High-rate GPS Data Research Articles

Geometry-dependent rupture process of the 2015 Gorkha, Nepal, earthquake determined using a dip-varying inversion approach with teleseismic, high-rate GPS, static GPS and InSAR data

SUMMARYFault geometry is widely recognized as one of the most important factors that affect the rupture process and damages of earthquakes. However, there have been few earthquake cases in which the close relation between the fault geometry and rupture process is resolved from inversions of seismic and geodetic observations. In this study, we develop an approach to simultaneously estimate the rupture process and dip-angle variation on the fault. The effectiveness of our new approach was validated through inverse numerical tests. We apply the new approach to the 2015 Mw7.8 Gorkha earthquake and obtain a dip-varying rupture model by jointly inverting the teleseismic, near-fault high-rate GPS, static co-seismic GPS and InSAR data. Our results show a ramp–flat décollement-ramp fault geometry of the earthquake. The shallow ramp may have prevented the rupture from breaking through to the surface. The variation of dip angle changing with depth leads to significantly different rupture velocities and rupture lengths at shallow and deep fault portions. Particularly, the northeastern downdip ramp behaves as a geometric barrier and rapidly slows down the rupture propagation in 35–45 s after the rupture initiation. In contrast, the rupture duration and fault length in the updip portion are relatively long since there is no significant lateral dip change. Furthermore, the approach can improve our understanding of the relationship between rupture behaviour and fault geometry for other thrust low-dip-angle (dip < 45°) earthquakes.

Focal mechanism inversion of the 2018 MW7.1 Anchorage earthquake based on high-rate GPS observation

The MW7.1 Anchorage earthquake is the most destructive earthquake since the 1964 MW9.2 great Alaska earthquake in the United States. In this study, high-rate GPS data and near-field broadband seismograms are used in separate and joint inversions by the generalized Cut-and-Paste (gCAP) method to estimate the focal mechanism. In order to investigate the influence of crustal velocity structure on the focal mechanism inversion results, two velocity models (Crust1.0 and Alaska Earthquake Center (AEC)) are used for detailed comparison and analysis. The results show that: (1) The two nodal planes of the optimal double-couple solution are nearly north-south striking, with dip angles of about 30° and 60°respectively, and the centroid focal depth is 54–55 km, which is an intraplate normal fault event. (2) The inversion results for the two types of data and the two velocity models are consistent with some previous studies, which indicates that the results are stable and reliable. The more accurate velocity structure model is helpful for focal mechanism inversion of the complex earthquake. (3) The inclusion of high-rate GPS data in joint inversion provides a more effective constraint on centroid depth.

Interplay of seismic and a-seismic deformation during the 2020 sequence of Atacama, Chile

An earthquake sequence occurred in the Atacama region of Chile throughout September 2020. The sequence initiated by a mainshock of magnitude Mw= 6.9, followed 17 hours later by a Mw= 6.4 aftershock. The sequence lasted several weeks, during which more than a thousand events larger than Ml= 1 occurred, including several larger earthquakes of magnitudes between 5.5 and 6.4. Using a dense network that includes broad-band, strong motion and GPS sites, we study in details the seismic sources of the mainshock and its largest aftershock, the afterslip they generate and their aftershock, shedding light of the spatial temporal evolution of seismic and aseismic slip during the sequence. Dynamic inversions show that the two largest earthquakes are located on the subduction interface and have a stress drop and rupture times which are characteristics of subduction earthquakes. The mainshock and the aftershocks, localized in a 3D velocity model, occur in a narrow region of interseismic coupling (ranging 40%-80%), i.e. between two large highly coupled areas, North and South of the sequence, both ruptured by the great Mw∼8.5 1922 megathrust earthquake. High rate GPS data (1 Hz) allow to determine instantaneous coseismic displacements and to infer coseismic slip models, not contaminated by early afterslip. We find that the total slip over 24 hours inferred from precise daily solutions is larger than the sum of the two instantaneous coseismic slip models. Differencing the two models indicates that rapid aseismic slip developed up-dip the mainshock rupture area and down-dip of the largest aftershock. During the 17 hours separating the two earthquakes, micro-seismicity migrated from the mainshock rupture area up-dip towards the epicenter of the Mw 6.4 aftershocks and continued to propagate upwards at ∼ 0.7 km/day. The bulk of the afterslip is located up-dip the mainshock and down-dip the largest aftershock, and is accompanied with the migration of seismicity, from the mainshock rupture to the aftershock area, suggesting that this aseismic slip triggered the Mw= 6.4 aftershock. Unusually large post-seismic slip, equivalent to Mw= 6.8 developed during three weeks to the North, in low coupling areas located both up-dip and downdip the narrow strip of higher coupling, and possibly connecting to the area of the deep Slow Slip Event detected in the Copiapo area in 2014. The sequence highlights how seismic and aseismic slip interacted and witness short scale lateral variations of friction properties at the megathrust.

