Data Quality of Seismic Records from the Tohoku, Japan, Earthquake as Recorded across the Albuquerque Seismological Laboratory Networks

Abstract

Online material : Additional network summary figures. Great earthquakes recorded across modern digital seismographic networks, such as the recent Tohoku, Japan, earthquake on 11 March 2011 ( Mw = 9.0 ), provide unique datasets that ultimately lead to a better understanding of the Earth’s structure ( e.g. , Pesicek et al. 2008) and earthquake sources ( e.g. , Ammon et al. 2011). For network operators, such events provide the opportunity to look at the performance across their entire network using a single event, as the ground motion records from the event will be well above every station’s noise floor. Methods for in situ identification of possible instrumentation problems have been the focus of a number of recent studies (Davis et al. 2005; Ekstrom et al. 2006; Davis and Berger 2007; Ekstrom and Busby 2008; Ringler et al. 2010). One common thread to these studies is that they all rely on a large number of observations or focus on specific frequencies to identify possible instrumentation problems. In contrast, great earthquakes such as Tohoku provide the opportunity for station operators to verify instrument sensitivities as well as to identify other possible station problems ( e.g. , excessive noise at the station, clipped records, or low-gain instrument problems) from a single event, allowing station operators to identify current instrumentation problems without having to use a large number of historical events. This approach also allows station operators to see potential changes in data quality as a result of recent station maintenance visits ( e.g. , modernization of current station digitizers to Quanterra Q330HRs; Anderson et al. 2011), along with other improvements to data quality such as changes in calibration practices (Ringler et al. , 2012). Recent accessibility to high-quality full-waveform synthetic seismograms derived from 3D Earth models (Tromp et al. 2010), along with well-constrained …