The Van Allen radiation belts are two regions encircling the Earth in which energetic charged particles are trapped inside the Earth's magnetic field. Their properties vary according to solar activity and they represent a hazard to satellites and humans in space. An important challenge has been to explain how the charged particles within these belts are accelerated to very high energies of several million electron volts. Here we show, on the basis of the analysis of a rare event where the outer radiation belt was depleted and then re-formed closer to the Earth, that the long established theory of acceleration by radial diffusion is inadequate; the electrons are accelerated more effectively by electromagnetic waves at frequencies of a few kilohertz. Wave acceleration can increase the electron flux by more than three orders of magnitude over the observed timescale of one to two days, more than sufficient to explain the new radiation belt. Wave acceleration could also be important for Jupiter, Saturn and other astrophysical objects with magnetic fields.

The dipole configuration of the Earth's magnetic field allows for the trapping of highly energetic particles, which form the radiation belts. Although significant advances have been made in understanding the acceleration mechanisms in the radiation belts, the loss processes remain poorly understood. Unique observations on 17 January 2013 provide detailed information throughout the belts on the energy spectrum and pitch angle (angle between the velocity of a particle and the magnetic field) distribution of electrons up to ultra-relativistic energies. Here we show that although relativistic electrons are enhanced, ultra-relativistic electrons become depleted and distributions of particles show very clear telltale signatures of electromagnetic ion cyclotron wave-induced loss. Comparisons between observations and modelling of the evolution of the electron flux and pitch angle show that electromagnetic ion cyclotron waves provide the dominant loss mechanism at ultra-relativistic energies and produce a profound dropout of the ultra-relativistic radiation belt fluxes.

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[1] Global images of the plasmasphere obtained by the Extreme Ultraviolet (EUV) imager on the IMAGE satellite are used to study the evolving structure of the plasmasphere during two geomagnetic disturbances. By tracking the location of the plasmapause as a function of L shell and magnetic local time, quantitative measurements of radial and azimuthal motions of the boundary are made for intervals !7 hours in duration with a time resolution of 10 min. The two cases presented are 26-27 June 2001, a relatively weak but isolated geomagnetic disturbance, and 9-10 June 2001, a moderate event with a multistaged onset and recurring substorm activity after the main disturbance. In both cases the onset of the disturbance, correlated with a southward turning of the IMF, is characterized by inward motion or erosion of the plasmapause and a smoothing of any existing azimuthal variations across the nightside. Over a period of many hours, a plasmaspheric plume forms in the afternoon sector as a result of sunward flows from dusk and corotational flows across the dayside. Azimuthal variations in the plasmapause radius tend to form in the local time sector from dawn to the western edge of the plume, including mesoscale ( 0.5 in L and 2 hours in local time) crenulations and larger-scale shoulder features, while the nightside boundary remains featureless. In the 26-27 June 2001 case, the magnetosphere entered a period of deep quiet after the main disturbance, and the plasmaspheric plume began to corotate with the main plasmasphere from the afternoon sector across the nightside. In contrast, the plume in the 9-10 June 2001 event became wrapped around the main plasmasphere and a second plume formed in the afternoon sector, perhaps due to continued substorm activity. In situ density data for these events show highly irregular density structure within the plumes as measured at geosynchronous orbit, whereas a measurement by IMAGE RPI suggests that there may be less structure near the base of the plume closer to the main plasmasphere.

