Abstract

Because in large part of complex interactions between turbulence and moist processes, stratocumulus clouds have the ability to self-organize into a variety of topological structures, including closed and open convection cells, convection rolls, and scattered cumulus. A lot is known about the large-scale conditions in which shallow clouds and fog develop and decay. However, because of the various complex interactions of clouds with the turbulent environment and unresolved cloud radiative feedbacks, transitions between these various cloud regimes are hard to capture in numerical models. Recently Stechmann and Hottovy (2016) suggested that these cloud regimes as the equilibrium states of phase transition in a stochastic model from the balance between turbulent diffusion and large scale forcing. In Khouider and Bihlo (2019), we build on this idea to propose a new stochastic model based on the lattice particles-Ising model of statistical mechanics, bringing in important improvements by allowing, for example, multiple equilibria and for top of the boundary layer turbulence and cloud feedbacks onto the large-scale moisture dynamics. Idealized numerical simulations demonstrate that the new model reproduces qualitatively the observed regimes of stratocumulus when the external forcing is varied. The new model forms a metastable dynamical system where transitions between extreme regimes occur dynamically, that is, within the same numerical simulation, for a large range of fixed parameter values, and sometimes lead to the co-occurrence of mixed states with pockets of closed cells and open cells intercepted by regions of scattered cloudiness, resembling the emergence of convection rolls in nature. In essence, the nonlinear cloud-moisture interactions and turbulent mixing lead to a state of transient Turing patterns.    JoinT work with Alexander Bihlo.