Hasil untuk "Geomagnetism"

Gauthier Hulot, Louis Chauvet, Robin Deborde et al.

Abstract The ESA Swarm satellites carry a magnetometry payload consisting of an absolute scalar magnetometer (ASM), a fluxgate vector magnetometer (VFM), and a set of star trackers (STR). The primary role of the ASM is to provide 1 Hz absolute field intensity measurements, while the VFM and STR provide the additional data needed to reconstruct the attitude of the vector field and produce the official nominal Swarm L1b magnetic data. Each ASM instrument, however, can be run in an experimental mode to simultaneously produce its own self-calibrated 1 Hz vector data. Such 1 Hz experimental vector data have been routinely produced ever since launch on Swarm Alpha and Bravo, except during one-week periods every month when the burst mode was activated in yet another experimental mode to produce 250 Hz scalar data. These 1 Hz experimental vector data have been used to produce the only Definitive Geomagnetic Reference Field (DGRF) 2020 candidate model only relying on such data. All other candidate models relied on either nominal Swarm L1b data or data from other satellites and ground observatories. In this paper, we report on the way we built our DGRF candidate model and on the post-calibration strategy that we used to identify and remediate a calibration issue found in both the ASM and VFM vector data. We show that this post-calibration improves the quality of the data and contributes to also improving our DGRF candidate model. Our final candidate model, only based on post-calibrated ASM data, turns out to be one of the DGRF 2020 candidate models closest to the final official DGRF model, a posteriori providing evidence of both the quality of the Swarm ASM experimental vector mode data and the value of our post-calibration strategy. This post-calibration strategy could be used to improve magnetic data from other past, present, or future missions. Graphical abstract

Wenda Li, Tongya Zheng, Kaixuan Chen et al.

Geomagnetic map interpolation aims to infer unobserved geomagnetic data at spatial points, yielding critical applications in navigation and resource exploration. However, existing methods for scattered data interpolation are not specifically designed for geomagnetic maps, which inevitably leads to suboptimal performance due to detection noise and the laws of physics. Therefore, we propose a Physics-informed Diffusion Generation framework~(PDG) to interpolate incomplete geomagnetic maps. First, we design a physics-informed mask strategy to guide the diffusion generation process based on a local receptive field, effectively eliminating noise interference. Second, we impose a physics-informed constraint on the diffusion generation results following the kriging principle of geomagnetic maps, ensuring strict adherence to the laws of physics. Extensive experiments and in-depth analyses on four real-world datasets demonstrate the superiority and effectiveness of each component of PDG.

Ao Liu, Wenguang Wang, Changshun Yuan

Geomagnetic positioning (GP) stands as a formidable research frontier within the domain of indoor positioning. Various GP methods have recently brought remarkable improvements. Nevertheless, the geomagnetic mismatching leading to suboptimal positioning is still serious. To address this problem, we rethink GP in terms of geomagnetic steering features and gross error suppression. We propose a novel method named GIPos, which consists of two stages. In the fusion stage A, we propose a pedestrian dead reckoning (PDR) heading-based geomagnetic distinguishability improvement method. We first construct geomagnetic candidate sets and extract the geomagnetic steering features. Then, a probability model is designed to describe the relationship between geomagnetic steering features and PDR heading, and sequence dynamic search is used to obtain the optimal position corresponding to the geomagnetic test subsequence in this stage. In the fusion stage B, we propose a robust fusion method with forward constraint to fuse PDR and the result of stage A, further reducing the geomagnetic gross error that still exists at seldom points. The performance of the method was evaluated using the MagPIE open dataset containing different indoor scenes. The experimental results show that our GIPos method can achieve superior positioning accuracy compared to other methods. Besides, pedestrian trajectories show the stability and continuity of positioning.

