fall Meeting