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Korean Meteorological Society (한국기상학회)
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Global Ocean Data Assimilation and Prediction System in KMA: Description and Assessment

기상청 전지구 해양자료동화시스템(GODAPS): 개요 및 검증

  • Chang, Pil-Hun (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Hwang, Seung-On (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Choo, Sung-Ho (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Lee, Johan (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Lee, Sang-Min (Operational Systems Development Department, National Institute of Meteorological Sciences) ;
  • Boo, Kyung-On (Operational Systems Development Department, National Institute of Meteorological Sciences)
  • 장필훈 (국립기상과학원 현업운영개발부) ;
  • 황승언 (국립기상과학원 현업운영개발부) ;
  • 추성호 (국립기상과학원 현업운영개발부) ;
  • 이조한 (국립기상과학원 현업운영개발부) ;
  • 이상민 (국립기상과학원 현업운영개발부) ;
  • 부경온 (국립기상과학원 현업운영개발부)
  • Received : 2021.03.30
  • Accepted : 2021.04.26
  • Published : 2021.06.30
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Abstract

The Global Ocean Data Assimilation and Prediction System (GODAPS) in operation at the KMA (Korea Meteorological Administration) is introduced. GODAPS consists of ocean model, ice model, and 3-d variational ocean data assimilation system. GODAPS assimilates conventional and satellite observations for sea surface temperature and height, observations of sea-ice concentration, as well as temperature and salinity profiles for the ocean using a 24-hour data assimilation window. It finally produces ocean analysis fields with a resolution of 0.25 ORCA (tripolar) grid and 75-layer in depth. This analysis is used for providing a boundary condition for the atmospheric model of the KMA Global Seasonal Forecasting System version 5 (GloSea5) in addition to monitoring on the global ocean and ice. For the purpose of evaluating the quality of ocean analysis produced by GODAPS, a one-year data assimilation experiment was performed. Assimilation of global observing system in GODAPS results in producing improved analysis and forecast fields with reduced error in terms of RMSE of innovation and analysis increment. In addition, comparison with an unassimilated experiment shows a mostly positive impact, especially over the region with large oceanic variability.

본 연구에서는 기상청에서 2018년부터 운영 중인 전지구 해양자료동화시스템 GODAPS에 대하여 소개하였으며, 2015년 2월부터 2016년 1월까지 일년간의 실험 수행을 통한 결과를 분석하여 이 시스템의 특성을 살펴보았다. GODAPS는 크게 해양-해빙 모델과 3차원 변분법 기반의 자료동화 시스템으로 구성되어 있고, 전지구적으로 수집된 현장 및 위성 관측자료를 자료동화하여 매일 1회 분석장과 예측장을 생산한다. 이때 해수면온도, 수온과 염분 프로파일, 해수면고도 변이, 그리고 해빙농도 관측자료를 자료동화한다. 분석증분 및 배경장/분석장으로부터의 관측증분에 대한 분석, 자료동화를 적용하지 않은 실험과의 비교 등을 통해 GODAPS 자료동화 결과를 비교검증하였다. 자료동화는 관측자료들을 효과적으로 활용하고 있었으며, 전지구 규모에서 편차를 줄인 분석장과 예측장을 생산하고 있는 것으로 나타났다. 이외에도, 변동성이 강한 중위도 해역의 쿠로시오와 걸프만 해류의 중규모 현상을 재현하는데 있어서도 결정적인 영향을 미치는 것으로 확인하였다. 해양초기장을 향상시키기 위해서는 모델과 자료동화 기술의 개발과 더불어, 다양한 관측자료를 활용하는 것이 중요하다. 하지만, 현업에서 활용할 수 있는 해양관측자료는 한계가 있으며, 따라서 가용한 자료를 자료동화 과정에 포함시키는 노력이 요구된다. 수온에 비해 염분의 경우 상대적으로 관측자료가 부족한데, 최근에는 SMAP (Soil Moisture Active Passive) 등 인공위성을 활용한 표층 염분자료가 제공되고 있으며, 기상청에서도 자료동화 과정에 독립적인 위성 염분자료를 활용한 분석장 검증 및 자료동화에 직접적용하는 연구를 추진하고 있다. 특히, 표층 염분의 자료동화를 통해 열대해역의 혼합층 깊이가 개선되고, 결과적으로 기후예측성을 향상시키는 연구결과(Hackert et al., 2020) 등을 고려할 때, 향후 위성관측 표층염분의 자료동화는 기후예측 분야에 있어서 점차 중요해질 것으로 판단된다. 본 연구의 실험결과에서도 GODAPS의 염분 관측증분 오차가 표층에서 상대적으로 크게 나타나고 있어, 해양초기장의 정확성을 높이고 나아가 기후예측성을 높이는데 위성 염분자료가 효과적으로 사용될 수 있을 것으로 기대된다.

Keywords

Acknowledgement

이 연구는 기상청 국립기상과학원 「장기예측시스템 개발」 (KMA2018-00322)의 지원으로 수행되었습니다. 그리고, 본 시스템의 개발에 있어 자문을 주신 영국기상청 해들리 센터 소속의 Matthew Martine과 Daniel Lea 박사께 깊은 감사말씀 드립니다.

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