نفیسه پگاه فر

پژوهش حاضر، عملکرد داده‌های بازتحلیل در بازتولید پارامترهای دما و رطوبت طی دوره 1990 تا 2020 را در 9 ایستگاه جو بالا با دوبار گمانه‌زنی در روز ارزیابی می‌کند. پارامترهای مورد بررسی شامل دما، دمای نقطه شبنم، رطوبت ویژه، آهنگ کاهش دما ( در لایه‌های یک کیلومتری، سه کیلومتری و سه تا شش کیلومتری از سطح) و نسبت اختلاط در ارتفاع‌های 100، 300 و 500 متری از سطح زمین بود. شاخص‌های آماری اریبی، همبستگی، ریشه میانگین مربعات خطا و شاخص توافق استفاده شد. نتایج نشان داد که داده‌های بازتحلیل دمای هوا در تراز 850 هکتوپاسکال را در شب/روز فراتخمین/فروتخمین کرده‌اند؛ اما در ترازهای بالاتر دقت و همبستگی بیشتری داشتند. دمای نقطه شبنم بازتحلیل در ترازهای 700 و 500 هکتوپاسکال در اغلب موارد بیش‌برآورد شده بودند و میزان خطا در تراز 500 بیشتر از 700 هکتوپاسکال بود. دقت برآورد آهنگ کاهش دما در یک کیلومتر ابتدایی جو در اغلب ایستگاه‌ها پایین بود و پدیده‌هایی، مانند، سرمایش سطحی و وارونگی دما به دقت بازیابی نشدند. پارامترهای رطوبتی نیز در سطوح پایین جو به‌ویژه در شب بیش‌برآورد شدند. نسبت اختلاط در ارتفاع‌های 100، 300 و 500 متری در تمامی ایستگاه‌ها به‌جز اهواز، به‌ویژه در شب بیش‌برآورد شدند. ایستگاه اهواز با کمترین ارتفاع از سطح دریا، هم در شب و هم در روز فروتخمین نسبت اختلاط را تجربه کرد. نتایج نشان می‌دهد که در این منطقه عملکرد داده‌های بازتحلیل در سطوح پایین جو نسبت به سطوح بالاتر از دقت کمتری برخوردار است و نیاز به اصلاح یا تلفیق با داده‌های مشاهداتی دارد.

Ashish P. Jadhav, Yosuke Yamazaki, S. Gurubaran et al.

Abstract This study establishes an observational connection between an ultra‐fast Kelvin wave (UFKW) and the occurrence of counter electrojet (CEJ) in the equatorial E region and planetary wave‐like oscillations in low‐latitude total electron content (TEC), based on a case study of CEJ events that occurred in December 2017. During this period, noontime CEJ was observed by ground‐based magnetometers with a periodicity of ∼2 days. The analysis of hourly wind data from the JAGUAR‐DAS Whole neutral Atmosphere Reanalysis reveals the presence of an eastward‐propagating UFKW with a zonal wavenumber of 1 (E1) and a period of ∼2 days along with an enhancement of eastward wind in the equatorial dynamo region which coincided with occurrence of CEJ. Observations from the Swarm satellite mission confirm the presence of equatorial electrojet (EEJ) oscillations associated with the UFKW. This is the first time that an UFKW has been identified as a source of day‐to‐day variability in CEJ. As CEJ is linked to a reduced daytime upward plasma drift over the magnetic equator, TEC at low latitudes also varies at a period of ∼2 days. The analysis of global TEC maps reveals that the 2‐day TEC variations consist not only of the eastward propagating wavenumber 1 component but also of the westward propagating wavenumber 2 (W2) component. The latter arises from the interaction of the E1 UFKW with the diurnally varying ionosphere. The 2‐day TEC variations exhibit significant longitudinal dependence due to the interplay of constructive and destructive interferences between the E1 and W2 2‐day oscillations.

S. Tulasi Ram, Deeksha Rai, B. Nilam et al.

Abstract The intensity of storm‐time disturbance in the ground magnetic field varies significantly at different longitudes due to the magnetic local time (MLT) dependent contributions from different magnetospheric and ionospheric currents. Local geomagnetic field disturbances at low‐to‐mid latitudes often deviate considerably from the global depression represented by symmetric geomagnetic storm indices (such as Dst/SymH/SMR). In this study, we quantitatively investigated the geomagnetic horizontal field depressions (ΔH) at different local time sectors, compared to the longitudinally averaged SuperMAG Ring current (SMR), at eleven low‐latitude stations during a large number (665) of geomagnetic storms that occurred from 1996 to 2024. The relative disturbances (i.e., ΔH‐SMR) exhibit significant asymmetry with respect to MLT, which further varies with storm evolution, intensity, and phase. The MLT asymmetry of ΔH grows rapidly in the early main phase and then grows gradually with storm intensity. Further, the MLT sector of weakest/strongest ΔH depression shifts from post‐dawn/post‐dusk to pre‐dawn/pre‐dusk periods as storm intensity increases. Finally, an empirical model is derived that can quantitatively represent the MLT variations in the low‐latitude ΔH disturbances during geomagnetic storms. This model is very useful in estimating the low‐latitude geomagnetic field disturbances at different longitudes/MLT sectors from the global SMR index and can have significant applications in space weather studies.

