A New Method to Estimate Diffusion in Stable, Low-Wind Conditions

Abstract

Sonic anemometer observations were made 10 m above ground level for a period of 1 yr. From these data, Eulerian autocorrelation functions were computed for the horizontal and vertical wind velocity fluctuations for low wind speeds. Although the autocorrelation function for the vertical velocity component exhibited the well-known exponential form, the function for the horizontal components of the wind vector showed a negative loop for all stability classes at low wind speeds. This result might be an effect of low-frequency meandering of the flow. Observations of the standard deviations of the vertical wind component confirmed the proportionality with the friction velocity, though with a slightly lower constant of proportionality than has been found by other authors. A Lagrangian dispersion model (LDM) with random time steps and a negative intercorrelation parameter ?u,? for the horizontal wind components was used to take the first of the above-mentioned findings into account. In a simple test case, it could be shown that using a negative tail in the autocorrelation function for the horizontal wind fluctuations in an LDM results in larger plume spreads as if the usual exponential law were used. This model characteristic is in agreement with enhanced dispersion in low-wind situations as found by different authors earlier. Because the model reduces to the Langevin equation for ?u,? = 0.9, it has the advantage that it can be used for all wind speeds by simply adjusting the intercorrelation parameter. Last, the model was tested against field experiment data gathered by the Idaho National Engineering Laboratory during stable, low-wind conditions. The results with the new method for these experiments are very promising in comparison with methods used by other authors earlier.