Understanding the three-dimensional geometric structure of the Earth’s magnetospheric magnetic field is crucial for analyzing plasma physics phenomena. However, conventional methods often overlook geometric properties orthogonal to magnetic field lines. To address this, we adopted a local-frame approach that extends the Frenet–Serret system, enabling the quantification of curvature and torsion in directions both parallel and perpendicular to the field lines. We developed an open-source Python library, geopack-vectorize, featuring the Mageometry component as the analysis framework, and leveraged NumPy-based vectorization to enable high-speed execution across multiple points. Performance benchmarks demonstrate that the vectorized implementation achieves speedups ranging from approximately 30 to 116 times compared to conventional scalar processing for Tsyganenko models when processing 1,000 points. Through application to dipole and Tsyganenko 96 models, we demonstrated that the spatial distributions of the eight independent derivative coefficients can be efficiently derived. Consequently, this library enables the quantitative and visual assessment of magnetic field curvature and torsion—properties that were previously understood only qualitatively through field-line tracing. This library provides a standard, efficient tool for the quantitative analysis of complex magnetic field configurations, facilitating large-scale simulations and data analysis in magnetospheric physics.
The El Niño–Southern Oscillation (ENSO) is a major driver of interannual climate variability, influencing terrestrial water storage (TWS) via atmospheric teleconnections and thereby affecting the Earth’s rotation through hydrological angular momentum (HAM) variations. To assess the relevance of these hydrological signals, we construct excitation budgets of the axial effective angular momentum and compare them with geodetic excitation from the IERS EOP 20 C04 series. On interannual time scales, the HAM contribution remains small due to the dominance of atmospheric angular momentum and partial compensation by barystatic ocean adjustments. Nevertheless, noticeable differences between the tested hydrological data sets are found. The hydrological model Open Source (OS) LISFLOOD slightly improves the budget closure, while the Land Surface Discharge Model (LSDM) reduces the agreement with geodetic excitation. We, therefore, revisit regional ENSO–TWS relationships and their contribution to axial HAM variability by comparing model-based TWS (OS LISFLOOD and LSDM) with respect to the satellite-based TWS observations from the GRACE/GRACE-FO missions. Lagged cross-correlation analyses identify regions with significant and temporally coherent responses to ENSO, from which basin-integrated HAM functions are derived. An EOF decomposition is used to quantify their contribution to hydrologically excited Length-of-Day (LOD) variability. The results reveal a robust ENSO-related signal in interannual HAM variability, dominated by a small number of tropical basins, with the Amazon basin emerging as the most influential contributor across all data sets. This indicates a low effective spatial dimensionality of the ENSO–HAM coupling. Among the data sets, OS LISFLOOD provides the best agreement with interannual variability, likely reflecting its more detailed representation of hydrological processes, whereas the older LSDM exhibits artificial variability linked to changes in atmospheric forcing of ECMWF operational data and the outdated ERA40 and ERA-Interim reanalyses. GRACE/GRACE-FO confirms the large-scale ENSO signal but is limited by the relatively short observational record.
This paper presents ionospheric scintillation observations in Southeast Asia during the ascending and maximum phases of Solar Cycle 25 (2020–2025). Ionospheric scintillation has been widely used to investigate equatorial plasma bubbles (EPBs) for several decades. However, such investigations have not yet been conducted in Southeast Asia during Solar Cycle 25, despite their importance in advancing our understanding of EPB behavior. In this study, we analyze the ionospheric scintillation data collected between 2020 and 2025 in Bac Lieu, Vietnam, and Chumphon, Thailand, using observations from the Southeast Asia low-latitude ionospheric network. The ionospheric scintillations intensified from the evening to the post-midnight sector, particularly during the equinoctial months (March–April and September–October) and years of higher solar activity, consistent with the general characteristics of EPBs. As solar activity increased, scintillations could occur until later post-midnight hours. Furthermore, the ionospheric scintillations tended to intensify when the main phase of geomagnetic storms occurred in the evening and weakened when the recovery phase began in the evening. The storm-time electric fields associated with the evening onset of the main and recovery phases of geomagnetic storms are likely important for the EPB intensification and suppression, respectively. Additionally, the storm-time electric fields associated with the onset of the recovery phase before sunrise can result in EPB development. Post-sunset ionospheric scintillations were suppressed for 1–2 days following the onset of the recovery phase, possibly because of the disturbance dynamo electric fields that can persist for several days. These results provide new insights into EPB morphology during the ascending and maximum phases of Solar Cycle 25 in Southeast Asia and highlight the critical role of the timing and evolution of geomagnetic storms in EPB development.
