Geomagnetic jerks are abrupt changes in the second temporal derivative of the core magnetic field and provide important constraints on core magnetohydrodynamic processes and mantle electrical conductivity structure.However,existing global geomagnetic jerk catalogs have limited temporal coverage,and the spatiotemporal characteristics of jerks after 2010 remain poorly constrained.In this study,one-minute geomagnetic data from 153 INTERMAGNET observatories covering 1997-2025 are combined with the CHAOS-8.2 model to derive robust monthly means of the internal magnetic field at 121 observatories.The eastward(Y)component,which is least affected by external field disturbances,is selected for analysis.Secular variation(SV)is estimated using the first annual differences of the monthly means,and geomagnetic jerks are identified from SV time series using a segmented linear fitting approach.The global geomagnetic jerk catalog is extended to 2024,with a mean timing uncertainty of 0.35 years.The results indicate that at least four large-scale jerks of the Y-component occurred globally between 2010 and 2020.Power spectrum analysis of the radial component of the internal-field secular acceleration(SA)at the core-mantle boundary indicates that jerks preferentially occur during the rising and falling phases of SA pulses.Moreover,the total SA energy summed over degrees 1-6 during this period exceeds that during 2000-2010,offering a physically consistent explanation for the broader spatial extent of geomagnetic jerks observed in 2010-2020.Further analysis identifies the 2023 jerk event as a regional event,with pronounced responses mainly observed at observatories in Europe,North America,and the South Atlantic,while only three observatories in Australia detected the signal in the Eastern Hemisphere.This spatial pattern is consistent with the surface distribution of the monthly mean SA.
The new generation of spaceborne single-photon LiDAR demonstrates remarkable advantages in beam capacity, data coverage density, and elevation measurement accuracy compared with linear-mode systems, offering significant potential for global three-dimensional topographic mapping from orbit. To address the need for onboard atmospheric delay correction, this study proposes a high spatiotemporal resolution ERA5-based atmospheric delay modeling approach. The temporal-spatial distribution characteristics of atmospheric delay are analyzed across different seasons, surface types, and latitudes. Furthermore, a global empirical correction model independent of auxiliary meteorological data is constructed and validated through simulation. The Advanced Topographic Laser Altimeter System (ATLAS) onboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), the only spaceborne single-photon LiDAR instrument currently operating in orbit, provides photon point cloud datasets along 16 global tracks for experimental verification. Results show that the proposed model achieves a correlation coefficient exceeding 0.99 with the official ICESat-2 atmospheric delay reference, with a mean bias of-2.5 cm and an average root mean square error (RMSE) of 2.7 cm. Due to spatiotemporal variability of atmospheric states, modeling errors are larger in spring and summer (average RMSE > 2.9 cm) and relatively stable in autumn and winter (average RMSE < 2.6 cm). The maximum deviation is less than 8.0 cm, indicating robust modeling performance. Surface type is identified as a primary error source: RMSE values over land and ocean are 2.7 cm and 2.6 cm, respectively, while sea ice yields up to 3.1 cm. Globally, atmospheric delay ranges from 0.9 to 2.6 m, with distinct geographic patterns and an exponential decay with photon height. The exponential model achieves an RMSE of 3.6 cm and mean absolute error (MAE) of 2.7 cm in residual fitting. Applying this model enables elevation correction with better than 0.25 m accuracy, while horizontal positioning remains unaffected. The findings confirm the effectiveness of ERA5 data in atmospheric delay modeling for spaceborne single-photon LiDAR and provide theoretical and practical reference for the onboard intelligent processing of next-generation spaceborne single-photon LiDAR data.
