Earthquake Early Warning: ShakeAlert in the Pacific Northwest (PDF ...

Bulletin of the Seismological Society of America, Vol. 106, No. 4, pp. –, August 2016, doi: 10.1785/0120150261

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Earthquake Early Warning: ShakeAlert in the Pacific Northwest by J. Renate Hartog, Victor C. Kress, Stephen D. Malone, Paul Bodin, John E. Vidale, and Brendan W. Crowell

Abstract

We evaluate the performance of earthquake early warning algorithm ElarmS-2 (earthquake alarm system v. 2) in the Pacific Northwest. Real-time and prerecorded seismic data from Oregon, California, and Washington in the United States and British Columbia in Canada are used. The earthquakes tested range up to moment magnitude 7.2, the limit for which the ElarmS-2 magnitude method is accurate. ElarmS-2 reliably detects catalog magnitude 3 and larger earthquakes within the network, but the cut-off magnitude for accurate event recognition is higher for events offshore and on the edges of the network. We have made several adjustments that make the ElarmS-2 algorithm less likely to falsely report multiple alerts for earthquakes. Replaying of past earthquakes shows that the new settings improve the algorithm’s behavior for edge cases while not degrading previously well-constrained solutions within the dense part of the network. We expect few false alerts, none that would predict significant shaking anywhere in our region. Even though ElarmS-2 assumes a fixed earthquake depth, the epicenter and magnitude estimates are accurate enough to provide good predictions of shaking intensities.

Online Material: Tables listing parameters of 31 calibration earthquakes, ElarmS-2 real-time detections, and comparison of ElarmS-2 performance for calibration events before and after adjusting configuration.

Introduction Earthquake early warning (EEW) systems quickly detect the beginning of an earthquake and provide warning of impending shaking to people and infrastructure located in harm’s way. Countries that currently have an EEW system in place include Mexico, Japan, Romania, Turkey, and Taiwan (Allen et al., 2009). Only the Mexican and Japanese systems provide alerts to the general public. EEW systems fit into three broad categories (e.g., Allen et al., 2009): (1) networkbased front detection systems, which detect the strong Swave shaking near the epicenter before it reaches population centers and send a warning ahead; (2) P-wave detection systems which use the arrival time, amplitude, and/or frequency content of the faster traveling P waves to estimate location and magnitude and predict the later stronger S-wave shaking levels (some, but not all, of those algorithms will update their estimates once S waves become available); and (3) single-site detection systems that simply use peak amplitude and frequency content of the P wave to warn for imminent stronger shaking at the site. Depending on how close the sensors are to the epicenter and how distant the user is, the warning time could be as short as no warning at all to as long as several minutes. For example, a great megathrust earthquake could initiate any-

where on the Cascadia subduction zone (CSZ, Fig. 1), from northern California to British Columbia. Such an earthquake would cause damaging shaking levels in the large metropolitan areas around Portland, Oregon; Seattle, Washington; and Vancouver, British Columbia, even though they may be located far from the initial rupture. An EEW system might be able to provide up to several minutes of lead times to these urban areas, depending on where the earthquake begins, the density of our seismic station network, and how long it takes seismic waveform data to reach the central processing center in Seattle (data latency) (Fig. 1). Communities closer to the rupture would receive warnings with much less lead times. EEW systems can produce large economic and social benefits to society if the population and infrastructure are sufficiently prepared to take full advantage of the provided warning. Starting in 2007, a demonstration EEW system was developed by partners in the California Integrated Seismic Network (CISN) and scientists from the Swiss Federal Institute of Technology (ETH Zurich). This system, called CISN ShakeAlert, started sending warnings to test users in January 2012, but warnings are not publicly available yet. Currently, three seismic point-source algorithms, ElarmS-2 (Kuyuk et al., 2014), Virtual Seismologist (Cua et al., 2009), and

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J. Renate Hartog, V. C. Kress, S. D. Malone, P. Bodin, J. E. Vidale, and B. W. Crowell

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Peak ground acceleration (g) Figure 1. Broadband and strong-motion seismic stations (triangles) superimposed on the 2014 U.S. National Seismic Hazard map (Petersen et al., 2014) and the 2005 Canadian National Seismic Hazard map (Halchuk and Adams, 2008). Onshore shades indicate peak ground acceleration in fraction of gravitational acceleration g with a 2% chance of being exceeded in the next 50 years. Offshore bathymetry (ETOPO1, Amante and Eakins, 2009) is also shown. Waveform data imported from other networks (inverted black triangles) currently have large latencies (6–120 s). Onsite (Wu and Kanamori, 2005; Wu et al., 2007; Böse et al., 2009), detect and locate earthquakes and estimate an initial magnitude. In addition, a finite-fault algorithm, FinDer (Böse et al., 2012, 2015), has been contributing to the demonstration CISN ShakeAlert system since April 2015. The event parameters and uncertainties estimated by the various algorithms are combined by a decision module into a single best estimate, after which it sends an event message to a public-facing message broker. The ShakeAlert system uses Apache ActiveMQ as the message broker (see Data and Resources). Client software run by the beta users calculates the predicted intensity of shaking and the time until its arrival at that user’s location. The ShakeAlert developer team maintains one application, called the UserDisplay, which pops up a visual warning on the user’s screen and plays an audio message when it detects a warning signal. The ShakeAlert UserDisplay determines the expected shaking intensity from the magnitude and the distance to the earthquake using an empirical ground-motion prediction equation (GMPE) and

