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@ARTICLE{Spang:845125,
      author       = {Spang, Reinhold and Hoffmann, Lars and Müller, Rolf and
                      Grooß, Jens-Uwe and Tritscher, Ines and Höpfner, Michael
                      and Pitts, Michael and Orr, Andrew and Riese, Martin},
      title        = {{A} climatology of polar stratospheric cloud composition
                      between 2002 and 2012 based on {MIPAS}/{E}nvisat
                      observations},
      journal      = {Atmospheric chemistry and physics},
      volume       = {18},
      number       = {7},
      issn         = {1680-7324},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2018-02444},
      pages        = {5089 - 5113},
      year         = {2018},
      abstract     = {The Michelson Interferometer for Passive Atmospheric
                      Sounding (MIPAS) instrument aboard the European Space Agency
                      (ESA) Envisat satellite operated from July 2002 to April
                      2012. The infrared limb emission measurements provide a
                      unique dataset of day and night observations of polar
                      stratospheric clouds (PSCs) up to both poles. A recent
                      classification method for PSC types in infrared (IR) limb
                      spectra using spectral measurements in different atmospheric
                      window regions has been applied to the complete mission
                      period of MIPAS. The method uses a simple probabilistic
                      classifier based on Bayes' theorem with a strong
                      independence assumption on a combination of a
                      well-established two-colour ratio method and multiple 2-D
                      probability density functions of brightness temperature
                      differences. The Bayesian classifier distinguishes between
                      solid particles of ice, nitric acid trihydrate (NAT), and
                      liquid droplets of supercooled ternary solution (STS), as
                      well as mixed types.A climatology of MIPAS PSC occurrence
                      and specific PSC classes has been compiled. Comparisons with
                      results from the classification scheme of the spaceborne
                      lidar Cloud-Aerosol Lidar with Orthogonal Polarization
                      (CALIOP) on the Cloud-Aerosol-Lidar and Infrared Pathfinder
                      Satellite Observations (CALIPSO) satellite show excellent
                      correspondence in the spatial and temporal evolution for the
                      area of PSC coverage (APSC) even for each PSC class.
                      Probability density functions of the PSC temperature,
                      retrieved for each class with respect to equilibrium
                      temperature of ice and based on coincident temperatures from
                      meteorological reanalyses, are in accordance with the
                      microphysical knowledge of the formation processes with
                      respect to temperature for all three PSC types.This paper
                      represents unprecedented pole-covering day- and nighttime
                      climatology of the PSC distributions and their composition
                      of different particle types. The dataset allows analyses on
                      the temporal and spatial development of the PSC formation
                      process over multiple winters. At first view, a more general
                      comparison of APSC and AICE retrieved from the observations
                      and from the existence temperature for NAT and ice particles
                      based on the European Centre for Medium-Range Weather
                      Forecasts (ECMWF) reanalysis temperature data shows the high
                      potential of the climatology for the validation and
                      improvement of PSC schemes in chemical transport and
                      chemistry–climate models.},
      cin          = {JSC / IEK-7},
      ddc          = {550},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IEK-7-20101013},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / 244 - Composition and dynamics of the upper
                      troposphere and middle atmosphere (POF3-244)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-HGF)POF3-244},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000430171500002},
      doi          = {10.5194/acp-18-5089-2018},
      url          = {https://juser.fz-juelich.de/record/845125},
}