SummaryGeothermal heat flow (GHF) provides a first-order constraint on lithospheric thermal structure, yet continental-scale prediction remains challenging due to sparse, uneven, and strongly nonstationary observations. Most existing machine-learning approaches treat GHF measurements as spatially independent, limiting their ability to capture geological coherence across tectonic provinces. Here, we develop a spatial correlation recurrent neural network (SCRNN) that explicitly incorporates spatial dependencies among multiple variables to predict continental-scale GHF. By employing SCRNN, we produce a high-resolution GHF distribution of the contiguous United States. Higher GHF values are concentrated in tectonically active western regions characterized by crustal thinning, lithospheric extension, and fault systems. Lower GHF values are in the geologically stable central and eastern Craton of North America. SHapley Additive exPlanations analysis indicates that lithosphere-asthenosphere boundary depth, Moho depth, Curie-point depth, and fault systems exert first-order controls on GHF patterns. These results demonstrate that SCRNN captures meaningful controls on continental GHF.
When we think of a volcanic eruption, rivers of glowing lava or giant columns of ash come to mind. But beneath Earth's surface, a more complex story is unfolding. Magma deep within volcanoes is more than molten rock. It is a thick mixture of melted rock and solid mineral crystals known as "magma mush". To picture it, imagine a semi-frozen granita: a slushy blend of solid ice crystals suspended in sweet liquid syrup.
Publication date: 15 November 2026
Source: Earth and Planetary Science Letters, Volume 694
Author(s): Chengshuai Yuan, Xiaomei Wang, Xingwang Tian, Lianjie Tian, Chunlong Yang, Yuke Liu, Sheng-Ao Liu, Shuichang Zhang
Publication date: 15 November 2026
Source: Earth and Planetary Science Letters, Volume 694
Author(s): Joseph Van Linn, Grace Barcheck, Camilla Cattania, Gregory C. McLaskey
Publication date: 15 November 2026
Source: Earth and Planetary Science Letters, Volume 694
Author(s): Dan A.J. Stepner, Jonathan O’Neil, Chris G. Couëslan
Publication date: 15 November 2026
Source: Earth and Planetary Science Letters, Volume 694
Author(s): Rumeng Guo, Yijun Zhang, Yang Xiao, Xiongwei Tang, Dechuan Liu, Ye Xu, Jihong Liu, Jingqi Wang, Jingwei Li, Jianqiao Xu, Heping Sun, Yong Zheng
Publication date: 15 November 2026
Source: Earth and Planetary Science Letters, Volume 694
Author(s): Carlos A. Vergara, Manuel A. Florez, German A. Prieto
Publication date: 15 November 2026
Source: Earth and Planetary Science Letters, Volume 694
Author(s): Pan Zhang, Kang-Jun Huang, Yan Hu, Fang-Zhen Teng, Long Ma, Tian-Yi Huang
Publication date: 15 November 2026
Source: Earth and Planetary Science Letters, Volume 694
Author(s): Matthew W. Schmidt, Brian J. Close, Jennifer E. Hertzberg, Franco Marcantonio
Publication date: 15 November 2026
Source: Earth and Planetary Science Letters, Volume 694
Author(s): Kun Wang, Jianfeng Yang, Liang Zhao
Publication date: 15 November 2026
Source: Earth and Planetary Science Letters, Volume 694
Author(s): Xinyu Jiang, Xiaodong Song, Xuezhen Zhang, Haoyu Xu, Xingchen Wang, Bin He, Hejun Zhu
SummarySeismic anisotropy, the dependence of seismic wave speeds on the direction of propagation and/or polarization, places crucial constraints on deformation and convective flow in the lowermost mantle (the D″ layer). Shear waves that diffract along the core-mantle boundary (CMB) are ideally suited for probing this region due to their long horizontal ray paths in the lowermost mantle. However, the inference of D″ anisotropy presents multiple methodological challenges, including the need for accurate upper mantle corrections and the potential for apparent splitting produced by isotropic structures. In this study, we leverage global wavefield simulations to develop an automated measurement procedure that excludes Sdiff waves that are strongly SVdiff-polarized, which can lead to apparent splitting even in the absence of seismic anisotropy. We apply this workflow to a global dataset of ~20 million three-component seismograms. By adhering to strict quality control criteria, we generate a highly regionally consistent dataset of high-confidence measurements. Overall, we obtain ~4, 300 Sdiff splitting measurements that constrain the presence or absence of D″ anisotropy. We project these measurements onto the D″ layer and report Sdiff splitting across 237 global geographic bins (approximately 28 per cent of the D″ layer by surface area) with sufficient data coverage. Of these, 55 bins exhibit clear splitting, many of which are located beneath the northern Pacific. Furthermore, we characterize the directional dependence of splitting using a backazimuth binning algorithm for regions with multi-directional coverage. We make this curated dataset of geographically and directionally binned Sdiff splitting measurements, along with all codes necessary to reproduce it, publicly available.