intensity prediction equation (IPE). Once a reliable production system is in place, many private partners are expected to develop their own software to refine shaking estimates and execute automatic actions in response to the ShakeAlert warning. In the United States, the seismic hazard is not only high in California, but all along the West Coast (Fig. 1), in Alaska, and in the central United States. Grants from the Gordon and Betty Moore Foundation were provided to the University of California Berkeley (UCB), the California Institute of Technology (CalTech), the University of Washington (UW), and the U.S. Geological Survey (USGS) to develop and coordinate a West-Coast-wide prototype EEW system based on the CISN ShakeAlert system (Given et al., 2014). The Pacific Northwest Seismic Network (PNSN) at the UW was the group designated to tailor the EEW system to Cascadia. Of the three available CISN ShakeAlert seismic algorithms, the PNSN opted to test ElarmS-2 (Kuyuk et al., 2014) first in isolation for use in the Pacific Northwest (PNW). Evaluation of the ShakeAlert system in California shows it to be fast and to generate the fewest false alarms. Tests of ElarmS-2, similar to this article, with data from California, Japan (Brown et al., 2011), and Italy (Olivieri et al., 2008) show it typically has more difficulty determining a good location and magnitude for events that occur far from the seismic network. Thus, a major focus of this article is the performance of the EEW system for earthquakes offshore on the CSZ megathrust. For an end user it is important to know what the error rate of the EEW system is. What are the chances that a significant event will be missed? What are the chances of a false alert? How well will the shaking intensity at my location be predicted? How much warning time will I get? In this article, we specifically address the first two questions with a detailed evaluation of ElarmS-2’s ability to detect, locate, and estimate magnitude for events in the Pacific Northwest. We also validate that the IPEs that are used by the CISN UserDisplay work well for the Pacific Northwest. How much warning time an end user might get depends on how far the user is located from the earthquake and how quickly the system can detect an earthquake and generate and send an alert. As we require ElarmS-2 to wait for a P-wave detection at a minimum of four stations, the two main sources of delay in alert time are the time it takes for the P wave to be detected at four stations and the data latency of those four stations (Bodin et al., 2015). To increase alert lead times, we are reconfiguring and replacing dataloggers at existing sites to decrease data latency, and we are installing new stations to increase network density, mainly along the coast. Detailed analysis of the expected alert lead times is beyond the scope of this article.

PNW ShakeAlert Overview Figure 2 gives an overview of the PNW ShakeAlert system. When ElarmS-2 detects an event and creates a solution that satisfies various quality criteria, it sends an alert message

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Earthquake Early Warning: ShakeAlert in the Pacific Northwest Data

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Figure 2. Flowchart for the Pacific Northwest (PNW) ShakeAlert system, arrows indicate direction of information flow. Dashed lines show components in development, solid lines indicate components currently operational. to the ActiveMQ broker which is processed by the decision module (Fig. 2). Because we only run a single-earthquake detection algorithm, we configured the decision module to pass on the alert without waiting for confirmation from additional algorithms. The decision module checks whether the event’s magnitude is large enough and whether it falls within a preconfigured geographic region. If it does, it passes on an event xml message to the ActiveMQ broker. These messages get relayed to a public-facing ActiveMQ broker. Client software applications register with the publicfacing ActiveMQ broker to receive event messages. Each application calculates the predicted intensity of shaking and its predicted arrival time at that user’s location, based on the earthquake’s estimated magnitude and epicenter. We modified the CISN UserDisplay application with maps appropriate for the Pacific Northwest, and labeled it PNW UserDisplay. It uses the same equations as the CISN version to predict shaking intensity and predicted S-wave arrival time. The empirical GMPE used (Cua et al., 2009) estimates peak ground acceleration and peak ground velocity, and these values are then converted to a modified Mercalli intensity estimate (Worden et al., 2012). Figure 3 shows geocoded community-derived intensity observations from the National Earthquake Information Center “Did You Feel It?” input as a function of epicentral distance for one M w 6.8 earthquake at 52 km depth and four ML 4.3 earthquakes at various depths, as well as the corresponding intensity prediction curves. Even though the current system assumes all earthquakes occur at a depth of 8 km, the intensities observed for these five example earthquakes are predicted reasonably well. For all distances, the majority of the observed intensities are within one intensity unit of the prediction curve. Although this is not a thorough study of seismic intensity patterns in Washington and Oregon, it does provide confidence that the GMPE and IPE used in California are effective here as well. It is difficult to derive robust GMPEs specific to the Pacific Northwest because of a paucity of earthquakes of magnitude greater than Mw 4.5 (e.g., Atkinson, 2005). For earthquakes greater than

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Examples of the intensity attenuation relation used by the PNW UserDisplay (Cua et al., 2009; Worden et al., 2012). Curves for 8-km-deep earthquakes of moment magnitude 3, 4.3, and 6.8 are shown. Solid and dashed lines show the relation for soil (V S30 ≤ 434 m=s) and soft-rock sites (V S30 > 434 m=s), respectively. The shades and descriptive text for each predicted intensity level show the User Display scale. Black crosses are the geocoded community-derived intensities from the “Did You Feel It?” website for the 2001 M w 6.8 Nisqually earthquake. Gray crosses are the geocoded community-derived intensities from four different M L 4.3 Washington earthquakes (see Data and Resources). The color version of this figure is available only in the electronic edition.

