中国Argo海洋观测十五年

doi:10.11867/j.issn.1001-8166.2016.05.0445.

地球科学进展 ›› 2016, Vol. 31 ›› Issue (5): 445 -460. doi: 10.11867/j.issn.1001-8166.2016.05.0445.

中国Argo海洋观测十五年

刘增宏 ¹(

), 吴晓芬 ¹, 许建平 ^1,,A; ^*(

), 李宏 ², 卢少磊 ¹, 孙朝辉 ¹, 曹敏杰 ¹

1.卫星海洋环境动力学国家重点实验室,国家海洋局第二海洋研究所,浙江杭州 310012
2.浙江省水利河口研究院,浙江杭州 310020

收稿日期:2016-02-18 修回日期:2016-04-28 出版日期:2016-05-20
通讯作者: 许建平 E-mail:liuzenghong@139.com;sioxjp@139.com
基金资助:
科技部科技基础性工作专项重点项目“西太平洋Argo实时海洋调查”(编号:2012FY112300);国家海洋公益性行业科研专项经费项目“印度洋海域海洋环境数值预报系统研制与示范”(编号:201005033)资助

Fifteen Years of Ocean Observations with China Argo

Zenghong Liu ¹( ), Xiaofen Wu ¹, Jianping Xu ^1, ^*( ), Hong Li ², Shaolei Lu ¹, Chaohui Sun ¹, Minjie Cao ¹

1.State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China
2.Zhejiang Institute of Hydraulics and Estuary, Hangzhou 310020, China

Received:2016-02-18 Revised:2016-04-28 Online:2016-05-20 Published:2016-05-10
Contact: Jianping Xu E-mail:liuzenghong@139.com;sioxjp@139.com
About author:
First author:Liu Zenghong(1977-), male, Wuxi City, Jiangsu Province, Associate Professor. Research areas include physical oceanographic investigation and research.E-mail:liuzenghong@139.com

Corresponding author:Xu Jianping(1956-), male, Changshu City, Jiangsu Province, Professor. Research areas include physical oceanographic investigation and research.E-mail:sioxjp@139.com
Supported by:
Project supported by the Science and Technology Basic Work of Ministry of Science and Technology “Argo real-time investigation in the Western Pacific ocean”(No.2012FY112300);The Program of Marine Public Welfare Research Special Funds “Development and demonstration of numerical predicting system for ocean environment in Indian Ocean”(No.201005033)

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中国Argo计划组织实施15年以来,在太平洋和印度洋等海域布放了350多个剖面浮标,建成了我国Argo大洋观测网,并建立了针对Argo剖面浮标的资料接收、处理和分发系统,利用Argo资料开发了多个数据产品,在一定程度上推动了国内海洋数据的共享进程。海量的Argo资料已成为我国海洋和大气科学领域基础研究及业务化应用的主要数据源,特别是在热带气旋(台风)、海洋环流、中尺度涡、湍流、海水热盐储量与输送、大洋水团以及海洋、天气/气候业务化预测预报等方面取得了一批重要的研究和应用成果。随着国际Argo计划由“核心Argo”向“全球Argo”拓展,我国Argo大洋观测网的长期维护和持续发展面临巨大挑战,应紧紧抓住这一难得的机遇,利用国产北斗剖面浮标在南海及邻近我国的西北太平洋和印度洋海域建成Argo区域海洋观测网,为应对全球气候变化及防御自然灾害,更多地承担一个海洋大国的责任和义务。

关键词: Argo计划, Argo大洋观测网, Argo资料, 基础研究, 业务化应用

For 15 years since the beginning of China Argo project, China has deployed over 350 profiling floats in Pacific and Indian ocean, and constructed China Argo ocean observing network. Moreover, we have setup the Argo data receiving, processing and distributing system, and developed various Argo data products using Argo observations, which has promoted the progress of ocean data sharing in China. The abundant Argo data have become a main data source in oceanic and atmospheric basic researches and operational applications. A batch of important achievements in basic research and operational application have been brought, e.g. in aspects of tropical cyclone (typhoon), ocean circulation, meso-scale eddy, turbulence, heat/salt storage and transport and water mass, as well as in ocean, atmosphere/climate operational forecasting and predicting. With the extension of the international Argo program from “Core Argo” to “Global Argo”, we are faced with great challenges in the long-term maintaining and sustained developing of our Argo ocean observing network. It is suggested that we should take the opportunity to construct China regional Argo ocean observing network as soon as possible in adjacent northwestern Pacific and Indian ocean using Chinese BeiDou profiling floats, which will make us to take responsibility and obligation of a big country for addressing global climate changes and preventing natural disasters.

