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@ARTICLE{Strebel:905583,
      author       = {Strebel, Lukas and Bogena, Heye R. and Vereecken, Harry and
                      Hendricks-Franssen, Harrie-Jan},
      title        = {{C}oupling the {C}ommunity {L}and {M}odel version 5.0 to
                      the parallel data assimilation framework {PDAF}: description
                      and applications},
      journal      = {Geoscientific model development},
      volume       = {15},
      number       = {2},
      issn         = {1991-959X},
      address      = {Katlenburg-Lindau},
      publisher    = {Copernicus},
      reportid     = {FZJ-2022-00815},
      pages        = {395 - 411},
      year         = {2022},
      abstract     = {Land surface models are important for improving our
                      understanding of the Earth system. They are continuously
                      improving and becoming better in representing the different
                      land surface processes, e.g., the Community Land Model
                      version 5 (CLM5). Similarly, observational networks and
                      remote sensing operations are increasingly providing more
                      data, e.g., from new satellite products and new in situ
                      measurement sites, with increasingly higher quality for a
                      range of important variables of the Earth system. For the
                      optimal combination of land surface models and observation
                      data, data assimilation techniques have been developed in
                      recent decades that incorporate observations to update
                      modeled states and parameters. The Parallel Data
                      Assimilation Framework (PDAF) is a software environment that
                      enables ensemble data assimilation and simplifies the
                      implementation of data assimilation systems in numerical
                      models. In this study, we present the development of the new
                      interface between PDAF and CLM5. This newly implemented
                      coupling integrates the PDAF functionality into CLM5 by
                      modifying the CLM5 ensemble mode to keep changes to the
                      pre-existing parallel communication infrastructure to a
                      minimum. Soil water content observations from an extensive
                      in situ measurement network in the Wüstebach catchment in
                      Germany are used to illustrate the application of the
                      coupled CLM5-PDAF system. The results show overall
                      reductions in root mean square error of soil water content
                      from $7 \%$ up to $35 \%$ compared to simulations
                      without data assimilation. We expect the coupled CLM5-PDAF
                      system to provide a basis for improved regional to global
                      land surface modeling by enabling the assimilation of
                      globally available observational data.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2173},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000747097400001},
      doi          = {10.5194/gmd-15-395-2022},
      url          = {https://juser.fz-juelich.de/record/905583},
}