Feed aggregator

Editors’ Highlights are summaries of recent papers by AGU’s journal editors. Source: AGU Advances

Plasma density irregularities are small-scale ripples in the ionized gas surrounding the Earth and other planets – some no larger than a hundred-meter city block in length. They can affect the propagation of radio waves by steering, trapping, or scattering specific portions of a radio signal, and thereby impact satellite communications and navigation in a complex manner – GPS navigation being a good example on Earth.

NASA’s Mars Atmosphere and Volatile Evolution (MAVEN) satellite recently revealed that the plasma density irregularities in the Mars ionosphere are electromagnetic in nature, in contrast to the electrostatic nature in the terrestrial ionosphere: the variations in density are accompanied by changes in the magnetic field.

Using numerical simulations to investigate how these irregularities form and evolve, Jiang et al. [2026] find that electromagnetic Rayleigh-Taylor instability (RTI) – a special kind of plasma instability caused by gravity – can induce their formation in the nighttime Mars ionosphere. The magnetic field variations would reach the level of 1 nano-Tesla for plasma density variations up to 70% of the background density.

In addition to improving our understanding of the physical processes shaping the Mars ionosphere, these findings suggest that electromagnetic Rayleigh-Taylor instabilities may also be applicable on other weakly magnetized planets or satellites in the solar system.

Citation: Jiang, K., Lei, J., & Yan, M. (2026). Beyond the electrostatic approach: Numerical simulations of Martian ionospheric irregularities. AGU Advances, 7, e2026AV002327. https://doi.org/10.1029/2026AV002327

—Andrew Yau, Editor, AGU Advances

Text © 2026. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Tide levels can vary by almost a meter across a single bay, according to a new study that uses decades of satellite images to measure tides at the scale of individual beaches.

SummaryThe statistics of earthquake populations are governed by stress changes and event interactions at various scales which promote non-linear event cascades and seismicity clustering. Earthquake clustering in space and time is observed in both tectonic and volcanically dominated regions; however, notable differences exist for instance during eruptive sequences. Here, we characterize seismicity statistics in California and Hawaii and quantify differences in background rates and clustering. We compare three statistical approaches, i.e, i) Reasenberg declustering, ii) Gamma distribution fit, and iii) Nearest Neighbor Clustering which are applied to seismicity in Hawaii, southern California, and ETAS catalogs with known clustering characteristics. Tests with ETAS-catalogs suggest that background rate variations are more consistently resolvable using the Nearest Neighbor and Gamma distribution algorithm without requiring parameter adjustments to the specific study area. The Nearest Neighbor method tends to overestimate background rates, whereas the Gamma distribution algorithm shows systematic underestimation, suggesting that an ensemble model can improve the performance over any single method. Uncertainties in background rate estimates based on small magnitude events (e.g., M≥2.5) are high, in particular for the Reasenberg method, which overpredicts true rates by up to a factor of 4, and extrapolations to larger magnitudes need to be treated cautiously. Our analysis shows that the combination of the three approaches generates new insights into the processes that govern seismicity clustering. The analysis of southern California seismicity produces consistent results between the different methods, and the distribution of background seismicity rates is indistinguishable from Poissonian rates at magnitudes above 3.5. Conversely, the seismicity in Hawaii exhibits notable non-Poissonian background rate changes. Results from the Nearest Neighbor clustering analysis suggest notable differences between tectonic and volcano seismicity, including background rate changes and more pronounced spatiotemporal clustering around active volcanoes. Hawaiian seismicity is characterized by more localized spatial-temporal clustering, in particular during the 2018 eruption. This difference may be a result of magmatic, hydrothermal and eruptive processes, which make volcanic areas susceptible to stress perturbations and earthquake triggering at small scales.

