scholarly journals A Cloud-Base Quasi-Balance Constraint for Parameterized Convection: Application to the Kain–Fritsch Cumulus Scheme

2005 ◽  
Vol 133 (11) ◽  
pp. 3315-3334 ◽  
Author(s):  
James A. Ridout ◽  
Yi Jin ◽  
Chi-Sann Liou
Keyword(s):  
Great Plains ◽  
Mass Flux ◽  
Deep Convection ◽  
Convective Cloud ◽  
Cumulus Parameterization ◽  
Precipitation Forecast ◽  
Cloud Base ◽  
Naval Research ◽  
Supporting Evidence ◽  
Skill Scores

Abstract A quasi balance with respect to parcel buoyancy at cloud base between destabilizing processes and convection is imposed as a constraint on convective cloud-base mass flux in a modified version of the Kain–Fritsch cumulus parameterization. Supporting evidence is presented for this treatment, showing a cloud-base quasi balance (CBQ) on a time scale of approximately 1–3 h in explicit simulations of deep convection over the U.S. Great Plains and over the tropical Pacific Ocean with the Naval Research Laboratory’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS).1 With the exception of the smaller of two convective events in the Great Plains simulation, a CBQ is still observed upon restriction of the data analysis to instances where the available buoyant energy (ABE) exceeds a threshold value of 1000 J kg−1. This observation is consistent with the view that feedbacks between convection and cloud-base parcel buoyancy can control the rate of convection on shorter time scales than those associated with the elimination of buoyant energy and supports the addition of a CBQ constraint to the Kain–Fritsch mass-flux closure. Tests of the modified Kain–Fritsch scheme in single-column-model simulations based on the explicit three-dimensional simulations show a significant improvement in the representation of the main convective episodes, with a greater amount of convective rainfall. The performance of the scheme in COAMPS precipitation forecast experiments over the continental United States is also investigated. Improvements are obtained with the modified scheme in skill scores for middle to high rainfall rates.

scholarly journals Fluctuations in a quasi-stationary shallow cumulus cloud ensemble

2014 ◽  
Vol 1 (2) ◽  
pp. 1223-1282 ◽  
Author(s):  
M. Sakradzija ◽  
A. Seifert ◽  
T. Heus
Keyword(s):  
Weibull Distribution ◽  
Mass Flux ◽  
Flux Distribution ◽  
Deep Convection ◽  
Convective Cloud ◽  
Cloud Base ◽  
Cumulus Clouds ◽  
Large Eddy Simulation Model ◽  
Shallow Cumulus ◽  
Distribution Mode

Abstract. We propose an approach to stochastic parameterization of shallow cumulus clouds to represent the convective variability and its dependence on the model resolution. To collect the information about the individual cloud lifecycles and the cloud ensemble as a whole, we employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by conditional sampling of clouds at the cloud-base level. In the case of a shallow cumulus ensemble, the cloud-base mass flux distribution is bimodal due to the different shallow cloud subtypes. Each distribution mode can be approximated with a Weibull distribution, explaining the deviation from a single-parameter exponential shape through the diversity in cloud lifecycles. The exponential distribution of cloud mass flux previously suggested for deep convection parameterization is a special case of the Weibull distribution, which opens a way towards unification of the statistical convective ensemble formalism of shallow and deep cumulus clouds. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate a shallow convective cloud ensemble. It is formulated as a compound random process, with the number of convective elements drawn from a Poisson distribution, and the cloud mass flux sampled from a mixed Weibull distribution. Convective memory is accounted for through the explicit cloud lifecycles, making the model formulation consistent with the choice of the Weibull cloud mass flux distribution function. The memory of individual shallow clouds is required to capture the correct convective variability. The resulting distribution of the subgrid convective states in the considered shallow cumulus case is scale-adaptive – the smaller the grid size, the broader the distribution.

scholarly journals A Mass-Flux Cumulus Parameterization Scheme across Gray-Zone Resolutions

