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Solar energetic particles (SEPs) associated with shocks driven by fast coronal mass ejections (CMEs) or shocks developed by corotating interaction regions (CIRs) often extend to high energies, and are thus key elements of space weather. The PUNCH mission, set to be launched in 2025, is equipped with photometric that enables 3D tracking of solar wind structures in the interplanetary space through polarized light. Tracking techniques are used to estimate speeds and speed gradients of solar structures, including speed jumps at fast shocks. We report on a strong and a robust relation between the shock speed jump magnitude at CME and CIR shocks and the peak fluxes of associated energetic particles from the analysis of 59 CME-driven shocks and 74 CIRs observed by Wind/STEP between 1997-2023. We demonstrate that this relation, along with PUNCH anticipated observations of solar structures can be used to forecast shock-associated particle events close to the Sun; thus, advancing and providing a crucial input to forecasting of SEP fluxes in the heliosphere.

We examined the origin of 3He abundance enhancement in 23 high-energy (25-50 MeV) solar proton events that coincide with 3He-rich periods detected by ACE ULEIS in 1997-2021. In seven events, 3He enhancement was due to 3He leftover from preceding events or independent 3He events occurring during proton events. One event is the most likely impulsive (3He-rich), and another is unclear. Reaccelerated remnant flare material was the most probable cause of 3He enhancements in the remaining 14 proton events. Imaging observations showed coronal jets in the parent active regions in six of these 14 events. Remarkably, the highest 3He/4He occurred in events with jets, implying their contribution to 3He enhancement., Comment: 6 pages, 4 figures, 2 tables, accepted for publication in IAU Symposium 388 Proceedings

We investigate the East-West asymmetry in energetic storm particle (ESP) heavy ion intensities at interplanetary shocks driven by coronal mass ejections (CMEs) during solar cycles (SCs) 23 and 24. We use observations from NASA's ACE and STEREO missions of helium (He), oxygen (O), and iron (Fe) intensities from ~0.13 to 3 MeV/nucleon. We examine the longitudinal distribution of ESP intensities and the correlation of ESP intensities with the near-Sun CME speed and the average transit CME speed for eastern and western events. We observed an East-West asymmetry reversal of ESP heavy ion intensities from SC 23 to 24. We have determined that this change in asymmetry is caused by a shift in the heliolongitude distribution of the CME speed ratio (the ratio of CME near-Sun speed to CME average transit speed) from west to east.

We introduce a new multivariate data set that utilizes multiple spacecraft collecting in-situ and remote sensing heliospheric measurements shown to be linked to physical processes responsible for generating solar energetic particles (SEPs). Using the Geostationary Operational Environmental Satellites (GOES) flare event list from Solar Cycle (SC) 23 and part of SC 24 (1998-2013), we identify 252 solar events (flares) that produce SEPs and 17,542 events that do not. For each identified event, we acquire the local plasma properties at 1 au, such as energetic proton and electron data, upstream solar wind conditions, and the interplanetary magnetic field vector quantities using various instruments onboard GOES and the Advanced Composition Explorer (ACE) spacecraft. We also collect remote sensing data from instruments onboard the Solar Dynamic Observatory (SDO), Solar and Heliospheric Observatory (SoHO), and the Wind solar radio instrument WAVES. The data set is designed to allow for variations of the inputs and feature sets for machine learning (ML) in heliophysics and has a specific purpose for forecasting the occurrence of SEP events and their subsequent properties. This paper describes a dataset created from multiple publicly available observation sources that is validated, cleaned, and carefully curated for our machine-learning pipeline. The dataset has been used to drive the newly-developed Multivariate Ensemble of Models for Probabilistic Forecast of Solar Energetic Particles (MEMPSEP; see MEMPSEP I (Chatterjee et al., 2023) and MEMPSEP II (Dayeh et al., 2023) for associated papers).

