Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning
文献类型：期刊论文
| 作者 | Zhang, Xudong1,2; Li, Xiaofeng1,2 |
| 刊名 | EARTH SYSTEM SCIENCE DATA
 |
| 出版日期 | 2024-11-06 |
| 卷号 | 16期号:11页码:5131-5144 |
| ISSN号 | 1866-3508 |
| DOI | 10.5194/essd-16-5131-2024 |
| 通讯作者 | Li, Xiaofeng(lixf@qdio.ac.cn) |
| 英文摘要 | Internal waves (IWs) are an important ocean phenomenon facilitating energy transfer between multiscale ocean processes. Understanding such processes necessitates the collection and analysis of extensive observational data. IWs predominantly occur in marginal seas, with the South China Sea (SCS) being one of the most active regions, characterized by frequent and large-amplitude IW activities. In this study, we present a comprehensive IW dataset for the northern SCS (10.12157/IOCAS.20240409.001, Zhang and Li, 2024), covering the area from 112.40 to 121.32 degrees E and from 18.32 to 23.19 degrees N, spanning the period from 2000 to 2022 with a 250 m spatial resolution. During the 22 years, a total of 15 830 MODIS images were downloaded for further processing. Out of these, 3085 high-resolution MODIS true-color images were identified to contain IW information and were included in the dataset with precise IW positions extracted using advanced deep learning techniques. IWs in the northern SCS are categorized into four regions based on extracted IW spatial distributions. This classification enables detailed analyses of IW characteristics, including their spatial and temporal distributions across the entire northern SCS and its specific sub-regions. Interestingly, our temporal analysis reveals characteristic "double-peak" patterns aligned with the lunar day, highlighting the strong connection between IWs and tidal cycles. Furthermore, our spatial analysis identifies two IW quiescent zones within the IW clusters influenced by underwater topography, highlighting regional variations in IW characteristics and suggesting underlying mechanisms which merit further investigation. There are also three gap regions between distinct IW clusters, which may indicate different IW sources. The constructed dataset holds significant potential for studying IW-environment interactions, developing monitoring and prediction models, validating numerical simulations, and serving as an educational resource to promote awareness and interest in IW research. |
| WOS关键词 | SOLITARY WAVES ; NUMERICAL-SIMULATION ; DONGSHA ATOLL ; OCEAN ; REFRACTION |
| 资助项目 | National Natural Science Foundation of China-Shandong Joint Fund ; NASA Earth Observing System Data and Information System (EOSDIS) |
| WOS研究方向 | Geology ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:001348310600001 |
| 出版者 | COPERNICUS GESELLSCHAFT MBH |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/199411]  |
| 专题 | 海洋研究所_海洋环流与波动重点实验室 |
| 通讯作者 | Li, Xiaofeng |
| 作者单位 | 1.Key Lab Ocean Observat & Forecasting, Qingdao, Peoples R China 2.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Xudong,Li, Xiaofeng. Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning[J]. EARTH SYSTEM SCIENCE DATA,2024,16(11):5131-5144. |
| APA | Zhang, Xudong,&Li, Xiaofeng.(2024).Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning.EARTH SYSTEM SCIENCE DATA,16(11),5131-5144. |
| MLA | Zhang, Xudong,et al."Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning".EARTH SYSTEM SCIENCE DATA 16.11(2024):5131-5144. |
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。