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Christian Jakob
and
A. Pier Siebesma

Abstract

All convection parameterizations in models of the atmosphere include a decision tree to decide on at least the occurrence, and often the type, of convection in a model grid volume. This decision tree is sometimes referred to as the “trigger function.” This study investigates the role that the decision-making processes play in the simulation of convection in the European Centre for Medium-Range Weather Forecasts global forecast model.

For this purpose, a new simple parcel-ascent model based on an entraining plume model is developed to replace the currently used undilute ascent in the initial decision making. The consequences of the use of the more realistic model for the behavior of convection itself and its impact on the model climate are investigated. It is shown that there are profound changes to both the convection characteristics, and consequently, the model climate. The wider implications of the findings here for the general design of a mass-flux convection parameterization are discussed.

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Wim C. de Rooy
and
A. Pier Siebesma

Abstract

For a wide range of shallow cumulus convection cases, large-eddy simulation (LES) model results have been used to investigate lateral mixing as expressed by the fractional entrainment and fractional detrainment rates. It appears that the fractional entrainment rates show much less variation from hour to hour and case to case than the fractional detrainment rates. Therefore, in the parameterization proposed here, the fractional entrainment rates are assumed to be described as a fixed function of height, roughly following the LES results. Based on the LES results a new, more flexible parameterization for the detrainment process is developed that contains two important dependencies. First, based on cloud ensemble principles it can be understood that deeper cloud layers call for smaller detrainment rates. All current mass flux schemes ignore this cloud-height dependence, which evidently leads to large discrepancies with observed mass flux profiles. The new detrainment formulation deals with this dependence by considering the mass flux profile in a nondimensionalized way. Second, both relative humidity of the environmental air and the buoyancy excess of the updraft influence the detrainment rates and, therefore, the mass flux profiles. This influence can be taken into account by borrowing a parameter from the buoyancy-sorting concept and using it in a bulk sense. LES results show that with this bulk parameter, the effect of environmental conditions on the fractional detrainment rate can be accurately described. A simple, practical but flexible parameterization for the fractional detrainment rate is derived and evaluated in a single-column model (SCM) for three different shallow cumulus cases, which shows the clear potential of this parameterization. The proposed parameterization is an attractive and more robust alternative for existing, more complex, buoyancy-sorting-based mixing schemes, and can be easily incorporated in current mass flux schemes.

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Stephan R. de Roode
,
A. Pier Siebesma
,
Harm J. J. Jonker
, and
Yoerik de Voogd

Abstract

The application of a steady-state vertical velocity equation for parameterized moist convective updrafts in climate and weather prediction models is currently common practice. This equation usually contains an advection, a buoyancy, and a lateral entrainment term, whereas the effects of pressure gradient and subplume contributions are typically incorporated as proportionality constants a and b for the buoyancy and the entrainment terms, respectively. A summary of proposed values of these proportionality constants a and b in the literature demonstrates that there is a large uncertainty in their most appropriate values. To shed new light on this situation an analysis is presented of the full vertical budget equation for shallow cumulus clouds obtained from large eddy simulations of three different Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) intercomparison cases. It is found that the pressure gradient term is the dominant sink term in the vertical velocity budget, whereas the entrainment term only gives a small contribution. This result is at odds with the parameterized vertical velocity equation in the literature as it employs the entrainment term as the major sink term. As a practical solution the damping effect of the pressure term may be parameterized in terms of the lateral entrainment rates as used for thermodynamic quantities like the total specific humidity. By using a least squares method, case-dependent optimal values are obtained for the proportionality constants a and b, which are linearly related with each other. This relation can be explained from a linear relationship between the lateral entrainment rate and the buoyancy.

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Jerôme Schalkwijk
,
Harmen J. J. Jonker
,
A. Pier Siebesma
, and
Fred C. Bosveld

Abstract

Results are presented of two large-eddy simulation (LES) runs of the entire year 2012 centered at the Cabauw observational supersite in the Netherlands. The LES is coupled to a regional weather model that provides the large-scale information. The simulations provide three-dimensional continuous time series of LES-generated turbulence and clouds, which can be compared in detail to the extensive observational dataset of Cabauw. The LES dataset is available from the authors on request.

This type of LES setup has a number of advantages. First, it can provide a more statistical approach to the study of turbulent atmospheric flow than the more common case studies, since a diverse but representative set of conditions is covered, including numerous transitions. This has advantages in the design and evaluation of parameterizations. Second, the setup can provide valuable information on the quality of the LES model when applied to such a wide range of conditions. Last, it also provides the possibility to emulate observation techniques. This might help detect limitations and potential problems of a variety of measurement techniques.

The LES runs are validated through a comparison with observations from the observational supersite and with results from the “parent” large-scale model. The long time series that are generated, in combination with information on the spatial structure, provide a novel opportunity to study time scales ranging from seconds to seasons. This facilitates a study of the power spectrum of horizontal and vertical wind speed variance to identify the dominant variance-containing time scales.

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