Rapid determination of source parameters for the 2017 Mw 8.2 Mexico earthquake based on high-rate GPS data

Aiming to rapidly determine source parameters (i.e., static offset, seismic wave arrival, moment magnitude, and hypocentral location) for the Mexico 8.2 earthquake, the records of 7 high-rate GPS stations are utilized. Smoothness Priors Method (SPM) is introduced to rapidly extract the static offset from GPS displacement waveforms, and the result suggests this approach is feasible. The seismic wave arrival detection is carried out with the aid of S-transform, and the propagation velocity of seismic wave detected by most GPS stations are within 4–5 km/s, implying the seismic wave captured by GPS station may be S wave or surface wave. After that, an empirical regression model is adopted to characterize the moment magnitude for this earthquake, and this empirical formula can obtain reliable magnitude in comparison with the reference magnitude. The convergence time of average moment magnitude is 298 s, suggesting that a reliable and robust magnitude (Mw 8.37) can be estimated by the 7 GPS stations with about 298 s after earthquake occurrence. Considering the influence of the spatial distribution of GPS stations, 4 nearest GPS stations evenly distributed on both sides of the fault are selected to determine the warning-magnitude for the Earthquake Early Warning (EEW). A reliable and robust moment magnitude (Mw 8.2) can be estimated by the 4 stations with about 251 s, which is 57 s ahead of 7 stations. Finally, the coordinates of 6 GPS stations and corresponding seismic wave arrival time are utilized to determine the hypocentral location, and the latitude and longitude of estimated location is 14.925°N and 93.765°W, which is 17.9 km from the reference location. The results indicate that the source parameters required for EEW can be rapidly determined based on high-rate GPS displacement waveforms, and integrating real-time GPS into a joint EEW system will be crucial going forward.

Coseismic displacements and Mw estimation of the El Mayor-Cucapah earthquake, Mexico, from GPS source spectra

El Mayor-Cucapah earthquake Mw 7.2 on April 4, 2010, occurred on Mexicali Valley near the international border between California, USA and Baja California, Mexico. The objective of this paper was to examine GPS as a complementary tool for seismic studies and to estimate earthquake seismic moment and Mw. For this purpose the capabilities of high-rate GPS (5 Hz) data located in the northern part of the seismic rupture has been explored to obtain the kinematic coseismic displacements. GPS data were processed using Precise Point Positioning method with GIPSY-OASIS II software, then applying the Fast Fourier Transform to the position time series, spectral parameters, seismic moment and Mw were calculated. A good agreement was found in terms of signal correlation of the GPS displacements, by comparing strong-motion seismic records integrated to displacement, using filtering parameters for two sets of instruments. Kinematic GPS displacement spectra clearly shows the low frequency displacement spectral level (~0.2 Hz) when compared with double integration of strong-motion data. It is easy to calculate the static coseismic motion from GPS data, however it is very difficult to calculate it from strong-motion data. A simple earthquake source model is suitable for the GPS dataset used in this work, estimated on Mw=7.19±0.13, was in according with Mw 7.2 obtained in other studies of the El Mayor-Cucapah earthquake.

