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.

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

2013 ◽  
Vol 70 (9) ◽  
pp. 2751-2767 ◽  
Author(s):  
Dorota Jarecka ◽  
Wojciech W. Grabowski ◽  
Hugh Morrison ◽  
Hanna Pawlowska
Keyword(s):  
Large Eddy Simulation ◽  
Turbulent Mixing ◽  
Droplet Radius ◽  
Subgrid Scale ◽  
Shallow Convection ◽  
Eddy Simulation ◽  
Droplet Concentration ◽  
Large Eddy ◽  
Double Moment ◽  
The Mean

Abstract This 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 inside small convective clouds, from close to homogeneous to close to extremely inhomogeneous. The mean mixing characteristics become more homogeneous with height, reflecting increases of the mean droplet size and the mean turbulence intensity, both favoring homogeneous mixing. Model results are consistent with microphysical effects of entrainment and mixing deduced from field observations. Mixing close to homogeneous is predicted in volumes with the highest liquid water content (LWC) and strongest updraft at a given height, whereas mixing in strongly diluted volumes is typically close to extremely inhomogeneous. The simulated homogeneity of mixing has a small impact on mean microphysical characteristics. This result agrees with the previous study applying prescribed mixing scenarios and can be explained by the high humidity of the clear air involved in the subgrid-scale mixing.

Radiative Impacts on the Growth of Drops within Simulated Marine Stratocumulus. Part I: Maximum Solar Heating

2005 ◽  
Vol 62 (7) ◽  
pp. 2323-2338 ◽  
Author(s):  
Christopher M. Hartman ◽  
Jerry Y. Harrington
Keyword(s):  
Drop Size ◽  
Onset Time ◽  
Solar Heating ◽  
Size Spectrum ◽  
Marine Stratocumulus ◽  
Eddy Simulation ◽  
Cloud Properties ◽  
Large Eddy ◽  
Radiative Impacts ◽  
The Mean

Abstract The effects of solar heating and infrared cooling on the vapor depositional growth of cloud drops, and hence the potential for collection enhancement, is investigated. Large eddy simulation (LES) of marine stratocumulus is used to generate 600 parcel trajectories that follow the mean motions of the cloud. Thermodynamic, dynamic, and radiative cloud properties are stored for each trajectory. An offline trajectory ensemble model (TEM) coupled to a bin microphysical model that includes the influences of radiation on drop growth is driven by the 600-parcel dataset. In line with previous results, including infrared cooling causes a reduction in the time for collection onset. This collection enhancement increases with drop concentration. Larger concentrations (400 cm−3) show a reduction in collection onset time of as much as 45 min. Including infrared cooling as well as solar heating in the LES and microphysical bin models has a number of effects on the growth of cloud drops. First, shortwave (SW) heating partially offsets cloud-top longwave (LW) cooling, which naturally reduces the influence of LW cooling on drop growth. Second, SW heating dominates over LW cooling at larger drop radii (≳200 μm), which causes moderately sized drops to evaporate. Third, unlike LW cooling, SW heating occurs throughout the cloud deck, which suppresses drop growth. All three of these effects tend to narrow the drop size spectrum. For intermediate drop concentrations (100–200 cm−3), it is shown that SW heating primarily suppresses collection initiation whereas at larger drop concentrations (≳250 cm−3) LW cooling dominates causing enhancements in collection.

scholarly journals Capturing Day-to-day Diurnal Variations in Stability in the Convective Atmospheric Boundary Layer Using Large Eddy Simulation

2018 ◽  
Vol 12 (1) ◽  
pp. 107-131 ◽  
Author(s):  
Jordan Nielson ◽  
Kiran Bhaganagar
Keyword(s):  
Heat Flux ◽  
Standard Deviation ◽  
Surface Heat Flux ◽  
Field Data ◽  
Geostrophic Wind ◽  
Surface Heat ◽  
Diurnal Cycles ◽  
Eddy Simulation ◽  
Large Eddy ◽  
The Mean

