A universal scaling law for Lagrangian snowflake accelerations in atmospheric turbulence

Author:

Singh Dhiraj K.1ORCID,Pardyjak Eric R.1ORCID,Garrett Timothy J.2ORCID

Affiliation:

1. Department of Mechanical Engineering, University of Utah 1 , Salt Lake City, Utah 84112, USA

2. Department of Atmospheric Sciences, University of Utah 2 , Salt Lake City, Utah 84112, USA

Abstract

We use a novel experimental setup to obtain the vertical velocity and acceleration statistics of snowflakes settling in atmospheric surface-layer turbulence, for Taylor microscale Reynolds numbers (Reλ) between 400 and 67 000, Stokes numbers (St) between 0.12 and 3.50, and a broad range of snowflake habits. Despite the complexity of snowflake structures and the non-uniform nature of the turbulence, we find that mean snowflake acceleration distributions can be uniquely determined from the value of St. Ensemble-averaged snowflake root mean square (rms) accelerations scale nearly linearly with St. Normalized by the rms value, the acceleration distribution is nearly exponential, with a scaling factor for the (exponent) of −3/2 that is independent of Reλ and St; kurtosis scales with Reλ, albeit weakly compared to fluid tracers in turbulence; gravitational drift with sweeping is observed for St < 1. Surprisingly, the same exponential distribution describes a pseudo-acceleration calculated from fluctuations of snowflake terminal fall speed in still air. This equivalence suggests an underlying connection between how turbulence determines the trajectories of particles and the microphysics determining the evolution of their shapes and sizes.

Funder

National Science Foundation

Publisher

AIP Publishing

Subject

Condensed Matter Physics,Fluid Flow and Transfer Processes,Mechanics of Materials,Computational Mechanics,Mechanical Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Turbulence effect on disk settling dynamics;Journal of Fluid Mechanics;2024-08-10

2. Finite domains cause bias in measured and modeled distributions of cloud sizes;Atmospheric Chemistry and Physics;2024-07-26

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