Reallocation in modal aerosol models: impacts on predicting aerosol radiative effects

Atmospheric models often represent the aerosol particle size distribution with a modal approach, in which particles are described with log-normal modes within predetermined size ranges. This approach reallocates particles numerically from one mode to another for example during particle growth, potentially leading to artificial changes in the aerosol size distribution. In this study we analysed how the modal reallocation affects climate-relevant variables: cloud droplet number concentration (CDNC), aerosol-cloud interaction parameter (ACI) and light extinction coefficient (q(ext)). The ACI parameter gives the response of CDNC to a change in total aerosol number concentration. We compared these variables between a modal model (with and without reallocation routines) and a high resolution sectional model, which was considered a reference model. We analysed the relative differences in the chosen variables in four experiments designed to assess the influence of atmospheric aerosol processes. We find that limiting the allowed size ranges of the modes, and subsequent remapping of the distribution, leads almost always to an underestimation of cloud droplet number concentrations (by up to 100 %) and an overestimation of light extinction (by up to 20 %). On the other hand, the aerosol-cloud interaction parameter can be either over-or underestimated by the reallocating model, depending on the conditions. For example, in the case of atmospheric new particle formation events followed by rapid particle growth, the reallocation can cause on average a 10% overestimation of the ACI parameter. Thus it is shown that the reallocation affects the ability of a model to estimate aerosol climate effects accurately, and this should be taken into account when using and developing aerosol models.