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@ARTICLE{Sulis:885664,
      author       = {Sulis, M. and Keune, J. and Shrestha, P. and Simmer, C. and
                      Kollet, S. J.},
      title        = {{Q}uantifying the {I}mpact of {S}ubsurface-{L}and {S}urface
                      {P}hysical {P}rocesses on the {P}redictive {S}kill of
                      {S}ubseasonal {M}esoscale {A}tmospheric {S}imulations},
      journal      = {Journal of geophysical research / D},
      volume       = {123},
      number       = {17},
      issn         = {2169-897X},
      address      = {Hoboken, NJ},
      publisher    = {Wiley},
      reportid     = {FZJ-2020-03995},
      pages        = {9131 - 9151},
      year         = {2018},
      abstract     = {Integrated terrestrial system modeling platforms, which
                      simulate the 3‐D flow of water both in the subsurface and
                      the atmosphere, are expected to improve the realism of
                      predictions through a more detailed physics‐based
                      representation of hydrometeorological processes and
                      feedbacks. We test this expectation by evaluating simulation
                      results from different configurations of an atmospheric
                      model with increasing complexity in the representation of
                      land surface and subsurface physical processes. The
                      evaluation is performed using observations during the
                      ($HD(CP)^2$) Observational Prototype Experiment field
                      campaign in April–May 2013 over western Germany. The
                      augmented model physics do not improve the prediction of
                      daily cumulative precipitation and minimum temperature
                      during this period. Moreover, a cold bias is introduced in
                      the simulated daily maximum temperature, which decreases the
                      performance of the atmospheric model with respect to its
                      standard configuration. The decreased performance in the
                      maximum temperature is traced in part to a higher simulated
                      soil moisture, which shifts surface flux partitioning toward
                      higher latent and lower sensible heat fluxes. The better
                      reproduced air temperature profiles simulated by the
                      standard atmospheric model comes, however, with an
                      overestimated heat flux at the land surface caused by a warm
                      bias in the simulated soil temperature. Simulated
                      atmospheric states do not correlate significantly with
                      differences in soil moisture and temperature; thus,
                      different turbulent flux parameterizations dominate the
                      propagation of the subsurface signal into the atmosphere.
                      The strong influence of the lateral synoptic forcings on the
                      results suggests, however, the need for further
                      investigations encompassing different weather situations or
                      regions with stronger land‐atmosphere coupling
                      conditions.},
      ddc          = {550},
      pnm          = {Terrestrial Systems Modeling – Validation with
                      Polarimetric Radar Retrievals and Data Assimilation
                      $(hbn33_20190501)$},
      pid          = {$G:(DE-Juel1)hbn33_20190501$},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1029/2017JD028187},
      url          = {https://juser.fz-juelich.de/record/885664},
}