Yoshita Baruah

Energetic events on the Sun, particularly coronal mass ejections and high speed streams, regulate the near Earth space environment and give rise to space weather. A major terrestrial manifestation of such events are geomagnetic storms. A geomagnetic storm results in dissipation of energy from the solar wind into the atmosphere, leading to Joule heating and thermospheric expansion. This has serious consequences on Low Earth Orbit satellite lifetimes. Our work demonstrates the impact of different kinds of geomagnetic storms on satellite orbits. We also briefly discuss about some physical attributes of satellites that can make them prone to higher orbital decay. Our work highlights the importance of monitoring and predicting space weather, and assessing their impacts on space-based human technologies.

Denny M. Oliveira, Robert C. Allen, Livia R. Alves et al.

Abstract Interplanetary (IP) shocks are perturbations observed in the solar wind. IP shocks correlate well with solar activity, being more numerous during times of high sunspot numbers. Earth‐bound IP shocks cause many space weather effects that are promptly observed in geospace and on the ground. Such effects can pose considerable threats to human assets in space and on the ground, including satellites in the upper atmosphere and power infrastructure. Thus, it is of great interest to the space weather community to (a) keep an accurate catalog of shocks observed near Earth, and (b) be able to forecast shock occurrence as a function of the solar cycle (SC). In this work, we use a supervised machine learning regression model to predict the number of shocks expected in SC25 using three previously published sunspot predictions for the same cycle. We predict shock counts to be around 275 ± 10, which is ∼47% higher than the shock occurrence in SC24 (187 ± 8), but still smaller than the shock occurrence in SC23 (343 ± 12). With the perspective of having more IP shocks on the horizon for SC25, we briefly discuss many opportunities in space weather research for the remainder years of SC25. The next decade or so will bring unprecedented opportunities for research and forecasting effects in the solar wind, magnetosphere, ionosphere, and on the ground. As a result, we predict SC25 will offer excellent opportunities for shock occurrences and data availability for conducting space weather research and forecasting.

S. Reay

The World Data Centre (WDC) for Geomagnetism, Edinburgh serves the geomagnetism community providing access to geomagnetic data records for over 550 magnetic observatories worldwide, both past and present. It holds observatory minute, hourly, and annual means, as well as yearbooks, magnetic survey data and activity indices, with data reaching back to the early 1800s. This paper describes recent work to develop a new API (Application Programming Interface) to deliver the observatory data and metadata programmatically. In addition, a new data portal for users to interactively search for and download geomagnetic datasets has been developed (https://wdc.bgs.ac.uk/). More datasets are now available including monthly means and K-indices. Improvements to the user interface allow users to view data availability, observatory metadata, and download datasets in a range of data formats. We also describe a new tool under development to allow geomagnetic observatory operators to review, update, and enhance the metadata records currently held for observatories.

Rungployphan Kieokaew, Veronika Haberle, Aurélie Marchaudon et al.

Geomagnetic indices derived from ground magnetic measurements characterize the intensity of solar-terrestrial interaction. The \textit{Kp} index derived from multiple magnetic observatories at mid-latitude has commonly been used for space weather operations. Yet, its temporal cadence is low and its intensity scale is crude. To derive a new generation of geomagnetic indices, it is desirable to establish a geomagnetic `baseline' that defines the quiet-level of activity without solar-driven perturbations. We present a new approach for deriving a baseline that represents the time-dependent quiet variations focusing on data from Chambon-la-Forêt, France. Using a filtering technique, the measurements are first decomposed into the above-diurnal variation and the sum of 24h, 12h, 8h, and 6h filters, called the daily variation. Using correlation tools and SHapley Additive exPlanations, we identify parameters that dominantly correlate with the daily variation. Here, we predict the daily `quiet' variation using a long short-term memory neural network trained using at least 11 years of data at 1h cadence. This predicted daily quiet variation is combined with linear extrapolation of the secular trend associated with the intrinsic geomagnetic variability, which dominates the above-diurnal variation, to yield a new geomagnetic baseline. Unlike the existing baselines, our baseline is insensitive to geomagnetic storms. It is thus suitable for defining geomagnetic indices that accurately reflect the intensity of solar-driven perturbations. Our methodology is quick to implement and scalable, making it suitable for real-time operation. Strategies for operational forecasting of our geomagnetic baseline 1 day and 27 days in advance are presented.