The effects of the May 22nd 1960 Chile tsunami are well documented along the Pacific Ocean coastlines, yet its characteristics within the source region remain poorly documented. Here, we address this gap by offering a compiled dataset of near-field tsunami observations. The dataset integrates published data, observations inferred from eyewitnesses interviewed 50–60 years after, and high-resolution runups based on the combination of post-event aerial photographs and LiDAR at two sites. Our compiled dataset comprises 246 qualitative and quantitative entries, substantially reducing reliance on the limited set of historically well-documented sites. In the compiled dataset, runup observations increase from 21 to 51, and five new flow-depth measurements are added to the existing 31 entries. The compiled dataset shows maximum and average runups of 25.9 and 9.6 m, respectively, and other types of records. To reconcile the heterogeneity among sources, we introduce a multi-criteria reliability data index that provides a comparative yet subjective measure of data quality. Despite being the largest instrumentally recorded earthquake (Mw 9.2–9.6), runups are comparable to smaller events in the Pacific Rim (Chile 2010, Japan 2011 and Russia 2025), but they extend over a larger stretch of coastline as a consequence of the longer rupture zone. However, the limited number of observations in the curated database may result in an underrepresentation of localized extremes when compared to recent events.
The magnetotelluric (MT) method is a widely used tool for geothermal reservoir exploration due to its capability of imaging fluids in the Earth’s crust. However, in urbanised environments, its application is often challenged by anthropogenic noise and low signal-to-noise ratios. In this study, we investigate the potential of MT data to image a low-enthalpy hydrothermal reservoir located at 1.5–2 km depth beneath the urban region of Annecy (France), a geologically complex area marked by the active Vuache Fault systems. A total of 46 broadband MT stations were deployed over a 100 km ^2 area. We aimed to: (1) Enhance MT signal quality in an urban setting using a processing based on multivariate linear regression and eigenvalue-based selection criteria performed on long-duration recordings; and (2) Assess the potential impact of electrical anisotropy on data interpretation through dimensionality analysis, isotropic and anisotropic inversions. Results show that the processing significantly improved the signal-to-noise ratio and MT responses, especially from 1 to 0.1 Hz when long duration (1 week) recordings are performed. Dimensionality analysis reveals a consistent geoelectrical strike direction and anisotropic hints, yet with spatial variability suggesting a structurally complex medium. A 3D isotropic inversion imaged the main local geological units and structures that are expected in the Annecy area: a clear resistivity contrast associated with the Vuache Fault, high resistivity associated with Jurassic and Cretaceous limestones and a shallow conductive area in the Molasse units. An outstanding conductive area (10–20 Ω m) is found around the Vuache Fault trace, close to a known thermal spring. An axial anisotropic impedance inversion provided a better fit and the calculation of the horizontal anisotropy index showed remarkable consistency with seismicity distribution. The anisotropy index indicates a higher conductivity along the Vuache Fault, in the 1996’s M5.3 earthquake aftershock zone. We discuss the computed anisotropy and propose a simple test to identify the possible presence of spurious anisotropy related to resistivity and topography contrasts. Our findings demonstrate the feasibility of MT for urban geothermal exploration when advanced processing techniques are applied, and highlights the importance and challenges of considering electrical anisotropy in MT data.
