대기 (Atmosphere)

  • 제25권2호
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  • Pages.323-337
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  • 2015
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  • 1598-3560(pISSN)
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  • 2288-3266(eISSN)
한국기상학회 (Korean Meteorological Society)
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GloSea5 모형의 6개월 장기 기후 예측성 검증

Assessment of 6-Month Lead Prediction Skill of the GloSea5 Hindcast Experiment

  • 정명일 (서울대학교 자연과학대학 지구환경과학부) ;
  • 손석우 (서울대학교 자연과학대학 지구환경과학부) ;
  • 최정 (서울대학교 자연과학대학 지구환경과학부) ;
  • 강현석 (국립기상과학원 기후연구과)
  • Jung, Myung-Il (School of Earth and Environmental Sciences, Seoul National University) ;
  • Son, Seok-Woo (School of Earth and Environmental Sciences, Seoul National University) ;
  • Choi, Jung (School of Earth and Environmental Sciences, Seoul National University) ;
  • Kang, Hyun-Suk (Climate Research Division, National Institute of Meteorological Research)
  • 투고 : 2015.03.10
  • 심사 : 2015.04.16
  • 발행 : 2015.06.30
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초록

This study explores the 6-month lead prediction skill of several climate indices that influence on East Asian climate in the GloSea5 hindcast experiment. Such indices include Nino3.4, Indian Ocean Diploe (IOD), Arctic Oscillation (AO), various summer and winter Asian monsoon indices. The model's prediction skill of these indices is evaluated by computing the anomaly correlation coefficient (ACC) and mean squared skill score (MSSS) for ensemble mean values over the period of 1996~2009. In general, climate indices that have low seasonal variability are predicted well. For example, in terms of ACC, Nino3.4 index is predicted well at least 6 months in advance. The IOD index is also well predicted in late summer and autumn. This contrasts with the prediction skill of AO index which shows essentially no skill beyond a few months except in February and August. Both summer and winter Asian monsoon indices are also poorly predicted. An exception is the Western North Pacific Monsoon (WNPM) index that exhibits a prediction skill up to 4- to 6-month lead time. However, when MSSS is considered, most climate indices, except Nino3.4 index, show a negligible prediction skill, indicating that conditional bias is significant in the model. These results are only weakly sensitive to the number of ensemble members.

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  3. One-Month-Lead Predictability of Asian Summer Monsoon Indices Based on the Zonal Winds by the APCC Multimodel Ensemble vol.31, pp.21, 2018, https://doi.org/10.1175/JCLI-D-17-0816.1