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Most global climate models with convective parameterization have trouble in simulating the observed diurnal cycle of convection. Maximum precipitation usually happens too early during summertime, especially over land. Observational analyses indicate that deep convection over land cannot keep pace with rapid variations in convective available potential energy, which is largely controlled by boundary‐layer forcing. In this study, a new convective closure in which shallow and deep convection interact strongly, out of equilibrium, is implemented in atmosphere‐only and ocean‐atmosphere coupled models. The diurnal cycles of convection in both simulations are significantly improved with small changes to their mean states. The new closure shifts maximum precipitation over land later by about three hours. Compared to satellite observations, the diurnal phase biases are reduced by half. Shallow convection to some extent equilibrates rapid changes in the boundary layer at subdiurnal time scales. Relaxed quasi‐equilibrium for convective available potential energy holds in significant measure as a result. Future model improvement will focus on the remaining biases in the diurnal cycle, which may be further reduced by including stochastic entrainment and cold pools. Plain Language Summary: In this study, we tackled a common challenge in general circulation models concerning the timing of intense rainfall over land during summertime. Many models tend to predict the peak of precipitation too early in the day. To address this, our study introduced a new approach to simulate convection by accounting for the role of shallow convection in stabilizing rapid changes in the atmospheric boundary layer at shorter time scales. This approach delayed maximum precipitation over land by approximately three hours. This adjustment significantly improved the simulated precipitation, aligning them more closely with observations from satellite data. Overall, our research contributes to improving numerical models, bringing them closer to accurately simulating the intricate dynamics of convection and precipitation over land. Key Points: A new convective closure is applied to Geophysical Fluid Dynamics Laboratory's CMIP6 climate models AM4 (atmosphere‐only) and CM4 (ocean‐atmosphere coupled)The diurnal cycle of precipitation is significantly improved over landThe new closure does not significantly change many aspects of AM4 and CM4's mean state and variability aside from their diurnal precipitation cycles [ABSTRACT FROM AUTHOR]

Abstract Most global climate models with convective parameterization have trouble in simulating the observed diurnal cycle of convection. Maximum precipitation usually happens too early during summertime, especially over land. Observational analyses indicate that deep convection over land cannot keep pace with rapid variations in convective available potential energy, which is largely controlled by boundary‐layer forcing. In this study, a new convective closure in which shallow and deep convection interact strongly, out of equilibrium, is implemented in atmosphere‐only and ocean‐atmosphere coupled models. The diurnal cycles of convection in both simulations are significantly improved with small changes to their mean states. The new closure shifts maximum precipitation over land later by about three hours. Compared to satellite observations, the diurnal phase biases are reduced by half. Shallow convection to some extent equilibrates rapid changes in the boundary layer at subdiurnal time scales. Relaxed quasi‐equilibrium for convective available potential energy holds in significant measure as a result. Future model improvement will focus on the remaining biases in the diurnal cycle, which may be further reduced by including stochastic entrainment and cold pools.

Shallow convection plays an important role in transporting heat and moisture from the near-surface to higher altitudes, yet its parameterization in numerical models remains a great challenge, partly due to the lack of high-resolution observations. This study describes a large eddy simulation (LES) dataset for four shallow convection cases that differ primarily in inversion strength, which can be used as a surrogate for real data. To reduce the uncertainty in LES modeling, three different large eddy models were used, including SAM (System for Atmospheric Modeling), WRF (Weather Research and Forecasting model), and UCLA-LES. Results show that the different models generally exhibit similar behavior for each shallow convection case, despite some differences in the details of the convective structure. In addition to grid-averaged fields, conditionally sampled variables, such as in-cloud moisture and vertical velocity, are also provided, which are indispensable for calculation of the entrainment/detrainment rate. Considering the essentiality of the entraining/detraining process in the parameterization of cumulus convection, the dataset presented in this study is potentially useful for validation and improvement of the parameterization of shallow convection. [ABSTRACT FROM AUTHOR]

The meteorology of ridging highs on the coast of KwaZulu‐Natal (KZN) South Africa was studied using Principal Component (pc) analysis of daily ERA5 sea level air pressure (SLP) fields 1980–2021. The second pc mode time score representing ridging highs, was associated with rain‐showers moving northeast‐ward along the KZN coast. Temporal analysis revealed an Oct‐Dec peak occurrence and 12‐day pulse intervals induced by the eastward migration of atmospheric Rossby waves in early summer. From a ranking of SLP pc2 and associated daily time series, a case study emerged: 14–18 Nov. 2009. This ridging high weather scenario had cold southerly winds subsiding over the warm Agulhas Current. Surface moisture fluxes >350 W/m2 create a buoyant airmass that slows and lifts over the coastal plains, inducing shallow clouds that reduce net solar radiation and potential evaporation. Interannual variability of ridging highs was studied by filtering the daily SLP pc2 time score to retain seasonal fluctuations and correlating with regional fields of SST. This revealed warming in the SW Indian Ocean associated with positive phase Indian Ocean Dipole (IOD). The atmospheric circulation forms a NW trough over Madagascar which deforms eastward moving mid‐latitude anticyclones. Thus, ridging highs that bring beneficial Oct‐Dec rains to the coast of KZN depend on downstream climate coupling with the IOD. Long‐term trends from a coupled model simulation 1980–2100 suggest a poleward retreat of the anticyclonic ridge, consistent with declining Durban‐area river flow in early summer. [ABSTRACT FROM AUTHOR]

The meso‐scale variability in cloudiness of the marine trade‐wind layer is explored with large‐eddy simulations of regional extent and validated against observations of the EUREC4A field campaign. 41 days of realistically forced simulations present a representative, statistical view on shallow convection in the winter North Atlantic trades that includes a wide range of meso‐scale variability including the four recently identified patterns of spatial organization: Sugar, Gravel, Flowers and Fish. The results show that cloud cover is on average captured well but with discrepancies in its vertical and spatial distribution. Cloudiness at the lifting condensation level depends on the model resolution with the finer one producing on average a more realistic cloud profile. Independent of the resolution, the variability in cloudiness below the trade inversion is not captured, leading to a lack of stratiform cloudiness with implications on the detectability of meso‐scale patterns whose cloud patches are characterized by stratiform clouds. The simulations tend to precipitate more frequently than observed, with a narrower distribution of echo intensities. The observed co‐variability between cloudiness and environmental conditions is well captured. Plain Language Summary: Clouds generally cool the planet due to their ability to reflect sunlight efficiently. To estimate this cooling in a future climate, the processes leading to cloud formation need to be understood. A process that current climate simulations struggle to capture due to their coarse resolution is the variability and patterning of cloudiness on scales on the order of 10–100 km. In this study we ran higher resolved simulations at hm‐resolutions by limiting the region to the downstream North Atlantic trades where the patterning of shallow clouds is common. Coinciding our simulations with the measurements of the EUREC4A field campaign and being able to run them for over a month allowed us to pin‐point current deficits that these higher resolved simulations have. These are in particular the vertical cloud distribution with too little stratiform cloud amount and too much precipitation that hardly changes with the patterning in cloudiness. Nevertheless, the simulations do a good job in capturing the day‐to‐day variability in total cloud cover and its co‐variability with environmental conditions justifying a further study of the phenomenon with these kind of simulations and ultimately improving the climate simulations on this aspect. Key Points: A 41 days, hm‐resolution simulation is run to quantify the ability of ICON‐LEM to reproduce the observed cloudinessThe simulated cloudiness co‐varies with precipitable water, temperature and wind speed mimicking the observationsThe vertical distribution of cloudiness remains challenging at the cost of representing mesoscale patterns with stratiform cloud amount [ABSTRACT FROM AUTHOR]

Abstract The meso‐scale variability in cloudiness of the marine trade‐wind layer is explored with large‐eddy simulations of regional extent and validated against observations of the EUREC4A field campaign. 41 days of realistically forced simulations present a representative, statistical view on shallow convection in the winter North Atlantic trades that includes a wide range of meso‐scale variability including the four recently identified patterns of spatial organization: Sugar, Gravel, Flowers and Fish. The results show that cloud cover is on average captured well but with discrepancies in its vertical and spatial distribution. Cloudiness at the lifting condensation level depends on the model resolution with the finer one producing on average a more realistic cloud profile. Independent of the resolution, the variability in cloudiness below the trade inversion is not captured, leading to a lack of stratiform cloudiness with implications on the detectability of meso‐scale patterns whose cloud patches are characterized by stratiform clouds. The simulations tend to precipitate more frequently than observed, with a narrower distribution of echo intensities. The observed co‐variability between cloudiness and environmental conditions is well captured.

