Parameterization Of Shallow Convection 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.

Evaluating Shallow Convection Parameterization Assumptions With a qt–w Quadrant Analysis

AbstractUncertainties 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.

Measuring Shallow Convective Mass Flux Profiles in the Trade Wind Region

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. 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.

Local Impact of Stochastic Shallow Convection on Clouds and Precipitation in the Tropical Atlantic

AbstractThe local impact of stochastic shallow convection on clouds and precipitation is tested in a case study over the tropical Atlantic on 20 December 2013 using the Icosahedral Nonhydrostatic Model (ICON). ICON is used at a grid resolution of 2.5 km and is tested in several configurations that differ in their treatment of shallow convection. A stochastic shallow convection scheme is compared to the operational deterministic scheme and a case with no representation of shallow convection. The model is evaluated by comparing synthetically generated irradiance data for both visible and infrared wavelengths against actual satellite observations. The experimental approach is designed to distinguish the local effects of parameterized shallow convection (or lack thereof) within the trades versus the ITCZ. The stochastic cases prove to be superior in reproducing low-level cloud cover, deep convection, and its organization, as well as the distribution of precipitation in the tropical Atlantic ITCZ. In these cases, convective heating in the subcloud layer is substantial, and boundary layer depth is increased as a result of the heating, while evaporation is enhanced at the expense of sensible heat flux at the ocean’s surface. The stochastic case where subgrid shallow convection is deactivated below the resolved deep updrafts indicates that local boundary layer convection is crucial for a better representation of deep convection. Based on these results, our study points to a necessity to further develop parameterizations of shallow convection for use at the convection-permitting resolutions and to assuredly include them in weather and climate models even as their imperfect versions.

Characterizing Subsiding Shells in Shallow Cumulus Using Doppler Lidar and Large‐Eddy Simulation

AbstractThe existence of subsiding shells on the periphery of shallow cumulus clouds has major implications concerning the parameterization of shallow convection, with the mass exchange between the shell and cloudy air representing a significant deviation from the commonly used bulk‐plume parameterization. We examine the structure and frequency of subsiding shells in shallow cumulus convection using Doppler lidars at the Atmospheric Radiation Measurement Southern Great Plains facility in the central United States and at the Jülich ObservatorY for Cloud Evolution in western Germany. Doppler lidar indicates that the vertical subsiding shell extent is asymmetric, while shell width is typically ~100 m. Large‐eddy simulation can reasonably simulate the observed shell structure using a grid spacing of 10 m and suggests that much of the observed asymmetry is not a result of transient cloud evolution.

An Eddy‐Diffusivity Mass‐Flux Parameterization for Modeling Oceanic Convection

AbstractA new one‐dimensional (1‐D) parameterization of penetrative convection has been developed in order to have a better representation of the vertical mixing in ocean general circulation models. Our approach is inspired from atmospheric parameterizations of shallow convection which assumes that in the convective boundary layer, the subgrid‐scale fluxes result from two different mixing scales: small eddies, which are represented by an Eddy‐Diffusivity (ED) contribution, and large eddies associated with thermals, which are represented by a mass‐flux contribution. In the present work, the local (small eddies) and nonlocal (large eddies) contributions are unified into an Eddy‐Diffusivity‐Mass‐Flux (EDMF) parameterization which treats simultaneously the whole vertical mixing. EDMF is implemented in the community ocean model NEMO and tested in its 1‐D column version. Deepening of dense water in analytic cases, successfully reproduced in LES simulations, is more realistic with EDMF than with standard diffusion parameterizations. Also the convective events observed in the western Mediterranean at the Lion station and in the North Pacific Ocean at the PAPA station are more realistic in terms of sequencing and amplitude with EDMF.

Sensitivity of a Mediterranean Tropical-Like Cyclone to Physical Parameterizations

The accurate prediction of Mediterranean tropical-like cyclones, or medicanes, is an important challenge for numerical weather prediction models due to their significant adverse impact on the environment, life, and property. The aim of this study is to investigate the sensitivity of an intense medicane, which formed south of Sicily on 7 November 2014, to the microphysical, cumulus, and boundary/surface layer schemes. The non-hydrostatic Weather Research and Forecasting model (version 3.7.1) is employed. A symmetric cyclone with a deep warm core, corresponding to a medicane, develops in all of the experiments, except for the one with the Thompson microphysics. There is a significant sensitivity of different aspects of the simulated medicane to the physical parameterizations. Its intensity is mainly influenced by the boundary/surface layer scheme, while its track is mainly influenced by the representation of cumulus convection, and its duration is mainly influenced by microphysical parameterization. The modification of the drag coefficient and the roughness lengths of heat and moisture seems to improve its intensity, track, and duration. The parameterization of shallow convection, with explicitly resolved deep convection, results in a weaker medicane with a shorter lifetime. An optimum combination of physical parameterizations in order to simulate all of the characteristics of the medicane does not seem to exist.

