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Publication Date
29 April 2015

Improving Representation of Convective Transport for Scale-Aware Parameterization, Part II: Analysis of Cloud-Resolving Model Simulations

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Summary

Cumulus clouds play an important role in energy and water transfers in the climate system. However, representation of those cumulus clouds in the regional and global climate models is one of the major error sources of weather and climate prediction. Using the cloud-resolving modeling simulations of convective clouds at the mid-latitudes and tropics, a team of scientists led by a U.S. Department of Energy researcher at Pacific Northwest National Laboratory, found the cumulus cloud fraction and convective transport of moisture by the unsolved cumulus clouds are strongly grid-spacing dependent. The team found that there are strong grid-spacing dependencies of updraft and downdraft fractions regardless of altitudes, cloud life stage, and geographical location. The single updraft approach for representing unsolved cumulus clouds significantly underestimates updraft eddy transport of water vapor because it fails to account for the large internal variability of updrafts, while a single downdraft represents the downdraft eddy transport of water vapor well. The team developed a new representation, accounting for the variability of updrafts and well representing the convective transport calculated from CRM simulations at different model grid-spacings.

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Acknowledgements

Support for this work was provided through Scientific Discovery through Advanced Computing (SciDAC) program funded by U.S. Department of Energy Office of Advanced Scientific Computing Research and Office of Biological and Environmental Research. The Pacific Northwest National Laboratory (PNNL) is operated for the DOE by Battelle Memorial Institute under contract DE-AC06-76RLO 1830. Kuan-Man Xu was supported by NASA Modeling, Analysis and Prediction program. The authors would like to thank Dr. Heng Xiao, Dr. Kyo-Sun Lim, and Dr. Zhe Feng from PNNL for valuable discussion. The data used in this study were produced by Pacific Northwest National Laboratory (PNNL), and are stored on PNNL Olympus. They will be available upon request by contacting the corresponding author.

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