An Assessment of Applicability of Heat Waves Using Extreme Forecast Index in KMA Climate Prediction System (GloSea5)

기상청 현업 기후예측시스템(GloSea5)에서의 극한예측지수를 이용한 여름철 폭염 예측 성능 평가

  • Heo, Sol-Ip (Earth System Research Division, National Institute of Meteorological Sciences) ;
  • Hyun, Yu-Kyung (Earth System Research Division, National Institute of Meteorological Sciences) ;
  • Ryu, Young (Earth System Research Division, National Institute of Meteorological Sciences) ;
  • Kang, Hyun-Suk (Numerical Model Development Division, Numerical Modeling Center, Korea Meteorological Administration) ;
  • Lim, Yoon-Jin (Climate Research Division, National Institute of Meteorological Sciences) ;
  • Kim, Yoonjae (Earth System Research Division, National Institute of Meteorological Sciences)
  • 허솔잎 (국립기상과학원 지구시스템연구과) ;
  • 현유경 (국립기상과학원 지구시스템연구과) ;
  • 류영 (국립기상과학원 지구시스템연구과) ;
  • 강현석 (기상청 수치모델링센터 수치모델개발과) ;
  • 임윤진 (국립기상과학원 기후연구과) ;
  • 김윤재 (국립기상과학원 지구시스템연구과)
  • Received : 2019.03.13
  • Accepted : 2019.07.29
  • Published : 2019.09.30


This study is to assess the applicability of the Extreme Forecast Index (EFI) algorithm of the ECMWF seasonal forecast system to the Global Seasonal Forecasting System version 5 (GloSea5), operational seasonal forecast system of the Korea Meteorological Administration (KMA). The EFI is based on the difference between Cumulative Distribution Function (CDF) curves of the model's climate data and the current ensemble forecast distribution, which is essential to diagnose the predictability in the extreme cases. To investigate its applicability, the experiment was conducted during the heat-wave cases (the year of 1994 and 2003) and compared GloSea5 hindcast data based EFI with anomaly data of ERA-Interim. The data also used to determine quantitative estimates of Probability Of Detection (POD), False Alarm Ratio (FAR), and spatial pattern correlation. The results showed that the area of ERA-Interim indicating above 4-degree temperature corresponded to the area of EFI 0.8 and above. POD showed high ratio (0.7 and 0.9, respectively), when ERA-Interim anomaly data were the highest (on Jul. 11, 1994 (> $5^{\circ}C$) and Aug. 8, 2003 (> $7^{\circ}C$), respectively). The spatial pattern showed a high correlation in the range of 0.5~0.9. However, the correlation decreased as the lead time increased. Furthermore, the case of Korea heat wave in 2018 was conducted using GloSea5 forecast data to validate EFI showed successful prediction for two to three weeks lead time. As a result, the EFI forecasts can be used to predict the probability that an extreme weather event of interest might occur. Overall, we expected these results to be available for extreme weather forecasting.


GloSea5;extreme weather;ensemble;EFI


Grant : 장기예측시스템 개발

Supported by : 국립기상과학원


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