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Abstract: Magmatic systems below volcanoes are often dominated by partially crystalline magma over the long term. Rejuvenation of these systems during eruptive events can impact lava composition and eruption style—sometimes resulting in more violent or explosive activity than would be expected, as was the case at Fissure 17 during Kīlauea’s 2018 eruption. Here, we explore how the crystallinity of unerupted intrusion magmas affect hybrid magma compositions and petrological signatures by constructing phase-equilibria models to evaluate mineral and melt compositions of low-MgO lavas erupted along the East Rift Zone of Kīlauea volcano on 30 to 31 January 1997 (Episode 54, Fissures A-F). We then compare calculated mixing proportions and petrologically derived magma volumes to GPS-based geodetic inversions of ground deformation and intrusion growth in an attempt to reconcile geodetic and petrologically estimated magma volumes. Open-system phase-equilibria thermodynamic models were used to constrain the composition, degree of differentiation, and thermodynamic state of a rift-stored, two pyroxene + plagioclase saturated low-MgO magma body immediately preceding its mixing with high-MgO recharge and degassed drainback (lava lake) magma from Pu‘u‘ō‘ō‘, shortly before fissure activity within Nāpau Crater began on 29 January 1997. Mixing models constructed using the Magma Chamber Simulator reproduce the mineralogy and compositions of Episode 54 lavas within uncertainties and suggest that the identity of the low-MgO magma body may be either variably differentiated remnants of un-erupted magmas intruded into Nāpau Crater in October 1968, or another spatially and compositionally similar magma body. We find that magmas derived from a single, compositionally stratified magma emplaced beneath Nāpau Crater in 1968 can mix with mafic Kīlauea magmas to reproduce average Episode 54 bulk lava, mineralogy and mineral compositions without necessitating the interaction of multiple, low-MgO rift-stored magma bodies to produce Episode 54 lava compositions. Further, by constructing phase equilibria-based mixing models of Episode 54, we can better define the pre-eruptive state of the magmatic system. The resultant mineral assemblages and compositions are consistent with the possibility that the now-fractionated, rift-stored magma body was compositionally stratified and ~ 40% to 50% crystalline at the time of mixing. Finally, we estimate the volume of the low-MgO magma body to be ~7.51 Mm3. Phase-equilibria model results corroborate field and geochemical relationships demonstrating how shallow intrusions at intraplate shield volcanoes can crystallize, evolve, and then be remobilized by new, later batches of mafic magma. Most notably, our MCS models demonstrate that the pre-eruptive conditions of an intrusive body may be recovered by examining mineral compositions within mixed lavas. Discrepancies between the geodetic constraints on volumes of stored rift versus newly intruded (recharge) magma and our best-fit results produced by MCS mixing models (which respectively are mmafic:mlow-MgO ≈ 2 vs. mmafic:mlow-MgO ≈ 0.75) are interpreted to highlight the complex nature of incomplete mixing on more localized scales as reflected in erupted lavas, compared to geodetically constrained volumes that likely reflect large spatial scale contributions to a magmatic system. These dissimilar volume relationships may also help to constrain eruptive versus unerupted volumes in magmatic systems undergoing mixing. By demonstrating the usefulness of MCS in modeling past eruptions, we highlight the potential to use it as a tool to aid in petrologic monitoring of ongoing activity.

Motivated by an application from geodesy, we study the connected k-center problem and the connected k-diameter problem. The former problem has been introduced by Ge et al. (ACM Trans Knowl Discov Data 2(2):1–35, 2008. https://doi.org/10.1145/1376815.1376816) to model clustering of data sets with both attribute and relationship data. These problems arise from the classical k-center and k-diameter problems by adding a side constraint. For the side constraint, we are given an undirected connectivity graphG on the input points, and a clustering is now only feasible if every cluster induces a connected subgraph in G. Usually in clustering problems one assumes that the clusters are pairwise disjoint. We study this case but additionally also the case that clusters are allowed to be non-disjoint. This can help to satisfy the connectivity constraints. Our main result is an O (log 2 k) -approximation algorithm for the disjoint connected k-center and k-diameter problem. For Euclidean spaces of constant dimension and for metrics with constant doubling dimension, the approximation factor improves to O(1). Our algorithm works by computing a non-disjoint connected clustering first and transforming it into a disjoint connected clustering. We complement these upper bounds by several upper and lower bounds for variations and special cases of the model. [ABSTRACT FROM AUTHOR]

The document is a corrigendum for an article on data-driven modeling of dissolved iron in the global ocean. It addresses errors in figures and equations, providing corrections to ensure accuracy. The main findings and conclusions of the study remain unaffected by these corrections, emphasizing the reliance on the dissolved iron projection derived from the random forest algorithm. The authors also provide updated data availability statements for readers to access historical versions of the simulated dissolved iron product. [Extracted from the article]

Neoproterozoic snowball Earth events lasted for multiple million years, experiencing many orbital cycles. Here we investigate whether the deglaciation of these events would be triggered more easily at certain orbital configurations than others, by using an atmosphere‐land model that considers meltpond formation on land ice. Results show that the threshold concentration of atmospheric CO2 (pCO2) required for deglaciation can vary from 6 to 10 × 104 ppmv under different orbital forcings. The threshold pCO2 decreases with the equatorial maximum monthly insolation (EMMI), which is affected most by the eccentricity and secondarily by obliquity. Therefore, we conclude that the snowball Earth deglaciation likely occurred when the eccentricity was high and obliquity was low. Compared to previous estimate that used present‐day orbital configuration which has a minimal eccentricity, the duration of snowball Earth events would likely be much shorter when the influence of orbital variations are considered. Plain Language Summary: This study explores how different orbital configurations might have influenced the termination of the Neoproterozoic snowball Earth events, during which Earth was covered by ice globally. Using a coupled atmosphere‐land model that is capable of simulating the formation of melt ponds on ice, we find that the atmospheric CO2 level needed to initiate the deglaciation varies with the Earth's orbital configurations. Specifically, the required CO2 levels are lower when the maximum monthly solar insolation received at the equator is higher, which is achieved when the Earth's orbit is more eccentric and the tilt of Earth's rotational axis is small. The results suggest that the duration of snowball Earth events could have been shorter when the influence of orbital forcing is considered. Key Points: Influence of orbital forcing on the snowball Earth deglaciation is tested using an atmosphere‐land model that considers meltpond on iceThe equatorial maximum monthly insolation is the most important factor that triggers the deglaciation of a snowball EarthThe needed CO2 to deglaciate a snowball Earth at the optimal orbital configuration is 40% lower than that under modern orbit [ABSTRACT FROM AUTHOR]

We present an approach to calculate potential fields on a planet's surface from regionally confined gradient data at spacecraft altitude, such as measurements of magnetic fields or gravitational acceleration. Our method uses altitude cognizant Slepian functions with a reference radial position that varies as a function of longitude and latitude. This is an evolution from previous altitude cognizant Slepian functions which use a fixed reference radial position. We demonstrate the advantage of these variable altitude cognizant Slepian functions over the fixed altitude cognizant Slepian functions and the classical Slepian functions using numerical tests. [ABSTRACT FROM AUTHOR]

The spatiotemporal pattern of surface displacements from large earthquakes provides crucial insights about the deformation of Earth’s crust at various scales and the interactions among tectonic plates. However, the lack of extensive and large-scale geodetic networks near such seismic events hinders our thorough understanding of the large-scale crustal deformation resulting from earthquakes. Using Türkiye’s extensive and continuous global navigation satellite system (GNSS) network during the moment magnitude 7.8 and 7.6 Kahramanmaraş earthquakes on 6 February 2023, we show that large earthquakes can induce far-field crustal deformations (>700 kilometers), exceeding current predictions from elastic dislocation models. They can lead to the mobilization of tectonic plates and the triggering of far-field earthquakes, which carries profound implications for seismic hazard assessments and necessitates a new perspective on crustal deformation and earthquake mechanics. [ABSTRACT FROM AUTHOR]

