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Seeking a family of models filling the hierarchy between steady plumes and cloud-resolving simulations, Part I of this study presented a formulation termed anelastic convective entities (ACEs). The solution includes pressure-mediated nonlocal effects in both vertical and horizontal and thus yields time-dependent simulations of convective updrafts, downdrafts, and other aspects of convection even for a single column interacting with a fixed environment through dynamically determined inflow and outflow. Here, we show how a straightforward iteration of that formulation can capture interactions among entities in a variety of choices for the geometry of the interactions. Using an oceanic sounding to contrast with land cases in Part I, we first illustrate that a single ACE can exhibit ongoing time-dependent evolution depending, e.g., on choices in the parameterized turbulence. For a case in which a single ACE with a fixed environment would yield a near-steady deep-convective state, we examine the adjustment process in a multi-ACE prototype for adjustment within a climate model grid cell. This embedded ACE configuration exhibits time-dependent stratiform cloud expansion through convective outflow modified by dynamic feedbacks. The gridscale adjustment process not only includes traditional warming by large-scale descent but also captures the spread of the convective cold top. The formulation also illustrates the possibility of multihour time lag before the transition to deep convection and remote initiation by small vertical velocities in the gridcell environment. Comparing 1-, 2-, 4-, and 8-ACE instances suggests promise as a potential convective-parameterization class between traditional and superparameterization, while providing a sandbox to aid understanding of convective and adjustment processes. 

A formulation based on the anelastic approximation yields time-dependent simulations of convective updrafts, downdrafts, and other aspects of convection, such as stratiform layers, under reasonably flexible geometry assumptions. Termed anelastic convective entities (ACEs), such realizations can aid understanding of convective processes and potentially provide time-dependent building blocks for parameterization at a complexity between steady-plume models and cloud-resolving simulations. Formulation and behavior of single-ACE cases are addressed here, with multi-ACE cases in Part II. Even for cases deliberately formulated to provide a comparison to a traditional convective plume, ACE behavior differs substantially because dynamic entrainment, detrainment, and nonhydrostatic perturbation pressure are consistently included. Entrainment varies with the evolution of the entity, but behavior akin to deep-inflow effects noted in observations emerges naturally. The magnitude of the mass flux with nonlocal pressure effects consistently included is smaller than for a corresponding traditional steady-plume model. ACE solutions do not necessarily approach a steady state even with a fixed environment but can exhibit chains of rising thermals and even episodic deep convection. The inclusion of nonlocal dynamics allows a developing updraft to tunnel through layers with substantial convective inhibition (CIN). For cases of nighttime continental convection using GoAmazon soundings, this is found to greatly reduce the effect of surface-inversion CIN. The observed convective cold top is seen as an inherent property of the solution, both in a transient, rising phase and as a persistent feature in mature deep convection. 

Abstract Recent research suggests atmospheric cloud radiative effect (ACRE) acts as an important feedback mechanism for enhancing the development of convective self‐aggregation in idealized numerical simulations. Here, we seek observational relationships between longwave (LW) ACRE and the spatial organization of mesoscale convective systems (MCSs) in the tropics. Three convective organization metrics that are positively correlated with the area of MCS, that is, convective organization potential, the area fraction of precipitating MCS, and the precipitation fraction of MCS, are used to indicate the degree of convective organization. Our results show that the contrast in the LW ACRE inside and outside an MCS is consistent across different MCS precipitation intensities throughout the life cycle of an MCS, typically 90–100 W/m², and provides important positive feedback to the circulation of the given MCS. However, the LW ACRE inside and outside an MCS as well as their difference are not strongly related to the degree of organization, suggesting that the LW cloud radiative feedback may be supportive of MCS formation and maintenance without necessarily being a dominant factor for spatial organization of MCSs. The domain average vertical velocity does tend to be related to the measures of convective organization, suggesting that factors that favor large‐scale low‐level convergence may exert a leading effect in creating an environment favorable for mesoscale organization of deep convection. 

