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@ARTICLE{Montzka:844293,
      author       = {Montzka, Carsten and Rötzer, Kathrina and Bogena, Heye and
                      Sanchez, Nilda and Vereecken, Harry},
      title        = {{A} {N}ew {S}oil {M}oisture {D}ownscaling {A}pproach for
                      {SMAP}, {SMOS}, and {ASCAT} by {P}redicting {S}ub-{G}rid
                      {V}ariability},
      journal      = {Remote sensing},
      volume       = {10},
      number       = {3},
      issn         = {2072-4292},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2018-01731},
      pages        = {427},
      year         = {2018},
      abstract     = {Several studies currently strive to improve the spatial
                      resolution of coarse scale high temporal resolution global
                      soil moisture products of SMOS, SMAP, and ASCAT. Soil
                      texture heterogeneity is known to be one of the main sources
                      of soil moisture spatial variability. With the recent
                      development of high resolution maps of basic soil properties
                      such as soil texture and bulk density, relevant information
                      to estimate soil moisture variability within a satellite
                      product grid cell is available. We use this information for
                      the prediction of the sub-grid soil moisture variability for
                      each SMOS, SMAP, and ASCAT grid cell. The approach is based
                      on a method that predicts the soil moisture standard
                      deviation as a function of the mean soil moisture based on
                      soil texture information. It is a closed-form expression
                      using stochastic analysis of 1D unsaturated gravitational
                      flow in an infinitely long vertical profile based on the
                      Mualem-van Genuchten model and first-order Taylor
                      expansions. We provide a look-up table that indicates the
                      soil moisture standard deviation for any given soil moisture
                      mean, available at https://doi.org/10.1594/PANGAEA.878889.
                      The resulting data set helps identify adequate regions to
                      validate coarse scale soil moisture products by providing a
                      measure of representativeness of small-scale measurements
                      for the coarse grid cell. Moreover, it contains important
                      information for downscaling coarse soil moisture
                      observations of the SMOS, SMAP, and ASCAT missions. In this
                      study, we present a simple application of the estimated
                      sub-grid soil moisture heterogeneity scaling down SMAP soil
                      moisture to 1 km resolution. Validation results in the
                      TERENO and REMEDHUS soil moisture monitoring networks in
                      Germany and Spain, respectively, indicate a similar or
                      slightly improved accuracy for downscaled and original SMAP
                      soil moisture in the time domain for the year 2016, but with
                      a much higher spatial resolution.},
      cin          = {IBG-3},
      ddc          = {620},
      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:000428280100073},
      doi          = {10.3390/rs10030427},
      url          = {https://juser.fz-juelich.de/record/844293},
}