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Short‐term time step convergence in a climate model

This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral‐element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process‐coupling time step is varied betwe...

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Autores principales: Wan, Hui, Rasch, Philip J., Taylor, Mark A., Jablonowski, Christiane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016774/
https://www.ncbi.nlm.nih.gov/pubmed/27660669
http://dx.doi.org/10.1002/2014MS000368
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author Wan, Hui
Rasch, Philip J.
Taylor, Mark A.
Jablonowski, Christiane
author_facet Wan, Hui
Rasch, Philip J.
Taylor, Mark A.
Jablonowski, Christiane
author_sort Wan, Hui
collection PubMed
description This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral‐element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process‐coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid‐scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate of the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full‐physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid‐scale physical parameterizations, the stratiform cloud schemes are associated with the largest time‐stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time‐stepping errors and identify the related model sensitivities.
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spelling pubmed-50167742016-09-20 Short‐term time step convergence in a climate model Wan, Hui Rasch, Philip J. Taylor, Mark A. Jablonowski, Christiane J Adv Model Earth Syst Research Articles This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral‐element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process‐coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid‐scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate of the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full‐physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid‐scale physical parameterizations, the stratiform cloud schemes are associated with the largest time‐stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time‐stepping errors and identify the related model sensitivities. John Wiley and Sons Inc. 2015-02-11 2015-03 /pmc/articles/PMC5016774/ /pubmed/27660669 http://dx.doi.org/10.1002/2014MS000368 Text en © 2015. The Authors. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs (http://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Wan, Hui
Rasch, Philip J.
Taylor, Mark A.
Jablonowski, Christiane
Short‐term time step convergence in a climate model
title Short‐term time step convergence in a climate model
title_full Short‐term time step convergence in a climate model
title_fullStr Short‐term time step convergence in a climate model
title_full_unstemmed Short‐term time step convergence in a climate model
title_short Short‐term time step convergence in a climate model
title_sort short‐term time step convergence in a climate model
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016774/
https://www.ncbi.nlm.nih.gov/pubmed/27660669
http://dx.doi.org/10.1002/2014MS000368
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