https://doi.org/10.1007/s100510051180
A wavelet-based method for multifractal image analysis. III. Applications to high-resolution satellite images of cloud structure
1
Centre de Recherche Paul Pascal, avenue Schweitzer, 33600
Pessac, France
2
Climate & Radiation Branch, NASA's Goddard Space Flight
Center, Greenbelt, Maryland 20771, USA
Received:
17
August
1999
Published online: 15 June 2000
We apply the 2D wavelet transform modulus maxima
(WTMM) method to high-resolution LANDSAT satellite images of
cloudy scenes. The computation of the and D(h)
multifractal spectra for both the optical depth and the radiance
fields confirms the relevance of the multifractal description to
account for the intermittent nature of marine stratocumulus clouds.
When assisting the 2D WTMM method by the wavelet based
deconvolution method designed to compute the self-similarity kernel,
we show that our numerical tools are very efficient to disentangle
the anisotropic texture induced by the presence of convective rolls
from the background radiance fluctuations which are likely to
display isotropic scale invariance. Moreover, this analysis reveals
that with the available set of experimental data, there is no way to
discriminate between various phenomenological cascade models
recently proposed to account for intermittency and their log-normal
approximations. When further investigating the "two-point"
space-scale correlation functions, we bring definite proof of the
existence of an underlying multiplicative structure from an
"integral"coarsest scale which is given by the characteristic
width of the convective patterns. We emphasize the log-normal
random
-cascade model on separable wavelet orthogonal basis
introduced in paper II (N. Decoster, S.G. Roux, A. Arnéodo, Eur. Phys. J. B 15, 739 (2000)),
as a very attractive model (at least as
compared to the models commonly used in the literature) of the cloud
architecture. Finally, we comment on the multifractal properties of
marine stratocumulus radiance fields comparatively to previous
experimental analysis of velocity and temperature fluctuations in
high Reynolds number turbulence.
PACS: 92.60.Nv – Cloud physics / 47.27.Jv – High-Reynolds-number turbulence / 05.40.+j – Fluctuation phenomena, random processes, noise, and Brownian motion / 47.53.+n – Fractals
© EDP Sciences, Società Italiana di Fisica, Springer-Verlag, 2000