Uncertainties associated with the response of shallow clouds to global warming remain a great challenge for climate projection. Due to the small size of these clouds, parameterizations are required to represent them in both current‐ and next‐generation climate models. We present a quantitative evaluation of several important assumptions used in both mass‐flux and Assumed‐PDF Higher‐Order Closure parameterizations of shallow convection. We use large‐eddy simulations (LESs) of four different shallow convection regimes as benchmarks and apply a qt (total moisture)–w (vertical velocity) quadrant analysis technique to identify the "coherent structures" of moist and dry up/down‐drafts. The statistics of these coherent structures and the environment are then used to evaluate commonly used assumptions in mass‐flux parameterizations related to (a) the convective downdrafts and (b) the subplume variability of convective updrafts. For quantitative evaluation of the PDF closure used in AP‐HOCs, we perform offline calculations with the PDF closure used in the Cloud Layers Unified By Bi‐normals and the Simplified Higher‐Order Closure schemes by supplying the closure with statistical quantities directly calculated from the LESs. Then, the impact of parameterization assumptions embedded in the PDF closure in the same two categories is analyzed and understood through comparisons of the output from the closure with the statistics of the moist and dry up/down‐drafts from the LESs. Plain Language Summary: This study examines critically several key simplifying assumptions about convective downdrafts and small‐scale variability associated with shallow clouds that are made in two types of shallow convection parameterizations widely used in numerical weather and climate models and demonstrates quantitatively the impact of these assumptions on the parameterized cloud water content, depth, and turbulent transport. Key Points: A qt–w quadrant analysis is applied to identify convective coherent structures in large‐eddy simulations of various shallow cloud regimesStatistics from the quadrant analysis is used to evaluate assumptions in mass‐flux and Assumed‐PDF Higher‐Order Closure shallow convection parameterizationsSimplifying assumptions on convective downdrafts and subplume variability are linked to parameterization deficiencies [ABSTRACT FROM AUTHOR]

This study investigates the lifetime and temporal evolution of physical properties of trade‐wind cumuli based on tracking individual clouds in observations with the Advanced Baseline Imager aboard the geostationary GOES‐16 satellite during the "ElUcidating the RolE of Cloud–Circulation Coupling in ClimAte" (EUREC4A) campaign east of Barbados in winter 2020. A first application of our upgraded cloud‐tracking toolbox to measurements with high spatio‐temporal resolution (2 × 2 km2 and 1 min) provides probability density functions of lifetime and area of clouds that develop as a consequence of meso‐to‐synoptic scale motions. By separately considering clouds that exist during daytime and live in distinct lifetime intervals, we find that shallow marine cumuli live longer when they cover a larger surface area and show higher cloud optical thickness (COT). Besides the effect of COT, the scale of the atmospheric motions with which the clouds interact is also critical to their lifetime. Plain Language Summary: We present a detailed investigation of the lifetime of Caribbean trade‐wind cumulus clouds and the temporal evolution of their physical properties based on geostationary observations with the Advanced Baseline Imager aboard the geostationary GOES‐16 satellite during the "ElUcidating the RolE of Cloud–Circulation Coupling in ClimAte" (EUREC4A) field experiment in winter 2020. The tracking of 2.7 million individual clouds in measurements with high spatio‐temporal resolution enables the investigation of processes that control the lifetime of shallow marine cumulus (SMC) clouds. Our analysis reveals that SMC clouds live longer when they span over a surface area that exceeds an order of tens of square kilometers. While these clouds show similar median cloud droplet size and number concentration compared to shorter‐lived clouds, they contain more liquid water and, thus, show a COT that is increased by about one third. Besides the effect of COT, we find that the scale of the atmospheric motions with which the clouds interact is also critical to their lifetime. Key Points: First study of the life cycle of shallow marine cumulus based on observations with the Advanced Baseline Imager aboard GOES‐16Confirmation of the double power law in the distribution of cloud lifetime from measurements with a temporal resolution of 1 minuteCloud lifetime is related to large‐scale circulation and affects cloud optical thickness [ABSTRACT FROM AUTHOR]

Idealized large-eddy simulations of shallow convection often utilize horizontally periodic computational domains. The development of precipitation in shallow cumulus convection changes the spatial structure of convection and creates large-scale organization. However, the limited periodic domain constrains the horizontal variability of the atmospheric boundary layer. Small computational domains cannot capture the mesoscale boundary layer organization and artificially constrain the horizontal convection structure. The effects of the horizontal domain size on large-eddy simulations of shallow precipitating cumulus convection are investigated using four computational domains, ranging from 40 × 40 km 2 to 320 × 320 km 2 and fine grid resolution (40 m). The horizontal variability of the boundary layer is captured in computational domains of 160 × 160 km 2 . Small LES domains (≤40 km) cannot reproduce the mesoscale flow features, which are about 100 km long, but the boundary layer mean profiles are similar to those of the larger domains. Turbulent fluxes, temperature and moisture variances, and horizontal length scales are converged with respect to domain size for domains equal to or larger than 160 × 160 km 2 . Vertical velocity flow statistics, such as variance and spectra, are essentially identical in all domains and show minor dependence on domain size. Characteristic horizontal length scales (i.e., those relating to the mesoscale organization) of horizontal wind components, temperature and moisture reach an equilibrium after about hour 30. [ABSTRACT FROM AUTHOR]

A new spectral convection scheme, the stochastic unified convection scheme (stochastic UNICON), is implemented in a general circulation model. The global climate simulation using stochastic UNICON is evaluated and compared with UNICON, focusing on the simulation of the Madden–Julian oscillation (MJO). Stochastic UNICON extends the original UNICON by randomly sampling convective updrafts from the joint probability density function constructed at the near‐surface, generating a spectrum of convective updrafts in a physically based manner. The performances of UNICON and stochastic UNICON on simulating observed mean climates are comparable, while stochastic UNICON slightly reduces the mean bias of climate variables. For the simulation of intraseasonal variabilities, stochastic UNICON outperforms UNICON in many aspects. Stochastic UNICON improves the simulation of the intensity and propagation patterns of boreal winter MJO, which are too weakly simulated in UNICON. The coherency between MJO‐related convection and large‐scale circulation is also enhanced, which many climate models underestimate. The improvement of MJO simulation by stochastic UNICON is related to a better representation of the relationship between moisture and convection in the model. The increased frequency of shallow convection in stochastic UNICON leads to stronger moisture convergence that precedes convection activity peak and results in the more robust development of organized convection and more frequent intense precipitation. A precipitation budget analysis reveals that the moisture tendencies due to horizontal advection and convective process are consistently enhanced during MJO developing periods by stochastic UNICON. Plain Language Summary: The Madden–Julian oscillation (MJO) emerges in the tropics as a pattern of rainy periods followed by dry periods that fluctuates on weekly to monthly time scales. The MJO is important for various weather and climate phenomena but poorly represented in global climate models (GCMs). To simulate realistic MJO, convection needs to be realistically modeled. Recently, a new spectral convection scheme named stochastic unified convection scheme (stochastic UNICON) is developed based on the unified convection scheme (UNICON). Stochastic UNICON can represent different types of convective clouds in a model grid. The GCM with stochastic UNICON simulates better strength and propagation of winter MJO and better relationship between convection and large‐scale circulation compared to that of UNICON. The improvements come from a more realistic relationship between moisture and convection. The increased frequency of shallow convection in stochastic UNICON produces the condition for the MJO to develop more robustly. Key Points: The global simulation of the Madden–Julian oscillation (MJO) with a new spectral convection scheme named stochastic unified convection scheme (UNICON) is evaluatedStochastic UNICON improves various properties of the simulated MJO compared to the non‐stochastic versionThe increased shallow convection in stochastic UNICON leads to a stronger moistening tendency in MJO developing stage [ABSTRACT FROM AUTHOR]

The EUREC4A (Elucidating the role of clouds–circulation coupling in climate) and ATOMIC (Atlantic Tradewind Ocean‐Atmosphere Mesoscale Interaction Campaign) joint field campaign gathered observations to better understand the links between trade‐wind cumulus clouds, their organization, and larger scales, a large source of uncertainty in climate projections. A recent large‐eddy simulation study showed a cloud transition that occurred during this field campaign, where small shallow clouds developed into larger clouds with detrainment layers, was caused by an increase in mesoscale organization generated by a dynamical feedback in mesoscale vertical velocities. We show that kilometer‐scale simulations with the Met Office's Unified Model reproduce this increase in mesoscale organization and the process generating it, despite being much lower resolution. The timing of development is associated with large‐scale convergence. Sensitivity tests with a shorter spin‐up time, to reduce initial organization, still have the same timing of development and sensitivity tests with cold pools suppressed show only a small effect on mesoscale organization. Mesoscale organization and clouds are sensitive to resolution, with higher resolution simulations producing weaker organization and less cloud, which affects changes in net radiation. The clouds also have substantial differences to observations. Therefore, while kilometer‐scale simulations can be useful for understanding processes of mesoscale organization and links with large scales, including responses to climate change, simulations will still suffer from significant errors and uncertainties in radiative budgets. Plain Language Summary: A recent field campaign made extensive measurements of shallow clouds upstream of Barbados and the surrounding region. These clouds are important because their effect on climate change is highly uncertain. Cloud patterns in satellite images in this region can vary dramatically. One example, from 2 February 2020, is when the clouds changed from a region of small clouds that looks like a scattering of sugar to larger patches of clouds that look like flowers separated by clear sky. A previous study with a very high resolution model has shown the physical mechanism behind this change in the cloud pattern. We show that lower resolution simulations can reproduce this transition and the physical mechanism associated with it. Low resolution allows for a much larger domain which can capture features of the atmospheric flow on larger scales. However, the development of individual clouds is poorly represented. The results show the model is a useful testbed for better understanding the physical mechanism behind changes in cloud patterns and what might affect it, but the impacts of clouds on climate, via reflecting sunshine and absorbing infrared radiation, will still have large errors and uncertainties in climate projections. Key Points: Kilometer‐scale Unified Model simulations capture an increase in mesoscale organization associated with an observed "flowers" cloud patternThe time during which clouds and mesoscale organization develop is associated with large‐scale convergenceInitial organization and cold pools have little effect on timing and cold pools only have a small opposing effect to mesoscale organization [ABSTRACT FROM AUTHOR]

