Study of thermodynamic properties of cumulus clouds: from strategy design in numerical simulation to application during a measurement campaign

Abstract:

Trade wind cumulus clouds have a significant impact on the Earth's radiative balance, due to their extensive coverage in subtropical regions. The feedback of low clouds on the climate system as well as biases still existing in their representation in Global Climate Models (GCMs) results in a climatic response with relatively large uncertainty and induce a significant divergence in GCMs. Indeed, shallow convection is parametrized in GCM due to the characteristic size of cumulus clouds and their development is still underestimated (Nuijens et al., 2015). Many studies and campaigns have focused on a better understanding of the thermodynamic properties of cumulus clouds with ground-based and satellite-based remote sensing and also in-situ airborne observations. However, few studies provide information on the multi-dimensional properties of individual cumulus clouds. The development of a fleet of UAVs contributes to an increase in the resolution of these observations with an ability to move rapidly. Miniaturized instruments installed on a UAV and permit following a cloud in time and space thus allowing to detail the microphysical heterogeneities due to mixing to be detailed.Our understanding of cumulus clouds is also based on high-resolution numerical simulations (LES) that reproduce the average characteristics of cumulus clouds fairly reliably, but these simulations still depend on parametrizations turbulence and microphysics. An experimental strategy has been developed using LES simulation of a cumulus field for the BOMEX case (Siebesma et al., 2003) with the Meso-NH model. The 12km x12km x 4km domain with a spatial resolution of 25m, and model outputs every 5s for 30 minutes allow high-frequency monitoring of cloud evolution. A cloud identification method was used to track individual clouds from their creation to their dissipation. The UAVs adaptively sampled an individual cumulus cloud to create a horizontal cross section of the cloud optical properties using Gaussian process regression to map the cloud. We will also report the first results of observations obtained by a fleet of UAVs deployed during the EUREC4A campaign in Barbados in 2020. Several cumulus clouds were followed for at least ten minutes, and their thermodynamic evolution has been compared with those of cumulus clouds simulated in a BOMEX case.