Data-driven identification of earthquake clusters: Clusters before the 2010 El mayor-Cucapah earthquake MW 7.1, Baja California, Mexico

Abstract

Seismic clusters in background seismicity have been associated with high stress levels and can be an important precursor to large earthquakes, but there is not a unanimous concept of cluster and most cluster identification methods are cumbersome and involve a priori assumptions. We propose a simple definition of seismic cluster and a straightforward method of identification involving a minimum of parameters that can be objectively determined in a data-driven way according to a principle of low random occurrence. As an illustration, definition and method were applied to the identification of cluster activity from October 1979 to March 2010 in northern Baja California, Mexico, between 118°W to 113°W and 30°N to 33°N, a tectonically complex seismic region with several fault systems. Twenty-one clusters were identified, of which 17 located around the places at the northeastern corner of the study area that would be ruptured on April 4, 2010 by the El Mayor-Cucapah M_w 7.1 earthquake, the largest recorded earthquake in Baja California, Mexico, and the four others occurred within 9 km from its epicenter. Clustering also became slightly more frequent as the time of the earthquake approached, so that if the clustering survey had been carried out before the whole northern Baja California area, the clustering might have identified the future epicentral region as a region of interest to be closely monitored (this earthquake featured foreshock activity starting some 15 days before the main event). Although the reliability of clusters as precursors to large earthquakes is still to be studied, it is certainly useful to have a reliable and simple method to identify and characterize them.