ALBERT

Description: In this study, we reestimate the source model of the 1997 Mw 7.2 Zirkuh earthquake (northeastern Iran) by jointly optimizing intermediate-field Interferometry Synthetic Aperture Radar data and near-field optical correlation data using a two-step fault modeling procedure. First, we estimate the geometry of the multisegmented Abiz fault using a genetic algorithm. Then, we discretize the fault segments into subfaults and invert the data to image the slip distribution on the fault. Our joint-data model, although similar to the Interferometry Synthetic Aperture Radar-based model to the first order, highlights differences in the fault dip and slip distribution. Our preferred model is ∼80° west dipping in the northern part of the fault, ∼75° east dipping in the southern part and shows three disconnected high slip zones separated by low slip zones. The low slip zones are located where the Abiz fault shows geometric complexities and where the aftershocks are located. We interpret this rough slip distribution as three asperities separated by geometrical barriers that impede the rupture propagation. Finally, no shallow slip deficit is found for the overall rupture except on the central segment where it could be due to off-fault deformation in quaternary deposits. ©2018. American Geophysical Union. All Rights Reserved.

Description: An 8 year archive of Envisat synthetic aperture radar (SAR) data over a 300 × 500 km 2 wide area in northwestern Tibet is analyzed to construct a line-of-sight map of the current surface velocity field. The resulting velocity map reveals (1) a velocity gradient across the Altyn Tagh fault, (2) a sharp velocity change along a structure following the base of the alluvial fans in southern Tarim, and (3) a broad velocity gradient, following the Jinsha suture. The interferometric synthetic aperture radar velocity field is combined with published GPS data to constrain the geometry and slip rates of a fault model consisting of a vertical fault plane under the Altyn Tagh fault and a shallow flat décollement ending in a steeper ramp on the Tarim side. The solutions converge toward 0.7 mm/yr of pure thrusting on the décollement-ramp system and 10.5 mm/yr of left-lateral strike-slip movement on the Altyn Tagh fault, below a 17 km locking depth. A simple elastic dislocation model across the Jinsha suture shows that data are consistent with 4–8 mm/yr of left-lateral shear across this structure. Interferometric synthetic aperture radar processing steps include implementing a stepwise unwrapping method starting with high-quality interferograms to assist in unwrapping noisier interferograms, iteratively estimating long-wavelength spatial ramps, and referencing all interferograms to bedrock pixels surrounding sedimentary basins. A specific focus on atmospheric delay estimation using the ERA-Interim model decreases the uncertainty on the velocity across the Tibet border by a factor of 2. ©2018. American Geophysical Union. All Rights Reserved.

Description: SUMMARY Earthquakes often rupture across more than one fault segment. If such rupture segmentation occurs on a significant scale, a simple point-source or one-fault model may not represent the rupture process well. As a consequence earthquake characteristics inferred, based on one-source assumptions, may become systematically wrong. This might have effects on follow-up analyses, for example regional stress field inversions and seismic hazard assessments. While rupture segmentation is evident for most Mw 〉 7 earthquakes, also smaller ones with 5.5 〈 Mw 〈 7 can be segmented. We investigate the sensitivity of globally available data sets to rupture segmentation and their resolution to reliably estimate the mechanisms in presence of segmentation. We focus on the sensitivity of InSAR (Interferometric Synthetic Aperture Radar) data in the static near-field and seismic waveforms in the far-field of the rupture and carry out non-linear and Bayesian optimizations of single-source and two-sources kinematic models (double-couple point sources and finite, rectangular sources) using InSAR and teleseismic waveforms separately. Our case studies comprises of four Mw 6–7 earthquakes: the 2009 L’Aquila and 2016 Amatrice (Italy) and the 2005 and 2008 Zhongba (Tibet) earthquakes. We contrast the data misfits of different source complexity by using the Akaike informational criterion (AIC). We find that the AIC method is well suited for data-driven inferences on significant rupture segmentation for the given data sets. This is based on our observation that an AIC-stated significant improvement of data fit for two-segment models over one-segment models correlates with significantly different mechanisms of the two source segments and their average compared to the single-segment mechanism. We attribute these modelled differences to a sufficient sensitivity of the data to resolve rupture segmentation. Our results show that near-field data are generally more sensitive to rupture segmentation of shallow earthquakes than far-field data but that also teleseismic data can resolve rupture segmentation in the studied magnitude range. We further conclude that a significant difference in the modelled source mechanisms for different segmentations shows that an appropriate choice of model segmentation matters for a robust estimation of source mechanisms. It reduces systematic biases and trade-off and thereby improves the knowledge on the rupture. Our study presents a strategy and method to detect significant rupture segmentation such that an appropriate model complexity can be used in the source mechanism inference. A similar, systematic investigation of earthquakes in the range of Mw 5.5–7 could provide important hazard-relevant statistics on rupture segmentation. In these cases single-source models introduce a systematic bias. Consideration of rupture segmentation therefore matters for a robust estimation of source mechanisms of the studied earthquakes.

