Spatiotemporal and Synoptic Analysis of PM10 Based on Self-Organizing Map (SOM) During Asian Dust Events in South Korea
Year: 2025
Type: article
Abstract: This study analyzes the spatiotemporal characteristics of PM10 across 53 Asian dust events that affected the Korean Peninsula between January 2019 and June 2024. Self-Organizing Map (SOM) analysis was applied to sea level pressure and 850 hPa wind fields from the NCEP/DOE Reanalysis II dataset, classifying synoptic patterns into four distinct clusters. Cluster 1, associated with a deep low over Manchuria and strong westerly inflow, produced the highest PM10 concentrations and the longest durations across most regions, with sharp afternoon peaks and the highest skewness values, and was mainly sourced from the Gobi Desert. Cluster 2 featured a high–low pressure dipole, generating localized impacts in northwestern regions and shorter durations, with moderate afternoon increases, originating primarily from the Gobi Desert and Inner Mongolia. Cluster 3, linked to a low east of Japan, resulted in elevated PM10 mainly in central and southeastern regions, with peaks often occurring earlier in the day, and was associated with Manchurian dust sources. Cluster 4 exhibited a straight northwesterly flow with the high shifted eastward, producing moderate but spatially widespread concentrations and relatively consistent afternoon peaks, also linked to Manchurian sources. These results suggest that integrating synoptic pattern classification into dust forecasting can improve accuracy, enable early recognition of high-concentration events, and support the development of timely and region-specific warning strategies.
Source: Atmosphere
Institution: National Institute of Environmental Research
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $2,896
Award: G3861137159
OpenAlex ID: W4414452178