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The input from the solar wind (SW) and the accompanying Interplanetary Magnetic Field (IMF) is the defining feature of the solar wind-magnetosphere interactions. One of the most important SW drivers is the solar wind dynamic pressure, and most significantly its sharp changes known as pressure fronts. Sudden enhancements in solar wind dynamic pressure, SWP, have been shown to lead to intensification of the auroral electrojets (and Region 1 field-aligned currents), increase in auroral emissions, and significant enhancement in ionospheric convection and the transpolar potential. Case studies of the interaction between pressure fronts and the terrestrial space environment shed great light on their importance to the structure and dynamics of the system. However, thorough understanding of the interaction requires fully statistical investigations. These statistical studies require a large number of suitable pressure front events. In the past these have been obtained through laborious manual inspection of solar wind data. We present an automated procedure that identifies sudden step enhancements in SWP that satisfy a desired set of limiting step-like characteristics, such as magnitude of the change, sign of the change (positive/negative), and rate of change. The procedure yields a list of suitable events, along with their step features within minutes. The technique is tested for missed events and false positives by direct comparison to manual inspection of the data. Its utility is illustrated by application to the statistical effect of pressure fronts to the transpolar potential as measured by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) technique.

The accurate determination of the Field Line Resonance (FLR) frequency of a resonating geomagnetic field line is necessary to remotely monitor the plasmaspheric mass density during geomagnetic storms and quiet times alike. Under certain assumptions the plasmaspheric mass density at the equator is inversely proportional to the square of the FLR frequency. The most common techniques to determine the FLR frequency from ground magnetometer measurements are the amplitude ratio and phase difference techniques, both based on geomagnetic field observations at two latitudinally separated ground stations along the same magnetic meridian. Previously developed automated techniques have used statistical methods to pinpoint the FLR frequency using the amplitude ratio and phase difference calculations. We now introduce a physics-based automated technique, using non-linear least square fitting of the ground magnetometer data to the analytical resonant wave equations, that reproduces the wave characteristics on the ground, and from those determine the FLR frequency. One of the advantages of the new technique is the estimation of physics-based errors of the FLR frequency, and as a result of the equatorial plasmaspheric mass density. We present analytical results of the new technique, and test it using data from the Inner-Magnetospheric Array for Geospace Science (iMAGS) ground magnetometer chain along the coast of Chile and the east coast of the United States. We compare the results with the results of previously published statistical automated techniques.