Pattern formation in clouds via Turing instabilities

TL;DR

This paper investigates the potential for Turing instabilities to explain pattern formation in clouds, extending a generic cloud model with diffusion and analyzing conditions for instability and pattern emergence through numerical simulations.

Contribution

It introduces a framework for analyzing Turing instabilities in cloud models, identifying conditions under which patterns can form, and demonstrating pattern emergence via numerical simulations.

Findings

Certain cloud models do not support Turing instabilities.

A class of models allows Turing pattern formation with nonlinear accretion terms.

Numerical simulations show spatial cloud patterns influenced by collision and sedimentation processes.

Abstract

Pattern formation in clouds is a well-known feature, which can be observed almost every day. However, the guiding processes for structure formation are mostly unknown, and also theoretical investigations of cloud patterns are quite rare. From many scientific disciplines the occurrence of patterns in non-equilibrium systems due to Turing instabilities is known, i.e. unstable modes grow and form spatial structures. In this study we investigate a generic cloud model for the possibility of Turing instabilities. For this purpose, the model is extended by diffusion terms. We can show that for some cloud models, i.e special cases of the generic model, no Turing instabilities are possible. However, we also present a general class of cloud models, where Turing instabilities can occur. A key requisite is the occurrence of (weakly) nonlinear terms for accretion. Using numerical simulations for a special case of the general class of cloud models, we show spatial patterns of clouds in one and two spatial dimensions. From the numerical simulations we can see that the competition between collision terms and sedimentation is an important issue for the existence of pattern formation.