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@ARTICLE{Baatz:825831,
      author       = {Baatz, Roland and Hendricks-Franssen, Harrie-Jan and Han,
                      Xujun and Hoar, Tim and Bogena, Heye and Vereecken, Harry},
      title        = {{E}valuating the value of a network of cosmic-ray probes
                      for improving land surface modelling},
      journal      = {Hydrology and earth system sciences discussions},
      volume       = {},
      issn         = {1812-2116},
      address      = {Katlenburg-Lindau},
      publisher    = {Soc.},
      reportid     = {FZJ-2017-00133},
      pages        = {},
      year         = {2016},
      abstract     = {Land surface models can model matter and energy fluxes
                      between the land surface and atmosphere, and provide a lower
                      boundary condition to atmospheric circulation models. For
                      these applications, accurate soil moisture quantification is
                      highly desirable but not always possible given limited
                      observations and limited subsurface data accuracy.
                      Cosmic-ray probes (CRPs) offer an interesting alternative to
                      indirectly measure soil moisture and provide an observation
                      that can be assimilated into land surface models for
                      improved soil moisture prediction. Synthetic studies have
                      shown the potential to estimate subsurface parameters of
                      land surface models with the assimilation of CRP
                      observations. In this study, the potential of a network of
                      CRPs for estimating subsurface parameters and improved soil
                      moisture states is tested in a real-world case scenario
                      using the local ensemble transform Kalman filter with the
                      Community Land Model. The potential of the CRP network was
                      tested by assimilating CRP-data for the years 2011 and 2012
                      (with or without soil hydraulic parameter estimation),
                      followed by the verification year 2013. This was done using
                      (i) the regional soil map as input information for the
                      simulations, and (ii) an erroneous, biased soil map. For the
                      regional soil map, soil moisture characterization was only
                      improved in the assimilation period but not in the
                      verification period. For the biased soil map, soil moisture
                      characterization improved in both periods strongly from a
                      ERMS of 0.11 cm3/cm3 to 0.03 cm3/cm3 (assimilation
                      period) and from 0.12 cm3/cm3 to 0.05 cm3/cm3
                      (verification period) and the estimated soil hydraulic
                      parameters were after assimilation closer to the ones of the
                      regional soil map. Finally, the value of the CRP network was
                      also evaluated with jackknifing data assimilation
                      experiments. It was found that the CRP network is able to
                      improve soil moisture estimates at locations between the
                      assimilation sites from a ERMS of 0.12 cm3/cm3 to
                      0.06 cm3/cm3 (verification period), but again only if the
                      initial soil map was biased.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.5194/hess-2016-432},
      url          = {https://juser.fz-juelich.de/record/825831},
}