Quantifying the Spatiotemporal Evolution of Radiation Belt Electrons Scattered by Lower Band Chorus Waves: An Integrated Model

Wave particle interactions are very important to understand the intricate evolution of the Earth's radiation belt electrons. Kinetic simulations, in terms of solving the Fokker-Planck equation based on the quasilinear theory, are usually used to simulate the radiation belt electron dynamic evolution. However, the global wave and plasma density distributions adopted in the kinetic simulations are very difficult to be directly obtained by satellites. Here we present a new model, by integrating the machine learning technique and kinetic simulations, to analyze the spatiotemporal evolution of radiation belt electrons scattered by lower band chorus (LBC). Compared to the observations, our integrated model produces effectively the global distribution of plasmapause location, plasma density, and LBC intensity, and assesses quantitatively the scattering effect driven by LBC waves at different magnetic local times (MLT), L-shell (the Mcllwain L-parameter), and time. Incorporating the effect of radiation electron drift, we further use the 2-D Fokker-Planck equation to simulate the variations of electron phase space density in different MLT sectors at a fixed L, and find that the integrated model replicates reasonably the multi-MeV electron acceleration at L = 4.5 during the period from the main phase to the early recovery phase of the storm. Our results demonstrate that such an integrated model, on basis of a combination of the machine learning technique and kinetic simulations, provides valuable means for improved understanding of the global dynamic evolution of the Earth's radiation belt electrons. Understanding the complex behavior of electrons in Earth's radiation belts, including acceleration, loss, and transport, is crucial for space weather research. This study introduces an integrated model that combines machine learning technique and kinetic simulation to quantitatively analyze how lower band chorus (LBC) waves influences electrons during the 17 March 2015 storm. Through comparisons with observations, our results indicate that the integrated model effectively reproduces global distribution of plasmapause location, plasma density, and LBC intensity, and enables a quantitative assessment of how LBC affects electrons over space and time, closely matching observations during the main phase to the early recovery phase of the storm. Incorporating electron drift motion improves the spatial resolution of simulated electron behavior, particularly impacting the simulation of the tens of keV electron behavior during periods of strong LBC intensity. This integrated approach can enhance our understanding of the radiation belt electron dynamics. A numerical model integrating machine learning technique and kinetic simulations is developed to study the wave-driven electron scattering Machine learning technique provides inputs for kinetic simulations, allowing the wave-driven evolution to be estimated The integrated model reproduces effectively the multi-MeV electron acceleration during a strong geomagnetic storm