SummaryMapping the internal structure of sedimentary basins, including the depth to basement, is valuable for a variety of geological applications, particularly the identification of natural resources such as groundwater and minerals, or of the geological structures associated with them. The magnetotelluric (MT) method has proven to be a reliable technique for imaging complete sedimentary sequences, especially in areas where thick sedimentary cover makes imaging challenging. However, due to the high regularisation required by MT inversion procedures, it is limited in its ability to precisely locate geological interfaces, which is crucial for exploration. Building on previous work where we imaged the basement using interface probabilities derived from 1D probabilistic inversion of MT data, we present a new method which allows for the simultaneous classification of multiple interfaces across an entire survey, incorporating constraints on the spatial relationships between models. As a result, we obtain spatially consistent model ensembles and classified interfaces corresponding to transitions between layers of consistent electrical resistivity. This classification effectively reduces the size of the model ensemble, decreasing uncertainty in the estimated depth of the interfaces of interest. We apply this method to the Eucla sedimentary basin in Western Australia, analysing 550 MT sites distributed across 12 profiles. The ensemble clustering clearly identifies three interfaces which are consistent with the sedimentary succession expected from this basin. The results show great consistency across all the survey, providing valuable insights into the geological setting of the area. This research demonstrates the capability to reliably image the structure of a sedimentary basin using MT, within a workflow that integrates probabilistic inversion and model ensemble classification.

SummaryThe Tournemire Underground Research Laboratory (URL) operated by ASNR (Autorité de Sûreté Nucléaire et de Radioprotection) is a French test site specifically developed to study and comprehend the confinement properties of low-porosity claystone formations. More specifically, this site allows developing an improved knowledge of the transport properties of the Toarcian (Early Jurassic) shale formation. This claystone shares indeed similar characteristics to the Callovo-Oxfordian claystone formation encountered at the Meuse/Haute-Marne underground research laboratory operated by ANDRA (Agence Nationale pour la gestion des Déchets RAdioactifs) to study the feasibility of the long-tern storage of nuclear wastes. In the present study, 18 rock samples of the Toarcian formation are used to study (i) the induced polarization properties of this formation at full water saturation and (ii) the desiccation of this claystone by looking at the evolution of the complex conductivity spectra with the decrease of the water saturation in the frequency range 1 mHz-45 kHz. In this second set of experiments, the complex conductivity spectra are fitted with a double Cole Cole complex conductivity model. We then obtain the values of the first and second Archie’s exponents and estimates of both surface conductivity and normalized chargeability. We also test relationships between the surface conductivity, the normalized chargeability, the quadrature conductivity, and both the cation exchange capacity and water content of these clay-rocks. Furthermore, the laboratory data are favorably explained by the so-called Dynamic Stern Layer (DSL) model developed in the last decade. In order to test this new knowledge in field conditions, an in situ experiment is performed in a gallery of the Tournemire URL to test the ability of the method to image the damage zone around a 80-cm hole drilled normal to the gallery axis. For this purpose, a set of 5 wells equipped with a total of 240 non-polarizing electrodes is successfully used to get both electrical conductivity and normalized chargeability tomograms, which are in turn used to image the water content around the main hole. The results are analysed in terms of stress distribution including the effect of plasticity.

Marine heat waves and extreme ocean acidification events are each damaging on their own. But when both stressors hit simultaneously, their individual effects can be exacerbated.

Under global warming, scientists have widely expected tropical cyclones (including typhoons and hurricanes) to bring more intense and frequent rainfall. The underlying physics seems intuitive: Rising temperatures allow the atmosphere to hold more moisture, which, combined with intensifying storms, should theoretically trigger more destructive downpours. However, when researchers analyze climate model projections, they encounter a puzzling phenomenon.

Editors’ Vox is a blog from AGU’s Publications Department.

As climate models become more advanced and complex, it is increasingly important to evaluate model performance with respect to observations. A new article in Reviews of Geophysics explores climate model evaluation and benchmarking efforts in the scientific community. Here, we asked the authors to give an overview of climate modeling, how scientists evaluate models, and what challenges remain.

When did scientists first start developing climate models?

While today’s climate models are comprised of millions of lines of code and need to be run on large supercomputers, climate modeling started over a century ago. Lewis Fry Richardson published his 1922 book ‘Weather Predication by Numerical Process’, outlining his idea to forecast the weather using differential equations. It took him six weeks to derive an eight-hour forecast by hand. It wasn’t until 1950 when the first computerized weather forecast was run at Princeton University, led by Jule G. Charney. Six years later, Norman Phillips published a paper titled ‘The general circulation of the atmosphere: a numerical experiment’, in which he details the first General Circulation Model (GCM) of the atmosphere.

