Reconstructing the dynamics of the outer electron radiation belt by
means of the standard and ensemble Kalman filter with the VERB-3D code
Abstract
Reconstruction and prediction of the state of the near-Earth space
environment is important for anomaly analysis, development of empirical
models and understanding of physical processes. Accurate reanalysis or
predictions that account for uncertainties in the associated model and
the observations, can be obtained by means of data assimilation. The
ensemble Kalman filter (EnKF) is one of the most promising filtering
tools for non-linear and high dimensional systems in the context of
terrestrial weather prediction. In this study, we adapt traditional
ensemble based filtering methods to perform data assimilation in the
radiation belts. We use a one-dimensional radial diffusion model with a
standard Kalman filter (KF) to assess the convergence of the EnKF.
Furthermore, with the split-operator technique, we develop two new
three-dimensional EnKF approaches for electron phase space density that
account for radial and local processes, and allow for reconstruction of
the full 3D radiation belt space. The capabilities and properties of the
proposed filter approximations are verified using Van Allen Probe and
GOES data. Additionally, we validate the two 3D split-operator Ensemble
Kalman filters against the 3D split-operator KF. We show how the use of
the split-operator technique allows us to include more physical
processes in our simulations and offers computationally efficient data
assimilation tools that deliver accurate approximations to the optimal
solution of the KF and are suitable for real-time forecasting. Future
applications of the EnKF to direct assimilation of fluxes and non-linear
estimation of electron lifetimes are discussed.