Glacial isostatic adjustment (GIA) describes the response of the solid Earth, oceans, and gravitational field to the spatio‐temporal evolution of ice sheets during a glacial cycle. Present‐day vertical displacements and sea‐level changes vary throughout eastern North America in response to the melting of the Laurentide Ice Sheet following the Last Glacial Maximum. We use the open‐source software SELEN4.0 (a SealEveL EquatioN solver) to investigate the influence of GIA on vertical land motions and sea‐level changes in eastern North America. Further, we evaluate the uncertainties associated with the lithospheric thickness and viscosity structure using an ensemble modeling approach (129,956 total simulations). We identify the best‐fitting rheological profiles by comparing modeled vertical displacements to vertical velocity rates derived from Global Positioning System (GPS). We find a general pattern of subsidence (causing accelerated relative sea‐level rise) in the eastern United States region and uplift (causing relative sea‐level fall) in the eastern Canada region consistent with previous studies for two tested ice sheet models (ICE‐6G(VM5a) and ICE‐7G(VM7)). Overall, we find lower rates of modeled vertical displacement using ICE‐6G(VM5a) compared with ICE‐7G(VM7), which produces lower residuals when compared with the GPS‐derived vertical velocity rates. Our ensemble analysis identifies adjustments to the nominal VM5a and VM7 viscosity models that improve fits to the GPS‐imaged vertical velocity rates throughout eastern North America and on the North American Atlantic Coast. The differences in our best‐fitting models for inland versus coastal regions highlight the importance of exploring lateral viscosity variations for GIA modeling throughout North America and elsewhere. Plain Language Summary: Approximately 19,000–26,000 years ago a massive ice sheet covered Canada and a portion of the northern United States. We investigate the Earth's surface movements following the melting of the ice sheet throughout eastern North America. Through computational modeling, we predict rates of vertical land motion and relative sea‐level change throughout eastern North America. We see a general pattern of downward movements (causing relative sea‐level rise) in the eastern United States region and upward movements (causing relative sea‐level fall) in the eastern Canada region. However, modeled rates vary depending on the assumptions about Earth's internal structure. We test different models of Earth structure, based upon variations of the Earth structure profiles paired with two published models of ice sheet history. Our different models vary the lithospheric thickness and radial viscosity structure (viscosity varies by depth only). By comparing the rates of Earth's surface movements generated by these different models to published data of observed vertical land motions, we determine which Earth structure models produce the best fits to the published observations. Differences in the best‐fitting Earth structure for different regions of eastern North America indicate the importance of exploring Earth structures that vary both radially and laterally. Key Points: Modeled present‐day vertical displacement and sea‐level change rates fit observed data better using ICE‐6G(VM5a) compared with ICE‐7G(VM7)Ensemble analysis suggests adjustments to VM5a and VM7 viscosity models improve fits to geodetic data throughout eastern North AmericaRegional differences in best‐fitting Earth structure support the adoption of lateral viscosity in glacial isostatic adjustment modeling [ABSTRACT FROM AUTHOR]

The seismic event of the 2016 Amatrice earthquake and its subsequent aftershocks have provided a significant opportunity to study seismic waves and their effects on the Apennine región, a very active seismic area. This research utilizes GPS data from three geodetic networks (ItalPos, NetGEO, and RING) to analyze the seismic waves generated by the earthquake, capturing seismic effects with great precision and resolution. By examining data from various GPS stations within the region, the study demonstrates the efficacy of GPS in providing detailed and accurate representations of ground motion. The study identifies co-seismic displacements and accelerations at monitoring stations by processing and analyzing GPS data, including precise point positioning strategies and wavelet adjustments. Moreover, a least squares adjustment method is employed to optimize the estimation of temporal parameters associated with seismic event detection across the spatial network of stations. The results obtained from GPS data are validated against seismic equipment, affirming their reliability in characterizing seismic events. Furthermore, the study elucidates the propagation of surface waves and path effects over the affected region, contributing to a comprehensive understanding of the earthquake impact. This research underscores the potential of GPS data as a valuable tool for rapid and precise characterization of seismic events, offering insights into ground motion dynamics and facilitating timely response and mitigation efforts. [ABSTRACT FROM AUTHOR]

Inter-satellite interferometric missions are critical in the ongoing monitoring of climate change. Next-generation Earth geodesy missions are opportunities to improve on mission cost and measurement sensitivity through revised design. To be considered feasible, mission architectures must meet an optical power requirement that factors in both shot noise and laser frequency noise. Reference-transponder mission configurations, like the Gravity Recovery and Climate Experiment-Follow On (GRACE-FO) mission, are designed for measurement down to a received carrier-to-noise density ratio of 70 dB-Hz—1.9 picowatts in shot-noise-limited detection. This work shows, through modeling and simulation, that the optical power level required to perform robust measurement varies significantly between mission configurations. Alternate configurations, such as retro-reflector-based schemes, can operate robustly down to much lower carrier-to-noise density ratios, with the example parameters considered here: down to 29 dB-Hz—150 attowatts in shot-noise-limited detection. These results motivate exploration of alternate missions configurations with revised optical power requirements, increasing the feasibility of new designs. [ABSTRACT FROM AUTHOR]

We examine whether geocoded World Bank foreign aid projects affect economic activity at the level of equally sized grid cells with a spatial resolution of 0.5 decimal degrees latitude and longitude. We use geospatial data for 58,676 grid cells during the period 1997-2013 with about one million grid-by-year observations. Using fixed effects estimating techniques, we evaluate the impact of World Bank foreign aid projects on grid cell night-time light growth. The estimates reveal that World Bank foreign aid projects contribute significantly and positively to grid cell economic activity measured by night-time light growth. We complement the fast-growing literature using geocoded data to assess aid effectiveness at the subnational level. We provide evidence that the lack of robust empirical findings at the country and subnational (e.g., ADM1 and ADM2) level can be explained due to spatial aggregation and the choice of spatial units. Additional estimates and robustness tests further corroborate our main findings. [ABSTRACT FROM AUTHOR]

According to General Relativity Theory (GRT), by comparing the frequencies between two precise clocks at two different stations, the gravity potential (geopotential) difference between the two stations can be determined due to the gravity frequency shift effect. Here, we conduct a clock-transportation experiment for measuring geopotential differences based on frequency comparisons via satellite links between two remote hydrogen atomic clocks. Based on the net frequency shift between the two clocks in two different periods, the geopotential difference between stations of the Beijing 203 Institute Laboratory (BIL) and Luojiashan Time-frequency Station (LTS) is determined. Comparisons show that the experimental result deviated from the reference of Earth gravity model EGM2008 result by (38.5 $ \pm $ ± 45.9) m in Orthometric Height (OH). The results are consistent with the frequency stabilities of the hydrogen clocks (at the level of ${10^{ - 15}}$ 10 − 15 ) used in the experiment. With the rapid development of time and frequency science and technology, the approach discussed in this study for measuring the geopotential is prospective and thus, could have broad applications. [ABSTRACT FROM AUTHOR]

Multiplicative error models have become increasingly vital in geodesy because observations based on electromagnetic wave measurement techniques are often disturbed by multiplicative errors. Currently, research on multiplicative error models primarily focuses on accuracy evaluation, equation or inequality constraints, coefficient matrix pathology, and variance component estimation; however, the issue of outliers has yet to be systematically addressed. In light of this, this study addresses the outliers problem in multiplicative error models. Initially, we analyzed the impact of outliers on least squares and bias-corrected weighted least squares; the findings indicated that the impact on bias-corrected weighted least squares propagates via the least squares solution. Subsequently, we proposed an algorithm for detecting outliers in multiplicative error models. Finally, we statistically analyzed the algorithm's accuracy through simulation cases; the results confirm its feasibility and superiority. [ABSTRACT FROM AUTHOR]