SummaryThe mechanical properties of Earth’s uppermost layers are seismically relevant because they can modify seismic waves as they pass through them. These properties may significantly modify the intensity of ground shaking during an earthquake. The relatively common presence of fluids in these layers raises the question of whether they can affect ground motion during earthquakes. In general, seismic ground motion results from the complex interaction of P- and S-waves within the subsurface, and it is certainly influenced by the presence of fluids. This work examines the effects of varying the groundwater level on seismic ground motion by studying the propagation of P- and S-waves through a saturated porous layer over an elastic half-space. Our results show that ground motion due to both types of incident waves is affected by the presence of water, with changes in amplitude and resonance frequency. These results highlight the importance of accounting for fluid saturation in both site characterization and site response.
SummaryThe potential for geothermal resources and the tectonic activity of the north-central region of the Gulf of California, Mexico (GoC) offer a good opportunity to investigate the lithospheric structure of this region. We used one year of ambient seismic noise and 11 shallow earthquakes recorded by the Gulf of California Broadband Seismological Network (RESBAN) and stations from the Northwest Mexico Seismic Network (RESNOM) and the National Seismological Service (SSN) to estimate the three-dimensional S-wave velocity structure. We used surface wave travel times at short and long periods, and a two-stage tomography technique to retrieve an S-wave velocity model. We use coarse mesh of 16×40 cells with dimensions of 20×20 km in the horizontal direction and variable up to 60 km in depth. The absolute velocity model shows three areas in depth and significant lateral changes from the north to the center of the GoC associated with crustal and upper-mantle structure. We observed variations in crustal thickness that would indicate a variable Moho depth in the northern GoC and a likely constant depth towards the center of the Gulf. We identified low-velocity anomalies that could confirm the existence of a geothermal system in the north of the Gulf. The velocity models show relative changes associated with a heterogeneous lithosphere from the central region to the north of the GoC, which would indicate a transition from weak to stronger lithosphere. Velocity anomalies explain some of the tectonic differences between the north and the central GoC, as well as geophysical observations, including heat flow measurements and seismicity.
SummaryWe examined source characteristics of the recent earthquake sequence that occurred in February 2025 between the volcanic fields of Santorini, Kolumbo, Anydros, and Amorgos in south-central Aegean. This region lies within the volcanic back-arc domain of the Hellenic subduction zone in the Aegean Sea. During this period, the area experienced intense seismic activity (ten earthquakes 5.0 < Mw < 5.5), with earthquake magnitudes generally increasing towards Amorgos Island. The largest event was the Mw 5.4 earthquake on 10 February 2025, located northeast of Santorini. In this study, we first obtained 4,869 earthquakes that occurred between 2 January 2024 and 23 March 2025. We then derived full moment-tensor (MT) solutions for 30 earthquakes (Mw ≥ 4.5) by inverting seismological datasets. In addition, principal stress orientations were calculated by stress tensor inversion to recognize the most recent crustal stress field in the region. The spatio-temporal distribution of the relocated aftershocks indicates that the seismic activity initiated beneath the Santorini and Kolumbo volcanic centers, and subsequently migrated northeastward towards Anydros and Amorgos. Most earthquakes occurred at shallow crustal depths of approximately 5–15 km. Stress-inversion results and the orientation of T-axes highlight a dominant NW–SE extensional regime that characterizes the combined effects of deep geodynamic processes and shallow crustal dynamics in the back-arc area of the Aegean. The full MT solutions reveal predominantly normal, oblique-normal, and strike-slip faulting mechanisms, accompanied by significant non-double-couple (non-DC) components. These non-DC signatures strongly suggest tensile processes that are likely related to magma intrusion, fluid migration, or hydraulic fracturing. We therefore conclude that the 2025 seismic sequence was largely driven by crack-opening mechanisms and fluid- or magma-induced activity within the crust, consistent with the broader structural framework and volcanic nature of the Santorini–Amorgos region. Overall, this study enhances our knowledge on tectonic characteristics of the 2025 Santorini-Amorgos earthquake activity, which is significant for evaluating and monitoring the potential hazards in the south-central Aegean region.