A comprehensive study of the 2016 Mw 6.0 Italy earthquake based on high-rate (10 Hz) GPS data

The 2016 Mw 6.0 Italy earthquake is successfully recorded by the near-field 10 Hz GPS and 200 Hz Strong Motion (SM) stations, providing valuable data for this study. A comprehensive study of this earthquake is carried out based on GPS data, which contains coseismic deformations analysis, noise analysis, seismic wave picking, and magnitude determination. The noise of most GPS-derived displacement waveforms can be described as a combination of white noise, flicker noise, and random walk noise after the earthquake occurrence, and the spectral indices vary significantly for most stations, implying that the seismic signals have affected the noise characteristic of GPS-derived displacement waveforms. S-transform is employed to assess the GPS capability to detect the seismic arrival time. The SM station AMT and the GPS station AMAT are in good agreement in seismic wave picking, and the difference is only 1.2 s in the north component, suggesting that the outcome of seismic wave picking using GPS data is reliable. Then, a classic empirical formula is employed to determine the moment magnitude. A robust moment magnitude (Mw 5.90) can be estimated by the nine GPS stations with about 23.9 s. If four GPS stations near the epicenter is chosen to determine the magnitude, it only take 13.0 s to retrieve a reliable preliminary (Mw 5.82) magnitude, which is 5.4 s ahead of nine stations. In addition, Cross Wavelet Transform (XWT) is adopted to measuring the correlation and phase relationship between GPS and SM records. The result of XWT analysis indicates 10 Hz GPS is capable of capturing reliable and accurate coseismic dynamic deformations, as evidenced by the XWT-based semblance being close to 1 between GPS and SM records. The above results confirm the capability of 10 Hz GPS to capture coseismic dynamic deformations, detect seismic arrival time, and determine earthquake magnitude. Moreover, rapid magnitude determination based on 10 Hz GPS data can be regarded as an important supplement to Earthquake Early Warning (EEW).

Loose integration of high-rate GPS and strong motion data considering coloured noise

Loose integration of high-rate GPS and strong motion data considering coloured noise

Joint inversion of GNSS and teleseismic data for the rupture process of the 2017 Mw6.5 Jiuzhaigou, China, earthquake

The spatio-temporal slip distribution of the earthquake that occurred on 8 August 2017 in Jiuzhaigou, China, was estimated from the teleseismic body wave and near-field Global Navigation Satellite System (GNSS) data (coseismic displacements and high-rate GPS data) based on a finite fault model. Compared with the inversion results from the teleseismic body waves, the near-field GNSS data can better restrain the rupture area, the maximum slip, the source time function, and the surface rupture. The results show that the maximum slip of the earthquake approaches 1.4 m, the scalar seismic moment is ~ 8.0 × 1018 N·m (Mw ≈ 6.5), and the centroid depth is ~ 15 km. The slip is mainly driven by the left-lateral strike-slip and it is initially inferred that the seismogenic fault occurs in the south branch of the Tazang fault or an undetectable fault, a NW-trending left-lateral strike-slip fault, and belongs to one of the tail structures at the easternmost end of the eastern Kunlun fault zone. The earthquake rupture is mainly concentrated at depths of 5–15 km, which results in the complete rupture of the seismic gap left by the previous four earthquakes with magnitudes > 6.0 in 1973 and 1976. Therefore, the possibility of a strong aftershock on the Huya fault is low. The source duration is ~ 30 s and there are two major ruptures. The main rupture occurs in the first 10 s, 4 s after the earthquake; the second rupture peak arrives in ~ 17 s. In addition, the Coulomb stress study shows that the epicenter of the earthquake is located in the area where the static Coulomb stress change increased because of the 12 May 2017 Mw7.9 Wenchuan, China, earthquake. Therefore, the Wenchuan earthquake promoted the occurrence of the 8 August 2017 Jiuzhaigou earthquake.