Songnan Yang, Shiliang Zhang, Qianyun Zhang et al.

Geomagnetic navigation leverages the ubiquitous Earth's magnetic signals to navigate missions, without dependence on GPS services or pre-stored geographic maps. It has drawn increasing attention and is promising particularly for long-range navigation into unexplored areas. Current geomagnetic navigation studies are still in the early stages with simulations and computational validations, without concrete efforts to develop cost-friendly test platforms that can empower deployment and experimental analysis of the developed approaches. This paper presents a hardware-in-the-loop simulation testbed to support geomagnetic navigation experimentation. Our testbed is dedicated to synthesizing geomagnetic field environment for the navigation. We develop the software in the testbed to simulate the dynamics of the navigation environment, and we build the hardware to generate the physical magnetic field, which follows and aligns with the simulated environment. The testbed aims to provide controllable magnetic field that can be used to experiment with geomagnetic navigation in labs, thus avoiding real and expensive navigation experiments, e.g., in the ocean, for validating navigation prototypes. We build the testbed with off-the-shelf hardware in an unshielded environment to reduce cost. We also develop the field generation control and hardware parameter optimization for quality magnetic field generation. We conduct a detailed performance analysis to show the quality of the field generation by the testbed, and we report the experimental results on performance indicators, including accuracy, uniformity, stability, and convergence of the generated field towards the target geomagnetic environment.

F. J. Acero, J. M. Vaquero, M. C. Gallego et al.

The study of the extreme weather space events is important for a technological dependent society. Extreme Value Theory could be decisive to characterize those extreme events in order to have the knowledge to make decisions in technological, economic and social matters, in all fields with possible impacts. In this work, the hourly values of the Dst geomagnetic index has been studied for the period 1957-2014 using the peaks-over-threshold technique. The shape parameter obtained from the fit of the generalized Pareto distribution to the extreme values of the |Dst| index leads to a negative value implying an upper bound for this time series. This result is relevant, because the estimation of this limit for the extreme values lead to 850 nT as the highest expected value for this geomagnetic index. Thus, from the previous characterization of the Carrington geomagnetic storm and our results, it could be considered the worst case scenario.

Chaoyong Yang, Zhenhao Cheng, Xiaoxue Jia et al.

For positioning tasks of mobile robots in indoor environments, the emerging positioning technique based on visual inertial odometry (VIO) is heavily influenced by light and suffers from cumulative errors, which cannot meet the requirements of long-term navigation and positioning. In contrast, positioning techniques that rely on indoor signal sources such as 5G and geomagnetism can provide drift-free global positioning results, but their overall positioning accuracy is low. In order to obtain higher precision and more reliable positioning, this paper proposes a fused 5G/geomagnetism/VIO indoor localization method. Firstly, the error back propagation neural network (BPNN) model is used to fuse 5G and geomagnetic signals to obtain more reliable global positioning results; secondly, the conversion relationship from VIO local positioning results to the global coordinate system is established through the least squares principle; and finally, a fused 5G/geomagnetism/VIO localization system based on the error state extended Kalman filter (ES-EKF) is constructed. The experimental results show that the 5G/geomagnetism fusion localization method overcomes the problem of low accuracy of single sensor localization and can provide more accurate global localization results. Additionally, after fusing the local and global positioning results, the average positioning error of the mobile robot in the two scenarios is 0.61 m and 0.72 m. Compared with the VINS-mono algorithm, our approach improves the average positioning accuracy in indoor environments by 69.0% and 67.2%, respectively.

