We investigate ionospheric flow patterns occurring on 28 January 2002 associated with the development of the nightside distorted end of a J-shaped transpolar arc (nightside distorted TPA). Based on the nightside ionospheric flows near to the TPA, detected by the SuperDARN (Super Dual Auroral Radar Network) radars, we discuss how the distortion of the nightside end toward the pre-midnight sector is produced. The J-shaped TPA was seen under southward interplanetary magnetic field (IMF) conditions, in the presence of a dominant dawnward IMF-By component. At the onset time of the nightside distorted TPA, particular equatorward plasma flows at the TPA growth point were observed in the post-midnight sector, flowing out of the polar cap and then turning toward the pre-midnight sector of the main auroral oval along the distorted nightside part of the TPA. We suggest that these plasma flows play a key role in causing the nightside distortion of the TPA. SuperDARN also found ionospheric flows typically associated with Tail Reconnection during IMF Northward Non-substorm Intervals (TRINNIs) on the nightside main auroral oval, before and during the TPA interval, indicating that nightside magnetic reconnection is an integral process to the formation of the nightside distorted TPA. During the TPA growth, SuperDARN also detected anti-sunward flows across the open–closed field line boundary on the dayside that indicate the occurrence of low-latitude dayside reconnection and ongoing Dungey cycle driving. This suggests that nightside distorted TPA can grow even in Dungey-cycle-driven plasma flow patterns.
We consider the flare prediction problem that distinguishes flare-imminent active regions that produce an M- or X-class flare in the future 24 hours, from quiet active regions that do not produce any flare within $\pm 24$ hours. Using line-of-sight magnetograms and parameters of active regions in two data products covering Solar Cycle 23 and 24, we train and evaluate two deep learning algorithms—CNN and LSTM—and their stacking ensembles. The decisions of CNN are explained using visual attribution methods. We have the following three main findings. (1) LSTM trained on data from two solar cycles achieves significantly higher True Skill Scores (TSS) than that trained on data from a single solar cycle with a confidence level of at least 0.95. (2) On data from Solar Cycle 23, a stacking ensemble that combines predictions from LSTM and CNN using the TSS criterion achieves significantly higher TSS than the “select-best” strategy with a confidence level of at least 0.95. (3) A visual attribution method called Integrated Gradients is able to attribute the CNN’s predictions of flares to the emerging magnetic flux in the active region. It also reveals a limitation of CNN as a flare prediction method using line-of-sight magnetograms: it treats the polarity artifact of line-of-sight magnetograms as positive evidence of flares.
Ganymede is the only Solar System moon known to generate a permanent magnetic field. Jovian plasma motions around Ganymede create an upstream magnetopause, where energy flows are thought to be driven by magnetic reconnection. Simulations indicate Ganymedean reconnection events may be transient, but the nature of magnetopause reconnection at Ganymede remains poorly understood, requiring an assessment of reconnection onset theory. We present an analytical model of steady-state conditions at Ganymede’s magnetopause, from which the first Ganymedean reconnection onset assessment is conducted. We find that reconnection may occur wherever Ganymede’s closed magnetic field encounters Jupiter’s ambient magnetic field, regardless of variations in magnetopause conditions. Unrestricted reconnection onset highlights possibilities for multiple X-lines or widespread transient reconnection at Ganymede. The reconnection rate is controlled by the ambient Jovian field orientation and hence driven by Jupiter’s rotation. Future progress on this topic is highly relevant for the JUpiter ICy moon Explorer (JUICE) mission.
