Quantifying Aerosol-Cloud Interactions over the Western North Atlantic Ocean during the ACTIVATE Field Campaign

Aerosol-cloud interactions (ACI) pose the largest uncertainty for climate projection due to the poor understanding of nonlinear multi-scale processes and limited observations in various cloud regimes. One of the main challenges of understanding and representing ACI in climate models is to determine the relationship between cloud droplet number concentration N_c and aerosol number concentration N_a and the key physical processes governing N_a - N_c. Here we examine the N_a - N_c relationship in marine stratocumulus and shallow cumulus sampled during the Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). The N_a - N_c relationship is quantified primarily based on aerosol properties (e.g., aerosol size distribution f, composition X, and hygroscopicity k), vertical velocity w, and meteorological states (pressure P, temperature T, and water vapor mixing ratio q_v). We use these quantities from the ACTIVATE observations and large-eddy simulations as predictor variables to estimate N_c = G(f, X, k, w, P, T, q_v), which could be used to evaluate and improve the representation of ACI in climate models. Homogeneous and inhomogeneous mixing at cloud top and edges have been argued to generate strong fluctuations of cloud microphysical properties and, therefore, affect the N_a - N_c relationship. We particularly investigate the role of mixing process and its contribution to aerosol and cloud droplet size distribution using the ACTIVATE observations.