Entraining Plume Model Research Articles

Giant Planet Lightning in Nonideal Gases

Lightning has been directly observed or inferred on all giant planets, generally accepted to be occurring in their water clouds. However, much as Earth has both cloud–cloud and cloud–ground lightning, this does not mean all flashes occur in a narrow altitude range: on Jupiter, the Galileo spacecraft detected lightning flashes apparently below the cloud base, explicable as lightning due to precipitation, and the Juno SRU detected small flashes far above it, at pressures of only 1–2 bars. We use a computationally light 1D entraining plume model, incorporating particle growth and noninductive charging, which predicts this wide range of Jovian lightning provides freezing point depressions caused by ammonia, and modify it to use a van der Waals equation of state instead of an ideal gas, as well as integrating the evaporation of rain; this allows modeling of planets colder than Jupiter, where clouds and lightning occur at greater pressures. For Saturn, the uppermost lightning is predicted at 3–4 bars; unlike on Jupiter, ammonia is not required to match the Cassini observations. For Uranus and Neptune, depending on their convective structures, very high rates of lightning are possible in the deep water clouds; while deeper than on Jupiter or Saturn, lightning is predicted likely to peak above the water cloud base, at pressures around 100 bars. Voyager 2's radio observations of Uranian and Neptunian sferics may thus be either due to attenuation of deep water lightning of this type, or due to lightning in the shallow ammonia clouds; future observations are required to resolve this dichotomy.

Factors Governing Cloud Growth and Entrainment Rates in Shallow Cumulus and Cumulus Congestus During GoAmazon2014/5

AbstractShallow cumulus and cumulus congestus clouds play an important role in the large‐scale tropical circulation by mixing heat and moisture vertically and preconditioning the environment for deeper convection. Different representations of these shallow clouds account for much of the spread in General Circulation Model (GCMs) climate sensitivity, potentially because of how entrainment is represented in GCM parameterizations. This study uses observations from the Department of Energy's Atmospheric Radiation Measurement (ARM) mobile facility deployed at Manacapuru, Brazil, during the Green Ocean Amazon (GoAmazon2014/5) Campaign. Environmental thermodynamic profiles and observations of cloud top height (CTH) are used to constrain an entraining plume model to estimate bulk entrainment rates (ERs). Estimates of CTH are obtained from a combination of vertically pointing W‐band ARM cloud radar and 1,290 MHz Radar Wind Profiler observations. A combination of radiosonde, microwave radiometer profiler, and microwave radiometer observations provides new best estimates of the environmental thermodynamic state. We quantify uncertainty in ERs considering uncertainties in estimated CTH, environmental thermodynamic properties, and assumed initial parcel characteristics. We find ERs ranging from 0.16 to 2.8 km−1 with an average of 0.58 ± 0.10 km−1 over a selected population of 469 shallow cumulus and cumulus congestus clouds. Using the retrieved estimates of ER, we evaluate several entrainment closures that are currently used in atmospheric models or have been proposed based on theory or large eddy simulation. Entrainment rates in cumulus clouds are weakly correlated with low‐level buoyancy, cloud depth, and cloud size.

Convective Dynamics and the Response of Precipitation Extremes to Warming in Radiative–Convective Equilibrium

AbstractTropical precipitation extremes are expected to strengthen with warming, but quantitative estimates remain uncertain because of a poor understanding of changes in convective dynamics. This uncertainty is addressed here by analyzing idealized convection-permitting simulations of radiative–convective equilibrium in long-channel geometry. Across a wide range of climates, the thermodynamic contribution to changes in instantaneous precipitation extremes follows near-surface moisture, and the dynamic contribution is positive and small but is sensitive to domain size. The shapes of mass flux profiles associated with precipitation extremes are determined by conditional sampling that favors strong vertical motion at levels where the vertical saturation specific humidity gradient is large, and mass flux profiles collapse to a common shape across climates when plotted in a moisture-based vertical coordinate. The collapse, robust to changes in microphysics and turbulence schemes, implies a thermodynamic contribution that scales with near-surface moisture despite substantial convergence aloft and allows the dynamic contribution to be defined by the pressure velocity at a single level. Linking the simplified dynamic mode to vertical velocities from entraining plume models reveals that the small dynamic mode in channel simulations (2% K−1) is caused by opposing height dependences of vertical velocity and density, together with the buffering influence of cloud-base buoyancies that vary little with surface temperature. These results reinforce an emerging picture of the response of extreme tropical precipitation rates to warming: a thermodynamic mode of about 7% K−1 dominates, with a minor contribution from changes in dynamics.

