Dynamical and microphysical evolution during mixed-phase cloud glaciation simulated using the bulk adaptive habit prediction model

A bulk microphysics scheme predicting ice particle habit evolution has been implemented in the Weather Research and Forecasting Model. Large-eddy simulations are analyzed to study the effects of ice habit and number concentration on the bulk ice and liquid masses, dynamics, and lifetime of Arctic mixed-phase boundary layer clouds. The microphysical and dynamical evolution simulated using the adaptive habit scheme is compared with that assuming spherical particles with a density of bulk ice or a reduced density and with mass–dimensional parameterizations. It is found that the adaptive habit method returns an increased (decreased) ice (liquid) mass as compared to spheres and provides a more accurate simulation as compared to dendrite mass–size relations. Using the adaptive habit method, simulations are then completed to understand the microphysical and dynamical interactions within a single-layer mixed-phase stratocumulus cloud observed during flight 31 of the Indirect and Semi-Direct Aerosol Campaign. With cloud-top longwave radiative cooling as a function of liquid mass acting as the primary dynamic driver of turbulent eddies within these clouds, the consumption of liquid at the expense of ice growth and subsequent sedimentation holds a strong control on the cloud lifetime. Ice concentrations ≥ 4 L−1 collapse the liquid layer without any external maintaining sources. Layer maintenance is possible at 4 L−1 when a constant cloud-top cooling rate or the water mass lost due to sedimentation is supplied. Larger concentrations require a more substantial source of latent or sensible heat for mixed-phase persistence.

To Access Resource:

Questions? Email Resource Support Contact:

  • opensky@ucar.edu
    UCAR/NCAR - Library

Resource Type publication
Temporal Range Begin N/A
Temporal Range End N/A
Temporal Resolution N/A
Bounding Box North Lat N/A
Bounding Box South Lat N/A
Bounding Box West Long N/A
Bounding Box East Long N/A
Spatial Representation N/A
Spatial Resolution N/A
Related Links N/A
Additional Information N/A
Resource Format PDF
Standardized Resource Format PDF
Asset Size N/A
Legal Constraints

Copyright 2014 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or amspubs@ametsoc.org. Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work.


Access Constraints None
Software Implementation Language N/A

Resource Support Name N/A
Resource Support Email opensky@ucar.edu
Resource Support Organization UCAR/NCAR - Library
Distributor N/A
Metadata Contact Name N/A
Metadata Contact Email opensky@ucar.edu
Metadata Contact Organization UCAR/NCAR - Library

Author Sulia, Kara
Morrison, Hugh
Harrington, Jerry
Publisher UCAR/NCAR - Library
Publication Date 2014-11-01T00:00:00
Digital Object Identifier (DOI) Not Assigned
Alternate Identifier N/A
Resource Version N/A
Topic Category geoscientificInformation
Progress N/A
Metadata Date 2023-08-18T18:56:22.799473
Metadata Record Identifier edu.ucar.opensky::articles:14427
Metadata Language eng; USA
Suggested Citation Sulia, Kara, Morrison, Hugh, Harrington, Jerry. (2014). Dynamical and microphysical evolution during mixed-phase cloud glaciation simulated using the bulk adaptive habit prediction model. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7z320mp. Accessed 23 May 2025.

Harvest Source