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    Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition
    (London : Nature Publ. Group, 2017) Schmale, Julia; Henning, Silvia; Henzing, Bas; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Bougiatioti, Aikaterini; Kalivitis, Nikos; Stavroulas, Iasonas; Jefferson, Anne; Park, Minsu; Schlag, Patrick; Kristensson, Adam; Iwamoto, Yoko; Pringle, Kirsty; Reddington, Carly; Aalto, Pasi; Äijälä, Mikko; Baltensperger, Urs; Bialek, Jakub; Birmili, Wolfram; Bukowiecki, Nicolas; Ehn, Mikael; Fjæraa, Ann Mari; Fiebig, Markus; Frank, Göran; Fröhlich, Roman; Frumau, Arnoud; Furuya, Masaki; Hammer, Emanuel; Heikkinen, Liine; Herrmann, Erik; Holzinger, Rupert; Hyono, Hiroyuki; Kanakidou, Maria; Kiendler-Scharr, Astrid; Kinouchi, Kento; Kos, Gerard; Kulmala, Markku; Mihalopoulos, Nikolaos; Motos, Ghislain; Nenes, Athanasios; O’Dowd, Colin; Paramonov, Mikhail; Petäjä, Tuukka; Picard, David; Poulain, Laurent; Prévôt, André Stephan Henry; Slowik, Jay; Sonntag, Andre; Swietlicki, Erik; Svenningsson, Birgitta; Tsurumaru, Hiroshi; Wiedensohler, Alfred; Wittbom, Cerina; Ogren, John A.; Matsuki, Atsushi; Yum, Seong Soo; Myhre, Cathrine Lund; Carslaw, Ken; Stratmann, Frank; Gysel, Martin
    Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.
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    Historical greenhouse gas concentrations for climate modelling (CMIP6)
    (München : European Geopyhsical Union, 2017) Meinshausen, Malte; Vogel, Elisabeth; Nauels, Alexander; Lorbacher, Katja; Meinshausen, Nicolai; Etheridge, David M.; Fraser, Paul J.; Montzka, Stephen A.; Rayner, Peter J.; Trudinger, Cathy M.; Krummel, Paul B.; Beyerle, Urs; Canadell, Josep G.; Daniel, John S.; Enting, Ian G.; Law, Rachel M. Law; Lunder, Chris R.; O'Doherty, Simon; Prinn, Ron G.; Reimann, Stefan; Rubino, Mauro; Velders, Guus J.M.; Vollmer, Martin K.; Wang, Ray H.J.; Weiss, Ray
    Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800000 years. Those elevated GHG concentrations warm the planet and – partially offset by net cooling effects by aerosols – are largely responsible for the observed warming over the past 150 years. An accurate representation of GHG concentrations is hence important to understand and model recent climate change. So far, community efforts to create composite datasets of GHG concentrations with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since the 1980s. Here, we provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project – Phase 6 (CMIP6) experiments. The presented datasets are based on AGAGE and NOAA networks, firn and ice core data, and archived air data, and a large set of published studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved and include seasonality. We focus on the period 1850–2014 for historical CMIP6 runs, but data are also provided for the last 2000 years. We provide consolidated datasets in various spatiotemporal resolutions for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as 40 other GHGs, namely 17 ozone-depleting substances, 11 hydrofluorocarbons (HFCs), 9 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3) and sulfuryl fluoride (SO2F2). In addition, we provide three equivalence species that aggregate concentrations of GHGs other than CO2, CH4 and N2O, weighted by their radiative forcing efficiencies. For the year 1850, which is used for pre-industrial control runs, we estimate annual global-mean surface concentrations of CO2 at 284.3ppm, CH4 at 808.2ppb and N2O at 273.0ppb. The data are available at https://esgf-node.llnl.gov/search/input4mips/ and http://www.climatecollege.unimelb.edu.au/cmip6. While the minimum CMIP6 recommendation is to use the global- and annual-mean time series, modelling groups can also choose our monthly and latitudinally resolved concentrations, which imply a stronger radiative forcing in the Northern Hemisphere winter (due to the latitudinal gradient and seasonality).