On the role of aerosols, humidity, and vertical wind shear in the transition of shallow-to-deep convection at the Green Ocean Amazon 2014/5 site

Abstract. The preconditioning of the atmosphere for a shallow-to-deep convective transition during the dry-to-wet season transition period (August–November) is investigated using Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) GoAmazon2014/5 campaign data from March 2014 to November 2015 in Manacapuru, Brazil. In comparison to conditions observed prior to shallow convection, anomalously high humidity in the free troposphere and boundary layer is observed prior to a shallow-to-deep convection transition. An entraining plume model, which captures this leading dependence on lower tropospheric moisture, is employed to study indirect thermodynamic effects associated with vertical wind shear (VWS) and cloud condensation nuclei (CCN) concentration on preconvective conditions. The shallow-to-deep convective transition primarily depends on humidity, especially that from the free troposphere, which tends to increase plume buoyancy. Conditions preceding deep convection are associated with high relative humidity, and low-to-moderate CCN concentration (less than the 67th percentile, 1274 cm−3). VWS, however, shows little relation to moisture and plume buoyancy. Buoyancy estimates suggest that the latent heat release due to freezing is important to deep convective growth under all conditions analyzed, consistent with potential pathways for aerosol effects, even in the presence of a strong entrainment. Shallow-only convective growth, however, shows an association with a strong (weak) low (deep) level VWS and with higher CCN concentration.

GoAmazon2014/5 campaign points to deep-inflow approach to deep convection across scales

A substantial fraction of precipitation is associated with mesoscale convective systems (MCSs), which are currently poorly represented in climate models. Convective parameterizations are highly sensitive to the assumptions of an entraining plume model, in which high equivalent potential temperature air from the boundary layer is modified via turbulent entrainment. Here we show, using multiinstrument evidence from the Green Ocean Amazon field campaign (2014-2015; GoAmazon2014/5), that an empirically constrained weighting for inflow of environmental air based on radar wind profiler estimates of vertical velocity and mass flux yields a strong relationship between resulting buoyancy measures and precipitation statistics. This deep-inflow weighting has no free parameter for entrainment in the conventional sense, but to a leading approximation is simply a statement of the geometry of the inflow. The structure further suggests the weighting could consistently apply even for coherent inflow structures noted in field campaign studies for MCSs over tropical oceans. For radar precipitation retrievals averaged over climate model grid scales at the GoAmazon2014/5 site, the use of deep-inflow mixing yields a sharp increase in the probability and magnitude of precipitation with increasing buoyancy. Furthermore, this applies for both mesoscale and smaller-scale convection. Results from reanalysis and satellite data show that this holds more generally: Deep-inflow mixing yields a strong precipitation-buoyancy relation across the tropics. Deep-inflow mixing may thus circumvent inadequacies of current parameterizations while helping to bridge the gap toward representing mesoscale convection in climate models.

Insights into convective momentum transport and its parametrization from idealized simulations of organized convection

Deep convection is a multiscale process that influences the budgets of heat, moisture and momentum significantly. In global climate models, the thermodynamic effects of convection are normally treated by parametrization schemes, with a separate formulation for convective momentum transport (CMT). The schemes for current thermodynamic and momentum parametrizations are based on upright entraining plume models that do not account for vertically tilted mesoscale circulations, which characterize organized convection in sheared environments. The associated countergradient vertical transport of horizontal momentum fundamentally affects dynamical interactions between the convection and the mean flow. This study examines the CMT properties of simulated idealized mesoscale convective systems, including their sensitivity to horizontal resolution, domain size and lateral boundary conditions. It is found that, even for large domains, the horizontal gradient terms are important, especially the mesoscale pressure gradients, which are neglected in CMT parametrizations. A nonlinear analytic model provides a dynamical foundation for the effects of convective organization, including the role of the horizontal pressure gradient. It is found that a small computational domain affects the convective organization adversely by generating artificially large compensating subsidence and an unrealistic evolution of CMT. Finally, analyses of the cross‐updraught/downdraught pressure gradients expose significant uncertainties in their representation in contemporary CMT parametrization schemes.

