% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Marcal:276360,
      author       = {Marécal, V. and Peuch, V.-H. and Andersson, C. and
                      Andersson, S. and Arteta, J. and Beekmann, M. and
                      Benedictow, A. and Bergström, R. and Bessagnet, B. and
                      Cansado, A. and Chéroux, F. and Colette, A. and Coman, A.
                      and Curier, R. L. and Denier van der Gon, H. A. C. and
                      Drouin, A. and Elbern, H. and Emili, E. and Engelen, R. J.
                      and Eskes, H. J. and Foret, G. and Friese, E. and Gauss, M.
                      and Giannaros, C. and Guth, J. and Joly, M. and Jaumouillé,
                      E. and Josse, B. and Kadygrov, N. and Kaiser, J. W. and
                      Krajsek, K. and Kuenen, J. and Kumar, U. and Liora, N. and
                      Lopez, E. and Malherbe, L. and Martinez, I. and Melas, D.
                      and Meleux, F. and Menut, L. and Moinat, P. and Morales, T.
                      and Parmentier, J. and Piacentini, A. and Plu, M. and
                      Poupkou, A. and Queguiner, S. and Robertson, L. and Rouïl,
                      L. and Schaap, M. and Segers, A. and Sofiev, M. and
                      Tarasson, L. and Thomas, M. and Timmermans, R. and
                      Valdebenito, Á. and van Velthoven, P. and van Versendaal,
                      R. and Vira, J. and Ung, A.},
      title        = {{A} regional air quality forecasting system over {E}urope:
                      the {MACC}-{II} daily ensemble production},
      journal      = {Geoscientific model development},
      volume       = {8},
      number       = {9},
      issn         = {1991-9603},
      address      = {Katlenburg-Lindau},
      publisher    = {Copernicus},
      reportid     = {FZJ-2015-06818},
      pages        = {2777 - 2813},
      year         = {2015},
      abstract     = {This paper describes the pre-operational analysis and
                      forecasting system developed during MACC (Monitoring
                      Atmospheric Composition and Climate) and continued in the
                      MACC-II (Monitoring Atmospheric Composition and Climate:
                      Interim Implementation) European projects to provide air
                      quality services for the European continent. This system is
                      based on seven state-of-the art models developed and run in
                      Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE
                      and SILAM). These models are used to calculate multi-model
                      ensemble products. The paper gives an overall picture of its
                      status at the end of MACC-II (summer 2014) and analyses the
                      performance of the multi-model ensemble. The MACC-II system
                      provides daily 96 h forecasts with hourly outputs of 10
                      chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5,
                      NO, NH3, total NMVOCs (non-methane volatile organic
                      compounds) and PAN+PAN precursors) over eight vertical
                      levels from the surface to 5 km height. The hourly analysis
                      at the surface is done a posteriori for the past day using a
                      selection of representative air quality data from European
                      monitoring stations.The performance of the system is
                      assessed daily, weekly and every 3 months (seasonally)
                      through statistical indicators calculated using the
                      available representative air quality data from European
                      monitoring stations. Results for a case study show the
                      ability of the ensemble median to forecast regional ozone
                      pollution events. The seasonal performances of the
                      individual models and of the multi-model ensemble have been
                      monitored since September 2009 for ozone, NO2 and PM10. The
                      statistical indicators for ozone in summer 2014 show that
                      the ensemble median gives on average the best performances
                      compared to the seven models. There is very little
                      degradation of the scores with the forecast day but there is
                      a marked diurnal cycle, similarly to the individual models,
                      that can be related partly to the prescribed diurnal
                      variations of anthropogenic emissions in the models. During
                      summer 2014, the diurnal ozone maximum is underestimated by
                      the ensemble median by about 4 μg m−3 on average.
                      Locally, during the studied ozone episodes, the maxima from
                      the ensemble median are often lower than observations by
                      30–50 μg m−3. Overall, ozone scores are generally good
                      with average values for the normalised indicators of 0.14
                      for the modified normalised mean bias and of 0.30 for the
                      fractional gross error. Tests have also shown that the
                      ensemble median is robust to reduction of ensemble size by
                      one, that is, if predictions are unavailable from one model.
                      Scores are also discussed for PM10 for winter 2013–1014.
                      There is an underestimation of most models leading the
                      ensemble median to a mean bias of −4.5 μg m−3. The
                      ensemble median fractional gross error is larger for PM10 (~
                      0.52) than for ozone and the correlation is lower (~ 0.35
                      for PM10 and ~ 0.54 for ozone). This is related to a larger
                      spread of the seven model scores for PM10 than for ozone
                      linked to different levels of complexity of aerosol
                      representation in the individual models. In parallel, a
                      scientific analysis of the results of the seven models and
                      of the ensemble is also done over the Mediterranean area
                      because of the specificity of its meteorology and
                      emissions.},
      cin          = {IEK-8},
      ddc          = {910},
      cid          = {I:(DE-Juel1)IEK-8-20101013},
      pnm          = {243 - Tropospheric trace substances and their
                      transformation processes (POF3-243)},
      pid          = {G:(DE-HGF)POF3-243},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000364325700005},
      doi          = {10.5194/gmd-8-2777-2015},
      url          = {https://juser.fz-juelich.de/record/276360},
}