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Earthquake early warning systems (EEWSs) aim to rapidly detect earthquakes and provide timely alerts, so that users can take protective actions prior to the onset of strong ground shaking. The promise and limitations of EEWSs have both been widely debated. On one hand, an operational EEWS could mitigate earthquake damage by triggering potentially cost- and life-saving actions. These range from automated system responses such as slowing down trains to the actions of individuals that receive the alerts and take protective measures. On the other hand, the effectiveness of an EEWS is conditional on the ability to issue warnings that are sufficiently accurate and timely to facilitate an appropriate action. The refinement of earthquake early warning (EEW) algorithms and the installation of denser and faster seismic networks have improved performance; however, the benefit in risk reduction that an EEWS could achieve remains unquantified. In this study, we leverage upon regional event-based probabilistic seismic risk assessment to devise a quantitative and fully customizable framework for evaluating the effectiveness of EEW in mitigating seismic risk. We demonstrate this framework using Switzerland as a testbed, for which we compute and contrast human loss exceedance curves with and without EEW., Earthquake Spectra, 39 (2), ISSN:8755-2930, ISSN:1944-8201

Supplemental material, sj-pdf-1-eqs-10.1177_87552930231153424 for A framework to quantify the effectiveness of earthquake early warning in mitigating seismic risk by Athanasios N Papadopoulos, Maren Böse, Laurentiu Danciu, John Clinton and Stefan Wiemer in Earthquake Spectra

The ShakeAlert Earthquake Early Warning (EEW) System issues public alerts in the states of California, Oregon, and Washington with a mission of reducing injuries and property loss from damaging earthquakes.Shortly after ShakeAlert went live in 2019, the Ridgecrest earthquake sequence provided a major test of the system’s capabilities.For several reasons ranging from the inherent limitations of EEW, to data telemetry and algorithm deficiencies, ShakeAlert failed to provide useable warnings for most locations where people were in danger for both the M6.4 and M7.1 mainshocks [Chung et al. 2020].Since Ridgecrest, the ShakeAlert algorithm development and testing team has improved all components of the software and evaluation mechanisms, resulting in dozens of updates to the operational system. We expect version 3.0 of the ShakeAlert software to go live in the summer of 2023. This version is the first to include a geodetic algorithm aimed at large subduction ruptures in Cascadia. We will present various evaluations of expected performance of ShakeAlert in large earthquakes from offline testing.For instance, over 70% of instrumented sites that experienced strong or greater shaking in the 2016 M7.1 Kumamoto earthquake could have received at least 10 s of warning before strong shaking began using the ShakeAlert MMI 4 contour product depending on delivery latencies.Similarly, during the 2022 M6.4 Ferndale earthquake in Northern California, the real-time system published the MMI 4 contour product more than 10 s before strong shaking at about 50% of instrumented sites., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The goal of earthquake early warning (EEW) is to issue an alert before the damagingseismic waves of an earthquake hit a given exposure. We develop a framework to evaluatethe EEW performance in a loss-based context. We use warning time as a key performanceindicator and determine statistics of warning time by loss severity to assess therate and consistency with which an EEW system can deliver timely alerts. In the secondpart of this work, we develop a Genetic Algorithm approach to optimize an existing sensornetwork by proposing sites for new stations to enhance the EEW performance indamaging earthquakes.We demonstrate this framework for Switzerland using 2000 realizationsof a 50-yr-long stochastic earthquake catalog, which samples the earthquakerate forecast of the Swiss Hazard Model in space and time. For each of the almost24k earthquake scenario ruptures (5.0 ≤ M ≤ 7.4), we predict shaking intensitiesand losses (here, fatalities and injuries) at the largest Swiss cities. We find that the currentSwiss Seismic Network could provide positive warning times to the affected sites forabout 80% of very damaging earthquakes (≥100 fatalities) and for around 85% ofearthquakes with ≥10 fatalities. Warning times of > 5 s could be achieved for about40%–55% of very damaging earthquakes and > 10 s for about 35%. For around 50%of events with ≥1 fatality (≥10 injuries), EEW could provide > 15 s of warning. Thegreatest benefit of EEW is expected in Zürich, where the population density and, consequently,absolute long-term expected losses are highest and the warning times fordamaging earthquakes are often long ( > 15 s). Densifying the Swiss Seismic Networkwith additional stations can increase warning times in selected scenarios by up to 5 s.However, because it is already very dense (7 ± 5 km interstation distance), decreasingdata latencies (currently ∼ 2 s) may be more important.

