Modeling of the Subgrid-scale Pressure-Strain-Rate Correlation in the Atmospheric Surface Layer

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The research focuses on subgrid-scale modeling in large-eddy simulation (LES) of the atmospheric boundary layer (ABL). LES has become an effective research tool for the ABL and probably the most important simulation method for it. However, in the surface layer LES suffers from inherent under-resolution and poor subgrid-scale (SGS) model performance. This study will address this problem through analysis of field measurement data, modeling, and numerical simulations to improve SGS model performance.Issues in SGS modeling based on the SGS stress and flux transport equations will be analyzed. In particular, the focus will be put on modeling of the SGS pressure-strain-rate correlation, which is the main challenge in this modeling approach. Recent Advection Horizontal Array Turbulence Study (AHATS) field program has revealed new behavior of this variable as the cause of anisotropy in the SGS stress in the convective surface layer, contradicting the widely accepted understanding of its role of return to isotropy. With this knowledge, the physics of the SGS pressure-strain-rate correlation will further be investigated, and new transport equation models will be developed.Intellectual Merit:The research will address the critical issue of modeling the SGS pressure-strain-rate correlation in SGS stress transport equation-based SGS modeling for LES of the ABL. It is expected to significantly advance the understanding of the dynamics of the SGS stress and temperature flux. Due to the central role of the SGS pressure-strain-rate correlation in the SGS stress dynamics, new understanding of the physics of this correlation will have a profound impact on future SGS modeling. The model development activities will be a first step towards incorporating the new SGS physics into SGS models.Broader Impacts:The research has broader impacts in several areas. It will provide education and research opportunities for graduate and undergraduate students. Improved prediction of the surface layer turbulence and the ABL in general will be of importance to developing predictive models for atmospheric dispersion and diffusion, weather forecasting, atmospheric chemistry, wind energy, and land-atmosphere exchange. The modeling approach will also be important for modeling boundary layers with strong pressure gradient (e.g., curved boundary layers) in the ABL and in engineering flows. Advances in these areas will benefit the environment and society.