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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 M-w > 7 earthquakes, also smaller ones with 5.5 < M-w < 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 M-w 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 M-w 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.
Studies of seismic tomography have been highly successful at imaging the deep structure of subduction zones. In a study complementary to these tomographic studies, we use array seismology and reflected waves to image a stagnant slab in the mantle transition zone. Using P and S (SH) waves we find a steeply dipping reflector centred at ca. 400 km depth and ca. 550 km west of the present Mariana subduction zone (at 20N, 140E). The discovery of this anomaly in tomography and independently in array seismology (this paper) helps in understanding the evolution of the Mariana margin. The reflector/stagnant slab may be the remains of the hypothetical North New Guinea Plate, which was theorized to have subducted ca. 50 Ma.
A 3-D crustal shear wave velocity model and Moho map below the Semail Ophiolite, eastern Arabia
(2022)
The Semail Ophiolite in eastern Arabia is the largest and best-exposed slice of oceanic lithosphere on land. Detailed knowledge of the tectonic evolution of the shallow crust, in particular during and after ophiolite obduction in Late Cretaceous times is contrasted by few constraints on physical and compositional properties of the middle and lower continental crust below the obducted units. The role of inherited, pre-obduction crustal architecture remains therefore unaccounted for in our understanding of crustal evolution and the present-day geology. Based on seismological data acquired during a 27-month campaign in northern Oman, Ambient Seismic Noise Tomography and Receiver Function analysis provide for the first time a 3-D radially anisotropic shear wave velocity (V-S) model and a consistent Moho map below the iconic Semail Ophiolite. The model highlights deep crustal boundaries that segment the eastern Arabian basement in two distinct units. The previously undescribed Western Jabal Akhdar Zone separates Arabian crust with typical continental properties and a thickness of similar to 40-45 km in the northwest from a compositionally different terrane in the southeast that is interpreted as a terrane accreted during the Pan-African orogeny in Neoproterozoic times. East of the Ibra Zone, another deep crustal boundary, crustal thickness decreases to 30-35 km and very high lower crustal V-S suggest large-scale mafic intrusions into, and possible underplating of the Arabian continental crust that occurred most likely during Permian breakup of Pangea. Mafic reworking is sharply bounded by the (upper crustal) Semail Gap Fault Zone, northwest of which no such high velocities are found in the crust. Topography of the Oman Mountains is supported by a mild crustal root and Moho depth below the highest topography, the Jabal Akhdar Dome, is similar to 42 km. Radial anisotropy is robustly resolved in the upper crust and aids in discriminating dipping allochthonous units from autochthonous sedimentary rocks that are indistinguishable by isotropic V-S alone. Lateral thickness variations of the ophiolite highlight the Haylayn Ophiolite Massif on the northern flank of Jabal Akhdar Dome and the Hawasina Window as the deepest reaching unit. Ophiolite thickness is similar to 10 km in the southern and northern massifs, and <= 5 km elsewhere.
Records from ocean bottom seismometers (OBSs) are highly contaminated by noise, which is much stronger
compared to data from most land stations, especially on the horizontal components. As a consequence, the high energy of the oceanic noise at frequencies below 1 Hz considerably complicates the analysis of the teleseismic earthquake signals recorded by OBSs.
Previous studies suggested different approaches to remove low-frequency noises from OBS recordings but mainly focused on the vertical component. The records of horizontal components, which are crucial for the application of many methods in passive seismological analysis of body and surface waves, could not be much improved in the teleseismic frequency band. Here we introduce a noise reduction method, which is derived from the harmonic–percussive separation algorithms used in Zali et al. (2021), in order to separate long-lasting narrowband signals from broadband transients in the OBS signal. This leads to significant noise reduction of OBS records on both the vertical and horizontal components and increases the earthquake signal-to-noise ratio (SNR) without distortion of the broadband earthquake waveforms. This is demonstrated through tests with synthetic data. Both SNR and cross-correlation coefficients showed significant improvements for different realistic noise realizations. The application of denoised signals in surface wave analysis and receiver functions is discussed through tests with synthetic and real data.
Records from ocean bottom seismometers (OBSs) are highly contaminated by noise, which is much stronger compared to data from most land stations, especially on the horizontal components. As a consequence, the high energy of the oceanic noise at frequencies below 1 Hz considerably complicates the analysis of the teleseismic earthquake signals recorded by OBSs.
Previous studies suggested different approaches to remove low-frequency noises from OBS recordings but mainly focused on the vertical component. The records of horizontal components, which are crucial for the application of many methods in passive seismological analysis of body and surface waves, could not be much improved in the teleseismic frequency band. Here we introduce a noise reduction method, which is derived from the harmonic–percussive separation algorithms used in Zali et al. (2021), in order to separate long-lasting narrowband signals from broadband transients in the OBS signal. This leads to significant noise reduction of OBS records on both the vertical and horizontal components and increases the earthquake signal-to-noise ratio (SNR) without distortion of the broadband earthquake waveforms. This is demonstrated through tests with synthetic data. Both SNR and cross-correlation coefficients showed significant improvements for different realistic noise realizations. The application of denoised signals in surface wave analysis and receiver functions is discussed through tests with synthetic and real data.