Abstract Uncertainties associated with the response of shallow clouds to global warming remain a great challenge for climate projection. Due to the small size of these clouds, parameterizations are required to represent them in both current‐ and next‐generation climate models. We present a quantitative evaluation of several important assumptions used in both mass‐flux and Assumed‐PDF Higher‐Order Closure parameterizations of shallow convection. We use large‐eddy simulations (LESs) of four different shallow convection regimes as benchmarks and apply a qt (total moisture)–w (vertical velocity) quadrant analysis technique to identify the “coherent structures” of moist and dry up/down‐drafts. The statistics of these coherent structures and the environment are then used to evaluate commonly used assumptions in mass‐flux parameterizations related to (a) the convective downdrafts and (b) the subplume variability of convective updrafts. For quantitative evaluation of the PDF closure used in AP‐HOCs, we perform offline calculations with the PDF closure used in the Cloud Layers Unified By Bi‐normals and the Simplified Higher‐Order Closure schemes by supplying the closure with statistical quantities directly calculated from the LESs. Then, the impact of parameterization assumptions embedded in the PDF closure in the same two categories is analyzed and understood through comparisons of the output from the closure with the statistics of the moist and dry up/down‐drafts from the LESs.

Abstract This study investigates the lifetime and temporal evolution of physical properties of trade‐wind cumuli based on tracking individual clouds in observations with the Advanced Baseline Imager aboard the geostationary GOES‐16 satellite during the “ElUcidating the RolE of Cloud–Circulation Coupling in ClimAte” (EUREC4A) campaign east of Barbados in winter 2020. A first application of our upgraded cloud‐tracking toolbox to measurements with high spatio‐temporal resolution (2 × 2 km2 and 1 min) provides probability density functions of lifetime and area of clouds that develop as a consequence of meso‐to‐synoptic scale motions. By separately considering clouds that exist during daytime and live in distinct lifetime intervals, we find that shallow marine cumuli live longer when they cover a larger surface area and show higher cloud optical thickness (COT). Besides the effect of COT, the scale of the atmospheric motions with which the clouds interact is also critical to their lifetime.

Abstract A new spectral convection scheme, the stochastic unified convection scheme (stochastic UNICON), is implemented in a general circulation model. The global climate simulation using stochastic UNICON is evaluated and compared with UNICON, focusing on the simulation of the Madden–Julian oscillation (MJO). Stochastic UNICON extends the original UNICON by randomly sampling convective updrafts from the joint probability density function constructed at the near‐surface, generating a spectrum of convective updrafts in a physically based manner. The performances of UNICON and stochastic UNICON on simulating observed mean climates are comparable, while stochastic UNICON slightly reduces the mean bias of climate variables. For the simulation of intraseasonal variabilities, stochastic UNICON outperforms UNICON in many aspects. Stochastic UNICON improves the simulation of the intensity and propagation patterns of boreal winter MJO, which are too weakly simulated in UNICON. The coherency between MJO‐related convection and large‐scale circulation is also enhanced, which many climate models underestimate. The improvement of MJO simulation by stochastic UNICON is related to a better representation of the relationship between moisture and convection in the model. The increased frequency of shallow convection in stochastic UNICON leads to stronger moisture convergence that precedes convection activity peak and results in the more robust development of organized convection and more frequent intense precipitation. A precipitation budget analysis reveals that the moisture tendencies due to horizontal advection and convective process are consistently enhanced during MJO developing periods by stochastic UNICON.

We investigate a significant model-observation difference found between cloud-base vertical velocity for continental shallow cumulus simulated using large-eddy simulations (LES) and observed by Doppler lidar measurements over the U.S. Southern Great Plains Atmospheric Radiation Measurement Facility. The LES cloud-base vertical velocity is dominated by updrafts that are consistent with a general picture for convective clouds but is inconsistent with Doppler lidar observations that also show the presence of considerable downdrafts. The underestimation of simulated downdrafts is found to be a robust feature, being insensitive to various numerical, physical, or dynamical choices. We find that simulations can more closely reproduce observations only after improving the model physics to use size-resolved microphysics and horizontal longwave radiation, both of which modify the cloud buoyancy and velocity structure near cloud side edges. The results suggest that treatments that capture these structures are needed for the proper simulation and subsequent parameterization development of shallow cumulus vertical transport.

Flower clouds are trade‐wind shallow cumuli, with tops reaching 3 km altitude, organised into 100‐km wide clusters. They are widespread over the subtropics and associated with the strongest cloud radiative effect among trade‐wind cumuli mesoscale organisations. In the context of large uncertainty in climate projections due to the representation of shallow clouds, major knowledge gaps remain about the global impact of mesoscale organisations and the local processes driving them. Here, the processes governing the flower organisation are investigated based on the case study of February 2, 2020 from the Elucidate the Couplings Between Clouds, Convection, and Circulation (EUREC4$$ {}^4 $$A) campaign, east of Barbados. One flower cloud is simulated with a large‐eddy simulation (LES), using the Meso‐NH model at 100‐m horizontal grid spacing, and validated extensively with high‐resolution observations from the High Altitude and Long‐range Research Aircraft (HALO), dropsondes, and satellite measurements. The cloud‐top altitudes exhibit a trimodal distribution. The processes shaping flower clouds are wide cold pools and cloudy updrafts organised in one large arc at the western edge. These updrafts are responsible for the highest cloud tops and drive most of the vertical turbulent fluxes of sensible heat, humidity, and momentum. A mesoscale circulation takes place at the scale of the flower clouds and makes them very similar to deep mesoscale convective systems. [ABSTRACT FROM AUTHOR]

Two‐fluid modelling has recently emerged as a promising approach to representing cumulus convection in weather and climate models. This study applies the two‐fluid model described in Part II to a shallow cumulus convection case study over land (ARM). Large‐eddy simulation data are used to tune the majority of the closures that determine the properties of entrained and detrained air. The two‐fluid model is generally able to reproduce the profiles of the mean and turbulent quantities over all stages of the diurnal cycle. As such, the initiation of shallow convection and the evolution of the cloud layer are well captured. The robustness of the two‐fluid model is verified further using a steady‐state test case (BOMEX), in which the cloud properties are also well modelled. [ABSTRACT FROM AUTHOR]

The two‐fluid single‐column model of Thuburn et al. (Quart. J. R. Meteorol. Soc., 2019, 145, 1535–1550) is extended to include moisture and horizontal wind shear. Turbulent kinetic energy is introduced as a prognostic variable, dependence on a diagnosed boundary‐layer height is removed, and subfilter fluxes are approximated using a two‐fluid version of a Mellor–Yamada scheme. Three mechanisms for entrainment and detrainment processes are introduced, which represent entrainment of unstable air at the surface, forced detrainment of air at the top of the boundary/cloud layers, and turbulent mixing that relaxes the convective fluid to a reference profile. A semi‐implicit Eulerian discretization replaces the semi‐implicit semi‐Lagrangian implementation of Thuburn et al. (Quart. J. R. Meteorol. Soc., 2019, 145, 1535–1550) to improve numerical stability and conservation. The equations for the implicit time step are solved using a quasi‐Newton method, which is shown to perform well in numerical tests for conservation and convergence. The two‐fluid single‐column model presented in this article will be applied to simulations of shallow cumulus convection in Part III. [ABSTRACT FROM AUTHOR]

This study evaluates the ability of the French convection‐permitting model AROME‐OM to represent shallow cumulus and their main organisations for boreal winter conditions in the North Atlantic trades. It uses a set of three winter seasons (January–February, 2018–2020) of high‐resolution (1.3 and 2.5 km) simulations over the Caribbean domain (9.7–22.9°N, 75.3–51.7°W). The model is assessed against soundings at Grantley Adams Airport and remote‐sensing observations at a site located on the east coast of Barbados which is representative of downwind trade regimes. The thermodynamic environment of the model fits the observations overall but the boundary layer is slightly too deep, resulting in a weak cold and dry bias. Both model and observations clearly exhibit (a) a double peak of cloud fraction, a first peak near the cloud base and a second one near the cloud top and (b) a larger variance in cloudiness near the top of the deepest cumuli, at around 2 km, with a higher sensitivity to the environment. We then take advantage of the EUREC4A field campaign which took place in January–February 2020 to assess the ability of the model to reproduce the four main mesoscale patterns and to characterize the air masses in which they develop. All the observations confirm the capacity of the model to predict the different mesoscale organizations and their associated environment. [ABSTRACT FROM AUTHOR]

