Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 16, issue 12
Articles | Volume 16, issue 12
https://doi.org/10.5194/essd-16-5737-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-5737-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 12
Data description paper
 | 
18 Dec 2024
Data description paper |  | 18 Dec 2024

A submesoscale eddy identification dataset in the northwest Pacific Ocean derived from GOCI I chlorophyll a data based on deep learning

Yan Wang, Ge Chen, Jie Yang, Zhipeng Gui, and Dehua Peng

Viewed

Total article views: 761 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
509 111 141 761 35 18 17
  • HTML: 509
  • PDF: 111
  • XML: 141
  • Total: 761
  • Supplement: 35
  • BibTeX: 18
  • EndNote: 17
Views and downloads (calculated since 30 May 2024)
Cumulative views and downloads (calculated since 30 May 2024)

Viewed (geographical distribution)

Total article views: 761 (including HTML, PDF, and XML) Thereof 738 with geography defined and 23 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Dec 2024
Download
Short summary
Mesoscale eddies are ubiquitous in the ocean and account for 90 % of its kinetic energy, but their generation and dissipation are difficult to observe using current remote sensing technology. Our submesoscale eddy dataset, formed by suppressing large-scale circulation signals and enhancing small-scale chlorophyll structures, has important implications for understanding marine environments and ecosystems, as well as improving climate model predictions.
Read more
Altmetrics
Final-revised paper
Preprint