Shallow Convection Case Research Articles

Shallow Convection Dataset Simulated by Three Different Large Eddy Models

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.

Parameterization of Stochastically Entraining Convection Using Machine Learning Technique

AbstractA stochastic mixing model with a machine learning technique is proposed for mass flux convection schemes. The model consists of the stochastic differential equations (SDEs) for the fractional entrainment rate, fractional detrainment rate, fractional dilution rate, and vertical acceleration. Unknowns in SDEs are parameterized using a deep neural network with the inputs of cloud and environment properties. The deep neural network is found to predict entrainment and detrainment rates better than previously proposed parameterizations. The new mixing model is implemented in a unified convection scheme (UNICON) and tested in a single‐column mode for two marine shallow convection cases. It is shown that the simulations with the new mixing model produce realistic mean and variance of various convective updraft properties and that the appropriate amount of stochasticity is generated. Consistently accurate simulations of updraft mass fluxes and moist conserved variables reduce model errors in the original UNICON. Additional sensitivity simulations enabling or disabling the stochasticity in mixing and initialization suggest that most of the cloud variabilities are generated from the mixing process.

Turnover Time of the East Sea (Sea of Japan) Meridional Overturning Circulation

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 (<300 m) and deep areas (>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.

A Stochastic Unified Convection Scheme (UNICON). Part I: Formulation and Single-Column Simulation for Shallow Convection

AbstractBy extending the previously developed unified convection scheme (UNICON), we develop a stochastic UNICON with convective updraft plumes at the surface randomly sampled from the correlated multivariate Gaussian distribution for updraft vertical velocity w^ and thermodynamic scalars ϕ^, of which standard deviations and intervariable correlations are derived from the surface-layer similarity theory. The updraft plume radius R^ at the surface follows a power-law distribution with a specified scale break radius. To enhance computational efficiency, we also develop a hybrid stochastic UNICON consisting of n bin plumes and a single stochastic plume, each of which mainly controls the ensemble mean and variance of grid-mean convective tendency, respectively. We evaluated the stochastic UNICON using the large-eddy simulation (LES) of the Barbados Oceanographic and Meteorological Experiment (BOMEX) shallow convection case in a single-column mode. Consistent with the assumptions in the stochastic UNICON, the LES w^ and ϕ^ at the surface follow approximately the half- and full-Gaussian distributions, respectively. LES showed that a substantial portion of the variability in ϕ^ at the cloud base stems from the surface, which also supports the concept of stochastic UNICON that simulates various types of moist convection based on the dry stochastic convection launched from the surface. Overall, stochastic UNICON adequately reproduces the LES grid-mean thermodynamic states as well as the mean and variance of ϕ^, including their dependency on the domain size and R^. A sensitivity test showed that the perturbations of ϕ^ as well as R^ at the surface are important for the correct simulation of the grid-mean thermodynamic states.

The Impact of Surface Heterogeneities and Land‐Atmosphere Interactions on Shallow Clouds Over ARM SGP Site

AbstractContinental shallow clouds are an important component of the land‐atmosphere coupled climate system because of their role in modulating energy and water budgets. The parameterization of these clouds in climate models presents a significant challenge. We evaluate the potential impact of subgrid‐scale (for climate models) land‐atmosphere interactions on shallow clouds using nested large‐eddy simulations (LESs). We compare LESs that allow for land‐atmosphere interactions to ones that artificially suppress all or part of them by smoothing out surface heterogeneities in surface heat, moisture and radiation fluxes within the domain. The LES domains are coupled to an interactive land surface model and nested inside a mesoscale domain. Three summertime shallow convection cases over the Department of Energy Atmospheric Radiation Measurement Facility's Southern Great Plains site are examined. A consistent increase in cloud water content is observed in all cases when surface heterogeneities and the land‐atmosphere interactions they induce in the LES domain are removed. By comparing experiments where only surface flux heterogeneities induced by cloud shadows are removed to ones where all surface flux heterogeneities are removed, we find that cloud shading‐induced surface heterogeneities can have a larger impact on shallow convection than static land surface heterogeneities in our cases. Furthermore, the impact of cloud shading on cloud water content and cloud size is found to vary significantly with the solar incidence angle. Our results suggest that the impact of cloud shadows needs to be considered when parameterizing land‐atmosphere interactions in the presence of shallow clouds for regional or global climate models.