Idealized large-eddy simulations of shallow convection often utilize horizontally periodic computational domains. The development of precipitation in shallow cumulus convection changes the spatial structure of convection and creates large-scale organization. However, the limited periodic domain constrains the horizontal variability of the atmospheric boundary layer. Small computational domains cannot capture the mesoscale boundary layer organization and artificially constrain the horizontal convection structure. The effects of the horizontal domain size on large-eddy simulations of shallow precipitating cumulus convection are investigated using four computational domains, ranging from 40×40km2 to 320×320km2 and fine grid resolution (40 m). The horizontal variability of the boundary layer is captured in computational domains of 160×160km2. Small LES domains (≤40 km) cannot reproduce the mesoscale flow features, which are about 100km long, but the boundary layer mean profiles are similar to those of the larger domains. Turbulent fluxes, temperature and moisture variances, and horizontal length scales are converged with respect to domain size for domains equal to or larger than 160×160km2. Vertical velocity flow statistics, such as variance and spectra, are essentially identical in all domains and show minor dependence on domain size. Characteristic horizontal length scales (i.e., those relating to the mesoscale organization) of horizontal wind components, temperature and moisture reach an equilibrium after about hour 30.

An update of the two‐energy turbulence scheme is presented, the 2TE + APDF scheme. The original version of the two‐energy scheme is able to successfully model shallow convection without the need of an additional parameterization for non‐local fluxes. However, the performance of the two‐energy scheme is worse in stratocumulus cases, where it tends to overestimate the erosion of the stable layers. We have identified the causes: the non‐local stability parameter does not consider local stratification, the scheme lacks an internal parameter that could distinguish between a shallow convection regime and a stratocumulus regime, and it uses an inflexible turbulence length scale formulation. To alleviate this problem, we propose several modifications: an update of the stability parameter, a modified computation of the turbulence length scale, and the introduction of the entropy potential temperature to distinguish between a shallow convection and a stratocumulus regime. In addition, the two‐energy scheme is coupled to a simplified assumed probability density function method in order to achieve a more universal representation of the cloudy regimes. The updated turbulence scheme is evaluated for several idealized cases and one selected real case in the ICOsahedral Nonhydrostatic (ICON) modeling framework. The results show that the updated scheme corrects the overmixing problem in the stratocumulus cases. The performance of the updated scheme is comparable to the operational setup, and can be thus used instead of the operational turbulence and shallow convection scheme in ICON. Additionally, the updated scheme improves the coupling with dynamics, which is beneficial for the modeling of coherent flow structures in the atmospheric boundary layer. Plain Language Summary: The two‐energy turbulence scheme parametrizes turbulence and boundary layer clouds in a unified framework. This enables the scheme to be more consistent and more continuous in time and space than the classical combination of separate turbulence and convection schemes. The original version of the scheme tends to overestimate the erosion of the stable layers, particularly in stratocumulus cases. We have identified several reasons for this problem and updated the scheme accordingly. To achieve a more universal representation of the cloudy regimes, the two‐energy scheme has been also coupled to the assumed probability density function (PDF) method. This method is based on assuming the shape of the trivariate PDF of moisture, heat and vertical velocity. The new version of the scheme was implemented into the ICOsahedral Nonhydrostatic (ICON) modeling framework and was tested on several idealized cases and one realistic case. The results show that the updated scheme corrects the overmixing problem in the stratocumulus cases. The performance of the updated scheme is comparable to the operational setup, and can be thus used instead of the operational turbulence and shallow convection scheme in ICON. Additionally, the updated scheme improves the coupling with dynamics, which is beneficial for the modeling of coherent flow structures in the atmospheric boundary layer. Key Points: An update of the two‐energy scheme for the unified parameterization of the turbulence and clouds in the atmospheric boundary layer (ABL) is presentedThe performance of the updated scheme is comparable to the operational ICOsahedral Nonhydrostatic configurationThe updated scheme shows the ability to model coherent flow structures in the ABL [ABSTRACT FROM AUTHOR]

A segmentation algorithm is applied to high resolution simulations of shallow continental convection to identify individual convective 3D objects within the convective boundary layer, in order to investigate which properties of the objects vary with the object width. The study analyses the geometry of the objects, along with their profiles of vertical velocity and total water, to assess various assumptions often used in spectral mass‐flux convection schemes. The methodology of this paper is unique in that we use (a) a novel application of the watershed algorithm to detect individual objects in the constantly evolving continental boundary layer efficiently, and (b) an unprecedentedly large number of simulations being analyzed. In total, 26 days of LASSO simulations at the Atmospheric Radiation Measurement Southern Great Plains site are analyzed, yielding roughly one million objects. Plume‐like surface‐rooted objects are found to be omnipresent, the vertical extent of which is strongly dependent on the object width. The vertical velocity and moisture anomaly profiles of the widest objects are roughly consistent with the classic buoyancy‐driven rising plume model. The kinematic and thermodynamic properties of the objects vary with object width. This width dependence is strongest above cloud base, but much weaker below. Finally the impact of neglecting the contribution of covariances to the vertical moisture flux, which is commonly used in mass‐flux parameterizations, is investigated. The average effect of neglecting covariances increases linearly with object width, leading to a 20% flux underestimation for 2 km wide objects. Implications of the results for spectral convection scheme development are briefly discussed. Plain Language Summary: This paper studies updrafts, which are volumes of warm air traveling upwards in the atmosphere, using high‐resolution simulations. These simulations have sufficient resolution to capture how the sun heating the surface causes warm air to travel upwards. These updrafts are responsible for the formation of cumulus clouds. What separates the methodology of this study from others is the newly developed method used to detect these updrafts in the model output, and the comparatively large amount of simulations analyzed. The model domain is large enough to contain thousands of updrafts. 26 days of simulations over the great plains in Oklahoma are used, yielding about a million simulated updrafts in total for us to study. From our results we conclude that there is a clear positive relationship between updraft width and height. Thinner updrafts seldom reach up to the cloud base, and they tend to get thinner the further away they are from the surface. In contrast, we find that the thicker updrafts are wider at cloud base than at the surface. Other aspects of the updrafts, such as their vertical velocity and moisture transport, are studied to determine how these properties vary with the width of the updrafts. Key Points: A 3D segmentation analysis is applied to large‐eddy simulations of shallow cumulus cloud fields as observed at the Atmospheric Radiation Measurement Southern Great Plains sitePlume‐like surface‐rooted convective objects are omnipresent, with object height being strongly dependent on object widthWe find that the thermodynamic, geometric, kinematic, and flux properties of the objects also depend on object width [ABSTRACT FROM AUTHOR]

Abstract An update of the two‐energy turbulence scheme is presented, the 2TE + APDF scheme. The original version of the two‐energy scheme is able to successfully model shallow convection without the need of an additional parameterization for non‐local fluxes. However, the performance of the two‐energy scheme is worse in stratocumulus cases, where it tends to overestimate the erosion of the stable layers. We have identified the causes: the non‐local stability parameter does not consider local stratification, the scheme lacks an internal parameter that could distinguish between a shallow convection regime and a stratocumulus regime, and it uses an inflexible turbulence length scale formulation. To alleviate this problem, we propose several modifications: an update of the stability parameter, a modified computation of the turbulence length scale, and the introduction of the entropy potential temperature to distinguish between a shallow convection and a stratocumulus regime. In addition, the two‐energy scheme is coupled to a simplified assumed probability density function method in order to achieve a more universal representation of the cloudy regimes. The updated turbulence scheme is evaluated for several idealized cases and one selected real case in the ICOsahedral Nonhydrostatic (ICON) modeling framework. The results show that the updated scheme corrects the overmixing problem in the stratocumulus cases. The performance of the updated scheme is comparable to the operational setup, and can be thus used instead of the operational turbulence and shallow convection scheme in ICON. Additionally, the updated scheme improves the coupling with dynamics, which is beneficial for the modeling of coherent flow structures in the atmospheric boundary layer.

