The rapidly emerging field of Environmental Seismology (EnviroSeis) uses seismological techniques to monitor geomorphic processes at Earth’s surface, providing non-invasive, relatively inexpensive, continuous constraints on physical properties and dynamics of surface processes including landslides, debris flows, snow avalanches, river sediment transport, and variations in groundwater table. EnviroSeis has direct ties to real-time geohazards monitoring and provides timely warnings for the hazard mitigation and assessment. Nowadays, the places in world with real-time seismic networks are ready to implement EnviroSeis. The major topic focused on here is how to provide relevant information on the deep-seated landslides associated to the three-time stages:

• Pre-slide: (1) seismic precursor and (2) seismic velocity changes corresponding to basal sliding behavior.
• Sliding: A real-time landquake monitoring (RLMS; http://collab.cv.nctu.edu.tw/main.html)
• After-slide: (1) near-real-time monitoring of river sediment transport and (2) early warning of the landslide-generated tsunami.

How to cite: Chao, W.-A.: Environmental seismology: Listening to landslides whispering, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12702, https://doi.org/10.5194/egusphere-egu2020-12702, 2020.

We update our analysis on the ongoing seasonal induced microseismic activity in southeastern Brazil, in the interior of the state of Sao Paulo.  This is an area that not evidenced any active seismicity before 2016. We monitor this phenomenon as it is similar to other episodes of seasonal seismicity in other regions of Brazil, under similar aquifer and host rock conditions, commonly associated with those of the Parana Basin. 

This induced seismicity is seemingly triggered yearly during the high-rain season in Southeast Brazil, between December and May, and ceases as soon as the heavy rain season ends each year.  In these periods of increased precipitation during the annual onset of seismicity, we have found more than 1500 seismic events of magnitudes up to M2.0 in since 2017, after we deployed seismic stations in this area. Using phase weighing earthquake locations algorithms, we examine the clustering of the seismicity around recently drilled water wells, and seismicity rate changes, as it is modified by variations in the precipitation.

We perform full moment tensor analysis when possible to find the seismic activity is not only clustering horizontally, but at depth as well.  We identify two main regions where events are more frequently occurring and have mostly prevalent sub-horizontal dipping planes: The shallow events between 100 and 200 m and from 600 to 700 m depth. 

This phenomenon is facilitated mainly by the inadequate water well perforation practices in the region. Uncased water wells promote the transport of both rainwater and groundwater from upper to lower aquifers during higher precipitation months. The stress conditions of the fractured basaltic rock inside the confined aquifers are affected by the intrusion and percolation of significant amounts of water, which produce pore-pressure changes inside the host rock, and facilitates stress release though the microseisms.  This implies that the confined aquifer characteristics of intermittent sandstone layers and fractured basalt rocks from the Parana Basin condition the characteristics of the seismicity occurring in this region of Brazil. 

How to cite: Convers, J. A., Assumpção, M., and Barbosa, J. R.: Seismological Observations of the Seasonal Rain and Aquifer Induced Seismicity in Southeastern Brazil, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10161, https://doi.org/10.5194/egusphere-egu2020-10161, 2020.

The average stress drop during an earthquake is a parameter fundamental to ground motion prediction and earthquake source physics, but it has proved hard to measure accurately. This has limited our understanding of earthquake rupture, as well as the spatiotemporal variations of fault strength. In this study, we investigate the resolution limits of spectral analysis based on synthetic spectra with similar magnitude range, average stress drop and frequency bands to a fluid-injection induced earthquake sequence in Oklahoma near Guthrie.

Synthetic tests using joint spectral fitting method define the resolution limit of corner frequency as a function of maximum frequency for both individual spectra and averaged spectra from multiple stations. Synthetic tests based on stacking analysis find that the improved stacking approach can recover the true input stress drop if the corner frequencies are within the resolution limit defined by joint spectral fitting.

The improved approach is applied to the Guthrie sequence, different wave types and different signal-to-noise criteria are examined to understand the stability of the stress drop distributions. The results suggest no systematic scaling relationship for stress drop for M≤ 3.1 earthquakes, but larger events M≥3.5 tend to have higher average stress drops. Results with lower signal-to-noise ratio requirement and direct P-wave tend to have higher scaling factor compared to results with high signal-to-noise ratio and S-waves.

Comparison of results from several different methods suggest that the average stress drop is well resolved and not subject to tradeoff with attenuation. Some robust spatiotemporal variations can be linked to triggering processes and indicate possible stress heterogeneity within the fault zone. Tight clustering of low stress drop events at the beginning stage of the sequence suggests that pore pressure influences earthquake source processes. Events at shallow depth have much lower stress drop compared to deeper events. The largest earthquake occurred within a cluster of high stress drop events, and involved cascading failure of several sub-events.   

How to cite: Chen, X., Abercrombie, R., and Wu, Q.: Earthquake stress drop: what can we resolve from observations, and what can we infer about earthquake triggering processes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10935, https://doi.org/10.5194/egusphere-egu2020-10935, 2020.

In the aftermath of a significant earthquake, seismologists are frequently asked questions by the media and public regarding possible interactions with recent prior events, including events at great distances away, along with prospects of larger events yet to come, both locally or remotely.  For regions with substantial earthquake catalogs that provide information on the regional Gutenberg-Richter magnitude-frequency relationship, Omori temporal aftershock statistical behavior, and aftershock productivity parameters, probabilistic responses can be provided for likelihood of nearby future events of larger magnitude (as well as expected behavior of the overall aftershock sequence). However, such procedures do not provide answers to inquiries about long-range interactions, either retrospectively for interaction with prior remote large events or prospectively for interaction with future remote large events. Dynamic triggering that may be involved in such long-range interactions occurs, often with significant temporal delay, but is not well-understood, making it difficult to respond to related inquiries. One approach to addressing such inquiries is to provide retrospective or prospective occurrence histories for large earthquakes based on global catalogs; while not providing quantitative understanding of any physical interaction, experience-based guidance on the (typically very low) chances of causal interactions can inform public understanding of likelihood of specific scenarios they are commonly very interested in.

How to cite: Ye, L., Kanamori, H., and Lay, T.: Responding to Media Inquiries About Remote Triggering Interactions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5052, https://doi.org/10.5194/egusphere-egu2020-5052, 2020.

The most of intensity assessments provided by the large (more than 100000 intensity observations) Italian macroseismic database (DBMI15) were made using the traditional Mercalli-Cancani-Sieberg (MCS) scale but in most recent macroseismic surveys in Italy even the European Macroseismic Scale (EMS) scale was used by some research groups. In principle, MCS and EMS scales should give almost the same intensities if only damage to traditional masonry buildings is considered for MCS estimates. Some doubts remain on this equivalence even if MCS and EMS intensities were actually used as they were coincident, as in the case of or the compilation of the CPTI15 catalog used for seismic hazard assessment in Italy. In this work we compared intensity estimates made using both scales for the traditional (expert) estimates made for the same localities of some recent earthquakes as well as community intensities provided by on line questionnaires “Hai Sentito Il Terremoto” (HSIT) collected by INGV. We computed linear regressions between the two sets of intensity estimates and also compared the earthquake parameters (locations magnitude and fault orientations) computed by the Boxer code, using independently the two sets of intensities.

How to cite: Vannucci, G., Gasperini, P., Laura, G., and Barbara, L.: EMS and MCS macroseismic intensities assessed in Italy are equivalent?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20059, https://doi.org/10.5194/egusphere-egu2020-20059, 2020.

The national seismic networks in Central America have been developing network-based early warning since 2016 for Nicaragua, 2018 for El Salvador and 2019 for Costa Rica. This effort is part of a project with the Swiss Seismological Service (ETH Zurich) including funds for accelerograph deployment. At each network, delay for first earthquake parameter estimations have been significantly reduced by optimizing data acquisition, metadata quality, and configuration of the EEW algorithms implemented in SeisComP3, i.e. Virtual Seismologist and the Finite fault rupture Detector. Issues remain with significant numbers of deployed instrumentation that for a variety of reasons, do not optimally contribute to the EEW systems. Building on our experience so far, we design national network upgrades that will optimize the earthquake early warning performance in the Central America region, mitigating the current issues with velocimeter clipping during large events, datalogger delays, and incomplete network coverage. The new instruments have been selected after testing all available EEW-capable accelerographs natively compatible with SeisComP3 including class A force balance accelerometers as well as MEMs. To justify our instrument selection, we summarize the performance of these different instruments. We model and discuss reference maps for performance expectations, and present planned instrument vaults. Our primary focus is on minimizing first alert times but we also wish to accentuate the broad value of the network upgrade for seismological monitoring showing changes in the magnitude of completeness in the region. We demonstrate the value of the network upgrade for earthquake early warning with real-time processing simulation using synthetic data for the maximum magnitude earthquake expected for the Central America subduction zone.

How to cite: Massin, F., Clinton, J., Racine, R., Bose, M., Rossi, Y., Marroquin, G., Strauch, W., Arroyo, M., Linkimer, L., Chavez, E., Protti, M., and Yani, R.: The future strong motion national seismic networks in Central America designed for earthquake early warning., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19437, https://doi.org/10.5194/egusphere-egu2020-19437, 2020.

Yellow Sea and East Sea regions near Korea are two of the most seismically active marginal seas in the Far East.  While offshore earthquakes in the Yellow Sea may be attributed to potential micro-plate boundaries, East Sea earthquakes may be associated to the seaward extension of many active faults on land or the deformation boundary between oceanic and continental crust.  However, offshore earthquake locations using local seismic network are always subjecting to large uncertainties due to poor spatial coverage of seismic stations, discrepancies on velocity models, and limitations on traditional location technologies.  For instance, it is not uncommon that the same earthquake within Yellow Sea may be reported independently more than tens to hundreds of km apart in Chinese and Korean catalogs while there is no mechanism for earthquake data exchange between the two countries.   Multiple seismic array method can be applied to improve epicenter location of offshore earthquakes.  Seismic stations in Korea can be integrated into three arrays based on their latitude. Apparent azimuths and apparent velocities of the incoming seismic waves (mainly Pn) from a regional earthquake to each array can be reliably determined.  Epicenter of a regional earthquake can thus be located by tracing seismic rays following the back azimuths derived from multiple arrays.  Offshore earthquakes in the East Sea and Yellow Sea regions are located at shallow depth within crust that Pn waves are expected to be the first arrival phase at many Korean stations.  Thus, offshore earthquakes can be reasonably located using Pn arrivals.  In the Yellow Sea case, the apparent velocity ~8.0 km/sec is observed for all arrays suggesting a typical continental Pn waves propagating across the continent-continent transition region into Korea.  In the East Sea case, the apparent velocity of ~6.8 km/sec or lower is observed for all arrays suggesting a typical oceanic Pn wave propagating across the oceanic-continental margin into Korea.  A better relocated earthquake location in the offshore region is essential for our understanding of regional tectonics and earthquake hazard assessment.

How to cite: Chiu, S.-C., Chiu, J.-M., Kim, K., and Kang, S.: Relocation of Offshore Earthquakes around the Korean Peninsula using Multiple Seismic Arrays: Case Examples for East Sea and Yellow Sea Regions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13610, https://doi.org/10.5194/egusphere-egu2020-13610, 2020.

Owing to developments of geodetic observation using satellite systems such as GNSS, we can now estimate slip-deficit rate distribution at plate interfaces. There are roughly two types of attempts to predict possible scenarios for future megathrust earthquakes based on the estimated slip deficit rates. One is kinematic modeling, in which coseismic slip distribution is modeled by multiplying the estimated slip deficit rates by the recurrence time (e.g., Baranes et al. 2018 GRL; Watanabe et al, 2018 JGR). The rupture area and seismic moment can be easily modeled, but the model is not always consistent with the mechanics of fault rupture. The other is dynamic modeling, in which source models are obtained via dynamic rupture simulations using shear stress calculated from the slip deficit rates and assuming frictional parameters (e.g., Hok et al., 2011 JGR; Lozos et al., 2015 GRL; Yang et al., 2019 JGR). The method reasonably predicts the rupture processes based on the mechanics of fault rupture, but generally needs a lot of computing resources for parametric studies of the frictional parameters because of the difficulty to estimate them. In this study, we propose a mechanics-based method to bridge the gap between the kinematic and dynamic modeling. The method predicts possible static slip models with a small computational load, and then examines whether each model actually happens from the viewpoint of the mechanics of fault rupture.

First, we calculated shear stress change rates at the plate interface from the slip-deficit rate distribution estimated from GNSS data (Noda et al., 2018 JGR). In each scenario, we assumed a rupture region and obtained stress drop distribution by multiplying the shear stress change rates in the region by accumulation period. The coseismic slip distribution of each scenario was estimated from the assumed stress drop distribution by using an inversion method. We created scenarios for various rupture regions and various accumulation periods. Next, we investigated the possibility that the scenario happens based on the conservation law of energy. Fault rupture releases shear strain energy accumulated in the lithosphere and the released strain energy is consumed as the radiated energy and the dissipated energy. We assumed some plausible frictional constitutive relations for the plate interface to evaluate the dissipated energy for each case. We calculated the strain energy released by shear faulting in each scenario and compared it with the dissipated energy considering that the released strain energy is necessarily larger than the dissipated energy in earthquake occurrence. If the released strain energy is smaller than the dissipated energy, we find that the scenario will not happen in terms of earthquake mechanics.

We applied this method to the subduction zone along the Nankai trough, southwest Japan, where great thrust earthquakes have repeatedly occurred with a recurrence time of about 100 years. Based on possible scenarios predicted in this region, we discussed the necessary condition of fault strength and accumulation period for earthquake generation.

How to cite: Noda, A., Saito, T., Fukuyama, E., and Urata, Y.: Mechanics-based scenarios for great thrust earthquakes in subduction zones using GNSS data analysis: Released strain energy and dissipated energy, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12581, https://doi.org/10.5194/egusphere-egu2020-12581, 2020.

North China Craton is the oldest craton in the world. It contains the eastern, central and western part. Shanxi rift and Taihang mountain contribute the central part. With strong tectonic deformation and intense seismic activity, its crust-mantle deformation and deep structure have always been highly concerned. In recent years, China Earthquake Administration has deployed a dense temporary seismic array in North China. With the permanent and temporary stations, we obtained the crust-mantle S-wave velocity structure in the central North China Craton by using the joint inversion of receiver function and surface wave dispersion. The results show that the crustal thickness is thick in the north of the Shanxi rift (42km) and thin in the south (35km). Datong basin, located in the north of the rift, exhibits large-scale low-velocity anomalies in the middle-lower crust and upper mantle; the Taiyuan basin and Linfen basin, located in the central part, have high velocities in the lower crust and upper mantle; the Yuncheng basin, in the southern part, has low velocities in the lower crust and upper mantle velocities, but has a high-velocity layer below 80 km. We speculate that an upwelling channel beneath the west of the Datong basin caused the low velocity anomalies there. In the central part of the Shanxi rift, magmatic bottom intrusion occurred before the tension rifting, so that the heated lithosphere has enough time to cool down to form high velocity. Its current lithosphere with high temperature may indicate the future deformation and damage. There may be a hot lithospheric uplift in the south of the Shanxi rift, heating the crust and the lithospheric mantle. The high-velocity layer in its upper mantle suggests that the bottom of the lithosphere after the intrusion of the magma began to cool down.

How to cite: Cai, Y. and Wu, J.: Crust-mantle velocity structure in Shanxi rift, Central North China Craton, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20659, https://doi.org/10.5194/egusphere-egu2020-20659, 2020.

Although observations of seismic normal modes provide constraints on the structure of the entire Earth, the core-mantle boundary region remains poorly understood. Stoneley modes should offer better constraints, because they are confined near to the fluid-solid interface, but this property also makes them difficult to detect. In this study, we use recently-developed finite-element approach to show that Stoneley modes can be excited and detected, but only in certain special cases. We first investigate the physical explanation for these cases. Next, we describe how they could be detected in seismic data, and the sensitivity of these data to the material properties. We illustrate this sensitivity by calculating the modes of a three-dimensional Earth model containing a large low-shear-velocity province (LLSVP). Finally, we present some preliminary observations. We hope that this new understanding will lead to new constraints on the material properties and morphology of the core-mantle boundary region. In turn, this information, especially the constraints on density, should help to answer questions about the Earth, for example in mantle convection (are LLSVPs thermally or chemically buoyant? Primordial or slab graveyards? Passive or active?) and core convection (does the outermost core have a stable stratification?).

How to cite: Matchette-Downes, H., van der Hilst, R. D., Ye, J., Shi, J., Han, J., and de Hoop, M. V.: Improving Stoneley-mode constraints on the structures near the core-mantle boundary, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20958, https://doi.org/10.5194/egusphere-egu2020-20958, 2020.

An earthquake causes a sudden rock-mass redistribution through fault rupture and generates seismic waves that cause bulk density variations propagating with them. For a large earthquake, both processes can induce global gravity perturbations, whose signals propagate with the speed of light and therefore can arrive at remote stations earlier than the fastest elastic P wave. In turn, the gravity perturbations generate secondary seismic sources overall within the earth, a part of which can cause ground motion prior to the direct P wave arrival, too. Recently, these prompt elasto-gravity signals (Vallée et al. 2017) for large earthquakes like Tohoku 2011 Mw 9.1 have been detected in records of  broadband seismometers and superconducting gravimeters. Though the physics of the PEGS has been well understood, the tools used so far for a realistic modelling of them are complicated and computationally intensive. In this study, we present a new and rather simple approach that solves the full-coupled elasto-gravitational boundary-value problem more accurately, but no more complicated than to compute synthetic seismograms in a conventional way. Using the new tool, we simulate the PEGS of the 2011 Tohoku earthquake in both temporal and spatial scales, based on a realistic kinematic finite-fault source model. The temporal results show clearly how the ground motion is inspired by the gravity change in short- and long-term as well as how the combined PEGS behave at different epicentral distances from 400 to 3000 km. The spatial patterns of PEGS, especially that of gravity change, reveal the relationship between the PEGS and the focal mechanism. We also compare our simulation results with the predictions made before and with the observed waveforms and find a good agreement. Furthermore, we show particularly that the moment magnitude, rupture duration and focal mechanism of the 2011 Tohoku earthquake can be estimated robustly using the PEGS measured at a dozen selected stations, which could be helpful for the earthquake and tsunami early warning in the future.

How to cite: Wang, R., Zhang, S., Dahm, T., and Heimann, S.: Efficient simulation of prompt elasto-gravity signals (PEGS) based on a spherical self-gravitating earth model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18164, https://doi.org/10.5194/egusphere-egu2020-18164, 2020.

The Taiwan orogenic belt is relatively young and active with an ongoing arc-continent collision since the middle Miocene. In this study, we systematically investigate the use of seismic tomography, focal-mechanism and distribution of earthquakes to analysis the seismogenic patterns in the collision-subduction zone in the eastern Taiwan, which can be delineated five seismogenic zones of the Longitudinal Valley Fault Seismic Zone (LVFZ), the Central Range Fault Seismic Zone (CRFZ), the Backbone Range Seismic Zone (BRSZ), the Ludao-Lanyu Fault Seismic Zone (LLFZ), and the Wadati-Benioff Seismic Zone (WBSZ).

The LVFZ and CRFZ, formed along the collision zone between the Philippine Sea and the Eurasian Plates, earthquake focal mechanisms show P axes distributed in direction of 285-335°, reflecting the compressive stress field due to the collision. The LVSZ is the collisional boundary between the Philippine Sea and Eurasian plates. The LLFZ is a high-angle, east-dipping reverse fault separating the Luzon Volcanic Arc and the North Luzon Trough. The Eurasian plate (the South China Sea oceanic crust) subducts beneath the Philippine Sea plat in the southeastern Taiwan forming the WBSZ to a depth of 160 km.