[1] Remote sensing of the entire plasmasphere is routinely accomplished by the Extreme Ultraviolet (EUV) imager on the IMAGE satellite. EUV observes the helium distribution in the plasmasphere by detecting resonantly scattered solar 30.4-nm ultraviolet radiation. In EUV images the plasmapause is assumed to be the '' He + edge,'' i.e., the outermost sharp edge where the brightness of 30.4-nm He + emissions drops abruptly. This assumption is verified by comparing the L-shell of steep electron density gradients, extracted from passive mode dynamic spectrograms recorded by the IMAGE Radio Plasma Imager (RPI) when the satellite is at low magnetic latitude, with the L-shell of EUV He + edges obtained when the satellite is outside the plasmasphere near apogee. A statistical study of all inbound (dawn sector) plasmapause crossings was performed for the month of June 2001. When the plasmapause location observed by RPI is compared to the location of the He + edge extracted from the closest-in-time EUV image, a correlation coefficient of 0.83 is obtained. When the EUV He + edge location is taken as the average of two EUV measurements (one before and one after the RPI measurement), the correlation coefficient increases to 0.87. The high degree of correlation justifies the assumption that the He + edge coincides with the plasmapause. For eighteen cases in which the plasmasphere has no sharp outer boundary the intensity of the uncalibrated EUV images is compared with the electron number density extracted from the RPI data, and the lower sensitivity threshold of the EUV instrument is estimated to be 40 ± 10 electrons cm À3 .

Plasmaspheric hiss is a whistler‐mode emission that permeates the Earth's plasmasphere and is a significant driver of energetic electron losses through cyclotron resonant pitch angle scattering. The Electric and Magnetic Field Instrument Suite and Integrated Science instrument on the Van Allen Probes mission provides vastly improved measurements of the hiss wave environment including continuous measurements of the wave magnetic field cross‐spectral matrix and enhanced low‐frequency coverage. Here, we develop empirical models of hiss wave intensity using two years of Van Allen Probes data. First, we describe the construction of the hiss database. Then, we compare the hiss spectral distribution and integrated wave amplitude obtained from Van Allen Probes to those previously extracted from the Combined Release and Radiation Effects Satellite mission. Next, we develop a cubic regression model of the average hiss magnetic field intensity as a function of Kp, L, magnetic latitude, and magnetic local time. We use the full regression model to explore general trends in the data and use insights from the model to develop a simplified model of wave intensity for straightforward inclusion in quasi‐linear diffusion calculations of electron scattering rates.

Using data from the CRRES plasma wave experiment, we develop quadratic fits to the mean of the wave amplitude squared for plasmaspheric hiss as a function of Kp, L, and magnetic latitude (λ) for the dayside (6 < magnetic local time (MLT) ≤ 21) and nightside (21 < MLT ≤ 6) magnetic local time sectors. The empirical model of hiss waves is used to compute quasi-linear pitch angle diffusion coefficients for energetic, relativistic, and ultrarelativistic electrons in the energy range of 1 keV to 10 MeV. In our calculations, we account for changes in hiss wave normal angle and plasma density with increasing λ. Electron lifetimes are then calculated from the diffusion coefficients and parameterized as a function of energy, Kp, and L. Coefficients for both the hiss model and the electron lifetimes are provided and can be easily incorporated into existing diffusion, convection, and particle tracing codes.

We present the PINE (Plasma density in the Inner magnetosphere Neural network‐based Empirical) model ‐ a new empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. Utilizing the density database obtained using the NURD (Neural‐network‐based Upper hybrid Resonance Determination) algorithm for the period of 1 October 2012 to 1 July 2016, in conjunction with solar wind data and geomagnetic indices, we develop a neural network model that is capable of globally reconstructing the dynamics of the cold plasma density distribution for 2≤L≤6 and all local times. We validate and test the model by measuring its performance on independent data sets withheld from the training set and by comparing the model‐predicted global evolution with global images of He+ distribution in the Earth's plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. We identify the parameters that best quantify the plasmasphere dynamics by training and comparing multiple neural networks with different combinations of input parameters (geomagnetic indices, solar wind data, and different durations of their time history). The optimal model is based on the 96 h time history of Kp, AE, SYM‐H, and F10.7 indices. The model successfully reproduces erosion of the plasmasphere on the nightside and plume formation and evolution. We demonstrate results of both local and global plasma density reconstruction. This study illustrates how global dynamics can be reconstructed from local in situ observations by using machine learning techniques.