地球科学进展 ›› 2016, Vol. 31 ›› Issue (10): 1090 -1104. doi: 10.11867/j.issn.1001-8166.2016.10.1090

研究简报 上一篇    

中国全球业务化海洋学预报系统的发展和应用
王辉 1, 2, 万莉颖 1, 2, 秦英豪 1*, *, 王毅 1, 杨学联 1, 刘洋 1, 邢建勇 1, 陈莉 1, 王彰贵 1, 仉天宇 1, 刘桂梅 1, 杨清华 1, 吴湘玉 1, 刘钦燕 3, 王东晓 3   
  1. 1.国家海洋环境预报中心,北京 100081;
    2.国家海洋局海洋灾害预报技术研究重点实验室,国家海洋环境预报中心,北京 100081;
    3.热带海洋环境国家重点实验室,中国科学院南海海洋研究所,广东 广州 510301
  • 收稿日期:2016-07-10 修回日期:2016-09-12 出版日期:2016-10-20
  • 通讯作者: 秦英豪(1983-),男,河南焦作人,助理研究员,主要从事资料同化、数值模拟和海洋预报理论和方法研究.E-mail: qinyh@nmefc.gov.cn
  • 基金资助:
    国家自然科学基金青年科学基金项目“热带太平洋三种增暖事件次表层海温演变特征及机理研究”(编号:41406042); 热带海洋环境国家重点实验室(中国科学院南海海洋研究所)开放课题项目“全球海洋资料同化系统在热带太平洋三种不同海水增暖事件中盐度变化特征分析”(编号:LTO1303)资助

Development and Application of the Chinese Global Operational Oceanography Forecasting System

Wang Hui 1, 2, Wan Liying 1, 2, Qin Yinghao 1, *, Wang Yi 1, Yang Xuelian 1, Liu Yang 1, Xing Jianyong 1, Chen Li 1, Wang Zhanggui 1, Zhang Tianyu 1, Liu Guimei 1, Yang Qinghua 1, Wu Xiangyu 1, Liu Qinyan 3, Wang Dongxiao 3   

  1. 1.National Marine Environmental Forecasting Center,Beijing 100081, China;
    2.Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing 100081, China;
    3.State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou 510301, China
  • Received:2016-07-10 Revised:2016-09-12 Online:2016-10-20 Published:2016-10-20
  • About author:Wang Hui(1962-), male,Suixi City, Anhui Province, Professor. Research areas include ocean forecasting, operational oceanography and ocean dynamics.E-mail:wangh@nmefc.gov.cn*Corresponding author:Qin Yinghao(1983-), male, Jiaozuo City, Henan Province,Associate professor. Research areas include data assimilation, numerical simulation and ocean forecasting.E-mail:qinyh@nmefc.gov.cn
  • Supported by:
    Project supported by the National Natural Science Foundation of China “Spatial and temporal variability of sub-surface temperature in the three kinds of Pacific Ocean warming events and associated dynamic mechanisms”(No.41406042); The State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology Chinese Academy of Sciences “Salinity variability in the three kinds of Pacific Ocean warming events using a global ocean data assimilation system”(No.LTO1303)
中国全球业务化海洋学预报系统是国家海洋环境预报中心在国内首次构建的全球—大洋—近海3级嵌套的全球业务化海洋学预报系统体系,系统稳定高效业务运行,通过多种方式实时提供和发布全球多尺度多要素的海流、海浪、海温、海冰、海面风场等预报产品,实现了全球海域范围内从百公里级到公里级空间分辨率的一体化预报业务全覆盖。全球业务化海洋学预报系统从全球尺度、大洋尺度到中国周边海域包括8个子系统:全球海面风场数值预报子系统、全球海洋环流数值预报子系统、全球海浪数值预报子系统、全球潮汐潮流数值预报子系统、印度洋海域海洋环境数值预报子系统、极地海冰数值预报子系统、中国周边海域精细化海洋环境数值预报子系统、全球海洋环境预报业务化集成支撑子系统。该系统紧密结合我国经济社会发展和军事保障需求,在“雪龙号”极地遇险脱困预报保障、马航MH370失联飞机搜救预报保障、“蛟龙号”多次深潜海试预报保障、日本福岛“3.11”地震海啸核泄漏影响评估等重大事件的预报保障任务中发挥了至关重要的作用,为我国实施海洋强国战略,维护国家海洋权益、保障涉海安全生产、应对海上突发事件等提供有力的科技支撑。
