Windowed and Wavelet Analysis of Marine Stratocumulus Cloud Inhomogeneity

In order to improve radiative transfer calculations for inhomogeneous clouds, a consistent means of modeling inhomogeneity is needed. One current method of modeling cloud inhomogeneity is through the use of fractal parameters. This method is based on the supposition that cloud inhomogeneity over a large range of scales is related. An analysis technique named wavelet analysis provides a means of studying the multiscale nature of cloud inhomogeneity. In this paper, we discuss the analysis and modeling of cloud inhomogeneity through the use of wavelet analysis. Wavelet analysis as well as other windowed analysis techniques are used to study liquid water path (LWP) measurements obtained during the marine stratocumulus phase of the First ISCCP Regional Experiment (FIRE). Statistics obtained using analysis windows, which are translated to span the LWP data set, are used to study the local (small scale) properties of the cloud field as well as their time dependence. The LWP data is transformed onto an orthogonal wavelet basis which represents the data as a number of times series. Each of these time series lie within a frequency band and have a mean frequency which is half the frequency of the previous band. Wavelet analysis combined with translated analysis windows reveals that the local standard deviation of each frequency band is correlated with the local standard deviation of the other frequency bands. The ratio between the standard deviation of adjacent frequency bands is 0.9 and remains constant with respect time. This ratio defined as the variance coupling parameter is applicable to all of the frequency bands studied and appears to be related to the slope of the data's power spectrum. Similar analyses are performed on two cloud inhomogeneity models, which use fractal based concepts to introduce inhomogeneity into a uniform cloud field. The