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@ARTICLE{Young:844162,
      author       = {Young, Paul J. and Naik, Vaishali and Fiore, Arlene M. and
                      Gaudel, Audrey and Guo, J. and Lin, Meiyun Y. and Neu,
                      Jessica L. and Parrish, David D. and Rieder, H. E. and
                      Schnell, J. L. and Tilmes, Simone and Wild, Oliver and
                      Zhang, L. and Ziemke, Jerry and Brandt, J. and Delcloo, A.
                      and Doherty, Ruth M. and Geels, C. and Hegglin, Michaela I.
                      and Hu, L. and Im, Ulas and Kumar, R. and Luhar, A. and
                      Murray, L. and Plummer, D. and Rodriguez, J. and Saiz-Lopez,
                      Alfonso and Schultz, Martin and Woodhouse, M. T. and Zeng,
                      G.},
      title        = {{T}ropospheric {O}zone {A}ssessment {R}eport: {A}ssessment
                      of global-scale model performance for global and regional
                      ozone distributions, variability, and trends},
      journal      = {Elementa},
      volume       = {6},
      number       = {10},
      issn         = {2325-1026},
      address      = {Washington, DC},
      publisher    = {BioOne},
      reportid     = {FZJ-2018-01627},
      pages        = {265},
      year         = {2018},
      abstract     = {The goal of the Tropospheric Ozone Assessment Report (TOAR)
                      is to provide the research community with an up-to-date
                      scientific assessment of tropospheric ozone, from the
                      surface to the tropopause. While a suite of observations
                      provides significant information on the spatial and temporal
                      distribution of tropospheric ozone, observational gaps make
                      it necessary to use global atmospheric chemistry models to
                      synthesize our understanding of the processes and variables
                      that control tropospheric ozone abundance and its
                      variability. Models facilitate the interpretation of the
                      observations and allow us to make projections of future
                      tropospheric ozone and trace gas distributions for different
                      anthropogenic or natural perturbations. This paper assesses
                      the skill of current-generation global atmospheric chemistry
                      models in simulating the observed present-day tropospheric
                      ozone distribution, variability, and trends. Drawing upon
                      the results of recent international multi-model
                      intercomparisons and using a range of model evaluation
                      techniques, we demonstrate that global chemistry models are
                      broadly skillful in capturing the spatio-temporal variations
                      of tropospheric ozone over the seasonal cycle, for extreme
                      pollution episodes, and changes over interannual to decadal
                      periods. However, models are consistently biased high in the
                      northern hemisphere and biased low in the southern
                      hemisphere, throughout the depth of the troposphere, and are
                      unable to replicate particular metrics that define the
                      longer term trends in tropospheric ozone as derived from
                      some background sites. When the models compare unfavorably
                      against observations, we discuss the potential causes of
                      model biases and propose directions for future developments,
                      including improved evaluations that may be able to better
                      diagnose the root cause of the model-observation disparity.
                      Overall, model results should be approached critically,
                      including determining whether the model performance is
                      acceptable for the problem being addressed, whether biases
                      can be tolerated or corrected, whether the model is
                      appropriately constituted, and whether there is a way to
                      satisfactorily quantify the uncertainty.},
      cin          = {JSC / IEK-8},
      ddc          = {550},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IEK-8-20101013},
      pnm          = {512 - Data-Intensive Science and Federated Computing
                      (POF3-512) / Earth System Data Exploration (ESDE)},
      pid          = {G:(DE-HGF)POF3-512 / G:(DE-Juel-1)ESDE},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000423829500001},
      doi          = {10.1525/elementa.265},
      url          = {https://juser.fz-juelich.de/record/844162},
}