The Swiss Seismological Service (SED) at ETH has been developing methods and open-source software for Earthquake Early Warning (EEW) for more than a decade and has been using SeisComP for earthquake monitoring since 2012. The SED has built a comprehensive set of SeisComP modules that can provide EEW solutions in a quick and transparent manner by any seismic service operating SeisComP. To date, implementations of the Virtual Seismologist (VS) and Finite-Fault Rupture Detector (FinDer) EEW algorithms are available. VS provides rapid EEW magnitudes building on existing SeisComP detection and location modules for point-source origins. FinDer matches growing patterns of observed high-frequency seismic acceleration amplitudes with modeled templates to identify rupture extent, and hence can infer on-going finite-fault rupture in real-time. Together these methods can provide EEW for all event dimensions from moderate to great, if a high quality, EEW-ready, seismic network is available. In this paper, we benchmark the performance of this SeisComP-based EEW system using recent seismicity in Switzerland. Both algorithms are observed to be similarly fast and can often produce first EEW alerts within 4–6 s of origin time. In real time performance, the median delay for the first VS alert is 8.7 s after origin time (56 earthquakes since 2014, from M2.7 to M4.6), and 7 s for FinDer (10 earthquakes since 2017, from M2.7 to M4.3). The median value for the travel time of the P waves from event origin to the fourth station accounts for 3.5 s of delay; with an additional 1.4 s for real-time data sample delays. We demonstrate that operating two independent algorithms provides redundancy and tolerance to failures of a single algorithm. This is documented with the case of a moderate M3.9 event that occured seconds after a quarry blast, where picks from both events produced a 4 s delay in the pick-based VS, while FinDer performed as expected. Operating on the Swiss Seismic Network, that is being continuously optimised for EEW, the SED-ETHZ SeisComP EEW system is achieving performance that is comparable to operational EEW systems around the world. ISSN:2296-6463

The Finite-Fault Rupture Detector (FinDer) algorithm computes rapid line-source rupture models from high-frequency seismic acceleration amplitudes (PGA). In this paper, we propose two extensions to FinDer, called FinDerS and FinDerS+, which have the advantage of taking into account a geological property of the source fault, its structural maturity, as well as its relation to the earthquake slip distribution. These two new algorithms calculate real-time earthquake slip profiles by backprojecting seismic and/or geodetic displacement amplitudes onto the FinDer line-source. This backprojection is based on a general empirical equation established in previous work that relates dynamic peak ground displacement (PGD) at the stations to on-fault coseismic slip. While FinDerS projects PGD onto the current FinDer line-source, FinDerS+ allows the rupture to grow beyond the current model extent to predict future rupture evolution. For an informed interpolation and smoothing of the estimated slip values, FinDerS and FinDerS+ both employ a generic empirical function that has been shown to relate the along-strike gradient of structural maturity of the ruptured fault, the earthquake slip distribution, and the rupture length. Therefore, while FinDer derives magnitudes from a relatively uncertain and general empirical rupture length-magnitude relations, FinDerS and FinDerS+ provide alternate and better informed magnitude estimates using the mean slip of the profiles derived from the integration of fault source maturity. The two new algorithms can incorporate both seismic strong-motion and geodetic displacement data. In order to recover PGD from strong-motion instruments, we double-integrate and high-pass filter ( > 0.075 Hz) the seismic acceleration records. Together, the three algorithms exploit the full spectrum of ground-motions, including high frequencies to derive a source fault model (FinDer) and low frequencies to determine the static offsets along this model (FinDerS and FinDerS+). We test the three algorithms for the 2019 MW 7.1 Ridgecrest (California), 2016 MW 7.0 Kumamoto (Japan), and 2008 MW 7.9 Wenchuan (China) earthquakes. Conclusively, low frequency PGD data and integration of the fault maturity gradient do not speed-up calculations for these events, but provide additional information on slip distribution and final rupture length, as well as alternative estimates of magnitudes that can be useful to check for consistency across the algorithm suite. The FinDer algorithms systematically outperform previously established real-time PGD-based magnitude estimates in terms of speed and accuracy. The resulting slip distributions can be useful for improved ground motion prediction given the observed relationship between seismic radiation and fault maturity., Frontiers in Earth Sciences, 9, ISSN:1863-4621, ISSN:1863-463X

