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The distribution of ice particles strongly affects the microphysical processes in mixed-phase clouds, but the inhomogeneity of ice distribution is not well understood. In this presentation the inhomogeneity and clustering of ice distribution in a stratiform cloud system is quantitatively analyzed using the pair correlation function (PCF) method, based on airborne in-situ measurements from northeast China. The results show that ice clusters on scales of a few kilometers dominate the inhomogeneity of the ice distribution. Due to the cumulative impact of ice clusters on different scales, the probability of finding relative high ice concentration within a lag of 80 m can be enhanced by 0.1 to 3.5 times. On average, the scale of ice cluster is ~100 m for a sampling distance of 1 km, and increases to 3.2 km for a sampling distance of 20 km. It is also found that the ice growth is not fast enough to cluster the ice water content (IWC), and the inhomogeneity of IWC is strongly influenced by ice generation in addition to ice growth in the observed clouds. The results provide potentially important information to improve the parameterizations of microphysics in numerical weather prediction and climate models.
Yin et al. (Fri,) studied this question.