A total of sixteen global chemistry transport models and general circulation models have participated in this study. Fourteen models have been evaluated with regard to their ability to reproduce near-surface observed number concentration of aerosol particle and cloud condensation nuclei (CCN), and derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations, located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments, and on the seasonal and short-term variability in the aerosol properties.
There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50nm and >120 nm, and -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (
Revised: August 9, 2019 |
Published: July 8, 2019
Citation
Fanourgakis G.S., M. Kanakidou, A. Nenes, S.E. Bauer, T. Bergman, K.S. Carslaw, and A. Grini, et al. 2019.Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation.Atmospheric Chemistry and Physics 19, no. 13:8591-8617.PNNL-SA-143854.doi:10.5194/acp-19-8591-2019