Improving O3, PM25 and NO2 Surface Fields by Optimally Interpolating Updatable MOS Forecasts

Abstract

Updatable Model Output Statistics (UMOS) (Wilson JW, Vallée M, Weather Forecast, 17:206–222, 2001) methodology in air-quality forecasting (UMOS-AQ) has shown great ability to improve direct model output. The UMOS-AQ (Antonopoulos S, Bourgouin P, Montpetit J, Croteau G, Forecasting O₃, PM₂₅ and NO₂ hourly spot concentrations using an updateable MOS methodology. In: Proceedings for the 31st NATO/SPS international technical meeting on air pollution modeling and its application, Torino, Italy, pp 309–314, 2010) system produces one equation for each station, predictand, model run, forecast hour and season. A limitation of the method however is the fact that we only obtain point forecasts. An optimal interpolation solution on the UMOS-AQ forecasts using Simple Krigging is presented in which the model’s output is used as a trial field. The parametrization chosen is such that the radius of influence is approximately two grid points with most of the weight coming from the UMOS-AQ forecasts. Preliminary results showed significant improvements over the model’s forecasts in regions with a high density of observation stations.