On March 28, 2025, an MW7.7 earthquake struck Myanmar. Following the event, several international seismological research institutions computed the focal mechanism solutions of this earthquake using different datasets and methodologies, yielding results with notable discrepancies. This study simulated the Earth's free oscillations excited by the Myanmar earthquake based on eight published focal mechanism solutions. The simulated signals are compared with observations from 10 superconducting gravimeters (SGs) distributed throughout China. By analyzing and constraining the focal mechanism using spheroidal normal modes in the 2-space5 mHz frequency band, we further refined the solution. Additionally, based on the optimal focal mechanism, we compared observed and simulated values to determine a more accurate seismic moment and fault dip angle. The results demonstrate that SG observations can effectively evaluate the overall focal mechanism of the Myanmar earthquake. The best-fitting solution yields simulated free oscillation signals that closely match observations, with an average misfit ( ) of 0. 1020 and a scaling factor ( <(S)over bar>) of 0.9054 (close to 1), indicating that the free (<(F)over bar>) oscillation signals recorded by superconducting gravimeters enable an effective overall evaluation of the source mechanism of the Myanmar earthquake, providing an independent and high-precision basis for the comparison and validation of different solutions. Using minimum misfit between theoretical and observed data as the criterion, we conduct a joint search for the seismic moment and fault dip angle. The results indicate that the Myanmar earthquake had a seismic moment of (5.5 +/- 0.5) x 10(20) N center dot m (MW =7.8), with an optimal dip angle of 65 degrees.
The northeastern (NE) margin of the Tibetan Plateau is an ideal place for investigating the mechanisms of lateral growth of the Tibetan Plateau. Seismic anisotropy is a direct method to study crust-mantle deformation. In the paper, P-wave receiver functions are calculated by time-domain iterative deconvolution method using the over ten years teleseimic waveform data recorded by the regional permanent broadband stations from the Chinese National Seismic Netwok (CNSN). We obtained lateral variations of crustal anisotropy parameters at 52 stations on the basis shear-wave splitting of Pms phase with different azimuthal angle of receiver functions bin to investigate crustal deformation mechanisms beneath NE Tibetan Plateau. Our shear-wave splitting results indicate: (1) The fast polarization direction of Pms phase in the northeastern margin of the Tibetan Plateau is WNW. Time delay of Pms is significantly larger than from the local-earthquake S-wave in this area (about 0.1 similar to 0.3 s), indicating the observed crustal anisotropy primarily originates from the middle-lower crust. (2) The fast orientations of Pms, local-earthquake S-wave and SKS beneath the Kunlun Block and the East Qilian Block are consistent with that of the strike of the surface active fracture, which implies that crust-mantle may be vertically coherently deformation; (3) The fast polarization direction of Pms near the Kunlun aligns with its strike, which suggests that the anisotropy in this region may be related to the alignments of minerals due to the strike-slip motion.
Deep exploration of solid metallic mineral resources is a critical technical direction supporting national resource strategies.Ambient noise surface wave imaging has emerged as an effective method for subsurface investigations due to its high-resolution,non-destructiveness,and environmental friendliness.However,the stability of noise surface wave dispersion is challenged by the complexity of surface wave noise sources and lateral heterogeneity of subsurface media.The array stacking method based on the frequency-Bessel(F-J)transform significantly enhances the reliability of shallow surface wave dispersion by improving dispersion stability and expanding effective frequency bandwidth.In this study,we implemented the F-J transform-based dense array surface wave imaging technique at a polymetallic mining area characterized by metamorphic rock structures in southeastern Finland.Utilizing ambient noise data recorded by nearly 1,000 seismometers,we successfully extracted high-quality Rayleigh wave dispersion spectra and constructed a fine three-dimensional shear wave velocity model at depths of 40-300 meters beneath the mining area.The model reveals that ore-bearing rock masses exhibit a three-dimensional spatial configuration of"shallow convergence,middle expansion,and deep contraction",which aligns closely with the geological context of multi-type schist structures formed by regional metamorphism.These findings validate the effectiveness of ambient noise surface wave imaging in detecting spatial configurations of ore bodies within complex metamorphic terrains,and provide a reliable geophysical basis for mineral resource reserve assessment and development planning,further demonstrating the practical value of the F-J transform-based dense array surface wave imaging technology in deep mineral exploration.
