scholarly journals Perspectives on machine learning-augmented Reynolds-averaged and large eddy simulation models of turbulence

2021 ◽  
Vol 6 (5) ◽  
Author(s):  
Karthik Duraisamy
Keyword(s):  
Machine Learning ◽  
Large Eddy Simulation ◽  
Simulation Models ◽  
Eddy Simulation ◽  
Large Eddy

scholarly journals Assessment of Grid Anisotropy Effects on Large-Eddy-Simulation Models with Different Length Scales

AIAA Journal ◽  
2020 ◽  
Vol 58 (10) ◽  
pp. 4522-4533
Author(s):  
Jan-Erik Schumann ◽  
Siavash Toosi ◽  
Johan Larsson
Keyword(s):  
Large Eddy Simulation ◽  
Simulation Models ◽  
Length Scales ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Grid Anisotropy

Evaluation of the WRF PBL Parameterizations for Marine Boundary Layer Clouds: Cumulus and Stratocumulus

2013 ◽  
Vol 141 (7) ◽  
pp. 2265-2271 ◽  
Author(s):  
Hsin-Yuan Huang ◽  
Alex Hall ◽  
Joao Teixeira
Keyword(s):  
Boundary Layer ◽  
Large Eddy Simulation ◽  
Marine Boundary Layer ◽  
Layer Structure ◽  
Model Performance ◽  
Simulation Models ◽  
Eddy Diffusivity ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Boundary Layer Cloud

Abstract The performance of five boundary layer parameterizations in the Weather Research and Forecasting Model is examined for marine boundary layer cloud regions running in single-column mode. Most parameterizations show a poor agreement of the vertical boundary layer structure when compared with large-eddy simulation models. These comparisons against large-eddy simulation show that a parameterization based on the eddy-diffusivity/mass-flux approach provides a better performance. The results also illustrate the key role of boundary layer parameterizations in model performance.

scholarly journals On the application of the classic Kessler and Berry schemes in Large Eddy Simulation models with a particular emphasis on cloud autoconversion, the onset time of precipitation and droplet evaporation

1998 ◽  
Vol 16 (5) ◽  
pp. 628-637 ◽  
Author(s):  
S. Ghosh ◽  
P. R. Jonas
Keyword(s):  
Large Eddy Simulation ◽  
Onset Time ◽  
Simulation Models ◽  
Droplet Evaporation ◽  
Atmospheric Composition ◽  
Accurate Estimation ◽  
Eddy Simulation ◽  
Deep Model ◽  
Composition And Structure ◽  
Large Eddy

Abstract. Many Large Eddy Simulation (LES) models use the classic Kessler parameterisation either as it is or in a modified form to model the process of cloud water autoconversion into precipitation. The Kessler scheme, being linear, is particularly useful and is computationally straightforward to implement. However, a major limitation with this scheme lies in its inability to predict different autoconversion rates for maritime and continental clouds. In contrast, the Berry formulation overcomes this difficulty, although it is cubic. Due to their different forms, it is difficult to match the two solutions to each other. In this paper we single out the processes of cloud conversion and accretion operating in a deep model cloud and neglect the advection terms for simplicity. This facilitates exact analytical integration and we are able to derive new expressions for the time of onset of precipitation using both the Kessler and Berry formulations. We then discuss the conditions when the two schemes are equivalent. Finally, we also critically examine the process of droplet evaporation within the framework of the classic Kessler scheme. We improve the existing parameterisation with an accurate estimation of the diffusional mass transport of water vapour. We then demonstrate the overall robustness of our calculations by comparing our results with the experimental observations of Beard and Pruppacher, and find excellent agreement.Key words. Atmospheric composition and structure · Cloud physics and chemistry · Pollution · Meteorology and atmospheric dynamics · Precipitation

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