The first since 1960: A large event in the Valdivia segment of the Chilean Subduction Zone, the 2016 M7.6 Melinka earthquake

We present results for joint kinematic inversion of high-rate GPS, strong motion and InSAR data for the 2016 M7.6 Melinka earthquake. We show that the source is a compact 35 s long rupture with 5.0±0.15 m of peak slip. We find the Melinka earthquake occurs inside the slip region for the 1960 M9.5 Valdivia earthquake and within the highly locked portion of the megathrust inferred from inter-seismic velocity analysis. We show that there is very modest post-seismic deformation at a nearby GPS site QLLN and argue that this indicates the Melinka earthquake ruptures within the intermediate portion of the megathrust and is an isolated asperity surrounded by locked velocity weakening material. Further we find that the peak slip observed during this earthquake is larger than what has been accumulated in the intervening 57 years since the 1960 rupture and conclude that, at least in the area of the Melinka earthquake, this is indicates that the 1960 Valdivia event might not have used all the slip deficit available on the megathrust.

Measuring ground deformations caused by 2015 Mw7.8 Nepal earthquake using high-rate GPS data

The April 25, 2015 Mw7.8 Nepal earthquake was successfully recorded by Crustal Movement Observation Network of China (CMONOC) and Nepal Geodetic Array (NGA). We processed the high-rate GPS data (1 Hz and 5 Hz) by using relative kinematic positioning and derived dynamic ground motions caused by this large earthquake. The dynamic displacements time series clearly indicated the displacement amplitude of each station was related to the rupture directivity. The stations which located in the direction of rupture propagation had larger displacement amplitudes than others. Also dynamic ground displacement exceeding 5 cm was detected by the GPS station that was 2000 km away from the epicenter. Permanent coseismic displacements were resolved from the near-field high-rate GPS stations with wavelet decomposition-reconstruction method and P-wave arrivals were also detected with S transform method. The results of this study can be used for earthquake rupture process and Earthquake Early Warning studies.

Coseismic displacement waveforms for the 2016 August 24 Mw 6.0 Amatrice earthquake (central Italy) carried out from High-Rate GPS data

<p>We used High-Rate sampling Global Positioning System (HRGPS) data from 52 permanent stations to retrieve the coseismic dynamic displacements related to the 2016 August 24 <em>M<sub>w</sub></em> 6.0 Amatrice earthquake. The HRGPS position time series (named hereinafter "GPSgrams") were obtained with two different analysis strategies of the raw GPS measurements (Precise Point Positioning [PPP] and Double-Difference [DD] positioning approaches using the Gipsy-Oasis II and the TRACK (GAMIT/GLOBK) software, respectively). These GPSgrams show RMS accuracies mostly within 0.3 cm and, for each site, an agreement within 0.5 cm between the two solutions. By using cross-correlation technique, the GPSgrams are also compared to the doubly-integrated strong motion data at sites where the different instrumentations are co-located in order to recognize in the GPSgrams the seismic waves movements. The high values (mostly greater than 0.6) of the cross-correlation functions between these differently-generated waveforms (GPSgrams and the SM displacement time-histories) at the co-located sites confirm the ability of GPS in providing reliable waveforms for seismological applications.</p>

The 3-D strain patterns in Turkey using geodetic velocity fields from the RTK-CORS (TR) network

This study presents our use of GPS data to obtain and quantify the full continuous strain tensor using a 3-D velocity field in Turkey. In this study, GPS velocities improve the estimation of short-term strain tensor fields for determining the seismic hazard of Turkey. The tensorial analysis presents different aspects of deformation, such as the normal and shear strains, including their directions, the compressional and extensional strains. This analysis is appropriate for the characterizing the state of the current seismic deformation. GPS velocity data from continuous measurements (2009–2012) to estimate deformations were processed using the GAMIT/GLOBK software. Using high-rate GPS data from permanent 146 GNSS stations (RTK-CORS-TR network), the strain distribution was determined and interpolated using a biharmonic spline technique. We show the strain field patterns within axial and plane form at several critical locations, and discuss these results within the context of the seismic and tectonic deformation of Turkey. We conclude that the knowledge of the crustal strain patterns provides important information on the location of the main faults and strain accumulation for the hazard assessment. The results show an agreement between the seismic and tectonic strains confirming that there are active crustal deformations in Turkey.

