This study describes a revised approach for the subgrid-scale convective properties of a moist convection scheme in a global model and evaluates its effects on a simulated model climate. The subgrid-scale convective processes tested in this study comprise three components: 1) the random selection of cloud top, 2) the inclusion of convective momentum transport, and 3) a revised large-scale destabilization effect considering synoptic-scale forcing in the cumulus convection scheme of the National Centers for Environmental Prediction medium-range forecast model. Each component in the scheme has been evaluated within a single-column model (SCM) framework forced by the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment data. The impact of the changes in the scheme on seasonal predictions has been examined for the boreal summers of 1996, 1997, and 1999. In the SCM simulations, an experiment that includes all the modifications reproduces the typical convective heating and drying feature. The simulated surface rainfall is in good agreement with the observed precipitation. Random selection of the cloud top effectively moistens and cools the upper troposphere, and it induces drying and warming below the cloud-top level due to the cloud–radiation feedback. However, the two other components in the revised scheme do not play a significant role in the SCM simulations. On the other hand, the role of each modification component in the scheme is significant in the ensemble seasonal simulations. The random selection process of the cloud top preferentially plays an important role in the adjustment of the thermodynamic profile in a manner similar to that in the SCM framework. The inclusion of convective momentum transport in the scheme weakens the meridional circulation. The revised large-scale destabilization process plays an important role in the modulation of the meridional circulation when this process is combined with other processes; on the other hand, this process does not induce significant changes in large-scale fields by itself. Consequently, the experiment that involves all the modifications shows a significant improvement in the seasonal precipitation, thereby highlighting the importance of nonlinear interaction between the physical processes in the model and the simulated climate.