The forecasting of local GIC effects has largely relied on the forecasting of dB/dt as a proxy and, to date, little attention has been paid to directly forecasting the geoelectric field or GICs themselves. We approach this problem with machine learning tools, specifically recurrent neural networks or LSTMs by taking solar wind observations as input and training the models to predict two different kinds of output: first, the geoelectric field components Ex and Ey; and second, the GICs in specific substations in Austria. The training is carried out on the geoelectric field and GICs modelled from 26 years of one-minute geomagnetic field measurements, and results are compared to GIC measurements from recent years. The GICs are generally predicted better by an LSTM trained on values from a specific substation, but only a fraction of the largest GICs are correctly predicted. This model had a correlation with measurements of around 0.6, and a root-mean-square error of 0.7 A. The probability of detecting mild activity in GICs is around 50%, and 15% for larger GICs.
Advances in space weather science and small satellite (SmallSat) technology have proceeded in parallel over the past two decades, but better communication and coordination is needed among the respective worldwide communities contributing to this rapid progress. We identify six areas where improved international coordination is especially desirable, including: (1) orbital debris miti-gation; (2) spectrum management; (3) export control regulations; (4) access to timely and low-cost launch opportunities; (5) inclusive data policies; and (6) education. We argue the need for interna-tionally coordinated policies and programs to promote the use of SmallSats for space weather re-search and forecasting while realizing maximum scientific and technical advances through the inte-gration of these two increasingly important endeavors.
The Energetic Particle Detector (EPD) onboard Solar Orbiter is a suite of multiple sensors (Suprathermal Electrons Protons, STEP; Suprathermal Ion Spectrograph, SIS; Electron Proton Telescope, EPT; High Energy Telescope, HET), which measures particle intensities over a wide range of energies (from suprathermal to relativistic energies) and for different species (electron, protons, and heavy ions) in different directions. The EPD data center (http://espada.uah.es/epd) offers a primer venue to inspect the Solar Energetic Particle (SEP) activity, both to promptly check the most recent solar activity using quicklook plots based on low-latency data sets, and to perform deeper studies with data validated for scientific use. Among others, a series of plots and relevant information, such as the spacecraft maneuvers or sensor updates, are provided to the community. This facility gives access to all the data from the EPD sensors (which can be also found in the Solar Orbiter Archive), including Level 2 (calibrated) as well as more elaborated Level 3 data in the near future, which have further processing. An application programming interface (API) is also offered for accessing EPD data. Besides, during the first year and a half of observations, Solar Orbiter has completed three orbits, and EPD has measured several increases in particle fluxes, due to heliospheric and solar-origin events. Some of the events have been analysed and the flux enhancements have been tagged for future studies. This work aims to let the community know the availability of the instrument data products, and to explain how to properly use the provided data products and plots, as well as to summarise all the available studies published until now.
A new model validation and performance assessment tool is introduced, the sliding threshold of observation for numeric evaluation (STONE) curve. It is based on the relative operating characteristic (ROC) curve technique, but instead of sorting all observations in a categorical classification, the STONE tool uses the continuous nature of the observations. Rather than defining events in the observations and then sliding the threshold only in the classifier/model data set, the threshold is changed simultaneously for both the observational and model values, with the same threshold value for both data and model. This is only possible if the observations are continuous and the model output is in the same units and scale as the observations; the model is trying to exactly reproduce the data. The STONE curve has several similarities with the ROC curve – plotting probability of detection against probability of false detection, ranging from the (1,1) corner for low thresholds to the (0,0) corner for high thresholds, and values above the zero-intercept unity-slope line indicating better than random predictive ability. The main difference is that the STONE curve can be nonmonotonic, doubling back in both the x and y directions. These ripples reveal asymmetries in the data-model value pairs. This new technique is applied to modeling output of a common geomagnetic activity index as well as energetic electron fluxes in the Earth’s inner magnetosphere. It is not limited to space physics applications but can be used for any scientific or engineering field where numerical models are used to reproduce observations.