The CRFZ, located along the eastern limb of Backbone Range, is formed by a zone of west-dipping reverse fault. In addition, the earthquakes on the BRSZ generated by normal and strike-slip faults at about 5-15 km depth which occur in response to left-lateral transtensional deformation by the collision. Earthquake focal mechanisms show P and T axes distributed in direction of 280-330° and 20-70°, respectively.

How to cite: Chen, W.-S., Wu, Y.-M., Yang, H., Yeh, P.-Y., Lai, Y.-X., Ke, M.-C., Ke, S.-S., and Lin, Y.-K.: Seismogenic structures of the collision-subduction zone in the eastern Taiwan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4453, https://doi.org/10.5194/egusphere-egu2020-4453, 2020.

The seismological exploration of the Earth’s inner core has revealed some structural complexities such as seismic anisotropy and hemispherical separation. Investigating the travel times of PKP waves from at least two different ray paths, a polar and an equatorial one, is one of the commonly used methods to probe the inner core’s anisotropy. Since the waves are traversing anomalous structures in the lowermost mantle before entering the core, these heterogeneities have to be taken into account when investigating anisotropy in the inner core.

In this study we use data from an equatorial path with events from Indonesia recorded in Morocco and a nearly polar one with earthquakes in New Zealand recorded in England. The two waves used in our study, PKPdf and PKPab, both propagate through mantle and outer core and PKPab additionally traverses the inner core. Within this work, we do not only analyse the travel times of the waves but rather investigate their deviations from the originally assumed path along with their incidence angle. This is done with the methods of array seismology, mainly its two parameters slowness and backazimuth.

The results of this study reveal opposite deviations of slowness and backazimuth of the polar in contrast to the equatorial path. While the polar waves travel shallower and closer to North, the equatorial waves propagate deeper and farther from North than predicted by ak135. Additionally we observe hemispherical differences between waves that sample the eastern and the ones that sample the western hemisphere for both ray paths, PKPdf and PKPab, which leads us to the assumption that the deviations are not caused by the inner core but are rather due to mantle structures.

How to cite: Beiers, S. and Thomas, C.: Influence of Mantle Structures on Measurements of Anisotropy in the Inner Core, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8388, https://doi.org/10.5194/egusphere-egu2020-8388, 2020.

We present the first high resolution seismic images illuminating the hitherto-elusive crustal architecture beneath the Eastern Ghats Mobile Belt (EGMB) using teleseismic receiver functions. Data were collected using 27 broadband seismic stations operated in a continuous mode covering two distinct seismic profiles (~550 km long) during 2015–2018. Several interesting observations and inferences are made through analysis of the receiver functions such as (a) a very thick crust (>40 km) with oppositely dipping Moho beneath the EGMB and Archean Bastar Craton, (b) EGMB formed from amalgamation of different crustal domains thrust over one another possibly during the Pan-African orogeny, (c) the Archean Bastar Craton crust extends (~75 km) eastward beneath the EGMB, from its surficial geological boundary, (d) there is a sharp contrast in the crustal structure (with ~20 km Moho offset) at the contact between the Rengali Province and Singhbhum Craton which does not support southward growth of the Singhbhum Craton through accretion, (e) anorthosite complexes may possibly be created by rising diapirs channeled through the weak zones in the crust, from the magma chambers developed by melting of frontal portion of the underthrusting lower crust. We report a significant change in the crustal architecture just east of the most elevated topography observed along the profile covering the Bastar Craton and the EGMB. It requires further careful petrological investigations to ascertain the relationship of high elevation and its linkages with the deep crust, forming a separate domain. Our results do not support or discard a Grenvillian age (~1 Ga) docking of the EGMB with Proto-India, though it is preferred to explain the present day crustal features with intense Pan-African (0.5–0.6 Ga) reorganization.

How to cite: Singh, A. and Singh, C.: Seismic imaging of the deep crustal structure beneath Eastern Ghats Mobile Belt (India): Crustal growth in the context of assembly of Rodinia and Gondwana supercontinents, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-33, https://doi.org/10.5194/egusphere-egu2020-33, 2020.

As one of the most active intracontinental orogenic belts in the world, the Tien Shan orogenic belt originated in the Paleozoic and then experienced tectonic activities such as plate subduction and closure of the Paleo-Asian Ocean. Previous seismological and geodynamic studies have shown the observed the low-velocity anomaly (LVA) beneath the central Tien Shan at the uppermost mantle, which has a significant influence on the formation and modification of the crust and mantle lithosphere ( Lei et al, 2007). However, the distribution, morphology and physical property of the LVA are highly debatable.

We conduct 2-D forward waveform modeling based on spectral-element method (SEM) to investigate waveform distortions that were generated by the velocity contrast boundary of the LAV. The broadband P- and S- waves from three intermediate-depth earthquakes at Hindu Kush-Pamir were recorded by the Chinese Digital Seismograph Network (Zheng et al., 2010). We use these records to confirm the location, shape and velocity decrement of the LVA by fitting the observed records with the synthetics through SEM based on the 1D velocity structures (TSTB-B) of the central Tien Shan and northern Tarim basin (Gao et al., 2017). We find the LVA at 10~100 km beneath the eastern part of the central Tien Shan. And the northward under-thrusting of the Tarim Basin may trigger some mantle upwelling, contributing to the observed LVA.

Lei, J., Zhao, D. (2007). Teleseismic P-wave tomography and the upper mantle structure of the central Tien Shan orogenic belt. Physics of the Earth and Planetary Interiors, 162, 165-185, doi: 10.1016/j.pepi.200704010.

Zheng, X., Jiao, W., Zhang, C., et al. (2010). Short-Period Rayleigh-Wave Group Velocity Tomography through Ambient Noise Cross-Correlation in Xinjiang, Northwest China. Bulletin of the Seismological Society of America, 100(3): 1350-1355, doi: 10.1785/0120090225.

Gao, Y., Cui, Q., Zhou, Y. (2017). Seismic detection of P-wave velocity structure atop MTZ beneath the Central Tian Shan and Tarim Basin. Chinese Journal of Geophysics ( in Chinese with English Abstract ), 60 (1) : 98-111, doi: 10.6038 /cjg20170109.

How to cite: Cui, R. and Zhou, Y.: Seismic detection of the low-velocity anomaly at the crust and uppermost mantle beneath the central Tien Shan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3300, https://doi.org/10.5194/egusphere-egu2020-3300, 2020.

The South China Sea (hereafter as SCS) located in the southeastern Asia has been affected by the subduction of the western Pacific, Indo-Australian and Eurasian plates (Sun et al., 2018). Broadband P waveforms from the China Digital Seismograph Network (Zheng et al., 2010) for three intermediate-depth earthquakes that occurred closely in Mindoro, Philippine are used to detect velocity structures of the lowermost upper mantle and mantle transition zone (MTZ) beneath the northern SCS. The study area is divided into five profiles distributed from southwest to northeast azimuthally to reduce the computational costs and concern possible lateral variations (Li et al., 2018), and the corresponding 1-D best-fit velocity models are obtained from the observed and synthetic triplicated waveform fitting based on the iterative grid-search procedure. The searching grid can be described as below, three parameters for the low-velocity layer (LVL) atop the 410 km discontinuity (hereafter as the 410), five parameters for the high-velocity anomaly (HVA) atop the 660 km discontinuity (hereafter as the 660) and one parameter for the velocity perturbation below the 660. After the sensitivity tests of the synthetic waveforms with different parameters, the grid steps of the depth and velocity perturbation are set as 5 km and 0.5%, respectively.

Relative to the reference model IASP91 (Kennett and Engdahl, 1991), our results reveal that there are ubiquitous HVAs in five profiles at the bottom of the MTZ with a velocity increment of 1.5~3.5% and a thickness of 209~219 km, which show no apparent progressive velocity increment or decrement along the southwest-northeast direction. We prefer that the weak and abnormal thick HVAs are induced by the proto-SCS north slab remnants. We also observe an uplift 410 and depressed 660 with the depth change of 5 km and 5~15 km, respectively, which further support the low-temperature anomaly related to the stagnant slab. In addition, our results show there is an LVL atop the MTZ with a velocity decrement of 2.0~2.5% and a thickness of 60~75 km, and can be interpreted by the partial melting induced by upwelling materials from the MTZ, which are hydrated by water released from the stagnant slab. We infer that the LVL with little lateral variations may result from the percolation of the partial melts atop the MTZ under vertical pressure.

Kennett B L N, Engdahl E R. 1991. Traveltimes for global earthquake location and phase identification. Geophys. J. Int. 105(2): 429-465, doi:10.1111/j.1365-246X.1991.tb06724.x.

Li W, Wei R, Cui Q, et al. 2018. Velocity structure around the 410 km discontinuity beneath the East China Sea area based on the waveform fitting method. Chinese J. Geophys. 61(1): 150-160, doi:10.6038/cjg2018L0370.

Sun W, Lin C, Zhang L, et al. 2018. The formation of the South China Sea resulted from the closure of the Neo-Tethys: A perspective from regional geology. Acta Petrol. Sin. 34(12): 3467-3478, doi:1000-0569/2018/034(12)-3467-78.

Zheng X, Jiao W, Zhang C, et al. 2010. Short-Period Rayleigh-Wave Group Velocity Tomography through Ambient Noise Cross-Correlation in Xinjiang, Northwest China. Bull. Seismol. Soc. Am. 100(3): 1350-1355, doi:10.1785/0120090225.

How to cite: Li, W., Zhou, Y., Wei, R., Li, G., and Cui, Q.: P-wave velocity structures of the upper mantle and mantle transition zone beneath the northern South China Sea based on triplication fitting, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2008, https://doi.org/10.5194/egusphere-egu2020-2008, 2020.

We present two preliminary tomography models of Antarctica using seismic data recorded globally since 1994. Through combined efforts, several seismic broadband arrays have been deployed in Antarctica in previous decades, enabling the generation of two types of tomography models in this study: a multiple-frequency body-wave tomography and a waveform tomography model. Altogether, more than 2000 global events are collected resolving this region in great detail.

Crustal correction is crucial in seismic tomography, as it can cause the crustal smearing or leakage of shallow heterogeneities into the deep mantle. In global multiple-frequency tomography, synthetic seismograms are calculated on a spherically symmetric earth model (e.g. PREM, IASP91) in which effects of the crust, ellipticity, and topography are neglected. At a later stage, corrections are applied to the measured traveltimes to account for the known deviations from spherically symmetric earth models.

In waveform tomography, the crust has a significant impact on the Rayleigh and Love wave speeds. We invert for the crustal structure and explicitly account for its highly non-linear effects on seismic waveforms. Here, we implement a flexible workflow where different 3D reference crustal models can be plugged in. We test this using the CRUST2.0 and CRUST1.0 models.

In this study, we quantify the effects of these crustal models on two types of inversion techniques with a focus on the mantle structure beneath Antarctica. We compare the mantle structures beneath Antarctica imaged by a multiple-frequency body-wave tomography technique (e.g., Hosseini et al, 2019) and a waveform tomography method (Lebedev et al. 2005; Lebedev and van der Hilst 2008) using CRUST1.0 and CRUST2.0.

References:
K. Hosseini, K. Sigloch, M. Tsekhmistrenko, A. Zaheri, T. Nissen-Meyer, H. Igel, Global mantle structure from multifrequency tomography using P, PPand P-diffracted waves, Geophysical Journal International, Volume 220, Issue 1, January 2020, Pages 96–141, https://doi.org/10.1093/gji/ggz394

S. Lebedev, R. D. Van Der Hilst, Global upper-mantle tomography with the automated multimode inversion of surface and S-wave forms. Geophysical Journal International, Volume 173, Issue 2, May 2008, Pages 505–518, https://doi.org/10.1111/j.1365-246X.2008.03721.x

A. J. Schaeffer, S. Lebedev, Global shear speed structure of the upper mantle and transition zone, Geophysical Journal International, Volume 194, Issue 1, 1 July 2013, Pages 417–449, https://doi.org/10.1093/gji/ggt095

How to cite: Tsekhmistrenko, M. and Lebedev, S.: The impact of crustal structures on multiple frequency and waveform tomography of Antarctica, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16489, https://doi.org/10.5194/egusphere-egu2020-16489, 2020.

We present some preliminary results from ongoing seismic measurements aimed to assess the seismic noise levels in the Sos Enattos Mine (Sardina). Due to his geologic setting, low population density and lack of significant industrial activity, Sardinia is characterized by very low anthropogenic noise and very low seismic activity. These unique combinations of factors make Sardinia, and in particular the Sos Enattos site, suitable to host instruments that must be placed in particularly seismically quiet locations in order to meet their targeted sensitivity. This is certainly the case of gravitational waves detectors, whose next generation, called Einstein Telescope (ET), is planned to be able to measure a strain, induced by the passing wave on the interferometer’s arm, of the order of 2x10^-25Hz^-1/2. Three broadband seismometers has been installed since May 2019 both at surface and at different depths along the mine tunnels. We analyse the spectral distribution of the seismic noise with a special focus on the frequency bands that may affect the operation of a gravitational waves interferometer. We also study the correlation of seismic noise with the observed sea waves in the Mediterranean Sea. The results enlighten very low seismic noise levels at the surface and attenuation at the depths foreseen to build ET. Further, seismic noise levels appear to be strongly correlated with sea waves in NW Mediterranean Sea. We conclude that the selected site may meet the stringent seismic requirements needed to realize the ET infrastructure.

How to cite: Giunchi, C., Di Giovanni, M., Saccorotti, G., and Naticchioni, L.: Seismic noise characterization of the Sos Enattos Mine (Sardinia), a candidate site for the next generation of terrestrial gravitational waves detectors, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9692, https://doi.org/10.5194/egusphere-egu2020-9692, 2020.

A fundamental element of real-time mission critical seismic monitoring networks is the data acquisition system, comprising the underlying protocol and the telemetry solution. Selection of the acquisition protocol can have significant impact on the outcomes sought by the seismic network such as data availability and usability as well as operational cost and even station and data center design.

We examine the performance of various acquisition protocols using a set of standard measures of system performance. Primary measures include bandwidth utilization, data latency and robustness (data completeness). In addition, protocol functionality and features, including support for multiple data types and state-of-health, are assessed for system impact on options for station, telemetry, and data center design as well as the overall functionality of the system solution.

Real-world and system generated data are employed and key quantitative measures of system effectiveness are identified and used as the basis of the analysis. Results of the analysis show the real-world impact of low level aspects like protocol selection on system performance.

How to cite: Laporte, M., Perlin, M., Tatham, B., Hosseini, M., Baturan, D., Moores, A., and Townsend, B.: Acquisition Protocol - Its Impact on Real-time Data Acquisition System Performance, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20351, https://doi.org/10.5194/egusphere-egu2020-20351, 2020.

Seismic attenuation accompanying the velocity structures demonstrates the variations of the physical and chemical properties of the earth. The t* measurement using the seismic body wave spectrum, however, typically encounters the trade-off of corner frequency, t*, and site effect. Ko et al, [2012] proposed the cluster event method (CEM) that reduced the model parameter numbers by grouping the spatial-closed enough events for those traveling to each station along the adjacent paths and sharing one t*. Yet, the site effects among different stations collected in the same cluster bring the challenges on fitting all spectrum. We adapt the cluster strategy to group multiple nearby events recorded by one station only. Moreover, the new iterative CEM algorithm includes both the spectrum and spectral ratio data which provide constraints on seismic moments and corner frequencies of each earthquake inside the cluster, respectively. The final t* and corner frequencies are determined again by including the side effects which are averaging from spectrum residuals in the initial CEM stage. We applied the iterative CEM for earthquakes recorded at dense deployed F-net and Hi-net by NIED in the Tohoku area, Japan. The multitaper spectrums are retrieved from direct P waves with coda wavetrains tapered. Combining the spectral ratio and spectrum data with proper weightings, our new approach increases the stability of t* measurements contributed from better constrains on the corner frequency estimations.

How to cite: Jian, P.-R. and Kuo, B.-Y.: Robust measurements of corner frequency, t* and site effect: the iterative cluster event method, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2694, https://doi.org/10.5194/egusphere-egu2020-2694, 2020.

Several authors empirically observed that the scaling between local magnitude ML and moment magnitude Mw computed by spectral methods is not 1:1 for ML<2-4. In particular ML is found to be about proportional to 1.5 Mw but the exact threshold below which this occurs is argued. Such behavior was explained as due to attenuation and scattering along the path or to a minimum limit in the pulse duration or equivalently a maximum limit to the corner frequency of the observed spectra imposed by surface attenuation. The frequency-magnitude distribution of ML estimates provided by the Italian Seismic Instrumental Database (ISIDe) of INGV show a strictly linear behavior with b-value»1.0 down to about ML 1.4 at least. This implies that for Mw the b-value would be about 1.5 below magnitude 2-4 and 1 above. As the frequency magnitude relationship with b-value»1 in terms of Mw is recognized as a general characteristic of seismicity all over the world, based on both empirical and theoretical considerations, the question arises on the reasons of the observed discrepancy for small shocks. One explanation might be the assumption of incorrect seismic wave attenuation properties for the computation of ML, of spectral Mw or both.

How to cite: Lolli, B., Paolo, G., Biondini, E., and Vannucci, G.: The relationship between ML and Mw for small earthquakes (ML < 2-4) in Italy, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18821, https://doi.org/10.5194/egusphere-egu2020-18821, 2020.

Since the inception of 62 borehole seismic arrays deployed by Central Weather Bureau (CWB) in Taiwan until the end of 2018, a large quantity of strong-motion records have been accumulated from frequently occurring earthquakes around Taiwan, which provide an opportunity to detect micro-seismicity. Each borehole array includes two force balance accelerometers, one at the surface and other at a depth of a few ten-to-hundred (30-492) meters, as well as one broadband seismometer is below the borehole accelerometer. In general, the background seismic noise level are lower at the downhole stations than surface stations. However, the seismograms recorded by the downhole stations are smaller than surface stations due to the near-surface site effect. In Taiwan, the local magnitude (M_L) determinations use the attenuation function derived from surface stations. Therefore, the M_L will be underestimated by using current attenuation function for downhole stations. In this study, we used 19079 earthquakes to investigate the site amplification at subsurface materials between downhole and surface stations. Results demonstrate the amplification factors ranging from 1.11 to 5.74, provide the site effect parameter at shallow layers and have a strong relationship with Vs30. Further, we apply the amplification factors to revise the station local magnitude for downhole station. The revised M_L at downhole stations correlate well with the M_L at surface stations. Implement of the downhole station in the M_L determination, it enhances the ability to detect the micro-earthquake and makes the earthquake catalog more comprehensive in Taiwan.

How to cite: Lai, T.-S., Wu, Y.-M., and Chao, W.-A.: Application of Site Amplification Factors to Determine the Local Magnitude from Borehole Seismic Stations in Taiwan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6310, https://doi.org/10.5194/egusphere-egu2020-6310, 2020.

BCSF-RéNaSS (Bureau central sismologique français – Réseau national de surveillance sismique) manages the collection of data from the field for any earthquake in mainland France of magnitude greater than 3.7 and ensures their interpretation in terms of macro-seismic intensities (severity of ground shaking) on EMS98, European Macroseismic Scale (Grünthal, 1998). Unlike the magnitude, which is calculated from seismological records, the intensity of the tremor is only known in each location by analysing the observable effects on people, objects and structures. In case of damage, the GIM (Groupe d'intervention macrosismique = Macroseismic Response Group), coordinated by the BCSF-RéNaSS, establishes EMS98 intensities within a short time after the occurrence of the earthquake. It gathers together scientists (researchers and engineers in tectonics, geology, civil engineering, etc.) from various French scientific institutions.

