Statistics of Cirrus Horizontal Inhomogeneity in the Southern Great Plains

Variability of cloud properties on scales smaller than that of a GCM grid is potentially important both for realistic parameterizations of microphysical processes and for the prediction of the large-scale radiative effects of clouds, have suggested that a simple model of marine stratocumulus variability, based on the assumption of Gaussian variation statistics of cloud depth, can explain the liquid water path histogram shapes observed in Landsat data. In advance of ARM SGP MMCR ice water path climatologies, we have examined aircraft ice water content statistics for cirrus clouds observed over Coffeyville, Kansas during FIRE 2. We find similar associations of histogram shape and cloud cover for these clouds, and we show that a simple modification of the model for cirrus combined with observed mean cloud depths, their standard deviations, and ambient thermodynamic conditions predicts both the histogram shape and cirrus cloud cover fairly well. This suggests that subgrid variability of cloud properties may be similar for vastly different cloud types, and that a universal parameterization of the effects of subgrid variability in GCMs as a function of only a few parameters may be a realistic goal.