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MS Defense

Department of Atmospheric Science

Tues., June 4, 10:00 am, EN6085

The Effect of Turbulence on Snow Accumulation Parameterized by Laboratory Measurements

Kristie Smith

University of Wyoming

Abstract

A physical understanding of snow settling is necessary for reliably forecasting snowfall. Laboratory and field measurements indicate that air turbulence can significantly alter the settling velocity of inertial particles in general, and snowflakes in particular. We test whether this knowledge impacts snowfall predictions. The Predicted Particle Properties (P3) cloud microphysics scheme is employed, and laboratory data obtained in a zero-mean flow chamber with isotropic turbulence are incorporated into the model. Idealized orographic snowfall simulations in both two and three dimensions are performed. Contrary to expectations, the average precipitation does not change due to the with the introduction of turbulence-enhanced fall speeds. Two mechanisms are explored to explain the resulting dichotomy: changes in microphysical process rates and differences in in-cloud residence times, both of which can affect the growth of hydrometeors. It is found that the microphysical process rates, namely deposition and sublimation, exhibit negligible differences between the simulations. However, snow sizes are decreased and accompanied by higher fall speeds in the simulations with turbulence-enhanced fall speeds; this is explained by reduced time in cloud, limited ice crystal growth, and a turbulence enhancement effect allowing these crystals to still fall faster compared to a control simulation. These findings are extended to a wintertime cyclone over the Mountain West of the United States, where the conclusions drawn form the idealized simulations are found to be generally applicable to the real case.

 

 

 

 

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