A new technique designed to automatically identify and characterize waves in three‐axis 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°,−120.542°), 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).

[1] We use search-coil magnetometer data from a low-latitude station in Parkfield, California (L = 1.77) to study the occurrence of Pc1 pulsations associated with geomagnetic storms. The Pc1 pulsations and storms are identified using automatic algorithms, and the statistical distributions are examined using a superposed epoch analysis technique, as a function of local time, time relative to storm main phase, and storm intensity. Results show that Pc1 pulsations are 2-3 times more likely (than normal) to be observed in the 2-4 d following moderate storms and 4-5 times more likely in the 2-7 d following intense storms. The Pc1 frequencies are higher in moderate storms than they are in nonstorm times and become even higher and occupy a greater range of local times as the strength of the storms increase. These results are consistent with the idea that the source of EMIC waves extends to lower L values as storm intensity increases.

Abstract. We examine the association between earthquakes and Pc1 pulsations observed at a low-latitude station in Parkfield, California. The period under examination is ∼7.5 years in total, from February 1999 to July 2006, and we use an automatic identification algorithm to extract information on Pc1 pulsations from the magnetometer data. These pulsations are then statistically correlated to earthquakes from the USGS NEIC catalog within a radius of 200 km around the magnetometer, and M>3.0. Results indicate that there is an enhanced occurrence probability of Pc1 pulsations ∼5-15 days in advance of the earthquakes, during the daytime. We quantify the statistical significance and show that such an enhancement is unlikely to have occurred due to chance alone. We then examine the effect of declustering our earthquake catalog, and show that even though significance decreases, there is still a statistically significant daytime enhancement prior to the earthquakes. Finally, we select only daytime Pc1 pulsations as the fiducial time of our analysis, and show that earthquakes are ∼3-5 times more likely to occur in the week following these pulsations, than normal. Comparing these results to other events, it is preliminarily shown that the normal earthquake probability is unaffected by geomagnetic activity, or a random event sequence.