Articles | Volume 14, issue 4
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

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Cited articles

Alvera-Azcárate, A., Barth, A., Rixen, M., and Beckers, J. M.: Reconstruction of incomplete oceanographic data sets using empirical orthogonal functions: application to the Adriatic Sea surface temperature, Ocean Model., 9, 325–346,, 2005. a, b, c, d, e
Alvera-Azcárate, A., Barth, A., Beckers, J. M., and Weisberg, R. H.: Multivariate reconstruction of missing data in sea surface temperature, chlorophyll, and wind satellite fields, J. Geophys. Res.-Oceans, 112, C03008,, 2007. a
Alvera-Azcárate, A., Barth, A., Sirjacobs, D., and Beckers, J.-M.: Enhancing temporal correlations in EOF expansions for the reconstruction of missing data using DINEOF, Ocean Sci., 5, 475–485,, 2009. a
Alvera-Azcárate, A., Vanhellemont, Q., Ruddick, K., Barth, A., and Beckers, J.-M.: Analysis of high frequency geostationary ocean colour data using DINEOF, Estuar. Coast. Shelf S., 159, 28–36,, 2015. a
Alvera-Azcárate, A., Barth, A., Parard, G., and Beckers, J.-M.: Analysis of SMOS sea surface salinity data using DINEOF, Remote Sens. Environ., 180, 137–145,, 2016. a
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.