The Sun continuously affects the interplanetary environment through a host of interconnected and dynamic physical processes. Solar flares, Coronal Mass Ejections (CMEs), and Solar Energetic Particles (SEPs) are among the key drivers of space weather in the near-Earth environment and beyond. While some CMEs and flares are associated with intense SEPs, some show little to no SEP association. To date, robust long-term (hours-days) forecasting of SEP occurrence and associated properties (e.g., onset, peak intensities) does not effectively exist and the search for such development continues. Through an Operations-2-Research support, we developed a self-contained model that utilizes a comprehensive dataset and provides a probabilistic forecast for SEP event occurrence and its properties. The model is named Multivariate Ensemble of Models for Probabilistic Forecast of Solar Energetic Particles (MEMPSEP). MEMPSEP workhorse is an ensemble of Convolutional Neural Networks that ingests a comprehensive dataset (MEMPSEP III - (Moreland et al., 2023)) of full-disc magnetogram-sequences and in-situ data from different sources to forecast the occurrence (MEMPSEP I - this work) and properties (MEMPSEP II - Dayeh et al. (2023)) of a SEP event. This work focuses on estimating true SEP occurrence probabilities achieving a 2.5% improvement in reliability and a Brier score of 0.14. The outcome provides flexibility for the end-users to determine their own acceptable level of risk, rather than imposing a detection threshold that optimizes an arbitrary binary classification metric. Furthermore, the model-ensemble, trained to utilize the large class-imbalance between events and non-events, provides a clear measure of uncertainty in our forecast, Comment: 17 pages, 8 figures, 1 table, accepted for publication in Space Weather journal

Solar Energetic Particles (SEPs) form a critical component of Space Weather. The complex, intertwined dynamics of SEP sources, acceleration, and transport make their forecasting very challenging. Yet, information about SEP arrival and their properties (e.g., peak flux) is crucial for space exploration on many fronts. We have recently introduced a novel probabilistic ensemble model called the Multivariate Ensemble of Models for Probabilistic Forecast of Solar Energetic Particles (MEMPSEP). Its primary aim is to forecast the occurrence and physical properties of SEPs. The occurrence forecasting, thoroughly discussed in a preceding paper (Chatterjee et al., 2023), is complemented by the work presented here, which focuses on forecasting the physical properties of SEPs. The MEMPSEP model relies on an ensemble of Convolutional Neural Networks, which leverage a multi-variate dataset comprising full-disc magnetogram sequences and numerous derived and in-situ data from various sources. Skill scores demonstrate that MEMPSEP exhibits improved predictions on SEP properties for the test set data with SEP occurrence probability above 50%, compared to those with a probability below 50%. Results present a promising approach to address the challenging task of forecasting SEP physical properties, thus improving our forecasting capabilities and advancing our understanding of the dominant parameters and processes that govern SEP production.

Extreme Ultraviolet images of the Sun are becoming an integral part of space weather prediction tasks. However, having different surveys requires the development of instrument-specific prediction algorithms. As an alternative, it is possible to combine multiple surveys to create a homogeneous dataset. In this study, we utilize the temporal overlap of SoHO/EIT and SDO/AIA 171~\AA ~surveys to train an ensemble of deep learning models for creating a single homogeneous survey of EUV images for 2 solar cycles. Prior applications of deep learning have focused on validating the homogeneity of the output while overlooking the systematic estimation of uncertainty. We use an approach called `Approximate Bayesian Ensembling' to generate an ensemble of models whose uncertainty mimics that of a fully Bayesian neural network at a fraction of the cost. We find that ensemble uncertainty goes down as the training set size increases. Additionally, we show that the model ensemble adds immense value to the prediction by showing higher uncertainty in test data that are not well represented in the training data., Comment: 20 pages, 8 figures, accepted for publication in ApJS

We study the effect of sampling windows on derived shock and associated energetic storm particle (ESP) properties in 296 fast-forward interplanetary shocks using ACE measurements at 1 au between 02/1998 - 08/2013. We vary the time windows from 2-mins to 20-mins for the shock properties and from 2-mins to 540-mins for ESP properties. Variability is quantified by the median absolute deviation (MAD) statistic. We find that the magnetic, density, and temperature compression ratios vary from their median values by 17.03%, 20.05%, 25.91%, respectively; shock speed by 16.26%, speed jump by 45.46%, Alfvenic Mach number by 31.53%, and shock obliquity by 24.25%. Spectral indices in the 2-min to 540-min windows downstream of the shock vary from the median value of 1.79 by 26.05%, and by 30.53% from the 1.70 median value upstream of the shock. Similarity of ESP spectral indices upstream and downstream of the shock suggest that these ESP populations are likely locally accelerated at the shock. Furthermore, we find that for a moving sampling window around the shock, values for the density ratio hold for ~10-mins; the magnetic ratio and shock speed jump hold for ~30-mins, and ~60-mins, respectively. Fixing the upstream window to 2-mins and moving only in the downstream direction, then the density ratio holds for ~60-mins downstream, magnetic ratio for ~30-mins, and the shock speed jump holds for ~110-mins. Beyond these time windows, derived shock properties no longer representative of shock properties. These results provide constraints for modeling and forecasting efforts of shock and ESP-associated properties.

