Implicit Versus Explicit Convective Heating in Numerical Weather Prediction Models

Abstract

The ability of several explicit formulations of convective heating to predict the precipitation associated with a mesoscale convective complex was compared to that of a cumulus parameterization on a ½ deg latitude-longitude mesh. In the explicit approaches, prediction equations were present for both water vapor and cloud water, or vapor alone. The simplest explicit approach, for which any condensed water was assumed to fall immediately as rain, produced localized excessive rainfall. This explicit heating instability arose as a result of the requirements of saturation prior to rainfall, which delayed condensation and allowed excessive convective instability to build, and neglect of fluxes, which prevented the instability from being released in a realistic manner. These results, combined with those of previous investigators, indicate that the simplest form of explicit heating is prone to instability and unsuitable for mesoscale models. Instability problems were significantly reduced by the inclusion of the inhibiting effects of rainwater evaporation and a cloud phase with hydrostatic water loading, Nevertheless, bemuse significant nor occurred in nature in the absence of area-averaged saturation, rainfall was unrealistically delayed when a 100 percent saturation criterion was used. Reducing the saturation criterion improved the phase error of the rainfall prediction, but sometimes reintroduced local instability. Although only simple explicit formulations were used, inclusion of more sophisticated microphysical parameterizations from cloud models may be unrepresentative of processes in nature for meso-α scale models, for which the grid spacing exceeds 50 km. It is proposed for such models that implicit approaches offer the greatest potential for improvement. For meso-? scale models the optimum choice remains uncertain.