Andrew P. Roberts, Xiang Zhao, Chorng-Shern Horng, Pengxiang Hu, Mark J. Dekkers, Richard J. Harrison, David Heslop, Adrian R. Muxworthy, Hirokuni Oda, Wyn Williams
First-order reversal curve (FORC) diagrams are an important tool for assessing the domain state and anisotropy type of magnetic particles, as well as for detecting magnetostatic interactions among particles, in paleoclimatic, geomagnetic, tectonic, and planetary studies. We present here FORC diagrams for diverse natural monoclinic 4C pyrrhotite (Fe7S8) samples, including sieved particle size fractions. Experimental FORC distributions for natural pyrrhotite have a dominant asymmetric “kidney shaped” feature for fine particles in the stable single domain (SD) size range. As particles coarsen to the multi-domain state, FORC distributions diverge vertically at low coercivities. Vertical spreading in FORC distributions is also an intrinsic response of magnetic particle systems with multiaxial anisotropy even for magnetostatically noninteracting SD particles. The observed kidney shaped FORC distributions are attributed to twin domain and magnetic moment pinning along easy directions that follow the hexagonal parent structure to produce an apparent triaxial magnetocrystalline anisotropy signal. Similar FORC distributions have been reported for pyrrhotite, hematite, and smythite, which all have basal plane triaxial anisotropy. Central ridge-type signatures, which are typical of noninteracting uniaxial SD particle assemblages, have been reported for some pyrrhotite samples, but are not documented here. Our results explain FORC features for pyrrhotite and provide a catalog for comparison with other studies.
{"title":"Magnetic Domain State and Anisotropy in Monoclinic 4C Pyrrhotite (Fe7S8) From First-Order Reversal Curve Diagrams","authors":"Andrew P. Roberts, Xiang Zhao, Chorng-Shern Horng, Pengxiang Hu, Mark J. Dekkers, Richard J. Harrison, David Heslop, Adrian R. Muxworthy, Hirokuni Oda, Wyn Williams","doi":"10.1029/2025JB032900","DOIUrl":"10.1029/2025JB032900","url":null,"abstract":"<p>First-order reversal curve (FORC) diagrams are an important tool for assessing the domain state and anisotropy type of magnetic particles, as well as for detecting magnetostatic interactions among particles, in paleoclimatic, geomagnetic, tectonic, and planetary studies. We present here FORC diagrams for diverse natural monoclinic 4C pyrrhotite (Fe<sub>7</sub>S<sub>8</sub>) samples, including sieved particle size fractions. Experimental FORC distributions for natural pyrrhotite have a dominant asymmetric “kidney shaped” feature for fine particles in the stable single domain (SD) size range. As particles coarsen to the multi-domain state, FORC distributions diverge vertically at low coercivities. Vertical spreading in FORC distributions is also an intrinsic response of magnetic particle systems with multiaxial anisotropy even for magnetostatically noninteracting SD particles. The observed kidney shaped FORC distributions are attributed to twin domain and magnetic moment pinning along easy directions that follow the hexagonal parent structure to produce an apparent triaxial magnetocrystalline anisotropy signal. Similar FORC distributions have been reported for pyrrhotite, hematite, and smythite, which all have basal plane triaxial anisotropy. Central ridge-type signatures, which are typical of noninteracting uniaxial SD particle assemblages, have been reported for some pyrrhotite samples, but are not documented here. Our results explain FORC features for pyrrhotite and provide a catalog for comparison with other studies.</p>","PeriodicalId":15864,"journal":{"name":"Journal of Geophysical Research: Solid Earth","volume":"131 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146205468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Han Bai, Xuan Feng, Lei Fu, Enhedelihai Alex Nilot, Xin Wang, Michael Fehler, Stephen Brown
Monitoring disturbances in the subsurface medium of Antarctic glaciers and their connection to environmental changes is crucial for addressing sea level rise due to glacier melting. This study utilizes ambient noise data collected by dense seismic arrays deployed near Dalk Glacier in East Antarctica during the 36th Chinese National Antarctic Research Expedition. Using coda wave interferometry, we measured in situ nonlinear elasticity (relative velocity changes, dv/v) and observed hysteresis loop characteristics consistent with laboratory experiments. Our results demonstrate delayed dv/v responses to environmental forcing, with short-term variations independent of atmospheric pressure. Semi-diurnal dv/v variations are controlled by tidal strain, humidity, and ice melt dynamics, while sensitivity to melt rate exceeds the response to total melt volume. This cost-effective, high-resolution monitoring technique complements existing methods for monitoring mass changes in the Antarctic ice sheet, aiding in the detection and understanding of low-amplitude precursors to the systemic imbalances of glaciers.
