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@ARTICLE{Han:155400,
      author       = {Han, Xujun and Franssen, Harrie-Jan Hendricks and Montzka,
                      Carsten and Vereecken, Harry},
      title        = {{S}oil moisture and soil properties estimation in the
                      {C}ommunity {L}and {M}odel with synthetic brightness
                      temperature observations},
      journal      = {Water resources research},
      volume       = {50},
      number       = {7},
      issn         = {0043-1397},
      address      = {Washington, DC},
      publisher    = {AGU},
      reportid     = {FZJ-2014-04567},
      pages        = {6081 - 6105},
      year         = {2014},
      abstract     = {The Community Land Model (CLM) includes a large variety of
                      parameterizations, also for flow in the unsaturated zone and
                      soil properties. Soil properties introduce uncertainties
                      into land surface model predictions. In this paper, soil
                      moisture and soil properties are updated for the coupled CLM
                      and Community Microwave Emission Model (CMEM) by the Local
                      Ensemble Transform Kalman Filter (LETKF) and the state
                      augmentation method. Soil properties are estimated through
                      the update of soil textural properties and soil organic
                      matter density. These variables are used in CLM for
                      predicting the soil moisture retention characteristic and
                      the unsaturated hydraulic conductivity, and the soil texture
                      is used in CMEM to calculate the soil dielectric constant.
                      The following scenarios were evaluated for the joint state
                      and parameter estimation with help of synthetic L-band
                      brightness temperature data assimilation: (i) the impact of
                      joint state and parameter estimation; (ii) updating of soil
                      properties in CLM alone, CMEM alone or both CLM and CMEM;
                      (iii) updating of soil properties without soil moisture
                      update; (iv) the observation localization of LETKF. The
                      results show that the characterization of soil properties
                      through the update of textural properties and soil organic
                      matter density can strongly improve with assimilation of
                      brightness temperature data. The optimized soil properties
                      also improve the characterization of soil moisture, soil
                      temperature, actual evapotranspiration, sensible heat flux,
                      and soil heat flux. The best results are obtained if the
                      soil properties are updated only. The coupled CLM and CMEM
                      model is helpful for the parameter estimation. If soil
                      properties are biased, assimilation of soil moisture data
                      with only state updates increases the root mean square error
                      for evapotranspiration, sensible heat flux, and soil heat
                      flux.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {246 - Modelling and Monitoring Terrestrial Systems: Methods
                      and Technologies (POF2-246) / 255 - Terrestrial Systems:
                      From Observation to Prediction (POF3-255)},
      pid          = {G:(DE-HGF)POF2-246 / G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000342632000041},
      doi          = {10.1002/2013WR014586},
      url          = {https://juser.fz-juelich.de/record/155400},
}