Abstract A segmentation algorithm is applied to high resolution simulations of shallow continental convection to identify individual convective 3D objects within the convective boundary layer, in order to investigate which properties of the objects vary with the object width. The study analyses the geometry of the objects, along with their profiles of vertical velocity and total water, to assess various assumptions often used in spectral mass‐flux convection schemes. The methodology of this paper is unique in that we use (a) a novel application of the watershed algorithm to detect individual objects in the constantly evolving continental boundary layer efficiently, and (b) an unprecedentedly large number of simulations being analyzed. In total, 26 days of LASSO simulations at the Atmospheric Radiation Measurement Southern Great Plains site are analyzed, yielding roughly one million objects. Plume‐like surface‐rooted objects are found to be omnipresent, the vertical extent of which is strongly dependent on the object width. The vertical velocity and moisture anomaly profiles of the widest objects are roughly consistent with the classic buoyancy‐driven rising plume model. The kinematic and thermodynamic properties of the objects vary with object width. This width dependence is strongest above cloud base, but much weaker below. Finally the impact of neglecting the contribution of covariances to the vertical moisture flux, which is commonly used in mass‐flux parameterizations, is investigated. The average effect of neglecting covariances increases linearly with object width, leading to a 20% flux underestimation for 2 km wide objects. Implications of the results for spectral convection scheme development are briefly discussed.

Weather forecasting nowadays often requires some estimation of uncertainties associated with the output of meteorological models, in order to better inform decision making, especially in the context of intense weather events. Ensemble prediction systems provide such information through sets of possible scenarios which are designed to represent various uncertainty sources, including model uncertainties. A wide variety of methods have been proposed to estimate model uncertainties, among which perturbation methods targeting uncertain processes are a promising research field. In this study, we focus on the representation of small-scale variability by process-oriented perturbation schemes applied to two key physical processes, namely turbulence and shallow convection. The perturbations are applied to a single-column version of the convection-permitting AROME model, in three idealized boundary-layer cases. Large-eddy simulations (LESs) of the same cases serve as a reference for the subgrid variability that has to be represented, and the results are also compared to those given by the Stochastically Perturbed Parametrization Tendencies (SPPT) method, which is a method commonly used by weather forecast centres to represent model uncertainty. The spread produced by our process-oriented perturbations of turbulence and shallow convection does not represent all the small-scale variability implied by the LESs for temperature and humidity. However, it is of a similar order of magnitude for the wind, thanks to perturbations generated by the stochastic turbulence scheme. The dispersion is structurally different from what is obtained with SPPT. It is non-negligible in the lower levels, where SPPT perturbations are usually suppressed because of numerical instabilities, indicating a possible complementarity between the schemes. [ABSTRACT FROM AUTHOR]

A growing body of literature investigates convective organization, but few studies to date have sought to investigate how wind shear plays a role in the spatial organization of shallow (trade‐wind) convection. The present study hence investigates the morphology of precipitating marine cumulus convection using large‐eddy‐simulation experiments with zonal forward and backward shear and without shear. One set of simulations includes evaporation of precipitation, promoting cold‐pool development, and another set inhibits the evaporation of precipitation and thus cold‐pool formation. Without (or with only weak) subcloud‐layer shear, conditions are unfavorable for convective deepening, as clouds remain stationary relative to their subcloud‐layer roots so that precipitative downdrafts interfere with emerging updrafts. Under subcloud‐layer forward shear (FS), where the wind strengthens with height (a condition that is commonly found in the trades), clouds move at greater speed than their roots and precipitation falls downwind away from emerging updrafts. FS in the subcloud layer appears to promote the development of stronger subcloud circulations, with greater divergence in the cold‐pool area downwind of the original cell and larger convergence and stronger uplift at the gust front boundary. As clouds shear forward, a larger fraction of precipitation falls outside of clouds, leading to more moistening within the cold pool (gust front). Plain Language Summary: The most common type of clouds in Earth's trade wind regions are precipitating cumulus clouds with tops up to 4 km height. The precipitation from such clouds is frequent and intense enough to cause so‐called cold pools: cold and dry air that spreads out laterally near the surface in a circular fashion triggering new clouds in arc‐like patterns. We used a high‐resolution atmospheric model to investigate how the morphology of such clouds and the associated cold pools is affected by vertical changes in the wind speed (shear). When the wind speed at the surface and at cloud base is the same, clouds remain above their "roots," and downward‐moving air associated with rain falls into those cloud roots, which hinders the consequent deepening of these clouds. When the wind speed increases from the surface to cloud base (which it often does), clouds move away from their roots, which separates the location of updrafts and downdrafts, allowing for the development of deeper clouds. This type of shear also promotes the formation of new clouds further away at the edge of cold pools. Key Points: Without cold pools, new convection is triggered upwind of existing cells, and with cold pools, new convection is triggered downwindIn the absence of (or with only weak) subcloud‐layer shear, rain falls into emerging updrafts, hindering the convective developmentUplift at the cold‐pool gust fronts is strongest under subcloud‐layer forward shear (increasing wind speed with height) [ABSTRACT FROM AUTHOR]

The dominant modes of convection (vertical motion) in the tropical convective regions were explored using the EOF analysis method and the ERA-interim reanalysis data, with an emphasis on comparing their roles in transporting moisture and moist static energy (MSE). Two major types of convection orthogonal to each other were identified in the deep tropics, including deep and shallow convection. The deep convection, derived from the 1st EOF mode of vertical motion, shows different vertical structures (e.g., top-heavy versus bottom-heavy) under different thermodynamic environments (e.g., west versus east Pacific); while the shallow convection, derived from the 2nd EOF mode of vertical motion, exhibits opposite signs of vertical structure (e.g., positive and negative) between upper and lower troposphere. The two subtypes of deep convection exhibit distinct tendencies in moisture and MSE transport, i.e., while both import moisture into the atmosphere, the top-heavy one tends to export MSE, leading to a stabilized atmosphere; whereas the bottom-heavy counterpart inclines to import MSE, resulting in a destabilized atmosphere. On the contrary, the two subtypes of shallow convection display a consistent tendency in moisture and MSE transport, i.e., the positive shallow convection imports moisture and MSE; whereas the negative counterpart exports moisture and MSE. More importantly, the MSE transport by shallow convection (including positive and negative ones) can be comparable in size with the MSE transport by deep convection (including top-heavy and bottom-heavy ones), implying a non-negligible role played by shallow convection in charging and discharging the atmosphere in addition to the commonly recognized deep convection. [ABSTRACT FROM AUTHOR]

The East Sea (ES; Sea of Japan) meridional overturning circulation (MOC) serves as a crucial mechanism for the transportation of dissolved, colloidal, and suspended particulate matters, including pollutants, on the surface to deep waters via thermohaline circulation. Therefore, understanding the structure of the ES MOC is critical for characterizing its temporal and spatial distribution. Numerous studies have estimated these parameters indirectly using chemical tracers, severely limiting the accuracy of the results. In this study, we provide a method for directly estimating the turnover times of the ES MOC using the stream functions calculated from HYbrid Coordinate Ocean Model (HYCOM) reanalysis data by averaging the flow pattern in the meridional 2-D plane. Because the flow pattern is not consistent but various over time, three cases of stream function fields were computed over a 20-year period. The turnover time was estimated by calculating the time required for water particles to circulate along the streamlines. In the cases of multiple (two or three) convection cells, we considered all possible scenarios of the exchange of water particles between adjacent cells, so that they circulated over those cells until finally returning to the original position and completing the journey on the ES MOC. Three different cell cases were tested, and each case had different water particle exchange scenarios. The resulting turnover times were 17.91–58.59 years, 26.41–37.28 years, and 8.68–45.44 years for the mean, deep, and shallow convection cases, respectively. The maximum turnover time, namely 58.59 years, was obtained when circulating the water particle over all three cells, and it was approximately half of that estimated by the chemical tracers in previous studies (∼100 years). This underestimation arose because the streamlines and water particle movement were not calculated in the shallow (3,000 m) in this study. Regardless, the results of this study provide insight into the ES MOC dynamics and indicate that the traditional chemical turnover time represents only one of the various turnover scenarios that could exist in the ES.

