Application of nonlinear autoregressive moving average exogenous input models to geospace: advances in understanding and space weather forecasts

摘要

The nonlinear autoregressive moving average with exogenous inputs (NARMAX)system identification technique is applied to various aspects of themagnetospheres dynamics. It is shown, from an example system, how the inputsto a system can be found from the error reduction ratio (ERR) analysis, a keyconcept of the NARMAX approach. The application of the NARMAX approach to theDst (disturbance storm time) index and the electron fluxes at geostationary Earth orbit (GEO) arereviewed, revealing new insight into the physics of the system. The review ofstudies into the Dst index illustrate how the NARMAX approach is able to finda coupling function for the Dst index from data, which was then analyticallyjustified from first principles. While the review of the electron fluxdemonstrates how NARMAX is able to reveal new insight into the physics of theacceleration and loss processes within the radiation belt.