Physically Constrained Stochastic Shallow Convection in Realistic Kilometer‐Scale Simulations

AbstractA 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.

Analyses of Shallow Convection over the Amazon Coastal Region Using Satellite Images, Data Observations and Modeling

Abstract The Belem region of the state of Para, which is located in northern of Brazil and part of the Amazon biome is characterized by high temperatures, strong convection, unstable air conditions and high humidity favoring the formation of convective clouds. Shallow convection and deep convection are among the main components of the local energy balance. Typically a deep convection over the continents is preceded by a shallow convection. An analysis of the performance of the Jet Propulsion Laboratory / National Aeronautics and Space Administration (JPL/NASA) model of shallow convection parameterization in a framework of the single column model (SCM), in relation to the cluster of cumulus clouds formed in the coastal region of the Amazon forest due to squall lines, is provided. To achieve this purpose enhanced satellite images and infrared images from channels 2 and 4 from the GOES-12 satellite, and data obtained by the “Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)” - CHUVA - campaign, during the month of June of 2011, were used. During that period, clusters of cumulus clouds penetrated the interior of the Amazon, causing heavy rains. Results demonstrated that the parameterizations performed well in the case where only a core of clouds was observed, such as at 18:00h on 14 June. This period of the day also presents the smallest bias and root mean square error (rmse) values for the relative humidity. For the potential temperature the smallest value of bias is at 12:00h on June 7th (0.18 K), the largest one is on June 11th (-2.32 K) and the rmse ranges from 0.59 to 2.99 K.

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

Abstract. This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation. We used output of a perturbed parameter ensemble (PPE) experiment conducted with an atmosphere–ocean general circulation model (AOGCM) without flux adjustment. The Model for Interdisciplinary Research on Climate version 5 (MIROC5) was used for the PPE experiment. Output of the PPE was compared with satellite observation data to evaluate the model biases and the parametric uncertainty of the biases with respect to TOA radiation and clouds. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. In particular, the cooling bias of the shortwave cloud radiative effect at low latitudes could not be removed, neither in the zonal mean nor at each latitude–longitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases in radiation and clouds.

Idealized Large-Eddy and Convection-Resolving Simulations of Moist Convection over Mountainous Terrain

Abstract On summertime fair-weather days, thermally driven wind systems play an important role in determining the initiation of convection and the occurrence of localized precipitation episodes over mountainous terrain. This study compares the mechanisms of convection initiation and precipitation development within a thermally driven flow over an idealized double-ridge system in large-eddy (LESs) and convection-resolving (CRM) simulations. First, LES at a horizontal grid spacing of 200 m is employed to analyze the developing circulations and associated clouds and precipitation. Second, CRM simulations at horizontal grid length of 1 km are conducted to evaluate the performance of a kilometer-scale model in reproducing the discussed mechanisms. Mass convergence and a weaker inhibition over the two ridges flanking the valley combine with water vapor advection by upslope winds to initiate deep convection. In the CRM simulations, the spatial distribution of clouds and precipitation is generally well captured. However, if the mountains are high enough to force the thermally driven flow into an elevated mixed layer, the transition to deep convection occurs faster, precipitation is generated earlier, and surface rainfall rates are higher compared to the LES. Vertical turbulent fluxes remain largely unresolved in the CRM simulations and are underestimated by the model, leading to stronger upslope winds and increased horizontal moisture advection toward the mountain summits. The choice of the turbulence scheme and the employment of a shallow convection parameterization in the CRM simulations change the strength of the upslope winds, thereby influencing the simulated timing and intensity of convective precipitation.

Improved Low-Cloud Simulation from the Community Atmosphere Model with an Advanced Third-Order Turbulence Closure

