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Abstract We report a new population of outer belt electron acceleration events ranging from hundreds of keV to ∼1.5 MeV that occurred inside the plasmasphere, which we named “Inside Events” (IEs). Based on 6 year observations from Van Allen Probes, we compare the statistical distributions of IEs with electron acceleration events outside the plasmasphere (OEs). We find that most IEs were observed atL < 4.0 at energies below ∼1.5 MeV, with weaker acceleration ratio (<10) and larger event numbers (peaking value reaching >200), compared to stronger but less frequently occurred (peaking event numbers only reaching ∼80) OEs that were mostly observed atL > 4.0. The evolution of electron phase space density of a typical IE shows signature of inward radial diffusion or transport. Our study provides a feasible mechanism for IE, which is the results of the inward radial transport of the electron acceleration in the outer region of outer belt. 

Abstract We develop an Imbalanced Regression Artificial Neural Network model for the Auroral electrojet index (IRANNA) to predict the SuperMAG SML index, addressing the heavily imbalanced distribution of the SML data set. The data set contains mostly quiet‐time values of lesser importance and very few strong‐to‐extreme values of interest, such as those associated with super substorms. Traditional prediction models, which minimize mean squared error uniformly across the whole data set, are often skewed by this imbalance, prioritizing the lower, quiet‐time values and consequently underestimating strong geomagnetic events. The IRANNA model addresses this issue by using a customized weighting scheme in the loss function, enabling it to predict strong‐to‐extreme events accurately for the first time. The model takes solar wind parameters as inputs and predicts the logarithm of the absolute SML values. It does not rely on past values of the SML index, differentiating it from other models that use historical data for prediction. The model has demonstrated its ability to predict the peak amplitudes of strong‐to‐extreme events across various statistical analyses, event studies, and virtual experiments. Despite this success, challenges remain, particularly during localized electrojet events and when upstream solar wind data propagation is unreliable. This study emphasizes the importance of using imbalanced regression techniques, especially in space physics, where data sets are inherently skewed. It also highlights the potential of the IRANNA model to provide valuable insights into the magnetosphere's response to solar wind driving, improving space weather forecasting and offering new tools for investigating magnetospheric dynamics. 

Abstract Previous statistical studies have described the distributions and properties of whistler‐mode waves in Jupiter's magnetosphere, but explaining these wave distributions requires modeling wave propagation from their generation near the magnetic equator. In this letter, we conduct ray tracing of whistler‐mode waves based on realistic Jovian magnetic field and density models. The ray tracing results generally agree with the statistical wave distributions based on Juno measurements. The modeled ray paths show that high‐frequency waves generated near the equator are confined within 20° magnetic latitude due to Landau damping, low‐frequency waves can propagate to higher latitudes and lowerM‐shells, with changing wave normal angles, and a portion of low‐frequency waves could propagate to highMshells at high latitudes. Our modeling results provide a theoretical interpretation of whistler‐mode wave distributions and properties, providing essential insights for future radiation belt models at Jupiter. 

Abstract We perform a comprehensive investigation of the statistical distribution of outer belt electron acceleration events over energies from 300 keV to ∼10 MeV regardless of storm activity using 6‐years of observations from Van Allen Probes. We find that the statistical properties of acceleration events are consistent with the characteristic energies of combined local acceleration by chorus waves and inward radial diffusion. While electron acceleration events frequently occur both at <2 MeV atL < 4.0 and at multi‐MeV atL > 4.5, significant acceleration events are confined toL > ∼4.0. By performing superposed epoch analysis of acceleration events during storm and non/weak storm events and comparing their geomagnetic conditions, we reveal the strong correlation (>0.8) between accumulated impacts of substorms as measured by time‐integrated AL (Int(AL)) and the upper flux limit of electron acceleration. While intense storms can provide favorable conditions for efficient acceleration, they are not necessarily required to produce large maximum fluxes. 

Abstract Understanding and forecasting outer radiation belt electron flux dropouts is one of the top concerns in space physics. By constructing Support Vector Machine (SVM) models to predict storm‐time dropouts for both relativistic and ultra‐relativistic electrons overL = 4.0–6.0, we investigate the nonlinear correlations between various driving factors (model inputs) and dropouts (model output) and rank their relative importance. Only time series of geomagnetic indices and solar wind parameters are adopted as model inputs. A comparison of the performance of the SVM models that uses only one driving factor at a time enables us to identify the most informative parameter and its optimal length of time history. Its accuracy and the ability to correctly predict dropouts identifies the SYM‐H index as the governing factor atL = 4.0–4.5, while solar wind parameters dominate the dropouts at higher L‐shells (L = 6.0). Our SVM model also gives good prediction of dropouts during completely out‐of‐sample storms. 

