Turbulence near the earth's surface under low wind speed conditions (which are common to nighttime and other stably stratified conditions) is primarily generated by gravity waves and other small-scale non-turbulent motions. Although such processes have received little attention and are poorly understood, the nocturnal near-calm regime is common, particularly with high-pressure systems over flat terrain and under a wider variety of synoptic conditions in small basins and valleys with weak down-valley slope. The time-averaged surface flux is then dominated by infrequent mixing events of unknown origin. Existing methods of data analysis have generally failed to identify the basic physics of generation of mixing events under such conditions. Proper attribution of the root causes of the mixing events requires more emphasis on spatial variation than provided in existing analysis strategies. This project will provide such emphasis by initially focusing on dense networks of sonic anemometers and auxiliary data to more comprehensively characterize the temporal and spatial variability of the turbulence as well as mean turbulence quantities. Obtained representations will include scale-dependent probability distributions and stochastic models with extreme-value capabilities. Such approaches require very large data sets, which have been recently acquired. Since the non-turbulent motions and event mixing can be site dependent, a more limited version of the analysis will be applied to ~20 different field programs representing a wide range of surface conditions. To obtain more even finer spatial information, the investigator plans to deploy fiber-optic cables capable of providing high density information on temperature fluctuations and video based semi-Lagrangian tracking of machine-generated fog elements, all embedded within a new network of sonic anemometers and pressure sensors. These measurements will be integrated with tower profiles of turbulence quantities and deeper profiling from sodars to examine the generation of mixing events in a quasi-three dimensional framework.
The intellectual merit of this effort centers on pioneering work to understand and stochastically describe those complex flow features involving superposition of waves, microfronts and other complex non-deterministic signatures thought to be common under near-calm conditions via application of new observational tools and non-standard analysis techniques. Broader impacts will include contributions toward improved model parameterizations of surface fluxes and dispersion under weak winds conditions and improved ability to anticipate localized surface cooling associated with dense fog formation or frost damage to crops. An existing instructional video of near-surface motions based on machine-generated fog, currently used by a number of universities in boundary-layer course work, will be expanded into a set of more professional instructional videos on local atmospheric flows for broader distribution and use. A joint effort with a local high school will provide media suitable secondary school settings and public demonstrations.
