Studying Radiation Belt Electrons with Linear State-Space Models

Details Studying Radiation Belt Electrons with Linear State-Space Models Studying Radiation Belt Electrons with Linear State-Space Models

Dec 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005agufmsm12b..05r&link_type=abstract

American Geophysical Union, Fall Meeting 2005, abstract #SM12B-05

Physics

2720 Energetic Particles: Trapped, 2784 Solar Wind/Magnetosphere Interactions, 7924 Forecasting (2722), 7984 Space Radiation Environment

Scientific paper

Linear state-space models offer a compact data-derived modeling framework for describing the linear dynamics of geophysical systems. This framework is better suited to physical interpretation than traditional linear filters; it readily incorporates multiple inputs; and it allows for potential coupling between state variables in a way that is difficult if not impossible to replicate with more typical transfer function models. In this study a low-order, multi-output state-space model is combined with a subset of solar wind observations to model relativistic electron flux at altitudes measured by the SAMPEX satellite. Since unanticipated or unmeasured inputs, nonlinearities, and measurement noise almost certainly lead to sub-optimal predictions, we use a variant of the well-known Kalman Filter to help mitigate these problems through adaptive parameter identification and data assimilation. This provides better separation of external perturbations, as well as predictable stochastic variations in measured electron fluxes, from the deterministic internal dynamics of the radiation belts. The result is improved spatial interpolation (specification), and temporal extrapolation (forecast), with respect to current empirical radiation belt models used in operational settings.

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