In the framework of the MarParCloud (Marine biological production, organic aerosol particles and marine clouds: a Process Chain) project, measurements were carried out on the islands of Cape Verde, to investigate the abundance, properties, and sources of aerosol particles in general and cloud condensation nuclei (CCN) in particular, both close to sea and cloud level heights.A thorough comparison of particle number concentration (PNC), particle number size distribution (PNSD) and CCN number 5 concentration (N CCN ) at the Cape Verde Atmospheric Observatory (CVAO, sea level station) and Monte Verde (MV, cloud level station) reveals that during times without clouds the aerosol at CVAO and MV are similar and the boundary layer is generally well mixed. Therefore, data obtained at CVAO can be used to describe the aerosol particles at cloud level. Cloud events were observed at MV during roughly 58% of the time and during these, a large fraction of particles were activated to cloud droplets.A trimodal parameterization method was deployed to characterize PNC at CVAO. Based on number concentrations in dif-10 ferent aerosol modes, four well separable types of PNSDs were found, which were named the marine type, mixture type, dust type1 and dust type2. Aerosol particles differ depending on their origins. When the air masses came from the Atlantic Ocean, sea spray can be assumed to be one source for particles, besides for new particle formation. For these air masses, PNSDs featured the lowest number concentration in Aitken, accumulation and coarse mode. Particle number concentrations for the sea spray aerosol (SSA, i.e., the coarse mode for these air masses) accounted for about 3.7% of N CCN,0.30% (CCN number concen-15 tration at 0.30% supersaturation) and about 1.1% to 4.4% of N total (total particle number concentration). When the air masses came from the Saharan desert, we observed enhanced Aitken, accumulation and coarse mode particle number concentrations and overall increased N CCN . N CCN,0.30% during the strongest observed dust periods is about 2.5 times higher than that during marine periods. However, the particle hygroscopicity parameter κ for these two most different periods shows no significant difference and is generally similar, independent of air mass. 20Overall, κ averaged 0.28, suggesting the presence of organic material in particles. This is consistent with previous model work and field measurement. There is a slight increase of κ with increasing particle size, indicating the addition of soluble, likely inorganic material during cloud processing.

Polar environments are among the fastest changing regions on the planet. It is a crucial time to make significant improvements in our understanding of how ocean and ice biogeochemical processes are linked with the atmosphere. This is especially true over Antarctica and the Southern Ocean where observations are severely limited and the environment is far from anthropogenic influences. In this commentary, we outline major gaps in our knowledge, emerging research priorities, and upcoming opportunities and needs. We then give an overview of the large-scale measurement campaigns planned across Antarctica and the Southern Ocean in the next 5 years that will address the key issues. Until we do this, climate models will likely continue to exhibit biases in the simulated energy balance over this delicate region. Addressing these issues will require an international and interdisciplinary approach which we hope to foster and facilitate with ongoing community activities and collaborations.

Abstract.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). Numerous observations of CCN number concentration exist, and many closure studies have been performed to predict CCN number concentrations based on particle number size 5 distributions, chemical composition, and the κ-Köhler theory. Most of these studies provide details for short time periods or focus on special environmental conditions. These observations, however, cannot address questions of large-scale temporal and spatial CCN variability. Here we analyze long-term observations of CCN number concentrations, particle number size distributions and chemical composition from twelve sites on three continents. Eight of these stations are part of the European Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS). 10We group the observatories into categories according to their official classification: coastal background (Barrow, Alaska; Mace Head, Ireland; Finokalia, Crete; Noto Peninsula, Japan), rural background (Melpitz, Germany; Cabauw, the Netherlands; Vavihill, Sweden), alpine sites (Puy de Dôme, France; Jungfraujoch, Switzerland), remote forest sites (ATTO, Brazil; SMEAR, Finland) and the urban environment (Seoul, South Korea). Expectedly, CCN characteristics are highly variable across regions. However, they also vary within categories, most strongly in the coastal background group, where 15 CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behavior, most continental stations exhibit very similar relative activation ratios across the range of 0.1 to 1.0 % supersaturation. At the coastal sites the activation ratios spread more widely across the SS spectrum.Several stations show strong seasonal cycles of CCN number concentrations and particle number size distributions, e.g., atBarrow (Arctic Haze in spring), at the alpine stations (stronger influence of polluted boundary layer air masses in summer), 20 the rain forest (wet and dry season), or Finokalia (forest fire influence in fall). 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 the lowest at the rain forest station ATTO (0.2 -0.3). We performed closure studies to predict CCN number concentrations from the particle number size distribution and chemical composition measurements. 25The prediction accuracy for the average concentrations is high. The ratio between predicted and measured CCN concentrations is between 0.87 and 1.4. The temporal variability is also well represented, as reflected by Pearson c...

Abstract. The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter term variations, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a sparse Principal Component Analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. More specifically, we identify: the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as source processes near “hotspots” for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper ocean layer light intensity, surface wind speed and relative humidity, played an important role in the majority of latent variables, highlighting their importance for a large variety of processes and the necessity for Earth System Models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.

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