Journal Article

Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation

Makkonen, Risto, Kodros, John K., Wu, Mingxuan, Mahowald, Natalie M., Westervelt, Daniel M., Yoshioka, Masaru, Lohmann, Ulrike, Gysel-Beer, Martin, Daskalakis, Nikos, Pierce, Jeffrey R., Myriokefalitakis, Stelios, Tsimpidi, Alexandra P., Luo, Gan, Kanakidou, Maria, Nenes, Athanasios, Decesari, Stefano, Grini, Alf, Wang, Hailong, Sfakianaki, Maria, Bergman, Tommi, Carslaw, Ken S., Yang, Yang, Karydis, Vlassis A., Neubauer, David, Schrodner, Roland, Stier, Philip, Kalivitis, Nikos, Bauer, Susanne E., Fanourgakis, George S., Yu, Fangqun, Hamilton, Douglas S., Liu, Xiaohong, Kirkevag, Alf, Watson-Parris, Duncan, Matsui, Hitoshi, Tsigaridis, Kostas, van Noije, Twan, Johnson, Jill S., Schmale, Julia

2019

Overview

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as 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 > 50 and > 120nm, as well as -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 (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer.

• Publisher: European Geosciences Union,Copernicus GmbH,Copernicus Publications
• Subject: Aerosol concentrations / Aerosol effects / Aerosol formation / Aerosol measurements / Aerosol particles / Aerosol properties / Aerosol-cloud interactions / Aerosols / Bias / Cloud condensation nuclei / Cloud droplet concentration / Cloud droplet formation / Cloud formation / Cloud-climate relationships / Clouds / Clouds (Meteorology) / Comparative analysis / Composition / Computer simulation / Condensates / Condensation / Condensation nuclei / Droplets / Dry deposition / Earth and Related Environmental Sciences / ENVIRONMENTAL SCIENCES / Evaluation / General circulation models / Geovetenskap och relaterad miljövetenskap / Global aerosols / Meteorologi och atmosfärsvetenskap / Meteorology and Atmospheric Sciences / Meteorology And Climatology / Natural Sciences / Naturvetenskap / Nucleus / open climate campaign / Organic chemistry / Parameter uncertainty / Parameters / Particle composition / Particle formation / Polar environments / Polar regions / Properties / Seasonal variability / Seasonal variation / Seasonal variations / Secondary aerosols / Stations / Summer / Supersaturation / Velocity / Winter