Interplanetary Magnetic Field Research Articles

Magnetopause location modeling using machine learning: inaccuracy due to solar wind parameter propagation

An intrinsic limitation of empirical models of the magnetopause location is a predefined magnetopause shape and assumed functional dependences on relevant parameters. We overcome this limitation using a machine learning approach (artificial neural networks), allowing us to incorporate general, purely data-driven dependences. For the training and testing of the developed neural network model, a data set of about 15,000 magnetopause crossings identified in the THEMIS A-E, Magion 4, Geotail, and Interball-1 satellite data in the subsolar region is used. A cylindrical symmetry around the direction of the impinging solar wind is assumed, and solar wind dynamic pressure, interplanetary magnetic field magnitude, cone angle, clock angle, tilt angle, and corrected Dst index are considered as parameters. The effect of these parameters on the magnetopause location is revealed. The performance of the developed model is compared with other empirical magnetopause models. Finally, we demonstrate and discuss the inaccuracy of magnetopause models due to the inaccurate information about the impinging solar wind parameters based on measurements near the L1 point. This inaccuracy imposes a theoretical limit on the precision of magnetopause predictions, a limit that our model closely approaches.

Annual and Seasonal Occurrence Pattern of Auroral Kilometric Radiation Associated with the Interplanetary Magnetic Field* *Released on March 1st, 2024.

Auroral kilometric radiation (AKR) is a widely existing strong radio emission from the Earth’s magnetosphere and is generated by suprathermal (1–10 keV) electrons in the polar cavity. Previous works have demonstrated that AKR can contribute to the coupling of the magnetosphere–ionosphere–atmosphere, but its relation to the interplanetary magnetic field (IMF) has not been studied so far. Here, we examine the data of Van Allen Probes and identify a total of 5000 AKR events from 2012 October to 2019 July. Most AKR events (4282) correspond to the dominant parallel component B∥(=(Bx)2+(By)2) of IMF. There are the most (1391) events in 2018 (the solar minimum year) and the least (258) events in 2014 (the solar maximum year), corresponding to more (less) occurrences for the longer duration (> 30 minutes) of southward IMF (B z < 0) in 2018 (2014). In the Earth’s Northern Hemisphere, there are the most (865) events in the autumn (August–October), corresponding to dominant B x < 0. In the Earth’s Southern Hemisphere, there are the most (830) events in the autumn (February–April), corresponding to dominant B x > 0. The probable reason for the above results is that the longer duration of B z < 0 can yield the longer magnetic reconnection, and the dominant B x < 0 (B x > 0) is favorable for the single-lobe magnetic reconnection in the northern (southern) hemisphere, allowing more suprathermal electrons into the polar source cavity and generating more AKRs. These current results suggest that IMF is very important for the occurrence of AKR and can be widely applied to similar auroral radio emissions in other magnetized planets of the solar system.

Inter‐Hemispheric Energy Input Into the Ionosphere‐Thermosphere System During Magnetic Storms: What We Can and Cannot Learn From DMSP Observations

AbstractWe present a long‐term superposed epoch analysis and statistical study with 427 magnetic storms caused by coronal mass ejections and the subsequent magnetospheric energy input into the ionosphere‐thermosphere system. Electron and ion precipitating energy flux data along with plasma drift velocity and magnetic field data (used for Earth‐bound Poynting flux computations) are used in this study. By carefully exploring conjugated inter‐hemispheric energy inputs as a function of storm intensity and seasons, we find that near two‐decades of Defense Meteorological Satellite Program observations indicate that the northern hemisphere (NH) receives slightly more energy than the southern hemisphere (SH) (Poynting flux and integrated electron/ion precipitating energy flux), with the NH receiving more energy as the storm becomes more intense. However, for the Poynting flux case, we find that generally the SH receives more energy when the east‐west component of the interplanetary magnetic field (IMF) becomes highly positive (By ≥ +5 nT), whereas this pattern reverses for cases when IMF By is highly negative (By ≤ −5 nT). The inter‐hemispheric interpretation for electron and ion precipitation energy inputs is ambiguous due to a severe lack of conjugated observations around the midnight sector for both hemispheres.

