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A formal framework is established for the way in which cloud-resolving numerical models are used to investigate the role of precipitating cloud systems in climate and weather forecasting models. Emphasis is on models with periodic lateral boundary conditions that eliminate unrealistic numerically generated circulations caused by open boundary conditions in long-term simulations. Defined in this formalism is the concept of large-scale forcing and the cloud-environment interactions that are consistent with the periodic boundary conditions. Two-dimensional numerical simulations of the evolution of cloud systems during 1–7 September 1974 in Phase III of the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE) are conducted. Based on the above formalism, a simple technique is used to force an anelastic cloud-resolving model with evolving large-scale horizontal wind field and large-scale forcing for the temperature and moisture obtained from the GATE data. The 7-day period selected is characterized by transitions of the cloud systems through several regimes, in response to evolving large-scale forcing and vertical wind shear as an easterly wave passes over the region. The observed nonsquall cloud clusters, squall lines (squall clusters), and scattered convection are all simulated. Model-produced budgets of heat and moisture compare well with GATE observations. It is argued that differences between simulations and observations (most apparent in the relative humidity) result from the treatment of condensed water. In particular, the lack of observed fields to prescribe forcing for the upper-tropospheric ice, together with the periodic lateral boundary conditions, results in a middle and upper troposphere that is too moist by 10%–20%. A key conclusion is that tropical convection, forced in a simple way by large-scale analysis, is sorted into specific regimes as a result of dynamic control by the wind shear. The quantification of this large-scale control is fundamental to the concept of convective parameterization. Furthermore, the cloud-resolving model results by design satisfy the large-scale budgets and, therefore, can be applied directly to the strategic problem of convective parameterization in weather forecasting and climate models.
Grabowski et al. (Sun,) studied this question.