Mw 7, finite-fault models in combination with empirical GMPEs derived from global datasets (e.g., Zhao et al., 2006;

Boroschek et al., 2012; Stewart et al., 2013) are needed to estimate what the spatial distribution of ground motions will be. These can be augmented with local site, directivity, and basin amplification effects (e.g., Delorey et al., 2014).

ElarmS-2 Performance Evaluation In the Pacific Northwest, we are specifically interested in, but challenged by, rapidly finding the location and magnitude for subduction zone events, which are likely to initiate offshore (Fig. 1). We do not have any data from large or great earthquakes on the subduction zone with which to calibrate the system. Instead, we have to use smaller earthquakes and synthetic seismograms and estimate the extent to which we can extrapolate our findings to an actual large or great subduction zone earthquake. In this study, we only use real seismograms, not synthetics. The ElarmS-2 algorithm has evolved since it was first developed and described (Allen and Kanamori, 2003). In early 2013, we installed ElarmS v. 2.3.2, written in C++, which is described in detail in Kuyuk et al. (2014). Code development is ongoing, and we upgraded our real-time installation several times since its inception. ElarmS-2 consists of a waveform processor (ElarmSWP-2) that does the arrivaltime picking and measuring of waveform parameters and an event monitor (E2, or EM in Kuyuk et al., 2014) that associates triggers into events, locates events, and sends alerts to

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Figure 4. Map of earthquakes used in this study. White circles show catalog locations of events that occurred during real-time testing from 26 February 2013 to 27 January 2015. Labeled gray circles show catalog locations of events that we can replay. The size of the circles is scaled by catalog magnitude. Topographic relief (ETOPO1, Amante and Eakins, 2009) is represented in grayscale.

the ActiveMQ message broker. E2 sends event updates as it associates additional arrivals with an event. We ran ElarmS-2 in an initial configuration tuned for California for close to two years, and we replayed 31 calibration events using these settings. Figure 4 shows the seismicity during our real-time testing period, which ran from 26 February 2013 through 27 January 2015, except for several short intervals when the system was down. It also shows the locations of 31 prerecorded test events, whose parameters are listed in Ⓔ Table S1, available in the electronic supplement to this article. The test events are in 28 separate multichannel data files. An M w 3.8 earthquake near Mt. Saint Helens has two small (M D 0.8 and

MD 2.8) aftershocks within the same data file, and an M b 4.7 earthquake near Mt. Rainier has an M D 2.8 aftershock within the same data file. The information that we use for analyzing ElarmS-2 performance is obtained from E2 log files. We tried to match each E2 detection to a cataloged event of catalog magnitude one or larger that occurred within our region of interest (38° N–51° N, 115° W–130° W) or a teleseism with catalog magnitude of at least 5.5 that occurred farther than 500 km from Portland, Oregon. Our catalog was retrieved from the Advanced National Seismic System Comprehensive Catalog (ComCat) (see Data and Resources). We compare the

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Earthquake Early Warning: ShakeAlert in the Pacific Northwest ElarmS-2 magnitudes to the reported preferred magnitude (Mpref ), which may be of various types. For larger events, the catalog magnitude usually is the moment magnitude (Mw ), for smaller events the catalog magnitude could be a local magnitude (ML ) or coda duration magnitude (M D ). We declare a match when an E2 event’s first trigger is less than 30 s earlier, or 120 s later, than the arrival time at that station from a catalog event predicted using the ak135 velocity model (Kennett et al., 1995). If more than one catalog event matches, we pick the one that results in the smallest difference between predicted arrival times and observed trigger times. The large time window is required to properly associate poorly located events with the correct catalog event.

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Waveform Processor The waveform processor uses time-domain causal recursive filters to obtain acceleration, velocity, displacement, and instantaneous frequency (τP ) time series in real time (Kanamori et al., 1999). It also uses recursive filters to generate characteristic functions to use in a classic short-term-average over long-term-average (STA/LTA) automatic picker (Allen, 1978). When the STA/LTA ratio exceeds a configurable threshold (set to 20), a trigger is declared, and from 1 s to 4 s later the waveform processor sends signal-to-noise ratios, peak P-wave acceleration (Pa ), velocity (Pv ), displacement (Pd ), and instantaneous frequency (τmax P ) to the message broker every 0.1 s. Pd is used for the magnitude, and Pd and τmax are used to filter out teleseisms. P Initially we were concerned that the California STA/LTA filter parameters might not work for more distant offshore events, because longer travel paths, complex geology, and potential mantle refractions could result in more attenuation of the higher frequencies and thus different waveform characteristics. However, a comparison of the automatically picked trigger times with hand-picked times by our analyst shows that the picker functions well (Fig. 5). As expected for an automatic picker, it tends to pick the onset of the P wave a little late; also, once in a while an S-wave pick is erroneously associated with an event as a P wave. Upon closer inspection, it is clear that most of the misidentified S picks occur for small events (Mpref < 3), and that the picker parameters also work well when just offshore events are considered. The tails of the error distribution are long, but 89% of automatic picks are within 0.5 s of the analyst’s P-wave pick. Because E2 may use very few observations to locate an earthquake, a single very poor pick could result in a large location error. However, picking errors are not the main reason for poor locations; poor locations tend to happen most commonly for events outside of the network (see the Location Accuracy section) and result from poor station distribution. Teleseism Rejection Filter measurements have a large uncertainty, Individual τmax P and for that reason, since September 2012, ElarmS-2 no

