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@ARTICLE{Casanueva:280221,
      author       = {Casanueva, A. and Kotlarski, S. and Herrera, S. and
                      Fernández, J. and Gutiérrez, J. M. and Boberg, F. and
                      Colette, A. and Christensen, O. B. and Görgen, Klaus and
                      Jacob, D. and Keuler, K. and Nikulin, G. and Teichmann, C.
                      and Vautard, R.},
      title        = {{D}aily precipitation statistics in a {EURO}-{CORDEX} {RCM}
                      ensemble: added value of raw and bias-corrected
                      high-resolution simulations},
      journal      = {Climate dynamics},
      volume       = {47},
      number       = {3},
      issn         = {0930-7575},
      address      = {Berlin},
      publisher    = {Springer},
      reportid     = {FZJ-2016-00029},
      pages        = {719-737},
      year         = {2016},
      abstract     = {Daily precipitation statistics as simulated by the
                      ERA-Interim-driven EURO-CORDEX regional climate model (RCM)
                      ensemble are evaluated over two distinct regions of the
                      European continent, namely the European Alps and Spain. The
                      potential added value of the high-resolution 12 km
                      experiments with respect to their 50 km resolution
                      counterparts is investigated. The statistics considered
                      consist of wet-day intensity and precipitation frequency as
                      a measure of mean precipitation, and three
                      precipitation-derived indicators (90th percentile on wet
                      days—90pWET, contribution of the very wet days to total
                      precipitation—R95pTOT and number of consecutive dry
                      days—CDD). As reference for model evaluation high
                      resolution gridded observational data over continental Spain
                      (Spain011/044) and the Alpine region (EURO4M-APGD) are used.
                      The assessment and comparison of the two resolutions is
                      accomplished not only on their original horizontal grids
                      (approximately 12 and 50 km), but the high-resolution RCMs
                      are additionally regridded onto the coarse 50 km grid by
                      grid cell aggregation for the direct comparison with the low
                      resolution simulations. The direct application of RCMs e.g.
                      in many impact modelling studies is hampered by model
                      biases. Therefore bias correction (BC) techniques are needed
                      at both resolutions to ensure a better agreement between
                      models and observations. In this work, the added value of
                      the high resolution (before and after the bias correction)
                      is assessed and the suitability of these BC methods is also
                      discussed. Three basic BC methods are applied to isolate the
                      effect of biases in mean precipitation, wet-day intensity
                      and wet-day frequency on the derived indicators. Daily
                      precipitation percentiles are strongly affected by biases in
                      the wet-day intensity, whereas the dry spells are better
                      represented when the simulated precipitation frequency is
                      adjusted to the observed one. This confirms that there is no
                      single optimal way to correct for RCM biases, since
                      correcting some distributional features typically leads to
                      an improvement of some aspects but to a deterioration of
                      others. Regarding mean seasonal biases before the BC, we
                      find only limited evidence for an added value of the higher
                      resolution in the precipitation intensity and frequency or
                      in the derived indicators. Thereby, evaluation results
                      considerably depend on the RCM, season and indicator
                      considered. High resolution simulations better reproduce the
                      indicators’ spatial patterns, especially in terms of
                      spatial correlation. However, this improvement is not
                      statistically significant after applying specific BC
                      methods.},
      cin          = {JSC / IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IBG-3-20101118},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511)},
      pid          = {G:(DE-HGF)POF3-511},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000382111300003},
      doi          = {10.1007/s00382-015-2865-x},
      url          = {https://juser.fz-juelich.de/record/280221},
}