ALBERT

Description: 〈span〉〈div〉SUMMARY〈/div〉We use continuous seismic data recorded between January 2013 and December 2014 by Iranian Seismological Center (IRSC) and International Institute of Earthquake Engineering and Seismology (IIEES) networks. Empirical Green’s functions between the vertical components of the station pairs are reconstructed by cross-correlating the seismic noise (〈span〉C〈/span〉〈sup〉1〈/sup〉) and recorrelating the coda of the noise-correlations (〈span〉C〈/span〉〈sup〉3〈/sup〉). The combination of these two methods makes it possible to increase the number of retrieved empirical Green’s functions, which improves the spatial resolution of the tomographic imaging. We measure and then invert Rayleigh wave dispersion traveltimes to produce 2-D group velocity maps from a period range of 5–40 s for Iranian plateau. The sensitivity tests of tomography using traveltimes from 〈span〉C〈/span〉〈sup〉1〈/sup〉 and 〈span〉C〈/span〉〈sup〉1〈/sup〉+〈span〉C〈/span〉〈sup〉3〈/sup〉 indicates that 〈span〉C〈/span〉〈sup〉1〈/sup〉+〈span〉C〈/span〉〈sup〉3〈/sup〉 indeed enhances resolution. In general, results from seismic noise imaging show good agreement with the local geological units. The shear wave velocity sections resulting from the Bayesian inversion of dispersion curves are interpreted along four profiles in different directions in order to cover the main tectonics of Iranian plateau down to 60 km depth.〈/span〉

Description: 〈span〉〈div〉Summary〈/div〉We use continuous seismic data recorded between January 2013 and December 2014 by Iranian Seismological Center (IRSC) and International Institute of Earthquake Engineering and Seismology (IIEES) networks. Empirical Green’s functions between the vertical components of the station pairs are reconstructed by cross-correlating the seismic noise (〈span〉C〈/span〉〈sup〉1〈/sup〉) and re-correlating the coda of the noise-correlations (〈span〉C〈/span〉〈sup〉3〈/sup〉). The combination of these two methods makes it possible to increase the number of retrieved empirical Green’s functions, which improves the spatial resolution of the tomographic imaging. We measure and then invert Rayleigh wave dispersion travel times to produce 2-D group velocity maps from a period range of 5 to 40 seconds for Iranian plateau. The sensitivity tests of tomography using travel times from 〈span〉C〈/span〉〈sup〉1〈/sup〉 and 〈span〉C〈/span〉〈sup〉1〈/sup〉+〈span〉C〈/span〉〈sup〉3〈/sup〉 indicates that 〈span〉C〈/span〉〈sup〉1〈/sup〉+〈span〉C〈/span〉〈sup〉3〈/sup〉 indeed enhances resolution. In general, results from seismic noise imaging show good agreement with the local geological units. The shear wave velocity sections resulting from the Bayesian inversion of dispersion curves are interpreted along four profiles in different directions in order to cover the main tectonics of Iranian plateau down to 60 km depth.〈/span〉

Description: The subduction and roll-back of the African plate beneath the Eurasian plate along the arcuate Hellenic trench is the dominant geodynamic process in the Aegean and western Anatolia. Mantle flow and lithospheric kinematics in this region can potentially be understood better by mapping seismic anisotropy. This study uses direct shear-wave splitting measurements based on the Reference Station Technique in the southern Aegean Sea to reveal seismic anisotropy in the mantle. The technique overcomes possible contamination from source-side anisotropy on direct S-wave signals recorded at a station pair by maximizing the correlation between the seismic traces at reference and target stations after correcting the reference stations for known receiver-side anisotropy and the target stations for arbitrary splitting parameters probed via a grid search. We obtained splitting parameters at 35 stations with good-quality S-wave signals extracted from 81 teleseismic events. Employing direct S-waves enabled more stable and reliable splitting measurements than previously possible, based on sparse SKS data at temporary stations, with one to five events for local SKS studies, compared with an average of 12 events for each station in this study. The fast polarization directions mostly show NNE-SSW orientation with splitting time delays between 1.15 s and 1.62 s. Two stations in the west close to the Hellenic Trench and one in the east show N-S oriented fast polarizations. In the back-arc region three stations exhibit NE-SW orientation. The overall fast polarization variations tend to be similar to those obtained from previous SKS splitting studies in the region but indicate a more consistent pattern, most likely due to the usage of a larger number of individual observations in direct S-wave derived splitting measurements. Splitting analysis on direct shear waves typically resulted in larger split time delays compared to previous studies, possibly because S-waves travel along a longer path in the same anisotropic structure. Considering the S-derived splitting measurements of this study together with earlier SKS and Rayleigh wave anisotropy modelling results we suggest that the very consistent direct S-derived fast shear wave directions can be explained by the lattice-preferred orientation of olivine in the asthenospheric mantle due to mantle flow induced by the roll-back of the slab. It is possible that a small contribution originated in the lower crust beneath the study region where anisotropic fabric might have formed in response to extension in the Miocene.

