Statistical identification of solar wind origins of magnetic impulse events (MIEs)

Physics

Scientific paper

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2109 Discontinuities, 2708 Current Systems (2409), 2724 Magnetopause, Cusp, And Boundary Layers, 2736 Magnetosphere/Ionosphere Interactions, 2784 Solar Wind/Magnetosphere Interactions

Scientific paper

Magnetic impulse events (MIEs) are identified as large-amplitude, impulsive-type magnetic disturbances with durations of 5-15 min and amplitudes of 50-200 nT that occur predominantly at dayside high-latitudes. Because of theose solitary features, MIEs provide a good clue to understanding the transient response of the coupled magnetosphere-ionosphere system to solar wind disturbances. Traveling convection vortices (TCVs), which are transient ionospheric Hall current loops passing overhead of ground-based magnetometers, are the best interpretation of MIEs. In contrast to sudden commencements that are produced by abrupt increases in solar wind dynamic pressure, there is no consensus on the origins of MIEs among researchers. In this work, we report an investigation of the statistical properties of the solar wind origins of MIEs. We have analyzed fluxgate magnetometer data over 7 years from January 1, 1995 to January 1, 2002 at South Pole Station in Antarctica. Wavelet analysis was used to detect a large number of distinct MIEs automatically with high confidence. Solar wind pressure pulses and directional discontinuities were also detected automatically for the same period using data from the Wind and ACE satellites. Satellite-to-ground timing were determined using normal vectors of the interplanetary discontinuities. The new fully-automated analysis with the longest observation interval (extending from solar minimum to maximum) makes it possible for the first time to find not only the contribution rates to MIEs of different types of solar wind origins but also the seasonal and even the solar cycle dependence of the production of MIEs. Conjugate properties of the TCVs related to these MIEs are also investigated by statistical analysis, combining data sets from both northern and southern magnetometer networks.

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