{"title":"Monitoring the In Situ Nonlinear Elasticity Near the Dalk Glacier Area, Antarctica, Using Dense Seismic Arrays","authors":"Han Bai, Xuan Feng, Lei Fu, Enhedelihai Alex Nilot, Xin Wang, Michael Fehler, Stephen Brown","doi":"10.1029/2025JB031752","DOIUrl":"10.1029/2025JB031752","url":null,"abstract":"<p>Monitoring disturbances in the subsurface medium of Antarctic glaciers and their connection to environmental changes is crucial for addressing sea level rise due to glacier melting. This study utilizes ambient noise data collected by dense seismic arrays deployed near Dalk Glacier in East Antarctica during the 36th Chinese National Antarctic Research Expedition. Using coda wave interferometry, we measured in situ nonlinear elasticity (relative velocity changes, dv/v) and observed hysteresis loop characteristics consistent with laboratory experiments. Our results demonstrate delayed dv/v responses to environmental forcing, with short-term variations independent of atmospheric pressure. Semi-diurnal dv/v variations are controlled by tidal strain, humidity, and ice melt dynamics, while sensitivity to melt rate exceeds the response to total melt volume. This cost-effective, high-resolution monitoring technique complements existing methods for monitoring mass changes in the Antarctic ice sheet, aiding in the detection and understanding of low-amplitude precursors to the systemic imbalances of glaciers.</p>","PeriodicalId":15864,"journal":{"name":"Journal of Geophysical Research: Solid Earth","volume":"131 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146198562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Two primary mechanisms responsible for continental crustal growth at convergent margins have been acknowledged, including continental arc magmatism and allochthonous terrane accretion. As such, intra-oceanic arcs (IOAs), which represent potential accretion terranes, have been regarded as one of the fundamental contributors. It is noted that current IOAs, mainly outcropping in the western Pacific, show remarkable diversity in their crustal composition and rheological properties. However, it remains unclear how the diversity affects the accretion processes of IOAs and further determines their accretion efficiencies. Here, we conducted 2-D geodynamic modeling to explore these issues. Our models reveal the accretion process and efficiency relying on compositional differentiation and rheological stratification. Specifically, nascent IOAs characterized by a partially molten zone at the level of Moho, where buoyant crust can be separated from dense mantle, result in accretion efficiencies as high as ∼76.4% when slab break-off took place concurrently. In contrast, mature arcs with cold thermal gradients show a coherent crust-mantle transition and complete subduction, giving rise to the lowest accretion efficiency. Some of these modeling results align with geophysical observations from modern IOAs, such as the Izu-Bonin arc and Kyushu-Palau ridge, which display different accretion processes and efficiencies. The others are likely plausible mirrors of ancient orogenic belts, including the Cenozoic Kohistan arc and the Paleozoic Central Asian Orogenic Belt.
{"title":"Quantifying Accretion of Intra-Oceanic Arcs to Continent: Numerical Modeling of Their Crustal Composition and Rheological Property","authors":"Shengxuan Tang, Keda Cai, Kai Wang, Hao Zhou","doi":"10.1029/2025jb033391","DOIUrl":"https://doi.org/10.1029/2025jb033391","url":null,"abstract":"Two primary mechanisms responsible for continental crustal growth at convergent margins have been acknowledged, including continental arc magmatism and allochthonous terrane accretion. As such, intra-oceanic arcs (IOAs), which represent potential accretion terranes, have been regarded as one of the fundamental contributors. It is noted that current IOAs, mainly outcropping in the western Pacific, show remarkable diversity in their crustal composition and rheological properties. However, it remains unclear how the diversity affects the accretion processes of IOAs and further determines their accretion efficiencies. Here, we conducted 2-D geodynamic modeling to explore these issues. Our models reveal the accretion process and efficiency relying on compositional differentiation and rheological stratification. Specifically, nascent IOAs characterized by a partially molten zone at the level of Moho, where buoyant crust can be separated from dense mantle, result in accretion efficiencies as high as ∼76.4% when slab break-off took place concurrently. In contrast, mature arcs with cold thermal gradients show a coherent crust-mantle transition and complete subduction, giving rise to the lowest accretion efficiency. Some of these modeling results align with geophysical observations from modern IOAs, such as the Izu-Bonin arc and Kyushu-Palau ridge, which display different accretion processes and efficiencies. The others are likely plausible mirrors of ancient orogenic belts, including the Cenozoic Kohistan arc and the Paleozoic Central Asian Orogenic Belt.","PeriodicalId":15864,"journal":{"name":"Journal of Geophysical Research: Solid Earth","volume":"334 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146184433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gustavo Bejar, Gregory P. Waite, Rudiger Escobar-Wolf, Snehamoy Chatterjee, Ashley Bosa, Amilcar Roca, Jeffrey B. Johnson, Jerry Mock, Armando Pineda