A stacked machine learning model for the vertical total electron content forecasting

We design four Artificial Neural Network (ANN) models, namely a Multilayer Perceptron (MLP), a Convolutional Neural Network (CNN), an Extreme Learning Machine network (ELM) and an ensemble model based on stacking (STACKED) to forecast the ionospheric vertical Total Electron Content (vTEC) from 1 to 24 hours in advance on a single station at mid latitude. The time series used, spanning from January 2006 to December 2018, includes vTEC, provided by the Global Navigation Satellite System (GNSS) receiver at Tsukuba (TSKB), Japan (36.06o N, 140.05o E) and suitable external drivers selected among several helio-geophysical parameters. The selection of appropriate external drivers is made by rating their relevance on the vTEC at forecasting timescales (from 1 to 24 hours). The process, based on eleven machine learning models, highlights that the most important external drivers are: the 10.7 cm Solar Flux (F10.7), the magnitude BT of the Interplanetary Magnetic Field (IMF), and the Auroral Electrojet (AE) index. The forecasting performance of the four models (MLP, CNN, ELM, STACKED) is then analysed. The analysis relies on three statistical metrics to compare actual and forecasted vTEC: the coefficient of determination (R2), the Mean Absolute Error (MAE), and the Root Mean Squared Error (RMSE). Additionally, descriptive statistics are presented using box and whisker plots. The four ANN models show a quite satisfactory capability to forecast vTEC when applied to the test dataset which represents 10% of the available data from 2006 to 2018. Furthermore, by conducting a Wilcoxon signed rank test, it is shown that statistically significant improvements are achieved by the STACKED model with regard to MLP, CNN and ELM. On average, by analysing the forecasted (from 1 to 24 hours in advance) vs the actual vTEC, the STACKED model achieves R2=0.816,RMSE=0.426 TECu, and MAE=0.296 TECu (1 TECunit =1016 electrons/m2) whilst MLP, CNN and ELM show respectively R2=0.808,0.812,0.803,RMSE=0.436 TECu, 0.431 TECu, 0.441 TECu and MAE=0.304 TECu, 0.299 TECu, 0.312 TECu.

Earth’s geomagnetic environment—progress and gaps in understanding, prediction, and impacts

Understanding of Earth’s geomagnetic environment is critical to mitigating the space weather impacts caused by disruptive geoelectric fields in power lines and other conductors on Earth’s surface. These impacts are the result of a chain of processes driven by the solar wind and linking Earth’s magnetosphere, ionosphere, thermosphere and Earth’s surface. Tremendous progress has been made over the last two decades in understanding the solar wind driving mechanisms, the coupling mechanisms connecting the magnetically controlled regions of near-Earth space, and the impacts of these collective processes on human technologies on Earth’s surface. Studies of solar wind drivers have been focused on understanding the responses of the geomagnetic environment to spatial and temporal variations in the solar wind associated with Coronal Mass Ejections, Corotating Interaction Regions, Interplanetary Shocks, High-Speed Streams, and other interplanetary magnetic field structures. Increasingly sophisticated numerical models are able to simulate the magnetospheric response to the solar wind forcing associated with these structures. Magnetosphere-ionosphere-thermosphere coupling remains a great challenge, although new observations and sophisticated models that can assimilate disparate data sets have improved the ability to specify the electrodynamic properties of the high latitude ionosphere. The temporal and spatial resolution needed to predict the electric fields, conductivities, and currents in the ionosphere is driving the need for further advances. These parameters are intricately tied to auroral phenomena—energy deposition due to Joule heating and precipitating particles, motions of the auroral boundary, and ion outflow. A new view of these auroral processes is emerging that focuses on small-scale structures in the magnetosphere and their ionospheric effects, which may include the rapid variations in current associated with geomagnetically induced currents and the resulting perturbations to geoelectric fields on Earth’s surface. Improvements in model development have paralleled the advancements in understanding, yielding coupled models that better replicate the spatial and temporal scales needed to simulate the interconnected domains. Many realizations of such multi-component systems are under development, each with its own limitations and advantages. Challenges remain in the ability of models to quantify uncertainties introduced by propagation of solar wind parameters, to account for numerical effects in model codes, and to handle the special conditions occurring during extreme events. The impacts to technical systems on the ground are highly sensitive to the local electric properties of Earth’s surface, as well as to the specific technology at risk. Current research is focused on understanding the characteristics of geomagnetic disturbances that are important for geomagnetically induced currents, the development of earth conductivity models, the calculation of geoelectric fields, and the modeling of induced currents in the different affected systems. Assessing and mitigating the risks to technical systems requires quantitative knowledge of the range of values to be expected under all possible geomagnetic and technical conditions. Considering the progress that has been made in studying the chain of events leading to hazardous geomagnetic disturbances, the path forward will require concerted efforts to reveal missing physics, improve modeling capabilities, and deploy new observational assets. New understanding should be targeted to accurately quantify solar wind driving, magnetosphere-ionosphere-thermosphere coupling, and the impacts on specific technologies. The research, modeling, and observations highlighted here provide a framework for constructing a plan by which the international science community can comprehensively address the growing threat to human technologies caused by geomagnetic disturbances.