The 2019-11-11 Le Teil earthquake of magnitude ML 5.2 occurred at 10h52 UTC, 11h52 local time. It is a very shallow event, with hypocentre at about 2km depth and a fault rupture that reached the surface. More than 2000 people who felt the tremor responded to the online survey via the www.franceseisme.fr website, allowing a preliminary and rapid estimation of the intensity of the tremor. The day after the event, the BCSF-RéNaSS launched a survey toward the municipal authorities using a collective form designed for the town halls of the municipalities potentially affected. Given the damage described in the answers, the GIM was mobilized to accurately assess the EMS98 intensities of municipalities near the epicentre, based on the effects observed on buildings, people and objects, and taking into account their vulnerability.

Among the almost sixty experts that compose the GIM, seven from IRSN, ISTerre/RESIF-RAP, Cerema, Pacte/UGA, IPGS and EOST/BCSF-RéNaSS answered the call. Divided into teams of 2 or 3, they inspected 24 municipalities between November 18^thand 22^nd, assisted by mayors or municipal services and sometimes accompanied by the rescue brigade. Several hundred buildings of different vulnerabilities were inspected.

In most cases, many cracks, sometimes significant and open, were observed. Few of the oldest structures built mostly in the 19^thcentury, associated to vulnerability A, partially or totally collapsed in the most affected areas such as Le Teil and Viviers. For comparable buildings, more severe damages were observed on top of hills (Saint-Thomé) or on sedimentary filling (Savasse) which attests for local site effects. 

The highest intensities reach locally VIII in La Rouvière and Mélas, two neighbourhood of Le Teil, that are located the closest to the Rouvière fault. These are the highest intensities observed in mainland France since the Arette earthquake in 1967 (Rothé, 1972).

The macroseismic intensities EMS98, estimated during the GIM's field missions, are one of the major input on which is based the decision of the French commission to classify municipalities in a state of natural disasters.  That decision triggers insurance coverage of damages.  Over the 24 analysed by the GIM, the commission classified 19 municipalities during their meetings of November 20^thand December 11^th. Following commission meetings will examine the other impacted municipalities.

How to cite: Schlupp, A., Sira, C., Maufroy, E., Provost, L., Dretzen, R., Bertrand, E., Beck, E., and Schaming, M.: EMS98 intensity estimation of the shallow Le Teil earthquake, ML 5.2, by Macroseismic Response Group GIM, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3767, https://doi.org/10.5194/egusphere-egu2020-3767, 2020.

How to cite: Kang, T.-S. and Lee, H.: Complex seismic activity and local stress perturbation of the Pyeongnam basin, northern Korean Peninsula, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18365, https://doi.org/10.5194/egusphere-egu2020-18365, 2020.

Large earthquakes are regarded as important contributors to long-term erosion rates and considerable hazard to infrastructure and society, which were difficult to track because of the long recurrence time exceeding the time span of historical records. Geological records, especially the continuously accumulated lacustrine sediments, hold the potential to capture signals of prehistoric seismic events, which has been barely reported from the Tibetan Plateau. Here we present lacustrine sediment records recovered from Basom Tso in Southeastern Tibetan Plateau, in which two seismic events were preserved. Sediment lithology, grain size composition, magnetic susceptibility and XRF scanning induced element compositions showed dramatic variations in two turbidite-like sediment segments. Particularly, the grain size showed an abrupt increase at the bottom of the Turbidites which was followed by a fining-up pattern and covered by a fine clay cap, expressing similar sedimentary processes caused by the seiche effect triggered by seismic events. Consistent patterns were recorded in the element contents as well, i.e. obvious bias in the counts of Fe, Zr, Ti, Ca. In addition, scuh pattern were preserved in sediment cores from different part of the lake basin, indicating a basin wide event layer. Finally, according to the dating results from ¹³⁷Cs and ¹⁴C, the two Turbidites were formed around 1950 A.D. and during the late18^th/early 19^th century respectively. Such information was further confirmed by historical earthquake records that Chayu Earthquake (M=8.6, 1950 A.D.) and Nyingchi Earthquake (M=6.75, 1845 A.D.) have possibly responsible for the slump of underwater sediments and the formation of these two turbidites.

How to cite: Wang, Y., Ma, X., and Ni, Z.: Recent seismic events preserved in lacustrine sediments from the SE Tibetan Plateau, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7557, https://doi.org/10.5194/egusphere-egu2020-7557, 2020.

On 24^th and 26^th  September 2019, two earthquakes of M_w=4.5 and M_w=5.6 respectively took place in the Marmara Sea. They were associated with the Central Marmara segment of the North Anatolian Fault Zone, which is pinpointed by several investigators as the most likely segment to rupture in the near future giving way to an earthquake larger than M7.0. Both events were felt widely in the region. The M_w=5.6 event, in particular, led to a number of building damages in Istanbul, which were larger than expected in number and severity. There are several strong motion networks in operation in and around Istanbul. We have compiled a data set of recordings obtained at the stations of the Istanbul Earthquake Rapid Response and Early Warning operated by the Department of Earthquake Engineering of Bogazici University and of the National Strong Motion Network operated by AFAD. It consists of 148 three component recordings, in total.  444 records in the data set, after correction, were analyzed to estimate the source parameters of these events, such as corner frequency, source duration, radius and rupture area, average source dislocation and stress drop. Duration characteristics of two earthquakes were analyzed first by considering P-wave and S-wave onsets and then, focusing on S-wave and significant durations. PGAs, PGVs and SAs were calculated and compared with three commonly used ground motion prediction models (i.e  Boore et al., 2014; Akkar et al., 2014 and Kale et al., 2015). Finally frequency-dependent Q models were estimated using the data set and their validity was dicussed by comparing with previously developed models.

How to cite: Çakti, E., Malcioğlu, F. S., and Süleyman, H.: SEISMOLOGICAL AND ENGINEERING PARAMETERS OF 24 and 26 SEPTEMBER, 2019 MARMARA SEA EARTHQUAKES, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22107, https://doi.org/10.5194/egusphere-egu2020-22107, 2020.

The area of Zakynthos (Ionian Island) is located at a complex plate boundary region where two tectonic plates (Africa-Nubia and Eurasia) converge, thus forming the western Hellenic Arc. On the midnight of 26^th October (M_L = 6.6, 22:54:49 UTC) a very strong earthquake has struck at the eastern part of Zakynthos Island (Ionian Sea, Western Greece). Epicentral coordinates of the earthquake was determined as 37.3410° N, 20.5123° E and a focal depth at 10 km, according to the manual solution of National Observatory of Athens

(http://bbnet.gein.noa.gr/alerts_manual/2018/10/evman181025225449_info.html).

This earthquake was strongly felt at the biggest shock was felt as far afield as Naples in western Italy, and in Albania, Libya, and the capital Athens. Nobody was injured by these events but there was significant damage to the local port and a 13th Century island monastery south of Zakynthos.

A few minutes later (23:09:20, UTC) a second intermediate earthquake with magnitude M_L=5.1 was followed the first event. The M5+ events of 25 October 2019, as well as the rich aftershock sequence of 10.000+ events with magnitudes 1.0<ML<4.9 of the 12 following months have been relocated using the double – difference algorithm HYPODD.

For the aftershocks with 3.7<M_L<6.6 we applied the moment tensor inversion to determine the activation of the faulting type, the Seismic Moment (M₀) and the Moment Magnitude (M_w). For this purpose, 3–component broadband seismological data from the Hellenic Unified Seismological Network (HUSN) at epicentral distances less than 3˚ were selected and analyzed. The preparation of the data, includes the deconvolution of instrument response, following the velocity was integrated to displacement and finally the horizontal components rotated to radial and transverse. All the focal mechanisms were compared with those from other institutes and they are in agreement. The second part of this study refers to the calculation of the stress tensor using the STRESSINVERSE package by Václav Vavryčuk. The final part of this study includes an extensive kinematic analysis of geodetic data from local GNSS permanent station to further examine the dynamic displacement.

References:

How to cite: Moshou, A., Konstantaras, A., Argyrakis, P., and Sagias, N.: The ML = 6.8 25 October 2018 Earthquake Zakynthos Island (Ionian Sea) and the evolution of the aftershock sequence one year later, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3960, https://doi.org/10.5194/egusphere-egu2020-3960, 2020.

We report here a first comparative analysis between recent and historical earthquakes, occurred in the island of Ischia (Southern Italy), which produced heavy damages and thousands of fatalities. The island of Ischia is located in the Gulf of Naples, and represents a peculiar case of resurgent caldera in which volcano-tectonic earthquakes, with low magnitude, have generated large damages and catastrophic effects, as is the case for the 4 March 1881 (I_max8-9 MCS) and the 28 July 1883 (I_max10-11 MCS) events. Both the earthquakes struck the northern area of the island, similarly to the recent 21 August 2017 earthquake. The results allowed us to assess the location, as well as the possible dimension and the related maximum magnitude of the seismogenic structure, located in the northern sector of the island, and responsible of damaging earthquakes. Our results also provide an additional framework to interpret mechanisms leading to earthquakes associated with dynamics of calderas.

How to cite: Carlino, S., Convertito, V., Tramelli, A., De Novellis, V., and Pino, N. A.: New seismological insights from the analyses of historical and recent earthquakes at Ischia Island (Southern Italy) , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12975, https://doi.org/10.5194/egusphere-egu2020-12975, 2020.

To study the deep structure of the earth it is important to have an optimal monitoring network and reliable seismic baseline database for the investigated area. In addition, the territory of Armenia according to its geology and seismological conditions is a full-scale experimental polygon for seismic problems, in particular the study of Earth's deepest structure by seismic methods. For this purpose, the work aims to assess the effectiveness of the existing seismic monitoring system in Armenia, to offer optimal solutions for the station layout, to evaluate the accuracy of seismic information registered in the RA by performing hypocenter recalculation. Then, within of the work organized modern seismic stations in Armenia and Russia towns with seismic equipment made and produced in Armenia (IGES NAS RA). The work was supported by MESCS Science Committee of the Republic of Armenia (grant № 18SH-1E012).

How to cite: Karapetyan, J., Ghazaryan, K., Sargsyan, R., and Karapetyan, R.: Efficiency assessment of seismological information, monitoring system and seismicity study for the Republic of Armenia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11385, https://doi.org/10.5194/egusphere-egu2020-11385, 2020.

The Northern Apennines is a NW-SE striking fold-and-thrust belt composed of a pile of NE-verging tectonic units that developed during Cenozoic collision between the European plate (Corso–Sardinian block) and the Adria plate. Seismicity and geodetic data indicate that contemporaneous crustal shortening (in the external, Adriatic part) and extension (in the internal, Tyrrhenian side) characterize the current tectonic activity of the Apennines. The region around the Mugello basin (Northern Tuscany) represents one of the most important seismogenic areas of the Northern Apennines. Large historical earthquakes have occurred, such as the M=6.0, 1542 and the M=6.4, 1919 events. Its proximity to densely-urbanized areas and the potential impact of strong earthquakes on the cultural heritage in the nearby (~30km) city of Florence makes a better knowledge of the seismicity in the Mugello basin a target of paramount importance. Unresolved issues regard (i) the exact location and geometry of the fault(s) which produced the 1542 and 1919 earthquakes, (ii) the mechanism driving the abrupt transition from an extensional to compressional stress regime at the internal and external sides of the belt, respectively, and (iii) geometry of and role played by a close-by transfer zone oriented transversely (NE-SW) to the main strike of the belt. To address these problems, in early 2019 we initiated a project aiming at improving the knowledge about the seismo-tectonic setting of the basin and adjoining areas. At first, we integrated all the available seismic catalogs for the area, obtaining more than 12000 earthquakes spanning the 2005-2019 time interval. These data have been used to derive a minimum-misfit, 1-D velocity model to be subsequently used for a travel times inversion 3D tomography. At the same time, we Installed 9 temporary seismic stations, complementing the permanent networks presently operating in the area. This new deployment recorded a Mw=4.5 earthquake that struck the NW margin of the basin on Dec. 9, 2019. The mainshock and the ~200 aftershocks precisely delineate a 5-km-long, NW-striking and SW-dipping fault which extends over the 6-9 km depth interval. The focal mechanism of the mainshock yields consistent results, indicating a normal fault striking N105°E and dipping about 45°. This fault appears to be distinct from that (those) activated during the two last important sequences in the area, which occurred in 2008 and 2009. The earthquake caused unexpected, large accelerations (PGA~0.24g at ~7km epicentral range), provoking damages that resulted in the evacuation of more than 150 residents and economic losses of several millions of euro. Sample horizontal-to-vertical spectral ratios at the most damaged sites report significant amplification within the 1-5 Hz frequency range, likely responsible for the anomalous ground shaking. Given the proximity of the aforementioned fault to that inferred for the 1542 (and, possibly, 1919) earthquake(s), a detailed study of the 2019 seismic sequence is expected to shed new light into the overall dynamics of the basin.

How to cite: Bruni, R., Corti, G., D'Ambrosio, M., Fiaschi, A., Giunchi, C., Keir, D., Piccinini, D., Sani, F., and Saccorotti, G.: Present-day seismic activity in the Mugello Basin and adjoining areas (Northern Apennines, Italy), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11211, https://doi.org/10.5194/egusphere-egu2020-11211, 2020.

The geodynamic complexity in the interaction between Rivera, Cocos and NOAM plates is mainly reflected in the high and not well located seismicity of the region. In the framework of TsuJal Project, a study of the passive seismic activity was carried out. A temporal seismic network with 25 Obsidian stations with sensor Le-3D MkIII were deploying from the northern part of Nayarit state to the south of Colima state, including the Marias Islands, in addition to the Jalisco telemetric Seismic Network, being a total of 50 seismic stations on land. Offshore, ten Ocean Bottom Seismographs type LCHEAPO 2000 with 4 channels (3 seismic short period and 1 pressure sensors) were deployed and recover by the BO El Puma from UNAM in an array from the Marias Islands to off coast of the border of Colima and Michoacan state, in the period from 19th April to 7th November 2016.

A seismic sequence started on May 7, 2016 with an earthquake Mw = 5.6 reported by CMT-Harvard, USGS and SSN at the area north of Paleo Rivera Transform fault and west of the Middle America Trench, an area with a very complex tectonics due to the interaction of Rivera, Cocos and NOAM plates.

An analysis of this earthquake sequence from May 7 to May 11 using data from OBS and adequate P-Wave velocity model for Rivera plate is presented, 87 earthquakes were located. Data from onland stations were integrated after a travel-time residual analysis.

We observed that the new location is about 50 km southwest direction, from previous one, between the Paleo Rivera Transform fault and the northern tip of the East Pacific Rise – Pacific Cocos Segment.  This area has a different tectonic stress regime.

How to cite: Nunez-Cornu, F. J., Cordoba, D., Bandy, W. L., Dañobeitia, J. J., Mortera-Gutierrez, C., Alarcon, E., Nuñez, D., Quinteros-Cartaya, C. B., and Suarez-Plascencia, C.: The May 7 - 11, 2016 Earthquake Sequence at Rivera Fault Zone, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11945, https://doi.org/10.5194/egusphere-egu2020-11945, 2020.

Traditionally, the ability to study seismic phenomena is dependant on both the available hardware and time for processing data needed to produce a research grade catalogue. Consequently, shortages in either of these resources constrain the scope of studies available to the research scientist. This is becoming especially challenging as networks become larger and more dense, and as the community moves towards Large-N networks and arrays. We will look at alternative solutions to address these resource constraints and open the scientist up to a broader field of study.

Ownership of equipment or waiting in a queue for loan pool assets are the two most common methods for acquiring the hardware necessary to conduct a scientific study. Further, once the data has been collected, a good deal of time is spent processing that data to produce a catalogue before the scientific inquiry can begin.   

There is now an alternative model for acquiring and processing data in seismology that shortens the time and effort necessary to produce a research grade catalogue. We will demonstrate how we can customize acquisition arrays to meet experimental goals and apply proven processing models and AI techniques to deliver a bespoke research grade catalogue at a fraction of the time and cost of traditional acquisition and processing methods. This removes several of the challenging aspects of running an experiment in order to enable researchers to get straight to their science and shortening the time to publication.

How to cite: Baturan, D., Townsend, B., and Moores, A.: A new operational model that increases experiment diversity and shortens time to publication for research Seismology, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12535, https://doi.org/10.5194/egusphere-egu2020-12535, 2020.

The coda magnitude method of Mayeda and Walter (1996) provides stable source spectra and moment magnitudes (M_w) for local to regional events from as few as one station that are virtually insensitive to source and path heterogeneity. The method allows for a consistent measure of M_w over a broad range of event sizes rather than relying on empirical magnitude relationships that attempt to tie various narrowband relative magnitudes (e.g., M_L, M_D, m_b, etc.) to absolute M_w derived from long-period waveform modeling. The use of S-coda and P-coda envelopes has been well documented over the past several decades for stable source spectra, apparent stress scaling, and hazard studies. However, up until recently, the method requires extensive calibration effort and routine operational use was limited only to proprietary US NDC software. The Coda Calibration Tool (CCT) stems from a multi-year collaboration between the US NDC and LLNL scientists with the goal of developing a fast and easy Java-based, platform independent coda envelope calibration and processing tool. We present an overview of the tool and advantages of the method along with several calibration examples, all of which are freely available to the public via GitHub (https://github.com/LLNL/coda-calibration-tool). Once a region is calibrated, the tool can then be used in routine processing to obtain stable source spectra and associated source information (e.g., M_w, radiated seismic energy, apparent stress, corner frequency, source discrimination on event type and/or depth). As more events are recorded or new stations added, simple updates to the calibration can be performed. All calibration and measurement information (e.g., site and path correction terms, raw & measured amplitudes, errors, etc.) is stored within an internal database that can be queried for future use. We welcome future collaboration, testing and suggestions by the geophysical community.  

How to cite: Mayeda, K., Gok, R., Barno, J., Walter, W., and Roman-Nieves, J.: The Coda Calibration and Processing Tool: Java-Based Freeware for the Geophysical Community, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5874, https://doi.org/10.5194/egusphere-egu2020-5874, 2020.

A generic approach for real-time magnitude and stress drop is introduced that is based on the omega-squared model (Brune, 1970) and results from Lior and Ziv (2018). This approach leads to approximate expressions for earthquake magnitude and stress drop as functions of epicentral distance and ground motion root-mean-squares (rms). Because the rms of the ground motion (acceleration, velocity and displacement) may be calculated directly from the seismogram in the time domain, the use of this approach for automated real-time processing is rather straightforward. Once the seismic moment and stress drop are known, they may be plugged in the ground motion prediction equations (GMPE) of Lior and Ziv (2018) to map the predicted peak shaking.

This method is generic in the sense that it is readily implementable in any tectonic environment, without having to go through a calibration phase. The potential of these results for automated early warning applications is demonstrated using a large dataset of about 6000 seismograms recorded by strong-motion and broadband velocity sensors from different tectonic environments. Optimal real-time performance is achieved by integrating magnitude and stress drop estimates into an evolutionary algorithm. The result of such an evolutionary calculation for the Mw 7.1 Ridgecrest earthquake indicates close agreement with the true magnitude.

How to cite: ziv, A. and Lior, I.: Generic Source Parameter Determination for Earthquake Early Warning: Theory, Observations and Implications for the Mw 7.1 Ridgecrest Earthquake, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15078, https://doi.org/10.5194/egusphere-egu2020-15078, 2020.