Climate modeling, as a distinct field of study from weather forecasting, developed significantly throughout the 1960s, with several seminal studies being published which still underpin climate research today, culminating in the first results from a coupled atmosphere-ocean GCM, in which the atmosphere, ice, and ocean interact with each other for the first time (Manabe et al., 1975 Part 1 and Part 2).

What’s the difference between physical climate models and Earth System Models (ESMs)?

GCMs are predecessors of ESMs, which have been expanded to include more processes describing the climate system.

The difference between physical (“physics-based”) climate models (GCMs) and Earth System Models (ESMs) can be very clearly determined: GCMs are predecessors of ESMs, which have been expanded to include more processes describing the climate system. GCMs focus strictly on the physical processes and exchanges of energy and matter between the atmosphere, oceans, land surface, and sea ice. They therefore provide the means to understand the physics of the system.

ESMs are based on more comprehensive model configurations. In addition to the physical representation of the climate system, they also include processes such as interactive atmospheric chemistry, biogeochemical cycles, and marine/terrestrial ecosystems, and carbon exchange between Earth system components. These additional processes help with the realistic representation of the climate system and increase the confidence in future climate projections, but they come with increased costs in resources and time. Which configuration of climate models are used to prepare a simulation is therefore still very much dependent on the planned use of the simulation.

Why is it important to evaluate and benchmark climate models?

A diverse set of tests and diagnostics can help understand differences between models, differences caused by changes over model generations, and identify priorities for future scientific development.

Climate models are among the most important and useful scientific mechanisms to study the Earth system, and the past and future climate. Every generation of climate models brings new advances in representing processes in different components of the Earth system such as the atmosphere, oceans and land and their interactions. State-of-the-art models also include the representation of the carbon cycle across these different domains, allowing us to understand the role of carbon cycling in determining the Earth’s climate. Climate model evaluation with a wide variety of diagnostics is how we develop confidence in the fidelity with which models represent processes that affect future climate projections (IPCC AR 4). A diverse set of tests and diagnostics can help understand differences between models, differences caused by changes over model generations, and identify priorities for future scientific development.

What are some of the different ways that scientists evaluate climate model simulations?

Climate model evaluation is described as the process of comparing model simulations against observational or reanalyzes datasets. Benchmarking is the process where model simulations are evaluated with observations, reanalysis data, or with other models often resulting in a statement made about the “goodness” of the simulation or model based on a predetermined set of standards or criteria. One or more models can be compared against the same set of observations in evaluation. Some of the more basic diagnostics used in model evaluation are the comparison of climatological (average over a period of 30 years or so) means, inter-annual variability and biases often expressed as time series. Maps or spatial patterns comparing models and observations, statistical analyses such as distributions of a specific variable and portrait plots for multi-model evaluation are other approaches commonly used to evaluate models. More complex diagnostics such as water, energy or carbon budgets and cross-domain interactions (e.g. how does temperature vary with precipitation) are also used for better process-based evaluation.

The evaluation of climate model simulations can be grouped in six general approaches. Most approaches require observations and can be applied on a global or regional scale. Credit: Hassler et al. [2026], Figure 2

What are some specific model biases that have been improved due to routine assessments?

Systematic model evaluation assures scientists are frequently reminded of biases that have not been eliminated or that often recur, and it helps modeling centers identify process representations to prioritize in future model development. Biases in cloud and water vapor process representations have been reduced over the past 20 years due to the growth of detailed observations and improvements in cloud vertical distribution and parameter tuning.

The East Asian summer monsoon (EASM), which carries moisture from the Indian and Pacific Oceans to East Asia, exhibits intense interannual variability that results in severe droughts and floods. Several multi-model benchmarking studies have focused on model reproductions of the EASM, and they identified a weakened western North Pacific anticyclone as a primary cause of biases in the western Pacific subtropical high and the Meiyu-Baiu-Changma rainband.

Early efforts in evaluating land carbon cycle models identified persistent biases in the timing of the seasonal variation of vegetation growth, especially with respect to satellite-derived leaf area index (LAI), which were tied to an underestimate of carbohydrate pools carried from one growing season to the next. Land models substantially overestimated aboveground live biomass in the Amazon Basin compared to estimates from satellite observations, which researchers attributed primarily to low autotrophic respiration and excessive allocation of net primary production to wood. Improvements in model representation of vegetation processes significantly reduced these long-standing biases that have been routinely assessed through comparison with observational data for at least three decades.

