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@ARTICLE{Naz:845966,
      author       = {Naz, Bibi S. and Kurtz, Wolfgang and Montzka, Carsten and
                      Sharples, Wendy and Görgen, Klaus and Keune, Jessica and
                      Gao, Huilin and Springer, Anne and Hendricks-Franssen,
                      Harrie-Jan and Kollet, Stefan},
      title        = {{I}mproving soil moisture and runoff simulations over
                      {E}urope using a high-resolution data-assimilation modeling
                      framework},
      journal      = {Hydrology and earth system sciences discussions},
      volume       = {1},
      issn         = {1812-2116},
      address      = {Katlenburg-Lindau},
      publisher    = {Soc.},
      reportid     = {FZJ-2018-03144},
      pages        = {1 - 32},
      year         = {2018},
      abstract     = {Accurate and reliable hydrologic simulations are important
                      for many applications such as water resources management,
                      future water availability projections and predictions of
                      extreme events. However, the accuracy of water balance
                      estimates is limited by the lack of observations at large
                      scales and the uncertainties of model simulations due to
                      errors in model structure and inputs (e.g. hydrologic
                      parameters and atmospheric forcings). In this study, we
                      assimilated ESA CCI soil moisture (SM) information to
                      improve the estimation of continental-scale soil moisture
                      and runoff. The assimilation experiment was conducted over a
                      time period from 2000 to 2006 with the Community Land Model,
                      version 3.5 (CLM3.5) integrated with the Parallel Data
                      Assimilation Framework (PDAF) at spatial resolution of
                      0.0275° (~ 3 km) over Europe. The model was forced with
                      the high-resolution reanalysis COSMO-REA6 from the
                      Hans-Ertel Centre for Weather Research (HErZ). Our results
                      show that estimates of soil moisture have improved,
                      particularly in the summer and autumn seasons when
                      cross-validated with independent CCI-SM observations. On
                      average, the mean bias in soil moisture was reduced from
                      0.1 mm3/mm3 in open-loop simulations to 0.004 mm3/mm3
                      with SM assimilation. The assimilation experiment also shows
                      overall improvements in runoff, particularly during peak
                      runoff. The results demonstrate the potential of
                      assimilating satellite soil moisture observations to improve
                      high-resolution soil moisture and runoff simulations at the
                      continental scale, which is useful for water resources
                      assessment and monitoring.},
      cin          = {IBG-3 / JSC},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118 / I:(DE-Juel1)JSC-20090406},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255) / EoCoE - Energy oriented Centre of Excellence
                      for computer applications (676629) / 511 - Computational
                      Science and Mathematical Methods (POF3-511)},
      pid          = {G:(DE-HGF)POF3-255 / G:(EU-Grant)676629 /
                      G:(DE-HGF)POF3-511},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.5194/hess-2018-24},
      url          = {https://juser.fz-juelich.de/record/845966},
}