Chinese Global operational Oceanography Forecasting System (CGOFS) is configured in three levels of nested grids from global ocean, open ocean to offshore. This global operational oceanography forecasting system architecture is firstly bulit in China by the National Marine Environmental Forecasting Center (NMEFC). It has been put into operational forecasting at NMEFC, providing real-time forecasting of multi-scale ocean current, temperature, salinity, wave, sea surface wind, etc. All the ocean forecasting products are released in many ways and made available through the online, realizing full-range coverage in resolution from hundreds kilometer to several kilometer. The CGOFS includes 8 subsystems: global sea-surface wind numerical forecasting subsystem, global ocean circulation numerical forecasting subsystem, global ocean wave numerical forecasting subsystem, global tide and tidal current forecasting subsystem, Indian Ocean marine environment numerical forecasting subsystem, polar sea ice numerical forecasting subsystem, refined marine environment numerical forecasting for China’s surrounding waters,and integration management subsystem for operational support service of the CGOFS. Operational applications of the CGOFS are closely connected with China’s economic-social development and military security needs. For example, the CGOFS palys a crucial role in environmental forecasting for Chinese research vessel and icebreaker Xuelong, MH370 Searching, submersible “Jiaolong” exploration and nuclear contaminant transport from Fukushima Daiichi nuclear power plant, providing important scientific support for developing an ocean power, protecting national maritime rights, ensuring marine safety and coping with ocean problems in emergency.

中图分类号: 

[1] Schiller A, Brasssington G B. Operational Oceanography in the 21 st Century[M]. Netherland: Springer, 2011.
[2] Intergovernmental Oceanographic Commission (IOC),United Nations Educational, Scientific and Cultural Organization(UNESCO). Technical Report on Scoping of Operational Oceanography[R]. IOC/INF-1291 Paris, 2012.
[3] Woods J D, Dahlin H, Droppert L, et al. The Strategy for EuroGOOS[R]. EuroGOOS publication No.1, Southampton Oceanography Centre, ISBN 0-904175-22-7, Southampton, 1996.
[4] Pinardi N, Woods J. Ocean Forecasting: Conceptual Basis and Applications[M].Berlin:Springer Verlag, 2002.
[5] Pinardi N, Coppini G. Preface “Operational oceanography in the Mediterranean Sea: The second stage of development”[J]. Ocean Science , 2010, 6(1):263-267.
[6] Wang Hui. Scientific Frontier for Ocean Forecasting and Operational Oceanography[R]. Beijing:The 459 th Xiangshan Science Conferences (XSSC), 2013.
. 北京:第459次香山科学会议,2013.]
[7] Bell M J, Lefèbvre M, Le Traon P Y, et al. GODAE: The global ocean data assimilation experiment[J]. Oceanography , 2009, 22(3):14-21.
[8] Bell M J, Schiller A, Le Traon P Y, et al. An introduction to GODAE OceanView[J]. J ournal of Operational Oceanography , 2015, 8(Suppl.1):2-11.
[9] Martin M J, Balmaseda M, Bertino L, et al. Status and future of data assimilation in operational oceanography[J]. Journal of Operational Oceanography ,2015, 8(Suppl.1):28-48.
[10] Metzger E J, Smedstad O M, Thoppil P, et al. Validation Test Report for the Global Ocean Prediction System V3.0-1/12° HYCOM/NCODA: Phase I[R]. NRL Memo. Report, NRL/MR/7320-08-9148, 2008.