What are some of the remaining biases in climate models where additional research and development efforts are needed?

Identifying persistent biases and tracking their reductions are crucial to strengthening the utility of projections from climate and Earth system models.

A variety of biases exhibited by many climate models have been difficult to reduce or completely eliminate despite frequent model evaluation and bias characterization. Many of these have led scientists to perform extensive model tuning exercises or apply bias removal techniques to reduce the impacts of such biases. Examples include both positive and negative regional biases in precipitation, the double ITCZ (intertropical convergence zone), warming biases in the tropical troposphere, and low Arctic Sea ice sensitivity to global warming compared to observations. Identifying such persistent biases and tracking their reductions are crucial to strengthening the utility of projections from climate and Earth system models. Creating a wealth of additional model performance metrics and enhancing collections of observational data sets are required to understand the sources of these long-standing model biases.

—Birgit Hassler (birgit.hassler@dlr.de, 0000-0003-2724-709X), Deutsches Zentrum für Luft- und Raumfahrt (DLR), Germany; Forrest Hoffman (0000-0001-5802-4134), Oak Ridge National Laboratory, United States; Ranjini Swaminathan (0000-0001-5853-2673), University of Reading, United Kingdom; and Beth Dingley (0000-0002-9831-9671), European Space Agency, United Kingdom

Editor’s Note: It is the policy of AGU Publications to invite the authors of articles published in Reviews of Geophysics to write a summary for Eos Editors’ Vox.

Citation: Hassler, B., F. Hoffman, R. Swaminathan, and B. Dingley (2026), Climate model benchmarking: building trust and advancing science, Eos, 107, https://doi.org/10.1029/2026EO265032. Published on 24 August 2026. This article does not represent the opinion of AGU, Eos, or any of its affiliates. It is solely the opinion of the author(s). Text © 2026. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

A new study has reconciled a long-standing paradox in the South Asian summer monsoon cycle. Climate scientists have discovered why geological records from land and sea have told opposite stories about monsoons throughout history and found that rising temperatures over Southern Africa reduce upwelling in the Arabian Sea, which could damage marine productivity and fisheries. The work is published in the journal Proceedings of the National Academy of Sciences.

Source: AGU Advances

Marine heat waves and extreme ocean acidification events are each damaging on their own. But when both stressors hit simultaneously, their individual effects can be exacerbated.

That threat may be best exemplified by “the Blob” of 2013–2015, during which both a marine heat wave and an ocean acidification extreme event hit the northeastern Pacific. Fisheries were closed, marine mammals were stranded, seabirds died, and sea creatures either changed their distribution or perished.

But our understanding of these compound heat-acidity ocean extreme events is limited, with more research focused on the marine heat wave component than on the acidification aspect.

Gregor and Gruber used 43 years of monthly data (1982–2024) on surface ocean temperatures and acidity to determine when, where, and why compound heat-acidity extreme events have occurred. They defined extreme events as those situations when detrended acidity and temperature exceed their 95th percentiles.

Compound ocean heat-acidity events happen more often than would be expected by chance, the authors found. In the low to midlatitudes, they occur roughly 4 times more often than compared to chance, mostly in places with permanent stratification. In these places, heat waves drive waters to be more acidic. The compound events were least common in the eastern equatorial Pacific and around the poles, where deep waters upwell to the surface. When marine heat waves strike in these upwelling regions, a warm lens (top layer of water) prevents the surfacing of the deep acidic waters, leading to unusually low acidity for the region.

A majority (73%) of compound heat-acidity extreme events in the study period were smaller than 500,000 square kilometers (193,000 square miles, roughly the size of Spain) and lasted for about a month. But a few events, like the Blob in 2015, lasted for more than a year, sometimes with long-lasting consequences.

El Niño and La Niña events are important drivers of these compound events, but the events seldom happen at the weather events’ epicenter in the equatorial Pacific. During El Niño, warmer waters create a lens that prevents upwelling, thus reducing the typical acidity of the region. And during La Niña, cold, deep waters with higher acidity upwell, resulting in only an acidification extreme. However, it is in the neighboring regions where the knock-on effect of this warming or acidity causes compound extremes to occur.