Geomagnetically induced currents (GICs) at middle latitudes have received increased attention after reported power-grid disruptions due to geomagnetic disturbances. However, quantifying the risk to the electric power grid at middle latitudes is difficult without understanding how the GIC sensors respond to geomagnetic activity on a daily basis. Therefore, in this study the question “Do measured GICs have distinguishable and quantifiable long- and short-period characteristics?” is addressed. The study focuses on the long-term variability of measured GIC, and establishes the extent to which the variability relates to quiet-time geomagnetic activity. GIC quiet-day curves (QDCs) are computed from measured data for each GIC node, covering all four seasons, and then compared with the seasonal variability of Thermosphere-Ionosphere- Electrodynamics General Circulation Model (TIE-GCM)-simulated neutral wind and height-integrated current density. The results show strong evidence that the middle-latitude nodes routinely respond to the tidal-driven Sq variation, with a local time and seasonal dependence on the the direction of the ionospheric currents, which is specific to each node. The strong dependence of GICs on the Sq currents demonstrates that the GIC QDCs may be employed as a robust baseline from which to quantify the significance of GICs during geomagnetically active times and to isolate those variations to study independently. The QDC-based significance score computed in this study provides power utilities with a node-specific measure of the geomagnetic significance of a given GIC observation. Finally, this study shows that the power grid acts as a giant sensor that may detect ionospheric current systems.
It’s very difficult to understand the mechanism producing solar magnetic fields, as it mingled with various activities, it also hindered by gaseous model of the sun; an alternative view is suggested based on characteristics of electrons exhibited in electric current; in 1820 Ørsted discovered both the relation between electricity and magnesium and the Circular Magnetic Field (CMF) produced by electric current, later discovered its produced by electrons in motion; thus the bulky rotation of charged particles (electrons, protons and ions) in tornado mode, produced intense CMF, designated as Plasma Pillar Intense Magnetic Field (PPIMF) with magnitude exceeds millions Tesla; and since EUV images in F-A, illustrates subsurface intense Magnetic Lines of Force (MLF), it also shows activities of Solar Flare (SF), both are suggested as due to PPIMF, which accounted for most solar activities, the Active Region (AR) as in F-B suggested to represent the PPIMF, where AR near surface are in circle, while AR at deep depth in squares; at deep depths the influence of PPIMF on photosphere during quiet sun resulted in pairs of negative and positive magnetic fields represented by magnetogram in F-C; during active sun, PPIMF raise nearer photosphere, it’s negative and positive fields interacted with the photosphere’s state, resulted in pairs of sunspots in F-D, look like iron filings, but formed by plasma, their shapes determined by proximity to PPIMF; as charged particles gyrate around the pillar, any increase in field’s intensity reduced radius of gyration, hence the adjacent distances between ions, thus at critical distance Solar Flare (SF) is triggered producing great energy, radiations and plasma including heavy ions; this knowledge will unlock dynamics of the sun, it’s internal structures and related mechanisms, it will help attained the alternative renewable energy, avert negative consequences of climate change, improve prediction of solar activity and space weather among others.
The Galileo mission was the first to orbit Jupiter and lasted from 1995 to 2003. Its data set is unique even compared to contemporary data from the Juno mission since Galileo had an equatorial orbit, as it is necessary to sample equatorially mirroring particles. Galileo also had several close moon flybys. It carried instrumentation designed to provide measurements of MeV electrons. Different to for example optical instruments that can also respond to such particles, an instrument designed to measure radiation is much more straightforward to calibrate. Here we describe Galileos EPD suite (Energetic Particle Detector) and its measurements. EPD measures energetic charged particles roughly in the energy range of tens of keV to tens of MeV while distinguishing particle species. This document fills in gaps in the EPD documentation and summarizes already published information. We describe the content of the newly delivered PDS data and how the data has been processed. At the end we also show sample data, explain typical features and possible pitfalls.