Lahars are among the most frequent hazards associated with Volcán de Fuego, Guatemala. Despite their recurrence, early detection and automated alerts remain challenging since they often rely on manual monitoring and sparse visual confirmation. Yet, we can harness the high number of flows triggered every rainy season to characterize their seismic signatures and quantify their size and behavior. For this, we used seismic stations located along two active lahar channels on Fuego where this characterization describes a somewhat stable long-term flow behavior. This work revealed more varied short-term behavior characterized by increasing seismic activity in the time domain and a shift toward lower frequencies as these flows propagate downstream. Building on this characterization, we implemented K-nearest neighbor (KNN) based detectors using seismic signal attributes describing samples of the data in the time and frequency domains, as well as statistical functions of these samples. We trained generalized and station-specific detectors that achieved high accuracy for detecting moderate-to-large flows with lower performance for smaller or ambiguous events. We found that root mean square amplitude, a proxy for flow size, appears to control detector performance more than other signal features. The detector is computationally efficient and, in the case of Fuego, did not require additional instrumentation. This framework presents a portable solution for enhancing automated lahar detection while minimizing the use of location-specific parameters required by other methods.
火山泥流是危地马拉Volcán de Fuego最常见的灾害之一。尽管它们反复出现,但早期检测和自动警报仍然具有挑战性,因为它们通常依赖于手动监控和稀疏的视觉确认。然而,我们可以利用每个雨季触发的大量流动来表征它们的地震特征,并量化它们的大小和行为。为此,我们使用了位于Fuego的两个活跃火山泥流通道沿线的地震台站,该特征描述了某种程度上稳定的长期流动行为。这项工作揭示了更多变化的短期行为,其特征是地震活动在时域上增加,并且随着这些流向下游传播,向较低频率转移。在此特征的基础上,我们实现了基于k -最近邻(KNN)的检测器,该检测器使用地震信号属性来描述时域和频域的数据样本,以及这些样本的统计函数。我们训练了广义的和特定于站点的检测器,这些检测器在检测中大型流量时达到了高精度,而在较小或模糊的事件中性能较低。我们发现均方根振幅,流量大小的代理,似乎比其他信号特征更能控制检测器的性能。探测器的计算效率很高,在Fuego的情况下,不需要额外的仪器。该框架提供了一种便携的解决方案,用于增强自动火山泥流检测,同时最大限度地减少其他方法所需的特定位置参数的使用。
{"title":"Seismic Characterization of Lahars on Volcán de Fuego Toward the Development of a Machine Learning-Based Detection Algorithm","authors":"Gustavo Bejar, Gregory P. Waite, Rudiger Escobar-Wolf, Snehamoy Chatterjee, Ashley Bosa, Amilcar Roca, Jeffrey B. Johnson, Jerry Mock, Armando Pineda","doi":"10.1029/2025JB032019","DOIUrl":"10.1029/2025JB032019","url":null,"abstract":"<p>Lahars are among the most frequent hazards associated with Volcán de Fuego, Guatemala. Despite their recurrence, early detection and automated alerts remain challenging since they often rely on manual monitoring and sparse visual confirmation. Yet, we can harness the high number of flows triggered every rainy season to characterize their seismic signatures and quantify their size and behavior. For this, we used seismic stations located along two active lahar channels on Fuego where this characterization describes a somewhat stable long-term flow behavior. This work revealed more varied short-term behavior characterized by increasing seismic activity in the time domain and a shift toward lower frequencies as these flows propagate downstream. Building on this characterization, we implemented K-nearest neighbor (KNN) based detectors using seismic signal attributes describing samples of the data in the time and frequency domains, as well as statistical functions of these samples. We trained generalized and station-specific detectors that achieved high accuracy for detecting moderate-to-large flows with lower performance for smaller or ambiguous events. We found that root mean square amplitude, a proxy for flow size, appears to control detector performance more than other signal features. The detector is computationally efficient and, in the case of Fuego, did not require additional instrumentation. This framework presents a portable solution for enhancing automated lahar detection while minimizing the use of location-specific parameters required by other methods.</p>","PeriodicalId":15864,"journal":{"name":"Journal of Geophysical Research: Solid Earth","volume":"131 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146160276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Ireland, J. Biggs, N. Anantrasirichai, F. Albino, E. W. Dualeh
