Application of repeated passive source travel time tomography to reveal weak velocity changes related to the 2011 Tohoku‐Oki M_w 9.0 earthquake

Abstract

Temporal changes of seismic velocities may provide important information on the processes that occur inside the Earth. However, using body wave data with passive sources faces the problem of an uneven distribution of rays, which may cause artifacts with stronger amplitudes than the actual velocity changes in the Earth. We propose an algorithm for the selection of similar data sets in different time periods that minimize the artifacts related to variable data distributions. In this study, we used the data of the Japan Meteorological Agency for several years before and after the Mw 9.0 Tohoku‐Oki event that occurred on 11 March 2011. We performed careful testing using different synthetic models, showing that the selected data subsets allow detecting weak velocity changes with amplitudes above 0.2%. The analysis of the experimental data revealed important features associated with the stress and deformation distributions after the megathrust event. In the upper crust, we found a large zone along the coast with significant P velocity increase likely caused by compression of crustal rocks. This zone was cut by several elongated anomalies with local velocity decrease coinciding with the limits of the maximum slip area. These anomalies possibly mark the areas of major ruptures and deformations after the Tohoku‐Oki earthquake. In the coupling zone at a depth of 40 km, we observe a velocity decrease in the area of the Mw 7.7 aftershock representing strong fracturing in the focal zone. Beneath the volcanic arc, we observe significant (up to 0.5%) decrease of P velocity but less prominent S velocity changes.

Causes of volcanic unrest at Mt. Spurr in 2004–2005 inferred from repeated tomography

“…Here, we used an approach recently developed and tested in different structures, such as the area of the Tohoku-Oki earthquake 22 and at the Nevado del Ruiz volcano 23 . This method is based on selection of dataset series with similar distributions of events and seismic rays.…”

Breathing of the Nevado del Ruiz volcano reservoir, Colombia, inferred from repeated seismic tomography

“…Results are typically derived from the same calculations performed over different time intervals and hence may be affected by artefacts due to changes of data coverage. An algorithm was developed specifically to overcome this problem16 based on a selection process that generates data sets with similar data distributions. This algorithm was only suited to dense seismic networks and a homogeneous spatial distribution of seismicity and we have modified it to handle data from “non-ideal” networks, as is often the case in volcanic areas.…”

Exploring the Rheology of a Seismogenic Zone by Applying Seismic Variation

“…We divided this time span into three segments to investigate velocity structures in different time periods, namely, 1 January 1991-31 December 1995; 1 January 1996-19 September 1999; 1 January 2001-31 December 2003 (hereinafter, period I, period II, and period III, respectively) (see Figure 1b). We excluded the days immediately before and after the Chi-Chi earthquake because of complicated source effects that make some seismic events unsuitable to be adopted as a point source; therefore, these data could not be used for tomography [32]. This study suggests that a large earthquake caused by stress adjustment makes the subsurface structure unstable, so the data for the year after the Chi-Chi earthquake was eliminated.…”

“…This formula refers to the method of [32], and the description is simplified. In the subsequent study, the following formula was applied on the temporal variation in the velocity structure:…”