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Alexandrescu et al. 1995
Alexandrescu, M., Gibert, D., Hulot, G., Le Mouël, J. and Saracco, G. (1995). Detection of geomagnetic jerks using wavelet analysis. Journal of Geophysical Research 100: doi: 10.1029/95JB00314. issn: 0148-0227.
Wavelet analysis is applied to detect and characterize singular events, or singularities, or jerks, in the time series made of the last century monthly mean values of the east component of the geomagnetic field from European observatories. After choosing a well-adapted wavelet function, the analysis is first performed on synthetic series including an ''internal,'' or ''main,'' signal made of smooth variation intervals separated by singular events with different ''regularities,'' a white noise and an ''external'' signal made of the sum of a few harmonics of a long-period variation (11 years). The signatures of the main, noise, and harmonic signals are studied and compared, and the conditions in which the singular events can be clearly isolated in the composite signal are elucidated. Then we apply the method systematically to the real geomagnetic series (monthly means of Y from European observatories) and show that five and only five remarkable events are found in 1901, 1913, 1925, 1969, and 1978. The characteristics of these singularities (in particular, homogeneity of some derived functions of the wavelet transform over a large range of timescales) demonstrate that these events have a single source (of course, internal). Also the events are more singular than was previously supposed (their ''regularity'' is closer to 1.5 than to 2., indicating that noninteger powers of time should be used in representing the time series between the jerks). ¿ American Geophysical Union 1995 Wavelet analysis is applied to detect and characterize singular events, or singularities, or jerks, in the time series made of the last century monthly mean values of the east component of the geomagnetic field from European observatories. After choosing a well-adapted wavelet function, the analysis is first performed on synthetic series including an ''internal,'' or ''main,'' signal made of smooth variation intervals separated by singular events with different ''regularities,'' a white noise and an ''external'' signal made of the sum of a few harmonics of a long-period variation (11 years). The signatures of the main, noise, and harmonic signals are studied and compared, and the conditions in which the singular events can be clearly isolated in the composite signal are elucidated. Then we apply the method systematically to the real geomagnetic series (monthly means of Y from European observatories) and show that five and only five remarkable events are found in 1901, 1913, 1925, 1969, and 1978. The characteristics of these singularities (in particular, homogeneity of some derived functions of the wavelet transform over a large range of timescales) demonstrate that these events have a single source (of course, internal). Also the events are more singular than was previously supposed (their ''regularity'' is closer to 1.5 than to 2., indicating that noninteger powers of time shoul
BACKGROUND DATA FILES

Abstract
Abstract

Detection of Singularities with Wavelets
Detection of Singularities with Wavelets (continued)
Real Data Analysis
Processing of the Chambour-La-Foret Series

Keywords
Geomagnetism and Paleomagnetism, Time variations—diurnal to secular, Geomagnetism and Paleomagnetism, Dynamo theories, Mathematical Geophysics, General or miscellaneous, General or Miscellaneous, Techniques applicable in three or more fields
Journal
Journal of Geophysical Research
http://www.agu.org/journals/jb/
Publisher
American Geophysical Union
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