Evaluation of a numerically efficient aerosol activation scheme by using worldwide cloud data from multiple field campaigns in continental and marine regions

This research summarizes a numerically efficient aerosol activation scheme and evaluates it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in China, Canada, Brazil, and Chile. The scheme employs a Quasi-steady state approximation of the cloud Droplet Growth Equation (QDGE) to efficiently simulate aerosol activation and vertical profiles of supersaturation and cloud droplet number concentration (CDNC) near the cloud base. We evaluated the scheme by specifying observed environmental thermodynamic variables and aerosol properties from 36 cloud cases as input and comparing the simulated CDNC and other simulated variables with cloud microphysical observations. The relative error (RE) of the mean simulated CDNC ranges from 15.27 % for Chile to 23.97 % for China, with an average of 19.69 %, indicating that the scheme successfully reproduces observed variations in CDNC over a wide range of different meteorological conditions and aerosol regimes. Subsequently, we carried out an error analysis by calculating the Maximum Information Coefficient (MIC) values between RE and individual input variables and sorted them by aerosol properties, pollution degree, environmental humidity, and dynamic condition according to their importance. Based on this analysis we find that the magnitude of the RE is sensitive to the specification of aerosol chemical composition and updraft velocity in the simulation, which can partly explain differences between simulated and observed CDNC in some of the regions.