Aerosol–cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Here we present a data set – ready to be used for model validation – of long-term observations of CCN number concentrations, particle number size distributions and chemical composition from 12 sites 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 background group, where CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behaviour, most continental stations exhibit very similar activation ratios (relative to particles > 20 nm) across the range of 0.1 to 1.0 % supersaturation. At the coastal sites the transition from particles being CCN inactive to becoming CCN active occurs over a wider range of the supersaturation spectrum. Several stations show strong seasonal cycles of CCN number concentrations and particle number size distributions, e.g. at Barrow (Arctic haze in spring), at the alpine stations (stronger influence of polluted boundary layer air masses in summer), the rain forest (wet and dry season) or Finokalia (wildfire influence in autumn). The rural background and urban sites exhibit relatively little variability throughout the year, while short-term variability can be high especially at the urban site. The average hygroscopicity parameter, κ , calculated from the chemical composition of submicron particles was highest at the coastal site of Mace Head (0.6) and lowest at the rain forest station ATTO (0.2–0.3). We performed closure studies based on κ –Köhler theory to predict CCN number concentrations. The ratio of predicted to measured CCN concentrations is between 0.87 and 1.4 for five different types of κ . The temporal variability is also well captured, with Pearson correlation coefficients exceeding 0.87. Information on CCN number concentrations at many locations is important to better characterise ACI and their radiative forcing. But long-term comprehensive aerosol particle characterisations are labour intensive and costly. Hence, we recommend operating “migrating-CCNCs” to conduct collocated CCN number concentration and particle number size distribution measurements at individual locations throughout one year at least to derive a seasonally resolved hygroscopicity parameter. This way, CCN number concentrations can only be calculated based on continued particle number size distribution information and greater spatial coverage of long-term measurements can be achieved.

There are few shipborne observations addressing the factors influencing the relationships of the formation and growth of aerosol particles with cloud condensation nuclei (CCN) in remote marine environments. In this study, the physical properties of aerosol particles throughout the Arctic Ocean and Pacific Ocean were measured aboard the Korean icebreaker R/V Araon during the summer of 2017 for 25 d. A number of new particle formation (NPF) events and growth were frequently observed in both Arctic terrestrial and Arctic marine air masses. By striking contrast, NPF events were not detected in Pacific marine air masses. Three major aerosol categories are therefore discussed: (1) Arctic marine (aerosol number concentration CN_2.5: 413±442 cm⁻³), (2) Arctic terrestrial (CN_2.5: 1622±1450 cm⁻³) and (3) Pacific marine (CN_2.5: 397±185 cm⁻³), following air mass back-trajectory analysis. A major conclusion of this study is not only that the Arctic Ocean is a major source of secondary aerosol formation relative to the Pacific Ocean but also that open-ocean sympagic and terrestrially influenced coastal ecosystems both contribute to shaping aerosol size distributions. We suggest that terrestrial ecosystems – including river outflows and tundra – strongly affect aerosol emissions in the Arctic coastal areas, possibly more than anthropogenic Arctic emissions. The increased river discharge, tundra emissions and melting sea ice should be considered in future Arctic atmospheric composition and climate simulations. The average CCN concentrations at a supersaturation ratios of 0.4 % were 35±40 cm⁻³, 71±47 cm⁻³ and 204±87 cm⁻³ for Arctic marine, Arctic terrestrial and Pacific marine aerosol categories, respectively. Our results aim to help evaluate how anthropogenic and natural atmospheric sources and processes affect the aerosol composition and cloud properties.

Cloud droplet spectral relative dispersion is critical to parameterizations of cloud radiative properties, warm‐rain initiation, and aerosol‐cloud interactions in models; however, there is no consistent relationship between relative dispersion and volume‐mean radius in literature, which hinders improving relative dispersion parameterization and calls for physical explanation. Here we show, by analyzing aircraft observations of cumulus clouds during Routine AAF [Atmospheric Radiation Measurement (ARM) Aerial Facility] Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations, that the correlation between relative dispersion and volume‐mean radius changes from positive to negative as volume‐mean radius increases. With the new observation, we postulate that the sign of the correlation is determined by whether or not condensation (evaporation) occurs simultaneously with significant new activation (deactivation). The hypothesis is validated by simulations of both an adiabatic cloud parcel model and a parcel model accounting for entrainment‐mixing. A new quantity, first bin strength, is introduced to quantify this new observation. Theoretical analysis of truncated gamma and modified gamma size distributions further supports the hypothesis and reconciles the contrasting relationships between relative dispersion and volume‐mean radius, including the results in polluted fog observations. The results could shed new light on the so‐called “twilight zone” between cloudy and cloud‐free air, which in turn affects evaluation of aerosol‐cloud interactions and retrieval of aerosol optical depth.

In 2019, an unusually strong positive Indian Ocean Dipole spawned hot and dry weather in southeastern Australia, which promoted devastating wildfires in the period from September 2019 to February 2020. The fires produced large plumes of biomass burning aerosols that prevented sunlight from reaching the Earth’s surface, and in this way elicited regional radiative cooling. We estimated the direct aerosol radiative forcing (ARF) resulting from these wildfires, based on Moderate Resolution Imaging Spectroradiometer space-based data and an empirical relationship from AErosol RObotic NETwork ground-based data collected in biomass-burning regions. The wildfire-derived air pollution was associated with an aerosol optical thickness of >0.3 in Victoria and a strongly negative ARF of between −14.8 and −17.7 W m⁻², which decreased the surface air temperature by about 3.7 °C–4.4 °C. This is of the same order of magnitude as the radiative cooling from volcanic eruptions. Although the atmospheric lifetime of biomass-burning aerosols is relatively short (about a week), the Australian wildfire pollution plumes extended across the Pacific Ocean to South America. Since climate change is expected to lead to more frequent and increasingly intense fires in many regions worldwide, the consequent biomass burning aerosols may become a significant radiative forcing factor, which will need to be accounted for in climate model projections for the future.