Removal of nonconstant daily variation by means of wavelet and functional data analysis

Details Removal of nonconstant daily variation by means of wavelet and functional data analysis Removal of nonconstant daily variation by means of wavelet and functional data analysis

Mar 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009jgra..11403202m&link_type=abstract

Journal of Geophysical Research, Volume 114, Issue A3, CiteID A03202

Physics

Geophysics

Magnetospheric Physics: Ring Current, Magnetospheric Physics: Instruments And Techniques, Mathematical Geophysics: Wavelet Transform (3255, 4455), Mathematical Geophysics: Instruments And Techniques

Scientific paper

We propose a novel approach based on wavelet and functional principal component analysis to produce a cleaner index of the intensity of the symmetric ring current. We use functional canonical correlations to show that the new approach more effectively extracts symmetric global features. The main result of our work is the construction of a new index, which is an improved version of the existing wavelet-based index (WISA) and the old Dst index, in which a constant daily variation is removed. Here, we address the fact that the daily component varies from day to day and construct a ``cleaner'' index by removing nonconstant daily variations.

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