AGS-PRF: The Building Blocks of Shear-Driven Atmospheric Turbulence

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Irregular wind velocities and swirling motions contribute to an erratic phenomenon known as turbulence. Considered one of the most confounding problems in physics, turbulence remains a research frontier in many fields despite centuries of study. Yet society exists within the turbulence of atmospheric winds. For instance, the interaction of these winds with the earth surface affects local, short-term weather and global, long-term climate, determines the dispersion of pollutants and other chemicals in the atmosphere, alters the transport of organic matter such as dust and seeds, and influences the water security of ecosystems stressed by evapotranspiration. It suffices to state that turbulence is crucial to life on Earth as we know it. Traditional atmospheric models account for the erratic behavior of turbulence in terms of statistics such as averages and standard deviations, but these models have no connection to the instantaneous features – such as persistent swirling vortices – or the dynamics that lead to the statistics. The present project uses recent visualizations of turbulent flows to identify a representative turbulent feature or “building block” (a sort of DNA of eddies) to represent turbulence as a series of these building blocks. The research will address how turbulence phenomenology drives the mechanisms of complex processes such as pollutant transport. The building block framework will also inform modeling approaches that are implemented in large-scale simulations pertaining to weather and climate.Recent studies revealed that shear-driven atmospheric turbulence is predominately self-organized into relatively uniform flow regions separated by smaller-scale layers of concentrated shear and vorticity. The research will build on these studies to investigate a combined deterministic and stochastic framework for representing turbulence. This framework will bridge the observed self-organized structures, time-averaged and scale-dependent statistics, and similarity relations in atmospheric turbulence. While the organization of the flow into these two structural types, i.e. the building blocks, is deterministic, the size and intensity of the structures will be described stochastically. The project includes simulating a stably stratified atmospheric boundary layer to explore the effects of buoyancy on the self-organized structures. The research will lead to an improved phenomenological understanding of empirical similarity relations, specifically how modifications to the instantaneous structures due to buoyancy lead to quantitative changes in important time-averaged statistics such as the mean velocity profile and turbulent transport of momentum, energy, and mass.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.