Raymond A. Shaw

▪ Abstract Turbulence is ubiquitous in atmospheric clouds, which have enormous turbulence Reynolds numbers owing to the large range of spatial scales present. Indeed, the ratio of energy-containing and dissipative length scales is on the order of 10 5 for a typical convective cloud, with a corresponding large-eddy Reynolds number on the order of 10 6 to 10 7 . A characteristic trait of high-Reynolds-number turbulence is strong intermittency in energy dissipation, Lagrangian acceleration, and scalar gradients at small scales. Microscale properties of clouds are determined to a great extent by thermodynamic and fluid-mechanical interactions between droplets and the surrounding air, all of which take place at small spatial scales. Furthermore, these microscale properties of clouds affect the efficiency with which clouds produce rain as well as the nature of their interaction with atmospheric radiation and chemical species. It is expected, therefore, that fine-scale turbulence is of direct importance to the evolution of, for example, the droplet size distribution in a cloud. In general, there are two levels of interaction that are considered in this review: (a) the growth of cloud droplets by condensation and (b) the growth of large drops through the collision and coalescence of cloud droplets. Recent research suggests that the influence of fine-scale turbulence on the condensation process may be limited, although several possible mechanisms have not been studied in detail in the laboratory or the field. There is a growing consensus, however, that the collision rate and collision efficiency of cloud droplets can be increased by turbulence-particle interactions. Adding strength to this notion is the growing experimental evidence for droplet clustering at centimeter scales and below, most likely due to strong fluid accelerations in turbulent clouds. Both types of interaction, condensation and collision-coalescence, remain open areas of research with many possible implications for the physics of atmospheric clouds.

REASONS FOR PERFORMING STUDY: Previous studies have suggested that agreement between equine veterinarians subjectively evaluating lameness in horses is low. These studies were limited to small numbers of horses, evaluating movement on the treadmill or to evaluating previously-recorded videotape. OBJECTIVES: To estimate agreement between equine practitioners performing lameness evaluations in horses in the live, over ground setting. METHODS: 131 mature horses were evaluated for lameness by 2-5 clinicians (mean 3.2) with a weighted-average of 18.7 years of experience. Clinicians graded each limb using the AAEP lameness scale by first watching the horse trot in a straight line only and then after full lameness evaluation. Agreement was estimated by calculation of Fleiss' (kappa). Evaluators agreed if they picked the same limb as lame or not lame regardless of the severity of perceived lameness. RESULTS: After only evaluating the horse trot in a straight line clinicians agreed whether a limb was lame or not 76.6% of the time (kappa= 0.44). After full lameness evaluation clinicians agreed whether a limb was lame or not 72.9% of the time (kappa= 0.45). Agreement on forelimb lameness was slightly higher than on hindlimb lameness. When the mean AAEP lameness score was >1.5 clinicians agreed whether or not a limb was lame 93.1% of the time (kappa= 0.86), but when the mean score was < or = 1.5 they agreed 61.9% (kappa= 0.23) of the time. When given the task of picking whether or not the horse was lame and picking the worst limb after full lameness evaluation, clinicians agreed 51.6% (kappa= 0.37) of the time. CONCLUSIONS: For horses with mild lameness subjective evaluation of lameness is not very reliable. POTENTIAL RELEVANCE: A search for and the development of more objective and reliable methods of lameness evaluation is justified and should be encouraged and supported.

Ice formation in atmospheric clouds is crucial to our understanding of precipitation and cloud radiative properties. In recent work it was shown that heterogeneous ice nucleation rates can be strongly enhanced by a form of surface crystallization (Shaw et al., 2005). Here we present new laboratory data and consider the implications for contact nucleation and its relevance to ice nucleation in atmospheric clouds. Our observations contradict three leading hypotheses for contact nucleation and suggest, instead, that the notion of contact nucleation should be generalized to include surface crystallization from particles contacting a supercooled drop from the inside out, as well as from the outside in. Our findings lead to the hypothesis that the freezing temperature of an evaporating drop will suddenly become higher once the drop surface contacts an immersed ice nucleus. This mechanism for evaporation freezing is therefore a plausible explanation for the abundant observations of high ice concentrations associated with cloud dilution and droplet evaporation.

We report laboratory observations of higher freezing temperatures when an ice-forming nucleus is near the surface of an undercooled water drop than when the nucleus is immersed in the drop. The nucleation rate at the water surface is a factor of 10(10) greater than in bulk water, thereby complementing and providing evidence for homogeneous surface crystallization, which has been hypothesized recently. Interpretation of the data via classical nucleation theory shows that the free energy of formation of a critical ice germ is decreased by a factor of approximately 2 when the substrate is near the air-water interface. Furthermore, the analysis suggests that the jump frequency of molecules from the liquid to the solid may be greatly enhanced at the interface.

A mechanism is presented, based on the inherent turbulent nature of cumulus clouds, for the broadening of cloud droplet spectra during condensational growth. This mechanism operates independent of entrainment and, therefore, can operate in adiabatic cloud cores. Cloud droplets of sufficient size are not randomly dispersed in a cloud but are preferentially concentrated in regions of low vorticity in the turbulent flow field. Regions of high vorticity (low droplet concentration) develop higher supersaturation than regions of low vorticity (high droplet concentration). Therefore, on small spatial scales cloud droplets are growing in a strongly fluctuating supersaturation field. These fluctuations in supersaturation exist independent of large-scale vertical velocity fluctuations. Droplets growing in regions of high vorticity will experience enhanced growth rates, allowing some droplets to grow larger than predicted by the classic theory of condensational growth. This mechanism helps to account for two common observations in clouds: the presence of a large droplet tail in the droplet spectrum, important for the onset of collision–coalescence, and the possibility of new nucleation above cloud base, allowing for the formation of a bimodal droplet spectrum.