[11] Metzger E J, Smedstad O M, Thoppil P, et al. Validation Test Report for the Global Ocean Forecast System V3.0-1/12o HYCOM/NCODA: Phase II[R]. NRL Memo. Report, NRL/MR/7320-10-9236, 2010.
[12] Metzger E J, Smedstad O M, Thoppil P G, et al. US navy operational global ocean and Arctic ice prediction systems[J]. Oceanography , 2014, 27(3):32-43.
[13] Zhu Yaping, Cheng Zhoujie, He Xiyu. Overview of US naval operational ocean forecasting system[J]. Marine Forecasts , 2015, 32(5): 98-105.
. 海洋预报,2015, 32(5):98-105.]
[14] Divakaran P, Brassington G B, Ryan A G, et al . GODAE OceanView inter-comparison for the Australian region[J]. Journal of Operational Oceanography , 2015, 8(Suppl.1): s112-s126.
[15] Mehra A, Rivin I. A real time ocean forecast system for the north Atlantic Ocean[J]. Terrestrial , Atmospheric and Oceanic Sciences , 2010, 21(1):211-228.
[16] Cummings J A. Operational multivariate ocean data assimilation[J]. Quarterly Journal of the Royal Meteorological Society , 2005, 131(613):3 583-3 604.
[17] Cummings J A, Smedstad O M. Variational data assimilation for the global ocean[M]∥Park S K, Xu L,eds.Data Assimilation for Atmospheric, Oceanic & Hydrologic Applications (Vol. II) . Berlin Heidelberg:Springer,2013:303-343.
[18] Tranchant B, Testut C E, Ferry N, et al. SAM2: The second generation of Mercator assimilation system[C]∥Proceeding of the 4 th international Conference on EUROGOOS. Brest, 2005:650-655.
[19] Brasseur P, Bahurel P, Bertino L, et al. Data assimilation in operational ocean forecasting systems: The MERCATOR and MERSEA developments[J]. Quarterly Journal of the Royal Meteorological Society , 2005, 131(613):3 561-3 582.
[20] Tranchant B, Testut C E, Bourdallé-Badie R, et al. The global 1/12°Mercator Ocean forecasting system:Scientific design and first results[R]∥GODAE Final Symposium 2008. Nice,France:GODAE Prject office,2008.
[21] Ferry N, Parent L, Garric G, et al. Mercator Global Eddy Permitting Ocean Reanalysis GLORYS1V1: Description and Results[R]. Mercator Ocean Quarterly Newsletter #36,2010.
[22] Parent L, Ferry N, Barnier B, et al . GLOBAL Eddy-Permitting Ocean Reanalyses and Simulations of the Period 1992 to Present[R]. Technical Report, Mercator Ocean, 2013.
[23] Lellouche J M,Le Galloudec O, Drévillon M, et al . Evaluation of global monitoring and forecasting systems at Mercator Océan[J]. Ocean Science , 2013, 9(1):57-81.
[24] Lellouche J M, Legalloudec O, Bourdallé-Badie R, et al. The Global Mercator Ocean Analysis and Forecasting High Resolution System and Its Main Future Updates[R].Vienna, Austria: European Geosciences Union General Assembly,2015.
[25] Dombrowsky E, Bertino L, Brassington G B, et al. GODAE systems in operations[J]. Oceanography , 2009, 22(3):80-95.
[26] Bell M J, Forbes R M, Hines A. Assessment of the FOAM global data assimilation system for real-time operational ocean forecasting[J]. Journal of Marine Systems , 2000, 25(1):1-22.
[27] Blockley E W, Martin M J, McLaren A J, et al . Recent development of the Met Office operational ocean forecasting system: An overview and assessment of the new Global FOAM forecasts[J]. Geoscientific Model Development , 2014, 7(6):2 613-2 638.
[28] Mogensen K S, Balmaseda M A, Weaver A, et al. A variational data assimilation system for the NEMO ocean model[J]. ECMWF Newsletter ,2009,20:17-22.
