“O_(x)增减量”O_(3)人工订正预报方法与应用

Application of‘O_(x)Increase or Decrease’Method for O_(3) Human Forecast

为满足环境管理部门“O_(3)污染过程不漏、AQI类别准确和AQI范围预报准确”的要求,基于大气箱式模型和相似案例分析,引入O_(x)指标原创性提出“O_(x)增减量”O_(3)人工订正预报方法。介绍了该方法的预报思路、预报要点和步骤、历史相似案例库构建与基于大气条件预报的判别分析、方法普适性和局限性等,以期为提高区域、城市O_(3)业务预报准确率提供技术参考。以东部沿海城市青岛市为研究案例,结果显示,2020年6—9月24 h人工订正AQI类别预报、AQI范围预报准确率分别为91%和68%,比同期业务化运行的WRF-Chem数值模式预报准确率分别提高19%和25%,应用该预报方法可有效提高O_(3)污染过程预报准确率。

In order to fulfill the requirements of‘no-missing in ozone pollution forecast,and higher accuracy for forecast AQI-level and AQI-range’for department of environmental management,the study originally developed‘O_(x)increase or decrease’(ΔO_(x))method for human forecast based on the classic box model and similar case analysis.This paper introduced theoretical basis,key predictor variables and forecast procedure,development of historical similar case database and discriminant analysis forΔO_(x)method,as well as its strengths and limitations,as to improve the performance of regional and urban O_(3)human forecast.Qingdao,a coast city in Eastern China,was chose as a case study.The results showed that accuracy rates for AQI-level and AQI-range of human forecast during June to September 2020 were 91%and 68%,respectively.The accuracy rates were 19%and 25%higher than those of WRF-Chem forecasting results,respectively.The application ofΔO_(x)method can effectively improve O_(3)pollution event forecasting.