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. doi: 10.1007/s13131-018-1196-2
Citation: 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. doi: 10.1007/s13131-018-1196-2

Evaluation on data assimilation of a global high resolution wave-tide-circulation coupled model using the tropical Pacific TAO buoy observations

doi: 10.1007/s13131-018-1196-2
  • Received Date: 2017-05-31
  • 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.
  • loading
  • Anderson J E, Riser S C. 2014. Near-surface variability of temperature and salinity in the near-tropical ocean: observations from profiling floats. Journal of Geophysical Research: Oceans, 119(11): 7433-7448
    Balmaseda M, Anderson D. 2009. Impact of initialization strategies and observations on seasonal forecast skill. Geophysical Research Letters, 36(1): L01701
    Bennett A F, Chua B S, Harrison D E, et al. 1998. Generalized inversion of tropical atmosphere-ocean data and a coupled model of the tropical Pacific. Journal of Climate, 11(7): 1768-1792
    Bhowmick S A, Agarwal N, Ali M M, et al. 2016. Role of ocean heat content in boosting post-monsoon tropical storms over Bay of Bengal during La-Niña events. Climate Dynamics,, doi: 10.1007/s00382-016-3428-5
    Chen Jinnian, Lv Xinyan, Hu Dunxin. 2005. Variable properties of the equatorial undercurrent in the pacific and its anomalous warm water eastward propagation. Advances in Water Science (in Chinese), 16(6): 792-798
    Chowdary J S, Harsha H S, Gnanaseelan C, et al. 2017. Indian summer monsoon rainfall variability in response to differences in the decay phase of El Niño. Climate Dynamics, 48(7-8): 2707-2727
    Firing E, Lukas R, Sadler J, et al. 1983. Equatorial undercurrent disappears during 1982-1983 El Niño. Science, 222(4628): 1121-1123
    Fu Weiwei, Zhu Jiang, Yan Changxiang, et al. 2009. Toward a global ocean data assimilation system based on ensemble optimum interpolation: altimetry data assimilation experiment. Ocean Dynamics, 59(4): 587-602
    Gao Chuan, Zhang Ronghua. 2017. The roles of atmospheric wind and entrained water temperature (Te) in the second-year cooling of the 2010-12 La Niña event. Climate Dynamics, 48(1-2): 597-617
    Guan Bingxian. 1986. Current structure and its variation in the equatorial area of the western north Pacific Ocean. Chinese Journal of Oceanology and Limnology, 4(3): 239-255
    Hayes S P, Mangum L J, Picaut J, et al. 1991. TOGA-TAO: a moored array for real-time measurements in the tropical Pacific Ocean. Bulletin of the American Meteorological Society, 72(3): 339-347
    Henocq C, Boutin J, Reverdin G, et al. 2010. Vertical variability of near-surface salinity in the tropics: consequences for L-band radiometer calibration and validation. Journal of Atmospheric and Oceanic Technology, 27(1): 192-209
    Jiang Jingzhong. 1993. A event of Pacific equatorial undercurrent inversion during El Niño. Donghai Marine Science (in Chinese), 11(1): 1-9
    Keppenne C L, Rienecker M M. 2003. Assimilation of temperature into an isopycnal ocean general circulation model using a parallel ensemble Kalman filter. Journal of Marine Systems, 40-41: 363-380
    Kimoto M, Yoshikawa I, Ishii M. 1997. An ocean data assimilation system for climate monitoring (gtspecial issueltdata assimilation in meteology and oceanography: theory and practice). Journal of the Meteorological Society of Japan: Series Ⅱ, 75(1): 471-487
    Masuda S, Awaji T, Sugiura N, et al. 2003. Improved estimates of the dynamical state of the north pacific ocean from a 4 dimensional variational data assimilation. Geophysical Research Letters, 30(16): 1868
    McPhaden M J. 2002. El Niño and La Niña: causes and global consequences. In: Munn T, ed. Encyclopedia of Global Environmental Change. Chichester, UK: John Wiley and Sons, 353-370
    Moore A M. 1991. Data assimilation in a quasi-geostrophic open-ocean model of the gulf stream region using the adjoint method. Journal of Physical Oceanography, 21(3): 398-427
    Oke P R, Larnicol G, Fujii Y, et al. 2015. Assessing the impact of observations on ocean forecasts and reanalyses: Part 1. Global studies. Journal of Operational Oceanography, 8(S1): S49-S62
    Paek H, Yu Jinyi, Qian Chengcheng. 2017. Why were the 2015/2016 and 1997/1998 extreme El Niños different?. Geophysical Research Letters, 44(4): 1848-1856
    Parent L, Testut C E, Brankart J M, et al. 2003. Comparative assimilation of Topex/Poseidon and ERS altimeter data and of Tao temperature data in the tropical Pacific Ocean during 1994-1998, and the mean sea-surface height issue. Journal of Marine Systems, 40-41: 381-401
    Qiao Fangli, Ma Jian, Xia Changshui, et al. 2006. Influences of the surface wave-induced mixing and tidal mixing on the vertical temperature structure of the Yellow and East China seas in summer. Progress in Natural Science, 16(7): 739-746
    Qiao Fangli, Yang Yongzeng, Xia Changshui, et al. 2008. The role of surface waves in the ocean mixed layer. Acta Oceanologica Sinica, 27(3): 30-37