Earthquake early warning (EEW) not only improves resilience against the risk of earthquake disasters, but also provides new insights into seismological processes. The Finite-Fault Rupture Detector (FinDer) is an efficient algorithm to retrieve line-source models of an ongoing earthquake from seismic real-time data. In this study, we test the performance of FinDer in the Sichuan-Yunnan region (98.5oE–106.0oE, 22.0oN–34.0oN) of China for two datasets: the first consists of seismic broadband and strong-motion records of 58 earthquakes with 5.0 ≤ MS ≤ 8.0; the second comprises additional waveform simulations at sites where new stations will be deployed in the near future. We utilize observed waveforms to optimize the simulation approach to generate ground-motion time series. For both datasets the resulting FinDer line-source models agree well with the reported epicenters, focal mechanisms, and finite-source models, while they are computed faster compared to what traditional methods can achieve. Based on these outputs, we determine a theoretical relation that can predict for which magnitudes and station densities FinDer is expected to trigger, assuming that at least three neighboring stations must have recorded accelerations of 4.6 cm/s2 or more. We find that FinDer likely triggers and sends out a report, if the average distance between the epicenter and the three closest stations, Depi, is equal or smaller than log10 (Ma + b) + c, where a = 1.91, b = 5.93, and c = 2.34 for M = MW ≥ 4.8, and c = 2.49 for M = MS ≥ 5.0, respectively. If the data used in this study had been available in real-time, 40–70% of sites experiencing seismic intensities of V-VIII (on both Chinese and MMI scales) and 20% experiencing IX-X could have been issued a warning 5–10 s before the S-wave arrives. Our offline tests provide a useful reference for the planned installation of FinDer in the nationwide EEW system of Chinese mainland., Frontiers in Earth Science, 9, ISSN:2296-6463

On the 26th of November 2018, NASA’s InSight lander successfully touched down on the Martian ground in Elysium Planitia. The lander transported among other instruments a single three-component broadband seismometer to measure seismic events and subsequently determine the seismic activity level and eventually the internal structure of Mars. In this study we focus on characterizing the source mechanisms of the highest-quality marsquakes detected so far: The events with highest SNR occurred on sols 173 (S0173a, May 23rd 2019) and 235 (S0235b, July 27th 2019) with Mw > 3.5, showing clearly polarized P and S waves. The InSight MarsQuake Service has estimated their distances to be around 27 degrees, nearby the Cerberus Fossae Graben system. Two more events, S0183a and S0325b have less clear body wave phases and locations, but are also interpreted to be related to it.We have developed a grid-search based method to fit synthetic waveforms to the observed first arriving P and S wave trains. The four source parameters we invert for in this study are the three unique orientation angles of the source mechanism, strike (φ), dip (δ) and rake (λ), and the depth of the event. Synthetic seismograms are generated by computing Green’s functions based on the epicentral distance determined by the InSight MarsQuake Service (MQS) and radially symmetric velocity models. These Green’s function are then convolved with a source time function including an estimated global body wave attenuation to obtain realistic seismograms. The two high-quality event recordings originating from the Cerberus Fossae (CF) fault system were analyzed. Multiple velocity models, frequency bands and window lengths around the arriving phases were used to explore the non-uniqueness in the inverse problem of the inherently ambiguous single-station data. We found that using plausible structural models based on geophysical modeling, the first 10-15 seconds of the waveforms can be fit, constraining the source mechanism and depth, but that the estimation of the uncertainty remains challenging.

Although numerous Earthquake Early Warning (EEW) algorithms have been developed to date, we lack a detailed understanding of how often and under what circumstances useful ground motion alerts can be provided to end users. In particular, it is unclear how often EEW systems can successfully alert sites with high ground motion intensities. These are the sites that arguably need EEW alerts the most, but they are also the most challenging ones to alert because they tend to be located close to the epicenter where the seismic waves arrive first. Here we analyze the alerting performance of the Propagation of Local Undamped Motion (PLUM), Earthquake Point‐Source Integrated Code (EPIC), and Finite‐Fault Rupture Detector (FinDer) algorithms by running them retrospectively on the seismic strong‐motion data of the 219 earthquakes in Japan since 1996 that exceeded Modified Mercalli Intensity (MMI) of 4.5 on at least 10 sites (M_w 4.5–9.1). Our analysis suggests that, irrespective of the algorithm, EEW end users should expect that EEW can often but not always provide useful alerts. Using a conservative warning time (t_w) definition, we find that 40–60% of sites with strong to extreme shaking levels receive alerts with t_w > 5 s. If high‐intensity shaking is caused by shallow crustal events, around 50% of sites with strong (MMI~6) and 5 s. Our results provide detailed quantitative insight into the expected alerting performance for EEW algorithms under realistic conditions. We also discuss how operational systems can achieve longer warning times with more precautionary alerting strategies.