Evaluation of WRF/Chem model (v3.9.1.1) real-time air quality forecasts over the Eastern Mediterranean

Abstract. We describe and evaluate a high-resolution real-time air quality forecast system over the Eastern Mediterranean, based on a regional, on-line coupled atmospheric chemistry and aerosol model. The WRF/Chem model is used to perform daily, 3-day forecasts of regulated pollutants NO2, O3, PM2.5 over the Eastern Mediterranean, with three nested domains with horizontal resolutions of 50 km, 10 km and 2 km, focusing on Cyprus. Natural (dust, sea-salt, biogenic) emissions are calculated online, while anthropogenic emissions are based on the EDGAR-HTAP global emission inventory. A high spatial (1 km) and temporal (hourly) anthropogenic emission inventory is used for the island of Cyprus in the innermost domain. The model skill in forecasting the concentrations of atmospheric pollutants is evaluated using measurements from a network of nine ground stations in Cyprus and compared with the forecast skill of the EU Copernicus Atmosphere Monitoring Service – CAMS. The forecast of surface temperature, pressure, and wind speed is found to be accurate, with minor discrepancies between the modelled and observed 10 m wind speed at mountainous and coastal sites attributed to the limited representation of the complex topography of Cyprus. Compared to CAMS, the WRF/Chem model predicts with higher accuracy the NO2 mixing ratios at the residential site with a normalized mean bias of 7 % during winter and −44 % during summer, whereas the corresponding biases for CAMS are −81 % and −84 %. Due to the high temporal resolution of the anthropogenic emission inventory, the WRF/Chem model captures more accurately the diurnal profiles of NO2 and O3 mixing ratios at the residential site. Background PM2.5 concentrations influenced by long-range transport are overestimated by the WRF/Chem model during winter NMB = 54 % whereas the corresponding NMB for CAMS is 11 %. Our results support the adoption of regional, on-line coupled air quality models over chemical transport models for real-time air quality forecasts.