Research on the interpretation and correction of numerical ozone forecast based on Analog Ensemble
LI Zi-ming1,2, ZHAO Xiu-juan1, SUN Zhao-bin1, XU Jing1, ZHANG Xiao-ling3, QIU Yu-lu2, YIN Xiao-mei2, XIONG Ya-jun2, QIAO Lin2
1. Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China;
2. Environmental Meteorology Forecast Center of Beijing-Tianjin-Hebei, Beijing 100089, China;
3. School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China
A numerical correction of the O3 concentration forecasted by the Rapid refresh Multi-scale Analysis & Prediction System-CHEM (RMAPS-CHEM v1.0) was performed by using the Analog Ensemble (AnEn) method with 2a historical observations at 70 sites and forecast datasets in Beijing-Tianjin-Hebei region. The correction ability of the AnEn was evaluated against observed data from June to September 2018. The results showed that the performance of AnEn first increased and then decreased with the increase of ensemble member. The optimal performance was achieved when 14 members were used. The sensitivities of main forecast factors were different:the forecasted O3 from the RMAPS-CHEM showed the greatest weight, followed by temperature at 2m, relative humidity at 2m, wind speed at 10m, and planetary boundary layer height. The predicted O3 concentration from the RMAPS-CHEM was improved significantly using the AnEn method. The improvement was obvious for both the magnitude and spatiotemporal variation of predicted O3 concentrations. The correlation coefficients between observed and AnEn-predicted O3 concentrations were 68.6% larger than those between observed and RMAPS-CHEM-predicted concentrations. The root mean square errors after correction were 25% smaller. In addition, the performance of the AnEn method showed obvious spatial and diurnal variations in Beijing-Tianjin-Hebei region. In the daytime, the improvement was more evident in the eastern part of Beijing-Tianjin-Hebei region and in large cities, while at night, significant improvement mainly occured in urban areas. The performance of AnEn was generally better at night than in the daytime. Besides, the probability density distribution of O3 modified by the AnEn method is closer to the observation than that of the RMAPS-CHEM, especially in areas with low (<35μg/m3) and high (>200μg/m3) O3 concentrations. Evaluation at three cities during a typical O3 pollution event indicated that the performance of the AnEn method was better in the forecast period of 0~48h than in 48~96h. The AnEn method performed best in Tianjin city, followed by Beijing and Shijiazhuang. Overall, the AnEn method showed better performance than RMAPS-CHEM in terms of the prediction of O3 concentrations in Beijing-Tianjin-Hebei region, and thus could be applied more widely to the O3 concentration forecast in North China.
李梓铭, 赵秀娟, 孙兆彬, 徐敬, 张小玲, 邱雨露, 尹晓梅, 熊亚军, 乔林. 基于相似集合预报技术的臭氧预报释用研究[J]. 中国环境科学, 2020, 40(2): 475-484.
LI Zi-ming, ZHAO Xiu-juan, SUN Zhao-bin, XU Jing, ZHANG Xiao-ling, QIU Yu-lu, YIN Xiao-mei, XIONG Ya-jun, QIAO Lin. Research on the interpretation and correction of numerical ozone forecast based on Analog Ensemble. CHINA ENVIRONMENTAL SCIENCECE, 2020, 40(2): 475-484.
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