Modeling and observations have shown that energy diffusion by chorus waves is an important source of acceleration of electrons to relativistic energies. By performing long-term simulations using the three-dimensional Versatile Electron Radiation Belt code, in this study, we test how the latitudinal dependence of chorus waves can affect the dynamics of the radiation belt electrons. Results show that the variability of chorus waves at high latitudes is critical for modeling of megaelectron volt (MeV) electrons. We show that, depending on the latitudinal distribution of chorus waves under different geomagnetic conditions, they cannot only produce a net acceleration but also a net loss of MeV electrons. Decrease in high-latitude chorus waves can tip the balance between acceleration and loss toward acceleration, or alternatively, the increase in high-latitude waves can result in a net loss of MeV electrons. Variations in high-latitude chorus may account for some of the variability of MeV electrons.

The Van Allen Probes mission provides unique measurements of the most energetic radiation belt electrons at ultrarelativistic energies. Simultaneous observations of plasma waves allow for the routine inference of total plasma number density, a parameter that is very difficult to measure directly. On the basis of long-term observations in 2015, we show that the underlying plasma density has a controlling effect over acceleration to ultrarelativistic energies, which occurs only when the plasma number density drops down to very low values (~10 cm-3). Such low density creates preferential conditions for local diffusive acceleration of electrons from hundreds of kilo-electron volts up to >7 MeV. While previous models could not reproduce the local acceleration of electrons to such high energies, here we complement the observations with a numerical model to show that the conditions of extreme cold plasma depletion result in acceleration up to >7 MeV.

The Earth's magnetic field traps charged particles which are transported longitudinally around Earth, generating a near-circular current, known as the ring current. While the ring current has been measured on the ground and space for many decades, the enhancement of the ring current during geomagnetic storms is still not well understood, due to many processes contributing to its dynamics on different time scales. Here, we show that existing ring current models systematically overestimate electron flux observations of 10-50 keV on the nightside during storm onset. By analyzing electron drift trajectories, we show that this systematic overestimation of flux can be explained through a missing loss process which operates in the pre-midnight sector. Quantifying this loss reveals that the theoretical upper limit of loss has to be reached over a broad region of space in order to reproduce the observations. This missing loss may be attributed to inaccuracies in the parameterization of the loss due to chorus wave interactions, combined with the scattering by electrostatic electron cyclotron harmonic waves which is currently not included in ring current models.

The hazardous plasma environment surrounding Earth poses risks to satellites due to internal charging and surface charging effects. Accurate predictions of these risks are crucial for minimizing damage and preparing for system failures of satellites. To forecast the plasma environment, it is essential to know the current state of the system, as the accuracy of the forecast depends on the accuracy of the initial condition of the forecast. In this study, we use data assimilation techniques to combine observational data and model predictions, and present the first global validation of a data-assimilative electron ring current nowcast during a geomagnetic storm. By assimilating measurements from one satellite and validating the results against another satellite in a different magnetic local time sector, we assess the global response and effectiveness of the data assimilation technique for space weather applications. Using this method, we found that the simulation accuracy can be drastically improved at times when observations are available while eliminating almost all of the bias previously present in the model. These findings contribute to the construction of improved operational models in estimating surface charging risks and providing realistic source populations for radiation belt simulations.