海洋学研究 >

2015 , Vol. 33 >Issue 1: 1 - 8

DOI: https://doi.org/10.3969/j.issn.1001-909X.2015.01.001

研究论文

海表面温度的变分同化预报模式:初始场的全局优化

  • 高艳秋 ,
  • 苏洁 ,
  • 李磊 ,
  • 吕咸青
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  • 1.卫星海洋环境动力学国家重点实验室,浙江 杭州 310012;
    2.国家海洋局 第二海洋研究所,浙江 杭州310012;
    3.中国海洋大学 海洋环境学院 物理海洋学教育部重点实验室,山东 青岛 266100
高艳秋(1987-),女,山东临沂市人,助理研究员,主要从事物理海洋学方面的研究。E-mail:gaoyanqiujuly11th@163.com

收稿日期: 2014-09-18

  修回日期: 2014-12-03

  网络出版日期: 2022-11-25

基金资助

国家自然科学基金项目资助(41276029);国家“863“计划项目资助(2013AA122803);国家公益性行业(气象)科研专项项目资助(GYHY201306049)

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Application of adjoint assimilation method in a sea surface temperature prediction model:global optimization of the initial field

  • GAO Yan-qiu ,
  • SU Jie ,
  • LI Lei ,
  • LV Xian-qing
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  • 1. State Key Laboratory of Satellite Ocean Environment Dynamics, The Second Institute of Oceanography SOA, Hangzhou 310012, China;
    2. Key Laboratory of Physical Oceanography MOE China, Ocean University of China, Qingdao 266100, China

Received date: 2014-09-18

  Revised date: 2014-12-03

  Online published: 2022-11-25

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摘要

利用变分同化技术,将船舶报资料与海表面温度短期数值预报模式有机结合,实现了渤、黄、东海的海表面温度短期数值预报。本预报模式利用伴随方法实现了预报模式的全局优化,不但最大限度地利用了船舶报资料,而且初始温度场的调整由自动的数值迭代过程来实现。在渤、黄、东海海域,4个季节的典型月份的SST连续1个月的24 h后报结果与船舶报资料均方差均降至0.8 ℃以下。同化后海表面温度初始场的绝均差较同化前有显著下降。与以前所用的客观分析方法比较的结果表明,伴随同化的预报精度明显高于客观分析方法。

关键词： 伴随同化; 海表面温度; 短期数值预报; 渤、黄、东海

本文引用格式

高艳秋 , 苏洁 , 李磊 , 吕咸青 . 海表面温度的变分同化预报模式:初始场的全局优化[J]. 海洋学研究, 2015 , 33(1) : 1 -8 . DOI: 10.3969/j.issn.1001-909X.2015.01.001

Abstract

Variational assimilation technique, in conjunction with the ship reported data, is applied to a short term numerical prediction model in order to realize automatic short term SST forecast in the Bohai, the Yellow and the East China Seas. The prediction model, using the adjoint assimilation method, achieves a global optimization of the initial SST field. Corresponding to the four typical months (February, May, August and November) of four quarters respectively in 2002, we do forecast for a month continuously. The results indicate that the root mean square error between the hindcasts of 24 successive hours and the ship reported data is reduced to below 0.8 ℃. The mean absolute errors of SST are reduced markedly, compared with the values before assimilation. The forecast accuracy is improved with the adjoint assimilation method compared with the results from the objective analysis method.

Key words： adjoint assimilation method; sea surface temperature; short term numerical prediction; the Bohai, the Yellow and the East China Seas

