An automatic wave detection algorithm applied to Pc1 pulsations

[1] A new technique designed to automatically identify and characterize waves in three-xis data is presented, which can be applied in a variety of settings, including triaxial ground-magnetometer data or satellite wave data ( particularly when transformed to a field-aligned coordinate system). This technique is demonstrated on a single Pc1 event recorded on a triaxial search coil magnetometer in Parkfield, California (35.945 degrees, -120.542 degrees), and then applied to a 6-month period between 1 June 2003 and 31 December 2003. The technique begins with the creation of a standard dynamic spectrogram and consists of three steps: (1) for every column of the spectrogram ( which represents the spectral content of a short period in the time series), spectral peaks are identified whose power content significantly exceeds the ambient noise; (2) the series of spectral peaks from step 1 are grouped into continuous blocks representing discrete wave events using a "spectral-overlap'' criterion; and (3) for each identified event, wave parameters ( e. g., wave normal angles, polarization ratio) are calculated which can be used to check the continuity of individual identified wave events or to further filter wave events ( e. g., by polarization ratio).