Evaluating Low-Cloud Simulation from an Upgraded Multiscale Modeling Framework...

Xu, K., and A. Cheng (2013), Evaluating Low-Cloud Simulation from an Upgraded Multiscale Modeling Framework Model. Part I: Sensitivity to Spatial Resolution and Climatology, J. Climate, 26, 5717-5740, doi:10.1175/JCLI-D-12-00200.1.

The multiscale modeling framework, which replaces traditional cloud parameterizations with a 2D cloudresolving model (CRM) in each atmospheric column, is a promising approach to climate modeling. The CRM component contains an advanced third-order turbulence closure, helping it to better simulate low-level clouds. In this study, two simulations are performed with 1.98 3 2.58 grid spacing but they differ in the vertical resolution. The number of model layers below 700 hPa increases from 6 in one simulation (IP-6L) to 12 in another (IP-12L) to better resolve the boundary layer. The low-cloud horizontal distribution and vertical structures in IP-12L are more realistic and its global mean is higher than in IP-6L and closer to that of CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) observations. The spatial patterns of tropical precipitation are significantly improved; for example, a single intertropical convergence zone (ITCZ) in the Pacific, instead of double ITCZs in an earlier study that used coarser horizontal resolution and a different dynamical core in its host general circulation model (GCM), and the intensity of the South Pacific convergence zone (SPCZ), and the ITCZ in the Atlantic is more realistic. Many aspects of the global seasonal climatology agree well with observations except for excessive precipitation in the tropics. In terms of spatial correlations and patterns in the tropical/subtropical regions, most surface/vertically integrated properties show greater improvement over the earlier simulation than that with lower vertical resolution. The relationships between low-cloud amount and several large-scale properties are consistent with those observed in five low-cloud regions. There is an imbalance in the surface energy budget, which is an aspect of the model that needs to be improved in the future.

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Modeling Analysis and Prediction Program (MAP)