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Title: Regional assessment of the parameter-dependent performance of CAM4 in simulating tropical clouds

Abstract

Representation of clouds remains among the largest uncertainties in climate models and thus climate projections. Clouds vary significantly over different climate regimes and are controlled by different dynamics and physics. Using the cloud simulator output from perturbed-parameter ensemble climate runs with prescribed monthly sea surface temperature, this study examines the performance of the Community Atmosphere Model version 4 (CAM4) in simulating clouds over different tropical regions. Perturbing 28 selected parameters shows that model performance is quite sensitive to parameter values in different cloud regimes. Carefully adjusting these parameters could lead to a better simulation of clouds over many regions compared with the default model. Latin hypercube runs that pseudo-randomly sample the 28 parameters simultaneously have much wider spread and more spatial variations than the runs with parameters varied One-At-a-Time (OAT), suggesting the importance of non-linearities and interactions among parameters associated with different physical processes. The perturbed parameters have a relatively large impact on the mean bias compared to the pattern error

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1369383
Report Number(s):
LLNL-JRNL-548674
Journal ID: ISSN 0094-8276
Grant/Contract Number:  
AC52-07NA27344
Resource Type:
Accepted Manuscript
Journal Name:
Geophysical Research Letters
Additional Journal Information:
Journal Volume: 39; Journal Issue: 14; Journal ID: ISSN 0094-8276
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; CAM4; regional assessment; tropical clouds

Citation Formats

Zhang, Yuying, Xie, Shaocheng, Covey, Curt, Lucas, Donald D., Gleckler, Peter, Klein, Stephen A., Tannahill, John, Doutriaux, Charles, and Klein, Richard. Regional assessment of the parameter-dependent performance of CAM4 in simulating tropical clouds. United States: N. p., 2012. Web. doi:10.1029/2012GL052184.
Zhang, Yuying, Xie, Shaocheng, Covey, Curt, Lucas, Donald D., Gleckler, Peter, Klein, Stephen A., Tannahill, John, Doutriaux, Charles, & Klein, Richard. Regional assessment of the parameter-dependent performance of CAM4 in simulating tropical clouds. United States. doi:10.1029/2012GL052184.
Zhang, Yuying, Xie, Shaocheng, Covey, Curt, Lucas, Donald D., Gleckler, Peter, Klein, Stephen A., Tannahill, John, Doutriaux, Charles, and Klein, Richard. Tue . "Regional assessment of the parameter-dependent performance of CAM4 in simulating tropical clouds". United States. doi:10.1029/2012GL052184. https://www.osti.gov/servlets/purl/1369383.
@article{osti_1369383,
title = {Regional assessment of the parameter-dependent performance of CAM4 in simulating tropical clouds},
author = {Zhang, Yuying and Xie, Shaocheng and Covey, Curt and Lucas, Donald D. and Gleckler, Peter and Klein, Stephen A. and Tannahill, John and Doutriaux, Charles and Klein, Richard},
abstractNote = {Representation of clouds remains among the largest uncertainties in climate models and thus climate projections. Clouds vary significantly over different climate regimes and are controlled by different dynamics and physics. Using the cloud simulator output from perturbed-parameter ensemble climate runs with prescribed monthly sea surface temperature, this study examines the performance of the Community Atmosphere Model version 4 (CAM4) in simulating clouds over different tropical regions. Perturbing 28 selected parameters shows that model performance is quite sensitive to parameter values in different cloud regimes. Carefully adjusting these parameters could lead to a better simulation of clouds over many regions compared with the default model. Latin hypercube runs that pseudo-randomly sample the 28 parameters simultaneously have much wider spread and more spatial variations than the runs with parameters varied One-At-a-Time (OAT), suggesting the importance of non-linearities and interactions among parameters associated with different physical processes. The perturbed parameters have a relatively large impact on the mean bias compared to the pattern error},
doi = {10.1029/2012GL052184},
journal = {Geophysical Research Letters},
number = 14,
volume = 39,
place = {United States},
year = {2012},
month = {7}
}

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