Impact of HF radar current gap-filling methodologies on the Lagrangian assessment of coastal dynamics
Type
ArticleAuthors
Hernández-Carrasco, IsmaelSolabarrieta, Lohitzune
Rubio, Anna
Esnaola, Ganix
Reyes, Emma
Orfila, Alejandro
KAUST Department
Biological and Environmental Sciences and Engineering (BESE) DivisionRed Sea Research Center (RSRC)
Date
2018-08-24Permanent link to this record
http://hdl.handle.net/10754/628773
Metadata
Show full item recordAbstract
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.Citation
Hernández-Carrasco I, Solabarrieta L, Rubio A, Esnaola G, Reyes E, et al. (2018) Impact of HF radar current gap-filling methodologies on the Lagrangian assessment of coastal dynamics. Ocean Science 14: 827–847. Available: http://dx.doi.org/10.5194/os-14-827-2018.Sponsors
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).Publisher
Copernicus GmbHJournal
Ocean ScienceAdditional Links
https://www.ocean-sci.net/14/827/2018/ae974a485f413a2113503eed53cd6c53
10.5194/os-14-827-2018
Scopus Count
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