Dynamics Of Earth Research Articles

Bedding and bedding surfaces in carbonate and mixed carbonate-siliciclastic successions Part 1: a critical evaluation of biases in identification and interpretation across disciplines and schools

Carbonate sedimentary rocks are crucial for understanding Earth's geological history, ecosystems, and climate dynamics. However, their study is complicated by diagenetic processes that can alter original bedding and surfaces, leading to potential misinterpretations, for example of palaeoecological and sedimentological settings as well as the time represented by these surfaces and the overall succession of deposits. This study examines the varied definitions and interpretations of bedding and associated surfaces in carbonate rocks, highlighting differences across geoscientific disciplines and regions. Through a survey, we aim to clarify the usage of the terminology in bedding and associated surfaces to improve communication and reduce misunderstandings within the geoscientific community. The survey results highlight the highly diverse, but restrictive, individual perceptions of the term “bedding” in carbonate rocks. Significant differences exist between disciplines, a researcher's main region of education, and the main region of work. This study underscores the potential for miscommunication and misunderstandings among geoscientists regarding bedding and associated surfaces, emphasizing the importance of interdisciplinary and international exchange to recognize the varied origins of “bedding” in carbonate successions.

Two methods to analyze radial diffusion ensembles: The perils of space- and time-dependent diffusion

Particle dynamics in Earth's outer radiation belt can be modeled using a diffusion framework, where large-scale electron movements are captured by a diffusion equation across a single adiabatic invariant, L*(L). While ensemble models are promoted to represent physical uncertainty, as yet there is no validated method to analyze radiation belt ensembles. Comparisons are complicated by the domain dependent diffusion, since diffusion coefficient DLL is dependent on L. We derive two tools to analyze ensemble members: time to monotonicity tm and mass/energy moment quantities N,E. We find that the Jacobian (1/L2) is necessary for radiation belt error metrics. Components of ∂E/∂t are explicitly calculated to compare the effects of outer and inner boundary conditions, and loss, on the ongoing diffusion. Using tm, N, and E, we find that: (a) different physically motivated choices of outer boundary condition and location result in different final states and different rates of evolution; (b) the gradients of the particle distribution affect evolution more significantly than DLL; (c) the enhancement location, and the amount of initial background particles, are both significant factors determining system evolution; (d) loss from pitch-angle scattering is generally dominant; it mitigates but does not remove the influence of both initial conditions and outer boundary settings, which are due to the L-dependence of DLL. We anticipate that this study will promote renewed focus on the distribution gradients, on the location and nature of the outer boundary in radiation belt modeling, and provide a foundation for systematic ensemble modeling.

Technical Overview of ISRO and NASA’s First Joint Mission: NASA-ISRO Synthetic Aperture Radar (NISAR) Satellite

The NASA-ISRO Synthetic Aperture Radar (NISAR) mission represents a groundbreaking collaboration aimed at comprehensively monitoring Earth's surface dynamics. Through the fusion of L-band and S-band radar frequencies, NISAR promises unprecedented precision in detecting subtle surface changes, ranging from ecosystem disruptions to ice sheet collapses and natural hazard occurrences. This paper explores the mission's objectives, technology, and significance in advancing our understanding of climate change impacts and hazard mitigation. The partnership between NASA and ISRO, culminating in the signing of agreements in 2014, underscores the international cooperation vital for addressing complex global challenges. With its targeted launch, NISAR heralds a new era in Earth observation, enabled by the fusion of cutting-edge technology and collaborative scientific endeavour.

Deep Earth System Data Laboratory (DeepESDL)

Abstract. The Deep Earth System Data Lab (DeepESDL) provides an AI-ready, collaborative environment for researchers aiming to study the Earth's complex dynamics using various datasets and empirical approaches. Recently opened to Early Adopters, it builds on projects like CAB-LAB and ESDL, utilizing well-established Python and Julia technology stacks. DeepESDL offers programmatic access to extensive analysis-ready data cubes and computational resources, enabling researchers to focus on analysis without extensive preparations. Scientists can use persistently available data cubes or generate user-tailored cubes from own data or publicly available datasets. The goal is to streamline data processing through empirical or AI methods within high-dimensional Earth Observation workflows. DeepESDL addresses the complete research cycle, from discovery of earth data to powerful analyses, collaborative scientific research, advanced data visualisation and publication of results, promoting FAIR and Open Science. Apart from serving as a research environment, DeepESDL showcases scientific use cases and supports educational purposes through capacity building, academic programs, and Open Science initiatives. This paper presents an overview of DeepESDL.

