Alex Ayet

This study evaluates the ability of the French convection‐permitting model AROME‐OM to represent shallow cumulus and their main organisations for boreal winter conditions in the North Atlantic trades. It uses a set of three winter seasons (January–February, 2018–2020) of high‐resolution (1.3 and 2.5 km) simulations over the Caribbean domain (9.7–22.9°N, 75.3–51.7°W). The model is assessed against soundings at Grantley Adams Airport and remote‐sensing observations at a site located on the east coast of Barbados which is representative of downwind trade regimes. The thermodynamic environment of the model fits the observations overall but the boundary layer is slightly too deep, resulting in a weak cold and dry bias. Both model and observations clearly exhibit (a) a double peak of cloud fraction, a first peak near the cloud base and a second one near the cloud top and (b) a larger variance in cloudiness near the top of the deepest cumuli, at around 2 km, with a higher sensitivity to the environment. We then take advantage of the EUREC 4 A field campaign which took place in January–February 2020 to assess the ability of the model to reproduce the four main mesoscale patterns and to characterize the air masses in which they develop. All the observations confirm the capacity of the model to predict the different mesoscale organizations and their associated environment.