Key words: Argo program, Argo ocean observing network, Argo data, Basic research, Operational application.

中图分类号:

图1 2002—2015年由中国Argo计划布放的剖面浮标位置

Fig.1 The launch positions of Chinese Argo profiling floats in period of 2002-2015

图2 中国Argo实时资料中心数据处理流程

Fig.2 Data flow of processing at China Argo Real-time Data Center

表1 国内开发的Argo网格资料集及其应用情况

Table 1 Argo gridded datasets developed by China and their applications

范围	水平分辨率垂向分辨率	时间分辨率	原始资料	初始场	方法	开发机构	更新情况	参考文献	应用情况
太平洋(123°E~ 81.5°W , 58.5°S~ 58.5°N,)	3°×3°, 0~2 000 dbar不等45层	2002.01- 2005.12, 逐月	Argo	无	时空插值和经验正交函数法	C-ARDC	未更新,未见互联网共享	[18]	使用情况不详
太平洋 (120°E~ 80°W, 60°S~60°N)	3°×3°, 垂向层数不详	月平均,2007.01 -2007.12	Argo	无	克里格插值法	中国水产科学研究院东海水产研究所	未更新, 未共享	[19]	使用情况不详
太平洋 (120°E~ 90°W, 90°S~60°N)	3°×3°, 0~2 000 m 不等36层	2000.01.05- 2008.12.31, 逐周	Argo	无	时空插值和经验正交函数法	国家海洋局第二海洋研究所、解放军理工大学	未更新, 互联网共享	[20]	热带太平洋障碍层变化分析^{[ 28 ]}
全球海洋(180°W ~180°E, 59.5°S~ 59.5°N)	1°×1°, 0~2 000 m 不等26层	2002.01- 2009.12,逐月	Argo	气候态 Argo 资料	多尺度三维变分	国家海洋信息中心	未更新,互联网共享	[21]	混合层年际变化^{[ 29 ]}、太平洋流场^{[ 30 ]}、台湾以东海域海温与温跃层特征^{[ 31 ]}研究等
全球海洋(180°W ~180°E, 59.5°S~ 59.5°N)	1°×1°, 0~1 950 m 不等49层	2004.01至今,逐月	Argo	气候态 Argo 资料	逐步订正法	C-ARDC	每年更新一次, 互联网共享	[22~25]	热带印度洋声场^{[ 32 ]}、全球海洋最大混合层深度估算^{[ 33 ]}、上层海洋季节和年际四维变化结构^{[ 34 , 35 ]}研究等
南海海域(105°~ 122°E, 0°~25°N)	0.25°×0.25°, 0~1 500 m 不等24层	月平均,起始年份不详	WOD 09,Argo	WOA98	多种统计分析方法等	中国科学院南海海洋研究所	准实时更新,未进行互联网共享	[26]	使用情况不详
太平洋(120°E~ 70°W, 60°S~60°N)	1°×1°, 0~2 000 m 不等26层	2004.01- 2011.12,逐月	Argo	气候态 Argo 资料	最优插值	C-ARDC	未更新,互联网共享	[27]	太平洋海域温度^{[ 36 ]}、盐度变化特征研究^{[ 37 ]}等

