A Cumulant-based Analysis of Nonlinear Magnetospheric Dynamics

Johnson, Jay R. ; Wing, Simon

Princeton University. Plasma Physics Laboratory.

关键词: Solar Wind Geophysical Applications;    Forecasting;    Electromagnetic Fields;    Nonlinear Dynamics;    70 Plasma Physics And Fusion Technology;   

DOI  :  10.2172/821518
RP-ID  :  PPPL-3919
RP-ID  :  AC02-76CH03073
RP-ID  :  821518

美国|英语

来源: UNT Digital Library

【 摘 要 】

Understanding magnetospheric dynamics and predicting future behavior of the magnetosphere is of great practical interest because it could potentially help to avert catastrophic loss of power and communications. In order to build good predictive models it is necessary to understand the most critical nonlinear dependencies among observed plasma and electromagnetic field variables in the coupled solar wind/magnetosphere system. In this work, we apply a cumulant-based information dynamical measure to characterize the nonlinear dynamics underlying the time evolution of the Dst and Kp geomagnetic indices, given solar wind magnetic field and plasma input. We examine the underlying dynamics of the system, the temporal statistical dependencies, the degree of nonlinearity, and the rate of information loss. We find a significant solar cycle dependence in the underlying dynamics of the system with greater nonlinearity for solar minimum. The cumulant-based approach also has the advantage that it is reliable even in the case of small data sets and therefore it is possible to avoid the assumption of stationarity, which allows for a measure of predictability even when the underlying system dynamics may change character. Evaluations of several leading Kp prediction models indicate that their performances are sub-optimal during active times. We discuss possible improvements of these models based on this nonparametric approach.