Forecasting the Spatio-Temporal Dynamics of the Magnetosphere

Details Forecasting the Spatio-Temporal Dynamics of the Magnetosphere Forecasting the Spatio-Temporal Dynamics of the Magnetosphere

Dec 2007

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007agufmsm34a..05c&link_type=abstract

American Geophysical Union, Fall Meeting 2007, abstract #SM34A-05

Physics

2722 Forecasting (7924, 7964), 2740 Magnetospheric Configuration And Dynamics, 2784 Solar Wind/Magnetosphere Interactions, 2788 Magnetic Storms And Substorms (7954)

Scientific paper

The spatio-temporal dynamics of the magnetosphere is a crucial component of effective space weather forecasting. The extensive data of the solar wind-magnetosphere interaction has been used to build predictive models of the magnetosphere based on nonlinear dynamical approaches. The time series data of the distributed observations are used to develop spatio-temporal dynamics of the magnetosphere. In this approach the solar wind - magnetosphere coupling is modeled as an input-output system with the solar wind variables as the input and the magnetic field variations at the ground stations as the magnetospheric response. The magnetic field perturbation at the ground and the corresponding solar wind data stations during the solar maximum period are compiled for these studies. The ground magnetometer data are from from CANOPUS, IMAGE and WDC magnetometer chain of stations. This new data set is used to study the spatio-temporal structure, including the coupling between the high and mid-latitude regions. A technique that utilizes the daily rotation of the Earth as a longitudinal sampling process is used to construct a two dimensional representation of the high latitude magnetic perturbations both in magnetic latitude and magnetic local time. This nonlinear model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms. In order to understand the predictability of space weather, the correlated database is used to study the causal relationships based on information theoretic approaches. This yields the mutual information between the solar wind variables and the ground magnetic field variations, and among the ground stations themselves. The information flow within the coupled system is analyzed by computing the transfer entropy among them.

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