This study examines the accuracy and stability of three prominent Precise Point Positioning (PPP) services: AUSPOS, Trimble RTX, and OPUS, across varying observation periods from 30 to 180 minutes. Static GNSS data was collected at eight different locations over a three-hour timeframe. The analysis focused on comparing the geocentric coordinates (X, Y, Z) obtained from each service, utilizing metrics such as Root Mean Square Error (RMSE) and standard deviations to assess performance. The results revealed that processing time significantly influences accuracy, with Trimble RTX demonstrating the highest precision across all intervals. AUSPOS displayed considerable variations at shorter observation periods, while OPUS exhibited larger discrepancies, indicating potential challenges in stability. These findings underscore the strengths and weaknesses of each service, offering critical insights for selecting the most appropriate GNSS processing option tailored to specific geodetic applications. By highlighting the relationship between observation duration and positioning accuracy, this study contributes valuable knowledge to the field of geodesy and PPP service utilization. [ABSTRACT FROM AUTHOR]

Models of active deformation of the Earth's crust are predominantly represented with dislocations having a downdip continuation into the lower crust, where the fault slips continuously. This model predicts surface strain accumulation concentrated near the fault during the interseismic period. In an alternative model, faults do not extend beneath the elastic portion of the crust and are accompanied by a wide zone of distributed shear underneath, predicting a more constant strain rate lacking concentrations at the faults. We use high‐precision GPS data collected across the northern and central Walker Lane, USA— a region of complex faulting near the western edge of the Basin and Range Province to evaluate which model is appropriate. Despite the existence of dense continuous and semi‐continuous geodetic networks that have been surveyed for ∼20 years, the horizontal velocities reveal no evidence of localized strain accumulation across the fault surface expressions. Instead, deformation within the Walker Lane is uniformly linear, suggesting that the surface deformation reflects distributed shear within the ductile crust rather than focused deformation at faults. This suggests no downdip extension of the faults below the seismogenic layer. The shear zone is 172 ± 6 km wide in the northernmost Walker Lane narrowing to 116 ± 4 km in the central Walker Lane. The total velocity budget across the shear zone is 7.2 ± 0.1 mm/yr in the north, increasing to 10.1 ± 0.1 mm/yr in the central Walker Lane. We conclude that assuming the presence of lower crustal dislocations when estimating geodetic faults slip rates may be inappropriate. Plain Language Summary: Interpreting Earth's surface deformation, measured by high‐precision GPS stations, is crucial for understanding plate tectonics and assessing seismic hazard. Traditionally, the assumption has been that faults in the Earth's upper crust extend as discrete dislocations into the lower crust. In this paper, we show that there is no compelling evidence of this in the Northern Walker Lane region of California and Nevada. Instead, the geodetically measured deformation on the surface reflects uniform shearing in the lower crust. Our findings suggest that estimating slip rates on the faults with methods that assume deep dislocations may be inappropriate. Instead, the slip rate of a fault is likely to be controlled by the fault's position and orientation within the shear zone. This has significant implications for seismic hazard assessment, as accurate estimates of slip rates on faults are a crucial component in determining seismic risk. Key Points: Geodetic velocities in the Walker Lane reflect distributed shear in the lower crust rather than deformation due to discrete faultsEstimating fault slip rates with models assuming their continuation into the lower crust may be inappropriate in the northern Walker Lane [ABSTRACT FROM AUTHOR]

The issues in geodynamic research in Northern Eurasia over the past three decades with emphasis on the use of space technologies in geodesy and geodynamics are presented. The main focus is on the GNSS system as the most widespread and effective tool for geodynamic research due to the compactness and relative ease of installation of ground-based tracking equipment, as well as the possibility of its autonomous operation. The importance of precise GNSS positioning for monitoring small-scale geodynamic displacements of the Earth's surface, which requires millimeter-scale measurement accuracy, is emphasized. The issues of development of a precise reference frame for geodynamics and maintaining its long-term consistency based on the International Terrestrial Reference Frame (ITRF) are considered, as well as the problems and prospects of precise satellite geodetic measurements and geodynamic research in the context of the current reduction in interaction with international geodetic data centers. To solve the problems that have arisen, ways are proposed based on arranging a subcontinental-scale system for equalization of raw GNSS measurements. The capabilities of the GNSS network used for solving problems of geodesy and geodynamics are demonstrated by the example of the analysis of the tectonic rigidity of cratons of Northern Eurasia and the impact of motion of adjacent tectonic plates and variations of these motions in the past geological eras on the contemporary geodynamic setting of these cratons. [ABSTRACT FROM AUTHOR]

Abstract We propose a new reaction device for the microdiffusion analysis of CO2 in fluid samples from volcanic areas to improve the conventional analysis procedure, which requires a fixative and good handling skills. To accomplish this, a small resin reaction cell for the sample solution and acid (initiator for CO2 liberation) was devised and placed in a commercially available air-tight glass container with a Petri dish to form a microdiffusion analysis unit. The analysis was based on the principles of the conventional manual titration method that uses Ba(OH)2 as the CO2 absorbent. Using the new device, 99.5% recovery, with a relative standard deviation of 4.5% (n = 8), was achieved in a test analysis for 0.03 mmol of CO2 liberated from a Na2CO3 solution as a simulated sample. The analytical performance of the new device was almost comparable to that of conventional units under the experimental conditions of this study. Applying this new device for analyzing fluid samples from volcanic areas will contribute to enhancing the performance by reducing the possibility of CO2 contamination and by simplifying the process by eliminating the need for preparatory cleaning for fixative application. Graphical Abstract

Abstract To obtain novel information regarding normal faults that could cause tsunamis and large earthquakes on the outer slopes of the Kuril Trench, recently acquired multichannel seismic reflection (MCS) and bathymetric data are processed in this study to interpret the normal faults on the outer slope of the western Kuril Trench from near the Erimo Seamount to near the Nosappu Fracture Zone. This work also assesses the distribution and characteristics of the faults through comparisons with previous studies on the outer slope faults of the Japan Trench. The results of this study show that faulting starts approximately 100 km seaward of the trench axis, and a comparison with the normal fault distributions on the outer slope of the Japan Trench presented in previous studies reveals that the outer slope region of the Kuril Trench is narrower and more densely faulted than that of the Japan Trench. Additionally, the seismic and bathymetric data show that the Erimo and Takuyo-Daiichi Seamounts are deformed by normal faults. However, the number of faults in the seamount areas is lower than that in areas without them, which also affects the scale of the fault throws. The results of the MCS survey reveal that the thickness of the oceanic crust varies between 6 and 10 km due to the presence of these seamounts. Considering the positions of the outer swells presented in previous studies, the results suggest that the crustal and plate structures in the study area influence the distribution and formation of faults on the outer slope of the Kuril Trench. Graphical Abstract

Abstract Vertical holes of several tens of meters in diameter and depth have been discovered on the Moon, potentially serving as skylights into subsurface volcanic caverns resembling lava tubes. Because of their scientific importance and potential for use as future lunar bases, these lunar holes and caverns are expected to be targets of intensive exploration in the near future. Using numerical simulations, this study investigates the light environment within a directly and/or indirectly sunlit subsurface cavern accessed through a skylight hole. We specifically analyze the Mare Tranquillitatis Hole (MTH), one of the largest lunar vertical holes, situated near the Moon's nearside meridian. The floor and walls of the hole, and the walls and ceiling of its associated subsurface cavern are lit by reflected sunlight from other parts of the hole and cavern, such as the floors, depending on the solar elevation angle. Furthermore, this paper presents estimation results for camera imaging for a case in which solar elevation angle is 45° in the morning, which is appropriate timing for exploration. Assuming reflectance of 0.1 for the lunar hole and cavern surfaces, we estimate the incident energy onto each pixel of a camera as it descends to the hole's floor. We specifically simulate conditions for a camera with a 12-bit dynamic range, similar to the wide-angle optical navigation camera (ONC-W) onboard the Hayabusa 2 spacecraft. The results suggest that a camera with a fixed gain would struggle to capture both directly and indirectly sunlit areas simultaneously, without saturating bright areas and ensuring minimum incident energy resolution (say, a 10 digital number) for darker areas. To overcome this challenge, adjusting the camera gain based on the hole's and cavern's illumination conditions is necessary. Graphical abstract

