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@ARTICLE{vanNoije:56573,
      author       = {van Noije, T. P. C. and Eskes, H.J. and Dentener, F. J. and
                      Stevenson, D. S. and Ellingsen, K. and Schultz, M. G. and
                      Wild, O. and Amann, M. and Atherton, C. S. and Bergmann, D.
                      J. and Bey, I. and Boersma, K. F. and Butler, T. and Cofala,
                      J. and Drevet, J. and Fiore, A. M. and Gauss, M. and
                      Hauglustaine, D. A. and Horowitz, L. W. and Isaksen, I. S.
                      A. and Krol, M. C. and Lamarque, J.-F. and Lawrence, M. G.
                      and Martin, R. V. and Montanaro, V. and Müller, J.-F. and
                      Pitari, G. and Prather, M. J. and Pyle, J. A. and Richter,
                      A. and Rodriguez, J. M. and Savage, N. H. and Strahan, S.E.
                      and Sudo, K. and Szopa, S. and van Roozendael, M.},
      title        = {{M}ulti-model ensemble simulations of troposphere {NO}2
                      compared with {GOME} retrievals for the year 2000},
      journal      = {Atmospheric chemistry and physics},
      volume       = {6},
      issn         = {1680-7316},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {PreJuSER-56573},
      pages        = {2943 - 2979},
      year         = {2006},
      note         = {Record converted from VDB: 12.11.2012},
      abstract     = {We present a systematic comparison of tropospheric NO2 from
                      17 global atmospheric chemistry models with three
                      state-of-the-art retrievals from the Global Ozone Monitoring
                      Experiment (GOME) for the year 2000. The models used
                      constant anthropogenic emissions from IIASA/EDGAR3.2 and
                      monthly emissions from biomass burning based on the 1997 -
                      2002 average carbon emissions from the Global Fire Emissions
                      Database (GFED). Model output is analyzed at 10: 30 local
                      time, close to the overpass time of the ERS-2 satellite, and
                      collocated with the measurements to account for sampling
                      biases due to incomplete spatiotemporal coverage of the
                      instrument. We assessed the importance of different
                      contributions to the sampling bias: correlations on seasonal
                      time scale give rise to a positive bias of 30 - $50\%$ in
                      the retrieved annual means over regions dominated by
                      emissions from biomass burning. Over the industrial regions
                      of the eastern United States, Europe and eastern China the
                      retrieved annual means have a negative bias with significant
                      contributions ( between - $25\%$ and + $10\%$ of the NO2
                      column) resulting from correlations on time scales from a
                      day to a month. We present global maps of modeled and
                      retrieved annual mean NO2 column densities, together with
                      the corresponding ensemble means and standard deviations for
                      models and retrievals. The spatial correlation between the
                      individual models and retrievals are high, typically in the
                      range 0.81 - 0.93 after smoothing the data to a common
                      resolution. On average the models underestimate the
                      retrievals in industrial regions, especially over eastern
                      China and over the Highveld region of South Africa, and
                      overestimate the retrievals in regions dominated by biomass
                      burning during the dry season. The discrepancy over South
                      America south of the Amazon disappears when we use the GFED
                      emissions specific to the year 2000. The seasonal cycle is
                      analyzed in detail for eight different continental regions.
                      Over regions dominated by biomass burning, the timing of the
                      seasonal cycle is generally well reproduced by the models.
                      However, over Central Africa south of the Equator the models
                      peak one to two months earlier than the retrievals. We
                      further evaluate a recent proposal to reduce the NOx
                      emission factors for savanna fires by $40\%$ and find that
                      this leads to an improvement of the amplitude of the
                      seasonal cycle over the biomass burning regions of Northern
                      and Central Africa. In these regions the models tend to
                      underestimate the retrievals during the wet season,
                      suggesting that the soil emissions are higher than assumed
                      in the models. In general, the discrepancies between models
                      and retrievals cannot be explained by a priori profile
                      assumptions made in the retrievals, neither by diurnal
                      variations in anthropogenic emissions, which lead to a
                      marginal reduction of the NO2 abundance at 10: 30 local time
                      ( by 2.5 - $4.1\%$ over Europe). Overall, there are
                      significant differences among the various models and, in
                      particular, among the three retrievals. The discrepancies
                      among the retrievals ( 10 - $50\%$ in the annual mean over
                      polluted regions) indicate that the previously estimated
                      retrieval uncertainties have a large systematic component.
                      Our findings imply that top-down estimations of NOx
                      emissions from satellite retrievals of tropospheric NO2 are
                      strongly dependent on the choice of model and retrieval.},
      keywords     = {J (WoSType)},
      cin          = {ICG-II},
      ddc          = {550},
      cid          = {I:(DE-Juel1)VDB48},
      pnm          = {Atmosphäre und Klima},
      pid          = {G:(DE-Juel1)FUEK406},
      shelfmark    = {Meteorology $\&$ Atmospheric Sciences},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000239137200002},
      doi          = {10.5194/acp-6-2943-2006},
      url          = {https://juser.fz-juelich.de/record/56573},
}