A wavelet-based method for multifractal image analysis. III. Applications to high-resolution satellite images of cloud structure
Centre de Recherche Paul Pascal, avenue Schweitzer, 33600
2 Climate & Radiation Branch, NASA's Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
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