Abstract The time series of PALSAR-2 and Sentinel-1 images reveal inflation at the volcanic flank and contraction at the crater for approximately 5 months before the 2017 eruption of Shinmoe-dake volcano, Japan. While the observation of inflation at the volcano’s flank is ubiquitous, few studies have reported crater contraction preceding an eruption. The flank inflation stopped after the 2017 eruption, while the contraction at the crater continued until the 2018 eruption. We found that a pipe-shaped deformation source above sea level best fits the observation preceding the 2017 eruption. Suppose the flux of ejected materials constrains the conduit radius during the previous 2011 eruption. In that case, the amount of deformation of the pipe-shaped deformation source, whether open or closed at its top, is too large to be realistic. Although constraining the conduit radius from the eruption flux overestimates the pressure change of the pipe-shaped deformation source, water-saturated fractures along the volcanic conduit could extend the effective conduit radius of the pressure source. We propose one potential scenario for the mechanism of the crater contraction preceding volcanic eruptions based on the combination of compaction due to cooling by ambient groundwater and material withdrawal within the conduit. The groundwater inflows from the ambient aquifer through cracks in the porous conduit wall, which are generated by conduit expansion during the magma ascent. Decoupling from the conduit wall due to a decrease in volume of the material promotes material instability and crater contraction. The interaction between the groundwater and the magma triggers the 2017 eruption of Shinmoe-dake volcano, as previous studies have reported. Graphical Abstract

As global climate change accelerates, the need for precise and high-resolution carbon emission inventories becomes increasingly urgent, particularly in rapidly developing regions. This study introduces an advanced methodology for constructing regional-scale gridded anthropogenic CO2 emission inventories, integrating the latest energy consumption data and remote sensing technologies. By systematically calculating emissions across various sectors and energy types, and utilizing Geographic Information System (GIS) for spatial distribution, we have generated a high-resolution emission map with a 1 km × 1 km grid. The accuracy of the map was validated through regression analysis with the Multi-resolution Emission Inventory for China (MEIC) dataset, ensuring its reliability. This work provides critical insights for targeted emission reduction strategies, contributing to the formulation of sustainable development policies that align with global climate objectives.

Abstract We propose a new method for real-time uncertainty monitoring of earthquake and volcano source models using data from the global navigation satellite system (GNSS) and explore its application concerning observation station placement. The Geospatial Information Authority of Japan operates two main types of GNSS earth observation network system (GEONET) coordinates for crustal deformation monitoring on different time scales: post-processing analysis values and real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD uses the Markov Chain Monte Carlo (MCMC) method termed real-time automatic uncertainty estimation of a coseismic single rectangular model using GNSS data (RUNE) for single rectangular fault model estimation to handle uncertainty. Thus far, no GNSS monitoring system can automatically detect transient crustal deformation events, such as volcanic activity and earthquake swarms, on timescales of a day or less. We extended RUNE and developed a core program for a new monitoring system for earthquake and volcanic source models and their uncertainties. Our program achieved automatic and stable MCMC utilization for rectangular fault, dike, Mogi, and spheroid models by increasing the computational speed, improving search efficiency, and adjusting hyperparameters. The program automatically determines the standard deviation of the likelihood function assuming a normal distribution with weights for each observation station. The calculation time was within 15 s for 1 × 106 samples on a standard 1U server. We assessed the reliability of the developed method using synthetic and observed GNSS data from the 2015 Sakurajima volcanic event. The results were consistent with the assumed model and previous studies and indicated an advantage in automatically quantifying uncertainty in a short computation time. Based on MCMC samples, we developed a new visualization algorithm to indicate areas on a map in which the number of observation stations should be expanded. We assessed the reliability using data from the 2023 Noto Peninsula earthquake [Mj 6.5]. The results indicate that the algorithm is helpful in studying the placement of stations. The above model extensions and their application are essential to achieve a rapid quantitative understanding of disaster events near urban areas and for utilizing this information in emergency response activities. Graphical Abstract

The reliability theory has been an important element of the classical geodetic adjustment theory and methods in the linear Gauss-Markov model. Although errors-in-variables (EIV) models have been intensively investigated, little has been done about reliability theory for EIV models. This paper first investigates the effect of a random coefficient matrix A on the conventional geodetic reliability measures as if the coefficient matrix were deterministic. The effects of such geodetic internal and external reliability measures due to the randomness of the coefficient matrix are worked out, which are shown to depend not only on the noise level of the random elements of A but also on the values of parameters. An alternative, linear approximate reliability theory is accordingly developed for use in EIV models. Both the EIV-affected reliability measures and the corresponding linear approximate measures fully account for the random errors of both the coefficient matrix and the observations, though formulated in a slightly different way. Numerical experiments have been carried to demonstrate the effects of errors-in-variables on reliability measures and compared with the conventional Baarda's reliability measures. The simulations have confirmed our theoretical results that the EIV-reliability measures depend on both the noise level of A and the parameter values. The larger the noise level of A, the larger the EIV-affected internal and external reliability measures; the larger the parameters, the larger the EIV-affected internal and external reliability measures.

A high-precision regional gravity field model is significant in various geodesy applications. In the field of modelling regional gravity fields, the spherical radial basis functions (SRBFs) approach has recently gained widespread attention, while the modelling precision is primarily influenced by the base function network. In this study, we propose a method for constructing a data-adaptive network of SRBFs using a modified Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithm, and the performance of the algorithm is verified by the observed gravity data in the Auvergne area. Furthermore, the turning point method is used to optimize the bandwidth of the basis function spectrum, which satisfies the demand for both high-precision gravity field and quasi-geoid modelling simultaneously. Numerical experimental results indicate that our algorithm has an accuracy of about 1.58 mGal in constructing the gravity field model and about 0.03 m in the regional quasi-geoid model. Compared to the existing methods, the number of SRBFs used for modelling has been reduced by 15.8%, and the time cost to determine the centre positions of SRBFs has been saved by 12.5%. Hence, the modified HDBSCAN algorithm presented here is a suitable design method for constructing the SRBF data adaptive network.

Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements. We evaluated the robustness of multiple models, such as the Global Land Data Assimilation System (GLDAS), the Famine Early Warning System Network Land Data Assimilation System (FLDAS), the National Centers for Environmental Prediction (NCEP), and the WaterGAP Global Hydrology Model (WGHM). Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series, satellite gravity field Mascon solutions, and Global Precipitation Climatology Centre (GPCC) guide our assessment. Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP. In the Amazon River Basin, a 5-month lag between FLDAS, GLDAS, and satellite gravity results is observed. In eastern Asia and Australia, NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models. Three combined hydrological models (H-VCE, H-EWM, and H-CVM) utilizing Variance Component Estimation (VCE), Entropy Weight Method (EWM), and Coefficient of Variation Method (CVM) are formulated. Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%–17%. Correlation with precipitation increases by 25%–30%, and with satellite gravity, rises from 0.2 to 0.8 at maximum. The combined model eliminates time lag in the Amazon Basin TWSC analysis, exhibiting a four times higher signal-to-noise ratio than single models. H-VCE demonstrates the highest accuracy. In summary, the combined hydrological model minimizes discrepancies among individual models, significantly improving accuracy for monitoring large-scale TWSC.