Methodologies dealing with the detection of micro-earthquakes and the accurate estimation of body waves’ arrival time constitute, during the last decades, a topic of ongoing research. The extraction and efficient analysis of the useful information from the continuous recordings is of great importance, since it is a prerequisite for reliable interpretations.  Small magnitude seismic events, either naturally-occuring or induced, have been increasingly used in a wide range of industrial fields, with applications ranging from hydrocarbon and geothermal reservoir exploration, to passive seismic tomography surveys.

A great number of algorithms have been proposed and applied up to now for seismic event detection, exploiting specific properties of the seismic signals both in time and in frequency domain, with the energy-based detectors (STA/LTA) to be the most commonly used, due to their simplicity and the low computational cost they require. A significant obstacle emerging at seismological identification problems lies on the fact that such processes usually suffer from a number of false alarms, which is significantly increased in extremely noisy environments.

For that scope, we propose a “Decision-Making” mechanism, independent of the applied detection algorithm, which controls the results obtained during the detection process by minimizing false detections and providing the best possible outcome for further analysis. The specific scenario is based on the comparison among autoregressive models estimated on isolated seismic noise recordings, as well as on the detected intervals that resulted during the event identification procedure. A number of examples, associated with the implementation of the proposed scenario on real data, is presented with the scope of evaluating its performance. Several issues concerning the isolation of the seismic noise from the raw data, the estimation of the autoregressive models, the choice of the orders of the stochastic models etc., are discussed.

How to cite: Lois, A., Kopsaftopoulos, F., Giannopoulos, D., Polychronopoulou, K., and Martakis, N.: Remarks on the micro-earthquake detection problem: Refining the outcome using stochastic modeling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9095, https://doi.org/10.5194/egusphere-egu2020-9095, 2020.

The detection of microearthquakes is an important task in various seismological applications as volcano seismology, induced seismicity, and mining safety. In this work we have developed a novel technique in order to improve the quality and efficiency of STA/LTA based detection of microearthquakes. This technique consists of different stages of filtering employing an adaptive spectral subtraction method, which allows greatly improving the signal/noise ratio.

The implemented technique consists in a preliminary band-pass filtering of the signal followed by different stages of an adaptive spectral subtraction. The spectral subtraction technique is a non-linear filtering which allows taking into account the actual noise spectrum shape. It allows achieving a good filtering even in cases where the signal and noise spectrum overlaps. In order to take into account of the temporal variation in the background noise spectrum, we designed an adaptive technique. We first divide the incoming signals into short temporal windows. Each window is classified as “noise only” or “meaningful signal” (which can be either a microearthquake or any other relevant transient signal) using different features as the signal energy and the zero-crossing rate. Windows classified as “noise only” are continuously accumulated in a dynamic buffer which allows the average noise spectrum to be estimated and updated in an adaptive manner. This technique can be applied on subsequent stages to further improve the signal/noise ratio. This technique has been implemented in Python for the automatic detection of the microearthquakes on both off-line and near-real time data.

In order to check the efficiency of the results, we compared the results of an STA/LTA based automatic detection on the initial band-pass filtered signal and on the spectral subtracted signals after different stages of filtering. A notable improvement of the quality of the detection process is observed when repeated spectral subtraction stages are applied. 

We applied this procedure to seismic data recorded by Red Sísmica Canaria, managed by Instituto Volcanológico de Canarias (INVOLCAN), on Tenerife (Canary Islands), comparing results from the proposed detection algorithm with standard approaches as well as with manual detections. We present an extensive statistical analysis of the results, determining the percentage of correct detections, novel detections, false positives and false negatives after each stage of filtering. First results have shown that this technique is also able to detect automatically microearthquakes which went undetected after a manual analysis.

How to cite: Rajaeitabrizi, Y., Salehiozoumchelouei, R., D'Auria, L., and Sánchez de la Rosa, J. L.: Multistage adaptive spectral subtraction of seismic signals, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4853, https://doi.org/10.5194/egusphere-egu2020-4853, 2020.

Kouvola area, a part of the Vyborg rapakivi batholith in southeastern Finland, has been experiencing an intraplate earthquake swarm since December 2011. The events have magnitudes ranging from M_L -1.2 to 2.8 and they happen in the uppermost two kilometers of the crust. The Vyborg batholith has a long history of earthquake swarms with macroseismic data from 1751 onwards and the first instrumentally recorded swarm in 2003-2004.

Inspired by the ongoing activity, Institute of Seismology of University of Helsinki (ISUH) has installed temporary seismic stations in the area to complement seismic stations of the Finnish National Seismic network (FNSN). The detection threshold of FNSN is M_L1.0, not sufficiently low to catch the smallest earthquakes of the swarm.

Several tailored cross-correlators have been developed at the ISUH to lower the event detection threshold. These can be used to detect even very small seismic events well below the current FNSN detection threshold. The method is especially well suited to swarm events, which generate nearly identical signals due to their common origin.

Only the largest events of the swarm can be used to calculate focal mechanisms or other event parameters reliably. One approach to use all data is waveform clustering. Event groups with identical signal can be formed, allowing e.g. calculation of composite focal mechanisms for each event cluster.

How to cite: Luhta, T., Komminaho, K., Oinonen, K., Tiira, T., Uski, M., Veikkolainen, T., and Vuorinen, T.: Kouvola earthquake swarm - using a cross-correlator to find very small events and cluster them, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19417, https://doi.org/10.5194/egusphere-egu2020-19417, 2020.

The Alpine Fault is a major plate boundary oblique strike-slip fault, known to fail in large M 7-8 earthquakes, posing a significant seismic hazard to southern and central New Zealand. The central part of the Alpine Fault exhibits low seismic activity when compared to adjacent areas. We have examined the smaller-magnitude earthquake activity occurring along the central portion of the Alpine Fault using data from five temporary seismic networks from late 2008 to early 2017.

We have created the most complete and accurate earthquake catalog at the central Alpine Fault to date (9,111 earthquake locations with magnitudes ranging from M_L -1.2 to 4.6). We used this catalog as templates with a matched-filtering earthquake detection method and further extend the earthquake catalog. This even more comprehensive earthquake catalog will provide more definitive evidence for the seismicity characteristics observed and better insights into the fault zone’s geometry. 

Taking advantage of this extensive earthquake catalog, we also aim to examine whether there are any repeating highly similar seismic signals (repeating earthquakes). These repeating earthquakes can potentially help better determine the locked and creeping sections of the Alpine Fault and possibly quantify the total amount of creep taking place with respect to seismic deformation.

How to cite: Michailos, K., Chamberlain, C. J., and Townend, J.: Waveform cross-correlation-based earthquake detection applied to microseismicity near the central Alpine Fault, New Zealand, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5099, https://doi.org/10.5194/egusphere-egu2020-5099, 2020.

In order to assess the fault-geometry and the spatio-temporal evolution of natural and induced seismicity, high-precision (relative) micro-seismic hypocenter locations are key information. From such precise relative hypocenter locations, we can infer e.g. the spatial extent during a seismic sequence, the seismogenic volume affected by stimulation procedures as well as geometries (orientation, segmentation) of potentially activated faults. Additionally, in the case of induced seismicity, the spatio-temporal evolution of seismicity (e.g. migration velocities of seismicity, r-t-diagrams) can be indicative for fluid-flow processes and provides first-order estimates of hydraulic properties of the reservoir as well as on the existence of possible hydraulic connections. Information on spatial extent, geometries and the spatio-temporal evolution of seismogenic structures can help to improve the seismic hazard assessment of natural and induced seismicity in real-time or near-real-time.

However, to make prompt use of information provided by such high-precision hypocenter locations requires relative relocations computed in near-real-time. This can be rather challenging, especially at the beginning of a seismic sequence, when only little or no background seismicity is available for relative relocation. In addition, an automated relative relocation process requires differential times derived from precise and reliable (absolute) automatic picks as well as from waveform cross-correlation.

In this work, we present our strategy towards a near-real-time relative relocation procedure. The procedure follows the methodology described by Waldhauser 2009 (BSSA; doi:10.1785/0120080294) and combines differential times derived from automatic as well as manual picks with waveform cross-correlations measurements. Differential times of new events are inverted for relative locations with respect to a background reference catalog using the double-difference algorithm. We present results derived by a python-based prototype applied to natural and induced earthquake sequences. In addition, the prototype is fully implemented in a new SeisComP3 (SC3) module “scrtdd”, which allows the application in a full real-time environment, using detections and locations from various existing SC3 modules (“scautoloc”, “scanloc”, “screloc”) as input for relative relocation. We outline our implementation strategy, and compare SC3 results with results derived by our software for natural and induced earthquakes monitored be dense near-fault monitoring networks in the Valais (SW Switzerland), St. Gallen (Switzerland) and the Hengill Geothermal Field (SW Iceland).

How to cite: Scarabello, L., Diehl, T., Kästli, P., Clinton, J., and Wiemer, S.: Towards Real-Time Double-Difference Hypocenter Relocation of Natural and Induced Seismicity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13058, https://doi.org/10.5194/egusphere-egu2020-13058, 2020.

Understanding the dynamics of faulting is a crucial target in earthquake source physics (Yoo et al., 2010). To study earthquake dynamics it is indeed necessary to look at the source complexity from different perspectives; in this regard, useful information is provided by the seismic moment (M0), which is a static measure of the earthquake size, and the seismic radiated energy (ER), which is connected to the rupture kinematics and dynamics (e.g. Bormann & Di Giacomo 2011a). Studying spatial and temporal evolution of scaling relations between scaled energy (i.e., e = ER/M0) versus the static measure of source dimension (M0) can provide valuable indications for understanding the earthquake generation processes, single out precursors of stress concentrations, foreshocks and the nucleation of large earthquakes (Picozzi et al., 2019). In the last ten years, seismology has undergone a terrific development. Evolution in data telemetry opened the new research field of real-time seismology (Kanamori 2005), which targets are the rapid determination of earthquake location and size, the timely implementation of emergency plans and, under favourable conditions, earthquake early warning. On the other hand, the availability of denser and high quality seismic networks deployed near faults made possible to observe very large numbers of micro-to-small earthquakes, which is pushing the seismological community to look for novel big data analysis strategies. Large earthquakes in Italy have the peculiar characteristic of being followed within seconds to months by large aftershocks of magnitude similar to the initial quake or even larger, demonstrating the complexity of the Apennines’ faults system (Gentili and Giovanbattista, 2017). Picozzi et al. (2017) estimated the radiated seismic energy and seismic moment from P-wave signals for almost forty earthquakes with the largest magnitude of the 2016-2017 Central Italy seismic sequence. Focusing on S-wave signals recorded by local networks, Bindi et al. (2018) analysed more than 1400 earthquakes in the magnitude ranges 2.5 ≤ Mw ≤ 6.5 of the same region occurred from 2008 to 2017 and estimated both ER and M0, from which were derived the energy magnitude (Me) and Mw for investigating the impact of different magnitude scales on the aleatory variability associated with ground motion prediction equations. In this work, exploiting first steps made in this direction by Picozzi et al. (2017) and Bindi et al. (2018), we derived a novel approach for the real-time, robust estimation of seismic moment and radiated energy of small to large magnitude earthquakes recorded at local scales. In the first part of the work, we describe the procedure for extracting from the S-wave signals robust estimates of the peak displacement (PDS) and the cumulative squared velocity (IV2S). Then, exploiting a calibration data set of about 6000 earthquakes for which well-constrained M0 and theoretical ER values were available, we describe the calibration of empirical attenuation models. The coefficients and parameters obtained by calibration were then used for determining ER and M0 of a testing dataset

How to cite: Scafidi, D., Spallarossa, D., Picozzi, M., and Bindi, D.: Real-time monitoring of seismic moment and radiated energy, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19253, https://doi.org/10.5194/egusphere-egu2020-19253, 2020.

The Italian Seismic Network (IV) consists of more than 500 stations located throughout the Italian territory.

The detection capability of  network is constrained by its location performance that is affected by the seismic noise levels variations depending on the characteristics of the dominant source. Discriminating the noise level in each stations may allow to improve in its performance, in order to reduce noisy stations to detect even the smaller energetic seismic events sometimes hidden by high noise values. The main goal of this research has been to establish the characteristics (frequency content) and origin of seismic noise background at these sites and secondly to assess the effects of performance of the network.

For this purpose we have estimated the Power Spectral Density (PSD) of seismic noise selecting only a subset of 233 stations equiped with broadband velocimeters (with minimum period of 40 seconds and with a high sensitivity until to 120s) and operating at least three consecutive years of available data (2015-2017).

The variations of seismic background noise have been investigated using also the relative Probability Density Funcionts (PDF). The data processing of signals carried out with the robust method proposed by McNamara and Buland, (2004). In this study, the analysis was limited in the frequency band from 0.025 to 30 Hz, in accordance with the seismic sensors bandwidth. Four different frequency bands have been identified: 0.025-0.12, 0.12-1.2, 1.2-10 and 10-30 Hz. Each of these has been associated to a main type of source, in agreement with the literature.

A preliminary data analysis has been carried out to understand the statistical properties of the noise power, in the four class identified, both in space and frequency domains. Extracting  the PDFs  all stations, it was produced a representative seismic noise model that it could be considered as a new reference noise for Italian territory. Histograms have been computed for each band, both for vertical and horizontal components and its ratio. In addition, a spatial-statistical analysis was performed showing a good correlation of noise level with some weather conditions and anthropogenic source. Several clustering techniques were applied to the data to identified group of stations with similar PSD level, attributable to the same noise source. Furthermore, a correlation between the noise found at the different stations and spatial data (maps of rainfall, winds, coastlines, ect…) was carried out for a better characterization of the type of source.

How to cite: Catania, M., D'Alessandro, A., Greco, L., Martorana, R., and Scudero, S.: Seismic noise analysis of broadband stations of the Italian Seismic Network by Power Spectral Density, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20268, https://doi.org/10.5194/egusphere-egu2020-20268, 2020.

Ambient noise seismology has greatly reduced the cost of acquiring data for seismic monitoring and imaging by reducing the need for active sources. For applications requiring time-lapse imaging or continuous monitoring, we desire sensor arrays that require little effort, money, and power to maintain over long periods of time. Distributed Acoustic Sensing repurposes a standard fiber optic cable as a series of single-component strain rate sensors with spacing at the scale of meters over distances of kilometers. With a single location providing the power source and recording all data, along with the ability to use existing underground fiber optic networks, a small team is now able to easily establish a monitoring network and acquire massive amounts of strain rate data continuously.

This talk will explore two conceptual changes when using DAS data for ambient noise interferometry: greatly increased data volumes, and the difference between velocity and distributed strain-rate data. These two challenges will be illustrated in the context of experiments with applications in near-surface Vs imaging with applications in earthquake hazard analysis, permafrost thaw monitoring, and urban geohazard and hydrology monitoring.

On the issue of data volumes: Orders of magnitude more sensors and high sample rates (often in the kilohertz range) quickly result in data quantities that exceed the limits of computational infrastructure and algorithms available to many seismologists, potentially at the petabyte/year scale for modern acquisition instruments. New algorithms focused on reduced data movement are improving our ability to analyze more data with existing resources. This talk will include a brief overview of some recent algorithmic improvements for both ambient noise interferometry for imaging, and interferometry-based event detection.

On the issue of changing from velocity to distributed strain rate data: Because strain rate is a tensor quantity and velocities are a vector quantity, the sensitivity of DAS to seismic sources at different orientations is quite different from typical seismometers. This difference can be clear both in polarity and amplitude of the signal, and is particularly significant in shear and Love wave recordings. We will describe simple models to describe expected changes in how seismometers and DAS record the same noises, and the corresponding changes expected in noise correlation functions. These sensitivity differences are more pronounced in ambient noise correlation functions than they are in raw signal recordings, effectively emphasizing a different distribution of ambient noise sources. Modeling these sensitivities helps determine which sensor orientations are reliable for use in ambient noise interferometry imaging.

How to cite: Martin, E., Lindsey, N., Biondi, B., Ajo-Franklin, J., and Zhu, T.: What changes when we use ambient noise recorded by fiber optics? , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6022, https://doi.org/10.5194/egusphere-egu2020-6022, 2020.

Measuring seismic and acoustic signals on seafloor telecom cables has proven recently its very high potential for earthquake monitoring but also for beter understanding the interaction between the oceans and the solid earth. A consequence of these interactions is the generation of the primary and secondary microseismic noise on coastal regions and in the deep ocean respectively. These seismic noises that propagate across continents are central to a large fraction of todays' seismic imagery and monitoring campaigns. Compared to previous studies and instrumentation setups, acoustic sensing over oceanic telecom cables offer the unique ability to measure in a very dense manner waves that are generated on the seafloor. We analyse a week long record of ambient noise measurements on the 41.5 km-long seafloor telecom cable offshore Toulon, south of France. At shallow depth, close to the coast, we measure the pressure changes caused by the oceanic gravity waves. The bottom pressure is then compared to an oceanographic buoy located a few kilometers away from the cable. The amplitude and frequency of the pressure are modulated by the gravity waves height and dominant periods. This observation opens the way for a distributed measurement of the oceanic waves characteristics over several kilometers. At depth larger than a 1km, we observe Scholte waves at the ocean-solid earth interface produced by the non-linear interaction of gravity waves. These waves have the double frequency of the gravity waves seen at the coast. We find that the amplitude and frequency change over time, as do the gravity waves observed near the coast. The frequency-wave number decomposition of the signal reveals that the apparent velocity of the Scholte waves does not depend of the azimuth of the fiber. These observations confirm that these deep Scholte waves are secondary microseismic noise, generated locally from the interaction of landward gravity waves with oceanward gravity wave reflected on the coast. Spatially distributed monitoring of the ambient noise wave field at the ocean-solid earth interface provides a better understanding of the noise generation and therefore will allow a better modeling of the ambient noise in the future.

How to cite: Rivet, D., Guérin, G., Mata, D., Lior, I., Sladen, A., and Ampuero, J.-P.: In-situ microseism noise generation measured from distributed acoustic sensing on seafloor optical cable, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11124, https://doi.org/10.5194/egusphere-egu2020-11124, 2020.

The interactions of wind with the ocean surface, ocean wave with acoustic wave, acoustic wave with seismic wave below the sea bottom, and the interplay among them drive important energy flows from the atmosphere to the lithosphere. Uncertainty remains regarding the origin of wind-related noise in the ocean and its coupling to seismic noise below the sea floor. Seismic interferometry is a powerful tool that uses microseisms, or ambient noise within solid earth, to monitor temporal seismic velocity change by referring to the auto/cross-correlation as a Green’s function at the sites, and its temporal change. The most important assumption when detecting seismic velocity changes with seismic interferometry is that mutually uncorrelated noise sources are distributed randomly in space and time without any temporal changes in their density and intensity in a fully diffuse wave field. An effect of temporal variation on the ambit noise field to the retrieval of Green’s function is, however, not fully understood, nor is how reliable temporal changes in interferogram noise are, especially when accompanied by large earthquakes and slow slip events. Here, we show relationships among the temporal changes of sea surface wave, acoustic wave, and seismic wave fields, which are observed in ocean bottom pressure gauges and seismometer arrays installed in New Zealand. The temporal variation in the power spectrum obtained from continuous ocean bottom seismometer and pressure records near 200 mHz correlates with the temporal variation in wind speed above the sites, particularly during wind turbulence of more than 5 m/s. The temporal fluctuation in the ocean bottom pressure caused by the ocean surface wave field correlates to that of a microseism near 200 mHz. The temporal variations in the power spectrum from both continuous ocean bottom pressures and microseisms in the 200–800 mHz range show a positive correlation. After calculating the auto/cross-correlation functions (ACF/CCF) from ambient noise in a 200–800 mHz pass band every 6 h, the temporal variation in the correlation between the ACF/CCFs is investigated every 6 h. The temporal variation in the ACF/CCFs correlates with the time derivative of the temporal changes in the power spectrum amplitude of both the bottom pressure and the microseism rather than the temporal changes in the amplitude of the power spectrum. This suggests that the temporal change that occurs in the seismic interferogram owing to ambient noise, is mostly controlled by the temporal change in the ocean wave field undergoing fluctuations by the atmospheric turbulence over the sea surface. The temporal variations in the noise field in space and time may break the assumption on seismic interferometry, and eventually make the apparent temporal change in interferogram noise.

