Comparison of scaling parameters from spatial and temporal distributions of cloud properties

The most common method to evaluate the quality of cloud parameter retrieval s from satellite data is comparison with time series of ground-based measur ements. For highly variable cloud parameters, such as liquid water path (LW P), however, a direct comparison of spatial and temporal distributions has limited value. It is questionable which period in the time series is repres entative of an area in the satellite image. A necessary but not sufficient boundary condition for statistical analysis is that the variability of both subsets is similar. In this paper we study the variability in terms of sca ling properties of both spatial distributions and timeseries of LWP and foc us on the relation between them. The time series are obtained from ground-b ased microwave radiometer measurements at 1 Hz. The spatial distributions a re derived from Advanced Very High Resolution Radiometer 0.6 mum radiances. It is shown that the scaling properties of both distributions are similar for a stratocumulus field, which exhibits scale invariance, and for a cumul us field for which scales of preference were identified. A double logarithm ic representation was appropriate to obtain the spectral exponent. A log-li near representation was appropriate to identify a scale of preference. In t he cumulus case it was possible to calculate a feasible conversion factor t o map variability in time to variability in space. This enables an estimati on of the spatial variability at very high resolutions.