The dynamical evolution of the radiation belts has been extensively studied since their discovery in 1959. As a result, it has been found that the radiation belt electron environment originates from a delicate balance between acceleration and loss. Therefore, a proper understanding of these mechanisms may be a key to predicting the response of the belts to geomagnetic disturbances. However, analysis of radiation belt observations present a major challenge. Satellite observations are often incomplete and inaccurate and have only limited spatial coverage. Nevertheless, through data assimilation they can be blended with information from physics-based models, in order to fill gaps and lead to a better understanding of the underlying dynamical processes. Data assimilation methods have been extensively used to analyze and predict meteorological, oceanographic, and climate processes. With the advent of space-borne observational data and the development of more sophisticated space-physics models, dynamical processes in the Earth’s radiation belts can be analyzed and assessed using data assimilation methods.
We have developed a scheme that enables efficient data assimilation from multiple satellite missions (e.g. USA NASA’s Van Allen Probes and NOAA’s GOES satellites) into the state-of-the-art partial differential equation-based model of the inner magnetosphere Versatile Electron Radiation Belt (VERB-3D). This has allowed us to reconstruct the dynamics of the inner magnetosphere and has provided a comprehensive picture of the electron radiation belts.
- Kellerman, A. C., Y. Y. Shprits, D. Kondrashov, D. Subbotin, R. A. Makarevich, E. Donovan, and T. Nagai (2014), Three-dimensional data assimilation and reanalysis of radiation belt electrons: Observations of a four-zone structure using five spacecraft and the VERB code, J. Geophys. Res. Space Physics, 119, 8764–8783, doi:10.1002/2014JA020171.
- Ni, B., Y. Y. Shprits, R. H. W. Friedel, R. M. Thorne, M. Daae, and Y. Chen (2013), Responses of Earth's radiation belts to solar wind dynamic pressure variations in 2002 analyzed using multisatellite data and Kalman filtering, J. Geophys. Res. Space Physics, 118, 4400–4414, doi:10.1002/jgra.50437.
- Shprits, Y. Y., M. Daae, and B. Ni (2012), Statistical analysis of phase space density buildups and dropouts, J. Geophys. Res., 117, A01219, doi:10.1029/2011JA016939.