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Abstract While whistler‐mode waves are generated by injected anisotropic electrons on the nightside, the observed day‐night asymmetry of wave distributions raises an intriguing question about their generation on the dayside. In this study, we evaluate the distributions of whistler‐mode wave amplitudes and electrons as a function of distance from the magnetopause (MP) on the dayside from 6 to 18 hr in magnetic local time (MLT) within ±18° of magnetic latitude using the Time History of Events and Macroscale Interaction During Substorms measurements from June 2010 to August 2018. Specifically, under different levels of solar wind dynamic pressure and geomagnetic index, we conduct a statistical analysis to examine whistler‐mode wave amplitude, as well as anisotropy and phase space density (PSD) of source electrons across 1–20 keV energies, which potentially provide a source of free energy for wave generation. In coordinates relative to the MP, we find that lower‐band (0.05–0.5f_ce) waves occur much closer to the MP than upper‐band (0.5–0.8f_ce) waves, wheref_ceis electron cyclotron frequency. Our statistical results reveal that strong waves are associated with high anisotropy and high PSD of source electrons near the equator, indicating a preferred region for local wave generation on the dayside. Over 10–14 hr in MLT, as latitude increases, electron anisotropy decreases, while whistler‐mode wave amplitudes increase, suggesting that wave propagation from the equator to higher latitudes, along with amplification along the propagation path, is necessary to explain the observed waves on the dayside. 

Abstract Whistler mode waves scatter energetic electrons, causing them to precipitate into the Earth's atmosphere. While the interactions between whistler mode waves and electrons are well understood, the global distribution of electron precipitation driven by whistler mode waves needs futher investigations. We present a two‐stage method, integrating neural networks and quasi‐linear theory, to simulate global electron precipitation driven by whistler mode waves. By applying this approach to the 17 March 2013 geomagnetic storm event, we reproduce the rapidly varying precipitation pattern over various phases of the storm. Then we validate our simulation results with POES/MetOp satellite observations. The precipitation pattern is consistent between simulations and observations, suggesting that most of the observed electron precipitation can be attributed to scattering by whistler mode waves. Our results indicate that chorus waves drive electron precipitation over the premidnight‐to‐afternoon sector during the storm main phase, with simulated peak energy fluxes of 20 erg/cm²/s and characteristic energies of 10–50 keV. During the recovery phase, plume hiss in the afternoon sector can have a comparable or stronger effect than chorus, with peak fluxes of ∼1 erg/cm²/s and characteristic energies between 10 and 200 keV. This study highlights the importance of integrating physics‐based and deep learning approaches to model the complex dynamics of electron precipitation driven by whistler mode waves. 

Abstract Whistler‐mode chorus and hiss waves play an important role in Earth's radiation belt electron dynamics. Direct measurements of whistler wave‐driven electron precipitation and the resultant pitch angle distribution were previously limited by the insufficient resolution of low Earth orbit satellites. In this study, we use recent measurements from the Electron Losses and Fields INvestigation CubeSats, which provide energy‐ and pitch angle‐resolved electron distributions to statistically evaluate electron scattering properties driven by whistler waves. Our survey indicates that events with increasing precipitating‐to‐trapped flux ratios (evaluated at 63 keV unless otherwise specified) correlate with increasing trapped flux at energies up to ∼750 keV. Weak precipitation events (precipitation ratio <0.2) are evenly distributed, while stronger precipitation events tend to be concentrated atL > 5 over midnight‐to‐noon local times during disturbed geomagnetic conditions. These results are crucial for characterizing the whistler‐mode wave driven electron scattering properties and evaluating its impact on the ionosphere. 

Abstract We statistically evaluate the global distribution and energy spectrum of electron precipitation at low‐Earth‐orbit, using unprecedented pitch‐angle and energy resolved data from the Electron Losses and Fields INvestigation CubeSats. Our statistical results indicate that during active conditions, the ∼63 keV electron precipitation ratio peaks atL > 6 at midnight, whereas the spatial distribution of precipitating energy flux peaks between the dawn and noon sectors. ∼1 MeV electron precipitation ratio peaks near midnight atL > ∼6 but is enhanced near dusk during active times. The energy spectrum of the precipitation ratio shows reversal points indicating energy dispersion as a function ofLshell in both the slot region and atL > ∼6, consistent with hiss‐driven precipitation and current sheet scattering, respectively. Our findings provide accurate quantification of electron precipitation at various energies in a broad region of the Earth's magnetosphere, which is critical for magnetosphere‐ionosphere coupling. 

