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@ARTICLE{Lievens:281468,
      author       = {Lievens, H. and Al Bitar, A. and Verhoest, N. E. C. and
                      Cabot, F. and De Lannoy, G. J. M. and Drusch, M. and
                      Dumedah, G. and Hendricks-Franssen, Harrie-Jan and Kerr, Y.
                      and Tomer, S. K. and Martens, B. and Merlin, O. and Pan, M.
                      and van den Berg, M. J. and Vereecken, Harry and Walker, J.
                      P. and Wood, E. F. and Pauwels, V. R. N.},
      title        = {{O}ptimization of a {R}adiative {T}ransfer {F}orward
                      {O}perator for {S}imulating {SMOS} {B}rightness
                      {T}emperatures over the {U}pper {M}ississippi {B}asin},
      journal      = {Journal of hydrometeorology},
      volume       = {16},
      number       = {3},
      issn         = {1525-7541},
      address      = {Boston, Mass.},
      publisher    = {AMS},
      reportid     = {FZJ-2016-01161},
      pages        = {1109 - 1134},
      year         = {2015},
      abstract     = {The Soil Moisture Ocean Salinity (SMOS) satellite mission
                      routinely provides global multiangular observations of
                      brightness temperature TB at both horizontal and vertical
                      polarization with a 3-day repeat period. The assimilation of
                      such data into a land surface model (LSM) may improve the
                      skill of operational flood forecasts through an improved
                      estimation of soil moisture SM. To accommodate for the
                      direct assimilation of the SMOS TB data, the LSM needs to be
                      coupled with a radiative transfer model (RTM), serving as a
                      forward operator for the simulation of multiangular and
                      multipolarization top of the atmosphere TBs. This study
                      investigates the use of the Variable Infiltration Capacity
                      model coupled with the Community Microwave Emission
                      Modelling Platform for simulating SMOS TB observations over
                      the upper Mississippi basin, United States. For a period of
                      2 years (2010–11), a comparison between SMOS TBs and
                      simulations with literature-based RTM parameters reveals a
                      basin-averaged bias of 30 K. Therefore, time series of SMOS
                      TB observations are used to investigate ways for mitigating
                      these large biases. Specifically, the study demonstrates the
                      impact of the LSM soil moisture climatology in the magnitude
                      of TB biases. After cumulative distribution function
                      matching the SM climatology of the LSM to SMOS retrievals,
                      the average bias decreases from 30 K to less than 5 K.
                      Further improvements can be made through calibration of RTM
                      parameters related to the modeling of surface roughness and
                      vegetation. Consequently, it can be concluded that SM
                      rescaling and RTM optimization are efficient means for
                      mitigating biases and form a necessary preparatory step for
                      data assimilation.},
      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},
      UT           = {WOS:000355126500010},
      doi          = {10.1175/JHM-D-14-0052.1},
      url          = {https://juser.fz-juelich.de/record/281468},
}