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Korean Meteorological Society (한국기상학회)
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Mesoscale Features and Forecasting Guidance of Heavy Rain Types over the Korean Peninsula

한반도 호우유형의 중규모 특성 및 예보 가이던스

  • Kim, Sunyoung (AI Weather Forecast Research Team, National Institute of Meteorological Sciences) ;
  • Song, Hwan-Jin (AI Weather Forecast Research Team, National Institute of Meteorological Sciences) ;
  • Lee, Hyesook (AI Weather Forecast Research Team, National Institute of Meteorological Sciences)
  • 김선영 (국립기상과학원 인공지능예보연구팀) ;
  • 송환진 (국립기상과학원 인공지능예보연구팀) ;
  • 이혜숙 (국립기상과학원 인공지능예보연구팀)
  • Received : 2019.07.23
  • Accepted : 2019.09.25
  • Published : 2019.11.30
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Abstract

This study classified heavy rain types from K-means clustering for the hourly relationship between rainfall intensity and cloud top height over the Korean peninsula, and then examined their statistical characteristics for the period of June~August 2013~2018. Total rainfall amount of warm-type events was 2.65 times larger than that of the cold-type, whereas the lightning frequency divided by total rainfall for the warm-type was only 46% of the cold-type. Typical cold-type cases exhibited high cloud top height around 16 km, large reflectivity in the upper layer, and frequent lightning flashes under convectively unstable condition. Phenomenally, the cold-type cases corresponded to cloud cluster or multi-cell thunderstorms. However, two warm-type cases related to Changma and typhoon were characterized by heavy rainfall due to long duration, relatively low cloud top height and upper-level reflectivity, and the absence of lightning under the convectively neutral and extremely humid conditions. This study further confirmed that the forecast skill of rainfall could be improved by applying correction factor with the overestimation for cold-type and underestimation for warm-type cases in the Local Data Assimilation and Prediction System (LDAPS) operational model (e.g., BIAS score was improved by 5%).

Keywords

References

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