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Understanding rapid changes in phase partitioning between cloud liquid and ice in stratiform mixed-phase clouds: An arctic case study

  • Heike Kalesse
  • , Gijs de Boer
  • , Amy Solomon
  • , Mariko Oue
  • , Maike Ahlgrimm
  • , Damao Zhang
  • , Matthew D. Shupe
  • , Edward Luke
  • , Alain Protat
  • Leibniz Institute for Tropospheric Research
  • University of Colorado Boulder
  • National Oceanic and Atmospheric Administration
  • European Centre for Medium-Range Weather Forecasts
  • University of Wyoming
  • Brookhaven National Laboratory
  • Bureau of Meteorology Australia

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Understanding phase transitions in mixed-phase clouds is of great importance because the hydrometeor phase controls the lifetime and radiative effects of clouds. In high latitudes, these cloud radiative effects have a crucial impact on the surface energy budget and thus on the evolution of the ice cover. For a springtime low-level mixed-phase stratiform cloud case from Barrow, Alaska, a unique combination of instruments and retrieval methods is combined with multiple modeling perspectives to determine key processes that control cloud phase partitioning. The interplay of local cloud-scale versus large-scale processes is considered. Rapid changes in phase partitioning were found to be caused by several main factors. Major influences were the large-scale advection of different air masses with different aerosol concentrations and humidity content, cloud-scale processes such as a change in the thermodynamical coupling state, and local-scale dynamics influencing the residence time of ice particles. Other factors such as radiative shielding by a cirrus and the influence of the solar cycle were found to only play a minor role for the specific case study (11-12 March 2013). For an even better understanding of cloud phase transitions, observations of key aerosol parameters such as profiles of cloud condensation nucleus and ice nucleus concentration are desirable.

Original languageEnglish
Pages (from-to)4805-4826
Number of pages22
JournalMonthly Weather Review
Volume144
Issue number12
DOIs
StatePublished - 2016

Keywords

  • Arctic
  • Climate models
  • Cloud retrieval
  • Lidars/Lidar observations
  • Radars/Radar observations
  • Remote sensing

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