Search for: All records

Abstract We investigate the response of outer radiation belt electron fluxes to different solar wind and geomagnetic indices using an interpretable machine learning method. We reconstruct the electron flux variation during 19 enhancement and 7 depletion events and demonstrate the feature attribution analysis called SHAP (SHapley Additive exPlanations) on the superposed epoch results for the first time. We find that the intensity and duration of the substorm sequence following an initial dropout determine the overall enhancement or depletion of electron fluxes, while the solar wind pressure drives the initial dropout in both types of events. Further statistical results from a data set with 71 events confirm this and show a significant correlation between the resulting flux levels and the average AL index, indicating that the observed “depletion” event can be more accurately described as a “non‐enhancement” event. Our novel SHAP‐Enhanced Superposed Epoch Analysis (SHESEA) method can offer insight in various physical systems. 

Electron-acoustic waves (EAWs) as well as electron-acoustic solitary structures play a crucial role in thermalization and acceleration of electron populations in Earth's magnetosphere. These waves are often observed in association with whistler-mode waves, but the detailed mechanism of EAW and whistler wave coupling is not yet revealed. We investigate the excitation mechanism of EAWs and their potential relation to whistler waves using particle-in-cell simulations. Whistler waves are first excited by electrons with a temperature anisotropy perpendicular to the background magnetic field. Electrons trapped by these whistler waves through nonlinear Landau resonance form localized field-aligned beams, which subsequently excite EAWs. By comparing the growth rate of EAWs and the phase mixing rate of trapped electron beams, we obtain the critical condition for EAW excitation, which is consistent with our simulation results across a wide region in parameter space. These results are expected to be useful in the interpretation of concurrent observations of whistler-mode waves and nonlinear solitary structures and may also have important implications for investigation of cross-scale energy transfer in the near-Earth space environment. 

Empirical models have been previously developed using the large dataset of satellite observations to obtain the global distributions of total electron density and whistler-mode wave power, which are important in modeling radiation belt dynamics. In this paper, we apply the empirical models to construct the total electron density and the wave amplitudes of chorus and hiss, and compare them with the observations along Van Allen Probes orbits to evaluate the model performance. The empirical models are constructed using the Hp30 and SME (or SML) indices. The total electron density model provides an overall high correlation coefficient with observations, while large deviations are found in the dynamic regions near the plasmapause or in the plumes. The chorus wave model generally agrees with observations when the plasma trough region is correctly modeled and for modest wave amplitudes of 10–100 pT. The model overestimates the wave amplitude when the chorus is not observed or weak, and underestimates the wave amplitude when a large-amplitude chorus is observed. Similarly, the hiss wave model has good performance inside the plasmasphere when modest wave amplitudes are observed. However, when the modeled plasmapause location does not agree with the observation, the model misidentifies the chorus and hiss waves compared to observations, and large modeling errors occur. In addition, strong (>200 pT) hiss waves are observed in the plumes, which are difficult to capture using the empirical model due to their transient nature and relatively poor sampling statistics. We also evaluate four metrics for different empirical models parameterized by different indices. Among the tested models, the empirical model considering a plasmapause and controlled by Hp* (the maximum Hp30 during the previous 24 h) and SME* (the maximum SME during the previous 3 h) or Hp* and SML has the best performance with low errors and high correlation coefficients. Our study indicates that the empirical models are applicable for predicting density and whistler-mode waves with modest power, but large errors could occur, especially near the highly-dynamic plasmapause or in the plumes. 

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. 

Hiss waves play an important role in removing energetic electrons from Earth’s radiation belts by precipitating them into the upper atmosphere. Compared to plasmaspheric hiss that has been studied extensively, the evolution and effects of plume hiss are less understood due to the challenge of obtaining their global observations at high cadence. In this study, we use a neural network approach to model the global evolution of both the total electron density and the hiss wave amplitudes in the plasmasphere and plume. After describing the model development, we apply the model to a storm event that occurred on 14 May 2019 and find that the hiss wave amplitude first increased at dawn and then shifted towards dusk, where it was further excited within a narrow region of high density, namely, a plasmaspheric plume. During the recovery phase of the storm, the plume rotated and wrapped around Earth, while the hiss wave amplitude decayed quickly over the nightside. Moreover, we simulated the overall energetic electron evolution during this storm event, and the simulated flux decay rate agrees well with the observations. By separating the modeled plasmaspheric and plume hiss waves, we quantified the effect of plume hiss on energetic electron dynamics. Our simulation demonstrates that, under relatively quiet geomagnetic conditions, the region with plume hiss can vary from L = 4 to 6 and can account for up to an 80% decrease in electron fluxes at hundreds of keV at L > 4 over 3 days. This study highlights the importance of including the dynamic hiss distribution in future simulations of radiation belt electron dynamics. 

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. 

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 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 Whistler‐mode chorus waves play an essential role in the acceleration and loss of energetic electrons in the Earth’s inner magnetosphere, with the more intense waves producing the most dramatic effects. However, it is challenging to predict the amplitude of strong chorus waves due to the imbalanced nature of the data set, that is, there are many more non‐chorus data points than strong chorus waves. Thus, traditional models usually underestimate chorus wave amplitudes significantly during active times. Using an imbalanced regressive (IR) method, we develop a neural network model of lower‐band (LB) chorus waves using 7‐year observations from the EMFISIS instrument onboard Van Allen Probes. The feature selection process suggests that the auroral electrojet index alone captures most of the variations of chorus waves. The large amplitude of strong chorus waves can be predicted for the first time. Furthermore, our model shows that the equatorial LB chorus’s spatiotemporal evolution is similar to the drift path of substorm‐injected electrons. We also show that the chorus waves have a peak amplitude at the equator in the source MLT near midnight, but toward noon, there is a local minimum in amplitude at the equator with two off‐equator amplitude peaks in both hemispheres, likely caused by the bifurcated drift paths of substorm injections on the dayside. The IR‐based chorus model will improve radiation belt prediction by providing chorus wave distributions, especially storm‐time strong chorus. Since data imbalance is ubiquitous and inherent in space physics and other physical systems, imbalanced regressive methods deserve more attention in space physics.