Evaluation on data assimilation of a global high resolution wave-tide-circulation coupled model using the tropical Pacific TAO buoy observations
-
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。Abstract: 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.
-
Key words:
- tropical Pacific /
- tropical atmosphere ocean /
- data assimilation /
- evaluation
-
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
点击查看大图
计量
- 文章访问数: 1440
- HTML全文浏览量: 51
- PDF下载量: 695
- 被引次数: 0