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. Aerosol–cloud interactions (ACI) constitute the single largest uncertaintyin anthropogenic radiative forcing. To reduce the uncertainties and gainmore confidence in the simulation of ACI, models need to be evaluatedagainst observations, in particular against measurements of cloudcondensation nuclei (CCN). Here we present a data set – ready to be used formodel validation – of long-term observations of CCN number concentrations,particle number size distributions and chemical composition from 12sites on 3 continents. Studied environments include coastal background,rural background, alpine sites, remote forests and an urban surrounding.Expectedly, CCN characteristics are highly variable across site categories.However, they also vary within them, most strongly in the coastal backgroundgroup, where CCN number concentrations can vary by up to a factor of 30within one season. In terms of particle activation behaviour, mostcontinental stations exhibit very similar activation ratios (relative toparticles  >  20 nm) across the range of 0.1 to 1.0 %supersaturation. At the coastal sites the transition from particles beingCCN inactive to becoming CCN active occurs over a wider range of thesupersaturation spectrum. Several stations show strong seasonal cycles of CCN number concentrationsand particle number size distributions, e.g. at Barrow (Arctic haze inspring), at the alpine stations (stronger influence of polluted boundarylayer air masses in summer), the rain forest (wet and dry season) orFinokalia (wildfire influence in autumn). The rural background and urbansites exhibit relatively little variability throughout the year, whileshort-term variability can be high especially at the urban site. The average hygroscopicity parameter, κ , calculated from thechemical composition of submicron particles was highest at the coastal siteof Mace Head (0.6) and lowest at the rain forest station ATTO (0.2–0.3).We performed closure studies based on κ –Kohler theoryto predict CCN number concentrations. The ratio of predicted to measured CCNconcentrations is between 0.87 and 1.4 for five different types of  κ .The temporal variability is also well captured, with Pearsoncorrelation coefficients exceeding 0.87. Information on CCN number concentrations at many locations is important tobetter characterise ACI and their radiative forcing. But long-termcomprehensive aerosol particle characterisations are labour intensive andcostly. Hence, we recommend operating “migrating-CCNCs” to conductcollocated CCN number concentration and particle number size distributionmeasurements at individual locations throughout one year at least to derivea seasonally resolved hygroscopicity parameter. This way, CCN numberconcentrations can only be calculated based on continued particle number sizedistribution information and greater spatial coverage of long-termmeasurements can be achieved.

atmospheric chemistry and physics

Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories