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Title: Mean-state acceleration of cloud-resolving models and large eddy simulations: CRM AND LES MEAN-STATE ACCELERATION

Abstract

In this study, large eddy simulations and cloud-resolving models (CRMs) are routinely used to simulate boundary layer and deep convective cloud processes, aid in the development of moist physical parameterization for global models, study cloud-climate feedbacks and cloud-aerosol interaction, and as the heart of superparameterized climate models. These models are computationally demanding, placing practical constraints on their use in these applications, especially for long, climate-relevant simulations. In many situations, the horizontal-mean atmospheric structure evolves slowly compared to the turnover time of the most energetic turbulent eddies. We develop a simple scheme to reduce this time scale separation to accelerate the evolution of the mean state. Using this approach we are able to accelerate the model evolution by a factor of 2–16 or more in idealized stratocumulus, shallow and deep cumulus convection without substantial loss of accuracy in simulating mean cloud statistics and their sensitivity to climate change perturbations. As a culminating test, we apply this technique to accelerate the embedded CRMs in the Superparameterized Community Atmosphere Model by a factor of 2, thereby showing that the method is robust and stable to realistic perturbations across spatial and temporal scales typical in a GCM.

Authors:
 [1];  [1];  [2]
  1. Department of Atmospheric Sciences, University of Washington, Seattle Washington USA
  2. Department of Earth System Science, University of California, Irvine California USA
Publication Date:
Research Org.:
Univ. of California, Irvine, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1619305
Alternate Identifier(s):
OSTI ID: 1243064
Grant/Contract Number:  
SC0012152; SC0012451; SC0012548
Resource Type:
Published Article
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Name: Journal of Advances in Modeling Earth Systems Journal Volume: 7 Journal Issue: 4; Journal ID: ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Jones, C. R., Bretherton, C. S., and Pritchard, M. S. Mean-state acceleration of cloud-resolving models and large eddy simulations: CRM AND LES MEAN-STATE ACCELERATION. United States: N. p., 2015. Web. doi:10.1002/2015MS000488.
Jones, C. R., Bretherton, C. S., & Pritchard, M. S. Mean-state acceleration of cloud-resolving models and large eddy simulations: CRM AND LES MEAN-STATE ACCELERATION. United States. https://doi.org/10.1002/2015MS000488
Jones, C. R., Bretherton, C. S., and Pritchard, M. S. Thu . "Mean-state acceleration of cloud-resolving models and large eddy simulations: CRM AND LES MEAN-STATE ACCELERATION". United States. https://doi.org/10.1002/2015MS000488.
@article{osti_1619305,
title = {Mean-state acceleration of cloud-resolving models and large eddy simulations: CRM AND LES MEAN-STATE ACCELERATION},
author = {Jones, C. R. and Bretherton, C. S. and Pritchard, M. S.},
abstractNote = {In this study, large eddy simulations and cloud-resolving models (CRMs) are routinely used to simulate boundary layer and deep convective cloud processes, aid in the development of moist physical parameterization for global models, study cloud-climate feedbacks and cloud-aerosol interaction, and as the heart of superparameterized climate models. These models are computationally demanding, placing practical constraints on their use in these applications, especially for long, climate-relevant simulations. In many situations, the horizontal-mean atmospheric structure evolves slowly compared to the turnover time of the most energetic turbulent eddies. We develop a simple scheme to reduce this time scale separation to accelerate the evolution of the mean state. Using this approach we are able to accelerate the model evolution by a factor of 2–16 or more in idealized stratocumulus, shallow and deep cumulus convection without substantial loss of accuracy in simulating mean cloud statistics and their sensitivity to climate change perturbations. As a culminating test, we apply this technique to accelerate the embedded CRMs in the Superparameterized Community Atmosphere Model by a factor of 2, thereby showing that the method is robust and stable to realistic perturbations across spatial and temporal scales typical in a GCM.},
doi = {10.1002/2015MS000488},
journal = {Journal of Advances in Modeling Earth Systems},
number = 4,
volume = 7,
place = {United States},
year = {Thu Oct 29 00:00:00 EDT 2015},
month = {Thu Oct 29 00:00:00 EDT 2015}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1002/2015MS000488

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Cited by: 13 works
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Works referencing / citing this record:

Regional Superparameterization in a Global Circulation Model Using Large Eddy Simulations
journal, September 2019

  • Jansson, Fredrik; van den Oord, Gijs; Pelupessy, Inti
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Possible climate transitions from breakup of stratocumulus decks under greenhouse warming
journal, February 2019