Night-side chorus waves are often observed during plasma sheet injections, typically confined around the equator and thus potentially responsible for precipitation of ≲ 100𝑘𝑒𝑉 electrons. However, recent low-altitude observations have revealed the critical role of chorus waves in scattering relativistic electrons on the night-side. This study presents a night-side relativistic electron precipitation event induced by chorus waves at the strong diffusion regime, as observed by the ELFIN CubeSats. Through event-based modeling of wave propagation under ducted or unducted regimes, we show that a density duct is essential for guiding chorus waves to high latitudes with minimal damping, thus enabling the strong night-side relativistic electron precipitation. These findings underline both the existence and the important role of density ducts in facilitating night-side relativistic electron precipitation. 

Abstract Using particle and wave measurements from the Van Allen Probes, a 2‐D Fokker‐Planck simulation model driven by the time‐integrated auroral index (AL) value is developed. Simulations for a large sample of 186 storm‐time events are conducted, demonstrating that the AL‐driven model can reproduce flux enhancement of the MeV electrons. More importantly, the relativistic electron flux enhancement is determined by the sustained strong substorm activity. Enhanced substorm activity results in increased chorus wave intensity and reduced background electron density, which creates the required condition for local electron acceleration by chorus waves to MeV energies. The appearance of higher energy electrons in radiation belts requires a higher level of cumulative AL activity after the storm commencement, which acts as a type of switch, turning on progressively higher energies for longer and more intense substorms, at critical thresholds. 

Abstract The full spatiotemporal distribution of chorus wave‐induced relativistic electron microburst is modeled for chorus waves originated from different L shells and MLTs, based on the newly developed numerical precipitation model (Kang et al., 2022,https://doi.org/10.1029/2022gl100841). The wave‐particle interaction process that induces each microburst is analyzed in detail, and its relation to the chorus wave propagation effects is explained. The global distribution of maximum precipitation fluxes and scale sizes of relativistic microbursts is then obtained by modeling chorus waves at different L‐shells and local times. The characteristics of dawn and midnight sector microbursts have little difference, but the noon sector has much larger maximum flux and much smaller full width at half maximum, which may be due to dayside's low electron flux in the Landau resonance range. This suggests the controlling effect of keV electrons on the MeV electron precipitation intensity and properties and the overall relativistic electron loss in the outer radiation belt. 

Abstract Whistler‐mode hiss waves are crucial to the dynamics of Earth's radiation belts, particularly in the scattering and loss of energetic electrons and forming the slot region between the inner and outer belts. The generation of hiss waves involves multiple potential mechanisms, which are under active research. Understanding the role of hiss waves in radiation belt dynamics and their generation mechanisms requires analyzing their temporal and spatial evolutions, especially for strong hiss waves. Therefore, we developed an Imbalanced Regressive Neural Network (IR‐NN) model for predicting hiss amplitudes. This model addresses the challenge posed by the data imbalance of the hiss data set, which consists of predominantly quiet‐time background samples and fewer but significant active‐time intense hiss samples. Notably, the IR‐NN hiss model excels in predicting strong hiss waves (>100pT). We investigate the temporal and spatial evolution of hiss wave during a geomagnetic storm on 24–27 October 2017. We show that hiss waves occur within the nominal plasmapause, and follow its dynamically evolving shape. They exhibit intensifications with 1 and 2 hr timescale similar to substorms but with a noticeable time delay. The intensifications begin near dawn and progress toward noon and afternoon. During the storm recovery phase, hiss intensifications may occur in the plume. Additionally, we observe no significant latitudinal dependence of the hiss waves within |MLAT| < 20°. In addition to describing the spatiotemporal evolution of hiss waves, this study highlights the importance of imbalanced regressive methods, given the prevalence of imbalanced data sets in space physics and other real‐world applications. 

Abstract Using 5‐year of measurements from Van Allen Probes, we present a survey of the statistical dependence of the Earth's outer radiation belt electron flux dropouts during geomagnetic storms on electron energy and various driving parameters including interplanetary magnetic field B_z, P_SW, SYM‐H, and AE. By systematically investigating the dropouts over energies of 1 keV–10 MeV at L‐shells spanning 4.0–6.5, we find that the dropouts are naturally divided into three regions. The dropouts show much higher occurrence rates at energies below ∼100 keV and above ∼1 MeV compared to much smaller occurrence rate at intermediate energies around hundreds of keV. The flux decays more dramatically at energies above ∼1 MeV compared to the energies below ∼100 keV. The flux dropouts of electrons below ∼100 keV strongly depend on magnetic local time (MLT), which demonstrate high occurrence rates on the nightside (18–06 MLT), with the highest occurrence rate associated with northward B_z, strong P_SWand SYM‐H, and weak AE conditions. The strongest flux decay of these dropouts is found on the nightside, which strongly depends on P_SWand SYM‐H. However, there is no clear MLT dependence of the occurrence rate of relativistic electron flux dropouts above ∼1 MeV, but the flux decay of these dropouts is more significant on the dayside, with stronger decay associated with southward IMF B_z, strong P_SW, SYM‐H, and AE conditions. Our statistical results are crucial for understanding of the fundamental physical mechanisms that control the outer belt electron dynamics and developing future potential radiation belt forecasting capability.