Understanding the characteristics and origin of groundwater is important for evaluating groundwater, subsurface resources and their utilization, and assessing their relationships with volcanic activity and earthquakes. Northeast Japan is located in a typical subduction zone of the Pacific Plate and hosts numerous volcanoes from the volcanic front to back-arc region. In the Tohoku region, saline groundwater is widely distributed from coastal to inland areas, and 281 samples of this were collected for this study. Hydrogen and oxygen isotopic data indicate that the main possible sources of the chlorine are seawater, magmatic fluids, and marine pore water, including water associated with oil and gas fields. The spatial distribution of Br/Cl and I/Cl ratios shows characteristic variations across the fore-arc to back-arc regions. In particular, from 10 km east to 25 km west of the volcanic front, the saline groundwater commonly has low Br/Cl ratios (< 1 × 10⁻3, i.e., lower than seawater) and relatively high I/Cl ratios ((30–700) × 10⁻⁶; i.e., higher than seawater), suggesting that fluid affected by volcanic activity may contribute to the observed halogen signature. A three-component mixing analysis based on halogen ratios for seawater, magmatic fluid, and marine pore water (including water associated with oil and gas fields) was conducted using hypothetical endmembers to estimate the origins of the Cl. These results show that relatively high magmatic Cl contributions generally characterize samples collected within 25 km west of the volcanic front and within 20 km of the nearest Quaternary volcano. However, even within 20 km of the nearest Quaternary volcano, the contributions of magmatic Cl vary widely, suggesting that magmatic fluids are supplied locally through fractures and faults. The depth above which 90
Solar flares can cause fluctuations in the Earth's magnetic field, known as the solar flare effect (SFE). However, their impact on the geomagnetic field is highly complex and exhibits regional dependence, and its characteristics have not been established. Many X-class flares occurred consecutively in May and October 2024, resulting in numerous observed SFEs. This study investigated the characteristics of SFE by conducting a detailed analysis of geomagnetic data from a global network of magnetometers, including high-cadence observation stations such as Kakioka and Chichijima, for five major X-class flares that occurred during this period. The SFE signal was extracted using a 1-h moving-average-based difference method to reduce uncertainties associated with traditional quiet-day curve subtraction. Our analysis revealed a positive correlation between the SFE magnitude and solar elevation angle for each event; however, the magnitude of SFE is primarily determined by the GOES X-ray class (solar flare magnitude). The time evolution of the SFE showed typical response, with the SFE peak lagging flare X-ray peak by approximately 3 min, reflecting the ionospheric response time to flare emission. We found anomalous response during the X9.0 class flare occurred on 3rd Oct, 2024: an enhanced SFE at the high-latitude station Lerwick (LER), attributed to the superposition of the flare effect on the active auroral current system. This fact strongly suggests that a different physical mechanism is responsible for generating the local westward electric field. These results demonstrate that the SFE response is governed not only by the flare magnitude and solar elevation angle but also by the local ionospheric current system.
This study introduces structural upgrades to REGARD, Japan’s real-time GNSS-based coseismic analysis system, addressing two long-standing limitations in real-time geodetic source modeling: the absence of explicit uncertainty quantification in fault estimates and positioning instability due to reference‑station dependence. These limitations reduce the reliability and physical interpretability of automated products used for rapid earthquake and tsunami assessments. To quantify uncertainty under strict real-time constraints, we implement a Bayesian inversion framework based on Markov chain Monte Carlo (MCMC), termed RUNE, for estimating a single rectangular fault model. RUNE outputs posterior probability density functions for moment magnitude (Mw) and fault parameters. Stable and efficient operation is achieved through physically informed priors and likelihood regularization through variance lower bounds designed to ensure statistical consistency, thereby suppressing noise-driven overfitting while retaining sensitivity to genuine crustal deformation. To improve positioning robustness, we introduce a real-time precise point positioning (PPP) cluster that eliminates reference-station dependence and mitigates network-wide translational artifacts inherent in real-time kinematic (RTK) positioning. Additional procedures—automatic station screening based on per-epoch position uncertainty and removal of common-mode trends estimated from distant stations—further stabilize displacement fields and improve the validity of the statistical assumptions used in Bayesian inversion. Applications to recent Japanese earthquakes, including the 2024 Noto Peninsula and Hyuga-nada events, together with 5 years of operational statistics, demonstrate that the combined MCMC–PPP upgrades markedly reduce false alarms while remaining consistent with post-processed solutions. Overall, the introduction of explicit uncertainty quantification and stabilized real-time positioning enhances the reliability and interpretability of automated GNSS-based coseismic source modeling for rapid hazard assessment.
