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dc.contributor.authorHernández-Carrasco, Ismael
dc.contributor.authorSolabarrieta, Lohitzune
dc.contributor.authorRubio, Anna
dc.contributor.authorEsnaola, Ganix
dc.contributor.authorReyes, Emma
dc.contributor.authorOrfila, Alejandro
dc.identifier.citationHernández-Carrasco, I. Solabarrieta. L.; Rubio, A. et al (2018) Impact of HF radar current gap-filling methodologies on the Lagrangian assessment of coastal dynamics. Ocean Science, 14, pp.827-847. DOI:
dc.description.abstractHigh-frequency radar, HFR, is a cost-effective monitoring technique that allows us to obtain high-resolution continuous surface currents, providing new insights for understanding small-scale transport processes in the coastal ocean. In the last years, the use of Lagrangian metrics to study mixing and transport properties has been growing in importance. A common condition among all the Lagrangian techniques is that complete spatial and temporal velocity data are required to compute trajectories of virtual particles in the flow. However, hardware or software failures in the HFR system can compromise the availability of data, resulting in incomplete spatial coverage fields or periods without data. In this regard, several methods have been widely used to fill spatiotemporal gaps in HFR measurements. Despite the growing relevance of these systems there are still many open questions concerning the reliability of gap-filling methods for the Lagrangian assessment of coastal ocean dynamics. In this paper, we first develop a new methodology to reconstruct HFR velocity fields based on self-organizing maps (SOMs). Then, a comparative analysis of this method with other available gap-filling techniques is performed, i.e., open-boundary modal analysis (OMA) and data interpolating empirical orthogonal functions (DINEOFs). The performance of each approach is quantified in the Lagrangian frame through the computation of finite-size Lyapunov exponents, Lagrangian coherent structures and residence times. We determine the limit of applicability of each method regarding four experiments based on the typical temporal and spatial gap distributions observed in HFR systems unveiled by a K-means clustering analysis. Our results show that even when a large number of data are missing, the Lagrangian diagnoses still give an accurate description of oceanic transport properties.en_US
dc.rightsAttribution 4.0 International*
dc.subject.otherHF Radaren_US
dc.subject.otherLagrangian assessementen_US
dc.subject.otherGap filling techniquesen_US
dc.titleImpact of HF radar current gap-filling methodologies on the Lagrangian assessment of coastal dynamics.en_US
dc.typeJournal Contributionen_US
dc.subject.parameterDisciplineParameter Discipline::Physical oceanography::Currentsen_US
dc.bibliographicCitation.titleOcean Scienceen_US
dc.description.eovSurface currentsen_US
dc.description.maturitylevelTRL 8 Actual system completed and "mission qualified" through test and demonstration in an operational environment (ground or space)en_US
dc.description.bptypeManual (incl. handbook, guide, cookbook etc)en_US Hernández-Carrasco

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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International