Improving Model Representation of Convective Transport for Scale-Aware Parameterization


Cumulus clouds play an important role in energy and water transfers in the climate system. However, representation of such clouds in the regional and global climate models is one of the major error sources of weather and climate predictions. Using the cloud-resolving modeling (CRM) simulations of convective clouds at the midlatitudes 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 updraft variability and well representing the convective transport calculated from CRM simulations at different model grid-spacings.


Liu, Y.-C., J. Fan, G. Zhang, K.-M. Xu, and S. J. Ghan. 2015. “Improving Representation of Convective Transport for Scale-Aware Parameterization: 2. Analysis of Cloud-Resolving Model Simulations,” Journal of Geophysical Research Atmospheres 120(8), 3510-32. DOI: 10.1002/2014JD022145.