Márcio Antônio Sens

: The most scientifically accepted theory to justify geomagnetism was presented on November 15, 1919, by Joseph Larmor – that of the geodynamo, which would also justify solar magnetism. But this theory, under no circumstances, justifies all the geomagnetic behaviors already verified experimentally: the generation of magnetism – ability to generate ordered magnetic fields; magnetic decay between axes of rotation and magnetic alignment; erratic decline – the lag angle between the axes is erratic; not antipodes – the poles are not diametrically opposed; reversals - hundreds of magnetic pole reversals have occurred over millions of years; excursion - magnetic axis was temporarily aligned with the equator. Anyway, the origins of geomagnetism, until today, are not sufficiently well explained. Of the various theories already presented over a century ago, none of them meets all the geomagnetic phenomena and behaviors observed over time. The present work will present a new hypothesis to completely justify the generation, maintenance and behavior of geomagnetism, and that will certainly serve to justify, in the same way, the magnetic field existing in other celestial bodies.

YiJun Li, Yan Feng, SuQin Zhang et al.

The secular variation in the global geomagnetic field was analyzed in terms of the annual differences in monthly means by using the hourly mean data from 18 foreign (outside China) observatories of the World Data Center (WDC) for Geomagnetism from January 2010 to January 2020 as well as 9 observatories in the Geomagnetic Network of China from January 2015 to April 2021. In addition, according to the correlation of noisy components from the observatories, a covariance matrix was constructed based on residuals between observations and the CHAOS-7.4 model to remove external contamination. Through a comparison before and after denoising, we found that the overall average standard deviations were reduced by 29.97% in China and by 41.4% outside China. Results showed the correlation coefficient between external noise (mainly the magnetosphere ring current) and the Dst index was 0.82, and the correlation coefficient between external noise and the Ring Current (RC) index reached 0.94. A geomagnetic jerk was globally discovered around 2018.0 on the geomagnetic eastward component Y. The jerk timing in China was around 2020.0, and the earliest one was in 2018.75, whereas the timing outside China was around 2018.0, and the earliest one was in 2017.67. This 2-year lag may have been caused by the higher electrical conductivity of the deep mantle. After more data were added, this jerk event was found to occur in an orderly manner in the northern hemisphere as the longitude increased and the intensity gradually increased as well. The variations in location of the jerk center were analyzed according to the CHAOS-7.4 model. Results revealed six extreme points distributed nearby the equator. The strongest was near the equator, at 170°E, and the strength gradually decreased as it extended to the northern and southern hemispheres. Another extreme point with the opposite sign was located at the equator, at 20°W, in the south-central part of the Atlantic, and the strength gradually decreased as it extended into Europe. The covariance matrix method can be used to analyze data from the Macau Science Satellite-1 mission in the future, and this method is expected to play a positive role in modeling and separating the large-scale external field.

Matthew Shelby, Scott Scharlach, Petar Matejic et al.

Although a variety of phenomena may create a geomagnetic storm on Earth, the most severe geomagnetic storms arise from solar activity, and in particular, coronal mass ejections (CMEs) and solar flares. CMEs and flares originate primarily from sunspots. The "aa index" is a metric which ranks all of the strongest geomagnetic storms between 1868 and 2010 based on a variety of characteristics taken from several sources. This paper examines correlations between the aa index of the most severe geomagnetic storms and the intrinsic characteristics of the sunspots from which they originated. We find a correlation between the total rank of the aa index of the storms and the "total intensity" of the sunspot, where total intensity is defined as the sunspot's mean intensity multiplied by its area. The correlation has an R-Squared = 0.690 and R-Squared = 0.855 when a potentially corrupted data point is removed.

Fuyang Tian, Jun Wang, B. Xiong et al.

