The study of multidimensional data along time often needs data reduction methods to reduce dimension, and to study some particular phenomena. In the context of fluid mechanics, we propose to compare a version of Functional Principal Components Analysis (FPCA), named Proper Orthogonal Decomposition (POD), with two methods based on the spectral decomposition of data Fourier transform, the Spectral Proper Orthogonal Decomposition (SPOD) and Principal Components Analysis in the Frequency Domain (PCAFD). In this context, both POD and SPOD have been proposed, while PCAFD has been newly applied to this domain. Thus, we provide a discussion on the contribution of PCAFD to deal with multiscale physics.