Generalizing Monin-Obukhov Similarity Theory (1954) for Complex Atmospheric Turbulence.

Monin-Obukhov similarity theory (MOST) forms the basis for parametrizations of turbulent exchange in virtually all numerical models of atmospheric flows. Yet, its limitations to flat and horizontally homogeneous terrain have plagued the theory since its inception. Here we present a first generalized extension of MOST based on the inclusion of turbulence anisotropy as an additional nondimensional term.

Incorporating the effect of heterogeneous surface heating into a semi-empirical model of the surface energy balance closure.

It was discovered several decades ago that eddy covariance measurements systematically underestimate sensible and latent heat fluxes, creating an imbalance in the surface energy budget. Since then, many studies have addressed this problem and proposed a variety of solutions to the problem, including improvements to instruments and correction methods applied during data postprocessing. However, none of these measures have led to the complete closure of the energy balance gap.

Anisotropy of Unstably Stratified Near-Surface Turbulence.

Classic Monin-Obukov similarity scaling states that in a stationary, horizontally homogeneous flow, in the absence of subsidence, turbulence is dictated by the balance between shear production and buoyancy production/destruction, whose ratio is characterized by a single universal scaling parameter. An evident breakdown in scaling is observed though, through large scatter in traditional scaling relations for the horizontal velocity variances under unstable stratification, or more generally in complex flow conditions. This breakdown suggests the existence of processes other than local shear and buoyancy that modulate near-surface turbulence.

Universal Return to Isotropy of Inhomogeneous Atmospheric Boundary Layer Turbulence.

A recalcitrant problem in the physics of turbulence is the representation of the tendency of large-scale anisotropic eddies to redistribute their energy content with decreasing scales, a phenomenon referred to as return to isotropy. An unprecedented dataset of atmospheric turbulence measurements covering flat to mountainous terrain, stratification spanning convective to very stable conditions, surface roughness ranging over several orders of magnitude, and Reynolds numbers that far exceed the limits of direct numerical simulations and laboratory experiments was assembled for the first time and used to explore the scalewise return to isotropy. The multiple routes to energy equipartitioning among velocity components are shown to be universal once the initial anisotropy at large scales, linked to turbulence generation, is accounted for.

Utility-scale solar PV performance enhancements through system-level modifications.

Performance of solar PV diminishes with the increase in temperature of the solar modules. Therefore, to further facilitate the reduction in cost of photovoltaic energy, new approaches to limit module temperature increase in natural ambient conditions should be explored. Thus far only approaches based at the individual panel level have been investigated, while the more complex, systems approach remains unexplored.

Dependence of near-surface similarity scaling on the anisotropy of atmospheric turbulence.

Turbulence data from the CASES-99 field experiment, over comparatively horizontally homogeneous and flat terrain, are separated based on the anisotropy of the Reynolds stress tensor (into isotropic, two-component axisymmetric and one-component turbulence) and flux-variance similarity scaling relations are tested. Results illustrate that different states of anisotropy correspond to different similarity relations, especially under unstable stratification. Experimental data with close to isotropic turbulence match similarity relationships well.

Scaling, Anisotropy, and Complexity in Near-Surface Atmospheric Turbulence.

The development of a unified similarity scaling has so far failed over complex surfaces, as scaling studies show large deviations from the empirical formulations developed over flat and horizontally homogeneous terrain as well as large deviations between the different complex terrain data sets. However, a recent study of turbulence anisotropy for flat and horizontally homogeneous terrain has shown that separating the data according to the limiting states of anisotropy (isotropic, two-component axisymmetric and one-component turbulence) improves near-surface scaling. In this paper we explore whether this finding can be extended to turbulence over inclined and horizontally heterogeneous surfaces by examining near-surface scaling for 12 different data sets obtained over terrain ranging from flat to mountainous.

Pathways for mitigating thermal losses in solar photovoltaics.

To improve the performance of solar photovoltaic devices one should mitigate three types of losses: optical, electrical and thermal. However, further reducing the optical and electrical losses in modern photovoltaic devices is becoming increasingly costly. Therefore, there is a rising interest in minimizing the thermal losses.