Figure 5. Difference between automatic first arrival picks and analyst picks. (a) Difference between ElarmSWP-2 picks and analyst picks (in s) as a function of epicentral distance (km). (b) Histogram of differences (see the Waveform Processor section). longer uses them to determine magnitudes. However, the τmax are still measured to prevent sending out alerts for P distant events (teleseisms) misinterpreted as local events (Kuyuk et al., 2014). The predominant period of teleseisms is long compared to that of local earthquakes, because they are depleted in high frequencies due to longer travel paths. Figure 6 shows the California-calibrated teleseism discrimiand Pd versus τmax measurements nator based on Pd − τmax P P from our real time data and prerecorded data, shaded by whether they are local or teleseismic events. The figure only shows data from events of M pref 3 and larger. Small events often get flagged as teleseisms because of low signal-tovalues noise ratios. All actual teleseisms have average τmax P that are larger than ∼0:8 s, so we now only apply the teleseism filter if logaverageτmax P > −0:1, effectively turning it off for small events. The filter has prevented many false alerts due to misidentified teleseismic events. During our real-time testing period, 98 teleseisms resulted in the generation of 415 distinct ElarmS-2 event IDs, but, thanks to the teleseism filter, only 3 of these resulted in false alerts. One event generated two separate alerts and remained uncancelled. The other two generated one alert each; however, both were soon categorized as teleseisms and cancelled. The original discriminator line was intended to block all out-of-network events and was derived from data recorded within 100 km of an earthquake, whereas the offshore events occur further from many land-based stations. Nevertheless, measurements from offshore earthmost of the Pd − τmax P quakes also fall in the “not teleseism” category. Still the teleseism filter did flag several large offshore events as teleseisms, due to anomalously high τmax P values. Because we are particularly worried about those offshore events near the megathrust, we would like to prevent this from happening. The instantaneous period τP is unstable right after the onset

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Magnitudes ElarmS-2 v. 2.3.8 (3 September 2013 and later) use the Pd magnitude relation derived by Kuyuk and Allen (2013), using data from California and Japan EQ-TARGET;temp:intralink-;df1;313;679

M Pd 5:39 1:23 log10 Pd 1:38 log10 epicentral distance in km:

Figure 6. Illustration of the teleseism filter criteria. The horivalue for an event. zontal axis shows the log10 of the average τmax P The vertical axis shows the log10 of the average Pd -value. We plot measurements from earthquakes with catalog magnitude ≥ 3:0 from our real-time dataset (dark squares) as well as our replay events (larger filled squares). Teleseisms (white squares) tend to have values compared with local and regional earthquakes. higher τmax P We altered the discriminator line from Kuyuk et al. (2014) (dashed line), teleseisms are now assumed to have a minimum log(average τmax P ) of −0:1 (solid line). Some overlap between the local event and teleseism clusters exists. The color version of this figure is available only in the electronic edition. of a signal (e.g., Olson and Allen, 2005). The ElarmS-2 waveform processor therefore waits a configurable amount of time before looking for the maximum τP value. We had this delay set to 0.5 s. Visual inspection of recordings of some of the events that were flagged as teleseisms shows that for many records the large upswing occurs later than 0.5 s after the onset. Therefore, we increased the delay from 0.5 s to 1.5 s. This does prevent several of the replay events from being flagged as teleseisms; however, it is unclear at this time whether this change will result in better discrimination between teleseisms and out-of-network local events, as we have not done a comprehensive survey of waveforms. This issue deserves more attention, beyond the scope of this article. Even with this new setting, it is likely that some offshore events would still be flagged as teleseisms. Because we do want to be able to alert if a large subduction zone earthquake starts in that region, we could run two versions of the ElarmS-2 event manager: (1) a version configured to filter out teleseisms which sends messages to the production message queue that end users connect to, and (2) a version that does not filter out teleseisms so that it can trigger subsequent geodetic algorithms. When a geodetic algorithm confirms that there is a significant local event, it will send an alert message to the public-facing message queue.

