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.

scholarly journals Evaluating Boundary Layer–Based Mass Flux Closures Using Cloud-Resolving Model Simulations of Deep Convection

2010 ◽  
Vol 67 (7) ◽  
pp. 2212-2225 ◽  
Author(s):  
Jennifer K. Fletcher ◽  
Christopher S. Bretherton
Keyword(s):  
Boundary Layer ◽  
Mass Flux ◽  
Large Scale ◽  
Deep Convection ◽  
Cloud Base ◽  
Cumulus Convection ◽  
Model Simulations ◽  
Shallow Cumulus ◽  
Wide Range ◽  
Cloud Resolving Model

Abstract High-resolution three-dimensional cloud resolving model simulations of deep cumulus convection under a wide range of large-scale forcings are used to evaluate a mass flux closure based on boundary layer convective inhibition (CIN) that has previously been applied in parameterizations of shallow cumulus convection. With minor modifications, it is also found to perform well for deep oceanic and continental cumulus convection, and it matches simulated cloud-base mass flux much better than a closure based only on the boundary layer convective velocity scale. CIN closure maintains an important feedback among cumulus base mass flux, compensating subsidence, and CIN that keeps the boundary layer top close to cloud base. For deep convection, the proposed CIN closure requires prediction of a boundary layer mean turbulent kinetic energy (TKE) and a horizontal moisture variance, both of which are strongly correlated with precipitation. For our cases, CIN closure predicts cloud-base mass flux in deep convective environments as well as the best possible bulk entraining CAPE closure, but unlike the latter, CIN closure also works well for shallow cumulus convection without retuning of parameters.

scholarly journals Mesoscale Features Associated with Tropical Cyclone Formations in the Western North Pacific

2008 ◽  
Vol 136 (6) ◽  
pp. 2006-2022 ◽  
Author(s):  
Cheng-Shang Lee ◽  
Kevin K. W. Cheung ◽  
Jenny S. N. Hui ◽  
Russell L. Elsberry
Keyword(s):  
Tropical Cyclone ◽  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Deep Convection ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Synoptic Patterns ◽  
The Mean

Abstract The mesoscale features of 124 tropical cyclone formations in the western North Pacific Ocean during 1999–2004 are investigated through large-scale analyses, satellite infrared brightness temperature (TB), and Quick Scatterometer (QuikSCAT) oceanic wind data. Based on low-level wind flow and surge direction, the formation cases are classified into six synoptic patterns: easterly wave (EW), northeasterly flow (NE), coexistence of northeasterly and southwesterly flow (NE–SW), southwesterly flow (SW), monsoon confluence (MC), and monsoon shear (MS). Then the general convection characteristics and mesoscale convective system (MCS) activities associated with these formation cases are studied under this classification scheme. Convection processes in the EW cases are distinguished from the monsoon-related formations in that the convection is less deep and closer to the formation center. Five characteristic temporal evolutions of the deep convection are identified: (i) single convection event, (ii) two convection events, (iii) three convection events, (iv) gradual decrease in TB, and (v) fluctuating TB, or a slight increase in TB before formation. Although no dominant temporal evolution differentiates cases in the six synoptic patterns, evolutions ii and iii seem to be the common routes taken by the monsoon-related formations. The overall percentage of cases with MCS activity at multiple times is 63%, and in 35% of cases more than one MCS coexisted. Most of the MC and MS cases develop multiple MCSs that lead to several episodes of deep convection. These two patterns have the highest percentage of coexisting MCSs such that potential interaction between these systems may play a role in the formation process. The MCSs in the monsoon-related formations are distributed around the center, except in the NE–SW cases in which clustering of MCSs is found about 100–200 km east of the center during the 12 h before formation. On average only one MCS occurs during an EW formation, whereas the mean value is around two for the other monsoon-related patterns. Both the mean lifetime and time of first appearance of MCS in EW are much shorter than those developed in other synoptic patterns, which indicates that the overall formation evolution in the EW case is faster. Moreover, this MCS is most likely to be found within 100 km east of the center 12 h before formation. The implications of these results to internal mechanisms of tropical cyclone formation are discussed in light of other recent mesoscale studies.

scholarly journals On interpreting studies of tracer transport by deep cumulus convection and its effects on atmospheric chemistry

2008 ◽  
Vol 8 (20) ◽  
pp. 6037-6050 ◽  
Author(s):  
M. G. Lawrence ◽  
M. Salzmann
Keyword(s):  
Atmospheric Chemistry ◽  
Large Scale ◽  
Deep Convection ◽  
Convective Transport ◽  
Advective Transport ◽  
Tracer Transport ◽  
Transport Models ◽  
Mass Fluxes ◽  
Split Treatment ◽  
The Mean