[29] Mogensen K S, Balmaseda M A, Weaver A. The NEMOVAR Ocean Data Assimilation System as Implemented in the ECMWF Ocean Analysis for System 4[Z].ECMWF Technical Memorandum,2012.
[30] Martin M J, Hines A, Bell M J. Data assimilation in the FOAM operational short-range ocean forecasting system: A description of the scheme and its impact[J]. Quarterly Journal of the Royal Meteorological Society ,2007,133(625):59-89.
[31] Waters J, Lea D J, Martin M J, et al. Describing the Development of the New Foam-nemovar System in the Global 1/4 Degree Configuration[R]. Technical Report 578, Met Office, 2013.
[32] Waters J, Lea D J, Martin M J, et al. Implementing a variational data assimilation system in an operational 1/4 degree global ocean model[J]. Quarterly Journal of the Royal Meteorological Society , 2014, 141(687):333-334
[33] Blockley E W, Coauthors. Recent development of the Met Office operational ocean forecasting system: An overview and assessment of the new Global FOAM forecasts[J]. Geoscientific Model Development , 2013, 6(7):6 219-6 278.
[34] Brassington G B, Pugh T, Spillman C, et al. BLUElink> development of operational oceanography and servicing in Australia[J]. Journal of Research and Practice in Information Technology , 2007, 39(2):151-164.
[35] Oke P R, Brassington G B, Griffin D A, et al. The Bluelink Ocean Data Assimilation System (BODAS)[J]. Ocean Modelling , 2008, 21(1):46-70.
[36] Oke P R, Griffin D A, Schiller A, et al. Evaluation of a near-global eddy-resolving ocean model[J]. Geoscientific Model Development ,2013, 6(3):591-615.
[37] Usui N, Ishizaki S, Fujii Y, et al . Meteorological research institute Multivariate Ocean Variational Estimation (MOVE) system: Some early results[J]. Advances in Space Research , 2006, 37(4):806-822.
[38] Toyoda T, Fujii Y, Yasuda T, et al. Improved analysis of seasonal-interannual fields using a global ocean data assimilation system[J]. Theoretical and Applied Mechanics Japan , 2013, 61:31-48,doi: 10.11345/inctam.61.31.
[39] Toyoda T, Fujii Y, Yasuda T, et al. Data assimilation of sea ice concentration into a global ocean-sea ice model with corrections for atmospheric forcing and ocean temperature fields[J]. Journal of Oceanography , 2016, 72(2):235-262.
[40] Dupont F, Chittibabu P, Fortin V, et al. Assessment of a NEMO-based hydrodynamic modelling system for the Great Lakes[J]. Water Quality Research Journal of Canada , 2012, 47(3/4):198-214.
[41] Dupont F, Higginson S, Bourdallé-Badie R, et al. A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans[J]. Geoscientific Model Development , 2015, 8(5):1 577-1 594.
[42] Francis P A, Vinayachandran P N, Shenoi S S C. The Indian ocean forecast system[J]. Current Science , 2013, 104(10):1 354-1 368.
[43] Lima J A M, Martins R P, Tanajura C A S, et al . Design and implementation of the Oceanographic Modeling and Observation Network (REMO) for operational oceanography and ocean forecasting[J]. Revista Brasileira de Geofisica , 2013, 31(2):209-228.
[44] Clemente A S T, Alex N S, Davi M, et al . The REMO ocean data assimilation system into HYCOM (RODAS_H):General description and preliminary results[J]. Atmospheric and Oceanic Science Letters ,2014, 7(5):464-470.
[45] Wang H. Recent progress in operational oceanography in the National Marine Environment Forecasting Centre of China[R]∥ 3 rd Meeting of the GODAE OceanView Science Team.Paris, France,2011.
[46] Wan L, Zhu J, Bertino L, et al. Initial ensemble generation and validation for ocean data assimilation using HYCOM in the Pacific[J]. Ocean Dynamics , 2008, 58(2):81-99.
[47] Wan L, Zhu J, Wang H, et al. A “Dressed” ensemble Kalman filter using the hybrid coordinate ocean model in the Pacific[J]. Advances in Atmospheric Sciences , 2009, 26(5):1 042-1 052.
