Observations of Aerosol-Cloud Interactions during the North Atlantic Aerosol and Marine Ecosystem Study

Cloud droplet number concentration, N_d, which influences planetary albedo, is driven by the presence of cloud condensation nuclei (CCN) in the atmosphere. Many mechanisms of aerosol-cloud interactions have been identified, including the "cloud albedo effect" or first indirect effect. All else equal, more CCN lead to smaller droplets, which sediment slower (leading to faster cloud-top entrainment) and coalesce to raindrop size less efficiently, thereby suppressing precipitation. Depending on conditions, increased droplet number concentrations can increase or decrease cloud liquid water path and cloud cover. Such secondary indirect effects are can amplify or diminish the first indirect effect of aerosols on radiative fluxes.

We present data that has been collected during the North Atlantic and Marine Ecosystems Study (NAAMES), which is a multiple air-campaign study intended in part to better determine the relationship and seasonal cycle between marine aerosols and cloud properties. Over the North Atlantic, natural variations in marine particle sources occur as a result of seasonal changes in ecosystem properties and meteorology. Cloud properties (including: N_d and other size distribution parameters, cloud optical thickness and cloud physical thickness) are all retrieved using remote sensing data of the Research Scanning Polarimeter (RSP). Aerosol concentrations and chemical composition are measured using in situ aerosol instruments. Our results show how variations in CCN concentration and composition correlate with variations in cloud micro- and macro-physical properties. A 46% increase in CCN concentrations is observed during NAAMES-2 (spring) when compared with the NAAMES-1 (fall) campaign. A corresponding cloud seasonal cycle is seen whereby cloud droplets with large effective radii (R_eff) and low N_d are observed during the fall campaign and, conversely, smaller R_eff with high N_d are observed in the spring. Throughout both campaigns a correlation coefficient of 0.82 is found between N_d and CCN concentrations. As expected, a negative correlation coefficient of -0.69 is found between the mean R_eff and CCN concentration. We find a weak positive correlation between cloud optical thickness and CCN concentration and also between cloud physical thickness and CCN concentration. We use aerosol chemical composition and meteorological considerations to attribute primary drivers of seasonal changes in cloud properties. With the abundance of in situ and remote sensing instruments involved, this campaign provides an excellent opportunity to study aerosol-cloud interactions.