Assessment of Gradient-Based Similarity Functions in the Stable Boundary Layer Derived from a Large-Eddy Simulation

2017 ◽  
Vol 163 (3) ◽  
pp. 375-392 ◽  
Author(s):  
Zbigniew Sorbjan
Keyword(s):  
Boundary Layer ◽  
Large Eddy Simulation ◽  
Stable Boundary Layer ◽  
Similarity Functions ◽  
Stable Boundary ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Gradient Based

scholarly journals Large-Eddy Simulation of the Stable Boundary Layer with Explicit Filtering and Reconstruction Turbulence Modeling

2011 ◽  
Vol 68 (9) ◽  
pp. 2142-2155 ◽  
Author(s):  
Bowen Zhou ◽  
Fotini Katopodes Chow
Keyword(s):  
Boundary Layer ◽  
Large Eddy Simulation ◽  
Flow Structure ◽  
Stable Boundary Layer ◽  
Strong Stability ◽  
Stable Boundary ◽  
Closure Models ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Good Agreement

Abstract Large-eddy simulation (LES) of the stably stratified atmospheric boundary layer is performed using an explicit filtering and reconstruction approach with a finite difference method. Turbulent stresses are split into the resolvable subfilter-scale and subgrid-scale stresses. The former are recovered from a reconstruction approach, and the latter are represented by a dynamic eddy-viscosity model. The resulting dynamic reconstruction model (DRM) can sustain resolved turbulence with less stringent resolution requirements than conventional closure models, even under strong atmospheric stability. This is achieved by proper representation of subfilter-scale (SFS) backscatter of turbulent kinetic energy (TKE). The flow structure and turbulence statistics for the moderately stable boundary layer (SBL) are analyzed with high-resolution simulations. The DRM simulations show good agreement with established empirical formulations such as flux and gradient-based surface similarity, even at relatively coarse resolution. Similar results can be obtained with traditional closure models at the cost of higher resolution. SBL turbulence under strong stability is also explored. Simulations show an intermittent presence of elevated TKE below the low-level jet. Overall, the explicit filtering and reconstruction approach is advantageous for simulations of the SBL. At coarse resolution, it can extend the working range of LES to stronger stability, while maintaining agreement to similarity theory; at fine resolution, good agreement with theoretical formulations provides confidence in the results and allows for detailed investigation of the flow structure under moderate to strong stability conditions.

scholarly journals Large-eddy simulation and stochastic modeling of Lagrangian particles for footprint determination in the stable boundary layer

2016 ◽  
Vol 9 (9) ◽  
pp. 2925-2949 ◽  
Author(s):  
Andrey Glazunov ◽  
Üllar Rannik ◽  
Victor Stepanenko ◽  
Vasily Lykosov ◽  
Mikko Auvinen ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Large Eddy Simulation ◽  
Stochastic Modeling ◽  
Stochastic Models ◽  
Stable Boundary Layer ◽  
Particle Dispersion ◽  
Small Scale ◽  
Stable Boundary ◽  
Eddy Simulation ◽  
Large Eddy

Abstract. Large-eddy simulation (LES) and Lagrangian stochastic modeling of passive particle dispersion were applied to the scalar flux footprint determination in the stable atmospheric boundary layer. The sensitivity of the LES results to the spatial resolution and to the parameterizations of small-scale turbulence was investigated. It was shown that the resolved and partially resolved (“subfilter-scale”) eddies are mainly responsible for particle dispersion in LES, implying that substantial improvement may be achieved by using recovering of small-scale velocity fluctuations. In LES with the explicit filtering, this recovering consists of the application of the known inverse filter operator. The footprint functions obtained in LES were compared with the functions calculated with the use of first-order single-particle Lagrangian stochastic models (LSMs) and zeroth-order Lagrangian stochastic models – the random displacement models (RDMs). According to the presented LES, the source area and footprints in the stable boundary layer can be substantially more extended than those predicted by the modern LSMs.

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