Virtual Seismologist

Part of the EEW package.

The Virtual Seismologist [1] in SeisComP (VS(SC)) provides near instantaneous estimates of earthquake magnitude as soon as SeisComP origins are available. With a well-configured SeisComP system running on a dense network, magnitudes for local events can be available within 4-20 s of origin time (Massin et al., 2021). VS(SC) can be a key component of an earthquake early warning system, and can be used to provide rapid earthquake notifications. With the capability to estimate magnitude (given a location estimate) with 1-second (originally 3s) of P-wave information at a single station, VS(SC) magnitude estimates are tens of seconds faster than conventional Ml calculations, which require waiting for the peak S-wave amplitudes. The VS magnitude estimation relationships consist of 1) a relationship between observed ground motion ratios (between vertical acceleration and vertical displacement) and magnitude, and 2) envelope attenuation relationships describing how various channels of envelope amplitudes vary as a function of magnitude and distance. These relationships were derived from a Southern California dataset with events in the magnitude range 2.5 <= M <= 7.6 and the Next Generation Attenuation (NGA) strong motion dataset. Once a SeisComP location estimate is available, VS magnitude estimates can be computed with as little as 1 second of envelope data at a single station (i.e., 1 second after trigger time at a single station). Typically, usable envelope data is available at numerous stations by the time the first SeisComP origin is available. The VS magnitude estimates are then updated every second for 30 seconds (configurable). The SeisComP implementation allows for use of broadband high-gain seismometers (with clipping value selected) as well as strong motion data. For co-located stations, VS magnitudes are calculated using the strong motion channels if the broadband channels saturate. VS magnitudes in SeisComP are called MVS.

Development

The Virtual Seismologist method is a Bayesian approach to earthquake early warning (EEW) that estimates earthquake magnitude, location, and the distribution of peak ground shaking using observed picks and ground motion amplitudes, predefined prior information, and envelope attenuation relationships (Cua, 2005; Cua and Heaton, 2007; Cua et al., 2009). The application of Bayes’ theorem in EEW (Cua, 2005) states that the most probable source estimate at any given time is a combination of contributions from prior information (candidate priors include network topology or station health status, regional hazard maps, earthquake forecasts, and the Gutenberg-Richter magnitude-frequency relationship) and constraints from the available real-time ground motion and arrival observations. VS is envisioned as an intelligent, automated system capable of mimicking how human seismologists can make quick, relatively accurate “back-of-the-envelope” interpretations of real-time (and at times, incomplete) earthquake information, using a mix of experience, background information, and real-time data. The formulation of the VS Bayesian methodology, including the development of the underlying relationships describing the dependence of various channels of ground motion envelopes on magnitude and distance, and how these pieces come together in EEW source estimation, was the result of the PhD research of Dr. Georgia Cua with Prof. Thomas Heaton at Caltech, from 1998 through 2004.

The first real-time VS prototype system was developed by Georgia Cua and Michael Fischer at ETH Zurich from 2006-2012. For this and all subsequent implementations, prior information is not included. This first prototype used location estimates generated by the Earthworm Binder module (Dietz, 2002) as inputs to the VS magnitude estimation. This architecture underwent continuous real-time testing in California (since 2008-2018) and Switzerland (since 2010-2014). In California, VS was one of the three EEW algorithms that made up the original version of the CISN ShakeAlert EEW system [2]. Since 2018 it was retired from ShakeAlert. In 2012/13, with funding from the EU projects NERA (“Network of European Research Infrastructures for Earthquake Risk Assessment and Mitigation”) and REAKT (“Strategies and Tools for Real-Time EArthquake RisK ReducTion”), VS was integrated into SeisComP by the Seismic Network group at the SED in ETH Zurich and gempa GmbH. Both real-time VS implementations (Binder- and SeisComP-based) focus on real-time processing of available pick and envelope data. Although the codes were effectively re-written, the basic architecture used in the original Earthworm-based implementation is used in SeisComP. In the first SeisComP implementation, VS-specific pre-processing (scenvelope) and post-processing (scvsmaglog) modules were included, alongside the VS magnitude module (scvsmag). Currently, scenvelope and scvsmaglog are replaced by generic EEW pre/post-processing modules.

VS and SeisComP

The SeisComP location module of choice (scautoloc or scanloc if available) provides location estimates to the scevent module that defines events and preferred origins. The generic EEW pre-processing module sceewenv provides continuously updated envelope amplitudes. Once a SeisComP origin is available, scvsmag uses the envelope amplitudes from all stations used in the preferred origin to provide VS magnitudes (MVS):

• sceewenv

• scvsmag

MVS is calculated and updated (with updates attached to the preferred origin) each second for 30 seconds (unless configured differently) after its first invocation with a new SeisComP event.

An additional generic EEW module, sceewlog, creates log output and mails solutions once a new event is fully processed. It also provides an interface to send alerts in real-time using ActiveMQ. The Earthquake Early Warning Display [3] (Cauzzi et al., 2016), an open-source java application, can receive and display EEW messages broadcast via ActiveMQ.

Configuring and optimizing VS(SC) for EEW

The performance of VS(SC) is strongly dependent on: 1) the quality and density of the seismic network; 2) the configuration of the general SeisComP system. scautoloc requires between 4-6 triggers to create an origin. scanloc uses at least 4 stations. Given the network geometry, maps of when VS estimates would be first available (indicative of the size of the blind zone as a function of earthquake location relative to stations) can be generated for regions where EEW is of interest. VS(SC) can be used with either scautoloc or scanloc, neither of which were directly built for EEW, although experience and observations indicates processing delays are minimal (Behr et al., 2014, Massin et al., 2021). VS magnitudes (MVS) can be expected within 1-2 seconds after a SeisComP origin is available. In the densest part of the Swiss network, first SeisComP origins are available within 4-7 seconds after origin time; MVS is typically  available within a second.

