Radiation Belt Data Assimilation with an Extended Kalman Filter

Steve Naehr

Department of Physics and Astronomy
Rice University

This poster explores the application of the extended Kalman filter to specify and forecast the distribution of relativistic electrons within the Earth's radiation belts. A data assimilation algorithm is derived for a simple radiation belt forecast model driven by radial diffusion. The model assimilates particle flux measurements from spacecraft near the magnetic equatorial plane, using an external magnetic field model to calculate adiabatic invariants and phase space density. The algorithm is tested in a series of virtual experiments, with data from an idealized geomagnetic storm simulation. Compared to assimilation by direct insertion of data, the extended Kalman filter more accurately reconstructs the global particle distribution from sparse observational data. The response of the filter to errors in the observations, magnetic field model, and forecast model is examined, in anticipation of application to more realistic models and data sets.

Last Update: March 30, 2005