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1. Merging Mesoscale Magnetotail Features and Ground B‐Field Perturbation Network Connectivity During Substorm Activity

   https://doi.org/10.1029/2024JA032598  

   Adewuyi, M.; Keesee, A.; Ferdousi, B. (September 2024, Journal of Geophysical Research: Space Physics)

   Abstract The connection between the magnetosphere and ionosphere is particularly dynamic during substorms. Mesoscale features in the magnetotail are consistent with substorm activity, including magnetic reconnection in the tail, flow channels, and particle injections. Observations of substorm related phenomena can be made using energetic neutral atom (ENA) imagers, in situ satellite measurements, and ground based magnetic field perturbation measurements. Analysis of the 10 October 2014 isolated substorm event is presented. Comparison of the spatial and temporal dynamics of the features seen in equatorial maps generated from ENA data are made with inner magnetosphere in situ measurements and ionospheric features with network analysis of the SuperMAG data. An MHD simulation of the event using OpenGGCM is also compared with the data. 

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2. Mesoscale Features in the Global Geospace Response to the March 12, 2012 Storm

   https://doi.org/10.3389/fspas.2021.746459  

   Adewuyi, Mayowa; Keesee, Amy M.; Nishimura, Yukitoshi; Gabrielse, Christine; Katus, Roxanne M. (October 2021, Frontiers in Astronomy and Space Sciences)

   The geospace response to coronal mass ejections includes phenomena across many regions, from reconnection at the dayside and magnetotail, through the inner magnetosphere, to the ionosphere, and even to the ground. Phenomena occurring in each region are often connected to each other through the magnetic field, but that field undergoes dynamic changes during storms and substorms. Improving our understanding of the geospace response to storms requires a global picture that enables us to observe all the regions simultaneously with both spatial and temporal resolution. Using the Energetic Neutral Atom (ENA) imager on the Two Wide-Angle Imaging Neutral-Atom Spectrometers (TWINS) mission, a temperature map can be calculated to provide a global view of the magnetotail. These maps are combined with in situ measurements at geosynchronous orbit from GOES 13 and 15, auroral images from all sky imagers (ASIs), and ground magnetometer measurements to examine the global geospace response of a coronal mass ejection (CME) driven event on March 12th, 2012. Mesoscale features in the magnetotail are observed throughout the interval, including prior to the storm commencement and during the main phase, which has implications for the dominant processes that lead to pressure buildup in the inner magnetosphere. Auroral enhancements that can be associated with these magnetotail features through magnetosphere-ionosphere coupling are observed to appear only after global reconfigurations of the magnetic field. 

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3. Substorm Identification With the WINDMI Magnetosphere ‐ Ionosphere Nonlinear Physics Model

   https://doi.org/10.1029/2024SW003960  

   Adhya, P.; Spencer, E.; Kayode‐Adeoye, M. (February 2025, Space Weather)

   Abstract We investigate the applicability and performance of the plasma physics based WINDMI model to the analysis and identification of substorm onsets. There are several substorm onset criteria that have been developed into event lists, either from auroral observations or from auroral electrojet features. Five of these substorm onset lists are available at the SuperMAG website. We analyze these lists, aggregate them and use the WINDMI model to assess the identified events, emphasizing the loading/unloading mechanism in substorm dynamics. The WINDMI model employs eight differential equations utilizing solar wind data measured at L1 by the ACE satellite as input to generate outputs such as the magnetotail current, the ring current and the field‐aligned currents (FACs). In particular, the WINDMI model current output represents the westward auroral electrojet, which is related to the substorm SML index. We analyze a decade of solar wind and substorm onset data from 1998 to 2007, encompassing 39,863 onsets. Our findings reveal a significant correlation, with WINDMI‐derived enhancements in FAC coinciding with the identified substorm events approximately 32% of the time. This suggests that a substantial proportion of substorms may be attributed to solar wind driving that results in the loading and unloading of energy in the magnetotail. 

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4. A Deep Learning‐Based Approach to Forecast the Onset of Magnetic Substorms

   https://doi.org/10.1029/2019SW002251  

   Maimaiti, M.; Kunduri, B.; Ruohoniemi, J. M.; Baker, J. B. H.; House, Leanna L. (November 2019, Space Weather)

   Abstract The auroral substorm has been extensively studied over the last six decades. However, our understanding of its driving mechanisms is still limited and so is our ability to accurately forecast its onset. In this study, we present the first deep learning‐based approach to predict the onset of a magnetic substorm, defined as the signature of the auroral electrojets in ground magnetometer measurements. Specifically, we use a time history of solar wind speed (V_x), proton number density, and interplanetary magnetic field (IMF) components as inputs to forecast the occurrence probability of an onset over the next 1 hr. The model has been trained and tested on a data set derived from the SuperMAG list of magnetic substorm onsets and can correctly identify substorms ∼75% of the time. In contrast, an earlier prediction algorithm correctly identifies ∼21% of the substorms in the same data set. Our model's ability to forecast substorm onsets based on solar wind and IMF inputs prior to the actual onset time, and the trend observed in IMFB_zprior to onset together suggest that a majority of the substorms may not be externally triggered by northward turnings of IMF. Furthermore, we find that IMFB_zandV_xhave the most significant influence on model performance. Finally, principal component analysis shows a significant degree of overlap in the solar wind and IMF parameters prior to both substorm and nonsubstorm intervals, suggesting that solar wind and IMF alone may not be sufficient to forecast all substorms, and preconditioning of the magnetotail may be an important factor. 

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5. An Anomalous Cosmic-Ray Mediated Termination Shock: Implications for Energetic Neutral Atoms

   https://doi.org/10.3847/2041-8213/acb9e0  

   Kornbleuth, M.; Opher, M.; Zank, G. P.; Wang, B. B.; Giacalone, J.; Gkioulidou, M.; Dialynas, K. (February 2023, The Astrophysical Journal Letters)

   Abstract The Voyager 2 crossing of the termination shock indicated that most of the upstream energy from the thermal solar wind ions was transferred to pickup ions (PUIs) and other energetic particles downstream of the shock. We use hybrid simulations at the termination shock for the Voyager 2, flank, and tail directions to evaluate the distributions of different ion species downstream of the shock over the energy range of 0.52–55 keV. Here, we extend the work of Gkioulidou et al., which showed an energy-dependent discrepancy between modeled and energetic neutral atom (ENA) observations, and fit distributions to a hybrid model to show that a population of PUIs accelerated via diffusive shock acceleration (DSA) to become low-energy anomalous cosmic rays (ACRs) can bridge the gap between modeled and observed ENA fluxes. Our results with the inclusion of DSA via hybrid fitting give entirely new and novel evidence that DSA at the termination shock is likely to be an important physical process. These ACRs carry a significant fraction of the energy density at the termination shock (22%, 13%, and 19% in the Voyager 2, flank, and tail directions, respectively). Using these ACRs in global ENA modeling of the heliosphere from 0.52 to 55 keV, we find that scaling factors as large as 1.8–2.5 are no longer required to match ENA observations at energies of ∼1–4 keV. Large discrepancies between modeled and observed ENAs only remain over energies of 4–20 keV, indicating that there may be a further acceleration mechanism in the heliosheath at these energies. 

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