Magnetic Field Data Research Articles

Evolution of the magnetic field rotation distributions in the inner heliosphere

The nature and evolution of the solar wind magnetic field rotations is studied in data from the Parker Solar Probe We investigated the magnetic field deflections in the inner heliosphere below 0.5 au in a distance- and scale-dependent manner to shed some light on the mechanism behind their evolution. We used the magnetic field data from the FIELDS instrument suite to study the evolution of the magnetic field vector increment and rotation distributions that contain switchbacks. We find that the rotation distributions evolve in a scale-dependent fashion. They have the same shape at small scales regardless of the radial distance, in contrast to larger scales, where the shape evolves with distance. The increments are shown to evolve towards a log-normal shape with increasing radial distance, even though the log-normal fit works quite well at all distances, especially at small scales. The rotation distributions are shown to evolve towards a previously developed rotation model moving away from the Sun. Our results suggest a scenario in which the evolution of the rotation distributions is primarily the result of the expansion-driven growth of the fluctuations, which are reshaped into a log-normal distribution by the solar wind turbulence.

Observations of the 2022 September 5 Solar Energetic Particle Event at 15 Solar Radii

On 2022 September 5, Parker Solar Probe (Parker) observed a large solar energetic particle (SEP) event at the unprecedented distance of only 15 R S from the Sun. The observations from the Integrated Science Investigation of the Sun (IS⊙IS) obtained over the course of this event are remarkably rich, and an overview is presented here. IS⊙IS is capable of measuring ions from 20 keV to over 100 MeV nuc−1 and electrons from 30 keV to 6 MeV; here, we primarily focus on the proton and helium measurements above 80 keV. Among the surprising results are evidence of inverse velocity dispersion at energies above 1 MeV during the onset of the event, a sharp decrease in the energetic particle intensities at all energies at the interplanetary shock crossing, and repeated short durations of highly anisotropic sunward flow. Many changes in the SEP intensities, anisotropy, and spectral steepness are coincident with solar wind structure boundaries identified using the Parker solar wind magnetic field and plasma data. However, there are significant changes that are not correlated with any clearly visible solar wind variation. The observations presented here serve as an introduction to a complex event with numerous opportunities for future, more in-depth studies.

Dynamics of charged particles in a solenoid and the accurate determination of the magnetic axis of a solenoid using measured field data.

A fundamental understanding of the theory and measurement procedures for characterizing a solenoid is crucial for making a project cost-effective and achieving the desired performance for its use in a LINAC. This paper attempts to comprehend the beam dynamics of charged particles by considering the conservation of canonical angular momentum, which can take on positive, negative, and zero values. The analytical expression to generate a parallel beam using a solenoid is derived. The effect of the final beam size on the values of a solenoid's spherical aberration coefficient and the position of the minimum beam size with respect to the focal length is studied using electron trajectories. A practical procedure to tune the above two parameters of a solenoid is demonstrated by simply modifying the demountable disks connected at each end. A mathematical model is proposed to accurately determine the axis of a solenoid and the magnetic centre using the measured magnetic field data, which is validated experimentally. Several solenoids, used in the 9.5MeV 10kW electron LINAC suitable for sterilizing medical products and food irradiation, have been characterised using this procedure.

Tidal Effects on the Schumann Resonance Amplitudes Recorded by the Global Coherence Monitoring System

The main scientific result of this paper is the demonstration of the fact that tidal effects induced by the Moon affect the Schumann resonance amplitudes measured at magnetometers located at different geographical locations of the Global Coherence Monitoring System. Each magnetometer is paired with the closest monitoring station of the global tidal wave measurement network. This paper introduces the Schumann Resonance Complexity Index (SRCI), computed by using the calibrated H-rank algorithm on the local magnetic field data recorded by each magnetometer of the Global Coherence Monitoring System. Tidal wave data recorded at each monitoring station are also used to compute the Tidal Wave Complexity Index (TWCI). Eliminating diel cycles from the SRCI data yields significant statistical correlations between the SRCI and TWCI data, proving the hypothesis of tidal effects on the global network of magnetometers.

