2002 Annual

Wednesday, 16 January 2002: 4:45 PM
Evaluation of the Entraining-Detraining Plume Model applied to the cumulus parameterization of the large-scale model
Jung-Hee Ryu, Penn State University, State College, PA; and J. B. Ahn and J. H. Oh
In this study, the reconfiguration of the entraining-detraining plume model for application in large-scale cumulus parameterization is attempted. This procedure extends the entraining-plume model employed in the modified Arakawa-Schubert scheme while considering the detrainment at many levels of the cloud on the basis of the concept of the buoyancy-sorting mechanism of Raymond and Blyth.

According to the buoyancy-sorting mechanism, the detrainment results from the neutral buoyancy of the mixture, which is produced through mixing of the cloud air with the ambient air. Thus, it has been thought that more entrainments tend to produce more neutral buoyant mixtures. This is because the entrainment of environment air, which is drier than the cloud air usually, causes reducing or losing their buoyancy. Thus, we may simply assume that the rate of detrainment to be proportional to that of the entrainment. In this study, the arbitrary constant ratio between entrainment and detrainment is determined through a series of sensitivity tests rather than on the physical basis. The properties of the cloud air detrained into environment are specified from both bulk averaged properties of the updraft cloud air rising from the below and the entrained ambient air.

For the validation of the results based on the parameterization, both the single-column model and three-dimensional large-scale model are used. For the simulation of the single-column model, the Southern Great Plains data of the Atmospheric Radiation Measurement project and the Global Atmospheric Research Programs Atlantic Tropical Experiment Phase III data are used.

When the observed radiative heating is replaced the radiative heating calculated by the model, the simulated precipitation pattern is significantly improved in the simulations with both the ARM data and the GATE data. This illustrates that the entraining-detraining plume model may reasonably simulate the convective activity, if the reasonable radiative feedback is given. That is because the precipitation rate is largely affected by the deep convections.

In addition, it has also improved the GCM simulation. This improvement includes the decrease of the warming tendency in the upper-troposphere of the middle latitudes of the Northern Hemisphere.

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