Sensitivity of Simulated Aerosol and Cloud Properties to New Particle Formation and Aerosol Activation Parameterizations

Cloud properties are sensitive to the number concentrations and chemical composition of aerosols that can serve as cloud condensation nuclei (CCN). In this work, we will study the sensitivity of simulated aerosol and cloud properties to homogeneous nucleation and aerosol activation parameterizations using the Global-through-Urban Weather Research and Forecasting Model with Chemistry (GU-WRF/Chem) on a global scale. Several new particle formation parameterizations (e.g., binary, ternary, and ice-mediated), two aerosol activation parameterizations (i.e., the Abdul-Razzak and Ghan (A-R & G) and the Fountoukis and Nenes (FN)), and their combinations are being compared in the box models and will be further evaluated in the 3-D GU-WRF/Chem. Using identical CCN spectra and kinetic parameters (e.g., mass accommodation coefficient of water of 1.0), we compare the modal versions of AR-G and FN parameterizations for a single aerosol type (sulfate) under three atmospheric conditions (i.e., North Atlantic, Polluted Continent, Southern Ocean) with temperatures of 250-300 K, pressures of 500-1000 mb, and updraft velocities (0.01-5.0 m s-1) and found that FN gives higher maximum supersaturations thus higher activation fractions than AR-G under all test conditions. For example, under the test conditions of 283 K, 800 mb, and updraft velocities of 0.5 and 3.0 m s-1, FN gives activation fractions that are higher than AR-G by 41.4% and 12.4%, 16.2% and 16.6%, and 96.6% and 42.1% under the North Atlantic, Polluted Continent, Southern Ocean conditions, respectively. The differences in simulated aerosol properties (e.g., mass and number concentrations and size distributions) and cloud properties (e.g., CCN, cloud droplet number concentrations and cloud effective radius) with different parameterizations will be examined in both box and 3-D models. Their impacts on simulated aerosol-cloud-climate interactions and associated uncertainties will be discussed.