Volcano deformation measured through Interferometric Synthetic Aperture Radar (InSAR) is ideal for volcano monitoring in many regions due to its global coverage, characteristic spatio-temporal patterns, and modeling insights. Routinely acquired and processed Sentinel-1 InSAR datacubes provide the first opportunity to systematically catalog, model and compare volcano deformation globally. Here, we present a framework (GBIS-BULK) to systematically pre-process and model volcano deformation signals, designed to be applied to routinely processed InSAR data sets. This requires a robust (semi-) automated approach to estimate signal locations and footprints for effective pre-processing and modeling. Our approach combines (a) filtering and clustering to locate the signal center; (b) noise reduction using Independent Component Analysis (ICA); and (c) image classification using Otsu thresholding to delimit the signal footprint. We invert for the best-fit point source model using constraints from existing global volcano deformation catalogs. First, we examine the influence of downsampling schemes, image noise and coherence using synthetic interferograms, showing nested-uniform downsampling is more suited to automated processing than quadtree methods which typically require manual tuning. Then, we validate the approach using Sentinel-1 deformation images from the East African Rift System (EARS). The pre-processing steps reasonably locate the signal at 15/16 of the EARS volcanoes, and the signal footprint at 14/16. ICA reduces or approximately maintains the image RMS in all cases. Our systematic point source estimates showed consistency when directly compared with previous (bespoke) modeling studies. This approach has the potential to be integrated with existing toolkits for routinely processing and analyzing Sentinel-1 InSAR data and hence applied globally.
{"title":"Toward Systematic Modeling of Volcano Deformation Sources Using Automatically-Generated InSAR Products","authors":"B. Ireland, J. Biggs, N. Anantrasirichai, F. Albino, E. W. Dualeh","doi":"10.1029/2025JB032897","DOIUrl":"10.1029/2025JB032897","url":null,"abstract":"<p>Volcano deformation measured through Interferometric Synthetic Aperture Radar (InSAR) is ideal for volcano monitoring in many regions due to its global coverage, characteristic spatio-temporal patterns, and modeling insights. Routinely acquired and processed Sentinel-1 InSAR datacubes provide the first opportunity to systematically catalog, model and compare volcano deformation globally. Here, we present a framework (GBIS-BULK) to systematically pre-process and model volcano deformation signals, designed to be applied to routinely processed InSAR data sets. This requires a robust (semi-) automated approach to estimate signal locations and footprints for effective pre-processing and modeling. Our approach combines (a) filtering and clustering to locate the signal center; (b) noise reduction using Independent Component Analysis (ICA); and (c) image classification using Otsu thresholding to delimit the signal footprint. We invert for the best-fit point source model using constraints from existing global volcano deformation catalogs. First, we examine the influence of downsampling schemes, image noise and coherence using synthetic interferograms, showing nested-uniform downsampling is more suited to automated processing than quadtree methods which typically require manual tuning. Then, we validate the approach using Sentinel-1 deformation images from the East African Rift System (EARS). The pre-processing steps reasonably locate the signal at 15/16 of the EARS volcanoes, and the signal footprint at 14/16. ICA reduces or approximately maintains the image RMS in all cases. Our systematic point source estimates showed consistency when directly compared with previous (bespoke) modeling studies. This approach has the potential to be integrated with existing toolkits for routinely processing and analyzing Sentinel-1 InSAR data and hence applied globally.</p>","PeriodicalId":15864,"journal":{"name":"Journal of Geophysical Research: Solid Earth","volume":"131 2","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025JB032897","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146153670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Quan Zhang, Pascal Audet, Martha Savage, Rupert Sutherland, Tim Stern
The geology of New Zealand has been shaped by tectonic plate interactions driven by mantle convection over the past 60 million years, but the effects of these interactions on the transition to the lower mantle are not yet well understood. We analyze 10 years of teleseismic