Wavelet analysis of ULF magnetospheric waves

<p>Wavelet analysis is used to analyze magnetometer data and is compared to the traditional spectrogram technique, in particular, with respect to structured Pc 1--2 emissions. This results in the conclusion that the frequency modulation evident in Pearl pulsations is not continuous, but is comprised of waves localized in both time and space whose overall structure produces the stripe-like patterns. Utilizing information from the Multi-Resolution Analysis in conjunction with traditional spectrogram techniques this paper is the first to show clear signal power relationships between Pc 1--2 and Pc3 waves and also between Pc 1--2 and Pc 5 waves as detected on the ground. A technique in Wavelet analysis called signal decomposition will be used as a new technique for graphing wave power of all Pc categories simultaneously. This provides a way to compare ULF wave occurrences in order to determine if there is any relationship between them. The signal decomposition processing technique produces results directly contradicting the Bouncing Wave Packet model that has been traditionally invoked as the source of Pearl pulsation structures.</p><p>A detailed comparison of the Continuous Wavelet Transform (CWT) with Multi-Resolution Analysis (MRA) shows the MRA to be a superior technique because the interpretation of the resulting analysis is not subject to a high degree of parameter variability characteristic of the CWT. This paper illustrates the usefulness of the MRA in studying the relationship between all classifications of Pc 1--2 waves with the simultaneous appearance of low frequency emissions and suggests areas for further study.</p>

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Dissertation

Year

2003

Author dc:creator

• Brennison, Edward Scott

Contributors dc:contributor

• Roger Arnoldy

• Physics
• Astronomy and Astrophysics
• Fluid and Plasma

Repository record dc:identifier

https://scholars.unh.edu/dissertation/187

OAI identifier oai:identifier

oai:scholars.unh.edu:dissertation-1186