How to cite: Ito, Y., Uemura, M., Webb, S. C., Mochizuki, K., and Henrys, S.: Ambient noise field and temporal changes on ambient noise auto/cross-correlogram at the sea bottom inferred from ocean-bottom seismic and pressure arrays, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6159, https://doi.org/10.5194/egusphere-egu2020-6159, 2020.

Beamforming and backprojection methods offer a data-driven approach to image noise sources, but provide no opportunity to account for prior information or iterate through an inversion framework. In contrast, recent methods have been developed to locate ambient noise sources based on cross-correlations between stations and the construction of finite-frequency kernels, allowing for inversions over multiple iterations (i.e., Tromp et al., 2010, Ermert et al. 2017, Sager et al. 2018). These kernel-based approaches show great promise, both in mathematical rigour and in results, but may remain difficult to understand or implement for the wider community. Here we show that these two different classes of methods, beamforming and kernel-based inversion, are achieving exactly the same result in certain circumstances. This means existing beamforming and backprojection methods can also incorporate prior information in a mathematically correct manner.

We start with a description of a relatively simple beamforming or backprojection algorithm, based on time-domain shifting and measurement of waveform coherence. Only by changing the order of steps, we begin to resemble the kernel-based approaches. By adding a physical model for the distribution of noise sources, and therefore synthetic correlation functions, we can extend backprojection to an iterative, gradient-based inversion scheme. Adjoint methods and a direct simulation of correlation wavefields can later be used to increase computational efficiency, but we stress that these are not needed to understand the approach.

Given the equivalence of these approaches between these two communities, both sides can benefit from bridging the gap. For example, for kernel-based inversion schemes, a current challenge lies in defining the misfit and time window over which a correlation will be scored; a windowing function based on beamform images offers a more intuitive way to identify significant contributions in the noise wavefield, exploiting more than just the direct surface-wave arrivals.

How to cite: Bowden, D., Sager, K., Fichtner, A., and Chmiel, M.: On the link between Beamforming and Kernel-based Source Inversion, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15228, https://doi.org/10.5194/egusphere-egu2020-15228, 2020.

Wind turbines (WTs) have proven to be an increasingly cost-efficient source of sustainable energy. With further cost reductions and growth of environmental awareness, the amount and size of WTs will further expand. In the seismic literature, WTs have mainly been considered a threat rather than an opportunity. WTs act as infrasound and seismic sources, whose wavefield might overwhelm signal from earthquakes. Rather than focusing on the detrimental effects, we embrace the WT revolution and focus on the novel possibilities of the WT seismic source. We show detailed characteristics of this source using recordings over the Groningen seismic network. We further show examples of using the WT seismic noise for extracting medium parameters. Moreover, we exploit the repeatable nature of the source for subsurface monitoring.

How to cite: Ruigrok, E., Jagt, L., and van der Vleut, B.: Exploiting wind-turbine noise for seismic imaging and monitoring, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11208, https://doi.org/10.5194/egusphere-egu2020-11208, 2020.

The theory of ambient seismic noise interferometry offers techniques to retrieve estimates of inter-receiver responses from continuously recorded ambient seismic noise. This is usually achieved by correlating and stacking successive noise panels over sufficiently long periods of time. If the noise panels contain significant body-wave energy, the stacked correlations expected to result in retrieved estimates of the body-wave responses, including reflections. Such application combined with a dense surface seismic array is promising for imaging the subsurface structures at lower cost and lower environmental impact as compared to with controlled seismic sources. Subsequently, this technique can be an alternative to active-source surveys in a range of challenging scenarios and locations, and can also be used to perform time-lapse subsurface characterization.

In this study, we apply seismic body-wave noise interferometry to 30-days of continuous records from a surface line of 31 receivers spaced by 25 meters in the South of the Netherlands with the aim to image subsurface reflectors, at depths from a few hundreds of meters to a few kilometers. As a first step, we compute stacked auto-correlations and compare the retrieved zero-offset section with a co-located stacked section from a past active reflection survey on the site.

Yet, the retrieval of reflectivity estimates relies on the identification and collection of a sufficient number of noise panels with recorded body waves that have travelled from the subsurface towards the array. Even in the case of favorable body-wave noise conditions, the panels are most often contaminated with stronger anthropogenic coherent seismic noise, mainly in the form of surface waves, which in turn prevents the stacked correlations to reveal reflectivity. Because of the limited effect of frequency filtering, the application of seismic body-wave noise interferometry requires in fact extensive effort to identify noise panels without prominent coherent noise from the surface activity. Typically, this leads to disregard a significant amount of actually useful data.

For this reason, we designed, trained and tested a deep convolutional neural network to perform this classification task more efficiently and facilitate the repetition of the retrieval method over long periods of time. We tested several supervised learning schemes to classify the panels, where two classes are defined, according to the presence or absence of prominent coherent noise. The retained classification models achieved close to 90% of prediction accuracy on the test set.

We used the trained classification models to correlate and stack panels which were predicted in the class with coherent noise absent. The resulting stacked correlations exhibit potential reflectors in a larger depth range than previously achieved. The results show the benefits of using machine learning to collect efficiently a maximum amount of favorable noise panels and a way forward to the upscaling of seismic body-wave noise interferometry for reflectivity imaging.

How to cite: Boullenger, B., de Bakker, M., Verdel, A., and Carpentier, S.: Retrieval of reflectivity images from ambient seismic noise correlations using machine learning as a noise-panel classification tool, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1680, https://doi.org/10.5194/egusphere-egu2020-1680, 2020.

The overall purpose of the recently finalized GEMex project*, a European-Mexican collaboration, has been to gain an improved understanding of the subsurface at two unconventional geothermal sites: for EGS development at Acoculco and for a superhot resource near Los Humeros. Providing a more precise description of both the geological structure and the geothermal reservoir behavior for these two sites form important requirements for achieving that goal.

For delineating the main structural features at geothermal reservoir level, reflection retrieval from ambient seismic noise can be considered interesting because of its relatively low-cost and low environmental impact as compared to more conventional, controlled-source, seismic surveying practice, where (expensive) active sources are required.

In this study, we present results from the application of ambient noise seismic interferometry (ANSI) to retrieve zero-offset reflected P-waves from continuous seismic data recorded during the second half of 2017 at the Los Humeros geothermal field, Mexico. It is known from noise interferometry theory that reflected P-waves can provide local structural detail at locations directly underneath the employed seismic stations.

We address various data selection and processing aspects related to the retrieval of these reflected P-waves. The reflections are thereafter compared with modelled reflectivities at station locations with sufficient data availability, data quality and proximity to a location at which seismic interval velocity information is available from the literature.

From our study it can be concluded that the ANSI auto-correlation technique that was applied for zero-offset reflectivity retrieval at the Los Humeros site indeed can provide relatively high structural detail: for near-horizontal reflectors in the close vicinity of the selected stations, local depth-estimates of seismic velocity-contrasts were determined. This information can be used to constrain both the geological structure and geothermal reservoir property description.

As such, results from this passive-seismic method may partially complement and partially confirm subsurface information derived from active-seismic, that can only be acquired at a higher cost, which is more labor-intensive and which has more impact on the environment.

We thank the Mexican GEMex team around Angel Figueroa Soto from UMSNH and Marco Calo from UNAM for setting up the seismic network and station maintenance as well as data retrieval. The Comisión Federal de Electricidad (CFE) kindly provided us with access to their geothermal field and permission to install the seismic stations. OGS is thanked for providing us the location details of the four active seismic lines. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 727550 and the Mexican Energy Sustainability Fund CONACYT-SENER, project 2015-04-68074.

* http://www.gemex-h2020.eu/index.php?option=com_content&view=featured&Itemid=101&lang=en

How to cite: Verdel, A., Boullenger, B., E. Martins, J., Obermann, A., Toledo, T., and Jousset, P.: Structural delineation at the Los Humeros geothermal field, Mexico, by P-wave reflection retrieval from noise, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7324, https://doi.org/10.5194/egusphere-egu2020-7324, 2020.

With the advent of large and dense seismic arrays, there is an opportunity for novel inversion methods that exploit the information captured by stations in close proximity to each other. Estimating surface waves dispersion is an interest for many geophysical applications using both active and passive seismic data. We present an inversion scheme that exploits the spatial and temporal relationships of the Helmholtz equation to estimate dispersion relations directly from surface wave ambient noise data, while reconstructing the full wavefield in space and frequency. The scheme is a PDE constrained inverse problem in which we jointly estimate the state and parameter spaces of the seismic wavefield. Key to the application on ambient seismic noise recordings is to remove the boundary conditions from the PDE constraint, which renders a conventional waveform inversion formulation singular. With synthetic acoustic and elastic data examples we show that using a variable projection scheme, we can iteratively update an initial estimate of the medium parameters and recover an estimate for the true underlying velocity field. Our examples show that the we can reconstruct the full wavefield even in the case of strong aliasing and irregular sampling. This works forms the basis for a new approach to inverting ambient seismic noise using large and dense seismic arrays.

How to cite: de Ridder, S. A. L., Maddison, J. R., Shaiban, A., and Curtis, A.: Wavefield reconstruction inversion for ambient seismic noise, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22018, https://doi.org/10.5194/egusphere-egu2020-22018, 2020.

The ambient seismic noise has proven to be a powerful tool to assess velocity changes within the ground using coda-wave interferometry (CWI). CWI is based on the analysis of small waveform changes in the coda of the signals. Localizing and imaging the source that generates changes can be done with the help of sensitivity kernels which contain information on how each part of the surrounding medium contributes to the overall waveform perturbation that is recorded at a receiver. Although progress has been made in the theory of sensitivity kernels in the case of a full elastic space,  the inclusion of a free surface has proven to be difficult. Indeed, the free surface couples body waves and surface waves, which affects the sensitivity of coda waves with respect to the full-space case. Furthermore, one expects the depth sensitivity of coda waves to be strongly dependent on the relative contribution of surface and body waves, which depends on the lapse-time, source-receiver distance and scattering properties of the medium. Using the Monte-Carlo method, we compute traveltime-sensitivity kernels in a 3D scalar problem that includes body and surface waves, based on a recent theoretical model that integrates both through a mixed boundary condition. From these results, we assess the impact of the depth of a velocity perturbation on the recorded signals at the surface. Our results will be compared with previous numerical approaches from the literature. 

How to cite: Barajas, A., Margerin, L., and Campillo, M.: Sensitivity kernels for coda-wave interferometry in a three-dimensional scalar scattering media, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20890, https://doi.org/10.5194/egusphere-egu2020-20890, 2020.

Between 2013 and 2017, the Groningen gas field was monitored by several deployments of an array of geophones in a deep borehole at reservoir level (3 km). Zhou & Paulssen (2017) showed that the P- and S-velocity structure of the reservoir could be retrieved from noise interferometry by cross-correlation. Here we show that deconvolution interferometry of high-frequency train signals from a nearby railroad not only allows determination of the velocity structure with higher accuracy, but also enables time-lapse measurements. We found that the travel times within the reservoir decrease by a few tens of microseconds for two 5-month periods. The observed travel time decreases are associated to velocity increases caused by compaction of the reservoir. However, the uncertainties are relatively large. 
Striking is the large P-wave travel time anomaly (-0.8 ms) during a distinct period of time (17 Jul - 2 Sep 2015). It is only observed for inter-geophone paths that cross the gas-water contact (GWC) of the reservoir. The anomaly started 4 days after drilling into the reservoir of a new well at 4.5 km distance and ended 4 days after the drilling operations stopped. We did not find an associated S-wave travel time anomaly. This suggests that the anomaly is caused by a temporary elevation of the GWC (water replacing gas) of approximately 20 m. We suggest that the GWC is elevated due to pore-pressure variations during drilling. The 4-day delay corresponds to a pore-pressure diffusivity of ~5m²/s, which is in good agreement with the value found from material parameters and the diffusivity of (induced) seismicity for various regions in the world. 

How to cite: Paulssen, H. and Zhou, W.: Time-lapse changes within the Groningen gas field caused reservoir by compaction and distant borehole drilling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3567, https://doi.org/10.5194/egusphere-egu2020-3567, 2020.

To create virtual shot gather from passive signals it is essential to cross-correlate all the signals with the reference trace. Since surface sources dominate the origin of seismic noise, the correlated sections are highly dominated by surface waves. If the target is surface wave inversion general cross-correlation will suit the target. But if the extraction of body waves from those signals is the main objective, coherent ground roll events mask the body waves making it difficult to extract them. To tackle this issue a frequency-spatial nonCoherent filter (FX-NCF) plus a post-correlation processing module are introduced. FX-NCF is a prediction filter and the filter operator is a function of frequency, station interval and the slope of the interested event. In the frequency domain, the filter is looking for the prediction of n-th trace coherence spectrum from the (n-1)-th signal’s coherence spectrum by minimizing the objective function. Hybrid norms used to minimize the error. The coherence spectrum of each trace is the coherency between the reference signal and the desired trace. Applying the FX-NCF on 2D real recorded passive signals shows its superiority over general cross-correlation, deconvolution interferometry, cross-coherence and multi-taper-method-coherence-estimation methods in highlighting surface and body waves also improving the signal-to-noise (S/N) ratio. To show the necessity of post correlation processing (before applying on real recorded signals) to highlight reflection events, hyperbolic Radon transform (HRT) as a suitable post-correlation module applied on correlated section due to applied FX-NCF on simulated passive signals from a simple 2D synthetic model. The result encouraged us to apply the same hybrid modules (FX-NCF plus HRT) on real recorded passive signals to reconstruct wanted reflection events.

How to cite: Hariri Naghadeh, D. and Bean, C.: Retrieving the Reflection events from passive signals , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-43, https://doi.org/10.5194/egusphere-egu2020-43, 2020.

Seismic interferometry is widely applied in various scales to reconstruct seismic signals for investigating Earth interior. The method of Phase Cross Correlation (PCC) takes less pre-processing and is more stable for retrieving of crustal signals than that of the conventional cross correlations by using amplitude information. In order to obtain the crustal reflectors in Taiwan, we applied auto-correlation with PCC to two independent datasets, (1) temporary seismic array in eastern Taiwan with 110 short period seismometers and (2) broadband seismic arrays (BATS and TAIGER) in Taiwan. As a result, the retrieved crustal reflectors, such as Moho reflectors, are stable with different recording time periods and instruments: temporal and spatial signal consistencies in the same site and neighborhood stations, respectively, and also high waveform similarities between short period and broadband seismometers.

Comparing the results with previous studies of velocity model and receiver function, the reflections at 10-12 seconds (roughly 30-40 km) are often observed in most of the results which are correlated to the Moho depths inferred from the receiver function and tomography studies. It is interesting to note that, besides the Moho reflections, some inter-crustal reflectors beneath the Central Range are revealed. The results show that the autocorrelation method has the potential to investigate some signals that are difficult to observe in the past by using other methods.

Another interesting observation from a dense seismic array in eastern Taiwan shows that the chimei fault serves as a sharp boundary to separate the reflectional signals into the northern and southern parts. In the southern part few reflections can be observed and also lack high frequency energies from autocorrelation comparing with those in the northern part. It implies that the distribution of ambient sources or near surface materials could influence the results. After examining the PCC’s feasibility and stability in this study, it is necessary to verify the reliability of results by understanding the source’s properties and local geological situations before interpretation.

How to cite: Guan, Z.-K. and Kuo-Chen, H.: Investigating the crustal reflections of Taiwan from autocorrelation of seismic noise, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21542, https://doi.org/10.5194/egusphere-egu2020-21542, 2020.

In recent years, seismic interferometry (SI) has been widely used in passive seismic data, it allows to retrieve new seismic responses among physical receivers by cross-correlation or multidimensional deconvolution (MDD). Retrieval of reflected body waves from passive seismic data has been proved to be feasible. Marchenko method, as a new technique, retrieves Green’s functions directly inside the medium without any physical receiver there. Marchenko method retrieves precise Green’s functions and the up-going and down-going Green’s functions can be used in target-oriented Marchenko imaging, and internal multiples related artifacts in Marchenko image can be suppressed. 

Conventional Marchenko imaging uses active seismic data, in this abstract, we propose the method of passive seismic Marchenko imaging (PSMI) which retrieves Green’s functions from ambient noise signal. PSMI employs MDD method to obtain the reflection response without free-surface interaction as an input for Marchenko algorithm, such that free-surface multiples in the retrieved shot gathers can be eliminated, besides, internal multiples don’t contribute to final Marchenko image, which means both free-surface multiples and internal multiples have been taken into account. Although the retrieved shot gathers are contaminated by noises, the up-going and down-going Green’s functions can be still retrieved. Results of numerical tests validate PSMI’s feasibility and robustness. PSMI provides a new way to image the subsurface structure, it combines the low-cost property of passive seismic acquisition and target-oriented imaging property of Marchenko imaging, as well as the advantage that there are no artifacts caused by internal multiples and free-surface multiples.

Overall, the significant difference between PSMI and conventional Marchenko imaging is that passive seismic data is used into Marchenko scheme, which extends the Marchenko imaging to passive seismic field. Passive seismic Marchenko imaging avoids the effects of free-surface multiples and internal multiples in the retrieved shot gathers. PSMI combines the low-cost property of passive seismic acquisition and target-oriented imaging property of Marchenko imaging which is promising in future field seismic survey.

This work is supported by the Fundamental Research Funds for the Central Universities (JKY201901-03). 

How to cite: Jin, Z.: Passive Seismic Marchenko Imaging, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3413, https://doi.org/10.5194/egusphere-egu2020-3413, 2020.

How to cite: Ulrich, I.: Active Noise Tomography in Medical Ultrasound, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9140, https://doi.org/10.5194/egusphere-egu2020-9140, 2020.

Since the successful retrieval of surface-wave responses from the ambient seismic field via cross-correlation, noise-based interferometry has been widely used for high-resolution imaging of the Earth’s lithosphere from all around the globe. Further applications on geothermal fields reveal the potential of ambient noise techniques to either characterize the subsurface velocity field or to understand the temporal evolution of the velocity models due to field operations.

Following the completion of the GeMEX^* project, a European-Mexican collaboration to improve our understanding of two geothermal sites in Mexico, we present the results of ambient noise tomography (ANT) techniques over the Los Humeros geothermal field. We used the vertical component of the data recorded by the seismic network active from September 2017 to September 2018. The total network is composed of 45 seismometers from which 25 are Broadband (BB) and the remaining ones short-period stations. From the ambient noise recorded at the deployed seismic network, we extract surface-waves after the computation of the empirical Green’s functions (EGF) by cross-correlation and consecutive stacking. After the cross-correlations, we pick both phase and group velocity arrival times of the ballistic surface-waves for which we derive independent tomographic maps. Finally, using both the retrieved phase and group velocities, we jointly invert the tomographic results from frequency to depth.

