| SHI Junqiang,YIN Xunqiang,SHU Qi,XIAO Bin,QIAO Fangli.Evaluation on data assimilation of a global high resolution wave-tide-circulation coupled model using the tropical Pacific TAO buoy observations[J].Acta Oceanologica Sinica,2018,37(3):8-20 |
| 利用热带太平洋TAO浮标阵列评估全球高分辨率浪-潮-流耦合模式同化结果 |
| Evaluation on data assimilation of a global high resolution wave-tide-circulation coupled model using the tropical Pacific TAO buoy observations |
| 投稿时间：2017-05-31 |
| DOI：10.1007/s13131-018-1196-2 |
| 中文关键词: 热带太平洋 TAO浮标阵列 数据同化 评估 |
| 英文关键词:tropical Pacific tropical atmosphere ocean data assimilation evaluation |
| 基金项目:The National Program on Global Change and Air-sea Interaction of China under contract No. GASI-IPOVAI-05; the National Natural Science Foundation of China-Shandong Joint Fund for Marine Science Research Centers of China under contract No. U1606405; the International Cooperation Project on the China-Australia Research Centre for Maritime Engineering of Ministry of Science and Technology, China under contract No. 2016YFE0101400; the Aoshan Talents Program under contract No. 2015ASTP; the Transparency Program of Pacific Ocean-South China Sea-Indian Ocean supported by Qingdao National Laboratory for Marine Science and Technology China under contract No. 2015ASKJ01. |
| 作者 | 单位 | E-mail | | 史军强 | 中国海洋大学海洋与大气学院, 青岛, 266100
国家海洋局第一海洋研究所, 青岛, 266061 | | | 尹训强 | 国家海洋局第一海洋研究所, 青岛, 266061
区域海洋动力学与数值模拟功能实验室, 青岛海洋科学与技术国家实验室, 青岛, 266237
海洋科学与数值模拟重点实验室, 国家海洋局, 青岛, 266061 | | | 舒启 | 国家海洋局第一海洋研究所, 青岛, 266061
区域海洋动力学与数值模拟功能实验室, 青岛海洋科学与技术国家实验室, 青岛, 266237
海洋科学与数值模拟重点实验室, 国家海洋局, 青岛, 266061 | | | 肖斌 | 国家海洋局第一海洋研究所, 青岛, 266061
区域海洋动力学与数值模拟功能实验室, 青岛海洋科学与技术国家实验室, 青岛, 266237
海洋科学与数值模拟重点实验室, 国家海洋局, 青岛, 266061 | | | 乔方利 | 国家海洋局第一海洋研究所, 青岛, 266061
区域海洋动力学与数值模拟功能实验室, 青岛海洋科学与技术国家实验室, 青岛, 266237
海洋科学与数值模拟重点实验室, 国家海洋局, 青岛, 266061 | qiaofl@fio.org.cn |
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| 中文摘要: |
| 本文选取2014年8月至2015年7月之间的热带太平洋TAO(Tropical Atmosphere Ocean)浮标观测阵列评估基于全球高分辨率海洋模式的同化结果。全球高分辨率海洋模式FIOCOM(wave-tide-circulation Coupled Ocean Model developed by the First Institute of Oceanography)水平分辨率为0.1°×0.1°，其对应的同化结果由集合调整Kalman滤波数据同化方法同化了海表面温度(SST)、海表异常(SLA)和Argo温盐剖面数据得到。本文对该模式同化前后的结果进行对比分析。首先对总体误差进行统计，模式同化前后结果与对应观测的散点图以及相应的误差概率密度分布显示，包括温度、20℃等温线深度(D20)、盐度以及流速U、V分量的所有模式变量的误差在同化后都有一定程度的减小。其次，从时间平均的角度进一步探讨了模式同化前后结果所对应的各变量水平和垂向结构。结果表明，同化后，温度和D20相对于观测的偏差降低了70%以上，尤其在东太平洋改善效果更为显著。代表上混合层深度的D20结果的显著改善表明同化后温度的结构更加符合实际，上层海洋的垂向结构更加合理。最后，本文对同化前后变量的物理过程演变与观测进行了对比。同化后所有变量的时间演变过程更加接近观测。温度偏差和D20的均方根误差相对于同化前分别降低了76%和56%。在本文研究时间范围内，同化后，更多的物理过程和事件被重现。在2014/2016强El Nino背景下，TAO阵列观测显示，赤道潜流(EUC)强度在2014年8月至11月逐渐增强，而后逐渐减弱。由于同化后的结果改善了对上层海洋的结构的模拟，因此EUC的变化特征能够很好的被刻画出来。总之，在全球高分辨率模式中应用数据同化可以成功地降低模式偏差并改善对上层海洋结构的模拟，使得实际海洋中的物理过程能够较好地重现。 |
| 英文摘要: |
| In order to evaluate the assimilation results from a global high resolution ocean model, the buoy observations from tropical atmosphere ocean (TAO) during August 2014 to July 2015 are employed. The horizontal resolution of wave-tide-circulation coupled ocean model developed by The First Institute of Oceanography (FIOCOM model) is 0.1°×0.1°, and ensemble adjustment Kalman filter is used to assimilate the sea surface temperature (SST), sea level anomaly (SLA) and Argo temperature/salinity profiles. The simulation results with and without data assimilation are examined. First, the overall statistic errors of model results are analyzed. The scatter diagrams of model simulations versus observations and corresponding error probability density distribution show that the errors of all the observed variables, including the temperature, isotherm depth of 20°C (D20), salinity and two horizontal component of velocity are reduced to some extent with a maximum improvement of 54% after assimilation. Second, time-averaged variables are used to investigate the horizontal and vertical structures of the model results. Owing to the data assimilation, the biases of the time-averaged distribution are reduced more than 70% for the temperature and D20 especially in the eastern Pacific. The obvious improvement of D20 which represents the upper mixed layer depth indicates that the structure of the temperature after the data assimilation becomes more close to the reality and the vertical structure of the upper ocean becomes more reasonable. At last, the physical processes of time series are compared with observations. The time evolution processes of all variables after the data assimilation are more consistent with the observations. The temperature bias and RMSE of D20 are reduced by 76% and 56% respectively with the data assimilation. More events during this period are also reproduced after the data assimilation. Under the condition of strong 2014/2016 El Niño, the Equatorial Undercurrent (EUC) from the TAO is gradually increased during August to November in 2014, and followed by a decreasing process. Since the improvement of the structure in the upper ocean, these events of the EUC can be clearly found in the assimilation results. In conclusion, the data assimilation in this global high resolution model has successfully reduced the model biases and improved the structures of the upper ocean, and the physical processes in reality can be well produced. |
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