Reanalysis of Long Term Radiation Belt Electron Fluxes Relying on Four Spacecraft, the VERB Code, and a Sequential Kalman Filter

The dynamical evolution of the radiation belts has been a subject of extensive research since their discovery in 1959. After decades of study, it is now known that they experience significant changes due to acceleration, loss and transport of particles trapped in the Earth's magnetic field. Since high-energy electrons can potentially cause spacecraft anomalies and damage satellite hardware, understanding and predicting fluxes in the radiation belts is of great importance to satellite operators, engineers, and designers.

Nevertheless, analysis of radiation belt observations still presents major challenges. Satellite measurements are often restricted to a limited range of L-shells, pitch angles, and energies. Moreover, particle fluxes vary on short time scales, and observations from a single spacecraft do not allow for measuring the temporal variations on time scales shorter than the spacecraft orbital period. Analysis is further complicated by the fact that measurements are contaminated by errors, which are different for various instruments. As a consequence, to fill the spatiotemporal gaps and to understand the dominant physical processes in the radiation belts, observations can be combined with physics based dynamical models in an optimal way by means of data assimilation.

In this study we implement a data assimilation tool using a sequential split operator Kalman filter approach. Reanalysis of electron radiation belt fluxes is obtained over the period 2012 to 2016 by combining sparse observations from the Van Allen Probes spacecraft and the GOES 13 and 15 satellites with the 3D Versatile Electron Radiation Belt (VERB) code. At first, radial profiles of electron fluxes are reconstructed, and the innovation vector is analyzed to show how the data is correcting for physical mechanisms absent in the model. Such processes (mixed pitch angle - energy diffusion, losses to the magnetopause, and scattering by EMIC waves) are then added in the reanalysis, and a validation against LANL GPS data is presented. Finally, major improvements with respect to the pure physics based model are discussed. It is demonstrated that the 3D data assimilative code provides a comprehensive picture of the radiation belts and is an important step toward performing reanalysis using observations from current and future missions.