We report on the annual variation of quiet-time suprathermal ion composition for C through Fe using Advanced Composition Explorer (ACE)/Ultra-Low Energy Isotope Spectrometer (ULEIS) data over the energy range 0.3 MeV/nuc to 1.28 MeV/nuc from 1998 through 2019, covering solar cycle 23's rising phase through Solar Cycle 24's declining phase. Our findings are (1) quiet time suprathermal abundances resemble CIR-associated particles during solar minima; (2) quiet time suprathermals are M/Q fractionated in a manner that is consistent with M/Q fractionation in large gradual solar energetic particle events (GSEP) during solar maxima; and (3) variability within the quiet time suprathermal pool increases as a function of M/Q and is consistent with the analogous variability in GSEP events. From these observations, we infer that quiet time suprathermal ions are remnants of CIRs in solar minima and GSEP events in solar maxima. Coincident with these results, we also unexpectedly show that S behaves like a low FIP ion in the suprathermal regime and therefore drawn from low FIP solar sources., Comment: Accepted in Astrophysical Journal. 19 pages, 10 figures, 4 tables

Particles measured in large gradual solar energetic particle (SEP) events are believed to be predominantly accelerated at shocks driven by coronal mass ejections (CMEs). Ion charge state and composition analyses suggest that the origin of the seed particle population for the mechanisms of particle acceleration at CME-driven shocks is not the bulk solar wind thermal material, but rather a suprathermal population present in the solar wind. This suprathermal population could result from remnant material accelerated in prior solar flares and/or preceding CME-driven shocks. In this work, we examine the distribution of this suprathermal particle population in the inner heliosphere by combining a magnetohydrodynamic (MHD) simulation of the solar wind and a Monte-Carlo simulation of particle acceleration and transport. Assuming that the seed particles are uniformly distributed near the Sun by solar flares of various magnitudes, we study the longitudinal distribution of the seed population at multiple heliocentric distances. We consider a non-uniform background solar wind, consisting of fast and slow streams that lead to compression and rarefaction regions within the solar wind. Our simulations show that the seed population at a particular location (e.g., 1 au) is strongly modulated by the underlying solar wind configuration. Corotating interaction regions (CIRs) and merged interactions regions (MIRs) can strongly alter the energy spectra of the seed particle populations. In addition, cross-field diffusion plays an important role in mitigating strong variations of the seed population in both space and energy., Comment: 20 pages, 7 figures

A Ribbon of enhanced energetic neutral atom (ENA) emissions was discovered by the Interstellar Boundary Explorer (IBEX) in 2009, redefining our understanding of the heliosphere boundaries and the physical processes occurring at the interstellar interface. The Ribbon signal is intertwined with that of a globally distributed flux (GDF) that spans the entire sky. To a certain extent, Ribbon separation methods enabled examining its evolution independent of the underlying GDF. Observations over a full solar cycle revealed the Ribbon's evolving nature, with intensity variations closely tracking those of the solar wind (SW) structure after a few years delay accounting for the SW-ENA recycling process. In this work, we examine the Ribbon structure, namely, its ENA fluxes, angular extent, width, and circularity properties for two years, 2009 and 2019, representative of the declining phases of two adjacent solar cycles. We find that, (i) the Ribbon ENA fluxes have recovered in the nose direction and south of it down to ~ 25{\deg} (for energies below 1.7 keV) and not at mid and high ecliptic latitudes; (ii) The Ribbon width exhibits significant variability as a function of azimuthal angle; (iii) Circularity analysis suggests that the 2019 Ribbon exhibits a statistically consistent radius with that in 2009. The Ribbon's partial recovery is aligned with the consensus of a heliosphere with its closest point being southward of the nose region. The large variability of the Ribbon width as a function of Azimuth in 2019 compared to 2009 is likely indicative of small-scale processes within the Ribbon., Comment: 5 figures

