1NASA Goddard Institute for Space Studies, and Center for Climate Systems Research, Columbia University, New York, NY, USA
2Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
3Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA
4Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA
5Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada
Received: 16 Dec 2012 – Discussion started: 07 Feb 2013
Abstract. In models, nucleation mode (1 nm < Dp < 10 nm) particle microphysics can be represented explicitly with aerosol microphysical processes or can be parameterized to obtain the growth and survival of nuclei to the model's lower size boundary. This study investigates how the representation of nucleation mode microphysics impacts aerosol number predictions in the TwO-Moment Aerosol Sectional (TOMAS) aerosol microphysics model running with the GISS GCM II-prime by varying its lowest diameter boundary: 1 nm, 3 nm, and 10 nm. The model with the 1 nm boundary simulates the nucleation mode particles with fully resolved microphysical processes, while the model with the 10 nm and 3 nm boundaries uses a nucleation mode dynamics parameterization to account for the growth of nucleated particles to 10 nm and 3 nm, respectively. We also investigate the impact of the time step for aerosol microphysical processes (a 10 min versus a 1 h time step) to aerosol number predictions in the TOMAS models with explicit dynamics for the nucleation mode particles (i.e., 3 nm and 1 nm boundary). The model with the explicit microphysics (i.e., 1 nm boundary) with the 10 min time step is used as a numerical benchmark simulation to estimate biases caused by varying the lower size cutoff and the time step. Different representations of the nucleation mode have a significant effect on the formation rate of particles larger than 10 nm from nucleated particles (J10) and the burdens and lifetimes of ultrafine-mode (10 nm ≤ Dp ≤ 70 nm) particles but have less impact on the burdens and lifetimes of CCN-sized particles. The models using parameterized microphysics (i.e., 10 nm and 3 nm boundaries) result in higher J10 and shorter coagulation lifetimes of ultrafine-mode particles than the model with explicit dynamics (i.e., 1 nm boundary). The spatial distributions of CN10 (Dp ≥ 10 nm) and CCN(0.2%) (i.e., CCN concentrations at 0.2% supersaturation) are moderately affected, especially CN10 predictions above ~ 700 hPa where nucleation contributes most strongly to CN10 concentrations. The lowermost-layer CN10 is substantially improved with the 3 nm boundary (compared to 10 nm) in most areas. The overprediction in CN10 with the 3 nm and 10 nm boundaries can be explained by the overprediction of J10 or J3 with the parameterized microphysics, possibly due to the instantaneous growth rate assumption in the survival and growth parameterization. The errors in CN10 predictions are sensitive to the choice of the lower size boundary but not to the choice of the time step applied to the microphysical processes. The spatial distribution of CCN(0.2%) with the 3 nm boundary is almost identical to that with the 1 nm boundary, but that with the 10 nm boundary can differ more than 10–40% in some areas. We found that the deviation in the 10 nm simulations is partly due to the longer time step (i.e., 1 h time step used in the 10 nm simulations compared to 10 min time step used in the benchmark simulations), but, even with the same time step, the 10 nm cutoff showed noticeably higher errors than the 3 nm cutoff. In conclusion, we generally recommend using a lower diameter boundary of 3 nm for studies focused on aerosol indirect effects but down to 1 nm boundary for studies focused on CN10 predictions or nucleation.
Revised: 06 Jun 2013 – Accepted: 18 Jun 2013 – Published: 13 Aug 2013
Lee, Y. H., Pierce, J. R., and Adams, P. J.: Representation of nucleation mode microphysics in a global aerosol model with sectional microphysics, Geosci. Model Dev., 6, 1221-1232, doi:10.5194/gmd-6-1221-2013, 2013.