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Korean Meteorological Society (한국기상학회)
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Assessment of the Prediction Performance of Ensemble Size-Related in GloSea5 Hindcast Data

기상청 기후예측시스템(GloSea5)의 과거기후장 앙상블 확대에 따른 예측성능 평가

  • Park, Yeon-Hee (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Hyun, Yu-Kyung (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) ;
  • Ji, Hee-Sook (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Sciences)
  • 박연희 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 현유경 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 허솔잎 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 지희숙 (국립기상과학원 현업운영개발부 기후모델개발팀)
  • Received : 2021.08.04
  • Accepted : 2021.10.09
  • Published : 2021.12.31
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Abstract

This study explores the optimal ensemble size to improve the prediction performance of the Korea Meteorological Administration's operational climate prediction system, global seasonal forecast system version 5 (GloSea5). The GloSea5 produces an ensemble of hindcast data using the stochastic kinetic energy backscattering version2 (SKEB2) and timelagged ensemble. An experiment to increase the hindcast ensemble from 3 to 14 members for four initial dates was performed and the improvement and effect of the prediction performance considering Root Mean Square Error (RMSE), Anomaly Correlation Coefficient (ACC), ensemble spread, and Ratio of Predictable Components (RPC) were evaluated. As the ensemble size increased, the RMSE and ACC prediction performance improved and more significantly in the high variability area. In spread and RPC analysis, the prediction accuracy of the system improved as the ensemble size increased. The closer the initial date, the better the predictive performance. Results show that increasing the ensemble to an appropriate number considering the combination of initial times is efficient.

Keywords

Acknowledgement

이 연구는 기상청 국립기상과학원 「기후예측 현업 시스템 개발」(KMA2018-00322)의 지원으로 수행되었습니다.

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