We examine the production of energetic neutral atoms (ENAs) in solar flares and CME-driven shocks and their subsequent propagation to 1 au. Time profiles and fluence spectra of solar ENAs at 1 au are computed for two scenarios: 1) ENAs are produced downstream at CME-driven shocks, and 2) ENAs are produced at large-scale post-flare loops in solar flares. Both the time profiles and fluence spectra for these two scenarios are vastly different. Our calculations indicate that we can use solar ENAs as a new probe to examine the underlying acceleration process of solar energetic particles (SEPs) and to differentiate the two accelertion sites: large loops in solar flares and downstream of CME-driven shocks, in large SEP events., Comment: 11 pages, updated figures and paper is accepted by ApJ

Using ion measurements from Ultra-Low-Energy Isotope Spectrometer (ULEIS) observations onboard Advanced Composition Explorer (ACE) and Solar Isotope Spectrometer (SIS) observations onboard the Solar Terrestrial Observatory (STEREO)-A and STEREO-B spacecraft, we have identified 854 3He-rich time periods between 1997 September and 2021 March. We include all event types with observed 3He enhancements such as corotating interaction regions (CIRs), gradual solar energetic particle (SEP) events, interplanetary shocks, and impulsive SEP events. We employ two different mass separation techniques to obtain 3He, 4He, Fe, and O fluences for each event, and we determine the 3He/4He and Fe/O abundance ratios between 0.32 to 0.45 MeV/nucleon and 0.64 to 1.28 MeV/nucleon. We find a clear correlation in the 3He/4He and Fe/O abundance ratios between both energy ranges. We find two distinct trends in the 3He/4He vs. Fe/O relation. For low 3He/4He values, there is a positive linear correlation between 3He/4He and Fe/O. However, at 3He/4He ~ 0.3, Fe/O appears to reach a limit and the correlation weakens significantly. We provide a live catalogue of 3He rich time periods that includes the robust determination of the onset and end times of the 3He enhancements in SEP-associated periods for different types of events observed my multiple spacecraft. This catalogue is available for public use. New releases will follow after major additions such as adding new periods from new missions (e.g., Parker Solar Probe and Solar Orbiter), identifying event types (impulsive SEP events, etc.), or adding new parameters such as remote observations detailing characteristics of the active regions., Comment: 22 pages, 9 figures, publishing in ApJ Supplemental Series

The polytropic process characterizes the thermodynamics of space plasma particle populations. The polytropic index, ${\gamma}$, is particularly important as it describes the thermodynamic behavior of the system by quantifying the changes in temperature as the system is compressed or expanded. Using Wind spacecraft plasma and magnetic field data during $01/1995 - 12/2018$, we investigate the thermodynamic evolution in 336 Interplanetary Coronal Mass Ejection (ICME) events. For each event, we derive the index ${\gamma}$ in the sheath and magnetic ejecta structures, along with the pre- and post- event regions. We then examine the distributions of all ${\gamma}$ indices in these four regions and derive the entropic gradient of each, which is indicative of the ambient heating. We find that in the ICME sheath region, where wave turbulence is expected to be highest, the thermodynamics takes longest to recover into the original quasi-adiabatic process, while it recovers faster in the quieter ejecta region. This pattern creates a thermodynamic cycle, featuring a near adiabatic value ${\gamma}$ ~ ${\gamma}$${_a}$ (=5/3) upstream of the ICMEs, ${\gamma}$${_a}$ - ${\gamma}$ ~ 0.26 in the sheaths, ${\gamma}$${_a}$ - ${\gamma}$ ~ 0.13 in the ICME ejecta, and recovers again to ${\gamma}$ ~ ${\gamma}$${_a}$ after the passage of the ICME. These results expose the turbulent heating rates in the ICME plasma: the lower the polytropic index from its adiabatic value and closer to its isothermal value, the larger the entropic gradient, and thus, the rate of turbulent heating that heats the ICME plasma., Comment: 9 pages, 3 figures

The paper presents a new method for deriving turbulent heating of the solar wind using plasma moments and magnetic field data. We develop the method and then apply it to compute the turbulent heating of the solar wind proton plasma at 1AU. The method employs two physical properties of the expanding solar wind plasma, the wave-particle thermodynamic equilibrium, and the transport of entropic rate. We analyze plasma moments and field datasets taken from Wind S/C, in order to compute (i) the fluctuating magnetic energy, (ii) the corresponding correlation length, and (iii) the turbulent heating rate. We identify their relationships with the solar wind speed, as well as the variation of these relationships relative to solar wind and interplanetary coronal mass ejection plasma., Comment: 16 pages, 12 figures

