Magnetospheric impulse response for many levels of geomagnetic activity

Details Magnetospheric impulse response for many levels of geomagnetic activity Magnetospheric impulse response for many levels of geomagnetic activity

Jul 1985

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1985jgr....90.6387b&link_type=abstract

Journal of Geophysical Research (ISSN 0148-0227), vol. 90, July 1, 1985, p. 6387-6394. Research supported by the University of C

Physics

226

Earth Magnetosphere, Geomagnetic Pulsations, Solar Terrestrial Interactions, Solar Wind, Auroras, Linear Prediction, Time Series Analysis

Scientific paper

The temporal relationship between the solar wind and magnetospheric activity has been studied using 34 intervals of high time resolution IMP 8 solar wind data and the corresponding AL auroral activity index. The median values of the AL index for each interval were utilized to rank the intervals according to geomagnetic activity level. The linear prediction filtering technique was then applied to model magnetospheric response as measured by the AL index to the solar wind input function VB(s). The linear prediction filtering routine produces a filter of time-lagged response coefficients which estimates the most general linear relationship between the chosen input and output parameters of the magnetospheric system. It is found that the filters are composed of two response pulses speaking at time lags of 20 and 60 min. The amplitude of the 60-min pulse is the larger for moderate activity levels, while the 20-min pulse is the larger for strong activity levels. A possible interpretation is that the 20-min pulse represents magnetospheric activity driven directly by solar wind coupling and that the 60-min pulse represents magnetospheric activity driven by the release of energy previously stored in the magnetotail. If this interpretation is correct, the linear filtering results suggest that both the driven and the unloading models of magnetospheric response are important facets of a more comprehensive response model.

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