A new method to estimate diffusion in stable, low-wind conditions

Sonic anemometer observations were made 10 m above ground level for a perio d of 1 yr. From these data, Eulerian autocorrelation functions were compute d for the horizontal and vertical wind velocity fluctuations for low wind s peeds. Although the autocorrelation function for the vertical velocity comp onent exhibited the well-known exponential form, the function for the horiz ontal components of the wind vector showed a negative loop for all stabilit y classes at low wind speeds. This result might be an effect of low-frequen cy meandering of the flow. Observations of the standard deviations of the v ertical wind component confirmed the proportionality with the friction velo city, though with a slightly lower constant of proportionality than has bee n found by other authors. A Lagrangian dispersion model (LDM) with random t ime steps and a negative intercorrelation parameter rho (u,nu) for the hori zontal wind components was used to take the first of the above-mentioned fi ndings into account. In a simple test case, it could be shown that using a negative tail in the autocorrelation function for the horizontal wind fluct uations in an LDM results in larger plume spreads as if the usual exponenti al law were used. This model characteristic is in agreement with enhanced d ispersion in low-wind situations as found by different authors earlier. Bec ause the model reduces to the Langevin equation for rho (u,nu) = 0.9, it ha s the advantage that it can be used for all wind speeds by simply adjusting the intercorrelation parameter. Last, the model was tested against field e xperiment data gathered by the Idaho National Engineering Laboratory during stable, low-wind conditions. The results with the new method for these exp eriments are very promising in comparison with methods used by other author s earlier.