Submarine cable detection using an end-to-end neural network-based magnetic data inversion

Abstract To process magnetic anomaly data, appropriate parameters for field separation, denoising, and Euler deconvolution have to be manually selected. The traditional workflow is inefficient and cannot fulfill the rapid detection of submarine cables due to the complex processing and manual parameter tuning. This study presents an end-to-end deep learning approach for the identification and positioning of submarine cables based on magnetic anomalies. The proposed approach effectively establishes a direct mapping correlation between the magnetic field data and the position of the submarine cable. Synthetic tests suggest that our method has a better performance in terms of positioning accuracy than the conventional Euler method. Our results for the field data are comparable to those obtained using conventional techniques. Furthermore, the proposed method achieves an optimal solution by employing clustering technique and selecting the solution with the maximum confidence, which avoids spurious solutions associated with traditional methods. The proposed method can directly determine the position of the submarine cables using the raw magnetic field data. Contrary to the traditional processing workflow, field separation and denoising are not necessary in this novel approach, resulting in higher processing efficiency and a simpler processing process.

On the Global Features of the 10–60‐Min ULF Waves in Jovian Magnetosphere: Juno Observations

AbstractIn the Jovian magnetosphere, quasi‐periodic phenomena, with quasi‐periods on the order of 10–60 min, are frequently identified using different data sets. These pulsations are a branch of ultra‐low frequency (ULF) waves, which are believed to play a crucial role in driving the energy circulation within Jupiter's magnetosphere. In this study, we utilize magnetic field data collected by Juno between 2016 and 2022 to perform a comprehensive global statistical analysis of the spatial distribution and periodic characteristics of ULF waves in the Jovian magnetosphere. Our findings reveal distinct periodic features observed at different latitudes and distances, providing valuable insights into the generation mechanisms of ULF waves. Furthermore, we establish a close relationship between the presence of these ULF wave fluctuations and the magnetospheric state, such as under conditions of solar wind compression. By combining contemporaneous ultraviolet aurora observations from the Hubble Space Telescope (HST) and magnetic field data obtained by Juno, we have discovered that the compressed magnetospheres exhibit more pronounced ULF waves and enhanced auroral activity. These results provide a global picture of the distribution, implying potential generation of ULF waves in the Jovian magnetosphere, and shedding light on the processes behind the 10–60‐min energy releases.

Statistical Distribution of Whistler Mode Waves in the Martian Induced Magnetosphere Based on MAVEN Observations

AbstractWhistler mode waves are a common type of electromagnetic waves in the Martian induced magnetosphere. Using high‐resolution magnetic field data from the Magnetometer (MAG) instrument onboard Mars Atmosphere and Volatile Evolution (MAVEN) from October 2014 to November 2022, we perform a detailed analysis of the statistical distribution of the occurrence rate, averaged amplitude, peak frequency, wave normal angle and ellipticity of left‐hand and right‐hand polarized whistler mode waves in the Martian induced magnetosphere. Our results show that whistler mode waves are mainly observed in the subsolar and magnetic pileup region, with the occurrence rate of right‐hand mode waves higher than that of left‐hand mode waves. The averaged wave amplitude ranges from 0.02 to 0.13 nT and peak wave frequency ranges from 2 to 9 Hz. We also find that the wave normal angles for both left‐hand and right‐hand polarized whistler waves are relatively larger in the subsolar region and magnetic pileup region where the corresponding wave ellipticity is closer to the linear polarization. Our results are valuable to in‐depth understanding of the generation mechanism of whistler mode waves as well as their contributions to the electron dynamics in the Martian induced magnetosphere.