Abstract A set of diagnostics based on simple, statistical relationships between precipitation and the thermodynamic environment in observations is implemented to assess phase 6 of the Coupled Model Intercomparison Project (CMIP6) model behavior with respect to precipitation. Observational data from the Atmospheric Radiation Measurement (ARM) permanent field observational sites are augmented with satellite observations of precipitation and temperature as an observational baseline. A robust relationship across observational datasets between column water vapor (CWV) and precipitation, in which conditionally averaged precipitation exhibits a sharp pickup at some critical CWV value, provides a useful convective onset diagnostic for climate model comparison. While a few models reproduce an appropriate precipitation pickup, most models begin their pickup at too low CWV and the increase in precipitation with increasing CWV is too weak. Convective transition statistics compiled in column relative humidity (CRH) partially compensate for model temperature biases—although imperfectly since the temperature dependence is more complex than that of column saturation. Significant errors remain in individual models and weak pickups are generally not improved. The conditional-average precipitation as a function of CRH can be decomposed into the product of the probability of raining and mean precipitation during raining times (conditional intensity). The pickup behavior is primarily dependent on the probability of raining near the transition and on the conditional intensity at higher CRH. Most models roughly capture the CRH dependence of these two factors. However, compensating biases often occur: model conditional intensity that is too low at a given CRH is compensated in part by excessive probability of precipitation. 

Abstract In convective quasi-equilibrium theory, tropical tropospheric temperature perturbations are expected to follow vertical profiles constrained by convection, referred to as A-profiles here, often approximated by perturbations of moist adiabats. Differences between an idealized A-profile based on moist-static energy conservation and temperature perturbations derived from entraining and nonentraining parcel computations are modest under convective conditions—deep convection mostly occurs when the lower troposphere is close to saturation, thus minimizing the impact of entrainment on tropospheric temperature. Simple calculations with pseudoadiabatic perturbations about the observed profile thus provide useful baseline A-profiles. The first EOF mode of tropospheric temperature (TEOF1) from the ERA-Interim and AIRS retrievals below the level of neutral buoyancy (LNB) is compared with these A-profiles. The TEOF1 profiles with high LNB, typically above 400 hPa, yield high vertical spatial correlation (∼0.9) with A-profiles, indicating that tropospheric temperature perturbations tend to be consistent with the quasi-equilibrium assumption where the environment is favorable to deep convection. Lower correlation tends to occur in regions with low climatological LNB, less favorable to deep convection. Excluding temperature profiles with low LNB significantly increases the tropical mean vertical spatial correlation. The temperature perturbations near LNB exhibit negative deviations from the A-profiles—the convective cold-top phenomenon—with greater deviation for higher LNB. In regions with lower correlation, the deviation from A-profile shows an S-like shape beneath 600 hPa, usually accompanied by a drier lower troposphere. These findings are robust across a wide range of time scales from daily to monthly, although the vertical spatial correlation and TEOF1 explained variance tend to decrease on short time scales. 

Abstract The vertical structure of ocean eddies is generally surface-intensified, commonly attributed to the dominant baroclinic modes arising from the boundary conditions (BCs). Conventional BC considerations mostly focus on either flat- or rough-bottom conditions. The impact of surface buoyancy anomalies—often represented by surface potential vorticity (PV) anomalies—has not been fully explored. Here, we study the role of the surface PV in setting the vertical distribution of eddy kinetic energy (EKE) in an idealized adiabatic ocean model driven by wind stress. The simulated EKE profile in the extratropical ocean tends to peak at the surface and have ane-folding depth typically smaller than half of the ocean depth. This vertical structure can be reasonably represented by a single surface quasigeostrophic (SQG) mode at the energy-containing scale resulting from the large-scale PV structure. Due to isopycnal outcropping and interior PV homogenization, the surface meridional PV gradient is substantially stronger than the interior PV gradient, yielding surface-trapped baroclinically unstable modes with horizontal scales comparable to or smaller than the deformation radius. These surface-trapped eddies then grow in size both horizontally and vertically through an inverse energy cascade up to the energy-containing scale, which dominates the vertical distribution of EKE. As for smaller horizontal scales, the EKE distribution decays faster with depth. Guided by this interpretation, an SQG-based scale-aware parameterization of the EKE profile is proposed. Preliminary offline diagnosis of a high-resolution simulation shows the proposed scheme successfully reproducing the dependence of the vertical structure of EKE on the horizontal grid resolution. 

