In this study, the OCF method was applied to conduct the daily PM2.5 ensemble forecasts in Shanghai during June 2016 to May 2017 based on the outputs from 7 PANDA air quality models. The results showed that the PM2.5 forecast performance in Shanghai was significantly increased by OCF compared wit... Show moreIn this study, the OCF method was applied to conduct the daily PM2.5 ensemble forecasts in Shanghai during June 2016 to May 2017 based on the outputs from 7 PANDA air quality models. The results showed that the PM2.5 forecast performance in Shanghai was significantly increased by OCF compared with any of the PANDA models. The RMSE of daily averaged PM2.5 mass concentration decreased by 1.9 μg•m⁻³, the correlation coefficient increased by 0.04, and the false detection rate for pollution days reduced by 20%. Furthermore, both TS and TI marks which were used to evaluate the forecast accuracy for PM2.5 pollution day and the PM2.5 mean daily mass concentration were both advanced by 0.28 and 2.4 respectively. Similar positive results were achieved by OCF experiments for other 5 cities in YRD region. Thus it could be concluded that OCF can be regarded as an efficient ensemble method for current urban air quality forecast operations. Nevertheless the advantage of OCF was less effective in winter than in summer, and less skillful under rain day conditions. Show less
