Time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai earthquakes estimated from distant tsunami waveforms on the west coast of North America

We estimated the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai earthquakes from tidal records of two tide gauge stations (San Francisco and San Diego) on the west coast of North America. The first signals of the Ansei–Tokai tsunami were apparent, whereas those of the Ansei–Nankai tsunami were obscured by the later waves of the Ansei–Tokai tsunami. Waveforms of the Ansei–Nankai tsunami simulated with nonlinear dispersive wave theory by assuming an origin time of 07:00 GMT on 24 December arrived earlier than in the observations. The normalized root mean square and the misfit between the simulated and observed waveforms of the Ansei–Nankai tsunami showed a time difference between them of approximately 0.4 h. This finding suggests that the actual origin time of the Ansei–Nankai tsunami was approximately 07:24 GMT on 24 December. A previous study estimated the origin time of the Ansei–Tokai tsunami to be about 00:30 GMT on 23 December. Thus, we concluded that the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai tsunamis was 30.9 h. Despite the significant difference in the time resolution between the seasonal timekeeping system used in Japan in 1854 and waveform digitization, our result is roughly in agreement with historical descriptions of the tsunamis, suggesting that such information can be effectively used to determine the origin times of historical earthquakes.

Imaging crustal structures through a passive seismic imaging approach in a mining area in Saxony, Germany

We have used several flooding-induced microseismic events that occurred in an abandoned mining area to image geological structures close to the hypocentres in the vicinity of the mine. The events have been located using a migration-based localization approach. We used the recorded full waveforms of these localized microseismic events and have processed these passive source data as if they resulted from active sources at the known hypocentre location and origin time defined by the applied location approach. The imaging was then performed using a focusing 3D prestack depth migration approach for the secondary P-wave arrivals. The needed 3D migration velocity model was taken from a recent 3D active (controlled-source) seismic survey in that area. We observed several clear and pronounced reflectors in our obtained 3D seismic image cube, some of them related to a major fault zone in that area and some correlating well with information from the nearby mining activities. We compared our results to the 3D seismic image cube obtained directly from the 3D active seismic survey and have found new structures with our approach that were not known yet, probably because of their steep dips which the 3D active seismic survey had not illuminated. The location of the hypocentres at depth with respect to the illumination angles of those structures proved to be favourable in that case, and our 3D passive image complements the 3D active seismic image in an elegant way, thereby revealing new structures that cannot be imaged otherwise with surface seismic configurations alone.

The Impact of 3D Finite-Fault Information on Ground-Motion Forecasting for Earthquake Early Warning

ABSTRACT We identify aspects of finite-source parameterization that strongly affect the accuracy of estimated ground motion for earthquake early warning (EEW). EEW systems aim to alert users to impending shaking before it reaches them. The U.S. West Coast EEW system, ShakeAlert, currently uses two algorithms based on seismic data to characterize the earthquake’s location, magnitude, and origin time, treating it as a point or line source. From this information, ShakeAlert calculates shaking intensity and alerts locations where shaking estimates exceed a threshold. Several geodetic EEW algorithms under development would provide 3D finite-fault information. We investigate conditions under which this information produces sufficiently better intensity estimates to potentially improve alerting. Using scenario crustal and subduction interface sources, we (1) identify the most influential source geometry parameters for an EEW algorithm’s shaking forecast, and (2) assess the intensity alert thresholds and magnitude ranges for which more detailed source characterization affects alert accuracy. We find that alert regions determined using 3D-source representations of correct magnitude and faulting mechanism are generally more accurate than those obtained using line sources. If a line-source representation is used and magnitude is calculated from the estimated length, then incorrect length estimates significantly degrade alert region accuracy. In detail, the value of 3D-source characterization depends on the user’s chosen alert threshold, tectonic regime, and faulting style. For the suite of source models we tested, the error in shaking intensity introduced by incorrect geometry could reach levels comparable to the intrinsic uncertainty in ground-motion calculations (e.g., 0.5–1.3 modified Mercalli intensity [MMI] units for MMI 4.5) but, especially for crustal sources, was often less. For subduction interface sources, 3D representations substantially improved alert area accuracy compared to line sources, and incorrect geometry parameters were more likely to cause error in calculated shaking intensity that exceeded uncertainties.

The Rann of Cutch Earthquake of 21 July 1956

A seismometric study of the earthquake of 21 July 1956 in the Rann of Cutch, which caused destruction to life and property at Anjar, has been made. The epicentre and origin time have been determined by the method of least squares and are Lat. 23°20'N, Long 70000' E and 15h 32m 26S GMT respectively. The shock had a magnitude of 7 and a depth of focus of nearly 13 to 18 km.

Rapid Earthquake Source Description Using Variometric-Derived GPS Displacements toward Application to the 2019 Mw 7.1 Ridgecrest Earthquake

Using near-field high-rate Global Positioning System (GPS) displacements to invert for earthquake fault slips in real time has the potential to improve the accuracy of earthquake early warning or tsunami early warning. For such applications, real-time retrieval of high-accuracy GPS displacements is essential. Here, we report on rapid modeling of the 2019 Mw 7.1 Ridgecrest earthquake with real-time GPS displacements derived from a variometric approach with readily available broadcast ephemeris. This method calculates station variations in real time by differencing continuous phase observations and does not rely on precise orbit and clock information. The phase ambiguity is also removed, and thus the method does not suffer from a relatively long convergence time. To improve the accuracy of variometric displacements, we use a local spatial filter to decrease the influence of residual errors that cannot be removed completely by the time difference. We invert for the centroid moment tensor, static fault slips, and fault rupture process from the derived displacements. Our results show that all inverted models are available within about 65 s after the origin time of the earthquake and are comparable with models inverted by real-time precise point positioning displacements. This study highlights the great value of variometric displacements for the rapid earthquake source description with only broadcast ephemeris.