The behaviors of dairy cows, such as feeding, ruminating, running, resting (standing, lying), head-shaking, drinking, and walking, can indicate their health status. In this study, a multi-sensor was used to collect data of cow’s multi-behaviors for research on behavior recognition. Firstly, a collar style data acquisition system equipped with geomagnetic and acceleration sensors to collect the behavioral data of dairy cows during their daily activities was designed. Secondly, the dairy cow behavioral recognition fusion model based on K-Nearest-Neighbors (KNN) and Random Forest (RF) models were used for behavior classification. To verify the accuracy of the fusion model, the algorithms of KNN, RF, Gradient Boosting Decision Tree (GBDT), Support Vector Machine (SVM), and Learning Vector Quantization (LVQ) were introduced for comparative recognition experiments with different algorithms. The KNN-RF fusion model had the highest average recognition accuracy of 98.51%, followed by the KNN model with an average recognition accuracy of 95.37%, and the LVQ model had the lowest average recognition accuracy of 80.81%. For the recognition and verification of each behavior, the KNN-RF fusion model had the most obvious improvement in the recognition of dairy cow feeding behavior, with a recognition accuracy of 99.34%, followed by the KNN model with a recognition accuracy of 95.07%. All six models had the lowest recognition accuracy for cow head-shaking behavior: a recognition accuracy of 89.11% with the KNN-RF model followed by the RF model with a recognition accuracy of 85.14%. The system can quickly and continuously collect cow behavior information, accurately recognize individual behaviors, and provide a scientific basis for the optimal design and efficient management of digital facilities and equipment for dairy cows.

Seog-Yoon Jeong, Seung-Hwan Lee, Eunsuk Lee

A widely uniform and highly ambient robust DC magnetic field generator for precise motion sensors using inertial measurement units (IMUs) is newly proposed in this paper. Chronic problems such as low uniformity of magnetic field and geomagnetic disturbance of conventional Helmholtz, Merritt, Rubens, Lee-Whiting, and Tetra coils can be significantly mitigated by the proposed uniform DC magnetic field generator (UFG). Different from the previous air coils, the proposed UFG adopts a core-cage so that a strong and uniform DC magnetic field distribution can be generated inside the cage and that the UFG may be quite magnetically robust to ambient changes such as geomagnetic field and ferromagnetic objects. A dedicated power supply was developed for providing not only a DC current to generate the required magnetic field but also an exponentially decaying AC current to demagnetize the residual magnetic field in the core-cage. Design procedures for the UFG are fully established, considering the manufacturing cost, performance, and mechanical robustness for commercialization. Detailed designs of the UFG for magnetic field generation, enhancing uniformity, geomagnetic cancellation, and demagnetizing of the UFG are provided. Experimental results verified by a 30 cm $\times $ 30 cm $\times $ 30 cm prototype UFG showed that the geomagnetic field inside the UFG was significantly attenuated by 22 dB while the DC magnetic field uniformity ( $\theta _{t}) was achieved over 85% of the total volume of 27,000 cm3.

Peter Stauning

Abstract The standard polar cap (PC) indices, PCN (North) based on magnetic data from Qaanaaq in Greenland and PCS (South) based on data from Vostok in Antarctica, have been submitted from the Arctic and Antarctic Research Institute in St. Petersburg, Russia, the Danish Meteorological Institute, and the Danish Space Research Institute in different versions. In order to consolidate PCS indices based on Vostok data or replace poor or missing index data, derivation procedures have been developed to generate alternative PCS index values based on data from Dome Concordia (Dome‐C) magnetic observations from epoch 2009–2020 of solar cycle 24. The reference levels and calibration parameters needed for calculations of Dome‐C‐based PCS values in post‐event and real‐time versions are defined and explained in the present work. Assessments of the new PCS index have shown its unprecedented high relevance. Part of the methods used here, such as the quiet reference level construction and the correlation and regression procedures used for calculations of scaling parameters, deviate from corresponding features considered inadequate of the International Association for Geomagnetism and Aeronomy‐endorsed PC index derivation methods.

K. Qiu, Ruizhi Chen, He Huang

In order to solve the problem that the transition point facing indoor and outdoor seamless positioning is low in accuracy and the coordinates are difficult to be uniformly converted, in this paper, a combination of Baidu map app positioning technology using GPS, base station and Wi-Fi signal positioning and indoor geomagnetic fingerprint node is developed to develop a system for seamless positioning and navigation indoors and outdoors. We propose a novel and rapid method for establishing coordinate uniformity to solve the key problem of indoor and outdoor seamless positioning - coordinate smoothing conversion. Through the combination of 3D laser scanning technology and GPS positioning technology, the data from multiple viewing angles are organized into the same coordinate system according to the transformation matrix. The iterative closest point algorithm registration technique is used to obtain a three-dimensional model of the high-precision local coordinate system of indoor and outdoor critical points.