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Title: TURBULENT SCHMIDT NUMBER FROM A TRACER EXPERIMENT

Authors
item Flesch, Thomas - UNIVERSITY OF ALBERTA
item Prueger, John
item Hatfield, Jerry

Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 21, 2002
Publication Date: May 21, 2002
Citation: Flesch, T.K., Prueger, J.H., Hatfield, J.L. 2002. Turbulent Schmidt Number from a Tracer Experiment. Agricultural and Forest Meteorology. 111:299-307.

Interpretive Summary: Movement of gases from the earth's surface to the atmosphere is controlled by the windspeed and the roughness of the surface. The greater the roughness the more chaotic the motion of the wind and gases will tend to not follow a straight path through the air. One of the problems has been how to characterize the rate of movement of the air compared to the movement of the particles in the air. This is a complex problem that has implications for how particles like pesticides, pollen, or other biological materials are transported in the atmosphere. We found that it was difficult to assign a simple number to characterize how air moves relative to objects in the air. The current approaches that are used would underestimate the rate of movement of particles. When an improved estimate of this exchange parameter was used, a better representation of pesticide movement was found. If we improve our atmospheric models, then we can enhance our ability to predict how particles move in the atmosphere benefiting the scientific and air quality community in their understanding of transport processes in the atmosphere.

Technical Abstract: Measurements of pesticide emissions from bare-soil were used to calculate the turbulent Schmidt number (Sc): the ratio of eddy diffusivity (or eddy viscosity) for momentum to the diffusivity for tracer mass. The value of Sc has implications for the measurement of trace gas emissions, and there is a broad range of reported values for the atmosphere surface layer. During our experiment Sc averaged 0.6. There was large variability between our 19 observations, with values from 0.18 to 1.34. This variability makes it difficult to identify a trend in Sc with time, atmospheric stability, or wind conditions. Our results suggests that most flux-gradient formula, which assume higher values of Sc, give an underestimate of tracer emission flux rate Q. We also show that a dispersion model with Sc = 0.6 is better at estimating Q than a model with Sc = 0.45.

   
 
 
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