Introduction:Large Eddy Simulation (LES) modelers must begin to answer the question of how to better incorporate large datasets into simulations. This question is important because, at a given location, the diurnal, seasonal, and day-to-day variations of atmospheric stability have significant consequences for the power generated by wind turbines. The following study provides a methodology to obtain discrete values of surface flux, inversion height and geostrophic wind for LES using field data over multiple diurnal cycles (averaged over a month) at 12 Local Time (LT) (during the convective ABL). The methodology will allow the discrete LES to quantify the day-to-day variations over multiple diurnal cycles.Methods:The study tests the hypothesis that LES can capture the mean velocity and TKE profiles from the averaged variations in surface heat flux at 12 LT measured in the field (mean, +1 standard deviation, and -1 standard deviation). The discrete LES from the mean, +1 standard deviation, and -1 standard deviation surface heat flux represent the variations in the ABL due to the day-to-day variations in surface heat flux. The method calculates the surface heat flux for the NREL NWTC M5 dataset. The field data were used to generate Probability Density Functions (PDFs) of surface heat flux for the January and July 12 LT. The PDFs are used to select the surface heat fluxes as inputs into the discrete LES.Results / Conclusion:A correlation function between the surface heat flux and the boundary layer height was determined to select the initial inversion height, and the geostrophic departure function was used to determine the geostrophic wind for each surface heat flux. The LES profiles matched the averaged velocity profiles from the field data to 4% and the averaged TKE profiles to 6% and, therefore, validated the methodology. The method allows for further quantification of day-to-day stability variations using LES.

scholarly journals An alternative to the rejection of observations

1932 ◽  
Vol 137 (831) ◽  
pp. 78-87 ◽  
Keyword(s):  
Standard Deviation ◽  
Continuous Function ◽  
Large Deviations ◽  
Opposite Direction ◽  
Standard Error ◽  
The Other ◽  
Cause Of Error ◽  
The Mean ◽  
Normal Law ◽  
Usual Rule

1. It is widely felt that any method of rejecting observations with large deviations from the mean is open to some suspicion. Suppose that by some criterion, such as Peirce’s and Chauvenet’s, we decide to reject observations with deviations greater than 4 σ, where σ is the standard error, computed from the standard deviation by the usual rule; then we reject an observation deviating by 4·5 σ, and thereby alter the mean by about 4·5 σ/ n , where n is the number of observations, and at the same time we reduce the computed standard error. This may lead to the rejection of another observation deviating from the original mean by less than 4 σ, and if the process is repeated the mean may be shifted so much as to lead to doubt as to whether it is really sufficiently representative of the observations. In many cases, where we suspect that some abnormal cause has affected a fraction of the observations, there is a legitimate doubt as to whether it has affected a particular observation. Suppose that we have 50 observations. Then there is an even chance, according to the normal law, of a deviation exceeding 2·33 σ. But a deviation of 3 σ or more is not impossible, and if we make a mistake in rejecting it the mean of the remainder is not the most probable value. On the other hand, an observation deviating by only 2 σ may be affected by an abnormal cause of error, and then we should err in retaining it, even though no existing rule will instruct us to reject such an observation. It seems clear that the probability that a given observation has been affected by an abnormal cause of error is a continuous function of the deviation; it is never certain or impossible that it has been so affected, and a process that completely rejects certain observations, while retaining with full weight others with comparable deviations, possibly in the opposite direction, is unsatisfactory in principle.

scholarly journals Large-Eddy Simulations of a Drizzling, Stratocumulus-Topped Marine Boundary Layer

2009 ◽  
Vol 137 (3) ◽  
pp. 1083-1110 ◽  
Author(s):  
Andrew S. Ackerman ◽  
Margreet C. vanZanten ◽  
Bjorn Stevens ◽  
Verica Savic-Jovcic ◽  
Christopher S. Bretherton ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Marine Boundary Layer ◽  
Cloud Water ◽  
Large Eddy Simulations ◽  
Cloud Base ◽  
Entrainment Rate ◽  
Liquid Water Path ◽  
Average Maximum ◽  
Large Eddy ◽  
The Mean

Abstract Cloud water sedimentation and drizzle in a stratocumulus-topped boundary layer are the focus of an intercomparison of large-eddy simulations. The context is an idealized case study of nocturnal stratocumulus under a dry inversion, with embedded pockets of heavily drizzling open cellular convection. Results from 11 groups are used. Two models resolve the size distributions of cloud particles, and the others parameterize cloud water sedimentation and drizzle. For the ensemble of simulations with drizzle and cloud water sedimentation, the mean liquid water path (LWP) is remarkably steady and consistent with the measurements, the mean entrainment rate is at the low end of the measured range, and the ensemble-average maximum vertical wind variance is roughly half that measured. On average, precipitation at the surface and at cloud base is smaller, and the rate of precipitation evaporation greater, than measured. Including drizzle in the simulations reduces convective intensity, increases boundary layer stratification, and decreases LWP for nearly all models. Including cloud water sedimentation substantially decreases entrainment, decreases convective intensity, and increases LWP for most models. In nearly all cases, LWP responds more strongly to cloud water sedimentation than to drizzle. The omission of cloud water sedimentation in simulations is strongly discouraged, regardless of whether or not precipitation is present below cloud base.

scholarly journals Prediction of flow and dispersion in cross–ventilated buildings

