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Argo data assimilation in ocean general circulation model of Northwest Pacific Ocean

机译:西北太平洋海洋总环流模型中的Argo数据同化

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摘要

The Argo temperature and salinity profiles in 2005-2009 are assimilated into a coastal ocean general circulation model of the Northwest Pacific Ocean using the ensemble adjustment Kalman filter (EAKF). Three nu-merical tests, including the control run (CTL) (without data assimilation, which serves as the reference experiment), ensemble free run (EnFR) (without data assimilation), and EAKF experiment (with Argo data assimilation using EAKF), are carried out to examine the performance of this system. Using the restarts of different years as the initial conditions of the ensemble integrations, the ensemble spreads from EnFR and EAKF are all kept at a finite value after a sharp decreasing in the first few months because of the sensitive of the model to the initial conditions, and the reducing of the ensemble spread due to Argo data assimila-tion is not much. The ensemble samples obtained in this way can well represent the probabilities of the real ocean states, and no ensemble inflation is necessary for this EAKF experiment. Different experiment results are compared with satellite sea surface temperature (SST) data and the Global Temperature-Salinity Profile Program (GTSPP) data. The comparison of SST shows that modeled SST errors are reduced after data assimilation; the error reduction percent-age after assimilating the Argo profiles is about 10 % on average. The comparison against the GTSPP profiles, which are independent of the Argo profiles, shows improvements in both temperature and salinity. The comparison results indicated a great error reduction in all vertical layers relative to CTL and the ensemble mean of EnFR; the maximum value for temperature and salinity reaches to 85 % and 80 %, respectively. The standard deviations of sea surface height are employed to examine the simulation ability, and it is shown that the mesoscale variability is improved after Argo data assimilation, especially in the Kuroshio extension area and along the section of 10°N. All these results suggest that this system is potentially useful for improving the simula-tion ability of oceanic numerical models.
机译:使用集合调整卡尔曼滤波器(EAKF)将2005-2009年的Argo温度和盐度分布图吸收到西北太平洋的沿海海洋一般环流模型中。三个数字测试,包括控制运行(CTL)(无数据同化,用作参考实验),集成自由运行(EnFR)(无数据同化)和EAKF实验(使用EAKF进行Argo数据同化),进行检查该系统的性能。使用不同年份的重启作为集成集成的初始条件,由于模型对初始条件的敏感性,在最初几个月急剧下降之后,EnFR和EAKF的集成点差都保持在一个有限值,并且由于Argo数据同化而导致的集合散度的减小不是很多。以这种方式获得的合奏样本可以很好地表示真实海洋状态的概率,并且对于该EAKF实验而言,不需要合奏膨胀。将不同的实验结果与卫星海表温度(SST)数据和全球温度盐度剖面程序(GTSPP)数据进行了比较。 SST的比较表明,数据同化后,建模的SST误差减少了;吸收Argo配置文件后,错误减少的平均年龄约为10%。与GTSPP轮廓的比较(独立于Argo轮廓)显示出温度和盐度的改善。比较结果表明,相对于CTL和EnFR的整体平均值,所有垂直层的误差都大大降低了。温度和盐度的最大值分别达到85%和80%。利用海面高度的标准偏差来检验模拟能力,结果表明,Argo数据同化后,中尺度变化性得到了改善,特别是在黑潮延伸区和沿10°N的剖面上。所有这些结果表明,该系统对于提高海洋数值模型的仿真能力可能是有用的。

著录项

  • 来源
    《Ocean Dynamics 》 |2012年第7期| p.1059-1071| 共13页
  • 作者单位

    First Institute of Oceanography, State Oceanic Administration (SOA), 6 Xian-Xia-Ling Road, Hi-Tech Industry Park, Qingdao, China 266061;

    First Institute of Oceanography, State Oceanic Administration (SOA), 6 Xian-Xia-Ling Road, Hi-Tech Industry Park, Qingdao, China 266061;

    First Institute of Oceanography, State Oceanic Administration (SOA), 6 Xian-Xia-Ling Road, Hi-Tech Industry Park, Qingdao, China 266061;

    First Institute of Oceanography, State Oceanic Administration (SOA), 6 Xian-Xia-Ling Road, Hi-Tech Industry Park, Qingdao, China 266061;

    First Institute of Oceanography, State Oceanic Administration (SOA), 6 Xian-Xia-Ling Road, Hi-Tech Industry Park, Qingdao, China 266061;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    argo profiles; ensemble adjustment kalman filter; ensemble free runs; ensemble spread; mesoscale variability;

    机译:argo个人资料;集合调整卡尔曼滤波器;合奏自由奔跑;合奏传播中尺度变异;

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