Joint Gravity and Magnetic Inversion Using CNNs’ Deep Learning

Enhancing the reliability of inversion results has always been a prominent issue in the field of geophysics. In recent years, data-driven inversion methods leveraging deep neural networks (DNNs) have gained prominence for their ability to address non-uniqueness issues and reduce computational costs compared to traditional physically model-driven methods. In this study, we propose a GMNet machine learning method, i.e., a CNN-based inversion method for gravity and magnetic field data. This method relies more on data-driven training, and in the prediction phase after the model is trained, it does not heavily depend on a priori assumptions, unlike traditional methods. By forward modeling gravity and magnetic fields, we obtain a substantial dataset to train the CNN model, enabling the direct mapping from field data to subsurface property distribution. Applying this method to synthetic data and one-field data yields promising inversion results.

Spectrogram Inversion for Reconstruction of Electric Currents at Industrial Frequencies: A Deep Learning Approach.

In this paper, we present a deep learning approach for identifying current intensity and frequency. The reconstruction is based on measurements of the magnetic field generated by the current flowing in a conductor. Magnetic field data are collected using a magnetic probe capable of generating a spectrogram, representing the spectrum of frequencies of the magnetic field over time. These spectrograms are saved as images characterized by color density proportional to the induction field value at a given frequency. The proposed deep learning approach utilizes a convolutional neural network (CNN) with the spectrogram image as input and the current or frequency value as output. One advantage of this approach is that current estimation is achieved contactless, using a simple magnetic field probe positioned close to the conductor.

Comparison of magnetic data products from Solar Orbiter SO/PHI-FDT and SDO/HMI

The Polarimetric and Helioseismic Imager (SO/PHI), on board the Solar Orbiter mission, is the first photospheric magnetograph and tachograph to observe the Sun from outside the Sun-Earth line. The Full Disc Telescope (FDT) of SO/PHI, images the whole solar disk with a spatial resolution that varies with the distance between the Sun and the spacecraft. To check for consistency between the magnetic field strength ($B$), the field inclination (gamma ), the line-of-sight (LoS) magnetic component ($B_ LoS $) and the field azimuth (phi ), inferred by SO/PHI-FDT and the Helioseismic and Magnetic Imager (HMI), on board Solar Dynamics Observatory (SDO), and obtain linear correlation coefficients among them. We use data from both instruments obtained on 8 March 2022, when the angle between SDO and Solar Orbiter was $3.4^ circ $ and the solar disk showed four developed active regions. Before comparing the magnetic field products of both instruments we perform a precise alignment of the data, including a matching of the plate scale. Further, in order to improve the homogeneity of the compared data products, the SDO/HMI data were convolved with the SO/PHI-FDT point spread function (PSF). The linear correlation coefficients are obtained through a linear regression of SDO/HMI to SO/PHI-FDT. The two instruments yield comparable magnetic field data products. The slope coefficients for a linear fit are 1.37 for $B$, 1.11 for gamma , 1.35 for $B_ LoS $ and 1 for the azimuth. The corresponding fit offsets are $-94$ G, $-9.8^ circ $, $5.2$ G and $0.1^ circ $, respectively. The agreement between both instruments is significantly better when we take into account the different spatial resolution of both instruments. The fitting results vary slightly depending on the analyzed active region except for one of the four active regions, which shows larger differences and has been excluded from the comparison. The comparison of the LoS magnetic field products from SDO/HMI at 45 s and 720 s with SO/PHI-FDT shows a slope value of 1.17, with the offset less than $6$ G, in both cases.

Quasi-2D inversion of surface large fixed-loop transient electromagnetic sounding data

Abstract In many cases, 1D inversion is still an important step in transient electromagnetic data processing. Potential issues may arise in the calculation of apparent resistivity using induced electromotive force (EMF) due to overshoot and the presence of multi-valued functions. Obtaining reliable and consistent inversion results using a uniform half-space as the initial model is challenging, especially when aiming for efficient inversion. Focusing on these problems, we use the land-based transient electromagnetic (TEM) sounding data, which was acquired by using a large fixed-loop transmitter, and adopt a quasi-2D inversion scheme to generate improved images of the subsurface resistivity structure. First, we have considered directly using magnetic field data or converting induced EMF into magnetic field, and then calculating the apparent resistivity over the whole zone. Next, a resistivity profile that varies with depth is obtained through fast smoke ring imaging. This profile serves as the initial model for the subsequent optimal inversion. The inversion scheme uses a nonlinear least-squares method, incorporating lateral and vertical constraints, to produce a quasi-2D subsurface image. The potentiality of the proposed methodology has been exemplified through the interpretation of synthetic data derived from a 3D intricate resistivity model, as well as field data obtained from a TEM survey conducted in a coalmine field. In both cases, the inversion process yields quasi-2D subsurface images that exhibit a reasonable level of accuracy. These images appear to be less moulded by 3D effects and demonstrate a satisfactory level of agreement with the known target area.