Abstract In this study, a simplified intermediately prognostic higher-order turbulence closure (IPHOC) is implemented in the Community Atmosphere Model, version 5 (CAM5), to provide a consistent treatment of subgrid-scale cloud processes, except for deep convection. The planetary boundary layer (PBL) height is prognosticated to better resolve the discontinuity of temperature and moisture above the PBL top. Single-column model tests show that fluxes of liquid water potential temperature and total water, cloud fraction, and liquid water content are improved with this approach. The simplified IPHOC package replaces the boundary layer dry and moist turbulence parameterizations, the shallow convection parameterization, and the liquid-phase part of the cloud macrophysics parameterization in CAM5. CAM5-IPHOC improves the simulation of the low-level clouds off the west coasts of continents and the storm track region in the Southern Hemisphere (SH). The transition from stratocumulus to cumulus clouds is more gradual. There are also improvements on the cloud radiative forcing, especially shortwave, in the subsidence regime. The improvements in the relationships among low cloud amount, surface relative humidity, lower tropospheric stability, and PBL depth are seen in some stratocumulus regions. CAM5-IPHOC, however, produces weaker precipitation at the South Pacific convergence zone than CAM5 because of less energy flux into the SH atmosphere. The more downward surface shortwave radiative cooling and the less top-of-the-atmosphere longwave cloud radiative heating in the SH relative to the Northern Hemisphere explains the anomalous cooling and the lesser energy flux into the SH, which is related to the underestimate of extratropical middle/high clouds in the SH.

Implementation of a Stochastic Eddy-Diffusivity/Mass-Flux Parameterization into the Navy Global Environmental Model

Abstract A unified boundary layer and shallow convection parameterization based on a stochastic eddy-diffusivity/mass-flux (EDMF) approach is implemented and tested in the Navy Global Environmental Model (NAVGEM). The primary goals of this work are to improve the representation of convectively driven boundary layers and the coupling between the boundary layer and cumulus regions. Within the EDMF framework the subgrid vertical fluxes are calculated as a sum of an eddy-diffusivity part, which in the current implementation is based on the approach developed by Louis in the late 1970s, and a stochastic mass-flux parameterization. The mass-flux parameterization is a model for both dry and moist convective thermals. Dry thermals, which represent surface-forced coherent structures in a flow, provide countergradient mixing in the boundary layer and, if conditions permit, are the roots for moist thermals. Moist thermals represent shallow convective clouds. The new parameterization implemented in a single-column model (SCM) version of NAVGEM is shown to be able to realistically simulate a variety of dry and moist convective cases. The NAVGEM SCM results are validated against large-eddy-simulation results. The skill of NAVGEM as a global weather forecasting model is considerably improved with the new EDMF parameterization. The EDMF parameterization became part of the operational NAVGEM in November 2013.

Diagnosis of the marine low cloud simulation in the NCAR community earth system model (CESM) and the NCEP global forecast system (GFS)-modular ocean model v4 (MOM4) coupled model

We present a diagnostic analysis of the marine low cloud climatology simulated by two state-of-the-art coupled atmosphere–ocean models: the National Center for Atmospheric Research community earth system model version 1 (CESM1) and the National Center for Environmental Predictions global forecasting system-modular ocean model version 4 (GFS-MOM4) coupled model. In the CESM1, the coastal stratocumulus (Sc)-topped planetary boundary layers (PBLs) in the subtropical Eastern Pacific are well-simulated but the climatological transition from Sc to shallow cumulus (Cu) is too abrupt and occurs too close to the coast. By contrast, in the GFS-MOM4 the coastal Sc amount and PBL depth are severely underestimated while the transition from Sc to shallow Cu is “delayed” and offshore Sc cover is too extensive in the subtropical Eastern Pacific. We discuss the possible connections between these differences in the simulations and differences in the parameterizations of shallow convection and boundary layer turbulence in the two models.

The Dynamics of Idealized Convection Schemes and Their Effect on the Zonally Averaged Tropical Circulation

In this paper, the effect of a simple convection scheme on the zonally averaged tropical general circulation is examined within an idealized moist GCM to obtain broad classifications of the influence of convection on the Tropics. This is accomplished with a simplified convection scheme in the style of Betts and Miller. The scheme is utilized in a moist GCM with simplified physical parameterizations (gray radiation, with zonally symmetric, slab mixed layer ocean boundary conditions). Comparisons are made with simulations without a convection scheme [i.e., with large-scale condensation (LSC) only], with the moist convective adjustment (MCA) parameterization, and with various formulations and parameter sets with a simplified Betts–Miller (SBM) scheme. With the control run using the SBM scheme, the Tropics become quieter and less dependent on horizontal resolution as compared with the LSC or MCA simulations. The Hadley circulation mass transport is significantly reduced with the SBM scheme, as is the ITCZ precipitation. An important factor determining this behavior is the parameterization of shallow convection: without shallow convection, the convection scheme is largely ineffective at preventing convection from occurring at the grid scale. The sensitivities to convection scheme parameters are also examined. The simulations are remarkably insensitive to the convective relaxation time, and only mildly sensitive to the relative humidity of the reference profile, provided significant large-scale condensation is not allowed to occur. The changes in the zonally averaged tropical circulation that occur in all the simulations are understood based on the convective criteria of the schemes and the gross moist stability of the atmosphere.