The new findings are in line with several key facets of earlier work and offer more insights into temporal patterns and drivers. (AGU Advances, https://doi.org/10.1029/2025AV002112, 2026)

—Rebecca Dzombak, Science Writer

Citation: Dzombak, R. (2026), Why marine heat waves and acidification strike together, Eos, 107, https://doi.org/10.1029/2026EO260269. Published on 24 August 2026. Text © 2026. AGU. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

Editors’ Highlights are summaries of recent papers by AGU’s journal editors. Source: Community Science

What are the benefits of sustainable agriculture practice, who reaps those benefits, and how do we measure them? Komarek et al. [2026] tackle those questions by integrating national-scale frameworks for assessing sustainable practices in agriculture with on-the-ground knowledge of farmers in the midwestern United States.

Through a combination of surveys and workshops, farmers and scientists worked together to a develop of usable and localized set of indicators for assessing the use of cover crops. “Indicators” are things you can measure to see how something is working; you can measure carbon in the soil to see if cover crops are making soil healthier. The paper describes the resulting indicators, but more importantly it shows that iterative engagement with farmers produces indicators that are easier to measure, give a more complete picture, and are more useful in decision-making that the indicators that come from national-level frameworks alone. It also reveals things that might have been missed otherwise: in this case, farmers recognized that some of the long-term benefits of cover crops accrued to landowners, while much of the short-term cost of cover cropping was born by the farmers who rented that land, illuminating a key challenge for increasing sustainable practices.

In the workshop, farmers used colored dots to qualitatively show whether each indicator revealed an increase (green) or decrease (red) in sustainability. Yellow indicates uncertainty or both positive and negative impacts on sustainability. Credit: Komarek et al. [2026], Figure 4

Citation: Komarek, A. M., Castellano, M. J., Jackson, K., Lee, A., Zhang, W., & Zhang, X. (2026). A participatory framework to assess agricultural sustainability: Cover cropping as an illustrative example. Community Science, 5, e2025CSJ000138. https://doi.org/10.1029/2025CSJ000138

—Rajul Pandya, Editor, Community Science Exchange

Text © 2026. The authors. CC BY-NC-ND 3.0
Except where otherwise noted, images are subject to copyright. Any reuse without express permission from the copyright owner is prohibited.

SummaryAcoustic wave propagation under pressure is inherently nonlinear and often exhibits hysteresis in elastic properties. Understanding this behaviour is important in rock physics and exploration seismology because pressure-dependent elastic responses contain information on evolving rock microstructure. We present a petrophysical model that describes the relationship between acoustic P- and S-wave velocities and effective rock pressure during both loading and unloading phases. Instead of prescribing a single microscopic mechanism, the model introduces an effective extensive state variable that represents the cumulative effect of pressure-induced microstructural evolution. Depending on the dominant physical process, this variable may be associated with compliant pore and microcrack volume, grain-contact evolution, or other pressure-sensitive structural descriptors. The model distinguishes between open and closed microstructural states and describes their stress-dependent evolution through different sensitivities during loading and unloading, thereby reproducing irreversible velocity-pressure behaviour within a unified framework. Model parameters are estimated from laboratory-measured acoustic velocities using linearized joint inversion. The inversion further enables the reconstruction of an acoustically weighted effective descriptor that characterises the pressure-dependent contribution of compliant microstructural evolution to the observed velocity response. In parallel, we apply the Preisach theory of hysteresis to pressure-dependent acoustic velocities. In this framework, compliant microstructural features are represented by effective hysteretic units (hysteron) characterized by distributed closing and opening pressures. The resulting Preisach model reproduces the measured hysteresis with high accuracy and enables a model-dependent reconstruction of the Preisach density function, which provides an effective, non-unique representation of hysteretic switching contributions across closing and opening pressures. By combining the petrophysical and Preisach approaches, we introduce two diagnostic quantities, the Ratio of Hysteron Jumps (RHJ) and the Cumulative Hysteron Jumps (CHJ), which quantify the relative and cumulative contributions of hysteretic elements throughout loading and unloading. While both approaches reproduce the observed velocity–pressure hysteresis, they provide complementary information. The petrophysical model describes the macroscopic evolution of elastic properties via an effective state variable and its acoustically weighted representation, whereas the Preisach model resolves the distribution and activation of hysteretic switching contributions in Preisach space via the reconstructed density function. The results demonstrate that acoustic hysteresis measurements contain not only information on effective elastic properties but also recoverable signatures of pressure-dependent microstructural evolution relevant to seismic interpretation.