[48] Wan L, Bertino L, Zhu J. Assimilating altimetry data into a HYCOM model of the Pacific:Ensemble optimal interpolation versus Ensemble Kalman Filter[J]. Journal of Atmospheric and Oceanic Technology , 2010, 27(4):753-765.
[49] Zhang R H, Endoh M. A free surface general circulation model for the tropical Pacific Ocean[J]. Journal of Geophysical Research , 1992, 97(C7):11 237-11 255.
[50] Li Hong, Xu Jianping. Development of data assimilation and its application in ocean science[J]. Marine Science Bulletin , 2011, 30(4):463-472.
. 海洋通报, 2011,30(4):463-472.]
[51] Wang Yi, Yu Zhouwen. Validation of impact of assimilation of altimeter satellite significant wave height on wave forecast in the northwest Pacific[J]. Acta Oceanologica Sinica ,2009, 31(6):1-6.
. 海洋学报, 2009, 31(6):1-6.]
[52] Wang Hui, Liu Guimei, Sun Song, et al. A three-dimensional coupled physical and biological modelstudy in the spring of 1993 in Bohai Sea of China[J]. Acta Oceanologica Sinica ,2007, 26(6):1-12.
[53] Liu G, Chai F. Seasonal and interannual variation of physical and biological processes during 1994-2001 in the Sea of Japan/East Sea: A three-dimensional physicalbiogeochemical modeling study[J]. Journal of Marine Systems ,2009, 78(2):265-277.
[54] Liu G, Chai F. Seasonal and interannual variability of primary and export production in the South China Sea: A three-dimensional physical-biogeochemical model study[J]. ICES Journal of Marine Science ,2009, 66(2):420-431.
[55] Chai F, Liu G M, Xue H J, et al. Seasonal and interannual variability of carbon cycle in South China Sea: A three-dimensional physical-biogeochemical modeling study[J]. Journal of Oceanography , 2009, 65(5):703-720.
[56] Li Yan, Zhu Jiang, Wang Hui, et al. The assimilation technology application in the oil spill emergency forecasting system of the Bohai Sea[J]. Acta Oceanologica Sinica , 2014, 36(3):113-120.
. 海洋学报, 2014, 36(3):113-120.]
[57] Wang Dongxiao, Qin Yinghao, Xiao Xianjun, et al. El Niño and El Niño Modoki variability in a new ocean reanalysis[J]. Ocean Dynamics , 2012, 62(9):1 311-1 322.
[58] Wang Dongxiao, Qin Yinghao, Xiao Xianjun, et al . Preliminary results of a new global ocean reanalysis[J]. Chinese Science Bulletin , 2012, 57(26):3 509-3 517.
[59] Xiao Xianjun, He Na, Zhang Zuqiang, et al. Variation assimilation using satellite data of sea surface temperature and altimeter[J]. Journal of Tropical Oceanography , 2011, 30(3):1-8.
. 热带海洋学报, 2011, 30(3):1-8. ]
[60] Qin Y H, Wan L Y, Wang H. A global ocean assimilation system for real time operational forecast[R]∥5 th China-Italy Collaboration Workshop—Operational Oceanography and Regional Climate Change in the Adriatic and South-East China Seas. Lecce, Italy,2014.
[61] Wang H. Operational Oceanography Forecasting System in Developing Countries[R]. GODAE OceanView Symposium 2013.Washington, USA, 2013.
[62] Zhang Binjian. Chinese Global Operational Oceanography Forecasting System is Officially Issued[N]. China Ocean News, 2013-10-18.
. 中国海洋报, 2013-10-18.]
[63] Wang Hui, Liu Na, Pang Renbo, et al . Global ocean forecasting and scientific big data[J]. Chinese Science Bulletin , 2015, 60(5):479-484.
. 科学通报, 2015, 60(5):479-484.]
