  Modal decomposition techniques are important tools for the analysis of
unsteady flows and, in order to provide meaningful insights with respect to
coherent structures and their characteristic frequencies, the modes must
possess a robust spatial support. In this context, although widely used,
methods based on singular value decomposition (SVD) may produce modes that are
difficult to interpret when applied to problems dominated by intermittent and
transient events. Fortunately, specific modal decomposition techniques have
been recently developed to analyze such problems. However, a proper comparison
between existing methods is still lacking from the literature. Therefore, this
work compares two recent methods: the fast adaptive multivariate empirical mode
decomposition (FA-MVEMD) and the multi-resolution dynamic mode decomposition
(mrDMD). These techniques are employed here for the study of flow databases
involving transient and intermittent dynamics. Specifically, the investigated
problems include an SD7003 airfoil subjected to deep dynamic stall conditions,
and a steady NACA0012 airfoil operating at a transitional Reynolds number. In
the former case, the methods are employed to investigate the onset and
evolution of the dynamic stall vortex (DSV), while in the latter case,
intermittent vortex pairing is analyzed. We show that the combination of a
multidimensional EMD with the Hilbert transform provides modes with superior
spatial support when compared to the mrDMD, also allowing the characterization
of instantaneous frequencies of coherent structures. Moreover, the EMD also
condenses a larger amount of information within a single intrinsic mode
function (IMF).