2019 ◽  
Vol 128 ◽  
pp. 05002
Author(s):  
Ali Cemal Benim ◽  
Michael Diederich ◽  
Ali Nahavandi
Keyword(s):  
Computational Analysis ◽  
Turbulence Models ◽  
Reynolds Stress Model ◽  
Turbulence Structure ◽  
Detached Eddy Simulation ◽  
Mean Velocity ◽  
Eddy Simulation ◽  
Large Eddy ◽  
The Mean ◽  
Grid Independence

The present paper presents a detailed computational analysis of flow and dispersion in a generic isolated single–zone buildings. First, a grid generation strategy is discussed, that is inspired by a previous computational analysis and a grid independence study. Different turbulence models are appliedincluding two-equation turbulence models, the differential Reynolds Stress Model, Detached Eddy Simulation and Zonal Large Eddy Simulation. The mean velocity and concentration fields are calculated and compared with the measurements. A satisfactory agreement with the experiments is not observed by any of the modelling approaches, indicating the highly demanding flow and turbulence structure of the problem.

scholarly journals Catalogue of Clusters that are Members of Superclusters

1983 ◽  
Vol 104 ◽  
pp. 185-186
Author(s):  
M. Kalinkov ◽  
K. Stavrev ◽  
I. Kuneva
Keyword(s):  
Standard Deviation ◽  
Correlation Coefficient ◽  
The Other ◽  
Clusters Of Galaxies ◽  
Number Of Clusters ◽  
Abell Clusters ◽  
The Mean ◽  
Abell Cluster ◽  
Image Position

An attempt is made to establish the membership of Abell clusters in superclusters of galaxies. The relation is used to calibrate the distances to the clusters of galaxies with two redshift estimates. One is m10, the magnitude of the ten-ranked galaxy, and the other is the “mean population,” P, defined by: where p = 40, 65, 105 … galaxies for richness groups 0, 1, 2 …, and r is the apparent radius in degrees given by: The first iteration for redshift, z1, is obtained from m10 alone: The standard deviation for Eq. (1) is 0.105, the number of clusters with known velocities is 342 and the correlation coefficient between observed and fitted values is 0.921. With zi from Eq. (1), we define Cartesian galactic coordinates Xi = Rih−1 cosBi cosLi, Yi = Rih−1 cosBi sinLi, Zi = Rih−1 sinBi for each Abell cluster, i = 1, …, 2712, where Ri is the distance to the cluster (Mpc), and Ho = 100 h km s−1 Mpc−1.

Study of wave effect on vorticity in Langmuir turbulence using wave-phase-resolved large-eddy simulation

2019 ◽  
Vol 875 ◽  
pp. 173-224 ◽  
Author(s):  
Anqing Xuan ◽  
Bing-Qing Deng ◽  
Lian Shen
Keyword(s):  
Large Eddy Simulation ◽  
Correlation Effect ◽  
Wave Turbulence ◽  
Langmuir Turbulence ◽  
Streamwise Vorticity ◽  
Wave Phase ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Vorticity Dynamics ◽  
The Mean

The effects of a water surface wave on the vorticity in the turbulence underneath are studied for Langmuir turbulence using wave-phase-resolved large-eddy simulation. The simulations are performed on a dynamically evolving wave-surface-fitted grid such that the phase-resolved wave motions and their effects on the turbulence are explicitly captured. This study focuses on the vorticity structures and dynamics in Langmuir turbulence driven by a steady and co-aligned progressive wave and surface shear stress. For the first time, the detailed vorticity dynamics of the wave–turbulence interaction in Langmuir turbulence in a wave-phase-resolved frame is revealed. The wave-phase-resolved simulation provides detailed descriptions of many characteristic features of Langmuir turbulence, such as elongated quasi-streamwise vortices. The simulation also reveals the variation of the strength and the inclination angles of the vortices with the wave phase. The variation is found to be caused by the periodic stretching and tilting of the wave orbital straining motions. The cumulative effect of the wave on the wave-phase-averaged vorticity is analysed using the Lagrangian average. It is discovered that, in addition to the tilting effect induced by the Lagrangian mean shear gradient of the wave, the phase correlation between the vorticity fluctuations and the wave orbital straining is also important to the cumulative vorticity evolution. Both the fluctuation correlation effect and the mean tilting effect are found to amplify the streamwise vorticity. On the other hand, for the vertical vorticity, the fluctuation correlation effect cancels the mean tilting effect, and the net change of the vertical vorticity by the wave straining is negligible. As a result, the wave straining enhances only the streamwise vorticity and cumulatively tilts vertical vortices towards the streamwise direction. The above processes are further quantified analytically. The role of the fluctuation correlation effect in the wave-phase-averaged vorticity dynamics provides a deeper understanding of the physical processes underlying the wave–turbulence interaction in Langmuir turbulence.

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