New consideration of lateral boundary treatment for meso- and micro-scale nested PBL simulations over complex terrain

2021 ◽  
Vol 254 ◽  
pp. 105507
Author(s):  
Zihan Zhao ◽  
Yiqing Xiao ◽  
Chao Li ◽  
Jinghan Wang ◽  
Gang Hu
2009 ◽  
Vol 137 (1) ◽  
pp. 315-330 ◽  
Author(s):  
F. Voitus ◽  
P. Termonia ◽  
P. Bénard

Abstract The aim of this paper is to investigate the feasibility of well-posed lateral boundary conditions in a Fourier spectral semi-implicit semi-Lagrangian one-dimensional model. Two aspects are analyzed: (i) the complication of designing well-posed boundary conditions for a spectral semi-implicit scheme and (ii) the implications of such a lateral boundary treatment for the semi-Lagrangian trajectory computations at the lateral boundaries. Straightforwardly imposing boundary conditions in the gridpoint-explicit part of the semi-implicit time-marching scheme leads to numerical instabilities for time steps that are relevant in today’s numerical weather prediction applications. It is shown that an iterative scheme is capable of curing these instabilities. This new iterative boundary treatment has been tested in the framework of the one-dimensional shallow-water equations leading to a significant improvement in terms of stability. As far as the semi-Lagrangian part of the time scheme is concerned, the use of a trajectory truncation scheme has been found to be stable in experimental tests, even for large values of the advective Courant number. It is also demonstrated that a well-posed buffer zone can be successfully applied in this spectral context. A promising (but not easily implemented) alternative to these three above-referenced schemes has been tested and is also presented here.


2008 ◽  
Vol 47 (12) ◽  
pp. 3150-3169 ◽  
Author(s):  
Takenobu Michioka ◽  
Fotini Katopodes Chow

Abstract This paper presents high-resolution numerical simulations of the atmospheric flow and concentration fields accompanying scalar transport and diffusion from a point source in complex terrain. Scalar dispersion is affected not only by mean flow, but also by turbulent fluxes that affect scalar mixing, meaning that predictions of scalar transport require greater attention to the choice of numerical simulation parameters than is typically needed for mean wind field predictions. Large-eddy simulation is used in a mesoscale setting, providing modeling advantages through the use of robust turbulence models combined with the influence of synoptic flow forcing and heterogeneous land surface forcing. An Eulerian model for scalar transport and diffusion is implemented in the Advanced Regional Prediction System mesoscale code to compare scalar concentrations with data collected during field experiments conducted at Mount Tsukuba, Japan, in 1989. The simulations use horizontal grid resolution as fine as 25 m with up to eight grid nesting levels to incorporate time-dependent meteorological forcing. The results show that simulated ground concentration values contain significant errors relative to measured values because the mesoscale wind typically contains a wind direction bias of a few dozen degrees. Comparisons of simulation results with observations of arc maximum concentrations, however, lie within acceptable error bounds. In addition, this paper investigates the effects on scalar dispersion of computational mixing and lateral boundary conditions, which have received little attention in the literature—in particular, for high-resolution applications. The choice of lateral boundary condition update interval is found not to affect time-averaged quantities but to affect the scalar transport strongly. More frequent updates improve the simulated ground concentration values. In addition, results show that the computational mixing coefficient must be set to as small a value as possible to improve scalar dispersion predictions. The predicted concentration fields are compared as the horizontal grid resolution is increased from 190 m to as fine as 25 m. The difference observed in the results at these levels of grid refinement is found to be small relative to the effects of computational mixing and lateral boundary updates.


2010 ◽  
Vol 13 (6) ◽  
pp. 519-528 ◽  
Author(s):  
Lei Li ◽  
Li-Jie Zhang ◽  
Ning Zhang ◽  
Fei Hu ◽  
Yin Jiang ◽  
...  

2019 ◽  
Vol 238 ◽  
pp. 806-815 ◽  
Author(s):  
Xiao-Yu Tang ◽  
Shumian Zhao ◽  
Bo Fan ◽  
Joachim Peinke ◽  
Bernhard Stoevesandt

Author(s):  
Rey DeLeon ◽  
Kyle Felzien ◽  
Inanc Senocak

A short-term wind power forecasting capability can be a valuable tool in the renewable energy industry to address load-balancing issues that arise from intermittent wind fields. Although numerical weather prediction models have been used to forecast winds, their applicability to micro-scale atmospheric boundary layer flows and ability to predict wind speeds at turbine hub height with a desired accuracy is not clear. To address this issue, we develop a multi-GPU parallel flow solver to forecast winds over complex terrain at the micro-scale, where computational domain size can range from meters to several kilometers. In the solver, we adopt the immersed boundary method and the Lagrangian dynamic large-eddy simulation model and extend them to atmospheric flows. The computations are accelerated on GPU clusters with a dual-level parallel implementation that interleaves MPI with CUDA. We evaluate the flow solver components against test problems and obtain preliminary results of flow over Bolund Hill, a coastal hill in Denmark.


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