In this study, an explicit representation of vertical momentum transport by convective cloud systems, including mesoscale convective systems (MCSs), is proposed and tested in a multiscale modeling framework (MMF). The embedded cloud-resolving model (CRM) provides vertical momentum transport in one horizontal direction. The vertical momentum transport in the other direction is assumed to be proportional to the vertical mass flux diagnosed from the CRM in addition to the effects of entrainment and detrainment. In order to represent both upgradient and downgradient vertical momentum transports, the orientation of the embedded CRM must change with time instead of being stationary typically in MMFs. The orientation is determined by the stratification of the lower troposphere and environmental wind shear. Introducing the variation of the orientations of the embedded CRM is responsible for reducing the stationary anomalous precipitation and many improvements. Improvements are strengthened when the CRM simulated vertical momentum transport is allowed to modify the large-scale circulation simulated by the host general circulation model. These include an improved spatial distribution, amplitude, and intraseasonal variability of the surface precipitation in the tropics, more realistic zonal mean diabatic heating and drying patterns, more reasonable zonal mean large-scale circulations and the East Asian summer monsoon circulation, and an improved, annual mean implied meridional ocean transport in the Southern Hemisphere. Further tests of this convective momentum transport parameterization scheme will be performed with a higher-resolution MMF to further understand its roles in the intraseasonal oscillation and tropical waves, monsoon circulation, and zonal mean large-scale circulations.
An explicit representation of vertical momentum transport in a multiscale modeling frameworkthrough its 2-D cloud-resolving model component
Cheng, A., and K. Xu (2014), An explicit representation of vertical momentum transport in a multiscale modeling frameworkthrough its 2-D cloud-resolving model component, J. Geophys. Res., 119, 2356-2374, doi:10.1002/2013JD021078.
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Modeling Analysis and Prediction Program (MAP)