Shallow clouds remain greatly significant in improving our understanding of the atmosphere. Using the Met Office Unified Model, we compare highly idealised simulations of shallow cumuli with those using more realistic domains, with open lateral boundaries and varying large‐scale forcing. We find that the realistic simulations are more capable of representing the cloud field on large spatial scales, and appear to limit the aerosol perturbations leading to impacts on the thermodynamic conditions. Aerosol perturbations lead to changes in the cloud vertical structure, and thermodynamic evolution of the idealised simulations; a central feature of behavior seen previously in idealised simulations. Modelling approaches with open boundaries and time‐varying forcing may allow for improved representation of shallow clouds in the atmosphere, and greater understanding of how they may respond to perturbations. Plain Language Summary: Clouds, and shallow clouds in particular, are responsible for much uncertainty in our understanding of the atmosphere, and the response of the climate system to anthropogenic perturbations. The representation of shallow clouds in models has long been a challenge due to the myriad processes and scales involved; from micrometer cloud droplets, to cloud fields of tens or hundreds of km, leading to many computational difficulties. Here we present and compare a number of simulations using different approaches. We show that certain modelling choices allow for an improved representation of shallow cloud fields on large scales, and also show a different response to aerosol perturbations, with implications for future development of estimations of the effects of aerosol on shallow clouds. Key Points: Simulations including time‐varying large‐scale forcing and open boundaries may improve representation of shallow cumulus fieldsAerosol effects on shallow cumuli may be constrained by large‐scale forcing, but nonetheless significantMet Office Unified Model (UM) allows for a variety of configurations to compare modelling approaches [ABSTRACT FROM AUTHOR]

Macrophysical and microphysical features of clouds and precipitation at coastal [20 m above Mean Sea Level (MSL)] and high‐altitude cloud physics observatory (HACPO; 1820 m above MSL) sites on the windward side of Western Ghats are examined using ground (Ceilometer and Disdrometer) and satellite‐based observations for the years 2017 and 2018 during the pre‐ and post‐monsoon seasons. Low‐ and high‐level clouds dominate over the coastal site, whereas at HACPO, middle‐level clouds dominate with a prominent diurnal cycle. Stratiform and convective raindrop size distributions (RSDs) show that nearly 80% of total precipitation was convective in both the seasons at the coastal site. The relative increase in mass‐weighted mean diameter (Dm), lower value of normalized intercept parameter (Nw) and higher mean cloud effective radius of ice and liquid phase imply deeper cloud formation in the site. But at HACPO, 54.85% of precipitation is evolved from the convective core and 45.15% from the stratiform core. Lower specific humidity, less liquid water content and weak convective available potential energy signify a dry environment which delimits vertical growth of orographic clouds in coherence with RSD variations having low Dm and high Nw with low rainwater content. Enhanced collision‐coalescence in the deep convective clouds sustained by strong updraft results in precipitation with high concentration of mid and large size drops at coastal site, whereas in HACPO, middle‐level clouds persist for longer periods favoring warm rain processes by shallow convection that cause smaller drops at the surface. Plain Language Summary: In the present study, we address the characteristics of clouds and raindrop size distributions (RSDs) over two physiographically distinct locations ‐ coastal and high‐altitude on the windward side of southern Western Ghats which acts as the gateway of Indian summer monsoon. The study gives a comprehensive understanding of precipitation microphysics as, in most instances, there is inadequate representation of clouds and precipitation mechanisms in weather forecasting model. Analysis of the study is performed using ground and satellite‐based observation data with a focus on pre‐ and post‐monsoon rainfall for the years 2017 and 2018 and revealed that low and high‐level clouds dominate over the coastal location in both the seasons and precipitation is evolved from multi‐layered clouds. While at the high‐altitude location middle‐level clouds are more frequent and single layer clouds contribute more to the total precipitation. The regional thermodynamic conditions and higher moisture availability at coastal location favor the formation of deep convective clouds. The variations in rain integral parameters derived from RSDs reveal convective type of precipitation at coastal location. The dry environment and weak updraft delimit the vertical growth of clouds at the high‐altitudes and the raindrop spectra evolves from shallow convective clouds. Key Points: Macrophysical and microphysical features of clouds and precipitation are investigated using ground and satellite‐based observationsCoastal station records formation of deeper clouds with higher concentration of medium and large size dropsMiddle‐level clouds initiate warm rain processes by shallow convection and generate smaller drops at the surface in high‐altitude location [ABSTRACT FROM AUTHOR]

Motivated by the abundance of low clouds in the subtropics, where the easterly trade winds prevail, we study the role of shallow convection in the momentum budget of the trades. To this end, we use ICON‐LEM hindcasts run over the North Atlantic for 12 days corresponding to the NARVAL1 (winter) and NARVAL2 (summer) flight campaigns. The simulation protocol consists of several nested domains, and we focus on the inner domains (≈100 × 100 km2) which have been run at resolutions of 150–600 m and are forced by analysis data, thus exhibiting realistic conditions. Combined, the resolved advection and the subgrid stresses decelerate the easterly flow over a frictional layer that balances the prevailing geostrophic wind forcing. Irrespective of the horizontal resolution, this layer is about 2 km deep in the strong winter trades and 1 km in summer, as winds and geostrophic forcing weaken and cloudiness reduces. The unresolved processes are strongest near the surface and are well captured by traditional K‐diffusion theory, but convective‐scale motions which are not considered in K‐diffusion theory contribute the most in the upper part of the mixed layer and are strongest just below cloud base. The results point out that convection in the mixed layer – the roots of trade‐wind cumuli and subcloud‐layer circulations – play an important role in slowing down easterly flow below cloud base (but little in the cloud layer itself), which helps make the zonal wind jet more distinct. Most of the friction within the clouds and near the wind jet stems from smaller‐scale turbulence stresses. [ABSTRACT FROM AUTHOR]

Abstract Motivated by an observed relationship between marine low cloud cover and surface wind speed, this study investigates how vertical wind shear affects trade‐wind cumulus convection, including shallow cumulus and congestus with tops below the freezing level. We ran large‐eddy simulations for an idealized case of trade‐wind convection using different vertical shears in the zonal wind. Backward shear, whereby surface easterlies become upper westerlies, is effective at limiting vertical cloud development, which leads to a moister, shallower, and cloudier trade‐wind layer. Without shear or with forward shear, shallow convection tends to deepen more, but clouds tops are still limited under forward shear. A number of mechanisms explain the observed behavior: First, shear leads to different surface wind speeds and, in turn, surface heat and moisture fluxes due to momentum transport, whereby the weakest surface wind speeds develop under backward shear. Second, a forward shear profile in the subcloud layer enhances moisture aggregation and leads to larger cloud clusters, but only on large domains that generally support cloud organization. Third, any absolute amount of shear across the cloud layer limits updraft speeds by enhancing the downward oriented pressure perturbation force. Backward shear—the most typical shear found in the winter trades—can thus be argued a key ingredient at setting the typical structure of the trade‐wind layer.

Motivated by an observed relationship between marine low cloud cover and surface wind speed, this study investigates how vertical wind shear affects trade‐wind cumulus convection, including shallow cumulus and congestus with tops below the freezing level. We ran large‐eddy simulations for an idealized case of trade‐wind convection using different vertical shears in the zonal wind. Backward shear, whereby surface easterlies become upper westerlies, is effective at limiting vertical cloud development, which leads to a moister, shallower, and cloudier trade‐wind layer. Without shear or with forward shear, shallow convection tends to deepen more, but clouds tops are still limited under forward shear. A number of mechanisms explain the observed behavior: First, shear leads to different surface wind speeds and, in turn, surface heat and moisture fluxes due to momentum transport, whereby the weakest surface wind speeds develop under backward shear. Second, a forward shear profile in the subcloud layer enhances moisture aggregation and leads to larger cloud clusters, but only on large domains that generally support cloud organization. Third, any absolute amount of shear across the cloud layer limits updraft speeds by enhancing the downward oriented pressure perturbation force. Backward shear—the most typical shear found in the winter trades—can thus be argued a key ingredient at setting the typical structure of the trade‐wind layer. Plain Language Summary: We used a high‐resolution weather model to investigate the influence of the shape of the wind profile (i.e., whether the wind blows faster, slower, or with the same velocity at greater altitudes compared to the surface) on shallow cumulus clouds typical of the North Atlantic trade‐wind region. In this region, easterly winds that decrease with height (and eventually turn westerly) are most common. Generally, the surface winds are also affected by how the wind blows further aloft, influencing what kind of clouds form. But even when we eliminate this effect in our study, we find that when the wind blows faster or slower at greater heights, clouds are not only tilted but also wider and both effects increase the overall cloud cover. Furthermore, if the wind speed changes with height, the updraft speed within clouds is diminished, which potentially decreases the height of clouds. However, if the wind speed increases with height (which only rarely occurs in the trades), clouds tend to cluster more, which "offsets" the weaker updrafts and thus still allows for deeper clouds. Key Points: Shear in the zonal wind influences cloud‐top heights via the effect of momentum transport on the surface wind and surface fluxesBackward shear (surface easterlies turn westerlies) lowers cloud tops and shallows and moistens the trade‐wind layerAny absolute amount of wind shear limits in‐cloud updraft speeds and enhances low‐level cloud fraction [ABSTRACT FROM AUTHOR]

Abstract Assumed‐PDF (probability density function) higher‐order turbulence closures (APHOCs) are now widely used for parameterizing boundary layer turbulence and shallow convection in Earth system models (ESMs). A better understanding of the resolution‐dependent behavior of APHOCs is essential for improving the performance of next‐generation ESMs with intended horizontal resolutions finer than 10 km. In this study, we evaluate the PDF family of Analytic double‐Gaussian 1 implemented in Cloud Layers Unified By Binormals (CLUBB) over a range of spatial scales (Dx) from 2 to 100 km. A 120‐km‐wide large eddy simulation (LES) for a continental convection case during 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land‐Ecosystems (HI‐SCALE) field campaign serves as benchmark to evaluate the PDF closure using an off‐line approach. We find during the shallow convection period, the CLUBB PDF closure tends to produce positive biases of cloud properties and liquid water flux near cloud base for all scales of analysis. It produces negative biases for these variables near cloud top that are more severe for Dx larger than 25 km. Results show that replacing the CLUBB‐parameterized moisture and temperature skewnesses with LES‐derived ones can fix most of the biases if clipping of input moments is allowed to prevent the occurrence of unrealizable solutions. Overall, the performance of the PDF closure is better for smaller Dx = 2–5 km than for larger Dx = 50–100 km; for a given grid spacing, it is better when the convective clouds become deeper in the late afternoon. Likely causes for the resolution dependence and implications for improving the PDF closure are discussed.

