Statistical correction and downscaling of chemical transport model ozone forecasts over Atlanta

摘要

The Regional Air Quality forecAST (RAQAST) model is a regional chemical transport modeling system for ozone and its precursors over the United States. Since the grid size is 70 by 70 km, forecasts cannot be made for a specific surface site. We use EPA monitoring stations from the Atlanta area to downscale and improve local forecasts using RAQAST outputs. We use the Model Diagnostic and Correction (MDC) approach. First, we regress the observations on the model outputs with an autoregressive noise component. Second, we regress the residuals of this first regression on variables associated with wind speed, precipitation amounts and the diurnal cycle. Deficiencies of 3-D model results are identified and corrected. Evaluation using measurements for a different period confirms that the statistically adjusted outputs reduce forecast errors by up to 25%.