Denoising effect of multiscale multiway analysis on high-rate GPS observations

In general, high-rate GPS data sets are subject to common mode error (CME), multipath error, and high-frequency random noise, which adversely affect the GPS positioning accuracy. In order to improve the precision and reliability of GPS positioning, a multiscale multiway principal component analysis (MSMPCA) denoising method is introduced here. The 1-Hz GPS coordinate time series at ten stations from the California Real Time GPS Network are employed to assess the performance of MSMPCA. Its results are compared with those of the classical denoising methods, including wavelet denoising, PCA, multiway PCA, and multiscale PCA. The results indicate that MSMPCA is able to eliminate not only high-frequency random noise but also low-frequency errors and CME. Furthermore, quantitative analysis shows that MSMPCA is more accurate than the classical denoising methods. Spectral analysis shows that a combination of white plus flicker noise is considered to be the adequate model for the noise characteristics of all three components. Both white and power-law noise amplitudes are smallest in the north component and largest in the vertical component. MSMPCA decreases the mean amplitudes of white noise from 1.3 to 0.0, 0.9 to 0.0, and 2.8 to 0.1 mm in north, east, and vertical components, and those of power-law noise from 4.6 to 1.2, 3.9 to 1.1, and 19.9 to 8.4 mm, respectively. MSMPCA is a promising alternative for removing noise of various frequencies (0.00025---0.5 Hz) from high-rate GPS signals.

Rupture process of 2011 Mw7.1 Van, Eastern Turkey earthquake from joint inversion of strong-motion, high-rate GPS, teleseismic, and GPS data

We analyzed the rupture process of the 2011 Mw7.1 Van, Eastern Turkey earthquake using teleseismic, strong-motion, 1-Hz GPS waveforms and static GPS displacement measurements. We performed data sensitivity analyses using four different rupture scenarios. Overall, when geodetic and seismic datasets are modeled jointly, slip distribution is well-constrained and rupture velocity can be obtained. The 2011 Van earthquake is a case where none of the available datasets are sufficient to constrain the slip distribution and the rupture kinematics on their own. This study confirms that rather than fitting one dataset perfectly, using multiple datasets jointly leads to a better-constrained slip distribution. The kinematic model obtained from the joint inversion of all the available data shows a 45-km-long bilateral rupture with two sub-events; one larger slip patch propagating up-dip and toward west of the hypocenter and a smaller second slip patch toward the east. The highest slip is to the west of the hypocenter with a peak value of 4.5 m. The slip is confined to the depths of 7.5 to 20 km and the shallower part of the fault remains unbroken. The average rupture velocity is around 3 km/s, close the Rayleigh wave velocity. The rupture is faster with shorter rise times for the larger sub-event toward the west, while the rise times are longer for the smaller sub-event to the east. This difference in seismic behavior might be related to the segmentation of the fault.

Near-field surface displacement and permanent deformation induced by the Alaska Mw 7.5 earthquake determined by high-rate real-time ambiguity-fixed PPP solutions

High-rate GPS data from the United States continuously operating reference stations in the Alaska region are processed using the recently developed precise point positioning (PPP) technique. The traditional PPP technique does not fix ambiguities into their integers because these ambiguities do not have an integer nature when data from a single receiver, as well as precise orbit and clock corrections, are used. Additional corrections, i.e., uncalibrated phase delay (UPD), are needed to fix integer ambiguities and consequently improve positioning accuracy. This study proposes a methodology to compute for wide-lane and L2 (the second L-band frequency) UPDs using the geometry-based model and subsequently applies these parameters to the computation for ambiguity-fixed solutions. The instantaneous displacements of near-field sites, as well as the permanent deformations after the earthquake, are therefore obtained for the January 5, 2013, Alaska earthquake. The real-time performance of PPP solutions are assessed by considering realistic data latency and data interval of corrections. Ambiguity-fixed solutions are compared with ambiguity-float ones. The comparison shows that the positioning accuracy can be improved significantly when the ambiguities are fixed correctly. The solutions using the real-time corrections are also compared with those using post-processing corrections, i.e., Center for Orbit Determination in Europe final orbit and clock. Although the accuracy is somehow degraded because of the data latency and data interval, the real-time results are satisfactory for use in monitoring the small-scale deformation (1–2 cm) caused by the Alaska earthquake. In addition, the kinematic ambiguity-fixed PPP solutions for 7 days around the earthquake are calculated to obtain permanent pre- and post-earthquake deformations. The deformations computed from real-time and post-processing corrections do not appear to be significantly different.