Precise Locating of the Great 1897 Shillong Plateau Earthquake Using Teleseismic and Regional Seismic Phase Data

Pinched between the Eastern Himalaya and the Indo-Burman ranges, the Shillong Plateau represents a zone of distributed deformation with numerous visible and buried active faults. In 1897, a great (magnitude 8+) earthquake occurred in the area, and although a subsurface rupture plane has been proposed geodetically, its epicenter remained uncertain. We gathered original arrival time data of seismic waves from this early-instrumental era and combined them with modern, 3D velocity models to constrain the origin time and epicenter of this event, including uncertainties. Our results show that the earthquake has taken place in the northwest part of the plateau, at the junction of the short, surface-rupturing Chedrang fault and the buried Oldham fault (26.0°N, 90.7°E). This latter fault has been proposed earlier based on geodetic data and is long enough to host a great earthquake. Rupture has most likely propagated eastward. Stress change from the 1897 earthquake may have ultimately triggered the 1930 M 7.1 Dhubri earthquake, along a fault connecting the Shillong Plateau with the Himalaya.

Rapid Estimation of Earthquake Magnitude using GNSS Data

Earthquake parameters such as the hypocenter location and the magnitude size are important in the development of reliable Earthquake Early Warning (EEW) and Tsunami Early Warning System (TEWS). The Global Navigation Satellitte System (GNSS) data have been used to estimate the earthquake parameters rapidly over the last 15 years. In this study, we present the result and analysis of the scaling properties of Peak Ground Displacement (PGD) as measured by high-rate (sampled at 1 Hz or higher) GPS recordings from Lombok earthquake on August 05 th , 2018. The earthquake magnitude from the kinematic solution of CMAT GNSS station is equal to Mw 6.8. This value is achieved between 15 - 20 seconds after the origin time of the earthquake. Our result shows that the displacements from kinematic GNSS data can be used to rapidly determine the earthquake magnitude, typically within the first minute of rupture initiation. Rapid earthquake magnitude determination will be very useful to support EEW and TEWS.

Status of Earthquake Early Warning in Switzerland

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.

Time Difference Between the 1854 CE Ansei–Tokai and Ansei–Nankai Earthquakes Estimated from Distant Tsunami Waveforms on the West Coast of North America

We estimated the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai earthquakes from tidal records of two tide gauge stations (San Francisco and San Diego) on the west coast of North America. The first signals of the Ansei–Tokai tsunami were apparent, whereas those of the Ansei–Nankai tsunami were obscured by the later waves of the Ansei–Tokai tsunami. Waveforms of the Ansei–Nankai tsunami simulated with non-linear dispersive wave theory by assuming an origin time of 07:00 GMT on 24 December arrived earlier than in the observations. The normalized root mean square and the misfit between the simulated and observed waveforms of the Ansei–Nankai tsunami showed a time difference between them of approximately 0.4 h. This finding suggests that the actual origin time of the Ansei–Nankai tsunami was approximately 07:24 GMT on 24 December. A previous study estimated the origin time of the Ansei–Tokai tsunami to be about 00:30 GMT on 23 December. Thus, we concluded that the time difference between the 1854 CE Ansei–Tokai and Ansei–Nankai tsunamis was 30.9 h. Despite the significant difference in the time resolution between the seasonal timekeeping system used in Japan in 1854 and waveform digitization, our result is roughly in agreement with historical descriptions of the tsunamis, suggesting that such information can be effectively used to determine the origin times of historical earthquakes.

Four Years of Earthquake Early Warning in Southern Iberia: 2016–2019

The performance of an earthquake early warning system (EEWS) for southern Iberia during the period of 2016–2019 is analyzed. The software PRESTo (PRobabilistic and Evolutionary early warning SysTem; the University of Naples Federico II, Italy) operating at the Universidad Complutense de Madrid has detected 728 events (2 < Mw < 6.3), with 680 earthquakes occurring in southern Iberia. Differences between the EEWS origin time and epicenter and those of the Instituto Geográfico Nacional (IGN) catalog are less than 2 s and 20 km, respectively, for 70% of the detected earthquakes. The main differences correspond to the EEWS magnitude that is underestimated for earthquakes that occurred at the west of the Gibraltar Strait (Mw differences larger than 0.3 for 70%). To solve this problem, several relationships have been tested, and a modification to those that currently use PRESTo is proposed. Other improvements, such as to densify the network or to use 3D Earth models, are proposed to decrease the time needed to issue the alert and avoid the false alerts (19 events over a total of 728 events). The EEWS has estimated the depth for 680 events and compared to those from the IGN (491 events). The performance of PRESTo during the 2020–2021 Granada swarm is analyzed. The hypocentral locations for the three largest earthquakes are close to those from the IGN (differences from 1 to 7 km for the epicenter and 0 s for the time origin), although there are some differences in their magnitude estimations that varies from 0.2 to 0.5. The PRESTo first times are 17, 25, and 41 s after the origin time. This study shows that the actual PRESTo EEWS configured for the southern Iberia may generate effective warnings despite the low seismicity rate in this region. To decrease the warning time, the geometry and density of the seismic network must be improved together with the use of 3D Earth models and on-site system approaches.