2017 ◽  
Vol 145 (2) ◽  
pp. 583-598 ◽  
Author(s):  
Young Cheol Kwon ◽  
Song-You Hong
Keyword(s):  
South Korea ◽  
Mass Flux ◽  
Convective Cloud ◽  
Cumulus Parameterization ◽  
Parameterization Scheme ◽  
Cloud Base ◽  
Gray Zone ◽  
Cumulus Parameterization Scheme ◽  
Simulated Precipitation ◽  
Convective Inhibition

A method that enables a mass-flux cumulus parameterization scheme (CPS) to work seamlessly in various model grids across CPS gray-zone resolutions is proposed. The convective cloud-base mass flux, convective inhibition, and convective detrainment in the simplified Arakawa–Schubert (SAS) scheme are modified to be functions of the convective updraft fraction. The combination of two updraft fractions is used to modulate the cloud-base mass flux; the first one depends on the horizontal grid space and the other is a function of the grid-scale and convective vertical velocity. The convective inhibition and detrainment of hydrometeors are also modified to be a function of the grid-size-dependent convective updraft fraction. A set of sensitivity experiments with the Weather Research and Forecasting (WRF) Model is conducted for a heavy rainfall case over South Korea. The results show that the revised SAS CPS outperforms the original SAS. At 3 and 1 km, the precipitation core over South Korea is well reproduced by the experiments with the revised SAS scheme. On the contrary, the simulated precipitation is widespread in the case of the original SAS experiment and there are multiple spurious cores when the CPS is removed at those resolutions. The modified mass flux at the cloud base is found to play a major role in organizing the grid-scale precipitation at the convective core. A 1-month simulation at 3 km confirms that the revised scheme produces slightly better summer monsoonal precipitation results as compared to the typical model setup without CPS.

scholarly journals A Mass-Flux Scheme View of a High-Resolution Simulation of a Transition from Shallow to Deep Cumulus Convection

2006 ◽  
Vol 63 (7) ◽  
pp. 1895-1909 ◽  
Author(s):  
Zhiming Kuang ◽  
Christopher S. Bretherton
Keyword(s):  
High Resolution ◽  
Mass Flux ◽  
Deep Convection ◽  
Convective Available Potential Energy ◽  
Cumulus Parameterization ◽  
Cloud Base ◽  
Cumulus Convection ◽  
Thermodynamic Structure ◽  
Cumulus Schemes ◽  
Resolution Simulation

Abstract In this paper, an idealized, high-resolution simulation of a gradually forced transition from shallow, nonprecipitating to deep, precipitating cumulus convection is described; how the cloud and transport statistics evolve as the convection deepens is explored; and the collected statistics are used to evaluate assumptions in current cumulus schemes. The statistical analysis methodologies that are used do not require tracing the history of individual clouds or air parcels; instead they rely on probing the ensemble characteristics of cumulus convection in the large model dataset. They appear to be an attractive way for analyzing outputs from cloud-resolving numerical experiments. Throughout the simulation, it is found that 1) the initial thermodynamic properties of the updrafts at the cloud base have rather tight distributions; 2) contrary to the assumption made in many cumulus schemes, nearly undiluted air parcels are too infrequent to be relevant to any stage of the simulated convection; and 3) a simple model with a spectrum of entraining plumes appears to reproduce most features of the cloudy updrafts, but significantly overpredicts the mass flux as the updrafts approach their levels of zero buoyancy. A buoyancy-sorting model was suggested as a potential remedy. The organized circulations of cold pools seem to create clouds with larger-sized bases and may correspondingly contribute to their smaller lateral entrainment rates. Our results do not support a mass-flux closure based solely on convective available potential energy (CAPE), and are in general agreement with a convective inhibition (CIN)-based closure. The general similarity in the ensemble characteristics of shallow and deep convection and the continuous evolution of the thermodynamic structure during the transition provide justification for developing a single unified cumulus parameterization that encompasses both shallow and deep convection.

scholarly journals Fluctuations in a quasi-stationary shallow cumulus cloud ensemble