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MPd was calibrated against the preferred catalog magnitude of the earthquakes (i.e., a mix of magnitude types). Because the magnitude scale is based on the peak displacement amplitude of the P wave in the first 4 s, it will underestimate the magnitude of events larger than Mw 7. The first version of ElarmS-2 (v. 2.3.2) that we installed used different Pd magnitude relations for southern California (Tsang et al., 2007) and northern California (Wurman et al., 2007). We incorporated equation (1) on our real-time system on 19 March 2014. As the Pd measurement method has not changed, we can compare real-time measurements made before 19 March 2014 to the global magnitude relation as well. We compare the magnitude calculated using equation (1) with the catalog magnitude in Figure 7a. The magnitude estimate is the average of the channel Pd magnitudes. Considerable scatter of individual channel magnitude estimates are evident, but the event-averaged calculated magnitude using equation (1) matches the catalog magnitude fairly well. The Mw 7.2 event is a replay event (15 June 2005) that started out small, and the magnitude is underestimated by almost two magnitude units. In ElarmS-2, a channel’s magnitude estimate is only included if the channel is within a specified distance of the estimated epicenter. This distance was initially hardwired to 100 km in early versions of ElarmS (Brown et al., 2011). That distance is too short for events offshore northern California, which led to the definition of the “Eureka box” for which the station distance is ignored (Kuyuk et al., 2014). Also, since v. 2.3.2, if the closest station distance is greater than 150 km, the maximum distance for inclusion in the magnitude estimate is increased to 200 km. These settings are still not generous enough for determining the magnitudes for offshore events in the Pacific Northwest, because necessary stations may be even farther than 200 km from the estimated offshore epicenter. In Figure 7b, we plot all the measurements corrected to a common Pd magnitude of five to show the dependence on epicentral distance. The figure shows that the magnitude relation can be reasonably used in Washington and Oregon for measurements out to 600 km, although magnitudes would be slightly underestimated. We increased the maximum allowed station distance to 400 km and increased the Eureka box to encompass all of Cascadia (see Fig. 4). These changes prevent the magnitude of the event being set to zero in ElarmS-2 if the solution moves far from the closest stations.

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Earthquake Early Warning: ShakeAlert in the Pacific Northwest

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Figure 7. (a) Calculated channel Pd magnitudes versus catalog magnitudes for alerted real-time events as well as replay events. The squares show the event averages. We only plot the measurements used by the first ElarmS-2 event solution, and we correct for distance using the catalog epicentral distance (i.e., the correct distance). Our measurements fit the relation derived by Kuyuk and Allen (2013) satisfactorily. (b) All channel log10 Pd measurements corrected to a common magnitude (MPd 5) to show dependence on distance. The distance correction appears satisfactory to fairly large distances. The color version of this figure is available only in the electronic edition.

Event Associations The event monitor (E2) associates triggers into events, locates the events, and sends alerts after performing various quality checks on the event parameters. E2 can keep track of several events at once. The E2 associator tries first to associate any unassociated triggers with an existing event, and if it cannot, it then compares them to each other and will create a new event if they satisfy several criteria. If Pd and τmax P are sufficiently large, the associator might create a new event with just one or two stations. The associator checks whether a new trial event might be a duplicate event before adding it to the event pool, but this check has proven to be inadequate, and ElarmS-2 frequently created multiple events for a single

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earthquake. When it is a multistation event, it also checks whether a sufficiently large fraction of nearby stations have triggered (currently configured to 40%) before declaring a new event. Once at least three triggers have been associated into a trial event, the E2 Locator does a grid search to find the best horizontal location (Kuyuk et al., 2014). The current version of ElarmS-2 uses a travel-time table appropriate for an earthquake at 8 km depth, which could be a problem in the Pacific Northwest, because earthquake depths here range up to 100 km. However, because ElarmS-2 does a simple grid search, deeper events result in greater misfit to the observed travel times, but the minimum is located at roughly the correct horizontal location. Many event solutions (detections) do not result in an alert (see Ⓔ Table S2). We require a minimum of four distinct stations and a minimum Pd magnitude of 2.0 for an alert to be sent. The E2 alert module also checks whether a trial event is a teleseism or located on the edge of the grid before publishing a new alert or update to the ActiveMQ message queue. Triggers not associated with an event remain in the trigger pool for 30 s, after which they are removed. When a trigger is associated with an event within 4 s of its trigger time, its channel magnitude is based on Pd within a window less than 4 s in length. This value is then updated every 0.1 s. Figure 8a shows the catalog location of earthquakes with catalog magnitude three or larger that the system did not detect or that it detected but for which it did not send an alert. Most of these are far from the seismic network, and we do not expect to be able to correctly detect these. However, an Mw 6.5 off the coast of Vancouver Island on 24 April 2014 did not result in an alert either, and we would like to be able to alert for earthquakes in that part of the subduction zone. This event was split into multiple ElarmS solutions, and all of those were flagged as teleseisms. We added this event to our set of calibration events. We conclude that ElarmS-2 as configured in California can reliably detect catalog magnitude three and larger events within our network and that some improvements are needed to reliably detect large offshore earthquakes. Figure 8b shows the catalog locations of 11 events that resulted in multiple ElarmS-2 alerts. It also shows the initial E2 location for each alert it sent. E2 generated multiple events mostly for earthquakes far from the network; however, several events within the network were also split. The associator generated multiple solutions for 23 additional earthquakes, but the Alert module sent an alert (and updates) for only one of them. Those events are not shown in Figure 8b; they are included in the list of events with a single alert (see the Location Accuracy section). It is clear from Figure 8b that later-arriving triggers associated into their own local event instead of being added to an existing event, resulting in erroneous locations and magnitudes. The frequent occurrence of split events is a real problem and needs to be mitigated.