[64] Tonani M, Balmaseda M, Bertino L, et al. Status and future of global and regional prediction systems[J]. Journal of Operational Oceanography , 2015, 8(Suppl.2):s201-s220.
[65] Kleist D T, Parrish D F, Derber J C, et al. Improving incremental balance in the GSI 3DVAR analysis system[J]. Monthly Weather Review , 137(3):1 046-1 060.
[66] Kleist D T, Kleist D T, Parrish D F, et al. Implementation of a new 3DVAR analysis as part of the NCEP global data assimilation system[J]. Weather Forecasting ,2008,24:1 691-1 705,doi: 10.1175/2008MWR2623.1.
[67] Han J, Pan H L. Revision of convection and vertical diffusion schemes in the NCEP global forecast system[J]. Weather and Forecasting ,2011, 26(4):520-533.
[68] Xu Peng, Liu Zhiyu, Mao Xinyan, et al. Estimation of vertical eddy viscosity and bottom drag coefficients in tidally energetic narrow bay[J]. Journal of Ocean University of China , 2013,43(8):1-7.
.中国海洋大学学报,2013, 43(8):1-7.]
[69] Griffies S M, Harrison M J, Pacanowskir C, et al . A technical guide to MOM4[R]∥GFDL Ocean Group Technical Report.Princeton, New Jersey:NOAA/Geophysical Fluid Dynamics Laboratory,2013.
[70] Ardhuin F, Rogers E, Babanin A V, et al . Semiempirical dissipation source functions for ocean waves. Part I: Definition, calibration, and validation[J]. Journal of Physical Oceanography , 2010, 40(9):1 917-1 941.
[71] Bi Fan. On the Wave-Induced Effect to Circulation Transport and the Characteristics of Swell Propagation and Dissipation[D].Qingdao:Ocean University of China, 2013.
.青岛:中国海洋大学, 2013.]
[72] Chen C S, Beardsley R C, Cowles G. An Unstructured Grid, Finite-Volume Coastal Ocean Model FVCOM User Manual[R].SMAST/UMASSD, 2006:6-8.
[73] Li Hong, Xu Jianping, Liu Zenghong, et al. Study on the global ocean Argo gridded dataset and its validation community in coastal waters of Yantai[J]. Marine Science Bulletin ,2013,32(6):108-118.
. 海洋通报,2013,32(6):108-118.]
[74] Yang Q, Losa S N, Losch M, et al. Assimilating SMOS sea ice thickness into a coupled ice-ocean model using a local SEIK filter[J]. Journal of Geophysical Research Oceans , 2014, 119(10):6 680-6 692.
[75] Zhao Jiechen, Yang Qinghua, Li Ming, et al . Improving Arctic sea ice concentration forecasts with a nudging data assimilation method[J]. Acta Oceanologica Sinica , 2016, 38(5):70-82.
.海洋学报, 2016, 38(5):70-82.]
[76] Yang Qinghua, Liu Jiping, Zhang Zhanhai, et al . A preliminary study of the Arctic Sea ice numerical forecasting: Coupled sea ice-ocean modelling experiments based on MITgcm[J]. Chinese Journal of Atmospheric Sciences ,2011,35(3): 473-482.
. 大气科学, 2011, 35(3):473-482.]
[77] Yang Q, Liu J, Leppäranta M, et al. Albedo of coastal landfast sea ice in Prydz Bay, Antarctica: Observations and parameterization[J]. Advances in Atmospheric Sciences , 2016, 33(5):535-543.
[78] Yang, Q, Liu J, Zhang Z, et al. Sensitivity of the Arctic sea ice concentration forecasts to different atmospheric forcing: A case study[J]. Acta Oceanologica Sinica , 2014, 33(12):15-23.
[79] Yang Q, Losa S N, Losch M, et al . The role of atmospheric uncertainty in Arctic summer sea ice data assimilation and prediction[J]. Quarterly Journal of the Royal Meteorological Society ,2015, 141(691):2 314-2 323.