An Analytic Description of the Structure and Evolution of Growing Deep Cumulus Updrafts

Abstract New theoretical analytic expressions are derived for the evolution of a passive scalar, buoyancy, and vertical velocity in growing, entraining moist deep convective updrafts. These expressions are a function of updraft radius, height, convective available potential energy (CAPE), and environmental relative humidity RH. They are quantitatively consistent with idealized three-dimensional moist updraft simulations with varying updraft sizes and in environments with differing RH. In particular, the analytic expressions capture the rapid decrease of buoyancy with height due to entrainment for narrow updrafts in a dry environment despite large CAPE. In contrast to the standard entraining-plume model, the theoretical expressions also describe the effects of engulfment of environmental air between the level of free convection (LFC) and height of maximum buoyancy (HMB) required by mass continuity to balance upward acceleration of updraft air (i.e., dynamic entrainment). This organized inflow sharpens horizontal gradients, thereby enhancing smaller-scale lateral turbulent mixing below the HMB. For narrow updrafts in a dry environment, this enhanced mixing leads to a negatively buoyant region between the LFC and HMB, effectively cutting off the region of positive buoyancy at the HMB from below so that the updraft structure resembles a rising thermal rather than a plume. Thus, it is proposed that a transition from plume-like to thermal-like structure is driven by dynamic entrainment and depends on updraft width (relative to height) and environmental RH. These results help to bridge the entraining-plume and rising-thermal conceptual models of moist convection.

Dynamic subgrid heterogeneity of convective cloud in a global model: description and evaluation of the Convective Cloud Field Model (CCFM) in ECHAM6–HAM2

Abstract. The Convective Cloud Field Model (CCFM) attempts to address some of the shortcomings of both the commonly used bulk mass-flux parameterisations and those using a prescribed spectrum of clouds. By considering the cloud spectrum as a competitive system in which cloud types interact through their environment in competition for convective available potential energy (CAPE), the spectrum is able to respond dynamically to changes in the environment. An explicit Lagrangian entraining plume model for each cloud type allows for the representation of convective-cloud microphysics, paving the way for the study of aerosol–convection interactions at the global scale where their impact remains highly uncertain. In this paper, we introduce a new treatment of convective triggering, extending the entraining plume model below cloud base to explicitly represent the unsaturated thermals which initiate convection. This allows for a realistic vertical velocity to develop at cloud base, so that the cloud microphysics can begin with physically based activation of cloud condensation nuclei (CCN). We evaluate this new version of CCFM in the context of the global model ECHAM6–HAM, comparing its performance to the standard Tiedtke–Nordeng parameterisation used in that model. We find that the spatio-temporal distribution of precipitation is improved, both against a climatology from the Global Precipitation Climatology Project (GPCP) and also against diurnal cycles from the Tropical Rainfall Measurement Mission (TRMM) with a reduced tendency for precipitation to peak too early in the afternoon. Cloud cover is quite sensitive to the vertical level from which the dry convection is initiated, but when this is chosen appropriately the cloud cover compares well with that from Tiedtke–Nordeng. CCFM can thus perform as well as, or better than, the standard scheme while providing additional capabilities to represent convective-cloud microphysics and dynamic cloud morphology at the global scale.

