Articles | Volume 17, issue 4
https://doi.org/10.5194/essd-17-1693-2025
https://doi.org/10.5194/essd-17-1693-2025
Data description article
 | 
25 Apr 2025
Data description article |  | 25 Apr 2025

Gap-filled sub-surface mooring dataset off Western Australia during 2010–2023

Toan Bui, Ming Feng, and Christopher C. Chapman

Viewed

Total article views: 3,158 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,223 547 388 3,158 320 106 189
  • HTML: 2,223
  • PDF: 547
  • XML: 388
  • Total: 3,158
  • Supplement: 320
  • BibTeX: 106
  • EndNote: 189
Views and downloads (calculated since 10 Oct 2024)
Cumulative views and downloads (calculated since 10 Oct 2024)

Viewed (geographical distribution)

Total article views: 3,158 (including HTML, PDF, and XML) Thereof 3,120 with geography defined and 38 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Saved (final revised paper)

Latest update: 20 Jun 2026
Download
Short summary
Moored time series data are crucial for detecting changes in the ocean. However, mooring losses or instrument failures often result in data gaps. A gap-filled time series dataset of a shelf mooring array off the Western Australian coast is created using a machine learning tool to fill the data gaps. The gap-filled data show consistency with observations and can be used to characterize marine heat waves and cold spells influenced by ocean boundary currents.
Share
Altmetrics
Final-revised paper
Preprint