The Kelvin–Helmholtz (KH) instability is a fundamental plasma process in many astrophysical environments; its vortices facilitate solar wind energy transport and plasma mixing. We investigate the energy flux density distribution and fluctuations of a typical KH vortex event observed by THEMIS across different magnetopause regions. Power spectral density (PSD) analysis of different energy flux densities reveal that their peaks correspond to the main period with a maximum of approximately 138 s for efficient energy transport. Satellite observations show that the spatial distributions of mass and energy vary markedly across different regions of magnetopause KH vortices. The region near the inner magnetopause is predominantly governed by electromagnetic energy flux density, whereas the area near the outer magnetopause is more significantly influenced by a combination of thermal and kinetic energy flux densities. Mass transport mainly occurred near the outer magnetopause, while plasma heating may have taken place in the outer magnetosphere. Furthermore, we estimate a local, per-unit-area energy transmission fraction across the magnetopause during the KH interval by time integrating the boundary-normal energy flux density. Using upstream OMNI data as a proxy for the incident solar wind energy flux, we infer that up to ∼ 2.19
Earthquake swarms are known to reflect underground fluid movement and stress changes. However, their occurrence patterns and the mechanisms underlying hypocenter migration remain poorly understood. In this study, we focused on two earthquake swarms that occurred at Izu-Oshima in September and October 2023. By detecting microearthquakes and determining their hypocenters using seismic waveform correlation, we captured the hypocenter migration likely reflecting the underlying diffusional process. Specifically, in both swarms, the hypocenters exhibited southeastward migration. The diffusion coefficient, which quantifies the speed of diffusive migrations, was larger in the second swarm compared to the first one. These results suggest that fracture structures formed in the first swarm by magma intrusion or associated underground fluid movement may have facilitated hypocenter migration of the second swarm sequence.
In May 2024, multiple X-class solar flares, full-halo coronal mass ejections (CMEs), severe geomagnetic disturbances, and severe ionospheric negative storms were observed, and these space weather events caused some social impacts. In this study, we analyzed the performance of space weather forecasts for these extreme space weather events, focusing on maximum forecast levels; X-class solar flares, geomagnetic disturbances with K ≥ 7, and ionospheric storms with I-scale = I3, using multi verification indices such as proportion correct (accuracy), probability of detection (discrimination), false-alarm ratio (reliability), frequency bias (bias), and equitable threat score (skill). As a result, NICT’s forecasts were evaluated as having a strong discrimination ability with moderate reliability for X-class solar flare, and high accuracy with subject to discrimination ability for I3 ionospheric storms, while for K ≥ 7 geomagnetic disturbances forecast, nearly perfect performance had been achieved by using solar wind simulation (SUSANOO-CME) incorporating multiple earth-directing CMEs. Comparative analyses with forecasts issued by other regional warning centers (RWCs) of the International Space Environment Service (ISES) indicated that RWC Japan showed the highest discrimination capability for X-class solar flares, while RWC USA showed the highest skill with zero false alarms. Perfect skill for K ≥ 7 geomagnetic disturbances were archived by RWC Japan, together with RWC Australia. Although continued efforts to improve forecast performance are still significant subject, we anticipate that the evaluation presented here will support appropriate implementation of effective measures to mitigate space weather risks to modern social infrastructure.