Monitoring the baric modulation of gas concentration in the Baksan Neutrino Observatory tunnel in the Elbrus Region using a differential absorption lidar

For the first time, concentrations of gases 12CO2,13CO2, СН4, Н2О and the dynamics of Earth degassing under the changing atmospheric pressure were remotely analyzed using a differential absorption lidar. To reduce the influence of external meteorological factors, the sensing was carried out in a dead-end tunnel of the Baksan Neutrino Observatory of the Institute for Nuclear Research of the Russian Academy of Sciences.

Learning to enhance areal video captioning with visual question answering

ABSTRACT The utilization of Unmanned Aerial Vehicles (UAV) in remote sensing (RS) has witnessed a significant surge, offering valuable insights into Earth dynamics and human activities. However, this has led to a substantial increase in the volume of video data, rendering manual screening and analysis impractical. Consequently, there is a pressing need for the development of automated interpretation models for these aerial videos. In this paper, we propose a novel approach that leverages visual dialogue to enhance aerial video captioning. Our model adopts an encoder-decoder architecture, integrating a Visual Question Answering (VQA) task before the captioning task. The VQA task aims to enrich the captioning process by soliciting additional information about the image content. Specifically, our video encoder utilizes ViT-L/16, while the decoder employs Generative Pre-trained Transformer-2 (Distill-GPT-2). To validate our model, we introduce a novel benchmark dataset named CapERA-VQA, comprising videos accompanied by sets of questions, answers, and captions. Through experimental validation, we demonstrate the effectiveness of our proposed approach in enhancing the automated captioning of aerial videos.

Crucial future observations and directions for unveiling magnetopause dynamics and their geospace impacts

The dynamics of Earth’s magnetopause, driven by several different external/internal physical processes, plays a major role in the geospace energy budget. Given magnetopause motion couples across many space plasma regions, numerous forms of observations may provide valuable information in understanding these dynamics and their impacts. In-situ multi-point spacecraft measurements measure the local plasma environment, dynamics and processes; with upcoming swarms providing the possibility of improved spatiotemporal reconstruction of dynamical phenomena, and multi-mission conjunctions advancing understanding of the “mesoscale” coupling across the geospace “system of systems.” Soft X-ray imaging of the magnetopause should enable boundary motion to be directly remote sensed for the first time. Indirect remote sensing capabilities might be enabled through the field-aligned currents associated with disturbances to the magnetopause; by harnessing data from satellite mega-constellations in low-Earth orbit, and taking advantage of upgraded auroral imaging and ionospheric radar technology. Finally, increased numbers of closely-spaced ground magnetometers in both hemispheres may help discriminate between high-latitude processes in what has previously been a “zone of confusion.” Bringing together these multiple modes of observations for studying magnetopause dynamics is crucial. These may also be aided by advanced data processing techniques, such as physics-based inversions and machine learning methods, along with comparisons to increasingly sophisticated geospace assimilative models and simulations.

