Morphology Of stratocumulus, BoundarY-layer DYnamics, and Climate Change – MOBYDYC

Stratocumulus clouds are boundary-layer clouds that reflect a significant amount of the incoming solar radiation and that organize in various ways. Errors in representing such clouds in climate models are responsible for systematic biases and uncertainties in global warming projections.
This project aims at improving our knowledge in low-cloud feecback mechanisms, by investigating boundary-layer processes associated with stratocumulus clouds and their links with their structural morphology.
First, we will use satellite images by characterizing the different spatial organizations that these clouds can take through an unsupervised machine-learning method. The covariations of these cloud regimes with the surrounding environment over the long periods available (about 20 years) will allow us to quantify the low-frequency morphological sensitivity of stratocumulus clouds.
The second part of the project will consist in simulating the different observed morphologies using the high-resolution Meso-NH model and to analyze the processes controlling them. The object-oriented identification of coherent structures characterizing the boundary-layer dynamics will allow to establish a conceptual vision of the spatial organization, and thus to provide insights for improving the representation of the cloudy boundary layers in climate models.
The last part will analyze the sensitivity of coherent structures in perturbed boundary-layer simulations in order to establish innovative physical mechanisms of low-cloud feedback. The observed variability of cloud morphologies will serve as an observational constraint to these simulations, and to the physical interpretation we deduced from their analysis.
Therefore, this project aims at linking visible information given by the cloud spatial organization to invisible structures that control the life cycle of boundary layers for studying and better constraining low-cloud feedback.