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@PHDTHESIS{Costa:829847,
      author       = {Costa, Anja},
      title        = {{M}ixed-phase and ice cloud observations with
                      {NIXE}-{CAPS}},
      volume       = {397},
      school       = {Universität Wuppertal},
      type         = {Dissertation},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2017-03469},
      isbn         = {978-3-95806-273-3},
      series       = {Schriften des Forschungszentrums Jülich Reihe Energie $\&$
                      Umwelt / Energy $\&$ Environment},
      pages        = {xviii, 117 S.},
      year         = {2017},
      note         = {Universität Wuppertal, Diss., 2017},
      abstract     = {Clouds are a main component in the climate system. They
                      influence the energy balance of the atmosphere by changing
                      the earth’s albedo and greenhouse effect, and redistribute
                      energy by releasing and consuming latent heat in cloud
                      particle nucleation and dissolution processes. Climate
                      models therefore react sensitively on the implemented cloud
                      parametrizations, which have to be under constant review to
                      implement new insights into cloud formation and
                      evolutionprocesses. Ice clouds pose a particular challenge
                      for simulations: In mid-level and high clouds, several
                      possible ways for cloud glaciation and ice particle
                      formation compete. These processes produce particles that
                      vary strongly in habits, concentrations and radiative
                      properties. As long as it remains unclear which processes
                      are active, how their influence is distributed globally, how
                      these processes might change due to global warming, and what
                      the properties of the produced ice particles are, ice clouds
                      will remain a significant factor of uncertainty in climate
                      predictions. Over the last years, a number of studies has
                      been performed to examine these questions. The Jülich
                      instrument NIXE-CAPS has contributed a unique ice particle
                      concentration dataset that was used to evaluate global cloud
                      simulations. This thesis presents the extension of the
                      aforesaid dataset into mid-level clouds, where the
                      partitioning of ice and supercooled liquid water becomes
                      increasingly relevant. NIXE-CAPS provides three relevant
                      characteristics of the observed clouds: particle number
                      concentrations, particle size distributions and particle
                      asphericity - especially of small particles with diameters
                      below 50 $\mu$m, which have been rarely analysed so far. The
                      analysis of this data set was extended, evaluated and
                      accelerated in the course of this work: instrument
                      comparisons, error estimations and new corrections
                      complement earlier works with NIXE-CAPS. The improved
                      algorithms allowed a reanalysis of previous measurements and
                      resulted in a consistent data set covering 39 hours of
                      measurements within high clouds (cirrus) and over 38 hours
                      within mid-level clouds. With the NIXE-CAPS measurements,
                      the following tasks were performed: The proportions of
                      liquid, mixed-phase, ’small ice’, and ’large ice’
                      clouds were resolved for Arctic, mid-latitude and tropical
                      observations. Also, the new model CLaMS-Ice was evaluated
                      and improved with respect to its microphysical accuracy: It
                      provides detailed cirrus cloud simulations over a wide range
                      of meteorological conditions. It can thus be used for
                      large-scale cirrus cloud simulations which is expected to
                      lead to new insights regarding the global cirrus cloud
                      cover’s climatological characteristics.},
      cin          = {IEK-7},
      cid          = {I:(DE-Juel1)IEK-7-20101013},
      pnm          = {244 - Composition and dynamics of the upper troposphere and
                      middle atmosphere (POF3-244) / HITEC - Helmholtz
                      Interdisciplinary Doctoral Training in Energy and Climate
                      Research (HITEC) (HITEC-20170406)},
      pid          = {G:(DE-HGF)POF3-244 / G:(DE-Juel1)HITEC-20170406},
      typ          = {PUB:(DE-HGF)3 / PUB:(DE-HGF)11},
      url          = {https://juser.fz-juelich.de/record/829847},
}