CAJ | 학술논문

本研究发展了一个全球海洋资料同化系统ZFL_GODAS。该系统是一个短期气候数值预测业务系统的子系统，为短期气候预测海气耦合模式提供全球海洋初始场。系统能够同化的观测资料包括卫星高度计资料、卫星海表温度（SST）资料，以及 Argo、XBT、TAO 等各种不同来源的现场温盐廓线资料。系统使用的海洋模式为中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室开发的气候系统海洋模式LICOM1.0，同化方案为集合最优插值（EnOI）方案。系统使用一个由海洋模式自由积分得到的静态样本来估计背景场误差协方差。这样的基于集合样本的背景场误差协方差具有多变量协变、各向异性的特征，且能反映海洋物理过程固有的空间尺度特征。针对EnOI同化程序的特点，开发了一套特色鲜明、负载均衡、高效的并行化同化程序。<br>　　本文通过与不同类型观测资料的比较，对同化系统的性能进行了评估。通过比较海表温度和海面高度的年际变率，海表温度异常随时间的变化，SST、海面高度异常（SLA）以及次表层温盐预报产品的均方根误差，5年平均温度偏差廓线、平均盐度廓线、平均纬向流速廓线等发现：系统工作正常、同化效果较好；经过同化以后，各变量都更加接近观测，误差更小，与观测场的相关性更好，可以为短期气候预测系统提供较好的海洋初始场，也可以为物理海洋学的研究提供有效的再分析资料。
본연구발전료일개전구해양자료동화계통ZFL_GODAS。해계통시일개단기기후수치예측업무계통적자계통，위단기기후예측해기우합모식제공전구해양초시장。계통능구동화적관측자료포괄위성고도계자료、위성해표온도（SST）자료，이급 Argo、XBT、TAO 등각충불동래원적현장온염곽선자료。계통사용적해양모식위중국과학원대기물리연구소대기과학화지구류체역학수치모의국가중점실험실개발적기후계통해양모식LICOM1.0，동화방안위집합최우삽치（EnOI）방안。계통사용일개유해양모식자유적분득도적정태양본래고계배경장오차협방차。저양적기우집합양본적배경장오차협방차구유다변량협변、각향이성적특정，차능반영해양물리과정고유적공간척도특정。침대EnOI동화정서적특점，개발료일투특색선명、부재균형、고효적병행화동화정서。<br>　　본문통과여불동류형관측자료적비교，대동화계통적성능진행료평고。통과비교해표온도화해면고도적년제변솔，해표온도이상수시간적변화，SST、해면고도이상（SLA）이급차표층온염예보산품적균방근오차，5년평균온도편차곽선、평균염도곽선、평균위향류속곽선등발현：계통공작정상、동화효과교호；경과동화이후，각변량도경가접근관측，오차경소，여관측장적상관성경호，가이위단기기후예측계통제공교호적해양초시장，야가이위물리해양학적연구제공유효적재분석자료。
A global ocean data assimilation system named ZFL_GODAS is developed in this study. The system is a sub-system of an operational system for short-range climate forecasting, and provides the global ocean initial state field for coupled ocean-atmosphere models. It can assimilate observations such as satellite altimetry, sea surface temperature (SST), in situ temperature, and salinity from Argo, XBT, TAO, and other sources. ZFL_GODAS uses LICOM1.0 (a global OGCM developed by LASG/IAP) as its ocean model. It is an ensemble optimal interpolation system that uses an ensemble of a series of model states from a free LICOM running to estimate the background error covariances (BECs). The ensemble-based BECs are multivariate and inhomogeneous and they can reflect the length scales, anisotropy, and covariability of oceanic physical processes. To enhance the efficiency, a set of distinctive, efficient, and load-balanced parallelized Ensemble Optimal Interpolation (EnOI) programs have been developed. <br> The performance of ZFL_GODAS is evaluated by comparing its results with a range of satellite-derived and in situ observations. We compare the interannual variability of SST and sea surface height, the evolution of the SST anomaly at the equator, and the root-mean-square error of model results of SST, sea level anomaly, and sub-surface temperature and salinity. We also show the five-year-mean profiles for temperature bias, salinity, and zonal velocity. We find that the ocean data assimilation shows a very positive impact on the modeled fields. We can preliminarily conclude that ZFL_GODAS performs well, so it can provide a desirable global ocean initial state for the ocean model component of the climate forecasting system, and provide effective reanalysis data for improving our understanding of the oceans.