Seismicity Analyses Using Dense Network Data Catalogue Statistics and Possible Foreshocks Investigated Using Empirical and Synthetic Data

Abstract: Precursors related to seismicity patterns are probably the most promising phenomena for short-term earthquake forecasting, although it remains unclear if such forecasting is possible. Foreshock activity has often been recorded but its possible use as indicator of coming larger events is still debated due to the limited number of unambiguously observed foreshocks. Seismicity data which is inadequate in volume or character might be one of the reasons foreshocks cannot easily be identified. One method used to investigate the possible presence of generic seismicity behavior preceding larger events is the aggregation of seismicity series. Sequences preceding mainshocks chosen from empirical data are superimposed, revealing an increasing average seismicity rate prior to the mainshocks. Such an increase could result from the tendency of seismicity to cluster in space and time, thus the observed patterns could be of limited predictive value. Randomized tests using the empirical catalogues imply that the observed increasing rate is statistically significant compared to an increase due to simple clustering, indicating the existence of genuine foreshocks, somehow mechanically related to their mainshocks. If network sensitivity increases, the identification of foreshocks as such may improve. The possibility of improved identification of foreshock sequences is tested using synthetic data, produced with specific assumptions about the earthquake process. Complications related to background activity and aftershock production are investigated numerically, in generalized cases and in data-based scenarios. Catalogues including smaller, and thereby more, earthquakes can probably contribute to better understanding the earthquake processes and to the future of earthquake forecasting. An important aspect in such seismicity studies is the correct estimation of the empirical catalogue properties, including the magnitude of completeness (Mc) and the b-value. The potential influence of errors in the reported magnitudes in an earthquake catalogue on the estimation of Mc and b-value is investigated using synthetic magnitude catalogues, contaminated with Gaussian error. The effectiveness of different algorithms for Mc and b-value estimation are discussed. The sample size and the error level seem to affect the estimation of b-value, with implications for the reliability of the assessment of the future rate of large events and thus of seismic hazard.