A feasibility study of data assimilation in numerical simulations of earthquake fault systems

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• 作者：Jordan Van Aalsburg ; Lisa B. Grant ; Gleb Yakovlev ; Paul. B. Rundle ; John B. Rundle ; Donald L. Turcotte ; Andrea Donnellan
• 关键词：Earthquakes ; Virtual California ; Numerical simulations ; Forecasting ; Data assimilation
• 刊名：Physics of the Earth and Planetary Interiors
• 出版年：2007
• 出版时间：15 August 2007
• 年：2007
• 卷：163
• 期：1-4
• 页码：149-162
• 全文大小：1711 K

文摘

Topologically realistic simulations of earthquake faults systems have been constructed to understand the physics of interacting earthquake fault systems. We focus on one of these models, a simulation called Virtual California, that represents a model for the strike-slip fault system in California. In weather forecasting, current and past observations are routinely extrapolated forward to forecast future weather. The question addressed in this paper is whether a similar application of numerical simulations can be used in earthquake forecasting. Present simulation models are discussed and their ability to successfully generate earthquake recurrence statistics is demonstrated. An important question relates to how paleoseismic data can be used to constrain simulations, and whether these constrained simulations provide improved forecasts of future earthquakes. Here, we show first results from a consideration of these issues using a method of “datascoring”. The data are divided into “training intervals” and “testing intervals”. In the training intervals, the time history of paleoseismic data are used to evaluate space–time windows of simulations. Earthquakes following high-scoring space–time windows in the simulations are then used as a basis for developing waiting time statistics and used to forecast data in the testing intervals. In our present method, we focus on the problem of determining the timing of future earthquakes having magnitude m > 7. Our preliminary conclusion is that the amount of paleoseismic data currently available does not as yet improve the waiting time statistics to a level significantly beyond a random (temporal) predictor. However, this conclusion is based on a set of studies that are not extensive, so further investigations may well reveal important new avenues. In particular, it may be that the true value of this approach lies in defining the probable spatial locations of future earthquakes, rather than their timing.