Epicenter and magnitude of large earthquake determined from high-rate GPS observations: A case study of the 2008 M8.0 Wenchuan earthquake

For earthquake and tsunami early warning and emergency response, the earthquake epicenter and magnitude should be determined rapidly and correctly. Using high-rate GPS observations, we can readily obtain precise and high resolution displacement time series and the seismic waveforms during the earthquake. In this paper, a new algorithm is proposed for estimating the earthquake epicenter and magnitude with the seismic waveforms derived from high-rate GPS data during the earthquake. A case study of the 2008 Wenchuan earthquake is conducted from 1 Hz GPS data and the epicenter and magnitude are determined. Compared with the results issued by the China Seismological Bureau, the estimation error of the epicenter and the magnitude is about 12 km and 0.1 magnitude unit, respectively. It has shown that high-rate GPS could be a new tool feasible for estimating the earthquake epicenter and magnitude, independent of or combined with seismometers.

Co-seismic deformation derived from GPS observations during April 20th, 2013 Lushan Earthquake, Sichuan, China

We process the standard 30 s, static GPS data and the 1 s, high-rate GPS (HRGPS) data provided by the Crustal Movement Observation Network of China with GAMIT/GLOBK software package, and obtain the co-seismic displacements of near field and far field, and the epoch-by-epoch time series of HRGPS during Lushan earthquake. GPS data from about 20 sites in Sichuan province, which located between 40 and 450 km from the epicenter, are analyzed so as to study the characteristics of the static displacements and the dynamic crustal deformations, with periods ranging from several minutes to over a month. The result shows that: the static displacements caused by Lushan earthquake are limited to several centimeters; the nearest station SCTQ at 43 km from the epicenter has the largest static displacement of about 2 cm, while the other stations generally have insignificant displacements of less than 5 mm. the stations in the east of Sichuan–Yunnan region shifts 5–10 mm toward the southwest, and the stations in the middle-west of Sichuan Basin moves indistinctively 1–2 mm toward the northwest; station SCTQ has the largest kinematic displacement of about 4 and 3 cm peak-to-peak on the north and east component, respectively, and is much greater than the static permanent displacement; for the stations located at a distance greater than 150 km from the epicenter, the kinematic motions are generally insignificant; exceptionally, station SCNC and station SCSN in central Sichuan Basin have significant kinematic motions although they are more than 200 km away from the epicenter.