The effects of turbulent collision–coalescence on precipitation formation and precipitation-dynamical feedbacks in simulations of stratocumulus and shallow cumulus convection

Abstract. A double moment warm rain scheme that includes the effects of turbulence on droplet collision rates has been implemented in a large-eddy model to investigate the impact of turbulence effects on clouds and precipitation. Simulations of shallow cumulus and stratocumulus show that different precipitation-dynamical feedbacks occur in these regimes when the effects of turbulence are included in the microphysical processes. In both cases inclusion of turbulent microphysics increases precipitation due to a more rapid conversion of cloud water to rain. In the shallow convection case, the greater water loading in the upper cloud levels reduces the buoyancy production of turbulent kinetic energy and the entrainment. The stratocumulus case on the other hand shows a weak positive precipitation feedback, with enhanced rainwater producing greater evaporation, stronger circulations and more turbulence. Sensitivity studies in which the cloud droplet number was varied show that greater number concentrations suppress the stratocumulus precipitation leading to larger liquid water paths. This positive second indirect aerosol effect shows no sensitivity to whether or not the effects of turbulence on droplet collision rates are included. While the sign of the second indirect effect is negative in the shallow convection case whether the effects of turbulence are considered or not, the magnitude of the effect is doubled when the turbulent microphysics are used. It is found that for these two different cloud regimes turbulence has a larger effect than cloud droplet number and the use of a different bulk microphysics scheme on producing rainfall in shallow cumuli. However, for the stratocumulus case examined here, the effects of turbulence on rainfall are not statistically significant and instead it is the cloud droplet number concentration or the choice of bulk microphysics scheme that has the largest control on the rain water.

Vertical velocity in shallow convection for different plume types

AbstractThis study investigates the bulk budgets of the vertical velocity and its parameterization in convective cores, convective updrafts, and clouds by using large‐eddy simulation (LES) of four shallow convection cases in the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) programs. The relative magnitudes of the dominant momentum budget terms for the three types of plumes are presented. For all shallow cumulus except stratocumulus, the buoyancy force and the subplume transport in the core plume are the momentum source that offset the pressure gradient force. In the cloud updraft and cloud plumes, the buoyancy source is dominant in the lower and middle parts of the clouds, while the subgrid transport is a dominant source in the upper part, and the entrainment term is also a momentum source. For the stratocumulus, the subplume transport is a sink almost in the whole convective layer. For all types of plumes, the Simpson and Wiggert (1969) equation is found to be good paramaterization of the mean plume vertical velocity when appropriate scaling coefficients to buoyancy and entrainment terms are used. Optimal forms of the Simpson and Wiggert equation are given for convective cores, convective updrafts, and convective clouds. Results are compared with other studies published in the literature.

Homogeneity of the Subgrid-Scale Turbulent Mixing in Large-Eddy Simulation of Shallow Convection

Abstract This paper presents an approach to locally predict homogeneity of the subgrid-scale turbulent mixing in large-eddy simulation of shallow clouds applying double-moment warm-rain microphysics. The homogeneity of subgrid-scale mixing refers to the partitioning of the cloud water evaporation due to parameterized entrainment between changes of the mean droplet radius and changes of the mean droplet concentration. Homogeneous and extremely inhomogeneous mixing represent two limits of possible scenarios, where the droplet concentration and the mean droplet radius remains unchanged during the microphysical adjustment, respectively. To predict the subgrid-scale mixing scenario, the double-moment microphysics scheme is merged with the approach to delay droplet evaporation resulting from entrainment. Details of the new scheme and its application in the Barbados Oceanographic and Meteorological Experiment (BOMEX) shallow convection case are discussed. The simulated homogeneity of mixing varies significantly inside small convective clouds, from close to homogeneous to close to extremely inhomogeneous. The mean mixing characteristics become more homogeneous with height, reflecting increases of the mean droplet size and the mean turbulence intensity, both favoring homogeneous mixing. Model results are consistent with microphysical effects of entrainment and mixing deduced from field observations. Mixing close to homogeneous is predicted in volumes with the highest liquid water content (LWC) and strongest updraft at a given height, whereas mixing in strongly diluted volumes is typically close to extremely inhomogeneous. The simulated homogeneity of mixing has a small impact on mean microphysical characteristics. This result agrees with the previous study applying prescribed mixing scenarios and can be explained by the high humidity of the clear air involved in the subgrid-scale mixing.

A cloud chemistry module for the 3-D cloud-resolving mesoscale model Meso-NH with application to idealized cases

Abstract. A complete chemical module has been developed for use in the Meso-NH three-dimensional cloud resolving mesoscale model. This module includes gaseous- and aqueous-phase chemical reactions that are analysed by a pre-processor generating the Fortran90 code automatically. The kinetic solver is based on a Rosenbrock algorithm, which is robust and accurate for integrating stiff systems and especially multiphase chemistry. The exchange of chemical species between the gas phase and cloud droplets and raindrops is computed kinetically by mass transfers considering non-equilibrium between the gas- and the condensed phases. Microphysical transfers of chemical species are considered for the various cloud microphysics schemes available, which are based on one-moment or two-moment schemes. The pH of the droplets and of the raindrops is diagnosed separately as the root of a high order polynomial equation. The chemical concentrations in the ice phase are modelled in a single phase encompassing the two categories of precipitating ice particles (snow and graupel) of the microphysical scheme. The only process transferring chemical species in ice is retention during freezing or riming of liquid hydrometeors. Three idealized simulations are reported, which highlight the sensitivity of scavenging efficiency to the choice of the microphysical scheme and the retention coefficient in the ice phase. A two-dimensional warm, shallow convection case is used to compare the impact of the microphysical schemes on the temporal evolution and rates of acid precipitation. Acid wet deposition rates are shown to be overestimated when a one-moment microphysics scheme is used compared to a two-moment scheme. The difference is induced by a better prediction of raindrop radius and raindrop number concentration in the latter scheme. A two-dimensional mixed-phase squall line and a three-dimensional mixed-phase supercell were simulated to test the sensitivity of cloud vertical transport to the retention efficiency of gases in the ice phase. The 2-D and 3-D simulations illustrate that the retention in ice of a moderately soluble gas such as formaldehyde substantially decreases its concentration in the upper troposphere. In these simulations, retention of highly soluble species in the ice phase significantly increased the wet deposition rates.

