Physics
Scientific paper
Jul 2003
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003jgra..108.1298w&link_type=abstract
Journal of Geophysical Research Space Physics, Volume 108, Issue A7, pp. SMP 16-1, CiteID 1298, DOI 10.1029/2002JA009627
Physics
10
Ionosphere: Modeling And Forecasting, Ionosphere: Current Systems (2708), Magnetospheric Physics: Solar Wind/Magnetosphere Interactions, Magnetospheric Physics: Forecasting
Scientific paper
A spatial and dynamic study of solar wind driving of high-latitude ground magnetic fields and their time derivatives is given. Nonlinear, data-derived basis functions are used to determine the optimal solar wind driven dynamic coupling function at high-latitude locations. The method does not assume a solar wind driving function a priori so that an unbiased determination of the relative influence of different driving processes can be made. Using this method, the locations where high-latitude models capture signatures of different driving processes, such as reconnection and the Kelvin-Helmholtz instability, are revealed for both the amplitude of the field and its time derivative. The time rate of change of the field is a disturbance measure related to geomagnetically induced currents. For the amplitude of the ground magnetic field the primary driver is reconnection; the time rate of change of the field has signatures of both reconnection driving in the nightside sector and Kelvin-Helmholtz driving in the prenoon sector. The independent influence of the solar wind ion density and azimuthal component of the magnetic field in driving magnetic field fluctuations is found to be small at auroral-zone latitudes. The data-derived coupling functions are also used to estimate the expected prediction error of a general class of models that specify the ground magnetic field or its time derivative given solar wind plasma measurements. Prediction efficiencies as small as zero and as large as 0.7 for both the amplitude of the field and its time derivative are possible. The prediction efficiency is highly dependent on spatial location and the direction of field being predicted.
Klimas Alex J.
Vassiliadis Dimitris
Weigel Robert S.
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