HR: 09:00h
AN: NG41A-05    [Abstracts]
TI: An Information-Theoretical Approach that Identifies a Solar Cycle Dependence of Nonlinearity in Magnetospheric Activity
AU: Tuzla-Johnson, I N
AU: * Johnson, J R
EM: jrj@pppl.gov
AF: Princeton University, Princeton University Plasma Physics Laboratory PO Box 451 MS 28, Princeton, NJ 08525 United States
AU: Wing, S Z
EM: simon.wing@jhuapl.edu
AF: The Johns Hopkins University, Applied Physics Laboratory 11100 Johns Hopkins Road, Laurel, MD 20723 United States
AB: We discuss a method to detect nonlinear dependencies in multivariate time series using mutual information and cumulant-based cost as discriminating statistics. The method is applied to the historical data stream of the K_p index from 1932 to present. The discriminating statistics of the historical data set are compared with the discriminating statistics of surrogate data streams that share the same linear properties as the historical data set. Both discriminating measures are significantly different from the surrogates a few years prior to solar minima, while no differences are apparent at the time of solar maximum. The result suggests that the dynamics of the magnetosphere tend to be more linear at solar maximum than at solar minimum. The strong nonlinear dependencies tend to peak on a timescale around 40-50 hours and are statistically significant up to one week. Because the solar wind driver variables, VB_s and dynamical pressure exhibit a much shorter decorrelation time for nonlinearities the results seem to indicate that the nonlinearity is related to internal magnetospheric dynamics. Moreover, the timescales for the nonlinearity seem to be on the same order as that for storm/ring current transport. We suggest that the strong solar wind driving that occurs around solar maximum dominates the magnetospheric dynamics suppressing the internal magnetospheric nonlinearity. On the other hand, in the descending phase of the solar cycle just prior to solar minimum, when magnetospheric activity is weaker, the dynamics exhibit a significant nonlinear internal magnetospheric response that appears to be related to increased solar wind speed, and we discuss the physical origin of this nonlinear response. Finally, we discuss the relative merits of mutual information and cumulant based cost as discriminating statistics in the context of limited or noisy datasets.
UR: http://w3.pppl.gov/~/jrj/cumulant.html
DE: 2722 Forecasting (7924, 7964)
DE: 2784 Solar wind/magnetosphere interactions
DE: 3238 Prediction (3245, 4263)
DE: 3270 Time series analysis (1872, 4277, 4475)
DE: 4430 Complex systems
SC: Nonlinear Geophysics [NG]
MN: Fall Meeting 2005