Calibration of Numerical Model Output Using Nonparametric Spatial Density Functions

The evaluation of physically based computer models for air quality applications is crucial to assist in control strategy selection. Selecting the wrong control strategy has costly economic and social consequences. The objective comparison of the means and variances of modeled air pollution concentrations with the ones obtained from observed field data is the common approach for the assessment of model performance. One drawback of this strategy is that it fails to calibrate properly the tails of the modeled air pollution distribution. Improving the ability of these numerical models to characterize high pollution events is of critical interest for air quality management.