We present a reduced magnetohydrodynamic (MHD) mathematical model describing the dynamical behavior of highly conducting plasmas with frozen-in magnetic fields, constrained by the assumption that, there exists a frame of reference, where the magnetic field vector, B, is aligned with the plasma velocity vector, u, at each point. We call this solution “stream-aligned MHD” (SA-MHD). Within the framework of this model, the electric field, E = −u x B ≡ 0, in the induction equation vanishes identically and so does the electromagnetic energy flux (Poynting flux), E x B ≡ 0, in the energy equation. At the same time, the force effect from the magnetic field on the plasma motion (the Ampere force) is fully taken into account in the momentum equation. Any steady-state solution of the proposed model is a legitimate solution of the full MHD system of equations. However, the converse statement is not true: in an arbitrary steady-state magnetic field the electric field does not have to vanish identically (its curl has to, though). Specifically, realistic tree-dimensional solutions for the steady-state (ambient) solar atmosphere in the form of so-called Parker (1958) spirals, can be efficiently generated within the stream-aligned MHD (SA-MHD) with no loss in generality.
The Juno Waves instrument measured plasma waves associated with Ganymede’s magnetosphere during its flyby on 7 June, day 158, 2021. Three distinct regions were identified including a wake, and nightside and dayside regions in the magnetosphere distinguished by their electron densities and associated variability. The magnetosphere includes electron cyclotron harmonic emissions including a band at the upper hybrid frequency, as well as whistler-mode chorus and hiss. These waves likely interact with energetic electrons in Ganymede’s magnetosphere by pitch angle scattering and/or accelerating the electrons. The wake is accentuated by low-frequency turbulence and electrostatic solitary waves. Radio emissions observed before and after the flyby likely have their source in Ganymede’s magnetosphere.
We use numerical simulations to study the resonant interaction of relativistic electrons with rising-frequency EMIC wave packets in the H band. We find that precipitation fluxes are formed by quasi-linear interaction and several nonlinear interaction regimes having opposite effects. In particular, the influence of Lorentz force on the particle phase (force bunching) decreases precipitation for particles with low equatorial pitch angles (up to 15-25), and can even block it completely. Four other nonlinear regimes are possible: nonlinear shift of the resonance point (can cause pitch angle drift in both directions); phase bunching (slightly increases pitch angle for untrapped particles); directed scattering (strongly decreases pitch angle for untrapped particles) and particle trapping by the wave field (decreases pitch angle). Equatorial pitch angle distribution evolution during several passes of particles through the wave packet is studied. The precipitation fluxes are evaluated and compared with theoretical estimates. We show that strong diffusion limit is maintained for a certain range of energies by a wave packet with realistic amplitude and frequency drift. In this case, the quasi-linear theory strongly underestimates the precipitated flux. With increasing energy, the precipitated fluxes decrease and become close to the quasi-linear estimates.
Journals occasionally solicit manuscripts for special collections, in which all papers are focused on a particular topic within the journal’s scope. For the Journal of Geophysical Research: Space Physics, there have been 51 special collections from 2005 through 2018, with a total of 1009 papers out of the 8881 total papers in the journal over those years (11%). Taken together, the citations to special collection papers, as well as other metrics, are essentially the same as the non-special-collection papers. Several paper characteristics were examined to assess whether they could explain the higher citation and download values for SC papers, but they cannot. In addition, indirect methods were conducted for assessing self-citations as an explanation for the increased citations, but no evidence was found to support this hypothesis. It was found that some paper types, notably Commentaries and Technical Reports, have lower average citations but higher average downloads than Research Articles (the most common type of paper in this journal). This implies that such paper types have a different kind of impact than “regular” science-result-focused papers. In addition to having higher average citations and downloads, special collections focus community attention on that particular research topic, providing a deadline for manuscript submissions and a single webpage at which many related papers are listed. It is concluded that special collections are worth the extra community effort in organization, writing, and reviewing these papers.
