Improving of local ozone forecasting by integrated models.
This paper discuss the problem of forecasting the maximum ozone concentrations in urban microlocations, where reliable alerting of the local population when thresholds have been surpassed is necessary. To improve the forecast, the methodology of integrated models is proposed. The model is based on multilayer perceptron neural networks that use as inputs all available information from QualeAria air-quality model, WRF numerical weather prediction model and onsite measurements of meteorology and air pollution. While air-quality and meteorological models cover large geographical 3-dimensional space, their local resolution is often not satisfactory. On the other hand, empirical methods have the advantage of good local forecasts. In this paper, integrated models are used for improved 1-day-ahead forecasting of the maximum hourly value of ozone within each day for representative locations in Slovenia. The WRF meteorological model is used for forecasting meteorological variables and the QualeAria air-quality model for gas concentrations. Their predictions, together with measurements from ground stations, are used as inputs to a neural network. The model validation results show that integrated models noticeably improve ozone forecasts and provide better alert systems.
Jožef Stefan Institute, Jamova 39, SI-1000, Ljubljana, Slovenia. dejan.gradisar@ijs.si.
Dejan
D
Gradišar
MEIS d.o.o, Mali Vrh pri Šmarju 78, SI-1293, Šmarje - Sap, Slovenia.
Boštjan
B
Grašič
MEIS d.o.o, Mali Vrh pri Šmarju 78, SI-1293, Šmarje - Sap, Slovenia.
Marija Zlata
MZ
Božnar
MEIS d.o.o, Mali Vrh pri Šmarju 78, SI-1293, Šmarje - Sap, Slovenia.
Primož
P
Mlakar
Jožef Stefan Institute, Jamova 39, SI-1000, Ljubljana, Slovenia.|University of Nova Gorica, Vipavska 13, SI-5000, Nova Gorica, Slovenia.
Juš
J
Kocijan
D004784:Environmental Monitoring / Q000379:methods*; D005544:Forecasting; D055904:Meteorology / Q000379:methods*; D015233:Models, Statistical; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D010126:Ozone / Q000032:analysis / Q000737:chemistry
D010126:Ozone
Air pollution; Artificial neural networks; Ozone forecast; WRF numerical weather prediction model