For earthquakes (M ≥ 4.0) occurring along and around the East Anatolian fault zone and the Dead Sea fault zone within ten years immediately before the MW7.8 Gaziantep earthquake, Türkiye, of February 6, 2023, we explored the correlation between seismicity and the earth's rotation. We statistically evaluated the correlation using the Schuster's test. The results are quantitatively assessed by a p-value. We found a clear downward trend in the p-values from early 2020 to late 2022 in the studied region. We also obtained a spatial distribution of the p-values showing a low p-value area near the northeastern end of the aftershock zone. Although the stress induced by the rotation of the earth is very weak, it could control the earthquake occurrence when the focal medium is loaded to the critical state to release a large earthquake. The decrease in the b-value in the Gutenberg–Richter (G-R) relation is considered in the form of the tectonic stress increase in the crust. We investigated the b-value as a function of time in the study region. We found that the b-value had decreased for about eleven years before the p-value started to decrease, with a relative reduction of 57%. Therefore, the result of the lower p-values obtained in the present study infers that the earthquakes were dominated by the earth's rotation prior to the MW7.8 Türkiye earthquake due to a critical state of the focal region.

Since the late Cenozoic, the reactivated Tianshan orogenic belt has accommodated crustal shortening exceeding 200 km, primarily due to the far-field effects of the India-Eurasia plate collision. However, the details of the strain partitioning in the Tianshan Mountain range remain elusive. We interpret a new compilation of GPS velocities covering the whole Tianshan range with a classic elastic block model. Compared to previous studies with a block modeling approach, the Tianshan orogenic belt is further subdivided into several blocks based on geological fault traces and a clustering analysis approach. In addition to obvious crustal shortening on the bounding thrust faults of the Tianshan, our inverted fault slip rates also reveal that faults within the Tianshan orogenic belt, such as the Nalati Fault and the southern margin of the Issyk-Kul Lake Fault, which plays a crucial role in accommodating the tectonic crustal shortening. In the 72°E−78°E region, the internal shortening rate within the mountain is approximately 5–7 mm/yr. Besides crustal shortening, strike-slip motion occurs on faults in the interior of the mountain range as well as in the foreland fold-and-thrust belts, especially in the southern margin of the Tianshan. These findings suggest that the crustal deformation in the Tianshan Mountain range is more complex than previously thought, and the oblique convergence between the Tarim Basin and the Tianshan probably results in both strike-slip and thrust motion.

Studying the seasonal deformation in GPS time series is important to interpreting geophysical contributors and identifying unmodeled and mismodeled seasonal signals. Traditional seasonal signal extraction used the least squares method, which models seasonal deformation as a constant seasonal amplitude and phase. However, the seasonal variations are not constant from year to year, and the seasonal amplitude and phase are time-variable. In order to obtain the time-variable seasonal signal in the GPS station coordinate time series, singular spectrum analysis (SSA) is conducted in this study. We firstly applied the SSA on simulated seasonal signals with different frequencies 1.00 cycle per year (cpy), 1.04 cpy and with time-variable amplitude are superimposed. It was found that SSA can successfully obtain the seasonal variations with different frequencies and with time-variable amplitude superimposed. Then, SSA is carried out on the GPS observations in Yunnan Province. The results show that the time-variable amplitude seasonal signals are ubiquitous in Yunnan Province, and the time-variable amplitude change in 2019 in the region is extracted, which is further explained by the soil moisture mass loading and atmospheric pressure loading. After removing the two loading effects, the SSA obtained modulated seasonal signals which contain the obvious seasonal variations at frequency of 1.046 cpy, it is close with the GPS draconitic year, 1.040 cpy. Hence, the time-variable amplitude changes in 2019 and the seasonal GPS draconitic year in the region could be discriminated successfully by SSA in Yunnan Province.

Global inland surface water bodies such as lakes and reservoirs, important components of the hydrosphere and ecosphere, are increasingly affected by climate change. Generating bathymetric volume-area-height (BVAH) curves for global inland surface water bodies can enhance our understanding of their topography and climate impacts. However, accurately quantifying the topographic patterns of these water bodies remains challenging due to the difficulties in collecting comprehensive bathymetric data. Therefore, we collected and processed over 2000 bathymetric maps of global water bodies from over 50 different data sources and then developed the BVAH model. Finally, the BVAH hydrological curves of 16671 global inland surface water bodies (larger than 10 km2) were generated. The results include but are not limited to (1) For most targeted water bodies, area (A) and volume (V) exhibit significant power function relationships with surface heights (H), with optimal power values quantified as 1.42 for A and 2.42 for V. (2) The BVAH model outperforms GLOBathy in estimating area and volume changes, achieving higher correlation coefficients (CC) of approximately 0.962 for the area and 0.991 for volume, and demonstrating lower percentages of root mean squared errors (PRMSE) around 10.9% for the area and 4.8% for volume. (3) In the case study of the Xizang Plateau and various large global reservoirs, the BVAH curve database can capture dynamic volume changes. As a unified simulation of the bathymetric topographical patterns, our bathymetric dataset and corresponding BVAH curve database have great potential to contribute to effective water resource management and ecological conservation efforts worldwide.

The Global Navigation Satellite System (GNSS) is widely utilized for accurate positioning. One commonly applied method to obtain precise coordinate estimates is by implementing the relative positioning in network mode. However, this approach can be complex and challenging. Fortunately, The Japan Aerospace Exploration Agency (JAXA) offers freely available satellite orbit and clock correction products called Multi-GNSS Advanced Demonstration Tool for Orbit and Clock Analysis (MADOCA), which can enhance positioning accuracy through the precise point positioning (PPP) method. This study focuses on evaluating PPP static mode positioning using MADOCA products and comparing the results with the highly precise relative positioning method. By analyzing a network of 20 GNSS stations in Indonesia, we found that the PPP method using MADOCA products provided favorable positioning estimates. The median discrepancies and the corresponding median absolute deviation (MAD) for easting, northing, and up components were estimated as 9 ± 18 mm, 10 ± 9 mm, and 3 ± 40 mm, respectively. These results indicate that PPP with MADOCA products can be a reliable alternative for establishing Indonesia's horizontal control networks, particularly for orders 0, 1, 2, and 3, and for a broad spectrum of geoscience monitoring activities. However, considerations such as epoch transformations and seismic activities should be taken into account for accurate positioning applications that comply with the definition of the national reference framework.

Since the inception of the optimal sequence estimation (OSE) method, various research teams have substantiated its efficacy as the optimal stacking technique for handling array data, leading to its successful application in numerous geoscience studies. Nevertheless, concerns persist regarding the potential impact of aliasing resulting from the choice of distinct station distributions on the outcomes derived from OSE. In this investigation, I employ theoretical deduction and experimental analysis to elucidate the reasons behind the immunity of the Yl'm'-related common signal obtained through OSE to variations in station distribution selection. The primary objective of OSE is also underscored, i.e., to restore/strip a Yl'm'-related common periodic signal from various stations. Furthermore, I provide additional clarification that the ‘Yl'm'-related common signal’ and the ‘Yl'm'-related equivalent excitation sequence’ are distinct concepts. These analyses will facilitate the utilization of the OSE technique by other researchers in investigating intriguing geophysical phenomena and attaining sound explanations.

A novel artificial bee colony algorithm was introduced for the eruption event of the Sakurajima volcano on August 9, 2020, to invert the magma source characteristics below the volcano based on the point source Mogi model. Considering that the Sakurajima volcano is surrounded by sea, all the deformation data are used to obtain the location and magma eruption volume of the volcano. In response to the weak local search capability of the artificial swarm algorithm, the difference between the global optimal individual and the un-roulette screened individual is introduced as the variance component in the onlooker stage. Detailed simulation experiments verify the improvement of the algorithm in terms of convergence speed. In real experiments, the Sakurajima volcano inversion shows closer fitting results and smaller residuals compared to the existing literature. Meanwhile, the convergence speed of the algorithm echoes with the simulation experiments.

