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Creators/Authors contains: "Zesta, E."

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  1. Abstract Both ground based magnetometers and ionospheric radars at Earth have frequently detected Ultra Low Frequency (ULF) fluctuations at discrete frequencies extending below one mHz‐range. Many dayside solar wind drivers have been convincingly demonstrated as driver mechanisms. In this paper we investigate and propose an additional, nightside generation mechanism of a low frequency magnetic field fluctuation. We propose that the Moon may excite a magnetic field perturbation of the order of 1 nT at discrete frequencies when it travels through the Earth's magnetotail 4–5 days every month. Our theoretical prediction is supported by a case study of ARTEMIS magnetic field measurements at the lunar orbit in the Earth's magnetotail. ARTEMIS detects statistically significant peaks in magnetic field fluctuation power at frequencies of 0.37–0.47 mHz that are not present in the solar wind. 
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  2. Abstract One of the most significant observations associated with a sharp enhancement in solar wind dynamic pressure,, is the poleward expansion of the auroral oval and the closing of the polar cap. The polar cap shrinking over a wide range of magnetic local times (MLTs), in connection with an observed increase in ionospheric convection and the transpolar potential, led to the conclusion that the nightside reconnection rate is significantly enhanced after a pressure front impact. However, this enhanced tail reconnection has never been directly measured. We demonstrate the effect of a solar wind dynamic pressure front on the polar cap closure, and for the first time, measure the enhanced reconnection rate in the magnetotail, for a case occurring during southward background Interplanetary Magnetic Field (IMF) conditions. We use Polar Ultra‐Violet Imager (UVI) measurements to detect the location of the open‐closed field line boundary, and combine them with Assimilative Mapping of Ionospheric Electrodynamics (AMIE) potentials to calculate the ionospheric electric field along the polar cap boundary, and thus evaluate the variation of the dayside/nightside reconnection rates. We find a strong response of the polar cap boundary at all available MLTs, exhibiting a significant reduction of the open flux content. We also observe an immediate response of the dayside reconnection rate, plus a phased response, delayed by ∼15–20 min, of the nightside reconnection rate. Finally, we provide comparison of the observations with the results of the Open Geospace General Circulation Model (OpenGGCM), elucidating significant agreements and disagreements. 
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  3. Abstract 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 (AR) and phase difference (PD) 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 AR and PD calculations. We now introduce a physics‐based automated technique, using nonlinear least squares 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 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. 
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