Heat and moisture budgets associated with a midlatitude convective system (10–11 April 1979) are used to evaluate several versions of Kuo-type cumulus parameterization schemes on a semiprognostic basis. It is shown that the observed rainfall rate is closely related to the large-scale vertical advection of moisture and to a lesser extent to the large-scale moisture convergence. Both the Kuo and the Anthes schemes show considerable skill in reproducing the convective heating profile (Q1) when a moist adiabat is used to represent the cloud thermodynamic properties and the effect of eddy sensible heat flux is estimated by a steady-state cloud model. However, when a model cloud with a small radius is used to estimate the cloud's thermodynamic properties, both the Kuo and Authes schemes predict convective heating profiles with considerably lower levels of maximum heating than observed. This indicates that entrainment is not very important for the deep convection present in this case. Anthes' scheme is revised to utilize the condensation profile and eddy moisture flux estimated by a steady-state cloud model. The revised scheme shows moderate skill in reproducing the convective drying profile (Q2). The discrepancies between the observed and simulated profiles suggest that shallow convection and turbulent eddies transport substantial amounts of moisture from the subcloud layer to the cloud layer. We find that the convective moistening profile (∂q/∂t) during the developing stage can be very well-simulated by a function of saturation mixing ratio as proposed by Anthes and others. The moistening profile cannot be reproduced by the cloud-environment moisture differences as proposed by Kuo. These results suggest that it is possible to parameterize midlatitude organized convection in a large-scale numerical model because of the strong relationship between the convective rainfall rate, the convective heating profile, the convective moistening profile, and the large-scale variables.