A new formulation of partial cloudiness parameterization has been intr
oduced that agrees with that for a random model in one limit and appro
aches the simple updraft/downdraft model of larger-scale models in the
limit of very highly skewed flow. Each of the conserved variables, li
quid potential temperature and total humidity, along with the vertical
velocity, are assumed to have probability distributions that may be p
arameterized as combinations of two multivariate normal distributions.
This allows the skewness of the variables to be controlled by the bia
s between the means of the two normals and their relative fractions. I
t also provides a smooth transition between the normal distribution an
d the two limiting delta function distribution of the updraft/downdraf
t model. Comparisons with large-eddy-simulation data show this new mod
el to be valid over a much wider range of conditions than the single n
ormal distribution. When a simple cloud-top entrainment instability (C
TEI) analysis is made using the new binormal model, variations in the
dynamic characteristics, here represented by the skewness in the ''ten
ded liquid water function, s, are found to mask the variation with res
pect to the ratio in the thermodynamic jump conditions. This helps to
explain the observed poor correlation of empirical cloud fraction with
this jump condition. On the other hand, the analysis suggests that th
e ratio of the mean value of the extended liquid water variable, s, to
the square root of its variance, may be expected to show a much bette
r correlation with the empirical cloud fraction.