The main objective of the NASA-NSF SWQU “A New-generation Software to Improve the Accuracy of Space Weather Predictions” effort is to develop a data-driven time-dependent model of the solar corona and heliosphere. This model will provide coronal and solar wind predictions and be made available to the public. One key component of this model is the use of a data-assimilation flux transport model to generate an ensemble of synchronic radial magnetic field maps to use as boundary conditions for the coronal field model. While flux transport models have long been established in the community, they are not open source or available for public use. We therefore are developing a new Open-source Flux Transport (OFT) software suite. The computational core of the OFT is the High-Performance Flux Transport code (HipFT). HipFT implements advection, diffusion, and data assimilation for the solar surface on a logically rectangular non-uniform spherical grid. It is written in Fortran and parallelized for use with multi-core CPUs and GPUs using a combination of OpenACC/MP directives and Fortran’s standard parallel ‘do concurrent’. To alleviate the strict time-step stability criteria for the diffusion equation, we use a Legendre polynomial extended stability Runge-Kutta super time-stepping algorithm (RKL2). The code is designed to be modular, incorporating various differential rotation, meridianal flow, super granular convective flow, and data assimilation models. Multiple realizations of the evolving flux will be computed in parallel using MPI in order to produce an ensemble of model outputs for uncertainty quantification. Here, we describe the initial implementation of the HipFT code and demonstrate its validation and performance. We use an analytic solution of surface diffusion and rigid rotational longitudinal velocity to validate the advection and diffusion implementations. We also compare realistic flux transport test problems against the established AFT flux transport code.

We report observations of a relatively long period of 3He-rich solar energetic particles (SEPs) measured by Solar Orbiter. The period consists of several well-resolved ion injections. The high-resolution STEREO-A imaging observations reveal that the injections coincide with extreme ultraviolet jets and brightenings near the east limb, not far from the nominal magnetic connection of Solar Orbiter. The jets originated in two adjacent, large, and complex active regions, as observed by the Solar Dynamics Observatory when the regions rotated into the Earth’s view. It appears that the sustained ion injections were related to the complex configuration of the sunspot group and the long period of 3He-rich SEPs to the longitudinal extent covered by the group during the analyzed time period.

Solar X-ray flares often drive coronal mass ejections and solar energetic particles (SEPs), which are key elements of space weather near the Earth and beyond. Machine learning with capability to improve space weather forecasting, prevents the adverse consequences of the space weather phenomena. We study temporal parameters of the solar X-ray flares associated with the SEP events. The temporal profile of the X-ray flare is usually divided into rising and decaying phases each approximated by a single functional representation. We observe a more complex nature of the rising and decaying phase for number of X-ray flares, which includes a pre-flare increase of intensity and a break in the decay phase. We develop a method to define, derive, and provide an optimized set of X-ray flare temporal profile parameters which takes into account the complex nature of the flare. We create a set of X-ray flare temporal properties which we next apply to the machine learning algorithms for a better forecasting of X-ray flare evolution in time and the associated SEP events.

The performance of three global magnetohydrodynamic (MHD) models in estimating the Earth’s magnetopause location and ionospheric cross polar cap potential (CPCP) have been presented. Using the Community Coordinated Modeling Center’s Run-on-Request system and extensive database on results of various magnetospheric scenarios simulated for a variety of solar weather patterns, the aforementioned model predictions have been compared with magnetopause standoff distance estimations obtained from six empirical models, and with cross polar cap potential estimations obtained from the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) Model and the Super Dual Auroral Radar Network (SuperDARN) observations. We have considered a range of events spanning different space weather activity to analyze the performance of these models. Using a fit performance metric analysis for each event, the models’ reproducibility of magnetopause standoff distances and CPCP against empirically-predicted observations were quantified, and salient features that govern the performance characteristics of the modeled magnetospheric and ionospheric quantities were identified. Results indicate mixed outcomes for different models during different events, with almost all models underperforming during the extreme-most events. The quantification also indicates a tendency to underpredict magnetopause distances in the absence of an inner magnetospheric model, and an inclination toward over predicting CPCP values under general conditions.

Whistler-mode waves have often been proposed as a plausible mechanism for pitch angle scattering and energization of electron populations in the solar wind. Theoretical work suggested that whistler waves with wave vectors parallel to the interplanetary magnetic field must counter-propagate (sunward) to the electrons for resonant interactions to occur. However, recent studies reveal the existence of obliquely propagating, high amplitude, and coherent waves consistent with the whistler-mode. Initial results from a particle tracing simulation demonstrated that these waves were able to scatter and energize electrons. That simulation was limited and did not examine a broad range of electron distributions. We have adapted the original particle tracing code for the solar wind with wave parameters observed by the STEREO satellites and to model core, halo and strahl electrons. Simulations are run to record the response of a wide initial phase space volume with uniform waves and wave packets. Using a Hamiltonian analysis, resonant responses at different harmonics of the cyclotron frequency are included in the simulation. A numerical integration scheme that combines the Hamiltonian analysis and the relativistic 3d particle tracing deployed on a high performance cluster enables accurate mapping and large-scale statistical studies of phase space responses. Observations of electron distributions from WIND at 1 AU are used for normalization. This enables extrapolations for core, halo, and strahl electrons evolution with the numerical Green’s function method. Results provide evidence for pitch angle broadening of the strahl and energization of core and halo electrons. This model can also provide results that are applicable to a number of different wave-particle interactions in the heliosphere for comparison to in-situ measurements.

The ultraviolet imager (UVI) of the Polar spacecraft and an all-sky camera at Longyearbyen contemporaneously detected an auroral vortex structure (so-called “auroral spiral”) on 10 January 1997. From space, the auroral spiral was observed as a “small spot” (one of an azimuthally-aligned chain of similar spots) in the poleward region of the main auroral oval from 18 h to 24 h magnetic local time. These auroral spots were formed while the substorm-associated auroral bulge was subsiding and several poleward-elongated auroral streak-like structures appeared during the late substorm recovery phase. During the spiral interval, the geomagnetically north-south and east-west components of the geomagnetic field, which were observed at several ground magnetic stations around Svalbard island, showed significant negative and positive bays caused by the field-aligned currents related with the aurora spiral appearance. The negative bays were reflected in the variations of local geomagnetic activity index (SML) which was provided from the SuperMAG magnetometer network at high latitude. To pursue the spiral source region in the magnetotail, we trace each UVI image along field lines to the magnetic equatorial plane of the nightside magnetosphere using an empirical magnetic field model. Interestingly, the magnetotail region corresponding to the auroral spiral covered a broad region from Xgsm ~ -40 to -70 RE at Ygsm ~ 8 to 12 RE. The appearance of this auroral spiral suggests that extensive areas of the magnetotail (but local regions in the ionosphere) remain active even when the substorm almost ceases, and geomagnetic conditions are almost stable.

Conductivity of the ionosphere allows the complex system of magnetospheric currents to flow through. Conductivity is governed by several factors including electron density and temperature, whose influence is highly dynamic during geomagnetic storm events. Thus, it is a crucial parameter that must be determined for space weather modeling to specify the coupling between the magnetosphere, ionosphere and thermosphere systems. Major sources of ionospheric conductivity are solar EUV and particle precipitation which includes Diffuse (Diff.), Monoenergetic (ME) and Broadband (BB) precipitations. Conductance Σ is the height integrated version of conductivity. Empirically, total ionospheric conductance (Hall and Pedersen) is known to be the root sum square of individual conductance terms [Wallis and Budzinski, 1981], considering that conductivity resulting from different processes are not linearly additive and corresponding ionization rates shall be added at each altitude and then integrated over the desired altitude range. With the inclusion of the less energetic broadband precipitation that was found to cause ionization in the bottom-side F region, the expression for the total ionospheric conductance was modified by the linear addition of the contribution of the broadband precipitation to the total Hall and Pedersen conductance[Zhang et al., 2015].In this study, using a 3-dimensional global physics based model GITM (Global Ionosphere Thermosphere Model), the validity of this combination of vector and linear addition of individual source terms to the total ionospheric conductance is examined and the more accurate expression for the summation of sources contributing to the total conductance is quantified. GITM is employed to calculate the Hall and Pedersen conductance using the average energy, potential and energy flux for each of the sources of conductance. Several scenarios are simulated where the different sources of precipitation are paired with solar EUV radiation, and the total conductance is obtained. Linear and vector summation of conductance resulting from combinations of sources and individual sources indicate that the contribution of broadband precipitation to the total conductance also follows vector addition. To quantify the result that the total conductance is the vector sum of individual sources, error histograms are plotted and a set of metrics including RMSE, mean error, standard deviation, correlation coefficient and fractional error are enumerated for both linear and vector summation of individual sources to produce the total conductance.

