Europhys. Lett., 52 (1), pp. 40–46 (2000) EUROPHYSICS LETTERS 1 October 2000 Break-up of stratus cloud structure predicted from non-Brownian motion liquid water and brightness temperature fluctuations K. Ivanova 1,2 , M. Ausloos 3 , E. E. Clothiaux 1 and T. P. Ackerman 4 1 Department of Meteorology, Pennsylvania State University University Park, PA 16802, USA 2 Institute of Electronics, Bulgarian Academy of Sciences 72 Tzarigradsko chaussee, Sofia 1784, Bulgaria 3 SUPRAS and GRASP, Institute of Physics, B5, University of Li` ege B-4000 Li` ege, Belgium 4 Pacific Northwest National Laboratory, U.S. Department of Energy Richland, WA 99352, USA (received 10 January 2000; accepted in final form 28 July 2000) PACS. 05.45.Df – Fractals. PACS. 05.45.Tp – Time series analysis. PACS. 05.40.Jc – Brownian motion. Abstract. – The Detrended Fluctuation Analysis statistical method is applied to microwave radiometer and infrared thermometer radiance data in order to examine stratus cloud dynamics. The existence of long-range power law correlations in stratus cloud liquid water path and radiance (brightness temperature) fluctuations is demonstrated to occur over about a two-hour period. Moreover, using a finite-size (time) interval window, a change from non-Brownian to Brownian fluctuation regimes is clearly shown to define the cloud structure changes. Introduction. – Substantial progress has been made in the fields of predictive meteorology and climate in the past several decades. In some areas, however, the non-linear processes at work in the atmosphere often produce data series of such complexity that traditional analysis techniques fail to extract meaningful physical information. Better techniques are clearly required. Recently, there have been several reports that short- and long-range power law correlations can be analyzed in turbulence [1], biological [2, 3] and financial [4–6] data fluctuations, and more generally in self-organized critical systems [7,8]. If these methods can be adapted for meteorological and climatological time series and can serve to elucidate the underlying physical processes, they offer a path towards improved models of the atmosphere and of the weather [9,10]. The key ingredient to be introduced in this study is based on fractal geometry ideas and phase transitions in nonequilibrium states, i.e., bearing upon scale invariance [11,12], Brow- nian motion [13,14], a.s.o. phenomenology. Within the content of the Detrended Fluctuation c  EDP Sciences