Studying Radiation Belt Electrons with Adaptive Linear State-Space Models

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

May 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005agusmsm41a..06r&link_type=abstract

American Geophysical Union, Spring Meeting 2005, abstract #SM41A-06

Physics

2720 Energetic Particles, Trapped, 2722 Forecasting, 2753 Numerical Modeling, 2784 Solar Wind/Magnetosphere Interactions

Scientific paper

Linear state-space models offer a compact and flexible data-derived dynamical modeling framework for describing the coupled multi-output linear response of geophysical systems like the Earth's electron radiation belts. Unlike more traditional finite impulse response (FIR) linear filters, they effectively separate external perturbations from internal dynamics. In addition, when recent observations of the modeled system are available for comparison, prediction residuals, or innovations, can be filtered through an optimal gain matrix to further refine model output. This stochastic addition to the state-space model can reproduce persistent correlated structure in radiation belt observations that is unrelated to the external solar wind drivers. We use this so-called innovations form state-space model to more closely study both the temporal and spatial evolution of the deterministic radiation belt response to multiple solar wind inputs. A variant of the well-known Extended Kalman Filter (EKF) is used to determine time-varying linear coefficients for this model, thus providing additional flexibility that accounts for some portion of the nonlinear radiation belt response that cannot be modeled with time-stationary linear state-space models alone.

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