Slow Preconditioning for the Abrupt Convective Jump over the Northwest Pacific during Summer

Abstract The rapid intensification of convective activity in mid-July over the northwest Pacific marks the final stage of the Asian summer monsoon, accompanied by major shifts in regional rainfall and circulation patterns. An entraining plume model is used to investigate the physical processes underlying the abrupt convective jump. Despite little change in sea surface temperature (SST), gradual lower-troposphere mixing leads to a threshold transition in the model as follows. Before mid-July, although SST is already high (29°C), the convective plume is inhibited by the capping inversion above the trade cumulus boundary layer. As the lower troposphere is gradually mixed, the boundary layer top rises with reduced atmospheric stability and increased humidity in the lower troposphere. These factors weaken the inhibition effect of the inversion on the entraining plume. As soon as the plume is able to overcome the inversion barrier, it can rise all the way to the upper troposphere. This marks an abrupt threshold transition to a deep convection regime with heavy rainfall. The convective available potential energy (CAPE) of the entraining plume is found to be a better indicator of the rainfall intensity compared to the conventional undiluted CAPE. The latter fails to capture the onset by neglecting interactions between convective clouds and the environment. Current general circulation models (GCMs) fail to capture the abrupt convective jump and instead simulate a rather smooth seasonal evolution of rainfall. Compared to observations, GCMs simulate a higher trade cumulus top with excessive mixing in the lower troposphere. Convection is no longer inhibited by the inversion barrier, and rainfall simply follows the smooth variation of SST.

Processes Controlling Precipitation in Shallow, Orographic, Trade Wind Convection

Abstract A sharp reduction in precipitation was observed on the island of Dominica in the Caribbean during a 2011 field campaign when the trade winds weakened and convection transitioned from mechanically to thermally driven. The authors propose four hypotheses for this reduction, which relate to (i) the triggering mechanism, (ii) dry-air entrainment, (iii) giant sea-salt aerosol, and (iv) small-island-derived aerosol. The plausibility of the first three hypotheses is the focus of this study. Aircraft observations show the dynamics of the orographic cumulus clouds at flight level are surprisingly similar, irrespective of how they are triggered. However, the orographic cumulus clouds are consistently shallower when the trade winds are weak, which the authors attribute to a drier and shallower cloud layer compared to days with stronger trade winds. The strong negative influence of dry-air entrainment in a drier environment on cumulus depth and liquid water content is qualitatively demonstrated using an entraining plume model and the WRF Model. Although the models appear more sensitive than observations to entrainment and cloud size, the sensitivity tests have some resemblance to observations. The authors also find evidence of sea-salt aerosol entering the base of marine cumulus on strong wind days using an aircraft-mounted lidar and other instruments. Although each hypothesis is plausible, the complex interplay of these processes makes determining the controlling mechanisms difficult. Ultimately, the authors’ analysis rejects the hypothesis (i) triggering, while supporting (ii) entrainment and (iii) sea-salt aerosol.

Understanding Convective Extreme Precipitation Scaling Using Observations and an Entraining Plume Model

Abstract Previously observed twice-Clausius–Clapeyron (2CC) scaling for extreme precipitation at hourly time scales has led to discussions about its origin. The robustness of this scaling is assessed by analyzing a subhourly dataset of 10-min resolution over the Netherlands. The results confirm the validity of the previously found 2CC scaling for extreme convective precipitation. Using a simple entraining plume model, an idealized deep convective environmental temperature profile is perturbed to analyze extreme precipitation scaling from a frequently used relation based on the column condensation rate. The plume model simulates a steady precipitation increase that is greater than Clausius–Clapeyron scaling (super-CC scaling). Precipitation intensity increase is shown to be controlled by a flux of moisture through the cloud base and in-cloud lateral moisture convergence. Decomposition of this scaling relation into a dominant thermodynamic and additional dynamic component allows for better understanding of the scaling and demonstrates the importance of vertical velocity in both dynamic and thermodynamic scaling. Furthermore, systematically increasing the environmental stability by adjusting the temperature perturbations from constant to moist adiabatic increase reveals a dependence of the scaling on the change in environmental stability. As the perturbations become increasingly close to moist adiabatic, the scaling found by the entraining plume model decreases to CC scaling. Thus, atmospheric stability changes, which are expected to be dependent on the latitude, may well play a key role in the behavior of precipitation extremes in the future climate.