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Figure 8. (a) Catalog location of undetected (gray) and unalerted (white) earthquakes with catalog magnitude 3 or bigger. The arrow indicates the M w 6.5 Off Vancouver Island event of 24 April 2014 referred to in the text. (b) Catalog location (circle) of split events with multiple alerts and each initial ElarmS-2 solution (star). Symbol size is scaled by magnitude. The color version of this figure is available only in the electronic edition. We investigated whether the association criteria were too strict, preventing these later triggers from associating with an earlier declared event. For a trigger to be associated with an existing event, its arrival time has to satisfy several criteria. We verified that these criteria (Kuyuk et al., 2014) are reasonable using hand-picked arrival-time data from the local PNSN catalog. For E2 to associate unassociated triggers into a new trial event, they had to be within 100 km of each other. In some parts of our network, the interstation distance is large, and we realized that it was possible for the multithreaded code to create almost simultaneously several events if some of the triggers cannot be included in the first event because they are too far from other triggered stations. So we increased the maximum allowable interstation distance to 250 km to improve locations of events near less dense parts of our network. Using the suite of calibration events showed that changing this parameter decreased the number of split events but did not prevent the problem completely. We also found that the grid we used to locate the earthquake was sometimes too small. Solutions of some offshore events would lie so far from the closest stations that they were not on the grid, resulting in a failed location. With the first-event solution now removed from the event pool, the association of much later triggers led to a second solution that was far from the actual earthquake but not caught by

the split event filter. We increased the size of the search grid from 400 km × 400 km to 1000 km × 1000 km. This change means that the trial earthquake solution, in the center of the grid, can locate up to 500 km away from the closest stations. We kept a grid-point spacing of 2 km. Although the grid search is scanning many more grid points, the code is not significantly slower. The E2 associator module does a split event check before adding a trial event to the event pool. However, this simply checked whether a new event is close in time and space to an existing, previously alerted, event. The blackout time–space window was set to 15 s and 90 km. We did not want to simply increase the time–distance criteria, because we would like to be able to send alerts for potential aftershocks. Figure 9 shows the distance between subsequent distinct E2 solutions for a single event as a function of the difference between their origin times. The split event solutions are not necessarily located close to the actual epicenter of the earthquake; instead, their origin times and locations are consistent with a wave traveling at 8 km=s (mantle P wave). We altered the split event check accordingly (see Fig. 9). Also, previously the split event check only compared candidate event solutions with E2 solutions that had already triggered an alert. We removed this restriction, because initially poorly determined event solutions may still result in well-determined solutions after more phases are associated

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Earthquake Early Warning: ShakeAlert in the Pacific Northwest

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Improved Performance after Adjustments

Figure 9. Illustration of the new split event check criteria. Each circle represents a subsequent ElarmS-2 solution compared to the first ElarmS-2 solution for a split earthquake. The horizontal axis is the difference in estimated origin time, and the vertical axis shows the horizontal distance between the two solutions. PNW ElarmS-2 now rejects a subsequent ElarmS-2 trial solution if it falls between the two lines. Previously ElarmS-2 rejected a split event solution only if its origin time was within 15 s of an existing event and its location was within 90 km (rectangular box). with it. These changes to the split event check mitigate the problem, although they still do not completely prevent split events. False Alerts In addition to the four false alerts due to teleseisms and ghost alerts from the split events, it is possible that ElarmS-2 associates noise triggers into events. We found only one alert that was due to near simultaneous noise on several seismic stations. None of the false alerts would have resulted in predictions of damaging shaking levels anywhere. We anticipate that our modifications of the configuration will prevent the large number of split events, leaving at most a few false alerts per year, none of which are likely to predict high shaking levels. Location Accuracy Figure 10a shows the catalog locations and initial ElarmS-2 solutions for the 268 events that resulted in a single alert. This includes the 23 events for which ElarmS actually created multiple events but only sent an alert for one. Some of those alerted solutions were very poor, as is clear when comparing Figure 10a with Figure 10b, in which those events are removed. Overall, the simple grid search locates most events to within 25 km of the catalog location (67.5%). Sometimes, a location is biased toward the cluster of stations that were used in locating the event. Also, events on the edges of the seismic network have larger location errors due to a larger maximum azimuthal gap between the stations.

Replaying events through the system tests the picking, associating, and location ability of the algorithm as well as the total processing time. Because the data have no real latency, the alert times that come out of the system are a minimum. In the replay setup, after the P-wave triggers the furthest station used in the first alert, it takes 1.7 s–3.8 s before an alert is sent (“processing time”). Real-time data do have latencies when they arrive at our data center, and the processing times from 26 February 2013 to 27 January 2015 ranged from 0.8 to 100 s, with a peak around 5 s. Here, we contrast the results before and after adjusting ElarmS-2 based on our findings above from the real-time data. Our adjustments are to (1) assume that teleseisms have > 0:8, (2) start measuring τmax after 1.5 s instead of a τmax P P 0.5 s, (3) increase the allowable distance between triggered stations when creating a new trial event from 100 to 250 km, (4) use a much larger search grid for finding a location, (5) allow magnitude observations from farther distances, and (6) change the split event check. Ⓔ Table S3 summarizes the number of solutions, number of alerts sent, alert time, origin-time error, mislocation distance, and magnitude error for each calibration event before and after adjustment. Nine of the thirty-one events did not have sufficient station coverage for ElarmS-2 to create an alert before, as well as after, we made our adjustments to the configuration. Before adjustment, successful, single, alerts were sent for only 17 events, compared to 22 after the adjustment. Before adjustment, three events had multiple alerts; afterward none did. Three events were split after the adjustments were made, but in all three cases a single alert was sent for the best solution.

