준-운용 예보시스템에 Argo뜰개자료의 자료동화 실험

Abstract

As part of Korean Ocean Prediction System (KOPS), we present some features of Korean waters through data assimilation experiments carried out on a three-dimensional circulation model commonly known as the Princeton Ocean Model. In this paper, special emphasis is paid towards the assimilation of observational temperature and salinity data obtained from drifting Argo floats and AVISO Sea Surface Heights (SSH) data. The data assimilation is carried out by nudging as used in an optimal interpolation based analysis. Observational data obtained from the free-drifting Argo profiling float includes profiles of temperature and salinity of the upper 700 m of the ocean, whereas residual sea surface heights from AVISO contain information on vertically integrated dynamic structure of a water column. Conceptually, Argo floats build on the existing upper-ocean thermal networks, extending their spatial and temporal coverage, depth range and accuracy, and enhancing them through addition of salinity and velocity measurements. Incorporation of observational datasets from Argo profiles and AVISO Altimetry in initial conditions of the model through assimilation drastically improves the quality of forecast. The goal of the study is on construction of one unified ocean model for the entire Korean waters and building upon data assimilation scheme for the operational purpose.