We identify positive and negative velocity variations from an average velocity between -15% and 15% for group and between -10% and 10% for phase velocities in the frequency domain. While the velocity variations are consistent for both the phase and group velocities (with expected group velocities lower than the phase velocities), the group velocity anomalies are more pronounced than the phase velocity anomalies. Low-velocity anomalies fall mostly within the inner volcano caldera, the area of highest interest for geothermal energy. This is consistent with the surface temperatures measured at the Los Humeros caldera, indicating the presence of a heat source. Finally, we compare our results with other geophysical studies (e.g geodesy, gravity, earthquake tomography and magnetotelluric) performed during the GeMEX project within the same area.

We thank the European and Mexican GEMex team for setting up the seismic network and station maintenance as well as data retrieval (amongst which Tania Toledo, Emmanuel Gaucher, Angel Figueroa and Marco Calo). We thank the Comisión Federal de Electricidad (CFE) who kindly provided us with access to their geothermal field and permission to install the seismic stations. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 727550 and the Mexican Energy Sustainability Fund CONACYT-SENER, project 2015-04-68074.

* http://www.gemex-h2020.eu/index.php?option=com_content&view=featured&Itemid=101&lang=en

How to cite: Martins, J., Obermann, A., Verdel, A., and Jousset, P.: 3D-S wave velocity model of the Los Humeros geothermal field, Mexico, by ambient-noise tomography , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21956, https://doi.org/10.5194/egusphere-egu2020-21956, 2020.

One of the aims of project SIGHT (SeIsmic and Geochemical constraints on the Madeira HoTspot system) is to obtain a 3D model of SV-wave velocities of the crust and upper mantle of the Northeast Atlantic area encompassing Madeira and Canary Islands to the Atlas-Gibraltar zone, using seismic noise cross-correlations in the period range 2-100 s. Ambient noise cross-correlation has been successfully applied in a variety of tectonic environments to image the structure of the Earth subsurface. This technique overcomes some limitations ascribed to source–receiver geometry and sparse and irregular earthquake distribution, allowing to image Earth structure with a resolution that mainly depends on the network design. However, the effect of the water layer in the short period Empirical Green Functions, which are obtained by seismic noise cross-correlation, for interstation paths crossing the ocean is still poorly understood.

In several studies, it has been observed that the presence of water and sediments is responsible for later wave-train arrivals. Those later arrivals are frequently disregarded when measuring group velocity, either by considering only longer periods or by specifying a given velocity range.

In this work, we present a systematic study of the influence of the water layer on both vertical and radial synthetic Rayleigh waves, as well as on higher-mode conversion and on the group velocities dispersion measurements.

We show that although the fundamental mode dominates, the presence of the first overtones at short periods (typically below 8 seconds) cannot be neglected. We also show that specifying a given velocity range when retrieving group velocity can result in a mixture of modes. Our tests reveal that, at short periods, the water has a dominant effect on ocean-continent laterally varying media.

This is a contribution to projects SIGHT (Ref. PTDC/CTA-GEF/30264/2017) and STORM (Ref. UTAP-EXPL/EAC/0056/2017). The authors would like to acknowledge the financial support FCT through project UIDB/50019/2020 – IDL.

How to cite: Silveira, G., Carvalho, J., Pinzon, J., Custódio, S., Corela, C., and Matias, L.: Effect of the water layer on seismic noise cross-correlation across the Northeast Atlantic, from Madeira and Canaries to the Atlas-Gibraltar zone, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18561, https://doi.org/10.5194/egusphere-egu2020-18561, 2020.

The performances and sensitivity of gravitational wave (GW) detectors are significantly affected by the seismic environment. In particular, the seismic displacements and density fluctuations of the ground due to seismic-wave propagation introduce noise in the detector output signal; this noise is referred to as gravity-gradient noise, or Newtonian Noise (NN). The development of effective strategies for mitigating the effects of NN requires, therefore, a thorough assessment of seismic wavefields and medium properties at and around the GW detector. In this work, we investigate wave propagation and the subsurface velocity structure at the Virgo GW detector (Italy), using data from a temporary, 50-element array of vertical seismometers. In particular, we analyze the recordings from the catastrophic Mw=6.2 earthquake which struck Central Italy on August 24, 2016, and six of the following aftershocks.  The general kinematic properties of the earthquake wavefields are retrieved from the application of a broad-band, frequency-domain beam-forming technique. This method allows measuring the propagation direction and horizontal slowness of the incoming signal; it is applied to short time windows sliding along the array seismograms, using different subarrays whose aperture was selected in order to match different frequency bands. For the Rayleigh-wave arrivals, velocities range between 0.5 km/s and 5 km/s, suggesting the interference of different wave types and/or multiple propagation modes. For those same time intervals, the propagation directions are scattered throughout a wide angular range, indicating marked propagation effects associated with geological and topographical complexities. These results suggest that deterministic methods are not appropriate for estimating Rayleigh waves phase velocities. By assuming that the gradient of the displacement is constant throughout the array, we then attempt the estimation of ground rotations around an axis parallel to the surface (tilt), which is in turn linearly related to the phase velocity of Rayleigh waves. We calculate the ground tilt over subsequent, narrow frequency bands. Individual frequency intervals are investigated using sub-arrays with aperture specifically tailored to the frequency (wavelength) under examination. From the scaled average of the velocity-to-rotation ratios, we obtain estimates of the Rayleigh-wave phase velocities, which finally allow computing a dispersion relationship. Due to their diffusive nature, earthquake coda waves are ideally suited for the application of Aki’s autocorrelation method (SPAC). We use SPAC and a non-linear fitting of correlation functions to derive the dispersion properties of Rayleigh wave for all the 1225 independent inter-station paths. The array-averaged SPAC dispersion is consistent with that inferred from ground rotations, and with previous estimates from seismic noise analysis.  Using both a semi-analytical and perturbational approaches, this averaged dispersion is inverted to obtain a shear wave velocity profile down to ~1000m depth. Finally, we also perform an inversion of the frequency-dependent travel times associated with individual station pairs to obtain 2-D, Rayleigh wave phase velocity maps spanning the 0.5-3Hz frequency interval. 

How to cite: Saccorotti, G., Gaviano, S., Giunchi, C., Fiori, I., Koley, S., and Van den Brand, J.: Wave propagation and subsurface velocity structure at the Virgo gravitational wave detector (Italy), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21852, https://doi.org/10.5194/egusphere-egu2020-21852, 2020.

Although train-induced vibrations are mainly regarded as a source of unwanted noise for classical seismological applications, these vibrations act as powerful sources for seismic imaging using seismic interferometry. Most of the seismic interferometry studies to date have concentrated on using the ambient seismic field generated by natural processes but the appropriate use of train-induced vibrations could result in higher resolution images.

In this study, we present results of seismic interferometry applied on 3 days of railroad traffic data recorded by an array of 3-component seismographs along a railway in Dublin, Ireland. Train-generated waves show a significantly higher frequency range than those recovered from typical ambient noise interferometry. Analysing the recorded signal, we have been able to distinguish between different train types (e.g. cargo vs. passenger trains) and train lengths (3-4, 5-6, 7-9, and/or 10-11 wagons).

For seismic interferometry, a Common Mid-Point – Cross-Correlation (CMP-CC) stack approach has been used to directly image the structures beneath the array. This approach produces a reflection image with interfaces consistent with nearby borehole data at ~450-500 m and ~1350-1400 m depth.

In addition to this reflection image, our results document a strong relation between the ambient source location (trains in this case) and the retrieved seismic reflection image. Since we have train location GPS data, we extracted 2-s time windows for when the train is 1500 m, 1000 m, and 500 m away from the first sensor and we applied the CMP-CC procedure to produce reflection images. As expected, the reflection images are sensitive to the location of the ambient noise source.

Numerical forward modelling of seismic wavefields for various source-receiver configurations also documents a strong correlation between the source location and the retrieved reflection image.

This research emanates from PACIFIC - Passive seismic techniques for environmentally friendly and cost-effective mineral exploration - which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No~776622. We also acknowledge support from the European Research Council under grant No.~817803, FAULTSCAN.

How to cite: Rezaeifar, M., Maggio, G., Xu, Y., Bean, C., Lavoué, F., Boué, P., Pinzon-Rincon, L., and Brenguier, F.: Imaging shallow structures in Dublin city using seismic interferometry of seismic waves generated by train traffic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16678, https://doi.org/10.5194/egusphere-egu2020-16678, 2020.

Trains have recently been recognised as powerful sources for seismic imaging and monitoring based on the correlation of continuous noise records, but the optimal use of these signals still requires a better understanding of their source mechanisms. In this study, we present a simple approach for modelling train-generated seismic signals inspired from early work in the engineering community, which assumes that seismic waves are emitted by  sleepers regularly spaced along the railway and excited by the passage of the train wheels. 
     As already known in the engineering literature, we exemplify the importance of the spatial distribution of each axle load over the rail track on the high-frequency content of the corresponding source time functions, and therefore of the final seismograms resulting from the contributions of all sleepers. In practice, this high-frequency content mainly depends on ground stiffness beneath the railway.
     Furthermore, we identify two end-member mechanisms to explain the two types of observations documented in the seismological literature. The first is the case of a single stationary source (fixed sleeper) excited by successive wheels of a train. This generates a harmonic spectrum characterised by a narrow spacing between frequency peaks related to a fundamental frequency f₁ = V_train / L_w controlled by train speed and wagon length. The second is the case of a single moving load (single wheel) exciting all sleepers along the railway. This also yields a harmonic spectrum, but with a larger spacing between frequency peaks, related to a fundamental frequency f₂ = V_train / Δ_sleeper  controlled by train speed and sleeper spacing. This moving source also generates a clear Doppler effect. 
     In more realistic cases, considering all wheels and all sleepers, our modelling well reproduces the observations, both in the frequency domain (harmonic spectra) and in the time domain (tremor-like emergent shapes). The dominance of the previously-identified end-member mechanisms depends on sleeper regularity: perfectly-regular sleepers generate signals dominated by the signature of a single moving load with fundamental frequency f₂ and a clear Doppler effect, while slightly-irregular sleepers generate signals dominated by the signature of stationary sources with fundamental frequency f₁. We speculate that our modelling parameter of sleeper regularity actually depends on the properties of the railway infrastructure in real cases.
     Finally, we discuss the perspectives of this work in view of using train-generated signals for seismic imaging and monitoring. In this regard, an important conclusion is that the frequency content of the signals is dominated by interferences between harmonic waves. Therefore, the exact value of the fundamental frequency at play matters less than the generation and preservation of the high frequencies, which depend on the distribution of the train load over the rail track and on propagation effects (medium heterogeneities, scattering and attenuation). Therefore, most of train traffic worldwide is expected to generate signals with a significant frequency content in the band [1 - 50] Hz of interest for seismic applications, in particular in the case of trains travelling at variable speeds which are expected to produce truly broadband signals. 

How to cite: Lavoué, F., Coutant, O., Boué, P., Pinzon-Rincon, L., Brenguier, F., Dales, P., Mordret, A., Rezaeifar, M., Bean, C., and Working Group, T. A.: Understanding seismic waves generated by train traffic via modelling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16828, https://doi.org/10.5194/egusphere-egu2020-16828, 2020.

The general objectives of the “Seismic Ambient Noise Imaging and Monitoring of Shallow Structures” (SANIMS) project, funded by the Spanish Ministry of Science, Research and Innovation (Ref.: RTI2018-095594-B-I00), are focused into the application and development of methods based on ambient noise seismic data recorded by dense networks to image and monitor natural and human-altered environments. To achieve this objective, temporal seismic networks have been installed since late 2019 in two very different settings; the Cerdanya Basin, a sedimentary basin located in the eastern Pyrenees and the city of Barcelona.

Regarding the Cerdanya Basin, a relatively unaltered setting, a network of up to 25 broad-band stations has been installed for a period of one year. Additionally, a high resolution grid of seismic nodes will be deployed for 2 months in the central part of the basin, with interstation distances of 1.5 km. In order to constraint the uppermost crustal structure using ambient noise, vertical component recordings will be processed using the phase cross-correlation and time-frequency domain phase-weighted stacking to extract fundamental mode Rayleigh waves. The surface waves will then be used to measure inter-station group and phase velocity dispersion curves that will be inverted using the Fast Marching Surface Tomography method. Depending on data quality, we will also process the horizontal components to extract Love waves for joint inversions with Rayleigh waves to constrain radial anisotropy and/or the application of new strategies to perform attenuation tomography.

Regarding areas strongly altered by human activity, we have deployed a network of 15 short-period stations within the city of Barcelona, in most of the cases installed in the basement of secondary schools, for a duration of 9-12 months. The objective of this deployment is twofold; acquire new valuable scientific data and introduce the students in an Earth Science research project. Although the Barcelona area has been investigated using MHVSR methods by different authors, the new data acquired by the SANIMS project will expand the available data and will allow to analyze the time variability of the measurements. This new dataset will also be used to analyze the applicability of the methods based on Rayleigh wave ellipticity inversion of ambient noise and earthquake data to provide S-velocity depth profiles. Under the assumption of an isotropic horizontally layered medium, the ellipticity inversion is not affected by the directivity of the diffusive noise wave field and seems therefore to be a good option to determine local S-velocity depth profiles in areas with little lateral inhomogeneities and uneven distribution of noise sources.

We expect that the use of ambient noise methods will allow to map the basement and to obtain new higher resolution ambient noise tomographic images of the upper crust in the Cerdanya Basin and to better constrain the subsoil properties of Barcelona, hence improving the existing seismic hazard maps. Besides, comparing the results in both areas will allow to compare the performance of the different methods based on ambient noise in quiet and noisy areas.

How to cite: Diaz, J., Schimmel, M., Ruiz, M., and Carbonell, R.: Testing the applicability of ambient noise methods in zones with different degree of anthropogenic sources., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3418, https://doi.org/10.5194/egusphere-egu2020-3418, 2020.

Laboratory experiments report that detectable seismic velocity changes should occur in the vicinity of fault zones prior to earthquakes. However, operating permanent active seismic sources to monitor natural faults at seismogenic depth has been nearly impossible to achieve. The FaultScan project (Univ. Grenoble Alpes, Univ. Cal. San Diego, Univ. South. Cal.) aims at leveraging permanent cultural sources of ambient seismic noise to continuously probe fault zones at a few kilometers depth with seismic interferometry. Results of an exploratory seismic experiment in Southern California demonstrate that correlations of train-generated seismic signals allow daily reconstruction of direct P body-waves probing the San Jacinto Fault down to 4 km depth. In order to study long-term earthquake preparation processes we will monitor the San Jacinto Fault using such approach for at least two years by deploying dense seismic arrays in the San Jacinto Fault region. The outcome of this project may facilitate monitoring the entire San Andreas Fault system using the railway and highway network of California. We acknowledge support from the European Research Council under grant No.~817803, FAULTSCAN.

How to cite: Brenguier, F., Mordret, A., Ben-Zion, Y., Vernon, F., Boué, P., Johnson, C., and Share, P.-E.: Passive seismic velocity monitoring of natural faults: The FaultScan project, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5480, https://doi.org/10.5194/egusphere-egu2020-5480, 2020.

The observations of seismicity, ground deformation, and volcanic gas geochemistry indicate a magmatic unrest of the Changbaishan volcano, northeast China between July 2002 and July 2005. In this study, we collected the continuous waveform data from more than 10 stations of permanent and portable networks around Changbaishan volcano area from 2000 to 2018, and studied the temporal velocity changes beneath the volcano based on both the cross-correlation of station pairs and auto-correlation of singe station method. We adopted the time-frequency domain phase weighted technique to speed up the convergence process of the noise-based Green's function, and improved the time resolution of monitoring from several tens of days to several days. We measured the temporal seismic velocity of the Changbaishan volcano in various frequency bands. The results shown that there were obvious seasonal changes of the seismic velocity for most frequency bands, and for 0.5-1 Hz frequency band a sudden velocity drop was observed starting on June 10, 2002 and the amplitude of velocity changes was up to 0.5%. After that, the number of volcanic events increased significantly. Our results suggest that there may be a precursory velocity drop phenomenon before the magma unrest, which is of great scientific significance for the studies of magma unrest and possible volcanic eruption in the future.

How to cite: Liu, Z.: Temporal changes of seismic velocity associated with a magmatic unrest of Changbaishan volcano, northeast China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6847, https://doi.org/10.5194/egusphere-egu2020-6847, 2020.

Monitoring temporal changes in seismic wavespeed can inform our understanding of the evolution of crustal rocks’ mechanical state caused by perturbations in stress field, damages, and fluids. Furthermore, imaging these time-lapse changes in space can help unravel the response of rocks with different elastic properties. In this study, we analyze the spatiotemporal variations of seismic wavespeed in Southern California from 2007 to 2017. We compute the Green’s functions by daily cross-correlations using ambient noise at over three hundred broadband seismic stations. Instead of calculating simply the linear regressions of travel-time shifts over lag-times, which only resolves homogeneous changes, we scrutinize the variations of travel-time shifts at different lag-times and frequencies using coda-wave sensitivity kernels, in order to probe the spatial distribution of wavespeed changes. The long-term and large-scale analysis allows us to investigate the mechanical response of different crustal materials to various transient processes. As an example we use the 2010 Mw 7.2 El Mayor-Cucapah Earthquake (EMC) and show that large coseismic wavespeed reductions occur in Salton Sea area and the Los Angeles sedimentary basin. In the latter region, the ground motion amplification and high susceptibility of sedimentary materials explain the remote signature of the earthquake. In the Salton Sea region, particularly in the geothermal area with highly pressurized fluids, the non-linear crustal response illustrated by wavespeed changes can be analyzed with regard to the high-level micro-seismicity triggered by EMC.

How to cite: Mao, S., Lecointre, A., Wang, Q., van der Hilst, R., and Campillo, M.: Noise-Based Monitoring of Spatiotemporal Changes in Crustal Seismic Wavespeed across Southern California, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12871, https://doi.org/10.5194/egusphere-egu2020-12871, 2020.

In this work, we use seismic noise autocorrelations to monitor the temporal evolution of the upper crust in Central Italia in order to look for changes that could have occured before the 2009 Mw6.3 l'Aquila and the 2016 Mw 6.2 Amatrice earthquake.

To that end, we use the Coherence of Correlated Waveforms [CCW] method, that consists in measuring changes in the waveform of autocorrelations with a temporal resolution of 5 days.

Our measurements of the CCW show that the L'Aquila Earthquake  is preceded by a 150-days oscillation whose amplitude and frequency progressively increases until the rupture. Analysing 17 years of data, we found that this signal occured only before the L'Aquila and the Amatrice earhtquake.  This suggests the existence of a unique nucleation process.

Finally, we compare the results obtained using the CCW method with the temporal evolution of the seismic waves velocity (dv/v) obtained by analysing the coda of seismic noise autocorrelations.

How to cite: Stehly, L., Delouche, E., Voisin, C., and Poli, P.: Looking for changes in the upper crust associated with large magnitude earthquakes in central Italia using seismic noise autocorrelations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9578, https://doi.org/10.5194/egusphere-egu2020-9578, 2020.

We report the temporal change of the near-surface(<400m) seismic structure of Taiwan revealed by coda interferometry. Following our earlier work (Chen et al., 2017), the Empirical Green’s Functions (EGF) of shear waves extracted from the earthquake coda recorded by the vertical pairs of borehole array, deployed by the Central Weather Bureau, are used to examine the temporal variations of vs and Vs azimuthal anisotropy at the borehole sites. In total, about 700 local events, from 2013 to 2018, are used in this study. The band-passed (3 – 8 hz) EGF extracted from each single event are stacked over variable time period to ensure the reliability of measurements and the desired temporal resolution. The averaged Vs and patterns of Vs azimuthal anisotropy are in good agreement with the site geology, the ambient stress and those reported in our early work. Apparent drop in the Vs isotropic velocities and perturbations in Vs azimuthal anisotropy are observed in few representative borehole sites, and we also noticed that such variations are tightly correlated with the occurrence of major earthquakes in Taiwan. We present the preliminary results and discuss the triggering mechanisms, the healing revolution, and their relationship with the site geology.

