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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 (>100 pT). 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. Plain Language Summary: Whistler‐mode hiss waves play a crucial role in understanding the dynamics of Earth's radiation belts, particularly scattering and loss of energetic electrons and the formation of the slot region. The underlying generation mechanisms of hiss wave sources remain an active area of research, which needs to quantify the global evolution of these waves, especially powerful ones. We developed an Imbalanced Regressive Neural Network (IR‐NN) model, which excels at accurately predicting strong hiss wave activity, that is of particular interest in radiation belt studies. We analyzed the evolution of hiss waves during a geomagnetically active period in October 2017. We found that these waves predominantly occur within the plasmapause boundary and exhibit dynamics that follow the plasmapause's changes. These waves strengthen on timescales similar to those of magnetospheric substorms, with a slight delay, and move to different local times during different phases of the storm. These waves maintain uniform intensity across low to mid‐latitudes. This study underlines the importance of imbalanced regressive methods in handling imbalanced data sets, a common challenge in space physics and related physical science fields. This approach is not only significant for advancing our understanding of space weather phenomena but also has broader implications in other areas. Key Points: An imbalanced regressive neural network model of hiss amplitude developed that predicts quiet‐time background and active‐time intense wavesHiss waves are well organized inside the plasmapause and follow its dynamic shape, evolving from dawn toward later local time during a stormModeled hiss evolution correlates with chorus, supporting the hypothesis that hiss is generated by evolving chorus waves [ABSTRACT FROM AUTHOR]

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 at L > 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. Plain Language Summary: Whistler mode waves are known as one of the primary drivers of precipitating energetic electrons from the Earth's radiation belts into the upper atmosphere. We utilize plasma wave observations from the Van Allen Probes mission and conduct a survey of whistler mode waves inside the plasmasphere and plumes, which are plasma regions surrounding the Earth and filled with high‐density cold electrons. Statistical results indicate that extremely large amplitude whistler waves are more likely to occur at large L shells (L shell is defined as the distance from magnetic field lines to the center of the Earth at the magnetic equator) in the post‐midnight sectors during active geomagnetic conditions associated with high fluxes of tens of keV electrons exhibiting anisotropic pitch angle distributions (with a flux peak in the direction that is perpendicular to the background magnetic field). These waves tend to occur at higher latitudes with increasing amplitude. Results suggest that these waves could be generated locally by injected electrons during substorm activity and may be further amplified when propagating to higher latitudes. Key Points: Van Allen Probes wave measurements are used to statistically analyze the whistler waves in the plasmasphere or plume regionsExtremely large amplitude (>400 pT) whistler waves tend to occur at L shells >4 over 0–18 hr MLT with small wave normal angles (<10°)Larger amplitude whistler waves are observed during more active substorm activities and higher magnetic latitudes [ABSTRACT FROM AUTHOR]

The effects of plasma density on the plasmaspheric hiss amplitude and its spatial and temporal scale sizes are investigated using data from Van Allen Probes A and B. The plasmaspheric hiss amplitude and scale sizes are found to be more affected by the small‐scale density variations than the overall density profile of the plasmasphere. In detail, our results suggest that both the hiss wave amplitude and its scale sizes are (a) related to the total electron density when the density is less than ∼1,000 cm−3; (b) independent of the total electron density when the density is greater than ∼1,000 cm−3; and (c) better correlated with the detrended density (removing the background plasmasphere density profile from the total electron density) regardless of the density value. Key Points: Effects of plasma density on the spatial and temporal scale sizes of plasmaspheric hiss amplitude is statistically investigatedThe plasmaspheric hiss amplitude is better correlated with the detrended electron density than the total electron densityThe spatial and temporal scale sizes of plasmaspheric hiss are mainly related to that of the relatively small‐scale density variations [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: Whistler‐mode chorus waves are essential in accelerating radiation belt electrons. However, predicting the amplitude of strong chorus waves is difficult because of their imbalanced nature. In other words, there are many more observations of no‐chorus waves than strong chorus waves. A consequence is that these no‐chorus wave data dominate traditional models, so these models usually predict values that are too small for strong waves. Using an imbalanced regressive method, we developed a machine learning (ML) model of lower‐band chorus wave amplitude. For the first time, the ML‐chorus model can predict the amplitude of strong chorus waves. The ML‐chorus model shows the evolution of the chorus wave at the equator, similar to the drift path of injected electrons, which brings electron anisotropy that generates chorus waves. The ML‐chorus model shows that the chorus waves are stronger at the equator near midnight, the source region of plasma injection. Away from midnight, the chorus waves have an equatorial minimum instead. Our chorus model will improve the forecast of the radiation belt environment by providing chorus wave distributions, especially large‐amplitude strong chorus during geomagnetic storms. Because data imbalance is commonly seen in space physics and other physical systems, imbalanced regressive methods require more attention. Key Points: A neural network model of lower‐band chorus wave amplitude is developed using imbalanced regressionFor the first time, a chorus model can predict the large amplitude of strong chorus wavesChorus' evolution is consistent with electron injection drift paths, peak equatorial amplitude near midnight, and off‐equator peaks at noon [ABSTRACT FROM AUTHOR]

We extend our database of whistler mode chorus, based on data from seven satellites, by including ∼3 years of data from Radiation Belt Storm Probes (RBSP)‐A and RBSP‐B and an additional ∼6 years of data from Time History of Events and Macroscale Interactions during Substorms (THEMIS)‐A, THEMIS‐D, and THEMIS‐E. The new database allows us to probe the near‐equatorial region in detail, revealing new features. In the equatorial source region, |λm|<6°, strong wave power is most extensive in the 0.1–0.4fce bands in the region 21–11 magnetic local time (MLT) from the plasmapause out to L∗ = 8 and beyond, especially near dawn. At higher frequencies, in the 0.4–0.6fce frequency bands, strong wave power is more tightly confined, typically being restricted to the postmidnight sector in the region 4