2015 ◽  
Vol 22 (1) ◽  
pp. 65-85 ◽  
Author(s):  
M. Sakradzija ◽  
A. Seifert ◽  
T. Heus
Keyword(s):  
Weibull Distribution ◽  
Exponential Distribution ◽  
Mass Flux ◽  
Flux Distribution ◽  
Deep Convection ◽  
Convective Cloud ◽  
Cloud Base ◽  
Cumulus Clouds ◽  
Shallow Cumulus ◽  
Distribution Shape

Abstract. We propose an approach to stochastic parameterisation of shallow cumulus clouds to represent the convective variability and its dependence on the model resolution. To collect information about the individual cloud lifecycles and the cloud ensemble as a whole, we employ a large eddy simulation (LES) model and a cloud tracking algorithm, followed by conditional sampling of clouds at the cloud-base level. In the case of a shallow cumulus ensemble, the cloud-base mass flux distribution is bimodal, due to the different shallow cloud subtypes, active and passive clouds. Each distribution mode can be approximated using a Weibull distribution, which is a generalisation of exponential distribution by accounting for the change in distribution shape due to the diversity of cloud lifecycles. The exponential distribution of cloud mass flux previously suggested for deep convection parameterisation is a special case of the Weibull distribution, which opens a way towards unification of the statistical convective ensemble formalism of shallow and deep cumulus clouds. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate a shallow convective cloud ensemble. It is formulated as a compound random process, with the number of convective elements drawn from a Poisson distribution, and the cloud mass flux sampled from a mixed Weibull distribution. Convective memory is accounted for through the explicit cloud lifecycles, making the model formulation consistent with the choice of the Weibull cloud mass flux distribution function. The memory of individual shallow clouds is required to capture the correct convective variability. The resulting distribution of the subgrid convective states in the considered shallow cumulus case is scale-adaptive – the smaller the grid size, the broader the distribution.

Observed Boundary Layer Controls on Shallow Cumulus at the ARM Southern Great Plains Site

2018 ◽  
Vol 75 (7) ◽  
pp. 2235-2255 ◽  
Author(s):  
Neil P. Lareau ◽  
Yunyan Zhang ◽  
Stephen A. Klein
Keyword(s):  
Boundary Layer ◽  
Great Plains ◽  
Vertical Velocity ◽  
Mass Flux ◽  
Cloud Base ◽  
Liquid Water Path ◽  
Southern Great Plains ◽  
Clear Sky ◽  
Shallow Cumulus ◽  
In Situ Sensors

Abstract The boundary layer controls on shallow cumulus (ShCu) convection are examined using a suite of remote and in situ sensors at ARM Southern Great Plains (SGP). A key instrument in the study is a Doppler lidar that measures vertical velocity in the CBL and along cloud base. Using a sample of 138 ShCu days, the composite structure of the ShCu CBL is examined, revealing increased vertical velocity (VV) variance during periods of medium cloud cover and higher VV skewness on ShCu days than on clear-sky days. The subcloud circulations of 1791 individual cumuli are also examined. From these data, we show that cloud-base updrafts, normalized by convective velocity, vary as a function of updraft width normalized by CBL depth. It is also found that 63% of clouds have positive cloud-base mass flux and are linked to coherent updrafts extending over the depth of the CBL. In contrast, negative mass flux clouds lack coherent subcloud updrafts. Both sets of clouds possess narrow downdrafts extending from the cloud edges into the subcloud layer. These downdrafts are also present adjacent to cloud-free updrafts, suggesting they are mechanical in origin. The cloud-base updraft data are subsequently combined with observations of convective inhibition to form dimensionless “cloud inhibition” (CI) parameters. Updraft fraction and liquid water path are shown to vary inversely with CI, a finding consistent with CIN-based closures used in convective parameterizations. However, we also demonstrate a limited link between CBL vertical velocity variance and cloud-base updrafts, suggesting that additional factors, including updraft width, are necessary predictors for cloud-base updrafts.