E2 Performance by Source Region The three test events from just north of the Mendocino Triple Junction (15 June 2005 M w 7.2, 25 June 2007 M w 5.0, 17 August 2008 M w 4.6) resulted in single E2 alerts before and after adjustment, and the location and magnitudes are reasonable, except for the M w 7.2 event that started out small and is underestimated by almost 2 magnitude units. The realtime testing results confirm that we can get reasonable locations for many events in that area (Fig. 10); however, we also missed some of the Mpref 3 events (Fig. 8a), and several split events resulted in small-magnitude false alerts in central Oregon (Figs. 8b and 10). We conclude that ElarmS-2 can send an accurate alert for significant events in that region. Beta users from northern California subscribe to the prototype CISN ShakeAlert system; however, beta users in southern Oregon subscribe to the prototype PNW ShakeAlert system, and we therefore do include data from northern California as well. If funding is continued, eventually a West Coast wide ShakeAlert system will be implemented (Given et al., 2014) which will present to users as a single system.

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(a)


Events with single alert (N=264) Initial ElarmS-2 solution

(b)

Events with single alert (N=241) Initial ElarmS-2 solution

Figure 10.

(a) Catalog locations (circles) and initial ElarmS-2 solutions (stars) for all events with a single ElarmS-2 alert. 67.5% of solutions are within 25 km of the catalog solution and 83.5% are within 50 km. (b) same as (a), except that the 23 events that were split into multiple ElarmS-2 detections are removed (see text). The color version of this figure is available only in the electronic edition.

The two small test events beneath the coastline of southern Oregon (3 July 2010 Mw 3.7, 30 November 2012 M L 3.3) had good solutions both before and after adjustment. This gives us confidence that we can reliably send alerts for earthquakes there, even though two Mpref 3 earthquakes in that region were not alerted on during the real-time testing period (Fig. 8a). We are increasing the station density along the Oregon Coast, and our detection ability in that region will improve. The three test events from the Blanco transform fault system offshore southern Oregon (10 January 2008 Mw 6.3, 15 March 2008 M w 5.7, 12 July 2008 Mw 5.0) are too far away and did not generate any alerts. The same has been true for these types of events during real-time testing. A few were split events and generated small-magnitude false alerts within southwestern Washington (Fig. 10). We expect to reduce these type of split event alerts with the adjusted parameters. We do not need to send alerts for this type of earthquake, because they will not impact the population on land. The test event just beyond the CSZ front offshore southern Oregon (28 July 2010 Mw 5.2) resulted in many solutions and three poorly located alerts before adjustment and only a single, initially poorly located alert afterward. In contrast, the test event (12 July 2004 M w 4.9) closer to the coast within the CSZ in central Oregon generated an alert both before and after adjustment with a fair location and good magnitude estimate. We also detected three small central Oregon events during our real-time testing and missed none (Figs. 8a and 10). We

conclude that we are able to detect and locate offshore earthquakes as long as they are not too far from the coast. During real-time testing it became clear that, with the current station configuration, it is difficult to alert for earthquakes that happen off the northern Vancouver Island coast, near the CSZ interface. ElarmS-2 either did not detect them at all, labeled them as teleseisms (Fig. 10a), or sent multiple alerts (Fig. 8b). We selected eight events from this area to replay. ElarmS-2 cannot locate the three events from 2004 (15 July 2004 Mw 5.9, 19 July 2004 Mw 6.3, and 2 November 2004 M w 6.6) because too few Canadian stations are in the data file, illustrating the value of exchanging real-time data with the Canadian National Seismograph Network. The other four test events resulted in many split solutions before adjusting the parameters, most of which were labeled teleseisms. The adjusted system created single successful alerts for all four events. In particular, the 24 April 2014 M w 6.5 event generated three separate ElarmS-2 solutions when it was processed in real time, all of which were misclassified as teleseisms. When running it through our test system with the same configuration, it created seven solutions that were all labeled teleseisms. After our changes it created and alerted a single solution with an initial location estimate less than 15 km from the catalog location and a Pd magnitude of 6.1. We conclude that the adjusted parameters improve the ability of ElarmS-2 to detect and locate moderate-to-large earthquakes in this region but that additional seismic stations

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Earthquake Early Warning: ShakeAlert in the Pacific Northwest may be needed to reliably detect the beginning of a subduction zone earthquake there. Onshore, within the station network, E2 created single solutions and alerts for 13 of the 31 earthquakes with the original configuration. For almost all those events, adjusted E2 created an identical or slightly better solution. In one case it created a worse location, because it used more distant stations. E2 created split events for the Mt. St. Helens event and aftershocks (14 February 2011 [Mw 3.8, M D 0.8, M D 2.8]) in its original configuration but did not after adjustment. We conclude that the new configuration improves E2’s ability to find solutions for difficult-to-constrain events while retaining good solutions for well-constrained locations and magnitudes.

