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@ARTICLE{Sourdeval:857189,
      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},
      volume       = {18},
      number       = {19},
      issn         = {1680-7324},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2018-06426},
      pages        = {14327 - 14350},
      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 regarding
                      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 via a comparison of satellite estimates to
                      coincident 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 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 updrafts, such
                      as those related to convective or orographic uplifts.
                      Further evaluation and improvement of this method are
                      necessary, although these results already constitute a first
                      encouraging step towards large-scale observational
                      constraints for Ni. Part 2 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},
      UT           = {WOS:000446731000004},
      doi          = {10.5194/acp-18-14327-2018},
      url          = {https://juser.fz-juelich.de/record/857189},
}