How to cite: Cai, S.-J., Chen, L.-W., Lee, H.-Y., Chen, Y.-N., and Gung, Y.-C.: Temporal Variations of Near-surface seismic structure of Taiwan revealed by coda interferometry, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15135, https://doi.org/10.5194/egusphere-egu2020-15135, 2020.

To understand fault systems, it is required to identify the structure of the crust and upper mantle. Seismic investigations have long been relying on active sources generating an incident wave-field from the Earth surface. The reflected wave-field is then recorded by sensors deployed at the surface. Nowadays, passive imaging has been adopted as an alternative of this source-receiver configuration by computing the correlations of ambient noise. This process allows to estimate the Green’s function between two receivers. We here present a passive imaging technique applied to data recorded with the Dense Array of North Anatolia [1], which was deployed in western Turkey during 16 months. The array consists of 73 stations covering the two major fault branches of the North Anatolian Fault (NAF). Inspired by previous works in optics and acoustics, we introduce a matrix approach of seismic imaging based on seismic noise cross correlations. Our method applies focusing operations at emission and reception (Blondel et al.,2019) allowing to project the reflection matrix recorded at the surface to depth (redatuming). Although seismic noise is dominated by surface waves, focusing operations allow to extract the body wave components that carry information about the reflectivity of in-depth structures. However, complex velocity distribution of the Earth’s crust results in phase distortions, referred to as aberrations in the imaging process. Phase distortions prevent the imaging of the true reflectivity of the subsurface leading to unphysical features and blurry images. To overcome these issues, we introduce a new operator: the so-called distortion matrix. It connects any virtual source induced by focusing at emission with the distorted part of the reflected wave-front in the spatial Fourier domain. A time-reversal analysis of the distortion matrix allows to correct for high-order aberrations. Crustal-scale 3D images of the fault structure of the North Anatolian Fault are revealed with optimal resolution and contrast.

(1) DANA. Dense array for north anatolia. International Federation of Digital Seismograph Networks doi:10.7914/SN/YH2012, 2012.

How to cite: Touma, R., Campillo, M., Aubry, A., and Blondel, T.: Passive Reflection Seismic Imaging of the North Anatolian Fault at crustal-scale: A Matrix Framework for Aberrations Correction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18923, https://doi.org/10.5194/egusphere-egu2020-18923, 2020.

Monitoring of temporal seismic velocity changes can provide us with information on the mechanical state of the Earth’s crust due to processes of stress build-up and release. 

In current work, we use the Dense Array of North Anatolia [1], which has been continuously recording from May 2012 until October 2013, to analyse the spatio-temporal variations of seismic velocity changes in the North Anatolian Fault zone (NAF). We compute daily ambient-noise cross-correlation functions for all 63 three-component stations in the frequency band between 0.1 – 1 Hz.

To retrieve spatial distribution of seismic velocity changes in such an inhomogeneous fault zone, we go beyond the simple linear travel-time shifts approximation and homogeneous sensitivity kernel. We therefore invert for the travel-time shifts at different lag-times. Furthermore, we use sensitivity kernels for media with inhomogeneous scattering properties. The scattering properties for the sensitivity kernels are derived from the data: a scattering mean free path inside the fault zone (northern strand of NAF) of ∼ 10 km and ∼ 150 km outside the fault zone, the attenuation coefficient inside and outside the fault zone are 80 and 100 respectively. 

[1] DANA. Dense array for north anatolia. International Federation of Digital Seismograph Networks doi:10.7914/SN/YH2012, 2012.

How to cite: van Dinther, C., Campillo, M., Margerin, L., and Lecointre, A.: Monitoring of temporal seismic velocity changes in the North Anatolian Fault zone using data derived scattering properties, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15195, https://doi.org/10.5194/egusphere-egu2020-15195, 2020.

Scattered seismic coda waves are frequently used to characterize small scale medium heterogeneities, intrinsic attenuation or temporal changes of wave velocity. Spatial variability of these properties raises questions about the spatial sensitivity of seismic coda waves. Especially the continuous monitoring of medium perturbations using ambient seismic noise led to a demand for approaches to image perturbations observed with coda waves. An efficient approach to localize the property variations in the medium is to invert the observations from different source-receiver combinations and different lapse times in the coda for the location of the perturbations. The key of such an inversion is calculating the coda-wave sensitivity kernels which describe the connection between observations and the perturbation. Most discussions of sensitivity kernels use the acoustic approximation and assume wave propagation in the diffusion regime.

We model 2-D  elastic multiple nonisotropic scattering in a random medium with spatially variable heterogeneity and attenuation. The Monte Carlo method is used to numerically solve the radiative transfer equation that describes the wave scattering process here. Recording of the specific intensity of the wavefield I(r,n,t) which contains the complete information about the energy at position r at time t with the propagation direction n allows us to calculate sensitivity kernels according to rigorous theoretical derivations. We investigate sensitivity kernels that describe the relationships between changes of the model parameters P- and S-wave velocity, P- and S-wave attenuation, and the strength of fluctuation on the one hand and the observables envelope amplitude, travel time changes and decorrelation on the other hand. These sensitivity kernels reflect the effect of the spatial variations of medium properties on wavefield. Our work offers a direct approach to compute these new expressions and adapt them to spatially variable heterogeneities. The sensitivity kernels we derived are the first step in the development of an inversion approach based on coda waves.

How to cite: Zhang, T. and Sens-Schönfelder, C.: Simulation of seismic wave scattering for the computation of probabilistic coda-wave sensitivity kernels, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5408, https://doi.org/10.5194/egusphere-egu2020-5408, 2020.

A wide spectrum of processing schemes is commonly applied during the calculation of seismic noise correlations. This is intended to suppress large-amplitude transient and monochromatic signals, to accelerate convergence of the correlation process, or to modify raw correlations into more plausible approximations of inter-station Green's functions. Many processing schemes, such as one-bit normalisation or various non-linear normalizations, clearly break the linear physics of seismic wave propagation. This naturally raises the question: To what extent are the resulting noise correlations physically meaningful quantities?

In this contribution, we rigorously demonstrate that most commonly applied processing methods introduce an unphysical component into noise correlations. This affects noise correlation amplitudes but also, to a lesser extent, time-dependent phase information. The profound consequences are that most processed correlations cannot be entirely explained by any combination of Earth structure and noise sources, and that inversion results may thus be polluted.

The positive component of our analysis is a new class of processing schemes that are optimal in the sense of (1) completely avoiding the unphysical component, while (2) closely approximating the desirable effects of conventional processing schemes. The optimal schemes can be derived purely on the basis of observed noise, without any knowledge of or assumptions on the nature of noise sources.

In addition to the theoretical analysis, we present illustrative real-data examples from the Irish National Seismic Network and the Lost Hills array in Central California. This includes a quantification of potential artifacts that arise when mapping unphysical traveltime and amplitude variations into images of seismic velocities or attenuation.

How to cite: Fichtner, A., Bowden, D., and Ermert, L.: Optimal processing and unphysical effects in seismic noise correlations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7832, https://doi.org/10.5194/egusphere-egu2020-7832, 2020.

We have recently shown that all features in the earthquake-coda correlogram can be explained by the similarity of seismic phases that have a common slowness for the analysed receiver pair. This includes both the features that have their equivalents in the conventional traveltime stacks, but also those that were previously unexplained. Consequently, the information contained in the correlograms – cross-correlated ground-motion time-series in a two-dimensional representation – can be used to constrain Earth’s internal structure, however, that requires a proof of concept and further investigation into the origin of the correlation wavefield. We thus first decompose relevant correlogram features into discrete constituents with respect to their arrival times and we uniquely identify contributing seismic phases to each constituent. This confirms that the correlation wavefield does not arise due to the reconstruction of body waves between the two receivers (a.k.a. Green’s function) – instead, it is dominated by the interaction of various body waves, and its features are characterised by complex sensitivity kernels.

We demonstrate that the event locations relative to the receivers alter the similarities between the body waves, and may result in significant waveform distortions and inaccuracies in arrival-time predictions. We further show that the nature of source-mechanism and energy-release dynamics are the key influencers responsible for individual correlograms equal in quality to a stack of hundreds of correlograms. In other words, a single seismic event that meets a set of criteria in the presence of multiple receivers can completely `illuminate’ the Earth’s interior. Quantitative kernel-decomposition and identification of body-wave pairs that contribute to a given feature in the correlogram, along with informed choices of seismic events, thus makes the correlation-wavefield tomography and other applications fully feasible. This has the potential to change the course of global seismology in the coming decades.

How to cite: Tkalčić, H., Wang, S., and Pham, T. S.: The Earth’s Correlation Wavefield: Proof of Concept, Origin and Applications, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20464, https://doi.org/10.5194/egusphere-egu2020-20464, 2020.

Generated in the ocean, secondary microseisms result from the interaction of opposing ocean wave fronts and represent the strongest ambient seismic noise level measured on land. The recorded noise energy will vary with seasons due to changes in storm activity and associated secondary microseism source locations. Here, ocean bottom seismometer (OBS) data collected offshore Ireland in 2016 have been processed to look into the seasonal variations of the ambient noise wavefield recorded at the seafloor. Daily cross-correlations of OBS pairs located on top of thick sediments in deep water highlight seasonal changes between Rayleigh waves fundamental mode and first overtone for winter and summer months. Comparisons with ocean wave directional spectrum data derived from ocean wave model hindcasts suggest those variations are correlated with changing patterns in ocean waves interactions and therefore microseism source locations. In order to understand those observations in detail, we use 3D numerical simulations to show how the water column but also the subsurface structure below the sea bottom will affect the recorded wavefield at the seafloor for different stations and sources locations. Compared to land stations, the secondary microseism wavefield observed in the ocean and in particular changes in the excitation of Rayleigh modes due to site effects can help characterize the microseism source locations that fluctuate through the seasons.

How to cite: Le Pape, F. and Bean, C. J.: Seasonal fluctuations in the secondary microseism wavefield recorded offshore Ireland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19154, https://doi.org/10.5194/egusphere-egu2020-19154, 2020.

Using the three-component continuous waveform recordings of 880 broadband seismic stations in China Seismic Network from January 2014 to December 2015, we calculated power spectral densities and probability density functions over the entire period for each station，and  investigated the characteristics of seismic noise in Chinese mainland. The deep analysis on the vertical recordings  indicates that the spatial distribution of noise levels is characterized by obvious zoning for different period bands.  Densely populated areas have higher short-period noise level than sparsely populated ones, suggesting that short-period noise is related to the intensity distribution of human activities such as transportation and industry. Meanwhile，the short-period noise level near the basin is higher than the mountainous areas，which is probably caused by the amplification effect of the sedimentary layer. The microseism energy  gradually decreases from the southeastern coastal lines to the inland regions. Furthermore, horizontal-component noise level  showed a striking constrast with the vertical component at microseismic and long-period bands. In consideration of  the zoning chracteristics and the need of seismic observations, high and low noise models were  acquired for each network , which were proved to be a more effective tool to identify locally abnormal signals including earthquake, instrumental error and various distrubance compared with the global new high and low model. 

How to cite: Wang, F., Wang, W., Long, J., and Mu, L.: Seismic noise characteristics in Chinese mainland, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19017, https://doi.org/10.5194/egusphere-egu2020-19017, 2020.

The most pervasive seismic signal recorded on our planet – microseismic ambient noise -results from the coupling of energy between atmosphere, oceans and solid Earth. Because it carries information on ocean waves (source), the microseismic wavefield can be advantageously used to image ocean storms. Such imaging is of interest both to climate studies – by extending the record of oceanic activity back into the early instrumental seismic record – and to real-time monitoring – where real-time seismic data can potentially be used to complement the spatially dense but temporally sparse satellite meteorological data.

In our work, we develop empirical transfer functions between seismic observations and ocean activity observations. We start by following the classical approach of Bromirski et al (1999), who computed an empirical transfer function between ground-motion recorded at a coastal seismic station and significant wave height measured at a nearby ocean buoy. We explore further developments by considering other seismic data observations – such as the polarization of seismic ambient noise – and other indicators of ocean activity observations, including the spectra of ocean waves.

In addition to employing the classical approach of empirical transfer functions, we further present preliminary tests using machine learning techniques to: 1) infer which seismic and ocean activity observables are better predictors of each other, and 2) to predict ocean activity given observed ground motion.

The analysis is made using selected datasets around the North Atlantic, namely using seismic data from North America (west Atlantic), the Azores (central Atlantic) and Portugal (east Atlantic).

This work is supported by FCT through projects UIDB/50019/2020 – IDL and UTAP-EXPL/EAC/0056/2017 - STORM.

References:

How to cite: Custódio, S., Bolrão, F., Bui, T., Hadziioannou, C., Lima, M., Rodrigues, D., Sheriffdeen, S., Silveira, G., and Carvalho, J.: Predicting ocean activity from seismic data using machine learning techniques , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22619, https://doi.org/10.5194/egusphere-egu2020-22619, 2020.

Ocean bottom seismometers (OBS) are widely in use since recent past to monitor seismicity of slow earthquakes as well as that of ordinary earthquakes. Seismic velocity structures, especially of S-wave are essential to estimate hypocenters of them with accuracy. Here we focus on spatial and temporal stability of ambient noise horizontal to vertical spectral ratio (H/V) spectra calculated from ocean bottom seismometers, as the first step toward future application of ambient noise H/V to estimate S-wave velocity structure. We aim to use the Nakamura’s method (1989) for ambient noise H/V spectra using a 3-component OBS array in the Japan Trench, to image deep structure above the plate interface near the trench. To achieve the imaging, it is necessary to examine spatial and temporal stability of the derived H/V spectra from these seismometers. First, we split each 24-hours record into 1-hour windows after removing the instrumental response, Then, Fourier amplitude spectra of each component is taken and smoothed using Konno and Ohmachi (1998) method, with applying downsampling, mean and trend removal, and tapering to each window. Finally, a 1-hour H/V spectral ratio is calculated with taking quadratic mean of two horizontal components. However, a total of 21 OBS, 3 broadband and 18 short-period, stations have been used in this study. A daily variation and stability of the H/V spectra are examined along with comparing them spatially from one station to another. Stability of the H/V spectra from OBS is promising for carrying out our future endevour of deeper observation using the ambient noise H/V method.

How to cite: Farazi, A. H., Garcia, E. S. M., and Ito, Y.: Stability of ambient noise H/V spectra obtained from OBS near the Japan Trench, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3999, https://doi.org/10.5194/egusphere-egu2020-3999, 2020.

We present a proof-of-concept catalogue of full-waveform seismic source solutions for the Japanese Islands area. Our method is based on the Bayesian inference of source parameters and a tomographically derived heterogeneous Earth model, used to compute Green’s strain tensors. We infer the full moment tensor, location and centroid time of the seismic events in the study area.

To compute spatial derivatives of Green’s functions, we use a previously derived regional Earth model (Simutė et al., 2016). The model is radially anisotropic, visco-elastic, and fully heterogeneous. It was constructed using full waveforms in the period band of 15–80 s.

Green’s strains are computed numerically with the spectral-element solver SES3D (Gokhberg & Fichtner, 2016). We exploit reciprocity, and by treating seismic stations as virtual sources we compute and store the wavefield across the domain. This gives us a strain database for all potential source-receiver pairs. We store the wavefield for more than 50 F-net broadband stations (www.fnet.bosai.go.jp). By assuming an impulse response as the source time function, the displacements are then promptly obtained by linear combination of the pre-computed strains scaled by the moment tensor elements.

With a feasible number of model parameters and the fast forward problem we infer the unknowns in a Bayesian framework. The fully probabilistic approach allows us to obtain uncertainty information as well as inter-parameter trade-offs. The sampling is performed with a variant of the Hamiltonian Monte Carlo algorithm, which we developed previously (Fichtner and Simutė, 2017). We apply an L2 misfit on waveform data, and we work in the period band of 15–80 s.

We jointly infer three location parameters, timing and moment tensor components. We present two sets of source solutions: 1) full moment tensor solutions, where the trace is free to vary away from zero, and 2) moment tensor solutions with the isotropic part constrained to be zero. In particular, we study events with significant non-double-couple component. Preliminary results of ~Mw 5 shallow to intermediate depth events indicate that proper incorporation of 3-D Earth structure results in solutions becoming more double-couple like. We also find that improving the Global CMT solutions in terms of waveform fit requires a very good 3-D Earth model and is not trivial.

How to cite: Simutė, S., Krischer, L., Boehm, C., Vallée, M., and Fichtner, A.: Seismic source inversion using Hamiltonian Monte Carlo and a 3-D Earth model in the Japanese Islands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9229, https://doi.org/10.5194/egusphere-egu2020-9229, 2020.

Over the last decades, many types of slip-rate functions (SRFs) have been introduced into kinematic rupture modeling. Commonly used SRFs are the Haskell-type rectangular pulse, cosine and trapezoidal windows and the Kostrov-/Yoffe functions. All these functions and many functional shapes inferred from multiwindow inversion techniques can be well described or are even identical to the functional form of the generalized beta distribution—a widely used and well studied probability density function (pdf) in statistics. The generalized beta pdf has three parameters, where one parameter relates to the SRF duration and two describe the shape of the pulse. The shape parameters have simple analytic expressions for their estimators. Using the generalized beta pdf with free shape parameters as SRF can effectively reduce the number of required free parameters in the inversion when compared to multiwindow SRF techniques. The generalized beta pdf provides us not only with analytic solutions of the derivative (slip-rate change) and antiderivative (slip) of the slip-rate function but also analytic expressions for their Fourier spectra. We apply the beta SRF for rupture modeling of two well studied earthquakes in Taiwan—the 2016 M_W 6.4 Meinong earthquake and the M_W 6.3 2018 Hualien earthquake—and compare results in terms of slip distribution and model uncertainties.

How to cite: von Specht, S., Ma, K.-F., Lin, Y.-Y., and Cotton, F.: A generalized slip-rate function for kinematic modeling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21170, https://doi.org/10.5194/egusphere-egu2020-21170, 2020.

We present a back-projection method capable of being parameterized with multiples arrays. The rupture imaging is weighted to restrict uncertainties induced by non-symmetric azimuthal coverage of seismic arrays. The strategy also exploits the differences in time delays between P and depth phase (pP) waveforms by assuming them as proxies of the rupture that can be simultaneously back-projected. Surprisingly, this helps to improve the final results, even when depth phases overlap with the direct arrivals due to the rupture time exceeding the pP-P delay. Thus, the approach heightens the spatiotemporal resolvability enough to image rupture complexities. The rupture image of two large events demonstrates its robustness. The first one is the 14 November 2007 Mw 7.7 Tocopilla earthquake in northern Chile. The high-frequency rupture (0.5 - 2.0 Hz) encircles two asperities while the short-period energy radiated predominates up-dip of the coseismic slip. We propose the contribution of asperity rupture complexities and along-dip barriers to high-frequency emissions beyond the megathrust frictional structure. The second one is the Mw 7.5 Palu strike-slip earthquake, which occurred on 28 September 2018 in Sulawesi island. The back-projection reveals a prominent supershear rupture at a speed of 4.5 km/s. The result correlates with space geodesy data highlighting the successful recovery of fault structures. Finally, we discuss the potential and challenges of automating this analysis for near-real-time applications, including near-source back-projection with strong-motion data.

How to cite: Vera, F., Tilmann, F., and Saul, J.: Multi-Array Multi-Phase Back-Projection: Improving the imaging of earthquake rupture complexities, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11233, https://doi.org/10.5194/egusphere-egu2020-11233, 2020.

