Sigurjón Jónsson

The Red Sea hosts a young (< 13 Ma) ultra-slow spreading ridge organized into right-stepping segments. The largest ridge offset, about 100 km in the N–S direction, occurs at the transition between the northern and central Red Sea and is known as the Zabargad Fracture Zone (ZFZ). However, its precise geometry and tectonic structure remain poorly determined owing to widespread Miocene evaporites that obscure basement structures. This limited knowledge prevents addressing first-order questions such as: What can we learn about the early development of large ridge offsets from the structure of the ZFZ and its relationships with inherited continental fabrics? What is the seismic hazard posed by this structure for coastal communities, and how does it relate to a reported Mw ~6.5 historical earthquake? To address these questions, we acquired new high-resolution bathymetric data of the ZFZ seafloor, performed detailed mapping of a range of different seafloor structures, and analyzed the outcome in combination with existing geophysical and geological studies. Our results indicate that the ZFZ is composed of one 50-km-long and seismically active transform fault along with smaller non-transform offsets that gradually connect to the Mabahiss Deep spreading center in the northern Red Sea. Moreover, the transform fault runs in continuity with a seismically inactive shear zone that is marked by highly deformed seafloor and extends towards the Saudi coastline before apparently connecting with an inherited Proterozoic shear zone onshore. We propose that this inactive shear zone acted as a transfer zone during the continental rifting phase of the Red Sea. We further reconstructed the early development of the ZFZ by sequentially restoring the oceanic basin to specific time periods. This reconstruction suggests that the initiation of the transform fault was delayed by a few million years relative to the onset of oceanic spreading along nearby ridge segments, an interval during which plate motion was accommodated through an evolving ridge-offset geometry initiated from the transfer zone.

Seismic gaps are fault sections that have not hosted a large earthquake for a long time compared to neighbouring segments, making them likely sites for future large events. The 2025 Mw 7.7 Mandalay (Myanmar) earthquake, on the central section of the Sagaing Fault, ruptured through a known seismic gap and ~160 km beyond it, resulting in an exceptionally long rupture of ~460 km. Here we investigate the rupture process of this event and the factors that enabled it to breach the seismic gap by integrating satellite synthetic aperture radar observations, seismic waveform back-projection, Bayesian finite-fault inversion and dynamic rupture simulations. We identify a two-stage earthquake rupture comprising initial bilateral subshear propagation for ~20 s followed by unilateral supershear rupture for ~70 s. Simulation-based sensitivity tests suggest that the seismic gap boundary was not a strong mechanical barrier in terms of frictional strength, and that nucleation of the earthquake far from the gap boundary, rather than its supershear speed, allowed the rupture to outgrow the gap and propagate far beyond it. Hence, we conclude that the dimension of seismic gaps may not reflect the magnitude of future earthquakes. Instead, ruptures may cascade through multiple fault sections to generate larger and potentially more damaging events.

Recent studies of the Reykjanes Peninsula in Iceland have shown that Interferometric Synthetic Aperture Radar (InSAR) data can reveal surface movements across new and pre-existing fractures associated with stress changes during volcanic dyke intrusions. These data have revealed many fractures in areas where optical imagery or field observations are obscured by vegetation, infrastructure, or young lava flows. Mapping active faults and fractures in geologically dynamic regions is essential for assessing tectonic and volcanic hazards, as pre-existing fractures and crustal weaknesses can control magma pathways, dyke propagation, and the location of eruptive activity. However, systematic fracture mapping from wrapped interferograms remains a time-consuming manual task. Deep learning approaches have been widely utilized successfully for mapping faults in seismic data and optical images, and similarly, to detect glacier crevasses in SAR backscatter images. Here, we investigate the feasibility of automatic fracture mapping directly from wrapped interferograms using deep learning, focusing on the current volcanic unrest on the Reykjanes Peninsula. We address the task as a binary classification problem, and implement a convolutional neural network with a U-Net architecture trained using a Dice loss to address strong class imbalance. We initially trained our model on a rather small, highly imbalanced dataset consisting of Sentinel-1 and TerraSAR-X interferograms of the area from September 2023 to February 2024. Despite relatively modest F1-Score (~56%), the model successfully identifies all major fracture movements in the test data and is able to detect features absent from the original labels, providing a fairly robust fracture map that can be easily refined. These results demonstrate that deep learning can be used to extract meaningful structural information from wrapped interferograms, even with limited data and imperfect training labels, and constitute to the best our knowledge the first application of deep learning to fracture mapping in wrapped interferograms. Current work is aimed at improving the model performance by including the latest fractures dataset of the Reykjanes Peninsula, consisting of fractures mapped on TerraSAR-X interferograms from September 2021 to July 2024. Additionally, ongoing efforts are focused on generating physically realistic synthetic interferograms that capture the complexity of fracturing and fracture reactivation due to dyke emplacement and propagation and other sources of deformation. By addressing the current limitations, this approach has the potential to enable transferable fracture-mapping workflows applicable across diverse tectonic settings and InSAR datasets, contributing to more efficient geohazard monitoring.