Characteristics of Thin Magnetotail Current Sheet Plasmas at Lunar Distances

AbstractThe magnetotail current sheet plays a key role in the dynamics of Earth's magnetosphere. Specifically, the formation and subsequent reconnection of thin (ion‐gyroscale) current sheets are critical components of magnetospheric substorms. However, the precise mechanisms governing the configuration and distribution of current density in these thin current sheets remain elusive. By analyzing a data set consisting of 453 thin current sheet crossings observed by the Acceleration, Reconnection, Turbulence and Electrodynamics of Moon's Interaction with the Sun (ARTEMIS) mission, we explore the statistical properties of the ion and electron pressures and current densities, Ji and Je, in the spacecraft rest frame. Using magnetotail flapping and magnetic field measurements to estimate the total current density, J0, we find that it agrees well with the sum of those from direct ion and electron measurements, Ji + Je, respectively. In 65% of thin current sheets, electrons were found to dominate the contribution to the total current density in the spacecraft frame, with a typical dawnward drift velocity of ≳100 km/s. Diamagnetic drifts of electrons and ions estimated from their respective vertical pressure profiles (along the current sheet normal) reveal that the gradient of electron pressure alone cannot fully account for the observed high values of Je/Ji. Counter‐intuitively, for most (52% of) thin current sheets the electron vertical pressure profile is wider than the ion pressure profile, again suggesting that electron diamagnetism is an insufficient contributor to the current density at such sheets. These findings suggest the presence of a significant E × B dawnward drift that the electrons can fully acquire but ions cannot, being partially unmagnetized. We compare our results with those previously reported for the near‐Earth magnetotail and discuss them in the context of magnetotail current sheet modeling.

Pressure Dependence of Permeability in Cracked Rocks: Experimental Evidence of Non‐Linear Pore‐Pressure Gradients From Local Measurements

AbstractUnderstanding the coupling between rock permeability, pore pressure, and fluid flow is crucial, as fluids play an important role in the Earth's crustal dynamics. We measured the distribution of fluid pressure during fluid‐flow experiments on two typical crustal lithologies, granite and basalt. Our results demonstrate that the pore‐pressure distribution transitions from a linear to a non‐linear profile as the imposed pore‐pressure gradient is increased (from 2.5 to 60 MPa) across the specimen. This non‐linearity results from the effective pressure dependence of permeability, for which two analytical formulations were considered: an empirical exponential and a new micromechanics‐based model. In both cases, the non‐linearity of pore pressure distribution is predicted. Using a compilation of permeability versus Terzaghi's effective pressure data for granites and basalts, we show that our micromechanics‐based model has the potential to predict the pore pressure distribution over the range of effective pressures expected within the brittle crust.

Imbalanced Regressive Neural Network Model for Whistler‐Mode Hiss Waves: Spatial and Temporal Evolution

AbstractWhistler‐mode hiss waves are crucial to the dynamics of Earth's radiation belts, particularly in the scattering and loss of energetic electrons and forming the slot region between the inner and outer belts. The generation of hiss waves involves multiple potential mechanisms, which are under active research. Understanding the role of hiss waves in radiation belt dynamics and their generation mechanisms requires analyzing their temporal and spatial evolutions, especially for strong hiss waves. Therefore, we developed an Imbalanced Regressive Neural Network (IR‐NN) model for predicting hiss amplitudes. This model addresses the challenge posed by the data imbalance of the hiss data set, which consists of predominantly quiet‐time background samples and fewer but significant active‐time intense hiss samples. Notably, the IR‐NN hiss model excels in predicting strong hiss waves (>100 pT). We investigate the temporal and spatial evolution of hiss wave during a geomagnetic storm on 24–27 October 2017. We show that hiss waves occur within the nominal plasmapause, and follow its dynamically evolving shape. They exhibit intensifications with 1 and 2 hr timescale similar to substorms but with a noticeable time delay. The intensifications begin near dawn and progress toward noon and afternoon. During the storm recovery phase, hiss intensifications may occur in the plume. Additionally, we observe no significant latitudinal dependence of the hiss waves within |MLAT| < 20°. In addition to describing the spatiotemporal evolution of hiss waves, this study highlights the importance of imbalanced regressive methods, given the prevalence of imbalanced data sets in space physics and other real‐world applications.

Methyl-reducing methanogenesis by a thermophilic culture of Korarchaeia.

