Dorota Jarecka

Large-Eddy Simulations of EUCLIPSE–GASS Lagrangian Stratocumulus-to-Cumulus Transitions: Mean State, Turbulence, and Decoupling

AbstractResults of four Lagrangian stratocumulus-to-shallow-cumulus transition cases as obtained from six different large-eddy simulation models are presented. The model output is remarkably consistent in terms of the representation of the evolution of the mean state, which is characterized by a stratocumulus cloud layer that rises with time and that warms and dries relative to the subcloud layer. Also, the effect of the diurnal insolation on cloud-top entrainment and the moisture flux at the top of the subcloud layer are consistently captured by the models. For some cases, the models diverge in terms of the liquid water path (LWP) during nighttime, which can be explained from the difference in the sign of the buoyancy flux at cloud base. If the subcloud buoyancy fluxes are positive, turbulence sustains a vertically well-mixed layer, causing a cloud layer that is relatively cold and moist and consequently has a high LWP. After some simulation time, all cases exhibit subcloud-layer dynamics that appear to ...

Homogeneity of the Subgrid-Scale Turbulent Mixing in Large-Eddy Simulation of Shallow Convection

AbstractThis paper presents an approach to locally predict homogeneity of the subgrid-scale turbulent mixing in large-eddy simulation of shallow clouds applying double-moment warm-rain microphysics. The homogeneity of subgrid-scale mixing refers to the partitioning of the cloud water evaporation due to parameterized entrainment between changes of the mean droplet radius and changes of the mean droplet concentration. Homogeneous and extremely inhomogeneous mixing represent two limits of possible scenarios, where the droplet concentration and the mean droplet radius remains unchanged during the microphysical adjustment, respectively. To predict the subgrid-scale mixing scenario, the double-moment microphysics scheme is merged with the approach to delay droplet evaporation resulting from entrainment. Details of the new scheme and its application in the Barbados Oceanographic and Meteorological Experiment (BOMEX) shallow convection case are discussed. The simulated homogeneity of mixing varies significantly i...

Modeling of Subgrid-Scale Mixing in Large-Eddy Simulation of Shallow Convection

Abstract This paper discusses an extension of the approach proposed previously to represent the delay of cloud water evaporation and buoyancy reversal due to the cloud–environment mixing in bulk microphysics large-eddy simulation of clouds. In the original approach, an additional equation for the mean spatial scale of cloudy filaments was introduced to represent the progress toward microscale homogenization of a volume undergoing turbulent cloud–environment mixing, with the evaporation of cloud water allowed only when the filament scale approached the Kolmogorov microscale. Here, it is shown through a posteriori analysis of model simulations that one should also predict the volume fraction of the cloudy air that was diagnosed in the original approach. The resulting model of turbulent mixing and homogenization, referred to as the λ–β model, is applied in a series of shallow convection simulations using various spatial resolutions and compared to the traditional bulk model. This work represents an intermedi...

Modeling Condensation in Shallow Nonprecipitating Convection

AbstractTwo schemes for modeling condensation in warm nonprecipitating clouds are compared. The first one is the efficient bulk condensation scheme where cloudy volumes are always at saturation and cloud water evaporates instantaneously to maintain saturation. The second one is the comprehensive bin condensation scheme that predicts the evolution of the cloud droplet spectrum and allows sub- and supersaturations in cloudy volumes. The emphasis is on the impact of the two schemes on cloud dynamics. Theoretical considerations show that the bulk condensation scheme provides more buoyancy than the bin scheme, but the effect is small, with the potential density temperature difference around 0.1 K for 1% supersaturation. The 1D advection–condensation tests document the high-vertical-resolution requirement for the bin scheme to resolve the cloud-base supersaturation maximum and CCN activation, which is difficult to employ in 3D cloud simulations. Simulations of shallow convection cloud fields are executed applyi...

