A proper representation of aerosol properties is an essential first step in addressing potential impacts of aerosols on climate and clouds. In the context of temporal and spatial variability of concentration, size, and composition, maps of aerosol properties are usually based on insufficiently evaluated datasets of model simulations or satellite retrievals. Here, a new approach is offered. Quality data from ground-based remote-sensing networks are merged into multi-model median background fields. Global monthly maps are created (at a 1°xl° horizontal resolution) for aerosol column properties of aerosol optical depth (AOD), single-scattering albedo (ffl0), and Angstrom parameter (AnP, an easier to measure substitute for the asymmetry factor, g). Adopting the commonly observed bimodal size distribution shape for aerosol, AOD is partitioned into contributions from smaller (accumulation mode, radii: 0.05-0.50 p,m) and larger (coarse mode, radii >0.50 p,m) particle sizes. This simplifies the spectral extension of mid-visible optical properties and allows anthropogenic AOD estimates to be independent of interannual variations of (larger size) natural aerosol. The AOD is partitioned into its natural and anthropogenic components using global model estimates for the anthropogenic AOD fraction of all small particles, assuming that only small aerosol particles can be anthropogenic. Global modeling also provides the vertical distribution of AOD. Applying the arguments of Poschl et al. (see Part 2 of this chapter), namely, that hygroscopic growth of atmospheric aerosol particles is relatively well constrained, all necessary ingredients are assembled to derive global monthly maps for concentrations of cloud condensation nuclei (CCN) and to assess regional CCN enhancements as a result of anthropogenic activity.

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