Influence of entrainment on the thermal stratification in simulations of radiative‐convective equilibrium

Convective available potential energy (CAPE) is shown to increase rapidly with warming in simulations of radiative‐convective equilibrium over a wide range of surface temperatures. The increase in CAPE implies a systematic deviation of the thermal stratification from moist adiabatic that is non‐negligible at high temperatures. However, cloud buoyancy remains much smaller than what CAPE would imply because entrainment is more effective in reducing buoyancy in warmer atmospheres. An entraining plume model in the limit of zero cloud buoyancy is shown to reproduce the increase in CAPE with warming if the entrainment rate is held fixed and increases in the vertical extent of convection are taken into account. These model results together with radiosonde observations are used to support a conceptual model in which entrainment plays a role in determining the thermal stratification of the tropical atmosphere.

Spatial statistics of likely convective clouds in CloudSat data

[1] Spatial characteristics of cloud objects derived from 14 months of CloudSat data are analyzed with the aim of understanding global statistics for atmospheric convection. This study uses meteorological fields provided by NASA's Modern Era Reanalysis for Research and Applications (MERRA) and the European Center's ERA-Interim reanalysis to determine environmental conditions for the cloud objects. Width and aspect ratio statistics for clouds of likely convective origin are presented. Cloud object heights are compared with predictions from entraining plume models. A major finding of this study is that actual cloud depths are usually more than 50% smaller than those predicted by the plume models. This holds for a range of entrainment rate specifications, including rates based on observed cloud widths. A technique for isolating “mature” convective clouds based on their shape is proposed. When this technique is used to select objects, the comparison with the entraining plume model improves dramatically. Another result from this analysis is power law behavior in the cloud width distribution derived from CloudSat objects. After accounting for the difference between one-dimensional and two-dimensional sampling, the slope of the CloudSat distribution appears consistent with that found in earlier studies' cloud imagery. However, when clouds are selected using a minimum depth criterion, the resulting population is sharply peaked at widths close to this minimum depth. Finally, a weakly trimodal distribution of convective cloud depths is found, consistent with results from Johnson et al. (1999).

A Cumulus Parameterization with State-Dependent Entrainment Rate. Part I: Description and Sensitivity to Temperature and Humidity Profiles

Abstract A new cumulus parameterization is developed for which an entraining plume model is adopted. The lateral entrainment rate varies vertically depending on the surrounding environment. Two different formulations are examined for the rate. The cumulus ensemble is spectrally represented according to the updraft velocity at cloud base. Cloud-base mass flux is determined with prognostic convective kinetic energy closure. The entrainment rate tends to be large near cloud base because of the small updraft velocity near that level. Deep convection tends to be suppressed when convective available potential energy is small because of upward reduction of in-cloud moist static energy. Dry environmental air significantly reduces in-cloud humidity mainly because of the large entrainment rate in the lower troposphere, which leads to suppression of deep convection, consistent with observations and previous results of cloud-resolving models. The change in entrainment rate has the potential to influence cumulus convection through many feedbacks. The results of an atmospheric general circulation model are improved in both climatology and variability. A representation of the South Pacific convergence zone and the double intertropical convergence zone is improved. The moist Kelvin waves are represented without empirical triggering schemes with a reasonable equivalent depth. A spectral analysis shows a strong signal of the Madden–Julian oscillation. The scheme provides new insights and better understanding of the interaction between cumuli and the surrounding environment.