As autumn gives way to winter across the Arctic, the ground doesn't immediately freeze solid. Instead, soils often linger near the freezing point for days or even weeks in a phase called the zero curtain. In a new NASA-led study, researchers produced high-resolution maps of the Arctic zero curtain.

Sometimes science throws up the unexpected. When a team of researchers set out to model river erosion in Canada's High Arctic, they did not expect the findings to defy common sense.

SummaryThe São Francisco Paleocontinental block (SFPB) and the Congo Paleocontinental block (CPB) composed, prior to the Atlantic opening in the Cretaceous, the São Francisco-Congo Paleocontinent (SFCP). The SFCP was one of the landmasses involved in the Neoproterozoic Brasiliano-Pan African Orogeny and the assembly of Western Gondwana. Both the SFPB and CPB underwent reworking during the amalgamation of Western Gondwana, forming the orogenic belts that surround the preserved portions of the SFPB and CPB that are known today as the São Francisco and Congo cratons. Although the crustal portions in the outermost areas of these paleocontinents are no longer visible in the surface due to this reworking, the limits of these paleocontinents remain relatively intact at subcrustal depths. The objectives of this study are to delimit the SFPB and to image the structures beneath the Araçuaí belt at mantle lithosphere depths. We present the results of our study which were obtained by the multiple-frequency seismic tomography method for the SFPB and adjacent structures between depths of 68 and 587 km. Data were obtained by processing broadband seismograms recorded between 11-August-2023 and 31-July-2024 for P and PKIKP phases. The processed database comprised 9 254 residuals, which were added to the database of a previous regional study resulting in 97 150 traveltime delays. Checkerboard resolution tests using patterns with horizontal dimensions of 390×390 km reveal very good recovery between depths of 68 and 226 km, although the sharp vertical transition between the checkerboard layers is not fully recovered between the depths of 316 and 384 km. The checkerboard pattern with horizontal dimensions of 312×312 km reveals that the best recovery is observed in the southern and eastern portions of the São Francisco craton (SFCr) and in the Borborema province (BP) between depths of 68 and 226 km. Our results show a high-velocity anomaly with roughly NE-SW trend that extends from the Paranapanema block (PaBl), through the entire extension of the SFCr up to the southern BP. This anomaly contains two major segmentations, one in the southern Brasilia belt, marking the division of the PaBl with the SFPB, and the other dividing the eastern and western arms of the SFPB with a roughly NW-SE trend, interpreted as the Paramirim aulacogen. We also observe a high-velocity anomaly beneath the Araçuaí belt (ArBe) that dips with a SE direction. This anomaly starts at the northern end of the Abre Campo suture at a depth of 136 km, deepens to the south, and is interpreted as the foundered cratonic lithosphere that originated from the delamination of the SFCr due to the passage of the Trindade plume. To reinforce our interpretation, we tested several synthetic models with geometries that were based on our results and previous studies in the area. The synthetic model which presents the most resemblance to the real data model contains a high-velocity anomaly beneath the Araçuaí belt between depths of 226 and 384 km. A strong low-velocity anomaly beneath the Ribeira Belt is interpreted as material rising from the Nazca Slab dehydration.