表1 国内开发的Argo网格资料集及其应用情况

Table 1 Argo gridded datasets developed by China and their applications

范围	水平分辨率垂向分辨率	时间分辨率	原始资料	初始场	方法	开发机构	更新情况	参考文献	应用情况
太平洋(123°E~ 81.5°W , 58.5°S~ 58.5°N,)	3°×3°, 0~2 000 dbar不等45层	2002.01- 2005.12, 逐月	Argo	无	时空插值和经验正交函数法	C-ARDC	未更新,未见互联网共享	[18]	使用情况不详
太平洋 (120°E~ 80°W, 60°S~60°N)	3°×3°, 垂向层数不详	月平均,2007.01 -2007.12	Argo	无	克里格插值法	中国水产科学研究院东海水产研究所	未更新, 未共享	[19]	使用情况不详
太平洋 (120°E~ 90°W, 90°S~60°N)	3°×3°, 0~2 000 m 不等36层	2000.01.05- 2008.12.31, 逐周	Argo	无	时空插值和经验正交函数法	国家海洋局第二海洋研究所、解放军理工大学	未更新, 互联网共享	[20]	热带太平洋障碍层变化分析^{[ 28 ]}
全球海洋(180°W ~180°E, 59.5°S~ 59.5°N)	1°×1°, 0~2 000 m 不等26层	2002.01- 2009.12,逐月	Argo	气候态 Argo 资料	多尺度三维变分	国家海洋信息中心	未更新,互联网共享	[21]	混合层年际变化^{[ 29 ]}、太平洋流场^{[ 30 ]}、台湾以东海域海温与温跃层特征^{[ 31 ]}研究等
全球海洋(180°W ~180°E, 59.5°S~ 59.5°N)	1°×1°, 0~1 950 m 不等49层	2004.01至今,逐月	Argo	气候态 Argo 资料	逐步订正法	C-ARDC	每年更新一次, 互联网共享	[22~25]	热带印度洋声场^{[ 32 ]}、全球海洋最大混合层深度估算^{[ 33 ]}、上层海洋季节和年际四维变化结构^{[ 34 , 35 ]}研究等
南海海域(105°~ 122°E, 0°~25°N)	0.25°×0.25°, 0~1 500 m 不等24层	月平均,起始年份不详	WOD 09,Argo	WOA98	多种统计分析方法等	中国科学院南海海洋研究所	准实时更新,未进行互联网共享	[26]	使用情况不详
太平洋(120°E~ 70°W, 60°S~60°N)	1°×1°, 0~2 000 m 不等26层	2004.01- 2011.12,逐月	Argo	气候态 Argo 资料	最优插值	C-ARDC	未更新,互联网共享	[27]	太平洋海域温度^{[ 36 ]}、盐度变化特征研究^{[ 37 ]}等

图3 2012年8月21~26日台风Bolaven期间的逐日风矢量分布 ^{[

45
]}
(a)彩色阴影为风矢量;(b)黑色三角形为3个采用铱卫星双向通讯的Argo剖面浮标

Fig.3 Daily wind vector distributions for Typhoon Bolaven during August 21~26, 2012 ^{[

45
]}
(a)Wind speeds are shaded by colors;(b)The three selected Iridium profiling floats are marked with black triangles

图4 2001—2004年由Argo浮标轨迹资料获取的太平洋海域表层平均流速分布 ^{[

54
]}(单位:cm/s)

Fig.4 Mean surface velocity vectors derived from Argo trajectories in Pacific ocean in period of 2001-2004 ^{[

54
]} (unit: cm/s)

图5 南大洋地形粗糙程度及湍流混合的水平分布 ^{[

60
]}
(a)地形粗糙度及南大洋布放的高分辨率铱卫星Argo观测剖面位置分布(白点所示),颜色标尺的单位为log ₁₀(粗糙度)(单位:m ²);(b)300~1 800 m垂向积分所得的湍流跨等密度面混合扩散系数水平分布,颜色标尺的单位为log ₁₀(K)(单位:m ²/s)

Fig.5 Horizontal distribution of topographic roughness and diapycnal diffusivity in the Southern Ocean ^{[

60
]}
(a) Topographic roughness and geographic distribution of high-resolution profiles (white dots) obtained from the Argo Iridium floats used in the Southern Ocean and described in this paper, The colour scale represents Log ₁₀(roughness) in m ² ;(b) Horizontal distribution of diapycnal diffusivity, vertically averaged over the depth range 300~1 800 m;The colour scale represents Log ₁₀(K)(roughness) in m ²/s

图6 中尺度涡带来的经向输送的全球分布 ^{[

65
]}
(a)流经纬向断面的涡致经向输送;(b)涡致经向输送的纬向积分

Fig.6 Global distribution of the meridional transport of fluid trapped by mesoscale eddies ^{[

65
]}
(a) Eddy-induced meridional transport through a zonal cross-section per degree of longitude; (b) Distribution of the total zonal-integrated meridional transport induced by eddies as a function of latitude

图7 太平洋海域沿1°S断面海温变化谐振幅 ^{[

34
]}

Fig.7 Averaged longitude-depth cross section of recovered harmonic amplitude of sea temperature variability along 1°S of the Pacific sector (120°~285°E) ^{[

34
]}

图8 Zebiak-Cane海洋模式计算得到的热带西太平洋次表层温度距平与混合层深度的关系及与实况的对比 ^{[

84
]}
黄色代表利用Argo资料改进后方案的计算结果

Fig.8 Comparison of observed relationship between subsurface temperature anomaly and mixed-layer depth in the tropical western Pacific with that calculated by the parameterization scheme in Zebiak-Cane oceanic model ^{[

84
]}
Yellow colors represent improved parameterization scheme by Argo data

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