Interaction between a Coronal Mass Ejection and Comet 67P/Churyumov–Gerasimenko

The interaction between a coronal mass ejection (CME) and a comet has been observed several times by in situ observations from the Rosetta Plasma Consortium, which is designed to investigate the cometary magnetosphere of comet 67P/Churyumov–Gerasimenko (CG). Goetz et al. reported a magnetic field of up to 300 nT measured in the inner coma, which is among the largest interplanetary magnetic fields observed in the solar system. They suggested the large magnetic field observations in the inner coma come from magnetic field pileup regions, which are generated by the interaction between a CME and/or corotating interaction region and the cometary magnetosphere. However, the detailed interaction between a CME and the cometary magnetosphere of comet CG in the inner coma has not been investigated by numerical simulations yet. In this paper, we will use a numerical model to simulate the interaction between comet CG and a Halloween class CME and investigate its magnetospheric response to the CME. We find that the plasma structures change significantly during the CME event, and the maximum value of the magnetic field strength is more than 500 nT close to the nucleus. Virtual satellites at similar distances as Rosetta show that the magnetic field strength can be as large as 250 nT, which is slightly less than what Goetz et al. reported.

Comparative simulations of Kelvin–Helmholtz induced magnetic reconnection at the Earth's magnetospheric flanks

This study presents three-dimensional (3D) resistive Hall-magnetohydrodynamic simulations of the Kelvin–Helmholtz instability (KHI) dynamics at Earth's magnetospheric flanks during northward interplanetary magnetic field periods. By comparing two simulations with and without initial magnetic shear, we analyze the impact of distinct magnetic field orientations on plasma dynamics and magnetic reconnection events taking into account 3D mechanisms, such as KHI high latitude stabilization. The identical nature of the simulations, except for the presence/absence of an initial magnetic shear, enables, for the first time, a complete and coherent comparative analysis of the latitudinal distribution of KH vortices, current sheets, reconnection events, and the evolution of the mixing layer. In one configuration, a uniform magnetic field leads to double mid-latitude reconnection (MLR), while in the other, magnetic shear induces both type I vortex-induced reconnection (VIR) and MLR. Notably, the type I VIR observed in this second scenario results from the combined action of line advection and vortex-induced current sheet pinching (the classic mechanism driving two-dimensional type I VIR). Of particular importance is our quantification of newly closed field lines that experienced double reconnection, ultimately becoming embedded in solar wind plasma at low latitudes while remaining connected to magnetospheric plasma at high latitudes. The varying abundance of such lines in the two simulations holds implications for plasma transport at the magnetopause.