Assumed‐PDF (probability density function) higher‐order turbulence closures (APHOCs) are now widely used for parameterizing boundary layer turbulence and shallow convection in Earth system models (ESMs). A better understanding of the resolution‐dependent behavior of APHOCs is essential for improving the performance of next‐generation ESMs with intended horizontal resolutions finer than 10 km. In this study, we evaluate the PDF family of Analytic double‐Gaussian 1 implemented in Cloud Layers Unified By Binormals (CLUBB) over a range of spatial scales (Dx) from 2 to 100 km. A 120‐km‐wide large eddy simulation (LES) for a continental convection case during 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land‐Ecosystems (HI‐SCALE) field campaign serves as benchmark to evaluate the PDF closure using an off‐line approach. We find during the shallow convection period, the CLUBB PDF closure tends to produce positive biases of cloud properties and liquid water flux near cloud base for all scales of analysis. It produces negative biases for these variables near cloud top that are more severe for Dx larger than 25 km. Results show that replacing the CLUBB‐parameterized moisture and temperature skewnesses with LES‐derived ones can fix most of the biases if clipping of input moments is allowed to prevent the occurrence of unrealizable solutions. Overall, the performance of the PDF closure is better for smaller Dx = 2–5 km than for larger Dx = 50–100 km; for a given grid spacing, it is better when the convective clouds become deeper in the late afternoon. Likely causes for the resolution dependence and implications for improving the PDF closure are discussed. Plain Language Summary: Accurate representation of planetary boundary layer (PBL) and convection processes is important for Earth system models. APHOC (assumed probability density function [PDF] higher‐order turbulence closure) has proven to be a useful approach for representing PBL and shallow convection. With applying APHOC to atmospheric models with resolutions ranging from several kilometers to several hundred kilometers, it is important to understand the behavior of APHOC under changing resolution. This study uses a very high resolution simulation of continental convection to test how the assumed PDF in one type of APHOC called CLUBB (Cloud Layers Unified By Binormals) behaves with changing resolution. We found some persistent biases near the bottom and top of cloud layer but also a deteriorating trend in overall performance with decreasing resolution. Key Points: A nested large‐domain WRF LES is used to evaluate the PDF closure in CLUBB for a continental convection case across 2‐ to 100‐km spatial scalesCLUBB PDF closure underestimates cloud base height due to the parameterization of temperature and moisture skewnessesOverall CLUBB PDF closure performs better at finer spatial scale than at coarser spatial scale [ABSTRACT FROM AUTHOR]

Trade‐wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as flowers, fish, gravel, and sugar. We show that these four patterns can be identified objectively from satellite observations by analyzing the spatial distribution of infrared brightness temperatures. By applying this analysis to 19 years of data, we examine relationships between cloud patterns and large‐scale environmental conditions. This investigation reveals that on daily and interannual timescales, the near‐surface wind speed and the strength of the lower‐tropospheric stability discriminate the occurrence of the different organization patterns. These results, combined with the tight relationship between cloud patterns, low‐level cloud amount, and cloud‐radiative effects, suggest that the mesoscale organization of shallow clouds might change under global warming. The role of shallow convective organization in determining low‐cloud feedback should thus be investigated. Plain Language Summary: Satellite imagery shows that clouds in the trade‐wind regions exhibit a large diversity of patterns. Over the tropical Atlantic close to Barbados, the population of low‐level clouds can organize in different ways, adopting patterns evocatively referred to as "flowers","fish" ,"gravel," and "sugar." This study shows that these different patterns, originally identified subjectively, can be recognized more objectively from space measurements of infrared radiation. It also shows that the relative occurrence of these different patterns relates to the strength of the trade winds near the ocean surface and to the stability of the lower atmosphere. Finally, it shows that each pattern is associated with a different cloud amount and thus impacts the radiative cooling of the Earth differently. These results suggest that under global warming, the change in environmental conditions might perturb the frequency of different patterns, which might affect the Earth's radiative response to warming in a way that has not been previously considered. Key Points: Prominent mesoscale patterns of shallow convection are identified from satellite observationsMesoscale patterns exhibit strong relationships with surface wind speed and lower‐tropospheric stabilityOwing to their differences in low‐cloud fraction, mesoscale patterns exert different impacts on the top‐of‐atmosphere radiation budget [ABSTRACT FROM AUTHOR]

The third version of the Nanjing University of Information Science and Technology (NUIST) Earth System Model (NESM3.0) has been recently developed for sub-seasonal to seasonal climate prediction and projection of future climate change. This requires realistic simulation of both internal modes of climate variability and global energy balance and climate sensitivity. In the historical experiments based on the coupled model intercomparison project (CMIP6) forcings, the original version of NESM3.0 does a reasonably good job in capturing warming trends and climate sensitivity to external forcing, but not in simulating climatology and climate variability. For our project we modified the deep and shallow convective scheme, cloud cover, and cloud microphysics in the atmospheric model. We then conducted hundreds of experiments to test the results in the fully coupled model with comprehensive metrics to ensure that any individual targeted improvement does not affect the overall performance. The modifications in moist physics improved the model's climatology and internal variability significantly without degrading global energy balance and climate sensitivity. The key was to reduce the model's warm sea surface temperature (SST) bias and associated excessive precipitation bias in the tropics by reducing convective precipitation and increasing large-scale stable precipitation. This effort leads to more realistic simulation of the zonal mean circulation and temperature structure, global monsoon, and ocean salinity. The El Niño Southern Oscillation (ENSO) simulation was improved by reducing wind stress biases associated with ENSO in the central and eastern Pacific. Better ENSO leads to better teleconnection in mid-latitudes, particularly over the North Pacific and Atlantic Ocean. The eastward propagation of the Madden–Julian Oscillation (MJO) was significantly improved by enhancing the interaction between the boundary layer and lower tropospheric heating. These results suggest that improvement in moist physical parameterizations is an effective way to improve simulation of climatology and major modes of internal variability without degrading the global energy balance and climate sensitivity in the historical run. [ABSTRACT FROM AUTHOR]

The distribution of mass flux at the cloud base has long been thought to be independent of large‐scale forcing. However, recent idealized modelling studies have revealed its dependence on some large‐scale conditions. Such dependence makes it possible to isolate the observed large‐scale conditions, which are similar to those in large‐eddy simulations (LES), in order to compare the observed and modelled mass flux distributions. In this study, we derive for the first time the distribution of the cloud‐base mass flux among individual shallow cumuli from ground‐based observations at the Barbados Cloud Observatory (BCO) and compare it with the Rain In Cumulus over the Ocean (RICO) LES case study. The procedure of cloud sampling in LES mimics the pointwise measurement procedure at the BCO to provide a mass flux metric that is directly comparable with observations. We find a difference between the mass flux distribution observed during the year 2017 at the BCO and the distribution modelled by LES that is comparable to the seasonal changes in the observed distribution. This difference between the observed and modelled distributions is diminished and an extremely good match is found by subsampling the measurements under a similar horizontal wind distribution and area‐averaged surface Bowen ratio to those modelled in LES. This provides confidence in our observational method and shows that LES produces realistic clouds that are comparable to those observed in nature under the same large‐scale conditions. We also confirm that the stronger horizontal winds and higher Bowen ratios in our case study shift the distributions to higher mass flux values, which is coincident with clouds of larger horizontal areas and not with stronger updrafts. [ABSTRACT FROM AUTHOR]

In this study we use large‐eddy simulation to explore the factors controlling stratiform cloudiness in the downstream trades. We perform sensitivity experiments with different large‐scale forcings, radiation specifications and domain sizes, which isolate the influence of convective deepening, moisture–radiation interactions and mesoscale organization, respectively. Across the simulations with different large‐scale forcings, we find that the deepening of the cloud layer and the associated increase in precipitation strongly correlate with decreasing inversion strength and stratiform cloudiness. The relationship between cloud‐layer depth and cloud amount is largely independent of the way a specific change in the large‐scale forcing induces the deepening. The interaction of radiation with the domain‐averaged humidity and cloud profile is necessary for stratiform cloudiness to form. Strong radiative cooling experienced by updraughts overshooting a strong inversion induces the formation of detrained stratiform layers, and strong long‐wave cooling associated with the stratiform layers stabilizes the inversion. Interactive radiation is also important for exposing differences in shallow convection under different free‐tropospheric humidities. A drier initial free troposphere leads to both increased cloud‐layer and free‐tropospheric radiative cooling and increased surface evaporation, which forces deeper convection and more precipitation compared to a moister initial free troposphere. The simulations with a drier initial free troposphere thus have weaker inversions and less stratiform cloud. The organization of convection into larger clusters in large‐domain simulations increases precipitation and weakens the inversion compared to a simulation on a 16‐fold smaller domain, which does not support convective organization. Organized updraught clusters carry more moisture and liquid to the inversion, so that the same amount of stratiform cloudiness forms, despite the inversion being weaker. The simulations presented here suggest that the deepening and organization of shallow convection plays an important role in regulating stratiform cloudiness and thus total cloud cover in the downstream trades. [ABSTRACT FROM AUTHOR]

