Skip to main content
profile image
Selected Works of Minghui Diao
Article
Impacts of Representing Heterogeneous Distribution of Cloud Liquid and Ice on Phase Partitioning of Arctic Mixed‐Phase Clouds with NCAR CAM5
Journal of Geophysical Research: Atmospheres (2019)
  • Meng Zhang, University of Wyoming
  • Xiaohong Liu, University of Wyoming
  • Minghui Diao, San Jose State University
  • John J. D'Alessandro, University of Oklahoma
  • Yong Wang, Tsinghua University
  • Chenglai Wu, Chinese Academy of Sciences
  • Damao Zhang, Brookhaven National Laboratory
  • Zhien Wang, University of Colorado, Boulder
  • Shaocheng Xie, Lawrence Livermore National Laboratory
Find in your library
Abstract
In this study, we conduct sensitivity experiments with the Community Atmosphere Model version 5 to understand the impact of representing heterogeneous distribution between cloud liquid and ice on the phase partitioning in mixed‐phase clouds through different perturbations on the Wegener‐Bergeron‐Findeisen (WBF) process. In two experiments, perturbation factors that are based on assumptions of pocket structure and the partial homogeneous cloud volume derived from the High‐performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole‐to‐Pole Observation (HIPPO) campaign are utilized. Alternately, a mass‐weighted assumption is used in the calculation of WBF process to mimic the appearance of unsaturated area in mixed‐phase clouds as the result of heterogeneous distribution. Model experiments are tested in both single column and weather forecast modes and evaluated against data from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program's Mixed‐Phase Arctic Cloud Experiment (M‐PACE) field campaign and long‐term ground‐based multisensor measurements. Model results indicate that perturbations on the WBF process can significantly modify simulated microphysical properties of Arctic mixed‐phase clouds. The improvement of simulated cloud water phase partitioning tends to be linearly proportional to the perturbation magnitude that is applied in the three different sensitivity experiments. Cloud macrophysical properties such as cloud fraction and frequency of occurrence of low‐level mixed‐phase clouds are less sensitive to the perturbation magnitude than cloud microphysical properties. Moreover, this study indicates that heterogeneous distribution between cloud hydrometeors should be treated consistently for all cloud microphysical processes. The model vertical resolution is also important for liquid water maintenance in mixed‐phase clouds.
Keywords
  • atmospheric modeling,
  • cloud microphysics,
  • cloud water,
  • environmental research,
  • experiment,
  • heterogeneity,
  • model validation,
  • phase transition
Disciplines
Publication Date
November 18, 2019
DOI
10.1029/2019JD030502
Citation Information
Meng Zhang, Xiaohong Liu, Minghui Diao, John J. D'Alessandro, et al.. "Impacts of Representing Heterogeneous Distribution of Cloud Liquid and Ice on Phase Partitioning of Arctic Mixed‐Phase Clouds with NCAR CAM5" Journal of Geophysical Research: Atmospheres Vol. 124 Iss. 23 (2019) p. 13071 - 13090 ISSN: 2169-897X
Available at: http://works.bepress.com/minghui-diao/95/