汕头市2020—2022年臭氧污染特征及大气环流客观分型

利用2020—2022年汕头市环境空气自动监测站数据和气象数据，分析汕头市出现污染天气过程中臭氧污染的变化特征。采用自组织神经网络（self organizing feature mapping，SOM模型）智能天气分型算法对汕头市2020—2022年的天气形势的再分析资料进行客观分型，总结出汕头市容易出现臭氧污染的天气环流分型，分别为东海气旋低压槽型（秋季）、高压后部与南海低压型（春季）、弱高压底部型（秋季）、槽后脊前型（春季）和副高控制型（秋季）。对应的臭氧污染站次分别为125站次（16%），120站次（15%），115站次（14%），101站次（13%）和78站次（10%）。汕头市春、秋季较易发生臭氧污染，从近3年（2020—2022年）气团传输轨迹来看，臭氧污染的主要气团来源为东北沿海、西南沿海以及偏北内陆。

Study on Characteristics of Ozone Pollution and Objective Typing of Atmospheric Circulation in Shantou City from 2020—2022

In this article， the environmental air automatic monitoring data and meteorological data of Shantou City from 2020 to 2022 were used to statistically analyze the characteristics of ozone pollution changes in Shantou City during the pollution weather process. The self organizing feature mapping（SOM） method was applied for synoptic classification related to surface ozone pollution in Shantou basded on NCEP reanalysis data from 2020 to 2022. The results showed that the atmospheric circulation types below are prone to cause ozone pollution，including the East China Sea cyclone trough type（autumn），the high pressure rear and South China Sea low pressure type（spring），the weak high pressure bottom type（autumn），and the weak high pressure bottom type（autumn）， the trough back ridge front type（spring） and the subtropical high control type（autumn）. The corresponding ozone pollution stations are 125（16%），120（15%），115（14%），101（13%），and 78（10%），respectively. Through analyzing the characteristics of ozone pollution in Shantou and the main sources of regional transmission of air masses， it was found that ozone pollution is more prone to occur in autumn and spring in Shantou. Classifying the trajectory of air masses in the past three years（2020—2022）， the main sources of ozone pollution are the northeast coast， southwest coast， and northern inland.