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@ARTICLE{Sourdeval:852608,
      author       = {Sourdeval, Odran and Gryspeerdt, Edward and Krämer,
                      Martina and Goren, Tom and Delanoë, Julien and Afchine,
                      Armin and Hemmer, Friederike and Quaas, Johannes},
      title        = {{I}ce crystal number concentration estimates from
                      lidar-radar satellite remote sensing. {P}art 1: {M}ethod and
                      evaluation},
      journal      = {Atmospheric chemistry and physics / Discussions},
      volume       = {},
      issn         = {1680-7375},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2018-05512},
      pages        = {1 - 31},
      year         = {2018},
      abstract     = {The number concentration of cloud particles is a key
                      quantity for understanding aerosol-cloud interactions and
                      describing clouds in climate and numerical weather
                      prediction models. In contrast with recent advances for
                      liquid clouds, few observational constraints exist on the
                      ice crystal number concentration (Ni). This study
                      investigates how combined lidar-radar measurements can be
                      used to provide satellite estimates of Ni, using a
                      methodology that constrains moments of a parameterized
                      particle size distribution (PSD). The operational
                      liDAR-raDAR (DARDAR) product serves as an existing base for
                      this method, which focuses on ice clouds with temperatures
                      Tc<−30°C. Theoretical considerations demonstrate the
                      capability for accurate retrievals of Ni, apart from a
                      possible bias in the concentration in small crystals when
                      Tc≳−50°C, due to the assumption of a monomodal PSD
                      shape in the current method. This is verified by comparing
                      satellite estimates to co-incident in situ measurements,
                      which additionally demonstrates the sufficient sensitivity
                      of lidar-radar observations to Ni. Following these results,
                      satellite estimates of Ni are evaluated in the context of a
                      case study and a preliminary climatological analysis based
                      on 10 years of global data. Despite of a lack of other
                      large-scale references, this evaluation shows a reasonable
                      physical consistency in Ni spatial distribution patterns.
                      Notably, increases in Ni are found towards cold temperatures
                      and, more significantly, in the presence of strong
                      updraughts, such as those related to convective or
                      orographic uplifts. Further evaluation and improvements of
                      this method are necessary but these results already
                      constitute a first encouraging step towards large-scale
                      observational constraints for Ni. Part two of this series
                      uses this new dataset to examine the controls on Ni.},
      cin          = {IEK-7},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IEK-7-20101013},
      pnm          = {244 - Composition and dynamics of the upper troposphere and
                      middle atmosphere (POF3-244)},
      pid          = {G:(DE-HGF)POF3-244},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.5194/acp-2018-20},
      url          = {https://juser.fz-juelich.de/record/852608},
}