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Added by
Kenneth G. Libbrecht
Publication date
2019
fields
Physics
and research's language is
English
Authors
Kenneth G. Libbrecht
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This monograph reviews our current understanding of the physical dynamics of ice crystal growth, focusing on the spontaneous formation of complex structures from water vapor (called snow crystals) as a function of temperature, supersaturation, background gas pressure, and other extrinsic parameters. Snow crystal growth is a remarkably rich and rather poorly understood phenomenon, requiring a synthesis of concepts from materials science, crystal-growth theory, statistical mechanics, diffusion-limited solidification, finite-element modeling, and molecular surface processes. Building upon recent advances in precision measurement techniques, computation modeling methods, and molecular dynamics simulations of crystalline surfaces, I believe we are moving rapidly toward the long-sought goal of developing a full physical model of snow crystal formation, using ab initio molecular dynamics simulations to create a semi-empirical characterization of the nanoscale surface attachment kinetics, and then incorporating that into a full computational model that reproduces the growth of macroscopic crystalline structures. Section 1 of this monograph deals mainly with the material properties of ice Ih in equilibrium, including thermodynamics quantities, facet surface structures, terrace step energies, and crystal twinning behaviors.
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I describe a semi-empirical molecular model of the surface attachment kinetics governing ice crystal growth from water vapor as a function of temperature, supersaturation, and crystal mesostructure. An important new hypothesis in this model is surface-energy-driven molecular diffusion enabled by a leaky Ehrlich-Schwoebel barrier. The proposed surface-diffusion behavior is sensitive to facet width and surface premelting, yielding structure-dependent attachment kinetics with a complex temperature dependence. By incorporating several reasonable assumptions regarding the surface premelting behavior on basal and prism facets, this model can explain the overarching features of the snow crystal morphology diagram, which has been an enduring scientific puzzle for nearly 75 years.
I examine a variety of snow crystal growth measurements taken at a temperature of -5 C, as a function of supersaturation, background gas pressure, and crystal morphology. Both plate-like and columnar prismatic forms are observed under different conditions at this temperature, along with a diverse collection of complex dendritic structures. The observations can all be reasonably understood using a single comprehensive physical model for the basal and prism attachment kinetics, together with particle diffusion of water vapor through the surrounding medium and other well-understood physical processes. A critical model feature is structure-dependent attachment kinetics (SDAK), for which the molecular attachment kinetics on a faceted surface depend strongly on the nearby mesoscopic structure of the crystal.
I describe a new approach to the classification of snow crystal morphologies that focuses on the most common growth behaviors that appear in normal air under conditions of constant applied temperature and water-vapor supersaturation. The resulting morphological structures are generally robust with respect to small environmental changes and thus should be especially amenable to computational modeling. Because spontaneous structure formation depends on initial conditions, the choice of seed crystal can be an important consideration, and I have found that slender c-axis ice needles provide an exceptionally good starting point for this series of investigations. A sharp needle tip exposes a single basal surface that often simplifies subsequent morphological development, and the absence of a nearby substrate allows for the exploration of a broad range of supersaturations with well-controlled boundary conditions. The overarching goal of this endeavor is to facilitate detailed quantitative comparisons between laboratory ice-growth experiments and corresponding computational models, which will should greatly improve our understanding of the ice/vapor molecular attachment kinetics as well as our ability to model diffusion-limited growth dynamics in the ice/vapor system. This specific case-study of water ice connects broadly to many areas in aqueous chemistry, cryobiology, and environmental science, while the physical principles of molecular attachment kinetics and diffusion-limited growth apply more generally to other systems in crystal growth and materials science.
The effect of turbulence on snow precipitation is not incorporated into present weather forecasting models. Here we show evidence that turbulence is in fact a key influence on both fall speed and spatial distribution of settling snow. We consider three snowfall events under vastly different levels of atmospheric turbulence. We characterize the size and morphology of the snow particles, and we simultaneously image their velocity, acceleration, and relative concentration over vertical planes about 30 m2 in area. We find that turbulence-driven settling enhancement explains otherwise contradictory trends between the particle size and velocity. The estimates of the Stokes number and the correlation between vertical velocity and local concentration indicate that the enhanced settling is rooted in the preferential sweeping mechanism. When the snow vertical velocity is large compared to the characteristic turbulence velocity, the crossing trajectories effect results in strong accelerations. When the conditions of preferential sweeping are met, the concentration field is highly non-uniform and clustering appears over a wide range of scales. These clusters, identified for the first time in a naturally occurring flow, display the signature features seen in canonical settings: power-law size distribution, fractal-like shape, vertical elongation, and large fall speed that increases with the cluster size. These findings demonstrate that the fundamental phenomenology of particle-laden turbulence can be leveraged towards a better predictive understanding of snow precipitation and ground snow accumulation. They also demonstrate how environmental flows can be used to investigate dispersed multiphase flows at Reynolds numbers not accessible in laboratory experiments or numerical simulations.
We present a field study of snow settling dynamics based on simultaneous measurements of the atmospheric flow field and snow particle trajectories. Specifically, a super-large-scale particle image velocimetry (SLPIV) system using natural snow particles as tracers is deployed to quantify the velocity field and identify vortex structures in a 22 m $times$ 39 m field of view centered 18 m above the ground. Simultaneously, we track individual snow particles in a 3 m $times$ 5 m sample area within the SLPIV using particle tracking velocimetry (PTV). The results reveal the direct linkage among vortex structures in atmospheric turbulence, the spatial distribution of snow particle concentration, and their settling dynamics. In particular, with snow turbulence interaction at near-critical Stokes number, the settling velocity enhancement of snow particles is multifold, and larger than what has been observed in previous field studies. SLPIV measurements show higher concentration of snow particles preferentially located on the downward side of the vortices identified in the atmospheric flow field. PTV, performed on high resolution images around the reconstructed vortices, confirms the latter trend and provides statistical evidence of the acceleration of snow particles, as they move toward the downward side of vortices. Overall, the simultaneous multi-scale particle imaging presented here enables us to directly quantify the salient features of preferential sweeping, supporting it as an underlying mechanism of snow settling enhancement in the atmospheric surface layer.
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