Back-projection uses the time-reversal property of the seismic wavefield recorded at large aperture dense seismic arrays. Seismic energy radiation is imaged by applying array beam-forming techniques. The spatio-temporal rupture complexity of large earthquakes can be imaged simply and rapidly with a limited number of assumptions, which makes back-projection techniques an important tool of modern seismology. However, back-projection analyses exhibit frequency and array dependency (e.g. Wu et al., AGU19). In addition, the method relies on station network geometry and data quality and can suffer from imaging artifacts (e.g., Fan and Shearer, 2017) and back-projection results may not be consistently interpreted.

The Mw7.5 Palu, Sulawesi earthquake that occurred on September 28, 2018, ruptured a 180 km long section of the Palu-Koro fault. The earthquake triggered a localized but powerful tsunami within Palu Bay, which swept away houses and buildings. The supershear earthquake and unexpected tsunami led to more than 4000 fatalities. Ulrich et al. (2019) propose a physics-based, coupled earthquake-tsunami scenario of the event, tightly constrained by observations. The model matches key observed earthquake characteristics, including moment magnitude, rupture duration, fault plane solution, teleseismic waveforms, and inferred horizontal ground displacements. It suggests that time-dependent earthquake-induced uplift and subsidence could have sourced the observed tsunami within Palu Bay.

Back-projection has been used to track the rupture propagation of the Palu earthquake. Bao et al. (2019) image unilateral rupture traveling at a supershear rupture speed. Their results show array dependent ruptures, from a rather relatively linear rupture using the Australian array, to a spatio-temporally more scattered image using the seismic array in Turkey. In addition, they do not resolve any portion of the rupture as traveling at sub-Rayleigh speeds, while Wei et al. (AGU19) suggest a gradually accelerating rupture.

In this study, we build upon the dynamic rupture model of Ulrich et al. (2019) to investigate the reliability of standard back-projection techniques using a realistic and perfectly known earthquake model. In particular, we investigate whether or not rupture transfers across the segmented fault system, and the effect of specific geometric features of the fault system, such as fault bends, on rupture dynamics, leave a clear signal on the inferred beam power. Also, we investigate the effect of secondary phases, such as reflections from the free-surface or from fault segment boundaries, naturally captured by dynamic rupture modeling. In addition, we study the effect of small-scale source heterogeneities on the back-projection results by including different levels of fault roughness in the dynamic rupture simulations. Finally, we investigate the array dependence of back-projection results.

Overall, this study should help to better understand which features of rupture dynamics back-projection can capture. Our results are a first step towards fundamental analysis to better understand which features can be captured by back-projection and to provide guidelines for back-projection interpretation.

How to cite: Ulrich, T., Li, B., and Gabriel, A.-A.: Synthetic analysis of seismic back-projection using 3D dynamic rupture simulations of the 2018, Palu Sulawesi earthquake , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20703, https://doi.org/10.5194/egusphere-egu2020-20703, 2020.

A fundamental question of earthquake science is what produces damaging high-frequency ground motion, with the classic Brune-Haskell model postulating that abrupt initiation of fault slip causes it. However, even when amended with heterogeneous rupture, frictional slip models fail to explain observations of different sized repeating earthquakes, and have challenges explaining high-frequency radiation patterns as well as the dependence of stress drops on fault maturity and depth. We propose an additional cause for high-frequency earthquake spectra from elastic collisions of structures within a rupturing fault zone. The collision spectrum is set by an impact contact time that is proportional to the size of colliding structures, so that spectra depend on fundamentally different physical parameters compared with slip models. When added to standard frictional models, the collision model can reconcile the discrepant observations, since the size, shape and orientation of structures vary between different fault zones but remain constant within a given fault segment. High-frequency earthquake ground motions and damage may therefore be an outgrowth of fault-zone structure rather than sudden initiation of slip.

How to cite: Tsai, V. and Hirth, G.: Elastic Impact Consequences for High-Frequency Earthquake Ground Motions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10834, https://doi.org/10.5194/egusphere-egu2020-10834, 2020.

The 2016 Central Italy sequence showed a remarkable complexity involving multiple faults. Highly heterogeneous slip distributions were inferred from kinematic finite source inversions. The coverage and quality of the geodetic and seismic data allow resolving high-resolution details of rupture kinematics of the largest event of the sequence, the Mw 6.5 30 October 2016 Norcia earthquake. Composite fault rupture models suggest that two fault planes may have slipped simultaneously. Nevertheless, kinematic modeling cannot assess the mechanic viability of such multiple fault plane models.

Using SeisSol, a software package for simulating wave propagation and dynamic rupture based on the arbitrary high-order accurate derivative discontinuous Galerkin method, we therefore try to generate spontaneous dynamic ruptures models compatible with the two fault planes constrained by kinematic inversions. To this end, we adopt a simple slip-weakening friction law with spatially variable dynamic friction and initial strength parameters along multiple faults, compatible with the slip distributions found in the literature. Although we do not to aim to explore the full parameter space, our approach allows testing the feasibility of kinematic models in conjunction with successfully generating spontaneous dynamic rupture scenarios matching seismic and geodetic observations with geological constraints. Such linking enhances and validates the physical implications of kinematic earthquake source inversion.

How to cite: Tinti, E., Casarotti, E., Gabriel, A.-A., Taufiqurrahman, T., Ulrich, T., and Li, D.: Kinematic constraining of the multi-fault rupture dynamics of the Norcia, Mw 6.5, 30 October 2016, Central Italy earthquake, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10142, https://doi.org/10.5194/egusphere-egu2020-10142, 2020.

The September 20, 1999 (UTC) Mw7.6 Chi-Chi earthquake in Taiwan was a devastating event of historic proportions. Although this event caused severe damage, it also provided a large data set of high-quality near-field strong motion acceleration records from the Taiwan Strong Motion Instrumentation Program. Despite ongoing advances in kinematic modeling in the last two decades, some questions remain unresolved.  One of those questions is the seismic energy partition in radiated energy and fracture energy. We address this question by investigating the dynamic rupture behavior of this event. We constructed a 3D dynamic rupture model which is constrained by the well resolved spatiotemporal slip distribution and in-situ stress measurements from fault-zone drilling. In our model, we consider the fault ruptures with both spatially uniform and non-uniform frictional behavior and perform a series of numerical experiments with different sets of input variables (e.g., slip-weakening distance, d_c, and initial stress on fault plane) based on a slip-weakening friction law. We examined the parameters controlling the slip patterns as the result from kinematic modeling. For the constraints of the input variables, we first derived the constitutive relationship between slip and stress change on the subfaults from the temporal and spatial slip distribution of the kinematic models by Ji et al. (2003), and then determined the dynamic parameters (e.g., apparent slip-weakening distance, d_c', and the ratio of strength excess and stress drop,  S). Our initial normal stress on the fault plane is based on the geophysical logging analysis of the Taiwan Chelungpu-fault Drilling Project. Our optimal model can simulate a rupture similar to the kinematic model  by Ji et al. (2003) and suggests that the final slip distribution is mainly controlled by the spatial distribution of the normal stress. We require a downscaling (α) of the apparent slip-weakening distance, αd_c', from the derived constitutive law of the kinematic model to allow a dynamic rupture propagation with large slip velocity comparable to the observations. With the downscaled slip-weakening distance, αd_c', and a heterogeneous stress distribution, the slip-weakening curves from our optimal model suggests the downscaling in radiated seismic energy and fracture energy accordingly .

How to cite: Liao, J., Ma, K.-F., Specht, S., and Oglesby, D.: Dynamic modeling of the 1999 Chi-Chi (Mw7.6) earthquake: New insights on energy partition in large earthquakes by incorporating in-situ stress measurements into the constitutive relationship from kinematic modeling, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12423, https://doi.org/10.5194/egusphere-egu2020-12423, 2020.

The western extension and deformation mechanism of Flores back-arc thrust in eastern Sunda-Banda Arc (Indonesia) are poorly investigated, and, thus, poorly constrained. From late July to August 2018, a sequence of large earthquakes (M6.4+) took place in the north of Lombok Island that marked the previously westernmost termination of the continuous zone of the back-arc thrusting. The 2018 Lombok earthquake sequences that began with Mw 6.4 (28 July 2018), and followed by Mw 6.9 (5 August 2018), and Mw 6.9 (19 August 2019) with massive subsequent aftershocks claimed on more than 500 casualties, nearly 500,000 people displaced and serious damages on Lombok Island. Here we relocate the aftershocks and perform the finite fault inversions of M6.4+ earthquake sequences constrained with teleseismic body and surface waves. Both refined hypocenters of aftershocks and rupture processes of large earthquakes provide detail kinematic descriptions of the source mechanisms of the sequences. The aftershocks distributions and slip model suggest that the earthquakes occurred on south-dipping low angle thrust faulting that striking to the east while it also activated aftershocks on surrounding complex shallow faulting with distinguishing distributions. The source inversions of large earthquakes over the entire of the western part of Flores back-arc thrust resulted as simple circular rupture propagations initiated from ~15 km depth for all events except the westernmost events (Mw 6.9 on 5 August 2019) that had a more complex rupture and initiated from shallower depth, and with slip distributed cross over the former identified westernmost termination of the Flores back-arc thrust. Our study suggests the further extension of back-arc thrusting and the possible structures revealed from the subsequence aftershocks. The source characterizations revealed in this study would be important for further seismic hazard analysis in this region.

How to cite: Sianipar, D. S. J., Huang, B.-S., Ma, K.-F., Setiadi, T. A. P., Hsieh, M.-C., Haridhi, H. A., and Daryono, D.: Source Investigation of the 2018 Lombok (Indonesia) Earthquake Sequences, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18938, https://doi.org/10.5194/egusphere-egu2020-18938, 2020.

Interferometric Synthetic Aperture Radar (InSAR) data is of high spatial resolution and has been widely used in measuring surface deformation generated by earthquakes. However, the temporal resolution of InSAR data is relatively poor from an individual mode SAR sensor. A series of earthquakes hit Kumamoto, Japan in April 2016. These earthquakes were considered to be a sequence that started from two foreshocks (TFS) larger than Mw 6.0 and reached its climax for the largest earthquake of Mw7.0 only after 28 hours. To better reveal the source model characteristics of the TFS and the main shock, we firstly determined the geometrical parameters using the aftershock re-location data and the surface fault rupture data of field survey, and then applied multi-mode InSAR data only covering the TFS and the whole sequence, respectively, to carry out the joint inversion of respective source models based on the time correlation between the TFS and the main shock. The results show that both the source models determined here are well consistent with previous results constrained by seismological data. The strategy of inversion used in this study suggests that we may separate multiple seismic sources sequence from geodetic observations using the joint inversion based on the time correlation.

How to cite: Wang, Y., Feng, W., Chen, K., and Du, H.: Slip models of the 2016 Mw7.0 Kumamoto, Japan mainshock and its two foreshocks constrained by multi-mode InSAR data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12106, https://doi.org/10.5194/egusphere-egu2020-12106, 2020.

  Taiwan region is a seismically active region formed by the oblique convergence between Philippine Sea Plate and Eurasia Plate. Focal mechanisms of most small-moderate sized earthquakes can be well constrained by the local seismic array, except for those occurred offshore Taiwan where azimuthal coverage is limited. To better understand the tectonic structures, it is desirable to improve the focal mechanisms using better located hypocenters, reasonable velocity models, and the best available stations. In this study we focus on the shallow earthquakes in Taiwan Strait and the intermediate-depth earthquakes in southernmost Ryukyu. Both regions are less explored but large historic events had been reported.

  For earthquakes in Taiwan Strait, we systematically studied earthquakes from 1996 to 2019, including the M_w5.7 Taiwan Shoal sequence happened on 2018/11/25. A total of 22 new moment tensors (MTs) were resolved in the passive margin by combining Fujian and Taiwan seismic networks from either side of the strait. For events closer to Fujian, China, the velocity model with Moho depth of 35 km yields overall lower compensated linear vector dipole (CLVD) and acceptable misfit values; while as a 40 km thick crust is better for events closer to or on the shore of Taiwan. This Moho variation under the Taiwan Strait, although subtle, agrees well with the velocity structure constrained independently by previous studies. Earthquakes in the middle of the strait are dominant in strike-slip and normal slip within 30 km depth. Shallow thrusting events are found only in the Miaoli offshore area of Taiwan. As for the 2018 Taiwan Shoal earthquake sequence, it is located right on the region absence of known fault-plane solutions, therefore offers important new constraints. All events of the sequence show high angle strike-slips and shallow centroid depth of 11-21 km, more consistent with seismicity determined by Fujian seismic center. This event is far away from the M8 1604 Quanzhou earthquake, and is also clearly unrelated to the structure of 1994 M_w 6.7 normal-faulting event in Tainan Basin. The 2018 sequence is probably the reactivation of a pre-existing normal fault that was created by rifting during the Cenozoic.

  For future work, we will re-evaluate the MTs of M>5.5 intermediate-depth earthquakes of the Ryukyu subduction zone by including waveforms of stations YNG and IGK from Japan network in the inversion. We will also test different upper mantle velocities in the model for the computation of Green’s functions. We anticipate that our work can provide a set of parameters more suitable for the MT inversion, and the MT results can delineate the Ryukyu subduction zone properties better.

keywords : Taiwan Strait, focal mechanisms, moment tensor inversion

How to cite: Lee, C.-C., Tseng, T.-L., and Jian, P.-R.: Improving Focal Mechanisms for Earthquakes in Taiwan Strait and Ryukyu Subduction Zone with Broadband Waveforms of Combined Networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6855, https://doi.org/10.5194/egusphere-egu2020-6855, 2020.

The standard method to image the source rupture process of a large earthquake is finite fault inversion, which uses the low-frequency signal to invert the slip distribution of the fault. However, in different stages of the source rupture process of a large earthquake, the seismic waves radiated by the source have different dominant frequencies, such as high frequency seismic waves excited by the rupture front. If we can analyze seismic waves in different frequency bands, it is expected to obtain a more detailed source rupture process of large earthquakes. Therefore, we respectively adopted the high frequency signal back-projection imaging method and the low frequency signal finite fault inversion method, and took the 2016 Kaikoura M_W7.8 earthquake as an example to obtain the history of rupture propagation and fault slip distribution.The calculated results show that the high-frequency energy radiation of the earthquake can be divided into three stages, and the low-frequency energy radiation can be divided into two stages. The energy release process in different frequency bands is complementary in time and space. The rupture process of the whole source can be explained by the asperity model and the barrier model.

How to cite: Du, H., Zhang, X., and Wang, Y.: Multi-band imaging of seismic source rupture process, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7075, https://doi.org/10.5194/egusphere-egu2020-7075, 2020.

In the past decade, there have been several disaster earthquakes occurred in Taiwan.
From the observed data of the disaster earthquakes, the stations located in the source
rupture direction have obvious directivity pulses, and the distribution of the earthquake
disaster is related to the peak ground velocity. Therefore, how to use a large and high-
dense seismic database to develop a near-real-time detection system on the earthquake
rupture directivity, which is a very important task in Taiwan. In this study, we determine
the earthquake rupture directivity using near-field velocity data from 1991 to 2018, which
were collected under the Taiwan Strong Motion Instrument Program (TSMIP). The used
method is mainly constructed in the interpolation of the peak-ground-velocity map and
the directional attenuation regression analysis. Through the analysis of moderate-to-large
magnitude (M L > 5.5) seismic events, the source rupture directivity can be detected
effectively and quickly by the applied method. The detection results are also comparable
with those from the previous source studies. We also find out a linear relationship between
the directivity effect and earthquake magnitude. Since the TSMIP station may provide
real-time services in the future, the detection system proposed by this research can quickly
provide disaster prediction information, which is of great importance for earthquake
emergency response and hazard mitigation.

How to cite: Wu, C.-F., Lin, T.-L., and Chen, Y.-C.: Rapid Detection of Earthquake Rupture Directivity Using Strong Ground Motion Data in Taiwan, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22441, https://doi.org/10.5194/egusphere-egu2020-22441, 2020.

Phase unwrapping is the process of recovering the absolute phase from unambiguous wrapped phase values that are measured modulo 2pi rad. From a mathematical point of view, phase unwrapping is an inverse problem, however, it is ill-posed and notoriously difficult to solve in the presence of noise. Meanwhile, phase unwrapping errors severely impact the estimation of earthquake and volcano source parameters using interferometric observations, therefore avoiding phase unwrapping completely is desirable. 

A potential solution to avoid the unwrapping error issue completely, is to carry out a geophysical inversion directly on the wrapped phase observations. To overcome the need for phase unwrapping, we propose a novel approach that we can invert directly the interferometric wrapped phase, circumventing the ill-posed phase unwrapping processing step. This approach includes (1) a downsampling algorithm, (2) a method to estimate the covariance function of the wrapped phase, (3) an appropriate misfit function between the observed and the simulated wrapped phase. We also assess the uncertainties of source parameters within a Bayesian approach, and finally we test the robustness of the inversion methodology in multiple simulations including variable decorrelation and atmospheric noise simulations.

We demonstrate the proposed methodology on synthetic cases with variable noise and one real earthquake case. We show that the method is robust in challenging noise scenarios. We also show an improvement with the Bayesian approach in performance with respect to similar previous methods, resulting in avoiding any influence of seed starting models, and escaping local minima. We study the impact of a small percentage of incorrectly unwrapped phase observations in current state-of-the-art methods, and show that the presence of a small fraction of unwrapping errors affect strongly the estimation process. We conclude that in the cases where phase unwrapping is difficult or even impossible, the proposed inversion methodology with wrapped phase will provide an alternative approach to assess earthquake and volcano source model parameters.

How to cite: Jiang, Y. and González, P.: Bayesian Inversion of Wrapped Satellite Interferometric Phase to Estimate Fault and Volcano Surface Ground Deformation Models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5604, https://doi.org/10.5194/egusphere-egu2020-5604, 2020.

Earthquakes are multiscale phenomena with several scale invariant parameters, such as stress drop, apparent stress, and rupture propagation velocity, and dynamic rupture grows almost self-similarly. While the rupture process is always complex, the location of sources is not completely random, but nearly predetermined, especially along a well-developed fault system like a plate interface. To explain such behavior, some hierarchical structure is required, and one candidate is the hierarchical circular patch (fractal asperity) model suggested by Ide and Aochi (JGR, 2005) and Aochi and Ide (JGR, 2009), in which fracture energy inside a patch is proportional to the patch radius. In this paper, we review the characteristics of the model and show some observational evidence, which has been recently discovered mainly for subduction-type earthquakes in the Tohoku-Oki, Japan, region. Some hierarchical patch-like structure has been identified for several repeating earthquakes of M~5 (Uchida et al., GRL, 2012; Okuda and Ide, EPS, 2018). Identical onsets of seismic waves were observed for many pairs of large (M>4.5) and small (M<4.0) earthquakes (Okuda and Ide, Nature Communications, 2018; Ide, Nature, 2019). We can also observe long-term increase of seismicity before the rupture of system-size events (Okuda et al., Zishin, 2018). These lines of evidence suggest the qualitative validity of the hierarchical model and will be useful to improve the quantitative aspects of the model, such as patch density and the slip-weakening rate, to numerically simulate realistic earthquakes and seismicity (e.g., Aochi and Ide, EPS, 2011; Ide and Aochi, Tectonophysics, 2013; Aochi and Twardzik, Pageoph, 2019).

How to cite: Ide, S. and Aochi, H.: Hierarchical seismic sources model and recent observational evidence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11916, https://doi.org/10.5194/egusphere-egu2020-11916, 2020.