The Short‐Periodic Response of Equatorial Electrojet to the Temporal Variations of IMF Bz During Geomagnetic Quiet Time

AbstractThe equatorial electrojet (EEJ) is an important and intense ionospheric current, flowing in a narrow band along the dip equator. Using the total electron content from Global Navigation Satellite System, electron density from Swarm, EEJ from Tatuoca station, and the corresponding Thermosphere‐Ionosphere Electrodynamic General Circulation Model simulations, this work investigates the behaviors of quiet‐time EEJ during the temporal oscillations of interplanetary magnetic field (IMF) Bz. It is found that an average relative perturbation of 17.5%, 5.51% and 23.17% could be generated in the quiet time EEJ on August 24 in 2021, 2022, and 2023, respectively. The prominent feature shown in EEJ changes is the short‐periodic oscillations with high frequency and a period of tens of minutes. A power spectrum from wavelet supports that the small‐scale perturbations with high frequency are mainly attributed to the prompt penetration electric field (PPEF). During the temporal oscillations of IMF Bz, a similar spectrum is established between IMF Bz and PPEF. PPEF could be promptly superposed into the zonal equatorial electric field within minutes, producing similar frequent responses in EEJ. The large changes with low frequency are related to the disturbance wind dynamo electric field.

Identifying Coronal Sources of L1 Solar Wind Disturbances Using the Fisk Heliospheric Magnetic Field and Potential Field Extrapolations during Three Solar Minima

The solar minima between solar cycles 22–23, 23–24, and 24–25 are the best observed minima on record. In situ solar wind and interplanetary magnetic field measurements by the Wind and ACE spacecraft at L1 with 1 hr cadence are explored using wavelet analyses for the most quiescent year during each minimum. Times of local peaks in periodicities are identified in the solar wind velocity, magnetic field components, and proton number densities. The measured radial velocities at these times are used to trace magnetic field lines to the photosphere using two models. The first is the Fisk heliospheric magnetic field that traces field lines from L1 to the photosphere. They connect exclusively to solar poles and in 88% of instances to locations of polar coronal holes (PCHs). The second model uses the Parker spiral to trace from L1 to the solar source surface and potential-field extrapolations from the source surface to the photosphere. These field lines terminate at equatorial and midlatitude coordinates, of which some are located close to coronal holes (CHs). This study connects for the first time CH signatures in the ecliptic plane at L1 with PCHs using the Fisk field. It shows how sources from both the solar equator and poles influence the solar wind at L1 and how the two models complement each other to identify these sources.

Short large-amplitude magnetic structures (SLAMS) at Mercury observed by MESSENGER

Abstract. We present the first observations of short large-amplitude magnetic structures (denoted SLAMS) at Mercury. We have investigated approximately 4 years of MESSENGER (MErcury Surface, Space ENvironment, GEochemistry, and Ranging) data to identify SLAMS in the Mercury foreshock. Defining SLAMS as magnetic field compressional structures, with an increase in magnetic field strength of at least twice the background magnetic field strength, when MESSENGER is located in the solar wind, we find 435 SLAMS. The SLAMS are found either in regions of a general ultra-low frequency (ULF) wave field, at the boundary of such a ULF wave field, or in a few cases isolated from the wave field. We present statistics on several properties of the SLAMS, such as temporal scale size, amplitude, and the presence of whistler-like wave emissions. We find that SLAMS are mostly found during periods of low interplanetary magnetic field strength, indicating that they are more common for higher solar wind Alfvénic Mach number (MA). We use the Tao solar wind model to estimate solar wind parameters to verify that MA is indeed larger during SLAMS observations than otherwise. Finally, we also investigate how SLAMS observations are related to foreshock geometry.