Oceanic transform faults (OTFs) accommodate a significant portion of global plate motions, yet the physical mechanisms governing their characteristically low seismic coupling and the initiation of earthquake swarms remain poorly understood. Here, we provide the first direct geodetic evidence of shallow slow slip events (SSEs) on an OTF. By leveraging the increase of seismic activity during earthquake swarms as temporal constraints on high-resolution, land-based continuous GNSS data from near the just-offshore Húsavík-Flatey Fault (HFF) in North Iceland, we utilized a signal-stacking strategy to isolate ultra-slow transients from stochastic noise. This approach detected SSEs that are several weeks in duration and with an average moment magnitude of Mw 5.34, systematically preceding the seismic swarms. The marked spatial complementarity between SSEs and swarms, combined with their temporal synchronicity, seem to indicate that the aseismic transients act as a mechanical trigger for the swarm-like activity along the western portion of HFF. The pronounced contrast between the weakly coupled western segment of the HFF—characterized by concurrent SSEs and earthquake swarms—and the strongly coupled eastern segment, which lacks moderate to large earthquake clusters, reveals a fundamental along-strike heterogeneity in fault behavior. The evidence of systematic aseismic slip release along the HFF accompanying swarm activity indicates that the seismic moment deficit of OTFs can be reconciled by aseismic slip transients. Our results corroborate that OTFs are complex faults where rheological and geometrical segmentation result in a complex interplay of slow and fast slip release.Acknowledgements: We gratefully acknowledge Baptiste Rousset and Estelle Neyrinck for generously sharing their geodetic matched filter code for this analysis.

Postseismic surface deformation offers key insights into subsurface lithospheric rheology and earthquake fault behavior, yet geodetic data often fail to capture its full complexity. Here, we use satellite radar images to derive time series of three-dimensional surface displacements following the 2023 Kahramanmaraş (Türkiye) earthquakes. The results show strong spatial and temporal deformation asymmetry across the East Anatolian Fault with the stiffer Arabian lithosphere exhibiting slower deformation decay than the Anatolian side. The temporal asymmetry excludes elastic afterslip from being the main postseismic process and instead the postseismic response is dominated by asymmetric viscoelastic relaxation as well as poroelastic rebound. These findings underscore the importance of both temporal and three-dimensional spatial deformation data in advancing understanding of post-earthquake recovery processes and subsurface lithospheric structure.