The VS magnitude estimation relationships in Cua (2005) were derived from a dataset consisting of Southern California waveforms and the NGA strong motion dataset. In theory, customizing VS to a specific region requires deriving a set of envelope attenuation relationships (168 coefficients) and relationships between ground motion ratios and magnitude (6 coefficients) from a regional dataset. In practice, the VS magnitude estimation relationships derived from Southern California have been shown to work reasonably well in Northern California, Switzerland (Behr et al., 2012), Iceland, Turkey, and Romania (Behr et al., 2015). More recent works indicate similar performance across Central America (e.g., Porras et al., 2021). The envelope and ground motion ratio coefficients from Cua (2005) are hard-coded in scvsmag, and should not be modified without a full understanding of the VS methodology and potential consequences of the modifications.

Although scautoloc can produce origins at any depth, the VS magnitude estimation relationships assume a depth of 3 km. For this reason, it is expected that MVS will systematically underestimate magnitudes for deep earthquakes. It may be most practical to simply add empirically derived offsets to MVS for deeper events, or for particular regions.

Read the documentation of sceewenv, scvsmag and sceewlog for their configurations.

Understanding VS output

The VS system currently being offered is a test version. SED-ETHZ assumes no liability for its use.

False alarms, missed events, solution quality

The rate of false alarms and missed events is determined by the output of the normal SeisComP origin chain (scautopick, scautoloc), and will be similar to the performance of the automatic setup for typical network operations (i.e. if you do not trust your automatic origins for the network, you will not trust them for VS either). Solution quality is independently estimated by VS, combining information on location quality and station quality. See scvsmag on how the VS specific solution quality is computed.

EEW License

The SeisComP EEW modules are free and open source. They are distributed under the GNU Affero General Public License (Free Software Foundation, version 3 or later). For licence information on SED-ETHZ SeisComP EEW modules released before SeisComP v4.0.0 see the Timeline in EEW.

References

Dietz, L., 2002: Notes on configuring BINDER_EW: Earthworm’s phase associator, http://folkworm.ceri.memphis.edu/ew-doc/ovr/binder_setup.html (last accessed

June 2013)

Cua, G., 2005: Creating the Virtual Seismologist: developments in ground motion

characterization and seismic early warning. PhD thesis, California Institute of Technology, Pasadena, California.

Cua, G., and T. Heaton, 2007: The Virtual Seismologist (VS) method: a Bayesian

approach to earthquake early warning, in Seismic early warning, editors: P. Gasparini, G. Manfredi, J. Zschau, Springer Heidelberg, 85-132.

Cua, G., M. Fischer, T. Heaton, S. Wiemer, 2009: Real-time performance of the

Virtual Seismologist earthquake early warning algorithm in southern California, Seismological Research Letters, September/October 2009; 80: 740 - 747.

Behr, Y., Cua, G., Clinton, J., Heaton, T., 2012: Evaluation of Real-Time

Performance of the Virtual Seismologist Earthquake Early Warning Algorithm in Switzerland and California. Abstract 1481084 presented at 2012 Fall Meeting, AGU, San Francisco, Calif., 3-7 Dec.

Behr, Y. D., Cauzzi, C., Clinton, J. F., Jonsdottir, K., Comoglu, M.,

Erlendsson, P., et al. (2015) Exploring the Readiness for Earthquake Early Warning at Seismic Networks Across Europe. Seismological Research Letters, 86(2B), 738–739. http://doi.org/10.1785/0220150017

Behr, Y., J. F. Clinton, C. Cauzzi, E. Hauksson, K. Jónsdóttir, C. G. Marius, A.

Pinar, J. Salichon, and E. Sokos (2016) The Virtual Seismologist in SeisComP: A New Implementation Strategy for Earthquake Early Warning Algorithms, Seismological Research Letters, March/March 2016, v. 87, p. 363-373, doi:10.1785/0220150235

Behr, Y., J. Clinton, P. Kästli, C. Cauzzi, R. Racine, M‐A. Meier (2015)

Anatomy of an Earthquake Early Warning (EEW) Alert: Predicting Time Delays for an End‐to‐End EEW System, Seismological Research Letters, May/June 2015, v. 86, p. 830-840, doi:10.1785/0220140179

Cauzzi, C., Behr, Y. D., Clinton, J., Kastli, P., Elia, L., & Zollo, A. (2016)

An Open-Source Earthquake Early Warning Display. Seismological Research Letters, 87(3), 737–742, doi:10.1785/0220150284

Massin, F., J. F. Clinton, M. Boese (2021) Status of Earthquake Early Warning in

Switzerland, Frontiers in Earth Science, 9:707654. doi:10.3389/feart.2021.707654

Porras Loría, J.L., Massin, F., Arroyo-Solórzano, M., Arroyo, I., Linkimer, L.,

Böse, M., and Clinton, J., (2021) Preliminary Results of an Earthquake Early Warning System in Costa Rica, Frontiers in Earth Science, submitted

[1]

http://www.seismo.ethz.ch/en/knowledge/earthquake-data-and-analysis-tools/EEW/finite-fault-rupture-detector-finder/

[2]

http://www.cisn.org/eew/

[3]

https://github.com/SED-EEW/EEWD