Methanogenesis mediated by archaea is the main source of methane, a strong greenhouse gas, and thus is critical for understanding Earth's climate dynamics. Recently, genes encoding diverse methanogenesis pathways have been discovered in metagenome-assembled genomes affiliated with several archaeal phyla1-7. However, all experimental studies on methanogens are at present restricted to cultured representatives of the Euryarchaeota. Here we show methanogenic growth by a member of the lineage Korarchaeia within the phylum Thermoproteota (TACK superphylum)5-7. Following enrichment cultivation of 'Candidatus Methanodesulfokora washburnenis' strain LCB3, we used measurements of metabolic activity and isotope tracer conversion to demonstrate methanol reduction to methane using hydrogen as an electron donor. Analysis of the archaeon's circular genome and transcriptome revealed unique modifications in the energy conservation pathways linked to methanogenesis, including enzyme complexes involved in hydrogen and sulfur metabolism. The cultivation and characterization of this new group of archaea is critical for a deeper evaluation of the diversity, physiology and biochemistry of methanogens.

Sea Surface Wind Speed Estimation From the Combination of Satellite Scatterometer and Radiometer Parameters

AbstractSatellite research on global sea surface winds is crucial for understanding and monitoring the dynamics of earth's oceans, providing valuable insights into weather patterns, climate changes, and oceanographic processes. This study investigates the fusion of active (microwave scatterometer) and passive (microwave radiometer) satellite data using Machine learning (ML) for sea surface wind speed estimation. Employing Random Forest Regression (RF), Convolutional Neural Network Regression (CNN), and Multiple Linear Regression (MLR). Evaluation against reference data sets (Advanced Scatterometer, ERA5, Cross‐Calibrated Multi‐Platform (CCMP), buoy wind speeds) highlights the robustness of the proposed models. The research findings indicate that both RF and CNN exhibit superior accuracy in the active, passive, and joint active‐passive models compared to the simplistic MLR model. The joint models of the three regression methods outperform the individual active or passive models. The root mean square deviation (RMSD) accuracy of RF and CNN joint models, when compared with ASCAT, is in the order of 0.7 m/s, and when compared with buoys, the RMSD accuracy is around 1.1 m/s. The ML models, especially RF and CNN, demonstrate superior performance, providing accurate and reliable estimations crucial for meteorological and oceanographic applications. These findings underscore the potential operational use of ML techniques in enhancing remote sensing applications.

Ecoregional Site Study on Small Islands: A case study of the significance of flora for fisheries in the Anambas Islands

The formation of the Anambas Islands was a form of earth's surface dynamics that occurred over millions of years. In the process, there were at least eight land formations on the Sunda shelf. This evolution of the earth's surface led to the emergence of large islands on the Sunda shelf along with small islands around them. This also makes the Sundanese shelf part of the volcano's volcanic route. The Bunguran Formation was a bedrock complex that is thought to originate from deep-sea sediments of the Jurassic-Cretaceous age. The rocks are quite old, indicating that this formation was exposed to the surface and formed islands in the arc of the Anambas Islands group. All of these natural processes create a unique type of ecosystem, namely a rocky beach ecosystem, where the rocks at the study location were large rocks with cliffs on some of the coastlines. Meanwhile, sloping and protected locations allow the dust substrate to mix with sand to create a thin mud that allows mangrove forests to grow. Development in Anambas was carried out to grow the economy in this region. The Regional Government consistently develops in various fields. Some that stand out are the fisheries, tourism, and oil and gas sectors. It was believed that forests play a role in maintaining fisheries stocks on the coast, especially mangrove forests. Because of this, there was a need for a study that could display the flora profile in the Anambas Islands ecoregion. The results of the study show 23 species of flora in coastal forests and seven species of mangroves.

Inversion of fluid-release rates from episodic tremor and slip signals in subduction zones via a coarse-grained reaction diffusion model

Episodic Tremor and Slip (ETS) events showcase dynamic interactions of oscillatory slow slips and tremors deep within subduction zones and offer a window into Earth's internal dynamics. However, the exact mechanisms driving these events remain unresolved. This study proposes a novel approach that goes beyond traditional explanations focused on fluid pressure from mineral dehydration. Existing models often neglect the intricate interplay between fluid and rock pressures across various depths and potential fluid sources. This calls for a more comprehensive understanding of how fluid release from reactions interacts with rock deformation. The present formulation captures the interplay between fluid and solid pressures providing a more rigorous picture of ETS events. It employs a minimalistic and efficient approach based on integrating dehydration reactions. The model thereby develops a generic framework for mineral dehydration, offering an enhanced perspective of the underlying processes without the need to trace down to specific minerals. It allows a refined fit to GPS data by including high-frequency components from linear and nonlinear stability analyses, giving rise to improved correlation coefficients. Through the inclusion of the dynamic interplay between fluid and rock pressure diffusion within subduction zones, we propose a unified model of ETS events.

