A method that enables a mass-flux cumulus parameterization scheme (CPS) to work seamlessly in various model grids across CPS gray-zone resolutions is proposed. The convective cloud-base mass flux, convective inhibition, and convective detrainment in the simplified Arakawa–Schubert (SAS) scheme are modified to be functions of the convective updraft fraction. The combination of two updraft fractions is used to modulate the cloud-base mass flux; the first one depends on the horizontal grid space and the other is a function of the grid-scale and convective vertical velocity. The convective inhibition and detrainment of hydrometeors are also modified to be a function of the grid-size-dependent convective updraft fraction.A set of sensitivity experiments with the Weather Research and Forecasting (WRF) Model is conducted for a heavy rainfall case over South Korea. The results show that the revised SAS CPS outperforms the original SAS. At 3 and 1 km, the precipitation core over South Korea is well reproduced by the experiments with the revised SAS scheme. On the contrary, the simulated precipitation is widespread in the case of the original SAS experiment and there are multiple spurious cores when the CPS is removed at those resolutions. The modified mass flux at the cloud base is found to play a major role in organizing the grid-scale precipitation at the convective core. A 1-month simulation at 3 km confirms that the revised scheme produces slightly better summer monsoonal precipitation results as compared to the typical model setup without CPS.

In this study, a revised prognostic cloud fraction scheme for atmospheric models is proposed and its performance is evaluated with a diagnostic cloud fraction scheme. A revision is proposed through a direct linkage between hydrometeors in the cumulus parameterization scheme and the amount of predicted cloud fractions. Cloud fractions that are determined via the prognostic cloud fraction scheme appear to be more realistic than those determined via a diagnostic cloud fraction scheme when both are compared with satellite data. In a medium-range forecast test bed, the biases of large-scale features such as temperature, geopotential height, and mean sea level pressure are moderately reduced when the prognostic cloud fraction scheme is used.

Recent satellite observations suggested that medium‐depth heavy rain systems (i.e., warm‐type heavy rainfall) were predominantly found in the Korean peninsula under moist‐adiabatically near neutral conditions in contrast to the traditional view that deep convection induced by convective instability produced heavy rainfall (i.e., cold‐type heavy rainfall). In order to examine whether a numerical model could explain the microphysical evolution of the warm‐type as well as cold‐type heavy rainfall, numerical experiments were implemented with idealized thermodynamic conditions. Under the prescribed humid and weakly unstable conditions, the warm‐type experiments resulted in a lower storm height, earlier onset of precipitation, and heavier precipitation than was found for the cold‐type experiments. The growth of ice particles and their melting process were important for developing cold‐type heavy rainfall. In contrast, the collision and coalescence processes between liquid particles were shown to be the mechanism for increasing the radar reflectivity toward the surface in the storm core region for the warm‐type heavy rainfall.