Study of Atmospheric Turbulence in the Stable Boundary Layer

Marquette University, Milwaukee WI

Investigators

Abstract

The main objective is to study the structure of the stably stratified boundary layer based on results of field measurements and numerical simulations. For this purpose, observations obtained during two recent atmospheric boundary layer experiments will be analyzed. Turbulence data collected during these projects on instrumented towers and by the Tethered Lifting System (TLS) will be examined. Two numerical models: (i) a one-dimensional stochastic model, developed by Dr. A. Kerstein, and (ii) the three-dimensional large-eddy simulation (LES) model, developed by the principal investigator, will also be used. The first model will be used to simulate the observed temporal transformation in the nocturnal boundary layer during these projects. The LES model will be employed to evaluate gradient-based similarity functions. The specific aim of the proposed program is to systematically improve understanding, description, and parameterization of the stably stratified boundary layer. Investigations will be conducted of transitions from strong to weak stable turbulence. Asymptotic laws for turbulent statistics in these conditions will be defined. The classic similarity approach will be improved by developing and testing new scaling systems and techniques, which will reduce negative effects of diminishing scales and self-correlation. The intellectual merit of the project is improved understanding of processes and regimes in the nocturnal boundary layer, which currently are insufficiently understood and are not well-represented in current numerical models of the atmosphere. The broader impact of the project is application of this improved conceptual understanding of turbulence and diffusion in the stable boundary layer to important problems. Results will be disseminated through publications and presentations at scientific conferences. These results will be used to develop boundary layer parameterizations, which are essential in numerical weather predictions, climate simulations, and air pollution studies. The developed methods could also be applied in studies of tropospheric turbulence