Meta-learning-based estimation of the barrier layer thickness in the tropical Indian Ocean

doi:10.1088/2515-7620/acf9e1

CORC > 海洋研究所 > 中国科学院海洋研究所 > 海洋环流与波动重点实验室

	Meta-learning-based estimation of the barrier layer thickness in the tropical Indian Ocean
	Qi, Jifeng 2,3; Qu, Tangdong 1; Yin, Baoshu 2,3
刊名	ENVIRONMENTAL RESEARCH COMMUNICATIONS
	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.
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关键词	SEA-SURFACE SALINITY ; INTERANNUAL VARIABILITY ; EQUATORIAL PACIFIC ; MIXED-LAYER ; AQUARIUS ; BAY
WOS研究方向	Environmental Sciences & Ecology
语种	英语
出版者	IOP Publishing Ltd
WOS记录号	WOS:001070046500001
内容类型	期刊论文
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.Univ Calif Los Angeles, Joint Inst Reg Earth Syst Sci & Engn, Los Angeles, CA USA 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China
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.