Joint inversion of multiple geophysical datasets is a powerful approach to reducing the inherent non-uniqueness and uncertainty in subsurface imaging. However, traditional coupling constraints, such as the cross-gradient method, often struggle with the significant resolution disparity between magnetic and magnetotelluric (MT) data, leading to structural blurring or mutual interference. To address these challenges, we propose a novel coupling operator termed the Minimum Physical Property Variation Support Coupling (MPVS). By integrating the dot product of physical property variations with the minimum support functional, the MPVS operator introduces a spatially adaptive penalty mechanism: it imposes a heavy regularization penalty on structurally inconsistent regions while relaxing the constraint in regions exhibiting structural consistency. This synergy allows for the precise modulation of the degree of consistency through the minimum support function. We demonstrate the mechanism of our proposed new coupling strategy through a theoretical test, followed by two two-dimensional synthetic modeling tests that verify its effectiveness and practical applicability under diverse conditions. Numerical results from a dual-block synthetic model demonstrate that the MPVS operator successfully overcomes the inherent limitations of the cross-gradient method. Specifically, it prevents high-resolution MT results from being distorted by the diffuse nature of magnetic inversion, while simultaneously guiding the magnetic susceptibility model toward a more compact and geologically plausible geometry. Furthermore, the coupling strength is controlled by the focusing factor; a larger focusing factor promotes higher structural consistency between the two methods, whereas a smaller factor allows the results to converge toward their respective individual inversions. Finally, synthetic tests on a complex model further validate the robust applicability of the MPVS coupling framework in handling intricate scenarios. This MPVS based joint MT and magnetic inversion framework provides a robust and flexible solution for the integrated interpretation of multi-physics data in complex geological environments.
An Mw 8.8 earthquake on 29 July 2025 generated a tsunami near the Kamchatka Peninsula. The interferometric Synthetic Aperture Radar (InSAR) satellite Surface Water and Ocean Topography (SWOT) produced images of sea surface height anomalies (SSHAs) approximately 600 km from the epicenter about 70 min after the earthquake. The image shows concentric dispersive tsunamis as SSHA and we inverted the observed SSHA for the earthquake fault slip distribution using dispersive tsunami modeling. We adopted the Normalized Cross-Correlation (NCC) to determine the tsunami start time and to assess the agreement between the observed and synthetic images. The obtained slip distribution revealed a large slip of approximately 16 m in the southern region concentrated near the trench axis. This suggests a localized rupture extending to the trench axis at the shallowest part of the plate interface along the Kamchatka trench, where the Pacific Plate subducts beneath the North American Plate. The estimated magnitude of Mw 8.8 is consistent with the United States Geological Survey (USGS) estimate. Synthetic tsunami waveforms at the three nearest tsunami stations in the deep sea showed good agreement with the observed sea level time series. For the first time, we demonstrated that the earthquake slip can be estimated solely from SWOT satellite tsunami imagery. Our slip model revealed local spatial variability in the slip distribution that far exceeds the slip expected from plate motion and recurrence intervals. Such unexpectedly large fault motion that directly impacts the tsunami hazard forecast can be estimated quickly if SWOT-like imagery becomes available in near real time.
In recent decades, the monitoring of volcanoes has been revolutionized by the launch of Earth-observing satellites and advances in thermal infrared remote sensing. These developments have revealed a wide range of thermal responses of volcanic surfaces to subsurface processes, even demonstrating that eruptions are often preceded by measurable thermal anomalies. This recognition highlights the need for robust tools to systematically detect and track such anomalies, making full use of existing satellite datasets and maximizing the value of current instruments in orbit. To address this challenge, we present the Subtle Surface Thermal Anomalies Recognizer (SSTAR), a versatile and user-friendly application designed to analyze diffuse thermal anomalies, i.e., subtle thermal unrest ( 1 K) across large areas (several km2). SSTAR leverages data from NASA’s Terra and Aqua satellites, which host the Moderate Resolution Imaging Spectroradiometers (MODIS), and builds upon a robust statistical framework. By processing pixel-level data, SSTAR tracks the temporal evolution of diffuse thermal anomalies at specific target sites and maps their spatiotemporal distribution across extended areas. Key features include filtering tools that distinguish between long-term (years) and short-term (weeks) anomalies, as well as uncertainty quantification using bootstrapping. The application is standalone, features an interactive interface for streamlined analysis, and is accessible to newcomers to satellite-based thermal remote sensing. At the same time, specialized users can customize the underlying scripts for other specific research needs. As a demonstration, we apply SSTAR to Shishaldin volcano (Alaska), revealing the emergence of significant thermal anomalies around the summit crater and flanks prior to eruptions. We envision SSTAR as a valuable resource for studying subtle thermal unrest at active volcanoes and hydrothermal systems, where the detection of faint and spatially coherent anomalies may help identify subsurface fluid pathways. Its flexible design enables integration with additional satellite datasets, positioning SSTAR as a forward-looking tool for advancing space-based volcanic thermal monitoring. Building on this capability, daily updated diffuse thermal anomalies are provided for target volcanoes through an open web platform hosted at Geosciences Barcelona—CSIC ( https://sstar.geo3bcn.csic.es/ ), to support surveillance agencies and expert committees in alert-level assessments.
