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Spatial aggregation of deep convection and its possible role in larger-scale atmospheric behavior have received growing attention. Here we seek aggregation-correlated statistical properties of convective events in 5° × 5° boxes over the tropical Indian Ocean. Events are identified by box-averaged rainfall exceeding 5 mm day⁻¹at the center of a 4-day time window, and aggregation is estimated by an index [simple convective aggregation index (SCAI)] based on contiguous cold cloud areas and their geometrical distances in infrared imagery. A physical framework using gross moist stability (GMS) helps to interpret relationships between aggregation, box-scale ascent profiles, moist static energy budgets, and time evolution both within composite events and on longer time scales. For a given precipitation rate, more-aggregated events (with fewer and larger cloud objects on average) exhibit a drier area mean, greater horizontal gradient of moisture, more bottom-heavy ascent profile, and a greater prevalence of low-altitude cloud tops, especially for lower rain rates. In the GMS budget, this bottom-heavy ascent implies net energy import into the atmospheric column during the 4-day event composite. Consistently, net energy variations filtered to reveal longer time scales do indeed exhibit more-aggregated rain events in their growth phase than in their flat and decaying phases. More-aggregated scenes also have more drying by analysis than less-aggregated scenes in MERRA-2’s assimilation budgets. This suggests that parameterized convection (lacking any organization effect) is raining out less water than nature’s real, aggregated convection in such scenes.

To explore the interactions among column processes in the Community Atmosphere Model (CAM), the single‐column version of CAM (SCAM) is integrated for 1000 days in radiative‐convective equilibrium (RCE) with tropical values of boundary conditions, spanning a parameter or configuration space of model physics versions (v5 vs. v6), vertical resolution (standard and 60 levels), sea surface temperature (SST), and some interpretation‐driven experiments. The simulated time‐mean climate is reasonable, near observations and RCE of a cyclic cloud‐resolving model. Updraft detrainment in the deep convection scheme produces distinctive grid‐scale structures in humidity and cloud, which also interact with radiative transfer processes. These grid artifacts average out in multi‐column RCE results reported elsewhere, illustrating the nuts‐and‐bolts interpretability that SCAM adds to the hierarchy of model configurations. Multi‐day oscillations of precipitation arise from descent of warm convection‐capping layers starting near the tropopause, eventually reset by a burst of convective deepening. Experiments reveal how these oscillations depend critically on an internal parameter that controls the number of neutral buoyancy levels allowed for determining cloud top and computing dilute convective available potential energy in the deep convection scheme, and merely modified a little by disabling cloud‐base radiation (heating of cloud base). This strong dependence of transient behavior in 1D on this parameter will be tested in the second part of this work, in which SCAM is coupled to a parameterized dynamics of two‐dimensional, linearized gravity wave, and in the 3D simulations in future study.

A wide range of the observed variability in the ITCZ is frequently explained in terms of equatorially trapped modes arising from Matsuno’s linear shallow-water model. Here, a series of zonally constant, meridionally symmetric aquachannel WRF simulations are used to study the propagation of tropical cloud clusters (CCs; patches of deep cloudiness and precipitation) in association with eastward-moving super cloud clusters (SCCs), also called convectively coupled Kelvin waves (CCKWs). Two independent but complementary methods are used: the first, from a local approach, involves a CC-tracking algorithm, while the second uses Lagrangian trajectories in a nonlocal framework. We show that the large-scale flow in low to midlevels advects the CCs either eastward or westward depending on model climatology, proximity to the CCKW axis, and latitude. Moreover, for most analyzed cases, sequences of CCs oscillate, describing qualitatively sinusoidal-like paths in longitude–time space, although with sharp transitions from westward to eastward motion due to westerly wind burst activity associated with the CCKWs. We also find that the discrete precipitation elements (CCs) are embedded in continuous tracks of positive moisture anomalies, which are parallel to the Lagrangian trajectories themselves. A conceptual model of the nonlinear SCC–CC interaction is presented.