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

2020 ◽  
Vol 77 (2) ◽  
pp. 583-610 ◽  
Author(s):  
Jihoon Shin ◽  
Sungsu Park
Keyword(s):  
Similarity Theory ◽  
Domain Size ◽  
Cloud Base ◽  
Moist Convection ◽  
Shallow Convection ◽  
Power Law Distribution ◽  
Convection Scheme ◽  
Multivariate Gaussian Distribution ◽  
Single Column ◽  
Mean And Variance

Abstract By 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.

Convectively driven wind variability in connection to wind biases in the ECMWF operational weather model

2020 ◽  
Author(s):  
Louise Nuijens ◽  
Irina Sandu ◽  
Beatrice Saggiorato ◽  
Hauke Schulz ◽  
Mariska Koning ◽  
...  
Keyword(s):  
Model Development ◽  
Meridional Overturning Circulation ◽  
Momentum Transport ◽  
Cloud Base ◽  
Moist Convection ◽  
Shallow Convection ◽  
Wind Speeds ◽  
Wind Variability ◽  
Large Eddy

<p>Despite playing a key role in the atmospheric circulation, the representation of momentum transport by moist convection (cumulus clouds) has been largely overlooked by the model development community over the past decade, at least compared with diabatic and radiative effects of clouds. In particular, how shallow convection may influence surface and boundary layer winds is not thoroughly investigated. In this talk, we discuss the role of convective momentum transport (CMT) in setting low-level wind speed and its variability and evaluate its role in long-standing wind biases in the ECMWF IFS model.</p><p>We use high-frequency wind profiling measurements and high-resolution large-eddy simulations to inform our understanding of convectively driven wind variability. We do this at two locations: in the trades, using wind lidar and radiosonde measurements from the Barbados Cloud Observatory and the intensive EUREC4A field campaign, and over the Netherlands, using an observationally constrained reanalysis wind dataset and large-eddy simulation hindcasts.</p><p>At both locations we use the data and model output to investigate whether CMT can be responsible for a missing drag near the surface in the IFS model. Namely, at short leadtimes, the model produces stronger than observed easterly/westerly flow near the surface, while “a missing drag” produces weaker than observed wind turning. Consequently, the meridional overturning circulation in both the tropics and midlatitudes is weaker in the IFS and in ERA-Interim and ERA5 reanalysis products.</p><p>Comparing simulated and IFS wind tendencies at selected grid points at the above locations, and by turning off the process of CMT by shallow convection in the model, we gain insight in the role of CMT in explaining wind biases. We find that CMT alone does not explain a missing drag near the surface. CMT often acts to accelerate winds near the surface. But CMT plays a role in communicating biases in cloud base wind speeds towards the surface. In the trades, a strong jet near cloud base is determined by thermal wind and a strong flux of zonal momentum through cloud base, where “cumulus friction” minimizes. Near this jet, the presence of (counter-gradient) turbulent momentum fluxes produces most of the drag. Implications of these findings for CMT parameterization are discussed.</p>

scholarly journals Improvements in the Subgrid-Scale Representation of Moist Convection in a Cumulus Parameterization Scheme: The Single-Column Test and Its Impact on Seasonal Prediction

2007 ◽  
Vol 135 (6) ◽  
pp. 2135-2154 ◽  
Author(s):  
Young-Hwa Byun ◽  
Song-You Hong
Keyword(s):  
Large Scale ◽  
Meridional Circulation ◽  
Random Selection ◽  
The Other ◽  
Moist Convection ◽  
Subgrid Scale ◽  
Convection Scheme ◽  
Single Column ◽  
Convective Momentum Transport ◽  
Selection Of

