Assessing the magnetosphere's nonlinear behavior: Its dimension is low, its predictability, high

Abstract

The complexity of magnetospheric dynamics arises from a number of physical processes extending from the sun to the ionosphere and encompasses many space and time scales. Ground‐based and spacecraft observations have shown irregularity in magnetospheric dynamics, and their interpretation using the conventional tools such as the linear prediction filters has led to many interesting results. Recent developments in the theory of nonlinear dynamical systems that exhibit such irregular behavior have led to new techniques of reconstructing the intrinsic phase space structure using time series data. The key advantage of these techniques is their ability to yield the inherent dynamical characteristics of the system as represented in the observational data, independent of particular modeling assumptions. The basis for this approach is the realization that seemingly irregular behavior does not necessarily require a complex dynamical or statistical description, but can be understood from simple models containing nonlinearities. Thus a physical system that exhibits complex behavior may be a deterministic dynamical system with a few significant degrees of freedom. Such a possibility, among others, have led to a variety of techniques in the study of nonlinear phenomena.