Articles | Volume 14, issue 4
https://doi.org/10.5194/os-14-827-2018
https://doi.org/10.5194/os-14-827-2018
Research article
 | 
24 Aug 2018
Research article |  | 24 Aug 2018

Impact of HF radar current gap-filling methodologies on the Lagrangian assessment of coastal dynamics

Ismael Hernández-Carrasco, Lohitzune Solabarrieta, Anna Rubio, Ganix Esnaola, Emma Reyes, and Alejandro Orfila

Viewed

Total article views: 3,439 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,277 1,070 92 3,439 387 81 91
  • HTML: 2,277
  • PDF: 1,070
  • XML: 92
  • Total: 3,439
  • Supplement: 387
  • BibTeX: 81
  • EndNote: 91
Views and downloads (calculated since 15 Mar 2018)
Cumulative views and downloads (calculated since 15 Mar 2018)

Viewed (geographical distribution)

Total article views: 3,439 (including HTML, PDF, and XML) Thereof 3,089 with geography defined and 350 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 19 Apr 2024
Download
Short summary
A new methodology to reconstruct HF radar velocity fields based on neural networks is developed. Its performance is compared with other methods focusing on the propagation of errors introduced in the reconstruction of the velocity fields through the trajectories, Lagrangian flow structures and residence times. We find that even when a large number of measurements in the HFR velocity field is missing, the Lagrangian techniques still give an accurate description of oceanic transport properties.