Abstract This study describes a revised approach for the subgrid-scale convective properties of a moist convection scheme in a global model and evaluates its effects on a simulated model climate. The subgrid-scale convective processes tested in this study comprise three components: 1) the random selection of cloud top, 2) the inclusion of convective momentum transport, and 3) a revised large-scale destabilization effect considering synoptic-scale forcing in the cumulus convection scheme of the National Centers for Environmental Prediction medium-range forecast model. Each component in the scheme has been evaluated within a single-column model (SCM) framework forced by the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment data. The impact of the changes in the scheme on seasonal predictions has been examined for the boreal summers of 1996, 1997, and 1999. In the SCM simulations, an experiment that includes all the modifications reproduces the typical convective heating and drying feature. The simulated surface rainfall is in good agreement with the observed precipitation. Random selection of the cloud top effectively moistens and cools the upper troposphere, and it induces drying and warming below the cloud-top level due to the cloud–radiation feedback. However, the two other components in the revised scheme do not play a significant role in the SCM simulations. On the other hand, the role of each modification component in the scheme is significant in the ensemble seasonal simulations. The random selection process of the cloud top preferentially plays an important role in the adjustment of the thermodynamic profile in a manner similar to that in the SCM framework. The inclusion of convective momentum transport in the scheme weakens the meridional circulation. The revised large-scale destabilization process plays an important role in the modulation of the meridional circulation when this process is combined with other processes; on the other hand, this process does not induce significant changes in large-scale fields by itself. Consequently, the experiment that involves all the modifications shows a significant improvement in the seasonal precipitation, thereby highlighting the importance of nonlinear interaction between the physical processes in the model and the simulated climate.

scholarly journals Simulating deep convection with a shallow convection scheme

2011 ◽  
Vol 11 (20) ◽  
pp. 10389-10406 ◽  
Author(s):  
C. Hohenegger ◽  
C. S. Bretherton
Keyword(s):  
Climate Modeling ◽  
Global Climate ◽  
Deep Convection ◽  
Convective Precipitation ◽  
Cloud Base ◽  
Gradual Transition ◽  
Shallow Convection ◽  
Convection Scheme ◽  
Community Atmosphere Model ◽  
Simulated Precipitation

Abstract. Convective processes profoundly affect the global water and energy balance of our planet but remain a challenge for global climate modeling. Here we develop and investigate the suitability of a unified convection scheme, capable of handling both shallow and deep convection, to simulate cases of tropical oceanic convection, mid-latitude continental convection, and maritime shallow convection. To that aim, we employ large-eddy simulations (LES) as a benchmark to test and refine a unified convection scheme implemented in the Single-column Community Atmosphere Model (SCAM). Our approach is motivated by previous cloud-resolving modeling studies, which have documented the gradual transition between shallow and deep convection and its possible importance for the simulated precipitation diurnal cycle. Analysis of the LES reveals that differences between shallow and deep convection, regarding cloud-base properties as well as entrainment/detrainment rates, can be related to the evaporation of precipitation. Parameterizing such effects and accordingly modifying the University of Washington shallow convection scheme, it is found that the new unified scheme can represent both shallow and deep convection as well as tropical and mid-latitude continental convection. Compared to the default SCAM version, the new scheme especially improves relative humidity, cloud cover and mass flux profiles. The new unified scheme also removes the well-known too early onset and peak of convective precipitation over mid-latitude continental areas.

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 Simulating deep convection with a shallow convection scheme

2011 ◽  
Vol 11 (3) ◽  
pp. 8385-8430 ◽  
Author(s):  
C. Hohenegger ◽  
C. S. Bretherton
Keyword(s):  
Climate Modeling ◽  
Global Climate ◽  
Deep Convection ◽  
Convective Precipitation ◽  
Cloud Base ◽  
Gradual Transition ◽  
Shallow Convection ◽  
Convection Scheme ◽  
Community Atmosphere Model ◽  
Simulated Precipitation

Abstract. Convective processes profoundly affect the global water and energy balance of our planet but remain a challenge for global climate modeling. Here we develop and investigate the suitability of a unified convection scheme, capable of handling both shallow and deep convection, to simulate cases of tropical oceanic convection, mid-latitude continental convection, and maritime shallow convection. To that aim, we employ large-eddy simulations (LES) as a benchmark to test and refine a unified convection scheme implemented in the Single-Column Community Atmosphere Model (SCAM). Our approach is motivated by previous cloud-resolving modeling studies, which have documented the gradual transition between shallow and deep convection and its possible importance for the simulated precipitation diurnal cycle. Analysis of the LES reveals that differences between shallow and deep convection, regarding cloud-base properties as well as entrainment/detrainment rates, can be related to the evaporation of precipitation. Parameterizing such effects and accordingly modifying the University of Washington shallow convection scheme, it is found that the new unified scheme can represent both shallow and deep convection as well as tropical and continental convection. Compared to the default SCAM version, the new scheme especially improves relative humidity, cloud cover and mass flux profiles. The new unified scheme also removes the well-known too early onset and peak of convective precipitation over mid-latitude continental areas.

