Non-typhoon extreme waves in the Northeast Asian Marginal Seas: Observation-based identification, synoptic conditions, and classification

This study presents an observation-based approach for identifying, characterizing, and classifying non-typhoon extreme waves in the Northeast Asian Marginal Seas using in-situ wave and wind measurements, with reanalysis data used to interpret the associated synoptic conditions. Extreme-value analysis of wave power identifies hundreds of non-typhoon extreme waves across the East Sea, Yellow Sea, and East China Sea. These extreme waves are characterized and classified using quantitatively defined criteria based on the energy period and the correlation between significant wave height and local wind speed, distinguishing wind-sea-dominated, swell-influenced, and mixed wave conditions. Spectral-partition analysis supports the physical distinction among the identified extreme wave classes. Analysis of representative atmospheric fields reveals two predominant synoptic conditions associated with the occurrence of non-typhoon extreme waves: expansion of the Siberian High and extratropical cyclone. The Yellow Sea is predominantly characterized by locally forced wind-sea extremes associated with the expansion of the Siberian High, whereas the East Sea exhibits both wind-sea- and swell-influenced extremes under different synoptic conditions. The East China Sea similarly exhibits both wind-sea- and swell-influenced extremes associated with extratropical cyclone activity and atmospheric forcing over adjacent basins. These results demonstrate pronounced regional differences in non-typhoon extreme wave characteristics and their associated atmospheric conditions, with implications for regional wave modeling and coastal forecasting.

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Publication Details

Journal
Ocean Engineering
Published
2026-10-14
DOI
https://doi.org/10.1016/j.oceaneng.2026.128660
Primary Topic
Ocean Waves and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

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article

Non-typhoon extreme waves in the Northeast Asian Marginal Seas: Observation-based identification, synoptic conditions, and classification

Ki‐Young Heo, Taemin Ha, Seongho Ahn, Sumiya Uranchimeg et al.
Ocean Engineering
Ocean Waves and Remote Sensing
article

Non-typhoon extreme waves in the Northeast Asian Marginal Seas: Observation-based identification, synoptic conditions, and classification

Ki‐Young Heo, Taemin Ha, Seongho Ahn, Sumiya Uranchimeg, Kyungmo Kim
article en

Abstract

This study presents an observation-based approach for identifying, characterizing, and classifying non-typhoon extreme waves in the Northeast Asian Marginal Seas using in-situ wave and wind measurements, with reanalysis data used to interpret the associated synoptic conditions. Extreme-value analysis of wave power identifies hundreds of non-typhoon extreme waves across the East Sea, Yellow Sea, and East China Sea. These extreme waves are characterized and classified using quantitatively defined criteria based on the energy period and the correlation between significant wave height and local wind speed, distinguishing wind-sea-dominated, swell-influenced, and mixed wave conditions. Spectral-partition analysis supports the physical distinction among the identified extreme wave classes. Analysis of representative atmospheric fields reveals two predominant synoptic conditions associated with the occurrence of non-typhoon extreme waves: expansion of the Siberian High and extratropical cyclone. The Yellow Sea is predominantly characterized by locally forced wind-sea extremes associated with the expansion of the Siberian High, whereas the East Sea exhibits both wind-sea- and swell-influenced extremes under different synoptic conditions. The East China Sea similarly exhibits both wind-sea- and swell-influenced extremes associated with extratropical cyclone activity and atmospheric forcing over adjacent basins. These results demonstrate pronounced regional differences in non-typhoon extreme wave characteristics and their associated atmospheric conditions, with implications for regional wave modeling and coastal forecasting.

Ocean EngineeringVol. 369
Korea Institute of Ocean Science and Technology (KR), Hanyang University (KR), Jeju National University (KR)
National Research Foundation of Korea, Korea Institute of Marine Science and Technology promotion
Climate action
Openalex Percentile: Top 17%
Ocean Waves and Remote Sensing
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