Almanac is an elegant design to help Global Navigation Satellite Systems (GNSS) signal acquisition, which has been adopted by all global satellite navigation systems. For the future low Earth orbit (LEO) navigation constellation, the almanac will be more critical due to larger constellation and signal Doppler variation, while the LEO orbit prediction is more challenging due to complex perturbation forces, especially atmospheric drag. This study introduces a novel 9-parameter almanac model for LEO constellation, leveraging the Empirical Mode Decomposition (EMD) method. Our innovative approach uniquely balances almanac accuracy and simplicity by considering the atmosphere drag effects, addressing a critical gap in existing models. The proposed almanac model is validated with four in-orbit LEO satellites at various altitudes. For the LEO with a 600 km orbit or lower, our model achieves a 50% improvement in 23-day orbit prediction accuracy compared to the classical GPS almanac model. This significant enhancement extends to visibility prediction and signal acquisition performance. Our design limits the maximum elevation angle error to less than 1.5 degrees, efficiently excluding invisible satellites during LEO navigation signal acquisition. Furthermore, for visible satellite, the proposed LEO almanac reduces the signal frequency searching range by about 20 times during acquisition, with Doppler prediction errors better than 0.5 kHz/0.3 kHz for 95% of cases. These advancements represent a substantial leap in LEO navigation technology, offering improved efficiency and accuracy for future satellite systems.

The spatiotemporal heterogeneity of the parameters greatly impacts the estimation of Gross Primary Productivity (GPP) by Light Use Efficiency (LUE) models. Vegetation type-specific parameters are commonly set at present; however, the various environmental heterogeneities at global and regional scales can also induce disparate optimal parameter schemes, which has not been further explored. Therefore, in this study, we comparatively explored the parameter differences and GPP estimation accuracy under different parameter schemes, including Vegetation type Parameters (VPs), Fixed Parameters (FPs), Vegetation type Monthly Parameters (VMPs), and Fixed Monthly Parameters (FMPs), at both global and regional scales. Two different strategies were applied to validate the ability of the temporal prediction and spatial expansion for the four parameter schemes. The results indicate that the VP scheme shows only a limited superiority over the FP scheme for GPP estimation at the global scale (ΔR2 = 0.01–0.02), which indicates that the VP scheme is not necessary for the global application of LUE models, due to the considerable spatiotemporal heterogeneity of vegetation. However, for regional applications, such as the Mediterranean region, the VP scheme is preferable to the FP scheme, with an improved ΔR2 of more than 0.05, which is because the vegetation within the same type is much more similar than at a global scale. Furthermore, it is found that the time-varying parameters (VMPs and FMPs) contribute little to the GPP simulation at both global and regional scales, which is possibly due to the limited amount of available data. Overall, the results of this study will not only offer guidance and optimal parameter schemes for the global and regional estimation of GPP, but also highlight the importance of considering spatiotemporal heterogeneity for parameters.

In the era of increasingly advanced Earth Observation (EO) technologies, extracting pertinent information (such as water-bodies) from the Earth’s surface has become a crucial task. Deep Learning, especially via pre-trained models, currently offers a highly promising approach for the semantic segmentation of Remote Sensing Imagery (RSI). However, effectively adapting these pre-trained models to RSI tasks remains challenging. Typically, these models undergo fine-tuning for specialized tasks, involving modifications to their parameters or structure of the original architecture, which may impact their inherent generalization capabilities. Furthermore, robust pre-trained models on nature images are not specifically designed for RSI, presenting challenges in their direct application to RSI tasks. To alleviate these problems, our study introduces a light-weight Enhanced Semantic-positional Feature Fusion Network (ESFFNet), leveraging diverse pre-trained image encoders alongside extensive EO data. The proposed method begins by leveraging pre-trained encoders, specifically Vision Transformer (ViT)-based and Convolutional Neural Network (CNN)-based models, to extract deep semantic and precise positional features respectively, without additional training. Following this, we introduce the Enhanced Semantic-positional Feature Fusion Module (ESFFM). This module adeptly merges semantic features derived from the ViT-based encoder with spatial features extracted from the CNN-based encoder. Such integration is realized via multi-scale feature fusion, local and long-distance feature integration, and dense connectivity strategies, leading to a robust feature representation. Finally, the Primary Segmentation-guided Fine Extraction Module (PSFEM) further bolsters the precision of remote sensing image segmentation. Collectively, these two modules constitute our light-weight decoder, with a parameter size of less than 4 M. Our approach is evaluated on two distinct water-body datasets, indicating superiority over other leading segmentation techniques. In addition, our method also demonstrates exemplary efficacy in diverse remote sensing segmentation tasks, such as building extraction and land cover classification. The source codes will be available at https://github.com/zhilyzhang/ESFFNet.

In this paper, we introduce a challenging Global Large-scale Ship Database (GLSD), designed specifically for ship detection tasks. The designed GLSD database includes a total of 212,357 annotated instances from 152,576 images. Based on the collected images, we propose 13 ship categories that widely exist in international routes. These categories include Sailing boat, Fishing boat, Passenger ship, Warship, General cargo ship, Container ship, Bulk cargo carrier, Barge, Ore carrier, Speed boat, Canoe, Oil carrier, and Tug. The motivations for developing GLSD include the following: 1) providing a refined and extensive ship detection database that benefits the object detection community, 2) establishing a database with exhaustive labels (bounding boxes and ship class categories) in a uniform classification scheme, and 3) providing a large-scale ship database with geographic information (covering more than 3000 ports and 33 routes) that benefits multi-modal analysis. Additionally, we discuss the evaluation protocols corresponding to image characteristics in GLSD and analyze the performance of selected state-of-the-art object detection algorithms on GLSD, aiming to establish baselines for future studies.

Cross-Regional Model Transfer (CRMT) provides a solution to crop classification challenges in target regions with limited labeled samples. However, when the source region (source domain) and the target region (target domain) are spatially distant, a shift in crop Satellite Image Time Series (SITS) occurs, resulting in suboptimal performance of SITS-based classification models in the target domain. To address this issue, we propose a novel domain adaptation method, named SITS Correction. This method mitigates the SITS shift by introducing correction factors to improve the classification performance of CRMT. The correction factors consist of source domain correction units and target domain correction units, which are from variables associated with the SITS shift. In cases where labeled samples are available in the target domain, the SITS have calculated Barycenter (i.e. SitsB) as the correction units, which then combine the source domain and the target domain’s SitsB to form a SITS-based correction factor. When no labeled samples are available, the correction units are substituted by Barycenter of the temperature variables time series (i.e. temperature indicator) influencing crop growth, and the correction factors are composed of temperature indicators from both the source and target domains. We validate SITS Correction through transfer experiments conducted in four regions, encompassing various years, crops, and classification methods. Experimental results demonstrate a significant improvement in crop classification performance with SITS Correction in both scenarios – target domain with labeled samples (accuracy increased by 39.1%) and target domain without labeled samples (accuracy increased by 14.8%). This research provides a practical option for crop classification in target regions with either limited or no labeled samples.

Pan-sharpening aims to obtain high resolution multispectral (HRMS) images by integrating the information in the panchromatic and multispectral images. Existing pan-sharpening methods have demonstrated impressive sharpening performance. However, these methods inherently overlook the complementary characteristics and interaction between diverse source images, resulting in sharpened outcomes accompanied by distortion. To solve the above problems, we construct a novel cross fusion model with fine-grained detail reconstruction from the perspective of frequency-domain. The motivation of the model is twofold: (1) to reconstruct spatial detail representations from diverse source images, laying the foundation for the generation of fine details in the subsequent fused images; and (2) to enhance the interaction between diverse source features during the fusion process in order to attain high-fidelity fusion outcomes. Based on the theoretical model, we develop a frequency-spectral dual domain cross fusion network (CF2N) utilizing the deep learning technique. Consequently, the CF2N consist of two main stages, namely frequency-domain dominated detail reconstruction (FD2R) and frequency-spectral cross fusion (FSCF). Specifically, a more reasonable reconstruction of fine frequency details in HRMS can be achieved by performing adaptive weighted fusion of frequency details in the FD2R stage. Furthermore, the FSCF module, which seamlessly integrates frequency- and spectral-domain details in a highly interactive cross fusion manner. As a result, the CF2N possesses the capability to attain high frequency-spectral fidelity results with excellent interpretability. Extensive experiments show the superior performance of ours over state of the art, while maintaining high efficiency. All implementations of this work will be published at our website.

