Cloud microphysics is critical for weather and climate prediction, being at the center of precipitation formation and cloud-radiative interactions. Representing cloud microphysics in models requires statistical parameterizations of hydrometeor populations and the processes by which they evolve and interact. We invite presentations on all aspects of cloud microphysics parameterizations across different scales of modeling, with a focus on key issues for climate as clouds change in response to climate change. Topics may include the development of new parameterization methods and evaluation using observations in key regimes that are important for weather and climate. We invite topics on new data driven methods such as machine learning and Bayesian methods for parameterization development, emulation and evaluation.