A geodetic study of the 23 October 2011 Van, Turkey earthquake

The Van (Eastern Anatolia, Turkey) earthquake occurred on Sunday, October 23, 2011 with a moment magnitude of 7.2. The tectonics of this region is characterized by strike–slip faulting on the Bitlis Suture Zone, and thrusting in the Zagros fold and thrust belt. Using high-rate (1second) GPS data from permanent GNSS stations from the CORS-TR network, co-seismic displacements of eleven stations were determined using precise point positioning during this earthquake. We used the time series of coordinate changes for fourteen CORS-TR stations, and calculated the crust movements before and after the earthquake.According to the PPP solutions computed using high frequency GPS data to determine the co-seismic motions of stations, we conclude for the Van earthquake an occurrence time of 10:41:22 (UTC). No pre-seismic horizontal movement of stations at the level more than 5mm before the earthquake could be observed. That means that no kinematic warning or prediction before the earthquake exists. Along an east–west horizontal line north of the Van Sea with a length of about 100km, the northern part of this line experienced extension of 0.2–1ppm in a NW–SE direction. The southern part experienced N–S shortening of 0.5–1.5ppm. The N–S shortening we estimated geodetically matches well with the N–S shortening and thrust focal mechanism derived independently using seismic data by the USGS.Co-seismic surface displacements derived from the GPS data are consistent with the teleseismic source model given by the USGS. The geodetic source model derived from the GPS data reproduces the same moment magnitude and centroid as the teleseismic model, but shows a higher spatial resolution of the slip distribution. We also analyzed the post-seismic surface displacements derived from the GPS data within the first two weeks after the mainshock. No reasonable slip distribution on the co-seismic fault plane could be found, indicating that the sources for the early post-seismic deformation might come from the widely scattered aftershocks.

High-rate (1 Hz to 20 Hz) GPS coseismic dynamic displacements carried out during the Emilia 2012 seismic sequence

<p>In May-July 2012, Emilia Romagna (northern Italy) was struck by a significant seismic sequence, which was characterized by two moderate-magnitude earthquakes: a Ml 5.9 event on May 20, 2012, at 02:03:53 UTC, and a Ml 5.8 event on May 29, 2012, at 07:00:03 UTC, about 12 km to the west of the first mainshock. The earthquake sequence produced a total of 20 casualties and severe and widespread damage, mainly to historical and commercial buildings. A detailed description of the seismic sequence can be found in Sco-gnamiglio et al. [2012, this volume]. The largest of the earthquake static displacements were recorded by tens of continuous global positioning system (cGPS) stations, as described in Serpelloni et al. [2012, this volume]. Most of these stations were operating with a sampling frequency of 1 Hz, and they belonged to scientific or commercial networks: RING (http://ring.gm.ingv.it); ITALPOS (http://smartnet.leica-geosystems.it); GeoTop (http://www.netgeo.it); Fondazione Geometri Emilia Romagna (http://www.gpsemiliaromagna.it; Lombardia [http://www.gpslombardia.it); and Veneto (http://147.162.229.63). Some hours after the first mainshock, the sampling frequency of the near-field RING stations (SBPO and MODE) were switched to 20 Hz, thus recording the coseismic displacements produced by the May 29, 2012, earthquake at higher frequency. This sampling frequency was previously used for the detection of coseismic dynamic displacements only for the Mw 9 Tohoku-Oki 2011 event [Colosimo et al. 2011b]. Thus, the 20-Hz-sampling displacements for the Tohoku-Oki 2011 earthquake and the May 29, 2012, Emilia event might represent important recordings to investigate coseismic contributions at frequencies higher than 1 Hz with GPS. In the present study, after the description of the high-rate GPS (HRGPS) data analysis, we will show and compare the preliminary results. Then, for the two mainshocks, we will compare the displacements recorded by the HRGPS (1 Hz up to 20 Hz) and the strong-motion time histories (100 Hz) at MODE, where the different instruments were approximately co-located (Figure 1, inset, relative distance of ca. 90 m). […]</p>

5Hz GPS seismology of the El Mayor-Cucapah earthquake: estimating the earthquake focal mechanism

High-rate (5Hz) GPS records observed in the near field following the magnitude 7.2 El Mayor—Cucapah earthquake that occurred in northern Mexico on 2010 April 4 are compared with broad-band seismograms. The high-rate GPS displacement records are consistent with the twice-integrated strong-motion seismic records in the near field where broad-band seismograms are clipped due to strong shaking. Agreement degrades at distances greater than about 150 km from the epicentre where displacement amplitudes approach the noise level of GPS seismograms. Using high-rate GPS data the focal mechanism of the main shock is estimated and is shown to be consistent with teleseismic estimates. The result is seen as confirmation that high-rate GPS observed at near-field stations can be applied together with teleseismic seismometers to yield better information about earthquake rupture properties and parameters.