| Heat and moisture budgets are analyzed in a case (10-11 April 1979) observed in SESAME-79 to diagnose the effects of organized midlatitude convection on its environment. The major findings are: (1) The heating distribution of midlatitude cumulus convection does not have a significant variation on scales greater than 550 km x 550 km and periods longer than 6 h. Despite strong differences in midlatitude and tropical convection, the vertical heating distribution of midlatitude organized convection is similar to that obtained in the tropics for a much longer temporal scale and larger spatial scales. (2) The convective rainfall rate is closely related to vertical moisture advection and total horizontal moisture convergence, suggesting that it is possible to parameterize midlatitude organized convection in large-scale numerical models. (3) When a steady-state cloud model is used to simulate cloud thermodynamic properties with a small cloud radius, both Kuo's and Anthes's schemes simulate a level of maximum heating much lower than is observed. Both schemes are improved when a larger cloud radius is used. Kuo's scheme yields an extremely close reproduction of the observed profile when the moist adiabat is used to represent cloud thermodynamic properties and when cloud-scale eddy sensible heat flux is included. This result indicates that entrainment is not important for this intense convective case and supports the cloud-environment mixing hypothesis. It also shows the inadequacy of a one-dimensional steady-state cloud model in determining the mean cloud condensation rate. Since the cloud model used by Anthes is rather simple, improved results can be expected with an improved cloud model. (4) An error analysis shows a high noise level for budgets using the simulated SESAME data, indicating difficulties in diagnosing weak convective systems with a network similar to SESAME, and suggests the need for improved temporal and spatial resolutions for future field programs. In particular, it is shown that with the same number of stations, a regularly spaced network can significantly reduce the errors introduced by the objective analysis which is necessary for an irregularly spaced network. |
