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- ItemLong-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories(Katlenburg-Lindau : EGU, 2018) Schmale, Julia; Henning, Silvia; Decesari, Stefano; Henzing, Bas; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Pöhlker, Mira L.; Brito, Joel; Bougiatioti, Aikaterini; Kristensson, Adam; Kalivitis, Nikos; Stavroulas, Iasonas; Carbone, Samara; Jefferson, Anne; Park, Minsu; Schlag, Patrick; Iwamoto, Yoko; Aalto, Pasi; Äijälä, Mikko; Bukowiecki, Nicolas; Ehn, Mikael; Frank, Göran; Fröhlich, Roman; Frumau, Arnoud; Herrmann, Erik; Herrmann, Hartmut; Holzinger, Rupert; Kos, Gerard; Kulmala, Markku; Mihalopoulos, Nikolaos; Nenes, Athanasios; O'Dowd, Colin; Petäjä, Tuukka; Picard, David; Pöhlker, Christopher; Pöschl, Ulrich; Poulain, Laurent; Prévôt, André Stephan Henry; Swietlicki, Erik; Andreae, Meinrat O.; Artaxo, Paulo; Wiedensohler, Alfred; Ogren, John; Matsuki, Atsushi; Yum, Seong Soo; Stratmann, Frank; Baltensperger, Urs; Gysel, MartinAerosol-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 20nm) 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, 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 -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 . 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.
- ItemStatus and future of numerical atmospheric aerosol prediction with a focus on data requirements(Katlenburg-Lindau : EGU, 2018) Benedetti, Angela; Reid, Jeffrey S.; Knippertz, Peter; Marsham, John H.; Di Giuseppe, Francesca; Rémy, Samuel; Basart, Sara; Boucher, Olivier; Brooks, Ian M.; Menut, Laurent; Mona, Lucia; Laj, Paolo; Pappalardo, Gelsomina; Wiedensohler, Alfred; Baklanov, Alexander; Brooks, Malcolm; Colarco, Peter R.; Cuevas, Emilio; da Silva, Arlindo; Escribano, Jeronimo; Flemming, Johannes; Huneeus, Nicolas; Jorba, Oriol; Kazadzis, Stelios; Kinne, Stefan; Popp, Thomas; Quinn, Patricia K.; Sekiyama, Thomas T.; Tanaka, Taichu; Terradellas, EnricNumerical prediction of aerosol particle properties has become an important activity at many research and operational weather centers. This development is due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, climate services providers, and health professionals. Owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions, the prediction of aerosol particle concentrations and properties in the numerical weather prediction (NWP) framework faces a number of challenges. The modeling of numerous aerosol-related parameters increases computational expense. Errors in aerosol prediction concern all processes involved in the aerosol life cycle including (a) errors on the source terms (for both anthropogenic and natural emissions), (b) errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), and (c) errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transformation and growth, hygroscopicity). Finally, there are fundamental uncertainties and significant processing overhead in the diverse observations used for verification and assimilation within these systems. Indeed, a significant component of aerosol forecast development consists in streamlining aerosol-related observations and reducing the most important errors through model development and data assimilation. Aerosol particle observations from satellite- and ground-based platforms have been crucial to guide model development of the recent years and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near surface, and aircraft) and freely shared. This paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centers. While some of the requirements are equally applicable to aerosol-climate, the focus here is on global operational prediction of aerosol properties such as mass concentrations and optical parameters. It is also recognized that the term "requirements" is loosely used here given the diversity in global aerosol observing systems and that utilized data are typically not from operational sources. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of "bin" and bulk schemes with limited capability of simulating the size information. However the next generation of aerosol operational models will output both mass and number density concentration to provide a more complete description of the aerosol population. A brief overview of the state of the art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements.
- ItemA European aerosol phenomenology - 6: Scattering properties of atmospheric aerosol particles from 28 ACTRIS sites(Katlenburg-Lindau : EGU, 2018) Pandolfi, Marco; Alados-Arboledas, Lucas; Alastuey, Andrés; Andrade, Marcos; Angelov, Christo; Artiñano, Begoña; Backman, John; Baltensperger, Urs; Bonasoni, Paolo; Bukowiecki, Nicolas; Collaud Coen, Martine; Conil, Sébastien; Coz, Esther; Crenn, Vincent; Dudoitis, Vadimas; Ealo, Marina; Eleftheriadis, Kostas; Favez, Olivier; Fetfatzis, Prodromos; Fiebig, Markus; Flentje, Harald; Ginot, Patrick; Gysel, Martin; Henzing, Bas; Hoffer, Andras; Holubova Smejkalova, Adela; Kalapov, Ivo; Kalivitis, Nikos; Kouvarakis, Giorgos; Kristensson, Adam; Kulmala, Markku; Lihavainen, Heikki; Lunder, Chris; Luoma, Krista; Lyamani, Hassan; Marinoni, Angela; Mihalopoulos, Nikos; Moerman, Marcel; Nicolas, José; O'Dowd, Colin; Petäjä, Tuukka; Petit, Jean-Eudes; Pichon, Jean Marc; Prokopciuk, Nina; Putaud, Jean-Philippe; Rodríguez, Sergio; Sciare, Jean; Sellegri, Karine; Swietlicki, Erik; Titos, Gloria; Tuch, Thomas; Tunved, Peter; Ulevicius, Vidmantas; Vaishya, Aditya; Vana, Milan; Virkkula, Aki; Vratolis, Stergios; Weingartner, Ernest; Wiedensohler, Alfred; Laj, PaoloThis paper presents the light-scattering properties of atmospheric aerosol particles measured over the past decade at 28 ACTRIS observatories, which are located mainly in Europe. The data include particle light scattering (σsp) and hemispheric backscattering (σbsp) coefficients, scattering Ångström exponent (SAE), backscatter fraction (BF) and asymmetry parameter (g). An increasing gradient of σsp is observed when moving from remote environments (arctic/mountain) to regional and to urban environments. At a regional level in Europe, σsp also increases when moving from Nordic and Baltic countries and from western Europe to central/eastern Europe, whereas no clear spatial gradient is observed for other station environments. The SAE does not show a clear gradient as a function of the placement of the station. However, a west-to-east-increasing gradient is observed for both regional and mountain placements, suggesting a lower fraction of fine-mode particle in western/south-western Europe compared to central and eastern Europe, where the fine-mode particles dominate the scattering. The g does not show any clear gradient by station placement or geographical location reflecting the complex relationship of this parameter with the physical properties of the aerosol particles. Both the station placement and the geographical location are important factors affecting the intraannual variability. At mountain sites, higher σsp and SAE values are measured in the summer due to the enhanced boundary layer influence and/or new particle-formation episodes. Conversely, the lower horizontal and vertical dispersion during winter leads to higher σsp values at all low-altitude sites in central and eastern Europe compared to summer. These sites also show SAE maxima in the summer (with corresponding g minima). At all sites, both SAE and g show a strong variation with aerosol particle loading. The lowest values of g are always observed together with low σsp values, indicating a larger contribution from particles in the smaller accumulation mode. During periods of high σsp values, the variation of g is less pronounced, whereas the SAE increases or decreases, suggesting changes mostly in the coarse aerosol particle mode rather than in the fine mode. Statistically significant decreasing trends of σsp are observed at 5 out of the 13 stations included in the trend analyses. The total reductions of σsp are consistent with those reported for PM2.5 and PM10 mass concentrations over similar periods across Europe.