Feed aggregator

Abstract

Since the Voyager mission flybys in 1979, we have known the moon Io to be both volcanically active and the main source of plasma in the vast magnetosphere of Jupiter. Material lost from Io forms neutral clouds, the Io plasma torus and ultimately the extended plasma sheet. This material is supplied from Io’s upper atmosphere and atmospheric loss is likely driven by plasma-interaction effects with possible contributions from thermal escape and photochemistry-driven escape. Direct volcanic escape is negligible. The supply of material to maintain the plasma torus has been estimated from various methods at roughly one ton per second. Most of the time the magnetospheric plasma environment of Io is stable on timescales from days to months. Similarly, Io’s atmosphere was found to have a stable average density on the dayside, although it exhibits lateral (longitudinal and latitudinal) and temporal (both diurnal and seasonal) variations. There is a potential positive feedback in the Io torus supply: collisions of torus plasma with atmospheric neutrals are probably a significant loss process, which increases with torus density. The stability of the torus environment may be maintained by limiting mechanisms of either torus supply from Io or the loss from the torus by centrifugal interchange in the middle magnetosphere. Various observations suggest that occasionally (roughly 1 to 2 detections per decade) the plasma torus undergoes major transient changes over a period of several weeks, apparently overcoming possible stabilizing mechanisms. Such events (as well as more frequent minor changes) are commonly explained by some kind of change in volcanic activity that triggers a chain of reactions which modify the plasma torus state via a net change in supply of new mass. However, it remains unknown what kind of volcanic event (if any) can trigger events in torus and magnetosphere, whether Io’s atmosphere undergoes a general change before or during such events, and what processes could enable such a change in the otherwise stable torus. Alternative explanations, which are not invoking volcanic activity, have not been put forward. We review the current knowledge on Io’s volcanic activity, atmosphere, and the magnetospheric neutral and plasma environment and their roles in mass transfer from Io to the plasma torus and magnetosphere. We provide an overview of the recorded events of transient changes in the torus, address several contradictions and inconsistencies, and point out gaps in our current understanding. Lastly, we provide a list of relevant terms and their definitions.

Information on geomagnetic field intensity in the past is essential for understanding the behavior and mechanism of the geodynamo. A fundamental unresolved problem of relative paleointensity (RPI) estimations ...

Abstract

Trends in the deep-ocean M \(_2\) barotropic tide, deduced from nearly three decades of satellite altimetry and recently presented by Opel et al. (Commun Earth Environ 5:261, https://doi.org/10.1038/s43247-024-01432-5, 2024), are here updated with a slightly longer time series and with a focus on potential systematic errors. Tidal changes are very small, of order 0.2 mm/year or less, with a tendency for decreasing amplitudes, which is evidently a response to the ocean’s increasing stratification and an increasing energy loss to baroclinic motion. A variety of systematic errors in the satellite altimeter system potentially corrupt these small trend estimates. The Dynamic Atmosphere Correction (DAC), derived from an ocean model and used for de-aliasing, introduces a spurious trend (exceeding 0.1 mm/year in places) caused by changes in ECMWF atmospheric tides. Both operational and reanalysis atmospheric tides have spurious trends over the altimeter era. Tidally coherent errors in satellite orbits, including from use of inconsistent tidal geocenter models, are more difficult to bound, although differences between two sets of satellite ephemerides are found to reach 0.1 mm/year for M \(_2\) . Orbit errors are more deleterious for some other constituents, including the annual cycle. Tidal leakage in the “mesoscale correction,” needed here to suppress non-tidal ocean variability, is a known potential problem, and if the leakage changes over time, it impacts ocean-tide trend estimation. Tests show the error is likely small in the open ocean ( \(<0.04\)  mm/year) but large in some marginal seas ( \(>0.2\)  mm/year). Potential contamination from other altimeter corrections (e.g., ionospheric path delay) is likely negligible for M \(_2\) but can be difficult to bound.

Abstract

Global navigation satellite system (GNSS) Doppler measurements are immune to cycle slips, providing a robust way to detect ionospheric irregularities. This study presents a novel approach to detect equatorial plasma bubble (EPB) using a support vector machine (SVM) algorithm based on the GNSS Doppler measurements. The input of the detector is the Doppler index (DI), which is extracted from the dual-frequency differential Doppler observations. Data from HKWS station located in Hong Kong during 2022 are employed to train the SVM model and validate its performance. The results show the trained SVM model achieves 96.7% validation accuracy of EPB detection. To assess the general capability of the model, EPB events throughout the entire year of 2023 are investigated at both the HKWS station and the HYDE station. The results show the performance of EPB detection by the SVM model using DI is comparable to that of by visually inspecting the total electron content time series based on GNSS carrier-phase measurements. In addition, the characteristics of EPB occurrence are also consistent to previous studies, suggesting the detection results are reliable.

Abstract

Chondritic meteorites (chondrites) contain evidence for the interaction of liquid water with the interiors of small bodies early in Solar System history. Here we review the processes, products and timings of the low-temperature aqueous alteration reactions in CR, CM, CI and ungrouped carbonaceous chondrites, the asteroids Ryugu and Bennu, and hydrated dark clasts in different types of meteorites. We first consider the nature of chondritic lithologies and the insights that they provide into alteration conditions, subdivided by the mineralogy and petrology of hydrated chondrites, the mineralogy of hydrated dark clasts, the effects of alteration on presolar grains, and the evolution of organic matter. We then describe the properties of the aqueous fluids and how they reacted with accreted material as revealed by physicochemical modelling and hydrothermal experiments, the analysis of fluid inclusions in aqueously formed minerals, and isotope tracers. Lastly, we outline the chronology of aqueous alteration reactions as determined using the 53Mn-53Cr and 129I-129Xe systems.

Abstract

It is often accepted that the magnetic field structure of coronal mass ejections (CMEs) is accurately represented by the highly twisted circular cross-section magnetic flux rope model, which is the basis of all most commonly used sketches and representations of CMEs. This paradigm has been developed based on studies in the 1970s and 1980s, and it was the inspiration for a series of fitting models developed in the 1990s and 2000s to provide 3-D visualizations and representations for data obtained by remote sensing and in situ measurements. There has been a wealth of measurements since this paradigm was first developed, in particular numerous multi-point measurements and remote heliospheric observations of CMEs in addition to more physical models and numerical simulations. Taken together, they have demonstrated that such a paradigm, although it provides an explanation for certain CME signatures, is inadequate to represent the complexity of the magnetic field structure in numerous other cases. This manuscript reviews 40 years of continuous observations and ongoing research efforts since the proposal of the highly twisted circular cross-section flux rope model, and presents a more elaborate and realistic representation that better reflects the true complexity of the magnetic ejecta within CMEs.

Nature Geoscience, Published online: 03 February 2025; doi:10.1038/s41561-024-01636-6

Greenland-wide observations of crevasse volume and distribution suggest substantial increases in crevassing between 2016 and 2021 at marine-terminating sectors with accelerating ice flow.

We conduct a series of numerical experiments of thermal convection of compressible fluids with temperature-dependent viscosity, in order to study how the adiabatic compression and model geometries affect the m...

Many studies have estimated crustal deformation from observed geodetic data. So far, because most studies have applied a smoothness constraint, which includes the assumption of local uniformity of a strain-rat...

The Kenyan rift system is prone to deformation due to various geological processes and human activities, such as overexploitation of groundwater and exploitation of geothermal energy. Crustal deformation monit...

Abstract

Integrated Water Vapor (IWV) is crucial in environmental research, offering insights into atmospheric dynamics. Direct IWV measurement is challenging, necessitating alternative estimation technologies. Existing methods including Global Navigation Satellite System (GNSS), radiosondes, water vapor radiometers (WVR), satellite remote sensing, and numerical weather models (NWM), have specific limitations. GNSS and WVR provide high precision and temporal resolution (e.g., 5 min) but are limited to specific locations. Radiosondes, while accurate, have sparse spatial distribution and low temporal resolution (e.g., twice daily). Satellite remote sensing offers broad spatial resolution but lower temporal resolution (hours to days) and reduced accuracy under cloudy conditions and due to satellite tracks. NWMs provide global hourly products but their accuracy depends on meteorological data and model precision.