A Probabilistic Bulk Model of Coupled Mixed Layer and Convection. Part II: Shallow Convection Case

Abstract The probabilistic bulk convection model (PBCM) developed in a companion paper is here extended to shallow nonprecipitating convection. The PBCM unifies the clear-sky and shallow convection boundary layer regimes by obtaining mixed-layer growth, cloud fraction, and convective inhibition from a single parameterization based on physical principles. The evolution of the shallow convection PBCM is based on the statistical distribution of the surface thermodynamic state of convective plumes. The entrainment velocity of the mixed layer is related to the mass flux of the updrafts overshooting the dry inversion capping the mixed layer. The updrafts overcoming the convective inhibition generate active cloud-base mass flux, which is the boundary condition for the shallow cumulus scheme. The subcloud-layer entrainment velocity is directly coupled to the cloud-base mass flux through the distribution of vertical velocity and fractional cover of the updrafts. Comparisons of the PBCM against large-eddy simulations from the Barbados Oceanographic and Meteorological Experiment (BOMEX) and from the Southern Great Plains Atmospheric Radiation Measurement Program (ARM) facility demonstrate good agreement in terms of thermodynamic structure, cloud-base mass flux, and cloud top. The equilibrium between the cloud-base mass flux and rate of growth of the mixed layer determines the equilibrium convective inhibition and cloud cover. This process is an important new insight on the coupling between the mixed-layer and cumulus dynamics. Given its relative simplicity and transparency, the PBCM represents a powerful tool for developing process-based understanding and intuition about the physical processes involved in boundary layer–convection interactions, as well as a test bed for diagnosing and validating shallow convection parameterizations.

A Warm-Bin–Cold-Bulk Hybrid Cloud Microphysical Model*

AbstractThis study describes a newly developed bin–bulk hybrid cloud microphysical model named MSSG-Bin, which has been implemented in the Multi-Scale Simulator for the Geoenvironment (MSSG). In the hybrid approach, a spectral bin scheme is used for liquid droplets, while a bulk scheme is used for solid particles. That is, the expensive but more reliable spectral bin scheme treats the relatively well-understood physics of the liquid phase, and the computationally efficient but less robust bulk scheme is used to treat the poorly understood physics of the ice phase. In the bulk part, the prognostic variables are the mixing ratios of cloud ice, snow, and graupel and the number density of cloud ice particles. The bulk component is consistent with MSSG-Bulk, which is a conventional bulk model implemented in MSSG. One-dimensional kinetic simulations and three-dimensional cloud simulations have confirmed the reliability of MSSG-Bin for warm clouds, free from the approximations made in bulk parameterizations, and its applicability to cold clouds, without the significant additional costs required for a bin treatment of the ice phase. Compared with MSSG-Bulk, MSSG-Bin with 33 bins requires 8.3 times more floating-point operations for a one-dimensional shallow convection case, and 4.9 times more for a three-dimensional shallow convection case. Present results have shown the feasibility of using this model for a 25-m-resolution simulation of shallow cumulus on a 512 × 512 × 200 grid.

Analytical expressions for entrainment and detrainment in cumulus convection

AbstractAnalytical expressions for entrainment and detrainment are derived based on general total water specific humidity and mass budget equations. From these expressions, containing a small‐scale turbulent and a larger‐scale organized term, a physical picture emerges for a shallow cumulus cloud ensemble in which the individual clouds have a massive entrainment at the bottom, lateral turbulent mixing with constant mass flux between bottom and top, and massive detrainment at the top. Combining these results with the general budget equation for vertical velocity, new formulae for entrainment and detrainment rates can be expressed in terms of buoyancy, vertical velocity and cloud fraction. For a variety of shallow convection cases, results from large‐eddy simulations show a good correspondence of these new formulae with more traditional methods to diagnose entrainment and detrainment rates. Moreover, the formulae give insight into the behaviour and the physical nature of the mixing coefficients. They explain the observed large variability of the detrainment. The formulae cannot be directly applied as a parametrization. However, it is demonstrated how they can be used to evaluate existing parametrization approaches and as a sound physical base for future parametrization developments. Copyright © 2010 Royal Meteorological Society