Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning

Zhang, Xudong; Li, Xiaofeng

doi:https://doi.org/10.5194/essd-16-5131-2024

Articles | Volume 16, issue 11

https://doi.org/10.5194/essd-16-5131-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-16-5131-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 16, issue 11

Data description paper

|

06 Nov 2024

Data description paper |

| 06 Nov 2024

Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning

Xudong Zhang and Xiaofeng Li

Data sets

Constructing a 22-Year Internal Wave Dataset for the Northern South China Sea: Spatiotemporal Analysis Using MODIS Imagery and Deep Learning Xudong Zhang and Xiaofeng Li https://doi.org/10.12157/IOCAS.20240409.001

Short summary

Internal wave (IW) is an important ocean process and is frequently observed in the South China Sea (SCS). This study presents a detailed IW dataset for the northern SCS spanning from 2000 to 2022, with a spatial resolution of 250 m, comprising 3085 IW MODIS images. This dataset can enhance understanding of IW dynamics and serve as a valuable resource for studying ocean dynamics, validating numerical models, and advancing AI-driven model building, fostering further exploration into IW phenomena.