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Korean Meteorological Society (한국기상학회)
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Global Ocean Data Assimilation and Prediction System 2 in KMA: Operational System and Improvements

기상청 전지구 해양자료동화시스템 2(GODAPS2): 운영체계 및 개선사항

  • Hyeong-Sik Park (Climate Research Division, National Institute of Meteorological Sciences) ;
  • Johan Lee (Climate Research Division, National Institute of Meteorological Sciences) ;
  • Sang-Min Lee (Climate Research Division, National Institute of Meteorological Sciences) ;
  • Seung-On Hwang (Climate Research Division, National Institute of Meteorological Sciences) ;
  • Kyung-On Boo (Climate Research Division, National Institute of Meteorological Sciences)
  • 박형식 (국립기상과학원 기후연구부) ;
  • 이조한 (국립기상과학원 기후연구부) ;
  • 이상민 (국립기상과학원 기후연구부) ;
  • 황승언 (국립기상과학원 기후연구부) ;
  • 부경온 (국립기상과학원 기후연구부)
  • Received : 2023.03.31
  • Accepted : 2023.06.13
  • Published : 2023.08.31
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Abstract

The updated version of Global Ocean Data Assimilation and Prediction System (GODAPS) in the NIMS/KMA (National Institute of Meteorological Sciences/Korea Meteorological Administration), which has been in operation since December 2021, is being introduced. This technical note on GODAPS2 describes main progress and updates to the previous version of GODAPS, a software tool for the operating system, and its improvements. GODAPS2 is based on Forecasting Ocean Assimilation Model (FOAM) vn14.1, instead of previous version, FOAM vn13. The southern limit of the model domain has been extended from 77°S to 85°S, allowing the modelling of the circulation under ice shelves in Antarctica. The adoption of non-linear free surface and variable volume layers, the update of vertical mixing parameterization, and the adjustment of isopycnal diffusion coefficient for the ocean model decrease the model biases. For the sea-ice model, four vertical ice layers and an additional snow layer on top of the ice layers are being used instead of previous single ice and snow layers. The changes for data assimilation include the updated treatment for background error covariance, a newly added bias scheme combined with observation bias, the application of a new bias correction for sea level anomaly, an extension of the assimilation window from 1 day to 2 days, and separate assimilations for ocean and sea-ice. For comparison, we present the difference between GODAPS and GODAPS2. The verification results show that GODAPS2 yields an overall improved simulation compared to GODAPS.

Keywords

Acknowledgement

이 연구는 기상청 국립기상과학원 「기후예측 현업시스템 운영 및 개발」(KMA2018-00322)의 지원으로 수행되었습니다. 검증을 위한 SST 및 MLD 자료는 ECMWF의 Copernicus Climate Data Store 포털 (CDS)에서, CryoSat-2 해빙 두께 자료는 www.cpom.ucl.ac.uk/csopr에서 입수하였다.

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