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:
-
- 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. https://doi.org/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. https://doi.org/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 = {Tue Jul 31 00:00:00 EDT 2012},
month = {Tue Jul 31 00:00:00 EDT 2012}
}
Web of Science
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