On the Importance of the Kelvin‐Helmholtz Instability on Magnetospheric and Solar Wind Dynamics During High Magnetic Shear

AbstractThe secondary processes driven by the velocity shear driven Kelvin‐Helmholtz Instability (KHI) in the magnetized plasmas have been shown to be important in producing plasma transport and heating from the shocked solar wind into the Earth's magnetosphere (MSP). The plasma transport into the MSP due to KHI has been shown to be strongest during northward interplanetary magnetic field (IMF) via KHI driven low‐ and mid‐latitude reconnection process. In a recent article, Li et al. (2023), https://doi.org/10.1029/2023gl105539 show Magnetosphere Multi‐Scale (MMS) spacecraft observations of multiple, Alfvénic reconnection jets during southward IMF at the dawn‐side MSP flank. The quasi‐periodic oscillations in plasma parameters and compressed, ion‐scale current sheets were strongly indicative of the MMS crossing regions of MSP‐like and magnetosheath‐like plasma within Kelvin‐Helmholtz waves. In this brief commentary, the importance of this new discovery for magnetospheric and solar wind dynamics is discussed.

Quantification of magnetosphere–ionosphere coupling timescales using mutual information: response of terrestrial radio emissions and ionospheric–magnetospheric currents

Abstract. Auroral kilometric radiation (AKR) is a terrestrial radio emission excited by the same accelerated electrons which excite auroral emissions. Although it is well correlated with auroral and geomagnetic activity, the coupling timescales between AKR and different magnetospheric or ionospheric regions have yet to be determined. Estimation of these coupling timescales is non-trivial as a result of complex, non-linear processes which rarely occur in isolation. In this study, the mutual information between AKR intensity and different geomagnetic indices is used to assess the correlation between variables. Indices are shifted to different temporal lags relative to AKR intensity, and the lag at which the variables have the most shared information is found. This lag is interpreted as the coupling timescale. The AKR source region receives the effects of a shared driver before the auroral ionosphere. Conversely, the polar ionosphere reacts to a shared driver before the AKR source region. Bow shock interplanetary magnetic field BZ is excited about 1 h before AKR enhancements. This work provides quantitatively determined temporal context to the coupling timelines at Earth. The results suggest that there is a sequence of excitation following the onset of a shared driver: first, the polar ionosphere feels the effects, followed by the AKR source region and then the auroral ionosphere.

Physics-informed loss functions for vertical total electron content forecast

AbstractWe design physics-informed loss functions for training Artificial Neural Network (ANN) models to forecast the ionospheric vertical Total Electron Content (vTEC) from 1 to 24 hours in advance. The ANN models exploit our physics-informed loss functions, data provided by the Global Navigation Satellite Systems (GNSS) receiver installed at Tsukuba (36.06$$^{o}$$ o N, 140.05$$^{o}$$ o E), Japan, and external drivers (solar and geomagnetic indices). The time series used span from January 1, 2006, to December 31, 2018, i.e., a full solar cycle. A proper set of external drivers for the ANN models training are selected by ranking their importance in relation to the vTEC dynamics at different forecasting horizons. They result to be the 10.7 cm Solar Flux (F10.7), the magnitude of the Interplanetary Magnetic Field (IMF) $$\boldsymbol{B}_{\boldsymbol{T}}$$ B T , and the Auroral Electrojet (AE) index. Moreover, a second set of indices among those available has been considered as constraints in the design of the physics-informed loss functions. They are the Disturbance Storm Time (Dst) index, the solar wind speed $$\boldsymbol{v}, \boldsymbol{B}_{\boldsymbol{T}}$$ v , B T , and the By and Bz components of the interplanetary magnetic field. To assess the performance of the resulting ANN models, we use the statistical parameter coefficient of determination ($$\boldsymbol{R}^{{\textbf {2}}}$$ R 2 ), the standard deviation (SD), and the Wilcoxon non-parametric signed ranked test. We show that, in the testing period analyzed (from 2017-09-13, at 04:40:00, to 2018-12-31, at 23:55:00), one of our physics-informed loss functions provides a better performance of the ANN with regard to the standard loss function commonly adopted. In particular, when the new loss function is used in the ANN model, the average SD is minimized across all forecasting horizons in the training, validation and test datasets. SD is 0.2560 TECU, 0.3183 TECU and 0.4240 TECU for the training, validation and test dataset respectively, where 1 TECU = $${\textbf {10}}^{{\textbf {16}}}$$ 10 16 electrons/$$\boldsymbol{m}^{{\textbf {2}}}$$ m 2 . The ANN model, incorporating the new loss function and applied to the test dataset, shows a significant improvement according to the Wilcoxon signed ranked test. In fact by selecting a significance level $$\boldsymbol{\alpha }~ \mathbf {= 0.05}$$ α = 0.05 , the probability to obtain results by chance with the new loss function as compared to the standard loss function is 0.01504 (i.e., $$&lt;\alpha $$ &lt; α ), which implies that the new loss function gives a statistical improvement to the forecasting capability of the ANN model. To the best of our knowledge, this is the first time a physics-informed loss function has been designed for the task of forecasting the ionospheric vTEC.