Acquiring quantitative metrics-based analysis regarding the performance of most first-principle space physics modeling approaches is key in understanding the solar and space weather. As established by the successive the Geospace Environment Modeling Challenges, quantification of performance help set a precedent in understanding the science behind the various phenomena observed naturally in addition to elucidating the merits and demerits of a space weather prediction method. In this study, the performance of three magnetohydrodynamic models (SWMF/BATS-R-US, LFM and OpenGGCM) in estimating the Earth’s magnetopause location and the ionospheric cross polar cap potential (CPCP) have been studied. Using the Community Coordinated Modeling Center’s Run-on-Request system and extensive database on results of various magnetospheric scenarios run during a variety of solar weather patterns, the aforementioned model predictions have been compared with magnetopause standoff distance estimations obtained from six empirical models, and with cross polar cap potential estimations obtained from AMIE and SuperDARN. The events considered in this study contain a spectrum of possibilities – solar storms, substorms, constant solar wind events, which have been categorized using the Kp index as high, moderate and low magnitude solar events. Several of these storms have been well documented as part of the Geospace Environment Modeling (GEM) Challenges and other studies. The root-mean-square difference (RMS), prediction efficiency (PE) and maximum amplitude (Max Amp) metrics are used to quantify the model performances for the solar events considered. A separate metric called Wrong Prediction (WP) has also been used to study the models’ hit and miss rates with the empirical data. While almost all the cases considered for the magnetopause standoff distances have a satisfactory performance, there is huge deviation for the CPCP data both in the physics based models and the empirical data. The metric data is therefore valid for the magnetopause location comparisons, while not being that thorough for the CPCP comparative study.

Estimation of the ionospheric conductance is a crucial step in coupling the magnetosphere & ionosphere (MI). Since the high-latitude ionosphere closes magnetospheric currents, conductance in this region is pivotal to examine & predict MI coupling dynamics, especially during extreme events. In spite of its importance, only recently have impacts of key magnetospheric & ionospheric contributors affecting auroral conductance (e.g., particle distribution, ring current, anomalous heating, etc.) been explored using global models. Addressing these uncertainties require new capabilities in global magnetosphere - ionosphere - thermosphere models, in order to self-consistently obtain the multi-scale, dynamic sources of conductance. This work presents the new MAGNetosphere - Ionosphere - Thermosphere (MAGNIT) auroral conductance model, which delivers the requisite capabilities to fully explore the sources of conductance & their impacts. MAGNIT has been integrated into the Space Weather Modeling Framework to couple dynamically with the BATSRUS magnetohydrodynamic (MHD) model, the Rice Convection Model (RCM) of the ring current, the Ridley Ionosphere Model (RIM) & the Global Ionosphere Thermosphere Model (GITM). This new model is used to address the precise impact of diverse conductance contributors during geomagnetic events. First, the coupled MHD-RIM-MAGNIT model is used to establish diffuse & discrete precipitation using kinetic theory. The key innovation is to include the capability of using distinct particle distribution functions (PDF) in a global model: in this study, we explore precipitation fluxes estimated using isotropic Maxwellian & Kappa PDFs. RCM is then included to investigate the effect of the ring current. Precipitating flux computed on closed field lines by RCM is compared against MAGNIT results, to show that expected results are alike. Lastly, GITM is coupled to study the impact of the ionosphere thermosphere system. Using the MAGNIT model, aforementioned conductance sources are progressively applied in idealized simulations & compared against the OVATION Prime Model. Finally, data-model comparisons against SSUSI, AMPERE & SuperMAG measurements during the March 17, 2013 Storm are shown. Results show remarkable progress of conductance modeling & MI coupling layouts in global models.

