This study utilizes GPS‑derived total electron content (TEC), critical frequency (foF2) from ionosondes, TEC from Swarm satellite measurements, the [O]/[N2] ratio from TIMED/GUVI, and the vertical electron density profiles from COSMIC to examine the ionospheric response over the East‑Southeast Asia and Australian sector during the May 2024 magnetic storm, the strongest since November 2003. The storm began at 17:05 UT on May 10, marked by a Sudden Storm Commencement (SSC) with an amplitude of approximately 74 nT in the SYM‑H index, which rapidly declined to about –518 nT by 02:14 UT on May 11. GNSS receiver chains were used to study the morphology of the equatorial ionization anomaly (EIA) during the entire storm period. During the main phase, a negative ionospheric storm effect was observed, as indicated by the decrease in foF2 at the PHUT and BACL stations and TEC at both of hemispheres. The decrease in foF2 and TEC is believed to be caused by the impact of the prompt penetration electric field (PPEF). A complex evolution of the EIA morphology was observed during the recovery phase. During the recovery phase on May 11, hmF2 exhibited repeated uplifts over Southeast Asia in response to fluctuating PPEF associated with successive southward‑to‑northward and northward‑to‑southward reversals of the interplanetary magnetic field (IMF) Bz before 15:00 UT. On May 11, the EIA structure showed degradation, with a double‑peak morphology in both hemispheres associated with strong PPEF fluctuations. The EIA crests shifted equatorward, and an enhancement/reduction of foF2 at the equator/near EIA crest region in the Northern Hemisphere was observed, which is associated with PPEF, equatorward meridional winds and changes in [O]/[N2] ratio. The effect of the ionospheric disturbance dynamo was identified from magnetic data at PHUT and GUAM observatories. The disappearance of the northern EIA crest observed on May 12 might have resulted from the combined influence of factors such as the ionospheric disturbance dynamo effect, meridional winds (the equatorward meridional and transequatorial meridional winds), and the decrease in the [O]/[N2] density ratio. Hemispheric asymmetry of the EIA was observed during the first two days of the recovery phase (May 11‑12). On May 13, an increase in the amplitude of the southern crest (14 TECU) was observed compared to May 12; the northern crest reappeared, and both crests showed a tendency to shift polewards.
The 10–11 May 2024 superstorm had three main phase steps with peak intensities SYM-H=-183, −354 and −518 nT. During the second main phase red and green auroras occurred over Braunschweig and Göttingen, Germany. The Braunschweig and Göttingen red and green auroral images were taken during intense substorms within the storm second main phase. The high-altitude red aurora displayed brightness streaks/rays, which continued to lower-altitude green auroral brightness streaks/rays. Of the many postulated mechanisms for causing red auroras, it is concluded that high energy electron precipitation along the Earth's magnetic field lines was the main mechanism for both auroral streaks/rays. The plasmapause location estimated using the Dst index was L∼2.6, corresponding to the approximate L shell of Braunschweig and Göttingen.
Eastern Anatolia is one of the most tectonically active regions of the Alpine‑Himalayan orogenic belt, shaped by the ongoing Arabia‑Eurasia continental collision and major strike‑slip fault systems. In this study, we constrain the crustal structure beneath the Karlıova Triple Junction‑Bingöl region using teleseismic receiver function analysis combined with H‑𝜅 stacking. We analyze a high‑quality and long‑term dataset recorded by permanent broadband seismic stations of the Kandilli Observatory and Earthquake Research Institute, using teleseismic earthquakes with Mw ≥ 6.2 selected from an initial larger dataset and epicentral distances of 30°‑95°. The results reveal strong lateral variations in crustal thickness, with Moho depths ranging from ~30 km to ~47 km. Stations located along major active fault zones generally exhibit thicker crust. Average crustal Vp/Vs ratios vary between 1.64 and 1.95, indicating significant heterogeneity in crustal elastic properties. Clear Ps conversions and well‑developed crustal multiples confirm the robustness of the results, while additional early arrivals at several stations suggest internal crustal complexity. The observed patterns are consistent with geophysical and geodynamic models suggesting a hot, thinned, and relatively low‑density lithosphere beneath Eastern Anatolia. These results provide a consistent basis for interpreting lithospheric deformation and the relationship between crustal structure and major fault systems in Eastern Anatolia.
The Southern Mountain Zone of East Java is a structurally complex volcanic‑arc region characterized by strong lateral lithological heterogeneity and limited subsurface constraints. This study uses regional gravity‑anomaly analysis, horizontal‑derivative methods, and regularized three‑dimensional inversion to constrain regional‑scale subsurface density variations and identify candidate structural boundaries. Satellite‑derived gravity data from the GGMplus dataset were processed to obtain a Complete Bouguer Anomaly ranging from –134.3 to 170.5 mGal and a longer‑wavelength Regional Bouguer Anomaly ranging from –130.8 to 132.8 mGal. The regional component is interpreted primarily as a constraint on broad, deeper‑seated density variations rather than as a direct or unique image of subsurface geological structures. Sequential gravity inversion using Singular Value Decomposition (SVD) and Occam regularization was applied to iteratively update the model‑base geometry, density distribution, and block thickness. The normalized RMS data misfit decreased from approximately 15.5% to 3.02%, indicating progressively improved agreement between the observed and calculated gravity responses. This reduction represents improved data fitting and should not be interpreted as a direct measure of uncertainty or geological accuracy because gravity inversion remains intrinsically non‑unique. The resulting model delineates broad low‑, intermediate‑, and high‑density domains that are consistent with the regional distribution of sedimentary, volcanic, carbonate, and intrusive units. Horizontal‑derivative responses integrated with inversion cross‑sections identify several candidate structural boundaries associated with lateral density contrasts. Apparent normal‑ and reverse‑fault styles, including horst‑graben‑ and half‑graben‑like geometries, are inferred where prominent derivative responses coincide with density‑block variations. However, fault dip, displacement, and kinematics are not uniquely resolved from the gravity data. The results therefore provide regional‑scale constraints on major subsurface density domains and candidate structural boundaries rather than a unique high‑resolution reconstruction of the subsurface.
We present a new dataset of earthquake ground‑motion records for the volcanic area of Mount Etna (eastern Sicily, Italy), aimed at supporting seismological analyses and seismic microzonation studies. The dataset includes 200 volcano‑tectonic earthquakes with local magnitude ML ≥ 3.0 that occurred between 2008 and 2023, recorded by a dense network of permanent and temporary stations up to 150 km. Waveforms were processed using a uniform workflow based on manual phase picking, signal‑to‑noise criteria, and instrument correction. From the processed signals, we derived peak parameters (Peak Ground Acceleration and Peak Ground Velocity), Fourier Amplitude Spectra, and 5% damped response spectra, all distributed through a parametric table integrating ground‑motion measures with event, station, and record metadata. Site conditions were characterized through a multi‑level approach combining existing databases, geological information, Horizontal‑to‑Vertical Spectral Ratio analyses, and dedicated geophysical surveys at selected stations. Dataset consistency was evaluated through residual analysis, allowing the identification of anomalous records while preserving statistical representativeness. To support future ground motion modeling in the area, we identified two clusters with specific seismological characteristics, corresponding to different depth ranges. The resulting dataset provides a unique resource for investigating ground‑motion variability in volcanic environments, which are underrepresented in existing strong‑motion archives, and for advanced applications in ground‑motion modeling and seismic microzonation.