High-Resolution Simulation of Shallow-to-Deep Convection Transition over Land

Results are presented from a high-resolution three-dimensional simulation of shallow-to-deep convection transition based on idealization of observations made during the Large-Scale Biosphere–Atmosphere (LBA) experiment in Amazonia, Brazil, during the Tropical Rainfall Measuring Mission (TRMM)-LBA mission on 23 February. The doubly periodic grid has 1536 × 1536 × 256 grid cells with horizontal grid spacing of 100 m, thus covering an area of 154 × 154 km2. The vertical resolution varies from 50 m in the boundary layer to 100 m in the free troposphere and gradually coarsens to 250 m near the domain top at 25.4 km. The length of the simulation is 6 h, starting from an early morning sounding corresponding to 0730 local time. Convection is forced by prescribed surface latent and sensible heat fluxes and prescribed horizontally uniform radiative heating Despite a considerable amount of convective available potential energy (CAPE) in the range of 1600–2400 J kg−1, and despite virtually no convective inhibition (CIN) in the mean sounding throughout the simulation, the cumulus convection starts as shallow, gradually developing into congestus, and becomes deep only toward the end of simulation. Analysis shows that the reason is that the shallow clouds generated by the boundary layer turbulence are too small to penetrate deep into the troposphere, as they are quickly diluted by mixing with the environment. Precipitation and the associated cold pools are needed to generate thermals big enough to support the growth of deep clouds. This positive feedback involving precipitation is supported by a sensitivity experiment in which the cold pools are effectively eliminated by artificially switching off the evaporation of precipitation; in the experiment, the convection remains shallow throughout the entire simulation, with a few congestus but no deep clouds. The probability distribution function (PDF) of cloud size during the shallow, congestus, and deep phases is analyzed using a new method. During each of the three phases, the shallow clouds dominate the mode of the PDFs at about 1-km diameter. During the deep phase, the PDFs show cloud bases as wide as 4 km. Analysis of the joint PDFs of cloud size and in-cloud variables demonstrates that, as expected, the bigger clouds are far less diluted above their bases than their smaller counterparts. Also, thermodynamic properties at cloud bases are found to be nearly identical for all cloud sizes, with the moist static energy exceeding the mean value by as much as 4 kJ kg−1. The width of the moist static energy distribution in the boundary layer is mostly due to variability of water vapor; therefore, clouds appear to grow from the air with the highest water vapor content available. No undiluted cloudy parcels are found near the level of neutral buoyancy. It appears that a simple entraining-plume model explains the entrainment rates rather well. The least diluted plumes in the simulation correspond to an entrainment parameter of about 0.1 km−1.

The mesoscale convection life cycle: Building block or prototype for large-scale tropical waves?

A cumulonimbus cloud may ascend and spawn its anvil cloud, precipitation, and downdrafts within an hour or so. This paper inquires why a similar progression of events (life cycle) is observed for tropical weather fluctuations with time scales of hours, days, and even weeks. Regressions using point data illustrate the characteristic unit of rain production: the mesoscale convective system (MCS), covering tens of kilometers and lasting several hours, with embedded convective rain cells. Meanwhile, averages over larger spatial areas indicate a self-similar progression from shallow to deep convection to stratiform anvils on many time scales. Synthetic data exercises indicate that simple superpositions of fixed-structure MCS life cycles (the Building Block hypothesis) cannot explain why longer period life cycles are similar. Rather, it appears that an MCS may be a small analogue or prototype of larger scale waves. Multiscale structure is hypothesized to occur via a Stretched Building Block conceptual model, in which the widths (durations) of zones of shallow, deep, and stratiform anvil clouds in MCSs are modulated by larger scale waves. Temperature ( T) and humidity ( q) data are examined and fed into an entraining plume model, in an attempt to elucidate their relative roles in these large-scale convection zone variations. T profile variations, with wavelengths shorter than troposphere depth, appear important for high-frequency ( ∼ 2–5-day period) convectively coupled waves, as density directly links convection (via buoyancy) and large-scale wave dynamics (via restoring force). Still, the associated q anomalies are several times greater than adiabatic, suggesting a strong amplification by shallow convective feedbacks. For lower frequency (intraseasonal) variability, q anomalies are considerably larger compared to T, and may be dominant.

An Integrated Turbulence Scheme for Boundary Layers with Shallow Cumulus Applied to Pollutant Transport

Abstract A scheme is described that provides an integrated description of turbulent transport in free convective boundary layers with shallow cumulus. The scheme uses a mass-flux formulation, as is commonly found in cumulus schemes, and a 1.5-order closure, involving turbulent kinetic energy and eddy diffusivity. Both components are active in both the subcloud and cloud layers. The scheme is called “mass flux–diffusion.” In the subcloud layer, the mass-flux component provides nonlocal transport. The scheme combines elements from schemes that are conceptually similar but differ in detail. An entraining plume model is used to find the mass flux. The mass flux is continuous through the cloud base. The lateral fractional entrainment rate is constant with height, while the detrainment-rate profile reduces the mass flux smoothly to zero at the cloud top. The eddy diffusivity comes from a turbulent kinetic energy–length scale formulation. The scheme has been implemented in a simple one-dimensional (single column) model. Results of simulations of a standard case that has been used for other model intercomparisons [Atmospheric Radiation Measurement (ARM), 21 June 1997] are shown and indicate that the scheme provides good results. The model also simulates the profile of a conserved scalar; this capability is applied to a case from the 1999 Southern Oxidants Study Nashville (Tennessee) experiment, where it produces good simulations of vertical profiles of carbon monoxide in a cloud-topped boundary layer.