An activity designed to characterise patterns of mesoscale (20 to 2,000 km) organisation of shallow clouds in the downstream trades is described. Patterns of mesoscale organisation observed from space were subjectively defined and learned by 12 trained scientists. The ability of individuals to communicate, learn and replicate the classification was evaluated. Nine‐hundred satellite images spanning the area from 48°W to 58°W, 10°N to 20°N for the boreal winter months (December–February) over 10 years (2007/2008 to 2016/2017) were classified. Each scene was independently labelled by six scientists as being dominated by one of six patterns (one of which was "no‐pattern"). Four patterns of mesoscale organisation could be labelled in a reproducible manner, and were labelled Sugar, Gravel, Fish and Flowers. Sugar consists of small, low clouds of low reflectivity, Gravel clouds form along apparent gust fronts, Fish are skeletal networks (often fishbone‐like) of clouds, while Flowers are circular clumped features defined more by their stratiform cloud elements. Both Fish and Flowers are surrounded by large areas of clear air. These four named patterns were identified 40% of the time, with the most common pattern being Gravel. Sugar was identified the least and suggests that unorganised and very shallow convection is unlikely to dominate large areas of the downstream trade winds. Some of the patterns show signs of seasonal and interannual variability, and some degree of scale selectivity. Comparison of typical patterns with radar imagery suggests that even this subjective and qualitative visual inspection of imagery appears to capture several important physical differences between shallow cloud regimes, such as precipitation and radiative effects. [ABSTRACT FROM AUTHOR]

The key assumption underlying convection parameterizations is that rising plumes develop in a horizontally homogeneous environment. With this in mind, we investigate the impact of environmental cloud layer heterogeneities on shallow convection using large‐eddy simulation that applies a master‐slave methodology. In the master‐slave approach, two independent sets of thermodynamic variables (master and slave) are driven by one dynamics (coupled with the master) to remove the impact of internal variability of the dynamical system considered. The two thermodynamic sets include either a realistic heterogeneous environment or an environment that is homogenized outside clouds. The key is that homogenization also excludes subsiding shells surrounding cumulus clouds. The results show a small impact of the homogenization on cloud field properties. The physical explanation highlights the role of the subsiding shell shielding a shallow cumulus cloud from its environment. Plain Language Summary: Coarse‐resolution weather and climate models need to use convection parameterizations for representing vertical transport by ascending plumes or bubbles. Those parameterizations typically assume that convective elements develop in a homogeneous environment. This key assumption was recently questioned in a study showing that plume properties critically depend on the local environment in which they rise. The current study revisits this assumption by explicitly simulating the development of shallow convective clouds using a method that facilitates comparing the same portions of cloudy air undergoing two different scenarios: mixing either with a heterogeneous or homogeneous environment. The results highlight an insignificant impact of environmental temperature and moisture perturbations on the cloud development and strongly support the homogeneous environment assumption in convection parameterizations. Key Points: The impact of environmental heterogeneities on the development of shallow convection is quantified using large‐eddy simulationThe master‐slave method is used to show that presence or absence of heterogeneities has little impact on the cloud developmentThe heterogeneities can thus be neglected in shallow convection parameterizations [ABSTRACT FROM AUTHOR]

In current operational numerical weather prediction models, the effect of shallow convection is parametrized. The grey zone of shallow convection is found between the horizontal resolutions of mesoscale numerical models (2-3 km) and large-eddy simulations (10-100 m or finer). At these horizontal scales the shallow convection is to some extent explicitly resolved by the model. The shallow-convection parametrization is still needed, but has to be regulated according to the model horizontal resolution. Here the behaviour of the non-hydrostatic mesoscale numerical weather prediction model Application of Research to Operations at Mesoscale is examined in the grey zone and a new scale-adaptive surface closure of its shallow-convection parametrization, dependent on horizontal resolution, is defined based on large-eddy simulation. The new closure is tested on a series of numerical experiments and validated on a 15-day-long real case period. Its impact on the development of deep convection is examined in detail. The idealized simulations show promising results, as the mean profiles of the subgrid and resolved turbulence change in the desired way. Based on the real case tests our modification has a low impact on model performance, but is part of a set of upgrades of the current parametrization that is aimed to treat the shallow convection grey zone. [ABSTRACT FROM AUTHOR]

The physical mechanism of low‐cloud feedbacks is examined by using perturbed‐parameter ensemble experiments in a unified scheme of boundary layer turbulence and shallow convection, named Cloud Layers Unified by Binormals (CLUBB) coupled to Community Atmosphere Model version 5 (CAM5). The shortwave cloud feedbacks in CAM5‐CLUBB are positive in the most stable tropical regime, which is related to the weaker turbulence in the planetary boundary layer (PBL) in a warmer climate that is possibly triggered by the strengthened stability of the cloud layer. The positive feedback between low cloud cover (LCC), cloud top radiative cooling, and PBL turbulent mixing may further enhance the decrease in LCC. The stronger inversion stability of PBL partly counters the decrease in LCC, and a recently developed index, the estimated cloud‐top entrainment index, is a better predictor for LCC changes than conventional stability indices. The relative strength of shallow convection increases in the warmer climate, but its effect on low‐cloud feedback is complicated by the unified treatment of shallow convection and PBL turbulence in CLUBB. Stronger shallow convection means more convective drying but also less PBL turbulence and less LCC in the present climate, which leads to less reduction in LCC. The parameters related to dynamic turbulent structure and double Gaussian closure in CLUBB are the most influential parameters on low‐cloud feedbacks. Our results suggest that a unified treatment of shallow convection and turbulence may give rise to the predominate role of the PBL turbulent mixing in determining low‐cloud feedback. Plain Language Summary: Low‐cloud feedbacks are examined in a unified scheme of boundary layer turbulence and shallow convection (Cloud Layers Unified by Binormal) by using perturbed‐parameter ensemble experiments. The shortwave low‐cloud feedbacks are found to be positive in the most stable cloud regime, which is related to the weaker turbulence in the planetary boundary layer (PBL) in a warmer climate. The relative strength of shallow convection increases in the warmer climate, but its effect on low‐cloud feedback is complicated by the unified treatment of shallow convection and PBL turbulence in Cloud Layers Unified by Binormal. The stronger inversion stability of PBL partly counters the decrease in low cloud cover, and a recently developed index, the estimated cloud‐top entrainment index, is a better predictor for low cloud cover changes than conventional stability indices. Our results suggest that a unified treatment of shallow convection and turbulence may give rise to the predominate role of the PBL turbulent mixing in determining low‐cloud feedback. Key Points: A unified turbulence and shallow convection scheme produces a positive low‐cloud feedbackThe positive low‐cloud feedback is related to the weaker turbulence in the planetary boundary layerThe effect of shallow convection on low‐cloud feedback is complicated in this unified scheme [ABSTRACT FROM AUTHOR]

A new configuration of a parameterization for shallow convection in the Icosahedral Nonhydrostatic Model (ICON) is described and tested on a single realistic test case. As a test case, a shallow convective day over Germany is simulated using four different configurations of ICON. These configurations differ by the choice of the shallow convection parameterization, which can be deterministic, stochastic, or completely switched off. As the fourth configuration, the ICON large eddy simulation setup is used as a reference against which the three other ICON model configurations are tested and compared at resolutions from 1 to 10 km. It is demonstrated that a deterministic mass flux closure combined with the stochastic sampling of the cloud base mass fluxes corrects the spatial and temporal distribution of cloudiness. The mean vertical structure of the cloud layer and vertical profiles of the thermodynamic variables in the boundary layer are also improved. The stochastic parameterization adapts to the model resolution by its formulation, while a limited scale‐aware behavior is present in the outcome of the simulations. This limitation stems from the resolution dependence of the resolved dynamics, which produces incorrect distributions of cloudiness, and scale‐dependence opposite of what is expected based on the reference large eddy simulation results. The deterministic version of the convection scheme cannot correct the behavior of the resolved dynamics, while the stochastic version corrects the resolved dynamics to some extent and improves the overall behavior across resolutions. Key Points: A new implementation of a stochastic shallow convection parameterization is presented and tested on a realistic case using the ICON modelThe distributions of cloud cover and liquid water path are significantly improved by introducing stochastic perturbationsThe resolved convective circulation regime is partly corrected by the new formulation of the shallow convection across kilometer‐scale resolutions [ABSTRACT FROM AUTHOR]