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@ARTICLE{Naz:859669,
      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 at 3 km
                      over {E}urope using land surface data assimilation},
      journal      = {Hydrology and earth system sciences},
      volume       = {23},
      number       = {1},
      issn         = {1607-7938},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2019-00511},
      pages        = {277 - 301},
      year         = {2019},
      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 large-scale
                      observations, model simulation uncertainties and biases
                      related to errors in model structure and uncertain inputs
                      (e.g., hydrologic parameters and atmospheric forcings). The
                      availability of long-term and global remotely sensed soil
                      moisture offers the opportunity to improve model estimates
                      through data assimilation with complete spatiotemporal
                      coverage. In this study, we assimilated the European Space
                      Agency (ESA) Climate Change Initiative (CCI) derived soil
                      moisture (SM) information to improve the estimation of
                      continental-scale soil moisture and runoff. The assimilation
                      experiment was conducted over a time period 2000–2006 with
                      the Community Land Model, version 3.5 (CLM3.5), integrated
                      with the Parallel Data Assimilation Framework (PDAF) at a
                      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). The performance of assimilation was assessed against
                      open-loop model simulations and cross-validated with
                      independent ESA CCI-derived soil moisture (CCI-SM) and
                      gridded runoff observations. Our results showed improved
                      estimates of soil moisture, particularly in the summer and
                      autumn seasons when cross-validated with independent CCI-SM
                      observations. The assimilation experiment results also
                      showed overall improvements in runoff, although some regions
                      were degraded, especially in central Europe. The results
                      demonstrated the potential of assimilating satellite soil
                      moisture observations to produce downscaled and improved
                      high-resolution soil moisture and runoff simulations at the
                      continental scale, which is useful for water resources
                      assessment and monitoring.},
      cin          = {IBG-3 / JARA-HPC / JSC},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118 / $I:(DE-82)080012_20140620$ /
                      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) / IRTG, Graduate School -
                      Patterns in Soil-Vegetation-Atmosphere-Systems: Monitoring,
                      Modelling and Data Assimilation (TR32) (IRTG, Graduate
                      School) (IRTG-GRADUATE-20170406) / Water4Enery
                      $(jibg31_20160501)$ / 511 - Computational Science and
                      Mathematical Methods (POF3-511)},
      pid          = {G:(DE-HGF)POF3-255 / G:(EU-Grant)676629 /
                      G:(DE-Juel1)IRTG-GRADUATE-20170406 /
                      $G:(DE-Juel1)jibg31_20160501$ / G:(DE-HGF)POF3-511},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000456148000001},
      doi          = {10.5194/hess-23-277-2019},
      url          = {https://juser.fz-juelich.de/record/859669},
}