Conclusions We have run ElarmS-2, the decision module, and the PNW ShakeAlert UserDisplay in real-time testing mode for almost two years and have adjusted the ElarmS-2 algorithm so that it is less likely to send multiple alerts for earthquakes on the edges and outside of our station network. Because solutions within the denser part of the network are not negatively impacted by the changes, we believe that our configuration also could be safely adopted in California. We expect few false alerts, and we expect none that would predict significant shaking anywhere. Location and magnitude estimates are crude but sufficient to provide reasonable predictions of shaking intensities for earthquakes up to about M w 7. We have enough confidence in the updated system that we have been sending alerts to a select group of external users since mid-February 2015. This group of users has been briefed about the uncertainties and limitations of the current system. The current PNW ShakeAlert demonstration system does not have 24/7 support, nor does it have an adequate high-density, low-data latency station network everywhere in the region. However, it is a proof of concept and allows the participating companies and institutions to begin to plan how they will use EEW within their respective organizations. At the time of this writing, we have run the newly adjusted system in real time for a year. On 30 May 2015, a very deep Mw 7.8 earthquake south of Japan generated exceptionally large P-wave displacements on the United States West Coast, which caused PNW ShakeAlert to send five false alerts, underscoring the need for a better teleseism filter. Although no multiple alerts were sent out for any local or offshore events, a few far offshore earthquakes resulted in single alerts with poor locations, because they had been split into several detections by the associator. As expected, all M pref 3 and larger events within the network generated accurate alerts. All original algorithms used in ShakeAlert assume a point-source earthquake, which is not adequate to correctly predict the shaking intensity due to very large (M w > 7) earthquakes. Therefore, ongoing research efforts in both the Pacific Northwest and California have focused on quickly determining the dimensions of the rupture, using either seismic or geodetic data (Böse et al., 2012, 2013, Grapentin et al., 2014a,b).

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The FinDer algorithm is already contributing solutions in real time to the prototype CISN ShakeAlert system (Böse et al., 2015). In the Pacific Northwest, we are currently testing the G-FAST method (Crowell et al., 2016), which uses real-time Global Navigation Satellite Systems precise-point position measurements to update magnitude estimates using peak ground displacement (Crowell et al., 2013) and a method that models the total slip distribution to be able to more accurately predict ground shaking at a distance (Crowell et al., 2012). In summary, PNW ShakeAlert is now producing reliable estimates of location and magnitude for the purposes of EEW. Current shortcomings are understood and will be minimized over the next few years as the PNSN fully implements our existing plan (Given et al., 2014), assuming funding is forthcoming.

Data and Resources The U.S. National Hazard Map data for Figure 1 were downloaded from http://earthquake.usgs.gov/hazards/products /conterminous/index.php#2014 (last accessed November 2014). The Canadian National Hazard Map data for Figure 1 were downloaded from http://www.earthquakescanada.nrcan. gc.ca/hazard-alea/interpolat/index-eng.php (last accessed 20 January 2015). The ETOPO1 (Amante and Eakins, 2009) model was downloaded from https://www.ngdc.noaa.gov/mgg /global/global.html (last accessed November 2014). Documentation for Apache ActiveMQ can be found at http://activemq. apache.org/ (last accessed May 2016). Event parameters from the Advanced National Seismic System Comprehensive Catalog (ComCat) were downloaded on 31 March 2015 (http:// earthquake.usgs.gov/fdsnws/event/1/, last accessed May 2016). The “Did You Feel It?” (DYFI) data in Figure 3 were downloaded from U.S. Geological Survey DYFI archive on 27 March 2015: 28 February 2001 Mw 6.8, Nisqually (http:// earthquake.usgs.gov/earthquakes/eventpage/usp000aam8#dyfi, last accessed May 2016); 22 July 2001 M b 3.6 (MD 4.3), Seattle-Tacoma Urban Area, Washington (http://earthquake. usgs.gov/earthquakes/eventpage/usp000ajzn#dyfi, last accessed May 2016); 14 February 2011 Mw 3.8 (M D 4.3), Mount St. Helens Area, Washington (http://earthquake.usgs.gov/earthquakes/ eventpage/usp000huhd#dyfi, last accessed May 2016); 27 June 2013 M L 4.3, North of Leavenworth, Washington (http:// earthquake.usgs.gov/earthquakes/eventpage/uw60546146#dyfi, last accessed May 2016); and 18 February 2015 ML 4.3, Eastnortheast of Cle Elum, Washington (http://earthquake.usgs. gov/earthquakes/eventpage/uw60971201#dyfi, last accessed May 2016). Figures were made using a combination of Generic Mapping Tools (GMT, Wessel et al., 2013), Matplotlib (Hunter, 2007), and Adobe Illustrator CS6.

Acknowledgments We would like to thank the reviewers and the California Integrated Seismic Network (CISN) ShakeAlert development team, in particular Ivan Henson and Doug Neuhauser of the University of California Berkeley, Claude Felizardo of the California Institute of Technology, and Maren Böse,

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now at ETH Zurich. This work was funded by the Gordon and Betty Moore Foundation and the U.S. Geological Survey.

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Department of Earth and Space Sciences University of Washington Johnson Hall Rm-070 Box 351310, 4000 15th Avenue NE Seattle, Washington 98195-1310 jrhartog@uw.edu

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Manuscript received 23 September 2015; Published Online 5 July 2016