High-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.
|Original language||English (US)|
|Number of pages||21|
|State||Published - Aug 24 2018|
Bibliographical noteFunding Information:
Acknowledgements. This study has been supported by the JERICO-NEXT project funded by the European Union’s Horizon 2020 research and innovation program under grant agreement no. 654410. Ismael Hernández-Carrasco acknowledges the Juan de la Cierva contract funded by the Spanish government. The work of Anna Rubio was partially supported by the LIFE-LEMA project (LIFE15 ENV/ES/000252), the Directorate of Emergency Attention and Meteorology of the Basque Government and the Department of Environment, Regional Planning, Agriculture and Fisheries of the Basque Government (Marco Program).
© 2018. Author(s).
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