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    Simulation of atmospheric organic aerosol using its volatility-oxygen-content distribution during the PEGASOS 2012 campaign
    (Katlenburg-Lindau : EGU, 2018) Karnezi, Eleni; Murphy, Benjamin N.; Poulain, Laurent; Herrmann, Hartmut; Wiedensohler, Alfred; Rubach, Florian; Kiendler-Scharr, Astrid; Mentel, Thomas F.; Pandis, Spyros N.
    A lot of effort has been made to understand and constrain the atmospheric aging of the organic aerosol (OA). Different parameterizations of the organic aerosol formation and evolution in the two-dimensional volatility basis set (2D-VBS) framework are evaluated using ground and airborne measurements collected in the 2012 Pan-European Gas AeroSOls-climate interaction Study (PEGASOS) field campaign in the Po Valley (Italy). A number of chemical aging schemes are examined, taking into account various functionalization and fragmentation pathways for biogenic and anthropogenic OA components. Model predictions and measurements, both at the ground and aloft, indicate a relatively oxidized OA with little average diurnal variation. Total OA concentration and O: C ratios are reproduced within experimental error by a number of chemical aging schemes. Anthropogenic secondary OA (SOA) is predicted to contribute 15-25% of the total OA, while SOA from intermediate volatility compound oxidation contributes another 20-35%. Biogenic SOA (bSOA) contributions varied from 15 to 45% depending on the modeling scheme. Primary OA contributed around 5% for all schemes and was comparable to the hydrocarbon-like OA (HOA) concentrations derived from the positive matrix factorization of the aerosol mass spectrometer (PMF-AMS) ground measurements. The average OA and O: C diurnal variation and their vertical profiles showed a surprisingly modest sensitivity to the assumed vaporization enthalpy for all aging schemes. This can be explained by the interplay between the partitioning of the semi-volatile compounds and their gas-phase chemical aging reactions.
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    A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: An example from the Amazon region
    (Katlenburg-Lindau : Copernicus, 2018) Rammig, Anja; Heinke, Jens; Hofhansl, Florian; Verbeeck, Hans; Baker, Timothy R.; Christoffersen, Bradley; Ciais, Philippe; De Deurwaerder, Hannes; Fleischer, Katrin; Galbraith, David; Guimberteau, Matthieu; Huth, Andreas; Johnson, Michelle; Krujit, Bart; Langerwisch, Fanny; Meir, Patrick; Papastefanou, Phillip; Sampaio, Gilvan; Thonicke, Kirsten; von Randow, Celso; Zang, Christian; Rödig, Edna
    Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25% and up to 60%, respectively. Our comparison metrics provide a quantitative measure for model-data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products.
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    Simultaneous observations of NLCs and MSEs at midlatitudes: Implications for formation and advection of ice particles
    (Göttingen : Copernicus GmbH, 2018) Gerding, M.; Zöllner, J.; Zecha, M.; Baumgarten, K.; Höffner, J.; Stober, G.; Lübken, F.-J.
    We combined ground-based lidar observations of noctilucent clouds (NLCs) with collocated, simultaneous radar observations of mesospheric summer echoes (MSEs) in order to compare ice cloud altitudes at a midlatitude site (Kühlungsborn, Germany, 54° N, 12° E). Lidar observations are limited to larger particles ( > 10 nm), while radars are also sensitive to small particles ( < 10 nm), but require sufficient ionization and turbulence at the ice cloud altitudes. The combined lidar and radar data set thus includes some information on the size distribution within the cloud and through this on the of the cloud. The soundings for this study are carried out by the IAP Rayleigh-Mie-Raman (RMR) lidar and the OSWIN VHF radar. On average, there is no difference between the lower edges (lowNLC and lowMSE). The mean difference of the upper edges upNLC and upMSE is g1/4 500 m, which is much less than expected from observations at higher latitudes. In contrast to high latitudes, the MSEs above our location typically do not reach much higher than the NLCs. In addition to earlier studies from our site, this gives additional evidence for the supposition that clouds containing large enough particles to be observed by lidar are not formed locally but are advected from higher latitudes. During the advection process, the smaller particles in the upper part of the cloud either grow and sediment, or they sublimate. Both processes result in a thinning of the layer. High-altitude MSEs, usually indicating nucleation of ice particles, are rarely observed in conjunction with lidar observations of NLCs at Kühlungsborn. © Author(s) 2018.