CCN measurements during ACE-2 and their relationship to cloud microphysical properties

Abstract

Measurements of cloud condensation nuclei (CCN) concentration at 0.1% supersaturation were made onboard the CIRPAS Pelican over the northeast Atlantic during June and July, 1997, in the vicinity of Tenerife, Spain, as part of the second Aerosol Characterization Experiment (ACE-2). The average CCN concentration (N_(ccn)) in the marine boundary layer for clean air masses was 27±8 and 42±14 cm⁻³ for cloudy and clear conditions, respectively, consistent with measurements made near the British Isles and close to Tasmania, Australia, during ACE-1 for similar conditions. A local CCN closure experiment was conducted. Measured N_(ccn) is compared with predictions based on aerosol number size distributions and size-resolved chemical composition profiles determined from measurements and the literature. A sublinear relationship between measured and predicted N_(ccn), N_(ccn)∼N^(0.51)_(ccn,predicted), was found. This result is consistent with some previous studies, but others have obtained results much closer to the expected 1 : 1 relationship between measured and predicted N_(ccn). A large variability between measured and predicted N_(ccn) was also observed, leading to the conclusion that, for 95% of the data, the predictions agree with measurements to within a factor of 11. Relationships between below-cloud N_(ccn) and aerosol accumulation mode concentration, and in-cloud cloud droplet number concentration, measured onboard the Pelican and the Météo-France Merlin-IV, respectively, are calculated for periods while the 2 aircraft were in close proximity at approximately the same time. Measured relationships are reproduced by an adiabatic parcel model, and are also consistent with some previous studies. However, the shape of the CCN spectrum, or the aerosol size distribution, and the updraft velocity are predicted by the model to affect these relationships to a significant extent. Therefore, parameterizations of cloud microphysical properties need to include these variables to accurately predict cloud droplet number concentration. A relationship between N_(ccn) and cloud droplet effective diameter is also calculated and shown to be consistent both with the literature and with the parameterization of effective diameter proposed by Martin et al.

Additional details