Geophysical Journal International

SummaryDetermining the gravity potential is a fundamental task in geodesy and plays a critical role in various fields, including seismology, geodynamics and aerospace engineering. Grounded in the principles of general relativity, the high-precision determination of gravity potential using time and frequency signals has become a prominent research frontier in modern geodesy. This study employs multi-GNSS (Global Navigation Satellite System) carrier phase time and frequency comparison to determine the gravity potential. It develops a model for multi-GNSS Precise Point Positioning (PPP) time and frequency comparison, incorporating gravity potential estimation, and further investigates simulation methods for high-precision clock offsets and GNSS observations. Ten time and frequency links formed by eleven stations from the IGS (International GNSS Service) were analyzed using a simulation framework. The experiment incorporated simulated GNSS observations and eight types of clocks with varying performance levels to assess the capability of the multi-GNSS PPP time and frequency comparison model in determining gravity potential. The results demonstrate that the accuracy of gravity potential determination with multi-GNSS time frequency signal after coverage is approximately 0.1 m²/s². These findings affirm the feasibility and reliability of using GNSS time and frequency signals to determine gravity potential. Moreover, the convergence speed and accuracy of PPP solutions with ambiguity resolution show notable improvements over ambiguity float solutions, with accuracy enhanced by roughly 10 per cent. As atomic clock performance and GNSS satellite products continue to advance, GNSS-based time and frequency comparison holds great promise for achieving even higher precision in gravity potential measurements and contributing to the unification of the global vertical height datum.

SummaryCoulomb failure stress change (ΔCFS) quantifies the earthquake-induced difference of shear stress and frictional resistance on a receiver fault, with the latter being proportional to the effective normal stress change. ΔCFS has become a widely used measure for studying earthquake triggering, dynamic rupture processes and earthquake-induced secondary disasters. In simple layered or half-space elastic media, methods for computing static ΔCFS have been well established, with programs such as Coulomb3, PSGRN-PSCMP, and AutoCoulomb being widely used. In contrast, dynamic ΔCFS evaluation generally relies on numerical discretization schemes, such as finite-difference, finite-element, boundary-element and discontinuous Galerkin methods, which, while suitable for complex structures, are computationally expensive. To overcome these limitations, we develop DynCFS, a user-friendly, Green’s function based and therefore computationally efficient program for calculating both static and dynamic ΔCFS in layered elastic media. The tool enables rapid assessment of dynamic triggering effects, both between successive earthquakes and among multiple sub-events or faults during an earthquake.

SummaryIn February-March 2025 a seismic sequence occurred in the western sector of the Aeolian Archipelago (Southern Tyrrhenian Sea, Italy), a seismotectonic complex region located along the Africa-Eurasia plate boundary and mainly controlled by their NW-trending convergence. The seismicity, located ∼20 km south of Alicudi Island and ∼40 km north of the coast of Sicily, started on February 7 with an earthquake of magnitude Mw 4.7 that was followed in the next month by 42 events with local magnitudes between 1.2 and 3.4. Notwithstanding its moderate energy, this recent seismicity offers a unique opportunity to investigate seismogenic processes in a region for which a seismic potential of ∼M7 or even more has been suggested and a relevant data paucity mainly related to its offshore location was widely recognized. We tackle the limitations of not-optimal network configuration, by designing an ad-hoc approach, which integrates different advanced techniques. Specifically, we combine Bayesian methodology for accurate absolute hypocenter locations, machine learning techniques for detection of weaker events, Distance Geometry Solvers for relative locations, and a probabilistic inversion tool for source mechanism estimation. Our analysis led us to strongly enrich the dataset of detected earthquakes, and to define the causative source of the 2025 sequence as a NE-SW trending N-dipping thrust faulting structure. The proposed source agrees with the regional seismogenic stress field and with the structural architecture of the southern Tyrrhenian portion of the Africa-Eurasia plate margin by also adding new constraints in a sector where no known fault segments were previously reported. This study provides new insights on seismogenic processes in the investigated area, while proving the effectiveness of the employed combined approach for characterizing seismogenic sources in poor network configurations.