SummaryJoint inversion of electrical and electromagnetic (E&EM) data can reduce the non-uniqueness of geophysical inversion by exploiting the complementary sensitivities of galvanic and inductive measurements. However, many existing approaches either rely on one-dimensional electromagnetic (1D EM) forward modelling or neglect induced polarization (IP) effects, which can be limiting in the presence of polarizable targets or laterally complex structures. We present a joint inversion framework that combines three-dimensional electromagnetic (3D EM) modelling with two-dimensional direct current resistivity and induced polarization (2D DCIP) modelling. The framework uses a common maximum phase angle (MPA) reparameterization of the Cole-Cole model for both inductive and galvanic data, together with decoupled forward and model meshes that allow each EM system to be modelled on a dedicated 3D forward mesh while all datasets update a common 2D inversion model. The method is evaluated using two synthetic examples and a mineral exploration field dataset. The synthetic examples represent a hydrogeological setting with weak-to-moderate IP effects and a mineral exploration setting with stronger IP effects associated with a finite conductive and polarizable intrusion. For both cases, we compare EM-only inversion, DCIP-only inversion, 1D EM/2D DCIP joint inversion, and 3D EM/2D DCIP joint inversion. The results show that the 3D EM/2D DCIP joint inversion improves the recovery of resistivity and IP structures when 3D EM effects are significant. In the hydrogeological example, the 3D EM kernel improves the imaging of laterally complex clay-rich structures, whereas in the mineral exploration example it reduces artefacts associated with the finite intrusion and improves the separation of distinct polarizable zones. The field application combines airborne EM and ground DCIP data acquired over Fe-Ti-V oxide mineralization in southern Portugal. The joint inversion honours both datasets and provides a single resistivity and IP model compatible with the main geological setting. Overall, the results indicate that 3D EM/2D DCIP joint inversion is useful for interpreting inductive and galvanic datasets across different IP regimes, particularly where finite or laterally complex polarizable structures make 1D EM modelling inadequate.
SummaryGeophysical inversion is inherently non-unique, and efficient uncertainty quantification remains a major challenge for large-scale applications. Conventional Bayesian approaches, such as Markov chain Monte Carlo (McMC), provide rigorous posterior estimates but are often computationally prohibitive, while deterministic inversion methods lack uncertainty characterization. In this study, we develop a Stein variational gradient descent (SVGD) framework for one-dimensional (1-D) geophysical Bayesian inversion. SVGD is a variational inference method that approximates the posterior distribution using an ensemble of interacting particles, which are iteratively updated through gradient-based optimization. The proposed framework is evaluated using airborne electromagnetic (AEM) data in both synthetic and field scenarios. Synthetic tests demonstrate that SVGD effectively recovers subsurface resistivity structures while capturing associated uncertainty. The influence of particle number on posterior resolution and computational cost is analyzed, and comparison with McMC highlights differences in posterior characteristics and computational efficiency. Application to field data from the Mississippi Alluvial Plain shows that the SVGD posterior mean agrees well with deterministic inversion results, while providing the uncertainty estimates. In addition, noise sensitivity tests are conducted to investigate the impact of data errors on inversion behavior. We find that increasing noise level degrades resolution and shifts the posterior toward prior-dominated regimes. Overall, the SVGD framework provides a flexible and scalable approach to probabilistic geophysical inversion, with strong potential for extension to higher-dimensional problems.
When Pliny the Younger recorded his firsthand experience of the eruption of Mount Vesuvius 2,000 years ago—a cataclysm that buried Pompeii and killed his uncle, Pliny the Elder—he provided enough detail about the date to allow scientists to benchmark methods for dating volcanic eruptions.
Returning global temperatures to a climate target does not necessarily undo the damage caused by exceeding it, new Concordia-led research published in the journal Communications Earth & Environment finds.
Dryland ecosystems cover 40% of the Earth's land surface and support more than 2 billion people. According to a new study published in Nature Climate Change, they're becoming increasingly unstable.