How Small-scale Jetlike Solar Events from Miniature Flux Rope Eruptions Might Produce the Solar Wind

We consider small-scale jetlike events that might make the solar wind, as has been suggested in recent studies. We show that the events referred to as “coronal jets” and as “jetlets” both fall on a power-law distribution that also includes large-scale eruptions and spicule-sized features; all of the jetlike events could contribute to the solar wind. Based on imaging and magnetic field data, it is plausible that many or most of these events might form by the same mechanism: Magnetic flux cancelation produces small-scale flux ropes, often containing a cool-material minifilament. This minifilament/flux rope erupts and reconnects with adjacent open coronal field, along which “plasma jets” flow and contribute to the solar wind. The erupting flux ropes can contain twist that is transferred to the open field, and these become Alfvénic pulses that form magnetic switchbacks, providing an intrinsic connection between switchbacks and the production of the solar wind.

Constraints on the Spatial Distribution of Lunar Crustal Magnetic Sources From Orbital Magnetic Field Data

AbstractSpacecraft measurements show that the crust of the Moon is heterogeneously magnetized. The sources of these magnetic anomalies are yet not fully understood, with most not being related to known geological structures or processes. Here, we use an inversion methodology that relies on the assumption of unidirectional magnetization, commonly referred to as Parker's method, to elucidate the origin of the magnetic sources by constraining the location and geometry of the underlying magnetization. This method has been used previously to infer the direction of the underlying magnetization but it has not been tested as to whether it can infer the geometry of the source. The performance of the method is here assessed by conducting a variety of tests, using synthetic magnetized bodies of different geometries mimicking the main geological structures potentially magnetized within the lunar crust. Results from our tests show that this method successfully localizes and delineates the two‐dimensional surface projection of subsurface three‐dimensional magnetized bodies, provided their magnetization is close to unidirectional and the magnetic field data are of sufficient spatial resolution and reasonable signal‐to‐noise ratio. We applied this inversion method to two different lunar magnetic anomalies, the Mendel‐Rydberg impact basin and the Reiner Gamma swirl. For Mendel‐Rydberg, our analysis shows that the strongest magnetic sources are located within the basin's inner ring, whereas for Reiner Gamma, the strongest magnetic sources form a narrow dike‐like body that emanates from the center of the Marius Hills volcanic complex.

Mapping Geoelectric Field Hazards in Ireland

AbstractGeoelectric fields are generated at the Earth's surface and can lead to the induction of hazardous geomagnetically induced currents (GIC) in infrastructure like power grids, railways and pipelines during geomagnetic storms. Magnitude and orientation of the geoelectric fields, in relation to the infrastructure, are key features needed to determine the intensity of GIC. Here, we developed the first geoelectric hazard map for the island of Ireland, with the aim of providing detailed information that can help stakeholders mitigate the impact of GICs. The hazard map was developed by modeling and mapping the geoelectric field across Ireland for 28 years (1991–2018) using magnetic field data with magnetotelluric transfer functions. The approach for developing the hazard map calculates the probability of exceeding a hazardous geoelectric field threshold (500 mV/km) during large geomagnetic storms, taking directionality and amplitude into account. We found hazardous geoelectric fields to be mostly localized in areas in the west, south‐west and northern coast. We observed that the geoelectric field have a stronger dominant orientation than the orientation of the geomagnetic field, often constraining the hazardous geoelectric field in particular directions only. We demonstrate a seasonal/diurnal effect is present in the geoelectric field time series. The impact of galvanic distortion was also assessed, and we demonstrate that there is a significant difference in terms of amplitude and direction between both models.