Abstract The transition to deep convection and associated precipitation is often studied in relationship to the associated column water vapor owing to the wide availability of these data from various ground or satellite-based products. Based on radiosonde and ground-based Global Navigation Satellite System (GNSS) data examined at limited locations and model comparison studies, water vapor at different vertical levels is conjectured to have different relationships to convective intensity. Here, the relationship between precipitation and water vapor in different free tropospheric layers is investigated using globally distributed GNSS radio occultation (RO) temperature and moisture profiles collocated with GPM IMERG precipitation across the tropical latitudes. A key feature of the RO measurement is its ability to directly sense in and near regions of heavy precipitation and clouds. Sharp pickups (i.e. sudden increases) of conditionally averaged precipitation as a function of water vapor in different tropospheric layers are noted for a variety of tropical ocean and land regions. The layer-integrated water vapor value at which this pickup occurs has a dependence on temperature that is more complex than constant RH, with larger subsaturation at warmer temperatures. These relationships of precipitation to its thermodynamic environment for different layers can provide a baseline for comparison with climate model simulations of the convective onset. Furthermore, vertical profiles before, during, and after convection are consistent with the hypothesis that the lower troposphere plays a causal role in the onset of convection, while the upper troposphere is moistened by de-trainment from convection. 

Abstract Purpose of Review: Review our current understanding of how precipitation is related to its thermodynamic environment, i.e., the water vapor and temperature in the surroundings, and implications for changes in extremes in a warmer climate. Recent Findings: Multiple research threads have i) sought empirical relationships that govern onset of strong convective precipitation, or that might identify how precipitation extremes scale with changes in temperature; ii) examined how such extremes change with water vapor in global and regional climate models under warming scenarios; iii) identified fundamental processes that set the characteristic shapes of precipitation distributions. Summary: While water vapor increases tend to be governed by the Clausius-Clapeyron relationship to temperature, precipitation extreme changes are more complex and can increase more rapidly, particularly in the tropics. Progress may be aided by bringing separate research threads together and by casting theory in terms of a full explanation of the precipitation probability distribution. 

Abstract Conditional instability and the buoyancy of plumes drive moist convection but have a variety of representations in model convective schemes. Vertical thermodynamic structure information from Atmospheric Radiation Measurement (ARM) sites and reanalysis (ERA5), satellite-derived precipitation (TRMM3b42), and diagnostics relevant for plume buoyancy are used to assess climate models. Previous work has shown that CMIP6 models represent moist convective processes more accurately than their CMIP5 counterparts. However, certain biases in convective onset remain pervasive among generations of CMIP modeling efforts. We diagnose these biases in a cohort of nine CMIP6 models with subdaily output, assessing conditional instability in profiles of equivalent potential temperature,θ_e, and saturation equivalent potential temperature,θ_es, in comparison to a plume model with different mixing assumptions. Most models capture qualitative aspects of theθ_esvertical structure, including a substantial decrease with height in the lower free troposphere associated with the entrainment of subsaturated air. We define a “pseudo-entrainment” diagnostic that combines subsaturation and aθ_esmeasure of conditional instability similar to what entrainment would produce under the small-buoyancy approximation. This captures the trade-off between largerθ_eslapse rates (entrainment of dry air) and small subsaturation (permits positive buoyancy despite high entrainment). This pseudo-entrainment diagnostic is also a reasonable indicator of the critical value of integrated buoyancy for precipitation onset. Models with poorθ_e/θ_esstructure (those using variants of the Tiedtke scheme) or low entrainment runs of CAM5, and models with low subsaturation, such as NASA-GISS, lie outside the observational range in this diagnostic. 

Abstract Observations and cloud‐resolving simulations suggest that a convective updraft structure drawing mass from a deep lower‐tropospheric layer occurs over a wide range of conditions. This occurs for both mesoscale convective systems (MCSs) and less‐organized convection, raising the question: is there a simple, universal characteristic governing the deep inflow? Here, we argue that nonlocal dynamics of the response to buoyancy are key. For precipitating deep‐convective features including horizontal scales comparable to a substantial fraction of the troposphere depth, the response to buoyancy tends to yield deep inflow into the updraft mass flux. Precipitation features in this range of scales are found to dominate contributions to observed convective precipitation for both MCS and less‐organized convection. The importance of such nonlocal dynamics implies thinking beyond parcel models with small‐scale turbulence for representation of convection in climate models. Solutions here lend support to investment in parameterizations at a complexity between conventional and superparameterization.