This study introduces a regional IWV predictive model using Machine Learning to address these challenges. Utilizing IWV data from GNSS stations, the study develops a predictive model based on least squares support vector machine, which autonomously determines optimal parameters to enhance performance. The model enables accurate IWV estimation at any location within a region, using inputs such as latitude, longitude, altitude, and temperature, achieving an average root mean square error of 0.95 mm. The model’s performance varies across seasons and terrains, showing adaptability to diverse conditions. The model’s reliability is validated by comparing its predictions with the conventional ERA5 IWV method, showing a 61% improvement rate. This refined IWV estimation model is applied for regional climate analysis, demonstrating its practical utility in environmental research, specifically for the Upper Rhine Graben Region.

Nature Geoscience, Published online: 30 January 2025; doi:10.1038/s41561-024-01628-6

Waves breaking on sandy beaches globally contribute a similar amount of dissolved silicon to oceans as that from rivers, according to a global analysis informed by experiments performed on a simulated quartz sand beach.

The precise position and geometry of a fault and the recognition of contemporary active strands are pivotal elements for formulating regulations for earthquake fault zones and fault setbacks. The western front...

Abstract—The editing problem in clustering (deletion and addition of edges and/or vertices in an initial graph for building a cluster structure), including various options of the problem (edge cluster editing, vertex cluster editing, etc.) is studied. A literature survey on the problems (problem types and solving approaches) is presented. The cluster edge editing problem is in focus. Several mathematical optimization models for the problem are described: (i) the basic edge editing problem with minimization of the general number of added edges and the number of deleted edges, (ii) the option of the above-mentioned problem with weights of all vertex pairs (including the bi-criteria problem case), and (iii) a multi-criteria problem with vector weights of the vertex pairs. In addition, some other editing problems are briefly described: (a) the edge deletion editing problem, (b) edge editing problem with several vertex types, and (c) vertex deletion editing problem. The problems discussed are illustrated by numerical examples. Some future research directions are pointed out.

Abstract—An estimation problem distributionally robust with respect to random noise is considered for a signal with the bounded second-order derivative on a finite number of observations. The objective functional is the probability that the L2-norm of the estimation error will exceed a pre-specified threshold. Its worst-case value on the set of all signals with the bounded second-order derivative and arbitrary distributions of the noise vector with fixed mean and covariance is to be minimized over the finite-dimensional class of spline estimators. The optimization problem is solved using the methods of convex programming by representing the objective functional in terms of the mean square bound following Markov’s inequality and the tight bound in the form of the multivariate Selberg inequality. A numerical experiment is carried out to compare the obtained solutions to the problem of restoration of the trajectory of a target with bounded acceleration.

Abstract—Problems of image smoothing and segmentation are among the most important directions of processing and analysis of video information, which have much in common in their formulation, final goals, and solution methods. The similarities and differences of the problems are shown on the base of the image model using the analysis and comparison of known smoothing and segmentation algorithms.

Abstract

A comprehensive approach to the analysis of electroencephalographic (EEG) signals obtained from human brain and artificially synthesized using machine learning methods is presented. The main focus is on data preprocessing, including signal normalization and filtering, as well as application of various feature extraction methods, in particular, Fast Fourier Transform and Mel-Frequency Cepstral Coefficients. A comparative analysis of classification accuracy using logistic regression, random forest, gradient boosting, and recurrent neural network LSTM is performed. Special attention is given to the effect of filtering parameters on classification accuracy. The results show that filtering and proper tuning of model parameters significantly improve the accuracy of EEG signal classification, ensuring separation of real and synthetic EEG pools. The results and discussion may serve as a basis for further research in the field of biomedical signal analysis and processing.

