2013, Westervelt, D.M., Pierce, J.R., Riipinen, I., Trivitayanurak, W., Hamed, A., Kulmala, M., Laaksonen, A., Decesari, S., Adams, P.J.

Aerosol nucleation occurs frequently in the atmosphere and is an important source of particle number. Observations suggest that nucleated particles are capable of growing to sufficiently large sizes that they act as cloud condensation nuclei (CCN), but some global models have reported that CCN concentrations are only modestly sensitive to large changes in nucleation rates. Here we present a novel approach for using long-term size distribution observations to evaluate a global aerosol model's ability to predict formation rates of CCN from nucleation and growth events. We derive from observations at five locations nucleation-relevant metrics such as nucleation rate of particles at diameter of 3 nm (J3), diameter growth rate (GR), particle survival probability (SP), condensation and coagulation sinks, and CCN formation rate (J100). These quantities are also derived for a global microphysical model, GEOS-Chem-TOMAS, and compared to the observations on a daily basis. Using GEOS-Chem-TOMAS, we simulate nucleation events predicted by ternary (with a 10−5 tuning factor) or activation nucleation over one year and find that the model slightly understates the observed annual-average CCN formation mostly due to bias in the nucleation rate predictions, but by no more than 50% in the ternary simulations. At the two locations expected to be most impacted by large-scale regional nucleation, Hyytiälä and San Pietro Capofiume, predicted annual-average CCN formation rates are within 34 and 2% of the observations, respectively. Model-predicted annual-average growth rates are within 25% across all sites but also show a slight tendency to underestimate the observations, at least in the ternary nucleation simulations. On days that the growing nucleation mode reaches 100 nm, median single-day survival probabilities to 100 nm for the model and measurements range from less than 1–6% across the five locations we considered; however, this does not include particles that may eventually grow to 100 nm after the first day. This detailed exploration of new particle formation and growth dynamics adds support to the use of global models as tools for assessing the contribution of microphysical processes such as nucleation to the total number and CCN budget.

2012, Pietikäinen, J.-P., O'Donnell, D., Teichmann, C., Karstens, U., Pfeifer, S., Kazil, J., Podzun, R., Fiedler, S., Kokkola, H., Birmili, W., O'Dowd, C., Baltensperger, U., Weingartner, E., Gehrig, R., Spindler, G., Kulmala, M., Feichter, J., Jacob, D., Laaksonen, A.

REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes most of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM is coupled with a two-moment stratiform cloud scheme. On the other hand, REMO-HAM does not include an online coupled aerosol-radiation nor a secondary organic aerosol module. In this work, we evaluate the model and compare the results against ECHAM5-HAM and measurements. Four different measurement sites were chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50 × 50 km2 and 10 × 10 km2. Based on our simulations, REMO-HAM is in reasonable agreement with the measured values. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. Since we did not use activation nor kinetic nucleation for the boundary layer, the total number concentrations are somewhat underestimated. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we show that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.