• 关键词：臭氧  臭氧污染气象指数（OWI）  GRAPES模式  气象要素  干季  湿季  佛山

• 基金项目：广东省重点研发计划项目（No.2020B1111360003）；国家重点研发计划项目（No.2019YFC0214605， 2018YFC0213902）； 广东省基础与应用基础研究基金项目（No.2021A1515011539）；广东省科技计划项目（科技创新平台类）（No.2019B121201002）；广东省气象局科技创新团队项目（No.GRMCTD202003）；广东省气象局科学技术研究项目（No.GRMC2020M12）

• 潘巧英
• 佛山市气象局，佛山 528000;广东省生态气象中心，广州 510640;广东省环珠江口气候环境与空气质量变化野外科学观测研究站，广州 510275

• 李婷苑
• 广东省生态气象中心，广州 510640

• 陈靖扬
• 广东省生态气象中心，广州 510640

• 李伟炽
• 佛山市气象局，佛山 528000

• 陈辰
• 佛山市气象局，佛山 528000;广东省环珠江口气候环境与空气质量变化野外科学观测研究站，广州 510275

• 摘要：选取2017—2018年佛山市空气质量监测资料、地面气象观测资料和ECMWF再分析资料，得到对臭氧污染天气具有指示意义的气象因子，从GRAPES模式可预报性出发构建适用于佛山市干季和湿季的臭氧污染气象指数（OWI），并对OWI进行预报评估检验.结果表明：干季地面气象要素对区分佛山市臭氧污染和清洁天气的能力更强，出现臭氧污染时往往气温高、地面为弱北风；850 hPa风速较小，高空主要受副热带高压影响.湿季高空气象要素区分臭氧污染和清洁天气的能力更强，出现臭氧污染时往往850 hPa风速较小，850 hPa与地面风场垂直切变 较小，多数情况下500 hPa呈辐散形势或700 hPa为下沉运动.综合考虑上述要素构建的臭氧污染气象指数可较好地反映臭氧浓度变化趋势，当OWI超过阈值（干季12.0、湿季10.8）时，出现臭氧污染事件的可能性较大，在湿季该指数区分臭氧清洁天气和污染天气的差异性较干季更显著.基于GRAPES模式预报的OWI与臭氧浓度实况呈正相关关系，相关系数在0.5~0.6之间，能较为有效地预判臭氧污染过程发生、发展和消散的不同阶段；其阈值具有较高的预报参考性，24 h预报性能尤为理想，48、72 h依次下降，在干季空报率偏高.

• Abstract：This study combined historical （2017—2018） air quality monitoring data， meteorological monitoring data and ECMWF reanalysis data to obtain the dominating meteorological factors indicating the ozone pollution weather in Foshan. Further， the numerical simulated output from the GRAPES model was also used to construct a localized ozone weather index （OWI） for both dry and wet seasons of Foshan. The results showed that the surface meteorological parameters could relatively well indicate ozone levels during the dry season. High ozone events were usually characterized by high temperature， weak northerly winds at surface， and controlled by the subtropical high. With regard to the wet season， meteorological parameters acquired from the upper air had a stronger ability in identifying the surface ozone levels. When ozone pollution occurred， the wind speed at 850 hPa and the vertical wind shear between 850 hPa and ground were usually light. In usual， Foshan was either in the district of divergence at 500 hPa or downdraft at 700 hPa. The constructed OWI performed well indicating ozone concentrations especially in the wet season. The statistical results showed that ozone pollution events usually occurred when OWI exceeded the threshold （12.0 in dry season and 10.8 in wet season）. The predicted OWI by GRAPES model was positively correlated with the observed ozone concentration （the correlation coefficient is between 0.5 and 0.6） which can effectively predict the occurrence， development and dissipation of ozone pollution. The OWI serves as a reference for forecast and the performance of 24 hour-prediction is relatively well， while the precision decreased with the predicted time.

• Key words：ozone  ozone weather index （OWI）  GRAPES model  meteorological parameters  dry season  wet season  Foshan

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