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.
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)