Magnetic power spectrum variability with large-scale total magnetic field fluctuations

The Parker Solar Probe (PSP) is operational since 2018 and has provided invaluable new data that measure the solar vicinity in situ at smaller heliocentric distances than ever before. These data can be used to shed new light on the turbulent dynamics in the solar atmosphere and solar wind, which in turn are thought to be important to explain long-standing problems of the heating and acceleration in these regions. In recent years, it was realized that background inhomogeneities in magnetohydrodynamics could influence the development of turbulence and might enable other cascade channels, such as the self-cascade of waves, in addition to the well-known Alfvén collisional cascade. This phenomenon has been called uniturbulence. However, the precise influence of the background inhomogeneity on turbulent spectra has not been not studied so far. In this work, we study the influence of background roughness on the turbulent magnetic field spectrum in PSP data, including data from encounter 1 up to and including encounter 14. The magnetic spectral index $ receives our highest attention. Motivated by the presumably different turbulent dynamics in the presence of large-scale inhomogeneities, we searched for correlations between the magnetic power spectra and a measure for the degree of inhomogeneity. The latter was probed by taking the standard deviation (STD) of the total magnetic field magnitude after applying an appropriate averaging. The data of each PSP encounter were split into many short time windows, of which we subsequently calculated both $ and background STD. We find a significant impact of the background STD on $ As the variations in the background become stronger, $ becomes more negative, indicating a steepening of the magnetic power spectrum. We show that this effect is consistent in all investigated PSP encounters, and it is unaffected by heliocentric distance up to $50 R_ By making use of artificial magnetic field data in the form of synthetic colored noise, we show that this effect is not simply due to the fluctuations imposed on the total magnetic field, but must have another as yet unidentified cause. There is a strong indication that the background inhomogeneity affects the turbulent dynamics, possibly through uniturbulence. This leads to a different power spectrum in the presence of large-scale total magnetic field variations. The fact that it is present in all investigated encounters and at all radial distances up to $50 R_ suggests that it represents a general and ubiquitous feature of solar wind dynamics. The analysis with the synthetic colored noise indicates that the observed steepening effect is not to be attributed simply to the small-scale fluctuations superposed on the total magnetic field. This conclusion is confirmed by the fact that no similar consistent steepening trend is observed for the magnetic compressibility $C_b$ instead of background STD. The steepening trend is instead a real physical effect induced by the large-scale variations in the background magnetic field.

On the magnetic field in Earth’s interior

This paper discusses the possible distribution of Earth’s magnetic field in its three main layers. As a first step, using the IGRF-13 model, it was found that the magnetic field energy exterior to the liquid outer core (i.e., inside the mantle and the surrounding Earth’s atmosphere) is about J (for epoch 2010) while the field strength exactly at the Core-Mantle-Boundary (CMB) is about 0.42 mT (RMS value). These findings can be further considered as reliable reference values among the large dispersion of published data for the total magnetic field in Earth’s interior. Therefore, utilizing the layer breakdown reported in a pioneering paper (Glatzmaier and Roberts [8]) according to which the inner core includes about 10% of the total energy content, it was made possible to validate a previously reported figure (year 1949: 9×1020 J) regarding the total magnetic field energy of the Earth. But due to substantial deviation of the latter from a later reported figure (year 1980: 7×1021 J), this paper continues the investigation for the purpose of clarifying the issue. In this context, two inverse-cubic dipole models and the bar magnet (tiny and cylindrical) model, as well as the IGRF-13 standard were applied and compared in the Earth’s interior. Overall, under certain conditions these findings are successfully compared with literature reports, and eventually (after many assumptions) reached an acceptable compromise regarding the spatial distribution of the magnetic field, while a stimulus for further reflection to other researchers was provided. At the end, a question is posed and somewhat answered whether the available magnetic field energy is abundant to feed the motion of futuristic lightweight electromagnetic vehicles revived in recent literature.

