Grid sensitivity analysis for the calibration of a prognostic meteorological model in complex terrain by a screening experiment

In this study we present an application of a sensitivity analysis to identify a set of important factors that are allowed to be calibrated in the grid setup of a prognostic meteorological model for laboratory-based simulations. The use of a calibrated grid is of paramount importance for repeated procedures by leaving unnecessary information unprocessed and inevitably reducing run times. Identification and evaluation of sensitivity, importance and uncertainty elements is attempted by the design of a ‘good practice experiment’ for site-specific calibration. The factors of varied grid size and resolution, based on a one-factor-at-a-time approach, are used for the determination of local sensitivity in the area of interest. A total of five simulations was performed for a grid configuration study that aimed to calibrate The Air Pollution Model.