Readdressing convective-surface interaction in global climate models
A large part of our knowledge on climate change is provided by the usage of coupled atmospheric-ocean Global Climate Models (GCMs), which produce numerical simulations of the Earth’s climate system for both the present and the future. However, state-of-the-art GCMs show considerable systematic errors: they are limited by low spatial resolutions and by the problematic representation of many physical processes. In particular, one of the largest sources of uncertainty is associated with the coupling between the atmospheric circulation and the water cycle.
COGNAC is conceived as a fundamental theoretical project framed in this context. It aims at readdressing the representation of moist convection, clouds and precipitation and their interaction with the surface and the soil in GCMs. A recently developed theoretical framework capable of treating in a unified way the soil, the Planetary Boundary Layer (PBL), clouds, and both shallow and deep convection will be used. Such model - the Probabilistic Plume Model, PPM - is capable to represent the whole atmospheric column (from the PBL to the tropopause) with results comparable to Large Eddies Simulations and with a minor numerical cost. COGNAC aims at improving and refining the PPM and integrating it into two models, the LMDz GCM and the EC-Earth GCM, in the form a new unified parameterization. First evaluation will be carried out on Single Column Models, and hence extended to the full 3D case. Once operational, these new GCM configurations will provide a powerful tool to study complex interactions among surface, PBL and moist convection, as the ones occurring in the Sahel, the Amazon Rainforest or the Mediterranean region. These advancements will have notable potential for improving the representation, the forecast and the evaluation of the future changes of large-impact hydro-meteorological events.