Vertical Mixing and Horizontal Transport for Weak-wind Stable Conditions

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New results in the literature have dramatically altered our conceptual framework for the stable nocturnal boundary layer, and also have identified serious inadequacies in our understanding for weak-wind strongly-stratified conditions. Similarity theory, which forms the basis for representation of the turbulent mixing in numerical models, is not supported by recent analyses for weak-wind very-stable conditions. Additional influences not in standard similarity theory include: a) intermittency on a variety of scales, b) downward transport of shear-generated turbulence from above the surface inversion layer, c) significant horizontal advection over even weak surface heterogeneity with strongly-stratified conditions, d) more efficient transport of momentum compared to transport of heat in some situations and e) coupling with small-scale mesoscale motions, such as gravity waves and meandering motions. The PI is evaluating the role of these influences in order to generalize commonly-used similarity theories for turbulent fluxes, and for several alternatives to similarity theory as well. These theories are being expanded to include probability distributions to account for the broad range of turbulence characteristics for a given set of external conditions when unpredictable gravity waves and meandering motions also are present. For this work he will use quality-controlled tower flux data from 20 sites that has been accumulated for a wide variety of surface types and climate regimes. The datasets include five micro-networks of flux towers for examination of the spatial structure of the turbulence and mesoscale motions. Computation of fluxes with a new more careful method is essential for this examination of weak turbulence. Intellectual Merit: The combination of improved analysis techniques and the networks of eddy-correlation measurements yields new insight into the space-time structure of turbulence and mesoscale meandering/gravity waves, and their interaction, for very stable conditions. These analyses improve our understanding of intermittency of turbulence and its influence on the flux-gradient relationship.Broader Impacts: The work will improve formulations of turbulent mixing and mesoscale transport in atmospheric models, particularly for cases of very weak mixing when risk of frost damage and ground fog formation are greatest. These are the cases where models suffer the largest errors in predicted surface variables. The new formulations of turbulent mixing and mesoscale transport improve modeling of dispersion of atmospheric contaminants in weak-wind nocturnal conditions when buildup of contaminant concentrations are greatest. In addition, the massive quality-controlled datasets are being made available to the research community. Two undergraduate students, and an international graduate student or post-doctoral researcher with separate funding, are working with this veteran researcher on this project.