Variances and Covariance Assessment of Liquid Water Content in Precipitating Warm Cloud

A shallow cloud of warm microphysics is used to analyze the subgrid variability of liquid water content. These turbulent flows are diagnosed by means of second-order moment transport equations for liquid water quantities. These equations show that liquid water variabilities are controlled by the production of the gradient of mean liquid water quantities and microphysical processes. The contributions (source or sink) of these different productions reflect the effects of the gradient of average quantities of liquid water content and microphysical processes on the evolution of liquid water variability. It emerges that cloud water variance is mainly produced by the cloud water gradient term and constantly destroyed by the effects of auto conversion and accretion processes. Inversely, the processes of rain droplet formation and growth contribute as the main source for the variance of precipitating water and the cloud water-precipitating water covariance. Microphysical depletion processes, notably cloud droplet evaporation and precipitable droplet sedimentation, act as sinks for liquid water variances and covariance. Finally, for rainwater variability, the gradient term may be less important, but it provides real support for the source or sink terms of microphysics. This work particularly highlights the subgrid variabilities associated with precipitating droplets. In particular, this work focuses on the subgrid variabilities associated with liquid water content. Incorporating a good parameterization of liquid water variances and cloud water-rainwater correlation in statistical schemes could improve rainwater formation, growth and loss processes in large-scale models.