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

2010 ◽  
Vol 67 (7) ◽  
pp. 2171-2193 ◽  
Author(s):  
Minoru Chikira ◽  
Masahiro Sugiyama
Keyword(s):  
General Circulation ◽  
Deep Convection ◽  
Convective Available Potential Energy ◽  
Lower Troposphere ◽  
South Pacific Convergence Zone ◽  
Cumulus Parameterization ◽  
Cloud Base ◽  
Convergence Zone ◽  
Entrainment Rate ◽  
Surrounding Environment

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

scholarly journals A Stochastic Parameterization for Deep Convection Based on Equilibrium Statistics

2008 ◽  
Vol 65 (1) ◽  
pp. 87-105 ◽  
Author(s):  
R. S. Plant ◽  
G. C. Craig
Keyword(s):  
Mass Flux ◽  
Large Scale ◽  
Deep Convection ◽  
Cloud Base ◽  
Local Fluctuations ◽  
Single Column ◽  
Ensemble Mean ◽  
The Mean ◽  
Closure Method ◽  
Deterministic Limit

Abstract A stochastic parameterization scheme for deep convection is described, suitable for use in both climate and NWP models. Theoretical arguments and the results of cloud-resolving models are discussed in order to motivate the form of the scheme. In the deterministic limit, it tends to a spectrum of entraining/detraining plumes and is similar to other current parameterizations. The stochastic variability describes the local fluctuations about a large-scale equilibrium state. Plumes are drawn at random from a probability distribution function (PDF) that defines the chance of finding a plume of given cloud-base mass flux within each model grid box. The normalization of the PDF is given by the ensemble-mean mass flux, and this is computed with a CAPE closure method. The characteristics of each plume produced are determined using an adaptation of the plume model from the Kain–Fritsch parameterization. Initial tests in the single-column version of the Unified Model verify that the scheme is effective in producing the desired distributions of convective variability without adversely affecting the mean state.

Climatological sensitivities of shallow-cumulus bulk entrainment in continental and oceanic locations

2021 ◽  
Author(s):  
Daniel J. Kirshbaum ◽  
Katia Lamer
Keyword(s):  
Great Plains ◽  
Cumulus Parameterization ◽  
Cloud Base ◽  
Shallow Cumulus ◽  
Mass Fluxes ◽  
Complex Process ◽  
The Us ◽  
Atmospheric Radiation Measurement ◽  
Cumulus Parameterization Schemes ◽  
Eastern North Atlantic

AbstractCumulus entrainment is a complex process that has long challenged conceptual understanding and atmospheric prediction. To investigate this process observationally, two retrievals are used to generate multi-year climatologies of shallow-cumulus bulk entrainment (ϵ) at two Atmospheric Radiation Measurement cloud observatories, one in the US southern Great Plains (SGP) and the other in the Azores archipelago in the eastern North Atlantic (ENA). The statistical distributions of ϵ thus obtained, as well as certain environmental and cloud-related sensitivities of ϵ, are consistent with previous findings from large-eddy simulations. The retrieved ϵ robustly increases with cloudlayer relative humidity and decreases in wider clouds and cloud ensembles with larger cloud-base mass fluxes. While ϵ also correlates negatively with measures of cloud-layer vigor (e.g., maximum in-cloud vertical velocity and cloud depth), the extent to which these metrics actually regulate ϵ (or vice-versa) is unclear. Novel sensitivities of ϵ include a robust decrease of ϵ with increasing subcloud wind speed in oceanic flows, as well as a decrease of ϵ with increasing cloud-base mass flux in individual cumuli. A strong land–ocean contrast in ϵ is also found, with median values of 0.5-0.6 km−1 at the continental SGP site and and 1.0-1.1 km−1 at the oceanic ENA site. This trend is associated with drier and deeper cloud layers, along with larger cloud-base mass fluxes, at SGP, all of which favor reduced ϵ. The flow-dependence of retrieved ϵ implies that its various sensitivities should be accounted for in cumulus parameterization schemes.