Abstract. Global chemistry-transport models (CTMs) and chemistry-GCMs (CGCMs) generally simulate vertical tracer transport by deep convection separately from the advective transport by the mean winds, even though a component of the mean transport, for instance in the Hadley and Walker cells, occurs in deep convective updrafts. This split treatment of vertical transport has various implications for CTM simulations. In particular, it has led to a misinterpretation of several sensitivity simulations in previous studies in which the parameterized convective transport of one or more tracers is neglected. We describe this issue in terms of simulated fluxes and fractions of these fluxes representing various physical and non-physical processes. We then show that there is a significant overlap between the convective and large-scale mean advective vertical air mass fluxes in the CTM MATCH, and discuss the implications which this has for interpreting previous and future sensitivity simulations, as well as briefly noting other related implications such as numerical diffusion.

scholarly journals Estimating the Shallow Convective Mass Flux from the Subcloud-Layer Mass Budget

2020 ◽  
Vol 77 (5) ◽  
pp. 1559-1574 ◽  
Author(s):  
Raphaela Vogel ◽  
Sandrine Bony ◽  
Bjorn Stevens
Keyword(s):  
Vertical Velocity ◽  
Diurnal Cycle ◽  
Mass Flux ◽  
Large Scale ◽  
Cloud Base ◽  
Entrainment Rate ◽  
Field Campaign ◽  
Mass Budget ◽  
Convective Mixing ◽  
Convective Mass Flux

Abstract This paper develops a method to estimate the shallow-convective mass flux M at the top of the subcloud layer as a residual of the subcloud-layer mass budget. The ability of the mass-budget estimate to reproduce the mass flux diagnosed directly from the cloud-core area fraction and vertical velocity is tested using real-case large-eddy simulations over the tropical Atlantic. We find that M reproduces well the magnitude, diurnal cycle, and day-to-day variability of the core-sampled mass flux, with an average root-mean-square error of less than 30% of the mean. The average M across the four winter days analyzed is 12 mm s−1, where the entrainment rate E contributes on average 14 mm s−1 and the large-scale vertical velocity W contributes −2 mm s−1. We find that day-to-day variations in M are mostly explained by variations in W, whereas E is very similar among the different days analyzed. Instead E exhibits a pronounced diurnal cycle, with a minimum of about 10 mm s−1 around sunset and a maximum of about 18 mm s−1 around sunrise. Application of the method to dropsonde data from an airborne field campaign in August 2016 yields the first measurements of the mass flux derived from the mass budget, and supports the result that the variability in M is mostly due to the variability in W. Our analyses thus suggest a strong coupling between the day-to-day variability in shallow convective mixing (as measured by M) and the large-scale circulation (as measured by W). Application of the method to the EUREC4A field campaign will help evaluate this coupling, and assess its implications for cloud-base cloudiness.

Measuring shallow convective mass flux profiles in the trade wind region

2021 ◽  
Author(s):  
Marcus Klingebiel ◽  
Heike Konow ◽  
Bjorn Stevens
Keyword(s):  
Mass Flux ◽  
Large Scale ◽  
Doppler Radar ◽  
Cloud Base ◽  
Trade Wind ◽  
Doppler Lidar ◽  
Shallow Convection ◽  
Lidar Measurements ◽  
Flux Profile ◽  
Convective Mass Flux

AbstractMass flux is a key quantity in parameterizations of shallow convection. To estimate the shallow convective mass flux as accurately as possible, and to test these parameterizations, observations of this parameter are necessary. In this study, we show how much the mass flux varies and how this can be used to test factors that may be responsible for its variation. Therefore, we analyze long term Doppler radar and Doppler lidar measurements at the Barbados Cloud Observatory over a time period of 30 months, which results in a mean mass flux profile with a peak value of 0.03 kg m−2 s−1 at an altitude of ~730 m, similar to observations from Ghate et al. (2011) at the Azores Islands. By combining Doppler radar and Doppler lidar measurements, we find that the cloud base mass flux depends mainly on the cloud fraction and refutes an idea based on large eddy simulations, that the velocity scale is in major control of the shallow cumulus mass flux. This indicates that the large scale conditions might play a more important role than what one would deduce from simulations using prescribed large-scale forcings.

scholarly journals Deep Convection Triggering by Boundary Layer Thermals. Part II: Stochastic Triggering Parameterization for the LMDZ GCM

2014 ◽  
Vol 71 (2) ◽  
pp. 515-538 ◽  
Author(s):  
Nicolas Rochetin ◽  
Jean-Yves Grandpeix ◽  
Catherine Rio ◽  
Fleur Couvreux
Keyword(s):  
General Circulation ◽  
Deep Convection ◽  
Circulation Model ◽  
Cloud Base ◽  
Trade Wind ◽  
Shallow Convection ◽  
Model Framework ◽  
Main Hypothesis ◽  
Single Column ◽  
The Impact

