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Korean Meteorological Society (한국기상학회)
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Extratropical Prediction Skill of KMA GDAPS in January 2019

기상청 전지구 예측시스템에서의 2019년 1월 북반구 중고위도 지역 예측성 검증

  • Hwang, Jaeyoung (School of Earth and Environmental Sciences, Seoul National University) ;
  • Cho, Hyeong-Oh (School of Earth and Environmental Sciences, Seoul National University) ;
  • Lim, Yuna (Department of Earth System Science, University of California) ;
  • Son, Seok-Woo (School of Earth and Environmental Sciences, Seoul National University) ;
  • Kim, Eun-Jung (Numerical Model Development Division, Numerical Modeling Center, Korea Meteorological Administration) ;
  • Lim, Jeong-Ock (Numerical Model Development Division, Numerical Modeling Center, Korea Meteorological Administration) ;
  • Boo, Kyung-On (Numerical Model Development Division, Numerical Modeling Center, Korea Meteorological Administration)
  • 황재영 (서울대학교 지구환경과학부) ;
  • 조형오 (서울대학교 지구환경과학부) ;
  • 임유나 (캘리포니아 대학교 어바인캠퍼스 지구시스템과학부) ;
  • 손석우 (서울대학교 지구환경과학부) ;
  • 김은정 (기상청 수치모델링센터 수치모델개발과) ;
  • 임정옥 (기상청 수치모델링센터 수치모델개발과) ;
  • 부경온 (기상청 수치모델링센터 수치모델개발과)
  • Received : 2020.02.24
  • Accepted : 2020.05.11
  • Published : 2020.06.30
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Abstract

The Northern Hemisphere extratropical prediction skill of the Korea Meteorological Administration (KMA) Global Data Assimilation and Prediction System (GDAPS) is examined for January 2019. The real-time prediction skill, evaluated with mean squared skill score (MSSS) of 30-90°N geopotential height field at 500 hPa (Z500), is ~8 days in the troposphere. The MSSS of Z500 considerably decreases after 3 days mainly due to the increasing eddy errors. The eddy errors are largely explained by the eddy-phased errors with minor contribution of amplitude errors. In particular, planetary-scale eddy errors are considered as a main reason of rapidly increasing errors. It turns out that such errors are associated with the blocking highs over North Pacific (NP) and Euro-Atlantic (EA) regions. The model overestimates the blocking highs over NP and EA regions in time, showing dependence of blocking predictability on blocking initializations. This result suggests that the extratropical prediction skill could be improved by better representing blocking in the model.

Keywords

References

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