SummaryNon-Newtonian pore-fluid behaviour is incorporated into a generalized Lagrangian–dissipation framework for wave propagation in fluid-saturated porous media. In contrast to approaches that rely on prescribed pore-scale flow patterns, pore geometries, or other microscopic structural assumptions, the present formulation introduces nonlinear rheological effects directly at the macroscopic constitutive level. The resulting model remains consistent with continuum mechanics and Biot-type poroelasticity while allowing non-Newtonian effects to enter three fluid-related dissipation mechanisms: Darcy-type fluid–solid friction, local-deformation (LD) relaxation, and bulk-viscous dissipation. Nonlinear dissipation potentials are constructed for these mechanisms and then reduced, through a first-harmonic approximation, to effective frequency-dependent coefficients for harmonic wave analysis. Numerical examples show that the non-Newtonian Darcy-friction and LD mechanisms primarily modify the characteristic frequencies of the corresponding relaxation processes, whereas the non-Newtonian bulk-viscosity mechanism affects both the frequency range and the strength of attenuation and dispersion, with a strong sensitivity to the assumed magnitude of the pore-fluid bulk viscosity. The framework also allows alternative nonlinear representations of Darcy-type fluid–solid friction to be compared within the same Lagrangian–dissipation structure; an alternative nonlinear dissipation operator produces wave-propagation predictions nearly indistinguishable from those obtained using the power-law Darcy-friction model, suggesting that different nonlinear constitutive assumptions may lead to similar effective attenuation structures at the macroscopic scale. Calibration against laboratory measurements on tight carbonate rocks shows that the observed attenuation and velocity-dispersion behaviour can be reproduced using physically interpretable non-Newtonian parameters. These results suggest that non-Newtonian pore-fluid rheology may contribute to frequency-dependent wave-propagation effects in fluid-saturated porous media and provide a flexible macroscopic framework for investigating fluid-related dissipation beyond conventional Newtonian poroelastic models.

SummaryGravity data is widely applied to determine Moho topography due to globally dense and homogeneous gravity observations. Compared with gravity data, gravity gradients can reveal more details of Moho structure, which are more competitive. However, gravity gradients must be transformed into gravity data for common Vening Meinesz-Moritz (VMM) methods, which causes loss of some high-frequency signals. Thus, an improved method by constructing direct function relation between Moho topography and gravity gradients is proposed in this paper. Subsequently, A case study in Tibetan Plateau is conducted using this improved method, and a new Moho topography with higher spatial resolution is determined. More refined tectonic implications can be also revealed from this new Moho topography: (1) the prevailing wavelengths of detected Moho folds are approximately 578 km in the east-west direction and approximately 515 km - 708 km in the north-south direction; (2) two possible lower crustal mass flow channels can be identified clearly according to the traces leaving on Moho topography in the southeastern Tibetan Plateau (3) clearer Moho subsidence, approximately 5 km, can be observed in the central Tarim Basin.

SummaryThe northeastern margin of the Tibetan Plateau exhibits pronounced spatial variations in present-day vertical crustal deformation, yet the mechanisms controlling these differences remain debated. In particular, contrasting uplift patterns are observed between the Liupanshan tectonic belt and the Maxianshan Fault, two key tectonic structures along the northeastern expansion front of the plateau. Here we develop two three-dimensional viscoelastic finite element models constrained by geological structures, seismic profiles, and GNSS observations to investigate the controls on vertical deformation. The modeling results show that when the mid–lower crustal viscosity is laterally uniform between the Longxi Basin and the Ordos Block, vertical deformation of ~2 mm/a is concentrated within a ~50 km-wide zone near the Liupanshan tectonic belt, consistent with leveling observations. This deformation pattern mainly reflects crustal shortening and thickening dominated by pure shear. In contrast, the observed ~4 mm/a uplift along the hanging wall of the Maxianshan Fault can only be reproduced when weak mid–lower crust and enhanced crustal flow are introduced beneath the Linxia Basin, indicating that northeastward mid–lower crustal flow is converted into vertical uplift along the fault. These results suggest that the Maxianshan Fault represents the northeastern termination of mid–lower crustal flow within the Qilian Block, whereas deformation in the Liupanshan tectonic belt is primarily accommodated by crustal shortening. Our findings highlight the fundamental role of lateral rheological heterogeneity in controlling vertical deformation and provide new insights into the mechanisms of present-day lateral growth of the northeastern Tibetan Plateau.

Earth's inner core, composed primarily of iron with a small percentage of light elements, may enter a superionic state at extreme pressure and temperature, according to experimental results from researchers at Science Tokyo. Using laser-heated and electrically wired diamond-anvil cells, the researchers identified experimental signatures of superionic iron hydride at conditions relevant to Earth's core. These findings provide new insights into the composition and dynamics of Earth's deep interior.

Why do some lakes remain plagued by harmful algal blooms even after phosphorus pollution has been reduced? Part of the answer lies beneath the surface. A new Concordia study has uncovered a previously overlooked chemical process that can help trap phosphorus in lake sediments, preventing it from returning to the water, where it can fuel excessive plant and algal growth.