The Magnetospheric Multiscale (MMS) mission has presented a new opportunity to study the fine scale structures and phenomena of the Earth’s magnetosphere, including cross scale processes associated with the Kelvin-Helmholtz Instability (KHI), but such studies of the KHI and its secondary processes will require a database of MMS encounters with Kelvin-Helmholtz (KH) waves. Here we present an overview of 45 MMS observations of the KHI from September 2015 to March 2020. Growth rates and unstable solid angles for each of the 45 events were calculated using a new technique to automatically detect plasma regions on either side of the magnetopause boundary. There was no apparent correlation between solar wind conditions during the KHI and its growth rate and unstable solid angle, which is not surprising as KH waves were observed downstream of their source region. We note all KHI were observed for solar wind flow speeds between 295 km/s and 610 km/s, likely due to a filtering effect of the instability onset criteria and plasma compressibility. Two-dimensional Magnetohydrodynamic (2D MHD) simulations were compared with two of the observed MMS events. Comparison of the observations with the 2D MHD simulations indicates that the new region sorting method is reliable and robust. The ability to automatically detect separate plasma regions on either side of a moving boundary and determine the KHI growth rate may prove useful for future work identifying and studying secondary processes associated with the KHI.
The Wind spacecraft is a critical element in NASA’s Heliophysics System Observatory (HSO) – a fleet of spacecraft created to understand the dynamics of the sun-Earth system – owing to the combination of its longevity (>25 years in service), its diverse compliment of instrumentation, and high resolution and accurate measurements. Wind has over 55 selectable public data products with over ~1100 total data variables (including OMNI data products) on SPDF/CDAWeb alone. These data have led to paradigm shifting results in studies of statistical solar wind trends, magnetic reconnection, large-scale solar wind structures, kinetic physics, electromagnetic turbulence, the Van Allen radiation belts, coronal mass ejection topology, interplanetary and interstellar dust, the lunar wake, solar radio bursts, solar energetic particles, and extreme astrophysical phenomena such as gamma-ray bursts. This review introduces the mission and instrument suites then discusses examples of the contributions by Wind to these scientific topics that emphasize its importance to both the fields of heliophysics and astrophysics.
Horizontal winds from four low-latitude (+/-15o) specular meteor radars (SMRs) and the MIGHTI instrument on the ICON satellite, are combined to investigate quasi-2-day waves (Q2DWs) in early 2020. SMRs cover 80-100 km altitude whereas MIGHTI covers 95-300 km. Q2DWs are the largest dynamical feature of the summertime middle atmosphere. At the overlapping altitudes, comparisons between the derived Q2DWs exhibit excellent agreement. The SMR sensor array analyses show that the dominant zonal wavenumbers are s=+2 and +3, and help resolve ambiguities in MIGHTI results. We present the first Q2DW depiction for s=+3 up to 200 km and for $s=+2$ above 95 km, and show that their amplitudes are almost invariant between 80 and 100 km. Above 106 km, Q2DW amplitudes and phases present structures that might result from the superposition of Q2DWs and their aliased secondary waves.
This paper describes a method for analyzing the kinematic properties of ions composing the solar wind. The core technology is a velocity analysis performed by dual rotating electric field (REF) units arranged coaxially in tandem, where the electric field in the downstream unit is set in the opposite direction to the upstream one. When the solar wind flies freely through the REF units, ions diverge outwards in the upstream unit and converge inwards in the downstream unit. Since the degree of diversion and conversion correspond to each ion’s velocity, ions separate into multiple groups flying through the REF units, terminate their flights on an image sensor placed on the tail end, and create sorted patterns that exhibit the velocity distribution of ions. As the REF units act on ions only by dynamic lateral electric force, the initial velocity and charge state of the ions remain invariant during the analysis process, which can be advantageous for solar wind analysis. This paper introduces a proposed instrument equipped with multiple functions, including an energy analysis, an overall velocity analysis, and a detailed ion velocity analysis. The kinematic properties of the measured ions correspond to energy levels ranging from 300 eV to 20 keV, velocities from 20 km/s to 1,900 km/s, and mass numbers from 1 to 200.