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Korean Meteorological Society (한국기상학회)
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Reliability Assessment of Temperature and Precipitation Seasonal Probability in Current Climate Prediction Systems

현 기후예측시스템에서의 기온과 강수 계절 확률 예측 신뢰도 평가

  • Hyun, Yu-Kyung (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Park, Jinkyung (School of Earth and Environmental Sciences, Seoul National University) ;
  • Lee, Johan (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Lim, Somin (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Heo, Sol-Ip (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Ham, Hyunjun (Hydrometeorological and Meteorological Drought Team, Climate Science Bureau, Korea Meteorological Administration) ;
  • Lee, Sang-Min (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Ji, Hee-Sook (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Kim, Yoonjae (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
  • 현유경 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 박진경 (서울대학교 지구환경과학부) ;
  • 이조한 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 임소민 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 허솔잎 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 함현준 (기상청 기후과학국 수문기상팀) ;
  • 이상민 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 지희숙 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 김윤재 (국립기상과학원 현업운영개발부 기후모델개발팀)
  • Received : 2020.03.13
  • Accepted : 2020.06.08
  • Published : 2020.06.30
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Abstract

Seasonal forecast is growing in demand, as it provides valuable information for decision making and potential to reduce impact on weather events. This study examines how operational climate prediction systems can be reliable, producing the probability forecast in seasonal scale. A reliability diagram was used, which is a tool for the reliability by comparing probabilities with the corresponding observed frequency. It is proposed for a method grading scales of 1-5 based on the reliability diagram to quantify the reliability. Probabilities are derived from ensemble members using hindcast data. The analysis is focused on skill for 2 m temperature and precipitation from climate prediction systems in KMA, UKMO, and ECMWF, NCEP and JMA. Five categorizations are found depending on variables, seasons and regions. The probability forecast for 2 m temperature can be relied on while that for precipitation is reliable only in few regions. The probabilistic skill in KMA and UKMO is comparable with ECMWF, and the reliabilities tend to increase as the ensemble size and hindcast period increasing.

Keywords

References

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