A spreading drop of shallow water

Abstract The theoretical solutions and corresponding numerical simulations of Schar and Smolarkiewicz (1996) [3] are revisited. The original abstract problem of a parabolic, slab-symmetric drop of shallow water spreading under gravity is extended to three spatial dimensions, with the initial drop defined over an elliptical compact support. An axisymmetric drop is considered as a special case. The elliptical drop exhibits enticing dynamics, which may appear surprising at the first glance. In contrast, the evolution of the axisymmetric drop is qualitatively akin to the evolution of the slab-symmetric drop and intuitively obvious. Besides being interesting per se, the derived theoretical results provide a simple means for testing numerical schemes concerned with wetting–drying areas in shallow water flows. Reported calculations use the libmpdata++ , a recently released free/libre and open-source software library of solvers for generalized transport equations. The numerical results closely match theoretical predictions, demonstrating strengths of the nonoscillatory forward-in-time integrators comprising the libmpdata++ .

Formula Translation in Blitz++, NumPy and Modern Fortran: A Case Study of the Language Choice Tradeoffs

Three object-oriented implementations of a prototype solver of the advection equation are introduced. The presented programs are based on BlitzThree object-oriented implementations of a prototype solver of the advection equation are introduced. The presented programs are based on Blitz++ (C++), NumPy (Python), and Fortran’s built-in array containers .T he solvers include an implementation of the Multidimensional Positive-Definite Advective Transport Algorithm (MPDATA). The introduced codes exemplify ho wt he application of object-oriented programming (OOP) techniques allows to reproduce the mathematical notation used in th el iterature within the program code. A discussion on the tradeo! so f the programming language choice is presented. The main a ngles of comparison are code brevity and syntax clarity (and hence maintainability and auditability) as well as performance. In the case of Python, a significant performance gain is observed when switching from the standard interpreter (CPython) to the PyPy implementation of Python. Entire source code of all three implementations is embedded in the text and is licensed under the terms of the GNU GPL license.

Object-oriented implementations of the MPDATA advection equation solver in C++, Python and Fortran

Three object-oriented implementations of a prototype solver of the advection equation are introduced. The presented programs are based on BlitzThree object-oriented implementations of a prototype solver of the advection equation are introduced. The presented programs are based on Blitz++ (C++), NumPy (Python), and Fortran’s built-in array containers .T he solvers include an implementation of the Multidimensional Positive-Definite Advective Transport Algorithm (MPDATA). The introduced codes exemplify ho wt he application of object-oriented programming (OOP) techniques allows to reproduce the mathematical notation used in th el iterature within the program code. A discussion on the tradeo! so f the programming language choice is presented. The main a ngles of comparison are code brevity and syntax clarity (and hence maintainability and auditability) as well as performance. In the case of Python, a significant performance gain is observed when switching from the standard interpreter (CPython) to the PyPy implementation of Python. Entire source code of all three implementations is embedded in the text and is licensed under the terms of the GNU GPL license.

Modeling of subgrid-scale cloud-clear air turbulent mixing in Large Eddy Simulation of cloud fields

This paper presents computational approach to locally predict the homogeneity of subgrid-scale turbulent mixing between a cloud and its environment in large-eddy simulation of warm (ice-free) shallow convective clouds applying a double-moment bulk microphysics scheme. The term homogenity of mixing refers to the change of the mean droplet size associated with evaporation of cloud water due to entrainment. The two contrasting limits are the homogeneous mixing, where the radius of all droplets is reduced and the concentration does not change during microscale homogenization, and the extremely inhomogeneous mixing, where the microscale homogenization leads to complete evaporation of some droplets and does not affect the rest. The novel approach is applied to simulations of shallow convective cloud field. The results show that locally the homogeneity of mixing can vary significantly because of the spatial variability of the intensity of turbulence and the mean droplet radius. On average, however, the mixing becomes more homogeneous with height because of higher turbulence intensities and larger droplet sizes aloft.