    Qiao Fangli, Yuan Yeli, Deng Jia, et al. 2016. Wave-turbulence interaction-induced vertical mixing and its effects in ocean and climate models. Philosophical Transactions of the Royal Society: A. Mathematical, Physical and Engineering Sciences, 374(2065): 20150201
    Qiao Fangli, Yuan Yeli, Ezer T, et al. 2010. A three-dimensional surface wave-ocean circulation coupled model and its initial testing. Ocean Dynamics, 60(5): 1339-1355
    Qiao Fangli, Yuan Yeli, Yang Yongzeng, et al. 2004. Wave-induced mixing in the upper ocean: distribution and application to a global ocean circulation model. Geophysical Research Letters, 31(11): L11303
    Ren Hongli, Liu Ying, Zuo Jinqing, et al. 2016. The new generation of ENSO prediction system in Beijing Climate Centre and its predictions for the 2014/2016 super El Niño event. Meteorological Monthly, 42(5): 521-531
    Salau O R, Akinyemi S A. 2015. The impacts of El Niño/southern oscillation on changing precipitation over the tropical Pacific. International Journal of Environmental Sciences, 5(5): 995-1010
    Shi Qiang, Pu Shuzhen, Su Jie, et al. 1999. Investigation of main current system and equatorial planetary waves in the tropical Pacific during twice untypical El Niño events. Haiyang Xuebao (in Chinese), 21(4): 27-34
    Shu Qi, Qiao Fangli, Bao Ying, et al. 2014. Assessment of arctic sea ice simulation by FIO-ESM based on data assimilation experiment. Haiyang Xuebao (in Chinese), 37(11): 33-40
    Shu Qi, Qiao Fangli, Song Zhenya, et al. 2011. Improvement of MOM4 by including surface wave-induced vertical mixing. Ocean Modelling, 40(1): 42-51
    Stammer D, Köhl A, Awaji T, et al. 2010. Ocean information provided through ensemble ocean syntheses. In: Proceedings of Ocean Obs'09: Sustained Ocean Observations and Information for Society. Venice, Italy: ESA Publication, 920-930
    Sun Chaojiao, Rienecker M M, Rosati A, et al. 2007. Comparison and sensitivity of odasi ocean analyses in the tropical pacific. Monthly Weather Review, 135(6): 2242-2264
    Torma P, Krámer T. 2017. Modeling the effect of waves on the diurnal temperature stratification of a shallow lake. Periodica Polytechnica Civil Engineering, 61(2): 165-175,, doi: 10.3311/PPci.8883
    Vidard A, Anderson D L, Balmaseda M. 2007. Impact of ocean observation systems on ocean analysis and seasonal forecasts. Monthly Weather Review, 135(2): 409-429
    Wang Hongna, Chen Jinnian, He Yijun. 2009. Variations of Equatorial Undercurrent and its relationship with ENSO cycle. Haiyang Xuebao (in Chinese), 31(3): 1-11
    Wang Ou, Fukumori I, Lee T, et al. 2004. Eastern equatorial Pacific Ocean T-S variations with El Niño. Geophysical Research Letters, 31(4): L04305
    Wen Na, Liu Zhengyu, Liu Yinghui. 2015. Direct impact of El Niño on East Asian summer precipitation in the observation. Climate Dynamics, 44(11-12): 2979-2987
    Wu Lichuan, Rutgersson A, Sahlée E. 2015. Upper-ocean mixing due to surface gravity waves. Journal of Geophysical Research: Oceans, 120(12): 8210-8228,, doi: 10.1002/2015JC011329
    Xuan Jiliang, Huang Daji, Zhou Feng, et al. 2012. Application of data assimilation to synoptic temperature mapping of the coastal ocean survey. Oceanologia et Limnologia Sinica (in Chinese), 43(1): 17-26
    Xue Yan, Wen Caihong, Yang Xiaosong, et al. 2017. Evaluation of tropical Pacific observing systems using NCEP and GFDL ocean data assimilation systems. Climate Dynamics, 49(3): 843-868
    Yin Xunqiang, Qiao Fangli, Shu Qi. 2011. Using ensemble adjustment Kalman filter to assimilate Argo profiles in a global OGCM. Ocean Dynamics, 61(7): 1017-1031
    Yin Xunqiang, Qiao Fangli, Yang Yongzeng, et al. 2010. An ensemble adjustment Kalman filter study for Argo data. Chinese Journal of Oceanology and Limnology, 28(3): 626-635
    Yin Xunqiang, Qiao Fangli, Yang Yongzeng, et al. 2012. Argo data assimilation in ocean general circulation model of northwest Pacific Ocean. Ocean Dynamics, 62(7): 1059-1071
    Yuan Yuan, Gao Hui, Jia Xiaolong, et al. 2016. Influences of the 2014-2016 super El Niño event on climate. Meteorological Monthly (in Chinese), 42(5): 532-539
    Yuan Yeli, Hua Feng, Pan Zengdi, et al. 1991. LAGFD-WAM numerical wave model-I. Basic physical model. Acta Oceanologica Sinica, 10(4): 483-488
    Zhai Panmao, Yu Rong, Guo Yanjun, et al. 2016. The strong El Niño in 2015/2016 and its dominant impacts on global and China's climate. Acta Meteorologica Sinica (in Chinese), 74(3): 309-321
    Zhang Ronghua, Levitus S. 1996. Structure and evolution of interannual variability of the tropical Pacific upper ocean temperature. Journal of Geophysical Research: Oceans, 101(C9): 20501-20524
    Zhang Ronghua, Levitus S. 1997. Interannual variability of the coupled tropical Pacific ocean-atmosphere system associated with the El Niño-Southern Oscillation. Journal of Climate, 10(6): 1312-1330
    Zuo T, Chen Jinnian, Wang Hongna. 2014. Impact of the central Pacific zonal wind divergence and convergence on the central Pacific El Niño event. Acta Oceanologica Sinica, 33(11): 85-89
  • 加载中


    通讯作者: 陈斌,
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (1385) PDF downloads(693) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint