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000019863 0247_ $$2DOI$$a10.5194/gmd-4-1077-2011
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000019863 084__ $$2WoS$$aGeosciences, Multidisciplinary
000019863 1001_ $$0P:(DE-HGF)0$$aKnote, C.$$b0
000019863 245__ $$aTowards an online-coupled chemistry-climate model: evaluation of trace gases and aerosols in COSMO-ART
000019863 260__ $$aKatlenburg-Lindau$$bCopernicus$$c2011
000019863 300__ $$a1077 - 1102
000019863 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
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000019863 440_0 $$021722$$aGeoscientific Model Development$$v4$$x1991-959X
000019863 500__ $$3POF3_Assignment on 2016-02-29
000019863 500__ $$aWe acknowledge the EBAS team at NILU, Norway, for providing measurement data through their web interface. Pirmin Kaufmann, MeteoSuisse, made SYNOP measurement data available. The Swiss National Supercomputing Center (CSCS) and the Ipazia-team at Empa provided computing ressources for our simulations. The Swiss National Science Foundation is acknowledged for partly financing the IPAZIA computational cluster (project 206021 128754). We thank the AERONET PI investigators and their staff for establishing and maintaining the 36 sites used in this investigation. Louisa Emmons provided MOZART-NCEP output which we have used as initial and boundary conditions in our simulations, and we are also thankful for advice and help she gave us via email. The work of the AMS measurement group from Manchester has been funded by ACCENT and the UK Natural Environment Research Council (NERC). The Colorado AMS group was supported by NSF ATM-0919189 and NOAA NA08OAR4310565. The AMS measurements at Melpitz were supported by the Umweltbundesamt (UBA) grants no. 351 01 031 and no. 351 01 038, and UFOPLAN contract 3703 43 200.
000019863 520__ $$aThe online-coupled, regional chemistry transport model COSMO-ART is evaluated for periods in all seasons against several measurement datasets to assess its ability to represent gaseous pollutants and ambient aerosol characteristics over the European domain. Measurements used in the comparison include long-term station observations, satellite and ground-based remote sensing products, and complex datasets of aerosol chemical composition and number size distribution from recent field campaigns. This is the first time these comprehensive measurements of aerosol characteristics in Europe are used to evaluate a regional chemistry transport model. We show a detailed analysis of the simulated size-resolved chemical composition under different meteorological conditions. Mean, variability and spatial distribution of the concentrations of O-3 and NOx are well reproduced. SO2 is found to be overestimated, simulated PM2.5 and PM10 levels are on average underestimated, as is AOD. We find indications of an overestimation of shipping emissions. Time evolution of aerosol chemical composition is captured, although some biases are found in relative composition. Nitrate aerosol components are on average overestimated, and sulfates underestimated. The accuracy of simulated organics depends strongly on season and location. While strongly underestimated during summer, organic mass is comparable in spring and autumn. We see indications for an overestimated fractional contribution of primary organic matter in urban areas and an underestimation of SOA at many locations. Aerosol number concentrations compare well with measurements for larger size ranges, but overestimations of particle number concentration with factors of 2-5 are found for particles smaller than 50 nm. Size distribution characteristics are often close to measurements, but show discrepancies at polluted sites. Suggestions for further improvement of the modeling system consist of the inclusion of a revised secondary organic aerosols scheme, aqueous-phase chemistry and improved aerosol boundary conditions. Our work sets the basis for subsequent studies of aerosol characteristics and climate impacts with COSMO-ART, and highlights areas where improvements are necessary for current regional modeling systems in general.
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000019863 7001_ $$0P:(DE-HGF)0$$aBrunner, D.$$b1
000019863 7001_ $$0P:(DE-HGF)0$$aVogel, H.$$b2
000019863 7001_ $$0P:(DE-HGF)0$$aAllan, J.$$b3
000019863 7001_ $$0P:(DE-HGF)0$$aAsmi, A.$$b4
000019863 7001_ $$0P:(DE-HGF)0$$aAijälä, M.$$b5
000019863 7001_ $$0P:(DE-HGF)0$$aCarbone, S.$$b6
000019863 7001_ $$0P:(DE-HGF)0$$avan der Gon, H.D.$$b7
000019863 7001_ $$0P:(DE-HGF)0$$aJimenez, J.L.$$b8
000019863 7001_ $$0P:(DE-Juel1)4528$$aKiendler-Scharr, A.$$b9$$uFZJ
000019863 7001_ $$0P:(DE-HGF)0$$aMohr, C.$$b10
000019863 7001_ $$0P:(DE-HGF)0$$aPoulain, L.$$b11
000019863 7001_ $$0P:(DE-HGF)0$$aPrevot, A.S.H.$$b12
000019863 7001_ $$0P:(DE-HGF)0$$aSwietlicki, E.$$b13
000019863 7001_ $$0P:(DE-HGF)0$$aVogel, B.$$b14
000019863 773__ $$0PERI:(DE-600)2456725-5$$a10.5194/gmd-4-1077-2011$$gVol. 4, p. 1077 - 1102$$p1077 - 1102$$q4<1077 - 1102$$tGeoscientific model development$$v4$$x1991-959X$$y2011
000019863 8567_ $$uhttp://dx.doi.org/10.5194/gmd-4-1077-2011
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