Collaborative Research: Measurements and Modeling of Subgrid-scale Turbulence in the Atmospheric Surface Layer

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This research will be conducted collaboratively at Clemson University, the Pennsylvania State University, and the National Center for Atmospheric Research. It focuses on issues met in using large-eddy simulation (LES) to predict the statistics 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. In LES, processes occurring on scales too small to be resolved by the numerical grid are diagnosed based on larger scale processes that can be resolved by the grid, using a subgrid-scale (SGS) model. However, near the ground, in the atmospheric surface layer, LES suffers from inherent under-resolution and poor SGS model performance. An integrated research program will be conducted consisting of field measurements and numerical simulations to improve SGS model performance. This research investigates the impact of the SGS turbulence on the resolvable-scale statistics in the surface layer by using field measurements to analyze the transport equations of SGS stress and flux, and the transport equation of the joint probability density function (JPDF) of resolvable-scale velocity and scalars. The field program will employ the array technique developed during prior NSF-supported research to measure the resolvable- and subgrid-scale variables. It will, for the first time, include measurements of the advection of the SGS stress and flux, which is essential for studying the SGS dynamics and for evaluating the new SGS models. The observations will be further analyzed by obtaining modeled SGS stress and flux using LES fields as model inputs to compute the SGS variables in the JPDF equation, which then will be compared with observations. This research is expected to significantly advance the understanding of the dynamics of the SGS stress and temperature flux, and their impact on the resolvable-scale dynamics. The research has broader impacts in several areas. It will provide education and research opportunities for two graduate students. New data analyses and processing methods developed in this research will further the understanding of the potentials and limitations of the array measurement technique as an essential tool for other important boundary layer applications such as area-averaged flux measurements. Improved LES will be important for improving predictive tools for applications to air-pollution modeling, weather forecasting, and land-atmosphere interaction modeling. These improved tools will greatly benefit society.