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search.filters.applied.f.access: openAccess × End date: 2017 × Start date: 2017 × Subject: atmospheric chemistry ×

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    The HD(CP)2 Observational Prototype Experiment (HOPE) - An overview
    (Katlenburg-Lindau : EGU, 2017) Macke, Andreas; Seifert, Patric; Baars, Holger; Barthlott, Christian; Beekmans, Christoph; Behrendt, Andreas; Bohn, Birger; Brueck, Matthias; Bühl, Johannes; Crewell, Susanne; Damian, Thomas; Deneke, Hartwig; Düsing, Sebastian; Foth, Andreas; Di Girolamo, Paolo; Hammann, Eva; Heinze, Rieke; Hirsikko, Anne; Kalisch, John; Kalthoff, Norbert; Kinne, Stefan; Kohler, Martin; Löhnert, Ulrich; Madhavan, Bomidi Lakshmi; Maurer, Vera; Muppa, Shravan Kumar; Schween, Jan; Serikov, Ilya; Siebert, Holger; Simmer, Clemens; Späth, Florian; Steinke, Sandra; Träumner, Katja; Trömel, Silke; Wehner, Birgit; Wieser, Andreas; Wulfmeyer, Volker; Xie, Xinxin
    The HD(CP)2 Observational Prototype Experiment (HOPE) was performed as a major 2-month field experiment in Jülich, Germany, in April and May 2013, followed by a smaller campaign in Melpitz, Germany, in September 2013. HOPE has been designed to provide an observational dataset for a critical evaluation of the new German community atmospheric icosahedral non-hydrostatic (ICON) model at the scale of the model simulations and further to provide information on land-surface-atmospheric boundary layer exchange, cloud and precipitation processes, as well as sub-grid variability and microphysical properties that are subject to parameterizations. HOPE focuses on the onset of clouds and precipitation in the convective atmospheric boundary layer. This paper summarizes the instrument set-ups, the intensive observation periods, and example results from both campaigns.

    HOPE-Jülich instrumentation included a radio sounding station, 4 Doppler lidars, 4 Raman lidars (3 of them provide temperature, 3 of them water vapour, and all of them particle backscatter data), 1 water vapour differential absorption lidar, 3 cloud radars, 5 microwave radiometers, 3 rain radars, 6 sky imagers, 99 pyranometers, and 5 sun photometers operated at different sites, some of them in synergy. The HOPE-Melpitz campaign combined ground-based remote sensing of aerosols and clouds with helicopter- and balloon-based in situ observations in the atmospheric column and at the surface.

    HOPE provided an unprecedented collection of atmospheric dynamical, thermodynamical, and micro- and macrophysical properties of aerosols, clouds, and precipitation with high spatial and temporal resolution within a cube of approximately 10 × 10 × 10km3. HOPE data will significantly contribute to our understanding of boundary layer dynamics and the formation of clouds and precipitation. The datasets have been made available through a dedicated data portal.

    First applications of HOPE data for model evaluation have shown a general agreement between observed and modelled boundary layer height, turbulence characteristics, and cloud coverage, but they also point to significant differences that deserve further investigations from both the observational and the modelling perspective.
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    The Global Aerosol Synthesis and Science Project (GASSP): Measurements and Modeling to Reduce Uncertainty
    (Boston, Mass. : ASM, 2017) Reddington, C.L.; Carslaw, K.S.; Stier, P.; Schutgens, N.; Coe, H.; Liu, D.; Allan, J.; Browse, J.; Pringle, K.J.; Lee, L.A.; Yoshioka, M.; Johnson, J.S.; Regayre, L.A.; Spracklen, D.V.; Mann, G.W.; Clarke, A.; Hermann, M.; Henning, S.; Wex, H.; Kristensen, T.B.; Leaitch, W.R.; Pöschl, U.; Rose, D.; Andreae, M.O.; Schmale, J.; Kondo, Y.; Oshima, N.; Schwarz, J.P.; Nenes, A.; Anderson, B.; Roberts, G.C.; Snider, J.R.; Leck, C.; Quinn, P.K.; Chi, X.; Ding, A.; Jimenez, J.L.; Zhang, Q.
    The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.
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    Nitrate radicals and biogenic volatile organic compounds: Oxidation, mechanisms, and organic aerosol
    (München : European Geopyhsical Union, 2017) Ng, Nga Lee; Brown, Steven S.; Archibald, Alexander T.; Atlas, Elliot; Cohen, Ronald C.; Crowley, John N.; Day, Douglas A.; Donahue, Neil M.; Fry, Juliane L.; Fuchs, Hendrik; Griffin, Robert J.; Guzman, Marcelo I.; Herrmann, Hartmut; Hodzic, Alma; Iinuma, Yoshiteru; Jimenez, José L.; Kiendler-Scharr, Astrid; Lee, Ben H.; Luecken, Deborah J.; Mao, Jingqiu; McLaren, Robert; Mutzel, Anke; Osthoff, Hans D.; Ouyang, Bin; Picquet-Varrault, Benedicte; Platt, Ulrich; Pye, Havala O.T.; Rudich, Yinon; Schwantes, Rebecca H.; Shiraiwa, Manabu; Stutz, Jochen; Thornton, Joel A.; Tilgner, Andreas; Williams, Brent J.; Zaveri, Rahul A.
    Oxidation of biogenic volatile organic compounds (BVOC) by the nitrate radical (NO3) represents one of the important interactions between anthropogenic emissions related to combustion and natural emissions from the biosphere. This interaction has been recognized for more than 3 decades, during which time a large body of research has emerged from laboratory, field, and modeling studies. NO3-BVOC reactions influence air quality, climate and visibility through regional and global budgets for reactive nitrogen (particularly organic nitrates), ozone, and organic aerosol. Despite its long history of research and the significance of this topic in atmospheric chemistry, a number of important uncertainties remain. These include an incomplete understanding of the rates, mechanisms, and organic aerosol yields for NO3-BVOC reactions, lack of constraints on the role of heterogeneous oxidative processes associated with the NO3 radical, the difficulty of characterizing the spatial distributions of BVOC and NO3 within the poorly mixed nocturnal atmosphere, and the challenge of constructing appropriate boundary layer schemes and non-photochemical mechanisms for use in state-of-the-art chemical transport and chemistry–climate models. This review is the result of a workshop of the same title held at the Georgia Institute of Technology in June 2015. The first half of the review summarizes the current literature on NO3-BVOC chemistry, with a particular focus on recent advances in instrumentation and models, and in organic nitrate and secondary organic aerosol (SOA) formation chemistry. Building on this current understanding, the second half of the review outlines impacts of NO3-BVOC chemistry on air quality and climate, and suggests critical research needs to better constrain this interaction to improve the predictive capabilities of atmospheric models.