The Burr distribution as an asymptotic law for extreme order statistics and its application to the analysis of statistical regularities in the interplanetary magnetic field

Abstract The representability of the Burr distribution as a mixture of Weibull distribution is studied in order to justify its utility for modelling the statistical regularities in extreme values registered in non-stationary flows of informative events. A result of [24] is improved by extending the domain of admissible values of the parameters which provide the representability of the (generalized) Burr distribution as a scale mixture of the Weibull distribution. This result gives an argument in favour of application of the Burr distribution as a model of statistical regularities of extreme values registered within moderate regular time intervals, say, daily (short-term) extremes. In turn, if we are interested in the statistical regularities of the behaviour of the absolute extreme observation over a long period, say, a decade (the long-term extreme), then it can be noted that the daily extreme values form a sample of the Burr-distributed random variables. As is known, the Burr distribution belongs to the domain of max-attraction of the Fréchet distribution. The problem of improving the accuracy of the approximation of the distribution of the absolute extreme by the Fréchet distribution by the construction of an asymptotic expansion for the distribution of the extreme order statistics in the sample of independent identically Burr-distributed random variables is also considered. These results are illustrated by an example of fitting the Burr distribution to the data representing the extreme values of characteristics of the interplanetary magnetic field.

Tracking the Subsolar Bow Shock and Magnetopause: Applying the Magnetosheath Velocity Gradient Method

AbstractBoth the bow shock and magnetopause move in response to varying solar wind and magnetospheric conditions. Tracking their locations can provide important clues to the state of the solar wind‐magnetosphere interaction, but is difficult with single spacecraft observations. This paper employs multipoint THEMIS observations of velocity gradients in the subsolar magnetosheath to remotely sense boundary locations on a continual basis for various solar wind conditions. We present three cases: (a) continuous northward IMF and no magnetopause motion; (b) southward IMF and no magnetopause motion with evidence of nightside activity; and (c) southward IMF and pressure increase with inward motion. When observing spacecraft are located near the Sun‐Earth line, inferred boundary locations agree well with the predictions of the BATS‐R‐US global magnetohydrodynamic model, confirming the utility of both the new method and the models. Results show that boundaries often lie nearly at rest with amplitudes less than 0.5 RE. They provide evidence indicating that nightside reconnection and a strong sunward convection in the outer magnetosphere can counteract the magnetopause erosion expected when a southward interplanetary magnetic field (IMF) initiates reconnection on the dayside magnetopause.

Calculating the High‐Latitude Ionospheric Electrodynamics Using a Machine Learning‐Based Field‐Aligned Current Model

AbstractWe introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML‐AIM). ML‐AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020, https://doi.org/10.1029/2020JA027908), the FAC‐derived auroral conductance model of Robinson et al. (2020, https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993, https://doi.org/10.1029/92gl02109). The ML‐AIM inputs are 60‐min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML‐AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML‐AIM produces physically accurate ionospheric potential patterns such as the two‐cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (ΦPC) from ML‐AIM, the Weimer (2005, https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data‐assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML‐AIM than others. ML‐AIM is unique and innovative because it predicts ionospheric responses to the time‐varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005, https://doi.org/10.1029/2004ja010884) designed to provide a quasi‐static ionospheric condition under quasi‐steady solar wind/IMF conditions. Plans are underway to improve ML‐AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times.

Spatial Distribution of the Eddy Diffusion Coefficient in the Plasma Sheet of Earth’s Magnetotail and Its Dependence on the Interplanetary Magnetic Field and Geomagnetic Activity Based on MMS Satellite Data

Spatial Distribution of the Eddy Diffusion Coefficient in the Plasma Sheet of Earth’s Magnetotail and Its Dependence on the Interplanetary Magnetic Field and Geomagnetic Activity Based on MMS Satellite Data

Statistical Features of Polar Cap North and South Indices in Response to Interplanetary and Terrestrial Conditions: A Revisit

AbstractIn this study, we investigate statistical features of polar cap north (PCN) and south (PCS) indices in response to various interplanetary conditions (interplanetary magnetic field [IMF] orientation in three‐dimensions) and terrestrial conditions (seasonal and magnetic local time [MLT] locations of the index stations). The concurrent PCN‐PCS pairs for 1998–2002 and 2004–2018 are divided based on their sign type (positive‐positive, negative‐negative, negative‐positive, and positive‐negative PCN‐PCS pairs) and time coverage (the times when both index stations are in the dawn/dusk MLT sector during northern summer/winter). Analyzing the IMF orientation dependence on the occurrence probabilities of concurrent indices and on the differences between the indices in various sign types for each time coverage reveals that the statistical features in PCN‐PCS pairs obtained in the dawn MLT sector can be largely explained by the effects of the three‐component IMF (related to the polar cap convection patterns) combined with season (related to the hemispheric asymmetry in solar illumination‐induced ionospheric conductance). However, those obtained in the dusk MLT sector are controlled dominantly by seasonal effects rather than IMF orientation effects. Our findings indicate that PCN‐PCS pair data provide local views about the solar wind‐magnetosphere‐ionosphere (SW‐M‐I) coupling system with different control efficiencies of IMF orientation and season depending on the MLT location of the stations. Therefore, introducing polar cap indices recorded simultaneously at various locations in both hemispheres and analyzing them are strongly required to infer global views of the coupled SW‐M‐I system in the open field regions with higher confidence.

Increase in the count rates of ground-based cosmic-ray detectors caused by the heliomagnetic disturbance on 5 November 2023

This letter presents a rare physical phenomenon associated with solar activity, manifesting in anomalies within neutron, electron, and gamma-ray fluxes in the atmosphere. Conventionally, the Earth's magnetic-field disturbances reduce cosmic-ray intensity reaching the surface. However, a temporary surge in cosmic-ray flux occurs intermittently known as the magnetospheric effect (ME). Our observations reveal that this effect predominantly induces a count rate increase in particle detectors positioned at middle latitudes on mountaintops. On November 5, 2023, a 2–3% increase in neutron monitors at mountain altitudes and up to 5% increase in thin plastic scintillators registering electrons and gamma rays was observed. This flux escalation coincided with a southward orientation of the interplanetary magnetic field. Importantly, we present, for the first time, the energy spectrum of the Magnetospheric Effect observed at two mountaintops: Aragats and Zugspitze. Simulations of low-energy proton interactions in the terrestrial atmosphere affirm the augmentation of low-energy cosmic rays. Protons, typically restricted by the geomagnetic cutoff, reached the Earth's atmosphere, generating detectable particle showers on the Earth's surface. To sum up, 1) we measure an increase in the count rate of magnetospheric origin using particle detectors located at mountain altitudes and middle latitudes; 2) for the first time, we measured the energy spectra of the particle fluxes during the magnetospheric effect with spectrometers located on Mount Aragats and Zugspitze; 3) particle flux enhancement coincides with the depletion of the horizontal component of the geomagnetic field; 4) we explain why the magnetospheric effect was observed at mountain altitudes and not at sea level.

Structure and Dynamics for Graphs of Interplanetary Magnetic Field Vectors

Structure and Dynamics for Graphs of Interplanetary Magnetic Field Vectors