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@ARTICLE{Spang:811918,
      author       = {Spang, Reinhold and Hoffmann, Lars and Höpfner, Michael
                      and Griessbach, Sabine and Müller, Rolf and Pitts, Michael
                      C. and Orr, Andrew M. W. and Riese, Martin},
      title        = {{A} multi-wavelength classification method for polar
                      stratospheric cloud types using infrared limb spectra},
      journal      = {Atmospheric measurement techniques},
      volume       = {9},
      number       = {8},
      issn         = {1867-8548},
      address      = {Katlenburg-Lindau},
      publisher    = {Copernicus},
      reportid     = {FZJ-2016-04232},
      pages        = {3619 - 3639},
      year         = {2016},
      abstract     = {The Michelson Interferometer for Passive Atmospheric
                      Sounding (MIPAS) instrument on board the ESA Envisat
                      satellite operated from July 2002 until April 2012. The
                      infrared limb emission measurements represent a unique
                      dataset of daytime and night-time observations of polar
                      stratospheric clouds (PSCs) up to both poles. Cloud
                      detection sensitivity is comparable to space-borne lidars,
                      and it is possible to classify different cloud types from
                      the spectral measurements in different atmospheric windows
                      regions.Here we present a new infrared PSC classification
                      scheme based on the combination of a well-established
                      two-colour ratio method and multiple 2-D brightness
                      temperature difference probability density functions. The
                      method is a simple probabilistic classifier based on Bayes'
                      theorem with a strong independence assumption. The method
                      has been tested in conjunction with a database of radiative
                      transfer model calculations of realistic PSC particle size
                      distributions, geometries, and composition. The Bayesian
                      classifier distinguishes between solid particles of ice and
                      nitric acid trihydrate (NAT), as well as liquid droplets of
                      super-cooled ternary solution (STS).The classification
                      results are compared to coincident measurements from the
                      space-borne lidar Cloud-Aerosol Lidar with Orthogonal
                      Polarization (CALIOP) instrument over the temporal overlap
                      of both satellite missions (June 2006–March 2012). Both
                      datasets show a good agreement for the specific PSC classes,
                      although the viewing geometries and the vertical and
                      horizontal resolution are quite different. Discrepancies are
                      observed between the CALIOP and the MIPAS ice class. The
                      Bayesian classifier for MIPAS identifies substantially more
                      ice clouds in the Southern Hemisphere polar vortex than
                      CALIOP. This disagreement is attributed in part to the
                      difference in the sensitivity on mixed-type clouds. Ice
                      seems to dominate the spectral behaviour in the limb
                      infrared spectra and may cause an overestimation in ice
                      occurrence compared to the real fraction of ice within the
                      PSC area in the polar vortex.The entire MIPAS measurement
                      period was processed with the new classification approach.
                      Examples like the detection of the Antarctic NAT belt during
                      early winter, and its possible link to mountain wave events
                      over the Antarctic Peninsula, which are observed by the
                      Atmospheric Infrared Sounder (AIRS) instrument, highlight
                      the importance of a climatology of 9 Southern Hemisphere and
                      10 Northern Hemisphere winters in total. The new dataset is
                      valuable both for detailed process studies, and for
                      comparisons with and improvements of the PSC
                      parameterizations used in chemistry transport and climate
                      models.},
      cin          = {JSC / IEK-7},
      ddc          = {550},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IEK-7-20101013},
      pnm          = {244 - Composition and dynamics of the upper troposphere and
                      middle atmosphere (POF3-244) / 511 - Computational Science
                      and Mathematical Methods (POF3-511)},
      pid          = {G:(DE-HGF)POF3-244 / G:(DE-HGF)POF3-511},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000383146000001},
      doi          = {10.5194/amt-9-3619-2016},
      url          = {https://juser.fz-juelich.de/record/811918},
}