Towards Assessing the Quality of Surface Wave Associations in the Reviewed Event Bulletin
Authors: Condon John , Selby Neil , Keeble Jessica 
Published: March 2022

&lt;p&gt;. ABSTRACT&lt;br&gt;When monitoring for possible underground nuclear tests,&lt;br&gt;identifying shallow earthquakes from explosive sources can&lt;br&gt;be achieved using the ratio of the body-wave magnitude to&lt;br&gt;the surface-wave magnitude (mb:Ms criterion), with explosive&lt;br&gt;sources producing less energetic surface wave excitation.&lt;br&gt;Current methods for automated surface-wave detection at the&lt;br&gt;International Data Centre (IDC) rely on a dispersion test - a&lt;br&gt;global group-velocity model is used to predict a time window&lt;br&gt;based on event origins in the IDC Reviewed Event Bulletin&lt;br&gt;(REB). The data in the predicted time window are narrowband&lt;br&gt;filtered into eight frequency bands - if the time of the maximum&lt;br&gt;energy of at least 6/8 of the bands sits within a specified error&lt;br&gt;of the expected dispersion curves, a surface wave is said to be&lt;br&gt;detected. Stevens et al. (2001) added phase match filtering to&lt;br&gt;the process to improve the signal-to-noise ratio, and this was&lt;br&gt;implemented into provisional operations at the IDC in 2010,&lt;br&gt;under the name Maxpmf.&lt;/p&gt;&lt;p&gt;A number of issues can potentially arise with this automatic&lt;br&gt;detection technique, leading to false detections and mis-associations, these include:&lt;br&gt;&amp;#8226; local noise passing the dispersion test and being erroneously associated;&lt;br&gt;&amp;#8226; surface waves detected at close-to-regional distances&lt;br&gt;experience little dispersion and hence impulsive signals&lt;br&gt;can pass the dispersion test;&lt;br&gt;&amp;#8226; since automatic detection is only attempted for REB&lt;br&gt;events, some surface waves may be missed entirely, as&lt;br&gt;they lack an origin from which to calculate an arrival-time&lt;br&gt;window.&lt;/p&gt;&lt;p&gt;Assuming random noise and that the signals are independent,&lt;br&gt;Stevens (2007) defined parameters that determine the false&lt;br&gt;alarm rate, determined empirically from the network as it was&lt;br&gt;in 2007. Stevens (2007) recommended that these parameters be&lt;br&gt;continually reviewed. Since automated surface wave processing&lt;br&gt;at the IDC was implemented, the number of International&lt;br&gt;Monitoring System (IMS) seismic stations with at least one&lt;br&gt;surface-wave detection in the REB has significantly increased&lt;br&gt;(from around 50 stations in 2002, to around 145 in 2020)&lt;br&gt;without review of the false alarm rate parameters.&lt;br&gt;We have designed interactive software to manually review&lt;br&gt;stages of the IDC automatic surface-wave detection algorithm.&lt;br&gt;We will use this to investigate the false-detection rate and&lt;br&gt;how it has changed over time, and interrogate whether the&lt;br&gt;independence and random noise assumptions this prediction is&lt;br&gt;predicated on are still valid for a larger network.&lt;/p&gt;&lt;p&gt;&lt;br&gt;REFERENCES&lt;br&gt;Stevens, J. L., 2007. Automatic surface wave processing support&lt;br&gt;and documentation, Tech. rep., CTBTO Vienna International&lt;br&gt;Centre.&lt;br&gt;Stevens, J. L., Adams, D. A., &amp; Baker, G. E., 2001. Improved&lt;br&gt;surface wave detection and measurement using phasematched filtering with a global one-degree dispersion model,&lt;br&gt;Tech. rep., Science Applications International Corp San&lt;br&gt;Diego CA.&lt;/p&gt;