A competition–species model for water vapour-aerosol-cloud-rain interactions.

• Three non-linear differential equations are proposed to examine water vapour-aerosol-cloud-rain interactions. • Some macro features of warm clouds are captured efficiently by the model. • The model behaves similarly as era5 reanalyses. • Satellite data confirms the promising ability of this species-competition model. • An optimization scheme is developed to determine important theoretical parameters difficult to access. In this paper, a non-linear bulk model inspired from species competition dynamics is proposed in order to describe the physics of water vapour-aerosol-cloud-rain interactions. Despite the complexity of such interactions, certain non-trivial aspects of the macro behavior of a cloud are predictable without concerning the full complexity of the dynamical system. The model is for warm clouds (no ice) and it consists in a set of three non-linear differential equations. This species-competition model is confronted with in situ measurements in different situations: for pristine environments (1) at the high-altitude Maïdo Observatory (Indian Ocean, Reunion Island) and (2) in a pure oceanic context around the Reunion Island (aeromarine field campaign) and for a continental urban context (3) in Lille (North of France). Compared with observations (radar, radiometric measurements), it is shown that, whatever the situation considered, the model reproduces efficiently the macro features of clouds, like cloud occurrences, cloud water content magnitudes, and cloud-rain links. The model is adapted to a two-dimensional (horizontal) grid and its predictions are compared with the era5 reanalyses above the Hauts-de-France region and in the pristine Southwest Indian Ocean (around Reunion Island). Furthermore, satellite data enable to corroborate that the model clearly shows promising results for the horizontal cloud field organization. The spatiotemporal resolution of this model is adaptable according to the needs and it can be used in any region and at the desired altitude provided that data be available for implementation. In this paper, it is also suggested that the model may be fruitful to derive from measurements, by means of an optimization scheme, different theoretical parameters not easy to determine. The model runs on a laptop with a relatively short time (of the order of the minute); it is not intended to supplant comprehensive models, but it may be fruitful to understand the essential mechanisms in warm cloud formation. [ABSTRACT FROM AUTHOR]