The Alpine‐Himalayan belt is one of Earth's most dynamic and complex regions, characterized by intense tectonic deformation and seismicity. Comprehensive analyses of continental‐scale crustal deformation and seismic hazards along this extensive orogenic belt require the compilation of large geodetic data sets. In this study, we integrate 42 published Global Navigation Satellite System (GNSS) velocity fields, building an internally consistent data set for the entire belt, spanning from Iberia to Southeast Asia and comprising 11,177 horizontal and 3,940 vertical velocities. We use this unified GNSS velocity field to estimate surface strain rates and their posterior uncertainties in the eastern Mediterranean region and the India‐Asia collision zone. Our results show large‐scale agreement between the orientation and style of geodetic and seismic strain rate tensors across the belt. Additionally, our analyses substantiate previously documented azimuthal alignments between principal strain rate directions and seismic anisotropy orientations, often used as a proxy for finite strain in the convecting mantle. These correlations are particularly apparent in the Aegean, North Anatolia, Tibet, Tian Shan, Altai, Sayan, and Baikal regions, underscoring the need for future research on the relationship between mantle flow and lithospheric deformation.

The Alpine-Himalayan belt is one of Earth's most dynamic and complex regions, characterized by intense tectonic deformation and seismicity. Comprehensive analyses of continental-scale crustal deformation and seismic hazards along this extensive orogenic belt require the compilation of large geodetic datasets. In this study, we integrate 42 published Global Navigation Satellite System (GNSS) velocity fields, building an internally consistent dataset for the entire belt, spanning from Iberia to Southeast Asia and comprising 11,177 horizontal and 3,940 vertical velocities. We use this unified GNSS velocity field to estimate surface strain rates and their posterior uncertainties in the eastern Mediterranean region and the India-Asia collision zone. Our results show large-scale agreement between the orientation and style of geodetic and seismic strain rate tensors across the belt. Additionally, our analyses substantiate previously documented azimuthal alignments between principal strain rate directions and seismic anisotropy orientations, often used as a proxy for finite strain in the convecting mantle. These correlations are particularly apparent in the Aegean, North Anatolia, Tibet, Tian Shan, Altai, Sayan, and Baikal regions, underscoring the need for future research on the relationship between mantle flow and lithospheric deformation.

The Gulf of Aqaba (GoA) is the seismically most active region in the Red Sea, with a history of large earthquakes and posing a high seismic hazard to coastal communities. This study uses back‐projection and dynamic rupture simulation to investigate the largest instrumentally recorded earthquake in the GoA, the 1995 7.2 Nuweiba earthquake, to understand stress loading, failure mechanisms, and cascading rupture potential on complex multi‐segment fault systems. Our results reveal a multi‐segment cascading rupture with supershear rupture on the optimally prestressed Aragonese Fault. Supershear rupture significantly amplified offshore ground shaking, elevating seismic hazard for the narrow gulf's coastal regions. This event partially ruptured the GoA fault system, increasing Coulomb stress on the unbroken southern Arnona Fault, which has been silent since 1588. This stress loading likely advanced a future rupture on this critical segment, requiring close monitoring and increased preparedness for a potential large earthquake in the region.

The Zabargad Fracture Zone (ZFZ), the largest rift‐axis offset in the Red Sea, extends from 23.5°N to 26°N. It is covered by thick sedimentary layers that have hindered the ability of geophysical data sets to image the geometry of the normal faults and any potential transform faults. Passive seismology observations in the region have been limited to onshore recordings, leading to high uncertainty in earthquake locations and hampering detailed seismicity analyses. To address this limitation, we deployed a network of ocean bottom seismometers (OBSs) and land‐based stations for a duration of 12 months. From these data, we built the first high‐resolution earthquake catalog for this region of the Red Sea by applying a deep‐learning‐based algorithm to automatically detect earthquakes and pick P‐ and S‐phases. To obtain reliable earthquake locations, we derived a 1‐D seismic velocity model of the ZFZ. We established a calibration between measured on land and on OBSs to overcome magnitude overestimation using the OBS data alone. Additionally, we computed focal mechanisms of selected events using waveform polarities and amplitude ratios. The hypocenter distribution reveals two major seismicity clusters, the North and South clusters. The North cluster highlights NW–SE trending normal faults reflecting the extensional tectonics of the Red Sea. In the South cluster, we discover a NE–SW transform fault, possibly in its early development stage and NW–SE normal faults. The depth of seismicity reveals variations in the brittle‐ductile transition zone depth, with shallow depth in the north indicating higher shallow lithospheric temperature.