EMERALD: A Web Application for Seismic Event Data Processing

Seismologists studying earthquake sources and the structure of the Earth’s interior commonly use event-based seismic data processing, with typical workflow including the acquisition, preprocessing, and analysis of data associated with one or more discrete seismic events. Until recently, most seismic event datasets were relatively small, including at most a few thousands or tens of thousands of seismic waveforms used in a given study (e.g., Dziewonski and Woodhouse, 1987; Grand, 1987, 1994; Woodward and Masters, 1991; Engdahl et al., 1998). More recently, however, the size of datasets has increased significantly, not only from larger-scale investigator-driven temporary field experiments such as the Kaapvaal Project (Carlson et al., 1996), La RISTRA (Wilson et al., 2005), the High Lava Plains Project (Carlson et al., 2005), NorthEast China Extended SeiSmic Array (NECESSArray; Grand et al., 2006), the Carpathians Basin Project (Hetényi et al., 2009), and Project INDEPTH (e.g., Langin et al., 2003; Karplus et al., 2011) but also from large regional networks (i.e., from several dozens to 100+ broadband stations) such as the Advanced National Seismic System (earthquake.usgs.gov/ monitoring/anss), Pacific Northwest Seismic Network (www.pnsn.org), Hi-net (http://www.hinet.bosai.go.jp), ORFEUS (http://www.orfeus-eu.org), and AfricaArray (www .africaarray.psu.edu). Furthermore, new projects such as the EarthScope’s USArray (www.usarray.org) and SinoProbe (www.sinoprobe.org) are generating unprecedented volumes of data from hundreds to thousands of broadband stations. The advent of datasets potentially containing millions of seismic waveforms has exposed limitations of traditional seismic processing methods. Preprocessing and processing methods for seismic data vary widely by investigator, but they have some common attributes. They frequently consist of some combinations of standardized command-line programs such as Seismic Analysis Code (SAC; Goldstein et al., 2003) and Generic Mapping Tools (GMT; Wessel and Smith, 1991) and custom modules written or adapted by the investigator in C, FORTRAN, or other programming languages. The standardized and custom modules are generally stitched together using a series of shell scripts that transfer data between modules using a series of flat files. This approach is flexible, is powerful, and has worked well for most natural-source seismic data applications over the years. However, for very large datasets, this approach is much less efficient, and in some applications, this does not work. For instance, shell scripts and operating system calls can break down when confronted with very large numbers of files, the methods for each researcher are dependent on individualized file and directory naming conventions and cannot be easily shared, transferring intermediate data between modules using a series of flat files is inefficient, and basic data processing efforts are duplicated between projects and between researchers. Although some of these issues can be overcome with the application of advanced coding and scripting methods, the skills required for these methods can present a steep learning curve for some new graduate students and significantly limit the ability for new seismic data to be used in simple class projects and other more basic educational settings. Another issue affecting current dataset handling methods is that once a raw dataset has been acquired from a data center, it has not been possible to simply acquire information regarding updates to seismic station metadata. Station metadata contain, among other things, information regarding precise station location, elevation, sensor orientation, sensor type, and sensor instrument response and are typically acquired along with the initial data download. To address these limitations of current methodologies, we have developed EMERALD (Explore, Manage, Edit, Reduce, and Analyze Large Datasets), an open-source, easily extensible framework for seismic-event-based processing and analysis. This paper summarizes the present state of the EMERALD system, which is currently in beta testing but is approaching its first formal release. Our beta testers are using the hosted beta version of EMERALD to perform new seismological research and will transition to locally installed copies of the system after formal release. The primary components of EMERALD are outlined here, and we also refer the reader to the online information available on EMERALD’s web site at emerald.dtm.ciw.edu.