Physics
Scientific paper
May 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agusmsm41c..04c&link_type=abstract
American Geophysical Union, Fall Meeting 2007, abstract #SM41C-04
Physics
6939 Magnetospheric Physics (2700), 7839 Nonlinear Phenomena (4400, 6944), 7954 Magnetic Storms (2788), 2784 Solar Wind/Magnetosphere Interactions, 2788 Magnetic Storms And Substorms (7954)
Scientific paper
During geomagnetically active periods the magnetosphere exhibits global, regional and local features. The global features are in general captured by the geomagnetic indices and the regional and local features are measured by spacecraft-based imagers and ground-based instruments. The global features of the magnetosphere have been studied extensively using nonlinear dynamical techniques, such as phase space reconstruction from observational data. The time series data of the distributed observations are used to develop spatio-temporal dynamics of the magnetosphere using phase space reconstruction techniques. 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 ground-based magnetic field variations as the magnetospheric response. The magnetic field perturbation at 57 ground stations during year 2002 and the corresponding solar wind data are compiled for this study. The ground magnetometer data are from the three chains of stations: CANOPUS (13), IMAGE (26) and WDC (18). This new data set, with 1-minute resolution, 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 linear and nonlinear model is used to predict the spatial structure of geomagnetic disturbances during intense geospace storms. From the point of view of space weather the predictions of the spatial structure are crucial, as it is important to identify the regions of strong disturbances during intense geospace storms
Chen Jiahua
Sharma Aashish
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