Multi-Point Monin-Obukhov Similarity and Spectral Dynamics in the Convective Atmospheric Surface Layer

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The research focuses on the Monin-Obukhov similarity hypothesis, which is the theoretical foundation for understanding the surface layer of the atmospheric boundary layer (ABL). The hypothesis has been used successfully to scale many statistics (e.g., those containing the vertical velocity) in the surface layer. However, it fails to scale some other important statistics, such as the horizontal velocity variances and the large-scale horizontal velocity spectra in the convective surface layer.The research will provide a more universal scaling framework for the influence of shear and buoyancy on the surface layer turbulence, termed multi-point Monin-Obukhov similarity (MMO). In the research, the PI will systematically investigate MMO through its spectral predictions and the spectral dynamics in the surface layer. Systematical tests of the predicted large-scale velocity and temperature spectra using high-resolution large-eddy simulation (LES) fields will be conducted. The research will be conducted in collaboration with Dr. Martin Otte at Computer Science Corporation (CSC), a research firm contracting with the Environmental Protection Agency.Intellectual Merit:The research addresses the critical issue of Monin-Obukhov similarity of the atmospheric surface layer. It is expected to further validate MMO through its prediction of the turbulence spectra and cospectra; it will provide an important understanding of the physical basis for MMO. Due to the central role of the Monin-Obukhov similarity in our understanding of the surface layer dynamics, the research on MMO will provide a new framework for analyzing and understanding the surface layer turbulence, and will have a strong impact on the understanding and modeling of the ABL in general.Broader Impacts:The research has broader impacts in several areas. It will provide education and research opportunities for graduate and undergraduate students. Improved understanding 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 a strong pressure gradient (e.g., curved boundary layers) in the atmosphere and in engineering flows. Advances in these areas will benefit the environment and society.