This paper investigates the evolution of the La Fossa crater and Baia di Levante system at Vulcano Island between 2018 and 2024, focusing on the period following the 2021 unrest. Using a multiparametric dataset of ground and remote observations, we tracked the extent and intensity of volcanic degassing as it migrated from a primary and deeply sourced (La Fossa crater) to a peripheral and more hydrothermal zone (Baia di Levante, a bay at the base of the volcano). Our spatiotemporal analysis identified five distinct periods, each marked by specific physicochemical changes in the two areas. We observed a variable delay between the peaking of degassing in the central area and the arrival of gas in the peripheral zone, spanning from 7 months to nearly synchronous timing. Specifically, we suggest that the intense influx of deep fluids in mid-September 2021 transformed the complex network of fractures and shallow geothermal aquifers beneath Baia di Levante, significantly reducing its buffering capacity. This altered state persisted until the end of 2024, when a new deep fluid input observed at La Fossa crater was followed by an increased delay in degassing at Baia di Levante. We explain this variable delay through mechanisms such as fluid drainage and/or hydrothermal sealing of the more peripheral areas. This study underscores the critical importance of continuous monitoring of a volcano's fluid discharge capacity, particularly in identifying areas, where reduced degassing could lead to the hazardous accumulation of gas overpressure, as highlighted by the case of Vulcano Island.
Numerous studies have addressed the disastrous 2014 phreatic eruption of Mt. Ontake, central Japan, but limited studies have reported its post-eruptive activity. We report our latest analysis results of post-eruptive seismicity beneath the summit region of Mt. Ontake based on dense near-summit seismic observations since November 2017 and the latest subsurface velocity model. Long-term post-eruptive seismicity at a rate of several tens of events/month has continued for more than ten years, overlapped by unrest periods with more than ten events/day from February to March 2022 and from December 2024 to January 2025. Extremely high seismicity rates of more than 30 events during several minutes (spasmodic bursts) on February 23, 2022, and January 21, 2025, were associated with a tremor, the largest earthquake in each unrest period, a very long period (VLP) event, and a tilt change. The seismicity was clustered at two elevations: one near the boundary between younger (< 0.1 Ma) and older (0.78–0.39 Ma) eruptive deposit layers (YED and OED, respectively) and the other near the boundary between the OED and the basement. Long-term seismicity occurred mainly near the YED–OED boundary, and seismicity during the unrest periods mainly occurred near the OED–basement boundary. The 2025 spasmodic burst involved the rapid migration of hypocenters from the OED–basement to YED–OED boundary. We modeled these features by the upward migration of volcanic fluids impeded by a relatively low permeability OED and a lost buoyancy at the groundwater surface immediately above the OED. The results were horizontal intrusions of fluids along the OED–basement to YED–OED boundaries, which may have caused pore-pressure increase and seismicity near the two boundaries. The 2025 spasmodic burst may have created new fractures in the OED, similar to the 2014 eruption, as revealed by changes in the spatial distribution of the hypocenters. These findings are essential to link the observation of seismicity with the subsurface flow of volcanic fluids beneath Mt. Ontake.