Effect of shallow cumulus convection on the eastern Pacific climate in a coupled model

Shallow cumulus convection evaporates stratocumulus clouds in the atmospheric boundary layer. The effect of shallow convection on the large‐scale climate of the eastern tropical Pacific is investigated with a coupled ocean‐atmosphere model by disabling the shallow convection parameterization (noSC). Without shallow convection, the stratiform cloud fraction increases and surface solar radiation decreases. The sea surface temperature (SST) cools on average by 2°C. The cooling in noSC is larger under the low cloud deck south of the equator than north of the equator, resulting in an increase in the climatic meridional asymmetry. In the control run an ITCZ forms south of the equator in March‐April. In noSC the SST is at most 24°C south of the equator and an ITCZ does not form. The perennial northern‐hemisphere ITCZ in noSC is accompanied by year‐round southerlies of at least ∼3 m s−1 on the equator, considerably reducing the seasonal cycle of equatorial SST.

The role of shallow convection in the water and energy cycles of the atmosphere

The Canadian Centre for Climate Modelling and Analysis atmospheric general circulation model (AGCM4) is used to study the role of shallow convection in the hydrologic and energy cycles of the atmosphere. Sensitivity tests with AGCM4 show a marked effect of the parameterization of shallow convection in the model. In particular, including the parameterization of shallow convection produces considerably enhanced vertical mixing and decreased stratiform cloud amounts in the lower subtropical atmosphere over the oceans. The differences in simulated stratiform cloud amounts are associated with a change in the globally averaged outgoing shortwave radiative flux at the top of the atmosphere of about 11 W m−2. Additionally, precipitation rates are considerably reduced for stratiform clouds and enhanced for convective clouds in the subtropics, if the parameterization of shallow convection is included in the model. Additional tests show that the simulated responses in cloud amounts and precipitation to the treatment of shallow convection are robust. Additional simulations with modified closures for deep convection and other changes to the treatment of convection in the model still lead to similar responses of the model results.

A Shallow-Convection Parameterization for Mesoscale Models. Part I: Submodel Description and Preliminary Applications

Abstract A shallow-convection parameterization suitable for both marine and continental regimes is developed for use in mesoscale models. The scheme is closely associated with boundary layer turbulence processes and can transition to either a deep-convection scheme in conditionally unstable environments or to an explicit (resolved scale) moisture scheme in moist stable environments. The shallow-convection mass-closure assumption uses a hybrid formulation based on boundary layer turbulent kinetic energy (TKE) and convective available potential energy (CAPE), while the convective trigger is primarily a function of boundary layer TKE. Secondary subgrid clouds having nearly neutral buoyancy can form as shallow-convective updrafts detrain mass to their environment. Called neutrally buoyant clouds (NBCs), these can be dissipated through lateral and vertical mixing, light precipitation, ice-crystal settling, and cloud-top entrainment instability (CTEI). The shallow-convection scheme is developed and demonstrated...

A Shallow-Convection Parameterization for Mesoscale Models. Part II: Verification and Sensitivity Studies

Abstract Formulations describing a new shallow-convection parameterization intended for mesoscale models have been described in a companion paper, Part I. In the present paper the convection scheme is tested and evaluated against observed datasets in both marine and continental environments. Additional experiments explore the sensitivity of the scheme to changes in model vertical resolution, key parameters of the closure, and the cloud-dissipation mechanisms. The new shallow-convection scheme uses a hybrid mass flux closure that adjusts linearly between two closure options based on (i) boundary layer turbulent kinetic energy (TKE) for very shallow clouds and (ii) convective available potential energy (CAPE) for deep clouds. Meanwhile, cloud mass detrained from convective updrafts acts as the source for a second class of subgrid clouds having nearly neutral buoyancy, which can persist for hours. Performance of the convection submodel is found to be quite reasonable in four cases covering a range of conditi...

Use of Differentiable and Nondifferentiable Optimization Algorithms for Variational Data Assimilation with Discontinuous Cost Functions

Abstract Cost functions formulated in four-dimensional variational data assimilation (4DVAR) are nonsmooth in the presence of discontinuous physical processes (i.e., the presence of “on–off” switches in NWP models). The adjoint model integration produces values of subgradients, instead of gradients, of these cost functions with respect to the model’s control variables at discontinuous points. Minimization of these cost functions using conventional differentiable optimization algorithms may encounter difficulties. In this paper an idealized discontinuous model and an actual shallow convection parameterization are used, both including on–off switches, to illustrate the performances of differentiable and nondifferentiable optimization algorithms. It was found that (i) the differentiable optimization, such as the limited memory quasi-Newton (L-BFGS) algorithm, may still work well for minimizing a nondifferentiable cost function, especially when the changes made in the forecast model at switching points to the...