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@ARTICLE{Grosz:836859,
      author       = {Grosz, Balázs and Dechow, Rene and Gebbert, Sören and
                      Hoffmann, Holger and Zhao, Gang and Constantin, Julie and
                      Raynal, Helene and Wallach, Daniel and Coucheney, Elsa and
                      Lewan, Elisabet and Eckersten, Henrik and Specka, Xenia and
                      Kersebaum, Kurt-Christian and Nendel, Claas and Kuhnert,
                      Matthias and Yeluripati, Jagadeesh and Haas, Edwin and
                      Teixeira, Edmar and Bindi, Marco and Trombi, Giacomo and
                      Moriondo, Marco and Doro, Luca and Roggero, Pier Paolo and
                      Zhao, Zhigan and Wang, Enli and Tao, Fulu and Rötter,
                      Reimund and Kassie, Belay and Cammarano, Davide and Asseng,
                      Senthold and Weihermüller, Lutz and Siebert, Stefan and
                      Gaiser, Thomas and Ewert, Frank},
      title        = {{T}he implication of input data aggregation on up-scaling
                      soil organic carbon changes},
      journal      = {Environmental modelling $\&$ software},
      volume       = {96},
      issn         = {1364-8152},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2017-05895},
      pages        = {361 - 377},
      year         = {2017},
      abstract     = {In up-scaling studies, model input data aggregation is a
                      common method to cope with deficient data availability and
                      limit the computational effort. We analyzed model errors due
                      to soil data aggregation for modeled SOC trends. For a
                      region in North West Germany, gridded soil data of spatial
                      resolutions between 1 km and 100 km has been derived by
                      majority selection. This data was used to simulate changes
                      in SOC for a period of 30 years by 7 biogeochemical models.
                      Soil data aggregation strongly affected modeled SOC trends.
                      Prediction errors of simulated SOC changes decreased with
                      increasing spatial resolution of model output. Output data
                      aggregation only marginally reduced differences of model
                      outputs between models indicating that errors caused by
                      deficient model structure are likely to persist even if
                      requirements on the spatial resolution of model outputs are
                      low.},
      cin          = {IBG-3},
      ddc          = {690},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255) / MACSUR - Modelling European Agriculture with
                      Climate Change for Food Security (2812-ERA-158)},
      pid          = {G:(DE-HGF)POF3-255 / G:(DE-BLE)2812-ERA-158},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000408356600029},
      doi          = {10.1016/j.envsoft.2017.06.046},
      url          = {https://juser.fz-juelich.de/record/836859},
}