Abstract
Abstract. An integrated modelling system based on the regional online coupled meteorology–atmospheric chemistry WRF-Chem model configured with two nested domains with horizontal resolutions of 11.1 and 3.7 km has been applied for numerical weather prediction and for air quality forecasts in Slovenia. In the study, an evaluation of the air quality forecasting system has been performed for summer 2013. In the case of ozone (O3) daily maxima, the first- and second-day model predictions have been also compared to the operational statistical O3 forecast and to the persistence. Results of discrete and categorical evaluations show that the WRF-Chem-based forecasting system is able to produce reliable forecasts which, depending on monitoring site and the evaluation measure applied, can outperform the statistical model. For example, the correlation coefficient shows the highest skill for WRF-Chem model O3 predictions, confirming the significance of the non-linear processes taken into account in an online coupled Eulerian model. For some stations and areas biases were relatively high due to highly complex terrain and unresolved local meteorological and emission dynamics, which contributed to somewhat lower WRF-Chem skill obtained in categorical model evaluations. Applying a bias correction could further improve WRF-Chem model forecasting skill in these cases.
Highlights
Real-time air quality forecasting (RT-AQF) is a relatively new discipline in atmospheric sciences, which has evolved as a response to societal and economic needs, reflecting the progress in scientific understanding of physical processes and numerical and computational technologies (Zhang et al, 2012a)
The step in evolution of RT-AQF systems was the use of sophisticated chemical transport models that represent all major processes that lead to the formation and accumulation of air pollutants
A high resolution modelling system based on an online coupled WRF-Chem has been applied for numerical weather prediction and for forecasting air quality in Slovenia
Summary
Real-time air quality forecasting (RT-AQF) is a relatively new discipline in atmospheric sciences, which has evolved as a response to societal and economic needs, reflecting the progress in scientific understanding of physical processes and numerical and computational technologies (Zhang et al, 2012a). The step in evolution of RT-AQF systems was the use of sophisticated chemical transport models that represent all major processes (meteorological and chemical) that lead to the formation and accumulation of air pollutants. Many of these RT-AQF systems consist of an offline coupled meteorological model and a chemical-transport model, where the meteorological model (e.g. ALADIN, ALADIN International Team, 1997; MM5, Grell et al, 1994; WRF, Skamarock et al, 2008) provides meteorological input for the chemical-transport model Žabkar et al.: Evaluation of the high resolution WRF-Chem air quality forecast
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