HR: 0830h
AN: SM31B-1109    [PDF]
TI: Forecasting Magnetospheric Dynamics Using Solar Wind Measurements: Role of Global and Multi-Scale Processes
AU: * Ukhorskiy, A Y
EM: aleksandr.ukhorskiy@jhuapl.edu
AF: JHU APL, Applied Physics Laboratory 11100 Johns Hopkins Road MS MP3-E116, Laurel, MD 20723 United States
AU: Sitnov, M I
EM: sitnov@umd.edu
AF: University of Maryland, University of Maryland College Park, MD, MD 20742 United States
AU: Sharma, S A
EM: ssh@astro.umd.edu
AF: University of Maryland, University of Maryland College Park, MD, MD 20742 United States
AU: Papadopoulos, D
AF: University of Maryland, University of Maryland College Park, MD, MD 20742 United States
AB: Earth's magnetosphere is a nonlinear spatially extended system which is driven far from the equilibrium by the turbulent solar wind. On the global scales the magnetospheric dynamics appear to be well organized and coherent and therefore allow deterministic considerations. However, on the smaller scales it exhibits scale-invariant behavior which is retained over a wide range of spatial and temporal scales. These multi-scale features do not reveal low effective dimension and therefore can not be predicted dynamically. At the same time, the input-output statistical analysis shows that the scale-free properties of magnetospheric dynamics are strongly affected by the solar wind and therefore can be described in terms of conditional probability. This allows constructing a unified data-derived model of solar wind - magnetosphere coupling which combines the elements of nonlinear dynamical approach with Bayesian consideration of statistical physics. It yields deterministic predictions of the global component of the dynamics and probabilistic predictions of its multi-scale features.
DE: 2744 Magnetotail
DE: 2784 Solar wind/magnetosphere interactions
DE: 2788 Storms and substorms
DE: 3220 Nonlinear dynamics
DE: 3240 Chaos
SC: SPA - Magnetospheric Physics [SM]
MN: 2003 Fall Meeting