Abstract Whistler‐mode waves are commonly observed within the lunar environment, while their variations during Interplanetary (IP) shocks are not fully understood yet. In this paper, we analyze two IP shock events observed by Acceleration, Reconnection, Turbulence and Electrodynamics of the Moons Interaction with the Sun (ARTEMIS) satellites while the Moon was exposed to the solar wind. In the first event, ARTEMIS detected whistler‐mode wave intensification, accompanied by sharply increased hot electron flux and anisotropy across the shock ramp. The potential reflection or backscattering of electrons by the lunar crustal magnetic field is found to be favorable for whistler‐mode wave intensification. In the second event, a magnetic field line rotation around the shock region was observed and correlated with whistler‐mode wave intensification. The wave growth rates calculated using linear theory agree well with the observed wave spectra. Our study highlights the significance of magnetic field variations and anisotropic hot electron distributions in generating whistler‐mode waves in the lunar plasma environment following IP shock arrivals. 

Abstract Whistler mode waves in the plasmasphere and plumes drive significant losses of energetic electrons from the Earth's radiation belts into the upper atmosphere. In this study, we conducted a survey of amplitude‐dependent whistler wave properties and analyzed their associated background plasma conditions and electron fluxes in the plasmasphere and plumes. Our findings indicate that extremely large amplitude (>400 pT) whistler waves (a) tend to occur atL > 4 over the midnight‐dawn‐noon sectors and have small wave normal angles; (b) are more likely to occur during active geomagnetic conditions associated with higher fluxes of anisotropic electrons at 10 s keV energies; and (c) tend to occur at higher latitudes up to 20° with increasing amplitude. These results suggest that extremely large amplitude whistler waves in the plasmasphere and plumes could be generated locally by injected electrons during substorms and further amplified when propagating to higher latitudes. 

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. 

Auroral precipitation is the second major energy source after solar irradiation that ionizes the Earth’s upper atmosphere. Diffuse electron aurora caused by wave-particle interaction in the inner magnetosphere (L < 8) takes over 60% of total auroral energy flux, strongly contributing to the ionospheric conductance and thus to the ionosphere-thermosphere dynamics. This paper quantifies the impact of chorus waves on the diffuse aurora and the ionospheric conductance during quiet, medium, and strong geomagnetic activities, parameterized by AE <100, 100 < AE < 300, and AE > 300, respectively. Using chorus wave statistics and inner-magnetosphere plasma conditions from Timed History Events and Macroscale Interactions during Substorms (THEMIS) observations, we directly derive the energy spectrum of diffuse electron precipitation under quasi-linear theory. We then calculate the height-integrated conductance from the wave-driven aurora spectrum using the electron impact ionization model of Fang et al. (Geophys. Res. Lett., 2010, 37) and the MSIS atmosphere model. By utilizing Fang’s ionization model, the US Naval Research Laboratory Mass Spectrometer and Incoherent Scattar Radar (NRLMSISE-00) model from 2000s for the neutral atmosphere components, and the University of California, Los Angeles (UCLA) Full Diffusion Code, we improve upon the standard generalization of Maxwellian diffuse electron precipitation patterns and their resulting ionosphere conductance. Our study of global auroral precipitation and ionospheric conductance from chorus wave statistics is the first statistical model of its kind. We show that the total electron flux and conductance pattern from our results agree with those of Ovation Prime model over the pre-midnight to post-dawn sector as geomagnetic activity increases. Our study examines the relative contributions of upper band chorus (UBC) and lower band chorus wave (LBC) driven conductance in the ionosphere. We found LBC waves drove diffuse electron precipitation significantly more than UBC waves, however it is possible that THEMIS data may have underestimated the upper chorus band wave observations for magnetic latitudes below 65 $°$. 

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.