scholarly journals Triggering Deep Convection with a Probabilistic Plume Model

2014 ◽  
Vol 71 (11) ◽  
pp. 3881-3901 ◽  
Author(s):  
Fabio D’Andrea ◽  
Pierre Gentine ◽  
Alan K. Betts ◽  
Benjamin R. Lintner
Keyword(s):  
Climate Models ◽  
Proper Time ◽  
Deep Convection ◽  
Potential Temperature ◽  
Specific Humidity ◽  
Cloud Base ◽  
Moist Convection ◽  
Density Currents ◽  
Shallow Convection ◽  
Plume Model

Abstract A model unifying the representation of the planetary boundary layer and dry, shallow, and deep convection, the probabilistic plume model (PPM), is presented. Its capacity to reproduce the triggering of deep convection over land is analyzed in detail. The model accurately reproduces the timing of shallow convection and of deep convection onset over land, which is a major issue in many current general climate models. PPM is based on a distribution of plumes with varying thermodynamic states (potential temperature and specific humidity) induced by surface-layer turbulence. Precipitation is computed by a simple ice microphysics, and with the onset of precipitation, downdrafts are initiated and lateral entrainment of environmental air into updrafts is reduced. The most buoyant updrafts are responsible for the triggering of moist convection, causing the rapid growth of clouds and precipitation. Organization of turbulence in the subcloud layer is induced by unsaturated downdrafts, and the effect of density currents is modeled through a reduction of the lateral entrainment. The reduction of entrainment induces further development from the precipitating congestus phase to full deep cumulonimbus. Model validation is performed by comparing cloud base, cloud-top heights, timing of precipitation, and environmental profiles against cloud-resolving models and large-eddy simulations for two test cases. These comparisons demonstrate that PPM triggers deep convection at the proper time in the diurnal cycle and produces reasonable precipitation. On the other hand, PPM underestimates cloud-top height.

The Role of Negative Buoyancy in Surface-Based Convection and Its Representation in Cumulus Parameterization Schemes

2013 ◽  
Vol 52 (12) ◽  
pp. 2887-2905 ◽  
Author(s):  
Manisha Ganeshan ◽  
Raghu Murtugudde ◽  
John Strack
Keyword(s):  
Wrf Model ◽  
Warm Season ◽  
Cumulus Parameterization ◽  
Cloud Base ◽  
Moist Convection ◽  
Shallow Convection ◽  
Parameterization Schemes ◽  
Cumulus Parameterization Schemes ◽  
Weak Constraints ◽  
Negative Buoyancy

AbstractSeveral warm season, late-afternoon precipitation events are simulated over the Chesapeake Bay watershed using the Weather Research and Forecasting (WRF) model at three different resolutions. The onset and peak of surface-based convection are predicted to occur prematurely when two popular cumulus parameterization schemes (Betts–Miller–Janjić and Kain–Fritsch) are used. Rainfall predictions are significantly improved with explicit convection. The early bias appears to be associated with the inadequacy in representing convective inhibition (CIN) or negative buoyancy in the trigger for moist convection. In particular, both schemes have weak constraints for the negative buoyancy above cloud base and below the level of free convection, leading to premature rainfall. Satellite-derived soundings suggest that, even with extremely favorable conditions, negative buoyancy in this layer may delay the onset of surface-based convection. Other factors, such as enhanced mixing due to overactive shallow convection, also appear to contribute to the early rainfall bias through the premature removal of CIN during the day.

scholarly journals Improvement and Implementation of a Parameterization for Shallow Cumulus in the Global Climate Model ECHAM5-HAM

2011 ◽  
Vol 68 (3) ◽  
pp. 515-532 ◽  
Author(s):  
Francesco A. Isotta ◽  
P. Spichtinger ◽  
U. Lohmann ◽  
K. von Salzen
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Model Simulation ◽  
Global Climate Model ◽  
Circulation Model ◽  
Sensitivity Analyses ◽  
Cloud Base ◽  
Shallow Convection ◽  
Max Planck ◽  
Convection Scheme

