Editorial Type:
Article
Article Type:
Research Article

Multivariate Probability Density Functions with Dynamics in the GFDL Atmospheric General Circulation Model: Global Tests

Huan Guo UCAR Visiting Scientist Programs, NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Jean-Christophe Golaz NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Leo J. Donner NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Paul Ginoux NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey

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Richard S. Hemler High Performance Technologies Group, DRC/GFDL, Princeton, New Jersey

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Print Publication:
01 Mar 2014
DOI:
https://doi.org/10.1175/JCLI-D-13-00347.1
Page(s):
2087–2108
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Abstract

A unified turbulence and cloud parameterization based on multivariate probability density functions (PDFs) has been incorporated into the GFDL atmospheric general circulation model (AM3). This PDF-based parameterization not only predicts subgrid variations in vertical velocity, temperature, and total water, which bridge subgrid-scale processes (e.g., aerosol activation and cloud microphysics) and grid-scale dynamic and thermodynamic fields, but also unifies the treatment of planetary boundary layer (PBL), shallow convection, and cloud macrophysics. This parameterization is called the Cloud Layers Unified by Binormals (CLUBB) parameterization. With the incorporation of CLUBB in AM3, coupled with a two-moment cloud microphysical scheme, AM3–CLUBB allows for a more physically based and self-consistent treatment of aerosol activation, cloud micro- and macrophysics, PBL, and shallow convection.

The configuration and performance of AM3–CLUBB are described. Cloud and radiation fields, as well as most basic climate features, are modeled realistically. Relative to AM3, AM3–CLUBB improves the simulation of coastal stratocumulus, a longstanding deficiency in GFDL models, and their seasonal cycle, especially at higher horizontal resolution, but global skill scores deteriorate slightly. Through sensitivity experiments, it is shown that 1) the two-moment cloud microphysics helps relieve the deficiency of coastal stratocumulus, 2) using the CLUBB subgrid cloud water variability in the cloud microphysics has a considerable positive impact on global cloudiness, and 3) the impact of adjusting CLUBB parameters is to improve the overall agreement between model and observations.

Corresponding author address: Huan Guo, UCAR Visiting Scientist Programs, NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540. E-mail: huan.guo@noaa.gov

Abstract

A unified turbulence and cloud parameterization based on multivariate probability density functions (PDFs) has been incorporated into the GFDL atmospheric general circulation model (AM3). This PDF-based parameterization not only predicts subgrid variations in vertical velocity, temperature, and total water, which bridge subgrid-scale processes (e.g., aerosol activation and cloud microphysics) and grid-scale dynamic and thermodynamic fields, but also unifies the treatment of planetary boundary layer (PBL), shallow convection, and cloud macrophysics. This parameterization is called the Cloud Layers Unified by Binormals (CLUBB) parameterization. With the incorporation of CLUBB in AM3, coupled with a two-moment cloud microphysical scheme, AM3–CLUBB allows for a more physically based and self-consistent treatment of aerosol activation, cloud micro- and macrophysics, PBL, and shallow convection.

The configuration and performance of AM3–CLUBB are described. Cloud and radiation fields, as well as most basic climate features, are modeled realistically. Relative to AM3, AM3–CLUBB improves the simulation of coastal stratocumulus, a longstanding deficiency in GFDL models, and their seasonal cycle, especially at higher horizontal resolution, but global skill scores deteriorate slightly. Through sensitivity experiments, it is shown that 1) the two-moment cloud microphysics helps relieve the deficiency of coastal stratocumulus, 2) using the CLUBB subgrid cloud water variability in the cloud microphysics has a considerable positive impact on global cloudiness, and 3) the impact of adjusting CLUBB parameters is to improve the overall agreement between model and observations.

Corresponding author address: Huan Guo, UCAR Visiting Scientist Programs, NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540. E-mail: huan.guo@noaa.gov
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