  Hilbert-Huang transform is a method that has been introduced recently to
decompose nonlinear, nonstationary time series into a sum of different modes,
each one having a characteristic frequency. Here we show the first successful
application of this approach to homogeneous turbulence time series. We
associate each mode to dissipation, inertial range and integral scales. We then
generalize this approach in order to characterize the scaling intermittency of
turbulence in the inertial range, in an amplitude-frequency space. The new
method is first validated using fractional Brownian motion simulations. We then
obtain a 2D amplitude-frequency representation of the pdf of turbulent
fluctuations with a scaling trend, and we show how multifractal exponents can
be retrieved using this approach. We also find that the log-Poisson
distribution fits the velocity amplitude pdf better than the lognormal
distribution.