[80] Lyu Guokun, Wang Hui, Zhu Jiang, et al .Assimilating the along-track sea level anomaly into the regional ocean modeling system using the ensemble optimal interpolation[J]. Acta Oceanologica Sinica ,2014, 33(7):72-82.
[81] Ji Qiyan, Zhu Xueming, Wang Hui, et al . Assimilating operational SST and sea ice analysis data into an operational circulation model for the coastal seas of China[J]. Acta Oceanologica Sinica , 2015, 34(7):54-64.
[82] Ji Min,Chen Li, Jin Fengxiang, et al . Adaptive-step based marine fluid flow streamline constructing algorithm[J]. Geomatics and Information Science of Wuhan University , 2014, 39(9):1 052-1 056.
. 武汉大学学报:信息科学版, 2014, 39(9):1 052-1 056.]
[83] Zhang Lin, Li Chunhua, Chai Xianming, et al. Analysis of oceanic and meteorological elements when R/V Xuelong trapped in the Antarctic pack ice zone in early January 2014[J]. Chinese Journal of Polar Research ,2014, 26(4):487-495.
. 极地研究, 2014, 26(4):487-495.]
[84] Lu Qi. The Role of Chinese Global Operational Oceanography Forecasting System in the Search for MH370[N]. China Science Daily, 2014-03-24.
. 中国科学报, 2014-03-24.]
[85] Wu Mengmeng,Wan Liying,Liu Kewei, et al. Comparative study on the operational numerical prediction results from WRF and MM5 in the Indian Ocean[J]. Marine Forecasts , 2014, 31(3):66-71.
. 海洋预报, 2014, 31(3):66-71.]
[86] Wang H, Wang Z Y, Zhu X M, et al. Numerical study and prediction of nuclear contaminant transport from Fukushima Daiichi nuclear power plant in the North Pacific Ocean[J]. Chinese Science Bulletin , 2012, 57(26):3 518-3 524.
[87] Fang Changfang, Zhang Xiang, Yin Jianping. Development status and trends of ocean forecasting system in the 21st Century[J]. Marine Forecasts ,2013, 30(4):93-100.
. 海洋预报, 2013, 30(4):93-100.]
[88] Hurlburt H E, Chassignet E P, Cummings J A, et al. Eddy-resolving global ocean prediction[M]∥Hecht M, Hasumi H,eds. “Ocean Modeling in An Eddying Regime”. Geophysical Monograph 177. Washington:American Geophysical Union,2008.
[89] Cummings J A. Operational multivariate ocean data assimilation[J]. Quarterly Journal of the Royal Meteorological Society ,2005, 131(613):3 583-3 604.
[90] Ren Shihe, Wang Hui, Liu Na. Review of ocean front in Chinese marginal seas and frontal forecasting[J]. Advances in Earth Science , 2015,30(5):552-563.
. 地球科学进展,2015,30(5):552-563.]
[91] Xiong Chunhui, Zhang Lifeng, Guan Jiping, et al . Development and application of ensemble-variational data assimilation methods[J]. Advances in Earth Science , 2013, 28(6):648-656.
.地球科学进展, 2013, 28(6):648-656.]
[92] Wang Lei, Wang Zhanggui, Ling Tiejun, et al . Review of vertical mixing parameterization in ocean climate modeling[J]. Marine Forecasts , 2014, 31(5):93-104.
. 海洋预报, 2014, 31(5):93-104.]
[93] Griffies S M, Böning C, Bryan F O, et al. Developments in ocean climate modelling[J]. Ocean Modelling , 2000, 2(3):123-192.
[94] Griffies S M, Böning C, Bryan F O, et al. Problems and prospects in large-scale ocean circulation models[C]∥Proceedings of OceanObs’09: Sustained Ocean Observations and Information for Society (Vol. 2). Venice, Italy, 2010.
[95] Zhang Zhiyuan, Song Shunqiang, Liu Li, et al . Numerical simulation and verification of the wave-circulation coupled model[J]. Ocean Technology ,2011,30(4):87-92.
. 海洋技术, 2011, 30(4):87-92.]
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