Volcanic arc rigidity variations illuminated by coseismic deformation of the 2011 Tohoku-oki M9.

Rock strength has long been linked to lithospheric deformation and seismicity. However, independent constraints on the related elastic heterogeneity are missing, yet could provide key information for solid Earth dynamics. Using coseismic Global Navigation Satellite Systems (GNSS) data for the 2011 M9 Tohoku-oki earthquake in Japan, we apply an inverse method to infer elastic structure and fault slip simultaneously. We find compliant material beneath the volcanic arc and in the mantle wedge within the partial melt generation zone inferred to lie above ~100 km slab depth. We also identify low-rigidity material closer to the trench matching seismicity patterns, likely associated with accretionary wedge structure. Along with traditional seismic and electromagnetic methods, our approach opens up avenues for multiphysics inversions. Those have the potential to advance earthquake and volcano science, and in particular once expanded to InSAR type constraints, may lead to a better understanding of transient lithospheric deformation across scales.

Beam‐Driven Electron Cyclotron Harmonic and Electron Acoustic Waves as Seen in Particle‐In‐Cell Simulations

AbstractRecent study has demonstrated that electron cyclotron harmonic (ECH) waves can be excited by a low energy electron beam. Such waves propagate at moderately oblique wave normal angles (∼70°). The potential effects of beam‐driven ECH waves on electron dynamics in Earth's plasma sheet is not known. Using two‐dimensional Darwin particle‐in‐cell simulations with initial electron distributions that represent typical plasma conditions in the plasma sheet, we explore the excitation and saturation of such beam‐driven ECH waves. Both ECH and electron acoustic waves are excited in the simulation and propagate at oblique wave normal angles. Compared with the electron acoustic waves, ECH waves grow much faster and have more intense saturation amplitudes. Cold, stationary electrons are first accelerated by ECH waves through cyclotron resonance and then accelerated in the parallel direction by both the ECH and electron acoustic waves through Landau resonance. Beam electrons, on the other hand, are decelerated in the parallel direction and scattered to larger pitch angles. The relaxation of the electron beam and the continuous heating of the cold electrons contribute to ECH wave saturation and suppress the excitation of electron acoustic waves. When the ratio of plasma to electron cyclotron frequency ωpe/ωce increases, the ECH wave amplitude increases while the electron acoustic wave amplitude decreases. Our work reveals the importance of ECH and electron acoustic waves in reshaping sub‐thermal electron distributions and improves our understanding on the potential effects of wave‐particle interactions in trapping ionospheric electron outflows and forming anisotropic (field‐aligned) electron distributions in the plasma sheet.

Low-energy Earth–Moon transfers via Theory of Functional Connections and homotopy

Numerous missions leverage the weak stability boundary in the Earth–Moon–Sun system to achieve a safe and cost-effective access to the lunar environment. These transfers are envisaged to play a significant role in upcoming missions. This paper proposes a novel method to design low-energy transfers by combining the recent Theory of Functional Connections with a homotopic continuation approach. Planar patched transfer legs within the Earth–Moon and Sun–Earth systems are continued into higher-fidelity models. Eventually, the full Earth–Moon transfer is adjusted to conform to the dynamics of the planar Earth–Moon Sun-perturbed, bi-circular restricted four-body problem. The novelty lies in the avoidance of any propagation during the continuation process and final convergence. This formulation is beneficial when an extensive grid search is performed, automatically generating over 2000 low-energy transfers. Subsequently, these are optimized through a standard direct transcription and multiple shooting algorithm. This work illustrates that two-impulse low-energy transfers modeled in chaotic dynamic environments can be effectively formulated in Theory of Functional Connections, hence simplifying their overall design process. Moreover, its synergy with a homotopic continuation approach is demonstrated.

Ab initio determination of melting and sound velocity of neon up to the deep interior of the Earth.

