Abstract
Abstract. In this study we implement a data assimilation tool using a 3-D radiation belt model and an ensemble Kalman filter approach. High time and space reanalysis of the electron radiation belt fluxes is obtained over the time period 5 October to 25 October 1990 by combining sparse observations with the Salammbô 3-D model in an optimal way. The convergence of the ensemble Kalman filter is analyzed carefully. The risk of using a biased physical model is discussed and relative consequences are highlighted. Finally, a validation against CRRES data and major improvements compared to pure physics based model are presented.
Highlights
The natural energetic electron environment in the Earth’s radiation belts is of general importance as dynamic variations in this environment can impact space hardware and contribute significantly to background signals in a range of other instruments flying in that region
We describe a data assimilation tool based on the 3-D Salammbocode (Varotsou et al, 2005, 2008) and an ensemble Kalman filter (Evensen, 1994)
6 Conclusions A first data assimilation tool based on a 3-D radiation belt model, the Salammbocode, has been set up
Summary
The natural energetic electron environment in the Earth’s radiation belts is of general importance as dynamic variations in this environment can impact space hardware and contribute significantly to background signals in a range of other instruments flying in that region. Persistent two or three orders of magnitude flux intensifications of electrons with energy in the range of 0.001– 10 MeV occur regularly These observations clearly demonstrate that the relative importance of all competing physical processes involved in the radiation belt dynamics changes from storm to storm and the net result on particle distribution might be very different. In the radiation belt domain, data assimilation tools being developed so far rely on simple physical models They are in most cases 1-D, i.e. according to L∗, where only radial diffusion is considered (Naehr and Toffoletto, 2005; Koller et al, 2007; Kondrashov et al, 2007).
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