Intercomparison of large‐eddy simulations of Arctic mixed‐phase clouds: Importance of ice size distribution assumptions

By M. Ovchinnikov, A. Ackerman, A. Avramov, A. Cheng, Jiwen Fan, A. Fridlind, Steven Ghan, J. Harrington, C. Hoose, A. Korolev and 8 more. 2014

149 citations recorded by the source corpus.

Large‐eddy simulations of mixed‐phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi‐Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, Ni, exerts significant influence on the cloud structure. Increasing Ni leads to a substantial reduction in liquid water path (LWP), in agreement with earlier studies. In contrast to previous intercomparison studies, all models here use the same ice particle properties (i.e., mass‐size, mass‐fall speed, and mass‐capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSDs) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass‐weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case. Sensitivity tests indicate LWP and IWP are much closer to the bin model simulations when a modified shape factor which is similar to that predicted by bin model simulation is used in bulk scheme. These results demonstrate the importance of representation of ice PSD in determining the partitioning of liquid and ice and the longevity of mixed‐phase clouds.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/3e70794b8a6fa1a3a3e45de0dc020e4293de3209

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In Atmospheric Science

  1. M. Krämer
  2. Ulrike Lohmann
  3. Paul R. Field
  4. M. Schnaiter
  5. J. Crosier
  6. P. Lawson
  7. S. Abel
  8. G. McFarquhar

In Global and Planetary Change

  1. Ulrike Lohmann
  2. M. Krämer
  3. Paul R. Field
  4. M. Schnaiter
  5. J. Crosier
  6. P. Lawson
  7. S. Abel
  8. G. McFarquhar

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