Description: Inferring the geometry and evolution of an earthquake sequence is crucial to understand how fault systems are segmented and interact. However, structural geological models are often poorly constrained in remote areas and fault inference is an ill-posed problem with a reliability that depends on many factors. Here, we investigate the geometry of the Mw 6.3 2008 and 2009 Qaidam earthquakes, in northeast Tibet, by combining InSAR time series and teleseismic data. We conduct a multi-array back-projection analysis from broadband teleseismic data and process three overlapping Envisat tracks covering the two earthquakes to extract the spatio-temporal evolution of seismic ruptures. We then integrate both geodetic and seismological data into a self-consistent kinematic model of the earthquake sequence. Our results constrain the depth and along-strike segmentation of the thrust-faulting sequence. The 2008 earthquake ruptured a ∼32° north-dipping fault that roots under the Olongbulak pop-up structure at ∼12 km depth and fault slip evolved post-seismically in a downdip direction. The 2009 earthquake ruptured three south-dipping high-angle thrusts and propagated from ∼9 km depth to the surface and bilaterally along the south-dipping segmented 55–75° high-angle faults of the Olonbulak pop-up structure that displace basin deformed sedimentary sequences above Paleozoic bedrock. Our analysis reveals that the inclusion of the post-seismic afterslip into modelling is beneficial in the determination of fault geometry, while teleseismic back-projection appears to be a robust tool for identifying rupture segmentation for moderate-sized earthquakes. These findings support the hypothesis that the Qilian Shan is expanding southward along a low-angle décollement that partitions the oblique convergence along multiple flower and pop-up structures.

Description: The finite physical source problem is usually studied with the concept of volume and time integrals over Green's functions (GFs), representing delta-impulse solutions to the governing partial differential field equations. In seismology, the use of realistic Earth models requires the calculation of numerical or synthetic GFs, as analytical solutions are rarely available. The computation of such synthetic GFs is computationally and operationally demanding. As a consequence, the on-the-fly recalculation of synthetic GFs in each iteration of an optimisation is time-consuming and impractical. Therefore, the pre-calculation and efficient storage of synthetic GFs on a dense grid of source to receiver combinations enables the efficient lookup and utilisation of GFs in time-critical scenarios. We present a Python-based framework and toolkit – Pyrocko-GF – that enables the pre-calculation of synthetic GF stores, which are independent of their numerical calculation method and GF transfer function. The framework aids in the creation of such GF stores by interfacing a suite of established numerical forward modelling codes in seismology (computational back ends). So far, interfaces to back ends for layered Earth model cases have been provided; however, the architecture of Pyrocko-GF is designed to cover back ends for other geometries (e.g. full 3-D heterogeneous media) and other physical quantities (e.g. gravity, pressure, tilt). Therefore, Pyrocko-GF defines an extensible GF storage format suitable for a wide range of GF types, especially handling elasticity and wave propagation problems. The framework assists with visualisations, quality control, and the exchange of GF stores, which is supported through an online platform that provides many pre-calculated GF stores for local, regional, and global studies. The Pyrocko-GF toolkit comes with a well-documented application programming interface (API) for the Python programming language to efficiently facilitate forward modelling of geophysical processes, e.g. synthetic waveforms or static displacements for a wide range of source models.

Description: The Bayesian earthquake analysis tool (BEAT) is an open-source Python software to conduct source-parameter estimation studies for crustal deformation events, such as earthquakes and magma intrusions, by employing a Bayesian framework with a flexible problem definition. The software features functionality to calculate Green’s functions for a homogeneous or a layered elastic half-space. Furthermore, algorithm(s) that explore the solution space may be selected from a suite of implemented samplers. If desired, BEAT’s modular architecture allows for easy implementation of additional features, for example, alternative sampling algorithms. We demonstrate the functionality and performance of the package using five earthquake source estimation examples: a full moment-tensor estimation; a double-couple moment-tensor estimation; an estimation for a rectangular finite source; a static finite-fault estimation with variable slip; and a full kinematic finite-fault estimation with variable hypocenter location, rupture velocity, and rupture duration. This software integrates many aspects of source studies and provides an extensive framework for joint use of geodetic and seismic data for nonlinear source- and noise-covariance estimation within layered elastic half-spaces. Furthermore, the software also provides an open platform for further methodological development and for reproducible source studies in the geophysical community.

Description: The finite physical source problem is usually studied with the concept of volume and time integrals over Green's functions (GF), representing delta-impulse solutions to the governing partial differential field equations. In seismology, the use of realistic Earth models requires the calculation of numerical or synthetic GFs, as analytical solutions are rarely available. The computation of such synthetic GFs is computationally and operationally demanding. As a consequence, on-the-fly re-calculation of synthetic GFs in each iteration of an optimisation is time-consuming and impractical. Therefore, pre-calculation and efficient storage of synthetic GFs on a dense grid of source to receiver combinations enables efficient look-up and utilisation of GFs in time critical scenarios. We present a Python-based framework and toolkit – Pyrocko-GF – that enables pre-calculation of synthetic GF stores, which are independent of their numerical calculation method and GF transfer function. The framework integrates a suite of established numerical forward-modelling codes in seismology, and can incorporate new user-specified GF calculation methods. Pyrocko-GF defines an extensible GF storage format suitable for a wide range of GF types, handling especially elasticity- and wave propagation problems. The framework assists with visualisations, quality control and exchange of GF stores, which is supported through an online platform that provides many pre-calculated GF stores for local, regional and global studies. The Pyrocko-GF toolkit comes with a well-documented application programming interface (API) for the Python programming language to efficiently facilitate forward modelling of geophysical processes, e.g. synthetic waveforms or static displacements for a wide range of source models.

Description: The determination of seismic amplitude amplification is a fundamental contribution to seismic hazard assessment. While often only high-frequency amplitude variations (〉1 Hz) are taken into account, we analyse broadband waveforms from 0.14 to 8.6 Hz using a temporary network of 32 stations in and around the earthquake-prone city of Bucharest. Spectral amplitudes are calculated with an adaptive multiple-taper approach. Across our network (aperture 25 km × 25 km), we find a systematic northwest/southeast-oriented structural influence on teleseismic P-wave amplitudes from 0.14 to 0.86 Hz that can be explained by constructive interference in the dipping Cenozoic sedimentary layers. For higher frequencies (1.4-8.75 Hz), more local site effects prevail and can be correlated partly among neighbouring stations. The transition between systematic and localised amplitude variations occurs at about 1 Hz. © Springer Science+Business Media B.V. 2008.