This study presents a data-driven Sharp Boundary Inversion (SBI) algorithm for one-dimensional magnetotelluric data to objectively delineate abrupt subsurface resistivity transitions. Conventional smoothness-regularized inversions suffer from the unnatural blurring of discontinuous features, such as faults and lithological contacts. To overcome this limitation, the proposed SBI framework models these discontinuous features by locally relaxing smoothing constraints. The specific locations and relaxation strengths are determined within a novel two-stage optimization architecture guided by Akaike Bayesian Information Criterion (ABIC). In this scheme, an outer loop leveraging the Optuna hyperparameter optimization framework explores the optimal locations and relaxation parameters of sharp boundaries, and an inner Gauss–Newton loop iteratively updates the resistivity model, concurrently determining the global smoothing hyperparameter via ABIC minimization. This integrated scheme autonomously determines the optimal boundary depths and localized smoothing penalties without relying on subjective manual tuning or detailed a priori information. Numerical experiments demonstrate the stability of the algorithm, localizing boundaries with a maximum deviation of a single 50-m layer under severe 10
The present paper describes the construction of a global spherical harmonic model of the geomagnetic field, developed as the USTHB (University of Science and Technology Houari Boumediene) candidate for the 14th generation of International Geomagnetic Reference Field (IGRF). The model is based on scalar and vector data collected by the three satellites of the ESA Swarm mission. From 2 years of Swarm A observations, we derived the IGRF for the epoch 2025, its predictive secular variation (SV) for the 5-year period 2025.0–2030.0, as well as the Definitive Geomagnetic Reference Field (DGRF) for the epoch 2020.0. A brief description of the data sets, selection criteria, and the modelling methodology used to construct our candidate model is provided.
Large shallow slips play a key role in generating long-period ground motions near faults during inland crustal earthquakes with surface ruptures. In this study, we investigated the source characteristics of the shallow zone (≤ 3 km depth), interpreted as a weak layer with low S-wave velocities (≤ 3 km/s), to improve the recipe for broadband ground-motion simulations in Japan. We compiled source inversion results and long-period motion generation area (LMGA) models for six earthquakes (Mw ≥ 6.5) and examined slip and source time functions in the shallow zone. The results indicate that the average slip in the shallow zone is approximately 1.2 times the overall average slip in the rupture area. The LMGA, corresponding to large-slip areas in the shallow zone, exhibits a slip of 1.7 times the overall average slip and a slip duration of 2–8 s, suggesting that these regions are key in generating large long-period ground motion. Analysis of the geomorphological fault displacement data shows that the average fault displacement is approximately equal to the overall average slip, and the maximum fault displacement is approximately 2.5 times the overall average slip, indicating a quantitative proportional relationship between the geological and seismological parameters. These findings highlight the general characteristics of shallow-zone slip that are critical for reproducing large long-period ground motions in the near-fault region.
We investigated the factors contributing to variations in local magnitude (ML) among earthquakes of comparable moment magnitude (Mw). Specifically, we examined how radiated energy accounts for the difference between Mw and Mjma (∆M = Mw − Mjma), where Mjma is a form of ML routinely estimated by the Japan Meteorological Agency (JMA). To this end, we estimated the radiated energy (ER), seismic moment (M0), and moment-scaled radiated energy (eR = ER/M0) for small earthquakes (2.0 ≤ Mjma ≤ 3.0) in a highly active earthquake cluster near the Fukushima–Ibaraki border, northeastern Japan. We first determined source spectra by removing the site and path effects from the observed S-wave spectra and then estimated ER, M0, and eR for 9,538 earthquakes. The estimated eR was distributed around 10−5, comparable to previous estimates for crustal earthquakes, but varied by one order of magnitude, suggesting diversity of earthquake radiation processes. Mw was systematically larger than Mjma in the analyzed magnitude range (2.0 ≤ Mjma ≤ 3.0), consistent with previous studies, and likely reflecting the site and path effects. Notably, Mjma showed a stronger agreement with the energy magnitude (ME), derived from ER, than with Mw, suggesting that Mjma is more strongly controlled by ER than by M0. Consistent with this interpretation, ∆M systematically increased with decreasing eR among earthquakes with similar Mw. These trends persisted even after removing the depth and Mw dependence of eR. These results suggest that the diversity of Mjma at a given Mw reflects variability in dynamic rupture processes.
