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Abstract
A technique is developed for reducing the amount of aliasing in the spectral analysis of TIDI observations, by ingestion of ground‐based data into the satellite data set. A multi‐dimensional (space‐time) least squares fitting approach is applied to the satellite and ground‐based data to determine the aliasing spectra. The addition of ground‐based data to the TIDI data set reduces the aliased components in the aliasing spectrum. For example, at 20° latitude, the combined ground‐based and TIDI data set of a sampled input semidiurnal (frequency of 2 days−1) signal with zonal wavenumber 2 results in a factor of 2 reduction in the amount of power aliasing into a signal with zonal wavenumber 0 and frequency 0 days−1.
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