Abstract. Precipitation stable isotopes are critical tracers for understanding climate variability and the hydrological cycle, as they enable the tracing of moisture sources, air mass mixing, and evaporation vs. condensation mechanisms. In mid-latitude regions such as South Korea, which are influenced by tropical and extratropical circulation, long-term isotope records remain scarce. Here, we analyze stable isotopes in precipitation collected bi-weekly in Seoul, South Korea, from 2016 to 2020. The oxygen isotope composition (δ18O) ranged widely from 1.15 ‰ to −18.21 ‰, hydrogen isotope composition (δ2H) varied from 3.3 ‰ to −132.0 ‰, the deuterium excess (d-excess) ranged from 23.7 ‰–2.1 ‰ and the 17O-excess (Δ′17O) ranged from 69 to −28 per meg. All three primary isotopes exhibited a coherent sinusoidal seasonal cycle, with the most depleted values in winter, gradual enrichment through spring, and sharp depletion during the summer monsoon, reflecting the combined influence of temperature and the amount effect. The d-excess was highest during cold, dry months and lowest in humid, rainy months, reflecting shifts in near-surface relative humidity at the moisture source region and associated kinetic fractionation. Meanwhile, Δ′17O exhibited a similar season trend with a smaller amplitude, indicating a reduced sensitivity to seasonal variations in relative humidity compared to d-excess and suggesting additional modulation by large-scale transport and water vapor mixing. The local meteoric water line closely matches the global line but winter samples show a higher intercept and a slightly steeper δ17O–δ18O slope, suggesting enhanced kinetic fractionation under continental air masses. A consistently negative δ18O–Δ′17O relationship was observed except in winter when it weakened. This integrated analysis of δ18O, d-excess, and Δ′17O provides a comprehensive picture of source humidity, transport dynamics, and seasonal precipitation processed in a mid-latitude East Asia, and offers a valuable reference for refining isotope-enabled climate models over East Asia. The dataset is publicly available at https://doi.org/10.1594/PANGAEA.983390 (Kim et al., 2025).
Kim et al. (Thu,) studied this question.