Spatio-temporal variability of mean wave energy flux in the Caribbean Sea

Mean wave energy flux (hereinafter WEF) is assessed in the Caribbean Sea from a 60-year (1958–2017) wave hindcast. We use a novel approach, based on neural networks, to identify coherent regions of WEF and their association with different climate patterns. This method allows for a better evaluation...

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Detalles Bibliográficos
Autores: Orejarena-Rondón, Andrés F., Sayol, Juan Manuel, Hernández Carrasco, Ismael, Cáceres-Euse, Alejandro, Restrepo, Juan C., Orfila, Alejandro
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2023
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/338591
Acceso en línea:http://hdl.handle.net/10261/338591
https://api.elsevier.com/content/abstract/scopus_id/85136473430
Access Level:acceso abierto
Palabra clave:Caribbean Sea
El Niño-Southern Oscillation
Self-organizing maps
Spatio-temporal variability
Wave energy flux
Wind variability
Descripción
Sumario:Mean wave energy flux (hereinafter WEF) is assessed in the Caribbean Sea from a 60-year (1958–2017) wave hindcast. We use a novel approach, based on neural networks, to identify coherent regions of WEF and their association with different climate patterns. This method allows for a better evaluation of the underlying dynamics behind seasonal and inter-annual WEF variability, including the effect induced by the latitudinal migration of the Intertropical Convergence Zone (ITCZ) and the influence of El Niño-Southern Oscillation (ENSO) events. Results show regional differences in WEF variability likely due to both intensification and migration of the ITCZ. WEF exhibits a strong semi-seasonal signal in areas of the continental shelf, with maxima reached in January and June, in agreement with the known sea surface temperature and sea-level pressure variability patterns. At larger scales, WEF shows a significant correlation with the Oceanic Niño Index (ONI, which is the primary index for tracking the ocean part of ENSO climate pattern), depicting positive values in the central and western sides of the basin and negative ones at the eastern side.