High PM_2.5 episodes in Seoul, Korea, associated with Siberian High intensity

The Siberian High (SH) dominates the wintertime atmospheric circulation over East Asia which strongly modulates the concentration of particulate matter ≤ 2.5 μm in diameter (PM_2.5) in the region. While the SH exhibits considerable day-to-day variations, previous studies have focused on its seasonal and interannual effects rather than its short-term influence on PM_2.5 concentrations. This study investigates the link between the evolution of atmospheric circulation associated with the changes in the SH intensity and the occurrence of high PM_2.5 concentrations (≥ 35 µg m⁻³) in Seoul, Korea. Using a hierarchical clustering method, the synoptic patterns associated with 94 high-PM_2.5 episodes in Seoul during the winters of 2008–2022 are classified into two groups based on the intensity of SH: 49 episodes with strong SH and 45 episodes with weak SH. Each SH pattern can induce high-PM_2.5 episodes over distinct daily timescales through different dynamical and thermodynamical processes in the upper and lower troposphere. The strong SH is transformed into a migratory anticyclone over Korea, reducing wind speeds in the lower troposphere. These conditions suppress atmospheric ventilation and enhance dynamic stability, providing a favorable environment for rapid accumulation of PM_2.5 near the surface within two days. During the weak SH events, the anticyclonic flow in the upper troposphere increases air temperatures in the mid-to-lower troposphere, resulting in increased low-tropospheric thermal stability. Air pollutants cannot disperse into the upper atmosphere and gradually accumulate to high PM_2.5 levels over a period of four days. This study highlights that the development of atmospheric circulation in both strong and weak SH patterns plays an important role in the air quality degradation in Seoul through different temporal characteristics. These SH-driven atmospheric circulations provide valuable insights for improving forecast accuracy and enabling targeted emission control strategies based on the expected timing of pollution episodes.