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A simplified hybrid statistical-deterministic chemistry-transport model, is used in real time for the prediction of ozone in the area of Paris during Summer 1999. We present here a statistical validation of this experiment. We distinguish the forecasts in the urban area from forecasts in the pollution plume downwind of the city. The validation of model forecasts, up to 3 days ahead, is performed against ground based observations within and up to 50 km outside of Paris. In the urban area, ozone levels are fairly well forecast, with correlation coefficients between forecast and observations ranging between 0.7 and 0.8 and root mean square errors in the range 15–20 μg m−3 at short lead times. While the bias of urban forecast is very low, the largest peaks are somehow underestimated. The ozone plume amplitude is generally well reproduced, even at long lead times (root mean square errors of about 20–30 μg m−3), while the direction of the plume is only captured at short lead times (about 70% of the time). The model has difficulties in forecasting the direction of the plume under stagnant weather conditions. We estimate the model ability to forecast concentrations above 180 μg m−3, which are of practical relevance to air quality managers. It is found that about 60% of these events are well forecast, even at long lead times, while the exact monitoring station where the exceedance is observed can only be forecast at short lead times. Finally, we found that about half of the forecast error is due to the error in the estimation of the boundary conditions, which are forecast by a simple linear regression model here. |
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