% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@PHDTHESIS{Frick:283548,
      author       = {Frick, Claudia},
      title        = {{T}he numerical modeling of wet snowfall events},
      school       = {ETH Zurich},
      type         = {Dr.},
      publisher    = {Zürich, ETH},
      reportid     = {FZJ-2016-01864, 20624},
      pages        = {138},
      year         = {2012},
      note         = {ETH Zurich, Diss., 2013},
      abstract     = {The prediction of snowfall is particularly challenging for
                      numerical weather prediction models. At the beginning of
                      this dissertation, an event of wet and heavy snowfall in NW
                      Germany is investigated. Simulations reveal a low
                      predictability of the event more than one day in advance. An
                      appropriate simulation of the synoptic scale processes is as
                      essential for an accurate snowfall prediction as an adequate
                      microphysical representation of precipitation. Even for a
                      perfect simulation of the dynamics and the atmospheric
                      background conditions, the phase of surface precipitation is
                      difficult to predict, especially under near-surface melting
                      conditions. Additionally, a direct simulation of partially
                      melted snowfall is not possible for the standard
                      microphysical parameterization of the COSMO model.
                      Therefore, the development and implementation of a new
                      melting scheme including a new prognostic variable, the
                      meltwater of snow, is presented. The introduced bulk
                      microphysical parameterization allows an internal mixing of
                      water and ice in the snow category of the COSMO model.
                      Liquid water fraction is assumed to vary with the size in
                      the represented snowflake ensemble, leading to a faster
                      melting of smaller snowflakes compared to larger ones. For a
                      first validation of the effects of the new melting scheme,
                      two wet snowfall events are simulated using the standard and
                      the new parameterization. Approximately one third of the
                      surface precipitation is predicted as snowfall for both
                      schemes with 1 to 2 percent higher snow fractions for the
                      new melting scheme. A categorization of surface snowfall in
                      dry and wet snow for the new parameterization reveals that
                      approximately one third of the surface snowfall is predicted
                      to be wet snow. The modified melting process of the new
                      parameterization leads to an onset of rain at lower
                      altitudes and a deeper vertical penetration of snow into the
                      potential melting layer. The evolution of the precipitation
                      phase from snow to rain is decelerated especially for snow
                      fractions below 40 percent and liquid to ice ratios larger
                      than 1. Overall, the new melting scheme slows down the
                      melting process, slightly enhances surface snow fraction,
                      and allows a direct prediction of wet snowfall at the
                      surface. The new melting scheme also allows a realistic
                      simulation of a melting layer of wet snow, which is related
                      to the “bright band” in radar imagery.},
      typ          = {PUB:(DE-HGF)29 / PUB:(DE-HGF)11},
      doi          = {10.3929/ethz-a-007595470},
      url          = {https://juser.fz-juelich.de/record/283548},
}