A Triggering Process for Nonlinear EMIC Waves Driven by the Compression of the Dayside Magnetosphere

AbstractUsing the Arase and Van Allen Probes satellite observations, we investigate the nonlinear electromagnetic ion cyclotron (EMIC) rising‐tone (RT) emissions with an increase of the solar wind dynamic pressure in the dayside magnetosphere. We find that EMIC RT emissions are accompanied by the extended dayside uniform zone (DUZ) over |MLAT| < 25° due to the dayside magnetospheric compression by an increase in Pdyn. Using the observed plasma and magnetic field data, we modeled the threshold amplitude for the nonlinear EMIC waves and compared it with the observation. The small gradient of the ambient magnetic field strongly contributes to the reduction in the threshold amplitude of nonlinear wave growth compared to other parameters. When the threshold amplitude falls to comparable level of pre‐existing EMIC waves, EMIC RT emissions are immediately triggered, suggesting direct evidence that the DUZ is the preferred condition to cause the nonlinear EMIC RT emission in the dayside magnetosphere.

A cell-based association data integration method for locating potential drilling targets: A case study at the Dalli Cu–Au porphyry deposit in Iran

The presence of various spatial exploration proxies (predictor patterns) as vectors to distal porphyry mineralization in surrounding areas of a known outcropping mineralized porphyry center at the Dalli Cu–Au deposit in Iran provided evidence for the occurrence of similar porphyry mineralization in the subsurface. Factor analysis was applied to soil geochemical data from the Dalli South Hill area to define favorable geochemical variables and to create surface multi-element anomaly maps reflecting the presence of porphyry Cu–Au mineralization in the subsurface. Reduction-to-pole and analytical signal filters were applied to ground total magnetic field data to define high magnetic signatures that could be associated with potassic alteration and porphyry mineralization in the subsurface. Then, a data-driven cell based association (CBA) data integration method was applied to the favorable spatial proxies to define their association with Cu–Au mineralization and locate subtle high potential targets (cells) for drilling. The conventional CBA algorithms did not consider weights for the spatial proxies, and by using the ascendant hierarchical clustering (AHC) algorithm the results were classified into a binary map to show favorable and unfavorable cells with scores of 1 and 0, respectively. Predicting high potential targets for high-priced drilling, just based on using the binary map, could be very risky. Therefore, an innovative CBA data integration approach was employed to assign proper weights between 0 and 1 to the spatial proxies by calculating the importance of the presence of an exploration proxy in a cell using training (labeled) trenching geochemical data. A final continuous predictor map was generated and it successfully mapped the known outcropping porphyry center and its subsurface extension to the northeast as a high prospectivity class. This map also identified a narrow NE-trending high potential target (a few cells) of 200 m long in the southern part of the known porphyry center for drilling.

Exploration of the 2021 Mw 7.3 Maduo Earthquake by Fusing the Electron Density and Magnetic Field Data of Swarm Satellites

Exploration of the 2021 Mw 7.3 Maduo Earthquake by Fusing the Electron Density and Magnetic Field Data of Swarm Satellites

Magnetic anomaly detection of moving objects

Magnetometry is commonly used to detect and locate stationary as well as moving objects made of magnetic materials. The problem consists of detecting and determining any anomaly in the geomagnetic field generated by the presence and/or motion of a magnetic object, with the latter presenting a more challenging case. The data collected by a sensor or an array of sensors are treated by common signal and data processing techniques or by the objective base function (OBF) optimization methods which is the method employed in this work. A novel fluxgate sensor developed by the Sensors Laboratory is used to collect magnetic field data in an appropriately designed setup in the laboratory. The data are generated by a weakly magnetized object moving at a constant velocity and various distances from the sensor. The OBF method is used to construct the energy detection criterion. Results show that the energy value decreases at longer distances but the object is clearly detected even when the signal is buried in background noise. The performance of the overall system is promising for detecting and tracking moving objects in adverse environments such as marine traffic.