Parameterizing deep convection using the assumed probability density function method
Due to their coarse horizontal resolution, presentday climate models must parameterize deep convection. This paper presents singlecolumn 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 singlecolumn simulations are compared with 3D 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 largescale model in a unified way.
 Authors:

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 Univ. of Wisconsin  Milwaukee, Milwaukee, WI (United States)
 Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
 Publication Date:
 Grant/Contract Number:
 SC0008668; SC0008323; AC0676RL01830
 Type:
 Published Article
 Journal Name:
 Geoscientific Model Development (Online)
 Additional Journal Information:
 Journal Name: Geoscientific Model Development (Online); Journal Volume: 8; Journal Issue: 1; Journal ID: ISSN 19919603
 Publisher:
 European Geosciences Union
 Research Org:
 Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
 Sponsoring Org:
 USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC23); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC21). Scientific Discovery through Advanced Computing (SciDAC)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 54 ENVIRONMENTAL SCIENCES
 OSTI Identifier:
 1227792
 Alternate Identifier(s):
 OSTI ID: 1195623
Storer, R. L., Griffin, B. M., Höft, J., Weber, J. K., Raut, E., Larson, V. E., Wang, M., and Rasch, P. J.. Parameterizing deep convection using the assumed probability density function method. United States: N. p.,
Web. doi:10.5194/gmd812015.
Storer, R. L., Griffin, B. M., Höft, J., Weber, J. K., Raut, E., Larson, V. E., Wang, M., & Rasch, P. J.. Parameterizing deep convection using the assumed probability density function method. United States. doi:10.5194/gmd812015.
Storer, R. L., Griffin, B. M., Höft, J., Weber, J. K., Raut, E., Larson, V. E., Wang, M., and Rasch, P. J.. 2015.
"Parameterizing deep convection using the assumed probability density function method". United States.
doi:10.5194/gmd812015.
@article{osti_1227792,
title = {Parameterizing deep convection using the assumed probability density function method},
author = {Storer, R. L. and Griffin, B. M. and Höft, J. and Weber, J. K. and Raut, E. and Larson, V. E. and Wang, M. and Rasch, P. J.},
abstractNote = {Due to their coarse horizontal resolution, presentday climate models must parameterize deep convection. This paper presents singlecolumn 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 singlecolumn simulations are compared with 3D 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 largescale model in a unified way.},
doi = {10.5194/gmd812015},
journal = {Geoscientific Model Development (Online)},
number = 1,
volume = 8,
place = {United States},
year = {2015},
month = {1}
}