Global ocean gridded dataset and hypoxic zone expansion: reconstructed dissolved oxygen (1960-2021) based on machine learning technique
文献类型：期刊论文
| 作者 | Wang, Yanjun1,2,3; Song, Jinming2,3; Li, Xuegang2,3; Zhong, Guorong2; Zheng, Shuangqiang1; Li, Xiaofeng3,4 |
| 刊名 | INTERNATIONAL JOURNAL OF DIGITAL EARTH
 |
| 出版日期 | 2025-12-31 |
| 卷号 | 18期号:2页码:20 |
| 关键词 | Dissolved oxygen reconstruction hypoxic zone expansion machine learning ocean deoxygenation |
| ISSN号 | 1753-8947 |
| DOI | 10.1080/17538947.2025.2586914 |
| 通讯作者 | Song, Jinming(jmsong@qdio.ac.cn) |
| 英文摘要 | Due to global warming and the excessive input of nutrients resulting from human activities, ocean deoxygenation is gradually intensifying. However, the sparse spatiotemporal distribution of in situ global dissolved oxygen (DO) observations poses a significant challenge to understanding the spatiotemporal variations of DO in the world's oceans. In this study, we employed a SOM-FFNN approach to reconstruct a global monthly dissolved oxygen dataset from 1960 to 2021, with high spatial (1 degrees x 1 degrees) and vertical (to 2000 m) resolution. Compared to existing products, our model exhibits a lower RMSE (15.36 mu mol/kg), a higher R-2 (0.96), and strong agreement with long-term observations, outperforming other available datasets. Analysis of this dataset shows that the global ocean has been experiencing a steady loss of total oxygen content since the late 1980s, with the rate of depletion over the past decade nearly twice as high as that during 1980-2010. Further investigation reveals that low-oxygen zones have expanded both horizontally and vertically, with this expansion also intensifying in the past decade. These findings highlight the accelerating nature of ocean deoxygenation and the growing extent of low-oxygen habitats. |
| WOS关键词 | 21ST-CENTURY PROJECTIONS ; SOUTHERN-OCEAN |
| 资助项目 | National Natural Science Foundation of China[42176200] ; National Key Research and Development Program[2022YFC3104305] ; the Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB42000000] |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001623964100001 |
| 出版者 | TAYLOR & FRANCIS LTD |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/204320]  |
| 专题 | 海洋研究所_海洋生态与环境科学重点实验室 |
| 通讯作者 | Song, Jinming |
| 作者单位 | 1.Chinese Acad Sci, Inst Oceanol, Dept Marine Sci, Data Ctr, Qingdao, Peoples R China 2.Chinese Acad Sci, Key Lab Marine Ecol & Environm Sci, Inst Oceanol, Qingdao 266071, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Yanjun,Song, Jinming,Li, Xuegang,et al. Global ocean gridded dataset and hypoxic zone expansion: reconstructed dissolved oxygen (1960-2021) based on machine learning technique[J]. INTERNATIONAL JOURNAL OF DIGITAL EARTH,2025,18(2):20. |
| APA | Wang, Yanjun,Song, Jinming,Li, Xuegang,Zhong, Guorong,Zheng, Shuangqiang,&Li, Xiaofeng.(2025).Global ocean gridded dataset and hypoxic zone expansion: reconstructed dissolved oxygen (1960-2021) based on machine learning technique.INTERNATIONAL JOURNAL OF DIGITAL EARTH,18(2),20. |
| MLA | Wang, Yanjun,et al."Global ocean gridded dataset and hypoxic zone expansion: reconstructed dissolved oxygen (1960-2021) based on machine learning technique".INTERNATIONAL JOURNAL OF DIGITAL EARTH 18.2(2025):20. |
入库方式： OAI收割
来源：海洋研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。