Journal of the Korean earth science society (한국지구과학회지)

The Korean Earth Science Society (한국지구과학회)
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Large-scale Atmospheric Patterns associated with the 2018 Heatwave Prediction in the Korea-Japan Region using GloSea6

  • Jinhee Kang (Division of Science Education and Institute of Fusion Science, Jeonbuk National University) ;
  • Semin Yun (Division of Science Education and Institute of Fusion Science, Jeonbuk National University) ;
  • Jieun Wie (Division of Science Education and Institute of Fusion Science, Jeonbuk National University) ;
  • Sang-Min Lee (Climate Research Department, National Institute of Meteorological Sciences) ;
  • Johan Lee (Climate Research Department, National Institute of Meteorological Sciences) ;
  • Baek-Jo Kim (Observation Research Department, National Institute of Meteorological Sciences) ;
  • Byung-Kwon Moon (Division of Science Education and Institute of Fusion Science, Jeonbuk National University)
  • Received : 2024.02.20
  • Accepted : 2024.02.28
  • Published : 2024.02.29
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Abstract

In the summer of 2018, the Korea-Japan (KJ) region experienced an extremely severe and prolonged heatwave. This study examines the GloSea6 model's prediction performance for the 2018 KJ heatwave event and investigates how its prediction skill is related to large-scale circulation patterns identified by the k-means clustering method. Cluster 1 pattern is characterized by a KJ high-pressure anomaly, Cluster 2 pattern is distinguished by an Eastern European high-pressure anomaly, and Cluster 3 pattern is associated with a Pacific-Japan pattern-like anomaly. By analyzing the spatial correlation coefficients between these three identified circulation patterns and GloSea6 predictions, we assessed the contribution of each circulation pattern to the heatwave lifecycle. Our results show that the Eastern European high-pressure pattern, in particular, plays a significant role in predicting the evolution of the development and peak phases of the 2018 KJ heatwave approximately two weeks in advance. Furthermore, this study suggests that an accurate representation of large-scale atmospheric circulations in upstream regions is a key factor in seasonal forecast models for improving the predictability of extreme weather events, such as the 2018 KJ heatwave.

Keywords

Acknowledgement

This present paper is a part of the first author's M.S. thesis at Jeonbuk National University. This work was supported by the Korea Meteorological Administration Research and Development Program under Grant KMI2020-01212 and the National Research Foundation of Korea (NRF) grant funded by the Government of Korea (MSIT) (No. 2022R1A2C1008858).

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