“Mitigating Radar Field-of-View Bias in MSTID Wavenumber Spectrum Plots Calculated within pyDARN’s MUSIC Algorithm”

Medium Scale Traveling Ionospheric Disturbances (MSTIDs) are quasi-periodic variations in the ionospheric F region induced by atmospheric gravity waves (GWs), providing critical information for understanding neutral atmosphere-ionospheric coupling. Previous SuperDARN studies of MSTIDs have used the Multiple Signal Classification (MUSIC) technique to determine the horizontal wavelength, propagation direction, propagation speed, and period of MSTIDs moving through the SuperDARN radar field of view (FOV). Unfortunately, this angular coverage of the radars (FOV) is clearly visible when considering the wave number spectrum plots used to determine the direction of propagation of the MSTIDs. Distortions on the contour plots representing these disturbances, such as elongations in the direction of the radar's field of view, are noticeable in these plots. Therefore, removing these undesired effects from the wave number spectrum plots is crucial to better identify MSTIDs' direction of propagation and, thus, the different properties with these waves. In this project, we explore methods that will potentially eliminate the bias introduced by the radar's field of view, which allows us to obtain undistorted contour plots that can be used to correctly identify the wave numbers associated with the MSTIDs and then determine more accurately their direction of propagation.