Institutional Repository of Key Laboratory of Ocean Circulation and Wave Studies, Institute of Oceanology, Chinese Academy of Sciences
An Improved Method for Retrieving Subsurface Temperature Using the ConvLSTM Model in the Western Pacific Ocean | |
Zhang, Yuyuan1,2; Liu, Yahao2,3,4; Kong, Yuan1; Hu, Po2,3,4 | |
2024-04-01 | |
发表期刊 | JOURNAL OF MARINE SCIENCE AND ENGINEERING |
卷号 | 12期号:4页码:13 |
通讯作者 | Liu, Yahao([email protected]) ; Hu, Po([email protected]) |
摘要 | In the era of marine big data, making full use of multi-source satellite observations to accurately retrieve and predict the temperature structure of the ocean subsurface layer is very significant in advancing the understanding of oceanic processes and their dynamics. Considering the time dependence and spatial correlation of marine characteristics, this study employed the convolutional long short-term memory (ConvLSTM) method to retrieve the subsurface temperature in the Western Pacific Ocean from several types of satellite observations. Furthermore, considering the temperature's vertical distribution, the retrieved results for the upper layer were iteratively used in the calculation for the deeper layer as input data to improve the algorithm. The results show that the retrieved results for the 100 to 500 m depth temperature using the 50 m layer in the calculation resulted in higher accuracy than those retrieved from the standard ConvLSTM method. The largest improvement was in the calculation for the 100 m layer, where the thermocline was located. The results indicate that our improved ConvLSTM method can increase the accuracy of subsurface temperature retrieval without additional input data. |
关键词 | deep learning iterative optimization remote sensing data convolutional long short-term memory (ConvLSTM) marine temperature Western Pacific |
DOI | 10.3390/jmse12040620 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China |
WOS研究方向 | Engineering ; Oceanography |
WOS类目 | Engineering, Marine ; Engineering, Ocean ; Oceanography |
WOS记录号 | WOS:001210045900001 |
出版者 | MDPI |
WOS关键词 | WARMING HIATUS ; EL-NINO ; SLOWDOWN |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.qdio.ac.cn/handle/337002/185596 |
专题 | 海洋环流与波动重点实验室 |
通讯作者 | Liu, Yahao; Hu, Po |
作者单位 | 1.Shandong Univ Sci & Technol, Coll Math & Syst Sci, 579 Qianwangang Rd, Qingdao 266590, Peoples R China 2.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Observat & Forecasting, Key Lab Ocean Circulat & Waves, 7 Nanhai Rd, Qingdao 266071, Peoples R China 3.Pilot Natl Lab Marine Sci & Technol Qingdao, Lab Ocean Dynam & Climate, 1 Wenhai Rd, Qingdao 266237, Peoples R China 4.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China |
第一作者单位 | 中国科学院海洋研究所 |
通讯作者单位 | 中国科学院海洋研究所 |
推荐引用方式 GB/T 7714 | Zhang, Yuyuan,Liu, Yahao,Kong, Yuan,et al. An Improved Method for Retrieving Subsurface Temperature Using the ConvLSTM Model in the Western Pacific Ocean[J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING,2024,12(4):13. |
APA | Zhang, Yuyuan,Liu, Yahao,Kong, Yuan,&Hu, Po.(2024).An Improved Method for Retrieving Subsurface Temperature Using the ConvLSTM Model in the Western Pacific Ocean.JOURNAL OF MARINE SCIENCE AND ENGINEERING,12(4),13. |
MLA | Zhang, Yuyuan,et al."An Improved Method for Retrieving Subsurface Temperature Using the ConvLSTM Model in the Western Pacific Ocean".JOURNAL OF MARINE SCIENCE AND ENGINEERING 12.4(2024):13. |
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