The thermophysical properties and elemental abundances of the noble gases in terrestrial materials can provide unique insights into the Earth's evolution and mantle dynamics. Here, we perform extensive abinitio molecular dynamics simulations to determine the melting temperature and sound velocity of neon up to 370GPa and 7500K to constrain its physical state and storage capacity, together with to reveal its implications for the deep interior of the Earth. It is found that solid neon can exist stably under the lower mantle and inner core conditions, and the abnormal melting of neon is not observed under the entire temperature (T) and pressure (P) region inside the Earth owing to its peculiar electronic structure, which is substantially distinct from other heavier noble gases. An inspection of the reduction for sound velocity along the Earth's geotherm evidences that neon can be used as a light element to account for the low-velocity anomaly and density deficit in the deep Earth. A comparison of the pair distribution functions and mean square displacements of MgSiO3-Ne and Fe-Ne alloys further reveals that MgSiO3 has a larger neon storage capacity than the liquid iron under the deep Earth condition, indicating that the lower mantle may be a natural deep noble gas storage reservoir. Our results provide valuable information for studying the fundamental behavior and phase transition of neon in a higher T-P regime, and further enhance our understanding for the interior structure and evolution processes inside the Earth.

And now for something completely random: spatial distribution of Dickinsonia on the Ediacaran seafloor

The oldest evidence of motile complex benthic multicellular organisms is found in Ediacaran aged rocks. At Nilpena Ediacara National Park (NENP), South Australia, one of the most iconic of such organisms, Dickinsonia, are found in abundance, with over 500 individuals preserved across the site's 33 in situ, fossiliferous beds. These beds vary in mat type and maturity, community diversity and population size. Here, we investigate six beds using spatial point pattern analysis (SPPA) to compare Dickinsonia spatial distributions between populations. Five populations were best-fit to a completely spatially random pattern, with a single outlier (TC-MM3) exhibiting signs of environmental heterogeneity. When distributions were examined in relation to other taxa, no indication of spatial competition was detected. Univariate and bivariate spatial distributions imply that Dickinsonia was generally not impacted by competition with other taxa, meter-scale environmental heterogeneity, or other external factors. These patterns hold when analyses were split between populations of large and small individuals, and these two size cohorts had no measurable effect on each other's spatial distributions. Additionally, we find no indication of intraspecific competition for Dickinsonia or any change in the preferred resources or habitats with growth. These results suggest that the anactualistic environmental conditions produced by ubiquitous organic mats present across Ediacaran seafloors at NENP provided such abundant nutrients that Dickinsonia did not have to compete for resources at the meter scale. These results further inform community-scale dynamics of Earth's earliest complex ecosystem.

Unveiling the Geological Significance and Industrial Application of Limestone: A Comprehensive Review

Limestone emerges as a fundamental component within sedimentary rock formations, which provides important information about previous geological eras and environmental circumstances. It retains fossils and remnants of extinct living forms because it mostly contains calcium carbonate. These deposits are used as traces of freshwater, marine, and terrestrial habitats from the past. Furthermore, variations in the creation of limestone provide hints about past geological events like tectonic activity and sea level shifts. Scientists can reconstruct previous ecosystems, temperatures, and evolutionary patterns by analyzing limestone, which helps us better comprehend Earth's environmental dynamics and history over millions of years. Its versatility extends beyond its geological significance, and its primary uses are in the manufacturing of steel and cement, as well as in the purification of wastewater and the processes involved in the production of bread and sugar. Limestone is also essential for supporting the carbon cycle and improving soil health in agricultural settings. In the review paper, we endeavored to conduct additional research to comprehend the intricacies of geology and the industrial application of limestone, as well as the need for interdisciplinary collaboration, sustainable practices, and cutting-edge technologies to leverage mineral resources for industrial growth. To be effective, it is essential. This study concludes with a strong call to action, imploring stakeholders to emphasize sustainable practices and encourage interdisciplinary collaboration while using limestone. By adhering to these guidelines, we can maximize the benefits of this priceless natural resource for both industrial use and environmental sustainability while also protecting it for future generations.