Solar flares may be the best-known examples of the explosive conversion of magnetic energy into bulk motion, plasma heating, and particle acceleration via magnetic reconnection. The energy source for all flares is the highly sheared magnetic field of a filament channel above a polarity inversion line (PIL). During the flare, this shear field becomes the so-called reconnection guide field (i.e., the non-reconnecting component), which has been shown to play a major role in determining key properties of the reconnection including the efficiency of particle acceleration. We present new high-resolution, three-dimensional, magnetohydrodynamics simulations that reveal the detailed evolution of the magnetic shear/guide field throughout an eruptive flare. The magnetic shear evolves in three distinct phases: shear first builds up in a narrow region about the PIL, then expands outward to form a thin vertical current sheet, and finally is transferred by flare reconnection into an arcade of sheared flare loops and an erupting flux rope. We demonstrate how the guide field may be inferred from observations of the sheared flare loops. Our results indicate that initially the guide field is larger by about a factor of 5 than the reconnecting component, but it weakens by more than an order of magnitude over the course of the flare. Instantaneously, the guide field also varies spatially over a similar range along the three-dimensional current sheet. We discuss the implications of our results for understanding observations of flare particle acceleration.

Electric fields are generally measured or calculated using two intuitive assumptions: (1) the electric field equals the voltage divided by the antenna length when the antenna is electromagnetically short, (2) the antenna responds best to electric field along its length. Both assumptions are often incorrect for electrostatic fields because they scale as the Debye length or as the electron gyroradius, which may be smaller than the antenna length. Taking into account this little-known fact enables us to complete or correct several recent papers on plasma spontaneous fluctuations in various solar system environments.

The Heliophysics Application Programmer’s Interface (HAPI) is a standard mechanism for accessing time series data. Because of its adoption at multiple Heliophysics (HP) and Space Weather (SW) data centers, it is now a useful way to reach many different resources within the community. It is also a COSPAR standard. The use of HAPI so far has been as a standard layer on top of a traditional mission or instrument archive, where HAPI lives alongside an existing, custom web-based computer interface. We will give highlights of recent additions to the specification which is now at version 3.0, with 3.1 around the corner. We also will present explorations into two new ways in which HAPI can be utilized. 1) HAPI as a way to access output from model runs, which can generate large volumes of data at various time cadences and spatial distributions. 2) HAPI as an interface over cloud-based data resources. In the cloud, HAPI can connect large volumes of data to scientist-friendly front-end analysis capabilities, such as a JupyterHub or potentially a Pangeo-like environment. The evolution of HAPI and its uses is expected to keep enhancing interoperability among Heliophysics and Space Weather resources.

In this talk, I will draw distinction between linear plasma waves and strong turbulent fluctuations and argue general characteristics of 3He rich solar energetic particle events favor the scenario that 3He ions are mostly energized via cyclotron resonance with proton cyclotron waves. These waves can be produced via magnetic reconnection at the ion diffusion scale and/or via cascade of turbulence energy from low to high frequencies. Both PIC and hybrid simulations can be used to verify these scenarios.

In the field of Astrobiology, a quantitative approach has not been made to predict the number of extraterrestrial intelligent civilizations that may have existed on a habitable exoplanet as well their corresponding properties, such as intelligence, lifespan, and recovery time. Prior research indicates that numerous planetary systems within the Milky Way Galaxy are of over six billion years in age, implying many exoplanets, if sustainable to life, may have had several cycles of civilizations emergence and self-destruction, suggesting the ruins of advanced civilizations should be commonplace within the galaxy. We investigate this problem by utilizing statistical algorithmic simulations to predict and estimate the number of civilizations (both future and extinct) that may arise within an exoplanetary continuum, further generating the accompanying characteristics of said civilizations. Within the model, factors such as self-induced extinction/destruction, natural civilization decay, planetary disasters, and civilization rediscovery have been incorporated to examine the pathways a civilization can encounter. Our results corroborate the notion that on many of the older exoplanets in our galaxy, civilizations may have existed, however most have ultimately died out within a short period, further limiting the search for current extraterrestrial intelligence, but strengthening the approach of interstellar archeology.

We present in-situ ion composition and velocity measurements from the Enhanced Polar Outflow Probe during the August 2017 solar eclipse, which crossed the path of totality at ~640 km altitude within 10 minutes of totality passing. These measurements reveal two distinct H+ ion populations, and show a ~40% decrease in topside plasma density, a similar drop in upward but not downward H+ ion flux, and a downward O+ ion velocity of ~100 m/s. These features are directly linked to changes in the H+/O+ composition and field-aligned or interhemispheric light ion flow, and reduction in the negative spacecraft potential. These observed features were absent on the preceding, non-eclipse days, and corroborate the reduction in F-region plasma density and topside Total Electron Content (TEC) observed by the Global Position System (GPS) receivers onboard. They are attributed to the temporary reduction of photoionization in the eclipsed F-region.

The Heliospheric Imagers on board NASAs twin STEREO spacecraft show that coronal mass ejections (CMEs) can be visually complex structures. To explore this complexity, we created a web-based citizen science project in collaboration with the UK Science Museum, in which participants were shown pairs of differenced CME images, taken by the inner cameras of the Heliospheric Imagers (HI-1) on board the twin NASA STEREO spacecraft between 2008 and 2016. Participants were asked to decide which image in each pair appeared the most complicated. 4,028 volunteers conducted 246,692 comparisons of 20,190 image pairs, with each pair being classified by 12 independent users. A Bradley-Terry model was then applied to these data to rank the CMEs by their visual complexity. This complexity ranking revealed that the annual average visual complexity values follow the solar activity cycle, with a higher level of complexity being observed at the peak of the cycle, and the average complexity of CMEs observed by HI1-A was significantly higher than the complexity of CMEs observed by HI1-B. Visual complexity was found to be associated with CME size and brightness, but the differences between HI1-A and HI1-B images suggest that complexity may be influenced by the scale-sizes of structure in the CMEs. Whilst it might not be surprising that the complexity observed in these CME images follows the trend observed in sunspots and the solar cycle; these results demonstrate that there is a quantifiable change in the structure of CMEs seen in the inner heliosphere.

While flagship missions such as CHAMP and GOCE have shown us with accelerometer measurements that the thermospheric density in Low Earth Orbit (LEO) can increase by more than 200% during enhanced geomagnetic activity, current empirical models, such as those of the MSISE and Jacchia families, as well as the Drag Temperature Model, fail to reproduce this behavior, limiting the ability to perform orbit prediction and space situational awareness. Several methods have been employed to address this dilemma. One is the High-Accuracy Satellite Drag Model (HASDM), which uses its Dynamic Calibration Atmosphere to employ differential correction across 75 spherical calibration satellites to generate correction parameters to the density that are related to 10.7 cm solar radio flux and ap (Storz et al. 2005). Doornbos et al. 2008 has implemented a method that estimates height-dependent scale factors to the densities from empirical models with respect to densities directly derived from two- line element sets (TLEs). HASDM’s reliance on Space Surveillance Network observations limit its accessibility and detail, and Doornbos’ methods are limited by the fact that TLEs are mean elements; densities derived from them are subject to errors due to smoothing over an entire orbit. In addition, the method of deriving densities from TLEs was initially done only to provide inputs to the SGP4 orbital propagator, which was initially developed without consideration of solar radiation pressure on the trajectory of modeled spacecraft. We present a method to generate new model densities during geomagnetic storms by using an in-house orbital propagator, the Spacecraft Orbital Characterization Kit (SpOCK). This method estimates and applies scale factors to F10.7 and a p to minimize orbit propagation errors with TLEs. The method is tested on a variety of satellites, including CHAMP, GOCE, and the CubeSats of the QB50 and FLOCK constellations. This method proposes to grant insight into storm-time thermospheric density enhancement by modeling the effects of storms on the drag of numerous LEO spacecraft, increasing our understanding of thermospheric dynamics and granting us improved tools for space traffic management and thermospheric research.

Loss mechanisms act independently or in unison to drive rapid loss of electrons in the radiation belts. Electrons may be lost by precipitation into the Earth’s atmosphere, or through the magnetopause into interplanetary space; a process known as magnetopause shadowing. Whilst magnetopause shadowing is known to produce dropouts in electron flux, it is unclear if shadowing continues to remove particles in tandem with electron acceleration processes, limiting the overall flux increase. We investigated the contribution of shadowing to overall radiation belt fluxes throughout a geomagnetic storm starting on the 7 September 2017. We use new, multi-spacecraft phase space density calculations to decipher electron dynamics during each storm phase and identify features of magnetopause shadowing during both the net-loss and the net-acceleration storm phases. We also highlight two distinct types of shadowing; ‘direct’, where electrons are lost as their orbit intersects the magnetopause, and ‘indirect’, where electrons are lost through ULF wave driven radial transport towards the magnetopause boundary.

One of the most important steps in any AI/ML application is the pre-processing of the data. The objective of this step is to project the original data in a new basis, or in a new latent space, where the different features of the problem are comparable and where their distribution covers a large range of values. Using the data in its natural basis can lead to under-performing AI/ML models. While almost all papers in our domain are careful to normalize or standardize the data, it is less frequent to see the use of simple linear PCA transformations, and even less frequent the use of more complex non-linear projections in latent spaces. Here we show how our research team is using autoencoder neural networks to perform non-linear transformations of images, simulations and time-series used in heliophyisical applications. Autoencoder transformations allow to parametrize any type of data by projecting it onto a latent space of higher or lower dimension. In these latent spaces the transformed data commonly presents better statistical properties allowing improvements in the AI/ML modeling. In addition, autoencoders are also known as generative techniques, i.e. they can be used to produce “artificial” or “synthetic” data. We will present three particular examples of the use of autoencoders: 1) parametrization of solar wind observations using standard feed forward autoencoders, 2) parametrization of magnetosphere simulations using convolutional autoencoders, and 3) parametrization and generation of solar active regions using variational convolutional autoencoders. We will show how these parametrizations can then be used for AI/ML classification and forecasting. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776262 (AIDA).

We propose a new technique for energizing coronal magnetic equilibria toward eruptions. We achieve this via a sequence of MHD relaxations of small line-tied pulses of magnetic helicity, each of which is simulated by a suitable rescaling of the current-carrying part of the field. The whole procedure is ‘magnetogram-matching’ because it involves no changes to the normal component of the field at the lower boundary. The technique is illustrated by application to bipolar force-free configurations whose magnetic flux ropes (MFRs) are modeled with our regularized Biot-Savart law method. We have found that, in spite of the bipolar character of the ambient potential field in these examples, the resulting MFR eruption is generally sustained by two reconnection processes. The first, which we refer to as breakthrough reconnection, is analogous to breakout reconnection in quadrupolar configurations. It occurs at a quasi-separator field line located inside the current layer that wraps around the erupting MFR, and results from taking into account the line-tying effect at the photosphere. The second process is the classical tether-cutting reconnection that develops at the second quasi-separator inside a vertical current layer formed below the erupting MFR. Both reconnection processes work in tandem to propel the MFR through the overlying ambient field. The considered examples suggest that our technique will be beneficial for both the modeling of particular eruptive events and theoretical studies of eruptions in idealized magnetic configurations. This research was supported by NASA programs HTMS (award no. 80NSSC20K1274) and HSR (80NSSC19K0858 and 80NSSC20K1317); NASA/ NSF program DRIVE (80NSSC20K0604); and NSF grants AGS-1923377 and ICER-1854790.

Interplanetary shocks have been long known sources of suprathermal and energetic ions, and their origin will contribute in unveiling the origin of cosmic rays. Sudden ion intensity enhancements in the form of spikes that last anywhere between minutes to tens of seconds are observed during the passage of such shocks. Identification of spikes with peak intensities lasting ~1 min surveyed in over 304 shocks from January 2007 – December 2014 observed by the SEPT (Solar Electron and Proton Telescope) onboard STEREO (Solar Terrestrial Relations Observatory) A/B Spacecraft was performed using a new Python Code, followed by visual inspection. We also inspected the database of EPAM (Electron, Proton, and Alpha Monitor) onboard ACE (Advanced Composition Explorer) from 2003 to 2014. We present and discuss the statistical analysis of the shock spikes as a function of parameters such as shock normal angle and Mach number. The Python code can be used to analyse other databases such as WIND and this further paves the way for the employment of ML techniques to replace visual inspection. Such studies are vital in performing exhaustive and in-depth assessment of shock associated particle events.

We report observations of a Bursty Bulk Flow (BBF) penetrating to the outer edge of the radiation belt. The turbulent BBF braking region is characterized by ion velocity fluctuations, magnetic field (B) variations, and intense electric fields (E). In this event, energetic (>100 keV) electron and ion fluxes are appreciably enhanced. Importantly, fluctuations in energetic electrons and ions suggest that they are locally energized. Using correlation distances and other observed characteristics of turbulent E, test-particle simulations support that local energization by E favors higher-energy electrons and leads to an enhanced energetic shoulder and tail in the electron distributions. The energetic shoulder and tail can be amplified to MeV energies by adiabatic transport into the radiation belt where |B| is higher. This analysis suggests that turbulence generated by BBFs can, in part, supply energetic particles to the outer radiation belt and that turbulence can be a significant contributor to particle acceleration.

Flare suprathermal ions with enhanced 3He and heavy-ion abundances are an essential component of the seed population accelerated by CME-driven shocks in gradual solar energetic particle (GSEP) events. However, the mechanisms through which CME-driven shocks gain access to flare suprathermals and produce spectral and abundance variations in GSEP events remain largely unexplored. We report two recent GSEP events: one observed by Solar Orbiter on 2020 Nov 24 (the first GSEP event on Solar Orbiter) and the other by ACE on 2021 May 29 (the most intense GOES proton event in the present solar cycle). The events were preceded by impulsive SEP (ISEP) events. Abundances and energy spectra are markedly different in the examined events at < 1 MeV/nucleon. For example, in the May event, Fe/O is typical of ISEP events, a factor of 100 to 10 higher than Fe/O in the November event. 3He abundance in the November event is high, typical of ISEP events, while in the May event, it is much lower, though finite. The May event shows a hard 4He spectrum with a power-law index of −1.6, and the November event a soft spectrum with an index of −3.5. The events were associated with halo CMEs with speeds around 900 km/s. The November event was also measured by Parker Solar Probe and the May event by STEREO-A and Solar Orbiter. This paper discusses the origin of vastly different abundances and spectral shapes in terms of variable remnant population from preceding ISEP events. Furthermore, we discuss a possible direct contribution from parent flares.

We perform a statistical study of 3-s ultra-low frequency (ULF) waves using MMS observations in the Earth’s foreshock region. The average phase velocity in the plasma rest frame is determined to be anti-sunward, and the intrinsic polarization is right-handed. We further examine the linear instability conditions based on drift-bi-Maxwellian distribution functions according to observed plasma conditions. The resulting instability is a solution to the common dispersion equation of the ion/ion right-hand non-resonant and left-hand resonant instabilities. The predicted wave propagation is also predominantly anti-sunward. The cyclotron resonant conditions of the solar wind and backstreaming beam ions are evaluated, and we find that in some cases, the anti-sunward propagating waves can be resonant with beam ions, which was overlooked in previous studies. The result suggests that the dispersion equation provides the 3-s ULF waves a fundamental explanation that unifies a rich variety of resonant conditions. In the later stage, the 3s ULF waves could further develop into Short Large Amplitude Magnetic Structures, contributing to the turbulence in the foreshock region.