한국해안·해양공학회논문집 (Journal of Korean Society of Coastal and Ocean Engineers)

  • 제32권6호
  • /
  • Pages.373-383
  • /
  • 2020
  • /
  • 1976-8192(pISSN)
  • /
  • 2288-2227(eISSN)
한국해안·해양공학회 (Korean Society of Coastal and Ocean Engineers)
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NEMO 모델을 이용한 지역 폭풍해일예측시스템 개발 및 검증

Development and Verification of NEMO based Regional Storm Surge Forecasting System

  • 라나리 (국립기상과학원 현업운영개발부 예측모델연구팀) ;
  • 안병웅 (국립기상과학원 현업운영개발부 기후모델개발팀) ;
  • 강기룡 (국립기상과학원 현업운영개발부 예측모델연구팀) ;
  • 장필훈 (국립기상과학원 현업운영개발부 예측모델연구팀)
  • La, Nary (Marine & Asian Dust Modelling Team, Operational Systems Development Department, National Institute of Meteorological Science) ;
  • An, Byoung Woong (Climate Model Development Team, Operational Systems Development Department, National Institute of Meteorological Science) ;
  • Kang, KiRyong (Marine & Asian Dust Modelling Team, Operational Systems Development Department, National Institute of Meteorological Science) ;
  • Chang, Pil-Hun (Marine & Asian Dust Modelling Team, Operational Systems Development Department, National Institute of Meteorological Science)
  • 투고 : 2020.09.11
  • 심사 : 2020.11.03
  • 발행 : 2020.12.31
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초록

본 연구에서는 한반도 중심 해역을 포함하는 북서태평양 영역에서의 폭풍해일 예측을 위해 NEMO(Nucleus for European Modelling of the Ocean) 모형을 이용하여 지역규모의 폭풍해일 예측시스템을 구축하였다. 이 시스템은 조석과 해일 예측으로 구성되어 있으며보다 정확한 폭풍해일을 예측하기 위해 수심자료와 대기-해양 경계에서의 모수화(parameterization) 최적화 과정을 수행하였다. 이를 통해 2018년 8~10월과 태풍 솔릭 사례에 대하여 국립해양조사원 조위 관측자료를 이용한 통계 방법을 적용하여 검증을 수행하고, 이를 POM(Princeton Ocean Model) 기반의 예측모델 결과와 비교하였다. 수행결과 NEMO 기반의 폭풍해일 예측시스템이 POM 기반의 예측결과에 비해 평균오차와 RMSE가 각각 약 29%와 약 20% 감소한 것으로 나타났으며, 태풍 시기에도 NEMO 기반 예측결과에서 전반적으로 오차가 낮게 나타났다.

In this study we established an operational storm-surge system for the northwestern pacific ocean, based on the NEMO (Nucleus for European Modeling of the Ocean). The system consists of the tide and the surge models. For more accurate storm surge prediction, it can be completed not only by applying more precise depth data, but also by optimal parameterization at the boundaries of the atmosphere and ocean. To this end, we conducted several sensitivity experiments related to the application of available bathymetry data, ocean bottom friction coefficient, and wind stress and air pressure on the ocean surface during August~September 2018 and the case of typhoon SOULIK. The results of comparison and verification are presented here, and they are compared with POM (Princeton Ocean Model) based Regional Tide Surge forecasting Model (RTSM). The results showed that the RTSM_NEMO model had a 29% and 20% decrease in Bias and RMSE respectively compared to the RTSM_POM model, and that the RTSM_NEMO model had a lower overall error than the RTSM_POM model for the case of typhoon SOULIK.

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