An Explicit One-Dimensional Time-Dependent Tilting Cloud Model

2004 ◽  
Vol 61 (23) ◽  
pp. 2797-2816 ◽  
Author(s):  
Shu-Hua Chen ◽  
Wen-Yih Sun
Keyword(s):  
Mass Flux ◽  
Cloud Model ◽  
Deep Convection ◽  
Evaporative Cooling ◽  
Precipitation Amount ◽  
Time Dependent ◽  
Lower Atmosphere ◽  
Cumulus Parameterization ◽  
One Dimensional ◽  
Tilting Angle

Abstract An explicit one-dimensional time-dependent tilting cloud model has been developed for use in cumulus parameterizations. The tilting axis is not necessarily orthogonal to the (r, θ) plane, making the horizontal axisymmetric assumption more reasonable. This explicit time-dependent tilting model (ETTM) consists of an updraft and a downdraft, which are governed by the same dynamic and thermodynamic equations. The updraft is initiated by a moist thermal bubble, while the downdraft is consequently induced by evaporative cooling and the drag force of precipitation separating from the tilting updraft instead of being arbitrarily initialized. The updraft is capable of reproducing the major features of a deep cloud such as overshooting cooling above the cloud top, evaporative cooling near the surface, and drying in the lower atmosphere at dissipating stages. The entrainment–detrainment rate in this model is well defined, and its time variation is quite significant. Moreover, the vertical profile of the air inside the updraft does not follow the moist adiabat after deep convection. For the downdraft, the total precipitation and mass flux at low levels contributed from the downdraft cannot be neglected in this case study. In addition, the downdraft can bring dry air from middle levels to lower levels. Three sensitivity tests—the environmental sounding, the tilting angle, and the radius of the updraft–downdraft— have also been conducted. The cooling–warming of a downdraft near the surface is sensitive to the environmental sounding, consistent with results from Srivastava. The cloud life span, maximum vertical velocity, precipitation amount, and vertical mass flux are strongly influenced by the tilting angle and the radius of the cloud. The results from the ETTM simulation are quite reasonable and promising. However, some deficiencies of this model still exist, and more research will be conducted to improve its performance. The final goal is to implement this 1D model in a mesoscale model's cumulus parameterization scheme.

scholarly journals A new WRF-Chem treatment for studying regional-scale impacts of cloud processes on aerosol and trace gases in parameterized cumuli

2015 ◽  
Vol 8 (2) ◽  
pp. 409-429 ◽  
Author(s):  
L. K. Berg ◽  
M. Shrivastava ◽  
R. C. Easter ◽  
J. D. Fast ◽  
E. G. Chapman ◽  
...  
Keyword(s):  
Deep Convection ◽  
Trace Gases ◽  
Regional Scale ◽  
Cloud Droplet ◽  
Convective Cloud ◽  
Cumulus Parameterization ◽  
Sulfate Production ◽  
Shallow Clouds ◽  
The Impact ◽  
Wet Removal

Abstract. A new treatment of cloud effects on aerosol and trace gases within parameterized shallow and deep convection, and aerosol effects on cloud droplet number, has been implemented in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) version 3.2.1 that can be used to better understand the aerosol life cycle over regional to synoptic scales. The modifications to the model include treatment of the cloud droplet number mixing ratio; key cloud microphysical and macrophysical parameters (including the updraft fractional area, updraft and downdraft mass fluxes, and entrainment) averaged over the population of shallow clouds, or a single deep convective cloud; and vertical transport, activation/resuspension, aqueous chemistry, and wet removal of aerosol and trace gases in warm clouds. These changes have been implemented in both the WRF-Chem chemistry packages as well as the Kain–Fritsch (KF) cumulus parameterization that has been modified to better represent shallow convective clouds. Testing of the modified WRF-Chem has been completed using observations from the Cumulus Humilis Aerosol Processing Study (CHAPS). The simulation results are used to investigate the impact of cloud–aerosol interactions on regional-scale transport of black carbon (BC), organic aerosol (OA), and sulfate aerosol. Based on the simulations presented here, changes in the column-integrated BC can be as large as −50% when cloud–aerosol interactions are considered (due largely to wet removal), or as large as +40% for sulfate under non-precipitating conditions due to sulfate production in the parameterized clouds. The modifications to WRF-Chem are found to account for changes in the cloud droplet number concentration (CDNC) and changes in the chemical composition of cloud droplet residuals in a way that is consistent with observations collected during CHAPS. Efforts are currently underway to port the changes described here to the latest version of WRF-Chem, and it is anticipated that they will be included in a future public release of WRF-Chem.

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