A novel statistical-dynamical method for a seasonal forecast of particular matter in South Korea

Arctic/North Atlantic atmospheric variability causes Severe PM10 events in South Korea

Severe PM10 (particulate matter with a diameter of <10 μm) events in South Korea are known to be caused by stable atmospheric circulation conditions related to high-pressure anomalies in the upper troposphere. However, research on why these atmospheric circulation patterns occur is unknown. In this study, we propose new large-scale teleconnection pathways that cause severe PM10 events during the midwinter in South Korea. This study investigated instances of extremely high (EH)-PM10 in South Korea during mid-winter and examined the corresponding atmospheric teleconnection patterns to identify the factors contributing to EH-PM10 events. K-means clustering analysis revealed that EH-PM10 instances were associated with two large-scale teleconnection patterns. Cluster 1 exhibited a wave train pattern originating in the North Atlantic that developed from Eurasia to the Korean Peninsula. Cluster 2 was associated with a wave-like teleconnection pattern from the Barents-Kara Sea to the Korean Peninsula. The Rossby waves, triggered by the North Atlantic and the Arctic, propagated and weakened the surface pressure system. This led to a high-pressure anomaly over the Korean Peninsula, reducing atmospheric ventilation and causing a rapid increase in PM10 concentration within a few days. Furthermore, an experiment involving a linear baroclinic model established that atmospheric forcing in upstream regions has the potential to induce large-scale atmospheric teleconnection patterns, resulting in EH-PM10 cases in South Korea. These findings emphasize the ventilation effect and transport of PM10 concentrations modulated by two large-scale teleconnection patterns originating from the Arctic and North Atlantic, leading to EH-PM10 events in South Korea. Understanding this combined phenomenon may assist in the implementation of emission reduction measures based on the results of short-term forecasts of severe PM10 events.