• 关键词：多模式最优集成  PM_2.5  空气质量模式

• 基金项目：国家自然科学基金（No.41475040）；国家重点研发计划项目（No.2016YFC0201900，2016YFC0203400）；上海市科委研发计划（No.16DZ1204607）

• 瞿元昊
• 1. 长三角环境气象预报预警中心, 上海 200030;2. 上海市气象与健康重点实验室, 上海 200030

• 许建明
• 1. 长三角环境气象预报预警中心, 上海 200030;2. 上海市气象与健康重点实验室, 上海 200030

• Guy Brasseur
• 德国马普气象研究所, 汉堡 20095

• 谢英
• 1. 长三角环境气象预报预警中心, 上海 200030;2. 上海市气象与健康重点实验室, 上海 200030

• 周广强
• 1. 长三角环境气象预报预警中心, 上海 200030;2. 上海市气象与健康重点实验室, 上海 200030

• 马井会
• 1. 长三角环境气象预报预警中心, 上海 200030;2. 上海市气象与健康重点实验室, 上海 200030

• 摘要：采用多模式最优集成方法（OCF），对PANDA项目中国和欧洲7个空气质量模式的PM_2.5预报结果进行集成释用.2016年6月-2017年5月对上海逐日预报试验结果表明：和最优单模式预报结果相比，OCF预报的PM_2.5日均质量浓度的均方根误差降低1.9 μg·m^-3，相关系数提高0.04，日均质量浓度的精度评分TI提高了2.4，污染TS评分提高了0.28，污染空报率降低了20%，显著提高了PM_2.5污染等级预报、趋势预报和精度预报的技巧.对长三角合肥、南京、苏州、杭州、宁波5个城市的预报试验也得到类似的结果，为城市空气质量预报提供了新的方法和思路.但OCF对客观预报的改进幅度在夏季不如冬季显著，在降雨日相对较低.

• Abstract：In this study, the OCF method was applied to conduct the daily PM_2.5 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 PM_2.5 forecast performance in Shanghai was significantly increased by OCF compared with any of the PANDA models. The RMSE of daily averaged PM_2.5 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 PM_2.5 pollution day and the PM_2.5 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.

• Key words：OCF  PM_2.5  air quality model

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