Description: We develop and apply a full waveform inversion method that incorporates seismic data on a wide range of spatio-temporal scales, thereby constraining the details of both crustal and upper-mantle structure. This is intended to further our understanding of crust–mantle interactions that shape the nature of plate tectonics, and to be a step towards improved tomographic models of strongly scale-dependent earth properties, such as attenuation and anisotropy. The inversion for detailed regional earth structure consistently embedded within a large-scale model requires locally refined numerical meshes that allow us to (1) model regional wave propagation at high frequencies, and (2) capture the inferred fine-scale heterogeneities. The smallest local grid spacing sets the upper bound of the largest possible time step used to iteratively advance the seismic wave field. This limitation leads to extreme computational costs in the presence of fine-scale structure, and it inhibits the construction of full waveform tomographic models that describe earth structure on multiple scales. To reduce computational requirements to a feasible level, we design a multigrid approach based on the decomposition of a multiscale earth model with widely varying grid spacings into a family of single-scale models where the grid spacing is approximately uniform. Each of the single-scale models contains a tractable number of grid points, which ensures computational efficiency. The multi-to-single-scale decomposition is the foundation of iterative, gradient-based optimization schemes that simultaneously and consistently invert data on all scales for one multi-scale model. We demonstrate the applicability of our method in a full waveform inversion for Eurasia, with a special focus on Anatolia where coverage is particularly dense. Continental-scale structure is constrained by complete seismic waveforms in the 30–200 s period range. In addition to the well-known structural elements of the Eurasian mantle, our model reveals a variety of subtle features, such as the Armorican Massif, the Rhine Graben and the Massif Central. Anatolia is covered by waveforms with 8–200 s period, meaning that the details of both crustal and mantle structure are resolved consistently. The final model contains numerous previously undiscovered structures, including the extension-related updoming of lower-crustal material beneath the Menderes Massif in western Anatolia. Furthermore, the final model for the Anatolian region confirms estimates of crustal depth from receiver function analysis, and it accurately explains cross-correlations of ambient seismic noise at 10 s period that have not been used in the tomographic inversion. This provides strong independent evidence that detailed 3-D structure is well resolved.

Description: Stations on the Australian continent receive a rich mixture of continuous ground motion with ambient seismic noise from the surrounding oceans, and numerous small earthquakes in the earthquake belts to the north in Indonesia, and east in Tonga-Kermadec, as well as more distant source zones. The ground motion at a seismic station contains information about the structure in the vicinity of the site, and this can be exploited by applying an autocorrelation procedure to the continuous records. By creating stacked autocorrelograms of the ground motion at a single station, information on crust properties can be extracted in the form of a signal that includes the crustal reflection response convolved with the autocorrelation of the combined effect of source excitation and the instrument response. After applying suitable high-pass filtering, the reflection component can be extracted to reveal the most prominent reflectors in the lower crust, which often correspond to the reflection at the Moho. Because the reflection signal is stacked from arrivals from a wide range of slownesses, the reflection response is somewhat diffuse, but still sufficient to provide useful constraints on the local crust beneath a seismic station. Continuous vertical component records from 223 stations (permanent and temporary) across the continent have been processed using autocorrelograms of running windows 6 hr long with subsequent stacking. A distinctive pulse with a time offset between 8 and 30 s from zero is found in the autocorrelation results, with frequency content between 1.5 and 4 Hz, suggesting P -wave multiples trapped in the crust. Synthetic modelling, with control of multiple phases, shows that a local p m p phase can be recovered with the autocorrelation approach. This identification enables us to make out the depth to the most prominent crustal reflector across the continent. We obtain results that largely conform to those from previous studies using a combination of data from refraction, reflection profiles and receiver functions. This approach can be used for crustal property extraction using just vertical component records, and effective results can be obtained with temporary deployments of just a few months.