Parameterizing Deep Convection Using the Assumed Probability Density Function Method

TitleParameterizing Deep Convection Using the Assumed Probability Density Function Method
Publication TypeJournal Article
Year of Publication2015
JournalGeoscientific Model Development
Volume8
Pages1-19
Date Published01/2015
Abstract / Summary

Due to their coarse horizontal resolution, present day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.
The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.
The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.

URLhttp://www.geosci-model-dev.net/8/1/2015/gmd-8-1-2015.html
DOI10.5194/gmd-8-1-2015
Journal: Geoscientific Model Development
Year of Publication: 2015
Volume: 8
Pages: 1-19
Date Published: 01/2015

Due to their coarse horizontal resolution, present day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method.
The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak.
The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.

DOI: 10.5194/gmd-8-1-2015
Citation:
2015.  "Parameterizing Deep Convection Using the Assumed Probability Density Function Method."  Geoscientific Model Development 8: 1-19.  https://doi.org/10.5194/gmd-8-1-2015.