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Ann. Geophys., 26, 305-314, 2008
www.ann-geophys.net/26/305/2008/
© European Geosciences Union 2008
A statistical approach for identifying the ionospheric footprint of magnetospheric boundaries from SuperDARN observations
G. Lointier, T. Dudok de Wit, C. Hanuise, X. Vallières, and J.-P. Villain
1Laboratoire de Pysique et Chimie de l'Environnement, UMR 6115 CNRS/University of Orléans, 3A avenue de la recherche Scientifique, 45071 Orléans cedex 2, France
Abstract. Identifying and tracking the projection of magnetospheric regions on the
high-latitude ionosphere is of primary importance for studying the Solar
Wind-Magnetosphere-Ionosphere system and for space weather applications. By
its unique spatial coverage and temporal resolution, the Super Dual Auroral
Radar Network (SuperDARN) provides key parameters, such as the Doppler
spectral width, which allows the monitoring of the ionospheric footprint of
some magnetospheric boundaries in near real-time. In this study, we present
the first results of a statistical approach for monitoring these
magnetospheric boundaries. The singular value decomposition is used as a data
reduction tool to describe the backscattered echoes with a small set of
parameters. One of these is strongly correlated with the Doppler spectral
width, and can thus be used as a proxy for it. Based on this, we propose a
Bayesian classifier for identifying the spectral width boundary, which is
classically associated with the Polar Cap boundary. The results are in good
agreement with previous studies. Two advantages of the method are: the
possibility to apply it in near real-time, and its capacity to select the
appropriate threshold level for the boundary detection.
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