GDCSM-Argo数据在全球海洋热含量评估中的应用分析

doi:10.3969/j.issn.1001-909X.2024.02.004

海洋学研究 ›› 2024, Vol. 42 ›› Issue (2): 40-54.DOI: 10.3969/j.issn.1001-909X.2024.02.004

GDCSM-Argo数据在全球海洋热含量评估中的应用分析

苏涵¹, 闯子维¹, 张春玲¹^,²^,³^,^*

1.上海海洋大学海洋科学学院,上海 201306
2.上海海洋大学海洋科学与技术实验教学示范中心,上海 201306
3.自然资源部海洋生态监测与修复技术重点实验室,上海 201306

收稿日期:2023-06-19 修回日期:2023-09-21 出版日期:2024-06-15 发布日期:2024-08-09
通讯作者: 张春玲
作者简介:*张春玲(1981—),女,副教授,主要从事海洋动力学方面的研究,E-mail: clzhang@shou.edu.cn。
苏涵(1999—),男,内蒙古自治区呼和浩特市人,主要从事海洋动力学方面的研究,E-mail: m220200680@st.shou.edu.cn。
基金资助:
国家自然科学基金项目(42106090);农业农村部全球渔业资源调查监测评估(公海渔业资源综合科学调查)专项(D-8021-21-0109-01)

Application analysis of GDCSM-Argo in evaluating global ocean heat content

SU Han¹, CHUANG Ziwei¹, ZHANG Chunling¹^,²^,³^,^*

1. College of Marine Science, Shanghai Ocean University, Shanghai 201306, China
2. Demonstration Center for Experimental Teaching of Marine Science and Technology, Shanghai Ocean University, Shanghai 201306
3. Key Laboratory of Marine Ecological Monitoring and Restoration Technology, MNR, Shanghai 201306, China

Received:2023-06-19 Revised:2023-09-21 Online:2024-06-15 Published:2024-08-09
Contact: ZHANG Chunling

摘要/Abstract

摘要：

海洋热含量作为全球气候变化研究最关键、最稳定的指标之一,对其进行系统、准确的评估依赖于长时间序列、全球覆盖的海洋内部观测数据。利用立足Argo剖面观测构建并持续更新的全球海洋0~2 000 m水深多参数再分析数据集(gradient dependent correlation scale method Argo, GDCSM-Argo),通过时空序列和滞后回归等手段分析热含量变化,研究了2004—2021年间全球海洋热含量的时空演变特征及其与异常气候的响应关系。结果表明:自2004年起,全球海洋0~2 000 m水深热含量均有不同程度的增加,海洋热含量异常增幅超过2×10⁸ J/m²。2013年以后,700 ~2 000 m水深的海域表现出持续增暖趋势,至2017年,全球0~2 000 m水深变暖加剧。700 m水深的温度异常在海洋热含量整体变化中贡献突出。热带东太平洋海域在厄尔尼诺之前积蓄热量,在厄尔尼诺期间/之后失去热量,同时也向南、向北散发热量以中和前期积蓄的热量,变暖范围向赤道南、北两侧扩展。热带东太平洋海洋热含量正异常峰值先于ENSO(El Niño-Southern Oscillation)指数约0~1个月。由上述结论可知,GDCSM-Argo数据集能够更细致地刻画海洋热含量的时空演变。

关键词: 海洋热含量, GDCSM-Argo, 时空演变, 气候变化

Abstract:

The ocean heat content is one of the most critical and stable indicators of the global climate change research. It’s systematic and accurate evaluation depends on the ocean internal observation of long time series and global coverage. Based on a global multi-parameter reanalysis data set (gradient dependent correlation scale method Argo, GDCSM-Argo) as well as the trend analysis, spatiotemporal series analysis and delayed regression analysis, the spatiotemporal evolution of global ocean heat content was investigated, and the relationship between ocean heat content change and the abnormal climate during 2004-2021 were discussed. The results showed that the global ocean heat content of 0-2 000 m had increased with different levels since 2004, with a increment of more than 2×10⁸ J/m². After 2013, the deep sea (700-2 000 m) had shown a continuous warming trend. The warming of all depths ranging from 0 to 2000 m was intensified after 2017. The temperature anomaly of 700 m made a prominent contribution to the overall change of the ocean heat content. The tropical eastern Pacific Ocean accumulated heat before El Niño, lost heat and distributed heat to the north and south during/after El Niño in order to offset the accumulated heat from earlier stages. The warming range extended to the north and south of the equator. The positive peak of heat content anomaly in the tropical Pacific Ocean preceded the ENSO (El Niño-Southern Oscillation) index by about 0-1 month. All of the results indicate that GDCSM-Argo will be able to provide more detailed of the ocean heat content evolution.

Key words: ocean heat content, GDCSM-Argo, space-time evolution, climate change

中图分类号:

P733.4

苏涵, 闯子维, 张春玲. GDCSM-Argo数据在全球海洋热含量评估中的应用分析[J]. 海洋学研究, 2024, 42(2): 40-54.

SU Han, CHUANG Ziwei, ZHANG Chunling. Application analysis of GDCSM-Argo in evaluating global ocean heat content[J]. Journal of Marine Sciences, 2024, 42(2): 40-54.

图/表 8

图1 全球气候态海洋热含量和全球平均海洋热含量异常的空间分布

Fig.1 Spatial distribution of global climate ocean heat content and mean ocean heat content anomaly

图2 2004—2021年全球海洋热含量变化速率与海洋热含量总变化量的空间分布

Fig.2 Spatial distribution of global ocean heat content change rate and total ocean heat content change from 2004 to 2021

图3 全球海洋不同深度内热含量异常变化时间序列(a)和0~2 000 m水深温度异常时间序列(b) (图a中的灰色阴影代表0~2 000 m曲线的三倍标准差范围。)

Fig.3 Time series of ocean heat content anomaly at different depths (a) and time series of temperature anomaly from 0 to 2 000 m (b) (Gray shading in figure a represents the range of triple standard deviations of the 0-2 000 m curve.)

图4 全球海洋分层热含量异常随时间和深度变化的断面分布 (图中虚线代表海洋热含量异常由负转正的起始年份。)

Fig.4 Sections of global ocean heat content anomaly with time and depth at different depths (The dashed line represents the beginning year when the ocean heat content anomaly turned from negative to positive.)

图5 2004—2021年间0~2 000 m水深热带海洋热含量异常的纬向平均(a)和经向平均(b)的时间序列 (图中黑色实线为对应的Niño3.4区的ENSO指数。)

Fig.5 Time series of zonal mean (a) and meridional mean (b) of the ocean heat content anomaly at 0-2 000 m from 2004 to 2021 (The solid black lines are the ENSO index of the Niño3.4.)

图6 海洋热含量异常和海洋热含量变化趋势与异常气候的超前滞后相关分析

Fig.6 Correlation analysis of lead/lag relationship between ocean heat content anomaly and ocean heat content change tendency with abnormal climate

图7 分层海洋热含量变化量的时空演变特征 (图中热含量为2013—2021年平均热含量减去2004—2012年平均热含量。)

Fig.7 Temporal and spatial evolution characteristics of ocean heat contentat at different depths (The figure shows the average OHC from 2013 to 2021 minus the OHC from 2004 to 2012.)

图8 2004—2012年和2013—2021年不同深度的温度异常对海洋热含量异常的影响分布

Fig.8 Distribution of the ocean heat content anomaly influenced by the temperature anomaly at different depths during 2004—2012 and 2013—2021

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GDCSM-Argo数据在全球海洋热含量评估中的应用分析

Application analysis of GDCSM-Argo in evaluating global ocean heat content

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[3]	邓绍坤, 吴祥柏. 基于再分析数据的南大西洋上层海洋热含量变化研究[J]. 海洋学研究, 2019, 37(3): 12-20.