Abstract Combining the total electron content (TEC) data from two nationwide Global Navigation Satellite System (GNSS) networks in Japan with the L-band synthetic aperture radar (SAR) data, we reveal the fine spatial and temporal structure of a daytime sporadic-E (Es) episode in Shikoku, Japan. The snapshot of the Es is derived not only from interferometric SAR (InSAR) but also from multiple aperture interferometry (MAI), the latter of which performs better in isolating the fine spatial structure. The GNSS TEC maps indicate that the Es episode is accompanied by a primary east–west elongated (up to ~ 180 km) southward migrating TEC striation with a speed of ~ 90 m/s and ~ 10–20 km widths in the north–south direction. As previously suggested by the GNSS TEC time series, the present InSAR and MAI data independently confirm that electron density in the primary striation gradually increases from the frontal leading edge but abruptly drops in the trailing edge. MAI-based TEC map confirms multiple TEC striations as previously suggested in GNSS TEC time-series, which are reminiscent of the quasi-periodic (QP) echoes in nighttime Es detected by the middle and upper atmosphere (MU) radar, but the periodicity is not as clear as that observed by MU radar. The Kelvin–Helmholtz (KH) instabilities around the wind shear of neutral winds could be responsible for the QP TEC striations. Graphical abstract

Abstract We adapted a recently developed technique of oriented drill coring (100 m in depth) for paleomagnetic measurements, including additional techniques such as half-cutting of the drill cores and accurate cube sampling using an apparatus that precisely guides the cube into the half-cut drill core surface. Our techniques were successfully applied to sequential tephra layers (including loess) at Akan Quaternary caldera volcano in eastern Hokkaido, Japan. Directions of remanent magnetization for a total of 129 specimens were measured by Spinner magnetometer with thermal and alternating field demagnetizations. We detected clear Matuyama–Brunhes geomagnetic reversal between the depths of 20.59 m and 21.30 m, where inclinations change from 65.1 to –44.3°. With these techniques, we can in future obtain useful geologic information (e.g., radiometric ages and absolute paleo-intensities) from volcanic rocks around the Matuyama–Brunhes boundary in Akan volcano. This will clarify more detailed processes of the geomagnetic polarity transition. Our study demonstrates the utility of oriented drill cores from successive tephra and loess layers for high resolution investigate of continuous paleo-geomagnetic records. The new techniques can be adopted to other geological fields on Earth, like in studies of marine sediments, providing continuous paleomagnetic direction data from drill core. Graphical Abstract

Abstract Solar cycles have an asymmetrical shape with a fast rise and a slow decline, which varies from cycle to cycle. This makes it difficult to study the solar cycle phase dependence of the occurrence of intense solar-terrestrial events such as intense geomagnetic storms. In the previous works, differences in the rise and fall time lengths of each solar cycle were not fully considered. We normalized the asymmetric shape of each solar cycle using the rise and fall time lengths and showed the solar cycle phase dependence of occurrence of the intense geomagnetic storms selected using the Dst index for solar cycles 19−24 and using the aa index for solar cycles 12−24. The previous works noted that the occurrence of geomagnetic disturbances shows double peaks before and after solar maximum. Our results showed that the occurrence of the intense geomagnetic storms selected using the Dst and aa indices does not always show clear double peaks and increased more in the earlier half of the fall time than in the other time periods. The Dst and aa indices have been used to select geomagnetic storms in the previous studies. We pointed out that the solar cycle phase dependence of occurrence of the geomagnetic storms selected using the aa index is slightly different from those selected using the Dst index. We showed the geomagnetic storm on 4 August 1972 as an extreme case, which showed difference between Dst and aa. We also showed that intense geomagnetic storms associated with eruptive flares from the active sunspot groups occurred around the solar minima of cycles 17, 19, 20, and 21. Graphical Abstract

Abstract High signal-to-noise ratio (SNR) seismic waveform data are conductive to various studies in seismology. Seismic denoising aims to enhance SNR by eliminating additive noise through signal processing while preserving important features of the seismic signal. Conventional parametric seismic denoising methods often require selecting appropriate parameters to achieve optimal results, which may be limiting when dealing with various types and scales of seismic data. Here, we develop an adaptive parameter-free denoising method by combining general cross-validation (GCV) thresholding and pixel connectivity in synchrosqueezed (SS) domain. In this denoising framework, the synchrosqueezed continuous wavelet transform (SS-CWT) is first applied to obtain a high-resolution time–frequency representation. Then, the GCV approach, which allows for choosing the (nearly) optimal threshold without relying on any prior knowledge about the noise level, is employed to attenuate most of the low-energy noise. After that, the relatively isolated high-energy residual noise remaining in the SS-CWT spectrum is removed using pixel connectivity thresholding. Finally, the inverse SS-CWT is applied to the thresholded spectrum to obtain the denoised seismic record. As the thresholds for GCV and pixel connectivity are derived from the spectrum characteristics of the data being analyzed, the proposed denoising approach is highly adaptive and parameter-free. We demonstrate the effectiveness and versatility of the proposed denoising framework using synthetic data and real seismic data from diverse monitoring scenarios, including land, ocean, and emerging distributed acoustic sensing (DAS). The results indicate that the method is a stable and efficient tool for seismic data denoising. Graphical Abstract

Abstract The severe damage observed in the Kathmandu Basin, Nepal, during past earthquakes necessitates a thorough study of the seismic behavior of the basin sediments. As the shear-wave velocity is directly related to the elastic shear modulus of the material, it is essential to determine it to incorporate the behavior of the soil in the design of the structure. Hence, we determined average shear-wave velocity in upper 30 m (Vs30) of soil in Bhaktapur district in the eastern part of the Kathmandu Basin at 73 observation points, employing two methods involving the use of non-invasive microtremor array measurements (MAMs). These MAMs are widely used for determining subsurface soil characteristics by analyzing the ambient vibrations of the ground. The first method involves inversion using a genetic algorithm, and the second is a method for obtaining Vs30 directly from the dispersion curve. We found that Vs30 in the southeastern part of the study area was higher than that in other parts. Conversely, Vs30 in the western region was lower. The calculated Vs30 values were used to classify the sites. The elevated eastern and southeastern areas with high Vs30 were categorized as dense soil or soft rock, whereas the areas with low Vs30 that had suffered significant damage during the 2015 Gorkha earthquake were classified as soft soil sites. Graphical Abstract

Abstract Tectonic tremors occur around the subducting seamount of the Kyushu Palau Ridge (KPR) in Hyuga-nada, Japan. We investigate the relationship between tremor activity and structural and physical characteristics using high-resolution reflection seismic imaging of the KR0114-8 line, encompassing areas with both high and low occurrences of tremors. The reflection data are reprocessed using broadband processing, reflection tomography and Kirchhoff pre-stack depth migration. The resulting image delineates complex deformation and lithological boundaries, such as the accretionary prism, underthrust sediments, décollement, and top of the seamount. The observed splay faults and seafloor uplift to the west of the KPR, coupled with frequent tremors, confirm the compressional stress regime on the leading side of the subducting seamount. A stress shadow over the seamount effectively suppresses tremors. Numerous faults indicate significant deformation of the overburden when positioned on the leading side of the seamount. The trailing side exhibits a compressional stress regime, rather than an extensional one, as evidenced by the development of in-sequence thrusts and frequent tremors. Local physical, mechanical, and structural factors critically influence the tremor activity. The increased frequency of tremors is correlated with the thickness of the underthrust sediments and presence of in-sequence thrusts, whereas it is inversely correlated with the reflectivity of the décollement. Several potential mechanisms for this phenomenon include elevated pore pressure above the décollement and/or within the underthrust sediments, as well as structural effects. High-resolution velocity imaging, scientific drilling, and precise tremor-depth estimation are essential for advancing our understanding of these mechanisms. Graphical abstract

