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  4. 海洋环流与波动重点实验室
Retrieval of Subsurface Velocities in the Southern Ocean from Satellite Observations

文献类型：期刊论文

作者Xiang, Liang6,7,8; Xu, Yongsheng5,6,7,8; Sun, Hanwei4; Zhang, Qingjun3; Zhang, Liqiang3; Zhang, Lin1; Zhang, Xiangguang6,7,8; Huang, Chao6,7,8; Zhao, Dandan2
刊名REMOTE SENSING
出版日期2023-12-01
卷号15期号:24页码:19
关键词subsurface velocity light gradient boosting machine (LightGBM) The Southern Ocean satellite observations long-term variability
DOI10.3390/rs15245699
通讯作者Xu, Yongsheng(yongsheng.xu@qdio.ac.cn)
英文摘要Determining the dynamic processes of the subsurface ocean is a critical yet formidable undertaking given the sparse measurement resources available presently. In this study, using the light gradient boosting machine algorithm (LightGBM), we report for the first time a machine learning strategy for retrieving subsurface velocities at 1000 dbar depth in the Southern Ocean from information derived from satellite observations. Argo velocity measurements are used in the training and validation of the LightGBM model. The results show that reconstructed subsurface velocity agrees better with Argo velocity than reanalysis datasets. In particular, the subsurface velocity estimates have a correlation coefficient of 0.78 and an RMSE of 4.09 cm/s, which is much better than the ECCO estimates, GODAS estimates, GLORYS12V1 estimates, and Ora-S5 estimates. The LightGBM model has a higher skill in the reconstruction of subsurface velocity than the random forest and the linear regressor models. The estimated subsurface velocity exhibits a statistically significant increase at 1000 dbar since the 1990s, providing new evidence for the deep acceleration of mean circulation in the Southern Ocean. This study demonstrates the great potential and advantages of statistical methods for subsurface velocity modeling and oceanic dynamical information retrieval.
WOS关键词EMPIRICAL MODE ; SURFACE ; INTERIOR ; CURRENTS ; HEAT
资助项目NSFC-Shandong Joint Fund Key Project
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者MDPI
WOS记录号WOS:001131061600001
源URL[http://ir.qdio.ac.cn/handle/337002/184242]  
专题海洋研究所_海洋环流与波动重点实验室
通讯作者Xu, Yongsheng
作者单位1.Naval Submarine Acad, Qingdao 266199, Peoples R China
2.Qilu Univ Technol, Inst Oceanog Instrumentat, Shandong Acad Sci, Qingdao 266061, Peoples R China
3.China Acad Space Technol, Inst Remote Sensing Satellite, Beijing 100094, Peoples R China
4.Beijing Inst Radio Measurement, Spaceborne Radar Res Ctr, Beijing 100039, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
6.Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 266071, Peoples R China
7.Laoshan Lab, Lab Ocean Dynam & Climate, Qingdao 266237, Peoples R China
8.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China
推荐引用方式
GB/T 7714		 Xiang, Liang,Xu, Yongsheng,Sun, Hanwei,et al. Retrieval of Subsurface Velocities in the Southern Ocean from Satellite Observations[J]. REMOTE SENSING,2023,15(24):19.
APA Xiang, Liang.,Xu, Yongsheng.,Sun, Hanwei.,Zhang, Qingjun.,Zhang, Liqiang.,...&Zhao, Dandan.(2023).Retrieval of Subsurface Velocities in the Southern Ocean from Satellite Observations.REMOTE SENSING,15(24),19.
MLA Xiang, Liang,et al."Retrieval of Subsurface Velocities in the Southern Ocean from Satellite Observations".REMOTE SENSING 15.24(2023):19.

入库方式： OAI收割

来源：海洋研究所

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