WINDOWED AND WAVELET ANALYSIS OF MARINE STRATOCUMULUS CLOUD INHOMOGENEITY

To improve radiative transfer calculations for inhomogeneous clouds, a consistent means of modeling inhomogeneity is needed. One current met hod of modeling cloud inhomogeneity is through the use of fractal para meters. This method is based on the supposition that cloud inhomogenei ty over a large range of scales is related. An analysis technique name d wavelet analysis provides a means of studying the multiscale nature of cloud inhomogeneity. In this paper, the authors discuss the analysi s and modeling of cloud inhomogeneity through the use of wavelet analy sis. Wavelet analysis as well as other windowed analysis techniques ar e used to study liquid water path (LWP) measurements obtained during t he marine stratocumulus phase of the First ISCCP (International Satell ite Cloud Climatology Project) Regional Experiment. Statistics obtaine d using analysis windows, which are translated to span the LWP dataset , are used to study the focal (small scale) properties of the cloud fi eld as well as their time dependence. The LWP data are transformed ont o an orthogonal wavelet basis that represents the data as a number of times series. Each of these time series lies within a frequency band a nd has a mean frequency that is half the frequency of the previous ban d. 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 r atio between the standard deviation of adjacent frequency bands is 0.9 and remains constant with respect to time. This ratio defined as the variance coupling parameter is applicable to ail of the frequency band s studied and appears to be related to the slope of the data's power s pectrum. Similar analyses are performed on two cloud inhomogeneity mod els, which use fractal-based concepts to introduce inhomogeneity into a uniform cloud field. The bounded cascade model does this by iterativ ely redistributing LWP at each scale using the value of the local mean . This model is reformulated into a wavelet multiresolution framework, thereby presenting a number of variants of the bounded cascade model. One variant introduced in this paper is the ''variance coupled model, '' which redistributes LWP using the local standard deviation and the variance coupling parameter. While the bounded cascade model provides an elegant two-parameter model for generating cloud inhomogeneity, the multiresolution framework provides more flexibility at the expense of model complexity. Comparisons are made with the results from the LWP data analysis to demonstrate both the strengths and weaknesses of thes e models.