A hierarchy moment approach to the analysis and forecasting of linear-nonlinear propagation

This work is concerned with a new method for extracting inbred linear-nonlinear coupled differential equations from multivariate discrete time series data and is applied to f₀F2 forecasting. It is assumed that the solution of the coupled ordinary differential equations can be represented as a multivariate Volterra functional expansion. A tractable hierarchy of moment equations is generated by operating on a suitably truncated Volterra functional expansion. The hierarchy facilitates the calculation of the coefficients of the coupled differential equations. A dynamic global mid-/high-magnetic latitude ionospheric model is developed which can characterise nonlinear phenomena such as period doubling and quenching occurrences