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Turbulent space and astrophysical plasmas exhibit a complex dynamics, whichinvolves nonlinear coupling across different temporal and spatial scales. Thereis growing evidence that impulsive events, such as magnetic reconnectioninstabilities, lead to a spatially localized enhancement of energy dissipation,thus speeding up the energy transfer at small scales. Capturing such a diversedynamics is challenging. Here, we employ the Multidimensional IterativeFiltering (MIF) method, a novel technique for the analysis of nonstationarymultidimensional signals. Unlike other traditional methods (e.g., based onFourier or wavelet decomposition), MIF does not require any previous assumptionon the functional form of the signal to be identified. Using MIF, we carry outa multiscale analysis of Hall-magnetohydrodynamic (HMHD) and hybridparticle-in-cell (HPIC) numerical simulations of decaying plasma turbulence.The results assess the ability of MIF to spatially identify and separate thedifferent scales (the MHD inertial range, the sub-ion kinetic, and thedissipation scales) of the plasma dynamics. Furthermore, MIF decompositionallows to detect localized current structures and to characterize theircontribution to the statistical and spectral properties of turbulence. Overall,MIF arises as a very promising technique for the study of turbulent plasmaenvironments.

Multidimensional Iterative Filtering: a new approach for investigating plasma turbulence in numerical simulations