Meta-learning-based estimation of the barrier layer thickness in the tropical Indian Ocean
文献类型：期刊论文
| 作者 | Qi, Jifeng1,2; Qu, Tangdong3; Yin, Baoshu1,2 |
| 刊名 | ENVIRONMENTAL RESEARCH COMMUNICATIONS
 |
| 出版日期 | 2023-09-01 |
| 卷号 | 5期号:9页码:8 |
| 关键词 | Ocean barrier layer thickness Indian Ocean meta-learning machine learning |
| ISSN号 | 2515-7620 |
| DOI | 10.1088/2515-7620/acf9e1 |
| 通讯作者 | Qi, Jifeng(Jfqi@qdio.ac.cn) |
| 英文摘要 | Accurately estimating the barrier layer thickness (BLT) is crucial for enhancing our understanding of the ocean's role in climate variability on both regional and global scales. Here, we propose a meta-learning-based ensemble model to estimate the BLT using satellite observations in the tropical Indian Ocean. The results show that the meta-learning-based ensemble model outperforms the three individual models in terms of spatial distribution and accuracy, with significantly reduced root mean square errors in the Southeast Arabian Sea, Bay of Bengal, and eastern equatorial Indian Ocean. Furthermore, we found that sea surface salinity plays the most significant role in the estimation of BLT, highlighting the dominant influence of salinity stratification. These preliminary results provide an insight into the feasibility of predicting the BLT using satellite observations and have implications for studying the upper ocean dynamics using machine learning techniques. |
| WOS关键词 | SEA-SURFACE SALINITY ; INTERANNUAL VARIABILITY ; EQUATORIAL PACIFIC ; MIXED-LAYER ; AQUARIUS ; BAY |
| 资助项目 | National Key Research and Development Program of China[2022YFF0801400] ; National Natural Science Foundation of China[42176010] ; Natural Science Foundation of Shandong Province, China[ZR2021MD022] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001070046500001 |
| 出版者 | IOP Publishing Ltd |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/181758]  |
| 专题 | 海洋研究所_海洋环流与波动重点实验室 |
| 通讯作者 | Qi, Jifeng |
| 作者单位 | 1.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Univ Calif Los Angeles, Joint Inst Reg Earth Syst Sci & Engn, Los Angeles, CA USA |
| 推荐引用方式 GB/T 7714 | Qi, Jifeng,Qu, Tangdong,Yin, Baoshu. Meta-learning-based estimation of the barrier layer thickness in the tropical Indian Ocean[J]. ENVIRONMENTAL RESEARCH COMMUNICATIONS,2023,5(9):8. |
| APA | Qi, Jifeng,Qu, Tangdong,&Yin, Baoshu.(2023).Meta-learning-based estimation of the barrier layer thickness in the tropical Indian Ocean.ENVIRONMENTAL RESEARCH COMMUNICATIONS,5(9),8. |
| MLA | Qi, Jifeng,et al."Meta-learning-based estimation of the barrier layer thickness in the tropical Indian Ocean".ENVIRONMENTAL RESEARCH COMMUNICATIONS 5.9(2023):8. |
入库方式： OAI收割
来源：海洋研究所
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