Comparison of Cumulus Parameterizations and Entrainment Using Domain-Mean Wind Divergence in a Regional Model

Several different cumulus parameterizations are compared in a 10-day regional model simulation over the tropical Americas in northern summer. A simple bulk diagnostic test is devised, comparing the model's preferred domain-mean wind divergence profile with “observed” drivergence. The latter is obtained by a line integral of the normal wind component at the model's outer boundary, from the ECMWF reanalysis data used as lateral boundary conditions. The former is obtained from a line integral one grid point in from the boundary, a perimeter that encloses almost exactly the same region. Even though the model fields near the boundary are strongly nudged toward the ECMWF values, the difference is distinct, and indicative of systematic errors in the model's heating field throughout the interior of the domain. Heating reflects the effects of the convection scheme, both direct and indirect (e.g., through its impact on resolved condensation). A useful axis along which to characterize schemes appears to be overactive versus underactive. Underactive convective schemes tend to produce too little low-level convergence and upper-level divergence, while overactive schemes produce too much. This categorization is also reflected in rainfall fields, as overactive schemes produce widespread light convective rain while underactive schemes produce sparse occasional storms. For example, the Kain–Fritsch scheme is overactive with its default entraining-plume radius of 1500 m, a value optimized for midlatitudes over land. A value of 750 m makes the regional divergence magnitude about right, but makes the upper-tropospheric outflow altitude too low, illustrating a classic dilemma of entraining-plume models of convection. Schemes with other conceptual structures give widely varying divergence errors. The largest errors are found with the Anthes–Kuo scheme, while the smallest errors are found with the Betts–Miller–Janjic scheme, which has no consistent divergence bias over time. Diagnosis of other North American monsoon simulations supports the general underactive/ overactive characterization, but shows that the best scheme and parameters may depend on weather regime.

A Multiple Mass Flux Parameterization for the Surface-Generated Convection. Part II: Cloudy Cores

Abstract The multiple mass-flux approach introduced in a companion paper aims at parameterizing the surface-generated convection in the atmosphere. The original aspects of this model are as follows. A number of convective updrafts are released in the surface layer. They initially have distinct fractional area and thermodynamic properties, determined through surface layer similarity; that is, by assuming that the thermodynamic fluxes are constant throughout the surface layer. Each updraft ascent is diagnosed using an entraining plume model. In the case of cumulus convection, this comprehensive formulation provides consistent representations of the subcloud mixing, the cloud mixing, and the associated cloudiness. In the present paper, this model is evaluated in two shallow moist convection cases, using the one-dimensional modeling framework. In the continental convection case, the diurnal cloud growth and the related subcloud layer ventilation agree with large eddy simulations. In the oceanic convection cas...

A New Subcloud Model for Mass-Flux Convection Schemes: Influence on Triggering, Updraft Properties, and Model Climate

All convection parameterizations in models of the atmosphere include a decision tree to decide on at least the occurrence, and often the type, of convection in a model grid volume. This decision tree is sometimes referred to as the ‘‘trigger function.’’ This study investigates the role that the decision-making processes play in the simulation of convection in the European Centre for Medium-Range Weather Forecasts global forecast model. For this purpose, a new simple parcel-ascent model based on an entraining plume model is developed to replace the currently used undilute ascent in the initial decision making. The consequences of the use of the more realistic model for the behavior of convection itself and its impact on the model climate are investigated. It is shown that there are profound changes to both the convection characteristics, and consequently, the model climate. The wider implications of the findings here for the general design of a mass-flux convection parameterization are discussed.