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@PHDTHESIS{Lyapina:202685,
      author       = {Lyapina, Olga},
      title        = {{C}luster analysis of {E}uropean surface ozone observations
                      for evaluation of {MACC} reanalysis data},
      volume       = {265},
      school       = {Universität Bonn},
      type         = {Dr.},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2015-04869},
      isbn         = {978-3-95806-060-9},
      series       = {Schriften des Forschungszentrums Jülich Reihe Energie $\&$
                      Umwelt / Energy $\&$ Environment},
      pages        = {187 S.},
      year         = {2015},
      note         = {Universität Bonn, Diss., 2014},
      abstract     = {The high density of European surface ozone monitoring sites
                      offers good opportunities for investigation of the regional
                      ozone representativeness and for evaluation of chemistry
                      climate models. In this thesis we analyze both aspects with
                      close relation of one to another. As starting point we
                      analyze ozone trends and the seasonal behavior of ozone
                      concentrations at selected individual stations in different
                      regions of Europe. At this step we are interested to find
                      out how the observed long-term trends in surface ozone
                      concentrations are consistent across stations, and would the
                      annual ozone behaviour give any distinctive patterns within
                      Europe. The next analysis is extended to seasonal-diurnal
                      ozone variations, which appear as the main components of
                      ozone time series and therefore allow to describe the ozone
                      behavior more comprehensively. The regional
                      representativeness of European ozone measurements is
                      investigated through a cluster analysis (CA) of ozone air
                      quality data from 1492 European surface monitoring stations
                      (Airbase database). K-means clustering is implemented for 3
                      sets of properties: (i) seasonal-diurnal variations in
                      absolute mixing ratio units, (ii) normalized
                      seasonal-diurnal variations, and (iii) averaged and
                      normalized seasonal and diurnal variations. Each CA
                      identifies different ozone pollution regimes, and each of
                      them is compared with the output of the multi-year global
                      reanalysis produced within the Monitoring of Atmospheric
                      Composition and Climate (MACC) project. Recent methods for
                      evaluation of global chemistry-climate models often provide
                      only the comparison of the simulated output mean to
                      individual ozone observations or arbitrarily aggregated sets
                      of observations. This can give general information about the
                      model biases for area, captured bysites, but does not help
                      in the interpretation of these biases. Our CA approach
                      yields useful information for the evaluation of numerical
                      models, as it allows for a pre-selection of stations and
                      uses clusters as means to stratify the comparison with the
                      respective model output. Comparing the MACC data to cluster
                      results allows to see whether the model is able to capture
                      specifics of each group and how well it describes the
                      various ozone pollution regimes. The selected parameters for
                      the investigation of ozone representativeness provide
                      several possibilities to distinguish representative groups
                      of ozone over Europe. Relying on the most stable conditions,
                      there are 5 and 4 clusters which adequately describe the
                      seasonal-diurnal ozone European patterns in case of absolute
                      and normalized properties, respectively. Comparison of the
                      model with observations for individual clusters reveal first
                      of all different overestimation biases, and secondly
                      differences mainly in seasonal ozone behavior. These biases
                      are mostly driven by summertime ozone rather than
                      wintertime, where ozone is generally well predicted. Such
                      biases decrease from more polluted clusters to cleaner ones.
                      Also the seasonal and diurnal cycles are described better
                      for clusters with relatively clean signatures. The best fit
                      is observed for clusters, which stations are influenced more
                      by regional rather than local factors.},
      cin          = {IEK-8},
      cid          = {I:(DE-Juel1)IEK-8-20101013},
      pnm          = {243 - Tropospheric trace substances and their
                      transformation processes (POF3-243) / MACC II - Monitoring
                      Atmospheric Composition and Climate Interim Implementation
                      (283576)},
      pid          = {G:(DE-HGF)POF3-243 / G:(EU-Grant)283576},
      typ          = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
      urn          = {urn:nbn:de:0001-2015071615},
      url          = {https://juser.fz-juelich.de/record/202685},
}