参考文献

[1] WANG Ci-zhen, SU Yu-song. A model of SST prediction for limited region, I. The dynamical equations[J]. Oceanologia et Limnologia Sinica,1990,21(9):418-424.
王赐震,苏育蒿.一种有限区域海表面温度预报模式,I.动力学部分[J].海洋与湖沼,1990,21(9):418-424.
[2] WANG Ci-zhen, SU Yu-song. A model of SST prediction for limited region, Ⅱ. The model's physical equations [J]. Oceanologia et Limnologia Sinica,1991,22(1):69-77.
王赐震,苏育蒿.一种有限区域海表面温度预报模式,II.物理学部分[J].海洋与湖沼,1991,22(1):69-77.
[3] WALLCRAFT A J, KARA A B, HURLBURT H E, et al. Value of bulk heat flux parameterizations for ocean SST prediction [J].Journal of Marine Systems,2008,74(1):241-258.
[4] ZHANG W G, WILKIN J L, ARANGO H G. Towards an integrated observation and modeling system in the New York Bight using variational methods. Part I: 4DVAR data assimilation [J]. Ocean Modelling,2010,35(3):119-133.
[5] PENG Shi-qiu,XIE Lian. Effect of determining initial conditions by four-dimensional variational data assimilation on storm surge forecasting[J]. Ocean Modelling,2006,14(1):1-18.
[6] PENG Shi-qiu, XIE Lian,PIETRAFESA L J. Correcting the errors in the initial conditions and wind stress in storm surge simulation using an adjoint optimal technique[J]. Ocean Modelling,2007,18(3):175-193.
[7] ANDERSON D L T, SHEINBAUM J, HAINES K. Data assimilation in ocean models[J]. Reports on Progress in Physics,1996,59(10):1 209-1 266.
[8] NAVON I M. Practical and theoretical aspects of adjoint parameter estimation and identifiability in meteorology and oceanography [J]. Dynamics of Atmospheres and Oceans,1997,27(1):55-79.
[9] ROQUET H, PLANTON S. Determination of ocean heat fluxes by a variational method [J]. Journal of Geophysical Research,1993,98(c6):10 211-10 221.
[10] YU Li-san, O'BRIEN J J. Variational data assimilation for determining the seasonal net surface heat fluxes using a ropical Pacific Ocean Model [J]. Journal of Physical Oceanography,1995,25(10):2 319-2 343.
[11] YUAN Dong-liang, HSUEH Y. Inverse determination of surface heat flux over the Yellow Sea in winter 1986 from sea surface temperature data [J]. Journal of Physical Oceanography,1998,28(5):984-990.
[12] POWEL B S, ARANGO H G, MOORE A M, et al. 4DVAR data assimilation in the Intra-Americas Sea with the Regional Ocean Modeling System (ROMS) [J]. Ocean Modelling,2008,23(3):130-145.
[13] POWELB S, MOORE A M, ARANGO H G, et al. Near real-time ocean circulation assimilation and prediction in the Intra-Americas Sea with ROMS[J]. Dynamics of Atmospheres and Oceans,2009,48(1):46-68.
[14] BROQUET G, EDWARDS C A, MOORE A M, et al. Application of 4D-Variational data assimilation to the California Current System[J]. Dynamics of Atmospheres and Oceans,2009,48(1):69-92.
[15] WANG Ci-zhen, LI Xu-hua, QI Jian-hua, et al. A numerical model for predicting offshore SST anomaly in the East China Sea, I. Establishment of model [J]. Acta Oceanologica Sinica,1998,20(3):27-34.
王赐震,李许花,戚建华,等.中国近海异常海温数值预报模式研究,I.模式的建立[J].海洋学报,1998,20(3):27-34.
[16] WANG Ci-zhen, LI Xu-hua, QI Jian-hua, et al. A numerical model for predicting offshore SST anomaly in the East China Sea, II. Factor analyses and experiment forecast [J]. Acta Oceanologica Sinica,1998,20(5):19-26.
王赐震,李许花,戚建华,等.中国近海异常海温数值预报模式研究,II.因子分析和试预报[J].海洋学报,1998,20(5):19-26.
[17] SU Jie, LI Lei, BAO Xian-wen, et al. Numerical experiment of SST response to typhoon process in Yellow Sea and Bohai Sea [J]. Journal of Ocean University of Qingdao,2001,31(2):165-172.
苏洁,李磊,鲍献文,等.黄、渤海表层海温对台风过程响应数值试验[J].青岛海洋大学学报,2001,31(2):165-172.
[18] SU Jie, LI Lei, GAO Guo-ping, et al. Numerical experiment of the summer SSTA affected by sub-tropical high in the Yellow Sea and Bohai Sea[J]. Journal of Ocean University of Qingdao,2000,30(4):567-574.
苏洁,李磊,高郭平,等.副高对黄渤海夏季异常海温影响的数值试验[J].青岛海洋大学学报,2000,30(4):567-574.
[19] ZHANG Jian-hua, SU Jie, LI Lei, et al. A numerical model for predicting shortdated SST in the China Sea [J]. Marine Forecasts,2005,22(Supplement):122-127.
张建华,苏洁,李磊,等.SST短期数值预报[J].海洋预报,2005,22(增刊):122-127.
[20] ZHU Jiang, WANG Hui, ZHOU Guang-qing. Adaption variational assimilation of SST[J]. Chinese Sciences Bulletin,2002,47(19):1 517-1 520.
朱江,王辉,周广庆.海表温度的自适应变分同化[J].科学通报,2002,47(19):1 517-1 520.
[21] MA Ji-rui, HAN Gui-jun, LI Dong. A study on the application of variational adjoint data assimilation for numerical prediction of sea surface temperature [J]. Acta Oceanologica Sinica,2002,24(5):1-7.
马继瑞,韩桂军,李冬.变分伴随数据同化在海表面温度预报中的应用研究[J].海洋学报.2002,24(5):1-7.
[22] HUANG Si-xun, HAN Wei, WU Rong-sheng. Theoretical analysis and numerical experiment of variational data assimilation in one-dimensional SST model combining inverase problem skill[J]. Science in China :Series D,2003,33(9):903-911.
黄思训,韩威,伍荣生.结合反问题技巧对一维海温模式变分资料同化的理论分析及数值实验[J].中国科学:D缉,2003,33(9):903-911.
[23] HE Zhong-jie, HAN Gui-jun, LI Wei, et al. Experiments on assimilation of satellite data in the China Seas and adjacent seas[J]. Journal of Ocean University of China,2010,4(9):1-7.
何忠杰,韩桂军,李威,等.中国海及邻近海域卫星观测资料同化实验[J].中国海洋大学学报,2010,4(9):1-7.
[24] LING Tie-jun, ZHANG Yun-fei, YANG Xue-lian, et al. The application of MM5 model to predict sea surface wind field [J]. Marine Forecasts,2004,21(4):1-9.
凌铁军,张蕴斐,杨学联,等.中尺度数值预报模式(MM5)在海面风场预报中的应用[J].海洋预报,2004,21(4):1-9.
[25] GRELL G A. Prognostic evaluation of assumptions used by cumulus parameterization [J]. Monthly Weather Review,1993,121(3):764-787.
[26] YU Li-san, O'BRIEN J J. On the initial condition parameter estimation [J]. Journal of Physical Oceanography,1992,22(11):1 361-1 364.
[27] SIRKES Z. Finite difference of adjoint or adjoint of finite difference [J]. Monthly Weather Review,1997,125(12):3 373-3 378.
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