An outstanding problem in heliospheric physics is understanding the acceleration of solar energetic particles (SEP) in coronal mass ejections (CMEs) and flares. A fundamental question is whether the acceleration occurs in interplanetary space, or near the Sun. Recent work has shown that CME-driven shocks may produce SEPs while still below 5 solar radii. In this work we explore SEP acceleration during the onset of CMEs and shocks even lower in the corona, using realistic suprathermal spectra, for a selection of events. We have calculated quiet-time, pre-event suprathermal particle spectra from 1 AU observations, and scaled them back to the low corona to serve as seed spectra. For each event, AIA observations and the CASHeW framework were used to model the compressive/shock wave kinematics and its interaction with the corona. The proton acceleration was then modeled using an analytic diffusive shock acceleration model as the shock waves propagate between 1.05 and 1.3 solar radii. We demonstrate the capability of low coronal shock-related EUV waves to accelerate protons to multi-MeV energies in a matter of minutes, in the very early stages of the associated solar eruptions. We find that strong proton energization occurs for high values of the density jump, Alfven Mach number, and shock speed. In future work the results of this early-stage shock acceleration will be used to model the continued acceleration higher in the corona.

Neutral-Plasma charge exchange is a fundamental physical process that occurs ubiquitously across the universe. In geospace, charge exchange occurs in the Earth’s topside ionosphere, polar wind, plasmasphere, inner magnetosphere, and magnetosheath. Past and current space missions have profiled plasma and electromagnetic characteristics in various parts of the Earth’s magnetospheric system. However, observations of the exosphere, i.e., neutrals above 500 km altitude, are still sparse and, in some regions, non-existent, which limits our understanding of the neutral contribution to the overall dynamics of the geospace environment. Cold exospheric neutrals (< 10 eV) play an important role in the Sun-Earth interaction. Variability of exospheric density provides key information of the Earth’s atmospheric loss under dynamic space environment conditions. Various neutral species and their density variations in the polar wind can alter ion outflow patterns, modifying global magnetospheric dynamics. Exospheric neutrals also provide an energy sink for the inner magnetosphere by creating Energetic Neutral Atoms (ENAs) through charge exchange with high-energy ring current ions, which subsequently leave our geospace system unimpeded by magnetic fields. Exospheric neutrals also provide a means to observe the global interaction of the solar wind – magnetosphere, through global imaging of the system via ENAs (e.g., the TWINS and IMAGE missions) and soft X-rays (e.g., the upcoming LEXI and SMILE missions), the byproducts of neutral-plasma charge exchange. In the coming decade, we advocate that our community needs to increase our exploration of the neutral populations in the outermost reaches of the Earth’s atmosphere. It is imperative that we improve both in-situ and remote-sensing technologies for measuring key neutral species in our exosphere. We also encourage dedicated exosphere missions and to stimulate model developments of our exosphere and its interaction with the co-located magnetospheric system and neighboring Ionosphere - Thermosphere - Mesosphere system.

The acceleration of protons and electrons to high (sometimes GeV/nucleon) energies by solar phenomena is a key component of space weather. These solar energetic particle (SEP) events can damage spacecraft and communications, as well as present radiation hazards to humans. In-depth particle acceleration simulations have been performed for idealized magnetic fields for diffusive acceleration and particle propagation, and at the same time the quality of MHD simulations of coronal mass ejections (CMEs) has improved significantly. However, to date these two pieces of the same puzzle have remained largely decoupled. Such structures may contain not just a shock but also sizable sheath and pileup compression regions behind it, and may vary considerably with longitude and latitude based on the underlying coronal conditions. In this work, we have coupled results from a detailed global three-dimensional MHD time-dependent CME simulation to a global proton acceleration and transport model, in order to study time-dependent effects of SEP acceleration between 1.8 and 8 solar radii in the 2005 May 13 CME. We find that the source population is accelerated to at least 100 MeV, with distributions enhanced up to six orders of magnitude. Acceleration efficiency varies strongly along field lines probing different regions of the dynamically evolving CME, whose dynamics is influenced by the large-scale coronal magnetic field structure. We observe strong acceleration in sheath regions immediately behind the shock., Comment: 28 pages, 8 figures; Published in The Astrophysical Journal