Abstract This paper presents a stochastic triggering parameterization for deep convection and its implementation in the latest standard version of the Laboratoire de Météorologie Dynamique–Zoom (LMDZ) general circulation model: LMDZ5B. The derivation of the formulation of this parameterization and the justification, based on large-eddy simulation results, for the main hypothesis was proposed in Part I of this study. Whereas the standard triggering formulation in LMDZ5B relies on the maximum vertical velocity within a mean bulk thermal, the new formulation presented here (i) considers a thermal size distribution instead of a bulk thermal, (ii) provides a statistical lifting energy at cloud base, (iii) proposes a three-step trigger (appearance of clouds, inhibition crossing, and exceeding of a cross-section threshold), and (iv) includes a stochastic component. Here the complete implementation is presented, with its coupling to the thermal model used to treat shallow convection in LMDZ5B. The parameterization is tested over various cases in a single-column model framework. A sensitivity study to each parameter introduced is also carried out. The impact of the new triggering is then evaluated in the single-column version of LMDZ on several case studies and in full 3D simulations. It is found that the new triggering (i) delays deep convection triggering, (ii) suppresses it over oceanic trade wind cumulus zones, (iii) increases the low-level cloudiness, and (iv) increases the convective variability. The scale-aware nature of this parameterization is also discussed.

scholarly journals Parameterizing deep convection using the assumed probability density function method

2014 ◽  
Vol 7 (3) ◽  
pp. 3803-3849
Author(s):  
R. L. Storer ◽  
B. M. Griffin ◽  
J. Höft ◽  
J. K. Weber ◽  
E. Raut ◽  
...  
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Large Scale ◽  
Climate Models ◽  
Deep Convection ◽  
Scale Model ◽  
Time Step ◽  
Microphysics Scheme ◽  
Single Column

Abstract. Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and mid-latitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.

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 On interpreting studies of tracer transport by deep cumulus convection and its effects on atmospheric chemistry

2008 ◽  
Vol 8 (3) ◽  
pp. 12163-12195 ◽  
Author(s):  
M. G. Lawrence ◽  
M. Salzmann
Keyword(s):  
Atmospheric Chemistry ◽  
Large Scale ◽  
Deep Convection ◽  
Convective Transport ◽  
Advective Transport ◽  
Tracer Transport ◽  
Transport Models ◽  
Mass Fluxes ◽  
Split Treatment ◽  
The Mean

Abstract. Global chemistry-transport models (CTMs) and chemistry-GCMs (CGCMs) generally simulate vertical tracer transport by deep convection separately from the advective transport by the mean winds, even though a component of the mean transport, for instance in the Hadley and Walker cells, occurs in deep convective updrafts. This split treatment of vertical transport has various implications for CTM simulations. In particular, it has led to a misinterpretation of several sensitivity simulations in previous studies in which the parameterized convective transport of one or more tracers is neglected. We describe this issue in terms of simulated fluxes and fractions of these fluxes representing various physical and non-physical processes. We then show that there is a significant overlap between the convective and large-scale mean advective vertical air mass fluxes in the CTM MATCH, and discuss the implications which this has for interpreting previous and future sensitivity simulations, as well as briefly noting other related implications such as numerical diffusion.

scholarly journals Parameterizing deep convection using the assumed probability density function method

2015 ◽  
Vol 8 (1) ◽  
pp. 1-19 ◽  
Author(s):  
R. L. Storer ◽  
B. M. Griffin ◽  
J. Höft ◽  
J. K. Weber ◽  
E. Raut ◽  
...  
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Large Scale ◽  
Climate Models ◽  
Deep Convection ◽  
Scale Model ◽  
Time Step ◽  
Microphysics Scheme ◽  
Single Column

Abstract. Due to their coarse horizontal resolution, present-day climate models must parameterize deep convection. This paper presents single-column simulations of deep convection using a probability density function (PDF) parameterization. The PDF parameterization predicts the PDF of subgrid variability of turbulence, clouds, and hydrometeors. That variability is interfaced to a prognostic microphysics scheme using a Monte Carlo sampling method. The PDF parameterization is used to simulate tropical deep convection, the transition from shallow to deep convection over land, and midlatitude deep convection. These parameterized single-column simulations are compared with 3-D reference simulations. The agreement is satisfactory except when the convective forcing is weak. The same PDF parameterization is also used to simulate shallow cumulus and stratocumulus layers. The PDF method is sufficiently general to adequately simulate these five deep, shallow, and stratiform cloud cases with a single equation set. This raises hopes that it may be possible in the future, with further refinements at coarse time step and grid spacing, to parameterize all cloud types in a large-scale model in a unified way.

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