In numerical simulations of growing congestus clouds, the maximum upward velocities w typically occur in compact toroidal vortices or thermals. These maxima were tracked, and the momentum budget was analyzed within spherical regions centered on them with objectively determined radii approximately enclosing the vortex ring or pair. Such regions are proposed as an advantageous prototype for rising air parcels due to their prolonged identity as evident in laboratory flows. Buoyancy and other forces are generally less than 0.02 m s−2 (0.7 K). In particular, resolved mixing between thermals and their environment fails to produce the drag normally anticipated, often producing even a slight upward force, indicating that parcel models should allow for significantly different dilution rates for momentum than for material properties. A conceptual model is proposed to explain this as a result of the thermals' internal circulation and detrainment characteristics. The implications of momentum dilution for cumulus development are explored using a simple model of a heterogeneous entraining parcel. Without friction, parcels reach the upper troposphere even at a high entrainment rate [~(2 km)−1] if the environment is sufficiently humid, whereas with standard momentum dilution, a much lower entrainment rate is required. Peak condensed water amounts and sensitivities of cloud amount and height to ambient humidity are significantly more realistic in the high-entrainment case. This suggests that revised treatments of friction and momentum could help address the “entrainment paradox” whereby entrainment rates implied by detailed cloud studies are higher than those typically preferred for parcel-based calculations.

Convection is often assumed to be controlled by the simultaneous environmental fields. But to what extent does it also remember its past behavior? This study proposes a new framework in which the memory of previous convective-scale behavior, “microstate memory,” is distinguished from macrostate memory, and conducts numerical experiments to reveal these memory types. A suite of idealized, cloud-resolving radiative–convective equilibrium simulations in a 200-km square domain is performed with the Weather Research and Forecasting (WRF) Model. Three deep convective cases are analyzed: unorganized, organized by low-level wind shear, and self-aggregated. The systematic responses to sudden horizontal homogenization of various fields, in various atmospheric layers, designed to eliminate their specific microstructure, are compared in terms of precipitation change and time of recovery to equilibrium. Results imply a substantial role for microstate memory. Across organization types, microstructure in water vapor and temperature has a larger and longer-lasting effect on convection than in winds or hydrometeors. Microstructure in the subcloud layer or the shallow cloud layer has more impact than in the free troposphere. The recovery time scale dramatically increases from unorganized (2–3 h) to organized cases (24 h or more). Longer-time-scale adjustments also occur and appear to involve both small-scale structures and domain-mean fields. These results indicate that most convective microstate memory is stored in low-level thermodynamic structures, potentially involving cold pools and hot thermals. This memory appears strongly enhanced by convective organization. Implications of these results for parameterizing convection are discussed.