Abstract A transient shallow-convection scheme is implemented into the general circulation model ECHAM5 and the coupled aerosol model HAM, developed at the Max Planck Institute for Meteorology in Hamburg. The shallow-convection scheme is extended to take the ice phase into account. In addition, a detailed double-moment microphysics approach has been added. In this approach, the freezing processes and precipitation formation are dependent on aerosols. Furthermore, in the scheme, tracers are transported and scavenged consistently as in the rest of the model. Results of a single-column model simulation for the Barbados Oceanography and Meteorology Experiment (BOMEX) campaign are compared with previously published large-eddy simulation (LES) results. Compared to the standard version, the global ECHAM5-HAM simulations with the newly implemented scheme show a decreased frequency of shallow convection in better agreement with LES. Less shallow convection is compensated by more stratus and stratocumulus. Deep and especially midlevel convection are markedly affected by those changes, which in turn influence high-level clouds. Generally, a better agreement with the observations can be obtained. For a better understanding of the scheme’s impact and to test different setting parameters, sensitivity analyses are performed. The mixing properties, cloud-base vertical velocity, and launching layer of the test parcel, respectively, are varied. In this context, results from simulations without shallow convection are also presented.

scholarly journals The ICON Single-Column Mode

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 906
Author(s):  
Ivan Bašták Ďurán ◽  
Martin Köhler ◽  
Astrid Eichhorn-Müller ◽  
Vera Maurer ◽  
Juerg Schmidli ◽  
...  
Keyword(s):  
Data Storage ◽  
Model Development ◽  
Computational Cost ◽  
Three Dimensional ◽  
Shallow Convection ◽  
Modeling Framework ◽  
Additional Tool ◽  
Eddy Simulation ◽  
Single Column ◽  
Stratocumulus Clouds

The single-column mode (SCM) of the ICON (ICOsahedral Nonhydrostatic) modeling framework is presented. The primary purpose of the ICON SCM is to use it as a tool for research, model evaluation and development. Thanks to the simplified geometry of the ICON SCM, various aspects of the ICON model, in particular the model physics, can be studied in a well-controlled environment. Additionally, the ICON SCM has a reduced computational cost and a low data storage demand. The ICON SCM can be utilized for idealized cases—several well-established cases are already included—or for semi-realistic cases based on analyses or model forecasts. As the case setup is defined by a single NetCDF file, new cases can be prepared easily by the modification of this file. We demonstrate the usage of the ICON SCM for different idealized cases such as shallow convection, stratocumulus clouds, and radiative transfer. Additionally, the ICON SCM is tested for a semi-realistic case together with an equivalent three-dimensional setup and the large eddy simulation mode of ICON. Such consistent comparisons across the hierarchy of ICON configurations are very helpful for model development. The ICON SCM will be implemented into the operational ICON model and will serve as an additional tool for advancing the development of the ICON model.

scholarly journals Nature versus Nurture in Shallow Convection

2010 ◽  
Vol 67 (5) ◽  
pp. 1655-1666 ◽  
Author(s):  
David M. Romps ◽  
Zhiming Kuang
Keyword(s):  
Standard Deviation ◽  
The Other ◽  
Cloud Base ◽  
Shallow Convection ◽  
Eddy Simulation ◽  
Cloud Properties ◽  
Nature Versus Nurture ◽  
Large Eddy ◽  
The Mean ◽  
Single Set

Abstract Tracers are used in a large-eddy simulation of shallow convection to show that stochastic entrainment (and not cloud-base properties) determines the fate of convecting parcels. The tracers are used to diagnose the correlations between a parcel’s state above the cloud base and both the parcel’s state at the cloud base and its entrainment history. The correlation with the cloud-base state goes to zero a few hundred meters above the cloud base. On the other hand, correlations between a parcel’s state and its net entrainment are large. Evidence is found that the entrainment events may be described as a stochastic Poisson process. A parcel model is constructed with stochastic entrainment that is able to replicate the mean and standard deviation of cloud properties. Turning off cloud-base variability has little effect on the results, which suggests that stochastic mass-flux models may be initialized with a single set of properties. The success of the stochastic parcel model suggests that it holds promise as the framework for a convective parameterization.

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