地球科学进展

地球科学进展 ›› 2018, Vol. 33 ›› Issue (2): 131 -140. doi: 10.11867/j.issn.1001-8166.2018.02.0131

综述与评述 上一篇    下一篇

全球业务化海洋预报进展与展望
刘娜( ), 王辉, 凌铁军, 祖子清   
  1. 国家海洋环境预报中心国家海洋局海洋灾害预报技术研究重点实验室,北京 100081
  • 收稿日期:2017-08-31 修回日期:2017-12-26 出版日期:2018-02-20
  • 基金资助:
    国家自然科学基金项目“两类ENSO对太平洋北赤道流分叉年际变化的影响”(编号: 41406013)和“中国周边海域SST日变化及其对区域气候的影响”(编号:41376016)资助

Review and Prospect of Global Operational Ocean Forecasting

Na Liu( ), Hui Wang, Tiejun Ling, Ziqing Zu   

  1. Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing 100081, China
  • Received:2017-08-31 Revised:2017-12-26 Online:2018-02-20 Published:2018-04-02
  • About author:

    First author:Liu Na(1982-),female,Qingdao City,Shandong Province, Associate professor. Research areas include ocean circulation dynamics, theory and method of ocean forecasting.E-mail:liuna@nmefc.cn

  • Supported by:
    Project supported by the National Natural Science Foundation of China “Impacts of two types of ENSO on the interannual variability of North Equatorial Current bifurcation in the Pacific”(No.41406013) and “Diurnal variation of SST in China’s surrounding sea area and its influence on regional climate”(No.41376016)
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海洋环境预报在经济发展和基础设施建设等方面发挥着越来越重要的作用,涉及到海上安全、海洋能源开发与保护、远洋运输和海洋渔业等许多领域和方面。近年来,各国的全球海洋预报取得了显著的进展。全球海洋数据同化实验(GODAE)OceanView计划为各国提供协调和技术支持,发展并建立全球业务化海洋预报系统,将全球海洋预报的概念实现业务化运行。全球业务化海洋预报系统以海洋动力数值模式作为动力框架,将近实时高质量的观测输入场通过资料同化融入到模式中,实现对全球范围多时空尺度的海洋状况提供未来演替的预测,并对产品表现不间断地进行监测以保证预报服务的质量。简要介绍和回顾GODAE OceanView所涵盖的全球海洋预报系统的发展历程和现状,并对全球海洋预报未来发展的难点与问题给予展望。

关键词: 全球海洋预报, 业务化海洋学, 海洋数据同化, GODAE OceanView

The marine environmental forecast plays an increasingly important role in economic growth and infrastructure development, and touches upon many fields and aspects, including marine security, energy resources development and protection, ocean shipping and fisheries. Global Ocean Data Assimilation Experiment (GODAE) OceanView supports the national research groups providing them with coordination and technical support among the partners. Forecasting centers develop and establish global operational ocean forecast systems. The global operational ocean forecasting system uses the ocean dynamic numerical model as the dynamic framework, and the near real-time high-quality observation input field is integrated into the model by data assimilation to realize the future environmental forecasts of the marine conditions covering the multi-time scale. The products are routinely validated with observations in order to assess their quality. This paper briefly introduced and reviewed the development process and current situation of the global ocean forecasting system covered by GODAE OceanView, and outlined the future development of global ocean forecasting.

Key words: Global ocean forecasting, Operational oceanography, Data assimilation, GODAE OceanView.

中图分类号: 

图1 各国全球业务化海洋预报系统发展历程
Fig.1 Evolution of the development of the ocean forecasting systems in operation in the different countries
表1 国内外全球业务化海洋预报系统
Table 1 Global operational oceanography forecasting systems
系统名称 国家 海洋模式 水平分辨率 垂向层数/层 数据同化方案 海冰模式 大气强迫 预报时效/天
RTOFS 美国 HYCOM 1/12° 32 NCODA
(3DVAR)		 Energy Loan NCEP GFS 3 h
HWRF		 8
GOFS 美国 HYCOM 1/12° 32 NCODA
(3DVAR)		 海军全球环境模式
NAVGEM		 7
PSY4 法国 NEMO 3.1 1/12° 50 SAM2V1-3DVAR
大尺度温度、盐度误差订正		 LIM2_EVP ECMWF 3 h分析
场和预报场		 14
FOAM 英国 NEMO 3.2 1/4° 75 NEMOVAR
(3DVAR)		 CICE Met Office 3 h数值
天气预报		 7
ECMWF 欧洲 NEMO 3.0 1° 42 NEMOVAR
(3DVAR-FGAT)		 ECMWF业务
数值预报场		 18
MOVE/MRI.
COM-G		 日本 MRI.COM
v3.4		 0.3°~1° 50 MOVE(3DVAR) 气候态月
平均		 JRA55-JCDAS 6 h 30
Ocean-MAPS 澳大利亚 MOM4 1/10°~1° 51 BODAS
(ensenble OI)		 ACCESS-GAPS1
ERA-Interim		 7
CGOFS 中国 MOM4 1/4° 50 3DVAR NCEP GFS 6 h 7
CONCEPTS 加拿大 NEMO 3.1 1/4° 50 SAM2-ice 3DVAR CICE GEM 逐小时 10
INDOFOS 印度 MOM4 1/2°×(1/3°~1°) 40 3DVAR NCEP GFS 6 h 5
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[1] 王辉, 万莉颖, 秦英豪, 王毅, 杨学联, 刘洋, 邢建勇, 陈莉, 王彰贵, 仉天宇, 刘桂梅, 杨清华, 吴湘玉, 刘钦燕, 王东晓. 中国全球业务化海洋学预报系统的发展和应用[J]. 地球科学进展, 2016, 31(10): 1090-1104.
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