Abstract Detecting buried active faults presents the challenge of precisely locating the upper breakpoint, the shallowest point in the Quaternary system where faults occur. Microtremor survey technology, unaffected by urban electromagnetic interference, offers an eco-friendly and efficient method for investigating buried faults and stratigraphic structures in urban areas. This research uses microtremor survey technology to identify the upper breakpoint of the buried Nankou-Sunhe Fault in Changping, Beijing. For data collection, 17 microtremor survey points were deployed across the northern section of the Nankou-Sunhe fault, employing a three-point nested circular array with a point spacing of approximately 200 m to form a profile spanning approximately 320 m. For data analysis, the spatial autocorrelation method was utilized. Each measurement point was divided into 9 sets of radii, ranging from a minimum of approximately 4 m to a maximum of 28 m. The correlation coefficients for each set were calculated, and the dispersion curve for each measurement point was generated by fitting the average coefficients with the Bessel function of the first kind of order zero. The apparent S-wave velocity was determined directly from the dispersion curve using empirical formulas and interpolated to generate the contour cross-section map. Integrating the section and inverted S-wave velocity data can significantly enhance interpretation accuracy, and based on these data, the spatial development characteristics and upper breakpoint locations of the Nankou-Sunhe fault zone were analyzed, and the strata shallower than 100 m were deduced. The results align well with known geological data, such as luminescence dating and 14C dating from boreholes at nearby locations. Graphical Abstract

Abstract We have developed a 3-D forward modeling method for the magnetometric resistivity (MMR) technique, specially focusing on the marine MMR method, which utilizes a vertical bipole source and seafloor receivers to measure magnetic field variations. The bipole source generates an artificial electric current between two electrodes: one on the sea surface and another on the seafloor. When computing the electric potential using the relaxation method, while conserving electric current, singularities arise at the electrode locations. To address this issue, we introduce two electrical resistivity structures to mitigate the effects of these singularities and to obtain magnetic field anomalies caused by arbitrary 3-D electrical resistivity anomalies beneath the seafloor. By determining the sign of the magnetic field anomaly, we can infer whether the electrical resistivity of the anomalous body is more conductive or more resistive compared to the surrounding oceanic crust. Furthermore, we demonstrate that increasing the number of bipole sources is more effective in exploring anomalous bodies than increasing the number of receivers. Graphical abstract

Abstract The seismicity rate markedly increased in the northeastern Noto Peninsula of Ishikawa Prefecture around the end of 2020, with an Mw6.2 event on 5 May, 2023, followed by many aftershocks. Previous earthquake relocation studies have detected upward migration of microearthquakes via multiple faults and clusters, suggesting the involvement of crustal fluids in this sequence. Since some active faults exist near the source region, there was concern that this sequence could lead to a larger earthquake; it became a reality with the Mw7.5 earthquake on 1 January 2024. This study aims to develop an algorithm to precisely relocate microearthquake hypocenters in quasi-real time for better monitoring. A fine view of seismicity requires relative relocation methods such as the double-difference (DD) method with numerous arrival time difference data precisely measured by the waveform correlation analysis. However, the standard DD method has the disadvantage of huge computational costs when data increase, making it unsuitable for real-time monitoring in such situations. We developed a quasi-real-time algorithm that relocates only new earthquakes using the DD method each time a new time window of data is added. The major improvement is that our method incorporates a traditional simple relative relocation and preserves constraints between different time windows; the relative locations of new events are constrained from reference events that were already relocated in the previous time windows. We tested a daily relocation algorithm on 11,546 events from 19 June, 2022, to 31 May, 2023, in the Noto Peninsula earthquake sequence. We found that our modification substantially reduced artificial hypocenter offsets between different time windows and succeeded in resolving the fine fault structures from the cloud-like distribution of initial hypocenters. If we do not impose constraints between different windows, the relocated hypocenters are scattered and do not show fine planar structures. Our algorithm greatly reduces the computational cost, allowing for quasi-real-time earthquake relocation and monitoring. We hope this algorithm will help monitor the spatio-temporal distribution of future earthquake sequences. Graphical Abstract

Dynamic imaging of optical remote sensing satellites refers to the active acquisition of images while the satellite is maneuvering at a high angular velocity, which significantly enhances the efficiency and application value of remote sensing imagery. However, due to the influence of rapid maneuvering, the random error of star sensors significantly increases, resulting in a decrease in the geometric positioning accuracy of dynamic imaging remote sensing images. This paper proposes a dynamic fusion method for multisource attitude measurement data based on the noise adaptive estimation and bidirectional filter to achieve high-precision attitude determination and geometric positioning in dynamic imaging. Based on the measurement error model of star sensors, the weights of the star sensor and gyroscope are adaptively adjusted in multisource data fusion to reduce the impact of star sensor measurement errors on the gyroscope. Moreover, a bidirectional fusion filter that includes a low-velocity maneuvering stage is proposed to realize the optimal estimation of the satellite attitude parameter. The simulation data and onboard data of the Luojia3-01 (LJ3–01) satellite were tested to verify the effectiveness of the proposed method. The geometric positioning accuracy of the staring images of LJ3–01 improved from 10.048 m to 7.538 m. The registration accuracy of the sequential images improved from 3.568 pixels to 1.179 pixels. The proposed method can significantly improve the attitude determination accuracy and the geometric positioning accuracy of LJ3–01 satellite staring images. Moreover, for simulation data with various angular velocities, the attitude determination accuracies of the proposed method are better than 0.93”. The experimental results show that the proposed method can achieve high-precision attitude determination in dynamic imaging, reaching the accuracy in the traditional passive imaging.

Reservoir characterization is a vital task within the oil and gas industry, with the identification of lithofacies in subsurface formations being a fundamental aspect of this process. However, lithofacies identification in complex geological environments with high dimensions, such as the Lower Indus Basin in Pakistan, poses a notable challenge, especially when dealing with limited data. To address this issue, we propose four common data-driven machine learning approaches: multi-resolution graph-based clustering (MRGC), artificial neural networks (ANN), K-nearest neighbors (KNN), and self-organizing map (SOM). We utilized these proposed approaches to assess their performance in scenarios with varying core sample availability, specifically evaluating their effectiveness in identifying lithofacies within the Lower Goru formation of the middle Indus Basin. The study reveals that in scenarios with a limited number of core samples, MRGC is the preferred choice, while KNN or MRGC is more suitable for larger datasets. The results demonstrate the superior performance of MRGC and KNN in lithofacies identification within the specified geological environment, with SOM following closely behind, and ANN exhibiting comparatively lower efficacy. The accurate identification of lithofacies from the selected model is complemented by the application of the truncated Gaussian simulation method for facies modeling. Comparative results confirm the excellent agreement between the model identification of lithofacies from well logs and electro-facies obtained from the truncated Gaussian simulation electro-facies volume. This study highlights the crucial role of selecting the right machine learning approach for precise lithofacies identification and modeling in complex geological environments. The comparative analysis provides practitioners in the petroleum industry with insights into the strengths and limitations of each method, enhancing existing knowledge. In conclusion, this research emphasizes the significance of comprehensive research and method selection for advancing lithofacies identification in diverse formations or study areas, ultimately benefiting the broader field of subsurface characterization in the petroleum industry.