Abstract

The real-time ionospheric data streams are continuously being provided by a number of International GNSS service analysis centers such as Centre National d’Etudes Spatiales (CNES), Chinese Academy of Sciences (CAS), Universitat Politècnica de Catalunya (UPC), and Wuhan University, however, the performance evaluation of these Real-Time Global Ionosphere Map (RT-GIM) products is essential. We assess the quality and consistency of these RT-GIM products from the declining phase of solar cycle 24 (year 2017) to the maximum of solar cycle 25 (year 2024) by comparing with Final GIMs provided by Center for Orbit Determination in Europe (CODE) and Jason-3 altimetry satellite. The results suggest that during the low solar activity periods (2017–2022), all the RT-GIMs perform almost similar. However, the performance of the CNES and CAS RT-GIMs strongly deteriorates as the solar cycle proceeds towards the maximum (2022–2024) with annual RMS values remains between 9 and 7.5 TECU. The external validation vs Jason-3 during this maximum period suggested that the accuracy of the UPC RTGIMs is nearly identical to the final CODE GIMs at typically 4–10 TECU in standard deviation over oceans, while performance degradations are recorded for rest of the RTGIMs exhibiting high standard deviations. Results suggest that the high RMS errors in GIMs from CNES and CAS might be related to the geomagnetic inclination misalignments followed by the map projections as both maps form single peak along geomagnetic equator during high solar activities. In addition, under the presence of a severe G4-class geomagnetic storm, CNES RT-GIMs undergoes severe accuracy degradation across all continents recording a − 20 to − 40 TECU bias offset. Meanwhile, UPC RT-GIM remain the most consistent and stable performer (both, globally and over oceans) that provides accurate global ionospheric information which is promising for their applications in real-time precise GNSS positioning.

Abstract

The Surface Dust Analyser (SUDA) is a mass spectrometer onboard the Europa Clipper mission for investigating the surface composition of the Galilean moon Europa. Atmosphereless planetary moons such as the Galilean satellites are wrapped into a ballistic dust exosphere populated by tiny samples from the moon’s surface produced by impacts of fast micrometeoroids. SUDA will measure the composition of such surface ejecta during close flybys of Europa to obtain key chemical signatures for revealing the satellite’s composition such as organic molecules and salts, history, and geological evolution. Because of their ballistic orbits, detected ejecta can be traced back to the surface with a spatial resolution roughly equal to the instantaneous altitude of the spacecraft. SUDA is a Time-Of-Flight (TOF), reflectron-type impact mass spectrometer, optimized for a high mass resolution which only weakly depends on the impact location. The instrument will measure the mass, speed, charge, elemental, molecular, and isotopic composition of impacting grains. The instrument’s small size of \(268 ~\mathrm {mm} \times 250 ~\mathrm {mm} \times 171\) \(~\mathrm {mm}\) , radiation-hard design, and rather large sensitive area of 220 cm2 matches well the challenging demands of the Clipper mission.

Abstract

The risk of earthquakes and their effects on both nature and infrastructure in seismically active regions of India require adaptable and scalable earthquake early warning (EEW) systems. Developing a robust EEW system is crucial to mitigate earthquake risks in the region, but it is a challenging task. Various institutes have attempted to develop EEW systems using different methods. Still, there is no common consensus, and issues remain with response time and reliability of disseminated information to the public. Efforts by institutions like the Indian Institute of Technology, Roorkee, have advanced EEW technologies, focusing on dense seismic sensor networks, real-time data processing algorithms, and effective dissemination mechanisms. Recent initiatives aim to improve sensor sensitivity and accuracy through fast communication systems for quicker earthquake detection. However, challenges persist in making EEW accessible and affordable, particularly in remote areas, due to the lack of a nationwide system. The National Centre for Seismology (NCS), under the Ministry of Earth Sciences (MoES), is piloting an EEW system in the NW Himalayas, which could lead to a nationwide implementation. Developing region-specific algorithms for rapid data analysis and nurturing collaboration between academic institutions, government agencies, and international partners are crucial steps. Public awareness campaigns and educational programs are essential for community resilience and timely response to earthquake alerts. Establishing a robust EEW system in India could significantly enhance earthquake risk mitigation efforts in earthquake-prone zones of the country and should be viewed within the context of a holistic risk reduction framework. EEW systems can enhance mitigation efforts, but they must be complemented by other essential measures, such as improving building resilience and promoting public awareness.