Statistical evaluation of sigma schemes for estimating dispersion in low wind conditions

Previously described sigma schemes for the estimation of dispersion parameters in low wind-speed situations are evaluated statistically with the data obtained in a series of diffusion experiments (conducted by U.S. National Oceanic and Atmospheric Administration) under stable and low wind-speed conditions. The qualitative performances of the sigma schemes were intercompared in an earlier study using the same data. Various performance measures for the statistical evaluation of air-quality models are described. The evaluation exercise is carried out, essentially, on seven versions of a K-theory-based model which differed from one another in the choice of dispersion parameters (sigma schemes). The analysis based on selected statistical measures indicated consistency in the qualitative and quantitative performances of the schemes. The performances are evaluated for the peak concentrations as well as for the overall concentration distribution. Those schemes which are based on the approach of dividing the hourly test period into smaller intervals exhibit better performance in predicting the peak as well as the lateral spread. The blocked bootstrap resampling technique was adopted to investigate the statistical significance of the differences in performances of each of the schemes by computing 95% confidence limits on the parameters FB, NMSE and R.